This paper demonstrates how deep learning can be used to price and calibrate models of credit risk. Deep neural networks can learn structural and reduced-form models with high degrees of accuracy. For complex credit risk models, whose closed-form solutions are not available, deep learning offers...

We define and construct a credit-implied volatility (CIV) surface from the firm-by-maturity panel of CDS spreads. We use this framework to organize the behavior of corporate credit markets into three stylized facts. First, CIV exhibits a steep moneyness smirk. Second, the joint dynamics of...

This paper studies the dynamic propagation mechanisms of systemic risk shocks within and across macro-systems of governments and financial institutions. We propose a novel approach to identify relevant systemic shocks and to classify them into sovereign or banking categories. We find that...

I empirically decompose sovereign credit spreads into a default-risk component and its associated (credit) risk premium and study the effect of political uncertainty on them. On average, credit risk premia account for 42 percent of the observed spreads in the European sovereign credit market. I...