One of the remarkable features of the mean-variance capital asset pricing model is its robustness with respect to changes in assumption (Jensen [1]). An example of this property is given by David Mayers [4], who shows that the structure of prices of marketable assets is unaffected by relaxing the assumption that all risky assets are marketable. The result has been used in the analysis of public sector investments by Stapleton and Subrahmanyam [6]. However, although relative prices are unaffected, the general level may be due to the effect of marketability on the market price of risk.

Throughout the finance and economics literature, it is widely recognized that taxation can significantly alter individual behavior and market equilibrium conditions. Yet, in the area of bonds, the impacts of taxation upon bond pricing have generally been ignored. The primary purpose of this paper is to trace out the impact of differential taxation of regular income and capital gains upon the pricing of coupon-bearing bonds.

The operation and characteristics of the American securities markets have long been major preoccupations of financial research, especially during the last decade. Particular attention has been devoted to the question of whether there exist investment strategies, or investing entities, capable of producing consistently superior investment performance. The general consensus to date is that few, if any, such success stories are observable. Examinations of the value of professional investment research and counsel ([7] [8] [9] [24]), of the payoff from technical trading rules ([11] [13] [18] [20] [26] [34]), and of the investment results of institutional money management ([15] [29] [25] [28]) have, in almost every instance, provided little indication of performance better than that attainable from a simple passive strategy of buying and holding a randomly selected, well-diversified portfolio of securities, after appropriate adjustments for portfolio risk levels are taken into account. The intensive competition in, and rapid information-digesting properties of, the capital market environment have been cited as explanations ([2] [5] [12]).

Much of the current work in the analysis of security returns has been directed towards improving the specification of the Sharpe diagonal capital market model [9]. Because the residuals from the market model for different securities are observed to be correlated, some factor or factors are assumed to be common to large groups of stocks exclusive of the economy-wide influences captured by the market index. King [6], for example, found industry effects to be a significant determinant of security returns. In recent articles in this journal and elsewhere Lee and Lloyd, hereafter (L&L) ([7] [8]) attempt to capture the interaction of firms within an industry. They propose a recursive capital market model, an approach which is attractive because it allows for interaction in the determination of stock prices without the complications of a more fully simultaneous equations model (Simkowitz and Logue [10]). However, the L&L application of the recursive system is not without problems in both theory and application.

Recently, there has been an increased interest in the role that bankruptcy or ruin plays in the valuation process. Several authors have discussed this subject (Gordon [17], Quirk [27], and Smith [35]) and some have constructed theoretical models attempting to show how the probability or risk of ruin introduces an element of risk into valuation (for example, Bierman [5], Borch [8], Tinsely [37]). The question of corporate survival is, therefore, central to the financial considerations of the firm. None, however, has attempted empirical tests of the role of such a probability in valuation.

It Is commonplace within the confines of finance literature to explain variations in the firm's residual income stream via the dichotomy of business risk and financial risk. On an ex-post basis the business risk of the enterprise is a direct result of the firm's investment decision and is, thereby, embodied in its asset structure. It follows that the company's cost structure, product demand characteristics, intra-industry competitive position, and managerial talent all affect its business risk posture.

Since the publication of the work of Modigliani and Miller (MM) in the late 1950s there has been a recurrent controversy in the finance and economics literature about the interdependence of investment and financial variables. The arguments are too well known to recount at any length here. Basically MM would argue that in perfect capital markets, investment is, and should be independent of financing (which we will identify, as they would, with financial variables like dividends and new debt). The opposing view would argue that capital markets are sufficiently imperfect that the firm must consider financing in its investment decision. At least some of the proponents of this other view would argue that the firm must raise funds and allocate these scarce funds between investment and dividends. This view, then, holds that the firm's investment, dividend, and financing decisions are interdependent and must be studied in the context of a simultaneous equation model. There have been many articles discussing the MM position and many attempts to test it empirically. The first to focus directly on the question of interest here was done by Dhrymes and Kurz [1] in 1967. We will attempt to show that, despite several later studies, Dhrymes and Kurz were correct in their assertion that the investment and financing decisions are made simultaneously and must be studied in the context of a simultaneous equation model. To set the stage for our study we shall review the Dhrymes-Kurz study and subsequent related studies and show that each contained some error that affected their results.

It has long been recognized in the literature of finance that the robustness and analytical potential of mathematical programming procedures can be utilized to structure highly complex decision environments and to ascertain quickly and efficiently the dominant set(s) of actions for achieving an explicit objective(s). Although some formulations involve nonlinear relationships (for instance [13] [15]), the vast majority of the models appearing in the finance literature are variants of linear programming, including such identifiable methodologies as linear programming, goal programming, networks, integer programming, mixed integer programming, and chance-constrained programming. The decision processes for capital budgeting ([25] [1] [2] [4] [14] [16] [24]), working capital management ([20] [18] [21] [6]), cash management ([17] [23]), and portfolio selection ([22] [24]), have been structured as linear programs and have contributed significantly to understanding the dynamics of financial systems. Given the potential of these mathematical approaches, the limited industrial use of financial optimization models is disturbing.

The purpose of this paper is to provide evidence on the following question: Are there more banking offices available per person to furnish consumer and business services in branch banking states than in unit banking states? This question is a central part of a broader issue of what limitations should be placed on the ability of individual banks to branch. Indeed, in a recent review of the literature dealing with the branching question, and prepared for the Senate Banking Committee (McIntyre Committee), Guttentag [8] stated: “One of the most pervasive arguments for branch banking is that branch banks provide more office facilities than unit banking.” Yet the available evidence on the question is sparse and existing research contains methodological difficulties which make the findings of questionable value.