Tests of financial asset pricing models may yield misleading inferences when properties of the data are used to construct the test statistics. In particular, such tests are often based on returns to portfolios of common stock, where portfolios are constructed by sorting on some empirically motivated characteristic of the securities such as market value of equity. Analytical calculations, Monte Carlo simulations, and two empirical examples show that the effects of this type of data snooping can be substantial.
This article investigates why, in October 1987, almost all stock markets fell together despite widely differing economic circumstances. We construct a model in which “contagion” between markets occurs as a result of attempts by rational agents to infer information from price changes in other markets. This provides a channel through which a “mistake” in one market can be transmitted to other markets. We offer supporting evidence for contagion effects using two different sources of data.
If returns on some stocks systematically lead or lag those of others, a portfolio strategy that sells “winners” and buys “losers” can produce positive expected returns, even if no stock’s returns are negatively autocorrelated as virtually all models of overreaction imply. Using a particular contrarian strategy we show that, despite negative autocorrelation in individual stock returns, weekly portfolio returns are strongly positively autocorrelated and are the result of important cross-autocorrelations. We find that the returns of large stocks lead those of smaller stocks, and we present evidence against overreaction as the only source of contrarian profits.
This article shows that the one-state-variable interest-rate models of Vasicek (1977) and Cox, Ingersoll, and Ross (1985b) can be extended so that they are consistent with both the current term structure of interest rates and either the current volatilities of all spot interest rates or the current volatilities of all forward interest rates. The extended Vasicek model is shown to be very tractable analytically. The article compares option prices obtained using the extended Vasicek model with those obtained using a number of other models.
[When the price process for a long-lived asset is of a mixed jump-diffusion type, pricing of options on that asset by arbitrage is not possible if trading is allowed only in the underlying asset and a riskless bond. Using a general equilibrium framework, we derive and analyze option prices when the underlying asset is the market portfolio with discontinuous returns. The premium for the risk of jumps and the diffusion risk forms a significant part of the prices of the options. In this economy, an attempted replication of call and put options by the Black-Scholes type of trading strategies may require substantial infusion of funds when jumps occur. We study the cost and risk implications of such dynamic hedging plans.]
[We find that conditional means and variances of consumption growth vary through time, and this variation appears to be associated with the business cycle. A pricing model with fluctuating means and variances of consumption growth provides implications about conditional moments of returns for both short and long investment horizons, and these implications are explored empirically. The U-shaped pattern of first-order autocorrelations of returns, as well as business cycle patterns in the price of risk, appears to be consistent with the model, but our exploration suggests that other implications about conditional return moments are at odds with the data.]
[No analytic solution exists for the valuation of American options written on futures contracts and foreign currencies for which early exercise may be optimal. This article formulates the American option valuation problem in economically and mathematically meaningful ways. This enables us to derive valuation formulas for American options. The properties associated with the optimal exercise boundary are examined, and a numerical technique to implement the valuation formulas is presented.]
[Most models of the evolution of wealth and consumption assume that wealth volatility and risk premium are constant. But in fact, volatility declines, and risk premium seems to decline, as wealth rises. A model that allows mean reversion in the sense that the risk premium declines as wealth rises can help explain both the "consumption smoothing puzzle" and the "equity premium puzzle." In an example of such a model that gives us an analytic solution, direct and derived risk aversion are both constant, but differ.]
[Tests of financial asset pricing models may yield misleading inferences when properties of the data are used to construct the test statistics. In particular, such tests are often based on returns to portfolios of common stock, where portfolios are constructed by sorting on some empirically motivated characteristic of the securities such as market value of equity. Analytical calculations, Monte Carlo simulations, and two empirical examples show that the effects of this type of data snooping can be substantial.]