THE UNIVERSITY of EDINBURGH

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

Undergraduate Course: Simulation (MATH10015)

Course Outline
SchoolSchool of Mathematics CollegeCollege of Science and Engineering
Course typeStandard AvailabilityAvailable to all students
Credit level (Normal year taken)SCQF Level 10 (Year 4 Undergraduate) Credits10
Home subject areaMathematics Other subject areaSpecialist Mathematics & Statistics (Honours)
Course website https://info.maths.ed.ac.uk/teaching.html Taught in Gaelic?No
Course descriptionCourse for final year students in Honours programmes in Mathematics and/or Statistics.

Introduction to Monte Carlo methods and random number generation. Use of simulation for option pricing. Variance reduction methods. Stochastic programming, coherent risk measures and value at risk.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Students MUST have passed: Foundations of Calculus (MATH08005) AND Several Variable Calculus (MATH08006) AND Linear Algebra (MATH08007) AND Methods of Applied Mathematics (MATH08035) AND Probability (Year 2) (MATH08008)
Co-requisites Students MUST also take: Probability, Measure & Finance (MATH10024)
Prohibited Combinations Other requirements None
Additional Costs None
Information for Visiting Students
Pre-requisitesNone
Displayed in Visiting Students Prospectus?Yes
Course Delivery Information
Delivery period: 2014/15 Semester 2, Available to all students (SV1) Learn enabled:  Yes Quota:  None
Web Timetable Web Timetable
Course Start Date 12/01/2015
Breakdown of Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 22, Seminar/Tutorial Hours 5, Summative Assessment Hours 2, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 69 )
Additional Notes
Breakdown of Assessment Methods (Further Info) Written Exam 95 %, Coursework 5 %, Practical Exam 0 %
Exam Information
Exam Diet Paper Name Hours & Minutes
Main Exam Diet S2 (April/May)MATH10015 Simulation2:00
Summary of Intended Learning Outcomes
1. Understanding of Monte Carlo methods
2. Ability to simulate random numbers from standard distributions
3. Ability to numerically price some basic options
4. Understanding of variance-reduction techniques
5. Familiarity with stochastic programming
6. Understanding of coherent risk measures and Value at Risk (VaR)
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
KeywordsSim
Contacts
Course organiserDr Lukasz Szpruch
Tel: (0131 6)50 5742
Email: 		Course secretaryMrs Alison Fairgrieve
Tel: (0131 6)50 5045
Email:
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