| Course Name | Quantitative Methods in Finance |
| Code | Semester | Theory (hour/week) | Application/Lab (hour/week) | Local Credits | ECTS |
|---|---|---|---|---|---|
| ITF 304 | Fall/Spring | 3 | 0 | 3 | 6 |
| Prerequisites | None | |||||
| Course Language | English | |||||
| Course Type | Elective | |||||
| Course Level | First Cycle | |||||
| Mode of Delivery | - | |||||
| Teaching Methods and Techniques of the Course | Discussion Lecture / Presentation | |||||
| Course Coordinator | ||||||
| Course Lecturer(s) | ||||||
| Assistant(s) | ||||||
| Course Objectives | The aim of this lecture is to provide students with an understanding of the quantitative methods for finance and investment. This includes the ability to formulate problems into quantitative models, to aid the successful resolution of the problem. Using output from mathematical and statistical models, students will learn to analyze, interpret and derive potential outcomes from quantitative information. |
| Learning Outcomes | The students who succeeded in this course;
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| Course Description | This lecture guides the students through a wide array of mathematics, ranging from elementary basic mathematics, limit, derivative and integral, linear algebra and differential calculus to optimization and linear regression. These quantitative methods are illustrated with a rich and captivating assortment of applications to the analysis of portfolios, derivatives, exchange, fixed income securities and equities. |
| Related Sustainable Development Goals | |
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| Core Courses | |
| Major Area Courses | X | |
| Supportive Courses | ||
| Media and Managment Skills Courses | ||
| Transferable Skill Courses |
| Week | Subjects | Required Materials |
| 1 | Introduction and Overview: The Importance of Mathematics in Finance | |
| 2 | Financial Time Series and Their Features | Rachev, S., Mittnik, S., Fabozzi, F., Focardi, S. and Jasić, T., Financial Econometrics: From Basics to Advanced Modeling Techniques. John Wiley & Sons, 2007 |
| 3 | Basic Statistics | Rachev, S., Mittnik, S., Fabozzi, F., Focardi, S. and Jasić, T., Financial Econometrics: From Basics to Advanced Modeling Techniques. John Wiley & Sons, 2007 |
| 4 | Linear Relationship in Time Series analysis Classical Linear Regression Model (CLRM) | Rachev, S., Mittnik, S., Fabozzi, F., Focardi, S. and Jasić, T., Financial Econometrics: From Basics to Advanced Modeling Techniques. John Wiley & Sons, 2007 |
| 5 | Linear Time Series Analysis CLRM Assumptions | Rachev, S., Mittnik, S., Fabozzi, F., Focardi, S. and Jasić, T., Financial Econometrics: From Basics to Advanced Modeling Techniques. John Wiley & Sons, 2007 |
| 6 | Project | - |
| 7 | Univariate Time Series Modelling | Rachev, S., Mittnik, S., Fabozzi, F., Focardi, S. and Jasić, T., Financial Econometrics: From Basics to Advanced Modeling Techniques. John Wiley & Sons, 2007 |
| 8 | Univariate Time Series Modelling | Rachev, S., Mittnik, S., Fabozzi, F., Focardi, S. and Jasić, T., Financial Econometrics: From Basics to Advanced Modeling Techniques. John Wiley & Sons, 2007 |
| 9 | Project | |
| 10 | Multivariate Models | Rachev, S., Mittnik, S., Fabozzi, F., Focardi, S. and Jasić, T., Financial Econometrics: From Basics to Advanced Modeling Techniques. John Wiley & Sons, 2007 |
| 11 | Multivariate Models | Rachev, S., Mittnik, S., Fabozzi, F., Focardi, S. and Jasić, T., Financial Econometrics: From Basics to Advanced Modeling Techniques. John Wiley & Sons, 2007 |
| 12 | Modelling Long Run Relationships in Finance | Rachev, S., Mittnik, S., Fabozzi, F., Focardi, S. and Jasić, T., Financial Econometrics: From Basics to Advanced Modeling Techniques. John Wiley & Sons, 2007 |
| 13 | Modelling Long Run Relationships in Finance | Rachev, S., Mittnik, S., Fabozzi, F., Focardi, S. and Jasić, T., Financial Econometrics: From Basics to Advanced Modeling Techniques. John Wiley & Sons, 2007 |
| 14 | Modelling Volatility | Rachev, S., Mittnik, S., Fabozzi, F., Focardi, S. and Jasić, T., Financial Econometrics: From Basics to Advanced Modeling Techniques. John Wiley & Sons, 2007 |
| 15 | Modelling Volatility | Rachev, S., Mittnik, S., Fabozzi, F., Focardi, S. and Jasić, T., Financial Econometrics: From Basics to Advanced Modeling Techniques. John Wiley & Sons, 2007 |
| 16 | Final Exam |
| Course Notes/Textbooks | Rachev, S., Mittnik, S., Fabozzi, F., Focardi, S. and Jasić, T., Financial Econometrics: From Basics to Advanced Modeling Techniques. John Wiley & Sons, 2007, ISBN: 978-0-471-78450-0 |
| Suggested Readings/Materials | James H. Stock and Mark W. Watson, Introduction to Econometrics, Pearson Education, 2003, ISBN: 978-9352863501 Marek, Capiński, Mathematics for finance: an introduction to financial engineering, Springer, 2003, ISBN: 0857290819 Alpha C., Chiang, Fundamental methods of mathematical economics, Auckland : McGrawHill, 1983, 3rd edition. ISBN:9780070108134 Statistics and Business Economics by P. Newbold W. L. Carlson, B. Thorne, 8/e, Prentice Hall, ISBN:9780132745659 Zvi Bodie, Alex Kane, Alan J. Marcus, “Essentials of Investment”, 2010, ISBN:9781259354977 John L. Teall and Iftekhar Hasan, “Quantitative Methods for Finance and Investments, 2002, ISBN: 9780631223399 |
| Semester Activities | Number | Weighting |
| Participation | ||
| Laboratory / Application | ||
| Field Work | ||
| Quizzes / Studio Critiques | ||
| Portfolio | ||
| Homework / Assignments | ||
| Presentation / Jury | ||
| Project | 2 | 40 |
| Seminar / Workshop | ||
| Oral Exam | ||
| Midterm | ||
| Final Exam | 1 | 60 |
| Total |
| Weighting of Semester Activities on the Final Grade | 2 | 40 |
| Weighting of End-of-Semester Activities on the Final Grade | 1 | 60 |
| Total |
| Semester 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 | 14 | 3 | 42 |
| Field Work | |||
| Quizzes / Studio Critiques | |||
| Portfolio | |||
| Homework / Assignments | |||
| Presentation / Jury | |||
| Project | 2 | 20 | |
| Seminar / Workshop | |||
| Oral Exam | |||
| Midterms | |||
| Final Exams | 1 | 45 | |
| Total | 175 |
| # | Program Competencies/Outcomes | * Contribution Level | ||||
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | To be able to identify and analyze problems in the field of trade and finance, and to develop solutions. | X | ||||
| 2 | To be able to apply theoretical and practical knowledge of international trade and finance to real-world professional contexts. | |||||
| 3 | To be able to critically analyze global market developments and evaluate their implications for business and policy. | |||||
| 4 | To be able to collect, analyze, and interpret financial and economic data by using digital and information technologies effectively. | |||||
| 5 | To be able to understand and interpret legal frameworks, regulations and practices relevant to international trade and finance. | |||||
| 6 | To be able to anticipate, define, and manage financial and trade-related risks through informed decision-making. | |||||
| 7 | To be able to acquire and use verbal, written, and numerical skills effectively for the nature of international trade and finance program. | X | ||||
| 8 | To be able to obtain, synthesize, and report trade- and finance-related information clearly and effectively. | X | ||||
| 9 | To be able to contribute effectively as individuals, team members, and leaders in multidisciplinary environments. | |||||
| 10 | To be able to evaluate trade and finance issues from ethical, social, and sustainability perspectives. | |||||
| 11 | To be able to collect data in the areas of International Trade and Finance and communicate with colleagues in a foreign language ("European Language Portfolio Global Scale", Level B1). | |||||
| 12 | To be able to speak a second foreign at a medium level of fluency efficiently. | |||||
| 13 | To be able to relate the knowledge accumulated throughout human history to their field of expertise. | |||||
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest
