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Comparison of semiparametric methods to estimate VaR and ES
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 Title & Authors
Comparison of semiparametric methods to estimate VaR and ES
Kim, Minjo; Lee, Sangyeol;
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Basel committee suggests using Value-at-Risk (VaR) and expected shortfall (ES) as a measurement for market risk. Various estimation methods of VaR and ES have been studied in the literature. This paper compares semi-parametric methods, such as conditional autoregressive value at risk (CAViaR) and conditional autoregressive expectile (CARE) methods, and a Gaussian quasi-maximum likelihood estimator (QMLE)-based method through back-testing methods. We use unconditional coverage (UC) and conditional coverage (CC) tests for VaR, and a bootstrap test for ES to check the adequacy. A real data analysis is conducted for S&P 500 index and Hyundai Motor Co. stock price index data sets.
Value-at-Risk;expected shortfall;CAViaR method;CARE method;Gaussian QMLE;back-testing method;
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