A Variance Reduction Technique Based on Integral Representations

David Heath and Eckhard Platen ()

No 75, Research Paper Series from Quantitative Finance Research Centre, University of Technology, Sydney

Abstract: Standard Monte Carlo methods can often be significantly improved with the addition of appropriate variance reduction techniques. In this paper a new and powerful variance reduction technique is presented. The method is based directly on the Ito calculus and is used to find unbiased variance reduced estimators for the expectation of functionals of Ito diffusion processes. The approach considered has wide applicability, for instance, it can be used as a means of approximating solutions of parabolic partial differential equations or applied to valuation problems that arise in mathematical finance. We illustrate how the method can be applied by considering the pricing of European style derivative securities for a class of stochastic volatility models, including the Heston model.

Keywords: monte carlo method; variance reduction; stochastic volatility; heston model (search for similar items in EconPapers)
JEL-codes: G12 (search for similar items in EconPapers)
Pages: 19 pages
Date: 2002-03-01
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

Published as: Heath, D. and Platen, E., 2002, "A Variance Reduction Technique Based on Integral Representations", Quantitative Finance, 2(5), 362-369.

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