COURSE UNIT TITLE

: STATISTICAL DEPENDENCE AND COPULA THEORY IN FINANCE

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
STA 5027 STATISTICAL DEPENDENCE AND COPULA THEORY IN FINANCE ELECTIVE 3 0 0 7

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 AKTAŞ

Offered to

Statistics (English)
STATISTICS (ENGLISH)
Statistics (English)

Course Objective

In this course, copulas will be taught with respect to the statistical dependence concept. Theory of dependence concept will be given for analyzing properties of multivariate statistical model. The course provides the information students need to understand and model the relationship between variables in finance, insurance and economic structures etc. by using copula approach. Mainly, this course aims to present the basic theory of copulas and its applications in finance.

Learning Outcomes of the Course Unit

1   Model the dependence structure between random variables.
2   Examine various connections existing between dependence measures in detail.
3   Understand the copula concept and the need of copulas in statistical analysis of dependence structures.
4   Use copulas for modelling dependence.
5   5. Use copulas for modelling and analyzing financial events.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Probability, Probability Distributions and Probability Densities, Multivariate Distributions, Marginal Distributions, Conditional Distributions, Properties of Expectation
2 Dependence Measures, Positve quadrant and orthant dependence, Stochastic increasing positive dependece
3 Right tail increasing and left tail decreasing, Associated random variables Total positivity of order two
4 Relationships among dependence properties, Concordance, Kendall's Tau, Spearman's Rho, Tail dependence, Correlation and Dependence, Independence
5 Bivariate copula functions; definiton and basic properties, Sklar s theorem, Sklar s theorem in financial applications.
6 Survival copula, Frechet Hoeffding's bounds, The parametric families of bivariate copulas
7 Multivariate copulas
8 Examination
9 Archimedian copulas, Homework
10 Statistical inference for copulas, Exact maximum likelihood method
11 IFM method, CML method, Non-parametric estimation
12 Applications of copulas in Finance, Option Pricing with Copulas
13 Simulation of Market Scenarios; Monte Carlo simulation for copulas
14 General Review

Recomended or Required Reading

Textbook(s):
R.B. Nelsen, An introduction to copulas , Springer, 1999.
J. Rank, Copulas, From theory to application in Finance, RiskBooks, Wiley, 2007.
U. Cherubini, E. Luciano and W. Vecchiato, Copula Methods in Finance, 2004
H. Joe, Multivariate Models and Dependence Concepts, Chapman & Hall, 1997.
D.D. Mari and S. Kotz, Correlation and Dependence, Imperial College Press, 2001.

Planned Learning Activities and Teaching Methods

The course consists of lecture, class discussion, homework.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 ASG ASSIGNMENT
2 MTE MIDTERM EXAM
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE ASG * 0.30 + MTE * 0.30 + FIN * 0.40
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) ASG * 0.30 + MTE * 0.30 + RST * 0.40


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

Further Notes About Assessment Methods

None

Assessment Criteria

Homeworks and exams

Language of Instruction

English

Course Policies and Rules

Attendance is an essential requirement of this course and is the responsibility of the student. 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 www.fef.deu.edu.tr

Contact Details for the Lecturer(s)

DEU Fen Fakültesi Istatistik Bölümü
e-mail: burcu.hudaverdi@deu.edu.tr
Tel: 0232 301 85 97

Office Hours

To 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 13 1 13
Preparation for midterm exam 1 40 40
Preparation for final exam 1 45 45
Preparing assignments 1 20 20
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 164

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.15545443
LO.25545443
LO.35545443
LO.45545443
LO.55545443