In so far as the concept of systematic risk is predicated on the Sharpe-Lintner theory of capital market equilibrium [5, 4], the time-horizon of systematic risk must conform with the time-horizon of market equilibrium. Since it has been suggested that market equilibrium is instantaneous [3, p. 188], it would follow that systematic risk should also be instantaneous. This paper is, therefore, concerned with the evaluation and measurement of instantaneous risk. Although Jensen [3] has made a similar attempt in a much larger study, we have reason to believe it is not satisfactory. We shall then begin in Section I by discussing Jensen's approach to the horizon problem. In Section II, an alternative procedure of evaluating systematic risk is suggested. Section III concludes the paper by comparing estimates of instantaneous risks based upon weekly returns of 30 Dow-Jones stocks. The motivation behind the paper is obvious. A correct formulation of instantaneous systematic risk is not only a logical extension of the capital market equilibrium theory but is also a yardstick for measuring portfolio performance in terms of risk and return.

The advent of the computer has permitted financial theorists to collect and analyze large amounts of financial data. In the field of investments some of the most important work has focused on historical rates of return in investments in common stocks. The classical study in this area is the Fisher-Lorie study [8, 9] in which intern al rates of return were calculated for every security listed on the New York Stock Exchange from 1926–1965. Other studies related to the area have been complicated by Herzog [10], Fisher [6, 7], Latané and Young [11], Soldofsky and Biderman [12], and Evans [3, 4].

The author derives the limiting properties of the two-stage least squares estimator of an equation in a dynamic simultaneous model when variables are nonstationary and cointegrated. The implication on hypothesis testing is also discussed. It is shown that, in a structural equation approach, what one needs to worry about are the classical issues of identification and estimation, not nonstationarity and cointegration. Conventional formulae for computing the asymptotic covariance of the two-stage least squares estimator and the Wald-type test statistics remain good approximations despite the fact that variables may be integrated.

Identification conditions for binary choice errors-in-variables models are explored. Conditions for the consistency and asymptotic normality of the maximum likelihood estimators of binary choice models with unbounded explanatory variables are given. Two- or three-step estimators to simplify computation are also suggested.

We examine the impact of information asymmetry on a firm's capital structure decisions with a unique information rating scheme that draws from 114 measures over five dimensions of information disclosures on each firm from 2006 to 2012. We find that a firm with high (low) information rating is related to low (high) debt financing and leverage. In particular, a firm that moves from the lowest to the highest information rating experiences a 7.8% reduction in firm leverage on average. This relationship is robust to firm characteristics, incentive conflicts, and the agreement theory of Dittmar and Thakor (2007). Our results suggest that information asymmetry is influential on a firm's pecking order behavior independent of these effects.

Comments on a suggested alternative method based on the distributed lag form of adaptive expectations for estimating the parameters of the partial adjustment and adoptive expectations model. Potential problems of the alternative estimation procedure; Overview of the estimates of parameters by the suggested iterative ordinary least squares method; Findings of the regression model for the partial adjustment coefficient estimates.

[This paper analyzes the adjustment processes of financial ratios in the presence of costly adjustment and information uncertainty. The paper proposes a generalized partial adjustment-adaptive expectations model to characterize dynamic financial ratio adjustment processes. The proposed model incorporates the persistence of changes in industry averages into the process of financial ratio adjustment. The Gauss-Newton nonlinear regression method is used to estimate the structural parameters of the generalized model. Results show that adjustment to target ratios is not instantaneous. Results also show that there are differences in the patterns of ratio adjustment for firms in different industries with different sizes.]

Reviews the book 'International Accounting and Financial Reporting,' by Norlin G. Rueschhoff.

This study examines the impact of the presence of institutional dual‐holders, whose portfolios hold both loans and equity securities of the same firms, on those firms' voluntary disclosures. Using mergers between institutional shareholders and lenders to the same firms as exogenous shocks to identify firms with institutional dual‐holders that have high relative equity ownership, we document that such firms are less likely to provide management forecasts and disclose fewer voluntary 8‐K items. In cross‐sectional analyses, we find that the reduction in voluntary disclosures is more pronounced when institutional dual‐holders have higher board representation and when firms have lower litigation risk. In addition, we find that firms with institutional dual‐holders provide more private disclosures to their lenders via loan contract covenants. Additional analyses indicate that the impact of institutional dual‐holders on corporate disclosures is driven by both their monitoring and trading incentives.