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Using Quasi-Monte Carlo Scenarios in Risk Management

In: Monte Carlo and Quasi-Monte Carlo Methods 2002

Author

Listed:
  • Filip Pistovčák

    (Department of Computer Science, Fachhochschule Vorarlberg)

  • Thomas Breuer

    (Department of Computer Science, Fachhochschule Vorarlberg)

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.

Suggested Citation

  • Filip Pistovčák & Thomas Breuer, 2004. "Using Quasi-Monte Carlo Scenarios in Risk Management," Springer Books, in: Harald Niederreiter (ed.), Monte Carlo and Quasi-Monte Carlo Methods 2002, pages 379-392, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-18743-8_24
    DOI: 10.1007/978-3-642-18743-8_24
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