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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/121418


    Title: VaR/CVaR Estimation under Stochastic Volatility Models
    Authors: Han, Chuan-Hsiang;Liu, Wei-Han;Chen, Tzu-Ying
    Keywords: Stochastic volatility;Fourier transform method;importance sampling;(conditional) Value-at-Risk;backtesting
    Date: 2014-04-28
    Issue Date: 2021-09-30 12:11:24 (UTC+8)
    Publisher: World Scientific Publishing Co. Pte. Ltd.
    Abstract: This paper proposes an improved procedure for stochastic volatility model estimation with an application to Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) estimation. This improved procedure is composed of the following instrumental components: Fourier transform method for volatility estimation, and importance sampling for extreme event probability estimation. The empirical analysis is based on several foreign exchange series and the S&P 500 index data. In comparison with empirical results by RiskMetrics, historical simulation, and the GARCH(1,1) model, our improved procedure outperforms on average.
    Relation: International Journal of Theoretical and Applied Finance 17(2), 1450009
    DOI: 10.1142/S0219024914500095
    Appears in Collections:[Graduate Institute & Department of Insurance Insurance] Journal Article

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