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

2021W, VO, 3.0h, 5.0EC
TUWEL

Properties

  • Semester hours: 3.0
  • Credits: 5.0
  • Type: VO Lecture
  • Format: Distance Learning

Learning outcomes

After successful completion of the course, students are able to...eExplain and use the definition and properties of multidimensional normal distribution and related distributions,

  • to list the definition and elementary properties of Brownian motion and to sketch the proof of its existence and Hölder continuity by means of the of Kolmogorov-Chentsov continuity criterion,
  • put filtrations, stopping times, progressive measurability and path properties of processes in relation to each other,
  • explain martingales, sub- and supermartingales, uniform integrability and Vitali's convergence theorem,
  • to apply Doob's classical results (maximum inequalities, L^p inequality, optional stopping theorem) and sketch their proofs,
  • to discuss local martingales and to give examples for strict local martingales
  • to integrate predictable step processes, introduce the quadratic variation and the covariation process for continuous local martingales and calculate these processes for some examples,
  • derive the existence of the stochastic integral for continuous local martingales by means of the Kunita-Watanabe inequality and explain the generalization to continuous semimartingales.

Subject of course

Definition and properties of multi-dimensional normal distribution, definition and elementary properties of Brownian motion, existence and Hölder continuity of Brownian motion using the Kolmogorov-Chentsov continuity criterion, filtrations, stopping times, progressive measurability, path properties, martingales, uniform integrability, Vitali's convergence theorem, sub- and supermartingales, maximum inequality, Doob's inequality for p-integrable submartingales, Doob's optional sampling theorem with applications, local martingales and examples, integration of predictable step processes, p-variation of functions, quadratic variation and covariation process of continuous local martingales, Kunita-Watanabe inequality, stochastic integration for continuous local martingales and generalization for continuous semimartingales

Teaching methods

Presentation and derivation of the results by the lecturer on the blackboard, self-study of the lecture notes. Active participation in the accompanying exercises is strongly recommended; numerous exercises are included in the lecture notes.

Mode of examination

Oral

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Mon14:00 - 16:0004.10.2021 - 24.01.2022 Zoom / siehe TUWEL (LIVE).
Tue08:30 - 10:0005.10.2021 - 25.01.2022 Zoom / siehe TUWEL (LIVE).
Stochastic analysis in financial and actuarial mathematics 1 - Single appointments
DayDateTimeLocationDescription
Mon04.10.202114:00 - 16:00 Zoom / siehe TUWEL.
Tue05.10.202108:30 - 10:00 Zoom / siehe TUWEL.
Mon11.10.202114:00 - 16:00 Zoom / siehe TUWEL.
Tue12.10.202108:30 - 10:00 Zoom / siehe TUWEL.
Mon18.10.202114:00 - 16:00 Zoom / siehe TUWEL.
Tue19.10.202108:30 - 10:00 Zoom / siehe TUWEL.
Mon25.10.202114:00 - 16:00 Zoom / siehe TUWEL.
Mon08.11.202114:00 - 16:00 Zoom / siehe TUWEL.
Tue09.11.202108:30 - 10:00 Zoom / siehe TUWEL.
Tue16.11.202108:30 - 10:00 Zoom / siehe TUWEL.
Mon22.11.202114:00 - 16:00 Zoom / siehe TUWEL.
Tue23.11.202108:30 - 10:00 Zoom / siehe TUWEL.
Mon29.11.202114:00 - 16:00 Zoom / siehe TUWEL.
Tue30.11.202108:30 - 10:00 Zoom / siehe TUWEL.
Mon06.12.202114:00 - 16:00 Zoom / siehe TUWEL.
Tue07.12.202108:30 - 10:00 Zoom / siehe TUWEL.
Mon13.12.202114:00 - 16:00 Zoom / siehe TUWEL.
Tue14.12.202108:30 - 10:00 Zoom / siehe TUWEL.
Mon10.01.202214:00 - 16:00 Zoom / siehe TUWEL.
Tue11.01.202208:30 - 10:00 Zoom / siehe TUWEL.

Examination modalities

Oral examination

Course registration

Begin End Deregistration end
02.09.2021 00:00 01.07.2022 23:59 01.07.2022 23:59

Curricula

Literature

Registered students have access to an English script in electronic format with numerous references. The script will be updated on a continuing basis. It contains study assignments. 

Additional literature:
Olav Kallenberg: Foundations of Modern Probability. 3. Edition, Springer-Verlag, 2021, ISBN 978-3-030-61871-1.
Daniel Revuz and Marc Yor: Continuous Martingales and Brownian Motion, 3. Edition, Springer-Verlag, 1999, ISBN 3-540-64325-7.
Ioannis Karatzas und Steven E. Shreve: Brownian Motion and Stochastic Calculus. 2. Edition, Springer-Verlag, ISBN 0-38797-655-8.
Bernt Øksendal: Stochastic Differential Equations: An Introduction with Applications. 6. Edition, Springer-Verlag, 2007, ISBN 978-3-54004-758-2.

Foundations:
David Williams: Probability with Martingales. Cambridge University Press, 1991, ISBN 0-521-40605-6.
Heinz Bauer: Maß- und Integrationstheorie. 2. Edition, De Gruyter, 1992, ISBN 3-11013-626-0.
Heinz Bauer: Wahrscheinlichkeitstheorie. 5. Edition, De Gruyter, 2002, ISBN 3-11017-236-4.

Preceding courses

Accompanying courses

Continuative courses

Language

if required in English