Capturing Tail Risks Beyond VaR

Woon Kong Wong (), Guobin Fan () and Yong Zeng ()
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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

Review of Pacific Basin Financial Markets and Policies (RPBFMP), 2012, vol. 15, issue 03, 1-25

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.

Keywords: Value-at-Risk; expected shortfall; tail risk; backtesting; saddlepoint technique (search for similar items in EconPapers)
JEL-codes: G1 G2 G3 (search for similar items in EconPapers)
Date: 2012
References: View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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DOI: 10.1142/S0219091512500154

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