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Value-at-Risk and Extreme Returns

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Author Info
Jón Daníelsson () (London School of Economics, University of Iceland)
Casper G. de Vries () (Erasmus University Rotterdam)

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Abstract

Accurate prediction of the frequency of extreme events is of primary importance in many financial applications such as Value-at-Risk (VaR) analysis. We propose a semi-parametric method for VaR evaluation. The largest risks are modelled parametrically, while smaller risks are captured by the non- parametric empirical distribution function. The semi-parametric method is compared with historical simulation and the J.P. Morgan RiskMetrics technique on a portfolio of stock returns. For predictions of low probability worst outcomes, RiskMetrics analysis underpredicts the VaR while historical simulation overpredicts the VaR. However, the estimates obtained from applying the semi-parametric method are more accurate in the VaR prediction. In addition, an option is used in the portfolio to lower downside risk. Finally, it is argued that current regulatory environment provides incentives to use the lowest quality VaR method available.

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Publisher Info
Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 98-017/2.

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Date of creation: 16 Feb 1998
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Handle: RePEc:dgr:uvatin:19980017

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Web page: http://www.tinbergen.nl/

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Related research
Keywords: Value-at-Risk; Extreme Value Theory; RiskMetrics; Historical Simulation; Tail Density Estimation; Financial Regulation;

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Peter F. Christoffersen & Francis X. Diebold, 2000. "How Relevant is Volatility Forecasting for Financial Risk Management?," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 12-22, February. [Downloadable!] (restricted)
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  2. Michel M. Dacorogna, & Ulrich A. Muller & Olivier V. Pictet & Casper De Vries,, . "The Distribution of Extremal Foreign Exchange Rate Returns in Extremely Large Data Sets," Working Papers 1992-10-22, Olsen and Associates. [Downloadable!]
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This item has more than 25 citations. To prevent cluttering this page, these citations are listed on a separate page.
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