A fundamental function of any portfolio selection model is the identification of inefficient portfolios and the consequent reduction of the set of alternative investments that the decision maker must evaluate. In the absence of a specific utility function, the establishment of criteria for the identification of inefficient portfolios must strike a compromise in terms of convenience and effectiveness. Of the myriad possibilities, models employing a criterion based on two parameters have been found most convenient for reasons of simplicity of interpretation and computational feasibility. Certainly, the most popular of the two parameter models has been the expected value-variance (E-V) formulation first proposed by Markowitz [7]. The basic E-V model developed for individual decision making has been extended by Sharpe, Lintner, and others [1, 4, 3, 9] to set forth an extensive theory which seeks to explain the equilibrium price of risky assets. The purpose of the present paper is to review and extend some of the implications of an alternative two-parameter portfolio selection model, called the expected value-semivariance model (E-S). In particular, the discussion focuses on certain contrasts and similarities between the E-V and the E-S models.

On February 1, 1971, the National Association of Security Dealers instituted an automatic quoting system for over-the-counter stocks. Heralded as a major advance in the elimination of market imperfections, the National Association of Security Dealers Automatic Quote System (NASDAQ) allowed bidand- ask prices of different firms in this geographically dispersed market to be centralized. Essentially its operation allowed individual “houses” to obtain the various bid-and-ask prices of market makers for a given unlisted security.

Previous empirical studies of mutual fund performance relative to market performance were conducted using two- and three-moment analysis. This study has applied first-, second-, and third-degree stochastic dominance principles to investigate the same question. Our results support the earlier Sharpe study and oppose the recent Arditti work. From the investor's standpoint, mutual fund performance was inferior to market performance over the period 1954–1963.

A convertible bond is a hybrid financial instrument that incorporates features of a bond (fixed income security) and an equity claim (usually common stock). In most instances the convertible can be exchanged, at the holder's option, for the common shares of the corporation issuing the convertible. The conversion value, or stock value, is the market value of the common shares for which the convertible can be exchanged. The bond value or floor price is the market value of an equivalent bond that does not include a conversion feature. The market price of a convertible will be the conversion value or the bond value, whichever is higher, plus a premium. The purpose of this paper is to develop and test a model which estimates the premium. The premium estimated is defined as the difference between the market price of the convertible and the bond value or conversion value, whichever is larger. No consideration will be given to convertible preferreds.

A relationship between money supply and stock prices is fairly well recognized in the literature. More recently the studies of Hamburger and Kochin [7], Modigliani [12], Keran [9], and Homa and Jaffee [8] have attempted to specify the short- and long-run nature and the direct and indirect nature of these relationships. Also, these studies have focused on determining the transition variables through which the money-supply effect is transmitted to stock prices. A more pragmatic approach is that of Sprinkel [17 and 18] and Palmer [14] who have attempted to analyze the money-supply and stock-market relationships to see if the former can be a predictor of the latter. More reliable forecasts of future market movements, if available, could be extremely useful for individual and institutional investors. At one extreme, information could be used to time the investment in and out of the market portfolio. Alternatively, the investor could more profitably use the B information on market volatility of stocks available from the capital-asset pricing model, relating expected rate of return on a security, E(Ri), with that on the market portfolio, E(Rm). Accordingly, the prediction of the market would indicate when to shift the composition of the portfolio from relatively low to high or from relatively high to low β stocks and cash.

This paper examines a conceptual framework for normative models of financial management in commercial banks. Since the bank is viewed as a financial intermediary, it is argued that the appropriate conceptual framework for bank financial management models is one that focuses on imperfections in the markets in which the bank operates.

This paper has examined the investment performance of the common stock portfolios of 20 property-liability insurance companies over the period 1958–1967. The performance of these portfolios was compared with the performance of both equal-weighted and value-weighted random portfolios of common stocks. The evidence indicated that the returns earned by the insurance companies were significantly lower than the returns earned by random portfolios of equivalent risk.

While this study is not precisely comparable to the previously published studies of mutual funds in terms of either the methodology employed or the time period considered, the results are quite similar. An additional group of institutional investors can be seen not to have outperformed the “market.” The presumption of inferior performance is even stronger in the case of the property-liability companies because all the comparisons in this study were made on a gross basis. Most of the studies of mutual fund performance have compared fund returns net of investment expenses to the gross returns from random investments. In those instances where comparisons were made on a gross basis, the performance of fund portfolios was found to be very similar to the performance of random investments.

Traditional planning for working capital needs is typically conducted with a relatively short time horizon. In this process, management attempts to optimize the return on existing fixed assets. The period for capital investment planning is much longer, reflecting the irreversibility of these decisions. Current research in the two areas tends to dichotomize these decision processes. The implications seem to be that working capital policies only have impact in the short run. However, it is clear that cash flows for potential capital expenditures are based on assumptions relative to expected future demand and production to meet this demand—assumptions that are necessarily tied to working capital commitments in the long run. The overall planning for credit, inventory, and liquidity should, therefore, be carried out before, or simultaneously with, the capital investment decision. It is a planning requirement that becomes an integral part of the total asset planning system. The vast majority of existing working capital models or long-term capital planning models do not allow for the explicit existence of and the simultaneous interrelationships between these two important subsystems.

Selection of funding levels for research and development (R & D) projects is a major problem facing the firm. Models for selecting funding levels have frequently been formulated under the assumptions that the projects can be evaluated independently (Aldrich [1], Hess [4], Lucas [6]) or that the projects are interrelated only in terms of requirements for specialized input resources (Asher [2]). In fact, the projects of a given firm are likely to be highly interdependent, either in the sense that progress on one project eases work on another (research interdependency) or in the sense that completion of one project alters the market situation of another (output interdependency). While Weingartner [8] discusses these interdependencies, he does so under the assumption that the project funding level is fixed.

It is widely assumed in portfolio theory that investors are risk-averse expected-utility maximizers. There is a good theoretical reason for assuming expected-utility maximization. Such behavior is well known to be consistent with several quite plausible postulates of rationality [5]. On the other hand, the main empirical foundation for such behavior in portfolio selection appears to be the observation of diversification. Risk-averse, expected-utility maximization implies diversification in portfolio selection, and investors are observed to diversify.