Is Fixed-Weight Asset Allocation Really Better?

Abstract

In this article, the authors compare the performance of two long–term fixed–weight asset allocation models with two dynamic models—one based on historical data and one based in part on analysts9 forecasts. They find that fixed–weight asset allocation outperformed a dynamic approach that used only historical data. They also include a comparison of the performance of the asset allocation recommendations of eight Wall Street brokerage firms and a “Robot Blend.” Four of the eight firms nominally outperformed the Robot Blend after transaction costs, confirming the random chance prediction. The dynamic asset allocation model that used analysts9 forecasts outperformed all other models. This result is robust to the application of reasonable constraints to the dynamic models. The authors suggest that dynamic asset allocation models probably will not outperform fixed–weight asset allocation unless they employ superior analyst judgment. In their data, a static 60/30/10 mix of stocks, bonds, and cash appears to be an attractive long–term choice.

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