When to Pick the Losers: Do Sentiment Indicators Improve Dynamic Asset Allocation?
Authors : Devraj Basu EDHEC Business School
Chi-Hsiou Hun Durham Business School, University of Durham
Roel Oomen Warwick Business School, University of Warwick
Alexander Stremme Warwick Business School, University of Warwick
Recent finance research that draws on behavioral psychology suggests that investors systematically make errors in forming expectations about asset returns.
These errors are likely to cause significant mis-pricing in the short run, and the subsequent reversion of prices to their fundamental level implies that measures of investor sentiment are likely to be correlated with stock returns. A number of empirical studies using both market and survey data as proxies for investor sentiment have found support for this hypothesis. In this paper we investigate whether investor sentiment (as measured by certain components of the University of Michigan survey) can help improve dynamic asset allocation over and above the improvement achieved based on commonly used business cycle indicators. We find that the addition of sentiment variables to business cycle indicators considerably improves the performance of dynamically managed portfolio strategies, both for a standard market-timer as well as for a momentum investor. For example, sentiment-based dynamic trading strategies, even out-of-sample, would not have incurred any significant losses during the October 1987 crash or the collapse of the dot.com bubble in late 2000. In contrast, standard business cycle indicators fail to predict these events, so that investors relying on these variables alone would have incurred substantial losses. However, our strategies do not simply follow market sentiment, but instead systematically exploit investor over-reaction. They are active alpha strategies with low betas and high alphas, in contrast to business cycle based strategieswhich are effectively index-trackers with high betas and considerably lower alphas.
Created on October 2, 2006
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