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(updated version with corrections, full tables of numerical results, references appeared) Sensitivity Analysis for Monte Carlo Simulation of Option Pricing (1994)
BibTeX
@MISC{Fu94(updatedversion,
author = {Michael C. Fu and Jian-qiang Hu},
title = {(updated version with corrections, full tables of numerical results, references appeared) Sensitivity Analysis for Monte Carlo Simulation of Option Pricing},
year = {1994}
}
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Abstract
Monte Carlo simulation is one alternative for analyzing options markets when the assumptions of simpler analytical models are violated. We introduce techniques for the sensitivity analysis of option pricing which can be efficiently carried out in the simulation. In particular, using these techniques, a single run of the simulation would often provide not only an estimate of the option value but also estimates of the sensitivities of the option value to various parameters of the model. Both European and American options are considered, starting with simple analytically tractable models to present the idea and proceeding to more complicated examples. We then propose an approach for the pricing of options with early exercise features by incorporating the gradient estimates in an iterative stochastic approximation algorithm. The procedure is illustrated in a simple example estimating the option value of an American call. Numerical results indicate that the additional computational effort required over that required to estimate a European option is relatively small.
Keyphrases
numerical result sensitivity analysis monte carlo simulation option pricing option value full table updated version european option complicated example additional computational effort american call iterative stochastic approximation algorithm american option tractable model simpler analytical model various parameter option market single run early exercise feature simple example
