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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.
List of contents
Introduction.- Credit Risk Management.- Rating and Scoring Systems.- Portfolio Credit Risk.- Credit Derivatives.- Conclusion.- Index.
About the author
Education: Faculty of Mathematics and Physics, Charles University; Pennsylvania State University, Ph.D. in Mathematics. Work experience: 1996-2006 Komerční banka, a.s. – modern market risk management system development (implementation of the dealing system Trema, the Middle Office function and Management Information System for financial markets trading). 2000 – 2006 Director of The Credit Risk Management Division (scoring functions development, credit risk reporting and data management, implementation of Basel II, real estate valuation); 2006 – 2009 Senior Consultant CRA System (Nielsen Admosphere, a.s.). Since 2009 co-founder and managing director of Quantitative Consulting s.r.o. Academic activities: Lecturer at Pennsylvania State University and University of California in Los Angeles in the past; Associate Professor at Faculty of Mathematics and Physics at Charles University and at Faculty of Finance and Accounting of the University of Economics in Prague (Full Professor since 2016); Guarantor of the Financial Engineering Master degree program.
Summary
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.
