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CREDIT BARRIER MODELS CLAUDIO ALBANESE, GIUSEPPE CAMPOLIETI, OLIVER CHEN, AND ANDREI ZAVIDONOV
 

Summary: CREDIT BARRIER MODELS
CLAUDIO ALBANESE, GIUSEPPE CAMPOLIETI, OLIVER CHEN, AND ANDREI ZAVIDONOV
ABSTRACT. The model introduced in this article is designed to provide a consistent representation for both
the real-world and pricing measures for the credit process. We find that good agreement with historical
and market data can be achieved across all credit ratings simultaneously. The model is characterized by
an underlying stochastic process that represents credit quality and default events are associated to barrier
crossings. The stochastic process has state dependent volatility and jumps which are estimated by using
empirical migration and default rates. A risk-neutralizing drift and implied recovery rates are estimated to
consistently match the average spread curves corresponding to all the various ratings.
1. INTRODUCTION
Rating agencies rank the credit-worthiness of sovereigns and corporations into a number of credit
classes and provide migration and default rates based on historical data. A broad array of applications
requires accurate pricing models which are consistent with empirical credit migration and default rates
and which capture the relevant components of the price of risk. We introduce new credit barrier models
extending Hull and White [14] and Avellaneda and Zhu [5]. These are structural models based on a notion
of distance to default related to credit ratings. One can think of the distance to default as a measure of
an obligor's leverage relative to the volatility of its asset values. The model in this article attempts to
capture aggregate information including migration rates and average spread curves for all ratings within
a unified framework.
Pricing models for credit sensitive assets can be divided into three main categories: (i) structural-form

  

Source: Albanese, Claudio - Department of Mathematics, King's College London

 

Collections: Mathematics