IDEAS home Printed from https://ideas.repec.org/a/gam/jecomi/v9y2021i4p161-d662523.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7099/9/4/161/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7099/9/4/161/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. Kim, C.-J.Chang-Jin, 2004. "Markov-switching models with endogenous explanatory variables," Journal of Econometrics, Elsevier, vol. 122(1), pages 127-136, September.
    16. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
    17. 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).
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    24. Kim, Chang-Jin, 1994. "Dynamic linear models with Markov-switching," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 1-22.
    25. 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.
    26. 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".
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rakowski, David & Yamani, Ehab, 2021. "Endogeneity in the mutual fund flow–performance relationship: An instrumental variables solution," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 247-271.
    2. Oscar V. De la Torre-Torres & Evaristo Galeana-Figueroa & José Álvarez-García, 2020. "Markov-Switching Stochastic Processes in an Active Trading Algorithm in the Main Latin-American Stock Markets," Mathematics, MDPI, vol. 8(6), pages 1-22, June.
    3. Oscar V. De la Torre-Torres & Dora Aguilasocho-Montoya & María de la Cruz del Río-Rama, 2020. "A Two-Regime Markov-Switching GARCH Active Trading Algorithm for Coffee, Cocoa, and Sugar Futures," Mathematics, MDPI, vol. 8(6), pages 1-19, June.
    4. Oscar V. De la Torre-Torres & Evaristo Galeana-Figueroa & María de la Cruz Del Río-Rama & José Álvarez-García, 2022. "Using Markov-Switching Models in US Stocks Optimal Portfolio Selection in a Black–Litterman Context (Part 1)," Mathematics, MDPI, vol. 10(8), pages 1-28, April.
    5. Eisele, Alexander & Nefedova, Tamara & Parise, Gianpaolo & Peijnenburg, Kim, 2020. "Trading out of sight: An analysis of cross-trading in mutual fund families," Journal of Financial Economics, Elsevier, vol. 135(2), pages 359-378.
    6. Oscar V. De la Torre-Torres & Francisco Venegas-Martínez & Mᵃ Isabel Martínez-Torre-Enciso, 2021. "Enhancing Portfolio Performance and VIX Futures Trading Timing with Markov-Switching GARCH Models," Mathematics, MDPI, vol. 9(2), pages 1-22, January.
    7. Oscar V. De la Torre-Torres & Evaristo Galeana-Figueroa & José Álvarez-García, 2019. "A Test of Using Markov-Switching GARCH Models in Oil and Natural Gas Trading," Energies, MDPI, vol. 13(1), pages 1-24, December.
    8. Ibert, Markus, 2023. "What do mutual fund managers’ private portfolios tell us about their skills?," Journal of Financial Intermediation, Elsevier, vol. 53(C).
    9. Mount, Timothy D. & Ning, Yumei & Cai, Xiaobin, 2006. "Predicting price spikes in electricity markets using a regime-switching model with time-varying parameters," Energy Economics, Elsevier, vol. 28(1), pages 62-80, January.
    10. Billio, Monica & Casarin, Roberto & Ravazzolo, Francesco & van Dijk, Herman K., 2012. "Combination schemes for turning point predictions," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(4), pages 402-412.
    11. Joanna Janczura & Rafał Weron, 2012. "Efficient estimation of Markov regime-switching models: An application to electricity spot prices," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(3), pages 385-407, July.
    12. Andrew J. Filardo, 1998. "Choosing information variables for transition probabilities in a time-varying transition probability Markov switching model," Research Working Paper 98-09, Federal Reserve Bank of Kansas City.
    13. Zia-ur-Rehman Rao & Tanveer Ahsan & Muhammad Zubair Tauni & Muhammad Umar, 2018. "Performance and Persistence in Performance of Actively Managed Chinese Equity Funds," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(3), pages 727-747, September.
    14. ZHENG, Tingguo & WANG, Xia & GUO, Huiming, 2012. "Estimating forward-looking rules for China's Monetary Policy: A regime-switching perspective," China Economic Review, Elsevier, vol. 23(1), pages 47-59.
    15. Khim, Veasna & Razafitombo, Hery, 2023. "Scale and skills in European active management: Impact of a new regulatory context," Journal of Banking & Finance, Elsevier, vol. 154(C).
    16. Erlandsson, Ulf, 2004. "Reconnecting the Markov Switching Model with Economic Fundamentals," Working Papers 2004:4, Lund University, Department of Economics, revised 04 Nov 2004.
    17. Gallo, Giampiero M. & Otranto, Edoardo, 2008. "Volatility spillovers, interdependence and comovements: A Markov Switching approach," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3011-3026, February.
    18. Chew Lian Chua & Sandy Suardi, 2005. "Is There a Unit Root in East-Asian Short-Term Interest Rates?," Melbourne Institute Working Paper Series wp2005n14, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    19. Guidolin, Massimo & Ono, Sadayuki, 2006. "Are the dynamic linkages between the macroeconomy and asset prices time-varying?," Journal of Economics and Business, Elsevier, vol. 58(5-6), pages 480-518.
    20. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jecomi:v:9:y:2021:i:4:p:161-:d:662523. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.