Pathwise derivative methods on single-asset american option sensitivity estimation

Authors:
Nan Chen;Yanchu Liu
Affiliations:
The Chinese University of Hong Kong, Shatin, Hong Kong;The Chinese University of Hong Kong, Shatin, Hong Kong
Venue:
Proceedings of the Winter Simulation Conference
Year:
2010

Citing 5
Cited 0

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Abstract

In this paper, we investigate efficient Monte Carlo estimators to American option sensitivities on single asset. Using two features of the exercising boundary of the optimal stopping problem, the "continuous-fit" and "smooth-pasting" conditions, we derive unbiased pathwise estimators for first and second-order derivatives. Our method can be easily embedded into some popular algorithms for pricing one-dimensional American options. Numerical examples on vanilla puts illustrate accuracy and efficiency of the method.