While there is increasing interest in crypto assets, the credit risk of these exchanges is still relatively unexplored. To fill this gap, we considered a unique dataset of 144 exchanges, active from the first quarter of 2018 to the first quarter of 2021. We analyzed the determinants surrounding...

We develop a structural model that incorporates both macroeconomic risks and firm-specific jump risks. Using this model, we derive analytic formulas for default probability, equity price, and CDS spreads. We show that including the two types of risk in credit risk modeling can generate better...

In this paper we use a reduced form model for the analysis of Portfolio Credit Risk. For this purpose, we fit a Dynamic Factor model, DF, to a large dataset of default rates proxies and macro-variables for Italy. Multi step ahead density and probability forecasts are obtained by employing both...

We extend the Hidden Markov Model for defaults of Crowder, Davis, and Giampieri (2005) to include covariates. The covariates enhance the prediction of transition probabilities from high to low default regimes. To estimate the model, we extend the EM estimating equations to account for the time...

In this study, we consider the construction of through-the-cycle ("TTC") PD models designed for credit underwriting uses and point-in-time ("PIT") PD models suitable for early warning uses, considering which validation elements should be emphasized in each case. We build PD models using a long...

The estimation of probabilities of default (PDs) for low default portfolios by means of upper confidence bounds is a well established procedure in many financial institutions. However, there are often discussions within the institutions or between institutions and supervisors about which...

We present the framework for a distressed bond model. The utility is as a proxy for calculating the risk of a distressed bond portfolio. We elaborate several possible implementations and give an example

This article proposes a sequential Bayesian updating approach to estimate default probabilities on rating grade level for no- and low-default portfolios. Bayesian sequential updating allows to obtain default probabilities also for those rating grades for which no defaults have been observed. The...

The paper proposes a sequential Bayesian updating approach to estimate default probabilities on rating grade level for no- and low-default portfolios.Bayesian sequential updating enables default probabilities to be obtained also for those rating grades for which no defaults have been...

The article addresses the issue of stress testing based on the probability of bankruptcy and a rating migration matrix. The analysis is conducted on a sample of listed companies in Poland in the years 1998-2016, and the forecasts are made for the years 2016-2018. Particular attention is paid to...