Objectives and competences
Students acquire in-depth theoretical and practical knowledge necessary for the quantitative treatment of tasks and processes in the field of financial engineering. Students develop competencies for independent research in the area of financial engineering methods, critical thinking, and the interpretation of empirical results.
Content (Syllabus outline)
1.Mathematical tools
2.Financial derivatives
3.Options, futures, forwards
4. Options valuation, hedging
4.1 Binomial model
4.2 Black-Scholes model
5.The Greeks
6. Swaps
7. Machine learning in financial engineering
7.1 Pricing of financial derivatives
7.2 Deep hedging
Learning and teaching methods
Lectures, technical demonstration,
active work, seminary work
Intended learning outcomes - knowledge and understanding
In the course Methods of financial engineering, students:
1. Systematically acquire and enhance theoretical and practical knowledge necessary for the quantitative treatment of tasks and processes in the field of financial engineering.
2. Develop the ability to apply theoretical knowledge of financial engineering methods in quantitative models and approaches. (PILO 2a)
3. Acquire the ability to compare and critically evaluate different methodological approaches in the field of financial engineering.
4. Know how to apply acquired theoretical knowledge to solve empirical tasks in the field of financial engineering. They develop competencies for independent research work in this area. (PILO 2c)
5. Appropriately present and interpret results obtained with the help of financial engineering methods. (PILO 3b)
6. Acquire the ability to search for and synthesize information from the field of financial engineering methods in contemporary literature and the ability to think critically. (PILO 3a)
7. Are able to trade with derivative financial instruments on an online platform for virtual trading. (PILO 2a, PILO 3a)
8. Develop skills for independent and group empirical work and enhance their ability for collaboration and communication. (PILO 3c)
The PILO label (i.e., Programme Intended Learning Outcomes) defines the contribution of each listed intended learning outcome of a course towards achieving the general and/or subject-specific competencies or learning outcomes acquired through the programme.
Intended learning outcomes - transferable/key skills and other attributes
In the course Methods of financial engineering, students:
1. Systematically acquire and enhance theoretical and practical knowledge necessary for the quantitative treatment of tasks and processes in the field of financial engineering.
2. Develop the ability to apply theoretical knowledge of financial engineering methods in quantitative models and approaches. (PILO 2a)
3. Acquire the ability to compare and critically evaluate different methodological approaches in the field of financial engineering.
4. Know how to apply acquired theoretical knowledge to solve empirical tasks in the field of financial engineering. They develop competencies for independent research work in this area. (PILO 2c)
5. Appropriately present and interpret results obtained with the help of financial engineering methods. (PILO 3b)
6. Acquire the ability to search for and synthesize information from the field of financial engineering methods in contemporary literature and the ability to think critically. (PILO 3a)
7. Are able to trade with derivative financial instruments on an online platform for virtual trading. (PILO 2a, PILO 3a)
8. Develop skills for independent and group empirical work and enhance their ability for collaboration and communication. (PILO 3c)
The PILO label (i.e., Programme Intended Learning Outcomes) defines the contribution of each listed intended learning outcome of a course towards achieving the general and/or subject-specific competencies or learning outcomes acquired through the programme.
Readings
Osnovna študijska literature (Compulsory textbooks):
1. Hull, J. (2014 ali kasnejša izdaja). Options, Futures and other Derivatives. New Jersey: Prentice Hall.
2. Kavkler, A. (2014). Gradivo za vaje pri predmetu Metode finančnega inženiringa. Maribor: EPF.
3. Burkov, A. (2019). The Hundred-Page Machine Learning Book. Publisher: Andriy Burkov.
4. Izbrani članki s področja uporabe umetne inteligence v finančnem inženiringu (selected papers on artificial intelligence use in financial engineering)
Dodatna študijska literature (Additonal textbooks):
5. Wilmott, P. (2006). Paul Wilmott on Quantitative Finance. New York: Wiley.
Cuthbertson, K. (2001 ali kasnejša izdaja). Financial engineering: derivatives and risk management. New York: Wiley.
Prerequisits
No requirements
Additional information on implementation and assessment Written exam or 2 midterm tests
Seminar work
Active participation at tutorials (individual and group work)
Written exam or 2 midterm tests - written exam or 2 midterm tests. The students pass the exam if they collect at least 28 points out of 50 possible either in the written exam or on both tests combined, and at the same time, together with the seminar work and active participation, they collect at least 56 points (out of a total of 100 points).
Seminar work - the student writes a seminar paper on a selected topic and presents it.
Active participation at tutorials (individual and group work) - problems from each chapter
