Volatility Study of AI Investment Products
AIEQ Fund as an Example
DOI:
https://doi.org/10.54097/xdxjv267Keywords:
Artificial intelligence, Garch model, Financial investmentAbstract
In recent years, with the development of science and technology, artificial intelligence is applied in various fields of society. Among them, the application in financial market prediction has attracted a lot of attention. Artificial intelligence combined with machine learning, deep learning and other models has helped investors solve many problems related to financial investment. It improves the efficiency of investment and saves the cost of investment. However, while gaining benefits, there are also disadvantages of AI investment. In this paper, the volatility of the AIEQ fund is predicted using the Garch model, based on the AIEQ fund data, and the AI stock returns from January 2019 to July 2024 are used. The empirical results show that the volatility of the GARCH model under the t-distribution assumption of the fund is significant, and there are still some problems in the prediction, although the AIEQ fund has an advantage in processing data and executing the trading strategy, but there is still instability in still has a certain market risk. When considering investing in AIEQ funds, investors should fully understand their operating mechanisms and potential risks, and make decisions based on their risk tolerance and investment objectives. This study enhances the knowledge and understanding of AI investment, enabling future investors and financial institutions to make more reasonable investment choices when utilizing AI for investment decisions.
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