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...

It contains an introduction to how simulation methods can be used to price American options and a discussion of various existing methods. An application using one of these methods, the regression based method, to the GARCH option pricing model is also provided

Recently, simulation methods combined with regression techniques have gained importance when it comes to American option pricing. In this paper we consider such methods and we examine numerically their convergence properties. We first consider the Least Squares Monte-Carlo (LSM) method of...

The least squares Monte Carlo method of Longstaff and Schwartz (2001) has become a standard numerical method for option pricing with many potential risk factors. An important choice in the method is the number of regressors to use and using too few or too many regressors leads to biased results....

This paper introduces a class of multivariate GARCH models with sufficient flexibility to allow for pricing kernels dependent on variances and correlation. This extends the existing literature by explicitly modeling correlation dependent pricing kernels. A large subclass admits closed-form...