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{HtmlEncodeMultiline(EmailPreheader)} | CHATGPT, STOCK MARKET PREDICTABILITY AND LINKS TO THE MACROECONOMY |
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| ABSTRACT We find that positive news extracted by ChatGPT from the front pages of the Wall Street Journal is related to macroeconomic conditions and can predict monthly stock market returns. Consistent with existing theories, investors tend to underreact to positive news, especially during periods of economic downturns, high information uncertainty, and high news novelty. However, negative news is negatively associated with contemporaneous returns and has no predictive power. We find further that traditional methods, such as word lists and BERT, fail to have comparable predictability, and ChatGPT appears at present the best in capturing economic news about the market risk premium. |
Keywords: LLMs, ChatGPT, Textual Analysis, NLP, Return Predictability JEL Codes: C22, C53, G11, G12, G17 |
Click here to view the CV. Click here to view the paper. |
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PRESENTER Wu Zhu Tsinghua University |
RESEARCH FIELDS Finance AI (Artificial Intelligence) Big Data Network Economics Portfolio Management Macroeconomics Innovation Chinese Economy |
DATE: 26 August 2024 (Monday) |
VENUE: Meeting Room 5.1, Level 5 School of Economics Singapore Management University 90 Stamford Road Singapore 178903 |
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