Journal of Applied Probability
- J. Appl. Probab.
- Volume 53, Number 2 (2016), 531-542.
Optimal importance sampling for the Laplace transform of exponential Brownian functionals
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.
J. Appl. Probab., Volume 53, Number 2 (2016), 531-542.
First available in Project Euclid: 17 June 2016
Permanent link to this document
Mathematical Reviews number (MathSciNet)
Zentralblatt MATH identifier
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)
Kim, Je Guk. Optimal importance sampling for the Laplace transform of exponential Brownian functionals. J. Appl. Probab. 53 (2016), no. 2, 531--542. https://projecteuclid.org/euclid.jap/1466172872