Recommended prerequisite for participation in
The module builds on knowledge and skills obtained in the module
Stochastic Analysis. Experience with programming in R is expected.
Previous knowledge of models in financial mathematics is helpful
but not necessary.
Content, progress and pedagogy of the
Students who have completed the module will gain knowledge of
the theoretical background for stochastic integration as well as
its application to finance.
- Know about stochastic integration with respect to continuous
- Know about the quadratic variation of stochastic integrals
- Know about Itô’s formula
- Know about change of measures via Girsanov’s Theorem with
special emphasis on its use in arbitrage theory
- Know about Stochastic Differential Equations (SDE’s) and its
relevance in the modelling of asset prices
- Know how to solve SDE’s numerically
- Are able to apply basic computation rules and calculi
associated to stochastic integrals
- Are able to apply Itô’s formula
- Are able to conduct a change of measure via Girsanov’s
- Can apply basic methods of stochastic calculus to the modelling
of financial markets
- Are able to solve SDE’s theoretically and numerically
- Are able to read, understand, criticize and make use of
advanced literature on stochastic calculus
- Are able to connect, formulate, and analyze scientific problems
with the basic theory of stochastic integration
Type of instruction
As described in §17 in the curriculum.
Extent and expected workload
This is a 5 ECTS project module and the work load is
expected to be 150 hours for the student.
|Name of exam||Stochastic Calculus and Its Applications|
|Type of exam|
Written or oral exam
|Type of grading||Internal examination|
|Criteria of assessment||The criteria of assessment are stated in the Examination
Policies and Procedures|