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Optimal importance sampling for the Laplace transform of exponential Brownian functionals

Part of: Mathematical finance Limit theorems

Published online by Cambridge University Press:  21 June 2016

Je Guk Kim
Je Guk Kim*
Affiliation:
The University of Tennessee
*
* Current address: Department of mathematics, Yonsei University, 50 Yonsei-Ro, Seodaemun-Gu, Seoul, South Korea, 03722. Email address: [email protected]
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Abstract

We present an asymptotically optimal importance sampling for Monte Carlo simulation of the Laplace transform of exponential Brownian functionals which plays a prominent role in many disciplines. To this end we utilize the theory of large deviations to reduce finding an asymptotically optimal importance sampling measure to solving a calculus of variations problem. Closed-form solutions are obtained. In addition we also present a path to the test of regularity of optimal drift which is an issue in implementing the proposed method. The performance analysis of the method is provided through the Dothan bond pricing model.

Keywords

Exponential Brownian functionalMonte Carlo methodimportance samplingcalculus of variationlarge deviationsDothan model

MSC classification

Primary: 91G60: Numerical methods (including Monte Carlo methods)
Secondary: 60F10: Large deviations 91G80: Financial applications of other theories (stochastic control, calculus of variations, PDE, SPDE, dynamical systems)
Type
Research Papers
Information
Journal of Applied Probability , Volume 53 , Issue 2 , June 2016 , pp. 531 - 542
Copyright
Copyright © Applied Probability Trust 2016 

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