For financial management to make wealth maximizing capital budgeting decisions, a model that will determine correctly the market value of a project's levered cash flows is required. A capital budgeting model should account not only for the effects of the investment decision, but also for the effects of the financing decision and the interactions between the two decisions. In perfect capital markets all the effects of the financing decision pertain to the tax shield created by debt financing. Thus, as originally shown by Modigliani and Miller [8], the value of a project's levered cash flow stream equals the market value the stream would have if it were unlevered plus the market value of the stream of tax savings on interest payments associated with the debt employed to finance the project. While this result is completely general with respect to the specific processes utilized by the market to value the two components, MM specified the value of the unlevered component as the present value of the unlevered cash flows discounted at the appropriate risk adjusted unlevered cost of capital and they specified the value of the tax savings component as the present value of the tax shield on interest discounted at the cost of debt. Accordingly, the value of a project's levered cash flows is specified as the sum of these two present values, one representing the effects of the investment decision and the other capturing the effects of the financing decision. The MM valuation model has been extended to normative capital budgeting analysis by Myers [9] in terms of the adjusted present value (APV) model.

As an operational objective for firm management, the market value maximization criterion derives its theoretical validity from the Fisherian separation principle which states that production decisions for an economy can be made without regard to consumer-investors' preferences for consumption, given perfectly competitive markets. In other words, if the firm's activities do not affect the prices of consumptive goods, then maximizing the wealth of its shareholders will lead to a maximization of each shareholder's utility. Not only does this optimality criterion avoid the ambiguities and vagaries of constructing an aggregate shareholder preference function, but when implemented as a firm decision rule, should result in the same production plan that each investor would select himself, and thereby should represent a Pareto optimal allocation of resources: (Hirshleifer [5, Chapters 1, 9]; Fama and Miller [3, Chapters 2, 7]; and more recently, Ekern and Wilson [2], Merton-Subrahmanyam [7], LeRoy [6]).

Beta coefficients were initially defined by Sharpe [11] as the slope term in the simple linear regression function where the rate of return on a market index was the independent variable and a security's rate of return was the dependent variable. As indicated by Brenner and Smidt [4], accurate estimation of beta coefficients is important for at least two reasons. First, they are important for understanding risk-return relationships in capital market theory. Second, they are important for use in making investment decisions. Some confusion has appeared, however, in recent research regarding both the optimal estimation interval and the intertemporal stability of beta coefficients. The purpose of this paper is to examine this confusion and present new evidence on the estimation and stability of beta.

In capital budgeting when the net present value method (NPV) is used and future cash flows are uncertain, the measurement of the standard deviation of the project's net present value (σNPV) is unusually difficult. Typically the investment life of the project is more than one year, and the cash flows of each period are correlated with each other. The difficulty in determining the exact inter-temporal correlation (ρt, t+l) of cash flows creates special problems in estimating the overall variance of the investment project. For example, see [5, pp. 125–131]. This paper attempts to isolate the possible impact of the inter-temporal correlation of cash flows upon the total risk of the project under the assumption that the standard deviations of cash flows for each time period of the project are known. It also provides upper and lower bounds of σNPV for a multi-period investment project where the degree of the inter-temporal correlation is not exactly known.

Avner Kalay makes a point that managerial reluctance to cut dividends is a necessary condition for the existence of a signaling equilibrium in which dividends are employed as a signaling device. He argues, however, that the available empirical evidence is unable to confirm the reluctance to cut dividends. In particular, the well-known Lintner's (1956) partial adjustment model, which is often cited in support of the reluctance to cut dividends, is empirically indistinguishable from an alternative model which is devoid of such a reluctance. Kalay then conducts an alternative test, but it too leads to an inconclusive result on the issue.

In a recent paper the net present value (NPV) accept-reject decision rule, invoking the conventional definition of expected net cash flows of a finite, uneven character along with a weighted average cost of capital, was derived from the condition of shareholder wealth maximization (Beranek [2]). Since the entire textbook-NPV expression was established–its logical form, the content of its variables, and the implied specification of its parameters–this has served as a partial rescue of textbook approaches to capital budgeting, approaches which had heretofore rested on an intuitive basis. But attempts to rescue textbook treatments of mutually exclusive (ME) choices and capital rationing must fail. Explaining why they must fail, and developing what we shall denote as the AB alternative solution, is the object of this paper.

Among the many financial problems facing managers of firms, capital budgeting problems are often the most important. Over the years these problems have received considerable attention from financial economists with more recent work emphasizing two separate approaches. One currently popular approach to capital budgeting is based on the simple linear relationship between risk and return from the intertemporal capital asset pricing model (CAPM) of Merton [20]. Papers in this category include Brennan [7], Bogue and Roll [4], Treynor and Black [26], Myers and Turnbull [21], Fama [15], Bhattacharya [2], and Constantinides [9].

Statistical estimates of securities' systematic risk and the Market Model R2 are not invariant to the length of the differencing interval over which securities' returns are measured. This phenomenon, referred to as “The Intervaling Effect,” has been widely observed and discussed in the literature. Assuming that returns are multiplicative and independently distributed, Levhari and Levy [7] have developed a model that explains the intervaling effect on systematic risk for differencing intervals of one to 30 months. However, with intervals as, short as a day, their independence assumption does not usually hold.

During the past 20 years several theoretical valuation models with empirically testable implications regarding the impact of financial decisions, particularly debt policy and dividend policy, have appeared in the financial literature. Some of these models have been subjected to extensive testing. However, results of these investigations are inconclusive and/or conflicting as to the impact of financial policies on share value. For instance, on the basis of a study of electric utility firms, Miller and Modigliani (M&M) find that neither dividend nor debt policies of the firm affect the value of the firm. On the other hand, Weston, as well as Brigham and Gordon, disagree with M&M's findings based upon their own investigations of electric utility firms.

Several recent studies of the capital asset pricing model were designed to improve the understanding of the pricing of capital assets by expanding the singlefactor market model to include macroeconomic information, industry influences and individual firm characteristics. Stone [20] has offered another means of expanding the market model. He has proposed a two-index model consisting of the traditional “equity market” index and a “debt market” index. Stone justified the model by arguing that individual equity securities exhibit varying degrees of sensitivity to interest rates and that the opportunity to invest in risky debt securities may represent an attractive alternative to riskless assets and risky equity securities. He indicated the incorporation of an index for the return on debt in the market model might improve its explanatory power for such securities as “…gold, bank, savings and loan, public utility, and similar stocks exhibiting considerable interest rate sensitivity [20, p. 710].”

The problems associated with the investment horizon and systematic risk estimation have been investigated in some detail. Jensen [7] has shown that investment horizon has some impact on the estimated systematic risk; Cheng and Deets [1] have raised some questions about Jensen's instantaneous systematic risk estimation method; Lee [9] has derived the relationship between the estimated instantaneous systematic risk and the estimated finite systematic risk; Levhari and Levy [11] have shown that there exist some relationships between the magnitude of estimated systematic risk and the length of investment horizon; based upon Zellner and Montimarquette's [19] time aggregation technique, Lee and Morimune [10] have shown that the investment horizon problem can be treated either as a time aggregation problem or as a specification problem. However, systematic risk estimates in terms of additive and multiplicative rates of return have not been investigated in detail. The purpose of this paper is to employ the time aggregation technique proposed by Zellner and Montimarquette [19] to investigate the impact of time aggregation on systematic risk associated with the market model. It is shown that autocorrelation and variation in market rates of return are two important factors in determining the magnitude of the estimated systematic risk associated with additive as well as multiplicative models.

The rapid advancement of technology leading to quicker obsolescence, shorter life cycles, and more intensive competition has resulted in renewed emphasis on the abandonment and replacement decision in the analysis of investment projects. Once an investment was undertaken, many corporations in the past often abandoned a project only when it either suddenly ceased to function, or else when it became so unprofitable that abandonment was literally forced. Several authors have demonstrated that a project could be abandoned well before any of these terminal conditions existed. Robicheck and Van Home, for instance [14], showed that an asset could be abandoned even though it may be expected to generate positive cash flows in subsequent years. Dyl and Long (DL) [6], in a modification to the Robichek and Van Home (RVH) model regarding the year of abandonment, suggested that rather than abandoning a project at the earliest time–whenever the abandonment value exceeded the present value of all subsequent future flows– all possible cases of abandonment over the life of the asset should be considered. In this manner, the procedure is to select the highest net present value of an asset over all cash flow and abandonment possibilities. This result particularly holds when all projects have the same degree of risk and when there are frictionless markets and no capital rationing.

The convertible bond is a hybrid security which, while retaining most of the characteristics of straight debt, offers, in addition, the upside potential associated with theunderlying common stock. As a quid pro quo for the upside potential the convertible bond is typically subordinated to other corporate debt and carries a lower coupon rate than would an otherwise equivalent straight bond.

Since the early 1960's the European capital market has witnessed rapid growth as a source of short- and long-term dollar denominated funds to international borrowers and as an alternative investment area to potential lenders. While considerable work has analyzed the determinants of short-term dollar denominated Eurorates (Eurodollar yields), less work has concentrated on the determinants of long-term dollar denominated ($Eurobond) yields. In addition, work on the determinants of long-term $Eurobond rates has been conducted on data derived from periods of fixed exchange rates and capital controls and may not be applicable to periods of post-capital controls or floating exchange rates. Theoretically, there should exist a strong relationship between yield levels and yield changes in domestic and foreign securities under a fixed exchange rate system. Under a floating exchange rate system, however, domestic yield levels may move independently of foreign yields with the exchange rate adjusting price differentials. In addition, in a period of capital controls, the $Eurobond market and U.S. bond market may not necessarily be regarded as competing segments of a larger market or dollar denominated financial assets. The existence of a floating rate exchange system and the removal of U.S. capital controls may have, therefore, affected the relative behavior of $Eurobond, U.S., and foreign security yields. While previous studies have analyzed $Eurobond yields under fixed exchange rates and capital controls, in this paper we also have analyzed $Eurobond yields under floating rates and post-capital controls.

More than ten years have passed since Bierman and West [1] and Elton and Gruber [5] first used valuation models to study corporate stock repurchasing. Young [29] followed their work with an empirical investigation of the motivations for stock repurchasing and its impact on prices. Following Young, there seems to have been a five-year pause in the study of repurchasing. However, by 1973 repurchasing activity had increased in intensity, and this seems to have rekindled an interest in studying the phenomenon.

Since the early work of Durand (1941), there has been considerable interest in using quantitative models of consumer credit behavior for credit-granting decisions. Most models are based on the concept of “scoring” by use of weights usually determined as statistically significant coefficients of some linear statistical model, frequently the linear discriminant model. It is the purpose of this note, however, to propose maximum likelihood estimation of the logit model as an alternative, and to compare the two models in a “scoring experiment.”

In a recent issue of the Journal of Financial and Quantitative Analysis, Bernhard [2] has pointed out and discussed the seemingly paradoxical possibility that P < 0 even though there is a unique r in the [0, ∞) interval, and that r > it for all t. He showed that this can happen when there are one or more additional values of r in the (−1, 0) interval or when the unique r in the [0, ∞) interval consists of multiple coinciding roots. The further point to be shown here is that it can also happen even when r is unique and simple in the (−1, ∞) interval. Thus the phenomenon is considerably more general than Bernhard had implied.

The valuation of realistically complicated corporate liabilities is arguably one of the most exciting fields in finance today. It is exciting because it seems quite feasible that what was once a somewhat esoteric body of theory may soon be a viable method of valuing actual securities of many kinds. (This promise was, of course, clearly seen at the outset by both Black and Scholes and Merton in their respective seminal papers.)