Under the assumption that individuals are single-period maximizers of the expected utility of their future wealth, this essay extends the mean-variance security valuation model developed by Sharpe [10], Lintner [4, 5, and 6], and Mossin [7 and 8] to a general parameter-preference model, with and without the simplifications of homogeneous subjective probabilities and the existence of a risk-free security. Results with quadratic and cubic utility are developed as special cases.

Assaults on the “money power” had a profound influence on public policies in twentieth-century America. Tracing the history of the “money trust” controversy through the first half of this century, Professor Carosso concludes that the attacks were largely unjustified, either on economic or legal grounds.

The weighted average cost of capital is a widely used concept in the theoretical literature of finance as well as in the analysis of capital expenditures of business firms. The importance of the concept derives from its use as the cutoff point for investment in capital projects and as an indicator of optimal capital structure. Differences between the weighted average cost of capital and the true overall cost of capital are typically attributed to deviations of market values from book values, changes in the proportional use of specific capital sources, or alterations in the risk characteristics of the stream of payments to owners and creditors. This paper abstracts from the aforementioned problems to focus on the mathematical error of using weighted average cost of capital to represent the true overall capital cost. It is determined that, in general, the calculation of weighted average cost leads to an erroneous value of the minimum acceptable level of return. The fault lies in the general inability to express the root(s) of a polynomial as an algebraic combination of the roots of other related polynomials.

The importance of an explicit consideration of uncertainty in evaluating the economic desirability of investment propositions is generally recognized in contemporary literature on capital budgeting. The emphasis has been on analyzing the effects of uncertainty of future cash-flows which result from an investment on the economic desirability of that investment. However, although future cash-flows are one important source of uncertainty, it should be recognized that other factors may contribute to uncertainty in a significant way. Uncertainty regarding alternate future investment opportunities is of obvious importance in the capital budgeting context. Thus, an investor who makes the best possible investment decision at a given point in time may deplore such a decision a short time afterward simply because his commitment prevents him from exploiting a better opportunity. While it might be assumed implicitly that an investor, in considering his alternatives, ought to include in such deliberations all the courses of action that may become available in the future, this aspect seems important enough to warrant explicit attention.

The purpose of this article is to explore the relevance of the theory of Markov processes to the analysis of stock price movements.

The present study was prompted by the work of Dryden [6], in which aggregate data on United Kingdom share prices were analyzed within a Markovian framework, and which indicated that it might be fruitful to apply the Markov model to more disaggregated data, specifically to individual stock price data.

The interdependence of the optimal investment program and capital prices, when capital and other markets are imperfect, has been one of the least tractable problems in capital budgeting. The nature of the problem is described in Amey [1]. Suggested solutions to the problem may be found in Baumol and Quandt [2], Carleton [3], Hirshleifer [4], Lusztig and Schwab [7], and Weingartner [9]. The purpose of this note is to extend the mathematical results reported by Lusztig and Schwab (L & S) and draw implications that will shed light on the controversy.