# Quantitative Techniques

## Overview

• Credit value: 30 credits at Level 6
• Assessment: examinations in September and coursework

## Module description

This compulsory course is taught mostly through pre-sessional modules in September, and aims to ensure that you have the basic quantitative techniques for the MSc programme. If you are studying part-time, you review basic mathematics in September and study static and dynamic optimisation later in the academic year. Prior to the start of the second year, you review statistical techniques. Full-time students cover all modules in one year.

The course compromises three modules:

1. Mathematics
2. Statistics
3. Introduction to Finance

Details for these individual modules are provided below. Not all modules are relevant to all programmes.

• MSc Economics, MS Financial Economics students are required to do Mathematics and Statistics, and pass the associated exams.
• MSc Finance students are required to do Mathematics and Statistics, and pass the associated exams. They are invited to attend lectures for Introduction to Finance but not required to do the exam.

1. Mathematics

• understand the basics of sets and functions, including standard
• understand the basics of linear algebra and the use of matrices
• learn how to find the constrained optima of multivariate functions
• compute definite and indefinite integrals
• solve simple difference and differential equations
• use these techniques to solve simple problems.

Assessment: a two-hour written examination held at the end of September.

2. Statistics

This module covers the following topics:

• Probability and distribution theories (probability, random variables and probability distributions, expectations and moments, univariate and multi-variate distributions, functions of random variables)
• Statistical Inference (sampling, large sample theory, point estimation, parametric interval estimation, tests of statistical hypotheses)

Assessment: a two-hour written examination held at the end of September.

3. Finance

These introductory lectures in finance introduce key ideas and concepts, such as no-arbitrage pricing, risk-return trade-offs, the Capital Asset Pricing Model and the basics of derivative pricing.

Assessment: a short multiple choice test taken at the same time as the qualifying examination in statistics.

## Learning objectives

By the end of this course, you should be able to:

• use matrices for algebraic manipulations
• understand and use the techniques of static and dynamic optimisation
• compute definite and indefinite integrals
• solve simple difference and differential equations
• understand the basic of probability distributions
• understand statistical inference.