Investors must reasonably predict and optimize management of the risks they face in the investment process, so as to ensure the safety of investors' funds. Risk comes from the understanding of relevant information, cognitive analysis and prediction. For investors, this is precisely what they lack. Listed companies sometimes hide related risks with their own interests, resulting in asymmetric information differences between investors and their superior companies. This information asymmetry greatly exacerbates the risks of both parties. It is not conducive to the development of the entire investment market, nor is it conducive to risk control. This article aims to study the risk sources of listed company investors and how to avoid investors' risks. This article proposes to predict the investment risks of investors and manage the risks faced by investors. With the help of machine learning model, this article minimizes the risk of investors and effectively guarantees the safety of funds. The experimental results of this paper show that risk prediction of investor funds and portfolio management investment can minimize risks and improve the security of funds for more than 20% of investors.

Zhiwen Liu. Investor Risk Forecast and Management Path of Listed Companies Based upon Machine Learning. International Journal of Business Management and Economics and Trade (2024), Vol. 5, Issue 1: 152-168. https://doi.org/10.38007/IJBMET.2024.050118.

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