We propose and pilot-test a research design for measuring whether corporate exposure to artificial intelligence is priced in the cross-section of US equity returns. The methodology constructs a firm-level AI exposure measure from textual analysis of the Management Discussion and Analysis section of 10-K filings, sor…

We document a structural break in the relationship between the US Treasury yield curve and subsequent NBER recessions that has not, to our knowledge, been systematically characterized in the existing literature. Using monthly FRED data from January 1962 through April 2026, we estimate a probit model of 12-month-ahea…

We document the relationship between the CBOE Volatility Index (VIX) and subsequent realized volatility of the S&P 500 over the period 1990–2025 using 9,066 daily observations. Across the full sample, the VIX has averaged 19.5 (percent annualized), with realized volatility over the subsequent 21 trading days averagi…

We document a robust cross-sectional return premium associated with corporate disclosure of artificial intelligence in 10-K filings. Using a quarterly panel of S&P 1500 constituents from 2021Q1 through 2025Q3, we construct a firm-level AI-exposure measure from textual analysis of the Management Discussion and Analys…

We test whether passively-traded AI-themed exchange-traded funds (ETFs) have delivered risk-adjusted excess returns relative to broad and sector benchmarks over the period 2019–2025. Our sample comprises the four largest AI/robotics ETFs available to US retail investors—BOTZ (Global X Robotics & AI), ROBO (ROBO Glob…