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Asymmetric cross-sectional dispersion in stock returns: evidence and implications

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  • Gregory R. Duffee

Abstract

This paper documents that daily stock returns of both firms and industries are more dispersed when the overall stock market rises than when it falls. This positive relation is conceptually distinct from - and appears unrelated to - asymmetric return correlations. I argue that the source of the relation is positive skewness in sector-specific return shocks. I use this asymmetric behavior to explain a previously-observed puzzle: aggregate trading volume tends to be higher on days when the stock market rises than when it falls. The idea proposed here is that trading is more active on days when the market rises because on those days there is more non-market news on which to trade. I find that empirically, the bulk of the relation between volume and the signed market return is explained by variations in non-market volatility.

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  • Gregory R. Duffee, 2001. "Asymmetric cross-sectional dispersion in stock returns: evidence and implications," Working Paper Series 2000-18, Federal Reserve Bank of San Francisco.
  • Handle: RePEc:fip:fedfwp:2000-18
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    References listed on IDEAS

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    Cited by:

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    2. Das, Sonali & Demirer, Riza & Gupta, Rangan & Mangisa, Siphumlile, 2019. "The effect of global crises on stock market correlations: Evidence from scalar regressions via functional data analysis," Structural Change and Economic Dynamics, Elsevier, vol. 50(C), pages 132-147.
    3. Ren, Boru & Lucey, Brian, 2023. "Herding in the Chinese renewable energy market: Evidence from a bootstrapping time-varying coefficient autoregressive model," Energy Economics, Elsevier, vol. 119(C).
    4. Ozcan Ceylan, 2015. "Limited information-processing capacity and asymmetric stock correlations," Quantitative Finance, Taylor & Francis Journals, vol. 15(6), pages 1031-1039, June.
    5. Rıza Demirer & Shrikant P. Jategaonkar, 2013. "The conditional relation between dispersion and return," Review of Financial Economics, John Wiley & Sons, vol. 22(3), pages 125-134, September.
    6. Susan Sunila Sharma & Paresh Narayan & Kannan Thuraisamy, 2015. "Time-Varying Herding Behavior, Global Financial Crisis, and the Chinese Stock Market," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 18(02), pages 1-31.
    7. Economou, Fotini & Katsikas, Epameinondas & Vickers, Gregory, 2016. "Testing for herding in the Athens Stock Exchange during the crisis period," Finance Research Letters, Elsevier, vol. 18(C), pages 334-341.
    8. Riza Demirer & Rangan Gupta & Zhihui Lv & Wing-Keung Wong, 2019. "Equity Return Dispersion and Stock Market Volatility: Evidence from Multivariate Linear and Nonlinear Causality Tests," Sustainability, MDPI, vol. 11(2), pages 1-15, January.
    9. Thomas Chiang & Lin Tan & Jiandong Li & Edward Nelling, 2013. "Dynamic Herding Behavior in Pacific-Basin Markets: Evidence and Implications," Multinational Finance Journal, Multinational Finance Journal, vol. 17(3-4), pages 165-200, September.
    10. Fei, Tianlun & Liu, Xiaoquan & Wen, Conghua, 2019. "Cross-sectional return dispersion and volatility prediction," Pacific-Basin Finance Journal, Elsevier, vol. 58(C).

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