Postgraduate Course: Numerical Methods for Stochastic Differential Equations (MATH11156)
Course Outline
School | School of Mathematics |
College | College of Science and Engineering |
Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Not available to visiting students |
SCQF Credits | 5 |
ECTS Credits | 2.5 |
Summary | A rigorous course into the theory of numerical approximations for stochastic differential equations. |
Course description |
Preliminaries: Burkholder-Davis-Gundy inequality and Gronwall' s lemma. Strong and weak approximations of solutions to SDEs.
Euler's approximations and Milstein's scheme.
Order of accuracy of numerical approximations.
Higher order schemes, accelerated convergence.
Weak approximations of SDEs via numerical solutions of PDEs.
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Entry Requirements (not applicable to Visiting Students)
Pre-requisites |
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Co-requisites | |
Prohibited Combinations | Students MUST NOT also be taking
Simulation (MATH10015)
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Other requirements | Students must have taken Stochastic Analysis in Finance (MATH11154) |
Course Delivery Information
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Academic year 2015/16, Not available to visiting students (SS1)
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Quota: None |
Course Start |
Block 4 (Sem 2) |
Timetable |
Timetable |
Learning and Teaching activities (Further Info) |
Total Hours:
50
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Lecture Hours 11,
Supervised Practical/Workshop/Studio Hours 2,
Programme Level Learning and Teaching Hours 1,
Directed Learning and Independent Learning Hours
36 )
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Assessment (Further Info) |
Written Exam
100 %,
Coursework
0 %,
Practical Exam
0 %
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Additional Information (Assessment) |
Examination 100% |
Feedback |
Not entered |
No Exam Information |
Learning Outcomes
- Demonstrate familiarity with numerical schemes for simulating solutions of SDEs by answering relevant exam questions.
- Demonstrate conceptual understanding of the estimation of the rate of convergence of the Euler and Milstein schemes by answering relevant exam questions.
- Demonstrate conceptual understanding of the differences between weak and strong approximations by answering relevant exam questions.
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Reading List
Numerical Solution of Stochastic Differential Equations
by Peter E. Kloeden and Eckhard Platen, 1999, Springer. |
Additional Information
Graduate Attributes and Skills |
Not entered |
Keywords | NMSDE |
Contacts
Course organiser | Dr Sotirios Sabanis
Tel: (0131 6)50 5084
Email: |
Course secretary | Mrs Kathryn Mcphail
Tel: (0131 6)51 4351
Email: |
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© Copyright 2015 The University of Edinburgh - 27 July 2015 11:36 am
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