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Note: This page contains sample records for the topic "option pricing model" from the National Library of EnergyBeta (NLEBeta).
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they are not comprehensive nor are they the most current set.
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1

Forecasting future volatility from option prices, Working  

E-Print Network (OSTI)

Weisbach are gratefully acknowledged. I bear full responsibility for all remaining errors. Forecasting Future Volatility from Option Prices Evidence exists that option prices produce biased forecasts of future volatility across a wide variety of options markets. This paper presents two main results. First, approximately half of the forecasting bias in the S&P 500 index (SPX) options market is eliminated by constructing measures of realized volatility from five minute observations on SPX futures rather than from daily closing SPX levels. Second, much of the remaining forecasting bias is eliminated by employing an option pricing model that permits a non-zero market price of volatility risk. It is widely believed that option prices provide the best forecasts of the future volatility of the assets which underlie them. One reason for this belief is that option prices have the ability to impound all publicly available information – including all information contained in the history of past prices – about the future volatility of the underlying assets. A second related reason is that option pricing theory maintains that if an option prices fails to embody optimal forecasts of the future volatility of the underlying asset, a profitable trading strategy should be available whose implementation would push the option price to the level that reflects the best possible forecast of future volatility.

Allen M. Poteshman

2000-01-01T23:59:59.000Z

2

Pricing and hedging a barrier option  

E-Print Network (OSTI)

Barrier options are options where the payoff depends on whether the underlying asset's price reaches a certain level during a certain period of time. This path-dependency makes these options difficult to manage in practice. In this work, general methods of pricing and hedging are proposed. General properties of the Black - Scholes model are studied. Three methods of pricing are discussed and compared. Hedging issues are analyzed. Finally an improvement of the Black - Scholes model for the stock's price is proposed to take into account the stochastic aspect of the stock price volatility.

Bogossian, Alan

2002-01-01T23:59:59.000Z

3

Implementation of the Longstaff and Schwartz American Option Pricing Model on FPGA  

Science Conference Proceedings (OSTI)

American style options are widely used financial products, whose pricing is a challenging problem due to their path dependency characteristic. Finite difference methods and tree-based methods can be used for American option pricing. However, the major ... Keywords: American option, FPGA, Financial computing, Hardware acceleration, Least Squares Monte Carlo, Quasi Monte Carlo

Xiang Tian; Khaled Benkrid

2012-04-01T23:59:59.000Z

4

Energy Spot Price Models and Spread Options Pricing Samuel Hikspoors and Sebastian Jaimungal a  

E-Print Network (OSTI)

and calibrate our model to the NYMEX Light Sweet Crude Oil spot and futures data, allowing us to extract curves. Adding a perturbation on top of this first order model allows us to correct some

Jaimungal, Sebastian

5

Option pricing, maturity randomization and distributed computing  

Science Conference Proceedings (OSTI)

We price discretely monitored options when the underlying evolves according to different exponential Levy processes. By geometric randomization of the option maturity, we transform the n-steps backward recursion that arises in option pricing into an ... Keywords: Discrete monitoring, Grid computing, Integral equations, Lévy processes, Option pricing

Gianluca Fusai; Daniele Marazzina; Marina Marena

2010-07-01T23:59:59.000Z

6

Pricing and hedging Asian basket spread options  

Science Conference Proceedings (OSTI)

Asian options, basket options and spread options have been extensively studied in the literature. However, few papers deal with the problem of pricing general Asian basket spread options. This paper aims to fill this gap. In order to obtain prices and ... Keywords: 91G20, Asian basket spread option, Moment matching, Non-comonotonic sum, Shifted log-extended skew normal law

Griselda Deelstra; Alexandre Petkovic; Michèle Vanmaele

2010-04-01T23:59:59.000Z

7

Recovering a time-homogeneous stock price process from perpetual option prices  

E-Print Network (OSTI)

It is well-known how to determine the price of perpetual American options if the underlying stock price is a time-homogeneous diffusion. In the present paper we consider the inverse problem, i.e. given prices of perpetual American options for different strikes we show how to construct a time-homogeneous model for the stock price which reproduces the given option prices.

Ekstrom, Erik

2009-01-01T23:59:59.000Z

8

A Note on Pricing Options on Defaultable Stocks  

E-Print Network (OSTI)

In this note, we develop stock option price approximations for a model which takes both the risk o default and the stochastic volatility into account. We also let the intensity of defaults be influenced by the volatility. We show that it might be possible to infer the risk neutral default intensity from the stock option prices. Our option price approximation has a rich implied volatility surface structure and fits the data implied volatility well. Our calibration exercise shows that an effective hazard rate from bonds issued by a company can be used to explain the implied volatility skew of the implied volatility of the option prices issued by the same company.

Bayraktar, Erhan

2007-01-01T23:59:59.000Z

9

September 2000Forecasting Future Variance from Option Prices  

E-Print Network (OSTI)

Although it is widely believed that option prices provide the best possible forecasts of the future variance of the assets which underlie them, a large body of empirical evidence concludes that option prices consistently yield biased forecasts of future variance. The prevailing interpretation of these findings is that option investors may be forming unbiased forecasts of the future variance of underlying assets but that these unbiased forecasts fail to get impounded into option prices because of either (1) the difficulty of carrying out the necessary arbitrage strategies that would force the prices to their proper levels, or (2) the availability to market makers of lucrative alternative strategies in which they simply profit from the large bid-ask spreads in the options markets. This interpretation has significant consequences for nearly the entire range of option pricing research, since it implies that non-continuous trading, bid-ask spreads, and other market imperfections substantially influence option prices. This implication is important, both because incorporating these types of market imperfections into option pricing models is much more difficult than, for example, altering the dynamics of the underlying asset and also because it suggests that researchers cannot learn about option investor expectations by filtering option

Allen M. Poteshman; Mark R. Manfredo; Allen M. Poteshman; Allen M. Poteshman; Champaign Helpful; Jegadeesh Narasimhan

2000-01-01T23:59:59.000Z

10

A Model-Free No-arbitrage Price Bound for Variance Options  

SciTech Connect

We suggest a numerical approximation for an optimization problem, motivated by its applications in finance to find the model-free no-arbitrage bound of variance options given the marginal distributions of the underlying asset. A first approximation restricts the computation to a bounded domain. Then we propose a gradient projection algorithm together with the finite difference scheme to solve the optimization problem. We prove the general convergence, and derive some convergence rate estimates. Finally, we give some numerical examples to test the efficiency of the algorithm.

Bonnans, J. Frederic, E-mail: frederic.bonnans@inria.fr [Ecole Polytechnique, INRIA-Saclay (France); Tan Xiaolu, E-mail: xiaolu.tan@polytechnique.edu [Ecole Polytechnique, CMAP (France)

2013-08-01T23:59:59.000Z

11

Adaptive genetic programming for option pricing  

Science Conference Proceedings (OSTI)

Genetic Programming (GP) is an automated computational programming methodology, inspired by the workings of natural evolution techniques. It has been applied to solve complex problems in multiple domains including finance. This paper illustrates the ... Keywords: enetic programming, options pricing

Zheng Yin; Anthony Brabazon; Conall O'Sullivan

2007-07-01T23:59:59.000Z

12

A multi-level Monte Carlo FPGA accelerator for option pricing in the Heston model  

Science Conference Proceedings (OSTI)

The increasing demand for fast and accurate product pricing and risk computation together with high energy costs currently make finance and insurance institutes to rethink their IT infrastructure. Heterogeneous systems including specialized accelerator ...

Christian de Schryver; Pedro Torruella; Norbert Wehn

2013-03-01T23:59:59.000Z

13

Attachment 6 Volume V Pricing Matrix for Optional Enhancements...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Attachment 6 Volume V Pricing Matrix for Optional Enhancements.xls&0; Attachment 6 Volume V Pricing Matrix for Optional Enhancements.xls&0; Attachment 6 Volume V Pricing Matrix...

14

Renewal equations for option pricing  

E-Print Network (OSTI)

In this paper we will develop an original approach, based in the use of renewal equations, for obtaining pricing expressions for financial instruments whose underlying asset can be solely described through a simple continuous-time random walk (CTRW). This enhances the potential use of CTRW techniques in finance. We solve these equations for different contract specifications in a particular but exemplifying case. We recover the celebrated results for the Wiener process under certain limits.

Montero, Miquel

2007-01-01T23:59:59.000Z

15

Pricing Discretely Monitored Asian Options by Maturity Randomization  

Science Conference Proceedings (OSTI)

We present a new methodology based on maturity randomization to price discretely monitored arithmetic Asian options when the underlying asset evolves according to a generic Lévy process. Our randomization technique considers the option expiry ... Keywords: Asian option, Lévy process, discrete monitoring, fast Fourier transform, integral equation, option pricing, quadrature formula

Gianluca Fusai; Daniele Marazzina; Marina Marena

2011-01-01T23:59:59.000Z

16

PRICING A CLASS OF EXOTIC OPTIONS VIA MOMENTS AND SDP ...  

E-Print Network (OSTI)

which have been considered in the interest rate and the real option theories. In fact, any ... Here, T > 0 is the option's maturity time, K is the option's strike price,.

17

Exotic options under Lévy models: An overview  

Science Conference Proceedings (OSTI)

In this paper, we overview the pricing of several so-called exotic options in the nowadays quite popular exponential Levy models. Keywords: Exotic options, Financial derivatives, Lèvy processes

Wim Schoutens

2006-05-01T23:59:59.000Z

18

Rolling Up a Put Option as Prices Increase  

E-Print Network (OSTI)

Agricultural producers use put options to protect themselves against declining prices. The technique of "rolling up a put option, explained in this publication, allows the producer to raise the minimum expected selling price of a put option. Detailed examples are given for using this marketing method.

Johnson, Jason; Polk, Wade

2008-10-07T23:59:59.000Z

19

Quantum extension of European option pricing based on the Ornstein-Uhlenbeck process  

E-Print Network (OSTI)

In this work we propose a option pricing model based on the Ornstein-Uhlenbeck process. It is a new look at the Black-Scholes formula which is based on the quantum game theory. We show the differences between a classical look which is price changing by a Wiener process and the pricing is supported by a quantum model.

Edward W. Piotrowski; Malgorzata Schroeder; Anna Zambrzycka

2005-10-16T23:59:59.000Z

20

Price protection options for West Virginia beef cattle producers.  

E-Print Network (OSTI)

??The purpose of this study was to determine if a price protection option would be beneficial to West Virginia's beef cattle industry. Fourteen years of… (more)

Kleski, Matthew C., 1979-

2004-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "option pricing model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


21

On Asian option pricing for NIG Lévy processes  

Science Conference Proceedings (OSTI)

In this paper, we derive approximations and bounds for the Esscher price of European-style arithmetic and geometric average options. The asset price process is assumed to be of exponential Lévy type with normal inverse Gaussian (NIG) distributed ... Keywords: Esscher transform, comonotonicity, normal inverse Gaussian distribution

Hansjörg Albrecher; Martin Predota

2004-11-01T23:59:59.000Z

22

Expected annual electricity bill savings for various PPA price options |  

Open Energy Info (EERE)

Expected annual electricity bill savings for various PPA price options Expected annual electricity bill savings for various PPA price options Jump to: navigation, search Impact of Utility Rates on PV Economics Bill savings tables (main section): When evaluating PV systems under a PPA, it is important to look at the net effect on the building's annual electricity expense. If the solar value is greater than the PPA price, then the building will realize a net savings on annual energy expenses. If the solar value is less than the PPA price, then the building will realize a net loss. It is useful to understand how annual electricity expenses will be impacted at various PPA price levels. Bill Savings at PPA price of $0.04/kWhr Bill Savings at PPA price of $0.08/kWhr Bill Savings at PPA price of $0.12/kWhr Retrieved from "http://en.openei.org/w/index.php?title=Expected_annual_electricity_bill_savings_for_various_PPA_price_options&oldid=515464"

23

Pricing American Asian options with higher moments in the underlying distribution  

Science Conference Proceedings (OSTI)

We develop a modified Edgeworth binomial model with higher moment consideration for pricing American Asian options. With lognormal underlying distribution for benchmark comparison, our algorithm is as precise as that of Chalasani et al. [P. Chalasani, ... Keywords: American Asian options, Edgeworth binomial model, Higher moment

Keng-Hsin Lo; Kehluh Wang; Ming-Feng Hsu

2009-01-01T23:59:59.000Z

24

Options on Stock Indices, Precious Metals Debt, and Foreign Currency: Tests of Boundary Conditions and Pricing Models  

E-Print Network (OSTI)

5 b ) , and Shastri and & Tandon f i n d t h a t p rtransactions prices of it Tandon use about s i x t o t e nGerman mark S h a s t r i fc Tandon ( 1 9 8 5 ) and Whaley <

Bailey, Warren

1985-01-01T23:59:59.000Z

25

Bounds for the price of discrete arithmetic Asian options  

Science Conference Proceedings (OSTI)

In this paper the pricing of European-style discrete arithmetic Asian options with fixed and floating strike is studied by deriving analytical lower and upper bounds. In our approach we use a general technique for deriving upper (and lower) bounds for ... Keywords: Asian option, Black and Scholes setting, analytical bounds, comonotonicity

M. Vanmaele; G. Deelstra; J. Liinev; J. Dhaene; M. J. Goovaerts

2006-01-01T23:59:59.000Z

26

Moment matching approximation of Asian basket option prices  

Science Conference Proceedings (OSTI)

In this paper we propose some moment matching pricing methods for European-style discrete arithmetic Asian basket options in a Black & Scholes framework. We generalize the approach of [M. Curran, Valuing Asian and portfolio by conditioning on the geometric ... Keywords: 60J65, 91B28, Asian basket option, Log-extended-skew-normal, Moment matching, Sum of non-independent random variables

Griselda Deelstra; Ibrahima Diallo; Michèle Vanmaele

2010-06-01T23:59:59.000Z

27

Bounds for the price of discrete arithmetic Asian options  

Science Conference Proceedings (OSTI)

In this paper the pricing of European-style discrete arithmetic Asian options with fixed and floating strike is studied by deriving analytical lower and upper bounds. In our approach we use a general technique for deriving upper (and lower) bounds for ... Keywords: Analytical bounds, Asian option, Black and Scholes setting, Comonotonicity

M. Vanmaele; G. Deelstra; J. Liinev; J. Dhaene; M. J. Goovaerts

2006-01-01T23:59:59.000Z

28

Methods for Pricing American Options under Regime Switching  

Science Conference Proceedings (OSTI)

We analyze a number of techniques for pricing American options under a regime switching stochastic process. The techniques analyzed include both explicit and implicit discretizations with the focus being on methods which are unconditionally stable. In ... Keywords: American options, iterative methods, regime switching

Y. Huang; P. A. Forsyth; G. Labahn

2011-09-01T23:59:59.000Z

29

A Threshold Autoregressive Model for Wholesale Electricity Prices  

E-Print Network (OSTI)

A Threshold Autoregressive Model for Wholesale Electricity Prices B. Ricky Rambharat Carnegie model; electricity prices; spikes; Markov chain Monte Carlo. 1. Introduction The dynamics of electricity of electricity price dynamics is essential for pricing and hedging financial futures and options on power

30

Simulating option prices and sensitivities by higher rank lattice rules  

Science Conference Proceedings (OSTI)

In this paper we introduce the intermediate rank or higher rank lattice rule for the general case when the number of quadrature points is ntm, where m is a composite integer, t is the rank of the rule, n is an integer ... Keywords: Monte Carlo and Quasi-Monte Carlo methods, lattice rules, option pricing, simulation of multivariate integrations

Yongzeng Lai

2006-05-01T23:59:59.000Z

31

Perturbation Expansion for Option Pricing with Stochastic Volatility  

E-Print Network (OSTI)

We fit the volatility fluctuations of the S&P 500 index well by a Chi distribution, and the distribution of log-returns by a corresponding superposition of Gaussian distributions. The Fourier transform of this is, remarkably, of the Tsallis type. An option pricing formula is derived from the same superposition of Black-Scholes expressions. An explicit analytic formula is deduced from a perturbation expansion around a Black-Scholes formula with the mean volatility. The expansion has two parts. The first takes into account the non-Gaussian character of the stock-fluctuations and is organized by powers of the excess kurtosis, the second is contract based, and is organized by the moments of moneyness of the option. With this expansion we show that for the Dow Jones Euro Stoxx 50 option data, a Delta-hedging strategy is close to being optimal.

Jizba, Petr; Haener, Patrick

2007-01-01T23:59:59.000Z

32

Perturbation Expansion for Option Pricing with Stochastic Volatility  

E-Print Network (OSTI)

We fit the volatility fluctuations of the S&P 500 index well by a Chi distribution, and the distribution of log-returns by a corresponding superposition of Gaussian distributions. The Fourier transform of this is, remarkably, of the Tsallis type. An option pricing formula is derived from the same superposition of Black-Scholes expressions. An explicit analytic formula is deduced from a perturbation expansion around a Black-Scholes formula with the mean volatility. The expansion has two parts. The first takes into account the non-Gaussian character of the stock-fluctuations and is organized by powers of the excess kurtosis, the second is contract based, and is organized by the moments of moneyness of the option. With this expansion we show that for the Dow Jones Euro Stoxx 50 option data, a Delta-hedging strategy is close to being optimal.

Petr Jizba; Hagen Kleinert; Patrick Haener

2007-08-22T23:59:59.000Z

33

Original article: Using the continuous price as control variate for discretely monitored options  

Science Conference Proceedings (OSTI)

Variance reduction is of highest importance in financial simulation. In this study, we present a new and simple variance reduction technique for pricing discretely monitored lookback and barrier options. It is based on using the corresponding continuously ... Keywords: Control variate, Option pricing, Path dependent options, Variance reduction

Kemal Dinçer Dingeç; Wolfgang Hörmann

2011-12-01T23:59:59.000Z

34

On the Valuation of Warrants and Executive Stock Options: Pricing Formulae for Firms with Multiple Warrants/Executive Options  

E-Print Network (OSTI)

of the options or canceling an executive's existing options and granting him or her new options with a lower strike price, although not as frequent, are also in the agenda. Among others, Brenner, Sundaram, and Yermack (2000), Carter and Lynch (2001) examine... the “repricing” of ESOs and allocate it to poor firm-specific performance. The empirical evidence in Chance, Kumar, and Todd (2000) suggest that ESOs are usually repriced when the stock declines by about 25%. Acharya, John, and Sundaram (2000) investigate...

Darsinos, Theofanis; Satchell, Stephen E

2004-06-16T23:59:59.000Z

35

High-order accurate implicit methods for the pricing of barrier options  

E-Print Network (OSTI)

This paper deals with a high-order accurate implicit finite-difference approach to the pricing of barrier options. In this way various types of barrier options are priced, including barrier options paying rebates, and options on dividend-paying-stocks. Moreover, the barriers may be monitored either continuously or discretely. In addition to the high-order accuracy of the scheme, and the stretching effect of the coordinate transformation, the main feature of this approach lies on a probability-based optimal determination of boundary conditions. This leads to much faster and accurate results when compared with similar pricing approaches. The strength of the present scheme is particularly demonstrated in the valuation of discretely monitored barrier options where it yields values closest to those obtained from the only semi-analytical valuation method available.

Ndogmo, J C

2007-01-01T23:59:59.000Z

36

Pricing A Class of Multiasset Options using Information on Smaller ...  

E-Print Network (OSTI)

Mar 19, 2007 ... Information on Smaller Subsets of Assets. ? .... (iii) In Section 4, we extend the results to the finite market case where only the prices of a finite.

37

Asymptotic expansion for pricing options for a mean-reverting asset with multiscale stochastic volatility  

Science Conference Proceedings (OSTI)

This work investigates the valuation of options when the underlying asset follows a mean-reverting log-normal process with a stochastic volatility that is driven by two stochastic processes with one persistent factor and one fast mean-reverting factor. ... Keywords: Mean reversion, Multiscale asymptotic, Option pricing, Stochastic volatility

Mei Choi Chiu; Yu Wai Lo; Hoi Ying Wong

2011-07-01T23:59:59.000Z

38

Using high performance computing and Monte Carlo simulation for pricing american options  

E-Print Network (OSTI)

High performance computing (HPC) is a very attractive and relatively new area of research, which gives promising results in many applications. In this paper HPC is used for pricing of American options. Although the American options are very significant in computational finance; their valuation is very challenging, especially when the Monte Carlo simulation techniques are used. For getting the most accurate price for these types of options we use Quasi Monte Carlo simulation, which gives the best convergence. Furthermore, this algorithm is implemented on both GPU and CPU. Additionally, the CUDA architecture is used for harnessing the power and the capability of the GPU for executing the algorithm in parallel which is later compared with the serial implementation on the CPU. In conclusion this paper gives the reasons and the advantages of applying HPC in computational finance.

Cvetanoska, Verche

2012-01-01T23:59:59.000Z

39

Internet Resource Pricing Models, Mechanisms, and Methods  

E-Print Network (OSTI)

With the fast development of video and voice network applications, CDN (Content Distribution Networks) and P2P (Peer-to-Peer) content distribution technologies have gradually matured. How to effectively use Internet resources thus has attracted more and more attentions. For the study of resource pricing, a whole pricing strategy containing pricing models, mechanisms and methods covers all the related topics. We first introduce three basic Internet resource pricing models through an Internet cost analysis. Then, with the evolution of service types, we introduce several corresponding mechanisms which can ensure pricing implementation and resource allocation. On network resource pricing methods, we discuss the utility optimization in economics, and emphasize two classes of pricing methods (including system optimization and entities' strategic optimizations). Finally, we conclude the paper and forecast the research direction on pricing strategy which is applicable to novel service situation in the near future.

He, Huan; Liu, Ying

2011-01-01T23:59:59.000Z

40

A price discrimination modeling using geometric programming  

Science Conference Proceedings (OSTI)

This paper presents a price discrimination model which determines the product's selling price and marketing expenditure in two markets. We assume production as a function of price and marketing cost in two states. The cost of production is also assumed ... Keywords: economics, mathematical programming, production and operations management

Seyed J. Sadjadi; M. Ziaee

2006-05-01T23:59:59.000Z

Note: This page contains sample records for the topic "option pricing model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


41

Attachment 6 Volume V Pricing Matrix for Optional Enhancements.xls  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

6 6 VOLUME V Logistics Services A-76 Study - Service Provider Price Offer for Optional Enhancement, Volume V. Service Provider Name: GSA Schedule Contract Number: Expiration Date of GSA Schedule Contract: 1. PRIME SERVICE PROVIDER COMMERCIAL DISCOUNT ATO FEDERAL OR BASE LABOR PERCENTAGE COMMERCIAL PROPOSED TOTAL GSA LABOR RATE RATE/HOUR FROM GSA RATE BURDENED RATE HOURS PROPOSED COST SUBTOTAL $ 2. TEAM MEMBER (Subcontractor) COMMERCIAL DISCOUNT ATO FEDERAL OR BASE LABOR PERCENTAGE COMMERCIAL PROPOSED TOTAL GSA LABOR RATE RATE/HOUR FROM GSA RATE BURDENED RATE HOURS PROPOSED COST SUBTOTAL $ 3. OTHER DIRECT COST Must be applied by both the commercial service provider and the ATO $ -0- Approved G&A or Material Handling Rate % $ TOTAL PROPOSED COST $ PRICE MATRIX OPTIONAL ENHANCEMENT NUMBER ___________

42

Real-Time Pricing as an Optional Service: It's Alive, But Is It Well?  

Science Conference Proceedings (OSTI)

A small number of programs have demonstrated that RTP, offered as an optional tariff, is capable of attracting a substantial number of participants and that at least some of these customers are able and willing to respond when hourly prices rise. However, for the vast majority of programs, modest participation rates have limited the significance of their demand response impacts. Policymakers must therefore be realistic about the likely reception of RTP among customers that have become accustomed to fixed retail rates.

Goldman, Charles; Barbose, Galen; Neenan, Bernie

2006-02-01T23:59:59.000Z

43

Levy process-driven mean-reverting electricity price model: the marginal distribution analysis  

Science Conference Proceedings (OSTI)

We propose a class of stochastic mean-reverting models for electricity prices with Levy process-driven Ornstein-Uhlenbeck (OU) processes being the building blocks. We first fit marginal distributions of power price series to two special classes of distributions ... Keywords: Correlation structure, Electricity market signals, Electricity option pricing, Heavy-tail, Levy process, Ornstein-Uhlenbeck type process, Risk management, Unbalanced-tail

Shi-Jie Deng; Wenjiang Jiang

2005-10-01T23:59:59.000Z

44

Oil price shocks: Testing a macroeconomic model  

SciTech Connect

The main research objective was to answer the following question: Will Consumer Price Index forecast models utilizing computer oil-consumption ratios have better predictive capability as indicated by lower numerical differences from actual results than a model utilizing oil prices as the energy-related variable Multiple linear regressions were run on the components of the United States CPI to reduce them to a kernel set with meaningful predictive capability. New linear regressions were run with this kernel set and crude oil prices during the 1973 to 1984 time period. Crude oil prices were rationalized with a 1972 = 100 based index of GNP base petroleum consumption, the index of net energy imports, and the index of petroleum imports to create new oil substitute constructs to be used in multiple regressions with the CPI. Predictions obtained from the model were compared with actual results in the 1985-1987 time period to determine which model version showed the greatest predictive power. Results of the model tests show that oil prices are strongly related to the CPI, but neither the use of oil prices or the index of GNP-based petroleum consumption produced results that closely predict future prices.

Williams, D.D.

1988-01-01T23:59:59.000Z

45

Wind Derivatives: Modeling and Pricing  

Science Conference Proceedings (OSTI)

Wind is considered to be a free, renewable and environmentally friendly source of energy. However, wind farms are exposed to excessive weather risk since the power production depends on the wind speed, the wind direction and the wind duration. This risk ... Keywords: Forecasting, Pricing, Wavelet networks, Weather derivatives, Wind derivatives

A. Alexandridis; A. Zapranis

2013-03-01T23:59:59.000Z

46

Seasonal Volatility in Energy Prices: Modeling Seasonality in Natural Gas and Electricity Price Volatility  

Science Conference Proceedings (OSTI)

The modeling and measurement of price uncertainty are essential prerequisites to asset valuation and risk management in electric power. Practical, realistic models must take into account the systematic time patterns exhibited by price volatility. This report uses new data and techniques to reexamine the seasonal nature of energy price volatility.

2004-12-15T23:59:59.000Z

47

A NONGAUSSIAN ORNSTEINUHLENBECK PROCESS FOR ELECTRICITY SPOT PRICE MODELING AND  

E-Print Network (OSTI)

A NON­GAUSSIAN ORNSTEIN­UHLENBECK PROCESS FOR ELECTRICITY SPOT PRICE MODELING AND DERIVATIVES for analytical pricing of electricity forward and futures contracts. Electricity forward and futures contracts to capture the observed dynamics of electricity spot prices. We also discuss the pricing of European call

Kallsen, Jan

48

Price and Non-Price Influences on Water Conservation: An Econometric Model of Aggregate Demand under Nonlinear Budget Constraint  

E-Print Network (OSTI)

PRICE INFLUENCES ON WATER CONSERVATION: ECONOMETRIC AN MODELPrice Influences on Water Conservation: An Econometric ModelPrice Influences on Water Conservation: An Econometric Model

Corral, Leonardo; Fisher, Anthony C.; Hatch, Nile W.

1999-01-01T23:59:59.000Z

49

Swing options: a mechanism for pricing IT peak demand, http: //www.hpl.hp.com/research/idl/papers/swings  

E-Print Network (OSTI)

Since usage patterns of information technology within organizations can be bursty, the peak demand for IT resources can at times exceed the installed capacity within the enterprise. If providers of such peak capacity emerge, as was the case for electricity and natural gas, the problem arises as to how to efficiently provide and price such peak demand. We present a swing option mechanism that allows for the efficient pricing of IT resources ranging from CPU usage to storage and bandwidth. This mechanism allows users to buy the right but not the obligation to future peak use. A statistical simulation tool allows the users to price these swings according to their own utilization patterns and to recover some of their costs if the options are not exercised. The provider in turn exploits its ability to statistically multiplex its resources to price peak usage. The use of these swing options serves as an incentive to the users to accurately forecasts of their own needs, thus leading to more efficient utilization of the provider’s resources.

Scott H. Clearwater; Bernardo A. Huberman

2005-01-01T23:59:59.000Z

50

A Geographically Weighted Hedonic Pricing Model  

E-Print Network (OSTI)

Wind power is the most important renewable energy source in many countries today, characterized by a rapid and extensive diffusion since the 1990s. However, it has also triggered much debate with regard to the impact on landscape and vista. Therefore, siting processes of wind farm projects are often accompanied by massive public protest, because of visual and aural impacts on the surrounding area. These mostly negative consequences are often reflected in property values and house prices. The aim of this paper is to investigate the impact of wind farms on the surrounding property values by means of a geographically-weighted hedonic pricing model. By comparing the predictive performance of standard Ordinary Least Squares (OLS) regression models and Geographically Weighted Regression (GWR) models, we find that, mainly due to a local clustering bias, global OLS estimation is inadequate for capturing the impacts of wind farm proximity on

Yasin Sunak; Reinhard Madlener; Yasin Sunak; Reinhard Madlener; Y. Sunak; R. Madlener

2012-01-01T23:59:59.000Z

51

Why are gasoline prices sticky? A test of alternative models of price adjustment  

E-Print Network (OSTI)

Several macroeconomic models of business cycles rely on the assumption that …rms adjust prices infrequently to generate the short-run non-neutrality of money documented by the literature on monetary transmission. These models posit di¤erent mechanisms to generate price stickiness, with correspondingly di¤erent implications for in‡ation dynamics. While empirical implications regarding the response to macro shocks are indistinguishable on a time series of daily price changes, the models have distinct predictions on the dynamic patterns of price adjustment. In this paper, we use daily data on wholesale gasoline prices to test three explanations for price stickiness: menu-costs, information processing, and strategic interactions. Using an autoregressive conditional binomial (ACB) model, we show that both the past distribution of price changes and the lagged gap have signi…cant explanatory power for the probability of a price change over and above the current price-cost gap. Our results have important implications regarding which of the three explanations (menu-costs, information processing, or strategic interactions) best …ts the observed wholesale gasoline data. First, the signi…cant e¤ect of the historic distribution of price changes leads us to reject menu-costs as an explanation for price

Christopher Douglas; Ana María Herrera

2009-01-01T23:59:59.000Z

52

Asymmetric pricing: an agent based model  

Science Conference Proceedings (OSTI)

Asymmetric pricing is the tendency of prices to rise readily and fall slowly. Explanations of asymmetric pricing mention monopoly power, costs of changing prices or spreading information, and elasticity differences. In this paper we describe a general ... Keywords: agent based simulation, asymmetric pricing, competitive equilibria, microeconomy

Federico Cecconi; Domenico Parisi

2007-05-01T23:59:59.000Z

53

FPGA acceleration using high-level languages of a Monte-Carlo method for pricing complex options  

Science Conference Proceedings (OSTI)

In this paper we present an FPGA implementation of a Monte-Carlo method for pricing Asian options using Impulse C and floating-point arithmetic. In an Altera Stratix-V FPGA, a 149x speedup factor was obtained against an OpenMP-based solution in a 4-core ... Keywords: Field programmable gate arrays, Financial data processing, Floating-point arithmetic, High level language synthesis, Parallel machines

Diego Sanchez-Roman, Victor Moreno, Sergio Lopez-Buedo, Gustavo Sutter, Ivan Gonzalez, Francisco J. Gomez-Arribas, Javier Aracil

2013-03-01T23:59:59.000Z

54

A Threshold Autoregressive Model for Wholesale Electricity Prices  

E-Print Network (OSTI)

A Threshold Autoregressive Model for Wholesale Electricity Prices B. Ricky Rambharat, Department, 2003 Abstract We introduce a discrete-time model for electricity prices, which accounts for both spikes Introduction The study of electricity price dynamics has attracted significant attention from researchers

55

Real Time Pricing as a Default or Optional Service for C&ICustomers: A Comparative Analysis of Eight Case Studies  

Science Conference Proceedings (OSTI)

Demand response (DR) has been broadly recognized to be an integral component of well-functioning electricity markets, although currently underdeveloped in most regions. Among the various initiatives undertaken to remedy this deficiency, public utility commissions (PUC) and utilities have considered implementing dynamic pricing tariffs, such as real-time pricing (RTP), and other retail pricing mechanisms that communicate an incentive for electricity consumers to reduce their usage during periods of high generation supply costs or system reliability contingencies. Efforts to introduce DR into retail electricity markets confront a range of basic policy issues. First, a fundamental issue in any market context is how to organize the process for developing and implementing DR mechanisms in a manner that facilitates productive participation by affected stakeholder groups. Second, in regions with retail choice, policymakers and stakeholders face the threshold question of whether it is appropriate for utilities to offer a range of dynamic pricing tariffs and DR programs, or just ''plain vanilla'' default service. Although positions on this issue may be based primarily on principle, two empirical questions may have some bearing--namely, what level of price response can be expected through the competitive retail market, and whether establishing RTP as the default service is likely to result in an appreciable level of DR? Third, if utilities are to have a direct role in developing DR, what types of retail pricing mechanisms are most appropriate and likely to have the desired policy impact (e.g., RTP, other dynamic pricing options, DR programs, or some combination)? Given a decision to develop utility RTP tariffs, three basic implementation issues require attention. First, should it be a default or optional tariff, and for which customer classes? Second, what types of tariff design is most appropriate, given prevailing policy objectives, wholesale market structure, ratemaking practices and standards, and customer preferences? Third, if a primary goal for RTP implementation is to induce DR, what types of supplemental activities are warranted to support customer participation and price response (e.g., interval metering deployment, customer education, and technical assistance)?

Barbose, Galen; Goldman, Charles; Bharvirkar, Ranjit; Hopper,Nicole; Ting, Michael; Neenan, Bernie

2005-08-01T23:59:59.000Z

56

Modeling and simulation of consumer response to dynamic pricing.  

Science Conference Proceedings (OSTI)

Assessing the impacts of dynamic-pricing under the smart grid concept is becoming extremely important for deciding its full deployment. In this paper, we develop a model that represents the response of consumers to dynamic pricing. In the model, consumers use forecasted day-ahead prices to shift daily energy consumption from hours when the price is expected to be high to hours when the price is expected to be low while maintaining the total energy consumption as unchanged. We integrate the consumer response model into the Electricity Market Complex Adaptive System (EMCAS). EMCAS is an agent-based model that simulates restructured electricity markets. We explore the impacts of dynamic-pricing on price spikes, peak demand, consumer energy bills, power supplier profits, and congestion costs. A simulation of an 11-node test network that includes eight generation companies and five aggregated consumers is performed for a period of 1 month. In addition, we simulate the Korean power system.

Valenzuela, J.; Thimmapuram, P.; Kim, J (Decision and Information Sciences); (Auburn Univ.)

2012-08-01T23:59:59.000Z

57

Five Facts About Prices: A Reevaluation of Menu Cost Models  

E-Print Network (OSTI)

We establish five facts about prices in the U.S. economy: 1) The median implied duration of consumer prices when sales are excluded at the product level is between 8 and 11 months. The median implied duration of finished goods producer prices is 8.7 months. 2) One-third of regular price changes are price decreases. 3) The frequency of price increases responds strongly to inflation while the frequency of price decreases and the size of price increases and price decreases do not. 4) The frequency of price change is highly seasonal: It is highest in the 1st quarter and lowest in the 4th quarter. 5) The hazard function of price changes for individual consumer and producer goods is downward sloping for the first few months and then flat (except for a large spike at 12 months in consumer services and all producer prices). These facts are based on CPI microdata and a new comprehensive data set of microdata on producer prices that we construct from raw production files underlying the PPI. We show that the 1st, 2nd and 3rd facts are consistent with a benchmark menu-cost model, while the 4th and 5th facts are not.

Emi Nakamura; Jón Steinsson

2006-01-01T23:59:59.000Z

58

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

against the risk of energy price fluctuations. In theory,The poor track record of energy price forecasting models hasof information about future energy prices, including most

Wong-Parodi, Gabrielle; Dale, Larry; Lekov, Alex

2005-01-01T23:59:59.000Z

59

Forecasting Natural Gas Prices Using Time Series Models .  

E-Print Network (OSTI)

??The objective of this thesis is to estimate the natural gas component of the All Urban Consumer Price Index (CP-U) using time series forecasting models.… (more)

Berg, Andrew

2006-01-01T23:59:59.000Z

60

Electricity Price Curve Modeling and Forecasting by Manifold Learning  

E-Print Network (OSTI)

This paper proposes a novel nonparametric approach for the modeling and analysis of electricity price curves by applying the manifold learning methodology—locally linear embedding (LLE). The prediction method based on manifold learning and reconstruction is employed to make short-term and mediumterm price forecasts. Our method not only performs accurately in forecasting one-day-ahead prices, but also has a great advantage in predicting one-week-ahead and one-month-ahead prices over other methods. The forecast accuracy is demonstrated by numerical results using historical price data taken from the Eastern U.S. electric power markets.

Jie Chen; Shi-Jie Deng; Xiaoming Huo

2008-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "option pricing model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


61

Multi-layer model of correlated energy prices  

Science Conference Proceedings (OSTI)

In this article we develop an extension of the affine jump-diffusion modeling framework and use it to build an intuitive and tractable model of an energy price complex. The development is motivated by the need to model prices of electricity while capturing ... Keywords: Affine jump-diffusion, Correlation, Electricity markets

Slimane Grine; Pavel Diko

2010-03-01T23:59:59.000Z

62

Prices  

Gasoline and Diesel Fuel Update (EIA)

Information AdministrationPetroleum Marketing Annual 1998 Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon Excluding Taxes) -...

63

Prices  

Gasoline and Diesel Fuel Update (EIA)

Information AdministrationPetroleum Marketing Annual 2001 Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon Excluding Taxes) -...

64

Prices  

Annual Energy Outlook 2012 (EIA)

Information AdministrationPetroleum Marketing Annual 1999 Table 31. Motor Gasoline Prices by Grade, Sales Type, PAD District, and State (Cents per Gallon Excluding Taxes) -...

65

Forecasting Model for Crude Oil Price Using Artificial Neural Networks and Commodity Futures Prices  

E-Print Network (OSTI)

This paper presents a model based on multilayer feedforward neural network to forecast crude oil spot price direction in the short-term, up to three days ahead. A great deal of attention was paid on finding the optimal ANN model structure. In addition, several methods of data pre-processing were tested. Our approach is to create a benchmark based on lagged value of pre-processed spot price, then add pre-processed futures prices for 1, 2, 3,and four months to maturity, one by one and also altogether. The results on the benchmark suggest that a dynamic model of 13 lags is the optimal to forecast spot price direction for the short-term. Further, the forecast accuracy of the direction of the market was 78%, 66%, and 53% for one, two, and three days in future conclusively. For all the experiments, that include futures data as an input, the results show that on the short-term, futures prices do hold new information on the spot price direction. The results obtained will generate comprehensive understanding of the cr...

Kulkarni, Siddhivinayak

2009-01-01T23:59:59.000Z

66

Pricing the Internet - A visual 3-Dimensional Evaluation Model  

E-Print Network (OSTI)

We develop a novel visual approach to evaluating an Internet pricing scheme using a 3Dmetric model, which encompasses the dimensions of technical complexity, economic efficiency and social impact. We review the history of Internet pricing research over the last decade, summarizing the key features of the most significant models, and analyzing and evaluating them using our 3D model. Based on the analysis results, we address and discuss important factors that have inhibited the deployment of the reviewed models and suggest what might be future Internet pricing solutions.

Thuy T.T. Nguyen; Grenville J. Armitage

2003-01-01T23:59:59.000Z

67

On the effectiveness of returns policies in the price-dependent newsvendor model  

E-Print Network (OSTI)

5] Granot, D. and S. Yin. Price and Order Postponement inNewsvendor Model with Price-Dependent Demand. Working Paper.of Returns Policies in the Price-Dependent Newsvendor Model.

Granot, D; Yin, Shuya Y

2005-01-01T23:59:59.000Z

68

Short-Term Energy Outlook Model Documentation: Regional Residential Heating Oil Price Model  

Reports and Publications (EIA)

The regional residential heating oil price module of the Short-Term Energy Outlook (STEO) model is designed to provide residential retail price forecasts for the 4 census regions: Northeast, South, Midwest, and West.

Information Center

2009-11-09T23:59:59.000Z

69

Short-Term Energy Outlook Model Documentation: Regional Residential Propane Price Model  

Reports and Publications (EIA)

The regional residential propane price module of the Short-Term Energy Outlook (STEO) model is designed to provide residential retail price forecasts for the 4 census regions: Northeast, South, Midwest, and West.

Information Center

2009-11-09T23:59:59.000Z

70

Long-run models of oil stock prices  

Science Conference Proceedings (OSTI)

The identification of the forces that drive oil stock prices is extremely important given the size of the Oil & Gas industry and its links with the energy sector and the environment. In the next decade oil companies will have to deal with international ... Keywords: C32, Cointegration, Energy, Environment, Hydrocarbon fuels, L71, Non-renewable resources, Oil companies, Oil stock prices, Q30, Q40, Vector error correction models

Alessandro Lanza; Matteo Manera; Margherita Grasso; Massimo Giovannini

2005-11-01T23:59:59.000Z

71

Analysis of price diffusion in financial markets using PUCK model  

E-Print Network (OSTI)

Based on the new type of random walk process called the Potentials of Unbalanced Complex Kinetics (PUCK) model, we theoretically show that the price diffusion in large scales is amplified 2/(2 + b) times, where b is the coefficient of quadratic term of the potential. In short time scales the price diffusion depends on the size M of the super moving average. Both numerical simulations and real data analysis of Yen-Dollar rates are consistent with theoretical analysis.

Mizuno, T; Takayasu, M; Mizuno, Takayuki; Takayasu, Hideki; Takayasu, Misako

2006-01-01T23:59:59.000Z

72

Model documentation: Electricity market module, electricity finance and pricing submodule  

SciTech Connect

The purpose of this report is to define the objectives of the model, describe its basic approach, and provide detail on how it works. The EFP is a regulatory accounting model that projects electricity prices. The model first solves for revenue requirements by building up a rate base, calculating a return on rate base, and adding the allowed expenses. Average revenues (prices) are calculated based on assumptions regarding regulator lag and customer cost allocation methods. The model then solves for the internal cash flow and analyzes the need for external financing to meet necessary capital expenditures. Finally, the EFP builds up the financial statements. The EFP is used in conjunction with the National Energy Modeling System (NEMS). Inputs to the EFP include the forecast generating capacity expansion plans, operating costs, regulator environment, and financial data. The outputs include forecasts of income statements, balance sheets, revenue requirements, and electricity prices.

1994-04-07T23:59:59.000Z

73

Joint Modelling of Gas and Electricity spot prices  

E-Print Network (OSTI)

The recent liberalization of the electricity and gas markets has resulted in the growth of energy exchanges and modelling problems. In this paper, we modelize jointly gas and electricity spot prices using a mean-reverting model which fits the correlations structures for the two commodities. The dynamics are based on Ornstein processes with parameterized diffusion coefficients. Moreover, using the empirical distributions of the spot prices, we derive a class of such parameterized diffusions which captures the most salient statistical properties: stationarity, spikes and heavy-tailed distributions. The associated calibration procedure is based on standard and efficient statistical tools. We calibrate the model on French for electricity and on UK market for gas, and then simulate some trajectories which reproduce well the observed prices behavior. Finally, we illustrate the importance of the correlation structure and of the presence of spikes by measuring the risk on a power plant portfolio.

Frikha, Noufel

2009-01-01T23:59:59.000Z

74

Crude Oil Price Prediction Using Slantlet Denoising Based Hybrid Models  

Science Conference Proceedings (OSTI)

The accurate prediction of crude oil price movement has always been the central issue with profound implications across different levels of the economy. This study conducts empirical investigations into the characteristics of crude oil market and proposes ... Keywords: Slantlet Analysis, ARMA Model, Hybrid Forecasting Algorithm, Rrandom Walk Model, Support Vector Regression

Kaijian He; Kin Keung Lai; Jerome Yen

2009-04-01T23:59:59.000Z

75

On the Scarf-Hirota model in the price-scaled price adjustment process  

E-Print Network (OSTI)

Hirota's results given in (Hirota.M.,1981) on the asymptotically stability are generalized to the price-scaled price adjustment process.

Yamamoto, Tatsuro; Togawa, Yoshio; Ohya, Masanori

2008-01-01T23:59:59.000Z

76

Pricing and Cost Recovery for Internet Services: Practical Review, Classification, and Application of Relevant Models  

Science Conference Proceedings (OSTI)

Suitable pricing models for Internet services represent one of the main prerequisites for a successfully running implementation of a charging and accounting system. This paper introduces general aspects influencing the choice of a pricing model in practical ... Keywords: Internet pricing, auction pricing, cost recovery, peering agreements

Burkhard Stiller; Peter Reichl; Simon Leinen

2001-09-01T23:59:59.000Z

77

Modeling of CO2 Reduction Impacts on Energy Prices with Modelica Philip Machanick1  

E-Print Network (OSTI)

Price mean reversion rate" ; Real relEnergyPrice (start = 1); Real energyCostTrend (start = 1); Real[i,j,k]; end nextStep; equation energyCostTrend = relEnergyPrice * energyUse / baseEnergyUse; // usefulModeling of CO2 Reduction Impacts on Energy Prices with Modelica Philip Machanick1 , Ariel Liebman1

Machanick, Philip

78

Multivariate Analysis of Real Option Value Based on Grey Relational Model  

Science Conference Proceedings (OSTI)

Real option value is determined by a variety of uncertain factors. It is very important to assess the intensity and importance of these factors affecting the real option value for investment decision makers. In this paper, the real option value system ... Keywords: real option value, multivariate analysis, grey relational model, optimization

Zheng-Xin Wang; Ling-ling Pei

2011-10-01T23:59:59.000Z

79

Price supports and demand in commodity market modeling  

E-Print Network (OSTI)

Gerdner, B. L. "Futures Prices in Supply Analysis." Amer. J.Service. Spot and Futures Prices." Limited Dcpenden{avec Leuthold, R. ~1. "The Price Performance on the Futures

Riboud, Chris; Rausser, Gordon C.

1981-01-01T23:59:59.000Z

80

Optimal Execution Under Jump Models For Uncertain Price Impact  

E-Print Network (OSTI)

comes from price impacts of both the investor's own trades and other concurrent ... Indeed price impact of large trades have been considered as one of the main ...

Note: This page contains sample records for the topic "option pricing model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


81

Agent-based multi-optional model of innovations diffusion  

E-Print Network (OSTI)

We propose a formalism that allows the study of the process of diffusion of several products competing in a common market. It is based on the generalization of the statistics Ising model (Potts model). For the implementation, agent based modeling is used, applied to a problem of three options; to adopt a product A, a product B, or non-adoption. A launching strategy is analyzed for one of the two products, which delays its launching with the objective of competing with improvements. The proportion reached by one and another product is calculated at market saturation. The simulations are produced varying the social network topology, the uncertainty in the decision, and the population's homogeneity.

Laciana, Carlos E

2013-01-01T23:59:59.000Z

82

Crude Oil Price Forecasting with an Improved Model Based on Wavelet Transform and RBF Neural Network  

Science Conference Proceedings (OSTI)

The fluctuation of oil price decides the security of energy and economics. So the crude oil price forecasting performs importantly. In the paper, we apply the improved model based on Wavelet Transform and Radial Basis Function (RBF) neural network to ...

Wu Qunli; Hao Ge; Cheng Xiaodong

2009-05-01T23:59:59.000Z

83

Maximum entropy distribution of stock price fluctuations  

E-Print Network (OSTI)

The principle of absence of arbitrage opportunities allows obtaining the distribution of stock price fluctuations by maximizing its information entropy. This leads to a physical description of the underlying dynamics as a random walk characterized by a stochastic diffusion coefficient and constrained to a given value of the expected volatility, taking in this way into account the information provided by the existence of an option market. This model is validated by a comprehensive comparison with observed distributions of both price return and diffusion coefficient. Expected volatility is the only parameter in the model and can be obtained by analysing option prices. We give an analytic formulation of the probability density function for price returns which can be used to extract expected volatility from stock option data. This distribution is of high practical interest since it should be preferred to a Gaussian when dealing with the problem of pricing derivative financial contracts.

Bartiromo, Rosario

2011-01-01T23:59:59.000Z

84

COGENMASTER: A model for evaluating cogeneration options: Final report, Volume 2, User's guide  

Science Conference Proceedings (OSTI)

The COGENMASTER model was developed in this project. COGENMASTER is a micro-computer based menu-driven model which enables the user to examine the technical aspects of various types of cogeneration projects, evaluate their economic feasibility, and prepare detailed cash flow statements that spell out the costs and benefits to project participants. The model is designed to objectively evaluate and screen cogeneration options by comparing them to a base case scenario in which electricity is purchased from the utility and thermal energy is produced on-site. The model consists of many modules that may be individually edited. The different modules that constitute COGENMASTER are the technology, load shape, rates, sizing, operating, cash-flow, financing, pricing and simulation modules. A load shape library of electric and thermal loads in nine commercial buildings and seven weather zones was also developed as part of this project. In addition, a technology database of six generic cogeneration systems is also included in the package. The model has been written for IBM-PC compatible computers with 512K memory, a floppy drive and a hard disk.

Balakrishnan, S.; Limaye, D.R.; Ross, C.; Gavelis, B.; Scott, S.

1988-12-01T23:59:59.000Z

85

Real Time Pricing as a Default or Optional Service for C&I Customers: A Comparative Analysis of Eight Case Studies  

E-Print Network (OSTI)

the spot market price of energy in a competitive wholesalethrough” the spot market price of energy for all of theadditional energy at the spot market price. Another example

Barbose, Galen; Goldman, Charles; Bharvirkar, Ranjit; Hopper, Nicole; Ting, Michael; Neenan, Bernie

2005-01-01T23:59:59.000Z

86

Research on Multistep Electricity Price Model with Bidirectional Regulation for Large Consumers  

Science Conference Proceedings (OSTI)

A multistep electricity price model with bidirectional regulation is proposed for large adjustable consumers in the area with abundant hydropower. In order to guide large consumers to regulate electricity consumption manners for resource utilization, ... Keywords: multistep electricity price, bidirectional regulation, large consumers, high and low water period, Monte Carlo simulation, price elasticity of demand

Xia Lei; Dong-xian Yu; Xiao-li Bai

2010-06-01T23:59:59.000Z

87

A semi-Markov model with memory for price changes  

E-Print Network (OSTI)

We study the high frequency price dynamics of traded stocks by a model of returns using a semi-Markov approach. More precisely we assume that the intraday returns are described by a discrete time homogeneous semi-Markov which depends also on a memory index. The index is introduced to take into account periods of high and low volatility in the market. First of all we derive the equations governing the process and then theoretical results have been compared with empirical findings from real data. In particular we analyzed high frequency data from the Italian stock market from first of January 2007 until end of December 2010.

D'Amico, Guglielmo

2011-01-01T23:59:59.000Z

88

Update On The Wholesale Electricity Price Forecast & Modeling Results  

E-Print Network (OSTI)

Forecast Base Case includes § Medium Demand Forecast § Medium Natural Gas Price Forecast § Federal CO2 Rathdrum Power LLC-ID 4) CO2 Emissions - 2009 Selected Natural Gas Plants Plant level, emission percentage § Significantly lower electricity prices than 6th Plan Forecast, due to lower demand, lower gas prices, deferred

89

Buyout prices in online auctions  

E-Print Network (OSTI)

Buyout options allow bidders to instantly purchase at a specified price an item listed for sale through an online auction. A temporary buyout option disappears once a regular bid above the reserve price is made, while a ...

Gupta, Shobhit

2006-01-01T23:59:59.000Z

90

A semi-Markov model for price returns  

E-Print Network (OSTI)

We study the high frequency price dynamics of traded stocks by a model of returns using a semi-Markov approach. More precisely we assume that the intraday return are described by a discrete time homogeneous semi-Markov process and the overnight returns are modeled by a Markov chain. Based on this assumptions we derived the equations for the first passage time distribution and the volatility autocorreletion function. Theoretical results have been compared with empirical findings from real data. In particular we analyzed high frequency data from the Italian stock market from first of January 2007 until end of December 2010. The semi-Markov hypothesis is also tested through a nonparametric test of hypothesis.

D'Amico, Guglielmo

2011-01-01T23:59:59.000Z

91

Modeling and Analysis of Price-Responsive Loads in the Operation of Smart Grids.  

E-Print Network (OSTI)

??In this thesis, a demand elasticity model is developed and tested for the dispatch of high voltage power systems and microgrids. The price obtained from… (more)

Ramos-Gaete, Felipe

2013-01-01T23:59:59.000Z

92

Restaurant Industry Stock Price Forecasting Model Utilizing Artificial Neural Networks to Combine Fundamental and Technical Analysis.  

E-Print Network (OSTI)

??Stock price forecasting is a classic problem facing analysts. Forcasting models have been developed for predicting individual stocks and stock indices around the world and… (more)

Dravenstott, Ronald W.

2012-01-01T23:59:59.000Z

93

Stochastic models of electricity prices and risk premia in the PJM market.  

E-Print Network (OSTI)

??With a main focus on risk premia in a US electricity market, we propose three stochastic models for electricity spot prices. Based on the proposed… (more)

Xiao, Yuewen

2012-01-01T23:59:59.000Z

94

Real-time pricing -- supplanted by Price-risk derivatives?  

Science Conference Proceedings (OSTI)

Future trends in pricing options for wholesale electrical generation are discussed. Specifically, the effect of price derivatives on electricity consumption are examined. Economic analyses are presented for customer demand in real-time pricing scenarios with and without a price derivative hedge. It is determined that consumption will be curtailed even when price caps have been purchased. Consumption behavior is also analyzed to determine the effect of different price caps; regardless of price, consumption is curtailed in response to price.

O`Sheasy, M.

1997-03-01T23:59:59.000Z

95

Crude Oil Price Forecasting: A Transfer Learning Based Analog Complexing Model  

Science Conference Proceedings (OSTI)

Most of the existing models for oil price forecasting only use the data in the forecasted time series itself. This study proposes a transfer learning based analog complexing model (TLAC). It first transfers some related time series in source domain to ... Keywords: transfer learning method, analog complexing model, genetic algorithm, crude oil price forecasting

Jin Xiao; Changzheng He; Shouyang Wang

2012-08-01T23:59:59.000Z

96

Kinetic market models with single commodity having price fluctuations  

E-Print Network (OSTI)

We study here numerically the behavior of an ideal gas like model of markets having only one non-consumable commodity. We investigate the behavior of the steady-state distributions of money, commodity and total wealth, as the dynamics of trading or exchange of money and commodity proceeds, with local (in time) fluctuations in the price of the commodity. These distributions are studied in markets with agents having uniform and random saving factors. The self-organizing features in money distribution are similar to the cases without any commodity (or with consumable commodities), the commodity distribution shows an exponential decay. The wealth distribution shows interesting behavior: Gamma like distribution for uniform saving propensity and has the same power-law tail, as that of the money distribution for a market with agents having random saving propensity.

Chatterjee, A; Chakrabarti, Bikas K.; Chatterjee, Arnab

2006-01-01T23:59:59.000Z

97

Future world oil prices: modeling methodologies and summary of recent forecasts  

SciTech Connect

This paper has three main objectives. First, the various methodologies that have been developed to explain historical oil price changes and forecast future price trends are reviewed and summarized. Second, the paper summarizes recent world oil price forecasts, and, then possible, discusses the methodologies used in formulating those forecasts. Third, utilizing conclusions from the reviews of the modeling methodologies and the recent price forecasts, in combination with an assessment of recent and projected oil market trends, oil price projections are given for the time period 1987 to 2022. The paper argues that modeling methodologies have undergone significant evolution during the past decade as modelers increasingly recognize the complex and constantly changing structure of the world oil market. Unfortunately, at this point in time a consensus about the appropriate methodology to use in formulating oil price forecasts is yet to be reached. There is, however, a general movement toward the opinion that both economic and political factors should be considered when making price projections. Likewise, there is no consensus about future oil price trends. Forecasts differ widely. However, in general, forecasts have been adjusted downwardly in recent years. Further, an overall assessment of the forecasts and recent oil market trends suggests that oil prices will remain constant in real terms for the remainder of the 1980s. Real oil prices are expected to increase by between 2 and 3% during the 1990s and beyond. Forecasters are quick to point out, however, that all forecasts are subject to significant uncertainty. 69 references, 3 figures, 10 tables.

Curlee, T.R.

1985-04-01T23:59:59.000Z

98

Forecasting world oil prices: the evolution of modeling methodologies and summary of recent projections  

SciTech Connect

This paper has three main objectives: (1) to review and summarize the varios methodologies that have been developed to explain historical oil price changes and forecast future price trends, (2) to summarize recent world oil price forecasts, and, when possible, discuss the methodologies used in formulating those forecasts, and (3) utilizing conclusions from the reviews of the modeling methodologies and the recent price forecasts, in combination with an assessment of recent and projected oil market trends, to give oil price projections for the time period 1987 to 2022. The paper argues that modeling methodologies have undergone significant evolution during the past decade as modelers increasingly recognize the complex and constantly changing structure of the world oil market. Unfortunately, a consensus about the appropriate methodology to use in formulating oil price forecasts is yet to be reached. There is, however, a general movement toward the opinion that both economic and political factors should be considered when making price projections. Likewise, there is no consensus about future oil price trends. Forecasts differ widely. However, in general, forecasts have been adjusted downwardly in recent years. Further, an overall assessment of the forecasts and recent oil market trends suggests that oil prices will remain constant in real terms for the remainder of the 1980s. Real oil prices are expected to increase by between 2 and 3% during the 1990s and beyond. Forecasters are quick to point out, however, that all forecasts are subject to significant uncertainty. 68 references, 1 figure, 6 tables.

Curlee, T.R.

1985-01-01T23:59:59.000Z

99

Optimal Execution Under Jump Models For Uncertain Price Impact  

E-Print Network (OSTI)

Aug 13, 2012 ... A major source of the execution cost comes from price impacts of both the investor's own trades and other concurrent institutional trades.

100

Real Time Pricing as a Default or Optional Service for C&I Customers: A Comparative Analysis of Eight Case Studies  

E-Print Network (OSTI)

Response Program, ISO-NE Real-Time Price Response Program,rather than real time market prices) is more compatible withare correlated to real-time market prices, customers may be

Barbose, Galen; Goldman, Charles; Bharvirkar, Ranjit; Hopper, Nicole; Ting, Michael; Neenan, Bernie

2005-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "option pricing model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


101

Asymmetric Wholesale Pricing: Theory and Evidence  

Science Conference Proceedings (OSTI)

Asymmetric pricing or asymmetric price adjustment is the phenomenon where prices rise more readily than they fall. We offer and provide empirical support for a new theory of asymmetric pricing in wholesale prices. Wholesale prices may adjust asymmetrically ... Keywords: asymmetric price adjustment, asymmetric pricing, channel of distribution, channel pricing, cost of price adjustment, economic model, menu cost, retailing, scanner data, wholesale price

Sourav Ray; Haipeng (Allan) Chen; Mark E. Bergen; Daniel Levy

2006-03-01T23:59:59.000Z

102

Delta Hedged Option Valuation with Underlying Non-Gaussian Returns  

E-Print Network (OSTI)

The standard Black-Scholes theory of option pricing is extended to cope with underlying return fluctuations described by general probability distributions. A Langevin process and its related Fokker-Planck equation are devised to model the market stochastic dynamics, allowing us to write and formally solve the generalized Black-Scholes equation implied by dynamical hedging. A systematic expansion around a non-perturbative starting point is then implemented, recovering the Matacz's conjectured option pricing expression. We perform an application of our formalism to the real stock market and find clear evidence that while past financial time series can be used to evaluate option prices before the expiry date with reasonable accuracy, the stochastic character of volatility is an essential ingredient that should necessarily be taken into account in analytical option price modeling.

Moriconi, L

2006-01-01T23:59:59.000Z

103

Gasoline Prices  

NLE Websites -- All DOE Office Websites (Extended Search)

Gasoline Prices Gasoline Price Data Sign showing gasoline prices Local Prices: Find the cheapest gasoline prices in your area. State & Metro Area Prices: Average prices from AAA's...

104

A SURVEY OF COMMODITY MARKETS AND STRUCTURAL MODELS FOR ELECTRICITY PRICES  

E-Print Network (OSTI)

and the methods which have been proposed to handle them in spot and forward price models. We devote special sources, the main production process remains the conversion of fossil fuels like coal, gas and oil. Since and nuclear production as these plants are hardly ever setting the price. In other words, since electricity

Carmona, Rene

105

Modeling regional end user price/cost relationships in a widespread interconnected power system  

SciTech Connect

A combined programming and regression modeling approach is developed to analyze regional retail price/cost relationships for a widespread interconnected power system characterized by low population density and uniform (regulated) retail tariffs. The programming model is designed to calculate on the hour the delivered cost of electricity from 5 thermal power stations and one pumped storage hydrostation to end users in 8 distribution regions. A simultaneous equation regression model then analyses the link between retail prices charged end users, regional demand and supply characteristics, industry financial objectives and departures from economically efficient pricing. The electricity supply industry in Queensland Australia is used as a framework.

Tamaschke, R.; Docwra, G.; Stillman, R. [Univ. of Queensland, Brisbane, Queensland (Australia)

1995-11-01T23:59:59.000Z

106

www.cepe.ethz.ch A Real Options Evaluation Model for the Diffusion Prospects of New Renewable Power Generation Technologies  

E-Print Network (OSTI)

www.cepe.ethz.ch A real options evaluation model for the diffusion prospects of new renewable power generation technologies

Gürkan Kumbaroglu; Reinhard Madlener; Mustafa Demirel; Gürkan Kumbaroglu; Reinhard Madlener; Mustafa Demirel

2004-01-01T23:59:59.000Z

107

An Improved CAViaR Model for Oil Price Risk  

Science Conference Proceedings (OSTI)

As a benchmark for measuring market risk, Value-at-Risk (VaR) reduces the risk associated with any kind of asset to just a number (amount in terms of a currency), which can be well understood by regulators, board members, and other interested parties. ... Keywords: CAViaR, exponentially weighted moving average, oil price risk

Dashan Huang; Baimin Yu; Lean Yu; Frank J. Fabozzi; Masao Fukushima

2007-05-01T23:59:59.000Z

108

Modelling the environmental impact of an aluminium pressure die casting plant and options for control  

Science Conference Proceedings (OSTI)

This study describes a model (MIKADO) to analyse options to reduce the environmental impact of aluminium die casting. This model will take a company perspective, so that it can be used as a decision-support tool for the environmental management of a ... Keywords: Aluminium die casting plant, Environmental decision-support tool, Environmental impact assessment, Integrated Assessment Model, Modelling

Belmira Neto; Carolien Kroeze; Leen Hordijk; Carlos Costa

2008-02-01T23:59:59.000Z

109

Econometric Modelling of World Oil Supplies: Terminal Price and the Time to Depletion  

E-Print Network (OSTI)

This paper develops a novel approach by which to identify the price of oil at the time of depletion; the so-called "terminal price " of oil. It is shown that while the terminal price is independent of both GDP growth and the price elasticity of energy demand, it is dependent on the world real interest rate and the total life-time stock of oil resources, as well as on the marginal extraction and scarcity cost parameters. The theoretical predictions of this model are evaluated using data on the cost of extraction, cumulative production, and proven reserves. The predicted terminal prices seem sensible for a range of parameters and variables, as illustrated by the sensitivity analysis. Using the terminal price of oil, we calculate the time to depletion, and determine the extraction and price pro…les over the life-time of the resource. The extraction pro…les generated seem to be in line with the actual production and the predicted prices are generally in line with those currently observed.

Kamiar Mohaddes

2013-01-01T23:59:59.000Z

110

The Food Crises: A quantitative model of food prices including speculators and ethanol conversion  

E-Print Network (OSTI)

Recent increases in basic food prices are severely impacting vulnerable populations worldwide. Proposed causes such as shortages of grain due to adverse weather, increasing meat consumption in China and India, conversion of corn to ethanol in the US, and investor speculation on commodity markets lead to widely differing implications for policy. A lack of clarity about which factors are responsible reinforces policy inaction. Here, for the first time, we construct a dynamic model that quantitatively agrees with food prices. The results show that the dominant causes of price increases are investor speculation and ethanol conversion. Models that just treat supply and demand are not consistent with the actual price dynamics. The two sharp peaks in 2007/2008 and 2010/2011 are specifically due to investor speculation, while an underlying upward trend is due to increasing demand from ethanol conversion. The model includes investor trend following as well as shifting between commodities, equities and bonds to take ad...

Lagi, Marco; Bertrand, Karla Z; Bar-Yam, Yaneer

2011-01-01T23:59:59.000Z

111

Optioned Portfolio Selection: Models and Analysis Jianfeng LIANG  

E-Print Network (OSTI)

and Oldenkamp [8] proposed a linear programming model with a given level of guaranteed return. The so

Zhang, Shuzhong

112

Preliminary and Incomplete 1 General Equilibrium of a Monetary Model with State-Dependent Pricing ?  

E-Print Network (OSTI)

There is a long standing debate on whether nominal shocks have real effects on the economy. According to one theory, frictions in the price adjustment process can lead to the non-neutrality of money. Macroeconomic models of optimal price setting that nest these price adjustment frictions, however, have proven to be difficult to construct and apply to the data. This paper provides a rational expectations equilibrium model of optimal price setting that is solved numerically. The solution requires the speciÞcation and estimation of a price forecast rule. The structural parameters of the model, focusing on the parameters of the price adjustment cost process, are estimated through an indirect inference procedure using aggregate data from the U.S. economy. According to the estimated results, large and variable adjustment costs are required for the model to match up against U.S. data. This paper is a revised version of the third chapter of my Ph.D. dissertation. I would like to thank Russell Cooper, Simon Gilchrist, John Leahy, and Chris House for their valuable comments. The views expressed herein are solely those of the author and do not necessarily reßect the views of the Federal

Jonathan L. Willis

2000-01-01T23:59:59.000Z

113

Application of Hedonic Price Modeling to Estimate the Value of Algae Meal  

E-Print Network (OSTI)

High productivity rates, usage of nonproductive land, renewability and recovery of waste nutrients and potential for CO2 emission reduction represent some of the advantages that selected algae species might have over competing products. Many research studies have investigated potential usage of algae for different purposes, such as cosmetics or aquaculture; however most of the research studies have focused on the feasibility of algae as a source of second generation biodiesel and feed meal. Because of its high costs of production, using algae only for the purpose of biodiesel production might not be profitable. Thus, for global scale algae commercialization it is important that it be used as a feed meal along with being marketed to the biodiesel industry. One of the major problems faced by economists when attempting to analyze the feasibility of algae is the absence of a market for algae-based fuel and meal. Given that no market exists, prices for algae cannot be observed and realistic investment analysis becomes difficult to perform in this sector. The objective of this study is to estimate a potential price of algae meal using hedonic pricing techniques. For that purpose, twenty two different feed meals commonly having the same usage as Post Extracted Algae Residue (PEAR) are decomposed into their chemical constituents in order to calculate the market value of each characteristic. Calculated prices of these characteristics are then used to estimate the price of algae meal and compare it to different feed meals. Results suggest that algae prices are strictly variable to its chemical components across different algae types. Besides, PEAR represents a sustainable source of financial value and might be considered one of the cornerstones in making algae commercialization a feasible and profitable option.

Gogichaishvili, Ilia

2011-08-01T23:59:59.000Z

114

Modeling natural gas prices as a random walk: The advantages for generation planning  

SciTech Connect

Random walk modeling allows decision makers to evaluate risk mitigation strategies. Easily constructed, the random walk provides probability information that long-term fuel forecasts do not. This is vital to meeting the ratepayers` need for low-cost power, the shareholders` financial objectives, and the regulators` desire for straightforward information. Power generation planning depends heavily on long-term fuel price forecasts. This is particularly true for natural gas-fired plants, because fuel expenses are a significant portion of busbar costs and are subject to considerable uncertainty. Accurate forecasts, then, are critical - especially if electric utilities are to take advantage of the current low cost of natural gas technologies and their relatively clean burning characteristics, without becoming overdependent on a fuel that might significantly increase in price. Moreover, the transition to a more competitive generation market requires a more market-driven planning process. Current planning techniques use several long-term fuel forecasts - one serving as an expected case and others for sensitivity analysis - as inputs for modeling production costs. These forecasts are deterministic: For every time interval there is one, and only one projected fuel price - a serious limitation. Further, past natural gas price predictions have been erroneous and may be susceptible to bias. Today, deregulation of the natural gas production industry allows for a new approach in long-term fuel forecasting. Using NYMEX information, a random walk model of natural gas prices can be constructed. A random walk assumes that prices move randomly, and in modeling prices in this context one would be sure to include this all-important price volatility.

Felder, F.A.

1995-11-01T23:59:59.000Z

115

Socioeconophysics: Opinion Dynamics for number of transactions and price, a trader based model  

E-Print Network (OSTI)

Involving effects of media, opinion leader and other agents on the opinion of individuals of market society, a trader based model is developed and utilized to simulate price via supply and demand. Pronounced effects are considered with several weights and some personal differences between traders are taken into account. Resulting time series and probabilty distribution function involving a power law for price come out similar to the real ones.

Tuncay, C

2006-01-01T23:59:59.000Z

116

Modeling options for Current Energy Convertor Systems and Associated...  

NLE Websites -- All DOE Office Websites (Extended Search)

and Associated Challenges Marine and Hydrokinetic Instrumentation, Measurement & Computer Modeling Workshop Allie Cribbs Ocean Engineer Ecomerit Technologies, LLC July 10 th ,...

117

Price Responsive Demand in New York Wholesale Electricity Market using  

NLE Websites -- All DOE Office Websites (Extended Search)

Price Responsive Demand in New York Wholesale Electricity Market using Price Responsive Demand in New York Wholesale Electricity Market using OpenADR Title Price Responsive Demand in New York Wholesale Electricity Market using OpenADR Publication Type Report LBNL Report Number LBNL-5557E Year of Publication 2012 Authors Kim, Joyce Jihyun, and Sila Kiliccote Date Published 06/2012 Publisher LBNL/NYSERDA Keywords commercial, demand response, dynamic pricing, mandatory hourly pricing, open automated demand response, openadr, pilot studies & implementation, price responsive demand Abstract In New York State, the default electricity pricing for large customers is Mandatory Hourly Pricing (MHP), which is charged based on zonal day-ahead market price for energy. With MHP, retail customers can adjust their building load to an economically optimal level according to hourly electricity prices. Yet, many customers seek alternative pricing options such as fixed rates through retail access for their electricity supply. Open Automated Demand Response (OpenADR) is an XML (eXtensible Markup Language) based information exchange model that communicates price and reliability information. It allows customers to evaluate hourly prices and provide demand response in an automated fashion to minimize electricity costs. This document shows how OpenADR can support MHP and facilitate price responsive demand for large commercial customers in New York City.

118

Real Time Pricing as a Default or Optional Service for C&I Customers: A Comparative Analysis of Eight Case Studies  

E-Print Network (OSTI)

use of class average load profiles for setting the commodityof developing an hourly load profile for each individualneed for class-average load profiles for commodity pricing (

Barbose, Galen; Goldman, Charles; Bharvirkar, Ranjit; Hopper, Nicole; Ting, Michael; Neenan, Bernie

2005-01-01T23:59:59.000Z

119

ARIMA Model Estimated by Particle Swarm Optimization Algorithm for Consumer Price Index Forecasting  

Science Conference Proceedings (OSTI)

This paper presents an ARIMA model which uses particle swarm optimization algorithm (PSO) for model estimation. Because the traditional estimation method is complex and may obtain very bad results, PSO which can be implemented with ease and has a powerful ... Keywords: ARIMA model, Consumer price index, Moment estimation, Particle swarm optimization algorithm

Hongjie Wang; Weigang Zhao

2009-11-01T23:59:59.000Z

120

Automated Critical Peak Pricing Field Tests: Program Description and Results  

E-Print Network (OSTI)

Moderate Price (real-time) High Price (real-time) Note:Into EMCS Moderate Price (real-time) Indicator Light Same asIndication (optional) High Price (real-time) Indicator Light

Piette, Mary Ann; Watson, David; Motegi, Naoya; Kiliccote, Sila; Xu, Peng

2006-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "option pricing model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


121

The Window Strategy with Options  

E-Print Network (OSTI)

The window strategy is one of several marketing strategies using futures and options to establish a floor price and allow for upside price potential. It also reduces option premium costs. This publication discusses how the window strategy works and when to use it.

McCorkle, Dean; Amosson, Stephen H.; Fausett, Marvin

1999-06-23T23:59:59.000Z

122

Dynamic physical and economic modelling of riparian restoration options  

Science Conference Proceedings (OSTI)

A dynamic simulation framework is used to compare benefit-cost ratios of riparian restoration investment strategies to pursue ecosystem service benefits. The model is meant to be adaptable to generic restoration planning applications, with the Middle ... Keywords: Adaptive management, Benefit-cost analysis, Choice experiment, Dynamic simulation, Ecosystem service, Rio Grande, River restoration

Matthew A. Weber; Vincent C. Tidwell; Jennifer A. Thacher

2010-12-01T23:59:59.000Z

123

PRICE SPECULATION  

E-Print Network (OSTI)

The price of crude oil in the U.S. had never exceeded $40 per barrel until mid-2004. By 2006 it reached $70 per barrel, and in July 2008 it reached a peak of $145. By the end of 2008 it had plummeted to about $30 before increasing again, reaching about $110 in 2011. Are “speculators ” to blame for at least part of the volatility and sharp run-ups in price? We clarify the potential and actual effects of speculators, and investors in general, on commodity prices. We focus on crude oil, but our approach can be applied to other commodities. We first address the question of what is meant by “oil price speculation, ” and how it relates to investments in oil reserves, oil inventories, or oil price derivatives (such as futures contracts). Next we outline the ways in which one could speculate on oil prices. Finally, we turn to the data, and calculate counterfactual prices that would have occurred from 1999 to 2012 in the absence of speculation. Our framework is based on a simple and transparent model of supply and demand in the cash and storage markets for a commodity. It lets us determine whether speculation as the driver of price changes is consistent with the data on production, consumption, inventory changes, and changes in convenience yields given reasonable elasticity assumptions. We show speculation had little, if any, effect on prices and volatility.

Christopher R. Knittel; Robert S. Pindyck; Christopher R. Knittel; Robert S. Pindyck

2013-01-01T23:59:59.000Z

124

Asymptotic Behavior of the Stock Price Distribution Density and Implied Volatility in Stochastic Volatility Models  

Science Conference Proceedings (OSTI)

We study the asymptotic behavior of distribution densities arising in stock price models with stochastic volatility. The main objects of our interest in the present paper are the density of time averages of the squared volatility process and the density of the stock price process in the Stein-Stein and the Heston model. We find explicit formulas for leading terms in asymptotic expansions of these densities and give error estimates. As an application of our results, sharp asymptotic formulas for the implied volatility in the Stein-Stein and the Heston model are obtained.

Gulisashvili, Archil, E-mail: guli@math.ohiou.ed [Ohio University, Department of Mathematics (United States); Stein, Elias M., E-mail: stein@math.princeton.ed [Princeton University, Department of Mathematics (United States)

2010-06-15T23:59:59.000Z

125

UPDATE February 2012 - The Food Crises: Predictive validation of a quantitative model of food prices including speculators and ethanol conversion  

E-Print Network (OSTI)

Increases in global food prices have led to widespread hunger and social unrest---and an imperative to understand their causes. In a previous paper published in September 2011, we constructed for the first time a dynamic model that quantitatively agreed with food prices. Specifically, the model fit the FAO Food Price Index time series from January 2004 to March 2011, inclusive. The results showed that the dominant causes of price increases during this period were investor speculation and ethanol conversion. The model included investor trend following as well as shifting between commodities, equities and bonds to take advantage of increased expected returns. Here, we extend the food prices model to January 2012, without modifying the model but simply continuing its dynamics. The agreement is still precise, validating both the descriptive and predictive abilities of the analysis. Policy actions are needed to avoid a third speculative bubble that would cause prices to rise above recent peaks by the end of 2012.

Lagi, Marco; Bertrand, Karla Z; Bar-Yam, Yaneer

2012-01-01T23:59:59.000Z

126

Demand Response-Enabled Model Predictive HVAC Load Control in Buildings using Real-Time Electricity Pricing.  

E-Print Network (OSTI)

??A practical cost and energy efficient model predictive control (MPC) strategy is proposed for HVAC load control under dynamic real-time electricity pricing. The MPC strategy… (more)

Avci, Mesut

2013-01-01T23:59:59.000Z

127

Modeling of Asymmetry between Gasoline and Crude Oil Prices: A Monte Carlo Comparison  

Science Conference Proceedings (OSTI)

An Engle---Granger two-step procedure is commonly used to estimate cointegrating vectors and consequently asymmetric error-correction models. This study uses Monte Carlo methods and demonstrates that the Engle---Granger two-step method leads to biased ... Keywords: Asymmetry, Gasoline, Modeling, Oil prices

Afshin Honarvar

2010-10-01T23:59:59.000Z

128

A Dynamic Supply-Demand Model for Electricity Prices Manuela Buzoianu  

E-Print Network (OSTI)

played a role during the crisis period. 1 Introduction The energy industry provides electrical powerA Dynamic Supply-Demand Model for Electricity Prices Manuela Buzoianu , Anthony E. Brockwell of supply and demand equilibrium. The model includes latent supply and demand curves, which may vary over

129

Prices and Price Setting.  

E-Print Network (OSTI)

??This thesis studies price data and tries to unravel the underlying economic processes of why firms have chosen these prices. It focuses on three aspects… (more)

Faber, R.P.

2010-01-01T23:59:59.000Z

130

PRISM 2.0: Regional Energy and Economic Model Development and Initial Application: Phase 2: Electric Sector CO2 Reduction Options to 2050: Dimensions of Technology, Energy Costs, and Environmental Scenarios  

Science Conference Proceedings (OSTI)

EPRI conducted an analysis of electric sector CO2 reduction options to 2050 across a range of scenarios covering dimensions of technology costs and availability, energy costs, and CO2 constraints.  Using its U.S. Regional Economy, Greenhouse Gas, and Energy (US-REGEN) model, EPRI calculated the impact of changes in generation portfolio, generation capacity, expenditures, and electricity prices on power sector costs. This analysis estimates different levels of ...

2013-11-06T23:59:59.000Z

131

Sluggish Responses of Prices and Inflation to Monetary Shocks in an Inventory Model of Money Demand  

E-Print Network (OSTI)

We examine the responses of prices and inflation to monetary shocks in an inventory-theoretic model of money demand. We show that the price level responds sluggishly to an exogenous increase in the money stock because the dynamics of households ’ money inventories leads to a partially offsetting endogenous reduction in velocity. We also show that inflation responds sluggishly to an exogenous increase in the nominal interest rate because changes in monetary policy affect the real interest rate. In a quantitative example, we show that this nominal sluggishness is substantial and persistent if inventories in the model are calibrated to match U.S. households ’ holdings of M2. I.

Fernando Alvarez; Andrew Atkeson; Chris Edmond

2008-01-01T23:59:59.000Z

132

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

Energy futures markets are ‘hubs’ that price and marketenergy price fluctuations. In theory, futures market pricesenergy prices, including most prominently, energy futures markets.

Wong-Parodi, Gabrielle; Dale, Larry; Lekov, Alex

2005-01-01T23:59:59.000Z

133

Agent-Based Model of Price Competition, Capacity Choice, and Product Differentiation on Congested Networks  

E-Print Network (OSTI)

Using consistent agent-based techniques, this research models the decision-making processes of users and infrastructure owner/operators to explore the welfare consequence of price competition, capacity choice, and product differentiation on congested transportation networks. Component models include: (1) An agent-based travel demand model wherein each traveler has learning capabilities and unique characteristics (e.g. value of time); (2) Econometric facility provision cost models; and (3) Representations of road authorities making pricing and capacity decisions. Different from small-network equilibrium models in prior literature, this agent-based model is applicable to pricing and investment analyses on large complex networks. The subsequent economic analysis focuses on the source, evolution, measurement, and impact of product differentiation with heterogeneous users on a mixed ownership network (with tolled and untolled roads). Two types of product differentiation in the presence of toll roads, path differentiation and space differentiation, are defined and measured for a base case and several variants with different types of price and capacity competition and with various degrees of user

Lei Zhang; David Levinson

2006-01-01T23:59:59.000Z

134

Evolution of a Visual Impact Model to Evaluate Nuclear Plant Siting and Design Option1  

E-Print Network (OSTI)

for Analysis and Management of the Visual Resource, Incline Village, Nevada, April 23-25, 1979. 2 / AssociatesEvolution of a Visual Impact Model to Evaluate Nuclear Plant Siting and Design Option1 2/ Brian A/ The method can be used to train evaluators to use explicit criteria (vividness, intactness and unity

Standiford, Richard B.

135

Comparing Price Forecast Accuracy of Natural Gas Models andFutures Markets  

SciTech Connect

The purpose of this article is to compare the accuracy of forecasts for natural gas prices as reported by the Energy Information Administration's Short-Term Energy Outlook (STEO) and the futures market for the period from 1998 to 2003. The analysis tabulates the existing data and develops a statistical comparison of the error between STEO and U.S. wellhead natural gas prices and between Henry Hub and U.S. wellhead spot prices. The results indicate that, on average, Henry Hub is a better predictor of natural gas prices with an average error of 0.23 and a standard deviation of 1.22 than STEO with an average error of -0.52 and a standard deviation of 1.36. This analysis suggests that as the futures market continues to report longer forward prices (currently out to five years), it may be of interest to economic modelers to compare the accuracy of their models to the futures market. The authors would especially like to thank Doug Hale of the Energy Information Administration for supporting and reviewing this work.

Wong-Parodi, Gabrielle; Dale, Larry; Lekov, Alex

2005-06-30T23:59:59.000Z

136

Demand-Side Management (DSM) Opportunities as Real-Options  

NLE Websites -- All DOE Office Websites (Extended Search)

Demand-Side Management (DSM) Opportunities as Real-Options Demand-Side Management (DSM) Opportunities as Real-Options Speaker(s): Osman Sezgen Date: August 1, 2002 - 12:00pm Location: Bldg. 90 Seminar Host/Point of Contact: Kristina LaCommare As some end-users of energy and aggregators are choosing to be exposed to real-time prices and energy price volatility, they are coming across new DSM opportunities that would not be feasible under typical utility rate structures. Effective evaluation of such opportunities requires a good understanding of the wholesale energy markets and the use of models based on recent financial techniques for option pricing. The speaker will give examples of such modeling approaches based on his experience in the retail-energy industry. Specific examples will include evaluation of distributed generation, load curtailment, dual-fuel cooling, and energy

137

A supply-demand model for OPEC oil-pricing policies  

SciTech Connect

OPEC and its pricing policies have been subjected to constant international attention as well as criticism since 1973. Consumers find OPEC behavior irrational, while OPEC tries to justify its policies as rational and in accordance with the realities of the international oil market. The focus of this study is to contribute toward an analytical and empirical work on OPEC pricing behavior, and highlight the various factors believed to affect the future oil policies of OPEC member countries. After a survey of literature on the theoretical framework of world oil models in general, and OPEC models in particular, a linear econometric model for pricing OPEC oil is formulated which is a supply-demand equilibrium model comprising of supply, demand, and inflation-rate functions. Estimation of the behavioral equations are carried out by Ordinary and Two-Stage Least Square estimators. Econometric results from the estimation and simulation of the model seem to indicate that OPEC's pricing behavior is market-responsive and may best be explained by employing the theoretical framework of market-equilibrium condition.

Heiat, N.

1988-01-01T23:59:59.000Z

138

2H2A Hydrogen Delivery Infrastructure Analysis Models and Conventional Pathway Options Analysis Results - Interim Report  

NLE Websites -- All DOE Office Websites (Extended Search)

H2A Hydrogen Delivery Infrastructure Analysis Models and H2A Hydrogen Delivery Infrastructure Analysis Models and Conventional Pathway Options Analysis Results DE-FG36-05GO15032 Interim Report Nexant, Inc., Air Liquide, Argonne National Laboratory, Chevron Technology Venture, Gas Technology Institute, National Renewable Energy Laboratory, Pacific Northwest National Laboratory, and TIAX LLC May 2008 Contents Section Page Executive Summary ................................................................................................................... 1-9 Delivery Options ...................................................................................................................... 1-9 Evaluation of Options 2 and 3 ................................................................................................. 1-9

139

Reviewing progress in PJM's capacity market structure via the new reliability pricing model  

Science Conference Proceedings (OSTI)

The Reliability Pricing Model introduces significant changes to the capacity market structure of PJM. The main feature of the RPM design is a downward-sloping demand curve, which replaces the highly volatile vertical demand curve. The authors review the latest RPM structure, results of the auctions, and the future course of the implementation process. (author)

Sener, Adil Caner; Kimball, Stefan

2007-12-15T23:59:59.000Z

140

Application of price uncertainty quantification models and their impacts on project evaluations  

E-Print Network (OSTI)

This study presents an analysis of several recently published methods for quantifying the uncertainty in economic evaluations due to uncertainty in future oil prices. Conventional price forecasting methods used in the industry typically underestimate the range of uncertainty in oil and gas price forecasts. These forecasts traditionally consider pessimistic, most-likely, and optimistic cases in an attempt to quantify economic uncertainty. The recently developed alternative methods have their unique strengths as well as weaknesses that may affect their applicability in particular situations. While stochastic methods can improve the assessment of price uncertainty they can also be tedious to implement. The inverted hockey stick method is found to be an easily applied alternative to the stochastic methods. However, the primary basis for validating this method has been found to be unreliable. In this study, a consistent and reliable validation of uncertainty estimates predicted by the inverted hockey stick method is presented. Verifying the reliability of this model will ensure reliable quantification of economic uncertainty. Although we cannot eliminate uncertainty from investment evaluations, we can better quantify the uncertainty by accurately predicting the volatility in future oil and gas prices. Reliably quantifying economic uncertainty will enable operators to make better decisions and allocate their capital with increased efficiency.

Fariyibi, Festus Lekan

2006-08-01T23:59:59.000Z

Note: This page contains sample records for the topic "option pricing model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


141

A simulation based real options approach for the investment evaluation of nuclear power  

Science Conference Proceedings (OSTI)

The investment of nuclear power has several uncertainties. This paper establishes a nuclear power investment evaluation model by employing real options theory with Monte Carlo method to evaluate the value of nuclear power plant from the perspective of ... Keywords: Least Squares Monte-Carlo, Nuclear accident, Nuclear power investment, Price mechanism, Real options

Lei Zhu

2012-11-01T23:59:59.000Z

142

Bounds for Asian basket options  

Science Conference Proceedings (OSTI)

In this paper we propose pricing bounds for European-style discrete arithmetic Asian basket options in a Black and Scholes framework. We start from methods used for basket options and Asian options. First, we use the general approach for deriving upper ... Keywords: 60E15, 60J65, 91B28, Asian basket option, Non-comonotonic sum, Sum of non-independent random variables

Griselda Deelstra; Ibrahima Diallo; Michèle Vanmaele

2008-08-01T23:59:59.000Z

143

The world oil market and OPEC behavior: The leak-producer price leader model  

SciTech Connect

This is an economic study of the world's oil market in which OPEC plays the central role in determining the oil supply and price. Understanding OPEC's behavior is at the core of understanding the world's oil market. However, oil is a resource belonging to the family of natural resources known as exhaustible. We do not produce oil; we only extract and distribute a fixed amount of the resource over generations. Optimal extraction is a matter of concern to both suppliers and consumers. First, it is shown that using the traditional theory of producers behavior in the conventional commodity markets to explain extractors behavior in exhaustible resource markets is completely wrong. Second, current models of OPEC behavior are reviewed. Third, an alternative model is introduced. Previous authors have not directed their models to give explanations to the peculiar observations in oil market. This model divides the world's oil suppliers into: the free riders (non-OPEC oil producers), the OPEC hawks (a group within OPEC) and the leak-producer price leader (Saudi Arabia). Three factors, namely relatively big oil reserves, no other sources of income, and the avoidance of the so-called backstop technology make Saudi Arabia more interested in lower oil prices than are other oil extractors.

Aboalela, A.A.

1988-01-01T23:59:59.000Z

144

A Censored-Garch Model Of Asset Returns With Price Limits  

E-Print Network (OSTI)

As one important form of market circuit breakers, price limits have been often imposed in stock and futures markets. This paper considers modeling the return process of such assets, focusing on the treatment of price limits. As a result, a censored-GARCH model is formulated and a Bayesian approach to this model is developed. An application is provided to Treasury bill futures over a period of high volatility and frequent limit moves. The impacts of price limits are demonstrated with the real data and confirmed with a simulation example. Keywords: Price limits, censored-GARCH model, griddy Gibbs sampler-data augmentation. JEL classification: C13, C24 and G19 1 CORE, Universit'e Catholique de Louvain and Department of Finance, The Hong Kong University of Science and Technology, Email: weix@uxmail.ust.hk. I am indebted to Dale J. Poirier for his excellent supervision and encouragement and ackowledge helpful discussions and comments from Luc Bauwens, Jin-Chuan Duan, Philip H. Dybvig, Christian Hafner, Gary Koop, Tom McCurdy, Angelo Melino, Michel Mouchart, and Efthymios G. Tsionas on earlier versions of this paper. I would also like to thank I.G. Morgan who kindly provided me with his data set. Seminar participants at CORE, CREST, University of Toronto, University of Western Ontario, Washington University at St. Louis, the 1997 Bayesian Research Day at Erasmus University Rotterdam, and the 1997 conference of Forecasting Financial Market in London made help suggestions. This paper was partly done when I visited CORE, Universite Catholique de Louvain in 1997. Financial support from University of Toronto Doctor Fellowsihip and CORE fellowship is gratefully ackowledged. All remaining errors are my responsibility. This paper presents research results of the Belgian Pr...

Steven X. Wei; Jel Classification C; Comments From Luc Bauwens; Jin-chuan Duan; Philip H. Dybvig; Christian Hafner; Gary Koop; Tom Mccurdy; Angelo Melino; Michel Mouchart; Efthymios G. Tsionas On Earlier

1998-01-01T23:59:59.000Z

145

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

energy price fluctuations. In theory, futures market prices summarize privately available informationEnergy; Brookhaven National Laboratory Canadian Energy Research Institute U.S. Energy Information Administration Energy Marketsinformation about future energy prices, including most prominently, energy futures markets.

Wong-Parodi, Gabrielle; Dale, Larry; Lekov, Alex

2005-01-01T23:59:59.000Z

146

Impacts of Trades in an Error-Correction Model of Quote Prices  

E-Print Network (OSTI)

on Short-Selling and Asset Price Adjustment to PrivateF. , 2000, Time and the Price Impact of a Trade, Journal ofand O’Hara, Maureen, 1987, Price, Trade Size and Information

Engle, Robert F; Patton, Andrew J

2000-01-01T23:59:59.000Z

147

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

index.html. Appendix A.1 Natural Gas Price Data for FuturesError STEO Error A.1 Natural Gas Price Data for Futuresof forecasts for natural gas prices as reported by the

Wong-Parodi, Gabrielle; Dale, Larry; Lekov, Alex

2005-01-01T23:59:59.000Z

148

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

Appendix A.1 Natural Gas Price Data for Futures Market andSTEO Error A.1 Natural Gas Price Data for Futures Market andforecasts for natural gas prices as reported by the Energy

Wong-Parodi, Gabrielle; Dale, Larry; Lekov, Alex

2005-01-01T23:59:59.000Z

149

Pricing with uncertain customer valuations  

E-Print Network (OSTI)

Uncertain demand in pricing problems is often modeled using the sum of a linear price- response function and a zero-mean random variable. In this paper, we ...

150

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

the forecast. In 1978 the Natural Gas Policy Act was passedof Other Natural Gas Price Forecasts Researchers and policyresearchers and policy makers who utilize natural gas prices

Wong-Parodi, Gabrielle; Dale, Larry; Lekov, Alex

2005-01-01T23:59:59.000Z

151

Accounting for fuel price risk: Using forward natural gas prices instead of gas price forecasts to compare renewable to natural gas-fired generation  

Science Conference Proceedings (OSTI)

Against the backdrop of increasingly volatile natural gas prices, renewable energy resources, which by their nature are immune to natural gas fuel price risk, provide a real economic benefit. Unlike many contracts for natural gas-fired generation, renewable generation is typically sold under fixed-price contracts. Assuming that electricity consumers value long-term price stability, a utility or other retail electricity supplier that is looking to expand its resource portfolio (or a policymaker interested in evaluating different resource options) should therefore compare the cost of fixed-price renewable generation to the hedged or guaranteed cost of new natural gas-fired generation, rather than to projected costs based on uncertain gas price forecasts. To do otherwise would be to compare apples to oranges: by their nature, renewable resources carry no natural gas fuel price risk, and if the market values that attribute, then the most appropriate comparison is to the hedged cost of natural gas-fired generation. Nonetheless, utilities and others often compare the costs of renewable to gas-fired generation using as their fuel price input long-term gas price forecasts that are inherently uncertain, rather than long-term natural gas forward prices that can actually be locked in. This practice raises the critical question of how these two price streams compare. If they are similar, then one might conclude that forecast-based modeling and planning exercises are in fact approximating an apples-to-apples comparison, and no further consideration is necessary. If, however, natural gas forward prices systematically differ from price forecasts, then the use of such forecasts in planning and modeling exercises will yield results that are biased in favor of either renewable (if forwards forecasts). In this report we compare the cost of hedging natural gas price risk through traditional gas-based hedging instruments (e.g., futures, swaps, and fixed-price physical supply contracts) to contemporaneous forecasts of spot natural gas prices, with the purpose of identifying any systematic differences between the two. Although our data set is quite limited, we find that over the past three years, forward gas prices for durations of 2-10 years have been considerably higher than most natural gas spot price forecasts, including the reference case forecasts developed by the Energy Information Administration (EIA). This difference is striking, and implies that resource planning and modeling exercises based on these forecasts over the past three years have yielded results that are biased in favor of gas-fired generation (again, presuming that long-term stability is desirable). As discussed later, these findings have important ramifications for resource planners, energy modelers, and policy-makers.

Bolinger, Mark; Wiser, Ryan; Golove, William

2003-08-13T23:59:59.000Z

152

High Electricity Prices  

E-Print Network (OSTI)

Generators supplying electricity markets are subject to volatile input and output prices and uncertain fuel availability. Price-risk may be hedged to a considerable extent but fuel-risk — water flows in the case of hydro and gas availability in the case of thermal plants — may not be. We show that a price-taking generator will only generate when the output price exceeds its marginal cost by an amount that reflects the value of the option to delay the use of stored fuel. The corresponding offer price is different from the theorized offer prices of static uniform auctions and more akin to pay-as-bid auction prices. We argue that the option value of delaying fuel use, which is an increasing function of spot price volatility and the uncertainty about fuel availability, must be considered when evaluating whether market power is present in electricity markets. The engineering approach to simulating an electricity supply curve, which has been used in market power evaluations to date, may lead to supply curves that are quite different from those that recognize possible fuel availability limitations, even in the complete absence of market power.

Kevin Counsell; Graeme Guthrie; Steen Videbeck

2006-01-01T23:59:59.000Z

153

Modeling of NOx Destruction Options for INEEL Sodium-Bearing Waste Vitrification  

SciTech Connect

Off-gas NOx concentrations in the range of 1-5 mol% are expected as a result of the proposed vitrification of sodium-bearing waste at the Idaho National Engineering and Environmental Laboratory. An existing kinetic model for staged combustion (originally developed for NOx abatement from the calcination process) was updated for application to vitrification offgas. In addition, two new kinetic models were developed to assess the feasibility of using selective non-catalytic reduction (SNCR) or high-temperature alone for NOx abatement. Each of the models was developed using the Chemkin code. Results indicate that SNCR is a viable option, reducing NOx levels to below 1000 ppmv. In addition, SNCR may be capable of simultaneously reducing CO emissions to below 100 ppmv. Results for using high-temperature alone were not as promising, indicating that a minimum NOx concentration of 3950 ppmv is achievable at 3344°F.

Wood, Richard Arthur

2001-09-01T23:59:59.000Z

154

Operation of Distributed Generation Under Stochastic Prices  

Science Conference Proceedings (OSTI)

We model the operating decisions of a commercial enterprisethatneeds to satisfy its periodic electricity demand with either on-sitedistributed generation (DG) or purchases from the wholesale market. Whilethe former option involves electricity generation at relatively high andpossibly stochastic costs from a set of capacity-constrained DGtechnologies, the latter implies unlimited open-market transactions atstochastic prices. A stochastic dynamic programme (SDP) is used to solvethe resulting optimisation problem. By solving the SDP with and withoutthe availability of DG units, the implied option values of the DG unitsare obtained.

Siddiqui, Afzal S.; Marnay, Chris

2005-11-30T23:59:59.000Z

155

Natural Gas Citygate Price  

Gasoline and Diesel Fuel Update (EIA)

Pipeline and Distribution Use Price Citygate Price Residential Price Commercial Price Industrial Price Vehicle Fuel Price Electric Power Price Proved Reserves as of 1231 Reserves...

156

A Plant-Level Simulation Model for Evaluating CO2 Capture Options  

E-Print Network (OSTI)

C-, SC-, USC-PC) Dry feed gasifier and sulfur capture system (Shell) Added gas turbine option for IGCC

157

Fundamentals Explain High Prices  

Gasoline and Diesel Fuel Update (EIA)

9 9 Notes: One can use a simple model to deal with price/fundamental relationships. This one predicts monthly average WTI price as a function of OECD total petroleum stock deviations from the normal levels . The graph shows the model as it begins predicting prices in 1992. It shows how well the model has predicted not only the direction, but the magnitude of prices over this 8+ year period. While the model is simple and not perfect, it does predict the overall trends and, in particular, the recent rise in prices. It also shows that prices may have over-shot the fundamental balance for a while -- at least partially due to speculative concerns over Mideast tensions, winter supply adequacy, and Iraq's export policies. Prices now seem to be correcting, and may even undershoot briefly

158

The Effect of Energy Prices on Operation and Investment in OECD Countries: Evidence from the Vintage Capital Model  

E-Print Network (OSTI)

capital stock may reduce future energy (including fossil fuel) input consumption. To illustrate the outcome of such policies we use the vintage capital model predictions to evaluate the e¤ect of a greenhouse emissions tax on energy consumption. Because... (agriculture, commerce, manufacturing, and transport) between 1990 and 2005. Compared to earlier studies, our analysis relies on more accurate energy prices in different sectors and countries based on the end-use fuel prices and sector-specific energy mix...

Steinbuks, J; Meshreky, A; Neuhoff, Karsten

159

Point and Interval Forecasting of Spot Electricity Prices: Linear vs. Non-Linear Time Series Models  

E-Print Network (OSTI)

In this paper we assess the short-term forecasting power of different time series models in the electricity spot market. In particular we calibrate AR/ARX (”X” stands for exogenous/fundamental variable — system load in our study), AR/ARX-GARCH, TAR/TARX and Markov regime-switching models to California Power Exchange (CalPX) system spot prices. We then use them for out-ofsample point and interval forecasting in normal and extremely volatile periods preceding the market crash in winter 2000/2001. We find evidence that (i) non-linear, threshold regime-switching (TAR/TARX) models outperform their linear counterparts, both in point and interval forecasting, and that (ii) an additional GARCH component generally decreases point forecasting efficiency. Interestingly, the former result challenges a number of previously published studies on the failure of non-linear regime-switching models in forecasting.

Adam Misiorek; Stefan Trueck; Rafal Weron

2006-01-01T23:59:59.000Z

160

Price Server System for Automated Critical Peak Pricing  

NLE Websites -- All DOE Office Websites (Extended Search)

Price Server System for Automated Critical Peak Pricing Price Server System for Automated Critical Peak Pricing Speaker(s): David S. Watson Date: June 3, 2005 - 12:00pm Location: 90-3148 Overview of current California Energy Commission (CEC)/Demand Response Research Center (DRRC) Auto-CPP project: This summer, some select commercial CPP customers of PG&E will have the option of joining the Automated Critical Peak Pricing pilot. The pilot will have the same tariffs as standard CPP programs, but will include an added feature: automated shedding of electric loads. Through use of the Price Server System, day-ahead CPP event signals initiated by PG&E will ultimately cause electric loads to be automatically curtailed on commercial customer sites. These optional predetermined shed strategies will occur without

Note: This page contains sample records for the topic "option pricing model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


161

Apples with apples: accounting for fuel price risk in comparisons of gas-fired and renewable generation  

E-Print Network (OSTI)

fixed-price gas supply contracts and natural gas storage. Asnatural gas prices, rather than on prices that can be locked in through futures, swap, or fixed- price physical supplySupply, Renewable Energy Gas Options, Gas Storage Option Premium or Storage Cost Gas Price Falls Gas Price Rises Natural

Bolinger, Mark; Wiser, Ryan

2003-01-01T23:59:59.000Z

162

Impact of Deferral Option on Investment: Empirical Evidence from Residential Customers of District Heating Company  

E-Print Network (OSTI)

This paper examines an option to defer an investment in the thermal rehabilitation of a building. Heat savings generated by energy efficiency investment in two distinctive areas connected to the district heating system in Prague are studied. Despite substantial difference of heat price over several years, no significant difference in heat savings between the two areas was found. It is shown that different volatility of heat prices in different areas and its changes influencing value of deferral option can partly explain the observed flat owner’s behavior. Two specific “real ” features of the deferral option are further introduced, improvement of the option valuation model is proposed and expected impact on the value of deferral option is discussed.

Martin Hajek

2009-01-01T23:59:59.000Z

163

Electricity Real Options Valuation  

E-Print Network (OSTI)

In this paper a real option approach for the valuation of real assets is presented. Two continuous time models used for valuation are described: geometric Brownian motion model and interest rate model. The valuation for electricity spread option under Vasicek interest model is placed and the formulas for parameter estimators are calculated. The theoretical part is confronted with real data from electricity market.

Broszkiewicz-Suwaj, E

2006-01-01T23:59:59.000Z

164

Electricity Real Options Valuation  

E-Print Network (OSTI)

In this paper a real option approach for the valuation of real assets is presented. Two continuous time models used for valuation are described: geometric Brownian motion model and interest rate model. The valuation for electricity spread option under Vasicek interest model is placed and the formulas for parameter estimators are calculated. The theoretical part is confronted with real data from electricity market.

Ewa Broszkiewicz-Suwaj

2006-08-16T23:59:59.000Z

165

Dynamic filter weights neural network model integrated with differential evolution for day-ahead price forecasting in energy market  

Science Conference Proceedings (OSTI)

In this paper a new dynamic model for forecasting electricity prices from 1 to 24h in advance is proposed. The model is a dynamic filter weight Adaline using a sliding mode weight adaptation technique. The filter weights for this neuron constitute of ... Keywords: Differential evolution, Dynamic filter weights neuron, Energy market, Local linear wavelet neural network, Sliding mode control

S. Chakravarty; P. K. Dash

2011-09-01T23:59:59.000Z

166

Connecting the top-down to the bottom-up: pricing CDO under a conditional survival (CS) model  

Science Conference Proceedings (OSTI)

In this paper, we use exact simulation to price CDO under a new dynamic model, the Conditional Survival (CS) model, which provided excellent calibration to both iTraxx tranches and underlying single name CDS spreads on March 14, 2008, the day before ...

Xian Hua Peng; Steven S. G. Kou

2008-12-01T23:59:59.000Z

167

Role of Future Generation and Energy Efficiency Options  

Science Conference Proceedings (OSTI)

This Technical Update provides results of various policy scenarios using EPRI's financial model of the U.S. electric sector for generation capacity expansion and dispatch at the national and regional levels. The model evaluates the possible effects of climate policy, renewable portfolio standard (RPS), energy efficiency, technology availability, and market scenarios on the deployment and operation of nuclear, fossil, and renewable generation options and on electricity prices, emissions, fuel use, and oth...

2009-11-30T23:59:59.000Z

168

Phillip Price  

NLE Websites -- All DOE Office Websites (Extended Search)

Phillip Price Phil Price Sustainable Energy Systems Group Demand Response Research Center (DRRC) Lawrence Berkeley National Laboratory 1 Cyclotron Road MS 90R2002 Berkeley CA 94720...

169

Gasoline Prices  

NLE Websites -- All DOE Office Websites (Extended Search)

and diesel price estimates from the Energy Information Administration Understanding Gas Prices Photo of gasoline receipt What determines the cost of gasoline? What's the...

170

Examining Uncertainty in Demand Response Baseline Models and Variability in Automated Response to Dynamic Pricing  

Science Conference Proceedings (OSTI)

Controlling electric loads to deliver power system services presents a number of interesting challenges. For example, changes in electricity consumption of Commercial and Industrial (C&I) facilities are usually estimated using counterfactual baseline models, and model uncertainty makes it difficult to precisely quantify control responsiveness. Moreover, C&I facilities exhibit variability in their response. This paper seeks to understand baseline model error and demand-side variability in responses to open-loop control signals (i.e. dynamic prices). Using a regression-based baseline model, we define several Demand Response (DR) parameters, which characterize changes in electricity use on DR days, and then present a method for computing the error associated with DR parameter estimates. In addition to analyzing the magnitude of DR parameter error, we develop a metric to determine how much observed DR parameter variability is attributable to real event-to-event variability versus simply baseline model error. Using data from 38 C&I facilities that participated in an automated DR program in California, we find that DR parameter errors are large. For most facilities, observed DR parameter variability is likely explained by baseline model error, not real DR parameter variability; however, a number of facilities exhibit real DR parameter variability. In some cases, the aggregate population of C&I facilities exhibits real DR parameter variability, resulting in implications for the system operator with respect to both resource planning and system stability.

Mathieu, Johanna L.; Callaway, Duncan S.; Kiliccote, Sila

2011-08-15T23:59:59.000Z

171

A quantum mechanical model for the relationship between stock price and stock ownership  

SciTech Connect

The trade of a fixed stock can be regarded as the basic process that measures its momentary price. The stock price is exactly known only at the time of sale when the stock is between traders, that is, only in the case when the owner is unknown. We show that the stock price can be better described by a function indicating at any moment of time the probabilities for the possible values of price if a transaction takes place. This more general description contains partial information on the stock price, but it also contains partial information on the stock owner. By following the analogy with quantum mechanics, we assume that the time evolution of the function describing the stock price can be described by a Schroedinger type equation.

Cotfas, Liviu-Adrian [Faculty of Economic Cybernetics, Statistics and Informatics, Academy of Economic Studies, 6 Piata Romana, 010374 Bucharest (Romania)

2012-11-01T23:59:59.000Z

172

A quantum mechanical model for the relationship between stock price and stock ownership  

E-Print Network (OSTI)

The trade of a fixed stock can be regarded as the basic process that measures its momentary price. The stock price is exactly known only at the time of sale when the stock is between traders, that is, only in the case when the owner is unknown. We show that the stock price can be better described by a function indicating at any moment of time the probabilities for the possible values of price if a transaction takes place. This more general description contains partial information on the stock price, but it also contains partial information on the stock owner. By following the analogy with quantum mechanics, we assume that the time evolution of the function describing the stock price can be described by a Schrodinger type equation.

Liviu-Adrian Cotfas

2012-07-14T23:59:59.000Z

173

A Dual Approach to Estimation With Constant Prices  

E-Print Network (OSTI)

Profit Models with Constant Prices Technological Parametersexpected quantities and prices are used as instrumentaldemand functions when prices seem to be the same for all

Paris, Quirino; Caputo, Michael R.

2003-01-01T23:59:59.000Z

174

Electricity Forward Prices: A High-Frequency Empirical Analysis  

E-Print Network (OSTI)

P. 2002. Modelling Electricity Prices: Interna- tionalSchwartz, E. 2002. Electricity Prices and Power Derivatives:spot and forward electricity prices in more detail than in

Longstaff, Francis; Wang, Ashley

2002-01-01T23:59:59.000Z

175

ELECTRICITY FORWARD PRICES: A High-Frequency Empirical Analysis  

E-Print Network (OSTI)

P. 2002. Modelling Electricity Prices: Interna- tionalSchwartz, E. 2002. Electricity Prices and Power Derivatives:spot and forward electricity prices in more detail than in

Longstaff, Francis A; Wang, Ashley

2002-01-01T23:59:59.000Z

176

Sensitivity of a Spectrally Filtered and Nudged Limited-Area Model to Outer Model Options  

Science Conference Proceedings (OSTI)

Numerical filters required to control spatial computational modes in a limited-area model (LAM) that uses the unstaggered. A grid are developed and tested over the complex topography of the Great Basin of the western United States. The filters ...

Kim M. Waldron; Jan Paegle; John D. Horel

1996-03-01T23:59:59.000Z

177

State energy price projections for the residential sector, 1992--1993. [Contains model documentation  

SciTech Connect

The purpose of this report, State Energy Price Projections for the Residential Sector, 1992--1993, is to provide projections of State-level residential prices for 1992 and 1993 for the following fuels: electricity, natural gas, heating oil, liquefied petroleum gas (LPG), kerosene, and coal. Prices for 1991 are also included for comparison purposes. This report also explains the methodology used to produce these estimates and the limitations.

Not Available

1992-09-24T23:59:59.000Z

178

Modeling consumer preferences for status-signaling brands: branding, pricing, and product-line decisions  

E-Print Network (OSTI)

to such products. Hybrid cars, for example, are associatedThus, individuals may use hybrid cars to portray themselvesefficient though expensive hybrid cars. The price premium

Becerril Arreola, Rafael

2013-01-01T23:59:59.000Z

179

Credit derivatives : market dimensions, correlation with equity and implied option volatility, regression modeling and statistical price risk  

E-Print Network (OSTI)

This research thesis explores the market dimensions of credit derivatives including the prevalent product structures, leading participants, market applications and the issues confronting this relatively new product. We ...

Kureshy, Imran, A., 1965-

2004-01-01T23:59:59.000Z

180

Recovering Risk-Neutral Probability Density Functions from Options ...  

E-Print Network (OSTI)

Theorem 2 provides us with a simple mechanism to eliminate "artificial" arbitrage ..... options prices: An application to crude oil during theI² ulfcw risis. © o£ rd¨.

Note: This page contains sample records for the topic "option pricing model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


181

The delivery option in mortgage backed security valuation simulations  

Science Conference Proceedings (OSTI)

A delivery option exists in mortgage-backed security market, which has not been considered in existing mortgage pricing simulation literature. We explain the delivery option in the "To Be Announced" trade. We discuss how the presence of the delivery ...

Scott Gregory Chastain; Jian Chen

2005-12-01T23:59:59.000Z

182

Transmission Price Risk Management  

Science Conference Proceedings (OSTI)

This report is concerned with the financial risks that arise from the uncertain price of transmission service in restructured or competitive electricity markets. These risks are most severe in markets with locational pricing (LMP), but they also exist in more traditionally organized electricity markets. This report has two main purposes. The first is to review the existing mathematical models of electricity price formation in spot and forward markets that may be helpful as the foundations for developing ...

2006-12-04T23:59:59.000Z

183

Combining Financial Double Call Options with Real Options for Early Curtailment of Electricity Service  

E-Print Network (OSTI)

Combining Financial Double Call Options with Real Options for Early Curtailment of Electricity@IEOR.Berkeley.edu Abstract In a competitive electricity market traditional demand side management options offering customers curtailable service at reduced rates are replaced by voluntary customer responses to electricity spot prices

184

Analysis of federal options to support photovoltaic industry growth  

DOE Green Energy (OSTI)

This report presents the methodology and results of an analysis to determine the impact and leverage of federal options for supporting the growth of the photovoltaic industry. Results were projected for combinations of the following: an aggressive federal research and development program, achievement of a technological breakthrough, and immediate or breakthrough-dependent incentives including direct price reductions, keyed-to-breakeven subsidies, and federal puchases. The modeling methodology and market assumptions were also tested to determine their effect on analysis results.

Bennington, G.; Cherdak, A.; Williams, F.

1979-05-01T23:59:59.000Z

185

Optimization Online - Pricing with uncertain customer valuations  

E-Print Network (OSTI)

Feb 5, 2008 ... Abstract: Uncertain demand in pricing problems is often modeled using the sum of a linear price-response function and a zero-mean random ...

186

Option Value of Electricity Demand Response  

E-Print Network (OSTI)

4. Option Value of a Thermal Energy Storage System for 5counter Real-time Prices Thermal Energy Storage vii Abstractfor the day, operating thermal energy storage overnight for

Sezgen, Osman; Goldman, Charles; Krishnarao, P.

2005-01-01T23:59:59.000Z

187

Optimization Online - Option - Alloction funds- Transaction costs  

E-Print Network (OSTI)

Apr 18, 2009 ... Tests on portfolio efficiency concern, at first time, a long-term investor with Out- The-Country options and strike prices are approximate by a ...

188

Dynamic Pricing: A learning Approach  

E-Print Network (OSTI)

We present an optimization approach for jointly learning the demand as a functionof price, and dynamically setting prices of products in an oligopoly environment in order to maximize expected revenue. The models we consider ...

Bertsimas, Dimitris J.

189

Natural Gas Citygate Price  

Annual Energy Outlook 2012 (EIA)

Citygate Price Residential Price Commercial Price Industrial Price Electric Power Price Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross...

190

Cheese Prices  

E-Print Network (OSTI)

Cheese prices are derived from the USDA Agricultural Marketing Service Market News, the National Agricultural Statistics Service, and the Chicago Mercantile Exchange. This publication explains the process of cheese pricing. It includes information on hauling rates and freight differentials

Schwart Jr., Robert B.; Anderson, David P.; Knutson, Ronald D.

2003-08-25T23:59:59.000Z

191

Sarah Price  

NLE Websites -- All DOE Office Websites (Extended Search)

Sarah K Price Sarah Price Energy Efficiency Standards Group Lawrence Berkeley National Laboratory 1 Cyclotron Road MS 90R4000 Berkeley CA 94720 Office Location: 90-4128B (510)...

192

Marisa Price  

NLE Websites -- All DOE Office Websites (Extended Search)

Marisa Dawn Price Marisa Price Communications Office Lawrence Berkeley National Laboratory 1 Cyclotron Road MS 90R3029B Berkeley CA 94720 Office Location: 90-2056B (510) 495-2713...

193

Optimization models for joint airline pricing and seat inventory control : multiple products, multiple periods  

E-Print Network (OSTI)

Pricing and revenue management are two essential levers to optimize the sales of an airline's seat inventory and maximize revenues. Over the past few decades, they have generated a great deal of research but have typically ...

Cizaire, Claire (Claire Jia Ling)

2011-01-01T23:59:59.000Z

194

Gas Prices  

NLE Websites -- All DOE Office Websites (Extended Search)

Prices Gasoline Prices for U.S. Cities Click on the map to view gas prices for cities in your state. AK VT ME NH NH MA MA RI CT CT DC NJ DE DE NY WV VA NC SC FL GA AL MS TN KY IN...

195

Evaluation of the New CNDV Option of the Community Land Model: Effects of Dynamic Vegetation and Interactive Nitrogen on CLM4 Means and Variability  

Science Conference Proceedings (OSTI)

The Community Land Model, version 4 (CLM4) includes the option to run the prognostic carbon–nitrogen (CN) model with dynamic vegetation (CNDV). CNDV, which simulates unmanaged vegetation, modifies the CN framework to implement plant biogeography ...

C. Kendra Gotangco Castillo; Samuel Levis; Peter Thornton

2012-06-01T23:59:59.000Z

196

Energy and Financial Markets Overview: Crude Oil Price Formation  

U.S. Energy Information Administration (EIA)

• E&P costs • E&P investments • E&P innovations Physical balancing • Inventories Markets & market behavior • Energy prices ? spot ? futures ? options

197

Green Power Network: Green Pricing  

NLE Websites -- All DOE Office Websites (Extended Search)

Table of Utility Programs by State Table of Utility Programs by State List of Utilities Offering Green Power Top Ten Utility Green Power Programs Green Power Marketing Green Certificates Carbon Offsets State Policies Green Pricing Green pricing is an optional utility service that allows customers an opportunity to support a greater level of utility company investment in renewable energy technologies. Participating customers pay a premium on their electric bills to cover the incremental cost of the additional renewable energy. To date, more than 860 utilities, including investor-owned, municipal utilities, and cooperatives, offer a green pricing option. Table of Utility Programs by State List of Utilities Offering Green Power Top Ten Utility Green Power Programs National Green Pricing Map

198

Yardstick and Ex-post Regulation by Norm Model: Empirical Equivalence, Pricing Effect, and Performance in Sweeden  

E-Print Network (OSTI)

in average costs, quality of service, and network energy losses. The norm models seem to reflect the main network features, demand characteristics, and capital stocks of real utilities. However, the price of labour affects relative performance. Also... not adjusted their costs significantly in response to the incentives. Furthermore, we do not find evidence of improvement in quality of service and reduction in network energy losses although less efficient investor-owned networks seem to have improved...

Jamasb, Tooraj; Söderberg, M

199

Electric retail market options: The customer perspective  

SciTech Connect

This report describes various options that are now available for retail electric customers, or that may become available during the next few years as the electric utility industry restructures. These options include different ways of meeting demand for energy services, different providers of service or points of contact with providers, and different pricing structures for purchased services. Purpose of this document is to examine these options from the customer`s perspective: how might being a retail electric customer in 5--10 years differ from now? Seizing opportunities to reduce cost of electric service is likely to entail working with different service providers; thus, transaction costs are involved. Some of the options considered are speculative. Some transitional options include relocation, customer-built/operated transmission lines, municipalization, self-generation, and long-term contracts with suppliers. All these may change or diminish in a restructured industry. Brokers seem likely to become more common unless restructuring takes the form of mandatory poolcos (wholesale). Some options appear robust, ie, they are likely to become more common regardless of how restructuring is accomplished: increased competition among energy carriers (gas vs electric), real-time pricing, etc. This report identified some of the qualitative differences among the various options. For customers using large amounts of electricity, different alternatives are likely to affect greatly service price, transaction costs, tailoring service to customer preferences, and risks for customer. For retail customers using small amounts of electricity, there may be little difference among the options except service price.

Hadley, S.W.; Hillsman, E.L.

1995-07-01T23:59:59.000Z

200

The Dynamics of Price Discovery ?  

E-Print Network (OSTI)

When arbitrage related prices share the same underlying asset, there are multiple channels to incorporate new information on the fundamental value of the asset. In this paper, we present an empirical microstructure model to characterize each channel’s price discovery speed. We identify the information sources of price adjustments to separate price discovery from the market responses to liquidity shocks. We assess market efficiency of price discovery visually, by the time paths of price convergence toward the new fundamental value, and numerically, by the magnitude of pricing errors during the price discovery process. We also use our price discovery model to illustrate the structural determinants of two often used price discovery measures: the information share and component share. We show that two measures are static and unable to reveal the underlying price discovery dynamics between markets. Applying our new measures to quotes from spot foreign exchange rates, we find that substantial price discovery of the yen/euro exchange rate occurs through the US dollar. The dollar’s price discovery contribution is positively related to the relative liquidity of the dollar markets versus the cross rate market, and reaches a minimum during the European business hours.

Bingcheng Yan; Eric Zivot

2004-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "option pricing model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


201

Residential on site solar heating systems: a project evaluation using the capital asset pricing model  

SciTech Connect

An energy source ready for immediate use on a commercial scale is solar energy in the form of On Site Solar Heating (OSSH) systems. These systems collect solar energy with rooftop panels, store excess energy in water storage tanks and can, in certain circumstances, provide 100% of the space heating and hot water required by the occupants of the residential or commercial structure on which the system is located. Such systems would take advantage of a free and inexhaustible energy source--sunlight. The principal drawback of such systems is the high initial capital cost. The solution would normally be a carefully worked out corporate financing plan. However, at the moment it is individual homeowners and not corporations who are attempting to finance these systems. As a result, the terms of finance are excessively stringent and constitute the main obstacle to the large scale market penetration of OSSH. This study analyzes the feasibility of OSSH as a private utility investment. Such systems would be installed and owned by private utilities and would displace other investment projects, principally electric generating plants. The return on OSSH is calculated on the basis of the cost to the consumer of the equivalent amount of electrical energy that is displaced by the OSSH system. The hurdle rate for investment in OSSH is calculated using the Sharpe--Lintner Capital Asset Pricing Model. The results of this study indicate that OSSH is a low risk investment having an appropriate hurdle rate of 7.9%. At this rate, OSSH investment appears marginally acceptable in northern California and unambiguously acceptable in southern California. The results also suggest that utility investment in OSSH should lead to a higher degree of financial leverage for utility companies without a concurrent deterioration in the risk class of utility equity.

Schutz, S.R.

1978-12-01T23:59:59.000Z

202

Option Value of Electricity Demand Response  

E-Print Network (OSTI)

17 3.3.1 Distributed Generation Options17 3.3.2 Distributed Generation Modeling18 3.3.3 Distributed Generation Option Results and

Sezgen, Osman; Goldman, Charles; Krishnarao, P.

2005-01-01T23:59:59.000Z

203

Stock Price and Index Forecasting by Arbitrage Pricing Theory-Based Gaussian TFA Learning  

E-Print Network (OSTI)

Stock Price and Index Forecasting by Arbitrage Pricing Theory-Based Gaussian TFA Learning Kai Chun take advantage of those models. In literature, forecasting of stock prices within the framework Xu, (2002) "Stock price and index forecasting by arbitrage pricing theory-based gaussian TFA learning

Xu, Lei

204

A Spatio-Temporal Model of House Prices in the US  

E-Print Network (OSTI)

from the link to the labour market. For example, Bover, Maullbauer and Murphy (1989) argue that di¤erences in the level of house prices between regions lowers labour mobility. See also Meen (2002). House prices at the regional level also exhibit much... and between correlation coe¢ cients for three geographical regions dividing the USA into broadly the West, the Middle and the East. The results are shown in Tables 3 and 4. In Table 3 we tabulate within and between correlation coe¢ cients for the 8 BEA regions...

Holly, Sean; Pesaran, M Hashem; Yamagata, Takashi

205

Lynn Price  

NLE Websites -- All DOE Office Websites (Extended Search)

Lynn Price Lynn Price China Energy Group Lawrence Berkeley National Laboratory 1 Cyclotron Road MS 90R2002 Berkeley CA 94720 Office Location: 90-2108 (510) 486-6519 LKPrice@lbl.gov Lynn Price is a Staff Scientist and Leader of the China Energy Group of the Energy Analysis and Environmental Impacts Department, Environmental Energy Technologies Division, of Lawrence Berkeley National Laboratory. Ms. Price has a MS in Environmental Science from the University of Wisconsin-Madison and has worked at LBNL since 1990. Ms. Price has been a member of the Intergovernmental Panel on Climate Change, which won the Nobel Peace Prize in 2007, since 1994 and was an author on the industrial sector chapter of IPCC's Fourth Assessment Report on Mitigation of Climate Change. Since 1999, Ms. Price has provided technical assistance to the Energy

206

Forecast Prices  

Gasoline and Diesel Fuel Update (EIA)

Notes: Notes: Prices have already recovered from the spike, but are expected to remain elevated over year-ago levels because of the higher crude oil prices. There is a lot of uncertainty in the market as to where crude oil prices will be next winter, but our current forecast has them declining about $2.50 per barrel (6 cents per gallon) from today's levels by next October. U.S. average residential heating oil prices peaked at almost $1.50 as a result of the problems in the Northeast this past winter. The current forecast has them peaking at $1.08 next winter, but we will be revisiting the outlook in more detail next fall and presenting our findings at the annual Winter Fuels Conference. Similarly, diesel prices are also expected to fall. The current outlook projects retail diesel prices dropping about 14 cents per gallon

207

Uncertainty Representation: Estimating Process Parameters for Forward Price Forecasting  

Science Conference Proceedings (OSTI)

Market prices set the value of electric power assets and contracts, yet forward prices are unavailable for time horizons relevant to most valuations. Price forecasts are inherently uncertain because the drivers of prices are uncertain, but equilibrating market forces also work to reduce the growth of uncertainty over time. Consequently, quantifying the degree of future price uncertainty is difficult, but has tremendous strategic potential for power companies seeking to value real options and invest in fl...

1999-12-10T23:59:59.000Z

208

Stephanie Price  

Energy.gov (U.S. Department of Energy (DOE))

Stephanie Price is a communicator at the National Renewable Energy Laboratory, which assists EERE in providing technical content for many of its websites.

209

Snuller Price  

NLE Websites -- All DOE Office Websites (Extended Search)

Snuller Price Energy and Environmental Economics NOTICE Due to the current lapse of federal funding, Berkeley Lab websites are accessible, but may not be updated until Congress...

210

Accounting for fuel price risk: Using forward natural gas prices instead of gas price forecasts to compare renewable to natural gas-fired generation  

DOE Green Energy (OSTI)

Against the backdrop of increasingly volatile natural gas prices, renewable energy resources, which by their nature are immune to natural gas fuel price risk, provide a real economic benefit. Unlike many contracts for natural gas-fired generation, renewable generation is typically sold under fixed-price contracts. Assuming that electricity consumers value long-term price stability, a utility or other retail electricity supplier that is looking to expand its resource portfolio (or a policymaker interested in evaluating different resource options) should therefore compare the cost of fixed-price renewable generation to the hedged or guaranteed cost of new natural gas-fired generation, rather than to projected costs based on uncertain gas price forecasts. To do otherwise would be to compare apples to oranges: by their nature, renewable resources carry no natural gas fuel price risk, and if the market values that attribute, then the most appropriate comparison is to the hedged cost of natural gas-fired generation. Nonetheless, utilities and others often compare the costs of renewable to gas-fired generation using as their fuel price input long-term gas price forecasts that are inherently uncertain, rather than long-term natural gas forward prices that can actually be locked in. This practice raises the critical question of how these two price streams compare. If they are similar, then one might conclude that forecast-based modeling and planning exercises are in fact approximating an apples-to-apples comparison, and no further consideration is necessary. If, however, natural gas forward prices systematically differ from price forecasts, then the use of such forecasts in planning and modeling exercises will yield results that are biased in favor of either renewable (if forwards < forecasts) or natural gas-fired generation (if forwards > forecasts). In this report we compare the cost of hedging natural gas price risk through traditional gas-based hedging instruments (e.g., futures, swaps, and fixed-price physical supply contracts) to contemporaneous forecasts of spot natural gas prices, with the purpose of identifying any systematic differences between the two. Although our data set is quite limited, we find that over the past three years, forward gas prices for durations of 2-10 years have been considerably higher than most natural gas spot price forecasts, including the reference case forecasts developed by the Energy Information Administration (EIA). This difference is striking, and implies that resource planning and modeling exercises based on these forecasts over the past three years have yielded results that are biased in favor of gas-fired generation (again, presuming that long-term stability is desirable). As discussed later, these findings have important ramifications for resource planners, energy modelers, and policy-makers.

Bolinger, Mark; Wiser, Ryan; Golove, William

2003-08-13T23:59:59.000Z

211

Examination of Housing Price Impacts on Residential Properties Before and After Superfund Remediation Using Spatial Hedonic Modeling  

E-Print Network (OSTI)

Although recent brownfields redevelopment research using theories of real estate valuation and neighborhood change have indicated negative effects on surrounding residential housing, little evidence exists to show price impacts and sociodemographic change after remediation. This study examines the extent and size of the economic impact of Superfund sites on surrounding single-family residential properties before and after remediation in Miami-Dade County and examines trends for contemporaneous sociodemographic changes. The study combines the economic impact from changes in environmental quality with contemporaneous sociodemographic changes within the purview of environmental and social justice. This study uses spatial hedonic price modeling on a comprehensive dataset of property-level data, with corresponding sales prices of housing transactions while controlling for other structural, neighborhood, and submarkets characteristics for assessing economic impact. Findings revealed that housing sales prices for single-family residential properties significantly increases as distance to the nearest contaminated Superfund increases. Following remediation, this negative impact declined and housing values increased significantly in neighborhoods with remedied Superfund sites albeit more so in low housing submarkets than premium submarkets. Spatial hedonic models outperformed traditional OLS models in presenting unbiased efficient parameter estimates, correcting for spatial dependence. Although no evidence for gentrification was observed, there existed significant differences between certain sociodemographic characteristics of neighborhoods around contaminated Superfund sites and those of properties located elsewhere leading to concerns of environmental and social justice. Findings suggest that low-income minority populations are more likely to be living in neighborhoods around contaminated Superfund sites and experience a greater negative effect on housing sales prices; these sites are also less likely to be remedied as compared to sites located elsewhere. The findings highlight not only the revealed preferences of homeowners with respect to environmental disamenities, but also help inform policymakers and researchers of the impact of brownfields redevelopment on economic and sociodemographic characteristics of a growing urban region with evolving cultural and social diversity. Incorporating influences of housing submarkets, neighborhood amenities, and spatial dependence help provide a holistic and comprehensive model for examining environmental disamenities and provide a better understanding for neighborhood change.

Mhatre, Pratik Chandrashekhar

2009-08-01T23:59:59.000Z

212

An Equilibrium Pricing Model for Weather Derivatives in a Multi-commodity Setting  

E-Print Network (OSTI)

, Berkeley, CA, 94720-1777 USA August 20, 2008 Abstract Many industries are exposed to weather risk. Weather weather derivatives that are issued in a fixed quantity by a financial underwriter. The supply and demand of each industry has retail price, cost, and demand as common factors and these, possibly random, can

Oren, Shmuel S.

213

Revised Draft Fuel Price Forecasts for the Draft  

E-Print Network (OSTI)

Natural gas prices, as well as oil and coal prices, are forecast using an Excel spreadsheet model at this time, natural gas prices are forecast in more detail than oil and coal prices. Residential in the industrial boiler fuel market to help keep natural gas prices low. Continuing declines in coal prices coupled

214

Essays on Price Dynamics  

E-Print Network (OSTI)

Small Regular Price Changes . . . . . . . . . . . . . . .4 The Cyclicality of Effective Prices2.3 Wholesale Price vs. Retail

Hong, Gee Hee

2012-01-01T23:59:59.000Z

215

Study on Real Options Model of Operating Capital Value of Generator for Spinning Reserve and Risk Assessment Based on Monte Carlo Methods  

Science Conference Proceedings (OSTI)

Electricity market has complex market rules, and its operation with great uncertainty. In this paper, the real options model of operating capital value of generator for spinning reserve is constructed under uncertainty market conditions including uncertainty ...

Xin Ma

2008-10-01T23:59:59.000Z

216

Essays on Three Price Judgments: Price Fairness, Price Magnitude, and Price Expectation.  

E-Print Network (OSTI)

??This dissertation addresses three important price judgments: price fairness, price magnitude, and price expectation. Developed over three chapters, the main objective of this research is… (more)

Bhowmick, Sandeep

2010-01-01T23:59:59.000Z

217

Joint pricing and inventory control under reference price effects.  

E-Print Network (OSTI)

??In many firms the pricing and inventory control functions are separated. However, a number of theoretical models suggest a joint determination of inventory levels and… (more)

Gimpl-Heersink, Lisa

2008-01-01T23:59:59.000Z

218

Explanatory Factors and Causality in the Dynamics of Volatility Surfaces Implied from OTC Asian---Pacific Currency Options  

Science Conference Proceedings (OSTI)

Volatility implied from observed option contracts systematically varies with the contracts' strike price and time to expiration, giving rise to an instantaneously non-flat implied volatility surface (IVS) that exhibits substantial time variation. We ... Keywords: Causality, Factor model, Implied volatility surfaces

Georgios Chalamandaris; Andrianos E. Tsekrekos

2013-03-01T23:59:59.000Z

219

Variable-response model of electricity demand by time of day: Results of a Wisconsin pricing experiment: Final report  

Science Conference Proceedings (OSTI)

Observationally alike households may differ in demand parameters and thus in economic quantities that are functions of those parameters. We have proposed a methodology for dealing with this variation. Estimation of both translog and CES versions of the model with data from the Wisconsin Electricity Pricing Experiment revealed considerable variation among households in time-of-day electricity consumption demand parameters for both summer and winter seasons and for several different definitions of the peak period. Observed household characteristics explained only a small share of total household differences, but permanent household differences dominated month-to-month variation in either expenditure shares or log consumption ratios in most cases. Permanent differences among households are important relative to total variation, including transitory month-to-month variation. We calculated various economic variables from the demand parameters, including the partial elasticity of substitution, compensated and uncompensated elasticities, and a measure of electricity expenditure under peak load pricing required to maintain the utility level under flat rate pricing relative to the flat rate expenditure. Because these are nonlinear functions of the household demand parameters, the mean parameter value over households with different demand parameters may be substantially different from the value of the function at mean values, under the representative household paradigm. For time-of-day electricity demand, variation among households is significant but small relative to mean parameter values. Therefore, controlling for the effect of household variation makes little difference in these mean calculations, but it does imply substantial variation among households in the welfare implications (and elasticities of response) of the introduction of time-of-day pricing. 25 refs., 12 tabs.

Lillard, L.

1987-06-01T23:59:59.000Z

220

An analytic network process model for municipal solid waste disposal options  

SciTech Connect

The aim of this paper is to present an evaluation method that can aid decision makers in a local civic body to prioritize and select appropriate municipal solid waste disposal methods. We introduce a hierarchical network (hiernet) decision structure and apply the analytic network process (ANP) super-matrix approach to measure the relative desirability of disposal alternatives using value judgments as the input of the various stakeholders. ANP is a flexible analytical program that enables decision makers to find the best possible solution to complex problems by breaking down a problem into a systematic network of inter-relationships among the various levels and attributes. This method therefore may not only aid in selecting the best alternative but also helps decision makers to understand why an alternative is preferred over the other options.

Khan, Sheeba [Department of Civil and Environmental Engineering, Youngstown State University, OH 44555, United States of America (United States)], E-mail: sheebanishat@yahoo.com; Faisal, Mohd Nishat [Department of Management Studies, Indian Institute of Technology Delhi, New Delhi 110 016 (India)], E-mail: nishat786@yahoo.com

2008-07-01T23:59:59.000Z

Note: This page contains sample records for the topic "option pricing model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


221

Dynamic Pricing and Learning in Electricity Markets  

Science Conference Proceedings (OSTI)

We analyze the price-formation process in an infinite-horizon oligopoly model where hydroelectric generators engage in dynamic price-based competition. The analysis focuses on the role of "indifference" prices, i.e., prices that equate the gains from ... Keywords: Dynamic auctions, Economics, Games: stochastic, Natural resources: energy, Noncooperative, Restructured electricity markets, Water resources

Alfredo Garcia; Enrique Campos-Nañez; James Reitzes

2005-03-01T23:59:59.000Z

222

Pricing transmission rights using ant colony optimization  

Science Conference Proceedings (OSTI)

We propose a novel idea for pricing Transmission Rights (which are similar to financial options) using a nature inspired meta heuristic algorithm, Ant Colony Optimization (ACO). ACO has been used extensively in combinatorial optimization problems and ... Keywords: ant colony optimization, financial options, transmission rights

Sameer Kumar Singh; Ruppa K. Thulasiram; Parimala Thulasiraman

2011-07-01T23:59:59.000Z

223

Energy modeling applications for analysis of policy options-an overview  

Science Conference Proceedings (OSTI)

The paper reviews the complex relationships of the elements of a national energy system and the integrated energy planning approach that can be inevitably implemented through computer based modeling tools. General format of an IEP model and its main ... Keywords: energy models, integrated energy planning, modeling

Mukhtar H. Sahir; Arshad H. Qureshi

2006-09-01T23:59:59.000Z

224

Role of Future Generation Options for the U.S. Electric Sector  

Science Conference Proceedings (OSTI)

This Technical Update documents efforts to enhance, update, and apply EPRI's financial model of the U.S. electric sector for generation capacity expansion and dispatch at the national and regional levels. The model evaluates the possible effects of various climate policy, renewable portfolio standard (RPS), technology, and market scenarios on the deployment and operation of nuclear, fossil, and renewable generation options and on electricity prices, emissions, fuel use, and other parameters. Within indiv...

2009-03-30T23:59:59.000Z

225

NREL: More Search Options  

NLE Websites -- All DOE Office Websites (Extended Search)

More Search Options More Search Options Search More Search Options Site Map Printable Version The following options help you find information on the National Renewable Energy Laboratory site, locate NREL staff, browse publication and photograph collections, and see what hot topics other site visitors are looking for. Search the NREL Web Site Search Tip: use quotes to find exact phrases Example: "renewable energy" Tip: use plus signs to find results that contain all your search terms Example: +biodiesel +buses Search Help Find NREL Staff in the Employee Locator Search by first or last name: Search Select a search type Select your criteria Enter your search term Look at Recent Hot Topics Biomass HOMER (computer model) Hybrid Electric Vehicles Hydrogen and Fuel Cells Jobs PVWATTS (software)

226

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

0 0 1 June 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 June 8, 2010 Release Crude Oil Prices. WTI crude oil spot prices averaged less than $74 per barrel in May 2010, almost $11 per barrel below the prior month's average and $7 per barrel lower than forecast in last month's Outlook. EIA projects WTI prices will average about $79 per barrel over the second half of this year and rise to $84 by the end of next year, a decrease of about $3 per barrel from the previous Outlook (West Texas Intermediate Crude Oil Price Chart). Energy price forecasts are highly uncertain, as history has shown. Prices for near-term futures options contracts suggest that the market attaches

227

Microsoft Word - Price Uncertainty Supplement.doc  

Gasoline and Diesel Fuel Update (EIA)

May 2010 May 2010 Short-Term Energy Outlook Energy Price Volatility and Forecast Uncertainty 1 May 11, 2010 Release Crude Oil Prices. WTI crude oil spot prices averaged $84 per barrel in April 2010, about $3 per barrel above the prior month's average and $2 per barrel higher than forecast in last month's Outlook. EIA projects WTI prices will average about $84 per barrel over the second half of this year and rise to $87 by the end of next year, an increase of about $2 per barrel from the previous Outlook (West Texas Intermediate Crude Oil Price Chart). Energy price forecasts are highly uncertain, as history has shown. Prices for near-term futures options contracts suggest that the market attaches

228

Lynn Price  

NLE Websites -- All DOE Office Websites (Extended Search)

Lynn Price China Energy Group Lawrence Berkeley National Laboratory 1 Cyclotron Road MS 90R2002 Berkeley CA 94720 Office Location: 90-2108 (510) 486-6519 LKPrice@lbl.gov NOTICE Due...

229

Snuller Price  

NLE Websites -- All DOE Office Websites (Extended Search)

Snuller Price Energy and Environmental Economics This speaker was a visiting speaker who delivered a talk or talks on the date(s) shown at the links below. This speaker is not...

230

PRICE GOUGING  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

home heating costs? How will those be affected? With an overall increase in the price of heating oil and natural gas, we expect that there may be an increase in home heating costs...

231

Phillip Price  

NLE Websites -- All DOE Office Websites (Extended Search)

90-2006 (510) 486-7875 PNPrice@lbl.gov Dr. Phillip Price has a Ph.D. in physics from the University of Kentucky, and has worked in the Indoor Environment Department since 1992. In...

232

After the Fall: An Ex Post Characterization of Housing Price Declines Across Metropolitan Areas  

E-Print Network (OSTI)

Model: How Much Do House Prices Matter?" , Real EstateThe Subprime Crisis and House Price Appreciation", NationalT. 2005, "Assessing High House Prices: Bubbles, Fundamentals

Carson, Richard T; Dastrup, Samuel R.

2009-01-01T23:59:59.000Z

233

Stock market volatility and price discovery : three essays on the effect of macroeconomic information  

E-Print Network (OSTI)

Simple Microstructure Model of Price Determination . . 3.11Stock Market Volatility and Price Discovery: Three Essays onConstruction Spending PRICES CPI MONETARY POLICY FFR Source:

Rangel, Jose Gonzalo

2006-01-01T23:59:59.000Z

234

Putting downward pressure on natural gas prices: The impact of renewable energy and energy efficiency  

E-Print Network (OSTI)

in delivered natural gas prices. References American CouncilACEEE). 2003. Natural Gas Price Effects of Energy Efficiencydownward pressure on gas prices. 2 Many recent modeling

Wiser, Ryan; Bolinger, Mark; St. Clair, Matthew

2004-01-01T23:59:59.000Z

235

Price Dispersion on the Internet: Good Firms and Bad Firms  

E-Print Network (OSTI)

Abstract. Internet firms charge a wide range of prices for homogeneous products, and high-priced firms remain high-priced and low-priced firms remain low-priced over long periods. One explanation is that high-price firms are charging a premium for superior service. An alternative, price-dispersion explanation is that firms vary the prices for informed and uniformed consumers (Salop and Stiglitz, 1977) or serious shoppers and others (Wilde and Schwartz, 1979). The pricing pattern for a digital camera and a flatbed scanner is consistent with the price-dispersion model and inconsistent with the service-premium hypothesis. I.

Kathy Baylis; Jeffrey M. Perloff

2002-01-01T23:59:59.000Z

236

Assessment of solar options for small power systems applications. Volume V. SOLSTEP: a computer model for solar plant system simulations  

DOE Green Energy (OSTI)

The simulation code, SOLSTEP, was developed at the Pacific Northwest Laboratory to facilitate the evaluation of proposed designs for solar thermal power plants. It allows the user to analyze the thermodynamic and economic performance of a conceptual design for several field size-storage capacity configurations. This feature makes it possible to study the levelized energy cost of a proposed concept over a range of plant capacity factors. The thermodynamic performance is analyzed on a time step basis using actual recorded meteorological and insolation data for specific geographic locations. The flexibility of the model enables the user to analyze both central and distributed generation concepts using either thermal or electric storage systems. The thermodynamic and economic analyses view the plant in a macroscopic manner as a combination of component subsystems. In the thermodynamic simulation, concentrator optical performance is modeled as a function of solar position; other aspects of collector performance can optionally be treated as functions of ambient air temperature, wind speed, and component power level. The power conversion model accounts for the effects of ambient air temperature, partial load operation, auxiliary power demands, and plant standby and startup energy requirements. The code was designed in a modular fashion to provide efficient evaluations of the collector system, total plant, and system economics. SOLSTEP has been used to analyze a variety of solar thermal generic concepts involving several collector types and energy conversion and storage subsystems. The code's straightforward models and modular nature facilitated simple and inexpensive parametric studies of solar thermal power plant performance.

Bird, S.P.

1980-09-01T23:59:59.000Z

237

Crude Oil Affects Gasoline Prices  

U.S. Energy Information Administration (EIA)

Crude Oil Affects Gasoline Prices. WTI Crude Oil Price. Retail Gasoline Price. Source: Energy Information Administration

238

Perception of price when price information is costly: evidence from electricity demand  

Science Conference Proceedings (OSTI)

Economic theory predicts that a well-informed consumer facing multiple prices responds to marginal price rather than to average price because he equates benefits with costs at the margin. The marginal price postulate, however, may not be true if information regarding marginal price is costly. Residential consumption of electricity is an example of a good for which it is costly to determine marginal price since the price changes with quantity purchased according to a declining-block schedule. If the cost of determining marginal price exceeds its expected benefits, the consumer will base his consumption on simpler information rather than on marginal price. The most obvious candidate is the monthly bill. Since electricity expenditures are greater than they would be if priced at marginal price, perceived price is anticipated to be higher than marginal price. The model includes a price perception variable that depends on the complexity of the rate structure as measured by the ratio of average to marginal price. Pooled annual data from 1960 to 1980 on the seven Ohio electric utilities are used for estimation. The evidence supports the hypothesis that the residential consumer responds to average price. Further, the expected increase in consumer's surplus, if marginal price were correctly perceived, is calculated at the sample mean and found to be negligible compared to any possible cost of determining marginal price.

Shin, J.S.

1983-01-01T23:59:59.000Z

239

Option #1  

E-Print Network (OSTI)

The Novell Small Business Suite is a powerful tool for a small business, at a low price. Because small businesses have limited budgets, they have limited capability to install, configure, patch and maintain their servers. Because of the technical complexity of such products, it can be easy for security holes to be found and taken advantage of without a small business being aware. Novell has a reputation for strong security. But, since converting their product to become TCP/IP based, it has many potential security risks not yet recognized. Key fingerprint = AF19 FA27 2F94 998D FDB5 DE3D F8B5 06E4 A169 4E46

unknown authors

2003-01-01T23:59:59.000Z

240

Process Options Description for Vitrification Flowsheet Model of INEEL Sodium Bearing Waste  

SciTech Connect

The purpose of this document is to provide the technical information to Savannah River Site (SRS) personnel that is required for the development of a basic steady-state process simulation of the vitrification treatment train of sodium bearing waste (SBW) at Idaho National Engineering and nvironmental Laboratory (INEEL). INEEL considers simulation to have an important role in the integration/optimization of treatment process trains for the High Level Waste (HLW) Program. This project involves a joint Technical Task Plan (TTP ID77WT31, Subtask C) between SRS and INEEL. The work scope of simulation is different at the two sites. This document addresses only the treatment of SBW at INEEL. The simulation model(s) is to be built by SRS for INEEL in FY-2001.

Nichols, Todd Travis; Taylor, Dean Dalton; Lauerhass, Lance; Barnes, Charles Marshall

2001-02-01T23:59:59.000Z

Note: This page contains sample records for the topic "option pricing model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


241

ELECTRICITY FORWARD PRICES: A High-Frequency Empirical Analysis  

E-Print Network (OSTI)

and Optimal Hedging in Electricity Forward Markets. JournalP. 2002. Modelling Electricity Prices: Interna- tionalPricing and Risk Managing Electricity Derivatives. The U.S.

Longstaff, Francis A; Wang, Ashley

2002-01-01T23:59:59.000Z

242

Electricity Forward Prices: A High-Frequency Empirical Analysis  

E-Print Network (OSTI)

and Optimal Hedging in Electricity Forward Markets. JournalP. 2002. Modelling Electricity Prices: Interna- tionalPricing and Risk Managing Electricity Derivatives. The U.S.

Longstaff, Francis; Wang, Ashley

2002-01-01T23:59:59.000Z

243

Economics of gas supply: the effects of decontrol-policy options  

Science Conference Proceedings (OSTI)

A model for interpreting the effects of four alternatives to the Natural Gas Policy Act covers the options of accelerated partial decontrol, early full decontrol, and phased decontrol. The effects of these gas-pricing options on the development of domestic supplies of both conventional and unconventional sources, as well as the forecast under current policy, are examined in detail. All of the alternatives have a positive effect on supply relative to continuing controls indefinitely. The methodology for production forecasting appears in the appendix. 6 figures, 5 tables. (DCK)

Muzzo, S.E.

1982-10-01T23:59:59.000Z

244

SRM Pricing Policy  

Science Conference Proceedings (OSTI)

... rates are used to calculate the price for each ... Therefore, prices for new lots and renewal issues of ... changed, all SRMs may be re-priced taking into ...

2012-11-16T23:59:59.000Z

245

Pennsylvania Gasoline Price Data  

NLE Websites -- All DOE Office Websites (Extended Search)

- GasBuddy.com Pennsylvania Gas Prices (selected cities) - GasBuddy.com Pennsylvania Gas Prices (organized by county) - Automotive.com Gas Prices of the United States:...

246

Renewable Power Options for Electrical Generation on Kaua'i: Economics and Performance Modeling  

DOE Green Energy (OSTI)

The Hawaii Clean Energy Initiative (HCEI) is working with a team led by the U.S. Department of Energy's (DOE) National Renewable Energy Laboratory (NREL) to assess the economic and technical feasibility of increasing the contribution of renewable energy in Hawaii. This part of the HCEI project focuses on working with Kaua'i Island Utility Cooperative (KIUC) to understand how to integrate higher levels of renewable energy into the electric power system of the island of Kaua'i. NREL partnered with KIUC to perform an economic and technical analysis and discussed how to model PV inverters in the electrical grid.

Burman, K.; Keller, J.; Kroposki, B.; Lilienthal, P.; Slaughter, R.; Glassmire, J.

2011-11-01T23:59:59.000Z

247

Natural resource prices: will they ever turn up?  

E-Print Network (OSTI)

the same as the price of unextracted coal-here~ called theModel 1991 real price* Resource Aluminum Coal Copper Iron1991) 1991 actual price * Resource Aluminum Coal Copper Iron

Berck, Peter; Roberts, Mike

1995-01-01T23:59:59.000Z

248

Model-Based Analysis of Electric Drive Options for Medium-Duty Parcel Delivery Vehicles: Preprint  

DOE Green Energy (OSTI)

Medium-duty vehicles are used in a broad array of fleet applications, including parcel delivery. These vehicles are excellent candidates for electric drive applications due to their transient-intensive duty cycles, operation in densely populated areas, and relatively high fuel consumption and emissions. The National Renewable Energy Laboratory (NREL) conducted a robust assessment of parcel delivery routes and completed a model-based techno-economic analysis of hybrid electric vehicle (HEV) and plug-in hybrid electric vehicle configurations. First, NREL characterized parcel delivery vehicle usage patterns, most notably daily distance driven and drive cycle intensity. Second, drive-cycle analysis results framed the selection of drive cycles used to test a parcel delivery HEV on a chassis dynamometer. Next, measured fuel consumption results were used to validate simulated fuel consumption values derived from a dynamic model of the parcel delivery vehicle. Finally, NREL swept a matrix of 120 component size, usage, and cost combinations to assess impacts on fuel consumption and vehicle cost. The results illustrated the dependency of component sizing on drive-cycle intensity and daily distance driven and may allow parcel delivery fleets to match the most appropriate electric drive vehicle to their fleet usage profile.

Barnitt, R. A.; Brooker, A. D.; Ramroth, L.

2010-12-01T23:59:59.000Z

249

Spot pricing of public utility services  

E-Print Network (OSTI)

This thesis analyzes how public utility prices should be changed over time and space. Earlier static and non spatial models of public utility pricing emerge as special cases of the theory developed here. Electricity is ...

Bohn, Roger E.

1982-01-01T23:59:59.000Z

250

Three essays on product quality and pricing  

E-Print Network (OSTI)

This dissertation consists of three essays on product quality and pricing. Essay 1: Pricing and Quality Provision in a Channel: A Model of Efficient Relational Contracts The first essay analyzes how quality concerns affect ...

Nistor, Cristina (Cristina Daniela)

2012-01-01T23:59:59.000Z

251

Limit order markets, liquidity, and price impact  

E-Print Network (OSTI)

In this thesis, I explore various aspects of market liquidity and analyze its effect on asset prices. First, in a model of a limit order market I explain how to define liquidity and derive a price impact function. Second, ...

Rosu, Ioanid, 1970-

2004-01-01T23:59:59.000Z

252

Prices & Trends  

Energy.gov (U.S. Department of Energy (DOE))

The U.S. Energy Information Administration (EIA) collects, analyzes, and disseminates independent and impartial energy information to promote sound policymaking, efficient markets, and public understanding of energy and its interaction with the economy and the environment. Learn about EIA and Energy Department organizations that track energy prices and trends.

253

A semi-dynamic approach for valuing and hedging options on two assets with continuous payout  

Science Conference Proceedings (OSTI)

A central problem in risk management is how to develop effective and accurate hedging strategies for financial and physical assets which are usually not liquidly traded in the market. We consider the problem of replicating the payoffs of options on two ... Keywords: electricity derivatives, options pricing, real options, semi-dynamic hedging, spark spread, spread options

Shi-Jie Deng

2007-09-01T23:59:59.000Z

254

Conspicuous Consumption and Dynamic Pricing  

Science Conference Proceedings (OSTI)

How do firms develop marketing strategy when consumers seek to satisfy both quality and status-related considerations? We develop an analytical model to study this issue, examining both pricing and product management decisions in markets for conspicuous ... Keywords: conspicuous consumption, durable goods, dynamic pricing, game theory, status

Raghunath Singh Rao, Richard Schaefer

2013-09-01T23:59:59.000Z

255

HTTR criticality calculations with SCALE6: Studies of various geometric and unit-cell options in modeling  

Science Conference Proceedings (OSTI)

The fuel element of the High Temperature Engineering Test Reactor (HTTR) presents a doubly heterogeneous geometry, where tiny TRISO fuel particles dispersed in a graphite matrix form the fuel region of a cylindrical fuel rod, and a number of fuel rods together with moderator or reflector then constitute the lattice design of the core. In this study, a series of full-core HTTR criticality calculations were performed with the SCALE6 code system using various geometric and unit-cell options in order to systematically investigate their effects on neutronic analysis. Two geometric descriptions (ARRAY or HOLE) in SCALE6 can be used to construct a complicated and repeated model. The result shows that eliminating the use of HOLE in the HTTR geometric model can save the computation time by a factor of 4. Four unit-cell treatments for resonance self-shielding corrections in SCALE6 were tested to create problem-specific multigroup cross sections for the HTTR core model. Based on the same ENDF/B-VII cross-section library, their results were evaluated by comparing with continuous-energy calculations. The comparison indicates that the INFHOMMEDIUM result overestimates the system multiplication factor (k{sub eff}) by 55 mk, whereas the LATTICECELL and MULTIREGION treatments predict the k{sub eff} values with similar biases of approximately 10 mk overestimation. The DOUBLEHET result shows a more satisfactory agreement, about 4.2 mk underestimation in the k{sub eff} value. In addition, using cell-weighted cross sections instead of an explicit modeling of TRISO particles in fuel region can further reduce the computation time by a factor of 5 without sacrificing accuracy. (authors)

Wang, J. Y.; Chiang, M. H.; Sheu, R. J.; Liu, Y. W. H. [Inst. of Nuclear Engineering and Science, National Tsing Hua Univ., Hsinchu 30013, Taiwan (China)

2012-07-01T23:59:59.000Z

256

Simulating the daily gasoline price-setting behaviour of gas stations in Cincinnati by agent-based modeling.  

E-Print Network (OSTI)

??In the retail gasoline market, gas stations as independent entities set gas prices according to a number of factors related to global and local economic… (more)

Zhou, Li

2009-01-01T23:59:59.000Z

257

Understanding Crude Oil Prices  

E-Print Network (OSTI)

2004. “OPEC’s Optimal Crude Oil Price,” Energy Policy 32(2),percent change in real oil price. Figure 3. Price of crude023 Understanding Crude Oil Prices James D. Hamilton June

Hamilton, James Douglas

2008-01-01T23:59:59.000Z

258

The welfare effects of raising household energy prices in Poland  

Science Conference Proceedings (OSTI)

We examine the welfare effects from increasing household energy prices in Poland. Subsidizing household energy prices, common in the transition economies, is shown to be highly regressive. The wealthy spend a larger portion of their income on energy and consume more energy in absolute terms. We therefore rule out the oft-used social welfare argument for delaying household energy price increases. Raising prices, while targeting relief to the poor through a social assistance program is the first-best response. However, if governments want to ease the adjustment, several options are open, including: in-kind transfers to the poor, vouchers, in-cash transfers, and lifeline pricing for electricity. Our simulations show that if raising prices to efficient levels is not politically feasible at present and social assistance targeting is sufficiently weak, it may be socially better to use lifeline pricing and a large price increase than an overall, but smaller, price increase.

Freund, C.L. [Columbia Univ., New York, NY (United States); Wallich, C.I. [World Bank, Washington, DC (United States)

1996-06-01T23:59:59.000Z

259

Prices for Natural Gas | Open Energy Information  

Open Energy Info (EERE)

Prices for Natural Gas Prices for Natural Gas Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Prices for Natural Gas Agency/Company /Organization: Google Sector: Energy Focus Area: Economic Development Resource Type: Software/modeling tools User Interface: Website Website: www.google.com/publicdata/explore?ds=m49d2j928087j_ Country: United States Web Application Link: www.google.com/publicdata/explore?ds=m49d2j928087j_ Cost: Free Northern America Prices for Natural Gas Screenshot References: Public Data Explorer[1] EIA[2] Logo: Prices for Natural Gas Prices for Natural Gas Dollars per Thousand Cubic Feet and Percent in U.S. Total Represented by the Price. Overview A graphing tool that displays prices for natural gas dollars per thousand cubic feet and percent in U.S. Total represented by the price, using data

260

Optimization Online - Static-arbitrage bounds on the prices of basket ...  

E-Print Network (OSTI)

Jul 19, 2006 ... Static-arbitrage bounds on the prices of basket options via linear programming. Javier Pena (jfp ***at*** andrew.cmu.edu) Juan Vera (jvera ...

Note: This page contains sample records for the topic "option pricing model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


261

Accounting for fuel price risk: Using forward natural gas prices instead of gas price forecasts to compare renewable to natural gas-fired generation  

E-Print Network (OSTI)

and Policy Options of California’s Reliance on Natural Gas. ”policy is often formulated with ratepayers in mind. 2) Second, long-term fixed-price natural gas

Bolinger, Mark; Wiser, Ryan; Golove, William

2003-01-01T23:59:59.000Z

262

Average Commercial Price  

U.S. Energy Information Administration (EIA) Indexed Site

Residential Price Average Commercial Price Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes...

263

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

Policy Office Electricity Modeling System POEMS U.S. Department of Energy NANGAS/IPM NANGAS North American

Wong-Parodi, Gabrielle; Dale, Larry; Lekov, Alex

2005-01-01T23:59:59.000Z

264

A Hybrid ARCH-M and BP Neural Network Model For GSCI Futures Price Forecasting  

Science Conference Proceedings (OSTI)

As a versatile investment tool in energy markets for speculators and hedgers, the Goldman Sachs Commodity Index (GSCI) futures are quite well known. Therefore, this paper proposes a hybrid model incorporating ARCH family models and ANN model to forecast ... Keywords: ANN, ARCH-M, Commodity Index, Forecasting, GSCI

Wen Bo; Wang Shouyang; K. K. Lai

2007-05-01T23:59:59.000Z

265

Advances in Volatility Modeling for Energy Markets: Methods for Reproducing Volatility Clustering, Fat Tails, Smiles, and Smirks in Energy Price Forecasts  

Science Conference Proceedings (OSTI)

This report describes research sponsored by the Electric Power Research Institute (EPRI) to develop a new model of energy price volatility. For many years, EPRI has worked with a flexible and tractable volatility model that successfully captures the term "structure of volatility," including the properties commonly referred to as "mean reversion" and "seasonality." However, that model does not capture random volatility, evidenced by volatility clustering, nor does it capture skewness and excess kurtosis i...

2011-12-30T23:59:59.000Z

266

Testing alternative transport pricing strategies: A CGE analysis for Belgium 1 Paper to be presented at the Conference on “Input-Output and General Equilibrium: Data, Modeling and Policy Analysis”,  

E-Print Network (OSTI)

The objective of the paper is to compare the effects of two alternative transport pricing rules: average cost and marginal social cost pricing. For both pricing scenarios, two alternative ways of using surpluses or financing deficits of the transport sector are used. The first is to change the marginal labour tax rate, the second way is to vary the level of social transfers. The effects of the scenarios are tested using a computable general equilibrium model for Belgium. The model is also used to analyse whether the changes in the transport accounts caused by a pricing reform are good welfare indicators. 1.

Inge Mayeres; Stef Proost

2004-01-01T23:59:59.000Z

267

Option Returns and the Cross-Sectional Predictability of Implied Volatility  

E-Print Network (OSTI)

- tive forecast of the change in implied volatility and short in straddles with a large negative forecast://www.krannert.purdue.edu/faculty/saretto/. #12;1 Introduction Volatility is central to the pricing of options as there is a one-to-one correspondence between the price of an option and the volatility of the underlying asset. In the context of Black

Kearns, Michael

268

Fundamentals Explain High Crude Oil Prices  

Gasoline and Diesel Fuel Update (EIA)

6 6 Notes: One can use a simple model to deal with price/fundamental relationships. This one predicts monthly average WTI price as a function of OECD total petroleum stock deviations from the normal levels. The graph shows the model as it begins predicting prices in 1992. It shows how well the model has predicted not only the direction, but the magnitude of prices over this 8+ year period. While the model is simple and not perfect, it does predict the overall trends and, in particular, the recent rise in prices. It also shows that prices may have over-shot the fundamental balance for a while -- at least partially due to speculative concerns over Mideast tensions, winter supply adequacy, and Iraq's export policies. Prices moved lower in December, and even undershot briefly the

269

Comparing Price Forecast Accuracy of Natural Gas Models and Futures Markets  

E-Print Network (OSTI)

Update on Petroleum, Natural Gas, Heating Oil and Gasoline.of the Market for Natural Gas Futures. Energy Journal 16 (Modeling Forum. 2003. Natural Gas, Fuel Diversity and North

Wong-Parodi, Gabrielle; Dale, Larry; Lekov, Alex

2005-01-01T23:59:59.000Z

270

Managing Energy Price Risk with Derivatives  

NLE Websites -- All DOE Office Websites (Extended Search)

Managing Energy Price Risk with Derivatives Managing Energy Price Risk with Derivatives Speaker(s): Douglas Hale Date: September 18, 2003 - 12:00pm Location: Bldg. 90 Seminar Host/Point of Contact: Joseph Eto Energy derivatives came into being with the deregulation of the petroleum and natural gas industries in the early 1980s. Although derivatives-forwards, futures and options-have been used in American agriculture since the mid-1800's to manage price risk, they were unnecessary in regulated energy industries. Deregulation revealed that oil, gas and electricity prices are exceptionally volatile. Companies were forced to cope with the uncertainty in energy prices; they latched onto derivatives as one tool for managing that risk. Enron's collapse brought energy derivatives to public attention. Following the derivative linked

271

Renewable Power Options for Electricity Generation on Kaua'i...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Renewable Power Options for Electricity Generation on Kaua'i: Economics and Performance Modeling Renewable Power Options for Electricity Generation on Kaua'i: Economics and...

272

Solar PV Manufacturing Cost Model Group: Installed Solar PV System Prices (Presentation)  

SciTech Connect

EERE's Solar Energy Technologies Program is charged with leading the Secretary's SunShot Initiative to reduce the cost of electricity from solar by 75% to be cost competitive with conventional energy sources without subsidy by the end of the decade. As part of this Initiative, the program has funded the National Renewable Energy Laboratory (NREL) to develop module manufacturing and solar PV system installation cost models to ensure that the program's cost reduction targets are carefully aligned with current and near term industry costs. The NREL cost analysis team has leveraged the laboratories' extensive experience in the areas of project finance and deployment, as well as industry partnerships, to develop cost models that mirror the project cost analysis tools used by project managers at leading U.S. installers. The cost models are constructed through a "bottoms-up" assessment of each major cost element, beginning with the system's bill of materials, labor requirements (type and hours) by component, site-specific charges, and soft costs. In addition to the relevant engineering, procurement, and construction costs, the models also consider all relevant costs to an installer, including labor burdens and overhead rates, supply chain costs, and overhead and materials inventory costs, and assume market-specific profits.

Goodrich, A. C.; Woodhouse, M.; James, T.

2011-02-01T23:59:59.000Z

273

Solar PV Manufacturing Cost Model Group: Installed Solar PV System Prices (Presentation)  

DOE Green Energy (OSTI)

EERE's Solar Energy Technologies Program is charged with leading the Secretary's SunShot Initiative to reduce the cost of electricity from solar by 75% to be cost competitive with conventional energy sources without subsidy by the end of the decade. As part of this Initiative, the program has funded the National Renewable Energy Laboratory (NREL) to develop module manufacturing and solar PV system installation cost models to ensure that the program's cost reduction targets are carefully aligned with current and near term industry costs. The NREL cost analysis team has leveraged the laboratories' extensive experience in the areas of project finance and deployment, as well as industry partnerships, to develop cost models that mirror the project cost analysis tools used by project managers at leading U.S. installers. The cost models are constructed through a "bottoms-up" assessment of each major cost element, beginning with the system's bill of materials, labor requirements (type and hours) by component, site-specific charges, and soft costs. In addition to the relevant engineering, procurement, and construction costs, the models also consider all relevant costs to an installer, including labor burdens and overhead rates, supply chain costs, and overhead and materials inventory costs, and assume market-specific profits.

Goodrich, A. C.; Woodhouse, M.; James, T.

2011-02-01T23:59:59.000Z

274

Econometric Modelling of World Oil Supplies: Terminal Price and the Time to Depletion  

E-Print Network (OSTI)

demand, it is dependent on the world real interest rate and the total life-time stock of oil resources, as well as on the marginal extraction and scarcity cost parameters. The theoretical predictions of this model are evaluated using data on the cost...

Mohaddes, Kamiar

2012-03-02T23:59:59.000Z

275

MEAN REVERSION AND MOMENTUM: ANOTHER LOOK AT THE PRICE-VOLUME CORRELATION IN THE REAL ESTATE MARKET  

E-Print Network (OSTI)

Based on behavioral finance and economics literature, we construct a theoretical framework in which consumers of newly constructed housing units perceive prices to follow a stochastic mean reversion pattern. Given this belief and the high carrying cost maintained by real estate developers, potential buyers opt to either exercise immediately or defer the purchase. We simulate the model within a real option framework by which we show that the optimal time to wait before exercising a purchase is positively related to the price level; hence, a negative (positive) correlation between transaction volume and price level (yield) emerges. Observing data on housing prices and new construction sales in Israel for the years 1998-2007, we apply an adaptive expectation regression model to test consumers ' belief in both mean reversion and momentum price patterns. The empirical evidence shows that while consumers ’ demand pattern is simultaneously consistent with the belief in both momentum and mean reversion processes, the effect of the latter generally dominates. Moreover, while the data does not allow for testing the volume and price-level correlation, it does provide support to the positive volume-price yield correlation.

Yuval Arbel; Danny Ben-shahar; Eyal Sulganik

2008-01-01T23:59:59.000Z

276

Price controls and international petroleum product prices  

SciTech Connect

The effects of Federal refined-product price controls upon the price of motor gasoline in the United States through 1977 are examined. A comparison of domestic and foreign gasoline prices is made, based on the prices of products actually moving in international trade. There is also an effort to ascribe US/foreign market price differentials to identifiable cost factors. Primary emphasis is on price comparisons at the wholesale level, although some retail comparisons are presented. The study also examines the extent to which product price controls are binding, and attempts to estimate what the price of motor gasoline would have been in the absence of controls. The time period under consideration is from 1969 through 1977, with primary focus on price relationships in 1970-1971 (just before US controls) and 1976-1977. The foreign-domestic comparisons are made with respect to four major US cities, namely, Boston, New York, New Orleans, and Los Angeles. 20 figures, 14 tables.

Deacon, R.T.; Mead, W.J.; Agarwal, V.B.

1980-02-01T23:59:59.000Z

277

Natural Gas Wellhead Price  

U.S. Energy Information Administration (EIA) Indexed Site

Pipeline and Distribution Use Price City Gate Price Residential Price Percentage of Total Residential Deliveries included in Prices Commercial Price Percentage of Total Commercial Deliveries included in Prices Industrial Price Percentage of Total Industrial Deliveries included in Prices Vehicle Fuel Price Electric Power Price Period: Monthly Annual Pipeline and Distribution Use Price City Gate Price Residential Price Percentage of Total Residential Deliveries included in Prices Commercial Price Percentage of Total Commercial Deliveries included in Prices Industrial Price Percentage of Total Industrial Deliveries included in Prices Vehicle Fuel Price Electric Power Price Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Data Series Area 2007 2008 2009 2010 2011 2012 View History U.S. 6.25 7.97 3.67 4.48 3.95 2.66 1922-2012 Alabama 7.44 9.65 4.32 4.46 1967-2010 Alaska 5.63 7.39 2.93 3.17 1967-2010 Arizona 5.98 7.09 3.19 4.11 1967-2010 Arkansas

278

PRICE GOUGING | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

PRICE GOUGING PRICE GOUGING PRICE GOUGING More Documents & Publications PRICE GOUGING Department of Energy Response to Hurricane Katrina Fact Sheet Department of Energy Response to...

279

Price forecasting for notebook computers  

E-Print Network (OSTI)

This paper proposes a four-step approach that uses statistical regression to forecast notebook computer prices. Notebook computer price is related to constituent features over a series of time periods, and the rates of change in the influence of individual features are estimated. A time series analysis is used to forecast and can be used, for example, to forecast (1) notebook computer price at introduction, and (2) rate of price erosion for a notebook's life cycle. Results indicate that this approach can forecast the price of a notebook computer up to four months in advance of its introduction with an average error of under 10% and the rate of price erosion to within 10% of the price for seven months after introduction-the length of the typical life cycle of a notebook. Since all data are publicly available, this approach can be used to assist managerial decision making in the notebook computer industry, for example, in determining when and how to upgrade a model and when to introduce a new model.

Rutherford, Derek Paul

1997-01-01T23:59:59.000Z

280

RWP 10-18The Roles of Price Points and Menu Costs in Price Rigidity  

E-Print Network (OSTI)

Macroeconomic models often generate nominal price rigidity via menu costs. This paper provides empirical evidence that treating menu costs as a structural explanation for sticky prices may be spurious. Using supermarket scanner data, I note two empirical facts: (1) price points, embodied in nine-ending prices, account for more than 60 percent of prices; (2) at the conclusion of sales, post-sale prices return to their pre-sale levels nearly 90 percent of the time. I construct a model that nests roles for menu costs and price points and estimate model variants via simulated method of moments. Excluding the two facts yields a statistically and economically significant role for menu costs in generating price rigidity. Incorporating the two facts yields an incentive to set nine-ending prices two orders of magnitude larger than the menu costs in this model. In this setting, the price point model can match the two stylized facts, but menu costs are effectively irrelevant as a source of price rigidity. The choice of a mechanism for price rigidity matters for aggregate dynamics.

Edward S. Knotek Ii; Edward S. Knotek Ii

2010-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "option pricing model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


281

The Roles of Price Points and Menu Costs in Price Rigidity *  

E-Print Network (OSTI)

Macroeconomic models often generate nominal price rigidity via menu costs. This paper provides empirical evidence that treating menu costs as a structural explanation for sticky prices may be spurious. Using supermarket scanner data, I note two empirical facts: (1) price points, embodied in nine-ending prices, account for more than 60 percent of prices; (2) at the conclusion of sales, post-sale prices return to their pre-sale levels nearly 90 percent of the time. I construct a model that nests roles for menu costs and price points and estimate model variants via simulated method of moments. Excluding the two facts yields a statistically and economically significant role for menu costs in generating price rigidity. Incorporating the two facts yields an incentive to set nine-ending prices two orders of magnitude larger than the menu costs in this model. In this setting, the price point model can match the two stylized facts, but menu costs are effectively irrelevant as a source of price rigidity. The choice of a mechanism for price rigidity matters for aggregate dynamics.

Edward S. Knotek Ii

2010-01-01T23:59:59.000Z

282

Diesel prices decrease  

U.S. Energy Information Administration (EIA) Indexed Site

Diesel prices decrease The U.S. average retail price for on-highway diesel fuel fell to 4.05 a gallon on Monday. That's down 4.1 cents from a week ago, based on the weekly price...

283

Diesel prices flat  

U.S. Energy Information Administration (EIA) Indexed Site

Diesel prices flat The U.S. average retail price for on-highway diesel fuel saw no movement from last week. Prices remained flat at 3.89 a gallon on Monday, based on the weekly...

284

Overshooting of agricultural prices  

E-Print Network (OSTI)

Rotenberg, Julio J. , "Sticky Prices in the United States,"Monetary Policy on United States Agriculture. A Fix-Price,Flex-Price Approach," Unpublished Ph.D. Disser- tation,

Stamoulis, Kostas G.; Rausser, Gordon C.

1987-01-01T23:59:59.000Z

285

Diesel prices decrease  

U.S. Energy Information Administration (EIA) Indexed Site

Diesel prices decrease The U.S. average retail price for on-highway diesel fuel fell to 3.88 a gallon on Monday. That's down a penny from a week ago, based on the weekly price...

286

Diesel prices decrease  

U.S. Energy Information Administration (EIA) Indexed Site

Diesel prices decrease The U.S. average retail price for on-highway diesel fuel fell to 3.85 a gallon on Monday. That's down 2 cents from a week ago, based on the weekly price...

287

Diesel prices decrease  

U.S. Energy Information Administration (EIA) Indexed Site

Diesel prices decrease The U.S. average retail price for on-highway diesel fuel fell to 3.82 a gallon on Monday. That's down 2.1 cents from a week ago, based on the weekly price...

288

Diesel prices flat nationally  

U.S. Energy Information Administration (EIA) Indexed Site

Diesel prices flat nationally The U.S. average retail price for on-highway diesel fuel remained the same from a week ago at 3.98 a gallon on Monday, based on the weekly price...

289

Diesel prices decrease  

U.S. Energy Information Administration (EIA) Indexed Site

Diesel prices decrease The U.S. average retail price for on-highway diesel fuel fell to 3.87 a gallon on Monday. That's down 1.6 cents from a week ago, based on the weekly price...

290

Diesel prices increase  

U.S. Energy Information Administration (EIA) Indexed Site

Diesel prices increase The U.S. average retail price for on-highway diesel fuel rose to 3.84 a gallon on Monday. That's up 2.2 cents from a week ago, based on the weekly price...

291

Georgia Natural Gas Prices  

U.S. Energy Information Administration (EIA)

Natural Gas Prices ... History; Imports Price: 6.79: 9.71: 3.73: 4.39: 4.20: 2.78: 1999-2012: Pipeline and Distribution Use Price : 1967-2005: ...

292

Michigan Natural Gas Prices  

U.S. Energy Information Administration (EIA)

Natural Gas Prices (Dollars per Thousand Cubic Feet, except where noted) ... History; Wellhead Price: NA: 5.63: 3.92: 3.79 : 1967-2010: Imports Price: ...

293

Credit Price Optimisation within Retail Banking  

E-Print Network (OSTI)

For this purpose a response model is suggested that overcomes non- concavity and ... to a more flexible demand-based pricing strategy, see Skugge (2011).

294

Price Behavior of Paper and Paperboard Industry .  

E-Print Network (OSTI)

??This paper presents a model of the probability of price response to the previous periods inventory absolute and relative level for U.S. paper and paperboard… (more)

Zhang, Feng

2004-01-01T23:59:59.000Z

295

Retail Price Changes Lag Spot Prices  

Gasoline and Diesel Fuel Update (EIA)

1 1 Notes: While EIA cannot claim to explain all of the factors that drive retail gasoline prices, we have had a fair amount of success in exploring the relationship between wholesale and retail prices. In particular, we have looked closely at the "pass-through" of changes in spot prices to the retail market. This graph shows a weighted national average of spot prices for regular gasoline -both conventional and reformulated (shown in red), and EIA's weekly survey price for retail regular (again both conventional and reformulated). As you can see, spot prices tend to be more volatile (and would be even more so on a daily basis), while these changes are smoother by the time they reach the retail pump. Furthermore, by looking at the peaks, you can see the retail prices seem to lag the spot price changes

296

Higher oil prices: Can OPEC raise prices by cutting production  

Science Conference Proceedings (OSTI)

OPEC's ability to raise prices is evaluated with a model that projects the supply and demand. As part of the model, a new methodology to forecast for the rate of production by non-OPEC nations is developed. A literature review of techniques for estimating oil supply and annual rates of production indicates a new methodology is needed. The new technique incorporates the geological, engineering, and economic aspects of the oil industry by synthesizing curve fitting and econometric techniques. It is used to analyze data for eight regions for non-OPEC oil production: the lower 48 states, Alaska, Canada, Mexico, non-OPEC South America, Western Europe, non-OPEC Africa, and non-OPEC Asia. OPEC's ability to raise prices is examined by tracking the percentage oil US oil demand supplied by imports, the portion of oil demand in Western Europe supplied by local production, the percentage of WOCA oil demand supplied by OPEC and Real OPEC revenues. Results of the model indicate that OPEC can raise oil prices in the early 1990s. OPEC can raise and sustain oil prices near $25 (1982 dollars). Higher oil prices ($35) are not sustainable before 2000 because reduced demand and increased non-OPEC production shrink OPEC revenues below acceptable levels. After 2000, $35 prices are sustainable.

Kaufmann, R.K.

1988-01-01T23:59:59.000Z

297

Customer Strategies for Responding to Day-Ahead Market HourlyElectricity Pricing  

Science Conference Proceedings (OSTI)

Real-time pricing (RTP) has been advocated as an economically efficient means to send price signals to customers to promote demand response (DR) (Borenstein 2002, Borenstein 2005, Ruff 2002). However, limited information exists that can be used to judge how effectively RTP actually induces DR, particularly in the context of restructured electricity markets. This report describes the second phase of a study of how large, non-residential customers' adapted to default-service day-ahead hourly pricing. The customers are located in upstate New York and served under Niagara Mohawk, A National Grid Company (NMPC)'s SC-3A rate class. The SC-3A tariff is a type of RTP that provides firm, day-ahead notice of hourly varying prices indexed to New York Independent System Operator (NYISO) day-ahead market prices. The study was funded by the California Energy Commission (CEC)'s PIER program through the Demand Response Research Center (DRRC). NMPC's is the first and longest-running default-service RTP tariff implemented in the context of retail competition. The mix of NMPC's large customers exposed to day-ahead hourly prices is roughly 30% industrial, 25% commercial and 45% institutional. They have faced periods of high prices during the study period (2000-2004), thereby providing an opportunity to assess their response to volatile hourly prices. The nature of the SC-3A default service attracted competitive retailers offering a wide array of pricing and hedging options, and customers could also participate in demand response programs implemented by NYISO. The first phase of this study examined SC-3A customers' satisfaction, hedging choices and price response through in-depth customer market research and a Constant Elasticity of Substitution (CES) demand model (Goldman et al. 2004). This second phase was undertaken to answer questions that remained unresolved and to quantify price response to a higher level of granularity. We accomplished these objectives with a second customer survey and interview effort, which resulted in a higher, 76% response rate, and the adoption of the more flexible Generalized Leontief (GL) demand model, which allows us to analyze customer response under a range of conditions (e.g. at different nominal prices) and to determine the distribution of individual customers' response.

Goldman, Chuck; Hopper, Nicole; Bharvirkar, Ranjit; Neenan,Bernie; Boisvert, Dick; Cappers, Peter; Pratt, Donna; Butkins, Kim

2005-08-25T23:59:59.000Z

298

Residential Heating Oil Prices  

U.S. Energy Information Administration (EIA)

We normally collect and publish this data twice a month, but given the low stocks and high prices, we started tracking the prices weekly.

299

Natural Gas Wellhead Price  

U.S. Energy Information Administration (EIA) Indexed Site

included in Prices Electric Power Price Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes...

300

Primer on Gasoline Prices  

Reports and Publications (EIA)

This brochure answers, in laymen's terms, questions such as "What are the components of the retail price of gasoline? Why do gasoline prices fluctuate?

Information Center

2009-07-15T23:59:59.000Z

Note: This page contains sample records for the topic "option pricing model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

Natural Gas Wellhead Prices  

U.S. Energy Information Administration (EIA)

Slide 19 of 27. Price: Wellhead. Natural gas wellhead prices are projected to move up 5 percent this winter, averaging about $2.28 per Mcf during this ...

302

Crude Oil Price Forecast  

U.S. Energy Information Administration (EIA)

We believe crude oil prices will strengthen somewhat, but prices will rise much more slowly than they fell, and they are expected to remain lower in ...

303

Price Liquefied Sabine Pass, LA Natural Gas Exports Price ...  

U.S. Energy Information Administration (EIA)

Price Liquefied Sabine Pass, LA Natural Gas Exports Price to Brazil (Dollars per Thousand Cubic Feet)

304

What Is Price Volatility  

Gasoline and Diesel Fuel Update (EIA)

What Is Price Volatility? What Is Price Volatility? The term "price volatility" is used to describe price fluctuations of a commodity. Volatility is measured by the day-to-day percentage difference in the price of the commodity. The degree of variation, not the level of prices, defines a volatile market. Since price is a function of supply and demand, it follows that volatility is a result of the underlying supply and demand characteristics of the market. Therefore, high levels of volatility reflect extraordinary characteristics of supply and/or demand. Prices of basic energy (natural gas, electricity, heating oil) are generally more volatile than prices of other commodities. One reason that energy prices are so volatile is that many consumers are extremely limited in their ability to substitute other fuels when the price, of natural gas

305

Apples with apples: accounting for fuel price risk in comparisons of gas-fired and renewable generation  

E-Print Network (OSTI)

operating costs, long-term fixed-price renewable energyRenewable Energy Gas Options, Gas Storage Option Premium or Storage Costrenewable power is more cost- competitive than previously believed’, Renewable Energy

Bolinger, Mark; Wiser, Ryan

2003-01-01T23:59:59.000Z

306

Natural Gas Price Uncertainty: Establishing Price Floors  

Science Conference Proceedings (OSTI)

This report presents the results of comprehensive calculations of ceiling and floor prices for natural gas. Ceiling prices are set by the price levels at which it is more economic to switch from natural gas to residual fuel oil in steam units and to distillate in combined cycle units. Switching to distillate is very rare, whereas switching to fuel oil is quite common, varying between winter and summer and increasing when natural gas prices are high or oil prices low. Monthly fuel use was examined for 89 ...

2007-01-11T23:59:59.000Z

307

Appropriate Response to Rising Fuel Prices Citizens Should Demand, “Raise My Prices Now!”  

E-Print Network (OSTI)

This paper evaluates policy options for responding to rising fuel prices. There is popular support for policies that minimize fuel prices through subsidies and tax reductions, but such policies harm consumers and the economy overall because they increase total fuel consumption and vehicle travel, and therefore associated costs such as traffic and parking congestion, infrastructure costs, traffic crashes, trade imbalances and pollution emissions. Fuel price reductions are an inefficient way to help low-income households; other strategies do more to increase affordability and provide other benefits. Because many transport decisions are durable, low fuel price policies are particularly harmful over the long term. This report identifies responses that maximize total benefits, including mobility management strategies that increase transport system efficiency, incentives to choose fuel efficient vehicles, and revenue-neutral tax shifts. With these policies fuel prices can significantly increase without harming consumers or the economy, while helping to achieve other planning objectives.

Todd Litman

2010-01-01T23:59:59.000Z

308

Do Producer Prices Lead Consumer Prices?  

E-Print Network (OSTI)

increased rapidly. Excluding food and energy, prices of crude materials and intermediate goods rose at annual rates of 7.2 and 16.7 percent, respectively. At the same time, however, prices of consumer goods and services excluding food and energy increased a more modest 2.9 percent. Many analysts are concerned that recent increases in the prices of crude and intermediate goods may be passed through to consumers, resulting in a higher rate of inflation in consumer prices later this year and perhaps in 1996. This article examines whether price increases at the early stages of production should be expected to move through the production chain, leading to increases in consumer prices. In the first section, a review of basic economic theory suggests there should be a pass-through effect—that is, producer prices should lead and thereby help predict consumer prices. A more sophisticated analysis, though, suggests the pass-through effect may be weak. In the second section, an examination of the empirical evidence indicates that producer prices are not always good predictors of consumer prices. The article Todd E. Clark is an economist at the Federal Reserve Bank of Kansas City. Mangal Goswami, a research associate at the bank, helped prepare the article. concludes that the recent increases in some producer prices do not necessarily signal higher inflation.

E. Clark

1994-01-01T23:59:59.000Z

309

OIL PRICES AND LONG-RUN RISK  

E-Print Network (OSTI)

I show that relative levels of aggregate consumption and personal oil consumption provide an excellent proxy for oil prices, and that high oil prices predict low future aggregate consumption growth. Motivated by these facts, I add an oil consumption good to the long-run risk model of Bansal and Yaron [2004] to study the asset pricing implications of observed changes in the dynamic interaction of consumption and oil prices. Empirically I observe that, compared to the first half of my 1987- 2010 sample, oil consumption growth in the last 10 years is unresponsive to levels of oil prices, creating an decrease in the mean-reversion of oil prices, and an increase in the persistence of oil price shocks. The model implies that the change in the dynamics of oil consumption generates increased systematic risk from oil price shocks due to their increased persistence. However, persistent oil prices also act as a counterweight for shocks to expected consumption growth, with high expected growth creating high expectations of future oil prices which in turn slow down growth. The combined effect is to reduce overall consumption risk and lower the equity premium. The model also predicts that these changes affect the riskiness of of oil futures contracts, and combine to create a hump shaped

Robert Ready; Robert Clayton Ready; Robert Clayton Ready; Amir Yaron

2011-01-01T23:59:59.000Z

310

Price dispersion in the small and in the large: Evidence from an internet price comparison site  

E-Print Network (OSTI)

This paper examines 4 million price observations over an eight month time period for 1000 of the best-selling consumer electronics products found on the price comparison site Shopper.com. We find that observed levels of price dispersion vary systematically with the number of firms listing price quotes for a given product. For example, for products where only two firms list prices, the gap between their prices averages 22 percent. In contrast, for products where 17 firms list prices (the average in our sample), the gap is only about 3.5 percent. Further, we find little support for the notion that prices on the Internet are converging to the “law of one price. ” The average range in prices was about 40 percent, and the average gap between the two lowest prices listed for a given product remained stable at around 5 percent. We show that the combination of stable and ubiquitous price dispersion, coupled with dispersion that differs in the small and in the large, is consistent with a number of theoretical models of equilibrium price dispersion.

John Morgan; Patrick Scholten

2001-01-01T23:59:59.000Z

311

A Time Series Analysis of Food Price and Its Input Prices  

E-Print Network (OSTI)

Rapid increases in consumer food price beginning in 2007 generated interest in identifying the main factors influencing these increases. In subsequent years, food prices have fluctuated, but generally have continued their ascent. The effects of crude oil, gasoline, corn, and ethanol prices, as well as, the relative foreign exchange rate of the U.S. dollar and producer price indexes for food manufacturing and fuel products on domestic food prices are examined. Because the data series are non-stationary and cointegrated, a vector error correction model is estimated. Weak exogeneity and exclusion tests in the cointegration space are performed. Directed acyclical graphs are used to specify contemporaneous causal relationships. Dynamic interactions among the series are given by impulse response functions and forecast error variance decompositions. Weak exogeneity tests indicate all eight series work to bring the system back into equilibrium following a shock to the system. Further, exclusion tests suggest crude oil, gasoline, food CPI, ethanol, and food PPI variables are not in the long-run relationships. Dynamic analyses suggest the following relationships. Ethanol price is not a major factor in domestic food prices, suggesting that food prices are largely unaffected by the recent increased use of corn-based ethanol for fuel. Crude oil prices, corn prices, and the relative foreign exchange rate of the U.S. dollar, however, do influence domestic food prices with corn price contributing the most to food price variability. Innovation accounting inferences are robust to potential different contemporaneous causal specifications.

Routh, Kari 1988-

2012-12-01T23:59:59.000Z

312

The Cross-Section of Output and Inflation in a Dynamic Stochastic General Equilibrium Model with Sticky Prices  

E-Print Network (OSTI)

?cant Di¤erences to Economic Equilibria, American Economic Review, Vol. 75, pp 708-721. [2] Ball, L. Mankiw, N. G. (1994) Asymmetric Price Adjustment and Economic Fluc- tuations", The Economic Journal, Vol. 104, No. 423, March, pages 247-261. [3] Ball, L...

Döpke, J; Funke, M.; Holly, Sean; Weber, S

313

Demand and Price Outlook for Phase 2 Reformulated Gasoline, 2000  

Gasoline and Diesel Fuel Update (EIA)

Demand and Price Outlook for Demand and Price Outlook for Phase 2 Reformulated Gasoline, 2000 Tancred Lidderdale and Aileen Bohn (1) Contents * Summary * Introduction * Reformulated Gasoline Demand * Oxygenate Demand * Logistics o Interstate Movements and Storage o Local Distribution o Phase 2 RFG Logistics o Possible Opt-Ins to the RFG Program o State Low Sulfur, Low RVP Gasoline Initiatives o NAAQS o Tier 2 Gasoline * RFG Production Options o Toxic Air Pollutants (TAP) Reduction o Nitrogen Oxides (NOx) Reduction o Volatile Organic Compounds (VOC) Reduction o Summary of RFG Production Options * Costs of Reformulated Gasoline o Phase 1 RFG Price Premium o California Clean Gasoline Price Premium o Phase 2 RFG Price Premium o Reduced Fuel Economy

314

Price caps for standard offer service: A hidden stranded cost  

Science Conference Proceedings (OSTI)

Some utility commissions or legislatures, concerned about mis-estimating the market line when calculating stranded costs, are choosing to require a price-capped standard offer service (SOS) to be offered by utilities in the competitive marketplace. This grants to customers the flexibility to switch from a fixed-price alternative with the utility to (or even to and from) a non-utility power supplier. Given the enormous uncertainty in future power market prices, this flexibility, which is being bestowed free-of-charge to customers, may prove to be of considerable value. Valuation of this SOS flexibility using call option techniques shows that this can be a non-trivial fraction of total stranded costs. The costs of price-capped SOS can be ameliorated through the structure of the price cap. This article describes the option-based techniques for valuing SOS and some approaches to limiting its cost to utilities.

Graves, F.; Liu, P. [Brattle Group, Cambridge, MA (United States)]|[Brattle Group, Washington, DC (United States)]|[Brattle Group, London (United Kingdom)

1998-12-01T23:59:59.000Z

315

Renewable Energy Requirements for Future Building Codes: Options for Compliance  

Science Conference Proceedings (OSTI)

As the model energy codes are improved to reach efficiency levels 50 percent greater than current codes, use of on-site renewable energy generation is likely to become a code requirement. This requirement will be needed because traditional mechanisms for code improvement, including envelope, mechanical and lighting, have been pressed to the end of reasonable limits. Research has been conducted to determine the mechanism for implementing this requirement (Kaufman 2011). Kaufmann et al. determined that the most appropriate way to structure an on-site renewable requirement for commercial buildings is to define the requirement in terms of an installed power density per unit of roof area. This provides a mechanism that is suitable for the installation of photovoltaic (PV) systems on future buildings to offset electricity and reduce the total building energy load. Kaufmann et al. suggested that an appropriate maximum for the requirement in the commercial sector would be 4 W/ft{sup 2} of roof area or 0.5 W/ft{sup 2} of conditioned floor area. As with all code requirements, there must be an alternative compliance path for buildings that may not reasonably meet the renewables requirement. This might include conditions like shading (which makes rooftop PV arrays less effective), unusual architecture, undesirable roof pitch, unsuitable building orientation, or other issues. In the short term, alternative compliance paths including high performance mechanical equipment, dramatic envelope changes, or controls changes may be feasible. These options may be less expensive than many renewable systems, which will require careful balance of energy measures when setting the code requirement levels. As the stringency of the code continues to increase however, efficiency trade-offs will be maximized, requiring alternative compliance options to be focused solely on renewable electricity trade-offs or equivalent programs. One alternate compliance path includes purchase of Renewable Energy Credits (RECs). Each REC represents a specified amount of renewable electricity production and provides an offset of environmental externalities associated with non-renewable electricity production. The purpose of this paper is to explore the possible issues with RECs and comparable alternative compliance options. Existing codes have been examined to determine energy equivalence between the energy generation requirement and the RECs alternative over the life of the building. The price equivalence of the requirement and the alternative are determined to consider the economic drivers for a market decision. This research includes case studies that review how the few existing codes have incorporated RECs and some of the issues inherent with REC markets. Section 1 of the report reviews compliance options including RECs, green energy purchase programs, shared solar agreements and leases, and other options. Section 2 provides detailed case studies on codes that include RECs and community based alternative compliance methods. The methods the existing code requirements structure alternative compliance options like RECs are the focus of the case studies. Section 3 explores the possible structure of the renewable energy generation requirement in the context of energy and price equivalence. The price of RECs have shown high variation by market and over time which makes it critical to for code language to be updated frequently for a renewable energy generation requirement or the requirement will not remain price-equivalent over time. Section 4 of the report provides a maximum case estimate for impact to the PV market and the REC market based on the Kaufmann et al. proposed requirement levels. If all new buildings in the commercial sector complied with the requirement to install rooftop PV arrays, nearly 4,700 MW of solar would be installed in 2012, a major increase from EIA estimates of 640 MW of solar generation capacity installed in 2009. The residential sector could contribute roughly an additional 2,300 MW based on the same code requirement levels of 4 W/ft{sup 2} of r

Dillon, Heather E.; Antonopoulos, Chrissi A.; Solana, Amy E.; Russo, Bryan J.

2011-09-30T23:59:59.000Z

316

Reset Price Inflation and the Impact of Monetary Policy Shocks  

E-Print Network (OSTI)

A standard state-dependent pricing model generates little monetary non-neutrality. Two ways of generating more meaningful real effects are time-dependent pricing and strategic complementarities. These mechanisms have telltale implications for the persistence and volatility of “reset price inflation. ” Reset price inflation is the rate of change of all desired prices (including goods that have not changed price in the current period). Using the micro data underpinning the CPI, we construct an empirical measure of reset price inflation. We find that time-dependent models imply unrealistically high persistence and stability of reset price inflation. This discrepancy is only exacerbated by adding strategic complementarities, even under state-dependent pricing. A state-dependent model with no strategic complementarities aligns most closely with the data.

Mark Bils; Peter J. Klenow; Benjamin A. Malin

2008-01-01T23:59:59.000Z

317

MTBE Prices Responded to Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

6 6 Notes: On top of the usual factors impacting gasoline prices, natural gas has had some influence recently. MTBE is an oxygenate used in most of the RFG consumed in the U.S. Generally, it follows gasoline prices and its own supply/demand balance factors. But this winter, we saw it respond strongly to natural gas prices. MTBE is made from methanol and isobutylene, which in turn come from methane and butane. Both methane and butane come from natural gas streams. Until this year, the price of natural gas has been so low that it had little effect. But the surge that occurred in December and January pulled MTBE up . Keep in mind that about 11% MTBE is used in a gallon of RFG, so a 30 cent increase in MTBE is only about a 3 cent increase in the price of RFG. While we look ahead at this summer, natural gas prices should be

318

Simulating Price Responsive Distributed Resources  

SciTech Connect

Distributed energy resources (DER) include distributed generation, storage, and responsive demand. The integration of DER into the power system control framework is part of the evolutinary advances that allow these resources to actively particpate in the energy balance equation. Price can provide a powerful signal for independent decision-making in distributed control strategies. To study the impact of price responsive DER on the electric power system requires generation and load models that can capture the dynamic coupling between the energy market and the physical operation of the power system in appropriate time frames. This paper presents modeling approaches for simulating electricity market price responsive DER, and introduces a statistical mechanics approach to modeling the aggregated response of a transformed electric system of pervasive, transacting DER.

Lu, Ning; Chassin, David P.; Widergren, Steven E.

2004-10-15T23:59:59.000Z

319

OPTIONS for ENERGY EFFICIENCY  

E-Print Network (OSTI)

OPTIONS for ENERGY EFFICIENCY in EXISTING BUILDINGS December 2005 CEC-400-2005-039-CMF;OPTIONS FOR ENERGY EFFICIENCY in EXISTING BUILDINGS COMMISSION REPORT TABLE OF CONTENTS EXECUTIVE SUMMARY ............................................................................iii California's Successful Energy Efficiency Programs

320

Three Essays on Retail Price Dynamics  

E-Print Network (OSTI)

of Reference Prices . . . . . . . . . . . . . . . . . . . .2.4.5 Reference Prices andChain-Level Prices . . . . . . . . . . . . . .

Elberg, Andres

2010-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "option pricing model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


321

Appendix A: Fuel Price Forecast Introduction..................................................................................................................................... 1  

E-Print Network (OSTI)

Appendix A: Fuel Price Forecast Introduction................................................................................................................................. 3 Price Forecasts............................................................................................................................... 12 Oil Price Forecast Range

322

An overview of alternative fossil fuel price and carbon regulation scenarios  

SciTech Connect

The benefits of the Department of Energy's research and development (R&D) efforts have historically been estimated under business-as-usual market and policy conditions. In recognition of the insurance value of R&D, however, the Office of Energy Efficiency and Renewable Energy (EERE) and the Office of Fossil Energy (FE) have been exploring options for evaluating the benefits of their R&D programs under an array of alternative futures. More specifically, an FE-EERE Scenarios Working Group (the Working Group) has proposed to EERE and FE staff the application of an initial set of three scenarios for use in the Working Group's upcoming analyses: (1) a Reference Case Scenario, (2) a High Fuel Price Scenario, which includes heightened natural gas and oil prices, and (3) a Carbon Cap-and-Trade Scenario. The immediate goal is to use these scenarios to conduct a pilot analysis of the benefits of EERE and FE R&D efforts. In this report, the two alternative scenarios being considered by EERE and FE staff--carbon cap-and-trade and high fuel prices--are compared to other scenarios used by energy analysts and utility planners. The report also briefly evaluates the past accuracy of fossil fuel price forecasts. We find that the natural gas prices through 2025 proposed in the FE-EERE Scenarios Working Group's High Fuel Price Scenario appear to be reasonable based on current natural gas prices and other externally generated gas price forecasts and scenarios. If anything, an even more extreme gas price scenario might be considered. The price escalation from 2025 to 2050 within the proposed High Fuel Price Scenario is harder to evaluate, primarily because few existing forecasts or scenarios extend beyond 2025, but, at first blush, it also appears reasonable. Similarly, we find that the oil prices originally proposed by the Working Group in the High Fuel Price Scenario appear to be reasonable, if not conservative, based on: (1) the current forward market for oil, (2) current oil prices, (3) externally generated oil price forecasts, and (4) the historical difficulty in accurately forecasting oil prices. Overall, a spread between the FE-EERE High Oil Price and Reference scenarios of well over $8/bbl is supported by the literature. We conclude that a wide range of carbon regulation scenarios are possible, especially within the time frame considered by EERE and FE (through 2050). The Working Group's Carbon Cap-and-Trade Scenario is found to be less aggressive than many Kyoto-style targets that have been analyzed, and similar in magnitude to the proposed Climate Stewardship Act. The proposed scenario is more aggressive than some other scenarios found in the literature, however, and ignores carbon banking and offsets and does not allow nuclear power to expand. We are therefore somewhat concerned that the stringency of the proposed carbon regulation scenario in the 2010 to 2025 period will lead to a particularly high estimated cost of carbon reduction. As described in more detail later, we encourage some flexibility in the Working Group's ultimate implementation of the Carbon Cap-and-Trade Scenario. We conclude by identifying additional scenarios that might be considered in future analyses, describing a concern with the proposed specification of the High Fuel Price Scenario, and highlighting the possible difficulty of implementing extreme scenarios with current energy modeling tools.

Wiser, Ryan; Bolinger, Mark

2004-10-01T23:59:59.000Z

323

MTBE Prices Responded to Natural Gas Prices  

U.S. Energy Information Administration (EIA)

On top of the usual factors impacting gasoline prices, natural gas has had some influence recently. ... Both methane and butane come from natural gas streams.

324

Maryland Gasoline Price Data  

NLE Websites -- All DOE Office Websites (Extended Search)

Maryland Maryland Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Baltimore BaltimoreGasPrices.com Automotive.com MapQuest.com Bethesda BethesdaGasPrices.com Automotive.com MapQuest.com Bowie BowieGasPrices.com Automotive.com MapQuest.com Frederick FrederickGasPrices.com Automotive.com MapQuest.com Gaithersburg GaithersburgGasPrices.com Automotive.com MapQuest.com Other Maryland Cities MarylandGasPrices.com (search by city or ZIP code) - GasBuddy.com Maryland Gas Prices (selected cities) - GasBuddy.com Maryland Gas Prices (organized by county) - Automotive.com Gas Prices of the United States: Maryland Cities - MapQuest

325

Massachusetts Gasoline Price Data  

NLE Websites -- All DOE Office Websites (Extended Search)

Massachusetts Massachusetts Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Boston BostonGasPrices.com Automotive.com MapQuest.com Brockton BrocktonGasPrices.com Automotive.com MapQuest.com Cambridge CambridgeGasPrices.com Automotive.com MapQuest.com Fall River FallRiverGasPrices.com Automotive.com MapQuest.com Haverhill HaverhillGasPrices.com Automotive.com MapQuest.com Lawrence LawrenceGasPrices.com Automotive.com MapQuest.com Lowell LowellGasPrices.com Automotive.com MapQuest.com New Bedford NewBedfordGasPrices.com Automotive.com Mapquest.com Taunton TauntonGasPrices.com Automotive.com MapQuest.com

326

Ohio Gasoline Price Data  

NLE Websites -- All DOE Office Websites (Extended Search)

Ohio Ohio Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Akron AkronGasPrices.com Automotive.com Mapquest.com Cincinnati CincinnatiGasPrices.com Automotive.com Mapquest.com Cleveland ClevelandGasPrices.com Automotive.com Mapquest.com Columbus ColumbusGasPrices.com Automotive.com Mapquest.com Dayton DaytonGasPrices.com Automotive.com Mapquest.com Toledo ToledoGasPrices.com Automotive.com Mapquest.com Other Ohio Cities OhioGasPrices.com (search by city or ZIP code) - GasBuddy.com Ohio Gas Prices (selected cities) - GasBuddy.com Ohio Gas Prices (organized by county) - Automotive.com

327

Regional Retail Gasoline Prices  

Gasoline and Diesel Fuel Update (EIA)

7 7 Notes: Retail gasoline prices, like those for distillate fuels, have hit record prices nationally and in several regions this year. The national average regular gasoline price peaked at $1.68 per gallon in mid-June, but quickly declined, and now stands at $1.45, 17 cents higher than a year ago. Two regions, in particular, experienced sharp gasoline price runups this year. California, which often has some of the highest prices in the nation, saw prices peak near $1.85 in mid-September, while the Midwest had average prices over $1.87 in mid-June. Local prices at some stations in both areas hit levels well over $2.00 per gallon. The reasons for the regional price runups differed significantly. In the Midwest, the introduction of Phase 2 RFG was hampered by low stocks,

328

Virginia Gasoline Price Data  

NLE Websites -- All DOE Office Websites (Extended Search)

Virginia Virginia Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Alexandria AlexandriaGasPrices.com Automotive.com Mapquest.com Arlington ArlingtonGasPrices.com Automotive.com Mapquest.com Chesapeake ChesapeakeGasPrices.com Automotive.com Mapquest.com Hampton HamptonGasPrices.com Automotive.com Mapquest.com Newport News NewportNewsGasPrices.com Automotive.com Mapquest.com Norfolk NorfolkGasPrices.com Automotive.com Mapquest.com Portsmouth PortsmouthGasPrices.com Automotive.com Mapquest.com Richmond RichmondGasPrices.com Automotive.com Mapquest.com Virginia Beach VirginiaBeachGasPrices.com Automotive.com Mapquest.com

329

Illinois Gasoline Price Data  

NLE Websites -- All DOE Office Websites (Extended Search)

Illinois Illinois Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Arlington Heights ArlingtonHeightsGasPrices.com Automotive.com MapQuest.com Aurora AuroraGasPrices.com Automotive.com MapQuest.com Bloomington BloomingtonGasPrices.com Automotive.com MapQuest.com Champaign ChampaignGasPrices.com Automotive.com MapQuest.com Chicago ChicagoGasPrices.com Automotive.com MapQuest.com Decatur DecaturGasPrices.com Automotive.com Mapquest.com Elgin ElginGasPrices.com Automotive.com MapQuest.com Joliet JolietGasPrices.com Automotive.com MapQuest.com Naperville NapervilleGasPrices.com Automotive.com MapQuest.com

330

Oklahoma Gasoline Price Data  

NLE Websites -- All DOE Office Websites (Extended Search)

Oklahoma Oklahoma Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Lawton LawtonGasPrices.com Automotive.com Mapquest.com Norman NormanGasPrices.com Automotive.com Mapquest.com Oklahoma City OklahomaCityGasPrices.com Automotive.com Mapquest.com Tulsa TulsaGasPrices.com Automotive.com Mapquest.com Other Oklahoma Cities OklahomaGasPrices.com (search by city or ZIP code) - GasBuddy.com Oklahoma Gas Prices (selected cities) - GasBuddy.com Oklahoma Gas Prices (organized by county) - Automotive.com Gas Prices of the United States: Oklahoma Cities - MapQuest Oklahoma Gas Prices (organized by county, search by ZIP code) -

331

Tennessee Gasoline Price Data  

NLE Websites -- All DOE Office Websites (Extended Search)

Tennessee Tennessee Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Chattanooga ChattanoogaGasPrices.com Automotive.com Mapquest.com Clarksville ClarksvilleGasPrices.com Automotive.com Mapquest.com Knoxville KnoxvilleGasPrices.com Automotive.com Mapquest.com Memphis MemphisGasPrices.com Automotive.com Mapquest.com Murfreesboro MurfreesboroGasPrices.com Automotive.com Mapquest.com Nashville NashvilleGasPrices.com Automotive.com Mapquest.com Other Tennessee Cities TennesseeGasPrices.com (search by city or ZIP code) - GasBuddy.com Tennessee Gas Prices (selected cities) - GasBuddy.com Tennessee Gas Prices (organized by county) - Automotive.com

332

Wisconsin Gasoline Price Data  

NLE Websites -- All DOE Office Websites (Extended Search)

Wisconsin Wisconsin Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Appleton AppletonGasPrices.com Automotive.com Mapquest.com Eau Claire EauClaireGasPrices.com Automotive.com Mapquest.com Green Bay GreenBayGasPrices.com Automotive.com Mapquest.com Kenosha KenoshaGasPrices.com Automotive.com Mapquest.com Madison MadisonGasPrices.com Automotive.com Mapquest.com Milwaukee MilwaukeeGasPrices.com Automotive.com Mapquest.com Other Wisconsin Cities WisconsinGasPrices.com (search by city or ZIP code) - GasBuddy.com Wisconsin Gas Prices (selected cities) - GasBuddy.com Wisconsin Gas Prices (organized by county) - Automotive.com

333

PRICE & AVAILABILITY UPDATES  

E-Print Network (OSTI)

4.3 Price & Availability Updates File when titles transferred to new supplier..................... 5 4.4 Format of the ‘Day ’ element in Availability Dates......................................................... 5 5 Example of Price & Availability Updates transmission....................................................... 5 6 Price & Availability Updates file header............................................................................. 7 Example of a complete Price & Availability Updates file header....................................... 12 7 Price & Availability Updates “message level ” content...................................................... 13 8 Price & Availability Updates “line level ” content............................................................... 14 Example showing Order "line level " segments NOI to DNC.............................................. 21 9 Price & Availability Updates message trailer.................................................................... 21 10 Price & Availability Updates file trailer............................................................................ 22 NOTE: The TRADACOMS Price & Availability Updates message is not recommended for new implementations. The recommended formats for the communication of book product information are the ONIX for Books Product Information message and Supply Update message.

unknown authors

2010-01-01T23:59:59.000Z

334

Natural Gas Purchasing Options  

E-Print Network (OSTI)

As a result of economic and regulatory changes, the natural gas marketplace now offers multiple options for purchasers. The purpose of this panel is to discuss short-term purchasing options and how to take advantage of these options both to lower energy costs and to secure supply.

Watkins, G.

1988-09-01T23:59:59.000Z

335

Higher Prices from Entry: Pricing of Brand-Name Drugs  

E-Print Network (OSTI)

with Distance Figure 6 Cumulative Unexpected Price Effectsand Paul J. Seguin, "Price Volatility, Trading Volume andGoods in Pharmaceutical Price In- dexes," American Economic

Perloff, Jeffrey M.; Suslow, Valerie Y.; Seguin, Paul J.

1995-01-01T23:59:59.000Z

336

Higher Prices from Entry: Pricing of Brand-Name Drugs  

E-Print Network (OSTI)

4 Bertrand and Cartel Prices Vary with z 7T, CS L Figure 5Distance Cumulative Abnormal Price Changes (%) Dissimilarof New Drug Figure 6 Cumulative Unexpected Price Effects

Perloff, Jeffrey M.; Suslow, Valerie Y.; Seguin, Paul J.

1995-01-01T23:59:59.000Z

337

Practice Prize Report---An Assortmentwide Decision-Support System for Dynamic Pricing and Promotion Planning in DIY Retailing  

Science Conference Proceedings (OSTI)

The main objective of this report is to describe a decision-support system for dynamic retail pricing and promotion planning. Our weekly demand model incorporates price, reference price effects, seasonality, article availability information, features, ... Keywords: demand interdependency, dynamic pricing, pricing research, reference price, retail strategy, revenue management

Martin Natter; Thomas Reutterer; Andreas Mild; Alfred Taudes

2007-07-01T23:59:59.000Z

338

Appliance Efficiency Standards and Price Discrimination  

NLE Websites -- All DOE Office Websites (Extended Search)

Appliance Efficiency Standards and Price Discrimination Appliance Efficiency Standards and Price Discrimination Title Appliance Efficiency Standards and Price Discrimination Publication Type Report LBNL Report Number LBNL-6283E Year of Publication 2013 Authors Spurlock, Anna C. Date Published 05/2013 Keywords EES-EG Abstract I explore the effects of two simultaneous changes in minimum energy efficiency and ENERGY STAR standards for clothes washers. Adapting the Mussa and Rosen (1978) and Ronnen (1991) second-degree price discrimination model, I demonstrate that clothes washer prices and menus adjusted to the new standards in patterns consistent with a market in which firms had been price discriminating. In particular, I show evidence of discontinuous price drops at the time the standards were imposed, driven largely by mid-low efficiency segments of the market. The price discrimination model predicts this result. On the other hand, in a perfectly competition market, prices should increase for these market segments. Additionally, new models proliferated in the highest efficiency market segment following the standard changes. Finally, I show that firms appeared to use different adaptation strategies at the two instances of the standards

339

State Volume Price Volume Price Volume Price Volume Price Volume Price  

Gasoline and Diesel Fuel Update (EIA)

7 7 2000 2001 2002 2003 2004 State Volume Price Volume Price Volume Price Volume Price Volume Price Pipeline (Canada) Eastport, ID..................... 830,351 3.79 802,182 4.71 759,647 2.83 R 623,652 4.72 707,885 5.30 Calais, ME ...................... 123,521 4.50 152,486 4.47 124,991 3.49 R 115,301 R 5.85 102,292 6.44 Detroit, MI ....................... 6,171 3.82 405 9.34 1,948 3.56 2,514 5.96 1,117 6.27 Marysville, MI.................. 0 -- 0 -- 74 3.95 0 -- 303 7.80 St. Clair, MI..................... 17,198 4.45 21,747 4.54 28,441 3.19 5,202 5.84 22,853 6.50 International Falls, MN .... 3,022 2.77 617 4.85 602 3.01 0 -- 0 -- Noyes, MN...................... 469,361 3.75 448,898 4.19 402,621 3.09 R 359,801 5.04 399,298 5.77 Warroad, MN .................. 4,576 3.95 5,318 4.52

340

Diesel Fuel Price Pass-through  

Gasoline and Diesel Fuel Update (EIA)

Diesel Fuel Price Pass-through Diesel Fuel Price Pass-through EIA Home > Petroleum > Petroleum Feature Articles Diesel Fuel Price Pass-through Printer-Friendly PDF Diesel Fuel Price Pass-through by Michael Burdette and John Zyren* Over the past several years, the Energy Information Administration (EIA) has extensively studied the relationships between wholesale and retail markets for petroleum products. Beginning with gasoline, we looked at the two ends of the pricing structure in the U.S. market: daily spot prices, which capture sales of large quantities of product between refiners, importers/exporters, and traders; and weekly retail prices, measured at local gasoline outlets nationwide. In the course of this analysis, EIA has found that the relationships between spot and retail prices are consistent and predictable, to the extent that changes in spot prices can be used to forecast subsequent changes in retail prices for the appropriate regions. This article represents the extension of this type of analysis and modeling into the diesel fuel markets.

Note: This page contains sample records for the topic "option pricing model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


341

Examination Procedure for Price Verification  

Science Conference Proceedings (OSTI)

... advertised or displayed at the same price that was ... to permit 2 % of products to be inaccurately priced? ... overall quality of a store's pricing practices. ...

2013-06-28T23:59:59.000Z

342

C. Uniform Unit Pricing Regulation  

Science Conference Proceedings (OSTI)

... to permit retail stores that voluntarily provide unit pricing to present prices using various ... with requirements that specify that the unit price is to be ...

2013-10-25T23:59:59.000Z

343

All Price Tables.vp  

Annual Energy Outlook 2012 (EIA)

8. Coal and Retail Electricity Prices and Expenditures, Ranked by State, 2011 Rank Coal Retail Electricity Prices Expenditures Prices Expenditures State Dollars per Million Btu...

344

South Carolina Natural Gas Prices  

U.S. Energy Information Administration (EIA)

Natural Gas Prices (Dollars per Thousand Cubic Feet, except where noted) ... History; Pipeline and Distribution Use Price : 1967-2005: Citygate Price: ...

345

Spot Distillate & Crude Oil Prices  

U.S. Energy Information Administration (EIA)

Retail distillate prices follow the spot distillate markets, and crude oil prices have been the main driver behind distillate spot price increases until recently.

346

Do PV Systems Increase Residential Selling Prices If So, How Can Practitioners Estimate This Increase?  

E-Print Network (OSTI)

3% of the total sales price of non-PV homes. In the absenceModels Fig. 1: CA PV home sale price premiums expressed inthe selling prices of 329 homes with PV installed in the San

Hoen, Ben

2013-01-01T23:59:59.000Z

347

On the stability of wholesale electricity markets under real-time pricing  

E-Print Network (OSTI)

The paper proposes a mathematical model for the dynamic evolution of supply, demand, and clearing prices under a class of real-time pricing mechanisms characterized by passing on the real-time wholesale prices to the end ...

Roozbehani, Mardavij

348

Attachment 6 Volume V Pricing Matrix for Optional Enhancements...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Contract: 1. PRIME SERVICE PROVIDER COMMERCIAL DISCOUNT ATO FEDERAL OR BASE LABOR PERCENTAGE COMMERCIAL PROPOSED TOTAL GSA LABOR RATE RATEHOUR FROM GSA RATE BURDENED RATE HOURS...

349

PRICING AND HEDGING SPREAD OPTIONS RENE CARMONA AND VALDO DURRLEMAN  

E-Print Network (OSTI)

, or energy markets. As a matter of introduction, we present a general overview of the common features of all markets and the energy markets. One of our goals is to review the literature existing on the subject times. As evidenced by the title of the paper, we intend to concentrate on the energy markets. Standard

Carmona, Rene

350

Transmission Pricing and Renewables: Issues, Options, and Recommendations  

E-Print Network (OSTI)

, Office of Utility Technologies, Office of Energy Management Division of the U.S. Department of Energy

351

New Delhi http://www.nipfp.org.in Oil Price Shock, Pass-through Policy and its Impact on  

E-Print Network (OSTI)

This paper analyses the impact of transmission of international oil prices and domestic oil price pass-through policy on major macroeconomic variables in India with the help of a macroeconomic policy simulation model. Three major channels of transmission viz. import channel, price channel, and fiscal channel are explored with the help of a structural macroeconomic framework. The policy option of deregulation of domestic oil prices in the scenario of occurrence of a one-time shock in international oil prices as well as no oil price shock situation analysed through its impact on growth, inflation, fiscal balances and external balances during the 12 th Plan period of 2012-13 to 2016-17. The simulation results indicate that in the short run the deregulation policy would have adverse impact on the growth as well as on the inflation. But if this policy is complemented with the policy of switching of subsidy bill to capital expenditure it might result in positive growth effects in the medium and long run. Given, the current passthrough policy, one-time oil shock has adverse impact on growth and inflation in the year of shock while it mitigates slowly over time. The model shows that with the oil shock and with current partial pass-through regime, a 10 percent rise in oil prices result in a 0.6 percent fall in growth while in the full pass-through situation, it can reduce the growth by 0.9 percent. Overall, the paper argues that the pass-through has differential impact on growth and inflation over the 12 th Plan period. Hence, the policy of oil price deregulation must be carefully weighed and prioritised.

N R Bhanumurthy; Surajit Das; Sukanya Bose; N R Bhanumurthy; Surajit Das; Sukanya Bose

2012-01-01T23:59:59.000Z

352

Natural Gas Spot Prices:  

Gasoline and Diesel Fuel Update (EIA)

4 of 26 4 of 26 Notes: Spot wellhead prices last summer averaged well over $4.00 per thousand cubic feet during a normally low-price season. During the fall, these prices stayed above $5.00 per thousand cubic feet, more than double the year-ago average price. In January, the spot wellhead price averaged a record $8.98 per thousand cubic feet. Spot prices at the wellhead have never been this high for such a prolonged period. The chief reason for these sustained high gas prices was, and still is, uneasiness about the supply situation. Concern about the adequacy of winter supplies loomed throughout most of the summer and fall as storage levels remained significantly depressed. Last December, the most severe assumptions about low storage levels became real, when the spot price

353

Understanding Crude Oil Prices  

E-Print Network (OSTI)

2004. “OPEC’s Optimal Crude Oil Price,” Energy Policy 32(2),Figure 3. Price of crude oil contract maturing December ofbarrels per day. Monthly crude oil production Iran Iraq

Hamilton, James Douglas

2008-01-01T23:59:59.000Z

354

Diesel prices decrease slightly  

U.S. Energy Information Administration (EIA) Indexed Site

Diesel prices decrease slightly The U.S. average retail price for on-highway diesel fuel fell slightly to 3.84 a gallon on Monday. That's down 3-tenths of a penny from a week ago,...

355

Diesel prices rise slightly  

U.S. Energy Information Administration (EIA) Indexed Site

Diesel prices rise slightly The U.S. average retail price for on-highway diesel fuel rose slightly to 4.16 a gallon on Monday. That's up 2-tenths of a penny from a week ago, based...

356

Diesel prices slightly decrease  

U.S. Energy Information Administration (EIA) Indexed Site

3, 2013 Diesel prices slightly decrease The U.S. average retail price for on-highway diesel fuel fell to 3.87 a gallon on Monday. That's down 1.1 cents from a week ago, based on...

357

Diesel prices slightly decrease  

U.S. Energy Information Administration (EIA) Indexed Site

Diesel prices slightly decrease The U.S. average retail price for on-highway diesel fuel fell slightly to 3.84 a gallon on Monday. That's down 8-tenths of a penny from a week ago,...

358

Diesel prices increase nationally  

U.S. Energy Information Administration (EIA) Indexed Site

Diesel prices increase nationally The U.S. average retail price for on-highway diesel fuel rose to 3.91 a gallon on Monday. That's up 1.3 cents from a week ago, based on the...

359

Florida Natural Gas Prices  

U.S. Energy Information Administration (EIA)

Natural Gas Prices (Dollars per Thousand Cubic Feet, except where noted) ... History; Citygate Price: 4.79: 4.68: 4.54: 4.47: 4.26: 4.33: 1989-2013: ...

360

Michigan Natural Gas Prices  

U.S. Energy Information Administration (EIA)

Natural Gas Prices (Dollars per Thousand Cubic Feet, except where noted) Area: ... History; Citygate Price: 4.74: 4.99: 4.52: 4.48: 4.13: NA: ...

Note: This page contains sample records for the topic "option pricing model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


361

Maine Natural Gas Prices  

U.S. Energy Information Administration (EIA)

Natural Gas Prices (Dollars per Thousand Cubic Feet, except where noted) ... History; Citygate Price: 6.72: 8.18: 11.03: NA: NA: 7.19: 1989-2013: ...

362

Pennsylvania Natural Gas Prices  

U.S. Energy Information Administration (EIA)

Natural Gas Prices (Dollars per Thousand Cubic Feet, except where noted) ... History; Citygate Price: 6.14: 7.58: 8.34: 7.51: 7.39: 6.16: 1989-2013: ...

363

Alabama Natural Gas Prices  

U.S. Energy Information Administration (EIA)

Natural Gas Prices (Dollars per Thousand Cubic Feet, except where noted) Area: ... History; Citygate Price: 4.81: 5.12: 5.31: 4.92: 4.64: NA: ...

364

Career Services Pricing Information  

Science Conference Proceedings (OSTI)

Job/Resume Posting and Prices Career Services Pricing Information Career Services Career Services chemistry jobs classifieds employment fats global help wanted job Jobs member membership network oils science jobs ...

365

Diesel prices decrease  

U.S. Energy Information Administration (EIA) Indexed Site

to 3.88 a gallon on Monday. That's down 0.4 cents from a week ago, based on the weekly price survey by the U.S. Energy Information Administration. Diesel prices were highest in...

366

Retail Propane Prices  

Gasoline and Diesel Fuel Update (EIA)

6 Notes: Consistent with spot prices, residential propane prices have been higher all winter than during the past several years. The recent surge is mainly the result of the surge...

367

Edgeworth Price Cycles, Cost-based Pricing and Sticky Pricing in Retail Gasoline Markets  

E-Print Network (OSTI)

Asymmetrically to Crude Oil Price Changes? ”, QuarterlyS. , A. Shepard. “Sticky Prices, Inventories, and MarketGas Wars: Retail Gasoline Price Fluctua- tions”, Review of

Noel, Michael

2004-01-01T23:59:59.000Z

368

Price Sound Laboratory  

Science Conference Proceedings (OSTI)

Price Sound Laboratory. NVLAP Lab Code: 200874-0. Address and Contact Information: 638 RALEIGH STREET WINNIPEG ...

2013-10-31T23:59:59.000Z

369

EIA Energy Prices  

U.S. Energy Information Administration (EIA)

This publication includes total energy production, consumption, and trade; energy prices; overviews of petroleum, natural gas, coal, electricity, nuclear energy, ...

370

EIA Oil price timeline  

U.S. Energy Information Administration (EIA)

Crude oil, gasoline, heating oil, diesel, propane, ... Sales, revenue and prices, power plants, fuel use, stocks, generation, trade, demand & emissions.

371

Optimal Pricing in Networks with Externalities  

Science Conference Proceedings (OSTI)

We study the optimal pricing strategies of a monopolist selling a divisible good (service) to consumers who are embedded in a social network. A key feature of our model is that consumers experience a (positive) local network effect. In particular, ... Keywords: externalities, optimal pricing, social networks

Ozan Candogan; Kostas Bimpikis; Asuman Ozdaglar

2012-07-01T23:59:59.000Z

372

A study of pricing for cloud resources  

Science Conference Proceedings (OSTI)

We present a study of pricing cloud resources in this position paper. Our objective is to explore and understand the interplay between economics and systems designs proposed by recent research. We develop a general model that captures the resource needs ... Keywords: capacity right-sizing, cloud computing, economics, performance guarantees, pricing, throttling

Hong Xu; Baochun Li

2013-04-01T23:59:59.000Z

373

An analysis of nine-ending pricing  

E-Print Network (OSTI)

Prices ending in 9 are ubiquitous. In this paper I first develop a theoretical model of the effect of such prices on sales and review the empirical literature on the topic. Then I use a data set from an online experiment ...

Wu, Wei, 1973-

2004-01-01T23:59:59.000Z

374

House Price Booms and the Current Account  

E-Print Network (OSTI)

A simple open economy asset pricing model can account for the house price and current account dynamics in the G7 over the years 2001-2008. The model features rational households, but assumes that households entertain subjective beliefs about price behavior and update these using Bayes ’ rule. The resulting beliefs dynamics considerably propagate economic shocks and crucially contribute to replicating the empirical evidence. Belief dynamics can temporarily delink house prices from fundamentals, so that low interest rates can fuel a house price boom. House price booms, however, are not necessarily synchronized across countries and the model correctly predicts the heterogeneous response of house prices across the G7, following the fall in real interest rates at the beginning of the millennium. The response to interest rates depends sensitively on agents ’ beliefs at the time of the interest rate reduction, which are a function of the prior history of disturbances hitting the economy. According to the model, the US house price boom could have been largely avoided, if real interest rates had decreased by less after the year 2000.

Klaus Adam; Pei Kuang; Albert Marcet Abstract

2011-01-01T23:59:59.000Z

375

Option valuation of flexible investments : the case of a coal gasifier  

E-Print Network (OSTI)

This paper examines the use of contingent claim analysis to evaluate the option of retrofitting a coal gasifier on an existing gas-fired power plant in order to take advantage of changes in the relative prices of natural ...

Herbelot, Olivier

1994-01-01T23:59:59.000Z

376

Wisconsin Natural Gas Prices  

U.S. Energy Information Administration (EIA) Indexed Site

Pipeline and Distribution Use Price 1967-2005 Citygate Price 8.04 8.71 6.70 6.14 5.65 4.88 1984-2012 Residential Price 12.02 12.81 10.76 10.34 9.77 9.23 1967-2012 Percentage of...

377

Utility spot pricing study : Wisconsin  

E-Print Network (OSTI)

Spot pricing covers a range of electric utility pricing structures which relate the marginal costs of electric generation to the prices seen by utility customers. At the shortest time frames prices change every five ...

Caramanis, Michael C.

1982-01-01T23:59:59.000Z

378

Open Automated Demand Response Dynamic Pricing Technologies and Demonstration  

SciTech Connect

This study examines the use of OpenADR communications specification, related data models, technologies, and strategies to send dynamic prices (e.g., real time prices and peak prices) and Time of Use (TOU) rates to commercial and industrial electricity customers. OpenADR v1.0 is a Web services-based flexible, open information model that has been used in California utilities' commercial automated demand response programs since 2007. We find that data models can be used to send real time prices. These same data models can also be used to support peak pricing and TOU rates. We present a data model that can accommodate all three types of rates. For demonstration purposes, the data models were generated from California Independent System Operator's real-time wholesale market prices, and a California utility's dynamic prices and TOU rates. Customers can respond to dynamic prices by either using the actual prices, or prices can be mapped into"operation modes," which can act as inputs to control systems. We present several different methods for mapping actual prices. Some of these methods were implemented in demonstration projects. The study results demonstrate show that OpenADR allows interoperability with existing/future systems/technologies and can be used within related dynamic pricing activities within Smart Grid.

Ghatikar, Girish; Mathieu, Johanna L.; Piette, Mary Ann; Koch, Ed; Hennage, Dan

2010-08-02T23:59:59.000Z

379

OPTIONS - ALLOCATION FUNDS - TRANSACTION COSTS  

E-Print Network (OSTI)

with the expected stock price at maturity: USD 136. Therefore, even taking into account this price, the strike prices of calls are still high. Further, we show a large  ...

380

Green Pricing Experience and Lessons Learned Edward A. Holt  

NLE Websites -- All DOE Office Websites (Extended Search)

Pricing Experience and Lessons Learned Pricing Experience and Lessons Learned Edward A. Holt Ed Holt & Associates Pacific Grove, California, August 25-31 Prepared for 1996 ACEEE Summer Study, Seven electric utilities in the United States offer a green pricing program, an optional product or service that customers choose if they wish to increase their use of renewable energy resources. Some two dozen additional utilities are considering or are planning to offer this option. The multiple approaches used and being considered recognize that green pricing is still in an experimental stage of development. The seven operating programs offer a green tariff for extra renewables, fixed monthly fees, and the opportunity to contribute to a tax-deductible fund. The results, in terms of participation

Note: This page contains sample records for the topic "option pricing model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


381

Intraclass Price Elasticity & Electric Rate Design  

E-Print Network (OSTI)

Electric rate design relies on cost incurrance for pricing and pricing structures. However, as utilities move into a marketing mode, rate design needs to respond more to customer reactions to pricing changes. Intraclass price elasticities aid rate designers by estimating customer behavior to change. Intraclass price elasticities vary with customer usage. The more energy used by a customer, the greater the amount of elasticity. For an industrial customer, this means that all energy consumed up to the amount necessary for base operations is relatively inelastic. All energy consumption beyond this becomes more elastic as usage increases. In the book "Innovative Electric Rates," John Chamberlin and Charles Dickson utilize an economic model to test conservation programs. This model utilizes intraclass price elasticities and has a direct use in current electric rate design. The model is a strong indicator of how best a company's electric prices and pricing structures manage demand-side growth, increase energy sales consumption, and aide in non-discriminatory economic development.

Gresham, K. E.

1987-09-01T23:59:59.000Z

382

Average Residential Price  

Gasoline and Diesel Fuel Update (EIA)

Citygate Price Residential Price Commercial Price Industrial Price Electric Power Price Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Gas in Underground Storage Base Gas in Underground Storage Working Gas in Underground Storage Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

383

Average Commercial Price  

U.S. Energy Information Administration (EIA) Indexed Site

Citygate Price Residential Price Commercial Price Industrial Price Electric Power Price Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Gas in Underground Storage Base Gas in Underground Storage Working Gas in Underground Storage Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

384

Average Commercial Price  

Gasoline and Diesel Fuel Update (EIA)

Citygate Price Residential Price Commercial Price Industrial Price Electric Power Price Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Gas in Underground Storage Base Gas in Underground Storage Working Gas in Underground Storage Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

385

Natural Gas Industrial Price  

Gasoline and Diesel Fuel Update (EIA)

Citygate Price Residential Price Commercial Price Industrial Price Electric Power Price Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Gas in Underground Storage Base Gas in Underground Storage Working Gas in Underground Storage Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

386

Average Residential Price  

U.S. Energy Information Administration (EIA) Indexed Site

Citygate Price Residential Price Commercial Price Industrial Price Electric Power Price Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Gas in Underground Storage Base Gas in Underground Storage Working Gas in Underground Storage Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

387

Prepayment Funding Option  

NLE Websites -- All DOE Office Websites (Extended Search)

Prepayment Funding Option December 5, 2012 Prepayment Funding Meeting Prepayment Funding Presentation December 7, 2011 Prepayment Funding Meeting Prepayment Funding Process...

388

Optional Tour Program - TMS  

Science Conference Proceedings (OSTI)

TMS Logo. About the 1996 International Symposium on Extraction and Processing for the Treatment and Minimization of Wastes: Optional Tour Program  ...

389

Challenges for Long-Term Energy Models: Modeling Energy Use and Energy Efficiency  

U.S. Energy Information Administration (EIA) Indexed Site

Long-Term Energy Models: Long-Term Energy Models: Modeling Energy Use and Energy Efficiency James Sweeney Stanford University Director, Precourt Institute for Energy Efficiency Professor, Management Science and Engineering Presentation to EIA 2008 Energy Conference 34 ! Years of Energy Information and Analysis Some Modeling History * Original Federal Energy Administration Demand Models in PIES and IEES (1974) - Residential, Industrial, Commercial Sectors * Econometric models * Dynamic specification * Allowed matrix of own-elasticities and cross- elasticities of demand for PIES and IEES - Electricity, Natural Gas, Oil, Coal - Designed to examine implications of changes in energy prices, taxes, price regulation - For analysis of "energy conservation" options, estimate of direct impacts used as reduction of

390

Threshold Effects of Energy Price Changes ?  

E-Print Network (OSTI)

The effectiveness of policies to reduce the use of energy depend on the elasticity of substitution between the various inputs and on the rate of technological progress. This paper presents a theoretical model emphasising energy investments’ characteristics of uncertainty and irreversibility that result in hypotheses concerning the relative values of substitution parameters and rates of technological change in periods of high and increasing energy prices and in periods of low prices. The theoretical model suggests that threshold level effects exist. Firms are induced to substitute away from energy only if prices of energy exceed a certain threshold level and they reverse the technology only if prices are low enough. Using panel data for the Dutch economy we do not find threshold effects in the level of energy prices.

Daan P. Van Soest A; Gerard H. Kuper B; Jan Jacobs C

2000-01-01T23:59:59.000Z

391

Montana Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 5.72 7.50 3.16 3.64 1967-2010 Imports Price 6.66 8.22 3.88 4.13 3.75 2.45 1989-2012 Exports Price 6.16 8.14 3.63 4.05 3.82 2.40 1989-2012 Pipeline and Distribution Use Price 1967-2005 Citygate Price 6.42 7.71 5.63 5.17 5.11 4.23 1984-2012 Residential Price 9.91 11.45 9.50 8.64 8.80 8.06 1967-2012 Percentage of Total Residential Deliveries included in Prices 99.9 99.9 99.8 99.8 99.8 99.8 1989-2012 Commercial Price 9.76 11.32 9.41 8.54 8.66 7.98 1967-2012 Percentage of Total Commercial Deliveries included in Prices 78.5 79.6 49.2 54.6 53.3 52.9 1990-2012 Industrial Price 9.75 11.04 9.06 8.07 8.13 7.54 1997-2012 Percentage of Total Industrial Deliveries included in Prices

392

Louisiana Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 7.02 8.73 3.82 4.23 1967-2010 Imports Price 6.98 9.76 3.89 4.84 7.57 7.98 1989-2012 Exports Price -- -- -- 7.07 9.63 11.80 2007-2012 Pipeline and Distribution Use Price 1967-2005 Citygate Price 7.22 9.58 5.96 5.43 5.67 3.48 1984-2012 Residential Price 14.20 15.49 13.15 11.73 11.37 11.54 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 11.83 13.52 10.46 9.88 9.36 8.44 1967-2012 Percentage of Total Commercial Deliveries included in Prices 98.0 98.4 92.0 85.9 83.6 78.0 1990-2012 Industrial Price 7.08 9.32 4.31 4.68 4.25 2.96 1997-2012 Percentage of Total Industrial Deliveries included in Prices

393

Nebraska Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 4.86 6.22 2.97 3.98 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 7.67 8.12 5.87 5.62 5.11 4.31 1984-2012 Residential Price 11.15 11.11 9.34 8.95 8.84 8.68 1967-2012 Percentage of Total Residential Deliveries included in Prices 85.7 87.1 87.8 87.4 87.3 85.8 1989-2012 Commercial Price 9.16 9.62 7.44 7.08 6.69 6.19 1967-2012 Percentage of Total Commercial Deliveries included in Prices 63.9 57.5 61.3 60.6 60.6 55.8 1990-2012 Industrial Price 7.97 9.12 6.02 5.85 5.61 4.34 1997-2012 Percentage of Total Industrial Deliveries included in Prices 9.7 10.2 8.9 8.2 7.6 6.8 1997-2012 Vehicle Fuel Price 15.10 15.29 1994-2012 Electric Power Price

394

Describing Commodity Prices in the Energy Book System  

Science Conference Proceedings (OSTI)

The EPRI Energy Book System (EBS) Version 1.20 modules require that users specify a forward price curve and volatility term structure for each commodity market underlying their portfolio. If users wish to measure and manage portfolio risk and/or value certain cross-commodity derivatives, such as spread options and generation assets, then they must also specify commodity price correlations. This report provides a 'first-cut' method for helping EBS users estimate parameters that describe the relevant power...

2000-12-13T23:59:59.000Z

395

Average Residential Price  

Gasoline and Diesel Fuel Update (EIA)

Pipeline and Distribution Use Price Citygate Price Residential Price Commercial Price Industrial Price Vehicle Fuel Price Electric Power Price Proved Reserves as of 12/31 Reserves Adjustments Reserves Revision Increases Reserves Revision Decreases Reserves Sales Reserves Acquisitions Reserves Extensions Reserves New Field Discoveries New Reservoir Discoveries in Old Fields Estimated Production Number of Producing Gas Wells Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production Natural Gas Processed NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals LNG Storage Additions LNG Storage Withdrawals LNG Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Lease Fuel Plant Fuel Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

396

Average Commercial Price  

Gasoline and Diesel Fuel Update (EIA)

Pipeline and Distribution Use Price Citygate Price Residential Price Commercial Price Industrial Price Vehicle Fuel Price Electric Power Price Proved Reserves as of 12/31 Reserves Adjustments Reserves Revision Increases Reserves Revision Decreases Reserves Sales Reserves Acquisitions Reserves Extensions Reserves New Field Discoveries New Reservoir Discoveries in Old Fields Estimated Production Number of Producing Gas Wells Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production Natural Gas Processed NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals LNG Storage Additions LNG Storage Withdrawals LNG Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Lease Fuel Plant Fuel Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

397

Consumer Prices During  

Gasoline and Diesel Fuel Update (EIA)

City Gate City Gate City gate prices represent the total cost paid by gas distribu- tion companies for gas received at the point where the gas is physically transferred from a pipeline company or trans- mission system. This price is intended to reflect all charges for the acquisition, storage, and transportation of gas as well as other charges associated with the LDC's obtaining the gas for sale to consumers. Prices paid at the city gate by local distribution companies rose substantially between 1995 and 1996, climbing from $2.78 per thousand cubic feet to $3.27, an increase of 18 percent. Residential Residential consumers pay the highest price for natural gas. It increased to $6.34 per thousand cubic feet from the 1995 price of $6.06 per thousand cubic feet. However, the 1996 price was 1 percent lower than the 1994 price. In recent years, only modest changes in constant dollars have been

398

Connecticut Gasoline Price Data  

NLE Websites -- All DOE Office Websites (Extended Search)

Connecticut Connecticut Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Bridgeport BridgeportGasPrices.com Automotive.com MapQuest.com Hartford HartfordGasPrices.com Automotive.com MapQuest.com New Haven NewHavenGasPrices.com Automotive.com MapQuest.com Stamford Automotive.com MapQuest.com Waterbury Automotive.com MapQuest.com West Hartford Automotive.com MapQuest.com Other Connecticut Cities ConnecticutGasPrices.com (search by city or ZIP code) - GasBuddy.com Connecticut Gas Prices (selected cities) - GasBuddy.com Connecticut Gas Prices (organized by county) - Automotive.com Gas Prices of the United States: Connecticut Cities - MapQuest

399

Average Residential Price  

U.S. Energy Information Administration (EIA) Indexed Site

Pipeline and Distribution Use Price Citygate Price Residential Price Commercial Price Industrial Price Vehicle Fuel Price Electric Power Price Proved Reserves as of 12/31 Reserves Adjustments Reserves Revision Increases Reserves Revision Decreases Reserves Sales Reserves Acquisitions Reserves Extensions Reserves New Field Discoveries New Reservoir Discoveries in Old Fields Estimated Production Number of Producing Gas Wells Gross Withdrawals Gross Withdrawals From Gas Wells Gross Withdrawals From Oil Wells Gross Withdrawals From Shale Gas Wells Gross Withdrawals From Coalbed Wells Repressuring Nonhydrocarbon Gases Removed Vented and Flared Marketed Production Natural Gas Processed NGPL Production, Gaseous Equivalent Dry Production Imports By Pipeline LNG Imports Exports Exports By Pipeline LNG Exports Underground Storage Capacity Underground Storage Injections Underground Storage Withdrawals Underground Storage Net Withdrawals LNG Storage Additions LNG Storage Withdrawals LNG Storage Net Withdrawals Total Consumption Lease and Plant Fuel Consumption Lease Fuel Plant Fuel Pipeline & Distribution Use Delivered to Consumers Residential Commercial Industrial Vehicle Fuel Electric Power Period: Monthly Annual

400

Energy prices, production  

E-Print Network (OSTI)

on 0 1 2 3 4 5 6 7 8 9 price U K P ./kW h CHP adoption electyricity price to gas price ratio Figure 3. Energy price and CHP annual adoption (UK). Source: DTI (2002b) -5.00% 0.00% 5.00% 10.00% 15.00% 20... .00% 199119921993199419951996199719981999200020012002 an nu al g ro w th r at e in C H P a do pt io n 0 0.2 0.4 0.6 0.8 1 1.2 1.4 price U K P ./kW h CHP adoption Gas price 10 Gas prices leveled off from 1996 onwards and then increased considerably growing by 33% during 1999-2002. In recent...

Bonilla, David

Note: This page contains sample records for the topic "option pricing model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


401

Hedging Quantity Risks with Standard Power Options in a Competitive Wholesale Electricity Market  

E-Print Network (OSTI)

Hedging Quantity Risks with Standard Power Options in a Competitive Wholesale Electricity MarketScience (www.interscience.wiley.com). Abstract: This paper addresses quantity risk in the electricity market-serving entity, which provides electricity service at a regulated price in electricity markets with price

Oren, Shmuel S.

402

DIRECT USE OF NATURAL GAS: ANALYSIS AND POLICY OPTIONS  

E-Print Network (OSTI)

and at past market changes in the energy industry. Both electricity and natural gas distribution are regulated1 DIRECT USE OF NATURAL GAS: ANALYSIS AND POLICY OPTIONS Northwest Power Planning Council Issue Paper 94-41 August 11, 1994 Introduction Lower natural gas prices, apparently adequate gas supplies

403

DIRECT USE OF NATURAL GAS: ANALYSIS AND POLICY OPTIONS  

E-Print Network (OSTI)

. The important point is that whether natural gas or electricity is more energy efficient depends on specific1 DIRECT USE OF NATURAL GAS: ANALYSIS AND POLICY OPTIONS Northwest Power Planning Council Issue Paper 94-41 August 11, 1994 Introduction Lower natural gas prices, apparently adequate gas supplies

404

Optimal Production Planning under Time-sensitive Electricity Prices for  

E-Print Network (OSTI)

Optimal Production Planning under Time-sensitive Electricity Prices for Continuous Power-dependent electricity pricing schemes. In this paper, we describe a deterministic MILP model that allows optimal week and hourly changing electricity prices, we solve an industrial case study on air separation plants

Grossmann, Ignacio E.

405

Main elements for pig price forecasting A. VIGNE M. RIEU  

E-Print Network (OSTI)

Main elements for pig price forecasting A. VIGNE M. RIEU I.T.P., Service Economie, 34, boulevard de the analysis of the past results. Forecasting consists in modelizing each component of pig price from la Gare, 31500 Toulouse The highly fluctuating variation of pig prices results from several

Recanati, Catherine

406

Missouri Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 1967-1997 Pipeline and Distribution Use Price 1967-2005 Citygate Price 7.53 8.03 7.06 6.17 5.85 5.27 1984-2012 Residential Price 13.42 13.36 12.61 11.66 12.02 12.25 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 11.82 12.02 10.81 10.28 9.99 9.54 1967-2012 Percentage of Total Commercial Deliveries included in Prices 76.9 77.5 76.7 76.5 73.1 69.2 1990-2012 Industrial Price 10.84 11.32 9.55 8.70 8.54 7.93 1997-2012 Percentage of Total Industrial Deliveries included in Prices 12.8 13.9 13.2 13.1 13.4 12.5 1997-2012 Vehicle Fuel Price 8.44 8.66 7.86 6.34 6.11 5.64 1994-2012

407

Arkansas Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 6.61 8.72 3.43 3.84 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 8.55 8.88 7.86 6.76 6.27 5.36 1984-2012 Residential Price 13.08 14.09 13.39 11.53 11.46 11.82 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 10.07 11.32 10.72 8.89 8.90 7.99 1967-2012 Percentage of Total Commercial Deliveries included in Prices 70.4 64.5 59.4 55.6 51.5 40.2 1990-2012 Industrial Price 9.51 10.56 8.44 7.28 7.44 6.38 1997-2012 Percentage of Total Industrial Deliveries included in Prices 4.2 3.9 3.7 2.8 2.1 1.9 1997-2012 Vehicle Fuel Price 8.39 -- -- -- -- 9.04 1994-2012

408

Iowa Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Pipeline and Distribution Use Price 1967-2005 Citygate Price 7.80 8.28 5.62 5.69 5.27 4.84 1984-2012 Residential Price 11.76 11.91 9.83 9.57 9.54 9.46 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 9.97 10.25 7.88 7.81 7.55 7.13 1967-2012 Percentage of Total Commercial Deliveries included in Prices 77.7 75.8 72.5 72.0 72.1 72.3 1990-2012 Industrial Price 8.56 9.32 6.23 6.10 5.78 4.70 1997-2012 Percentage of Total Industrial Deliveries included in Prices 6.5 6.6 6.4 5.8 5.5 5.2 1997-2012 Vehicle Fuel Price 11.68 -- -- -- -- -- 1990-2012 Electric Power Price 7.73 W W W W 3.84 1997-2012

409

Maine Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Imports Price 7.57 9.77 4.48 4.94 4.40 3.45 1999-2012 Exports Price -- -- 5.62 4.53 4.46 4.30 2007-2012 Pipeline and Distribution Use Price 1967-2005 Citygate Price 10.46 13.47 8.64 8.19 8.14 7.73 1984-2012 Residential Price 16.90 17.47 16.43 14.14 14.20 15.94 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 99.9 100.0 100.0 1989-2012 Commercial Price 14.82 15.87 13.94 11.71 11.69 12.22 1967-2012 Percentage of Total Commercial Deliveries included in Prices 46.2 45.0 51.0 45.0 45.8 42.1 1990-2012 Industrial Price 13.40 14.89 9.12 11.23 10.89 10.35 1997-2012 Percentage of Total Industrial Deliveries included in Prices 0.8 0.8 1.2 0.6 0.5 0.4 1997-2012

410

Idaho Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Imports Price 6.31 7.88 3.86 4.19 3.90 2.59 1989-2012 Exports Price -- 7.43 4.49 5.85 4.74 -- 1999-2012 Pipeline and Distribution Use Price 1967-2005 Citygate Price 6.68 7.48 5.63 4.82 4.65 4.07 1984-2012 Residential Price 11.47 11.07 10.54 8.95 8.80 8.26 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 10.67 10.28 9.77 8.21 8.09 7.35 1967-2012 Percentage of Total Commercial Deliveries included in Prices 84.8 86.0 83.7 82.0 80.8 77.0 1990-2012 Industrial Price 9.39 9.18 8.53 6.39 6.36 5.73 1997-2012 Percentage of Total Industrial Deliveries included in Prices 2.0 1.9 1.7 1.8 2.0 1.9 1997-2012

411

Maryland Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price NA NA NA NA 1967-2010 Imports Price 7.25 9.09 4.05 5.37 5.30 13.82 1999-2012 Pipeline and Distribution Use Price 1967-2005 Citygate Price 9.24 10.23 8.02 6.49 6.26 5.67 1984-2012 Residential Price 15.17 16.07 13.73 12.44 12.10 12.17 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 79.3 77.0 1989-2012 Commercial Price 12.30 13.12 10.87 9.87 10.29 10.00 1967-2012 Percentage of Total Commercial Deliveries included in Prices 100.0 100.0 100.0 100.0 27.3 24.7 1990-2012 Industrial Price 11.59 13.46 10.70 9.05 8.61 8.01 1997-2012 Percentage of Total Industrial Deliveries included in Prices 7.8 6.3 5.3 5.3 5.5 5.1 1997-2012

412

Alabama Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 7.44 9.65 4.32 4.46 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 8.78 9.84 7.61 6.46 5.80 5.18 1984-2012 Residential Price 18.14 18.30 18.12 15.79 15.08 16.20 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 15.06 15.58 14.94 13.34 12.36 12.55 1967-2012 Percentage of Total Commercial Deliveries included in Prices 79.8 80.2 78.8 79.3 78.9 76.2 1990-2012 Industrial Price 8.70 10.57 6.48 6.64 5.57 4.35 1997-2012 Percentage of Total Industrial Deliveries included in Prices 24.0 27.2 27.9 23.7 23.5 22.1 1997-2012 Vehicle Fuel Price -- 17.32 19.17 16.24 11.45 17.99 1990-2012

413

Massachusetts Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Imports Price 7.32 10.34 5.90 4.86 4.77 3.69 1989-2012 Pipeline and Distribution Use Price 1967-2005 Citygate Price 9.34 10.29 8.29 7.74 7.04 6.03 1984-2012 Residential Price 16.99 17.18 14.85 14.53 13.81 13.22 1967-2012 Percentage of Total Residential Deliveries included in Prices 99.9 85.0 85.6 85.4 89.3 87.8 1989-2012 Commercial Price 15.08 15.25 12.85 12.00 11.68 10.68 1967-2012 Percentage of Total Commercial Deliveries included in Prices 65.3 57.9 56.9 52.1 50.0 48.6 1990-2012 Industrial Price 14.83 15.23 12.07 10.41 10.14 9.82 1997-2012 Percentage of Total Industrial Deliveries included in Prices 29.9 20.6 21.1 19.4 20.6 17.7 1997-2012 Vehicle Fuel Price 12.84 13.80 12.99 12.48 4.28 14.81 1990-2012

414

Vermont Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Imports Price 8.51 9.74 6.34 6.54 5.81 4.90 1989-2012 Pipeline and Distribution Use Price 1982-2005 Citygate Price 10.03 10.66 9.33 8.29 7.98 6.63 1984-2012 Residential Price 15.99 18.31 17.29 16.14 16.17 16.73 1980-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 12.79 14.31 12.96 11.82 11.90 12.09 1980-2012 Percentage of Total Commercial Deliveries included in Prices 100 100 100 100 100 100 1990-2012 Industrial Price 9.08 9.60 7.93 6.57 6.09 4.89 1997-2012 Percentage of Total Industrial Deliveries included in Prices 78.0 79.6 77.9 77.1 80.9 100.0 1997-2012 Electric Power Price 7.72 9.14 5.66 5.73 5.26 4.14 1997-2012

415

Pennsylvania Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price NA NA NA NA 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 9.35 10.39 7.81 7.04 6.28 5.52 1984-2012 Residential Price 14.66 16.22 14.74 12.90 12.46 11.99 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 91.2 88.6 1989-2012 Commercial Price 12.77 14.29 11.83 10.47 10.42 10.24 1967-2012 Percentage of Total Commercial Deliveries included in Prices 100.0 100.0 100.0 100.0 48.5 42.1 1990-2012 Industrial Price 10.64 12.09 9.19 8.23 9.86 9.58 1997-2012 Percentage of Total Industrial Deliveries included in Prices 5.4 5.7 4.5 3.8 2.0 1.3 1997-2012 Vehicle Fuel Price 10.83 8.30 5.15 3.76 3.40 7.96 1990-2012

416

Indiana Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 5.78 7.58 4.05 4.13 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 7.83 8.94 5.59 5.52 4.97 4.23 1984-2012 Residential Price 11.29 12.65 10.81 8.63 9.46 8.94 1967-2012 Percentage of Total Residential Deliveries included in Prices 96.2 95.0 93.6 94.1 94.6 94.5 1989-2012 Commercial Price 10.20 11.14 9.18 7.55 8.04 7.68 1967-2012 Percentage of Total Commercial Deliveries included in Prices 78.1 77.9 73.9 72.5 70.2 67.5 1990-2012 Industrial Price 8.45 10.48 6.91 5.65 6.53 6.19 1997-2012 Percentage of Total Industrial Deliveries included in Prices 7.4 6.7 7.0 5.6 3.5 1.9 1997-2012 Vehicle Fuel Price 6.09 7.94 4.08 5.19 13.24 12.29 1990-2012

417

Florida Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price NA NA NA NA 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 7.97 9.73 5.76 5.49 5.07 3.93 1984-2012 Residential Price 20.61 21.07 20.18 17.89 18.16 18.31 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 98.0 97.7 1989-2012 Commercial Price 13.07 14.45 11.09 10.60 11.14 10.41 1967-2012 Percentage of Total Commercial Deliveries included in Prices 100.0 100.0 100.0 100.0 38.5 37.0 1990-2012 Industrial Price 10.56 11.72 9.41 8.33 8.07 6.96 1997-2012 Percentage of Total Industrial Deliveries included in Prices 3.1 3.0 3.2 3.0 3.0 2.7 1997-2012 Vehicle Fuel Price 12.82 15.56 13.16 17.98 5.56 9.83 1989-2012

418

Utah Gasoline Price Data  

NLE Websites -- All DOE Office Websites (Extended Search)

Utah Utah Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Layton LaytonGasPrices.com Automotive.com MapQuest.com Ogden OgdenGasPrices.com Automotive.com MapQuest.com Orem OremGasPrices.com Automotive.com MapQuest.com Provo ProvoGasPrices.com Automotive.com MapQuest.com Salt Lake City SaltLakeCityGasPrices.com Automotive.com MapQuest.com Sandy SandyGasPrices.com Automotive.com MapQuest.com West Jordan WestJordanGasPrices.com Automotive.com MapQuest.com West Valley City WestValleyCityGasPrices.com Other Utah Cities UtahGasPrices.com (search by city or ZIP code) - GasBuddy.com Utah Gas Prices (selected cities) - GasBuddy.com

419

Connecticut Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Pipeline and Distribution Use Price 1967-2005 Citygate Price 8.67 10.24 6.81 6.58 5.92 5.12 1984-2012 Residential Price 16.39 17.85 14.81 14.93 13.83 14.17 1967-2012 Percentage of Total Residential Deliveries included in Prices 98.2 97.7 97.5 97.3 96.8 96.7 1989-2012 Commercial Price 12.61 13.81 9.92 9.55 8.48 8.40 1967-2012 Percentage of Total Commercial Deliveries included in Prices 71.5 70.7 69.0 65.4 65.4 65.1 1990-2012 Industrial Price 10.54 12.63 8.44 9.60 9.16 8.83 1997-2012 Percentage of Total Industrial Deliveries included in Prices 50.0 47.3 37.5 31.1 31.0 32.3 1997-2012 Vehicle Fuel Price 20.57 24.04 15.26 16.31 18.59 13.70 1992-2012 Electric Power Price 7.81 10.48 4.89 5.70 5.09 3.99 1997-2012

420

Oregon Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 5.27 5.33 4.00 4.92 1979-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 8.14 8.82 7.79 6.78 5.84 5.21 1984-2012 Residential Price 14.65 13.89 14.52 12.49 11.76 11.22 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 12.36 11.57 11.86 10.10 9.60 8.91 1967-2012 Percentage of Total Commercial Deliveries included in Prices 98.5 98.5 98.4 97.4 97.4 96.9 1990-2012 Industrial Price 9.30 9.07 9.70 7.05 6.84 5.87 1997-2012 Percentage of Total Industrial Deliveries included in Prices 21.8 20.1 18.9 17.1 17.1 16.7 1997-2012 Vehicle Fuel Price 6.59 8.03 7.11 5.61 4.23 4.57 1992-2012

Note: This page contains sample records for the topic "option pricing model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


421

Arizona Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 5.98 7.09 3.19 4.11 1967-2010 Exports Price 6.94 8.09 3.79 4.57 4.28 3.07 1989-2012 Pipeline and Distribution Use Price 1967-2005 Citygate Price 8.25 8.49 7.21 6.59 5.91 4.68 1984-2012 Residential Price 17.21 17.60 17.65 15.87 15.04 15.75 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 12.84 13.01 12.15 10.72 9.99 9.35 1967-2012 Percentage of Total Commercial Deliveries included in Prices 93.4 93.1 88.0 88.7 87.8 86.6 1990-2012 Industrial Price 10.49 10.47 8.19 7.54 6.86 5.78 1997-2012 Percentage of Total Industrial Deliveries included in Prices 31.3 29.6 29.1 25.5 24.2 21.4 1997-2012

422

Colorado Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 4.57 6.94 3.21 3.96 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 6.23 6.98 5.09 5.26 4.94 4.26 1984-2012 Residential Price 8.84 9.77 8.80 8.13 8.25 8.31 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 8.10 9.01 7.56 7.58 7.84 7.58 1967-2012 Percentage of Total Commercial Deliveries included in Prices 95.7 95.2 94.8 94.6 93.8 92.2 1990-2012 Industrial Price 7.21 8.76 6.57 5.84 6.42 5.79 1997-2012 Percentage of Total Industrial Deliveries included in Prices 0.5 0.6 0.5 5.2 7.5 6.8 1997-2012 Vehicle Fuel Price 8.72 13.57 9.12 10.79 9.56 11.65 1990-2012

423

Alaska Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 5.63 7.39 2.93 3.17 1967-2010 Exports Price 6.21 7.69 8.59 12.19 12.88 15.71 1989-2012 Pipeline and Distribution Use Price 1970-2005 Citygate Price 6.75 6.74 8.22 6.67 6.53 6.14 1988-2012 Residential Price 8.68 8.72 10.23 8.89 8.77 8.47 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 7.57 8.66 9.51 8.78 8.09 8.09 1967-2012 Percentage of Total Commercial Deliveries included in Prices 76.0 74.9 85.3 87.7 88.6 94.9 1990-2012 Industrial Price 4.67 5.49 4.02 4.23 3.84 5.11 1997-2012 Percentage of Total Industrial Deliveries included in Prices 70.0 78.2 72.5 70.5 60.8 100.0 1997-2012

424

Kansas Natural Gas Prices  

Gasoline and Diesel Fuel Update (EIA)

2007 2008 2009 2010 2011 2012 View 2007 2008 2009 2010 2011 2012 View History Wellhead Price 5.69 6.85 3.16 4.23 1967-2010 Pipeline and Distribution Use Price 1967-2005 Citygate Price 8.27 8.85 6.12 6.08 5.53 4.74 1984-2012 Residential Price 12.97 13.00 11.10 10.61 9.93 10.13 1967-2012 Percentage of Total Residential Deliveries included in Prices 100.0 100.0 100.0 100.0 100.0 100.0 1989-2012 Commercial Price 12.04 12.24 10.01 9.65 8.89 8.82 1967-2012 Percentage of Total Commercial Deliveries included in Prices 64.8 64.9 65.7 66.0 62.6 59.7 1990-2012 Industrial Price 7.17 9.42 4.59 5.49 5.28 3.95 1997-2012 Percentage of Total Industrial Deliveries included in Prices 5.9 7.8 6.7 7.0 9.5 8.8 1997-2012 Vehicle Fuel Price -- -- -- -- 9.87 9.00 1994-2012

425

Security is Not an Option | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Security is Not an Option Security is Not an Option A 10-year roadmap for achieving control system cyber security in the energy industry has been hailed as a model for other...

426

Residential Heating Oil Prices  

Gasoline and Diesel Fuel Update (EIA)

This chart highlights residential heating oil prices for the current and This chart highlights residential heating oil prices for the current and past heating season. As you can see, prices have started the heating season, about 40 to 50 cents per gallon higher than last year at this time. The data presented are from EIA's State Heating Oil and Propane Program. We normally collect and publish this data twice a month, but given the low stocks and high prices, we started tracking the prices weekly. These data will also be used to determine the price trigger mechanism for the Northeast Heating Oil Reserve. The data are published at a State and regional level on our web site. The slide is to give you some perspective of what is happening in these markets, since you probably will get a number of calls from local residents about their heating fuels bills

427

Retail Motor Gasoline Prices*  

Gasoline and Diesel Fuel Update (EIA)

6 6 Notes: Gasoline pump prices have backed down from the high prices experienced last summer and fall. The retail price for regular motor gasoline fell 11 cents per gallon from September to December. However, with crude oil prices rebounding somewhat from their December lows combined with lower than normal stock levels, we project that prices at the pump will rise modestly as the 2001 driving season begins this spring. For the summer of 2001, we expect only a little difference from the average price of $1.50 per gallon seen during the previous driving season, as motor gasoline stocks going into the driving season are projected to be slightly less than they were last year. The situation of relatively low inventories for gasoline could set the stage for some regional imbalances in supply that could once again

428

prices | OpenEI  

Open Energy Info (EERE)

prices prices Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is Table 12, and contains only the reference case. The dataset uses 2009 dollars per gallon. The data is broken down into crude oil prices, residential, commercial, industrial, transportation, electric power and refined petroleum product prices. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO EIA Petroleum prices Data application/vnd.ms-excel icon AEO2011: Petroleum Product Prices- Reference Case (xls, 129.9 KiB) Quality Metrics Level of Review Peer Reviewed Comment Temporal and Spatial Coverage Frequency Annually Time Period 2008-2035

429

Using Environmental Emissions Permit Prices to Raise Electricity Prices: Evidence from the California Electricity Market  

E-Print Network (OSTI)

Permit Prices to Raise Electricity Prices: Evidence from thePermit Prices to Raise Electricity Prices: Evidence from thehigher wholesale electricity prices, during the third and

Kolstad, Jonathan; Wolak, Frank

2003-01-01T23:59:59.000Z

430

Iowa Gasoline Price Data  

NLE Websites -- All DOE Office Websites (Extended Search)

Iowa Iowa Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Ames AmesGasPrices.com Automotive.com MapQuest.com Cedar Rapids CedarRapidsGasPrices.com Automotive.com MapQuest.com Council Bluffs CouncilBluffsGasPrices.com Automotive.com MapQuest.com Des Moines DesMoinesGasPrices.com Automotive.com MapQuest.com Dubuque DubuqueGasPrices.com Automotive.com MapQuest.com Iowa City IowaCityGasPrices.com Automotive.com MapQuest.com Quad Cities QuadCitiesGasPrices.com Sioux City SiouxCityGasPrices.com Automotive.com MapQuest.com Waterloo WaterlooGasPrices.com Automotive.com MapQuest.com Other Iowa Cities

431

Louisiana Gasoline Price Data  

NLE Websites -- All DOE Office Websites (Extended Search)

Louisiana Louisiana Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Baton Rouge BatonRougeGasPrices.com Automotive.com MapQuest.com Lafayette LafayetteGasPrices.com Automotive.com MapQuest.com Lake Charles LakeCharlesGasPrices.com Automotive.com MapQuest.com Metairie MetairieGasPrices.com Automotive.com MapQuest.com Monroe MonroeGasPrices.com Automotive.com MapQuest.com New Orleans NewOrleansGasPrices.com Automotive.com Mapquest.com Shreveport ShreveportGasPrices.com Automotive.com MapQuest.com Other Louisiana Cities LouisianaGasPrices.com (search by city or ZIP code) - GasBuddy.com Louisiana Gas Prices (selected cities) - GasBuddy.com

432

Utah Natural Gas Prices  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Prices are in ...

433

California Gasoline Price Data  

NLE Websites -- All DOE Office Websites (Extended Search)

California California Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Bakersfield BakersfieldGasPrices.com Automotive.com MapQuest.com Fresno FresnoGasPrices.com Automotive.com MapQuest.com Los Angeles LosAngelesGasPrices.com Automotive.com MapQuest.com Modesto ModestoGasPrices.com Automotive.com MapQuest.com Oakland OaklandGasPrices.com Automotive.com MapQuest.com Orange County OrangeCountyGasPrices.com Automotive.com MapQuest.com Riverside RiversideGasPrices.com Automotive.com MapQuest.com San Bernardino SanBernardinoGasPrices.com Automotive.com MapQuest.com San Diego SanDiegoGasPrices.com Automotive.com MapQuest.com

434

Michigan Gasoline Price Data  

NLE Websites -- All DOE Office Websites (Extended Search)

Michigan Michigan Exit Fueleconomy.gov The links below are to pages that are not part of the fueleconomy.gov. We offer these external links for your convenience in accessing additional information that may be useful or interesting to you. Selected Cities Ann Arbor AnnArborGasPrices.com Automotive.com MapQuest.com Battle Creek BattleCreekGasPrices.com Automotive.com MapQuest.com Detroit DetroitGasPrices.com Automotive.com MapQuest.com Flint FlintGasPrices.com Automotive.com MapQuest.com Grand Rapids GrandRapidsGasPrices.com Automotive.com MapQuest.com Kalamazoo KalamazooGasPrices.com Automotive.com MapQuest.com Lansing LansingGasPrices.com Automotive.com MapQuest.com Sterling Heights SterlingHeightsGasPrices.com Automotive.com MapQuest.com Other Michigan Cities MichiganGasPrices.com (search by city or ZIP code) - GasBuddy.com

435

Natural Gas Exports Price  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Prices are in ...

436

Natural Gas Wellhead Price  

Annual Energy Outlook 2012 (EIA)

Wellhead Price Marketed Production Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By:...

437

,"Wisconsin Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Wisconsin Natural Gas Prices",8,"Monthly","72013","1151989" ,"Release Date:","9302013"...

438

,"Texas Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

,"Workbook Contents" ,"Texas Natural Gas Prices" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for"...

439

Residential Price - Marketers  

U.S. Energy Information Administration (EIA)

Average Price of Natural Gas Delivered to Residential and Commercial Consumers by Local Distribution and Marketers in Selected States (Dollars per Thousand Cubic Feet ...

440

Crude Oil Prices  

Annual Energy Outlook 2012 (EIA)

Information AdministrationPetroleum Marketing Annual 1999 41 Table 21. Domestic Crude Oil First Purchase Prices (Dollars per Barrel) - Continued Year Month PAD District II...

Note: This page contains sample records for the topic "option pricing model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


441

Crude Oil Prices  

Annual Energy Outlook 2012 (EIA)

Information AdministrationPetroleum Marketing Annual 2000 41 Table 21. Domestic Crude Oil First Purchase Prices (Dollars per Barrel) - Continued Year Month PAD District II...

442

Crude Oil Prices  

Annual Energy Outlook 2012 (EIA)

Information AdministrationPetroleum Marketing Annual 1998 41 Table 21. Domestic Crude Oil First Purchase Prices (Dollars per Barrel) - Continued Year Month PAD District II...

443

Crude Oil Prices  

Gasoline and Diesel Fuel Update (EIA)

Information AdministrationPetroleum Marketing Annual 2001 41 Table 21. Domestic Crude Oil First Purchase Prices (Dollars per Barrel) - Continued Year Month PAD District II...

444

Price-Anderson Act  

Energy.gov (U.S. Department of Energy (DOE))

The Price-Anderson Act (PAA) provides a system of indemnification for legal liability resulting from a nuclear incident in connection with contractual activity for DOE.

445

,"Pennsylvania Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Of Series","Frequency","Latest Data for" ,"Data 1","Pennsylvania Natural Gas Prices",8,"Monthly","72013","1151989" ,"Release Date:","9302013" ,"Next Release...

446

Idaho Natural Gas Prices  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Prices are in ...

447

,"Idaho Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Idaho Natural Gas Prices",8,"Monthly","102013","1151989" ,"Release Date:","172014"...

448

Natural Gas Citygate Price  

U.S. Energy Information Administration (EIA)

... electric power price data are for regulated electric ... Gas volumes delivered for vehicle fuel are included in the State monthly totals from January ...

449

Crude Price & Differential  

U.S. Energy Information Administration (EIA)

... , making it more competitive with other boiler fuels, and the price of residual fuel relative to crude oil increases. Thus, both the light ...

450

Colorado Natural Gas Prices  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Prices are in ...

451

Retail Propane Prices  

Gasoline and Diesel Fuel Update (EIA)

19 Notes: Residential propane prices rose fairly strongly during the 1999-2000 heating season, gaining nearly 25 cents per gallon between October and March. Unfortunately,...

452

CA Following World Prices  

U.S. Energy Information Administration (EIA)

Light-heavy crude differentials fell and stayed down until the later part of 1997. Crude prices continued to weaken, but the light heavy difference ...

453

,"Wyoming Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

ame","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Wyoming Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

454

,"Iowa Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Iowa Natural Gas Prices",10,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

455

,"Nebraska Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Of Series","Frequency","Latest Data for" ,"Data 1","Nebraska Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

456

,"Vermont Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

ame","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Vermont Natural Gas Prices",10,"Annual",2012,"6301980" ,"Release Date:","10312013" ,"Next Release...

457

,"Ohio Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Ohio Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

458

,"California Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Of Series","Frequency","Latest Data for" ,"Data 1","California Natural Gas Prices",13,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

459

,"Wisconsin Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Of Series","Frequency","Latest Data for" ,"Data 1","Wisconsin Natural Gas Prices",10,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

460

,"Maryland Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Of Series","Frequency","Latest Data for" ,"Data 1","Maryland Natural Gas Prices",12,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

Note: This page contains sample records for the topic "option pricing model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


461

,"Michigan Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Of Series","Frequency","Latest Data for" ,"Data 1","Michigan Natural Gas Prices",13,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

462

,"Illinois Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Of Series","Frequency","Latest Data for" ,"Data 1","Illinois Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

463

,"Kansas Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Kansas Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

464

,"Arkansas Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Of Series","Frequency","Latest Data for" ,"Data 1","Arkansas Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

465

,"Texas Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Texas Natural Gas Prices",13,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

466

,"Arizona Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

ame","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Arizona Natural Gas Prices",12,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

467

,"Minnesota Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Of Series","Frequency","Latest Data for" ,"Data 1","Minnesota Natural Gas Prices",12,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

468

,"Florida Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

ame","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Florida Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

469

,"Tennessee Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Of Series","Frequency","Latest Data for" ,"Data 1","Tennessee Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

470

,"Colorado Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Of Series","Frequency","Latest Data for" ,"Data 1","Colorado Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

471

,"Virginia Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Of Series","Frequency","Latest Data for" ,"Data 1","Virginia Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

472

,"Oklahoma Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Of Series","Frequency","Latest Data for" ,"Data 1","Oklahoma Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

473

,"Washington Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Of Series","Frequency","Latest Data for" ,"Data 1","Washington Natural Gas Prices",12,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

474

,"Maine Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Maine Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

475

,"Louisiana Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Of Series","Frequency","Latest Data for" ,"Data 1","Louisiana Natural Gas Prices",13,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

476

,"Utah Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Utah Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

477

,"Oregon Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Oregon Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

478

,"Mississippi Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Of Series","Frequency","Latest Data for" ,"Data 1","Mississippi Natural Gas Prices",12,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

479

,"Massachusetts Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Of Series","Frequency","Latest Data for" ,"Data 1","Massachusetts Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

480

,"Nevada Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Nevada Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

Note: This page contains sample records for the topic "option pricing model" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


481

,"Delaware Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Of Series","Frequency","Latest Data for" ,"Data 1","Delaware Natural Gas Prices",10,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

482

,"Pennsylvania Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Of Series","Frequency","Latest Data for" ,"Data 1","Pennsylvania Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

483

,"Kentucky Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Of Series","Frequency","Latest Data for" ,"Data 1","Kentucky Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

484

,"Montana Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

ame","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Montana Natural Gas Prices",13,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

485

,"Idaho Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Idaho Natural Gas Prices",12,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

486

,"Missouri Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Of Series","Frequency","Latest Data for" ,"Data 1","Missouri Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

487

,"Georgia Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

ame","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Georgia Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

488

,"Indiana Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

ame","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Indiana Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

489

,"Alabama Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

ame","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Alabama Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

490

,"Connecticut Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Of Series","Frequency","Latest Data for" ,"Data 1","Connecticut Natural Gas Prices",10,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

491

,"Alaska Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Alaska Natural Gas Prices",11,"Annual",2012,"6301967" ,"Release Date:","10312013" ,"Next Release...

492

,"Hawaii Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

Name","Description"," Of Series","Frequency","Latest Data for" ,"Data 1","Hawaii Natural Gas Prices",8,"Annual",2012,"6301980" ,"Release Date:","10312013" ,"Next Release...

493

,"Iowa Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

,"Workbook Contents" ,"Iowa Natural Gas Prices" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for" ,"Data...

494

,"Alabama Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

,"Workbook Contents" ,"Alabama Natural Gas Prices" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for"...

495

,"Georgia Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

,"Workbook Contents" ,"Georgia Natural Gas Prices" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for"...

496

,"Connecticut Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

,"Workbook Contents" ,"Connecticut Natural Gas Prices" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for"...

497

,"Colorado Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

,"Workbook Contents" ,"Colorado Natural Gas Prices" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for"...

498

,"California Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

,"Workbook Contents" ,"California Natural Gas Prices" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for"...

499

,"Florida Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

,"Workbook Contents" ,"Florida Natural Gas Prices" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for"...

500

,"Arkansas Natural Gas Prices"  

U.S. Energy Information Administration (EIA) Indexed Site

,"Workbook Contents" ,"Arkansas Natural Gas Prices" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for"...