We present a dynamic theory of prices and volume in asset bubbles. In our framework, predictable price increases endogenously attract short-term investors more strongly than long-term investors. Short-term investors amplify volume by selling more frequently, and they destabilize prices through positive feedback. Our model predicts a lead lag relationship between volume and prices that we confirm in the 2000-2011 US housing bubble. Using data on 50 million home sales from this episode, we document that much of the variation in volume arose from the rise and fall in short-term investment.
The role of speculation in driving asset prices has long been a topic of debate among economists (Keynes, 1936; Fama, 1970; Shiller, 1981; Black, 1986).Modern empirical work on“ speculative dynamics” begins with Cutler et al. (1991), who document short-run momentum and long-run reversals in the prices of many diverse assets. These patterns are especially strong during asset bubbles, which have drawn attention due to their frenzied activity and subsequent social costs ( Shiller, 2005; Glaeser, 2013). Several distinct theories have been offered to explain these asset pricing facts.2This paper explores a less studied feature of asset bubbles—the speculative dynamics of volume. Large movements in transaction volume consistently accompany price cycles (Stein,1995; Genesove and Mayer, 2001; Hong and Stein, 2007), yet many theories of bubbles ignore implications for volume. As Cochrane (2011) writes. Every asset price “bubble” has coincided with a similar trading frenzy, from Dutch tulips in 1620 to Miami condos in 2006.  Is this a coincidence? Do prices rise and fall for other reasons, and large trading volume follows, with no effect on price? Or is the high price. . . explained at least in part by the huge volume.
To make this a deep theory, we must answer why people trade so much and plots time series patterns in prices and volume for four distinct bubble episodes  the 2000-2011 US housing market, the 1995-2005 market in technology stocks, the experimental bubbles studied by Smith et al. (1988), and the 1985-1995 Japanese stock market. During these episodes, prices and volume comove strongly. The figures also reveal a more nuanced feature of the data: in each case, volume peaks well before prices. Improving our understanding of bubbles requires focus on the complex, joint dynamics of prices and volume. To take up this challenge, we first present a simple model of the joint speculative dynamics of prices and volume during bubbles. Following past work, the model features extrapolative expectations investors expect prices to increase after past increases. The model departs from past work in two ways. First, instead of the standard dichotomy between feedback traders and rational arbitrageurs, investors differ not in their beliefs but in their expected investment horizons. Some buyers plan to sell after one year, while others plan to hold or many years.