I use an accounting reform to assess the agency cost of debt in diversified firms. Those firms that switch from single to multiple segments following the reform suffer a 12% increase in their bond spread when compared with their stand-alone peers. Consistent with lenders anticipating underinvestment and asset-substitution incentives, diversified firms with high cash-flow volatility across divisions suffer the highest increase in borrowing costs. I employ a novel approach that allows abstracting from unobservable characteristics that would otherwise influence the pricing of diversified firms’ debt.

Using three exogenous shocks to ex ante litigation risk, including federal judge ideology and two influential judicial precedents, we find that lower shareholder litigation risk reduces a firm’s propensity to delist from the U.S. stock markets. The effect is at least partially driven by indirect costs of litigation and that being a private firm can significantly reduce the threat of litigation. Overall, the results suggest that mitigating excessive litigation costs for public firms is crucial to ensure the continued vibrancy of the U.S. stock market.

Does proprietary knowledge protection (PKP) spur or hinder the product-market performance of new firms? Exploiting the staggered adoptions of the inevitable disclosure doctrine by U.S. State Courts, which enhance PKP, we show that treated firms increase industry-adjusted sales growth by 2% compared to control firms. The effect is concentrated among small and young firms and increases with the scope of proprietary knowledge and rivals’ access to external finance. PKP encourages firms to develop new products and stimulates initial public offering activity. Our results suggest that PKP alleviates predation risk associated with “deep-pocket” rivals by allowing firms to maintain competitive advantages.

We analyze whether industry competition influences analyst coverage decisions and whether analysts benefit from covering product market competitors. We find that analysts are more likely to cover a firm when this firm competes with more firms already covered by the analyst. We also find that the intensity of competition among these competitors is additionally important to the coverage decision. Moreover, we find that analysts who cover product market competitors are more likely to obtain analyst star status. These results are consistent with the importance to analysts of industry competition and product market knowledge accumulated through covering product market competitors.

This paper analyzes the optimal quality decision of a producer in a multi-period setting with reputation effects. Using a unique database of returns on real estate limited partnerships (RELPs), we empirically examine alternative theoretical predictions of optimal producer strategy. In particular, we test whether the producers in our market invest in reputation building by initially selling high quality goods and then lowering quality. Using a variety of statistical tests, we find evidence consistent with reputation building, both in the aggregate and for individual developers.

This paper examines trading patterns and market integration using laboratory asset markets. Our markets are designed to approximately correspond to the trading day for stocks cross-listed in markets in Europe and North America. Some of our markets feature timing restrictions so that participants cannot trade across markets except during a fully integrated overlap period. Comparison of markets with and without timing restrictions shows that restrictions reduce trading activity and shift transactions to the overlap period. When asset values are extreme, price discovery can be impeded when trading restrictions exist. The measurement of liquidity suggests that trading restrictions increase overall spreads.

What are the implications of an aging population for financial stability? To examine this question, we exploit geographic variation in aging across U.S. counties. We establish that banks with higher exposure to aging counties increase loan-to-income ratios. Laxer lending standards lead to higher nonperforming loans during downturns, suggesting higher credit risk. Inspecting the mechanism shows that aging drives risk-taking through two contemporaneous channels: deposit inflows due to seniors’ propensity to save in deposits; and depressed local investment opportunities due to seniors’ lower credit demand. Banks thus look for riskier clients, especially in counties where they operate no branches.

This paper reexamines the empirical relation between inflation and interest rates concentrating on the tax effect proposed by Darby and Feldstein. Using the random walk intercept model, relative responses of taxable yields and tax-exempt yields to expected inflation are estimated. The results show that for the sample period 1953–1982, the nominal yields on Treasury bills rise at a rate greater than one-for-one with expected inflation, while the nominal yields on default-free municipal bonds rise approximately one-for-one with expected inflation. Thus, the tax-adjusted Fisher hypothesis by Darby and Feldstein is empirically supported. The components of Treasury bills are also extracted and their variances are compared. It is shown that variation of expected inflation is not overwhelmingly larger than that of the after-tax real rate. Therefore, on an after-tax basis, changes in the real rate explain a substantial portion of changes in the nominal rate of interest.

In the standard setting in which an individual or firm has preferences for probabilistic monetary outcomes that satisfy the Neumann-Morgenstern [10] assumptions of “rational behavior” and has an exponential utility function for money, a popular index for evaluating any proposed single-period probabilistic project is its “risk-adjusted value” (RAV), i.e., its certainty equivalent, the certain amount of money that has the same utility as the expected utility for the project. Since the exponential function is completely characterized by just a single parameter, its risk aversion level, in comparing mutually exclusive projects one can simply plot their RAVs or their expected utilities as a function of this parameter and then, for any given value or range of values of the parameter, read off which project is best, i.e., has the highest RAV or, equivalently, the highest expected utility. (See, e.g., [7], p. 203 or [2].)

According to a now classic study of stock market price behavior by Fama [6], the empirical distributions of daily log price relatives are usually stable Paretian, non-Gaussian. However, there appears to have been substantial reluctance to accept Fama's [6] research results as indicative of a fundamental return generating process which is stable Paretian, non-Gaussian. Blattberg and Gonedes [1], Clarke [4], Officer [18], Praetz [19], and Press [20] have each in their own way questioned the Fama [6] results. Most recently Hsu, Miller, and Wichern (HMW) [13] have suggested that in periods of homogeneous activity for a firm the empirical distribution of rates of return on a common share may be Gaussian, in other words, that the fundamental return generating process may be normal.

In the past most of the studies whose aim was to explain earnings-to-price ratios (or alternatively, price-earnings ratios) of common stocks attempted to answer the much-debated question raised in both investment and academic circles: Why does a given common stock consistently command a higher price relative to its earnings vis-a-vis other stocks? Success in answering this question has been limited, largely due to (1) researchers' inability to incorporate expected earnings (E) correctly into the empirical measurement of earnings-to-price ratio and/or (2) inadequate treatment of risk variables to explain variability of earnings-to-price ratio.

In recent years we have seen significant progress in the development of models of capital asset pricing and the related models of portfolio selection and performance appraisal. The central focus, in all of these models, has been one of dealing directly with the difficult and perplexing issues of the measurement of risk and the underlying theories of investor choice-making under uncertainty.

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.

During the past 20 years several theoretical valuation models with empirically testable implications regarding the impact of financial decisions, particularly debt policy and dividend policy, have appeared in the financial literature. Some of these models have been subjected to extensive testing. However, results of these investigations are inconclusive and/or conflicting as to the impact of financial policies on share value. For instance, on the basis of a study of electric utility firms, Miller and Modigliani (M&M) find that neither dividend nor debt policies of the firm affect the value of the firm. On the other hand, Weston, as well as Brigham and Gordon, disagree with M&M's findings based upon their own investigations of electric utility firms.

Errors in recorded security prices are a source of misspecification in the market model. If recorded price errors are sufficiently nonrandom, they result in biased returns and in biased and inconsistent estimates of market model regression coefficients. This paper argues that tax-induced flow-supply pressures cause end-of-the-year recorded price errors to be nonrandom enough to create the appearance of anomalous turn-of-the-year stock return behavior. Empirical tests of returns and market model regression coefficients during the turn-of-the-year period cannot reject this errors-in-variables explanation of the turn-ofthe-year effect.

This article investigates the role external advice plays in the board’s determination of chief executive officer (CEO) compensation. We show that CEO incentive pay increases with the degree of compensation consultant independence using a quasi-natural experiment provided by the creation of an independent consultant after separation from an affiliated consultant. Specifically, switching to an independent consultant significantly increases the pay–performance sensitivity and relative performance evaluation of CEO contracts. Despite the benefits of independent advice, independent consultants may not be hired due to the influence of powerful CEOs or because boards already possess adequate expertise.

We investigate the implications of recovering real-world conditional expectation of return functions using options on the S&P 500 index and Treasury bond futures. First, we construct estimates of the probability of disasters, defined as higher than 6%, 5%, or 4% equity market declines over option expiration cycles. This measure of disaster probability forecasts realized disasters. Second, we employ options on the futures of the 10- and 30-year Treasury bonds to construct estimates for the expected return of bond futures. These measures display forecasting ability for subsequent futures returns beyond the level, slope, and curvature variables extracted from the yield curve.

In a recent article in this Journal, Amir Barnea [1] proposes a criterion for assessing the market-making efficiency of New York Stock Exchange specialists. The appealing aspects of Barnea's method are that it uses publicly available data (common stock prices) and operates on a variable of primary concern to investors, the variance of returns on common stock. The difficulty we see in applying his approach, however, is that Barnea's performance criterion can be sensitive to a number of factors in addition to any impact the specialist might have, and that effective specialist intervention might have either a positive or negative impact on the performance measure. Thus, his specialist ranking seems to be quite misleading, and his empirical findings appear to be amenable to a substantially different interpretation than that which he provides.

In recent years the cost of fuel to operate power plants for electric utilities has increased much faster than many utility executives and regulators have anticipated. In the presence of substantial regulatory lag in adjusting rates, stockholders have had to absorb the difference between revenues and unanticipated increases in fuel expenses. In an effort to shorten the time required for increased costs to be reflected in increased prices to consumers, many firms have been allowed to use an automatic fuel adjustment clause (FAC) to pass on increased costs to consumers as they occur. The FAC usually allows the firm to adjust the price of electricity when the price of fuel deviates from some fixed base price. Presently more than 40 of the 50 state regulatory commissions allow some type of FAC.

Under certainty the firm's average cost of capital is a directly observable magnitude — the rate of interest. Under uncertainty the firm–s average cost of capital is an ex ante expectational concept which is not directly observable. In a seminal application of their prior theoretical contributions to corporation finance, Miller and Modigliani (M-M) [11] obtained indirect econometric estimates of the cost of capital for electric utility firms. A sample of electric utilities was ideal for an empirical application of the A M-M valuation model which is rooted in the partial equilibrium framework of an equivalent risk class. For other industries where interfirm differences in operating risk are greater, the equivalent risk class assumption would be less appropriate. That is, each firm in a heterogeneous industry may be considered in a unique risk class and the concept of an industry cost of capital would be suspect. Furthermore, the M-M theoretical construct does not provide insights into the relationship among costs of capital of firms in divergent risk classes.