The course is connected to the following study programs

Teaching language

Norwegian or English

Recommended prerequisites

Topology and Measure Theory, Stochastic Processes

Course contents

Continuous stochastic processes. Brownian motion. Martingales. Itô integral. Martingale representation theorem. Itô formula. Stochastic differential equations; strong and weak solutions and criteria’s for well-posedness. Girsanov’s theorem. The Markov property of diffusions. Representation formulas for a class of parabolic differential equations.

Learning outcomes

After successful completion of the course the student

  • have knowledge about the key concepts of stochastic analysis.

  • have an understanding for stochastic dynamics and models.

  • know numerical methods for solving stochastic differential equations.

  • know Monte-Carlo methods for numerical approximations for a class of parabolic differential equations.

Examination requirements

Approved compulsory hand-ins. See Canvas for more information.

Teaching methods

Lectures, group work, and compulsory hand-ins. Estimated workload of the course is 267 hours.

Evaluation

The person responsible for the course decides, in cooperation with student representative, the form of student evaluation and whether the course is to have a midway or end of course evaluation in accordance with the quality system for education, chapter 4.1.

Assessment methods and criteria

Individual oral exam. Graded assessment.

Last updated from FS (Common Student System) June 30, 2024 8:44:46 PM