This research investigates the impact of interest rate volatility upon corporate bond yield spreads. We first consider the impact of interest rate volatility upon noncallable bond spreads. Because greater interest rate volatility likely increases the volatility of the firm's debt, we hypothesize that the relation will be positive. Given that we do find a positive relation, we thus investigate whether the positive effect of interest rate volatility on yield spreads is stronger or weaker for callable bonds. We find that the effect is weaker for callable bonds. This result indicates that there is a negative relation between default spreads and call spreads, which is consistent with the theory of Acharya and Carpenter (2002), but in contrast to the theory of King (2002). Furthermore, our results for the relationship between equity volatility and yield spread tend to support Acharya and Carpenter (2002) more than King (2002).

Despite its wide use, the Hill estimator and its plot remain to be difficult to use in Extreme Value Theory (EVT) due to substantial sampling variations in extreme sample quantiles. In this paper, we propose a new plot we call the eigenvalue plot which can be seen as a generalization of the Hill plot. The theory behind the plot is based on a heavy-tailed parametric distribution class called the scaled Log phase-type (LogPH) distributions, a generalization of the ordinary LogPH distribution class which was previously used to model insurance claims data. We show that its tail property and moment condition are well aligned with EVT. Based on our findings, we construct the eigenvalue plot from fitting a shifted PH distribution to the excess log data with a minimal phase size. Through various numerical examples we illustrate and compare our method against the Hill plot.

ABSTRACT Financial classification issues, and particularly the financial distress problem, continue to be subject to vigorous investigation. The corporate credit granting process has not received as much attention in the literature. This paper examines the relative effectiveness of parametric, nonparametric and judgemental classification procedures on a sample of corporate credit data. The judgemental model is based on the Analytic Hierarchy Process. Evidence indicates that (nonparametric) recursive partitioning methods provide greater information than simultaneous partitioning procedures. The judgemental model is found to perform as well as statistical models. A complementary relationship is proposed between the statistical and the judgemental models as an effective paradigm for granting credit.

Abstract ABSTRACT: Previous market-based research has generally failed to detect significantly negative market price reaction to the issuance of SFAS No. 8. Using standardized abnormal returns, this study re-examines the issue. Reaction to events culminating in the issuance of SFAS No. 52 is also studied. Finally, since the accounting method used prior to SFAS No. 8 may be related to the costs imposed by SFAS No. 8, the method is determined and its effect on the observed market reactions is investigated. Our results indicate an overall negative reaction to SFAS No. 8, with a positive reaction to SFAS No. 52. In addition, the pre-SFAS No. 8 method of accounting for foreign currency translation is found to be related to the market reactions to SFAS No. 8 and SFAS No. 52 in mixed and unpredictable ways.

Although several researchers have speculated that stock splits may affect the ownership structure of firms, there is very little empirical evidence available in this regard. We investigate a broad sample of stock splits by firms without confounding events, controlling for industry and size effects. Our results show that stock splits increase the numbers of both individual and institutional shareholders, and they do not affect the proportion of equity held by institutions. Further, changes in the numbers of individual and institutional shareholders are positively related to the split factor. Abnormal announcement returns are positively correlated with changes in the total number of shareholders. These findings support the signaling hypothesis.

We examine the impact of economic policy uncertainty (EPU) on bank liquidity hoarding. We create a comprehensive measure of bank liquidity hoarding that takes into account asset-, liability-, and off-balance sheet activities. Using over one million bank-quarter observations, we find that in response to EPU, banks hoard liquidity overall and through all three components. This behavior is more pronounced for banks with less liquidity, more peer-bank spillover effects, and more EPU exposure. Additional analyses of interest rate spreads on several bank products suggest that our findings reflect at least in part bank choices, rather than just the reactions of customers.

Abstract This paper explores how selective default expectations affect the pricing of sovereign bonds in a historical laboratory: the German default of the 1930s. We analyze yield differentials between identical government bonds traded across various creditor countries before and after bond market segmentation. We show that, when secondary debt markets are segmented, a large selective default probability can be priced in bond yield spreads. Selective default risk accounted for one-third of the yield spread of German external bonds over the risk-free rate during the 1930s. Selective default expectations arose from differences in the creditor countries’ economic power over the debtor.