Using Quasi-Monte Carlo Scenarios in Risk Management

Filip Pistovčák () and Thomas Breuer ()
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Filip Pistovčák: Department of Computer Science, Fachhochschule Vorarlberg
Thomas Breuer: Department of Computer Science, Fachhochschule Vorarlberg

A chapter in Monte Carlo and Quasi-Monte Carlo Methods 2002, 2004, pp 379-392 from Springer

Abstract: Summary We report on the use of quasi-random numbers in searching for worstcase scenarios of security portfolios. A systematic search for the worst-case scenario requires to find the global minimum of the portfolio-value function within a search domain of all plausible scenarios, which usually is an ellipsoid in the high dimensional space of risk factors. We compare the performance of a Monte Carlo and a Quasi Monte Carlo search algorithm, which use sequences of scenarios transformed from the unit cube. As a benchmark we use the Multilevel Coordinate Search algorithm of W. Huyer and A. Neumaier applied to the transformed problem on the cube. It turns out that QMC does not perform significantly better than MC for most parameter settings. This might be due to the destruction of low-discrepancy properties by the transformation from the cube to the ellipsoid.

Keywords: Monte Carlo; Market Risk; Search Domain; Monte Carlo Sequence; Equity Index (search for similar items in EconPapers)
Date: 2004
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-18743-8_24

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DOI: 10.1007/978-3-642-18743-8_24

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