Evaluating Portfolio Policies: A Duality Approach

26 Pages Posted: 22 Jul 2003

See all articles by Martin B. Haugh

Martin B. Haugh

Imperial College Business School

Leonid Kogan

Massachusetts Institute of Technology (MIT) - Sloan School of Management; National Bureau of Economic Research (NBER)

Jiang Wang

Massachusetts Institute of Technology (MIT) - Sloan School of Management; China Academy of Financial Research (CAFR); National Bureau of Economic Research (NBER)

Multiple version iconThere are 2 versions of this paper

Date Written: July 2003

Abstract

The performance of a given portfolio policy can in principle be evaluated by comparing its expected utility with that of the optimal policy. Unfortunately, the optimal policy is usually not computable in which case a direct comparison is impossible. In this paper we solve this problem by using the given portfolio policy to construct an upper bound on the unknown maximum expected utility. This construction is based on a dual formulation of the portfolio optimization problem. When the upper bound is close to the expected utility achieved by the given portfolio policy, the potential utility loss of this policy is guaranteed to be small. Our algorithm can be used to evaluate portfolio policies in models with incomplete markets and position constraints. We illustrate our methodology by analyzing the static and myopic policies in markets with return predictability and constraints on short sales and borrowing.

Keywords: Portfolio Choice, Duality, Dynamic Programming, Constraints, Monte Carlo, Simulation

JEL Classification: G11, C63

Suggested Citation

Haugh, Martin B. and Kogan, Leonid and Wang, Jiang, Evaluating Portfolio Policies: A Duality Approach (July 2003). MIT Sloan Working Paper No. 4329-03, Available at SSRN: https://ssrn.com/abstract=423020 or http://dx.doi.org/10.2139/ssrn.423020

Martin B. Haugh

Imperial College Business School ( email )

South Kensington Campus
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Leonid Kogan (Contact Author)

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

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National Bureau of Economic Research (NBER)

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Jiang Wang

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

E62-614
100 Main Street
Cambridge, MA 02142
United States
617-253-2632 (Phone)
617-258-6855 (Fax)

China Academy of Financial Research (CAFR) ( email )

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Shanghai P.R.China, 200030
China

National Bureau of Economic Research (NBER) ( email )

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Cambridge, MA 02138
United States

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