This study investigates the seasonal pattern of aggregate insider trading to help distinguish between two competing explanations for the seasonal pattern of security returns. The first potential explanation examined is that the January effect arises from predictable changes in turn‐of‐the‐year demand for securities. The second potential explanation examined is that the January effect represents compensation for the higher risk of trading against informed traders at the turn of the year.

Closed‐end funds' discounts contain information in the sense that they can be used to construct portfolios that earn returns exceeding those predicted by the two‐factor capital asset pricing model. The precise nature of the information contained in a discount is not clear, however. This paper provides evidence that the information contained in a discount is an incomplete prediction of the fund's likelihood of being open‐ended profitably.

In this paper, we focus on the optimal demand for futures contracts by an investor with a logarithmic utility function who attempts to hedge a nontraded cash position. When the analysis is conducted in the “cash‐commodity‐price” space, we show that the value function associated with the Bernoulli investor program is not additively separable, thus suggesting that this investor hedges against shifts in the opportunity set as represented by the commodity price. By establishing the equivalence between the cash formulation of the problem and the wealth formulation, we are able to analyze the problem in the “wealth‐commodity‐price” space. In this space, we show the additive separability of the value function when the futures settlement price process is perfectly locally correlated with the commodity price process. The demand for futures in this instance is composed of (a) a mean‐variance term and (b) a minimum‐variance component that is a classic feature of models with nontraded assets. Since the first‐best (nonmyopic) optimum is attained, however, the deviation from a mean‐variance demand should not be interpreted as the expression of a nonmyopic behavior but rather as an attempt to restore a first‐best optimum. On the other hand, when the correlation between the futures price and the underlying commodity price is imperfect, in general, the value function does not separate additively, the first‐best solution cannot be attained, and the optimal futures trading strategy involves a hedging term against shifts in the opportunity set.

This study shows that the competitive‐equilibrium version of the APT may be extended to develop an exact model if idiosyncratic risks obey the Ross separating distribution. The results indicate that one only need add the market portfolio as an extra factor to the factor model in order to obtain an exact asset‐pricing relation. Thus, this study presents an extension and integration of the CAPM and APT. The “empirical” APT is also generalized to allow for some factors to be omitted from the econometric model employed to test the theory. The developed model is extremely robust and may be reduced to the CAPM or expanded to approximate Ross's APT depending upon the number of omitted factors. Further, the importance of the market portfolio is shown to be a monotonic increasing function of the number of omitted factors. Finally, the study demonstrates that, in a finite economy, the pricing‐error bound of the Ross APT in a correlated‐residuals factor structure is an increasing function of the absolute value of market‐residual beta, rather than the weight of the asset in the market portfolio as is the case of uncorrelated factor residuals. However, under the normality assumption, the pricing error becomes an extra component related to the market‐portfolio factor, and the exact asset‐pricing relation is once again obtained.

The author presents a rapidly convergent algorithm to solve the general portfolio problem of maximizing concave utility functions subject to linear constraints. The algorithm is based on an iterative use of the Markowitz critical line method for solving quadratic programs. A simple example, taken from the theory of state‐contingent claims, is worked out in detail. For technical convergence results, the reader is referred to the appropriate mathematical programming literature.

Recent research shows that unsuccessful tender offers may affect target share returns for two years past the offer's announcement. This note examines target returns in the interim between the announcement and one year after the offer's withdrawal. Analyzing a recent sample of targets that did not get another bid in the year following a failed tender offer, this study reaches two conclusions. First, all of an offer's premium disappears by the time failure becomes public. Second, excess returns are zero in the post-failure year. An explanation that is based on the causes of the tender offers' failures is presented.