It has been suggested that information has the three following uses:

1. Information can be employed to earn trading profits.

2. Information can improve the operating decisions of a firm or group of firms and thereby increase the stock price.

3. Information can reduce the risk of a firm or group of firms and thereby increase the stock price.

The capital asset pricing model of Sharpe [39], Lintner [28], and Mossin [33] has been the basis for many theoretical and empirical studies in capital markets. One criticism of the model hasbeen directed at the assumption that investors optimize in a one-period framework. Fama [7] and Merton [30] have shown that the results of this one-period optimization model are consistent with the results for an intertemporal optimization model if the investment opportunity set is constant over time. Specifically, the relevant parameters for the distributions of risky securities (i.e., conditional means and variances) must be constant over time. Merton has argued that this is a restrictive assumption, but there has been very little empirical evidence to suggest that changes in the investment opportunity set are significant.

This paper analyzes risk-return relationships in regional and national securities markets. Specifically, it presents methods and results of an investigation of simulated portfolios of common stocks traded on the Minnesota over-the-counter (OTC) market and the New York Stock Exchange (NYSE).

The recent experience of increased volatility of exchange rates among major currencies coupled with highly unstable price levels necessitates a more fundamental understanding of exchange risk. This necessity is further enhanced by the increased internationalization of consumption, investment, and other aspects of economic activity.

The arithmetic formulas appearing in the mathematics of finance are practically useless unless one has available either excellent tables and infinite patience, or working computer programs, a machine, and a budget. The present article shows how a number of useful topics in this area can be dealt with effectively by the more tractable mathematics of continuous processes. The methods yield approximate answers of high quality, and in some cases exact answers as well, with small effort, and have obvious applications in “truth in lending” investigations.

A number of studies have recently attempted to explain cross sectional variations in selected characteristics of commercial bank operations through least squares regression analysis.1 Generally, whether the particular study objective was to explain inter bank differences in costs, revenues, profits, or loan rates, several explanatory variables were isolated which varied systematically among banks, and which at least partially explained differences in the dependent variable. The explanatory variables which were shown to be theoretically relevant, and statistically significant, were then interpreted literally and designated as having causal characteristics.

Recent literature, as it has been developing in this journal and others, suggests that a significant change has taken place in the field of finance. The “new finance” has broader and deeper analytic and empirical content. Its relevant characteristics are: (1) a weakening of the traditional distinction between security analysis and corporation finance; (2) an increased emphasis upon financial management as an integral part of the overall management function; (3) greater emphasis upon the relevance of economic theory in the analysis of financial relations; and (4) more attention to the measurement and testing of hypotheses.

In their comment on a paper by Porter, Wart, and Ferguson [7], Professors Frankfurter and Phillips [2] have raised two serious objections to “any attempt to compare and contrast SD and EV efficiency criteria on empirical grounds.” Essentially, they have argued that empirical comparisons of SD and EV selection rules are invalid because:

a. The EV portfolio building algorithms are not allowed to operate in such tests, and

b. While the estimators of true E and V are derived from and supported by elementary sampling theory, there exists no comparable sampling theory for the estimation of total probability functions.

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.

While the value of listing equity securities has been researched extensively, no studies have examined the market reaction to the decision to list corporate debt. Since the listing of corporate bonds on the major exchanges is a significant corporate activity, this study examines the impact of bond listing on shareholder wealth. Using a variety of possible announcement dates as well as cumulative abnormal returns between dates, no detectable market reaction to debt listing is found. Therefore, the listing of corporate bonds does not appear to be valued by the common shareholders of those same firms.

We investigate the Dead Hand Proxy Put, a contractual innovation in corporate debt agreements that may impact hedge fund activism. We find the provision principally in loans, not bonds, and provide evidence linking the adoption of the provision to hedge fund activism. Furthermore, controlling for endogeneity, we find that the provision significantly reduces the cost of loans. Bondholder wealth also increases. Moreover, cross-sectional analysis of share returns reveals that the provision is positively associated with repeat banking relationships and negatively associated with free cash flow problems, suggesting a cost-benefit tradeoff.

We show theoretically that the usual estimated investment strategies will not achieve the optimal Sharpe ratio when the dimensionality is high relative to sample size, and the $ 1/N $ rule is optimal in a 1-factor model with diversifiable risks as dimensionality increases, which explains why it is difficult to beat the $ 1/N $ rule in practice. We also explore conditions under which it can be beaten, and find that we can outperform it by combining it with the estimated rules when $ N $ is small, and by combining it with anomalies or machine learning portfolios, conditional on the profitability of the latter, when $ N $ is large.

We empirically study the strategic behavior of levered firms in competitive and noncompetitive environments. We find that regulation induces firms to increase leverage, and this reduces their ability to compete when deregulation occurs. Large and small levered firms adopt different strategies upon deregulation. Whereas more levered small firms charge higher prices to increase margins at the expense of market shares, highly levered large firms prey on their rivals by increasing output and reducing prices to increase their market shares. The difference in their behavior is due to differences in their probability of bankruptcy and their financing constraints.

Combining experimental data sets from seven individual studies, including 255 asset markets with 2,031 participants, and 36,326 short-term price forecasts, we analyze the role of heterogeneity of beliefs in the organization of trading behavior by reproducing and reconsidering earlier experimental findings. Our results confirm prior evidence that price expectations affect trading behavior. However, heterogeneity in beliefs does not seem to drive overpricing and asset market bubbles, as suggested by earlier studies, and we find no indication of short-term beliefs being better determinants of trading behavior than longer-term beliefs.

How should the lender of last resort provide liquidity to banks during periods of financial distress? During the 2008–2010 crisis, banks avoided borrowing from the Fed’s long-standing discount window but actively participated in its special monetary program, the Term Auction Facility, although both programs had the same borrowing requirements. Using an adverse selection model with endogenous borrowing decisions, we explain why the two programs suffer from different stigma costs and how the introduction of TAF incentivized banks’ borrowing. We discuss the empirical relevance of the model’s predictions.

Central counterparty (CCP) default waterfalls act as the last lines of defense in over-the-counter markets by managing and allocating resources to cover payment defaults. This article examines the impact of variations in waterfall design on financial system losses in the presence of payment network dependencies and frictions in the cleared and noncleared portion of the system. Through the development of a structural model, we draw several theoretical conclusions about the effectiveness of CCP default waterfalls under severe payment stress. These findings are empirically quantified by testing the model using supervisory data for the U.S. credit default swap market.

The most conspicuous deficiency of my study of underwriting compensation is my failure to examine the determinants of underwriting spreads on tax-exempt bond issues. That deficiency has now been remedied by Richard West. Unfortunately, my study was not published very long before West's and there was little opportunity for him to compare his results and speculation with my own. Although a few of the comments below are critical of West, and I point out some alternative interpretations of his statistical findings, this note should be considered a supplement to, rather than a critique of, West's paper.

Using a novel data set of over 3,500 public and private firms, we construct the network of executive and director connections prior to the 1929 financial market crash. We find that more connected firms have 17% higher 10-year survival rates. Consistent with a working capital channel, the results are strongest for small, private, cash-poor firms, and firms located in counties with high bank suspension rates. Moreover, connections to cash-rich firms that increase accounts receivable matter the most. Our results suggest that network connections can play a stabilizing role during a financial crisis by easing the flow of capital to constrained firms.

We show that the similarity of a firm’s technological expertise with that of other firms affects managerial labor market outcomes. Using each firm’s patent portfolio to estimate its technological expertise, we find that its similarity in technological expertise with other firms is strongly related to the benchmark group used for CEO compensation and job transitions. Furthermore, we show that a firm’s CEO pay is positively associated with the CEO compensation levels of technologically similar firms. Our results thus demonstrate the crucial role of technological similarity in determining the value of outside options and the boundaries of the managerial labor market.

Among the topics that have been subjected to intensive research by businessschool scholars over the past two decades, few have received more attention than those which collectively comprise the field of investments. What is more important, even fewer have witnessed the plethora of important research findings that has been forthcoming in the investments field. Indeed, it seems reasonable to argue that in recent years no other business field's research accomplishments have been either as impressive or as generally reinforcing.