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...

This paper examines whether financial buyers are more likely to initiate takeovers of inefficient firms. We show that they indeed are and thus conclude that takeovers by financial buyers play a potentially beneficial role in the allocation of corporate assets in the U.S. economy. Our analysis of...

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...

Despite overwhelming 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. In this paper we propose a parsimonious model that is a mixture of (two) Markov chains. We estimate this...

This paper considers a new mixture of time homogeneous finite Markov chains where the mixing is on the rate of movement and develops the EM algorithm for the maximum likelihood estimation of the parameters of the mixture. A continuous and discrete time versions of the mixture are defined and...

This paper examines whether financial buyers are more likely to initiate takeovers ofinefficient firms. We show that they indeed are and thus conclude that takeovers byfinancial buyers play a potentially beneficial role in the allocation of corporate assets in the U.S. economy. Our analysis of...

The usual tool for modeling bond ratings migration is a discrete, time homogeneous Markov chain. Such model assumes that all bonds are homogeneous with respect to their movement behavior among rating categories and that the movement behavior does not change over time. However, among recognized...