Dun & Bradstreet Predictors Explain 15% to 35% of the Total Variation in Credit Spreads
Investment managers consistently seek ways to better explain, price and ultimately, invest in corporate bonds and other corporate risk assets. We believe capital markets investors can benefit from the power of Dun & Bradstreet's unique B2B data and analytics to help them be more informed about corporate bond credit spreads.
To demonstrate the value of business insights to make confident investment decisions, our Advanced Analytics team recently published the study Explaining the variation in U.S. corporate bond credit spreads using Dun & Bradstreet data and analytics.
We specify a corporate bond model that explains over one half of the variation in credit spreads. Given the findings in this study, we think that Dun & Bradstreet’s unique data and analytics will be instrumental in pricing any corporate risk asset, whether it be investment grade corporate bonds, high yield bonds, credit default swaps, stock volatility (stock options or variance swaps) or for modeling equity risk.
After controlling for aggregate interest rate and credit spread risks, bond maturity, industry and time, we find that specified Dun & Bradstreet predictors explain 15% to 35% of the total variation in credit spreads. Those predictors are categorized into one of the following three groups:
- Payment Burden: When a company’s overdue payables or cash payables to suppliers are large relative to a company’s sales, credit spreads tend to be higher.
- Leverage Over Suppliers: If a company has leverage over its suppliers, it can sometimes benefit by delaying a payment, securing a lower borrowing rate from a supplier of debt capital or attaining a higher price from a supplier of equity capital. With greater leverage over suppliers, credit spreads tend to be lower.
- Risk Exposure: Established Dun & Bradstreet credit models define the likelihood that a company will experience financial stress, operation difficulty or failure in the coming year. Using only Dun & Bradstreet data, we have developed a new risk factor in our corporate bond model. As expected, as risk exposure increases, credit spreads tend to increase too.
The study Explaining the variation in U.S. corporate bond credit spreads using Dun & Bradstreet data and analytics highlights actual vs. predicted credit spreads for our model for an in-sample and out-of-sample period. The results demonstrate that Dun & Bradstreet business data and analytics can help investment managers price and ultimately invest in any corporate risk asset.