Credit Default Swaps: Implied Ratings versus Official Ones

Recently, in line with the progressive development of the credit derivatives market, the academic research has begun to explore the relationship between Credit Default Swap market and rating events. In this paper, following a market based approach, we calibrate an Implied Rating model on Credit Default Swap market spreads. The non parametric mapping of Implied Ratings is calibrated on a large data set of Credit Default Swap quotes that includes the years of financial turmoils. This allows also to investigate the existence of possible differences between normal and abnormal market conditions. Unlike other models, the one proposed considers a linear penalty function which allows to evaluate market quotes in a neutral way and to formalize a more computationally efficient programming model. We ompare the behaviors of credit rating agencies in different markets (EU and USA) and in different sub-periods, in order to analyze whether Implied Rating changes anticipate or follow the effective rating changes supplied by Fitch Ratings, Moody’s and Standard and Poor’s.