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今年4月,美国佛罗里达大学的一项探索ChatGPT在金融投资领域潜力的工作论文甫一发布,瞬间让北美及全球资本市场兴奋了起来。在北美,该论文被下载了33000多次,稳居5月全球社会科学研究领域下载量前列。
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论文标题:
Can ChatGPT Forecast Stock Price Movements? Return Predictability and Large Language Models
作者单位:
弗罗里达大学
Abstract
We examine the potential of ChatGPT and other large language models in predict- ing stock market returns using news headlines.We use ChatGPT to assess whether each headline is good, bad, or neutral for firms’stock prices. We document a sig- nificantly positive correlation between ChatGPT scores and subsequent daily stock returns. We find that ChatGPT outperforms traditional sentiment analysis methods. More basic models such asGPT-1, GPT-2, and BERT cannot accurately forecast re- turns, indicating return predictability is an emerging capacity of complex language models. Long-short strategies based on ChatGPT-4 deliver the highest Sharpe ratio. Furthermore, we find predictability in both small and large stocks, suggesting market underreaction to company news. Predictability is stronger among smaller stocks and stocks with bad news, consistent with limits-to-arbitrage also playing an important role. Finally, we propose a new method to evaluate and understand the models'reasoning capabilities. Overall, 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.
研究内容: