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Dispersion and Volatility in Stock Returns: An Empirical Investigation

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  • John Y. Campbell
  • Martin Lettau

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 1962-97 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.

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  • John Y. Campbell & Martin Lettau, 1999. "Dispersion and Volatility in Stock Returns: An Empirical Investigation," NBER Working Papers 7144, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:7144
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    1. 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.
    2. Jess Benhabib & Alberto Bisin & Mi Luo, 2019. "Wealth Distribution and Social Mobility in the US: A Quantitative Approach," American Economic Review, American Economic Association, vol. 109(5), pages 1623-1647, May.
    3. Mustafa Caglayan & Ozge Kandemir Kocaaslan & Kostas Mouratidis, 2017. "Financial Depth and the Asymmetric Impact of Monetary Policy," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(6), pages 1195-1218, December.
    4. Hyun-Han Shin & Rene M. Stulz, 2000. "Firm Value, Risk, and Growth Opportunities," NBER Working Papers 7808, National Bureau of Economic Research, Inc.
    5. 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.
    6. John Y. Campbell & Martin Lettau & Burton G. Malkiel & Yexiao Xu, 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.
    7. Yu, Edison G., 2018. "Dynamic market participation and endogenous information aggregation," Journal of Economic Theory, Elsevier, vol. 175(C), pages 491-517.
    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. Chang, Young Bong & Kwon, YoungOk, 2018. "Ambiguities in valuing information technology firms: Do internet searches help?," Journal of Business Research, Elsevier, vol. 92(C), pages 260-269.
    10. Taiji Harashima, 2004. "A More Realistic Endogenous Time Preference Model and the Slump in Japan," Macroeconomics 0402015, University Library of Munich, Germany, revised 09 Feb 2004.
    11. 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.
    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, University Library of Munich, Germany.
    14. 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.
    15. Gabriel Perez‐Quiros & Allan Timmermann, 2000. "Firm Size and Cyclical Variations in Stock Returns," Journal of Finance, American Finance Association, vol. 55(3), pages 1229-1262, June.
    16. 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.
    17. 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.
    18. Soleman Alsabban & Omar Alarfaj, 2020. "An Empirical Analysis of Behavioral Finance in the Saudi Stock Market: Evidence of Overconfidence Behavior," International Journal of Economics and Financial Issues, Econjournals, vol. 10(1), pages 73-86.
    19. 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.
    20. Shum, Wai Yan, 2020. "Modelling conditional skewness: Heterogeneous beliefs, short sale restrictions and market declines," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).

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    More about this item

    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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