In the previous sessions of this course, we developed default models based on certain assumptions about the underlying structure of the probability distribution of the capacity of payment of the borrower. In a way, we has to have a view of some kind of continuous process and a barrier, that once reached would trigger a default event.  The previous setting is propitious for a setting where the lender has some information on how the the shocks to which a borrower is exposed are distributed. 

In this session the construct is different.  We start from a dynamic setting in which there is a finite number of states. The subject moves from one state to another in the next consecutive moment with a given probability. Some of these states correspond to a default.

The transition probabilities are the subject of the modeling exercises, generally known as Markov Chains.

This is part 33 of a 45-document course on Modeling Financial Markets.