[ 404STCCSDEV23 ] VL Stochastic Differential Equations

Workload Education level Study areas Responsible person Hours per week Coordinating university
4,5 ECTS M1 - Master's programme 1. year Mathematics Evelyn Buckwar 3 hpw Johannes Kepler University Linz
Detailed information
Original study plan Master's programme Computational Mathematics 2023W
Objectives Motivation, theory and application of stochastic differential equations.
Subject Basics of stochastic analysis, stochastic differential equations (SDE) in concrete applications, basic solution techniques for SDEs, existence- and uniqueness-theorem for SDEs.
Criteria for evaluation Written exam
Methods Blackboard presentation
Language English
Study material
  • Bernt Oksendal, Stochastic Differential Equations, Springer Verlag
  • Tomas Björk, Arbitrage Theory in Continuous Time, Cambridge University Press
Changing subject? No
Further information Knowledge from probability theory and the theory of stochastic processes is necessary.
Corresponding lecture 402STMESDEV22: VL Stochastic Differential Equations (3 ECTS) + 201MASEPTMS22: SE Probability theory and mathematical statistics (1.5 ECTS)
Is completed if 402STMESDEV22: VO Stochastic Differential Equations (3 ECTS) + 403PTMSSDEV22: VL Stochastic Differential Equations 2 (3 ECTS)
On-site course
Maximum number of participants -
Assignment procedure Direct assignment