We thank Carola Frydman for helpful comments and discussions. We are grateful to Nathaniel Barlow and Jorge Colmenares-Miralles for excellent research assistance and Evan Soltas, SafeGraph, and the Risk Management Institute (RMI) of the National University of Singapore for sharing their data. Please see https://sites.google.com/site/lawrencedwschmidt/covid19 for additional information and data related to the analysis conducted in this paper. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

This paper studies daily investor flows to and from each money market mutual fund during the period surrounding and including the money fund crisis of September 2008. We focus on the determinants of flows in the prime money fund category to shed light on the covariates of money fund runs, since this category was, by far, the most heavily impacted by the money fund crisis. We find that outflows during the crisis period of September 17-19 are concentrated among a small fraction of funds having certain characteristics. Institutional investors focused their run-like behavior on large funds that were part of a complex having large amounts of institutional money funds (as a fraction of all money funds). In addition, such investors were more likely to run from funds with higher yields, lower expense ratios, and higher prior flow volatility, indicating that "hot money" chased yields, but selectively ran from higher-yield funds that were more vulnerable. Our analysis also suggests that prime retail money funds exhibited many of the same behaviors as institutional funds, although at a much slower and more drawnout pace. Our paper provides a framework that is useful in understanding potential further regulatory responses to the crisis.

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Summary A large class of asset pricing models predicts that securities which have high payoffs when market returns are low tend to be more valuable than those with high payoffs when market returns are high. More generally, we expect the projection of the stochastic discount factor on the market portfolio—that is, the discounted pricing kernel evaluated at the market portfolio—to be a monotonically decreasing function of the market portfolio. Numerous recent empirical studies appear to contradict this prediction. The non‐monotonicity of empirical pricing kernel estimates has become known as the pricing kernel puzzle. In this paper we propose and apply a formal statistical test of pricing kernel monotonicity. We apply the test using 17 years of data from the market for European put and call options written on the S&P 500 index. Statistically significant violations of pricing kernel monotonicity occur in a substantial proportion of months, suggesting that observed non‐monotonicities are unlikely to be the product of statistical noise. Copyright © 2014 John Wiley & Sons, Ltd.