Approximations of option price elasticities for importance sampling
Importance sampling is a powerful instrument to reduce the standard error of Monte-Carlo estimators. Different importance sampling approaches have in common that the optimal importance sampling probability density is unknown. To approximate this unknown density, in this article we will analyze approximations of option price elasticities. The considered importance sampling approach involves adding an additional drift term. For models with stochastic volatility and for pathdependent options, we show that several approaches exist to achieve considerable variance reduction.
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