ECTS - Statistical Methods and Financial Applications
Statistical Methods and Financial Applications (MATH437) Course Detail
Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
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Statistical Methods and Financial Applications | MATH437 | Area Elective | 3 | 0 | 0 | 3 | 6 |
Pre-requisite Course(s) |
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N/A |
Course Language | English |
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Course Type | Elective Courses |
Course Level | Bachelor’s Degree (First Cycle) |
Mode of Delivery | Face To Face |
Learning and Teaching Strategies | Lecture, Question and Answer, Problem Solving. |
Course Lecturer(s) |
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Course Objectives | The goal of this course is to provide students in mathematical finance programs with a basic background in statistical methods. The presentation of the course attempts to strike a balance between theory and applications. |
Course Learning Outcomes |
The students who succeeded in this course;
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Course Content | Central tendency/dispersion measures, moments, maximum likelihood estimation, correlation and simple linear regression, multi-regression model, autocorrelation and multi-collinearity on regression models, portfolio theory, CAPM and ARMA approaches. |
Weekly Subjects and Releated Preparation Studies
Week | Subjects | Preparation |
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1 | Role of statistical method in financial analysis, such as central tendency/dispersion measures of unclassified and classified data | [2] pp.254-262 |
2 | Moment of a random variable, skewness and kurtosis of distributions by moment | [2] pp. 266-270 |
3 | Lost function, Risk Function, Least Square and Maximum Likelihood Estimation of a parameter | [2] pp. 244-249 [2] pp. 267-270 |
4 | Pearson Correlation, sperman’s rank correlation Significance tests of correlation coefficient, confidence interval of correlation | [1] pp. 38-40 [2] pp. 383-390 |
5 | Simple Linear Regression Model, Estimation of Model Coefficients, Sum of Squared Error | [1] pp. 170-183 [2] pp. 359-376 |
6 | prediction of dependent variable, significance test of regression coefficient, confidence interval of predicted y value, determination coefficient | [1] pp.183-187 |
7 | Midterm | |
8 | Trend Analysis, Extrapolation of y value for time series | [1] pp.183-187 |
9 | Multi regression model, variance-covariance matrix, significance test of regression coefficients, ANOVA test | [1] pp. 192-206 |
10 | Multicollinearity, Autocorrelation, Von Neumann test | [1] pp. 187-219 |
11 | Portfolio Management, Expected Return and Volatility of portfolio | [1] pp. 138-143 |
12 | Risky asset and risk free asset, meaning of beta coefficient, SHARPE ,TREYNOR and JENSE indexs | [1] pp. 143-147 |
13 | CAPM approach, Market Line, Alfa value of any investment | [1] pp. 225-242 |
14 | Forecasting by Moving average method and ARMA model | [1] pp. 101-110 |
15 | Review | |
16 | Final |
Sources
Course Book | 1. Statistics and Finance, An introduction, David Ruppert, Springer Texts in statistics. |
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2. Mathematical Statistics, John E. Freund, Prentice/ Hall İnternational editions, Second edition | |
Other Sources | 3. Methods and Applications of Statistics in Business, Finance and Management Science, N. Balakrishnan, Editor, Wiley Publication |
Evaluation System
Requirements | Number | Percentage of Grade |
---|---|---|
Attendance/Participation | - | - |
Laboratory | - | - |
Application | - | - |
Field Work | - | - |
Special Course Internship | - | - |
Quizzes/Studio Critics | - | - |
Homework Assignments | 2 | 10 |
Presentation | - | - |
Project | - | - |
Report | - | - |
Seminar | - | - |
Midterms Exams/Midterms Jury | 2 | 50 |
Final Exam/Final Jury | 1 | 40 |
Toplam | 5 | 100 |
Percentage of Semester Work | 60 |
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Percentage of Final Work | 40 |
Total | 100 |
Course Category
Core Courses | X |
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Major Area Courses | |
Supportive Courses | |
Media and Managment Skills Courses | |
Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
# | Program Qualifications / Competencies | Level of Contribution | ||||
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1 | 2 | 3 | 4 | 5 | ||
1 | Acquiring the skills of understanding, explaining, and using the fundamental concepts and methods of economics | |||||
2 | Acquiring the skills of macro level economic analysis | |||||
3 | Acquiring the skills of micro level economic analysis | |||||
4 | Understanding the formulation and implementation of economic policies at the local, national, regional, and/or global level | |||||
5 | Learning different approaches on economic and related issues | |||||
6 | Acquiring the quantitative and/or qualitative techniques in economic analysis | X | ||||
7 | Improving the ability to use the modern software, hardware and/or technological devices | |||||
8 | Developing intra-disciplinary and inter-disciplinary team work skills | X | ||||
9 | Acquiring an open-minded behavior through encouraging critical analysis, discussions, and/or life-long learning | |||||
10 | Adopting work ethic and social responsibility | |||||
11 | Developing the skills of communication. | |||||
12 | Improving the ability to effectively implement the knowledge and skills in at least one of the following areas: economic policy, public policy, international economic relations, industrial relations, monetary and financial affairs. | X |
ECTS/Workload Table
Activities | Number | Duration (Hours) | Total Workload |
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Course Hours (Including Exam Week: 16 x Total Hours) | |||
Laboratory | |||
Application | |||
Special Course Internship | |||
Field Work | |||
Study Hours Out of Class | 16 | 3 | 48 |
Presentation/Seminar Prepration | |||
Project | |||
Report | |||
Homework Assignments | |||
Quizzes/Studio Critics | |||
Prepration of Midterm Exams/Midterm Jury | 2 | 20 | 40 |
Prepration of Final Exams/Final Jury | 1 | 40 | 40 |
Total Workload | 128 |