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
MAT5029 Financial Risk Analysis Fall 3 0 3 6
The course opens with the approval of the Department at the beginning of each semester

Basic information

Language of instruction: Tr
Type of course: Departmental Elective
Course Level:
Mode of Delivery: Face to face
Course Coordinator : Prof. Dr. İRİNİ DİMİTRİYADİS
Course Objectives: The purpose of the course is to introduce the student to types of risk and methods of measuring risk.

Learning Outputs

The students who have succeeded in this course;
The student will know the concepts of market, credit and operational risks and will be able to measure and estimate those risks.

Course Content

Definition of risk, market, credit and operational risks, financial derivatives, options, forwards and swaps. Measurment of market risk, Var and coherent risk measures, estimation of market risk, volatility, correlation, parametric methods, estimation of liquidity and credit risks, estimation of operational risk.




Weekly Detailed Course Contents

Week Subject Related Preparation
1) Definition of risk, types of risk, measures of risk, methods of mitigating risk.
2) Definition of market risk, credit risk and operational risk. Defining value at risk and risk metrics.
3) Financial derivatives: concepts, valuation. Hedging strategies, pricing forwards and futures, forward rate agreements, interest rates.
4) Options:concepts, strategies, valuation-binomial trees and Balck Scholes, greeks.
5) Interest rates: determining interest rates, futures, forwards, options and swaps, interest rate structured products.
6) Fixed income securities.
7) Market risk measurment. Sources of market risk. Measurment of financial risk, Var, Coherent risk measures.
8) Estimating market risk: non parametric approaches. Forecasting volatility, covariance and correlations.
9) Parametric approaches: Conditional v/s unconditional variances, Normal Var, Lognormal distribution, miscelleneous approaches:Levy, normal mixture, stochastic volatility, Cornish Fisher.
10) Multivariate normal variance-covariance approach. Extreme value theory.Uç değer kuramı.
11) Value at Risk. Computing Var. Var methods.Calculating Var for a portfolio, Calculating Var using simulation.
12) Backtesting Var, stress testing, limitations. Risk and return relationship. Liquidity, Credit and Operational Risks.
13) Modern Portfolio Theory, Minimizing risks by using portfolios, Efficient Frontier Concept
14) Basics of estimating operational risk. Applications of Efficient Frontier Portfolio with excel; Capital Asset Pricing Model and Beta measures.

Sources

Course Notes: Steven Allen, Financial Risk Management, Wiley.
References: Artzner, Ph., F. Delbaen, J.-M. Eber, D. Heath, “Coherent measures of risk”, Mathematical Finance, vol.9, no. 3 (1999), 203–228. Denault, Michel, “Coherent allocation of risk capital”, 2001 (update of 1999 original) Cummins, J. D., 2000, Allocation of Capital in the Insurance Industry, Risk Management & Insurance Review, 3: 7-27. Meyers, G. G., 2003, The Economics of Capital Allocation, in: The Casualty Actuarial Society Forum, Fall 2003 Edition, Download (2005/07/26): www.casact.org/pubs/forum/03fforum/03fftoc.htm, 391-418.

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Attendance % 0
Laboratory % 0
Application % 0
Field Work % 0
Special Course Internship (Work Placement) % 0
Quizzes % 0
Homework Assignments % 0
Presentation % 0
Project 2 % 30
Seminar % 0
Midterms 1 % 30
Preliminary Jury % 0
Final 1 % 40
Paper Submission % 0
Jury % 0
Bütünleme % 0
Total % 100
PERCENTAGE OF SEMESTER WORK % 30
PERCENTAGE OF FINAL WORK % 70
Total % 100

ECTS / Workload Table

Activities Number of Activities Duration (Hours) Workload
Course Hours 14 3 42
Laboratory 0 0 0
Application 0 0 0
Special Course Internship (Work Placement) 0 0 0
Field Work 0 0 0
Study Hours Out of Class 14 4 56
Presentations / Seminar 0 0 0
Project 2 24 48
Homework Assignments 0 0 0
Quizzes 0 0 0
Preliminary Jury 0
Midterms 1 24 24
Paper Submission 0
Jury 0
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) Ability to gain qualifications based on basic mathematical skills, problem solving, reasoning, association and generalization.
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.
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.
7) To apply mathematical principles to real world problems.
8) Ability to use the approaches and knowledge of other disciplines in Mathematics.
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.
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.
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,