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Capturing Tail Risks Beyond VaR

Author

Listed:
  • Woon Kong Wong

    (Centre for Global Finance, Bristol Business School, University of the West of England, Frenchay Campus, Coldharbour Lane, Bristol, BS16 1QY, U.K.)

  • Guobin Fan

    (School of Management and Economics, The University of Electronic Science and Technology of China, No. 4, Section 2, North Jianshe Road, Chengdu, China)

  • Yong Zeng

    (School of Management and Economics, The University of Electronic Science and Technology of China, No. 4, Section 2, North Jianshe Road, Chengdu, China)

Abstract

Since Value-at-Risk (VaR) disregards tail losses beyond the VaR boundary, the expected shortfall (ES), which measures the average loss when a VaR is exceeded, and the tail-risk-of-VaR (TR), which sums the sizes of tail losses, are used to investigate risks at the tails of distributions for major stock markets. As VaR exceptions are rare, we employ the saddlepoint or small sample asymptotic technique to backtest ES and TR. Because the two risk measures are complementary to each other and hence provide more powerful backtests, we are able to show that (a) the correct specification of distribution tail, rather than heteroscedastic process, plays a key role to accurate risk forecasts; and (b) it is best to model the tails separately from the central part of distribution using the Generalized Pareto Distribution (GPD). To sum up, we provide empirical evidence that financial markets behave differently during crises, and extreme risks cannot be modeled effectively under normal market conditions or based on a short data history.

Suggested Citation

  • Woon Kong Wong & Guobin Fan & Yong Zeng, 2012. "Capturing Tail Risks Beyond VaR," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 15(03), pages 1-25.
    • Handle: RePEc:wsi:rpbfmp:v:15:y:2012:i:03:n:s0219091512500154
    DOI: 10.1142/S0219091512500154
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    Citations

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    Cited by:

    1. Benjamin Mögel & Benjamin R. Auer, 2018. "How accurate are modern Value-at-Risk estimators derived from extreme value theory?," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 979-1030, May.
    2. Marcelo Brutti Righi & Paulo Sergio Ceretta, 2015. "Shortfall Deviation Risk: An alternative to risk measurement," Papers 1501.02007, arXiv.org, revised May 2016.
    3. Yam Wing Siu, 2020. "Impact of Expected Shortfall Approach on Capital Requirement Under Basel," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 22(04), pages 1-34, January.
    4. Righi, Marcelo Brutti & Ceretta, Paulo Sergio, 2015. "A comparison of Expected Shortfall estimation models," Journal of Economics and Business, Elsevier, vol. 78(C), pages 14-47.

    More about this item

    Keywords

    Value-at-Risk; expected shortfall; tail risk; backtesting; saddlepoint technique;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • G2 - Financial Economics - - Financial Institutions and Services
    • G3 - Financial Economics - - Corporate Finance and Governance

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