COURSE UNIT TITLE

: STATISTICS IN RISK MANAGMENT

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IST 4184 STATISTICS IN RISK MANAGMENT ELECTIVE 3 0 0 5

Offered By

Statistics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR DOCTOR BURCU HÜDAVERDI

Offered to

Statistics
Statistics(Evening)

Course Objective

Specifically statistical modelling issues in financial risk management will be given in this course. The aim of this course is to provide the basic information students need to understand and model the financial risks with statistical 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 statistical 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 Modeling Risks: The Probabilistic Description of Risks, Independence for Events and Conditional Probabilities, Random Variables.
2 Modeling Risks: Distribution Functions, Mathematical Expectation, Conditional Distribution, Comonotonicity, Mutual Exclusivity.
3 Introduction to multivariate models: Basics of Multivariate Modeling, Spherical and Elliptical Distributions
4 Introduction to multivariate models: Dimension Reduction Techniques.
5 Statistical Properties of Financial Data: Fundamentals of Time Series Analysis, Informal description of financial time series (stock returns, exchange rate returns, etc), serial correlation.
6 Statistical Properties of Financial Data: Conditional expected returns of financial time series, GARCH models for volatility.
7 Introduction to Quantitative Risk Management: Basic concepts in all branches of risk management, Risk in Perspective
8 Midterm exam
9 Measuring Risk: Risk Measures, Value at-Risk (VaR),
10 Measuring Risk: Tail Value-at-Risk(TVaR), Risk Measures Based on Expected Utility Theory
11 Measuring Risk: Standard Methods for Market Risks, Variance-Covariance Method, Monte Carlo, Backtesting
12 Modeling Dependence Using Copulas: Basic properties of copulas
13 Modeling Dependence Using Copulas: Dependence Measures
14 Modeling Dependence Using Copulas: Some copula Families.

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 supplementary 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 FINS 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

Evaluation of exams and homework.

Language of Instruction

English

Course Policies and Rules

Attendance to at least 70% for the lectures is an essential requirement of this course and is the responsibility of the student. It is necessary that attendance to the lecture and homework delivery must be on time. Any unethical behavior that occurs either in presentations or in exams will be dealt with as outlined in school policy. You can find the undergraduate policy at http://web.deu.edu.tr/fen

Contact Details for the Lecturer(s)

DEU Fen Fakültesi Istatistik Bölümü
e-mail: guckan.yapar@deu.edu.tr
Tel: 0232 301 85 59

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 3 39
Preparation before/after weekly lectures 12 1 12
Preparation for Mid-term Exam 1 24 24
Preparation for Final Exam 1 31 31
Preparing Group Assignments 2 3 6
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 116

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14
LO.1545445
LO.2545455
LO.3545455
LO.4545455
LO.5545455
LO.6545455

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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