Optimal Rebalancing Strategy Using Dynamic Programming for Institutional Portfolios
25 Pages Posted: 3 Jan 2005
Date Written: December 22, 2004
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: Suggested Citation