COURSE INFORMATION Course Title: ADVANCED FINANCIAL ECONOMETRICS

Code	Course Type	Regular Semester	Theory	Practice	Lab	Credits	ECTS
BAF 455	B	1	3	0	0	3	7.5

Academic staff member responsible for the design of the course syllabus (name, surname, academic title/scientific degree, email address and signature)	NA
Lecturer (name, surname, academic title/scientific degree, email address and signature) and Office Hours:	Uğur Ergün , on Mondays 15:00 to 17:00
Second Lecturer(s) (name, surname, academic title/scientific degree, email address and signature) and Office Hours:	Fatbardha Morina
Teaching Assistant(s) and Office Hours:	NA
Language:	English
Compulsory/Elective:	Elective
Classroom and Meeting Time:	Lab 3. Every Monday at 18:00
Course Description:	his course aims to give broad knowledge of modern econometric techniques in the finance literature. It is designed to cover essential tools for working with financial data, including the return forecasting, volatility and econometrics of asset pricing, such as testing the market models. This course focuses on the empirical techniques which are mostly used in the analysis of financial markets and how they are applied to actual data.
Course Objectives:	the main objective is to provide econometric skills which is necessary in academia and real life

COURSE OUTLINE

Week	Topics
1	Introduction
2	Pooling Cross Sections Across Time: Simple Panel Data Methods
3	Pooling Cross Sections Across Time: Simple Panel Data Methods
4	Advanced Panel Data Methods
5	Advanced Panel Data Methods
6	Instrumental variables Estimation and Two Stage Least Squares
7	Instrumental variables Estimation and Two Stage Least Squares
8	Midterm Exam
9	Simultaneous Estimation Models
10	Simultaneous Estimation Models
11	Limited Dependent Variable Models and Sample Selection Corrections
12	Limited Dependent Variable Models and Sample Selection Corrections
13	Advanced Time Series Methods
14	Review

Prerequisite(s):	NA
Textbook:	Wooldridge, J.M. Introduction to Econometrics, Cengage Learning
Other References:	NA
Laboratory Work:	2 hours per week
Computer Usage:	Eviews
Others:	No

COURSE LEARNING OUTCOMES

1	To learn advanced econometric methods and related theories
2	to have skills to set up robust parsimonious econometric model
3	To be able to describe and interpret the main features of the advanced econometric methods
4	To be able to assess the merits of complicated empirical tests of theories

COURSE CONTRIBUTION TO... PROGRAM COMPETENCIES (Blank : no contribution, 1: least contribution ... 5: highest contribution)

No	Program Competencies	Cont.
Master of Science in Banking and Finance Program
1	The students are gained the ability to look at the problems of daily life from a broader perspective. They gain the needed skills not only to understand economic problems in banking and finance but also to construct a model and defend in meaningful way.	4
2	They have knowledge about the finance and banking.	2
3	They have knowledge about the money and banking.	1
4	They have knowledge about the international finance and banking.	1
5	They have ability to use mathematical and statistical methods in banking and finance.	5
6	They know how to use computer programs in both daily office usage and statistical data evaluations in banking and finance department.	5
7	They have necessary banking and finance skills that needed in private and public sector.	3
8	They are intended to be specialist in one of departmental fields that they choose from the list of general economics, finance economics, public finance, corporate finance, finance management, international finance markets and institutions, banking and central banking, international finance and banking, money and banking, international trade and banking.	1
9	They have ability to utilize fundamental economic theories and tools to solve economic problems in banking and finance.	4
10	They are aware of the fact that banking and finance is a social science and they respect the social perspectives and social values of the society’s ethics.	4

COURSE EVALUATION METHOD

Method	Quantity	Percentage
Midterm Exam(s)	1	25
Presentation	1	10
Project	1	45
Attendance		20
	Total Percent:	100%

ECTS (ALLOCATED BASED ON STUDENT WORKLOAD)

Activities	Quantity	Duration(Hours)	Total Workload(Hours)
Course Duration (Including the exam week: 16x Total course hours)	16	4	64
Hours for off-the-classroom study (Pre-study, practice)	16	3	48
Mid-terms	1	15	15
Assignments	1	6.5	6.5
Final examination	1	20	20
Other	1	34	34
Total Work Load:			187.5
Total Work Load/25(h):			7.5
ECTS Credit of the Course:			7.5