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GPT's idea of stock factors

Author

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  • Yuhan Cheng
  • Ke Tang

Abstract

We amalgamate the capabilities of the GPT-4 computational model with the avant-garde methodology of autonomous factor generation, culminating in the synthesis of high-return factors within the equity investment milieu. Empirical outcomes elucidate that the factors conceptualized by ChatGPT attain a commendable Sharpe ratio peaking at 4.49, accompanied by an annualized return reaching 66.16%. Notably, the superlative excess returns garnered remain unaccounted for by the quintessential five-factor model. Through the implementation of an unembellished model averaging paradigm, the ensemble of 35 factors, conceived by ChatGPT, manifests an apex long-short annualized return of 88% and a Sharpe ratio registering at 2.46. In stark contrast to conventional data mining techniques, the temporal expenditure requisite for GPT's factor generation is minuscule. It relies on knowledge inference without the need for data input, and it can provide a thorough economic explanation for its factors.

Suggested Citation

  • Yuhan Cheng & Ke Tang, 2024. "GPT's idea of stock factors," Quantitative Finance, Taylor & Francis Journals, vol. 24(9), pages 1301-1326, September.
  • Handle: RePEc:taf:quantf:v:24:y:2024:i:9:p:1301-1326
    DOI: 10.1080/14697688.2024.2318220
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