Context

A Credit Default Swap (CDS) is a credit derivative contract between two counterparties. The buyer makes periodic payments to the seller, and in return receives a payoff if an underlying financial instrument defaults or experiences a similar credit event. The CDS may refer to a specified loan or bond obligation of a "reference entity", usually a corporation or government. The spread of a CDS is the annual amount the protection buyer must pay the protection seller over the length of the contract, expressed as a percentage of the notional amount. All things being equal, at any given time, if the maturity of two credit default swaps is the same, then the CDS associated with a company with a higher CDS spread is considered more likely to default by the market, since a higher fee is being charged to protect against this happening.

Source: Wikipedia

Content

The dataset includes timeseries of CDS spreads/prices for over 600 names in 10 different tenors. CDS curves can easily be constructed and tasks like bootstrapping for hazard rates can be performed.

Inspiration

I couldn't find any CDS datasets on Kaggle or other public platforms, so thought of sharing this clean dataset that I collated from multiple sources for a personal project to the Kaggle community.