Rashmi B. Thakkar, Comment: "Dynamics of Corporate Debt Management, Decision Rules, and Some Empirical Evidence", The Journal of Financial and Quantitative Analysis, Vol. 9, No. 6 (Dec., 1974), pp. 1065-1066

Dr. Severn and Professor Laurence present an analysis of the relationships between direct investment, research and development (R & D), and profitability. Early in the paper it is stated that the goal is to provide an explanation for the assumed high internal rate of return on investment abroad. Later it is restated that the paper studies “the profitability of the firm as a whole, rather than its reported profit on foreign assets alone.” Consequently, no evidence is presented of a high return on investment abroad. Indeed, the references to rates of return in the first few pages should be preceded by the word “expected” because these are ex ante returns, whereas the returns analyzed elsewhere in the paper are ex post returns.

Professors Alberts and Archer provide a valuable addition to our understanding of capital markets and how resources are allocated to firms of different asset sizes. Their hypothesis is that the cost of equity capital to smaller firms is higher than it is to larger industrial firms. They test their hypothesis by analyzing the variability of returns of 658 industrial firms and attempt to determine whether variability of return is inversely related to asset size. The authors assume that for all firms Ke must equal the sum of the risk-free rate of interest and a risk premium, when risk is defined by four different measures. Two measures of risk use ex post rates of return on book value and two measures of risk employ ex post rates of return on market value. In the first two cases, risk is defined as variability of the firm alone and, in the second two cases, risk is defined as the firm's variability incorporated with the variability of a market portfolio of securities.

Neil B. Murphy, A Reestimation of the Benston-Bell-Murphy Cost Functions for a Larger Sample with Greater Size and Geographic Dispersion, The Journal of Financial and Quantitative Analysis, Vol. 7, No. 5 (Dec., 1972), pp. 2097-2105

Aggregation of monies must be determined in accord with the theory using the aggregate. This theory must specify aggregation (1) eligibility rules and (2) weights. Four current methods are evaluated on this basis: Fisher's aggregation bases eligibility on significant quantities Vi of monies Mi and attaches quantity weights Vi/Vn (Vn being numeraire). Pesek-Saving aggregation merely substitutes social marginal value weights Vipi/Vnpn. Friedman-Schwartz aggregation has eligibility depend on good subsequent statistical performance and uses weights given by private marginal values (gross of subsidies). Chetty's aggregation has all assets eligible and weighted by cross-elasticities of demand.

This paper examines the random-walk hypothesis in the forward exchange market by applying spectral analysis to the three-month forward rates for dollars against sterling in the period 1961–1967.

Articles by Sharpe [1], Lintner [2], and Hastie [3] introduce concepts of systematic and unsystematic risk associated with portfolio rate of return. Defining risk as variation in portfolio return, such risk comprises two elements:1. Systematic risk or variation, which is the covariation of portfolio rate of return with market rate of return.2. Unsystematic risk or variation, which is the difference between total portfolio variation and systematic variation. Unsystematic variation is therefore variation due to attributes of individual securities.

This paper presents a discrete stochastic programming model for commercial bank bond portfolio management. It differs from previous bond portfolio models in that it provides an optimization technique that explicitly takes into consideration the dynamic nature of the problem and that incorporates risk by treating future cash flows and interest rates as discrete random variables. The model's data requirements and its computational demands are sufficiently limited so that it can be implemented as a normative aid to bond portfolio management. In addition, it can be extended by the addition of other asset and liability categories to serve as a more general model for commercial bank asset and liability management.

Commercial bank portfolio models developed by Hester [6], Porter [11], and Kane and Malkiel [7], among others, relate the structure of an asset portfolio to variation in the level of deposits. Similarly, in a recent application of linear programming to asset management, Cohen and Hammer [3] specify a liquidity constraint based upon deposit fluctuations. However, there have been few empirical studies of the determinants of demand deposit fluctuations. The purpose of this paper is to extend the work of Gramley [4], Rangarajan [12], and Wilkerson [14] on the determinants of deposit variability. In this paper, the analysis will be confined to demand deposit variability.

In a recent article, Donald R. Hodgman set forth a framework for analyzing commercial bank lending behavior which emphasized the relationship of customers to their banks as both depositors and borrowers. Specifically, Hodgman links the borrower's contract rate of interest to the profitability of his deposit account, i.e., banks compete for profitable deposit customers by offering the customer a rate which is lower than the comparable open market rate (adjusted for risk). Hodgman uses the terms deposit relationship and customer relationship to describe this behavior. He argues that compensating balance requirements, the prime rate convention, and provision of services below cost may be viewed as a systematic, rational attempt by commercial banks to maximize long-run profit under existing institutional arrangements when viewed from the perspective of the customer relationship.