THE UNIVERSITY of EDINBURGH

DEGREE REGULATIONS & PROGRAMMES OF STUDY 2013/2014 -
- ARCHIVE as at 1 September 2013 for reference only
THIS PAGE IS OUT OF DATE

University Homepage
DRPS Homepage
DRPS Search
DRPS Contact
DRPS : Course Catalogue : School of Mathematics : Mathematics

Postgraduate Course: Optimization Methods in Finance (MATH11110)

Course Outline
SchoolSchool of Mathematics CollegeCollege of Science and Engineering
Course typeStandard AvailabilityNot available to visiting students
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) Credits15
Home subject areaMathematics Other subject areaNone
Course website None Taught in Gaelic?No
Course description1. 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,
4. Stochastic Optimization: Asset/liability management and scenario generation,
5. Convex Optimization: Value-at-Risk, Conditional Value-at-Risk,
6. Robust Optimization: Robust portfolio selection
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Students MUST NOT also be taking Deterministic Optimization Methods in Finance (MATH11092)
Other requirements None
Additional Costs None
Course Delivery Information
Delivery period: 2013/14 Semester 2, Not available to visiting students (SS1) Learn enabled:  Yes Quota:  None
Web Timetable Web Timetable
Course Start Date 17/01/2014
Breakdown of Learning and Teaching activities (Further Info) Total Hours: 150 ( Lecture Hours 20, Seminar/Tutorial Hours 5, Supervised Practical/Workshop/Studio Hours 20, Summative Assessment Hours 2, Programme Level Learning and Teaching Hours 3, Directed Learning and Independent Learning Hours 100 )
Additional Notes
Breakdown of Assessment Methods (Further Info) Written Exam 50 %, Coursework 50 %, Practical Exam 0 %
Exam Information
Exam Diet Paper Name Hours:Minutes
Main Exam Diet S2 (April/May)MSc Optimization Methods in Finance2:00
Summary of Intended Learning Outcomes
Ability to formulate and solve practical problems arising in finance using modern optimization methods and software (CVX,MATLAB). Familiarity with deterministic and stochastic formulations, their purpose, strengths and weaknesses.
Assessment Information
See 'Breakdown of Assessment Methods' and 'Additional Notes', above.
Special Arrangements
None
Additional Information
Academic description Not entered
Syllabus Not entered
Transferable skills Not entered
Reading list Not entered
Study Abroad Not entered
Study Pattern Not entered
KeywordsOMF
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
Navigation
Help & Information
Home
Introduction
Glossary
Search DPTs and Courses
Regulations
Regulations
Degree Programmes
Introduction
Browse DPTs
Courses
Introduction
Humanities and Social Science
Science and Engineering
Medicine and Veterinary Medicine
Other Information
Combined Course Timetable
Prospectuses
Important Information
 
© Copyright 2013 The University of Edinburgh - 10 October 2013 4:53 am