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Evaluation of Various Approaches to Value at Risk

Schmidt, Henning and Duda, Matej (2009)
Department of Economics
Abstract
In the light of the current financial crisis, risk management and prediction of market losses seem to play a crucial role in finance. This thesis compares one day out-of-sample predictive performance of standard methods and conditional autoregressive VaR (CAViaR) by Engle & Manganelli (2004) for VaR (Value-at-risk) prediction of market losses. Comparison is made on US, Hong Kong, and Russian indices under tranquil period and current crisis using more than 10 years of daily returns. Performance is evaluated in terms of empirical coverage probability and predictive quantile loss on adequate models pointed out by Christoffersen test. The findings show that traditional methods such as historical simulation, normal VaR and t-VaR behave quite... (More)
In the light of the current financial crisis, risk management and prediction of market losses seem to play a crucial role in finance. This thesis compares one day out-of-sample predictive performance of standard methods and conditional autoregressive VaR (CAViaR) by Engle & Manganelli (2004) for VaR (Value-at-risk) prediction of market losses. Comparison is made on US, Hong Kong, and Russian indices under tranquil period and current crisis using more than 10 years of daily returns. Performance is evaluated in terms of empirical coverage probability and predictive quantile loss on adequate models pointed out by Christoffersen test. The findings show that traditional methods such as historical simulation, normal VaR and t-VaR behave quite well in tranquil period if accounted for the return volatility dynamics by using GARCH volatility estimates. When unfiltered, these models fail to produce reliable results. In crisis period symmetric and asymmetric specifications of CAViaR showed good results, generally better and more stable than traditional approaches. Overall, CAViaR was found to work better on 5% than on 1% level. However, this model class is in most cases outperformed by conventional filtered models in the tranquil period. Little evidence was found that the market type has impact on the choice of ideal VaR model. (Less)
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author
Schmidt, Henning and Duda, Matej
supervisor
organization
year
type
H1 - Master's Degree (One Year)
subject
keywords
GARCH, VaR, CAViaR, market risk measuring, coverage probability, Economics, econometrics, economic theory, economic systems, economic policy, Nationalekonomi, ekonometri, ekonomisk teori, ekonomiska system, ekonomisk politik
language
English
id
1436923
date added to LUP
2009-06-11 00:00:00
date last changed
2010-08-03 10:52:24
@misc{1436923,
  abstract     = {In the light of the current financial crisis, risk management and prediction of market losses seem to play a crucial role in finance. This thesis compares one day out-of-sample predictive performance of standard methods and conditional autoregressive VaR (CAViaR) by Engle & Manganelli (2004) for VaR (Value-at-risk) prediction of market losses. Comparison is made on US, Hong Kong, and Russian indices under tranquil period and current crisis using more than 10 years of daily returns. Performance is evaluated in terms of empirical coverage probability and predictive quantile loss on adequate models pointed out by Christoffersen test. The findings show that traditional methods such as historical simulation, normal VaR and t-VaR behave quite well in tranquil period if accounted for the return volatility dynamics by using GARCH volatility estimates. When unfiltered, these models fail to produce reliable results. In crisis period symmetric and asymmetric specifications of CAViaR showed good results, generally better and more stable than traditional approaches. Overall, CAViaR was found to work better on 5% than on 1% level. However, this model class is in most cases outperformed by conventional filtered models in the tranquil period. Little evidence was found that the market type has impact on the choice of ideal VaR model.},
  author       = {Schmidt, Henning and Duda, Matej},
  keyword      = {GARCH,VaR,CAViaR,market risk measuring,coverage probability,Economics, econometrics, economic theory, economic systems, economic policy,Nationalekonomi, ekonometri, ekonomisk teori, ekonomiska system, ekonomisk politik},
  language     = {eng},
  note         = {Student Paper},
  title        = {Evaluation of Various Approaches to Value at Risk},
  year         = {2009},
}