Post by Sapphire Capital on Jul 11, 2008 7:18:20 GMT 4
Evaluating Risk Forecasts with Central Limits
ANGELO BARBIERI
Affiliation Unknown
VLADISLAV DUBIKOVSKY
MSCI Barra
ALEXEI GLADKEVICH
MSCI Barra
LISA R. GOLDBERG
MSCI Barra
MICHAEL Y. HAYES
MSCI Barra
--------------------------------------------------------------------------------
March 28, 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.
papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID1114216_code881168.pdf?abstractid=1114216&mirid=4
ANGELO BARBIERI
Affiliation Unknown
VLADISLAV DUBIKOVSKY
MSCI Barra
ALEXEI GLADKEVICH
MSCI Barra
LISA R. GOLDBERG
MSCI Barra
MICHAEL Y. HAYES
MSCI Barra
--------------------------------------------------------------------------------
March 28, 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.
papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID1114216_code881168.pdf?abstractid=1114216&mirid=4