MAT9770 – Stochastic Modelling in Energy and Commodity Markets

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Course content

The course gives an introduction to dynamic stochastic models for prices in commodity and energy markets. Classical factor models based on Ornstein-Uhlenbeck processes are analyzed, and extended to so-called continuous-time autoregressive processes with a moving average. The stochastic processes are driven by Brownian motion and simple jump processes to model sudden price changes (spikes), which are characteristic for some energy markets (for example, power). In the course we also look at dynamic modelling of temperature, wind and sun, and analyze these in the context of energy markets, but also the independent markets for weather products. Particular case here is the seasonal variations. Further pricing techniques for forward contracts on commodity and energy are developed, in addition to relevant derivatives as "spread" and quanto options. The theory on pricing measures and risk premium is presented, and the term structure of volatility analyzed (the so-called Samuelson effect).

The topic will focus on making the models and analysis operational in practical applications. Techniques for estimation and calibration are presented, in addition to methods for numerical simulation.

    Learning outcome

    After completing the course you will:

    • know and understand the classical stochastic models for commodity and energy markets;
    • know how to establish forward prices based on factor models in the spot market;
    • know how to estimate and simulate the models, and apply these in different markets, like the market for weather derivatives;
    • understand important notions as pricing measure, market price of risk and the risk premium;
    • know how to analyze and price important derivatives in commodity and energy markets;
    • be able to present, on a scientific level, a short thesis on a chosen topic of relevance, selected in collaboration with the lecturer.

    Admission to the course

    PhD candidates from the University of Oslo should apply for classes and register for examinations through Studentweb.

    If a course has limited intake capacity, priority will be given to PhD candidates who follow an individual education plan where this particular course is included. Some national researchers’ schools may have specific rules for ranking applicants for courses with limited intake capacity.

    PhD candidates who have been admitted to another higher education institution must apply for a position as a visiting student within a given deadline.

    Overlapping courses

    Teaching

    4 hours of lectures/exercises every week throughout the semester.

    The course may be taught in Norwegian if the lecturer and all students at the first lecture agree to it.

    Examination

    1 mandatory assignment.

    Final oral or written examination. The form of examination will be announced by the teaching staff by 15 October/15 March for the autumn semester and the spring semester respectively.

    In addition, each PhD candidate is expected to give a one hour oral presentation on a topic of relevance chosen in cooperation with the lecturer. The presentation has to be approved by the lecturer for the student to be admitted to the final exam.

    Examination support material

    No examination support material is allowed.

    Language of examination

    Subjects taught in English will only offer the exam paper in English. You may write your examination paper in Norwegian, Swedish, Danish or English.

    Grading scale

    Grades are awarded on a pass/fail scale. Read more about the grading system.

    Resit an examination

    This course offers both postponed and resit of examination. Read more:

    Special examination arrangements, use of sources, explanations and appeals

    See more about examinations at UiO

    Last updated from FS (Common Student System) Jan. 24, 2020 6:21:07 AM

    Facts about this course

    Credits
    10
    Level
    PhD
    Teaching
    Spring
    Examination
    Spring
    Teaching language
    English