105.091 Stochastic analysis in financial and actuarial mathematics 2
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2024S, VO, 2.0h, 4.0EC


  • Semester hours: 2.0
  • Credits: 4.0
  • Type: VO Lecture
  • Format: Presence

Learning outcomes

After successful completion of the course, students are able to ...

  • introduce the stochastic exponential and the stochastic logarithm, explain basic properties and characterisations, 
  • use Lévy's characterization of Brownian motion, 
  • formulate Girsanov's theorem and apply it to adjust the drift of Brownian motion by a measure change, 
  • explain Doob's upcrossing inequality and derive Doob's convergence theorems for submartingales,
  • explain and apply the predictable integral representation theorem for Brownian local martingales, 
  • check and derive conclusions from Kazamaki's and Novikov's criterion,
  • explain the different notions of a solution of a stochastic differential equation (SDE) and illustrate the basic effects by examples,
  • derive the solution in the linear case and discuss its uniqueness,
  • define the Ornstein–Uhlenbeck process and derive its basic properties,
  • apply the extended Grönwall inequality and illustrate the necessity of some of its assumptions by corresponding counterexamples,
  • investigate SDEs for existence and uniqueness under Lipschitz and boundedness conditions, and estimate the moments of the solution,
  • describe and apply the ideas and methods used to prove tha main theorems of the course.

Subject of course

Stochastic exponential of continuous semimartingales, stochastic logarithm, Lévy's characterization of standard Brownian motion, Girsanov's theorem, change of drift using Girsanov's theorem, Doob's upcrossing inequality, Doob's convergence theorems for submartingales, representation of Brownian local martingales, Kazamaki's and Novikov's criterion, stochastic differential equations (examples, terminology, solution in the linear case), Ornstein–Uhlenbeck process, extended Grönwall inequality, existence and uniqueness of strong solutions under Lipschitz and boundedness conditions, moment estimates.

Teaching methods

The basic contents and concepts are presented by the head of the LVA and illustrated and discussed with the help of examples.

Mode of examination




Course dates

Thu09:00 - 11:0007.03.2024 - 27.06.2024Sem.R. DA grün 06A .
Stochastic analysis in financial and actuarial mathematics 2 - Single appointments
Thu07.03.202409:00 - 11:00Sem.R. DA grün 06A .
Thu14.03.202409:00 - 11:00Sem.R. DA grün 06A .
Thu21.03.202409:00 - 11:00Sem.R. DA grün 06A .
Thu11.04.202409:00 - 11:00Sem.R. DA grün 06A .
Thu18.04.202409:00 - 11:00Sem.R. DA grün 06A .
Thu25.04.202409:00 - 11:00Sem.R. DA grün 06A .
Thu02.05.202409:00 - 11:00Sem.R. DA grün 06A .
Thu16.05.202409:00 - 11:00Sem.R. DA grün 06A .
Thu23.05.202409:00 - 11:00Sem.R. DA grün 06A .
Thu06.06.202409:00 - 11:00Sem.R. DA grün 06A .
Thu13.06.202409:00 - 11:00Sem.R. DA grün 06A .
Thu20.06.202409:00 - 11:00Sem.R. DA grün 06A .
Thu27.06.202409:00 - 11:00Sem.R. DA grün 06A .

Examination modalities

The performance is assessed by an oral examination at the end of the semester.

Course registration

Begin End Deregistration end
06.01.2024 00:00 31.03.2024 23:59 31.03.2024 23:59



Preceding courses

Accompanying courses

Continuative courses


if required in English