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05 Jul 2006Working Paper Summaries

A Cross-Sectional Analysis of the Excess Comovement of Stock Returns

by Robin Greenwood

This paper develops cross-sectional predictions from a model in which the excess comovement of stock returns comes from correlated demand shocks. The model is tested on 298 Nikkei index stocks and 1,458 non-index stocks for the years 1993 through 2003. The study finds that controlling for index membership, index overweighting is a significant determinant of the comovement of returns with index returns. Key concepts include:

Correlated investor demand for securities causes periodic and widespread mispricing.
Members of arbitrarily weighted stock indexes, oftentimes "liquid" securities, are subject to frequent mispricing.

Author Abstract

In the presence of limits to arbitrage, cross-sectional variation in periodic investor demand should be related to the degree of comovement of returns. I exploit the unusual weighting system of the Nikkei 225 index in Japan to identify cross-sectional variation in periodic demand for index stocks. Relative to their weights in a value weighted index, some stocks in the Nikkei are overweighted by a factor of ten or more. Using overweighting as an instrument for the proportionality between demand shocks for index stocks, I find a strong positive relation between overweighting and the comovement of a stock with other stocks in the index, and a negative relationship between index overweighting and comovement with stocks outside of the index. Put simply, overweighted stocks have high betas. The results suggest that excess comovement of stock returns is a consequence of an institutionalized commonality in trading behavior, rather than inefficiencies related to the speed at which index stocks incorporate economy-wide information.

Paper Information

Full Working Paper Text
Working Paper Publication Date: April 2005
HBS Working Paper Number: 05-069
Faculty Unit(s): Finance

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Robin Greenwood

Robin Greenwood

George Gund Professor of Finance and Banking
Unit Head, Finance

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