Course development and history
Select the semester and course offering above to get information from the correct course syllabus and course offering.
Conditional expectation, martingales and stochastic integrals in discrete time, stopping times, Girsanov Theorem.
Martingales in continuous time, Brownian motion, Ito integral and Ito Lemma.
Martingale representation Theorem, stochastic differential equations, Ito diffusions, Kolmogorov equations, Feynman-Kac formula, stopping times and optional stopping.
After passing the course, the students should be able to
formulate and explain central definitions and theorems within the theory of martingales and stochastic integrals;
solve basic problems within the theory of martingales and stochastic integrals, and apply its methods to stochastic processes.
No information inserted
SF2940 Probability theory.
Djehiche Boualem: Stochastic Calculus, An Introduction with Applications. Compendium from KTH.
A, B, C, D, E, FX, F
Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability. The examiner may apply another examination format when re-examining individual students.
Written examination (7,5 university credits)
Further information about the course can be found on the Course web at the link below. Information on the Course web will later be moved to this site.
Kevin Schnelli (email@example.com)