Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

12-2013

Abstract

In this paper, we study the problem of estimating the price of an American option and its price sensitivities via Monte Carlo simulation. Compared to estimating the option price which satisfies a backward recursion, estimating the price sensitivities is more challenging. With the readily-computable pathwise derivatives in a simulation run, we derive a backward recursion for the price sensitivities. We then propose nonparametric estimators, the k-nearest neighbor estimators, to estimate conditional expectations involved in the backward recursion, leading to estimates of the option price and its sensitivities in the same simulation run. Numerical experiments indicate that the proposed method works well and is promising for practical problems.

Discipline

Operations and Supply Chain Management

Research Areas

Operations Management

Publication

Proceedings of the 2013 Winter Simulation Conference

First Page

619

Last Page

700

Identifier

10.5555/2675983.2676073

Publisher

IEEE

City or Country

Washington DC, USA

Additional URL

https://doi.org/10.5555/2675983.2676073

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