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We proposed a two-step Longstaff Schwartz Monte Carlo (LSMC) method with tworegression models fitted at each time step to price game options. Although theoriginal LSMC can be used to price game options with an enlarged range of pathin regression and a modified cashflow updating rule, we identified a drawbackof such approach, which motivated us to propose our approach. We implementednumerical examples with benchmarks using binomial tree and numerical PDE, andit showed that our method produces more reliable results comparing to theoriginal LSMC.

A Two-Step Longstaff Schwartz Monte Carlo Approach to Game Option Pricing