We propose procedures for estimating the time-dependent transition matrices for the general class of finite nonhomogeneous continuous-time semi-Markov processes. We prove the existence and uniqueness of solutions for the system of Volterra integral equations defining the transition matrices,...

Theoretical credit risk models a la Merton (1974) predict a non-linear negative link between a firm's default likelihood and asset value. This motivates us to propose a flexible empirical Markov-switching bivariate copula that allows for distinct time-varying dependence between credit default...

Recent regulatory reforms like the mandatory clearing of standardized swap contracts and mandatory trading on centralized execution platforms have significantly changed the derivatives landscape. These reforms have, in certain cases, led the market to increasingly trade on multilateral...

We propose a novel method of estimating default probabilities using equity option data. The resulting default probabilities are highly correlated with estimates of default probabilities extracted from CDS spreads, which assume constant recovery rates. Additionally, the option implied default...

In many credit risk and pricing applications, credit transition matrix is modeled by a constant transition probability or generator matrix for Markov processes. Based on empirical evidence, we model rating transition processes as piecewise homogeneous Markov chains with unobserved structural...

Credit migration matrices are cardinal inputs to many risk management applications; their accurate estimation is therefore critical. We explore two approaches: cohort and two variants of duration - one imposing, the other relaxing time homogeneity - and the resulting differences, both...

Despite mounting evidence to the contrary, credit migration matrices, used in many credit risk and pricing applications, are typically assumed to be generated by a simple Markov process. Based on empirical evidence we propose a parsimonious model that is a mixture of (two) Markov chains, where...

We estimate a model of natural default probabilities conditional on credit ratings and macroeconomic drivers. The output is an issuer-specific expected default rate at variable horizons, which can be combined to form an expected default rate for a given portfolio of rated credits. This permits...

We develop distress prediction models for non-financial small and medium sized enterprises (SMEs) using a dataset from eight European countries over the period 2000-2009. We examine idiosyncratic and systematic covariates and find that macro conditions and bankruptcy codes add predictive power...

We present a continuous-time maximum likelihood estimation methodology for credit rating transition probabilities, taking into account the presence of censored data. We perform rolling estimates of the transition matrices with exponential time weighting with varying horizons and discuss the...