This paper develops a hypothesis regarding the factors which influence the average maturity of corporate debt, and the hypothesis is tested with a cross-sectional sample of large industrial firms. The sample consists of 159 companies from the Fortune 500 list of the largest industrial firms as of 1971. A linear regression model is developed with the firm's average debt maturity expressed as a function of the firm's asset maturity, size, variability of income, growth, and the proportion of debt in the firm's capital structure.

This paper tests the Value Additivity Principle (VAP) of financial assets with the pricing of Standard Oil securities in 1912. The results are somewhat mixed: the VAP does not generally describe the daily prices of equivalent Standard Oil portfolios, but it accurately describes their average market values; and the portfolio values display convergent adjustment behavior that tends to equalize them quite rapidly. On balance, these findings are consistent with the VAP.

Several studies have investigated the reaction of the stock market to a firm's changing its method of accounting for external reporting purposes. By contrast, this study investigates the reaction of proper subsets of the stock market to changes in accounting methods–specifically, the reaction of the set of investors in the common stock of the firm which has changed its accounting measurement rules.

The measures of risk proposed by Vinso are properly motivated with a concern for the dynamic nature of a firm's operations. The measures are subject to restrictions in application and interpretation, however. Some of these restrictions were caused by the choice of the Cornish-Fisher expansion to incorporate the adjustment for skewness and the resulting quadratic equation. The problems created by the existence of multiple real or imaginary roots to this equation are unresolved in the paper.

Apart from these problems, the measures do not represent probabilities of ruin; they often significantly understate the true probability. We have shown that the measures related to εrp are applicable only to firms with positive-drift processes and argue that they should be evaluated in a multivariate context.

Current conditions in the money and credit markets, along with the memory of the “crunch” of late 1966, have caused both the managers of financial institutions and their regulators to reconsider their concepts of “liquidity.” Both Minsky and Ritter have argued forcefully that traditional attention paid to balance sheet proportions should be abandoned in favor of an intertemporal analysis of cash flows [6], [7], and [8]. Ritter states that: “With a multidimensional cash flow forecast extending several years into the future, probability estimates can be made regarding potential liquidity needs over time” [8]. The purpose of this paper is to suggest a forecasting method which explicitly deals with the problem of uncertainty. The method is specifically designed for a mutual savings bank, but it could easily be adapted for a savings and loan association and, with perhaps greater effort, a commercial bank.2 In Section I, components of cash inflows and outflows are examined with the general objective of classification according to: (1) degree of uncertainty and (2) degree of management control. A risk analysis simulation model which permits explicit consideration of uncertainty is presented in Section II. Problems of implementing the model are discussed in Section III, while the implications of the analysis for future research are considered in Section IV.

For some time there has been disagreement among financial economists as to the effect of dividend policy on the valuation of a firm under conditions of uncertainty. On one side of the debate Miller and Modigliani (MM) [11] argue that the capitalization rate on shares is independent of the dividend policy of the firm. Gordon [6], [7], [8], and others, on the other hand, reject this proposition and present theories of valuation where share prices and capitalization rates are very much dependent upon the dividend policies of firms.

We trace a corporate governance channel of bank shock transmission into the real economy. Using 1,245 U.S. bank enforcement actions (EAs) issued between 1990 and 2017, we show that when a nonfinancial firm (NFF) and bank share a common director, NFF stock prices fall around bank EAs. Severe EAs elicit more negative returns. During enforcement, valued directors substitute NFF board meeting attendance with bank board meeting attendance. Impaired credit relationships, director reputational damage, and endogenous director selection cannot fully explain our results. These findings imply that shared directors could transmit larger bank shocks into the real economy.

The comment by Linke and Kim correctly observes that the assumption regarding the maintenance of constant proportional use of capital sources is not appropriate for our argument and should be deleted. As our analysis did not make use of this assumption, the two conclusions hold.

1. The weighted average cost of capital calculated with the usual weights (original capital structure proportions) is not in general equal to the discount rate which equates the current value of the firm to the present value of future cash flows.

2. The above conclusion holds for any weights which can be constructed from the cash flows.

Information production associated with derivatives markets is not a sideshow; rather, it has significantly positive spillover effects on an array of corporate decisions of underlying firms. Using a regression-discontinuity design based on exogenous variation in options availability as an instrument for changes in the information environment, we show that options introductions have causal effects on corporate policies on both sides of the balance sheet. Through improved information efficiency, options availability reduces the need for debt and payout, increases efficient investment, and yields superior innovation. We conduct two independent experiments demonstrating that our instrument’s impact is not derived from alternative channels.

This article studies how changes in investor protection regulations affect local entrepreneurial activity, relying on the heterogeneous impact of a 2011 SEC regulation change on the definition of accredited investors across U.S. cities. Using a difference-in-differences approach, I show that cities more affected by the regulation change experienced a significantly larger decrease in local angel financing, entrepreneurial activity, innovation output, employment, and sales. I find that small business loans and second-lien mortgages became entrepreneurs’ partial substitutes for angel investment. My cost-benefit analysis suggests that the costs of protecting angel investors through the 2011 regulation change outweigh its benefits.

The speed of stock price reaction to news exhibits substantial time variation. Higher risk-bearing capacity of financial intermediaries, lower passive ownership of stocks, and more informative news increase price responses to contemporaneous news; surprisingly, these interaction variables also increase price responses to lagged news (underreaction). A simple model with limited attention and three investor types (institutional, noninstitutional, and passive) predicts the observed variation in news responses. A long–short trading strategy based on news sentiment earns high returns, which increase when conditioning on the interaction variables. The interactions we document are robust to the choice of news source.

Nonbank lenders have been playing an increasing role in supplying debt, especially after the Great Recession. How important are the distortions in the greater regulation of banks that differentially limit risk-taking across alternative providers of credit? How might the growing role of nonbanks in credit markets affect financial stability? This selective review addresses these questions and discusses how banks and nonbanks helped provide liquidity to the nonfinancial sector during the COVID-19 pandemic shock. We argue that tighter bank regulation has created incentives for nonbanks to increase their participation in credit markets, a trend that creates concerns about financial stability.

In a series of recent articles ([2], [3], [4], [5]) R. B. Porter and his associates have conducted empirical comparisons of the Mean-Variance (EV) and Stochastic Dominance portfolio choice criteria. The basic methodology of all these studies was first to compute the set of EV-efficient portfolios by an optimizing algorithm, then to find through heuristic methods “stochastically dominant” portfolios, and finally to compare the two. A major finding of these studies was that most EV-efficient portfolios survived the second-degree stochastic dominance (SSD) test against the randomly generated portfolios. The purpose of this note is to show that, for all cases of practical interest, a portion of the EV frontier is a subset of the SSD-efficient set. In other words, we offer here an exact theoretical justification of some empirical results of the aforementioned studies.

This paper is a pioneering effort in the examination of the workings of rationality and efficiency in capital markets. The central theme of the paper is the notion of informational efficiency in markets for durable assets. In its broadest terms this imposes a behavioral constraint on the intertemporal development of the asset markets; in a perfect market the development of the equilibrium over time must not be self-contradictory. Individual agents' anticipations of future developments determine their current actions and these, in turn, determine equilibrium prices. But, tomorrow the process will be repeated and it is at this second step that the possibility of conflict enters. The future development need not fulfill precisely people's previous anticipations, but in a perfectly functioning market it would be difficult to accept a blatant contradiction. To believe that prices are lognormally distributed, for example, and to have that belief generate the same equilibrium price period after period is such a contradiction.

This paper presents the results of a simulation study of the dynamic characteristics of the model built by Professor Chow whose purpose was to study statistically the relevance of the multiplier, accelerator, and liquidity preference as determinants of the national income of the United States.

The coefficient of variation (CV) in investment returns is often presented in introductory finance texts as a measure of project risk [7, 9, 13, 15]. Curiously, the resulting mean-coefficient of variation (MCV) efficiency criterion is usually casually proposed as an alternative to the more widely recommended mean-standard deviation (MSD) definition of efficiency, as if MCV possessed an obvious intuitive appeal for some investors or some investment situations. The pervasiveness of references to CV as a risk measure is perplexing in light of the absence of utility theoretic underpinnings, especially by contrast with the substantial theoretical effort underlying the MSD notion of efficiency [3, 6, 8, 10, 11, 12].