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Regime-Switching Determinants of Mutual Fund Performance in South Africa

Author

Listed:
  • Richard Apau

    (School of Accounting, Economics and Finance, University of KwaZulu-Natal, Bag X 5400, Durban 4000, South Africa)

  • Peter Moores-Pitt

    (School of Accounting, Economics and Finance, University of KwaZulu-Natal, Bag X 5400, Durban 4000, South Africa)

  • Paul-Francois Muzindutsi

    (School of Accounting, Economics and Finance, University of KwaZulu-Natal, Bag X 5400, Durban 4000, South Africa)

Abstract

This study assesses the effect of fund-level and systemic factors on the performance of mutual funds in the context of changing market conditions. A Markov regime-switching model is used to analyze the performance of 33 South African equity mutual funds from 2006 to 2019. From the results, fund flow and fund size exert more predictive influences on performance in the bearish state of the market than in the bullish state. Fund age, fund risk, and market risk were found to be the most significant factors driving the performance of active portfolios under time-varying conditions of the market. These variables exert more influence on fund performance under bearish conditions than under bullish conditions, emphasizing the flight-to-liquidity assets phenomenon and risk-aversion behavior of fund contributors during unstable conditions of the market. Consequently, fund managers need to maintain adequate asset bases while implementing policies that minimize dispersions in fund returns to engender persistence in performance. This study provides novel perspectives on how the determinants of fund performance change with market conditions as portrayed by the adaptive market hypothesis (AMH).

Suggested Citation

  • Richard Apau & Peter Moores-Pitt & Paul-Francois Muzindutsi, 2021. "Regime-Switching Determinants of Mutual Fund Performance in South Africa," Economies, MDPI, vol. 9(4), pages 1-20, October.
    • Handle: RePEc:gam:jecomi:v:9:y:2021:i:4:p:161-:d:662523
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    as
    1. Al-Khazali, Osamah & Mirzaei, Ali, 2017. "Stock market anomalies, market efficiency and the adaptive market hypothesis: Evidence from Islamic stock indices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 190-208.
    2. Pathairat Pastpipatkul & Petchaluck Boonyakunakorn & Kanyaphon Phetsakda, 2020. "The Impact of Thailand’s Openness on Bilateral Trade between Thailand and Japan: Copula-Based Markov Switching Seemingly Unrelated Regression Model," Economies, MDPI, vol. 8(1), pages 1-13, January.
    3. Diane Del Guercio & Jonathan Reuter, 2014. "Mutual Fund Performance and the Incentive to Generate Alpha," Journal of Finance, American Finance Association, vol. 69(4), pages 1673-1704, August.
    4. Steve Nenninger & David Rakowski, 2014. "Time-varying flow-performance sensitivity and investor sophistication," Journal of Asset Management, Palgrave Macmillan, vol. 15(5), pages 333-345, October.
    5. Zia-Ur-Rehman Rao & Muhammad Zubair Tauni, 2016. "Fund Performance And Fund Flow. Case Of China," Journal of Academic Research in Economics, Spiru Haret University, Faculty of Accounting and Financial Management Constanta, vol. 8(1 (March)), pages 146-156.
    6. Fratzscher, Marcel, 2012. "Capital flows, push versus pull factors and the global financial crisis," Journal of International Economics, Elsevier, vol. 88(2), pages 341-356.
    7. Kim, C.-J.Chang-Jin, 2004. "Markov-switching models with endogenous explanatory variables," Journal of Econometrics, Elsevier, vol. 122(1), pages 127-136, September.
    8. Nelson Areal & Maria Cortez & Florinda Silva, 2013. "The conditional performance of US mutual funds over different market regimes: do different types of ethical screens matter?," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 27(4), pages 397-429, December.
    9. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    10. 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.
    11. Miguel A. Ferreira & Aneel Keswani & António F. Miguel & Sofia B. Ramos, 2013. "The Determinants of Mutual Fund Performance: A Cross-Country Study," Review of Finance, European Finance Association, vol. 17(2), pages 483-525.
    12. Jun, Xiao & Li, Mingsheng & Shi, Jing, 2014. "Volatile market condition and investor clientele effects on mutual fund flow performance relationship," Pacific-Basin Finance Journal, Elsevier, vol. 29(C), pages 310-334.
    13. Huij, Joop & Post, Thierry, 2011. "On the performance of emerging market equity mutual funds," Emerging Markets Review, Elsevier, vol. 12(3), pages 238-249, September.
    14. Monica Billio & Jacques Anas & Laurent Ferrara & Marco Lo Duca, 2007. "Business Cycle Analysis with Multivariate Markov Switching Models," Working Papers 2007_32, Department of Economics, University of Venice "Ca' Foscari".
    15. Lorraine Rupande & Hilary Tinotenda Muguto & Paul-Francois Muzindutsi, 2019. "Investor sentiment and stock return volatility: Evidence from the Johannesburg Stock Exchange," Cogent Economics & Finance, Taylor & Francis Journals, vol. 7(1), pages 1600233-160, January.
    16. Meifen Qian & Chongbo Xu & Bin Yu, 2014. "Performance Manipulation and Fund Flow: Evidence from China," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 50(3), pages 221-239, May.
    17. Franz Fuerst & George Matysiak, 2013. "Analysing the performance of nonlisted real estate funds: a panel data analysis," Applied Economics, Taylor & Francis Journals, vol. 45(14), pages 1777-1788, May.
    18. Gray, Stephen F., 1996. "Modeling the conditional distribution of interest rates as a regime-switching process," Journal of Financial Economics, Elsevier, vol. 42(1), pages 27-62, September.
    19. Martin Rohleder & Dominik Schulte & Marco Wilkens, 2017. "Management of flow risk in mutual funds," Review of Quantitative Finance and Accounting, Springer, vol. 48(1), pages 31-56, January.
    20. Robert Kosowski, 2011. "Do Mutual Funds Perform When It Matters Most to Investors? US Mutual Fund Performance and Risk in Recessions and Expansions," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 1(03), pages 607-664.
    21. Jason Z. Ma & Xiang Deng & Kung-Cheng Ho & Sang-Bing Tsai, 2018. "Regime-Switching Determinants for Spreads of Emerging Markets Sovereign Credit Default Swaps," Sustainability, MDPI, vol. 10(8), pages 1-17, August.
    22. Francesco A. Franzoni & Martin C. Schmalz, 2013. "Fund Flows and Market States," Swiss Finance Institute Research Paper Series 13-41, Swiss Finance Institute, revised Jun 2017.
    23. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
    24. Ma, Jason Z. & Deng, Xiang & Ho, Kung-Cheng & Tsai, Sang-Bing, 2018. "Regime-switching determinants of emerging markets sovereign credit risk swaps spread," Economics Discussion Papers 2018-52, Kiel Institute for the World Economy (IfW Kiel).
    25. Francesco Franzoni & Martin C. Schmalz, 2017. "Fund Flows and Market States," The Review of Financial Studies, Society for Financial Studies, vol. 30(8), pages 2621-2673.
    26. Kim, Chang-Jin, 1994. "Dynamic linear models with Markov-switching," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 1-22.
    27. Gueddoudj, Sabbah, 2018. "Financial Variables as Predictive Indicators of the Luxembourg GDP Growth," Empirical Economic Review, Department of Economics and Statistics, Dr Hassan Murad School of Management, University of Management and Technology, Lahore, vol. 1(2), pages 49-62.
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