Algorithm 659: Implementing Sobol's quasirandom sequence generator
ACM Transactions on Mathematical Software (TOMS)
Latin supercube sampling for very high-dimensional simulations
ACM Transactions on Modeling and Computer Simulation (TOMACS) - Special issue on uniform random number generation
Accelerated simulation for pricing Asian options
Proceedings of the 30th conference on Winter simulation
Efficiency improvements for pricing American options with a stochastic mesh
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
Simulation in financial engineering: importance sampling in derivative securities pricing
Proceedings of the 32nd conference on Winter simulation
Randomized Polynomial Lattice Rules for Multivariate Integration and Simulation
SIAM Journal on Scientific Computing
An improved simulation method for pricing high-dimensional American derivatives
Mathematics and Computers in Simulation - Special issue: 3rd IMACS seminar on Monte Carlo methods - MCM 2001
Pricing American Options: A Duality Approach
Operations Research
Function-approximation-based importance sampling for pricing American options
WSC '04 Proceedings of the 36th conference on Winter simulation
Randomized Quasi-Monte Carlo: a tool for improving the efficiency of simulations in finance
WSC '04 Proceedings of the 36th conference on Winter simulation
Quasi-Monte Carlo methods in finance
WSC '04 Proceedings of the 36th conference on Winter simulation
American option pricing with randomized quasi-Monte Carlo simulations
Proceedings of the Winter Simulation Conference
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American option pricing is a challenging problem in financial mathematics for which several approaches have been proposed in the last few years. In this paper, we consider the regression-based method of Longstaff and Schwartz (2001) to price these options, and then investigate the use of different variance reduction techniques to improve the efficiency of the Monte Carlo estimators thus obtained. The techniques considered have been shown to work well for European option pricing. One of them is importance sampling, in which the approach of Glasserman, Heidelberger, and Shahabuddin (1999) is applied to find an appropriate change of measure. We also consider control variates and randomized quasi-Monte Carlo methods, and use numerical experiments on American Asian call options to investigate the performance of these methods.