| Detailinformationen |
| Quellcurriculum |
Masterstudium Computational Mathematics 2023W |
| Ziele |
(*)Motivation, theory and application of stochastic differential equations.
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| Lehrinhalte |
(*)Basics of stochastic analysis, stochastic differential equations (SDE) in concrete applications, basic solution techniques for SDEs, existence- and uniqueness-theorem for SDEs.
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| Beurteilungskriterien |
(*)Written exam
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| Lehrmethoden |
(*)Blackboard presentation
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| Abhaltungssprache |
Englisch |
| Literatur |
(*)- Bernt Oksendal, Stochastic Differential Equations, Springer Verlag
- Tomas Björk, Arbitrage Theory in Continuous Time, Cambridge University Press
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| Lehrinhalte wechselnd? |
Nein |
| Sonstige Informationen |
(*)Knowledge from probability theory and the theory of stochastic processes is necessary.
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| Äquivalenzen |
(*)402STMESDEV22: VL Stochastic Differential Equations (3 ECTS) + 201MASEPTMS22: SE Probability theory and mathematical statistics (1.5 ECTS)
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| Gilt als absolviert, wenn |
(*)402STMESDEV22: VO Stochastic Differential Equations (3 ECTS) + 403PTMSSDEV22: VL Stochastic Differential Equations 2 (3 ECTS)
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