Lehrinhalte
Levy processes: infinitely divisible distributions, Levy-Khinchine representation, Poisson random measures, Levy-Ito decomposition, stable Levy processes, subordinators
- random walks: relations to Levy processes, fluctuation theory
- Markov chains in discrete time, elementary theory of Markov chains in continuous time, renewal processes
- applications to queueing theory and risk theory
Literatur
Klenke: Wahrscheinlichkeitstheorie
Sato: Levy processes and infinitely divisible distributions
Bertoin: Levy processes
Protter: Stochastic integration and differential equations
Voraussetzungen
recommended: Stochastic Processes I
Levy processes: infinitely divisible distributions, Levy-Khinchine representation, Poisson random measures, Levy-Ito decomposition, stable Levy processes, subordinators
- random walks: relations to Levy processes, fluctuation theory
- Markov chains in discrete time, elementary theory of Markov chains in continuous time, renewal processes
- applications to queueing theory and risk theory
Literatur
Klenke: Wahrscheinlichkeitstheorie
Sato: Levy processes and infinitely divisible distributions
Bertoin: Levy processes
Protter: Stochastic integration and differential equations
Voraussetzungen
recommended: Stochastic Processes I
- Lehrende: Anonym
- Lehrende: Tobias Schmidt
- Lehrende: Cornelia Wichelhaus
Semester: ST 2020