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Related Experiment Video

Updated: Oct 8, 2025

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

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Published on: August 16, 2020

Cluster-Based Mutual Fund Classification and Price Prediction Using Machine Learning for Robo-Advisors.

Xiaofei Chen¹, Shujun Ye¹, Chao Huang¹

¹Beijing Jiaotong University, School of Economics and Management, Beijing, China.

Computational Intelligence and Neuroscience

|December 27, 2021

Summary

This study enhances financial technology (FinTech) by using machine learning for accurate mutual fund classification and price prediction. The AI-driven approach supports next-generation robo-advisors in wealth management.

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Area of Science:

Artificial Intelligence
Machine Learning
Financial Technology (FinTech)

Background:

The Chinese FinTech sector is rapidly growing, with robo-advisors innovating wealth management.
Machine learning and deep learning are increasingly applied to financial problem-solving.

Purpose of the Study:

To improve the accuracy and timeliness of mutual fund classification using machine learning.
To develop a deep learning model for predicting fund price movements based on classification results.

Main Methods:

Utilized the Gaussian hybrid clustering algorithm for fund classification.
Implemented a deep learning-based prediction model for price movement forecasting.
Applied a cluster-based spatiotemporal ensemble deep learning module.

Main Results:

Achieved accurate and efficient classification for 3,625 Chinese mutual funds.
The deep learning module demonstrated superior prediction accuracy compared to baseline models, even with limited data.

Conclusions:

The study presents a novel approach for fund classification and price prediction.
This AI-assisted method can enhance decision-making for advanced robo-advisors in FinTech.