We propose a relatively simple, accurate and flexible approach to forecasting the distribution of defaulted debt recovery outcomes. Our approach is based on mixtures of Gaussian distributions, explicitly conditioned on borrower characteristics, debt instrument characteristics and credit...

In this paper we have presented a new approach to measure the return-risk trade-off in portfolios of risky debt instruments, whether bonds or loans. The use of complex, statistically based portfolio techniques to manage assets of financial institutions and fixed income portfolio money managers...

In response to the recent elevated corporate credit risk environment in China’s credit market, we develop a probability of default (PD) measure for Chinese companies using actual corporate bond defaults by applying the Least Absolute Shrinkage and Selection Operator (LASSO) machine learning...

We estimate the impact of the COVID-19 pandemic on credit risk changes on a large sample of Polish SME firms. The Altman Z"-Score model, which has proven to be a powerful and robust bankruptcy prediction model across many industries and countries, is used to assess over 1,000 SMEs from seven...

We develop a structural model of credit risk in a network economy. In particular, we are able to account for complex counterparty relationships,where one company may be indirectly affected by the credit risk of another company in the network. In this re-spect,we generalize Jarrow and Yu...