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A reliable performance measure to differentiate China’s actively managed open-end equity mutual funds

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  • Ali M. Kutan
  • Hai Lin
  • Ping-Wen Sun
  • Bin Yu

Abstract

We compare different fund performance measures to examine which performance measures can generate risk-adjusted returns between high ranked and low ranked China’s actively managed open-end equity mutual funds. Our results show that only the six-factor (five factors (market, size, b/m, profitability & Investment facotrs) plus a momentum factor) alpha as the performance measure meets the criteria. Separated by the six-factor alpha, better performing funds have a larger asset under management, a better past 6-month cumulative return, a better stock picking ability, and a higher percentage of hybrid funds. Through our sample period from July 2004 to December 2015, the highest ranked quintile funds generate a monthly risk-adjusted return of 0.24% more than the lowest ranked quintile funds and the six-factor alpha reliably selects a better fund portfolio in both bear and bull markets on the basis of both fund return and holding data. Furthermore, our results from fund trading data show that funds with the highest six-factor alpha rank demonstrate a better trading skill in bear markets, suggesting that those better performing funds exhibit their market timing and stock picking abilities when investors need them most.

Suggested Citation

  • Ali M. Kutan & Hai Lin & Ping-Wen Sun & Bin Yu, 2018. "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, November.
    • Handle: RePEc:taf:applec:v:50:y:2018:i:52:p:5592-5603
    DOI: 10.1080/00036846.2018.1488055
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    Cited by:

    1. Jin Yuan & Xianghui Yuan, 2023. "A Comprehensive Method for Ranking Mutual Fund Performance," SAGE Open, , vol. 13(2), pages 21582440231, May.
    2. Jun, Xiao & Ren, He & Sun, Ping-Wen, 2021. "Deriving managerial skills by dissecting holding changes of mutual funds: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    3. 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.
    4. Liao, Wenbin & Du, Jianing & Sun, Ping-Wen, 2020. "Heterogeneous institutional preferences and informativeness: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 60(C).

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