Unit name | Martingale Theory with Applications 3 |
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Unit code | MATH36204 |
Credit points | 10 |
Level of study | H/6 |
Teaching block(s) |
Teaching Block 1A (weeks 1 - 6) |
Unit director | Dr. Balazs |
Open unit status | Not open |
Pre-requisites |
MATH20008 Probability 2 |
Co-requisites |
None |
School/department | School of Mathematics |
Faculty | Faculty of Science |
Unit Aims
To stimulate through theory and examples, an interest and appreciation of the power of this elegant method in probability theory. And to lay foundations for further studies in probability theory.
Unit Description
The theory of martingales is of fundamental importance to probability theory, statistics, and mathematical finance. This unit is a concise introduction of the basic concepts, results and examples of this powerful and elegant theory.
Relation to Other Units
Probability 2 has introduced Martingales, but only covers the most basic of results, mostly without rigorous proofs. This unit will prove most of the results in a rigorous measure-theoretic fashion, and will be essential for students who wish to go on to study postgraduate level probability theory. In particular, students will find the understanding of material in this unit very helpful in other related units, such as Financial Mathematics and Further Topics in Probability 3.
Learning Objectives
To gain an understanding of martingales, and to be able to formulate problems in probability/statistics theory in terms of martingales. Students will also gain more experience in writing proofs, thus laying the foundation for future studies in probability theory at a post-graduate level.
Transferable Skills
Formulation of probability/statistics problems in terms of martingales. Better ability in writing proofs.
Lectures and homework assignments. Bi-weekly assignments to be done by the student and handed in for marking.
80% Examination
20% Coursework
Raw scores on the examinations will be determined according to the marking scheme written on the examination paper. The marking scheme, indicating the maximum score per question, is a guide to the relative weighting of the questions. Raw scores are moderated as described in the Undergraduate Handbook.
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