Bubbles for Fama

Abstract

and the Federal Reserve Bank of Boston for their helpful suggestions. We are especially grateful to Niels Gormsen for extensive advice on Compustat Xpressfeed and independent replication of the results. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. At least one co-author has disclosed a financial relationship of potential relevance for this research. Further information is available online at http://www.nber.org/papers/w23191.ack 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 They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

Psychology-Based Models of Asset Prices and Trading Volume

“…According to the empirical definition suggested here, an episode can only be categorized as a bubble with a high degree of confidence "after the fact," once both the price rise and price decline have been observed. However, Greenwood et al (2018) show that, by conditioning on other observables, it is possible to say, even while the price of an asset is still rising, that there is an increased likelihood that the episode constitutes a bubble -in other words, that the price rise will eventually be followed by a sharp decline.…”

Is U.S. Technology Sector in a Bubble?

“…This definition of the bubbles and crashes also proves that there is predictability of a bubble, since sharp price runups do predict a heightened likelihood of a crash. The probability of a crash after a 100 percent increase in the previous two years is 53 percent (Greenwood et al, 2017).…”

Overconfidence, Information Diffusion, and Mispricing Persistence

“…3 Fama (2014) notes that policy makers and others seem to think of a bubble as an irrational strong price increase that implies a predictable strong decline. Recent discussions of bubbles from a theoretical and empirical perspective are provided by Barberis, Greenwood, Jin, and Shleifer (2018) and Greenwood, Shleifer, and You (2018).…”

“…7 The empirical challenge in identifying asset pricing bubbles has been the lack of observability of the fundamental value which leads to the joint hypothesis problem (Fama, 1970). Recent work by Greenwood, Shleifer, and You (2018) shows that sharp price increases of industries, along with certain characteristics of this run-up, help to forecast the probability of crashes and thereby help to identify and time a bubble. Our work adds to this strand of literature, as we show, on an individual stock basis, that price run-ups can be used to forecast low future returns when paired with indications of limits of arbitrage.…”