Do platform recommendations in the fund market work? Evidence from a quasi-experimental study

Author:

Hao Shuaikang,Peng Lifang,Tang Xinyin,Huang LingORCID

Abstract

PurposeThis study introduces a new type of platform recommendation about mutual funds and draws on the signaling theory to conduct a quasi-experimental design to investigate how the platform recommendation influences investors’ investment decisions. Moreover, the authors examine the combined effect of star ratings and the platform recommendation on fund flow and test the investment value of recommended funds.Design/methodology/approachThis study implements a quasi-experimental design based on 1,295 mutual funds traded on Alipay’s online platform to test the hypotheses.FindingsThe empirical results show that the recommended funds received higher fund flows from investors when the platform recommendation was established. Moreover, a substitution effect between tag recommendation and star ratings on fund flow was identified. We also uncovered that investing in platform-recommended funds can yield significant and higher fund returns for investors than those without platform recommendations.Originality/valueOur findings shed new insights into the role of platform recommendations in helping fund investors make investment decisions and contribute to the business of online mutual fund transactions by investigating the effect of platform recommendations on fund flow and performance.

Publisher

Emerald

Reference64 articles.

1. Mandatory portfolio disclosure, stock liquidity, and mutual fund performance;Journal of Finance,2015

2. Amac (2022), “China public fund industry data [in Chinese]”, available at: https://www.amac.org.cn/researchstatistics/datastatistics/mutualfundindustrydata/ (accessed December 8, 2022).

3. The impact of the morningstar sustainability rating on mutual fund flows;European Financial Management,2019

4. Do mutual fund ratings provide valuable information for retail investors?;Studies in Economics and Finance,2018

5. Choosing two business degrees versus choosing one: what does it tell about mutual fund managers’ investment behavior?;Journal of Business Research,2017

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