This paper investigates market manipulation trading strategies by large traders in a securities market. A large trader is defined as any investor whose trades change prices. A market manipulation trading strategy is one that generates positive real wealth with no risk. Market manipulation trading strategies are shown to exist under reasonable hypotheses on the equilibrium price process. Sufficient conditions for their nonexistence are also provided.

This paper critically evaluates the claim in recent papers that precisely estimated betas explain the cross-sectional differences in expected returns across size-based portfolios. In these studies, the correlations between firm size and betas across the test portfolios are close to one in magnitude, yielding potentially spurious inferences. This paper shows that when the test portfolios are constructed so that the correlations between firm size and beta are small, the betas explain virtually none of the cross-sectional differences in portfolio returns.

The paper analyzes lead-lag relationships for six major stock market indexes: New York S&P 500, Tokyo Nikkei, London FT–30, Hong Kong Hang Seng, Singapore Straits Times, and Australia All Ordinaries, for time periods before, during, and after the October 1987 market crash. Unidirectional and bidirectional causality tests are conducted by means of the Granger methodology. Practically no lead-lag relationships are found for the pre-crash and post-crash periods. However, important feedback relationships and unidirectional causality are detected for the month of the crash. There is also an increase in contemporaneous causality during and after the month of the crash. In general, our findings suggest that the October 1987 market crash probably was an international crisis of the equity markets and that it might have begun simultaneously in all the national stock markets.

A number of recent papers have reported evidence that stock prices are more volatile than is consistent with efficient markets. We argue that the excess volatility tests address a definition of efficient markets that makes an extreme information assumption. We go on to test a weaker definition of efficient markets, due to Jensen (1978). We show the existence of a profitable trading rule that earns a significantly higher rate of return than a buy-and-hold strategy, and so conclude that stock prices are too volatile, even when judged by this weaker definition.

This paper tests the overreaction hypothesis using monthly data for stocks listed on the Toronto Stock Exchange over the 1950–1988 period. Unlike De Bondt and Thaler (1985), (1987), it finds statistically significant continuation behavior for the next one (and two) year(s) for winners and losers, and insignificant reversal behavior for winners and losers over longer formation/test periods of up to ten years. While the systematic risks of the winners decrease significantly over all test periods, the systematic risks of the losers increase significantly for only the 12-month formation/test periods (unlike Chan (1988)). The only significant change in variance from the formation to test periods occurs for the losers for the 12-month formation/test periods. The findings are robust for January versus non-January and size-based portfolios (unlike Zarowin (1989), (1990)). The findings are robust for various performance measures (specifically, market-adjusted CAR, and the Jensen (1968) and Sharpe (1966) portfolio performance measures).

This paper develops a formal model of the effect of time-varying asymmetric information on the timing and pricing of equity issues when managers are better informed than outside investors. We assume that as time passes, the adverse selection problem becomes more severe as more managers receive a private signal. Under this assumption, the model predicts temporal variation in the quantity of issues, with a bunching of issues after information releases. It also predicts that the price drop at issue announcement increases with the time since the last information release. These predictions are consistent with several recent empirical studies relating equity issues to earnings and dividend announcements.

In a recent study, Tinic and West (1986) empirically reexamine the risk-return relationship posited by the traditional mean-variance CAPM. They find a positive nonlinear relationship between risk and return, except during January when the market rewards bearing nonsystematic risk. This study examines the hypothesis that nonnormality of return distributions may account for some of these anomalous results. We compare Shalit and Yitzhaki's (1984) mean-extended Gini CAPM—an equilibrium asset pricing relation that is independent of the form of the underlying asset distribution—with the traditional CAPM. Our results indicate that the nonlinear risk-return relationship and the size and January effects are robust to nonnormality of return distributions.

Using data that contain bid and ask quotes for both options and stocks, the analysis investigates the constant volatility assumption of the Black-Scholes model. The analysis adjusts for bid-ask spreads and finds evidence that is inconsistent with the constant volatility assumption. Instead, the results reveal a strong negative correlation between volatility and stock price, and they suggest that using a nonconstant volatility model such as the CEV model would be more appropriate to price long-term options. Finally, transaction costs associated with the dynamic hedge tend to increase with an option's maturity, but decrease as a percentage of the option's price.

This paper examines the temporal relationship between interest rates on Treasury securities ranging in maturity from three months to 30 years. We find strong empirical support that the seven Treasury rates selected are cointegrated, a conclusion that is insensitive to the normalization chosen. In particular, the hypothesis of noncointegration is rejected decisively regardless of the rate selected as the dependent variable in the cointegrating equation. To determine whether this information can be used to improve forecasts of Treasury rates, the seven rates are forecasted with a corresponding errorcorrection model that is shown to outperform an augmented VAR model that ignores the cointegration of the rates. The results are consistent with the belief that arbitrage limits the extent to which rates on different maturities of a given security diverge. In addition, the results confirm the appropriateness of imposing a common stochastic process for interest rates in equilibrium models of the term structure.

This paper evaluates a nonparametric sign test for abnormal security price performance in event studies. The sign test statistic examined here does not require a symmetrical distribution of security excess returns for correct specification. Sign test performance is compared to a parametric t-test and a nonparametric rank test. Simulations with daily security return data show that the sign test is better specified under the null hypothesis and often more powerful under the alternative hypothesis than a t-test. The performance of the sign test is dominated by the performance of a rank test, however, indicating that the rank test is preferable to the sign test in obtaining nonparametric inferences concerning abnormal security price performance in event studies.