Effectiveness of Artificial Intelligence in Stock Market Prediction based on Machine Learning

Sohrab Mokhtari, Kang K. Yen and Jin Liu

Papers from arXiv.org

Abstract: This paper tries to address the problem of stock market prediction leveraging artificial intelligence (AI) strategies. The stock market prediction can be modeled based on two principal analyses called technical and fundamental. In the technical analysis approach, the regression machine learning (ML) algorithms are employed to predict the stock price trend at the end of a business day based on the historical price data. In contrast, in the fundamental analysis, the classification ML algorithms are applied to classify the public sentiment based on news and social media. In the technical analysis, the historical price data is exploited from Yahoo Finance, and in fundamental analysis, public tweets on Twitter associated with the stock market are investigated to assess the impact of sentiments on the stock market's forecast. The results show a median performance, implying that with the current technology of AI, it is too soon to claim AI can beat the stock markets.

Date: 2021-06
New Economics Papers: this item is included in nep-big, nep-cmp, nep-cwa, nep-fmk and nep-pay
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Citations: View citations in EconPapers (3)

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