Sports Analytics Weekly by kubeia.io - 16/2023
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đź’° Quantitative Finance
Can ChatGPT Forecast Stock Price Movements? Return Predictability and Large Language Models
ssrn.com - Alejandro Lopez-Lira, Yuehua Tang
We examine the potential of ChatGPT, and other large language models, in predict- ing stock market returns using sentiment analysis of news headlines. We use ChatGPT to indicate whether a given headline is good, bad, or irrelevant news for firms’ stock prices. We then compute a numerical score and document a positive correlation be- tween these “ChatGPT scores” and subsequent daily stock market returns. Further, ChatGPT outperforms traditional sentiment analysis methods. We find that more basic models such as GPT-1, GPT-2, and BERT cannot accurately forecast returns, indi- cating return predictability is an emerging capacity of complex models. Our results suggest that incorporating advanced language models into the investment decision- making process can yield more accurate predictions and enhance the performance of quantitative trading strategies.
🤖 Machine Learning
Statistics Slam Dunk
manning.com
Learn statistics by analyzing professional basketball data! In this action-packed book, you’ll build your skills in exploratory data analysis by digging into the fascinating world of NBA games and player stats using the R language.