ECON 517 | Course Introduction and Application Information

Course Name
Financial Econometrics
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
ECON 517
Fall/Spring
3
0
3
7.5

Prerequisites
None
Course Language
English
Course Type
Elective
Course Level
Second Cycle
Course Coordinator -
Course Lecturer(s) -
Assistant(s) -
Course Objectives This course introduces the student to a wide range of techniques in financial econometrics, and their practical applications. Prior knowledge of statistics and econometrics is very useful, but it isn’t necessary. Each student is required to hand in a class project that applies class material to real financial data. Accordingly, one of the aims of the course is to give students the skills necessary to pursue independent research projects, and the backgrounds to be able to extend their knowledge to additional topics of interest without much difficulty.

Class applications will utilize the open source econometrics software, Gretl. It can be downloaded and installed free of charge from the website: http://gretl.sourceforge.net/
Learning Outcomes The students who succeeded in this course;
  • will be able to identify the specific properties of financial data.
  • will be able to use econometric tools that are specifically designed to analyze financial data.
  • will be able to build econometric models that describe the behavior of financial time series.
  • will be able to pursue an independent empirical research project from start to finish, including data collection, estimation, and interpretation of results.
  • will be able to extend his/her knowledge on financial econometrics without much difficulty.
  • will be able to seek answers to financial questions beyond the coverage of this class.
Course Description The course will mostly be based on Time Series econometric methods. While this is the ideal approach for an introduction to the fundamental methods of quantitative finance, the student should keep in mind that the range of econometric methods that can be used to answer questions related to finance and financial economics spans almost the entire spectrum of econometrics. The course starts by reviewing basic tools of statistics and econometrics, and makes brief introductions to regression analysis, least squares methods, and some extensions of these topics. Then, numerous time series methods are discussed, including the estimation and forecasting of ARMA and ARIMA models, models of conditional heteroscedasticity (ARCH/GARCH), vector autoregressions, and cointegration. Each topic is discussed along with its applications in finance, keeping in mind the peculiarities of financial data and methods that are designed to work with such data.

 



Course Category

Core Courses
Major Area Courses
X
Supportive Courses
Media and Management Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Foundations: A Review of Probability and Statistics Class notes.
2 Introduction to Regression Analysis Brooks, Chapters 2 & 3
3 Topics in Regression Analysis Brooks, Chapters 3 & 4
4 Foundations of Time Series Econometrics Brooks, Chapter 5
5 ARMA Modeling, pt.1 Brooks, Chapter 5
6 ARMA Modeling, pt.2 Brooks, Chapter 5, Class notes and additional reading material
7 Midterm Exam
8 Nonstationarity, Unit Roots, and ARIMA Models Brooks, Chapter 7
9 Forecasting with Time Series Brooks, Chapter 5
10 Autoregressive Conditional Heteroscedasticity: ARCH and GARCH, pt. 1 Brooks, Chapter 8, Class notes and additional reading material
11 Autoregressive Conditional Heteroscedasticity: ARCH and GARCH, pt.2 Brooks, Chapter 8, Class notes and additional reading material
12 Stationary Vector Models: VAR Brooks, Chapter 6
13 Cointegration and Common Trends Brooks, Chapter 7
14 Additional Topic (Optional and Time Permitting)
15 Additional Topic (Optional and Time Permitting)
16 Review of the Semester  

 

Course Notes/Textbooks Svetlozar T. Rachev, Stefan Mittnik, Frank J. Fabozzi, Sergio M. Focardi, and Teo Jasic, Financial Econometrics: From Basics to Advanced Modeling Techniques (John Wiley & Sons, Inc.).
Suggested Readings/Materials On Financial Econometrics: • Chris Brooks, Introductory Econometrics for Finance (Second Edition) • Carol Alexander, Market Models: A Guide to Financial Data Analysis. On Time Series: • Walter Enders, Applied Econometric Time Series (Second Edition) • Brockwell and Davis, Introduction to Time Series and Forecasting (Second Edition)

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques
-
-
Homework / Assignments
5
20
Presentation / Jury
Project
2
55
Seminar / Workshop
Oral Exams
Midterm
1
25
Final Exam
Total

Weighting of Semester Activities on the Final Grade
75
Weighting of End-of-Semester Activities on the Final Grade
25
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Theoretical Course Hours
(Including exam week: 16 x total hours)
16
3
48
Laboratory / Application Hours
(Including exam week: 16 x total hours)
16
Study Hours Out of Class
Field Work
Quizzes / Studio Critiques
-
Homework / Assignments
5
9
Presentation / Jury
Project
2
46
Seminar / Workshop
Oral Exam
Midterms
1
40
Final Exam
    Total
225

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1

To improve and deepen expertise in economics and finance.

X
2

To be able to comprehend the interaction between economics, finance and related fields.

3

To be able to apply the advanced level knowledge acquired in economics and finance.

X
4

To be able to create new knowledge by combining the knowledge of finance and economics with the knowledge coming from other disciplines and be able to solve problems which requires expert knowledge by applying scientific methods.

X
5

To be able to use computer programs needed in the fields of economics and finance as well as information and communication technologies in advanced levels.

X
6

To be able to think analytically to identify problems in finance and economics and to be able to make policy recommendations in economics and finance based on scientific analysis of issues and problems.

X
7

To be able to develop new strategic approaches for unexpected, complicated situations in finance and economics and take responsibility in solving it.

X
8

To protect the social, scientific and ethical values at the data collection, interpretation and dissemination stages and to be able to institute and observe these values.

X
9

To be able to critically evaluate the knowledge in finance and economics, to lead learning and carry out advanced level research independently.

10

To be able to use a foreign language for both following scientific progress and for written and oral communication.

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest