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ROM Simulation: Applications to Stress Testing and VaR
Year Of Publication: 2012
Month Of Publication: May
Pages: 24
Download Count: 6
View Count: 1331
Comment Num: 0
Language: English
Source: working paper
Who Can Read: Free
Date: 5-7-2012
Publisher: Administrator
Summary
Most banks employ historical simulation for Value-at-Risk (VaR) calculations, where VaR is computed from a lower quantile of a forecast distribution for the portfolio’s profit and loss (P&L) that is constructed from a single, multivariate historical sample on the portfolio’s risk factors. The implicit assumption is that history will repeat itself for certain over the forecast horizon. Until now, the only alternative is to assume the historical sample is generated by a multivariate, parametric risk factor distribution and (except in special cases where an analytic solution is available) to simulate P&L via Monte Carlo (MC). This paper introduces a methodology that encompasses historical and MC VaR as special cases, which is much faster than MC simulation and which avoids the single-sample bias of historical simulation. Random orthogonal matrix (ROM) simulation is a fast matrix-based simulation method that applies directly to an historical sample, or to a parametric distribution. Each simulation matches the first four multivariate sample moments to those of the observed sample, or of the target distribution. Stressed VaR is typically
Author(s)
Alexander, Carol Sign in to follow this author
Ledermann, Daniel Sign in to follow this author
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