probability and stochastic processes
Lectures
(18-9-2018) General introduction, probability spaces, examples, continuity of the probability, first Borel Cantelli lemma.
(19-9-2018) Random variables, sigma algebras generated by families of events and random variables, distributions, simple random variables.
(25-9-2018) Abstract integration on measurable spaces(short hints), expected values, integrable random variables, change of variables formula for integration
examples
(26-9-2018) Independence of sigma algebras, second Borel Cantelli lemma, example and exercises
(2-10-2018) Conditional expectations with respect to an event, conditional expectations with respect to a discrete random variable.
(3-10-2018)General definition of conditinal expectation with respect to a sigma algebra, existence (only statement), uniqueness, examples
(9-10-2018) Proofs of the properties of conditional expectations, conditional Jensen inequality, conditional expected value as a projection, filtrations, general definition of martingales, submartingales, supermartingales
(10-10-2018) Examples of martingales, Doob martingales, gambling strategies, martingale transform and preservation of the martingale property, stopping times.
(16-10-2018) Stopped processes and the process observed at the stopping time, stopped martingales are martingales, The martingale
(17-10-2018) The optional stopping Theorem, application to the exit from an interval of a random walk, the symmetric and the asymmetric case, Markov chains and conditional expectations
(23-10-2018) Remarkable example: mean time of hitting of a given pattern, Branching processes, Polya urn.
(24-10-2018) Maximal Doob inequality, example and exercises
textbooks
Main textbook: Zdzislaw Brzezniak, Tomasz Zastawniak: Basic stochastic processes (a course through exercises)
Suggested book for insights: D. Williams: Probability with martingales,
Useful material can be found in the lecture notes by Peter Morters
Past exams
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News
Partial examination on Tuesday 6 of November at 14.30 room A.1.3