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Volatility Models Malik MagdonIsmail
 

Summary: Validation
of
Volatility Models
Malik Magdon­Ismail
Caltech 136­93
Pasadena, CA 91125
USA
Yaser S. Abu­Mostafa
Caltech 136­93
Pasadena, CA 91125
USA
abstract
In forecasting a financial time series, the mean prediction can be validated
by direct comparison with the value of the series. However, the volatility
or variance can only be validated by indirect means such as the likelihood
function. Systematic errors in volatility prediction have an `economic value'
since volatility is a tradable quantity (e.g., in options and other derivatives)
in addition to being a risk measure. We analyze the fidelity of the likelihood
function as a means of training (in sample) and validating (out of sample) a
volatility model. We report several cases where the likelihood function leads

  

Source: Abu-Mostafa, Yaser S. - Department of Mechanical Engineering & Computer Science Department, California Institute of Technology
Magdon-Ismail, Malik - Department of Computer Science, Rensselaer Polytechnic Institute

 

Collections: Computer Technologies and Information Sciences