Optimal Rebalancing for Institutional Portfolios

摘要

Institutional fund managers generally rebalance using ad hoc methods such as calendar periods or tolerance band triggers. Another approach is to quantify the cost of a rebalancing strategy in terms of risk-adjusted returns net of transaction costs. An optimal rebalancing strategy that actively seeks to minimize that cost uses certainty-equivalents and the transaction costs associated with a policy to define a cost-to-go function. Stochastic programming is then used to minimize expected cost-to-go. Monte Carlo simulations demonstrate that the method outperforms traditional rebalancing strategies such as periodic and 5% tolerance rebalancing.