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Adaptations of Monte Carlo Simulation Techniques to American Option Pricing
Jan 1, 2010
Serena Agoro-Menyang presents a survey of Monte Carlo methods to price American options. As Serena points out in her introduction, standard Monte Carlo techniques are not well suited for this problem since they are fundamentally forward algorithms: at a given point in time, we know about the past evolution of the option underlying, but not about its future. This complicates the valuation of American options, since it is difficult to determine when it is optimal to exercise. Backward induction techniques are attractive for American option pricing, in that we have seen information about the future evolution of the underlying, and therefore know when it is optimal to exercise. Unfortunately, these algorithms typically come with a large computational burden. The approaches that Serena surveys attempt to blend the computational benefits of Monte Carlo with the applicability of the backward induction techniques.
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