<div> The Asset Allocation Wisdom of Wall Street: Implied <span>Beliefs from Target Date Fund Allocations</span></div>

SSRN Electronic Journal · 2026-01-01

Big Data Meets the Turbulent Oil Market

Financial Analysts Journal · 2026-01-02

Credit Information in Earnings Calls

SSRN Electronic Journal · 2025-01-01 · 1 citations

Factor Model Selection Using the ICAPM

SSRN Electronic Journal · 2025-01-01

Does Overnight News Explain Overnight Returns?

ArXiv.org · 2025-07-06

Over the past 30 years, nearly all the gains in the U.S. stock market have been earned overnight, while average intraday returns have been negative or flat. We find that a large part of this effect can be explained through features of intraday and overnight news. Our analysis uses a collection of 2.4 million news articles. We apply a novel technique for supervised topic analysis that selects news topics based on their ability to explain contemporaneous market returns. We find that time variation in the prevalence of news topics and differences in the responses to news topics both contribute to the difference in intraday and overnight returns. In out-of-sample tests, our approach forecasts which stocks will do particularly well overnight and particularly poorly intraday. Our approach also helps explain patterns of continuation and reversal in intraday and overnight returns. We contrast the effect of news with other mechanisms proposed in the literature to explain overnight returns.

Does Overnight News Explain Overnight Returns?

SSRN Electronic Journal · 2025-01-01

Time Variation in the News–Returns Relationship—ERRATUM

Journal of Financial and Quantitative Analysis · 2024-10-04

New News is Bad News

arXiv (Cornell University) · 2023-09-11

An increase in the novelty of news predicts negative stock market returns and negative macroeconomic outcomes over the next year. We quantify news novelty - changes in the distribution of news text - through an entropy measure, calculated using a recurrent neural network applied to a large news corpus. Entropy is a better out-of-sample predictor of market returns than a collection of standard measures. Cross-sectional entropy exposure carries a negative risk premium, suggesting that assets that positively covary with entropy hedge the aggregate risk associated with shifting news language. Entropy risk cannot be explained by existing long-short factors.

News and Markets in the Time of COVID-19

Journal of Financial and Quantitative Analysis · 2023-10-31 · 13 citations

Abstract The onset of COVID-19 was characterized by voluminous, negative news. Higher narrativity news topics (measured by textual proximity to articles describing the 1987 stock market crash and textual distance from Federal Reserve communications) were systematically associated with contemporaneous market responses, which were larger on high volatility days (hypersensitivity), and with markets–news feedback. Hypersensitive news topic-market pairs were associated with next-day reversals. A test using the news–markets relationship identifies a mid-March 2020 structural break, which was knowable by the end of April. Post break, markets and news became considerably less coupled, and hypersensitivity and reversals abated.

Time Variation in the News–Returns Relationship

Journal of Financial and Quantitative Analysis · 2023 · 13 citations

• Econometrics
• Economics
• Physics

Abstract The speed of stock price reaction to news exhibits substantial time variation. Higher risk-bearing capacity of financial intermediaries, lower passive ownership of stocks, and more informative news increase price responses to contemporaneous news; surprisingly, these interaction variables also increase price responses to lagged news (underreaction). A simple model with limited attention and three investor types (institutional, noninstitutional, and passive) predicts the observed variation in news responses. A long–short trading strategy based on news sentiment earns high returns, which increase when conditioning on the interaction variables. The interactions we document are robust to the choice of news source.