If you read the headlines, large language models such as ChatGPT could be set to transform industries, eliminate millions of jobs, or even destroy humanity as we know it. How much of this is hype remains to be seen, but research from Chicago Booth PhD student Alex G. Kim and Booth’s Maximilian Muhn and Valeri Nikolaev finds that ChatGPT, a chatbot with conversational applications, could be good for investors, who stand to benefit from its ability to cut the fat from corporate disclosures.

The researchers focused on two key sources for investors researching a company’s stock: MD&A disclosures—in written annual or quarterly reports, the section that provides management discussion and analysis of a company’s performance—and earnings conference calls, which dig into reported results and allow analysts to ask questions of executives.

Regulators have expressed concern that company disclosures contain information that’s too complex for many investors to comprehend, and that companies might hide negative news with redundant and irrelevant language.

The researchers put the ChatGPT model to the test to see if it could slash the length of corporate disclosures and provide summaries that were both fat free and effective. They gathered the MD&As and conference-call transcripts of all public US companies from 2009 to 2020, and then took a sample that included 1,790 MD&As from nearly 340 companies and about 8,900 conference calls from almost 370 companies. The researchers then prompted the 3.5 Turbo version of ChatGPT to summarize all the reports without referencing any outside information.

Shorter and clearer

The summarized MD&As and conference-call transcripts were, on average, substantially shorter than the original documents—less than half the size. Cutting out cautious language and generic statements contained in many of the longer reports provided more accurate assessment of the genuine sentiment—whether positive or negative—expressed in corporate disclosures, the research finds.

Kim, Muhn, and Nikolaev then studied the companies’ individual stock activity over a two-day window following their disclosures. They find that the clearer sentiment of the summarized reports better explained the price movements that followed disclosures. Additionally, when a company reported losses and displayed negative sentiment in its original report, the amount of bloat (that is, the redundant, irrelevant language not included in the summaries) was generally higher—consistent with the idea that companies seek to obscure downbeat news.

More bloated reports were also associated with a drop in overall price efficiency for a company’s stock. Prices are most efficient when both parties in a stock trade have equal information—and less efficient when one party is more informed than the other. A professional manager might use tools to analyze long reports, but a typical retail investor doesn’t have access to those. Through an estimate based on the statistical model, the researchers find that a 1 standard deviation increase in bloat for MD&As led to a 1.6 percent increase in the probability of “informed trading” (one party being more informed that the other), and thus less-efficient trading.

They also find the added bloat led to a 9 percentage point decrease in the speed of price discovery for a company’s stock, and an 18 percentage point increase in the bid-ask spread (the difference between the maximum price buyers are willing to pay and the minimum price sellers are willing to accept). The higher the bid-ask spread, the more expensive it is to trade.

For conference calls, the analysis indicates that a 1 standard deviation increase in bloat led to a 1.7 percent increase in the probability of informed trading, a 5 percentage point decrease in the speed of price discovery, and a 45 percentage point increase in the bid-ask spread.

Finally, the researchers find that ChatGPT can help investors target specific areas of interest within long financial reports. For example, if they are interested in understanding a company’s dedication to environmental, social, and governance policies, they can prompt the chatbot to target that information and get a clearer view.

Both institutional and retail investors could benefit from ChatGPT’s ability to get to the point of the reports, says Kim, who adds that he is not sure yet whether ChatGPT in its current form can directly help investors build better portfolios or uncover the most lucrative stocks. Instead, he says, it could save them the time and effort of poring over complex documents and help them to better process the most important information. Thus, when making a trade, they can at least have a clearer idea of the fundamentals behind it.

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