The purpose of the course is to introduce students to the study of stochastic processes in discrete and continuous time. Students will have learned the essentials of the subject and should be able to apply the acquired theoretical tools to problems in econometrics, economics, finance, and other fields.

Deterministic dynamic systems are usually not well suited for modelling real world dynamics in economics, finance and business. Allowing for random components in dynamic systems leads to stochastic dynamic modelling, which is based on stochastic processes. This course covers models of stochastic processes in discrete and continuous time. This includes Markov chains, Poisson processes and Brownian motion. We introduce various tools that are very useful for deriving and understanding the asymptotic properties of modern econometric techniques. They include the functional central limit theorem and stochastic integrals. Finally, we discuss stochastic differential equations and their applications in finance and related fields, e.g. for pricing financial derivatives.

Mikosch, T., (1998), Elementary stochastic calculus, World scientific Publishing, Singapore.
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This course is in transition for the master Business Research.
See the Master Education and Examination Regulations for more information.

The following rule applies to master Business Research students who started the programme prior to academic year 2024-2025.
TRANSITIONAL REGULATION (EBC4004):
The master Business Research has been discontinued.
Courses of the Business Research master’s programme will continue to be offered until and including academic year 2025-2026 with exam opportunities running until and including 2026-2027.


PREREQUISITES:
* Only Master students can take Econometrics Master courses.
* Students require a solid background in mathematical statistics and probability theory on the level of the BSc Econometrics programme.
* An advanced level of English.