This paper proposes a new method for pricing American options that uses importance sampling to reduce estimator bias and variance in simulation-and-regression based methods. Our suggested method uses regressions under the importance measure directly, instead of under the nominal measure as is...

Recently it was shown that the estimated American call prices obtained with regression and simulation based methods can be significantly improved on by using put-call symmetry. This paper extends these results and demonstrates that it is also possible to significantly reduce the variance of the...

This paper examines the efficiency of standard variance reduction techniques across option characteristics when pricing American-style call and put options with the Least-Squares Monte Carlo algorithm of Longstaff & Schwartz (2001). Our numerical experiments evaluate the efficiency of antithetic...

The Least-Squares Monte Carlo (LSM) algorithm of Longstaff and Schwartz (2001) prices American options with a regression-based early-exercise strategy. This paper analyzes LSM estimator variance to identify two sources: sampling design and stopping time estimation. We examine the effect of...

In the Longstaff-Schwartz Least-Squares Monte Carlo (LSM) method for American option pricing, the early-exercise strategy is based on a regression of future option values on current state variables. The dependence between continuation values and future cash flows results in potential model...

This paper proposes a new method for pricing American options that uses importance sampling to reduce estimator bias and variance in simulation-and-regression based methods. Our suggested method uses regressions under the importance measure directly, instead of under the nominal measure as is...

Recently it was shown that the estimated American call prices obtained with regression and simulation based methods can be significantly improved on by using put-call symmetry. This paper extends these results and demonstrates that it is also possible to significantly reduce the variance of the...