Evaluating Risk Forecasts with Central Limits
20 Pages Posted: 29 Mar 2008 Last revised: 11 Nov 2008
Date Written: July 9, 2008
Abstract
Portfolio risk forecasts are commonly evaluated using test statistics that are sums of random variables. We study the distributional properties of these test statistics for value at risk, expected shortfall, and volatility. For a diverse collection of 74 US equity portfolios, risk forecasts based on an extreme value theory model greatly outperform a conditional normal model with a 23-day halflife. On the other hand, we show that the common assumption of asymptotic normality in test statistics for these risk measures is not always satisfied, especially for test statistics related to volatility.
Keywords: hyptothesis test, value at risk, expected shortfall
Suggested Citation: Suggested Citation
Do you have negative results from your research you’d like to share?
Recommended Papers
-
Beyond Value at Risk: Forecasting Portfolio Loss at Multiple Horizons
By Lisa R. Goldberg, Guy Miller, ...
-
Maxvar: Long Horizon Value at Risk in a Mark-to-Market Environment
By Jacob Boudoukh, Richard Stanton, ...
-
Extreme Risk Analysis, July 2009
By Lisa R. Goldberg, Michael Y. Hayes, ...
-
By Lisa R. Goldberg, Michael Y. Hayes, ...
-
Central Limits and Financial Risk
By Angelo Barbieri, Vladislav Dubikovsky, ...
-
Understanding the Tails of the Return Distribution
By Msci Inc.
-
The Long View of Financial Risk
By Lisa R. Goldberg and Michael Y. Hayes
-
The Long View of Financial Risk, August 2009
By Lisa R. Goldberg and Michael Y. Hayes
-
Downside Risk Management in Emerging Markets
By Issam S. Strub and Edward D. Baker