Research papers
Disclaimer: The following papers complement this website but may not use identical outputs as we provide in the user interface.
bloated disclosures: can Chatgpt help investors process information? [ssrn]
Alex Kim, Maximilian Muhn, and Valeri Nikolaev (2023)
Chicago Booth Working Paper, Fama-Miller Center Working Paper, Becker Friedman Institute for Economics Working Paper
Ask GPT about this paper [Link]
We probe the economic usefulness of generative AI in summarizing complex corporate disclosures. The summaries are more effective at explaining stock market reactions to the disclosed information. We show that bloated disclosure is associated with adverse capital market consequences.
from transcripts to insights: uncovering corporate risks using generative ai [ssrn]
Alex Kim, Maximilian Muhn, and Valeri Nikolaev (2023)
Chicago Booth Working Paper, Fama-Miller Center Working Paper, Becker Friedman Institute for Economics Working Paper
Ask GPT about this paper [Link]
We explore the value of generative AI tools in helping investors uncover dimensions of firm-level corporate risk. Using the GPT 3.5 model to generate risk summaries and assessments from the context provided by earnings call transcripts, we show that GPT-based measures possess significant information content and outperform the existing risk measures in predicting (abnormal) firm-level volatility and firms' choices such as investment and innovation.
Learning fundamentals from text [ssrn]
Alex Kim, Maximilian Muhn, Valeri Nikolaev, and Yijing Zhang (2024)
Chicago Booth Working Paper, Fama-Miller Center Working Paper, Becker Friedman Institute for Economics Working Paper
We introduce a novel approach to learning the information that investors react to when processing textual information. We use the attention mechanism that learns to identify content that triggers market reactions to disclosed information. The explanatory power of the attention-based model significantly exceeds that of attention-free models. We then develop and analyze a comprehensive set of topics discussed in companies' annual reports. Segment information, goodwill and intangibles, revenues, and operating income are the topics that receive the most attention from investors. Despite their prominence in the public discourse, sustainability and governance are consistently among the least important topics judging by market reactions. Building on our approach, we show that regulatory interventions can successfully enhance the relevance of textual communication. We also show that firms strategically position information within MD\&A to influence investor focus.