  Credit Default Swap (CDS) levels provide a market appreciation of companies'
default risk. These derivatives are not always available, creating a need for
CDS approximations. This paper offers a simple, global and transparent CDS
structural approximation, which contrasts with more complex and proprietary
approximations currently in use. This Equity-to-Credit formula (E2C), inspired
by CreditGrades, obtains better CDS approximations, according to empirical
analyses based on a large sample spanning 2016-2018. A random forest regression
run with this E2C formula and selected additional financial data results in an
87.3% out-of-sample accuracy in CDS approximations. The transparency property
of this algorithm confirms the predominance of the E2C estimate, and the impact
of companies' debt rating and size, in predicting their CDS.
