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The mean–variance relation: A 24-hour story

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  • Wang, Wenzhao

Abstract

This paper investigates the mean–variance relation during different time periods within trading days. We reveal that there is a positive mean–variance relation when the stock market is closed (i.e., overnight), but the positive relation is distorted when the market is open (i.e., intraday). The evidence offers a new explanation for the weak risk-return tradeoff in stock markets.

Suggested Citation

  • Wang, Wenzhao, 2021. "The mean–variance relation: A 24-hour story," Economics Letters, Elsevier, vol. 208(C).
    • Handle: RePEc:eee:ecolet:v:208:y:2021:i:c:s016517652100330x
    DOI: 10.1016/j.econlet.2021.110053
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    References listed on IDEAS

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    1. Harvey, Campbell R., 2001. "The specification of conditional expectations," Journal of Empirical Finance, Elsevier, vol. 8(5), pages 573-637, December.
    2. Turner, Christopher M. & Startz, Richard & Nelson, Charles R., 1989. "A Markov model of heteroskedasticity, risk, and learning in the stock market," Journal of Financial Economics, Elsevier, vol. 25(1), pages 3-22, November.
    3. Ľuboš Pástor & Meenakshi Sinha & Bhaskaran Swaminathan, 2008. "Estimating the Intertemporal Risk–Return Tradeoff Using the Implied Cost of Capital," Journal of Finance, American Finance Association, vol. 63(6), pages 2859-2897, December.
    4. Lou, Dong & Polk, Christopher & Skouras, Spyros, 2019. "A tug of war: Overnight versus intraday expected returns," Journal of Financial Economics, Elsevier, vol. 134(1), pages 192-213.
    5. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2005. "There is a risk-return trade-off after all," Journal of Financial Economics, Elsevier, vol. 76(3), pages 509-548, June.
    6. Campbell, John Y., 1987. "Stock returns and the term structure," Journal of Financial Economics, Elsevier, vol. 18(2), pages 373-399, June.
    7. French, Kenneth R. & Schwert, G. William & Stambaugh, Robert F., 1987. "Expected stock returns and volatility," Journal of Financial Economics, Elsevier, vol. 19(1), pages 3-29, September.
    8. Hendershott, Terrence & Livdan, Dmitry & Rösch, Dominik, 2020. "Asset pricing: A tale of night and day," Journal of Financial Economics, Elsevier, vol. 138(3), pages 635-662.
    9. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    10. Aboody, David & Even-Tov, Omri & Lehavy, Reuven & Trueman, Brett, 2018. "Overnight Returns and Firm-Specific Investor Sentiment," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(2), pages 485-505, April.
    11. Robert Engle, 2001. "GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 157-168, Fall.
    12. Brandt, Michael W. & Kang, Qiang, 2004. "On the relationship between the conditional mean and volatility of stock returns: A latent VAR approach," Journal of Financial Economics, Elsevier, vol. 72(2), pages 217-257, May.
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    More about this item

    Keywords

    Mean–variance relation; Overnight return; Risk-return tradeoff;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets

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