Contains Nearly 100 Pages of New MaterialThe recent financial crisis has shown that credit risk in particular and finance in general remain important fields for the application of mathematical concepts to real-life situations. While continuing to focus on common mathematical approaches to model credit portfolios, Introduction to Credit Risk Modelin


Ideal for a one-semester course on mathematical probability, with examples and applications from credit risk, this self-contained text provides an introduction to the probabilistic concepts underlying the best practice credit risk models as they are used in banks today. Each chapter first presents the theory of the topic to give readers a solid background. The second part of each chapter provides applications to credit risk. The author provides mathematical proofs for all theorems and propositions. He covers such topics as random measures, probability distributions, limit theorems, stochastic simulation, Markov chains, and Brownian motion.


The financial industry is swamped by credit products whose economic performance is linked to the performance of some underlying portfolio of credit-risky instruments, like loans, bonds, swaps, or asset-backed securities. Financial institutions continuously use these products for tailor-made long and short positions in credit risks. Based on a stead