Investing Research Articles

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

Are there “trigger” words in risk sections of annual U.S. firm 10-K reports that materially influence buying and selling of associated stocks? In his December 2024 paper entitled “Risky Words and Returns”, Sina Seyfi tests a way to predict stock returns by analyzing the text of risk disclosures in respective firm 10-K reports. Specifically, he… Keep Reading

Should investors expect end-of-day rebounds in intraday loser stocks? In their November 2024 paper entitled “End-of-Day Reversal”, Amar Soebhag, Guido Baltussen and Zhi Da investigate intraday return reversal among individual stocks during the last 30 minutes of the trading day. They segment the 24-hour close-to-close trading day into: (1) overnight (close to open); (2) first… Keep Reading

Below is a weekly summary of our research findings for 12/30/24 through 1/3/25. 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.

Experimental (researcher-imagined) asset markets provide a controlled environment for testing hypotheses about investor behaviors. Do limits on abilities of researchers to model markets realistically, and researcher incentives/motivations, jeopardize the credibility of associated studies? In their December 2024 paper entitled “Do Experimental Asset Market Results Replicate? High-powered Preregistered Replications of 17 Claims”, Christoph Huber, Felix Holzmeister,… Keep Reading

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

How well have popular stock screens worked over the long term and since 2000? In their December 2024 paper entitled “Formula Investing”, Marcel Schwartz and Matthias Hanauer test four popular stock screening formulas with a common portfolio framework over a long period. These formulas focus on certain firm/stock characteristics, implicitly or explicitly translating stock market… Keep Reading

How can cross-currency equity investors best approach hedging the associated currency exchange risk? In their December 2024 paper entitled “The Best Strategies for FX Hedging”, Pedro Castro, Carl Hamill, John Harber, Campbell Harvey and Otto Van Hemert analyze pair-wise dynamic currency exchange risk hedging strategies for global equity markets based on three widely accepted exchange… Keep Reading

Below is a weekly summary of our research findings for 12/23/24 through 12/27/24. 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.

“Predicting Stock Market Return with Stocks-TIPS Yield Delta” summarizes results of a study finding that deviations of the S&P 500 earnings yield from the real government bond yield, as measured by the 10-year Treasury Inflation-Protected Securities (TIPS) coupon yield, has statistical power to predict future stock market returns. To corroborate this finding from an investing… Keep Reading