scholarly journals Credit Spreads, Business Conditions, and Expected Corporate Bond Returns

2020 ◽  
Vol 13 (2) ◽  
pp. 20 ◽  
Author(s):  
Hai Lin ◽  
Xinyuan Tao ◽  
Junbo Wang ◽  
Chunchi Wu
Keyword(s):  
Predictive Power ◽  
Return Predictability ◽  
Corporate Bond ◽  
Credit Spread ◽  
Credit Spreads ◽  
Economic Conditions ◽  
Bond Returns ◽  
Business Conditions

Using an aggregate credit spread index, we find that it has substantial predictive power for corporate bond returns over short and long horizons. The return predictability is economically and statistically significant and robust to various controls. The credit spread index and its components have more predictive power for bond returns than conventional default and term spreads. When decomposing the credit spread index into investment- and speculative-grade components, the latter has more predictive power for future bond returns. The source of the index’s predictive power is from its ability to forecast future economic conditions.

scholarly journals Common Factors in the Term Structure of Credit Spreads and Predicting the Macroeconomy in Japan

2021 ◽  
Vol 9 (2) ◽  
pp. 23
Author(s):  
Takeshi Kobayashi
Keyword(s):  
Business Cycle ◽  
Term Structure ◽  
Common Factors ◽  
Corporate Bond ◽  
Credit Spread ◽  
Credit Spreads ◽  
Real Economy ◽  
The Business Cycle ◽  
Bond Spreads ◽  
Predictive Content

This study extracts the common factors from firm-based credit spreads of major Japanese corporate bonds and examines the predictive content of the credit spread on the real economy. Instead of employing single-maturity corporate bond spreads, we focus on the entire term structure of the credit spread to predict the business cycle. We extend the dynamic Nelson-Siegel model to allow for both common and firm-specific factors. The results show that the estimated common factors are important drivers of individual credit spreads and have substantial predictive power for future Japanese economic activity. This study contributes to the literature by examining the relationship between firm-based credit spread curves and economic fluctuation and forecasting the business cycle.

Short Selling and Corporate Bond Returns

2013 ◽  
Author(s):  
Stephen E. Christophe ◽  
Michael G. Ferri ◽  
Jim Hsieh ◽  
Tao-Hsien Dolly King
Keyword(s):  
Short Selling ◽  
Corporate Bond ◽  
Bond Returns

Modeling Corporate Bond Returns

2020 ◽  
Author(s):  
Bryan T. Kelly ◽  
Diogo Palhares ◽  
Seth Pruitt
Keyword(s):  
Corporate Bond ◽  
Bond Returns

Rating Agency Adjustments to GAAP Financial Statements and Their Effect on Ratings and Credit Spreads

2014 ◽  
Vol 90 (2) ◽  
pp. 641-674 ◽  
Author(s):  
Pepa Kraft
Keyword(s):  
Default Risk ◽  
Credit Rating ◽  
Credit Ratings ◽  
Balance Sheet ◽  
Financial Statements ◽  
Financial Statement ◽  
Credit Spread ◽  
Credit Spreads ◽  
Term Structures ◽  
Interest Expense

ABSTRACT I examine a dataset of both quantitative (hard) adjustments to firms' reported U.S. GAAP financial statement numbers and qualitative (soft) adjustments to firms' credit ratings that Moody's develops and uses in its credit rating process. I first document differences between firms' reported and Moody's adjusted numbers that are both large and frequent across firms. For example, primarily because of upward adjustments to interest expense and debt attributable to firms' off-balance sheet debt, on average, adjusted coverage (cash flow-to-debt) ratios are 27 percent (8 percent) lower and adjusted leverage ratios are 70 percent higher than the corresponding U.S. GAAP ratios. I then find that Moody's hard and soft rating adjustments are associated with significantly higher credit spreads and flatter credit spread term structures. Overall, the results indicate that Moody's quantitative adjustments to financial statement numbers and qualitative adjustments to credit ratings enable it to better capture default risk, consistent with it effectively processing both hard and soft information.

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