What Does Futures Market Interest Tell Us about the Macroeconomy and Asset Prices?

Economists have traditionally viewed futures prices as fully informative about future economic activity and asset prices. We argue that open interest could be more informative than futures prices in the presence of hedging demand and limited risk absorption capacity in futures markets. We find that movements in open interest are highly pro-cyclical, correlated with both macroeconomic activity and movements in asset prices. Movements in commodity market interest predict commodity returns, bond returns, and movements in the short rate even after controlling for other known predictors. To a lesser degree, movements in open interest predict returns in currency, bond, and stock markets.

Simple Forecasts and Paradigm Shifts

We postulate that agents make forecasts using overly simplified models of the world—i. e. , models that only embody a subset of available information. We then go on to study the implications of learning in this environment. Our key premise is that learning is based on a model-selection criterion. Thus if a particular simple model does a poor job of forecasting over a period of time, it is eventually discarded in favor of an alternative, yet equally simple model that would have done better over the same period. This theory makes several distinctive predictions, which, for concreteness, we develop in a stock-market setting. For example, starting with symmetric and homoskedastic fundamentals, the theory yields forecastable variation in the size of the value/glamour differential, in volatility, and in the skewness of returns. Some of these features mirror familiar accounts of stock-price bubbles.

Advisors and Asset Prices: A Model of the Origins of Bubbles

We develop a model of asset price bubbles based on the communication process between advisors and investors. Advisors are well-intentioned and want to maximize the welfare of their advisees (like a parent treats a child). But only some advisors understand the new technology (the tech-savvies); others do not and can only make a downward-biased recommendation (the old-fogies). While smart investors recognize the heterogeneity in advisors, naive ones mistakenly take whatever is said at face value. Tech-savvies inflate their forecasts to signal that they are not old-fogies, since more accurate information about their type improves the welfare of investors in the future. A bubble arises for a wide range of parameters, and its size is maximized when there is a mix of smart and naive investors in the economy. Our model suggests an alternative source for stock over-valuation in addition to investor overreaction to news and sell-side bias.

The Neighbor's Portfolio: Word-of-Mouth Effects in the Holdings and Trade of Money Managers

A mutual-fund manager is more likely to hold (or buy, or sell) a particular stock in any quarter if other managers in the same city are holding (or buying, or selling) that same stock. This pattern shows up even when controlling for the distance between the fund manager and the stock in question, so it is distinct from a local-preference effect. It is also robust to a variety of controls for investment styles. These results can be interpreted in terms of an epidemic model in which investors spread information about stocks to one another by word of mouth.

Social Interaction and Stock-Market Participation

We investigate the idea that stock-market participation is influenced by social interaction. We build a simple model in which any given 'social' investor finds it more attractive to invest in the market when the participation rate among his peers is higher. The model predicts higher participation rates among social investors than among 'non-socials'. It also admits the possibility of multiple social equilibria. We then test the theory using data from the Health and Retirement Study. Social households - defined as those who interact with their neighbors, or who attend church - are indeed substantially more likely to invest in the stock market than non-social households, controlling for other factors like wealth, race, education and risk tolerance. Moreover, consistent with a peer-effects story, the impact of sociability is stronger in states where stock-market participation rates are higher.

The Only Game in Town: Stock-Price Consequences of Local Bias

Theory suggests that, in the presence of local bias, the price of a stock should be decreasing in the ratio of the aggregate book value of firms in its region to the aggregate risk tolerance of investors in its region. We test this proposition using data on U. S. Census regions and states, and find clear-cut support for it. Most of the variation in the ratio of interest comes from differences across regions in aggregate book value per capita. Regions with low population density—e. g. , the Deep South—are home to relatively few firms per capita, which leads to higher stock prices via an “only-game-in-town” effect. This effect is especially pronounced for smaller, less visible firms, where the impact of location on stock prices is roughly 12 percent.

Thy Neighbor's Portfolio: Word-of-Mouth Effects in the Holdings and Trades of Money Managers

A mutual-fund manager is more likely to hold (or buy, or sell) a particular stock in any quarter if other managers in the same city are holding (or buying, or selling) that same stock. This pattern shows up even when controlling for the distance between the fund manager and the stock in question, so it is distinct from a local-preference effect. It is also robust to a variety of controls for investment styles. These results can be interpreted in terms of an epidemic model in which investors spread information about stocks to one another by word of mouth.

The Only Game in Town: Stock-Price Consequences of Local Bias

Theory suggests that, in the presence of local bias, the price of a stock should be decreasing in the ratio of the aggregate book value of firms in its region to the aggregate risk tolerance of investors in its region. We test this proposition using data on U.S. Census regions and states, and find clear-cut support for it. Most of the variation in the ratio of interest comes from differences across regions in aggregate book value per capita. Regions with low population density--e.g., the Deep South--are home to relatively few firms per capita, which leads to higher stock prices via an "only-game-in-town" effect. This effect is especially pronounced for smaller, less visible firms, where the impact of location on stock prices is roughly 12 percent.