Paul Glasserman

Swing Pricing for Mutual Funds: Breaking the Feedback Loop Between Fire Sales and Fund Redemptions

Management Science · 2020 · 48 citations

We develop a model of the feedback between mutual fund outflows and asset illiquidity. Following a market shock, alert investors anticipate the impact on a fund’s net asset value (NAV) of other investors’ redemptions and exit first at favorable prices. This first-mover advantage may lead to fund failure through a cycle of falling prices and increasing redemptions. Our analysis shows that (i) the first-mover advantage introduces a nonlinear dependence between a market shock and the aggregate impa…

Investor Information Choice with Macro and Micro Information

The Review of Asset Pricing Studies · 2022 · 27 citations

Abstract We develop a model of information and portfolio choice in which ex ante identical investors choose to specialize because of fixed attention costs required in learning about securities. Without this friction, investors would invest in all securities and would be indifferent across a wide range of information choices. When securities’ dividends depend on an aggregate (macro) risk factor and idiosyncratic (micro) shocks, fixed attention costs lead investors to specialize in either macro or…

Collateralized Networks

Management Science · 2021 · 27 citations

This paper studies the spread of losses and defaults in financial networks with two interrelated features: collateral requirements and alternative contract termination rules. When collateral is committed to a firm’s counterparties, a solvent firm may default if it lacks sufficient liquid assets to meet its payment obligations. Collateral requirements can, thus, increase defaults and payment shortfalls. Moreover, one firm may benefit from the failure of another if the failure frees collateral com…

Time Variation in the News–Returns Relationship

Journal of Financial and Quantitative Analysis · 2023 · 13 citations

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 variati…

Assessing Look-Ahead Bias in Stock Return Predictions Generated By GPT Sentiment Analysis

arXiv (Cornell University) · 2023-09-29 · 12 citations

Large language models (LLMs), including ChatGPT, can extract profitable trading signals from the sentiment in news text. However, backtesting such strategies poses a challenge because LLMs are trained on many years of data, and backtesting produces biased results if the training and backtesting periods overlap. This bias can take two forms: a look-ahead bias, in which the LLM may have specific knowledge of the stock returns that followed a news article, and a distraction effect, in which general…