MA207      Half Unit
Further Quantitative Methods (Mathematics)

This information is for the 2017/18 session.

Teacher responsible

Dr James Ward

Availability

This course is available on the BSc in Accounting and Finance and BSc in Management. This course is available as an outside option to students on other programmes where regulations permit. This course is available with permission to General Course students.

Pre-requisites

Students should have previously taken MA107 Quantitative Methods (Mathematics). It is not available to students who have taken MA100 Mathematical Methods, or equivalent, nor higher level methods courses.

Course content

This is a second course in quantitative methods, following on directly from Quantitative Methods (Mathematics) (MA107). This course will contain further algebra and calculus. As with the course MA107, the emphasis will be on applications in economics and finance. Topics covered: Matrix methods in portfolio analysis. Linear independence. Rank of a matrix. Eigenvalues and eigenvectors. Diagonalisation. Linear systems of recurrence equations. Markov process. Second-order recurrence equations. Macroeconomic models. Vector geometry. Gradient and directional derivative. Tangent hyperplanes and the optimal bundle. Resource allocation and Pareto efficiency. Orthogonal matrices and quadratic forms. Critical points of quadratic functions. Taylor's approximation. Optimisation of functions of two or more variables.

Teaching

22 hours of lectures and 10 hours of classes in the LT.

Formative coursework

Written answers to set problems will be expected on a weekly basis.

Indicative reading

M Anthony & N Biggs, Mathematics for Economics and Finance (Cambridge, 1996); A Ostaszewski, Mathematics in Economics (Blackwell, 1993).

Assessment

Exam (100%, duration: 2 hours) in the main exam period.

Key facts

Department: Mathematics

Total students 2016/17: 83

Average class size 2016/17: 17

Capped 2016/17: No

Value: Half Unit

Guidelines for interpreting course guide information

PDAM skills

  • Self-management
  • Problem solving
  • Application of information skills
  • Communication
  • Application of numeracy skills
  • Specialist skills