COURSE UNIT TITLE

: QUANTITATIVE METHODS IN RISK MANAGEMENT

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
CSC 5015 QUANTITATIVE METHODS IN RISK MANAGEMENT ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR BURCU HÜDAVERDI

Offered to

Computer Science
Ph.D. in Computer Science

Course Objective

Specifically statistical modelling issues in quantitative risk management will be given in this course. The aim of this course is to provide some information graduate students need to understand and model the financial risks with mathematical point of view. In statistical terms, the joint distribution of the risk factors will be modelled using a multivariate concept.

Learning Outcomes of the Course Unit

1   Demonstrate the probabilistic description of risks
2   Know the general concepts about continuous multivariate distributions
3   Know the basic concepts used in all branches of quantitative risk management.
4   Describe the financial time series (stock returns, exchange rate returns, etc) with statistical properties.
5   Understand how to measure the financial risk with mathematical knowledge.
6   Learn how to model multivariate continuous distributions using copulas.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 The Probabilistic Description of Risks
2 Distribution Functions, Conditional Distribution, Comonotonicity, Mutual Exclusivity.
3 Basics of Multivariate Modeling
4 Dimension Reduction Techniques.
5 Statistical Properties of Financial Data, Fundamentals of Time Series Analysis.
6 Statistical Properties of Financial Data, Conditional expected returns of financial time series
7 MIDTERM Exam
8 Application
9 Introduction to Quantitative Risk Management
10 Risk Measures, Value at-Risk (VaR),
11 Tail Value-at-Risk(TVaR), Risk Measures Based on Expected Utility Theory
12 Standard Methods for Market Risks, Variance-Covariance Method, Monte Carlo, Backtesting
13 Modeling Dependence Using Copulas
14 Dependence Measures Some copula Families
15 Review

Recomended or Required Reading

Textbook(s): A.J. McNeil, R. Frey, and P. Embrechts. Quantitative risk management.
Princeton Series in Finance. Princeton University Press, 2005.
Supplementary Book(s): M. Denuit, J. Dhaene, M. Goovaerts and R. Kaas, Actuarial Theory for Dependent Risks: Measures, Orders and Models. John Wiley &Wiley Sons, 2005.

Planned Learning Activities and Teaching Methods

Teaching materials for the course come from the primary and supplemantary textbooks. Some projects/computer lab explorations are completed in class while some are expected to be done outside of class -as homework. Questions and discussion will be encouraged.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.30 +ASG * 0.20 +FIN * 0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + ASG * 0.20 + RST * 0.50


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Mid-term: 30%
Assignments: 20%
Final exam: 50%

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

burcu.hudaverdi@deu.edu.tr

Office Hours

will be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 12 1 12
Preparation for midterm exam 1 48 48
Preparation for final exam 1 48 48
Preparing assignments 4 9 36
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 190

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.134
LO.234
LO.334
LO.434
LO.534
LO.634

CONTACT INFORMATION
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Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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