Derivatives and Risk Management

FIE425 Derivatives and Risk Management

Spring 2024

  • Topics


    • Pricing by replication in the absence of arbitrage possibilities.
    • Binomial model of derivative pricing.
    • Black and Scholes model of derivative pricing.
    • Pricing of derivatives by Monte Carlo simulation.
    • Forward/futures.
    • Options.
    • Exotic options
    • American/European/Asian types of derivatives.
    • Hedging/replication/risk management
    • If time allows: Value at Risk, credit risk.

    The course covers financial derivative instruments such as forwards and options and shows how these may be priced by stylised models of financial markets such as the binomial or the Black/Scholes model. More advanced derivatives are priced numerically with simulation. As useful by-products of pricing, replicating strategies are derived, which are essential for risk management.

  • Learning outcome


    After completing this course the student knows the principles of pricing by (lack of) arbitrage. The student has knowledge about basic derivative instruments, as well as how such instruments are priced. by arbitrage free pricing. Furthermore, the student knows basic use such instruments in risk management.


    • The student knows how to replicate any derivative instrument's cashflow either by other derivatives or by so-called underlying assets.
    • The student can apply specific models based on no-arbitrage pricing theory to value new kinds of derivative instruments.
    • The student can suggest proper use of derivatives for various hedging situations.

    General competence

    A student will be able to communicate knowledge, both written and orally to both academics and market specialists of derivatives and to assess risk connected to the use of basic derivatives.

  • Teaching

    Regular classes 2 x 45 minutes twice a week.

    Active student participation is strongly encouraged.

    Teaching language is English.

  • Compulsory Activity

    One approved problem set - to be solved in groups and presented in class.

  • Assessment

    Final exam, comprising a 3 hour individual written take home exam. The final exam must be written in English.

  • Grading Scale

    Grading scale A-F.

  • Computer tools

    Familiar with spreadsheets. Knowledge of programming languages (R, C++, etc) are not required for this class, but may be an advantage. Examples of computer code are used for instructional purposes.

  • Literature

    The literature list is currently under review and

    will be available when the course starts.

  • Permitted Support Material



ECTS Credits
Teaching language

Autumn. Offered Autumn 2023.

Course responsible

Professor Svein-Arne Persson, Department of Finance, NHH