A general method for debiasing a Monte Carlo estimator

Don McLeish

Papers from arXiv.org

Abstract: Consider a process, stochastic or deterministic, obtained by using a numerical integration scheme, or from Monte-Carlo methods involving an approximation to an integral, or a Newton-Raphson iteration to approximate the root of an equation. We will assume that we can sample from the distribution of the process from time 0 to finite time n. We propose a scheme for unbiased estimation of the limiting value of the process, together with estimates of standard error and apply this to examples including numerical integrals, root-finding and option pricing in a Heston Stochastic Volatility model. This results in unbiased estimators in place of biased ones i nmany potential applications.

Date: 2010-05, Revised 2010-06
New Economics Papers: this item is included in nep-ecm and nep-ore
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