FINANCIAL ECONOMETRICS AND MODELLING

BF603

Course Code: BF603
Semester: First Term (Fall)
Theory+Practice: 3 + 0
ECTS: 15

Course Type

Compulsory Course

Course Level

Doctorate Of Science

Year of Study

Semester

First Term (Fall)

ECTS

Name of Lecturer(s)

Professor Atilla Gökçe

Learning Outcomes

At the end of this course, the students;

Understand advanced methods used in financial econometrics that are essential
Use the basic knowledge about data analysis and methods
Use regression models
Volatilite ve korelasyon modellemelerini örneklerle uygular.
Use ARCH, GARCH Models
Interpret financial issues by using financial econometric models
Interpret the results of financial econometric models to evaluate the numerical data concerning the financial markets
Read and undertsand the econometric literature in finance.
Write articles by using financial econometrics.

Mode of Delivery

Face to face

Prerequisites

Recommended Optional Programme Components

Course Description

This course aims to present the advanced methods that are used in financial econometrics. Data analysis, regression models, volatily and corelation modelling, ARCH, GARCH models are covered with their applications. By using these methods students can interpret developments in the financial sector. Also this module will be very important for students when writing their Phd thesis and for foolowing the relevant literatüre in the financial field.

Course Contents

WEEK	TOPICS
1^st Week	Introduction: Matrix Algebra
2^nd Week	Continious Multi Variate Distrubutions
3^rd Week	Multi Variate Normal Distrubution
4^th Week	Multi Variate Hypothesis Testing
5^th Week	Main Component Analysis
6^th Week	Main Component Analysis
7^th Week	Mid Term Exam
8^th Week	Factor Analysis
9^th Week	Factor Analysis
10^th Week	Canonic Correlation
11^th Week	Discriminant Analysis
12^th Week	Logistic Regresion
13^th Week	Clustering Analysis
14^th Week	Clustering Analysis
15^th Week

Recommended or Required Reading

1. Applied Multivariate Statistical Analysis, Richard A. Johnson & Dean W. Wichern, 2002
2. An Introduction to Multivariate Statistical Analysis, Anderson, Theodore, W.

Planned Learning Activities and Teaching Methods

Lecture
Discussion
Questions/Answers
Project
Presentation

Assessment Methods and Criteria

	Quantity	Percentage (%)
Mid-term	1	30
Project	1	25
Attendance	1	10
Total(%)		65
Contribution of In-term Studies to Overall Grade(%)		65
Contribution of Final Examination to Overall Grade(%)		35
Total(%)		100

ECTS Allocated Based on Student Workload

Activities	Quantity	Duration (Hour)	Total Workload (Hour)
Midterm exam
Preparation for Quiz
Individual or group work	14	20	280
Preparation for Final exam	1	50	50
Course hours	14	3	42
Preparation for Midterm exam
Laboratory (including preparation)	14	3	42
Final exam	1	3	3
Homework	2	16	32
Total Work Load			449
Total Work Load / 30 (h)			14.96
ECTS Credit of the Course			15

Language of Instruction

Turkish

Work Placement(s)

Programme Qualifications / Learning Outcomes

	LO1	LO2	LO3	LO4	LO5	LO6	LO7	LO8	LO9
K1			X	X	X	X	X
K2									X
K3									X
K4								X
K5								X