Investing Research Articles

How can investors best apply the available array of Large Language Models (LLM) in quantitative strategy development? In his December 2024 paper entitled “The LLM Quant Revolution: From ChatGPT to Wall Street”, William Mann summarizes the use of LLMs in quantitative finance, focusing on: the current state of LLM technology in financial applications; comparison of… Keep Reading

Can large language models (LLMs) mimic expert economic forecasters? In their December 2024 paper entitled “Simulating the Survey of Professional Forecasters”, Anne Hansen, John Horton, Sophia Kazinnik, Daniela Puzzello and Ali Zarifhonarvar employ a set of LLMs (primarily GPT-4o mini) to simulate economic forecasts of experts who participate in the Survey of Professional Forecasters. Specifically,… Keep Reading

Below is a weekly summary of our research findings for 1/22/24 through 1/26/24. These summaries give you a quick snapshot of our content the past week so that you can quickly decide what’s relevant to your investing needs. Subscribers: To receive these weekly digests via email, click here to sign up for our mailing list.

Can ChatGPT find red flags in firm earnings calls? In their January 2024 paper entitled “Unusual Financial Communication – Evidence from ChatGPT, Earnings Calls, and the Stock Market”, Lars Beckmann, Heiner Beckmeyer, Ilias Filippou, Stefan Menze and Guofu Zhou test the ability of ChatGPT-4 Turbo to identify and analyze unusual content and tone aspects of… Keep Reading

What does the body of research say about implications of new social media for financial markets? In their April 2024 paper entitled “Social Media and Finance”, Anthony Cookson, William Mullins and Marina Niessner survey research on social media in finance, distinguishing between research using social media to explore investor behaviors and research on the effects… Keep Reading

Can large language models (LLMs) create financial research? In their December 2024 paper entitled “AI-Powered (Finance) Scholarship”, Robert Novy-Marx and Mihail Velikov describe a process for automatically generating academic finance papers using LLMs and demonstrates its efficacy by producing hundreds of complete papers on stock return predictability. Specifically, they: Identify 31,460 potential stock return predictors… Keep Reading

In the spirit of “Complete Finance Research by LLMs?” and “Mimicking Economic Expertise with LLMs”, we have begun succinctly polling some publicly available large language models (LLM) on various aspects of economics/finance and posting results on our X feed. Some of these polls complement research findings here.

Can large language models (LLM) help improve portfolio performance metrics, portfolio optimization and strategy feature discovery? In his three January-February 2025 papers entitled “AlphaSharpe: LLM-Driven Discovery of Robust Risk-Adjusted Metrics”, “AlphaPortfolio: Discovery of Portfolio Optimization and Allocation Methods Using LLMs” and “AlphaQuant: LLM-Driven Automated Robust Feature Engineering for Quantitative Finance”, Kamer Yuksel explores use of… Keep Reading

Can aggregate, distilled daily stock sentiment and attention, as extracted from financial social media, usefully predict U.S. stock market returns? In their March 2025 paper entitled “Market Signals from Social Media”, Anthony Cookson, Runjing Lu, William Mullins and Marina Niessner construct purified daily sentiment and attention indexes from millions of posts on StockTwits, Twitter and… Keep Reading

How is the growing use of large language models (LLM) in production of academic papers in finance affecting outputs? In their June 2025 paper entitled “Certainly! Generative AI and its Impact on Academic Writing (in Finance)”, Thomas Walther and Marie Dutordoir investigate how use of LLMs has affected academic writing in finance, with focus on… Keep Reading