Determinants Of Credit Spreads Research Articles

Emerging Bond Markets in Asia: Credit Spread Dynamics

We present a comprehensive analysis of the credit spread determinants in five Asian bond markets over a sample period of 10 years, from January 2010 to December 2019. Consistent with the western literature, we find that the structural models are broadly valid even in emerging countries with developing bond markets. Empirical results unveiled that bond-specific liquidity is the most important driver that reduces the credit spread, followed by the slope of the term structure and industrial growth in the economy. In Emerging Asia, inflation is the key driver that aggravates credit spread for business firms, followed by financial market volatility. Cross-country data reveals that the Chinese corporate bond market is the largest in Asia. Indian markets offer higher yield rates, while credit spread is noted to be highest in China. The empirical findings of our study would provide important insights for the policy makers while developing the most sought-after liquid bond markets. Effective liquid bond markets would reduce the cost of capital for firms and price credit risks efficiently.

Credit spread determinants. How loan officer seniority matters

Cet article étudie le degré auquel l’ancienneté des chargés d’affaires au sein d’une banque interagit avec la relation clientèle et le climat des affaires pour influencer les taux d’intérêt facturés. À partir de données collectées manuellement, concernant des dossiers de crédits établis par des Petites et Moyennes Entreprises auprès d’une banque coopérative française entre 1998 et 2009, cette étude suggère que 1) les chargés d’affaires séniors facturent des taux d’intérêts plus élevés lorsque la relation clientèle est forte ; 2a) en période de climat économique défavorable, les chargés d’affaires séniors ont tendance à augmenter plus facilement les taux de crédit que les chargés d’affaires juniors, étant donné qu’ils bénéficient d’une meilleure perception du pouvoir de marché ; par contraste, 2b) ils ont tendance à modérer leur stratégie de tarification lorsque le climat des affaires devient plus favorable. Globalement, notre étude souligne le rôle crucial de l’ancienneté des chargés d’affaires dans la tarification des taux de crédit.

Explain the Determinants of Credit Spreads in the US

This paper focuses on how economic variables affect Baa corporate bond spreads in the US from January 1990 to December 2018. Credit spreads in this paper are defined as the Baa corporate bond yield minus the Aaa corporate bond yield, and are explained by four variables which are interest rates, the slope of yield curve, the stock market volatility and the economic environment. Cointegration analysis and VAR model are used in this paper to estimate the effects of the determinants of the credit spreads in the long-run and in the short-run respectively. The impacts of the industrial production index and the slope of yield curve on the Baa credit spread are negative, and the impacts of 10 year Treasury bond rate and the stock market volatility on the credit spreads are positive in the long run. In the short-run dynamic relationship, the impact of the industrial production index and the 10 years Treasury bond interest rate are negative for the credit spreads, and the slope of yield curve and stock market volatility are positive for the Baa credit spreads.

Why is bank credit in Brazil the most expensive in the world?

The article reviews the scientific literature about the determinants of credit spreads in Brazil. Econometric evidence shows that market concentration, a proxy for (un)competitive behavior, is statistically significant for all studies surveyed. We posit that that higher concentration is part of a well-defined strategy by the Brazilian Central Bank that favors prudence over efficiency. Other variables that help explain why spread in Brazil is among the highest in the world include market microstructure, operating costs, credit risk, opportunity costs, managerial quality, nominal interest rates (SELIC), market concentration, interest rate volatility, earmarked credit, and GDP.

An Integrated Analysis of the Fundamental Determinants of Credit Risk Premiums on Corporate Debt

This research investigates the fundamental components of corporate credit spreads through an integrated examination of how well different models, default probability functions, and market factors explain CDS prices. Individual company yield spreads are discovered to be determined by the interrelated risks of cash, income, and valuation insolvency, along with various measures of systematic downside risk. The empirical findings indicate that the priced risk of a jump to and at default is well explained by those fundamentals, including in ex-post tests, although the financial determinants of credit spreads are found to vary significantly across different groups of companies.

The Dollar Denominated Covered Bond Market: A Cross-Country Analysis of Credit Spreads

The authors analyze the determinants of credit spreads of 674 US dollar denominated covered bonds, issued by institutions domiciled in twenty-one countries, over the sample period 1/2001 to 1/2016. Even though covered bond contracts include strong credit enhancements, there is considerable heterogeneity in observed credit spreads through time and in the cross-section. The authors find that measures of sovereign risk and country specific legal frameworks are among the most important explanatory factors for differences in spreads across these bonds. TOPICS:Project finance, statistical methods, credit risk management Key Findings • The authors study the determinants of US dollar denominated covered bond credit spreads for bonds issued in twenty-one countries during the period 1/2001 to 1/2016. • Despite carrying strong credit enhancement features, US dollar denominated covered bonds still exhibit variation in spreads both through time and in the cross-section of issuer country of domicile. • Empirical results suggest sovereign risk and country-level legal frameworks are important determinants of US dollar denominated covered bond credit spreads.

The Analysis on Credit Spread Determinants of Chinese Enterprise Bond and Corporate Bond

The enterprise bond is basically the corporate bond. However, it has a different characteristic in that it mainly supports government financing for Chinese economic development. We analyse credit spread determinants of enterprise bond and corporate bond by using WIND system data from 2013 to 2018, which is the period when the volume of both bond types grew very rapidly. We use random effect panel regression. We find that factors related with default probability such as credit score and profitability have the same effect with theoretical expectation. However, there is a different or opposite effect between both bond types for GDP growth rate, inflation and debt ratio. Since the purpose of enterprise bond issues is supporting financing for economic development such as infrastructure, the enterprise bond spread has a negative effect for inflation and debt ratio, and a positive effect for GDP growth. We find there is no significant evidence for government premium proxied by the major shareholder dummy variable, which implies that the market poses its confidence at the profitability of the private sector rather than the government premium in the Chinese bond market.

Macroeconomic Determinants of Credit Spreads: An Empirical Comparison between Chinese and American Corporate Bonds

This paper discusses the determinants of credit spreads in China and the United states. Based on the sampled data of corporate bonds in the two countries from 2011 to 2017, we fit the yield curve of the treasury bonds with the Nelson-Siegel Model and calculate the credit spreads of each corporate bond. Then we use multiple linear regression and vector auto regression model (VAR) to analyze the determinants. The results indicate that the model can explain a large part of the credit spreads and the goodness of fit reaches over 60%. The specific results are as follows: (1) GDP and stock market volatility are negatively correlated with the credit spreads of Chinese corporate bonds but positively correlated with that of American corporate bonds with high significant level; (2) M2, stock market indexes and risk-free yield rate are negatively correlated with the credit spreads of both countries despite the fact that of all these three determinants M2 is not significant in the U.S. market and the risk-free rate of return is not significant in the Chinese market; (3) the slope of treasury bond yield curve is positively correlated with the credit spreads of corporate bonds in both countries; and (4) the impulse response shows that the impact of the determinants on credit spreads is obviously weaker than the impact of credit spreads on the determinants, which indicates that credit spreads might have a certain degree of predictive function.

Determinants of credit spreads in hotel CMBS loans

PurposeThis study aims to investigate the determinants of credit spreads in hotel loans securitized into commercial mortgage-backed securities (CMBS) between 2010 and 2015.Design/methodology/approachThe sample represents 1,579 US hotel fixed interest rate whole loans with an aggregate mortgage value of $26.6bn at loan origination. The relationship between credit spreads and property, loan and market characteristic is examined via multiple regression analysis. Additionally, the method of 2-stage least squares is used to control for endogeneity bias and identify the effect of the loan-to-value (LTV) ratio on credit spreads.FindingsThe multiple regression models explain 80 per cent of the variation in credit spreads and show a significant association of credit spreads with hotel and loan characteristics and market conditions. The findings indicate the debt coverage ratio to be the most important predictor of credit spreads followed by the loan maturity term, implied capitalization rate, LTV and yield curve. The results show the debt yield premium to be a stronger predictor of credit spreads than the debt yield ratio. The spread between the debt yield ratio and mortgage interest rate could be used in future research as an instrumental variable to identify the effect of the LTV on credit spreads.Research limitations/implicationsThis study is limited to the CMBS market and the period after the financial crisis. Additional limitations include sample selection bias, exclusion of multi-property loans and variable interest rate loans.Practical implicationsInterest rate increases in an expanding economy would likely increase the cost of borrowing for hotel owners leading to higher debt service payments and lower profitability. If an increase in interest rates is offset by a decline in credit spreads, hotel owners will still benefit from the ensuing stability in borrowing interest rates. The evidence also suggests that CMBS lenders favor select service and extended stay hotels. Owners and operators of these efficient and profitable hotels will likely obtain loans with lower credit spreads given their lower risk of default.Originality/valueThe current study provides evidence on the effects of loan and property characteristics in the pricing of loan risk and serves to inform CMBS market participants about the factors that drive credit spreads in hotel mortgage loans.

Credit Spread Determinants? Yes, Loan Officer Seniority Matters!

This paper investigates whether loan officer's level of seniority within the bank explains credit spreads. Based on a unique hand-collected database on loan applications from SMEs to a French cooperative bank between 1996 and 2009, the study suggests that senior loan officers charge higher interest rates than novice officers when -1- the bank-firm relationship is stronger and -2- the business climate is less favorable. The first result supports the idea that seniority of loan officers is a factor that fosters the hold-up problem while the second result shows that senior loan officers integrate the business climate into their pricing strategy to a greater extent than novice officers.

WITHDRAWN: Is there a missing factor? A canonical correlation approach to factor models

AbstractA common question in asset pricing research is if a finite set of observable variables can completely capture the systematic or common variations in a large number of response variables. This paper provides a new approach to answer this question. A novelty is that common factors are extracted using canonical relations between response variables and observable factors. We show how these factors in combination with tests for the number of factors can be used to evaluate if a given set of macroeconomic and financial variables is sufficient to capture all the systematic variation in the response variables. We illustrate the usefulness of our methods by analyzing the systematic determinants of credit spreads of U.S. corporate bonds.

Dynamic Dependence and Diversification in Corporate Credit*

We characterize dependence and tail dependence in corporate credit using a new class of dynamic copula models which can capture dynamic dependence and asymmetry in large samples of firms. We also document important differences between the dependence dynamics for credit spreads and equity returns. Modeling a decade of weekly CDS spreads for 215 firms, we find that copula correlations are highly time-varying and persistent, and that they increase significantly in the financial crisis and have remained high since. Perhaps most importantly, tail dependence of CDS spreads increases even more than copula correlations during the crisis and remains high as well. The most important shocks to credit dependence occur in August of 2007 and in August of 2011, but interestingly these dates are not associated with significant changes to median credit spreads. The decrease in diversification potential caused by the increase in dependence and tail dependence is large. Finally, we find that the CDS volatility, correlation and tail dependence measures that we have constructed using the dynamic copula model are important determinants of credit spreads over time. Monday, May 5, 2014, 10:30-12:00 Room 125, Extranef building at the University of Lausanne Dynamic Dependence and Diversi cation in Corporate Credit Peter Christo¤ersen Kris Jacobs University of Toronto, University of Houston CBS, and CREATES and Tilburg University Xisong Jin Hugues Langlois University of Luxembourg McGill University December 20, 2013 Abstract We characterize dependence and tail dependence in corporate credit using a new class of dynamic copula models which can capture dynamic dependence and asymmetry in large samples of rms. We also document important di¤erences between the dependence dynamics for credit spreads and equity returns. Modeling a decade of weekly CDS spreads for 215 rms, we nd that copula correlations are highly time-varying and persistent, and that they increase signi cantly in the nancial crisis and have remained high since. Perhaps most importantly, tail dependence of CDS spreads increases even more than copula correlations during the crisis and remains high as well. The most important shocks to credit dependence occur in August of 2007 and in August of 2011, but interestingly these dates are not associated with signi cant changes to median credit spreads. The decrease in diversi cation potential caused by the increase in dependence and tail dependence is large. Finally, we nd that the CDS volatility, correlation and tail dependence measures that we have constructed using the dynamic copula model are important determinants of credit spreads over time. JEL Classi cation: G12 Keywords: credit risk; default risk; CDS; dynamic dependence; copula.We characterize dependence and tail dependence in corporate credit using a new class of dynamic copula models which can capture dynamic dependence and asymmetry in large samples of rms. We also document important di¤erences between the dependence dynamics for credit spreads and equity returns. Modeling a decade of weekly CDS spreads for 215 rms, we nd that copula correlations are highly time-varying and persistent, and that they increase signi cantly in the nancial crisis and have remained high since. Perhaps most importantly, tail dependence of CDS spreads increases even more than copula correlations during the crisis and remains high as well. The most important shocks to credit dependence occur in August of 2007 and in August of 2011, but interestingly these dates are not associated with signi cant changes to median credit spreads. The decrease in diversi cation potential caused by the increase in dependence and tail dependence is large. Finally, we nd that the CDS volatility, correlation and tail dependence measures that we have constructed using the dynamic copula model are important determinants of credit spreads over time. JEL Classi cation: G12

Do FOMC Actions Speak Loudly? Evidence from Corporate Bond Credit Spreads*

We examine how corporate bond credit spreads react to Federal Open Market Committee (FOMC) announcements. FOMC change announcements (rate hikes or rate cuts) narrow credit spreads, while a no-change announcement leads to wider credit spreads. Reactions to FOMC announcements (especially cuts and no-actions) are particularly large for noninvestment-grade and short-maturity bonds. Our results hint at monetary policy as a possible candidate for macro determinants of credit spreads. Overall, the results partially support investors’ ambiguity aversion to FOMC inactions and the bond market’s greater attention to the Fed’s actions targeted at promoting growth and/or providing systemic liquidity.

Corporate Bond Credit Spreads and FOMC Announcements

We examine how corporate bond credit spreads react to Federal Open Market Committee (FOMC) announcements. FOMC change announcements (rate hikes or rate cuts) narrow credit spreads, while a no-change announcement leads to wider credit spreads. Reactions to FOMC announcements (especially cuts and no-actions) are particularly large for noninvestment-grade and short-maturity bonds. Our results hint at monetary policy as a possible candidate for macro determinants of credit spreads. Overall, the results partially support investors’ ambiguity aversion to FOMC inactions and the bond market’s greater attention to the Fed’s actions targeted at promoting growth and/or providing systemic liquidity.

Determinants of Euro-Denominated Corporate Bond Spreads

This paper computes time-varying indicators of the relative importance of different credit spread determinants, including rating, sector and country attribution as well as the coupon rate, maturity and liquidity on the basis of the comprehensive dataset of individual bonds. Additionally, it decomposes variances of rating-specific (country- and sector-specific) spread indices into the impacts of explanatory variables. Both cross-sectional and time series analyses confirm that the rating effect was the major driver of corporate bond spreads during the pre-crisis period, while the recent financial crisis was characterised by increased cross-country and cross-sector heterogeneity. The sector effects in corporate spreads together with the rating effects for high-rated and low-rated bonds are found to be more closely linked to default rates and stock indices, whereas the common effect also to be linked to business cycle conditions. The dataset also allows documenting a break-up in the existence of country ceilings for corporate bond ratings during the crisis.

A Pyrrhic Victory? Bank Bailouts and Sovereign Credit Risk

ABSTRACTWe model a loop between sovereign and bank credit risk. A distressed financial sector induces government bailouts, whose cost increases sovereign credit risk. Increased sovereign credit risk in turn weakens the financial sector by eroding the value of its government guarantees and bond holdings. Using credit default swap (CDS) rates on European sovereigns and banks, we show that bailouts triggered the rise of sovereign credit risk in 2008. We document that post‐bailout changes in sovereign CDS explain changes in bank CDS even after controlling for aggregate and bank‐level determinants of credit spreads, confirming the sovereign‐bank loop.

Investment‐Based Corporate Bond Pricing

ABSTRACTA standard assumption of structural models of default is that firms' assets evolve exogenously. In this paper, we examine the importance of accounting for investment options in models of credit risk. In the presence of financing and investment frictions, firm‐level variables that proxy for asset composition are significant determinants of credit spreads beyond leverage and asset volatility, because they capture the systematic risk of firms' assets. Cross‐sectional studies of credit spreads that fail to control for the interdependence of leverage and investment decisions are unlikely to be very informative. Such frictions also give rise to a realistic term structure of credit spreads in a production economy.

Credit spread changes within switching regimes

Empirical studies on credit spread determinants are predicated on the presence of a single-regime over the entire sample period and thus find limited explanatory power. A single-regime model hides the fact that explanatory variables take on different loadings across changing patterns in credit spreads. In a model with endogenous regimes for credit spreads or with monetary regimes, we find that market, default, and liquidity factors have superior explanatory power because of their interaction with the regime. Lower improvements are found when the regime is defined according to the credit supply regime or the NBER regimes (announced and official).

Dynamic Dependence in Corporate Credit

We characterize dependence in corporate credit and equity returns for 215 firms using a new class of large-scale dynamic copula models. Copula dependence and especially tail dependence are highly variable and persistent, increase signifi cantly in the fi nancial crisis, and have remained high since. The most drastic increases in credit dependence occur in July/August of 2007 and in August of 2011 and the decrease in diversifi cation potential caused by the increases in dependence and tail dependence is large. CDS correlation dynamics help explain the time-series variation in CDO tranche spreads and are also important determinants of credit spreads.

Determinants of credit spreads: The role of ambiguity and information uncertainty

This paper is a survey of the theoretical and empirical literature on the determinants of credit spreads. In particular I discuss whether some observations on credit spreads can be related to information risk and ambiguity about the probabilistic structure of the process driving the fundamental value of credit securities. Corporate bond yield spreads are a compensation for the various sources of risk such as default, liquidity, taxes and systematic factors. Empirical studies show that corporate bond yield spreads are still larger than can be explained by these known determinants of credit spreads. I intertwine the literature on information risk premia and ambiguity premia and argue that some observations can possibly be related to such risks.