Research on Fund Product Recommendation Based on Investor Profiles

DOI

10.2991/978-94-6463-218-7_45How to use a DOI?

Keywords

Investor Profiles; Collaborative Filtering; Fund Product Recommendation

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.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Kui Fu
AU  - Zhilin Li
PY  - 2023
DA  - 2023/08/16
TI  - Research on Fund Product Recommendation Based on Investor Profiles
BT  - Proceedings of the 2023 2nd International Conference on Urban Planning and Regional Economy (UPRE 2023)
PB  - Atlantis Press
SP  - 398
EP  - 408
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-218-7_45
DO  - 10.2991/978-94-6463-218-7_45
ID  - Fu2023
ER  -