In the classical account of a financial market bubble, the price of an asset rises dramatically over the course of a few months or even years, reaching levels that appear to far exceed reasonable valuations of the asset’s future cash flows. These price increases are accompanied by widespread speculation and high trading volume. The bubble eventually ends with a crash, in which prices collapse even more quickly than they rose. Bubble episodes have fascinated economists and historians for centuries (e.g., Mackay 1841, Bagehot 1873, Galbraith 1954, Kindleberger 1978, Shiller 2000), in part because human behavior in bubbles is so hard to explain, and in part because of the devastating side effects of the crash. ... At the heart of the standard historical narratives of bubbles is the concept of extrapolation— the formation of expected returns by investors based on past returns. In these narratives, extrapolators buy assets whose prices have risen because they expect them to keep rising. According to Bagehot (1873), “owners of savings . . . rush into anything that promises speciously, and when they find that these specious investments can be disposed of at a high profit, they rush into them more and more.” ... In this paper, we present a new model of bubbles based on extrapolation. In doing so, we seek to shed light on two key features commonly associated with bubbles. The first is what Kindleberger (1978) called “displacement”—the fact that nearly all bubbles from tulips to South Sea to the 1929 U.S. stock market to the late 1990s internet occur on the back of good fundamental news. ... Second, we would like to explain the crucial fact that bubbles feature very high trading volume (Galbraith 1954, Carlos, Neal, and Wandschneider 2006, Hong and Stein 2007). At first sight, it is not clear how extrapolation can explain this: if, during a bubble, all extrapolators have similarly bullish views, then they would not trade with each other.