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Performance of VaR Estimation Using Point Process Approach
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 Title & Authors
Performance of VaR Estimation Using Point Process Approach
Yeo, Sung-Chil; Moon, Seoung-Joo;
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VaR is used extensively as a tool for risk management by financial institutions. For convenience, the normal distribution is usually assumed for the measurement of VaR, but recently the method using extreme value theory is attracted for more accurate VaR estimation. So far, GEV and GPD models are used for probability models of EVT for the VaR estimation. In this paper, the PP model is suggested for improved VaR estimation as compared to the traditonal EV models such as GEV and GPD models. In view of the stochastic process, the PP model is regarded as a generalized model which include GEV and GPD models. In the empirical analysis, the PP model is shown to be superior to GEV and GPD models for the performance of VaR estimation.
Value at risk;extreme value theory;GEV model;GPD model;PP model;back-testing;
 Cited by
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