The effect of performance manipulation on fund flows under different market conditions in South Africa
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DOIhttp://dx.doi.org/10.21511/imfi.19(3).2022.17
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Article InfoVolume 19 2022, Issue #3, pp. 203-214
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Corrections to the article made on October 17, 2022
The previous list of authors Richard Apau, Leward Jeke was changed to Richard Apau, Leward Jeke, Peter Moores-Pitt, Paul-Francois Muzindutsi, October 17, 2022. Explanation in the documents: Authors contributions, Authors explanations.
This study analyzes the effect of performance manipulation on mutual fund flows under different market conditions to provide explanations to the increased flow of investors’ funds to persistently underperforming active mutual fund managers in South Africa. The study employs a system GMM technique to analyze panel data of 52 South African actively managed equity mutual funds for the 2006–2019 period. From the analysis, it is found that past fund flows and fund size constitute a set of fund-level factors with predictive influences on fund flows, while market risk exerts systemic effect on the flow of investors’ assets to fund managers. The results show that market conditions do not impact the relationship between mutual fund flows and performance manipulation, which implies that manipulation strategies implemented by fund managers do not engender increased funds’ flow from asset owners. This study thus concludes that other non-performance factors drive convexity in the relationship between fund flows and performance in South Africa.
- Keywords
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JEL Classification (Paper profile tab)G11, G14, G23
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References46
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Tables3
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Figures0
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- Table 1. Descriptive statistics
- Table 2. Correlation matrix
- Table 3. Effect of performance manipulation on fund flows under different market conditions
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- Apau, R., Muzindutsi, P. F., & Moores-Pitt, P. (2021a). Mutual fund flow-performance dynamics under different market conditions in South Africa. Investment Management and Financial Innovations, 18(1), 236-249.
- Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. The Review of Economic Studies, 58(2), 277-297.
- Asisa. (2021). Collective investments schemes and local funds statistics.
- Barber, B. M., Huang, X., & Odean, T. (2016). Which factors matter to investors? Evidence from mutual fund flows. The Review of Financial Studies, 10(29), 2600-2642.
- Ben-Rephael, A. (2017). Flight-to-liquidity, market uncertainty, and the actions of mutual fund investors. Journal of Financial Intermediation, 31, 30-44.
- Bergstresser, D., & Poterba, J. (2002). Do after-tax returns affect mutual fund inflows? Journal of Financial Economics, 63(3), 381-414.
- Blundell, R., & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87(1), 115-143.
- Bollen, N. P., & Pool, V. K. (2008). Conditional return smoothing in the hedge fund industry. Journal of Financial and Quantitative Analysis, 43(2), 267-298.
- Brown, K. C., Garlappi, L., & Tiu, C. (2010). Asset allocation and portfolio performance: Evidence from university endowment funds. Journal of Financial Markets, 13(2), 268-294.
- Chen, Y. (2011). Derivatives use and risk taking: Evidence from the hedge fund industry. Journal of Financial and Quantitative Analysis, 46(4), 1073-1106.
- Del Guercio, D., & Tkac, P. A. (2002). The determinants of the flow of funds of managed portfolios: Mutual funds vs. pension funds. Journal of Financial and Quantitative Analysis, 37(4), 523-557.
- Dormann, C. F., Elith, J., Bacher, S., Buchmann, C., Carl, G., Carré, G., & Leitao, P. J. (2013). Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography, 36(1), 27-46.
- Duong, T. X., & Meschke, F. (2019). The rise and fall of portfolio pumping among US mutual funds. Journal of Corporate Finance, 60, 101530.
- Dyakov, T., Harford, J., & Qiu, B. (2022). Better kept in the dark? Portfolio disclosure and agency problems in mutual funds. Journal of Financial and Quantitative Analysis, 57(4), 1529-1563.
- Ellis, C. D. (2015). In defense of active investing. Financial Analysts Journal, 71(4), 4-7.
- Ferson, W. E., & Schadt, R. W. (1996). Measuring fund strategy and performance in changing economic conditions. The Journal of Finance, 51(2), 425-461.
- Ferson, W., & Lin, J. (2014). Alpha and performance measurement: The effects of investor disagreement and heterogeneity. The Journal of Finance, 69(4), 1565-1596.
- Fletcher, J. (2000). On the conditional relationship between beta and return in international stock returns. International Review of Financial Analysis, 9(3), 235-245.
- Fu, R., Navone, M., Pagani, M., & Pantos, T. D. (2012). The determinants of the convexity in the flow-performance relationship. The Journal of Index Investing, 3(2), 81-95.
- Fuerst, F., Lim, W., & Matysiak, G. (2013). Non-listed real estate funds: leverage and macroeconomic effects. In The Narodowy Bank Polski Workshop: Recent Trends in the Real Estate Market and its Analysis. SSRN Electronic Journal.
- Glow, D. (2020). South African Fund Market Summary-2019. Lipper Alpha Insight.
- Goetzmann, W., Ingersoll, J., Spiegel, M., & Welch, I. (2007). Portfolio performance manipulation and manipulation-proof performance measures. The Review of Financial Studies, 20(5), 1503-1546.
- Gottesman, A. A., Morey, M. R., & Rosenberg, M. (2013). Do active managers of retail mutual funds have an incentive to closet index in down markets? fund performance and subsequent annual fund flows, 1997-2011. Journal of Investment Consulting, 14(2), 47-58.
- Huang, J., Sialm, C., & Zhang, H. (2011). Risk shifting and mutual fund performance. The Review of Financial Studies, 24(8), 2575-2616.
- Humphrey, J. E., Benson, K. L., & Brailsford, T. J. (2013). Do Fund Flow-Return Relations Depend on the Type of Investor? A Research Note. Abacus, 49(1), 34-45.
- Jones, R. C., & Wermers, R. (2011). Active management in mostly efficient markets. Financial Analysts Journal, 67(6), 29-45.
- Jun, X., Li, M., & Shi, J. (2014). Volatile market condition and investor clientele effects on mutual fund flow performance relationship. Pacific-Basin Finance Journal, 29, 310-334.
- Kacperczyk, M., Nieuwerburgh, S. V., & Veldkamp, L. (2014). Time-varying fund manager skill. The Journal of Finance, 69(4), 1455-1484.
- Kim, M. S. (2019). Changes in Mutual Fund Flows and Managerial Incentives. SSRN Electronic Journal.
- Kripfganz, S., & Schwarz, C. (2015). Estimation of linear dynamic panel data models with time-invariant regressors. Journal of Applied Econometrics, 34(4), 526-546.
- Natter, M., Rohleder, M., Schulte, D., & Wilkens, M. (2014). The impact of option use on mutual fund performance (Working Paper). University of Augsburg.
- Nenninger, S., & Rakowski, D. (2014). Time-varying flow-performance sensitivity and investor sophistication. Journal of Asset Management, 15(5), 333-345.
- Pástor, Ľ., Stambaugh, R. F., & Taylor, L. A. (2015). Scale and skill in active management. Journal of Financial Economics, 116(1), 23-45.
- Pettengill, G. N., Sundaram, S., & Mathur, I. (1995). The conditional relation between beta and returns. Journal of Financial and Quantitative Analysis, 30(1), 101-116.
- Qian, M., & Yu, B. (2015). Do mutual fund managers manipulate? Applied Economics Letters, 22(12), 967-971.
- Qian, M., Xu, C., & Yu, B. (2014). Performance manipulation and fund flow: evidence from China. Emerging Markets Finance and Trade, 50(3), 221-239.
- Rangongo, T. (2018). A fund with inflation-beating growth-fund in focus: Marriott divided growth fund. Sabinet African Journals, 19, 14-14.
- Roodman, D. (2009). How to do xtabond2: An introduction to difference and system GMM in Stata. The Stata Journal, 9(1), 86-136.
- Rupande, L., Muguto, H. T., & Muzindutsi, P. F. (2019). Investor sentiment and stock return volatility: Evidence from the Johannesburg Stock Exchange. Cogent Economics & Finance, 7(1), 1600233.
- S&P. (2019). SPIVA South Africa Year End 2018 Score card.
- Saeed, M. S. (2014). Bank-related, industry-related and macroeconomic factors affecting bank profitability: A case of the United Kingdom. Research Journal of Finance and Accounting, 5(2), 42-50.
- Tan, O. (2015). Mutual fund performance: Evidence from south Africa. Emerging Markets Journal, 5(2), 49-57.
- Titman, S., & Tiu, C. (2011). Do the best hedge funds hedge? The Review of Financial Studies, 24(1), 123-168.
- Wang, P. (2018). Portfolio Pumping in Mutual Fund Families. In Fifth Annual Conference on Financial Market Regulation. SSRN Electronic Journal.
- Wintoki, M. B., Linck, J. S., & Netter, J. M. (2012). Endogeneity and the dynamics of internal corporate governance. Journal of Financial Economics, 105(3), 581-606.
- Yao, J., Ma, C., & He, W.P. (2014). Investor herding behaviour of Chinese stock market. International Review of Economics & Finance, 29, 12-29.