Postgraduate Course: Optimization Methods in Finance (MATH11110)

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	15	ECTS Credits	7.5
Summary	1. 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
Course description	Not entered

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

Course Delivery Information

Academic year 2015/16, Not available to visiting students (SS1)		Quota: None
Course Start	Semester 2
Timetable	Timetable
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 )
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 Optimization Methods in Finance		2:00

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.