Research on Fund Product Recommendation Based on Investor Profiles

Kui Fu () and Zhilin Li ()
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Kui Fu: Wuhan University of Technology, School of Economics
Zhilin Li: Wuhan University of Technology, School of Economics

A chapter in Proceedings of the 2023 2nd International Conference on Urban Planning and Regional Economy (UPRE 2023), 2023, pp 398-408 from Springer

Abstract: Abstract In the field of fund product recommendation research, there has been limited study on investor profiling and personalized recommendation, overlooking the significant value of investors' multidimensional characteristics in influencing fund product selection. To address the issue of individual investors' fund product selection, this study proposes a fund product recommendation model based on investor profiles. Real data of investors from Eastmoney.com, a popular mutual fund investment platform in China, was collected through web crawling for experimentation, validating the practicality and effectiveness of the mutual fund product recommendation system based on investor profiling.

Keywords: Investor Profiles; Collaborative Filtering; Fund Product Recommendation (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-218-7_45

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DOI: 10.2991/978-94-6463-218-7_45

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