WARRANT PRICING USING OBSERVABLE VARIABLES

The classical warrant pricing formula requires knowledge of the firm value and of the firm‐value process variance. When warrants are outstanding, the firm value itself is a function of the warrant price. Firm value and firm‐value variance are then unobservable variables. I develop an algorithm for pricing warrants using stock prices, an observable variable, and stock return variance. The method also enables estimation of firm‐value variance. A proof of existence of the solution is provided.     

Syndicated Loan Announcements and Borrower Value

Announcements of syndication loans increase borrowers' shareholder wealth if they are revolving credit agreements but not if they are term loans. Share price responses to revolving credit announcements are positive and significant, whereas the wealth effect for term loans is negative and significant. The results show that announcements from both the financial press and commercial information providers can affect borrower share price reaction. Overall, single syndication announcements appear to be more newsworthy than multiple announcements reported in the financial press, and we find evidence of information leakage, post‐announcement drift, or both.     

Copyright Damages and Statistics

This paper discusses the statistical issues that arise in conducting an economic damages analysis in the context of a litigation matter involving copyrights. Calculating damages in copyright cases turns out to be a natural application for econometric modelling methods. Surprisingly, elementary statistical issues can be a source of significant debate between the experts in such matters. In this paper, we present a case study and illustrate how issues such as interpretation of p -values and what "rejection of the null hypothesis" really "means" in such matters.     

The Impact of Regulation Fair Disclosure on Information Asymmetry and Trading: An Intraday Analysis

This study examines the impact of Regulation Fair Disclosure (FD) on liquidity, information asymmetry, and institutional and retail investors trading behavior. Our main findings suggest three conclusions. First, Regulation FD has been effective in improving liquidity and in decreasing the level of information asymmetry. Second, retail trading activity increases dramatically after earnings announcements but there is a significant decline in institutional trading surrounding earnings announcements, particularly in the pre‐announcement period. Last, the decline in information asymmetry around earnings announcements is closely associated with a lower participation rate in the pre‐announcement period and more active trading of retail investors after earnings releases.     

Financial Distress and Optimal Capital Structure Adjustments

We show that asymmetric information may prevent firms with pure discount bonds from renegotiating their capital structure prior to the maturity of the debt, although this would increase the value of the firm when its prospects are poor. This inefficiency can be reduced if the firm issues debt with a risky intermediate debt payment, such as a coupon or a sinking fund payment. We also demonstrate that bankruptcy institutions leading to deviations from absolute priority can improve the timing of recapitalizations by financially distressed firms. Finally, we show that, under certain conditions, the optimal capital structure adjustment during financial distress consists of a convertible debt-for-straight debt swap.     

Bayesian MCMC Mapping of Quantitative Trait Loci in a Half-sib Design: a Graphical Model Perspective

Graphical models provide a powerful and flexible approach to the analysis of complex problems in genetics. While task-specific software may be extremely efficient for any particular analysis, it is often difficult to adapt to new computational challenges. By viewing these genetic applications in a more general framework, many problems can be handled by essentially the same software. This is advantageous in an area where fast methodological development is essential. Once a method has been fully developed and tested, problem-specific software may then be required. The aim of this paper is to illustrate the potential use of a graphical model approach to genetic analyses by taking a very simple and well-understood problem by way of example.     

On the Statistical Significance of Event Effects on Unsystematic Volatility

We develop a method for determining the significance of the effect of a certain event (stock split, corporate restructuring, change in regulation, etc.) on unsystematic volatility of asset returns. Simulations show that the suggested tests reject the true null hypothesis of no effect on volatility at appropriate levels, whereas the rejection rates of a false null hypothesis increase with the magnitude of the effect. An application of the method to corporate spin‐offs reveals statistically significant and long‐lasting estimated increases in unsystematic volatility of parent companies' returns.