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Dynamic Portfolio Choice: A Simulation Approach

Michael W. Brandt
Duke University - Fuqua School of Business; National Bureau of Economic Research (NBER)

Amit Goyal
Emory University - Goizueta Business School

Pedro Santa-Clara
Universidade Nova de Lisboa; National Bureau of Economic Research (NBER)


May 2001


Abstract:     
We present a simulation-based method for solving realistic portfolio choice problems that potentially involve non-standard preferences and a large number of assets with arbitrary return distribution. Specifically, the return distribution can be time-varying as a function of many observable or unobservable state variables and can even be path-dependent. Furthermore, the method is flexible enough to accommodate intermediate consumption, parameter and model uncertainty, and portfolio constraints. We first establish the properties of the method for the choice between a stock index and cash when the stock returns are either iid or predictable by the dividend yield. We then explore the optimal asset allocation across ten industry portfolios that exhibit momentum through its empirical pattern of own- and cross-serial correlations of returns.

Working Paper Series

Date posted: June 05, 2001 ; Last revised: September 12, 2001

Suggested Citation

Brandt, Michael W., Goyal, Amit and Santa-Clara, Pedro, Dynamic Portfolio Choice: A Simulation Approach (May 2001). Available at SSRN: http://ssrn.com/abstract=271188 or doi:10.2139/ssrn.271188


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Contact Information

Pedro Santa-Clara (Contact Author)
Universidade Nova de Lisboa ( email )
Campus de Campolide
Lisboa 1099-032
Portugal
HOME PAGE: http://docentes.fe.unl.pt/~psc/
National Bureau of Economic Research (NBER)
1050 Massachusetts Avenue
Cambridge, MA 02138
United States
Michael W. Brandt
Duke University - Fuqua School of Business ( email )
1 Towerview Drive
Durham, NC 27708-0120
United States
National Bureau of Economic Research (NBER)
1050 Massachusetts Avenue
Cambridge, MA 02138
United States
Amit Goyal
Emory University - Goizueta Business School ( email )
1300 Clifton Road
Atlanta, GA 30322-2722
United States
404-727-4825 (Phone)
Feedback to SSRN (Beta)


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Citations: 2
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