Open-ended mixed fund performance in the Chinese fund market: An empirical analysis based on Fama-French five-factor model

JIAO, ZHENGHONG (2019) Open-ended mixed fund performance in the Chinese fund market: An empirical analysis based on Fama-French five-factor model. [Dissertation (University of Nottingham only)]

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Abstract

This paper studies the performance of China's mixed fund market based on the Fama-French five-factor model and tests the investment ability of fund managers. Different from previous studies, this paper applies the latest five-factor model to the research of the mixed funds with the highest share in the developing countries market, and analyses the performance of these funds under different market conditions. Then use the Fama-French five-factor model to improve the Treynor-Mazuy model and the Henriksson-Merton model, and construct the TM-FF5 and HM-FF5 models to study the investment ability of fund managers. The results show that the Fama-French five-factor model is applicable in different market conditions and is superior to the Fama-French three-factor model and CAPM model in terms of interpretation ability. Fund managers can achieve excess returns above the market by investing in large-scale, low book-to-market ratios, strong profitability, and high-investment assets. In a bull market or a bear market, investing in funds do not bring more income or reduce losses to investors, which is consistent with the reality that the mixed fund still allocates a large proportion of stock assets. In contrast, the mixed fund performs well in the volatile market and can obtain excess returns. Finally, in terms of the fund manager's stock selection ability and market timing ability, the two models have consistent results after regression analysis, and most fund managers can use these two capabilities to bring excess returns to the fund. The study of these issues can help assess the current state of the development of China's mixed fund market and provide a reference for investors to choose the target.

Item Type: Dissertation (University of Nottingham only)
Depositing User: JIAO, ZHENGHONG
Date Deposited: 07 Dec 2022 10:49
Last Modified: 07 Dec 2022 10:49
URI: https://eprints.nottingham.ac.uk/id/eprint/58258

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