Dimension Reduction in the Computation of Value‐at‐Risk

Abstract

Regulators require banks to employ value‐at‐risk (VaR) to estimate the exposure of their trading portfolios to market risk, in order to establish capital requirements. However, portfolio‐level VaR analysis is a high‐dimensional problem and hence computationally intensive. This article presents two new portfolio‐based approaches to reducing the dimensionality of the VaR analysis.