ESAIM: Proceedings and Surveys (Jan 2017)

Truncated control variates for weak approximation schemes*

  • Belomestny Denis,
  • Häfner Stefan,
  • Urusov Mikhail

DOI
https://doi.org/10.1051/proc/201759015
Journal volume & issue
Vol. 59
pp. 15 – 42

Abstract

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In this paper we present an enhancement of the regression-based variance reduction approaches recently proposed in Belomestny et al. [1] and [4]. This enhancement is based on a truncation of the control variate and allows for a significant reduction of the computing time, while the complexity stays of the same order. The performances of the proposed truncated algorithms are illustrated by a numerical example.