Jackknife estimators for reducing bias in asset allocation

Amit Partani*, David P. Morton, Ivilina Popova

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

We use jackknife-based estimators to reduce bias when estimating the optimal value of a stochastic program. Our discussion focuses on an asset allocation model with a power utility function. As we will describe, estimating the optimal value of such a problem plays a key role in establishing the quality of a candidate solution, and reducing bias improves our ability to do so efficiently. We develop a jackknife estimator that is adaptive in that it does not assume the order of the bias is known a priori.

Original languageEnglish (US)
Title of host publicationProceedings of the 2006 Winter Simulation Conference, WSC
Pages783-791
Number of pages9
DOIs
StatePublished - Dec 1 2006
Event2006 Winter Simulation Conference, WSC - Monterey, CA, United States
Duration: Dec 3 2006Dec 6 2006

Publication series

NameProceedings - Winter Simulation Conference
ISSN (Print)0891-7736

Other

Other2006 Winter Simulation Conference, WSC
Country/TerritoryUnited States
CityMonterey, CA
Period12/3/0612/6/06

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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