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Beta herding through overconfidence: A behavioral explanation of the low-beta anomaly

Last Updated on 10 February, 2024 by Rejaul Karim

Beta herding through overconfidence: A behavioral explanation of the low-beta anomaly” by Soosung Hwang, Alexandre Rubesam, and Mark Salmon investigates asset returns using the concept of beta herding, which measures cross-sectional variations in betas due to changes in investors’ confidence about their market outlook.

Overconfidence causes beta herding (compression of betas towards the market beta), while under-confidence leads to adverse beta herding (dispersion of betas from the market beta). The study shows that the low-beta anomaly can be explained by return reversal following adverse beta herding, as high beta stocks underperform low beta stocks exclusively following periods of adverse beta herding.

This result is robust to investors’ preferences for lottery-like assets, sentiment, and return reversals, and beta herding leads time variation in betas.

Abstract Of Paper

We investigate asset returns using the concept of beta herding, which measures cross-sectional variations in betas due to changes in investors’ confidence about their market outlook. Overconfidence causes beta herding (compression of betas towards the market beta), while under-confidence leads to adverse beta herding (dispersion of betas from the market beta). We show that the low-beta anomaly can be explained by return reversal following adverse beta herding, as high beta stocks underperform low beta stocks exclusively following periods of adverse beta herding. This result is robust to investors’ preferences for lottery-like assets, sentiment, and return reversals, and beta herding leads time variation in betas.

Original paper – Download PDF

Here you can download the PDF and original paper of Beta herding through overconfidence: A behavioral explanation of the low-beta anomaly.

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Author

Soosung Hwang
Sungkyunkwan University – Department of Economics

Alexandre Rubesam
IESEG School of Management; French National Center for Scientific Research (CNRS) – Lille Economie & Management (LEM) UMR 9221

Mark Salmon
University of Cambridge – Faculty of Economics and Politics

Conclusion

In conclusion, the research by Hwang, Rubesam, and Salmon provides a compelling behavioral perspective on the low-beta anomaly, shedding light on the intricate dynamics of beta herding and its profound impact on asset returns.

Their investigation into the interplay between investors’ confidence levels, overconfidence, and adverse beta herding has unveiled an underlying mechanism that elucidates return reversal patterns following periods of adverse beta herding. This robust linkage not only lends insight into the ascendancy of the low-beta anomaly but also underscores the significance of under-confidence in driving the dispersion of betas from the market beta.

The study’s findings underscore the role of beta herding in instigating time-varying variations in betas, demonstrating the pervasive influence of investors’ behavioral biases on asset return dynamics.

As such, this research offers a compelling behavioral explanation for the low-beta anomaly, promoting a deeper understanding of how overconfidence and under-confidence can shape asset returns through beta herding dynamics.

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FAQ

What is the main focus of the research on “Beta herding through overconfidence: A behavioral explanation of the low-beta anomaly”?

The main focus of the research is to investigate asset returns using the concept of beta herding, which captures cross-sectional variations in betas resulting from changes in investors’ confidence about their market outlook. The study explores the impact of overconfidence and under-confidence on beta herding dynamics and their connection to the low-beta anomaly.

How does the research define and measure beta herding?

Beta herding is defined in the research as cross-sectional variations in betas due to changes in investors’ confidence. Overconfidence is associated with beta herding, leading to a compression of betas towards the market beta, while under-confidence is linked to adverse beta herding, resulting in the dispersion of betas from the market beta. The study measures beta herding by examining how variations in investor confidence influence the clustering or dispersion of betas.

What is the relationship between overconfidence, adverse beta herding, and the low-beta anomaly?

The research establishes a relationship between overconfidence, adverse beta herding, and the low-beta anomaly. Overconfidence is linked to beta herding, which leads to the compression of betas towards the market beta. Adverse beta herding, associated with under-confidence, results in the dispersion of betas from the market beta. The study demonstrates that the low-beta anomaly can be explained by return reversal following adverse beta herding, where high beta stocks underperform low beta stocks specifically after periods of adverse beta herding.

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