Abstract

We analyze the computational problem of estimating financial risk in a nested simulation. In this approach, an outer simulation is used to generate financial scenarios and an inner simulation is used to estimate future portfolio values in each scenario. We focus on one risk measure, the probability of a large loss, and we propose a new algorithm to estimate this risk. Our algorithm sequentially allocates computational effort in the inner simulation based on marginal changes in the risk estimator in each scenario. Theoretical results are given to show that the risk estimator has a faster convergence order compared to the conventional uniform inner sampling approach. Numerical results consistent with the theory are presented.

Authors
Mark Broadie, Yiping Du, and Ciamac Moallemi
Format
Journal Article
Publication Date
Journal
Management Science

Full Citation

. “Efficient Risk Estimation via Nested Sequential Simulation.”
Management Science
vol.
57
, (June 01, 2011):
1172
-
1194
.