Paul H. Cootner, The Theorems of Modern Finance in a General Equilibrium Setting: Paradoxes Resolved, The Journal of Financial and Quantitative Analysis, Vol. 12, No. 4, Proceedings of the 1977 Western Finance Association Meeting (Nov., 1977), pp. 553-562

We have formulated the mean-variance models of portfolio selection with stochastic cash demand. The results of the general model have indicated that the characteristic of the investor's stochastic cash demand, the liquidity risks of assets (measured by the covariance between an asset's return and the cash demand), and the structure of transfer costs also play important roles in the determination of the investor's optimal portfolio. We have also shown that the model of portfolio selection with stochastic cash demand can be greatly simplified if the assumption of symmetric transfer costs is invoked. Furthermore, it has been shown that the simplified model can be reformulated and solved by the LP techniques. Thus, LP formulation of portfolio selection with stochastic cash demand should have practical usefulness.Finally, along the line of works by Chen, Jen and Zionts [3, 4], Pogue [14, 15] and Stone and Reback [20], one can extend the analysis in this paper to the problem of dynamic portfolio management with stochastic cash demand and transfer costs.

Consider a productive investment project (or financial security), which would yield a stream of cash flows, positive and negative, over time. A major index of the acceptability of such a project is its internal rate of return, i.e., that rate of interest which discounts all the cash flows from the project to a present worth of zero. Soper [8] has developed a sufficient condition for the internal rate to be unique in the interval, (−1, ∞), along the real line. Then, if the project requires an initial outlay, if Soper's condition holds, and if the unique internal rate exceeds the market rate of interest in each period of the project's life, the project's present worth is positive, and hence, other things being equal, it is worth undertaking.

Ian H. Giddy, A Note on the Macroeconomic Assumptions of International Financial Management, The Journal of Financial and Quantitative Analysis, Vol. 12, No. 4, Proceedings of the 1977 Western Finance Association Meeting (Nov., 1977), pp. 601-605

Richard H. Pettway, The Effects of Large Bank Failures Upon Investors' Risk Cognizance in the Commercial Banking Industry, The Journal of Financial and Quantitative Analysis, Vol. 11, No. 3 (Sep., 1976), pp. 465-477

This brief paper will show that (a) a theoretical equilibrium state of the world exists in the absence of capital controls and trade barriers when prices for the same goods in different markets are equal, after translation at the spot exchange rate; (b) differences in rates of aggregate price change in different markets eventually cause offsetting exchange rate changes which restore condition (a); (c) returns on equivalent securities denominated in different currencies but covered in the forward market are almost instantaneously equalized; (d) the market's expected rate of change of the exchange rate equals, to a close approximation, the control-free interest rate differential between the two currencies; (e) in the absence of predictable exchange market intervention by central banks, the interest rate differential is the best possible forecaster of the future spot rate; and (f) the forward rate also provides the best forecast of the future spot rate. A final corollary identifies a relationship between inflation rates and international interest rate differentials.

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.

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.

In response to the suggestions of the editorial and reviewing staff of this journal, some additional explanation and extensions of the model presented in an earlier paper [4] seem desirable at this time. In that paper the investor in securities was assumed to have a utility function that depended on the first n moments of the statistical distribution of returns rather than just on the mean and variance. When the borrowing-lending possibility was introduced as in the Sharpe-Lintner model, the investor's perceived risk premium could be expressed in the higher moments' dimensions as well as in terms of the variance.

Solving capital budgeting problems with linear and integer programming has been part of the finance literature for some time [21, 22, 23, 7, 14, and 18]. Capital budgeting problems have unique properties that distinguish them from other integer linear problems discussed in the mathematical programming literature. Capital budgeting problems generally have the following characteristics: (1) the matrix tends to be rectangular with more variables than constraints; (2) they are all maximization problems with ≤ constraints and nonnegativity conditions in the general form 0≤xi≤1 in the case of linear programming and xi = 0, 1 in the case of integer problems; and (3) there are often mutually exclusive projects among the variables. The purposes of this note are to illustrate some computational experience using existing integer algorithms to solve a set of capital budgeting problems and to begin to catalog the performance of integer codes on financial problems.