With the recent significant growth in the single-name credit default swap (CDS) market has come the need for accurate and computationally efficient models to value these instruments. While the model developed by Duffie, Pan, and Singleton (2000) can be used, the solution is numerical (solving a series of ordinary differential equations) rather than explicit. In this paper, we provide an explicit solution to the valuation of a credit default swap when the interest rate and the hazard rate are correlated by using the “change of measure” approach and solving a bivariate Riccati equation. CDS transaction data for the period 2/15/2000 through 4/8/2003 for 60 firms are used to test both the goodness of fit of the model and provide estimates of the influence of economic variables in the market for credit-risky bonds.

When shareholders have different plans to sell their shares, they will, in general, have different preferences concerning the firm's decision to pay out cash using dividends or share repurchase. We illustrate these different preferences and explore a model of payout policy that highlights the adverse selection costs of repurchases when managers have superior information about the value of the firm. We show that, in the absence of fixed costs to repurchasing shares, there is a separating equilibrium in which managers use taxable dividends to signal the quality of the firm, with better firms paying lower dividends, using repurchases for the remainder of the payout. With fixed costs to repurchasing, small payouts are made via dividend and large payouts are divided between repurchases and dividends, as in the no-fixed cost case. In both cases, the percentage of shares repurchased increases with the size of the payout and larger repurchases are better news.

We investigate whether and how government interventions in the U.S. banking sector influence the stock market performance of corporate borrowers during the financial crisis of 2007–2009. We measure firms’ exposures to government interventions with an intervention score that is based on combined information on the firms’ structure of bank relationships and their banks’ participation in government capital support programs. We find that government capital infusions in banks have a significantly positive impact on borrowing firms’ stock returns. The effect is more pronounced for riskier and bank-dependent firms and for those that borrow from banks that are less capitalized and smaller.

In recent years a major controversy has formed in the finance literature regarding the empirical evidence of the informational content of dividends. Despite considerable support for the position of dividend nontriviality by various studies, the work by Watts [13] represents a formidable challenge. Because of the close proximity of the firm's earnings and dividend announcement dates, the major issue of the dispute has centered on the identification and control of contemporaneous earnings information. In an attempt to settle this controversy, the present study evaluates and extends Watts' methodology.

We examine empirically the existence of speculative bubbles in U.S. stock prices and, by building on West's procedure, propose direct and computationally simple tests of the “nobubble” hypothesis. These tests are likely to be close to their nominal size in small samples and to have small sample power against a wide class of bubbles including those orthogonal to the dividend process. We apply the tests to long-term annual U.S. stock market data for the 1871–1981 and 1871–1988 periods. Contrary to West, we do not reject the “no-bubble” hypothesis. We offer an explanation as to the cause of discrepancy between the two results.

We study the impact of parameter uncertainty on the expected utility of a multiperiod investor subject to quadratic transaction costs. We characterize the utility loss associated with ignoring parameter uncertainty, and show that it is equal to the product between the single-period utility loss and another term that captures the effects of the multiperiod mean-variance utility and transaction cost losses. To mitigate the impact of parameter uncertainty, we propose two multiperiod shrinkage portfolios and demonstrate with simulated and empirical data sets that they substantially outperform portfolios that ignore parameter uncertainty, transaction costs, or both.

The impact of liquidity-motivated institutional trading on firms’ real decisions is not confined to periods of financial crisis. Firms subject to mutual fund flow-driven selling pressure reduce share issuance and investment, whereas firms experiencing buying pressure do not increase investment, although they issue more equity. Firms under extreme selling pressure cut quarterly investment by 0.075 percentage points of total assets, which is 4.3% of the average quarterly investment in our sample. We also find evidence that the effect is not attributed to managerial learning or catering incentives. Rather, flow-driven trading affects investment mainly through its impact on the financing cost.

Using within-loan estimations to remove the impact of demand-side factors, we find that the capital levels of banks participating in the same syndicated loan are positively associated with the banks’ contributions to the loan. Consistent with the argument that higher capital reduces the cost of uninsured debt, the positive effect of bank capital on lending is stronger among banks that rely more on wholesale funding. Furthermore, we find that banks increase their contributions to syndicated loans after receiving Troubled Asset Relief Program (TARP) funding. Taken together, we provide new evidence on the importance and causal effect of bank capital on lending.

We conduct a comprehensive comparison of market beta estimation techniques. We study the performance of several historical, time-series model, and option-implied estimators for estimating realized market beta. Thereby, we find the hybrid methodology of Buss and Vilkov to consistently outperform all other approaches. In addition, all other approaches, including fully implied and dynamic conditional beta, based on generalized autoregressive conditional heteroskedasticity (GARCH) models, are dominated by a simple beta estimate based on historical (co-)variances and an approach based on the Kalman filter. Our conclusions remain unchanged after performing several robustness checks.

The adoption of liability limitation provisions (LLPs) is associated with insignificant stock price reactions for all firms, but with positive stock price reactions for poorly performing firms. This result is consistent with the hypothesis that the net benefit of LLPs is larger for financially troubled firms than for other firms because outside directors are valuable to the distressed firm and LLPs substantially affect experts' expected costs of serving as directors of troubled firms.

We propose that chief executive officer (CEO) exploratory mindset (inherent desire to search for novel ideas and long-term orientation) promotes innovation. Firms with CEOs with PhD degrees (PhD CEOs) produce more exploratory patents with greater novelty, generality, and originality. PhD CEOs engage less in managing earnings and stock prices, invest more in research and development (R&D) and alliances, generate higher long-term value of patents, and experience more positive market reactions to R&D alliances. Their firms achieve superior long-run operating performance. They tend to be hired by research-intensive firms with poor financial performance. Evidence from managerial incentive shocks and turnovers suggests that these effects do not derive solely from CEO–firm matching.

We document that fund managers are more likely to allocate assets to firms managed by executives and directors with whom they share a similar political partisan affiliation. We find that this bias is not associated with improved fund performance. Funds with more partisan bias suffer from higher levels of idiosyncratic volatility than those with less bias. Partisan bias is more evident when fund managers are less experienced, in more informationally opaque firms, and when the U.S. president comes from fund managers’ own party. These findings suggest that political partisan bias among fund managers may be due to in-group favoritism.

An increase in “unusual” news with negative sentiment predicts an increase in stock market volatility. Unusual positive news forecasts lower volatility. Our analysis is based on over 360,000 articles on 50 large financial companies, published during the period of 1996–2014. Unusualness interacted with sentiment forecasts company-specific and aggregate volatility several months ahead. Furthermore, unusual news is reflected more slowly in aggregate volatility than company-specific volatility. News measures from articles explicitly about the “market,” which are more easily accessible to investors, do not forecast volatility. The observed responses of volatility to news may be explained by attention constraints on investors.

We investigate the strict-exogeneity assumption, a necessary condition for estimator consistency in many finance panel-data applications. We outline tests for strict exogeneity in both traditional (non–instrumental variable (IV)) and IV settings. When we apply these tests in common traditional finance panel regressions, we find that the strict-exogeneity assumption is often strongly rejected, suggesting large inference errors. We test for strict exogeneity in specific finance panel-data IV settings and illustrate the potential for these tests to help confirm, or rule out, the validity of common panel-data IV estimators. We offer recommendations to address the strict-exogeneity issue in finance research.

The approach of selecting a portfolio of stocks on the basis of expected return and variance was introduced by Markowitz [18] in 1952 and subsequently was more fully developed by him [19] in 1959. Since this time, there has been considerable research either directly concerned with, or related to, the Markowitz model. The utility implications of his assumption that an investor chooses a portfolio solely on the basis of expected return and variance (where variance is identified with risk) have been studied, [1], [A], [22], and [31]. A simplified method of solving for the efficient set of portfolios under the assumption of a regression structure has been developed by Sharpe [26], and approximation methods have been suggested [25] and [29]. Empirical tests (with partially contradictory conclusions) of portfolio selection theory are described in [5], [7], [8], [20], and [27]. Studies of economic questions (such as liquidity preference, equilibrium stock prices, substitutability of risky assets, etc.), as formulated within the portfolio model, can be found in [10], [11], [13], [14], [16], [23], and [28]. A related portfolio selection approach, based on the assumption of a Pareto underlying distribution, has been suggested by Fama [6]. A modification by Baumol [2] introduced a confidence limit criterion. Also, some initial attempts have been made at deriving related adaptive models of portfolio selection, [21], [30].

In a dynamic framework, the advantage of leverage depends upon the firm's recapitalization policy. We show that if bonds are callable at par, then equityholders have an incentive to recapitalize too early. Call premia and issue discounts, however, mitigate the agency problem of early recapitalization. The model provides the optimal call premium and issue discount as a function of firm-specific characteristics. An analysis of a bond sample supports the model's prediction that the optimal call premium is positively related to firm risk.

We investigate potential mechanisms through which market-wide sentiment affects firms’ innovation activities. We provide evidence for the financing channel by showing that financially constrained firms are more likely to issue equity and invest more in research and development (R&D) than financially unconstrained firms at high market sentiment. Using time-varying manager sentiment measures, we find suggestive evidence for a sentiment spillover channel whereby market sentiment affects R&D investments through influencing manager sentiment. Furthermore, better patent portfolios are produced from R&D investments stimulated by high market sentiment. Market sentiment has a stronger impact on R&D than the capital expenditures of financially constrained firms.

In a recent article, Professors Stoll and Curley (hereinafter referred to as S–C) examined results for new issues during a short-run period and over long-run periods. The authors concluded that, “investors in new small issues floated under Regulation A in 1957, 1959, and 1963 experienced lower long-run rates of return than if they had invested in a portfolio of large stocks represented by the Standard and Poor's Industrial Average.” It was pointed out that these long-run results were consistent with the results of similar studies. Alternatively, regarding short-run results it was concluded that “in the short run, the stocks in the sample showed a remarkable price appreciation.” In fact, “short-run price appreciation was, however, considerably greater than the index appreciation.” They refer to this short-run performance as “.… perhaps the most interesting and certainly the most puzzling phenomenon encountered in the study.”

This paper exploits a quasi-natural experiment to investigate the relation between the Sarbanes–Oxley Act (SOX) of 2002 and corporate innovation: firms with a public float under $75 million can delay compliance with Section 404 of the act. We find a significant decrease in the number of patents and patent citations for firms that are subject to Section 404 compliance relative to firms that are not. This relation is more pronounced when firms are financially constrained and when firms face high litigation risk. Overall, our evidence suggests that SOX imparts real costs to the economy by decreasing corporate innovativeness.

Most research in modern portfolio theory and capital market theory is based on investor selection of portfolios that are efficient in the sense that they are not dominated by other portfolios in terms of their risk-expected return characteristics. The most widely used measure of portfolio risk is the variance about the mean of the exante distribution of portfolio returns. The theoretical framework from which this measure of risk is usually derived was initially suggested by Markowitz [12], and is by now well known. Although variance has the attention of most researchers, another measure, semivariance, had some early support from Markowitz himself, and from Quirk and Saposnik [17], Mao [10], and others. Semivariance as a measure of risk can be derived from the same theoretical framework as is variance; it requires only a slightly different utility function. The semivariance of returns of portfolio p below some point h is defined as

where fp (R) represents the probability density function of returns for portfolio p. Semivariance portfolio theory is enjoying something of a revival in the works of Porter [15, 16], Hogan and Warren [6] and Klemkosky [8], and semivariance capital market models have been developed by Hogan and Warren [7] and Greene [5].