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A Monte Carlo Method for Optimal Portfolios

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  • Jér�me B. Detemple

    (Boston University, School of Management and CIRANO,)

  • René Garcia

    (Université de Montréal, Department of Economics and CIRANO,)

  • Marcel Rindisbacher

    (University of Toronto, Rotman School of Management and CIRANO)

Abstract

This paper proposes a new simulation-based approach for optimal portfolio allocation in realistic environments with complex dynamics for the state variables and large numbers of factors and assets. A first illustration involves a choice between equity and cash with nonlinear interest rate and market price of risk dynamics. Intertemporal hedging demands significantly increase the demand for stocks and exhibit low volatility. We then analyze settings where stock returns are also predicted by dividend yields and where investors have wealth-dependent relative risk aversion. Large-scale problems with many assets, including the Nasdaq, SP500, bonds, and cash, are also examined. Copyright 2003 by the American Finance Association.

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Article provided by American Finance Association in its journal The Journal of Finance.

Volume (Year): 58 (2003)
Issue (Month): 1 (02)
Pages: 401-446

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Handle: RePEc:bla:jfinan:v:58:y:2003:i:1:p:401-446

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  1. Andrew W. Lo, . "Maximum Likelihood Estimation of Generalized Ito Processes with Discretely Sampled Data," Rodney L. White Center for Financial Research Working Papers 15-86, Wharton School Rodney L. White Center for Financial Research.
  2. Viceira, Luis & Campbell, John, 2001. "Who Should Buy Long-Term Bonds?," Scholarly Articles 3128709, Harvard University Department of Economics.
  3. Nelson, Daniel B & Foster, Dean P, 1994. "Asymptotic Filtering Theory for Univariate ARCH Models," Econometrica, Econometric Society, vol. 62(1), pages 1-41, January.
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