We investigate the one-month forward credit default swap (CDS) rate change as a function of the trailing one-month probability of default change.
Do StarMine models have predictive powers on future CDS rates?
A CDS is a contract that provides insurance against a credit event of a company, such as default, bankruptcy or debt restructuring. The buyer of protection agrees to pay periodic insurance premiums to the protection seller, until the expiration of the contract or a contractually defined credit event time, whichever occurs earlier. The annualised payment rate is called the CDS rate.
The CDS rate varies over time, depending particularly on the company probability of default.
In this research note we study and quantify how CDS rates react to changes in probability of default and assess whether the StarMine models have predictive power on future CDS rates.
Our research assesses:
- The frequency distribution of monthly percentage changes in 1Y CDS for different countries/geographic regions.
- The frequency of agency rating changes from month-end to month-end and the one-month forward rate percentage change as a function of one-month training agency rating change.
- One-month forward CDS rate percentage change versus the one-month trailing probability of default percentage change for:
- Different countries/regions
- Different 1Y CDS types for the US
- Different periods for the US for the 1Y tenor
- Subordinated Unsecure CDS for the US for the 1Y tenor
- 5Y Senior Unsecured CDS for different countries/regions
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This research demonstrates how the highly responsive StarMine Structural Credit Risk model can add value over traditional credit rating agencies, by providing a fast-moving signal that is predictive of the credit derivatives market.
powerful quantitative models are available in the StarMine suite
of default events in a 12-month horizon are captured in the StarMine Structural Credit Risk Model
credit and sovereign risk models are available in the StarMine suite