• 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