Quotation McNeil, Alexander, Frey, Rüdiger. 2000. Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach. Journal of Empirical Finance, 7, (3-4), 271-300.


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Abstract

We propose a method for estimating Value at Risk (VaR) and related risk measures describing the tail of the conditional distribution of a heteroscedastic financial return series. Our approach combines pseudo-maximum-likelihood fitting of GARCH models to estimate the current volatility and extreme value theory (EVT) for estimating the tail of the innovation distribution of the GARCH model. We use our method to estimate conditional quantiles (VaR) and conditional expected shortfalls (the expected size of a return exceeding VaR), this being an alternative measure of tail risk with better theoretical properties than the quantile. Using backtesting of historical daily return series we show that our procedure gives better 1-day estimates than methods which ignore the heavy tails of the innovations or the stochastic nature of the volatility. With the help of our fitted models we adopt a Monte Carlo approach to estimating the conditional quantiles of returns over multiple-day horizons and find that this outperforms the simple square-root-of-time scaling method

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal Journal of Empirical Finance
Citation Index SSCI
WU Journalrating 2009 A
WU-Journal-Rating new FIN-A, STRAT-B, VW-C, WH-B
Language English
Title Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach
Volume 7
Number 3-4
Year 2000
Page from 271
Page to 300
URL http://www.sciencedirect.com/science/issue/6010-2000-999929996-219757
DOI http://dx.doi.org/10.1016/S0927-5398(00)00012-8
Open Access N

Associations

People
Frey, Rüdiger (Details)
External
McNeil, Alexander
Organization
Institute for Statistics and Mathematics IN (Details)
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