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VaR/CVaR ESTIMATION UNDER STOCHASTIC VOLATILITY MODELS

Author

Listed:
  • CHUAN-HSIANG HAN

    (Department of Quantitative Finance, National Tsing-Hua University, Hsinchu, Taiwan 30013, R.O.C.)

  • WEI-HAN LIU

    (Department of Finance, La Trobe University, Melbourne, Australia)

  • TZU-YING CHEN

    (Department of Finance, National Taiwan University, Taipei, Taiwan)

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.

Suggested Citation

  • Chuan-Hsiang Han & Wei-Han Liu & Tzu-Ying Chen, 2014. "VaR/CVaR ESTIMATION UNDER STOCHASTIC VOLATILITY MODELS," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 17(02), pages 1-35.
    • Handle: RePEc:wsi:ijtafx:v:17:y:2014:i:02:n:s0219024914500095
    DOI: 10.1142/S0219024914500095
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    References listed on IDEAS

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    More about this item

    Keywords

    Stochastic volatility; Fourier transform method; importance sampling; (conditional) Value-at-Risk; backtesting; C13; C14; C63;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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