Although the effects of pure diversification and synergistic mergers on market valuation have been widely discussed and there have been a number of studies estimating. merger performance using the two-parameter model of Sharpe-Lintner, the investigation of the corporate determinants of beta is of recent vintage. A variation on this theme, namely whether merger activity is impounded into beta and its speed of being impounded, is the focus of the Joehnk-Nielsen (J-N) study.

In a previous issue of this journal Boot and Frankfurter (hereafter B-F) published the results of their study on the optimal mix of short-and-long-term debt. While interesting, their results appear to be open to question on the following grounds:

1. Use of wrong data: The short-term borrowing data used by B-F in their regression analysis include the following items which do not generally and, rightly so, belong to short-term debt:

(a) Reserve for deferred or future income taxes,

(b) Restricted surplus for deferred taxes,

(c) Insurance reserves,

(d) Surplus reserves,

(e) Unamortised debt premium, and

(f) Contributions for constructions.

This paper examines the problem of including intertemporally dependent cash flows in capital budgeting models under uncertainty, including review of previous efforts to resolve this problem. The difficulty involved in estimating autocorrelation coefficients and the magnitude of the error introduced by assuming independence are discussed.

Econometric research in the past two decades has vitnessed a considerable use of dummy variables in regression analysis. The analysis of covariance has long been a standard statistical technique to test the equality of coefficients in linear regressions. While students and researchers are generally aware of the close relationship between the two methods, they are often frustrated at choosing one method instead of the other in practice and wonder whether the two methods lead to the same test results. This note shows that the two methods are equivalent from the point of view of hypothesis testing.

Research in the area of portfolio management and capital markets has led to the development of a fundamental concept of market risk. Through work with the capital asset pricing model, “risk” has been decomposed into systematic or market risk and specific or diversifiable risk. Recent interest has focused on integrating these portfolio theory and capital market concepts with corporate finance. Hamada [5], and others, provide theoretically-based analyses which suggest that differences in degree of market risk should be related to differences in financial management activities and practices.

It has been said [2,4,5,6,7, and 8], and it seems to be widely accepted, that the geometric mean of the price relatives of a group of securities can be interpreted as the return which would have been earned on a portfolio of those securities, managed continuously over time to maintain an equal money investment in each security. This is a theoretical concept which could not be implemented literally by a portfolio manager, but it can still be treated rigorously in a mathematical sense. In a recent paper in this journal Rothstein [8] defined continuous reallocation as the limiting case of a policy which does have an operational definition. He showed that the index corresponding to a policy of the equalization of dollar investments approaches the geometrically averaged index as its limiting value. We shall argue that this interpretation of the geometric mean is a misleading one, since it depends upon assumptions which imply serious market inefficiencies.

This paper presents a descriptive theory of risk that may be applied to capital budgeting decisions. The proposed theory is actually much more general than a theory of financial risk and is consistent with reported laboratory experiments. The essential feature of this theory is the role that risk descriptively plays as a constraint in the decision-making process. Specifically, risk is modeled as a chance constraint such that projects are rejected if the probability of “failure” is larger than some prescribed level. This has the effect of making all investment decisions chance-constrained programming problems, although some classes of problems have trivial solution procedures. In this context, risk serves to “strike out” or eliminate alternatives from consideration.

In his comment [4], Pashmi Thakkar raises two questions concerning our study [1] in three points. Points 1 and 3 have to do with discrediting the existence or proper measurement of our dependent variable, while point 2 argues for a technically biased regression structure resulting in biased estimates.

The authors, Hodges and Schaefer, of the preceding paper [2], taking up where my own article [3] left off, have contributed to a better understanding of the geometric mean index of stock price relatives. Their basic point is that, if in any practical situation a portfolio were managed according to a policy of periodic reallocation, the wealth relative of the portfolio would not be approximated by the geometric index. This is demonstrated through simulation, using randomly generated price sequences as well as empirical data. In addition, they have presented a verbal characterization of the hypothetical portfolio policy whose wealth relative is measured by the mth-order power mean of price relatives discussed in my paper. This policy, as I had stated, is not an intuitively simple one like “maintain equal dollar amounts at all times” or “buy and hold.”

The research report abstracted here addresses the question: do firms of low risk before financial leverage introduce relatively more financial leverage than firms of relatively high risk before leverage? Most of the received theory of corporation finance suggests an affirmative response. Our empirical work encourages us to be far more cautious.

The mathematical difficulties encountered when attempting to express the internal rate of return (IRR) of a combination of two or more investments as a weighted algebraic sum of the individual investments' IRRs has been recognized in the financial literature for some time. However, in a recent issue of this journal, Professors Reilly and Wecker (hereafter R-W) [3] apply the well-known mathematical impossibility of expressing the root(s) of a polynomial as an algebraic combination of the roots of related polynomials to question the validity of the weighted cost of capital (kw) concept.

Professor Melicher has conducted an interesting study of the effects of financial factors on beta coefficients and their variations. He reduced the perennial multicollinearity problem by using a factor analysis to screen the financial variables used in the statistical analysis. This study is another in the growing body of literature concerned with beta coefficients as measures of risk. My comments on this paper will consider separately (1) the research design (i.e., what the study directly covered), and (2) the inferences drawn by the author versus what the beta coefficients and their variation really do measure.

Some recent works dealing with the subject of investment in common stocks have made cautious reference to the potential of some published, leading economic time series as inputs to stock price forecasting models. However, no prominent reports of systematic empirical research of the predictive usefulness of such series have appeared in the literature. Our study was designed to partially correct this seeming oversight.

The purpose of this paper is to obtain some quantitative evidence of whether what has been said of the capital markets of Central Europe is also true for the West-German capital market: that they lack depth, breadth, and resiliency; that they react strongly or even excessively to changes in demand and supply; and that they are vulnerable to adjustments in bank liquidity.

Many important results in the Neoclassical theory of consumer choice are derived from properties of the inverse of the bordered Hessian of a consumer's utility function. It is therefore not surprising that this type of matrix also plays an important part in the theory of portfolio choice. The purpose of this note is to establish a simple property of the inverse of a bordered matrix and to point out its implication for portfolio theory.