MATHEMATICS (TURKISH, PHD) | |||||
PhD | TR-NQF-HE: Level 8 | QF-EHEA: Third Cycle | EQF-LLL: Level 8 |
Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
ECF4444 | Macrofinance | Fall | 3 | 0 | 3 | 6 |
The course opens with the approval of the Department at the beginning of each semester |
Language of instruction: | En |
Type of course: | Departmental Elective |
Course Level: | |
Mode of Delivery: | Face to face |
Course Coordinator : | Prof. Dr. ASLI YÜKSEL |
Course Lecturer(s): |
Assoc. Prof. ÇAĞLAR YURTSEVEN |
Course Objectives: | This course provides a theoretical framework to analyze macro-finance market behavior. To highlight the features of each market, the entire financial system is structured into four markets: money, bond, stock, and foreign exchange. The domestic markets are linked through Fisher equation, term structure of interest rates, and CAPM. International markets are linked through various international parity conditions. Economic fundamentals provide the rationale for determination of asset prices (returns). Recent studies in behavioral models also shed some lights on the pricing process. In addition to theoretical expositions, many empirical issues and evidence will be discussed in this lecture. |
The students who have succeeded in this course; 1.understand the core concepts in finance and economics 2.demonstrate knowledge and understanding of the concept of the valuation, forecasting, prediction 3.understand the role of modelling in finance and economics 4.understand the used softvare in finance and economics, R and Python |
Week | Subject | Related Preparation | |
1) | Introduction & Understanding the concepts in finance and economics | ||
2) | Dynamics of the markets | ||
3) | Introduction to Financial Modelling in R | ||
4) | Data search in Bloomberg, Retrieve data to R. | ||
5) | Stock Market Valuation, Prediction in Stock Returns and role of the anamolies | ||
6) | Risk Premium and Volatility, Measuring the country risk, Financial Market Volatility, Equity Premium Puzzles, Conditional Variance Models and Risk Premium | ||
7) | Risk Premium and Volatility, Measuring the country risk, Financial Market Volatility, Equity Premium Puzzles, Conditional Variance Models and Risk Premium | ||
8) | The effects of scheduled and unscheduuled news in Financial and econometric models | ||
9) | Midterm Exam | ||
10) | Behavioral Finance | ||
11) | Behavioral Finance | ||
12) | Neuroeconomics and neurofinance | ||
13) | Neuroeconomics and neurofinance | ||
14) | High Frequency Data in Financial Markets, R |
Course Notes: | 1)Alexander. Carol. Market Models: A Guide to Financial Data Analysis. New York: John Wiley, 2003. 2.John, Hull, Options, Futures, and Other Derivatives, Pearson 3. Behavioral Finance: Understanding the Social, Cognitive, and Economic Debates, 2013 4. R Programming and Its Applications in Financial Mathematics, Shuichi Ohsaki, Jori Ruppert-Felsot, Daisuke Yoshikawa, 2017 |
References: |
Semester Requirements | Number of Activities | Level of Contribution |
Attendance | % 0 | |
Laboratory | % 0 | |
Application | % 0 | |
Field Work | % 0 | |
Special Course Internship (Work Placement) | % 0 | |
Quizzes | % 0 | |
Homework Assignments | 1 | % 10 |
Presentation | % 0 | |
Project | 1 | % 20 |
Seminar | % 0 | |
Midterms | 1 | % 30 |
Preliminary Jury | % 0 | |
Final | 1 | % 40 |
Paper Submission | % 0 | |
Jury | % 0 | |
Bütünleme | % 0 | |
Total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 40 | |
PERCENTAGE OF FINAL WORK | % 60 | |
Total | % 100 |
Activities | Number of Activities | Duration (Hours) | Workload |
Course Hours | 14 | 3 | 42 |
Laboratory | 0 | 0 | 0 |
Application | 30 | 2 | 60 |
Special Course Internship (Work Placement) | 0 | 0 | 0 |
Field Work | 0 | 0 | 0 |
Study Hours Out of Class | 0 | 0 | 0 |
Presentations / Seminar | 0 | 0 | 0 |
Project | 0 | 0 | 0 |
Homework Assignments | 0 | 0 | 0 |
Quizzes | 0 | 0 | 0 |
Preliminary Jury | 0 | 0 | 0 |
Midterms | 1 | 20 | 20 |
Paper Submission | 0 | 0 | 0 |
Jury | 0 | 0 | 0 |
Final | 1 | 30 | 30 |
Total Workload | 152 |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution |