COURSE INTRODUCTION AND APPLICATION INFORMATION


Course Name
Financial Econometrics
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
FIN 603
Fall
3
0
3
10
Prerequisites
None
Course Language
English
Course Type
Required
Course Level
Third 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.
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.will be able to indicate how the economic decisions of consumption, saving and investment by individuals is reflected in financial markets.
Course Content 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
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Introduction
2 Introduction to Financial Econometrics Analysis of Financial Time Series by Ruey S. Tsay, Introductry Econometrics for Finance by Chris Brooks
3 Empirical Characteristics of Return Analysis of Financial Time Series by Ruey S. Tsay, Introductry Econometrics for Finance by Chris Brooks
4 Applications of Linear Models Analysis of Financial Time Series by Ruey S. Tsay, Introductry Econometrics for Finance by Chris Brooks
5 Applications of Linear Models Analysis of Financial Time Series by Ruey S. Tsay, Introductry Econometrics for Finance by Chris Brooks
6 Risk and Volatility Analysis of Financial Time Series by Ruey S. Tsay, Introductry Econometrics for Finance by Chris Brooks
7 Risk and Volatility Analysis of Financial Time Series by Ruey S. Tsay, Introductry Econometrics for Finance by Chris Brooks
8 Midterm
9 Risk and Return Analysis of Financial Time Series by Ruey S. Tsay, Introductry Econometrics for Finance by Chris Brooks
10 Risk and Return Analysis of Financial Time Series by Ruey S. Tsay, Introductry Econometrics for Finance by Chris Brooks
11 Cointegration and Random Walk Analysis of Financial Time Series by Ruey S. Tsay, Introductry Econometrics for Finance by Chris Brooks
12 Cointegration and Random Walk Analysis of Financial Time Series by Ruey S. Tsay, Introductry Econometrics for Finance by Chris Brooks
13 High Frequency Data and Models Analysis of Financial Time Series by Ruey S. Tsay, Introductry Econometrics for Finance by Chris Brooks
14 High Frequency Data and Models Analysis of Financial Time Series by Ruey S. Tsay, Introductry Econometrics for Finance by Chris Brooks
15 Review of the Semester
16 Review of the Semester
Course Textbooks Book chapters indicated above
References Related papers

 

EVALUATION SYSTEM

Semester Requirements Number Percentage
Participation
16
10
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Homework / Assignments
Presentation / Jury
1
20
Project
1
20
Seminar / Workshop
1
20
Midterms / Oral Exams
1
30
Final / Oral Exam
Total

Contribution of Semester Work to Final Grade
100
Contribution of Final Work to Final Grade
Total

ECTS / WORKLOAD TABLE

Activities Number Duration (Hours) Workload
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
16
3
Field Work
Quizzes / Studio Critiques
Homework / Assignments
Presentation / Jury
1
2
Project
1
20
Seminar / Workshop
1
Midterms / Oral Exams
1
15
Final / Oral Exam
21
    Total
133

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Qualifications / Outcomes
* Level of Contribution
1
2
3
4
5
1 Developing scientific expertise and capabilities in the field of finance through using creative and critical thinking and research skills; innovatively contribute to the discipline by new ideas and definitions based on the graduate level qualifications.
2 Comprehending the interaction across various disciplines related to the field of finance, reaching at original conclusions by using new and complex analysis, synthesis and evaluation skills.
3 Developing and championing new approaches to contribute the field of finance through apprehending the research methods.
4 Contributing to the science of finance through developing new methods or implementing an existing method to a different field through investigating, comprehending, designing original topics.
5 Conducting independent research, analyzing scientific phenomenon through broad, deep and critical perspective, arriving at new syntheses and evaluations in the discipline of finance.
6 Publishing scientific articles in reputable refereed national and international journals, presenting papers in scientific conferences in the field of finance and its sub-disciplines.
7 Following, attending and organizing national and international events such as conferences, seminars and panels to keep up with developments and create new solutions to the problems in the field of finance.
8 Following pioneering and innovative theories and methods in the field of finance and implementing them in analysis and research.
9 Developing creative solutions to the social, scientific and ethical issues within the scope of finance and business life and extending values that supports these solutions.
10 Being able to use English fluently for both comprehending and publishing scientific publications and developing proper communication.

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

 

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