Knowledge that Transforms

Alternative ways of conducting inference and measurement for long-horizon forecasting are explored with an application to dividend yields as predictors of stock returns. Monte Carlo analysis indicates that the Hansen and Hodrick (1980) procedure is biased at long horizons, but the alternatives perform better. These include an estimator derived under the null hypothesis as in Richardson and Smith (1991), a reformulation of the regression as in Jegadeesh (1990), and a vector autoregression (VAR) as in Campbell and Shiller (1988), Kandel and Stambaugh (1988), and Campbell (1991). The statistical properties of long-horizon statistics generated from the VAR indicate interesting patterns in expected stock returns.

It is generally agreed that speculators can make profits from insider trading or from the release of false information. Both forms of stock-price manipulation have now been made illegal. In this article, we ask whether it is possible to make profits from a different kind of manipulation, in which an uninformed speculator simply buys and sells shares. We show that in a rational expectations framework, where all agents maximize expected utility, it is possible for an uninformed manipulator to make a profit, provided investors attach a positive probability to the manipulator being an informed trader.

Two homogeneous stocks of physical capital are located in two different countries, separated by an "ocean." They are consumed by local residents, invested in a random production process yielding real returns, or transferred abroad. Under proportional transfer costs, trade, consumption, and capital imbalances are shown to be persistent. The heteroskedastic process for the relative price of capital in the two countries has a nonlinear, mean-reverting drift. Nevertheless, the conditional probability of the price moving from the parity value of unity is greater than the probability of it moving toward parity. The real interest-rate differential incorporates a simple risk premium. Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies.

The intraday lead–lag relation between returns of the Major Market cash index and returns of the Major Market Index futures and S&P 500 futures is investigated. Empirical results show strong evidence that the futures leads the cash index and weak evidence that the cash index leads the futures. The asymmetric lead–lag relation holds between the futures and all component stocks, including those that trade in almost every five-minute interval. Evidence indicates that when more stocks move together (market-wide information) the futures leads the cash index to a greater degree. This suggests that the futures market is the main source of market-wide information.

Recent evidence suggests that past mutual fund performance predicts future performance. We analyze the relationship between volatility and returns in a sample that is truncated by survivorship and show that this relationship gives rise to the appearance of predictability. We present some numerical examples to show that this effect can be strong enough to account for the strength of evidence favoring return predictability. Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies.

We undertake a comprehensive investigation of price and volume co-movement using daily New York Stock Exchange data from 1928 to 1987. We adjust the data to take into account well-known calendar effects and long-run trends. To describe the process, we use a seminonparametric estimate of the joint density of current price change and volume conditional on past price changes and volume. Four empirical regularities are found: (i) positive correlation between conditional volatility and volume; (ii) large price movements are followed by high volume; (iii) conditioning on lagged volume substantially attenuates the “leverage” effect; and (iv) after conditioning on lagged volume, there is a positive risk-return relation.

Alternative ways of conducting inference and measurement for long-horizon forecasting are explored with an application to dividend yields as predictors of stock returns. Monte Carlo analysis indicates that the L. Hansen and R. Hodrick (1980) procedure is biased at long horizons, but the alternatives perform better. These include an estimator derived under the null hypothesis as in M. Richardson and T. Smith (1991), a reformulation of the regression as in N. Jegadeesh (1990), and a vector autoregression (VAR) as in J. Campbell and R. Shiller (1988), S. Kandel and R. Stambaugh (1988), and J. Campbell (1991). The statistical properties of long-horizon statistics generated from the VAR indicate interesting patterns in expected stock returns. Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies.

An integrated econometric view of maximum likelihood methods and more traditional two-pass approaches to estimating beta-pricing models is presented. Several aspects of the well-known “errors-in-variables problem ” are considered, and an earlier conjecture concerning the merits of simultaneous estimation of beta and price of risk parameters is evaluated. The traditional inference procedure is found, under standard assumptions, to overstate the precision of price of risk estimates and an asymptotically valid correction is derived. Modifications to accommodate serial correlation in market-wide factors are also discussed Sharpe (1964) and Lintner (1965) demonstrate that, in equilibrium, a financial asset’s expected return must be positively linearly related to its “beta, ” a measure of systematic risk or co-movement with the market portfolio return: 1 This article is an extension of the second chapter of my doctoral dissertation at Carnegie Mellon University. Recent versions were presented in seminars

[We undertake a comprehensive investigation of price and volume co-movement using daily New York Stock Exchange data from 1928 to 1987. We adjust the data to take into account well-known calendar effects and long-run trends. To describe the process, we use a seminonparametric estimate of the joint density of current price change and volume conditional on past price changes and volume. Four empirical regularities are found: (i) positive correlation between conditional volatility and volume; (ii) large price movements are followed by high volume; (iii) conditioning on lagged volume substantially attenuates the "leverage" effect; and (iv) after conditioning on lagged volume, there is a positive risk-return relation.]

[The continuous-time version of Kyle's (1985) model of asset pricing with asymmetric information is studied. It is shown that there is a unique equilibrium pricing rule within a certain class. This pricing rule is obtained in closed form for general distributions of the asset value. A particular example is a lognormal distribution, for which the equilibrium price process is a geometric Brownian motion. General trading strategies are allowed. In equilibrium, the informed agent, who is risk neutral, has many optima, but he does not correlate his trades locally with the noise trades nor does he submit discrete orders.]