Stock-market effectiveness in attracting and retaining firms under public ownership depends not only on stand-alone firms’ net listing benefits but also on gains from merging with a public acquirer. Using a novel merger-adjusted listing count, we show that the dramatic (≈50%) post-1996 U.S. listing decline—often attributed to declining listing benefits—is reversed as the “missing” firms de facto continue existing inside their public acquirers. Our merger adjustment also eliminates the U.S. listing gap, pointing instead to a distinct U.S. listing advantage: providing access to a well-functioning market for complex merger transactions.

We study trading and risk management decisions of banks in over-the-counter markets, accounting for 2 types of risk: payoff risk from loans and counterparty risk from trading activities. Our model provides empirically supported predictions on the structure of the interbank credit default swap (CDS) market: i) banks with high default probabilities either buy or sell CDS contracts; ii) because of the counterparty risk friction, payoff risk is only partially shared; and iii) safe banks act as intermediaries and help diversify counterparty risk. Banks manage their default probabilities to become creditworthy counterparties, but they do so in a socially inefficient way.

We investigate the dynamics of observed and target leverage ratios and deviations from the targets. The cross-sectional persistence in leverage ratios is driven by persistent targets, whereas time-series variation is driven by transitory deviations from targets. Consistent with dynamic trade-off theories, persistence is higher when the costs of deviating from targets are lower and when the adjustment costs are higher. Deviations are less persistent for firms that are over-levered and firms that are smaller, younger, or more focused or that have lower credit ratings. In recessions, excess leverage is less persistent for larger firms and is more persistent for smaller firms.

This article shows how structured financing can be used to solve the asset substitution problem in a dynamic setting. Structuring induces the firm’s owner to optimally choose the first best operating strategy even though the owner’s value function might be locally convex (concave), which would ordinarily lead to overinvestment (underinvestment) in risky projects. This result is demonstrated in two different continuous time settings—one that is based on the risk-shifting framework of Leland (1998) and one that generalizes the scaled return model of Green (1984). It is shown that the contractual nature of the structuring is a key determinant of the issuing firm’s dynamic asset volatility. Furthermore, unlike nonstructured financing, the default (conversion) probability of a structured debt security may be increasing (decreasing) in the firm’s total assets. Structured securities are therefore hedge assets, which potentially explains the popularity of structured securities among investors and third-party issuers.

We test the signaling view of corporate social responsibility (CSR) engagement using two complementary quasi-natural experiments that impose exogenous negative pressure on stock prices. Firms under such adverse price pressure increase CSR activities compared to otherwise similar firms. This effect concentrates among firms with stronger signaling incentives, namely, those facing greater information asymmetry, more product market competition, higher shareholder litigation risk, and higher stock price crash risk. Firms under the exogenous negative price pressure mainly improve CSR strengths, including costly environmental investments. We also find that CSR engagement attracts socially responsible investors and lowers the cost of capital for signaling firms.

This note has given results for the probability of committing a Type I error in first-order stochastic dominance when it is assumed that both options have been sampled from the same distribution of returns. The probabilities are based on known results in the stochastic processes and statistical goodness-of-fit literatures, but have not been recognized in connection with the problem of estimation of risk in stochastic dominance. Further work on FSD Type II error probabilities based on ideas in this paper is in progress.

An important maintained hypothesis in financial economics states that the average interest rate on a firm's debt is positively related to its leverage. This hypothesis has a long history going back at least to the work of Kalecki [4] where it was used to derive a determinate size for the competitive firm when the production function is homogeneous of degree one. The upward sloping interest rate-leverage relationship has also played an important role in the theory of finance. In this connection, it is somewhat interesting to find both Modigliani-Miller [5] and their many critics in complete agreement on the nature of this relationship. In particular, their statement on this subject conveys the impression that this relationship is governed by an unalterable law when they write: “Economic theory and market experience both suggest that the yields demanded by lenders tend to increase with the debt-equity ratio of the borrowing firm” [5, p. 273].

Financial or capital market theory is intimately concerned with the concept of a general equilibrium. But most of the empirical work in finance has been concerned with the estimation of single-equation ordinary least squares cross-sectional models. One way of capturing some of the flavor of a general equilibrium is to use a simultaneous equation valuation model. Thus the value or the return on a security can be determined simultaneously in relationship to and in competition with the other securities in the system. Simkowitz and Jones [4] have recently described how the methodology could be used. Simkowitz and Logue [5] have recently performed a study using this methodology.

We provide evidence of a network of information flow between activists and other investors prior to 13D filings. We match EDGAR search activity to investor IP addresses, identifying specific investors who persistently download information on an individual activist’s campaign targets in the days prior to that activist’s 13D disclosures. This outside investor’s knowledge of pending activist campaign plans seems to benefit both parties: the informed investor, unnamed in the 13D, increases its holdings in the targeted stock prior to the price surge upon 13D disclosure, while the activist earns voting support that increases their likelihood of pursuing and winning a proxy fight.

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.

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.

Solving capital budgeting problems with linear and integer programming has been part of the finance literature for some time [21, 22, 23, 7, 14, and 18]. Capital budgeting problems have unique properties that distinguish them from other integer linear problems discussed in the mathematical programming literature. Capital budgeting problems generally have the following characteristics: (1) the matrix tends to be rectangular with more variables than constraints; (2) they are all maximization problems with ≤ constraints and nonnegativity conditions in the general form 0≤xi≤1 in the case of linear programming and xi = 0, 1 in the case of integer problems; and (3) there are often mutually exclusive projects among the variables. The purposes of this note are to illustrate some computational experience using existing integer algorithms to solve a set of capital budgeting problems and to begin to catalog the performance of integer codes on financial problems.

Models developed to explain variations in cash balances of firms have generally postulated forms of rational choice for the decision maker. Two examples of these kinds of models are (1) Baumol's inventory-type model where the choice of the initial balance is made in terms of a planning period in which outflows of cash, but no inflows, are considered; (2) Miller and Orr's model wherein inflows and outflows occur randomly and a decision is triggered to increase or reduce cash balances when an upper or lower threshold is passed. Statistical tests of the inventory-type model have had limited success, particularly in attempts to identify the increasing efficiency in the use of cash balances as a function of the size of the firm. The apparent linear double logarithmic relationship between cash balances of firms and their sales volumes has cast doubt upon the increased efficiency proposition that derives from the Baumol model. Meltzer has modified this model to demonstrate that it implies linearity. The Meltzer tests will be challenged in this paper, and we shall establish that his results, as well as Baumol's conclusions, are particular outcomes that can be better explained in another type of model.

Most research dealing with portfolio selection under uncertain inflation is carried out by assuming either one of the following two approximations: a linear or a quadratic approximation. In this paper, we analyze the general case, namely assume that the nominal return is the product of the real return and one plus the rate of inflation. We demonstrate that the general analysis leads to the following results that are not found in the two approximations: (1) even if we assume that nominal returns are independent of inflation, the nominal and real efficient sets will not necessarily coincide. Mean-Variance (M-V) analysis leads to a nominal efficient set, that is, a subset of the real M-V efficient set, whereas the opposite holds assuming investors maximize expected utility of real wealth. (2) Similar results are obtained when real returns are independent of inflation (the Fisher hypothesis). Assuming normality of nominal returns, we derive the CAPM in real terms or its zero beta counterpart.

In a previous paper we reviewed the literature on normative stock price models. These models specified the present value of a share of common stock to be equal to the discounted value of dividends accruing to the holder. Using continuous discounting, the present value of a share is(1)

where Dt is the dividend rate at time t and k is the cost of equity capital. Presumably k is a function of both the stockholders' time value of money and the perceived risk or uncertainty associated with the future dividend stream.

We show that the currency risk embedded in the benchmarks of international mutual funds negatively affects fund performance. More specifically, a high benchmark-implied currency risk induces funds to invest in markets with less volatile currencies, leading to a higher degree of currency concentration in portfolio holdings. This currency concentration, however, departs from the optimal equity allocation strategy across countries and reduces fund performance. We document that funds resorting to high currency concentrations underperform funds with low currency concentrations by as much as 1%–2% per year.

We document that the likelihood of asset sales increases with union presence and union wages. Furthermore, acquiring firms gain significant concessions from the incumbent union following asset sales. Finally, the anticipation of union concessions helps explain the excess stock returns around asset sale announcements. We find no comparable effects for takeovers. We conclude that asset sales, but not takeovers, are partially motivated by the potential to extract concessions from unions.

This article investigates how the asset-return variance risk premium changes leverage. I find that the premium reduces leverage by increasing risk-neutral bankruptcy probability and costs in a model where asset returns have stochastic variance with the risk premium. Empirically, the model calibrations verify a significant reduction in optimal leverage, closer to observed leverage than the model without the premium. In model-free regressions, I document that leverage correlates negatively with the variance premium. The highest negative correlation is among investment-grade firms with low asset beta and historical variance but high variance premiums because their assets have high exposure to the market’s variance premium.

Foreign migration flows have important stock market consequences. Foreign-born resident networks within U.S. Metropolitan Statistical Areas (MSAs) are associated with excess return comovement between locally headquartered stocks and American Depositary Receipts (ADRs) from countries with ties to the MSA through the network of foreign-born residents. This comovement is hardly due to correlated fundamentals and at least partially driven by correlated trading within members of a common investor base consisting of foreign-born residents. Our evidence has implications for both investors and foreign multinational corporations (MNCs) seeking to reap benefits from cross-listings and is consistent with the notion that foreign-born residents exhibit both local bias and home (country) bias.