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Why Has Idiosyncratic Risk Been Historically Low in Recent Years?

Author

Listed:
  • Bartram, Sohnke M.

    (University of Warwick)

  • Brown, Gregory W.

    (University of North Carolina)

  • Stulz, Rene M.

    (Ohio State University)

Abstract

Since 1965, average idiosyncratic risk (IR) has never been lower than in recent years. In contrast to the high IR in the late 1990s that has drawn considerable attention in the literature, average market-model IR is 44% lower in 2013-2017 than in 1996-2000. Macroeconomic variables help explain why IR is lower, but using only macroeconomic variables leads to large prediction errors compared to using only firm-level variables. As a result of the dramatic change in the number and composition of listed firms since the late 1990s, listed firms are larger and older. Larger and older firms have lower idiosyncratic risk. Models that use firm characteristics to predict firm-level idiosyncratic risk estimated over 1963-2012 can largely or completely explain why IR is low over 2013-2017. The same changes that bring about historically low IR lead to unusually high market-model R-squareds.

Suggested Citation

  • Bartram, Sohnke M. & Brown, Gregory W. & Stulz, Rene M., 2018. "Why Has Idiosyncratic Risk Been Historically Low in Recent Years?," Working Paper Series 2018-02, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    • Handle: RePEc:ecl:ohidic:2018-02
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    Cited by:

    1. Beaver, William H. & McNichols, Maureen F. & Wang, Zach Z., 2020. "Increased market response to earnings announcements in the 21st century: An Empirical Investigation," Journal of Accounting and Economics, Elsevier, vol. 69(1).
    2. Everett Grant & Julieta Yung, 2019. "Upstream, Downstream & Common Firm Shocks," Globalization Institute Working Papers 360, Federal Reserve Bank of Dallas.
    3. Shuai Shao & Robert Stoumbos & X. Frank Zhang, 2021. "The power of firm fundamental information in explaining stock returns," Review of Accounting Studies, Springer, vol. 26(4), pages 1249-1289, December.
    4. Perera, Kasun & Kuruppuarachchi, Duminda & Kumarasinghe, Sriyalatha & Suleman, Muhammad Tahir, 2023. "The impact of carbon disclosure and carbon emissions intensity on firms' idiosyncratic volatility," Energy Economics, Elsevier, vol. 128(C).
    5. Ray Ball & Gil Sadka & Ayung Tseng, 2022. "Using accounting earnings and aggregate economic indicators to estimate firm-level systematic risk," Review of Accounting Studies, Springer, vol. 27(2), pages 607-646, June.
    6. Karen X. Yan & Qi Li, 2018. "Nonparametric Estimation of a Conditional Quantile Function in a Fixed Effects Panel Data Model," JRFM, MDPI, vol. 11(3), pages 1-10, August.

    More about this item

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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