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Credit Risk in Banking - NMFM537

Title:	Kreditní riziko v bankovnictví
Guaranteed by:	Department of Probability and Mathematical Statistics (32-KPMS)
Faculty:	Faculty of Mathematics and Physics
Actual:	from 2016 to 2017
Semester:	winter
E-Credits:	3
Hours per week, examination:	winter s.:2/0, Ex [HT]
Capacity:	unlimited
Min. number of students:	unlimited
4EU+:	no
Virtual mobility / capacity:	no
State of the course:	taught
Language:	English
Teaching methods:	full-time
Teaching methods:	full-time

Guarantor:	Sebastiano Vitali, Ph.D.
Class:	M Mgr. FPM M Mgr. FPM > Volitelné M Mgr. PMSE M Mgr. PMSE > Povinně volitelné
Classification:	Economics > Financial Economics Mathematics > Financial and Insurance Math.
Incompatibility :	NFAP042
Interchangeability :	NFAP042
Is interchangeable with:	NFAP042

Opinion survey results Examination dates Schedule Noticeboard

Annotation -

Last update: RNDr. Jitka Zichová, Dr. (16.05.2019)

During the lectures the basic introduction into the credit risk in banking industry will be given. At first the basic models for clients will be introduced (Altman model, logistic regression models etc.) for different types of clients (retail, corporate). The following lectures will deal with the basic notions concerning risk pricing (expected loss, unexpected loss). The students will get acquiant themselves with the standard credit risk models used in banking - Riskmetrics and Creditmetrics from JP Morgan, Credit Risk+ from Credit Swiss and Credit Portfolio View from McKinsey. At the same time the information about how the ideas of these models are reflected in banking legislative will be mentioned.

Aim of the course -

Last update: RNDr. Jitka Zichová, Dr. (16.05.2019)

The objective of the lecture is to give an overview of the methods connected with credit risk management: scoring, risk costs, portfolio value, Value At Risk. The students will learn the technique of logistic regression, the measurement of diversification power of scoring functions, the methods of risk costs estimation, i.e. the part of interest rate which cover the expected loss. In the last part of the lecture the VaR characteristic explanation and the methods of its estimation will be given. The lecture will make students acquainted with the current trends in credit risk management.

Literature - Czech

Last update: RNDr. Václav Kozmík, Ph.D. (26.09.2020)

[1] Hosmer, David W. and Stanley Lemeshow, Applied Logistic Regression, 2nd ed., New York; Chichester, Wiley, 2000, ISBN 0-471-35632-8.

[2] Creditmetrics, Technical document, J&P Morgan, New York 1977

Teaching methods -

Last update: RNDr. Václav Kozmík, Ph.D. (26.09.2020)

Lecture.

Syllabus -

Last update: RNDr. Jitka Zichová, Dr. (16.05.2019)

Basic models for clients will be introduced (Altman model, logistic regression models etc.) for different types of clients (retail, corporate).

Basic notions concerning risk pricing (expected loss, unexpected loss).

Standard credit risk models used in banking - Riskmetrics and Creditmetrics from JP Morgan, Credit Risk+ from Credit Swiss and Credit Portfolio View from McKinsey.