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The long-run relationship between stock return dispersion and output

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  • Ghassem A. Homaifar
  • Jonathan Adongo
  • Kevin M. Zhao

Abstract

Based on the rational that some industry groups are more closely linked to the business cycle than others, we re-examined a previous analysis on the long-term relationship between stock return dispersion by industry and Gross Domestic Product (GDP), which evaluated data until 1987 by extending it to 2008. Using Mean Square Forecast Errors (MSFE) statistics, we find that incorporating the return dispersion in Vector Autoregressive (VAR) models enhances their forecasting power for output (GDP) in the long run. This article also determines that the relationship between stock return dispersion by industry and GDP is tenuous in the recent decade from 1999.

Suggested Citation

  • Ghassem A. Homaifar & Jonathan Adongo & Kevin M. Zhao, 2013. "The long-run relationship between stock return dispersion and output," Applied Economics, Taylor & Francis Journals, vol. 45(7), pages 943-952, March.
    • Handle: RePEc:taf:applec:45:y:2013:i:7:p:943-952
    DOI: 10.1080/00036846.2011.613792
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    References listed on IDEAS

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    Cited by:

    1. Roman Horvath, 2012. "Do Confidence Indicators Help Predict Economic Activity? The Case of the Czech Republic," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 62(5), pages 398-412, November.
    2. Anindita Bhattacharjee & Monomita Nandy & Suman Lodh, 2025. "COVID-19 and persistence in the stock market: a study on a leading emerging market," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 22(2), pages 520-531, June.

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