Title :
Stratification issues in estimating value-at-risk
Author :
Glasserman, Paul ; Heidelberger, Philip ; Shahabuddin, Perwez
Author_Institution :
Columbia Univ., New York, NY, USA
fDate :
6/21/1905 12:00:00 AM
Abstract :
Considers the efficient estimation of value-at-risk, which is an important problem in risk management. The value-at-risk is an extreme quantile of the distribution of the loss in portfolio value during a holding period. An effective importance sampling technique is described for this problem. The importance sampling can be further improved by combining it with stratified sampling. In this setting, an effective stratification variable is the likelihood ratio itself. The paper examines issues associated with the allocation of samples to the strata, and compares the effectiveness of the combination of importance sampling and stratified sampling to that of stratified sampling alone
Keywords :
estimation theory; finance; importance sampling; risk management; simulation; extreme quantile; holding period; importance sampling; likelihood ratio; portfolio value loss distribution; risk management; sample allocation; stratification variable; stratified sampling; value-at-risk estimation; Computational modeling; Discrete event simulation; Economic indicators; Exchange rates; Instruments; Monte Carlo methods; Portfolios; Reactive power; Risk management; Sampling methods;
Conference_Titel :
Simulation Conference Proceedings, 1999 Winter
Conference_Location :
Phoenix, AZ
Print_ISBN :
0-7803-5780-9
DOI :
10.1109/WSC.1999.823095