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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2014/2015
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DRPS : Course Catalogue : School of Mathematics : Mathematics

Postgraduate Course: Deterministic Optimization Methods in Finance (MATH11092)

Course Outline
SchoolSchool of Mathematics CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityNot available to visiting students
SCQF Credits7.5 ECTS Credits3.75
Summary1. Linear Optimization: asset pricing and arbitrage, risk-neutral probability measure,
2. Quadratic Optimization: mean-variance portfolio selection (Markowitz model),
3. Conic Optimization: capital allocation line and Sharpe ratio.

This course is only available to students on the MSc Financial Mathematics programme.
Course description - Linear Optimization: asset pricing and arbitrage, risk-neutral probability measure
- Quadratic Optimization: mean-variance portfolio selection (Markowitz model)
- Conic Optimization: capital allocation line and Sharpe ratio
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Students MUST NOT also be taking Optimization Methods in Finance (MATH11110)
Other requirements None
Course Delivery Information
Academic year 2014/15, Not available to visiting students (SS1) Quota:  None
Course Start Semester 2
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 75 ( Lecture Hours 10, Supervised Practical/Workshop/Studio Hours 10, Summative Assessment Hours 1, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 52 )
Assessment (Further Info) Written Exam 50 %, Coursework 50 %, Practical Exam 0 %
Additional Information (Assessment) See 'Breakdown of Assessment Methods' and 'Additional Notes', above.
Feedback Not entered
Exam Information
Exam Diet Paper Name Hours & Minutes
Main Exam Diet S2 (April/May)MSc Deterministic Optimization Methods in Finance1:00
Learning Outcomes
Ability to formulate and solve practical problems arising in finance using modern optimization methods and software (CVX, MATLAB). Familiarity with deterministic formulations, their purpose, strengths and weaknesses.
Reading List
None
Additional Information
Graduate Attributes and Skills Not entered
KeywordsOMF1
Contacts
Course organiserDr Peter Richtarik
Tel: (0131 6)50 5049
Email: peter.richtarik@ed.ac.uk		 Course secretaryMrs Frances Reid
Tel: (0131 6)50 4883
Email: f.c.reid@ed.ac.uk
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