Stratification issues in estimating value-at-risk

Author

Glasserman, Paul ; Heidelberger, Philip ; Shahabuddin, Perwez

Author_Institution

Columbia Univ., New York, NY, USA

Volume

1

fYear

1999

fDate

6/21/1905 12:00:00 AM

Firstpage

351

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Simulation Conference Proceedings, 1999 Winter

Conference_Location

Phoenix, AZ

Print_ISBN

0-7803-5780-9

Type

conf

DOI

10.1109/WSC.1999.823095

Filename

823095