TU-E2211 - Financial Risk Management with Derivatives 1 D, Lecture, 4.9.2024-11.12.2024
Topic outline
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Autumn semester 2024: this course is called TU-E2211 Financial Risk Management with Derivatives 1. Previous name: TU-E2210 Financial Engineering I. Welcome!
The lectures are given both in person and by zoom.
How would you hedge a business where natural gas is bought at a floating price and sold at a fixed price with long contracts?
Your company buys components in dollars and sells cars in pounds.
What is the currency risk? How would you model the exchange rate as a stochastic process?
Which interest rate should you choose for your mortgage, 3-month Euribor, 6-month Euribor or 12-month Euribor?
This course will start on Wednesday, September 4, 2024 at 12.15 in lecture hall Skłodowska-Curie, Kide, and via zoom. Welcome!
Financial Risk Management is a multidisciplinary field involving financial theory, engineering methods, applied mathematics and the practice of programming.
This course is designed for students who wish to obtain positions in banking, financial risk management and consulting industries, or to work as quantitative analysts in finance departments of general manufacturing and service firms. Students who simply want to practice their skills in mathematics and finance are also most welcome.
The aim of the course Financial Risk Management with Derivatives I is to acquire an understanding in financial risk management. The objective is to get a mathematical intuition behind financial derivatives, as well as a working knowledge in option pricing, hedging, and volatility estimation. An optional assignment will be carried out using R, Python, or Julia and real market data.
You can choose the 3, 5 or 6 credit version of the course. For more information, see Passing the course.
The course can be included in the Minor in Computational Finance and Risk Management, 20-25 cr.
Main teacher: Ruth Kaila
Teacher: Eljas Toepfer
You can continue Financial Risk Management studies with
- Financial Risk Management with Derivatives II, periods 3-4
- Machine Learning in Financial Risk Management, periods 3-4