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Roula Khalaf, Editor of the FT, selects her favourite stories in this weekly newsletter. French markets took a hit after President Emmanuel Macron called for snap parliamentary elections, but the response was more of a shrug than a panic. The general consensus is that politics don’t have a significant impact on markets in the short term. The rise of artificial intelligence and the potential threat it poses to various industries including journalism is a growing concern. A large language model trained on Financial Times writings could potentially write newsletters that are almost indistinguishable from human writing.
A recent paper by scholars at the University of Chicago has shown that large language models could outperform human analysts in financial statement analysis. By feeding ChatGPT with thousands of balance sheets and income statements, stripped of identifying details, the model was able to predict future earnings with high accuracy. The key to its success was asking the model to compose narratives explaining the financial outputs. The study raised questions about the future of financial analysts and stock pickers, as well as the role of AI in generating alpha in the marketplace.
The results of the study may not be surprising, as computer models have shown capabilities of outperforming human analysts in the past. However, the ability of an out-of-the-box large language model to predict earnings with basic prompts is noteworthy. The study brings up questions about the value of financial analysts in the age of AI, and whether their role will evolve or become obsolete. It also raises the issue of AI’s ability to make “big calls” in the market, beyond short-term earnings predictions.
The potential impact of AI on the market, particularly in terms of competing with or supporting the smartest individuals, is a topic of discussion. While AI may not have a significant impact on the average stock picker, its ability to challenge top analysts and portfolio managers is noteworthy. The study’s findings on ChatGPT’s ability to generate model portfolios that outperform the broader market raise questions about the future of stock picking and investment strategies. This has implications for the financial services industry and how professionals adapt to the changing landscape.
Overall, the rise of artificial intelligence in financial analysis poses challenges and opportunities for professionals in the industry. AI’s ability to process vast amounts of data and generate accurate predictions raises questions about the future of human analysts and the role of AI in shaping investment strategies. The study sheds light on the potential of large language models in democratizing financial information processing and generating alpha in the market. It will be interesting to see how the industry adapts to the changing landscape and incorporates AI into its practices.
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