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Optimal Rebalancing Strategy Using Dynamic Programming for Institutional Portfolios

25 Pages Posted: 3 Jan 2005  

Walter Sun

MIT EECS; LIDS

Ayres C. Fan

MIT EECS; LIDS

Li-Wei Chen

MIT EECS

Tom Schouwenaars

MIT EECS

Marius A. Albota

MIT EECS

Date Written: December 22, 2004

Abstract

Institutional fund managers generally rebalance using ad hoc methods such as calendar basis or tolerance band triggers. We propose a different framework that quantifies the cost of a rebalancing strategy in terms of risk-adjusted returns net of transaction costs. We then develop an optimal rebalancing strategy that actively seeks to minimize that cost. We use certainty equivalents and the transaction costs associated with a policy to define a cost-to-go function, and we minimize this expected cost-to-go using dynamic programming. We apply Monte Carlo simulations to demonstrate that our method outperforms traditional rebalancing strategies like monthly, quarterly, annual, and 5% tolerance rebalancing. We also show the robustness of our method to model error by performing sensitivity analyses.

Keywords: Optimal portfolio rebalancing, dynamic programming, Monte Carlo simulations

JEL Classification: C15, C61, G11, G23

Suggested Citation

Sun, Walter and Fan, Ayres C. and Chen, Li-Wei and Schouwenaars, Tom and Albota, Marius A., Optimal Rebalancing Strategy Using Dynamic Programming for Institutional Portfolios (December 22, 2004). Available at SSRN: https://ssrn.com/abstract=639284 or http://dx.doi.org/10.2139/ssrn.639284

Walter Sun (Contact Author)

MIT EECS ( email )

77 Massachusetts Avenue
Cambridge, MA 02139-4307
United States

LIDS ( email )

77 Massachusetts Ave
32-D608
Cambridge, MA 02139
United States

Ayres C. Fan

MIT EECS ( email )

77 Massachusetts Ave
Cambridge, MA 02139
United States

LIDS ( email )

77 Massachusetts Ave
32-D608
Cambridge, MA 02139
United States

Li-Wei Chen

MIT EECS ( email )

77 Massachusetts Avenue
Cambridge, MA 02139-4307
United States

Tom Schouwenaars

MIT EECS ( email )

77 Massachusetts Ave
Cambridge, MA 02139
United States

Marius A. Albota

MIT EECS ( email )

77 Massachusetts Avenue
Cambridge, MA 02139-4307
United States

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