Stock Markets, Behavior, and the Limits of History.

• Author: Goetzmann, William N.

William N. Goetzmann [*]

Like many of my colleagues in financial economics, I have long been fascinated by the dynamics of the stock market. While the highs and lows of the Dow Jones Industrials Index are a topic of constant discussion in the financial press, the underlying forces behind its movements -- both in the long and the short term -- largely remain a mystery. For example, few scholars have a good explanation for why stock prices on a given day suddenly may be worth 20 percent less than the day before. By the same token, scholars disagree widely over the magnitude of the equity premium -- that is, how much investors expect to be compensated for taking stock market risk over the long term. However, despite our lack of understanding of its daily and long-term motivating forces, most of us are willing to invest a substantial portion of our savings in the stock market.

I have conducted much of my research on the stock market in close collaboration with co-authors intrigued by the same questions. In one way or another, our work has been tied closely to the dominant, underlying model of stock market behavior, Brownian motion, otherwise known as the random walk. In simplest terms, we look at what causes the market's apparent Brownian motion, when the market violates the laws of Brownian motion, and what happens when Brownian motion interacts with the forces of history.

Biologist Robert Brown in 1827 first observed through his microscope the curious random dance of suspended pollen particles, but it took nearly a century for science to understand how the movement results from bombardment by unseen molecules. The impact of tiny particles only could be inferred from motion, not observed directly. Until recently, stock market researchers have confronted the same problem. While we can chart the path of the market on a minute-by-minute basis, we rarely observe who buys, who sells, and how demand and supply shocks affect price movements. We have many interesting theories about how the behavior of different investors moves prices, but empirical evidence on the critical link between observable investor decisions and price dynamics is hard to find.

Investor Behavior and the Brownian Price Process

Despite the dearth of direct empirical links between demand and price changes in asset markets, some interesting exceptions exist. [1] For example, when the composition of the widely held S&P 500 Index changes, investment funds that hold the index need to rebalance. It is now well established that on such rebalancing days, the prices of added stocks move up and the prices of deleted stocks move down. [2] This evidence recently led my co-author Massimo Massa and me to ask whether daily shifts in demand by index funds could move the value of the entire S&P 500 Index rather than moving just one stock. In our NBER Working Paper, [3] we document a positive relationship between daily demand shifts by investors in S&P 500 Index funds and broad movements in the stock market. We reject the hypothesis that the market causes investor behavior: demand shifts are associated only with late-day price dynamics. However, we find some evidence that market declines cause some panic: the outflows are higher following down days. Curiously, we also find that investors respond to measures of the dispersion of beliefs about the market. Thus, while the stock market process very nearly follows a random walk, its random movements in part reflect aggregate daily decisions about the prospects for the market and uncertainty about those prospects.

Although index fund flows are an interesting special case, Massa, K. Geert Rouwenhorst, and I document dramatic correlations between mutual fund flows across broad asset classes. [4] We find that on days when money flows out of bond funds, it flows into stock funds. In effect, individual investor portfolio decisions are correlated strongly in time, suggesting the existence of an aggregate behavioral structure behind price dynamics. Other investigators offer intriguing current research in this area. [5]

Using individual account data from one large index...