Knowledge that Transforms

In the process of managing a financial institution there are decisions that require special considerations beyond those in other firms. In this paper dividend disbursal practices in the banking firms will be analyzed. The central issue is what part of profits should be distributed and what part should be retained within firms as an addition to the banks' net worth.

The need for a corporate marginal cost of capital to be used for internal accept-reject decisions (either as a rate of discount for net-present-value (NPV) computations or as a “cut-off” rate with the internal rate of return (IRR) criterion) has led numerous textbook writers to advocate some variant of a weighted average cost of capital. These authors agree substantially on how costs of individual sources of capital are to be assessed but are uncertain of how the weights should be determined, whether they should reflect the firm's existing capital structure, a target structure, or the mix, however determined, in the firm's forthcoming capital budget, and whether they should be based on book or market values. Moreover, it is not obvious how book or even market values should be measured. These writers have not proven that their intuitively held definitions do in general, for capital budgeting, imply maximizing shareholder wealth.

Jack Clack Francis' paper is a most interesting and provocative one, because it is the first to present empirical evidence questioning the importance of a distribution's skewness parameter in the investor's decision process. In particular, Francis claims his evidence demonstrates that stock market investors do not consider skewness in choosing among alternative investments.

The first major study of industry effects in market returns was performed by King [2]. He used principal components analysis and clustering techniques on a sample of 63 companies chosen from six 2-digit industries based on Security and Exchange Commission codes. SEC codes are similar to the Standard Industrial Classification codes defined by the U.S. Bureau of the Budget [4]. SIC codes are 4-digit codes based on the principal end product of the firm. They are chosen so that, as the lowest order digit is removed, the companies are aggregated into broader but still similar groups.

Since the appearance in 1969 of Kadar and Russell's paper [1] and in 1970 of Whitmore's paper [4] extending stochastic dominance to the second and third degrees, a considerable interest has developed in stochastic dominance methods as an alternative to moment methods in investment ranking models. The particular attraction of stochastic dominance is that its results are consistent with the expected utility hypothesis without depending on a particular mathematical form of utility function or on a specific type of distribution of investment returns. Although both stochastic dominance ranking models and moment ranking models are based on probability distributions of investment returns, it has been difficult to relate the two types of models mathematically for a complete comparison of results. In this paper the common moments are expressed in terms of successive integrals of a probability density function to allow a systematic comparison of the two methods.

As an alteration of the firm's productive asset portfolio, divestiture is the mirror-image of asset acquisition or merger. Yet, though significant efforts have been expended by researchers into the implications of acquisition and merger, the literature of finance is all but silent on the subject of divestiture.

The purpose of this note is to present a simple computational algorithm to approximate the E, S portfolio selection model. The essential feature of the model is the utilization of the familiar linear programming framework by representing risks as a series of linear constraints. Suppose we have m states and n securities, and we assume the investor is able to specify the contingent returns for all securities in each state. Following [7], we define risk as being the downside deviation from the investor's target rate of return.

New stock financing is assuming increasing significance as a source of funds for private firms. The problem of management of external financing has grown as well. As a practical matter, financial managers must depend on the assistance of underwriters with respect to pricing and distribution of new corporate stock. But recent changes, some set in the context of the capital asset pricing model, imply systematic underpricing of new securities. If these charges are true, the financial manager is faced with the dilemma of paying monopsony profits, or accepting the cost and risk involved in taking the issue to market without the investment banker, or seeking an alternative source of funds. In any event, the process of marketing new equity depends on the relationship among the many characteristics unique to the firm and that firm's cost of equity capital. This paper discussed these interrelated issues.

A market is commonly called thin if a large change in price is associated with a small change in supply or demand. The concept of thinness can refer to the markets for stocks, bonds, any category of financial instrument, or even any type of good. Most frequently, thinness has been casually discussed with regard to bond markets and stock markets.

R. Burr Porter, Roger C. Pfaffenberger, Efficient Algorithms for Conducting Stochastic Dominance Tests on Large Numbers of Portfolios: Reply, The Journal of Financial and Quantitative Analysis, Vol. 10, No. 1 (Mar., 1975), pp. 181-185