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The content of the course is an overview of risks (especially financial risks) and methods of their measuring and
management used in practice mainly in the financial sector. Students will also learn about issues of the application
of statistical methods used in practice in the process of risk measuring. The course will also include the description
of regulatory requirements of Basel II/III and Solvency II.
Last update: Zichová Jitka, RNDr., Dr. (01.06.2022)
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The objective of the course is to get the students acquainted with individual financial risks and practical methods of risk measuring and management (e.g. expected and unexpected loss, Value at Risk method, including the method of risk calculation, differences in using them for various types of risks and interpretation of results, use of rating and scoring methods, LDA and RCSA methods etc.). Students will also learn about issues of the application of statistical methods used in practice in the process of risk measuring. The course will also include the description of operations of banks, insurance companies and corporations from the point of risk management and description of regulatory requirements of Basel II/III and Solvency II.
Last update: Zichová Jitka, RNDr., Dr. (01.06.2022)
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Solving a problem and discussing it.
Last update: Zichová Jitka, RNDr., Dr. (09.05.2023)
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Hand, D.J.; Henley, W.E.: Statistical Classification Methods in Consumer Credit Scoring: A Review, Journal of the Royal Statistical Society, Series A (Statistics in Society), Vol. 160, No. 3, 1997, 523 - 541
Hull, J. C.: Options, Futures and Other Derivatives, Prentice Hall, New Yersey
Frachot, A. a další: Loss Distribution Approach in Practice; Credit Lyonnais, 2003
Gordy, M.B.: A Comparative Anatomy of Credit Risk Models; 2000; Journal of Banking and Finance
Saunders, Anthony: Credit Risk Measurement: New Approaches to Value at Risk and Other Paradigms, John Wiley & Sons, Inc.,
Vašíček, O.: Probability of Loss on Loan Portfolio; February 1987; KMV Corporation Last update: Branda Martin, doc. RNDr., Ph.D. (13.12.2020)
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Lecture. Last update: Zichová Jitka, RNDr., Dr. (01.06.2022)
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Solving a problem in advance, then its discussion during the oral exam together with some questions according to sylabus. Last update: Zichová Jitka, RNDr., Dr. (09.05.2023)
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1. Introduction to risk management, definition of risk, objective of risk management and risk classification 2. General methods of risk measuring (standard deviation, Value at Risk, stress testing, RCSA and others) and objective possibilities of risk management (technical and organizational solution or financial solution) 3. Description of operations of banks, insurance companies and corporations - business models and objectives, characteristics of activities, identification of key risks, examples of failures in risk management in the past 4. Market risk - definition, classification, market risk identification, measuring and management 5. Credit risk - definition, identification, risk measuring (individual assessment, statistical approaches, principles of rating and scoring, EWS), credit risk management, PD, LGD, credit margin 6. Liquidity risk - definition, classification, risk measuring, liquidity risk management including the use of stress scenarios, CFP 7. Operational risk - definition, identification, use of statistical methods in risk measuring (LDA method), management methods, BCM 8. Overview of risks - ERM concept, capital as a protection against risks, importance of the individual risks, risk categorisation, definition of other types of risk (IRRBB, reputational risk, concentration risk, model risk, ESG risks etc.) 9. Regulatory requirements of Basel II/III (or CRD 6 and CRR 3) and Solvency II - purpose of these measures, calculation methods of capital requirements, captured risks, limits of regulation 10. Financial crisis and lessons learned, reasons of its origin and development, discussion about the suitability of using advanced statistical methods for individual risks
Last update: Zichová Jitka, RNDr., Dr. (11.06.2024)
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Knowledge of basic mathematical and statistical concepts and methods (matrices, derivatives, integrals, distribution functions, probability density functions, various distributions of random variables, descriptive statistics, regression, Monte Carlo simulation) The course is not suitable for students of the first year of the bachelor study programme. Last update: Zichová Jitka, RNDr., Dr. (11.06.2024)
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