Derivatives have a very long history, the first derivatives contracts dating back to ancient times. Today, trillions of dollars' worth of financial derivatives contracts are traded worldwide. The development of a pricing formula for options (the Black Scholes formula) was the start of a revolution in finance. The result of this revolution has been a proliferation of marketplaces for trading derivative securities, such as futures and options, and continued expansion in the risks that can be hedged using derivatives. This course is an advanced course in derivatives and covers topics such as option pricing, risk management and empirical studies (research) of derivatives. The course introduces students to empirical methodology, and involves extensive use of R.
Course description for study year 2023-2024. Please note that changes may occur.
This course covers the pricing and use of financial derivatives in the energy and commodities sector. Derivatives are financial contracts on other assets (i.e. what we call the "underlying asset") such as the price of a stock, the price of Brent crude oil or the price of natural gas. The values of derivatives are driven by the behavior of its underlying asset. An option to buy a shipment of crude oil in the future is highly affected by the volatility of the price of oil. The price behaviour of the underlying energy and commodity prices will also be examined.
The course will provide the theoretical foundation for pricing derivatives and how it differs from standard financial valuation models. Various pricing models will be covered, and we will also cover how derivatives can be used as risk management tools. Empirical studies of derivatives and commodity price behaviour will also be an important part of the course.
After successful completion of the course the student will:
have basic theoretical knowledge of option pricing theory and models
have the ability to apply a variety of option pricing models such as binomial trees, and analytical solutions such as the Black-Scholes model and Monte Carlo simulation
understand the role of risk management tools for hedging market risk exposure, e.g., know how to hedge the price of crude oil
be able to price financial options and other derivatives such as forward and futures contracts
be able to identify and price structured products with embedded options
be able to apply numerical methods such as Monte Carlo simulation to price derivatives
be able to carry out empirical (econometric) analyses of derivative prices, e.g., volatility, risk premium, volatility spillovers, etc.
Required prerequisite knowledge
Students taking this course will benefit from having a basic understanding of:
- Finance theory
Form of assessment
Mandatory attendance 80%, Research proposal
80% attendance at lectures/seminars/workshops is mandatory. To be allowed to take the exam, students must pass a mandatory attendance requirement.
Sttudents need to hand in and receive approval for research proposals for their research project within certain deadlines. The deadlines will be announced at the beginning of the course.
The course is delivered as a combination of lectures/seminars and extensive coursework (research projects). Students will work in groups and deliver a series of research reports throughout the semester. All reports need a passing grade.
The course will be delivered in English. The expected workload for the students is 300 hours:
50 hours lectures/seminars/workshops/meetings
250 hours self-study and groupwork
Derivatives and Risk Management in Energy and Commodity Markets (MØA210_3)
There must be an early dialogue between the course coordinator, the student representative and the students. The purpose is feedback from the students for changes and adjustments in the course for the current semester.In addition, a digital course evaluation must be carried out at least every three years. Its purpose is to gather the students experiences with the course.