SADDLE POINT APPROXIMATION AND VOLATILITY ESTIMATION OF VALUE-AT-RISK
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香港中文大學研究人員

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摘要Value-at-Risk (VaR) is a commonly used risk measure adopted by financial engineers and regulators alike. Many of the techniques used in calculating VaR,, however, rely on simulations that can be difficult and time consuming. One of the objectives of this paper is to conduct statistical inference for VaR based on saddle point approximation and volatility estimation. Specifically, by assuming that the loss distribution is a generalized hyperbolic, we propose a quasi-residual based volatility estimate. Because saddle point approximation furnishes a fast and accurate means to approximate the loss distribution and its percentiles, including the VaR in particular, it is then used to approximate the loss distribution of the quasi-residuals from which VaR, can be estimated. Simulation studies and data analysis confirm that the proposed methodology works well both in theory and practice.
著者Tian MZ, Chan NH
期刊名稱Statistica Sinica
出版年份2010
月份7
日期1
卷號20
期次3
出版社STATISTICA SINICA
頁次1239 - 1256
國際標準期刊號1017-0405
電子國際標準期刊號1996-8507
語言英式英語
關鍵詞GARCH models; generalized hyperbolic distribution; heteroscedasticity; quasi-residuals; saddle point approximations; volatility estimate and value-at-Risk
Web of Science 學科類別Mathematics; Statistics & Probability; STATISTICS & PROBABILITY

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