MAT5028 Fixed Income Securities and Credit RiskBahçeşehir UniversityDegree Programs APPLIED MATHEMATICS (TURKISH, THESIS)General Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
APPLIED MATHEMATICS (TURKISH, THESIS)
Master TR-NQF-HE: Level 7 QF-EHEA: Second Cycle EQF-LLL: Level 7

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
MAT5028 Fixed Income Securities and Credit Risk Fall 3 0 3 12
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction: Turkish
Type of course: Departmental Elective
Course Level:
Mode of Delivery: Face to face
Course Coordinator : Prof. Dr. İRİNİ DİMİTRİYADİS
Recommended Optional Program Components: None
Course Objectives: This course aims to introduce students to the models used in the management of portfolio credit risk. Models currently used in the market are explored and an undrstanding of default dependence is acquired. The use of credit models to determine capital adequacy is shown and an introduction to credit derivatives is given.

Learning Outcomes

The students who have succeeded in this course;
On completion of the course the student will be able to demosntrate and understanding of credit risk, explain how dependence is modelled in credit portfolios, describe methods for calculating the protfolio loss distribution and will have some idea about credit derivatives.

Course Content

Review of financial derivatives, introduction to credit risk, Merton's model for default of a firm, KMV, CreditMetrics and CreditRisk+ models, showing dependence between defaults with factor models, calculating portfolio credit loss distribution,calibration amd inference for credit risk models, introduction to credit derivatives.

Weekly Detailed Course Contents

Week Subject Related Preparation
1) Review of financial derivatives.
2) Financial derivatives continued.
4) Introduction to credit risk;credit risky instruments, defaults, ratings.
5) Default of a firm and Merton's model.
6) Common industry models (KMV, CreditMetrics, CreditRisk+)
7) Modelling dependence between defaults with factor models.
8) Common industry models (KMV, CreditMetrics, CreditRisk+) continued.
9) Mixture models of default.
10) Calculating the portfolio credit loss distribution.
11) Large portfolio behaviour of the credit loss distribution.
12) Calibration and statistical inference for credit models.
13) Introduction to credit derivatives.
14) Credit derivatives continued.

Sources

Course Notes / Textbooks: McNeill, A.J. and Frey, R., and Embrechts, P, (2005), Quantitative Risk Management: Conceptes, Techniques and Tools, Princeton, New Jersey.

Bluhm, C., and Overbeck, L., and Wagner, C.(2002). An Introduction to Credit Risk Modeling. Chapmanqnd Hall/CRC Financial Mathematics Series, London.
References: CreditMetrics™– Technical Document, http://www.ma.hw.ac.uk/~mcneil/F79CR/CMTD1.pdf

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Total %
PERCENTAGE OF SEMESTER WORK % 0
PERCENTAGE OF FINAL WORK %
Total %

ECTS / Workload Table

Activities Number of Activities Duration (Hours) Workload
Course Hours 14 3 42
Homework Assignments 6 13 78
Midterms 2 25 50
Final 1 30 30
Total Workload 200

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) Ability to assimilate mathematic related concepts and associate these concepts with each other. 2
2) Ability to gain qualifications based on basic mathematical skills, problem solving, reasoning, association and generalization. 2
3) Be able to organize events, for the development of critical and creative thinking and problem solving skills, by using appropriate methods and techniques.
4) Ability to make individual and team work on issues related to working and social life. 2
5) Ability to transfer ideas and suggestions, related to topics about his/her field of interest, written and verball.
6) Ability to use mathematical knowledge in technology. 2
7) To apply mathematical principles to real world problems. 1
8) Ability to use the approaches and knowledge of other disciplines in Mathematics. 2
9) Be able to set up and develope a solution method for a problem in mathematics independently, be able to solve and evaluate the results and to apply them if necessary. 3
10) To be able to link abstract thought that one has to concrete events and to transfer the solutions and examine and interpret the results scientifically by forming experiments and collecting data. 2
11) To be able to conduct a research either as an individual or as a team member, and to be effective in each related step of the project, to take role in the decision process, to plan and manage the project by using time effectively.
12) To be able to acquire necessary information and to make modeling in any field that mathematics is used and to improve herself/himself,