DocumentCode :
1804492
Title :
Jackknife Estimators for Reducing Bias in Asset Allocation
Author :
Partani, Amit ; Morton, David P. ; Popova, Ivilina
Author_Institution :
Grad. Program in Oper. Res., Univ. of Texas at Austin, Austin, TX
fYear :
2006
fDate :
3-6 Dec. 2006
Firstpage :
783
Lastpage :
791
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.
Keywords :
estimation theory; resource allocation; stochastic processes; stochastic programming; asset allocation model; jackknife estimators; power utility function; stochastic program; Asset management; Degradation; Lagrangian functions; Operations research; Portfolios; Power generation economics; Pricing; Stochastic processes; Utility theory; Yield estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Simulation Conference, 2006. WSC 06. Proceedings of the Winter
Conference_Location :
Monterey, CA
Print_ISBN :
1-4244-0500-9
Electronic_ISBN :
1-4244-0501-7
Type :
conf
DOI :
10.1109/WSC.2006.323159
Filename :
4117683
Link To Document :
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