A general method for debiasing a Monte Carlo estimator
AbstractConsider 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.
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Bibliographic InfoPaper provided by arXiv.org in its series Papers with number 1005.2228.
Date of creation: May 2010
Date of revision: Jun 2010
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Web page: http://arxiv.org/
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-05-22 (All new papers)
- NEP-ECM-2010-05-22 (Econometrics)
- NEP-ORE-2010-05-22 (Operations Research)
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