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İzmir Ekonomi Üniversitesi

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    GRADUATE SCHOOL

    Logistics Management (Without Thesis)

    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
    Mode of Delivery -
    Teaching Methods and Techniques of the Course -
    National Occupation Classification -
    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.
    Related Sustainable Development Goals

     



    Course Category

    		Core Courses
    Major Area Courses
    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
    -
    -
    Portfolio
    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
    0
    Study Hours Out of Class
    0
    Field Work
    0
    Quizzes / Studio Critiques
    -
    0
    Portfolio
    0
    Homework / Assignments
    5
    9
    45
    Presentation / Jury
    0
    Project
    2
    46
    92
    Seminar / Workshop
    0
    Oral Exam
    0
    Midterms
    1
    40
    40
    Final Exam
    0
        Total
    225

     

    COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

    #
    		 Program Competencies/Outcomes
    * Contribution Level
    1
    2
    3
    4
    5
    1 Being able to contribute to the institution the participant works for and the logistics sector by the use of the knowledge and abilities gained during the education period; and manage change in the institution and the sector;
    -
    -
    -
    -
    -
    2 Reaching a competency about contemporary business and technology applications in the area of logistics and supply chain management and analysis and strategy development methods;
    -
    -
    -
    -
    -
    3 Being able to create opportunities by combining supply chain management with information technologies and innovative processes by the use of the interdisciplinary courses the participants take;
    -
    -
    -
    -
    -
    4 Having the ability to develop creative solutions by working on global logistics and supply chain subjects and realizing these by the use of their project management knowledge;
    -
    -
    -
    -
    -
    5 Having the knowledge, abilities and capabilities required for effective logistics and supply chain management by the use of a problem and case analysis based learning;
    -
    -
    -
    -
    -
    6 Being able to examine logistics and supply chain processes with the management science viewpoint, analyze related concepts and ideas by scientific methods;
    -
    -
    -
    -
    -
    7 If continuing to work in the academia, having the necessary information on logistics applications; if continuing to work in the sector, having the necessary knowledge on conceptual subjects;
    -
    -
    -
    -
    -
    8 Being able to specify appropriate research questions about his/her research area, conduct an effective research with the use of necessary methods and apply the research outcomes in the sector or the academia;
    -
    -
    -
    -
    -
    9 Being able to follow the changes and developments in the sector the participant works in, in order to keep his/her personal and professional competence updated and develop himself/herself when necessary;
    -
    -
    -
    -
    -
    10 Be experts in the fields of logistics and supply chain with the help of the sectorfocused education they receive;
    -
    -
    -
    -
    -
    11 Have the necessary capabilities to pursue doctoral studies in national and foreign institutions
    -
    -
    -
    -
    -

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

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