105.114 AKFVM Stochastic Integration
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2008S, VU, 3.0h, 4.5EC

Properties

  • Semester hours: 3.0
  • Credits: 4.5
  • Type: VU Lecture and Exercise

Aim of course

Introduction to the theory of stochastic integration with respect to general semimartingales

Subject of course

  1. Preliminaries: basic notation, martingales, Poisson process, Brownian motion, Lévy processes, local martingales
  2. Semimartingales and stochastic integrals: semimartingales (stability properties, examples), stochastic integral and properties, quadratic variation of a semimartingale, Itô's formula

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Tue12:30 - 15:3004.03.2008 - 24.06.2008Sem.R. DA grün 06A SCHMOCK
AKFVM Stochastic Integration - Single appointments
DayDateTimeLocationDescription
Tue04.03.200812:30 - 15:30Sem.R. DA grün 06A SCHMOCK
Tue11.03.200812:30 - 15:30Sem.R. DA grün 06A SCHMOCK
Tue18.03.200812:30 - 15:30Sem.R. DA grün 06A SCHMOCK
Tue25.03.200812:30 - 15:30Sem.R. DA grün 06A SCHMOCK
Tue01.04.200812:30 - 15:30Sem.R. DA grün 06A SCHMOCK
Tue08.04.200812:30 - 15:30Sem.R. DA grün 06A SCHMOCK
Tue15.04.200812:30 - 15:30Sem.R. DA grün 06A SCHMOCK
Tue22.04.200812:30 - 15:30Sem.R. DA grün 06A SCHMOCK
Tue29.04.200812:30 - 15:30Sem.R. DA grün 06A SCHMOCK
Tue06.05.200812:30 - 15:30Sem.R. DA grün 06A SCHMOCK
Tue13.05.200812:30 - 15:30Sem.R. DA grün 06A SCHMOCK
Tue20.05.200812:30 - 15:30Sem.R. DA grün 06A SCHMOCK
Tue27.05.200812:30 - 15:30Sem.R. DA grün 06A SCHMOCK
Tue03.06.200812:30 - 15:30Sem.R. DA grün 06A SCHMOCK
Tue10.06.200812:30 - 15:30Sem.R. DA grün 06A SCHMOCK
Tue17.06.200812:30 - 15:30Sem.R. DA grün 06A SCHMOCK
Tue24.06.200812:30 - 15:30Sem.R. DA grün 06A SCHMOCK

Examination modalities

Aktive participation in the exercises, oral examination.

Course registration

Not necessary

Curricula

Literature

  1. Philip E. Protter: Stochastic Integration and Differential Equations, Second Edition, Version 2.1, Springer-Verlag, 2005, ISBN 3-540-00313-4 (Chapter 1–3).
  2. Stewart N. Ethier and Thomas Kurtz: Markov Processes, Characterization and Convergence, Wiley, New York, 1986, ISBN 0-471-08186-8 (Chapter 2).

Previous knowledge

Good background in probability theory (Poisson process, Brownian motion, martingales, etc.)

Continuative courses

Language

English