Course Code & Number
BA 434
Course Title
Financial Econometrics
Credit Hours/ ECTS Credits
(3+0+0) 3 TEDU Credits, 6 ECTS Credits
Type of Course:
Compulsory
Mode of Delivery:
Face-to-face
Language of Instruction:
English
Pre-requisite / Co-requisite::
Pre-requisites: BA 304
Co-requisites: NONE
Catalog Description
Mathematical optimization. Data analysis. Probability models. Statistical analysis. Linear models. Dynamic factor models. Intertemporal behavior and method of moments. Econometrics of derivatives. Market indexes.
Course Objectives
The main objective of this course is to explain the basic econometric tools used in finance.
Software Usage
Students will use MS Office applications (Word, Excel, Access, Powerpoint) to work on their weekly assignments about 2 hours a week.
Course Learning Outcomes
Upon succesful completion of this course, a student will be able to
1. Define the basic econometric tools used in finance
2. Recognize the importance of using econometric tools in the assessment of risk in businesses
3. Identify the univariate, multivariate, dynamic and diffusion models
4. Evaluate business plans, sources of capital, marketing and distribution strategies, operations, organization issues, as well as key legal and ethical considerations affecting entrepreneurial ventures
5. Interpret the econometrics of derivatives and market indexes
6. Discover the applications of econometrics tools in the business environment
Learning Activities and Teaching Methods:
Telling/Explaining
Discussion/Debate
Questioning
Reading
Peer Teaching
Problem Solving
Case Study/Scenarion Analysis
Oral Presentations/Reports
Web Searching
Assessment Methods and Criteria:
Assessment Methods and Criteria Others:
Recommended Reading
1. Journal of Financial Econometrics.
2. The Econometrics Journal.
3. Oxford Review of Financial Studies.
4. Journal of Finance.
5. Related journal articles and publications.
Required Reading
1. Financial Econometrics, C. Gourieroux and J. Jasiak, Princeton Series in Finance, 2001.
Learning Activities and Teaching Methods Others:
Student Workload:
Workload |
Hrs |
Case Study Analysis |
12 |
Course & Program Learning Outcome Matching: