MATH2003J Optimisation in Economics

Academic Year 2021/2022

This course is an introduction to mathematical methods of optimization in financial models. The course introduces various tools for solving linear and non-linear optimization problems under unconstrained and constrained settings, such as linear programming, Kuhn-Tucker theory and optimization of convex functions.

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Curricular information is subject to change

Learning Outcomes:

On successful completion of this module, the student will:
(i) be familiar with basic mathematical techniques of constrained and unconstrained extrema in financial models;
(ii) be aware of the relationship between constraint parameters and shadow prices;
(iii) be able to set up and solve linear optimization problems by the simplex method and duality;
(iv) be able to apply convexity methods to certain extremum problems.

Student Effort Hours: 
Student Effort Type Hours
Lectures

36
Tutorial

16
Specified Learning Activities

32
Autonomous Student Learning

32
Total

116
Approaches to Teaching and Learning:
Lectures, tutorials, enquiry and problem-based learning. 
Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.
 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Examination: End of Trimester Exam Unspecified No Alternative linear conversion grade scale 40% No

65
Continuous Assessment: Continuous assessment Throughout the Trimester n/a Alternative linear conversion grade scale 40% No

35

Carry forward of passed components
No
 
Resit In Terminal Exam
Summer Yes - 2 Hour
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

Name Role
Dr Cornelia Roessing Lecturer / Co-Lecturer
Dr Daniele Casazza Tutor