Credit Risk Management e-bog

This book introduces to basic and advanced methods for credit risk management. It covers classical debt instruments and modern financial markets products. The author describes not only standard rating and scoring methods like Classification Trees or Logistic Regression, but also less known models that are subject of ongoing research, like e.g. Support Vector Machines, Neural Networks, or Fuzzy Inference Systems. The book also illustrates financial and commodity markets and analyzes the principles of advanced credit risk modeling techniques and credit derivatives pricing methods. Particular attention is given to the challenges of counterparty risk management, Credit Valuation Adjustment (CVA) and the related regulatory Basel III requirements.  As a conclusion, the book provides the reader with all the essential aspects of classical and modern credit risk management and modeling.