Credit Risk in G20 Nations: A Comparative Analysis in International Finance Using Option-Adjusted-Spreads

Corporate bond yields are the manifestation of the cost of financing for private firms, and if properly evaluated, they provide researchers with valuable risk information. Within this context, this work is the first study producing corporate yield spreads for all S&P-rated bonds of G20 nations to explain their comparative riskiness. The option-adjusted spread analysis is an advanced method that enables us to compare the bonds with embedded options and different cash flow characteristics. For securities with embedded options, the volatility in the interest rates plays a role in ascertaining whether the option is going to be invoked or not. Therefore, researchers need a spread that, when added to all the forward rates on the tree, will make the theoretical value equal to the market price. The spread that satisfies this condition is called the option-adjusted spread, since it considers the option embedded into the issue. Ultimately, this work investigates the credit risk differentials of S&P rated outstanding bonds issued by the G20 nations to provide international finance professionals with option-adjusted corporate yield spreads showing the credit risk attributable to debt instruments. Detailed results computed using OAS methodology are presented in tables and used to answer the six vital credit-risk-related questions introduced in the introduction.

Conducting Causal Analysis by Means of Approximating Probabilistic Truths

The current paper develops a probabilistic theory of causation using measure-theoretical concepts and suggests practical routines for conducting causal inference. The theory is applicable to both linear and high-dimensional nonlinear models. An example is provided using random forest regressions and daily data on yield spreads. The application tests how uncertainty in short- and long-term inflation expectations interacts with spreads in the daily Bitcoin price. The results are contrasted with those obtained by standard linear Granger causality tests. It is shown that the suggested measure-theoretic approaches do not only lead to better predictive models, but also to more plausible parsimonious descriptions of possible causal flows. The paper concludes that researchers interested in causal analysis should be more aspirational in terms of developing predictive capabilities, even if the interest is in inference and not in prediction per se. The theory developed in the paper provides practitioners guidance for developing causal models using new machine learning methods that have, so far, remained relatively underutilized in this context.

Corporate bond spreads and understated pension liabilities

PurposeThe question is whether debt market investors see through managers' attempts to hide their pension obligations. The authors establish a robust relation between understated pension liabilities and corporate bond yield spreads after controlling for factors that have been previously identified as having a significant impact on firms' cost of borrowing. The results support the idea that bond market investors are not being misled by the use of high pension liability discount rates by some companies to lower their reported pension obligations. For a small fraction of debt issuers, the reported pension liabilities are larger than the pension liabilities valued at the stipulated interest rate benchmarks. For these issuers with overstated pension liabilities, bond investors adjust their borrowing costs downward.Design/methodology/approachThe authors investigate the relation between corporate bond yield spreads and understated pension liabilities relative to long-term Treasury and high-grade corporate bond yields. They aim to answer two questions. First, what are the sizes of over or understated pension liabilities relative to guideline benchmarks? Second, do debt market investors see through the potential management manipulation of pension discount rates? The authors find that firms with large understated pension liabilities face higher marginal borrowing costs after taking into account issue-specific features, firm characteristics, macroeconomic conditions and other pension information such as funded status and mandatory contributions.FindingsThe average understated projected benefit obligations (PBOs) are understated by $394.3 and $335.6, equivalent to 3.5 and 3.0% of the beginning of the fiscal year market value, respectively. The average understated accumulated benefit obligations (ABOs) are understated by $359.3 and $305.3 million, equivalent to 3.1 and 2.6%, of the beginning of the fiscal year market value, respectively. Relative to AA-grade corporate bond yields, the average difference between firm pension discount rates and benchmark yields becomes much smaller; the percentage of firm pension discount rates higher than benchmark yields is also much smaller. As a result, understated pension liabilities become negligible. The authors establish a robust relation between corporate bond yield spreads and measures of understated pension liabilities after controlling for issue-specific features, firm characteristics, other pension information (funded status and mandatory contributions), macroeconomic conditions, calendar effects and industry effects.Originality/valueS&P Rating Services recognizes the issue that there is considerably more variability in discount rate assumptions among companies than in workforce demographics or the interest rate environment in which firms operate (Standard and Poor's, 2006). S&P also indicates that it would be desirable to normalize different discount rate assumptions but acknowledges that it is difficult to do so. In practice, S&P Rating Services conducts periodic surveys to see whether firms' assumed discount rates conform to the normal standard. The paper makes an initial attempt to quantify the size of understated pension liabilities and their impact on corporate bond yield spreads. This approach can be extended to study firms' costs of equity capital, the pricing of seasoned equity offerings and the pricing of merger and acquisition transaction deals, among other questions.

Shape Evolution of the Interest Rate Term Structure

This paper adopts a novel approach to studying the evolution of interest rate term structure over the U.S. business cycles and to predicting recessions. Applying an effective algorithm, I classify the Treasury yield curve into distinct shapes and find the less frequent shapes intrinsically linked to the recessions in the post-WWII data. In forecasting recessions, the median-short yield spread trumps the long-short spread for horizons up to 17 months ahead and the yield curve shape is nearly impressive as the median-short spread. Overall, the yield curve shape is an informative but more succinct indicator than the spreads in studying the term structure. Key words: Business cycle, recession forecast, U.S. Treasury yield curve, yield spreads.

The role of social capital in private placement: evidence from Rule 144A debt issuances

PurposeThe purpose of this paper is to investigate the role of social capital in the issuances of Rule 144A debt. Using a sample of 1,378 debt offerings from 1997 to 2015 in the US, this paper provides empirical evidence on whether and to what extent social capital affects the cost of Rule 144A debt.Design/methodology/approachThis paper employs a county-level measure of social capital and links social capital to the yield spreads of Rule 144A debt. A Heckman selection model is sued to address the sample selection bias, and an instrumental variable approach and propensity score matching methodology are implemented to deal with the potential endogeneity issue. The authors check for robustness using an alternative measure of social capital.FindingsThe results of the analysis provide evidence that issuers headquartered in the counties with higher levels of social capital experience lower yield spreads in their Rule 144A debt offerings. The findings are robust to a Heckman selection model, an instrumental variable approach and propensity score matching. Furthermore, the analysis reveals the marginal effect of social capital that the effect of social capital is more pronounced for the issuing firms with higher agency cost of debt and lower institutional ownership. The effect of social capital is more prominent after financial crisis.Originality/valueThis paper provides novel evidence of the effect of social capital on the cost of privately placed debt. The issuances of Rule 144A debt are subject to significant information asymmetry and are targeted at sophisticated institutional investors. This paper sheds further light on how institutional investors incorporate the regional social capital in their pricing scheme of private placement of Rule 144A debt.

Measuring redenomination risks in the Euro area – evidence from survey data

Purpose This paper aims to introduce a new indicator to measure redenomination risks in Euro area countries. The measure is based on survey data. The influence of this indicator in determining sovereign bond yield spreads is estimated. Design/methodology/approach An autoregressive distributed lag approach is used to estimate the effects of redenomination risks on sovereign bond yields. Additional control variables are added. Findings The results for 10 European Economic and Monetary Union (EMU) countries in the period June 2012 to May 2019 show that the risk of depreciation is almost abandoned for most Euro area countries, i.e. the former crisis countries Ireland and Portugal. If anything an appreciation may occur for some countries once they leave the EMU. The only countries facing depreciation problems once leaving the monetary union are Italy and to some extent Spain. Originality/value With this new indicator, the literature on sovereign bond determination and i.e. on redenomination risks is expanded by an additional approach. Moreover, this study is one of few also looking at the period after the most severe tensions of the sovereign debt crisis in the Euro area in 2012.

Principal component regression in GAMLSS applied to Greek–German government bond yield spreads

A solution to the problem of having to deal with a large number of interrelated explanatory variables within a generalized additive model for location, scale and shape (GAMLSS) is given here using as an example the Greek–German government bond yield spreads from 25 April 2005 to 31 March 2010. Those were turbulent financial years, and in order to capture the spreads behaviour, a model has to be able to deal with the complex nature of the financial indicators used to predict the spreads. Fitting a model, using principal components regression of both main and first order interaction terms, for all the parameters of the assumed distribution of the response variable seems to produce promising results.