Aurora Borealis
31 October 2019 CFA Institute Journal Review

Breadth of Ownership and Stock Excess Returns (Digest summary)

  1. Gregory G. Gocek, CFA

This is a summary of “Breadth of Ownership and Stock Excess Returns,” by Chunpeng Yang and Xiaoyi Hu, published in the Journal of Financial Economics, vol. 66.

Breadth of stock ownership, based on buying and selling trading data from China’s markets, is shown to have a positive and significant effect on stock excess returns derived from standard valuation models. This effect is stable across the size and age of stocks as well as over time.

What Is the Investment Issue?

By defining breadth in a non-traditional way, the authors strive to refine their understanding of the effect of breadth of ownership on the predictability of stock returns.

Previous research concerned with identifying potential valuation metrics has characterized breadth as the number of investors holding long positions in a particular stock. It has been shown as either directly correlated with future returns (in the case of individual stocks) or negatively correlated (in the case of mutual funds) when breadth is accompanied by significant differences in investor sentiment. Thus, findings on breadth’s impact have been somewhat ambiguous.

In contrast, the authors gauge the implications of relative breadth strength by accounting for both buyer- and seller-initiated volume for individual stock breadth. Redefined in this way, breadth of ownership is shown to have a positive, significant, and stable effect on stock excess returns for a variety of stock types and across markets, irrespective of short-selling constraints.

How Did the Authors Conduct This Research?

The analysis begins with the construction of a breadth measure developed from trading data exclusively from China’s stock markets (Shanghai and Shenzhen) in the mainland. They rely on an algorithm to distinguish buyer- and seller-generated stock volume. The sample covers about 2,400 common stocks over the period April 2005–March 2016.

The authors run panel regressions, testing the derived breadth measure against the Fama–French three factors as well as other firm-specific factors (size, age, book-to-market ratio, and turnover rate).

What Are the Findings and Implications for Investors and Investment Professionals?

After all these control variables are considered, breadth retains a positive (about 0.29%) and significant (1% level) effect on monthly excess returns. Comparable results are shown when also controlling for firm size and age, across different samples and different Chinese stock markets (Shanghai and Shenzhen) in the mainland, and with or without short-selling constraints.

This model’s dynamism in tracking trading flows may make it more precise than using the traditional, census-like indicator of the number of long investors. For example, when long investors are only reducing—as opposed to fully exiting—their positions, possible return implications could be overlooked if the aggregate investor count changed very little. This greater model precision may account for the enhanced consistency of the findings; the authors’ results have comparable magnitudes and signs (positive/negative) for the great majority of variables across all model specifications—all with strong statistical significance.

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