This paper presents a model of equilibrium in a capital market for linear shares of risky firms andin a market for managerial labor in which market participants function as both investors and managers. The model yields interesting and relevant equilibrium conditions that integrate earlier separate treatments of the capital market with human capital and the incentive contracting problem regarding shirking.The theory developed here provides a microeconomic explanation of how the price of risk established in the capital market is relevant to the labor contracting problem. The analysis also provides a logical rationale for the division of responsibilities between a board of directors and the management of the firm.

This paper is concerned with the effect of futures trading in Treasury bills on the volatility of yields in the cash market. It is found that futures trading led to a decrease in volatility initially, but the effect disappeared when futures volume became large and possibly resulted in increased volatility in the secondary cash market. The results also indicated that the deliverable bill appears to sell at a small premium relative to the adjacent maturities prior to the delivery date.

This paper considers two aspects of the tendency for systematic risk to change during the period surrounding a firm-specific event. First, a statistic allowing for heteroskedasticity is presented as a means of more precisely testing for the incidence of structural change in the market model. Secondly, the bias resulting from the imposition of a single, arbitrary event period on every firm in a market efficiency study is formally demonstrated. Using a sample based upon stock splits, the switching regression technique of Quandt is then adapted to show that event intervals are more appropriately considered on a case-by-case basis. A comparison of alternative residual measures illustrates these procedures.

Daily cash forecasting generally requires some method to reflect day-of-month and day-of-week effects. It requires the resolution of multiple seasonals, a problem given scant treatment in the econometrics literature. This paper first presents multiplticative and mixed-effects specifications of day-of-month and day-of-week effects as alternatives to the additive specifications. Then, several important estimation issues pertinent to each specification are investigated, namely collinearity, holiday effects, length-of-month distortion, varying weekly-monthly pattern mix, and daily-monthly consistency.

The paper develops a broad class of distribution-based linear forecasting models in great generality similar to the way that Box and Jenkins [1] provide a broad class of time-series models that can be specialized via parameter selection (specification). In our case, parameter selection (specification) gives particular members of the linear class of distribution models. A particular version can be tested against an alternative specification via hypothesis tests on model parameters.