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Idiosyncratic risk and mutual fund performance

  • S.I.: Risk in Financial Economics
  • Published:
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Abstract

In this paper we present new evidence on the relation between idiosyncratic risk and mutual fund performance using asset pricing models. We use a unique data set containing monthly returns of 949 UK equity mutual funds over a 28-year period to measure fund performance. We find that idiosyncratic risk cannot be eliminated in UK mutual funds. We show that idiosyncratic risk is negatively related to returns for all funds investment style categories. We present evidence that the inclusion of idiosyncratic risk significantly increases the number of funds showing statistically significant and positive selectivity skills (alpha). Furthermore, all equity mutual funds turn to show significant volatility timing performance when idiosyncratic risk is considered. Finally, we find that idiosyncratic risk can forecast fund returns after controlling for macroeconomic variables.

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Notes

  1. Assuming the market portfolio is well diversified.

  2. See, Vidal-García et al. (2016b) for more details on the short-term persistence of international mutual fund performance.

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Author information

Authors and Affiliations

  1. Complutense University of Madrid, Madrid, Spain

    Javier Vidal-García & Marta Vidal

  2. South Champagne Business School, Troyes, France

    Sabri Boubaker

  3. International School, Vietnam National University, Hanoi, Vietnam

    Sabri Boubaker

  4. Neoma Business School, Rouen, France

    Riadh Manita

Authors
  1. Javier Vidal-García
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  2. Marta Vidal
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  3. Sabri Boubaker
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  4. Riadh Manita
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Corresponding author

Correspondence to Javier Vidal-García.

Additional information

We appreciate helpful comments and suggestions from Keith Cuthbertson, Aneel Keswani, Doron Avramov, Natasha Todorovic, Germán López Espinosa, Marcin Kacperczyk, Massimo Guidolin, and Elaine Hutson, as well as seminar participants at Stevens Institute of Technology, Bristol Business School, Cass Business School, University of Stirling, Complutense University of Madrid, the Southwestern Finance Association Annual Conference, the Eastern Finance Association Annual Meeting, the Infiniti Conference, and the Paris Financial Management Conference. The work described in this paper was partially supported by a grant from Santander UK Bank. This paper was written while Sabri Boubaker was visiting professor in Finance at the International School, Vietnam National University, Hanoi, Vietnam.

Appendix A

Appendix A

See Tables 1, 2, 3, 4, 5, 6 and Figs. 1, 2, 3, 4.

Table 1 Descriptive statistics
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Table 2 Monthly performance statistics
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Table 3 Idiosyncratic risk measure
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Table 4 Summary statistics of market timing and volatility timing coefficients
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Table 5 Idiosyncratic risk and market fundamentals
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Table 6 Forecasts of fund returns controlling for business cycle variables
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Fig. 1
figure 1

Average return and risk. This figure plots the average return and standard deviation of fund categories for the period 1987:01 to 2015:12. Average return and standard deviation is calculated using monthly data for each category of funds

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Fig. 2
figure 2

Average return for all funds and the FTSE All Share Index. This figure plots average monthly returns for the whole sample of funds and the FTSE All Share Index for the period 1987:01 to 2015:12. It is possible to appreciate abnormal returns prior to the traditional turn of the year, as well as the “sell in May and go away” effect

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Fig. 3
figure 3

Average monthly return for each sub-sample of funds. This figure plots the pattern of returns for each sub-sample of funds for the period 1987:01 to 2015:12

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Fig. 4
figure 4

Market and idiosyncratic volatility. Panel A of this figure plots the average standard deviation of the whole sample of funds for the period 1987:01 to 2015:12. The average fund volatility is calculated using monthly data for the time period under consideration. Standard deviation is a statistical term that provides a good indication of volatility. It measures how widely fund closing prices are dispersed from the average. Panel B of this figure plots the annual idiosyncratic volatility for all funds for the period 1987:01 to 2015:12. Average idiosyncratic volatility is calculated using monthly data from regression (14). Market volatility fluctuates more than idiosyncratic volatility for the sample period. a Market volatility for all funds and b Idiosyncratic volatility for all funds

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Vidal-García, J., Vidal, M., Boubaker, S. et al. Idiosyncratic risk and mutual fund performance. Ann Oper Res 281, 349–372 (2019). https://doi.org/10.1007/s10479-018-2794-2

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  • DOI: https://doi.org/10.1007/s10479-018-2794-2

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