Quantitative Techniques for Financial Economics II

EMEC021S5 (30 credits)
Year 2

Lecturers: Anthony Garratt and Colin Rowat

Aims

This course covers the more advanced quantitative techniques that will be used throughout the degree. Mathematical techniques are used to build theoretical models and to analyse their properties. Statistical techniques are used to test and validate theories. Econometric techniques are used to estimate empirical models.

Objectives

On successful completion of this part of the course, students should be able to:

• carry out matrix manipulation;
• optimise two-variable continuous functions (including constrained optimisation using the Lagrangean function);
• manipulate sequences and series (including arithmetic, geometric and exponential series), understand convergence criteria and perform summations;
• solve first-order elementary difference and differential equations;
• understand the basic principles of estimation and hypothesis testing;
• test a hypothesis about a population mean and regression coefficients;
• know what is meant by the method of least squares and the “classical” two-variable linear regression model;
• interpret simple and multiple regression equations;
• understand and can apply the concept of a confidence interval.

Required Reading

• Chiang, AC and K Wainwright, Fundamental Methods of Mathematical Economics, McGraw-Hill.
• Newbold, P, WL Carlson and B Thorne, Statistics for Business and Economics, Sixth Edition. Pearson, Prentice Hall.

Assessment

A three-hour examination in June, based on the overall syllabus, counts for 80% of the mark. The remaining 20% comes from (i) written coursework on the mathematical techniques section, to be completed during the Christmas vacation (10%) (ii) written course work on the statistical techniques section (10%) to be completed in the Easter vacation.