Abstract:
This paper provides an efficient algorithm using Newton's method under sample average approximation (SAA) to solve the parametric optimization problem associated with the...Show MoreMetadata
Abstract:
This paper provides an efficient algorithm using Newton's method under sample average approximation (SAA) to solve the parametric optimization problem associated with the optimal importance sampling change of measure in simulating Lévy processes. Numerical experiments on variance gamma (VG), geometric Brownian motion (GBM), and normal inverse Gaussian (NIG) examples illustrate the computational advantages of the SAA-Newton algorithm over stochastic approximation (SA) based algorithms.
Published in: 2015 Winter Simulation Conference (WSC)
Date of Conference: 06-09 December 2015
Date Added to IEEE Xplore: 18 February 2016
ISBN Information:
Electronic ISSN: 1558-4305