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Dispersion and Volatility in Stock Returns: An Empirical Investigation

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  • Campbell, John Y
  • Kim, Sangjoon
  • Lettau, Martin

Abstract

This paper studies three different measures of monthly stock market volatility: the time-series volatility of daily market returns within the month; the cross-sectional volatility or ‘dispersion’ of daily returns on industry portfolios, relative to the market, within the month; and the dispersion of daily returns on individual firms, relative to their industries, within the month. Over the period 1962–95 there has been a noticeable increase in firm-level volatility relative to market volatility. All the volatility measures move together in a countercyclical fashion. While market volatility tends to lead the other volatility series, industry-level volatility is a particularly important leading indicator for the business cycle.

Suggested Citation

  • Campbell, John Y & Kim, Sangjoon & Lettau, Martin, 1998. "Dispersion and Volatility in Stock Returns: An Empirical Investigation," CEPR Discussion Papers 1923, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:1923
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    References listed on IDEAS

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    Cited by:

    1. Andreou, Elena & Ghysels, Eric, 2002. "Rolling-Sample Volatility Estimators: Some New Theoretical, Simulation, and Empirical Results," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 363-376, July.
    2. Campbell, John Y & Kim, Sangjoon & Lettau, Martin, 1998. "Dispersion and Volatility in Stock Returns: An Empirical Investigation," CEPR Discussion Papers 1923, C.E.P.R. Discussion Papers.
    3. Hyun-Han Shin & Rene M. Stulz, 2000. "Firm Value, Risk, and Growth Opportunities," NBER Working Papers 7808, National Bureau of Economic Research, Inc.
    4. Renatas Kizys & Peter Spencer, 2007. "Assessing the Relation between Equity Risk Premia and Macroeconomic Volatilities," Money Macro and Finance (MMF) Research Group Conference 2006 140, Money Macro and Finance Research Group.
    5. John Y. Campbell, 2001. "Have Individual Stocks Become More Volatile? An Empirical Exploration of Idiosyncratic Risk," Journal of Finance, American Finance Association, vol. 56(1), pages 1-43, February.
    6. Beaulieu, Marie-claude & Cosset, Jean-Claude & Essaddam, Naceur, 2002. "The Impact of Political Risk on the Volatility of Stock Returns: the Case of Canada," Cahiers de recherche 0208, CIRPEE.
    7. Li, Tao, 2007. "Heterogeneous beliefs, asset prices, and volatility in a pure exchange economy," Journal of Economic Dynamics and Control, Elsevier, vol. 31(5), pages 1697-1727, May.
    8. Dunbar, Geoffrey, 2013. "Returns-to-scale and the equity premium puzzle," Journal of Economic Dynamics and Control, Elsevier, vol. 37(9), pages 1736-1754.
    9. Taiji Harashima, 2004. "A More Realistic Endogenous Time Preference Model and the Slump in Japan," Macroeconomics 0402015, EconWPA, revised 09 Feb 2004.
    10. Mustafa Caglayan & Ozge Kandemir Kocaaslan & Kostas Mouratidis, 2013. "The Role of Financial Depth on the Asymmetric Impact of Monetary Policy," Working Papers 2013007, The University of Sheffield, Department of Economics.
    11. Fedorov, Pavel & Sarkissian, Sergei, 2000. "Cross-sectional variations in the degree of global integration: the case of Russian equities," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 10(2), pages 131-150, June.
    12. Hogan, Thomas L., 2015. "Capital and risk in commercial banking: A comparison of capital and risk-based capital ratios," The Quarterly Review of Economics and Finance, Elsevier, vol. 57(C), pages 32-45.
    13. Taiji Harashima, 2004. "The Bad Government: A Source of Uncertainty and Business Fluctuations," Microeconomics 0407010, EconWPA.

    More about this item

    Keywords

    Business Cycles; dispersion; Volatility;

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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