Course development and history
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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.
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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.
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.
Thomas Önskog (email@example.com)