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Origins of Mutual Fund Skill: Market versus Accounting Based Asset Pricing Anomalies

Author

Listed:
  • Charlotte Christiansen

    (Aarhus University and CREATES and DFI and Lund University)

  • Ran Xing

    (Aarhus University and DFI)

  • Yue Xu

    (Aarhus University and CREATES)

Abstract

We investigate the information source of active U.S. equity mutual funds’ value added using 234 public asset pricing anomalies. On average, mutual funds add value through their positive exposures to anomalies based on market information (e.g., momentum and liquidity risk) and lose value through their negative exposures to anomalies based on accounting information of firm fundamentals (e.g., investment and profitability), corroborating that both the semi-strong and weak forms of the efficient market hypothesis do not hold. We also find weak evidence that mutual funds profit from their private information, supporting the rejection of the strong form efficient market hypothesis.

Suggested Citation

  • Charlotte Christiansen & Ran Xing & Yue Xu, 2020. "Origins of Mutual Fund Skill: Market versus Accounting Based Asset Pricing Anomalies," CREATES Research Papers 2020-14, Department of Economics and Business Economics, Aarhus University.
    • Handle: RePEc:aah:create:2020-14
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    File URL: https://repec.econ.au.dk/repec/creates/rp/20/rp20_14.pdf
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    References listed on IDEAS

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    1. Judith Chevalier & Glenn Ellison, 1999. "Are Some Mutual Fund Managers Better Than Others? Cross‐Sectional Patterns in Behavior and Performance," Journal of Finance, American Finance Association, vol. 54(3), pages 875-899, June.
    2. Acharya, Viral V. & Pedersen, Lasse Heje, 2005. "Asset pricing with liquidity risk," Journal of Financial Economics, Elsevier, vol. 77(2), pages 375-410, August.
    3. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    4. Pástor, Ľuboš & Stambaugh, Robert F. & Taylor, Lucian A., 2015. "Scale and skill in active management," Journal of Financial Economics, Elsevier, vol. 116(1), pages 23-45.
    5. Paul Calluzzo & Fabio Moneta & Selim Topaloglu, 2019. "When Anomalies Are Publicized Broadly, Do Institutions Trade Accordingly?," Management Science, INFORMS, vol. 65(10), pages 4555-4574, October.
    6. David Hirshleifer & Kewei Hou & Siew Hong Teoh, 2012. "The Accrual Anomaly: Risk or Mispricing?," Management Science, INFORMS, vol. 58(2), pages 320-335, February.
    7. Edelen, Roger M. & Ince, Ozgur S. & Kadlec, Gregory B., 2016. "Institutional investors and stock return anomalies," Journal of Financial Economics, Elsevier, vol. 119(3), pages 472-488.
    8. Zhi Da & Pengjie Gao & Ravi Jagannathan, 2011. "Impatient Trading, Liquidity Provision, and Stock Selection by Mutual Funds," The Review of Financial Studies, Society for Financial Studies, vol. 24(3), pages 675-720.
    9. Andrea Frazzini, 2006. "The Disposition Effect and Underreaction to News," Journal of Finance, American Finance Association, vol. 61(4), pages 2017-2046, August.
    10. Joseph Chen & Samuel Hanson & Harrison Hong & Jeremy C. Stein, 2008. "Do Hedge Funds Profit From Mutual-Fund Distress?," NBER Working Papers 13786, National Bureau of Economic Research, Inc.
    11. Nicolae Gârleanu & Lasse Heje Pedersen, 2018. "Efficiently Inefficient Markets for Assets and Asset Management," Journal of Finance, American Finance Association, vol. 73(4), pages 1663-1712, August.
    12. Marcin Kacperczyk & Stijn Van Nieuwerburgh & Laura Veldkamp, 2014. "Time-Varying Fund Manager Skill," Journal of Finance, American Finance Association, vol. 69(4), pages 1455-1484, August.
    13. JONATHAN B. BERK & JULES H. van BINSBERGEN & BINYING LIU, 2017. "Matching Capital and Labor," Journal of Finance, American Finance Association, vol. 72(6), pages 2467-2504, December.
    14. Berk, Jonathan B. & van Binsbergen, Jules H., 2015. "Measuring skill in the mutual fund industry," Journal of Financial Economics, Elsevier, vol. 118(1), pages 1-20.
    15. Jonathan B. Berk & Richard C. Green, 2004. "Mutual Fund Flows and Performance in Rational Markets," Journal of Political Economy, University of Chicago Press, vol. 112(6), pages 1269-1295, December.
    16. Russ Wermers, 1999. "Mutual Fund Herding and the Impact on Stock Prices," Journal of Finance, American Finance Association, vol. 54(2), pages 581-622, April.
    17. Coval, Joshua & Stafford, Erik, 2007. "Asset fire sales (and purchases) in equity markets," Journal of Financial Economics, Elsevier, vol. 86(2), pages 479-512, November.
    18. repec:oup:rfinst:v:25:y::i:12:p:3457-3489 is not listed on IDEAS
    19. Xi Dong & Shu Feng & Ronnie Sadka, 2019. "Liquidity Risk and Mutual Fund Performance," Management Science, INFORMS, vol. 65(3), pages 1020-1041, March.
    20. Nikolai Roussanov & Hongxun Ruan & Yanhao Wei & Stijn Van Nieuwerburgh, 2021. "Marketing Mutual Funds," The Review of Financial Studies, Society for Financial Studies, vol. 34(6), pages 3045-3094.
    21. Robert Novy-Marx & Mihail Velikov, 2016. "A Taxonomy of Anomalies and Their Trading Costs," The Review of Financial Studies, Society for Financial Studies, vol. 29(1), pages 104-147.
    22. Marcin Kacperczyk & Clemens Sialm & Lu Zheng, 2008. "Unobserved Actions of Mutual Funds," The Review of Financial Studies, Society for Financial Studies, vol. 21(6), pages 2379-2416, November.
    23. repec:bla:jfinan:v:55:y:2000:i:4:p:1655-1703 is not listed on IDEAS
    24. James A. Bennett, 2003. "Greener Pastures and the Impact of Dynamic Institutional Preferences," The Review of Financial Studies, Society for Financial Studies, vol. 16(4), pages 1203-1238.
    25. Marcin Kacperczyk & Amit Seru, 2007. "Fund Manager Use of Public Information: New Evidence on Managerial Skills," Journal of Finance, American Finance Association, vol. 62(2), pages 485-528, April.
    26. Martijn Cremers & Antti Petajisto, 2006. "How Active is Your Fund Manager? A New Measure That Predicts Performance," Yale School of Management Working Papers amz2370, Yale School of Management, revised 01 May 2009.
    27. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    28. Marcin Kacperczyk & Clemens Sialm & Lu Zheng, 2005. "On the Industry Concentration of Actively Managed Equity Mutual Funds," Journal of Finance, American Finance Association, vol. 60(4), pages 1983-2011, August.
    29. Ashiq Ali & Xuanjuan Chen & Tong Yao & Tong Yu, 2008. "Do Mutual Funds Profit from the Accruals Anomaly?," Journal of Accounting Research, Wiley Blackwell, vol. 46(1), pages 1-26, March.
    30. Azi Ben-Rephael & Zhi Da & Ryan D. Israelsen, 2017. "It Depends on Where You Search: Institutional Investor Attention and Underreaction to News," The Review of Financial Studies, Society for Financial Studies, vol. 30(9), pages 3009-3047.
    31. Russ Wermers, 2000. "Mutual Fund Performance: An Empirical Decomposition into Stock‐Picking Talent, Style, Transactions Costs, and Expenses," Journal of Finance, American Finance Association, vol. 55(4), pages 1655-1695, August.
    32. Parrino, Robert & Sias, Richard W. & Starks, Laura T., 2003. "Voting with their feet: institutional ownership changes around forced CEO turnover," Journal of Financial Economics, Elsevier, vol. 68(1), pages 3-46, April.
    33. Dong Lou, 2012. "A Flow-Based Explanation for Return Predictability," The Review of Financial Studies, Society for Financial Studies, vol. 25(12), pages 3457-3489.
    34. Lewellen, Jonathan, 2011. "Institutional investors and the limits of arbitrage," Journal of Financial Economics, Elsevier, vol. 102(1), pages 62-80, October.
    35. Grinblatt, Mark & Titman, Sheridan & Wermers, Russ, 1995. "Momentum Investment Strategies, Portfolio Performance, and Herding: A Study of Mutual Fund Behavior," American Economic Review, American Economic Association, vol. 85(5), pages 1088-1105, December.
    36. Eugene F. Fama & Kenneth R. French, 2008. "Dissecting Anomalies," Journal of Finance, American Finance Association, vol. 63(4), pages 1653-1678, August.
    37. John R. Nofsinger & Richard W. Sias, 1999. "Herding and Feedback Trading by Institutional and Individual Investors," Journal of Finance, American Finance Association, vol. 54(6), pages 2263-2295, December.
    38. Akbas, Ferhat & Armstrong, Will J. & Sorescu, Sorin & Subrahmanyam, Avanidhar, 2015. "Smart money, dumb money, and capital market anomalies," Journal of Financial Economics, Elsevier, vol. 118(2), pages 355-382.
    39. Eugene F. Fama & Kenneth R. French, 2010. "Luck versus Skill in the Cross‐Section of Mutual Fund Returns," Journal of Finance, American Finance Association, vol. 65(5), pages 1915-1947, October.
    40. Clifford S. Asness & Tobias J. Moskowitz & Lasse Heje Pedersen, 2013. "Value and Momentum Everywhere," Journal of Finance, American Finance Association, vol. 68(3), pages 929-985, June.
    41. Russell Jame, 2018. "Liquidity Provision and the Cross Section of Hedge Fund Returns," Management Science, INFORMS, vol. 64(7), pages 3288-3312, July.
    42. S.G. Badrinath & Sunil Wahal, 2002. "Momentum Trading by Institutions," Journal of Finance, American Finance Association, vol. 57(6), pages 2449-2478, December.
    43. K. J. Martijn Cremers & Antti Petajisto, 2009. "How Active Is Your Fund Manager? A New Measure That Predicts Performance," The Review of Financial Studies, Society for Financial Studies, vol. 22(9), pages 3329-3365, September.
    44. Jacobs, Heiko & Müller, Sebastian, 2020. "Anomalies across the globe: Once public, no longer existent?," Journal of Financial Economics, Elsevier, vol. 135(1), pages 213-230.
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    More about this item

    Keywords

    Mutual funds; Anomalies; Value added; Public information; Investment decisions;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

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