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Assessing the performance of mutual funds with multifactor asset pricing models

Author

Listed:
  • Artur A. Trzebiński

    (Wroclaw University of Economics and Business)

Abstract

The subject of the article is assessing the performance of mutual funds. The main goal of the study is to indicate which multifactor asset pricing model fits the performance of the Polish mutual funds the best. Another objective is to examine the impact of risk factors on the excess returns of the Polish mutual funds. In the study, Carhart’s model and the three-, five- and six-factor Fama and French models were used. The main outcomes are as follows: (1) the Fama and French six-factor model best explains the performance of Polish equity mutual funds, (2) the size factor and the profitability factor has a positive, significant impact and the investment factor has a negative, significant impact on mutual funds’ performance, (3) the momentum factor delivers insignificant alpha and the value factor is associated with an insignificant and negative alpha.

Suggested Citation

  • Artur A. Trzebiński, 2022. "Assessing the performance of mutual funds with multifactor asset pricing models," Bank i Kredyt, Narodowy Bank Polski, vol. 53(1), pages 79-106.
  • Handle: RePEc:nbp:nbpbik:v:53:y:2022:i:1:p:79-106
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    References listed on IDEAS

    as
    1. Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    2. Adam Zaremba & Anna Czapkiewicz & Jan Jakub Szczygielski & Vitaly Kaganov, 2019. "An Application of Factor Pricing Models to the Polish Stock Market," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(9), pages 2039-2056, July.
    3. 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.
    4. Ali M. Kutan & Hai Lin & Ping-Wen Sun & Bin Yu, 2020. "A reliable performance measure to differentiate China’s actively managed open-end equity mutual funds," Applied Economics, Taylor & Francis Journals, vol. 50(52), pages 5592-5603, June.
    5. Lischewski, Judith & Voronkova, Svitlana, 2012. "Size, value and liquidity. Do They Really Matter on an Emerging Stock Market?," Emerging Markets Review, Elsevier, vol. 13(1), pages 8-25.
    6. Pastor, Lubos & Stambaugh, Robert F., 2002. "Investing in equity mutual funds," Journal of Financial Economics, Elsevier, vol. 63(3), pages 351-380, March.
    7. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    8. Adams, John C. & Nishikawa, Takeshi & Rao, Ramesh P., 2018. "Mutual fund performance, management teams, and boards," Journal of Banking & Finance, Elsevier, vol. 92(C), pages 358-368.
    9. Angelidis, Timotheos & Giamouridis, Daniel & Tessaromatis, Nikolaos, 2013. "Revisiting mutual fund performance evaluation," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1759-1776.
    10. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    11. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    12. Gibbons, Michael R & Ross, Stephen A & Shanken, Jay, 1989. "A Test of the Efficiency of a Given Portfolio," Econometrica, Econometric Society, vol. 57(5), pages 1121-1152, September.
    13. Mateus, Irina B. & Mateus, Cesario & Todorovic, Natasa, 2019. "Review of new trends in the literature on factor models and mutual fund performance," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 344-354.
    14. Bialkowski, Jedrzej & Otten, Roger, 2011. "Emerging market mutual fund performance: Evidence for Poland," The North American Journal of Economics and Finance, Elsevier, vol. 22(2), pages 118-130, August.
    15. Francisco Barillas & Jay Shanken, 2018. "Comparing Asset Pricing Models," Journal of Finance, American Finance Association, vol. 73(2), pages 715-754, April.
    16. Hiraki, Takato & Liu, Ming, 2021. "Do global equity mutual funds exhibit home bias?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 31(C).
    17. Narasimhan Jegadeesh & Sheridan Titman, 2001. "Profitability of Momentum Strategies: An Evaluation of Alternative Explanations," Journal of Finance, American Finance Association, vol. 56(2), pages 699-720, April.
    18. Philipp Dirkx & Franziska J. Peter, 2020. "The Fama-French Five-Factor Model Plus Momentum: Evidence for the German Market," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 72(4), pages 661-684, October.
    19. Sanjay Sehgal & Sonal Babbar, 2017. "Evaluating alternative performance benchmarks for Indian mutual fund industry," Journal of Advances in Management Research, Emerald Group Publishing Limited, vol. 14(2), pages 222-250, May.
    20. Ick Jin, 2018. "Is ESG a systematic risk factor for US equity mutual funds?," Journal of Sustainable Finance & Investment, Taylor & Francis Journals, vol. 8(1), pages 72-93, January.
    21. Jegadeesh, Narasimhan & Titman, Sheridan, 1993. "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
    22. Naqvi, Bushra & Rizvi, S.K.A. & Mirza, Nawazish & Reddy, Krishna, 2018. "Religion based investing and illusion of Islamic Alpha and Beta," Pacific-Basin Finance Journal, Elsevier, vol. 52(C), pages 82-106.
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    More about this item

    Keywords

    effectiveness; mutual funds; multifactor asset pricing model; risk factor;
    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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