Extreme Returns, Tail Estimation, and Value-at-Risk
Accurate prediction of extreme events are of primary importance in many financial applications. The properties of historical simulation and Risk Metrics techniques for computing Valu-at Risk (VaR) are compared with a method which involves modelling the tails of financial returns explicitly with a tail estimator. The methods are compared using a sample of U.S. stock returns. For predictions of low probability worst outcomes, RiskMetrics type analysis underpredicts while historical simulation overpredicts. However, the estimates obtained from applying the tail estimator are more accurate in the VaR prediction. This implies that capital requirements can be lower by doing VaR with the tail estimator.
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.:
- J. S. Butler & Barry Schachter, 1996. "Improving Value-At-Risk Estimates By Combining Kernel Estimation With Historical Simulation," Finance 9605001, EconWPA.
- J. S. Butler & Barry Schachter, 1996. "Improving value-at-risk estimates by combining kernel estimation," Proceedings 513, Federal Reserve Bank of Chicago.