A Simulation Approach to Dynamic Portfolio Choice with an Application to Learning About Return Predictability

50 Pages Posted: 15 Dec 2004 Last revised: 14 Aug 2009

See all articles by Michael W. Brandt

Michael W. Brandt

Duke University - Fuqua School of Business; National Bureau of Economic Research (NBER)

Amit Goyal

University of Lausanne; Swiss Finance Institute

Pedro Santa-Clara

New University of Lisbon - Nova School of Business and Economics; National Bureau of Economic Research (NBER); Centre for Economic Policy Research (CEPR)

Jonathan R Stroud

McDonough School of Business, Georgetown University

Multiple version iconThere are 2 versions of this paper

Date Written: November 2004

Abstract

We present a simulation-based method for solving discrete-time portfolio choice problems involving non-standard preferences, a large number of assets with arbitrary return distribution, and, most importantly, a large number of state variables with potentially path-dependent or non-stationary dynamics. The method is flexible enough to accommodate intermediate consumption, portfolio constraints, parameter and model uncertainty, and learning. We first establish the properties of the method for the portfolio choice between a stock index and cash when the stock returns are either iid or predictable by the dividend yield. We then explore the problem of an investor who takes into account the predictability of returns but is uncertain about the parameters of the data generating process. The investor chooses the portfolio anticipating that future data realizations will contain useful information to learn about the true parameter values.

Suggested Citation

Brandt, Michael W. and Goyal, Amit and Santa-Clara, Pedro and Stroud, Jonathan R., A Simulation Approach to Dynamic Portfolio Choice with an Application to Learning About Return Predictability (November 2004). NBER Working Paper No. w10934. Available at SSRN: https://ssrn.com/abstract=625565

Michael W. Brandt (Contact Author)

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

University of Lausanne ( email )

Quartier Chambronne
Lausanne, Vaud CH-1015
Switzerland

Swiss Finance Institute ( email )

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland

Pedro Santa-Clara

New University of Lisbon - Nova School of Business and Economics ( email )

Lisbon
Portugal

HOME PAGE: http://docentes.fe.unl.pt/~psc/

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Centre for Economic Policy Research (CEPR) ( email )

London
United Kingdom

Jonathan R. Stroud

McDonough School of Business, Georgetown University ( email )

3700 O Street NW
Washington, DC 20057
United States

HOME PAGE: http://jonathanrstroud.com

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