# Quantitative Methods in Finance

 Module Code BFIP013 Semester Autumn Prerequisite N/A Level 11 Credit Value 20 Module Co-ordinator Dr Maria Grydaki Assessment 35% Coursework, 10% practical & 55% examination

MODULE INTRODUCTION, AIMS AND OBJECTIVES

The aim of this module is to provide students with the statistical and computing skills which are necessary to understand modern finance literature and to operate in a commercial finance environment. After the completion of this course students should be able to conduct basic econometric analysis and use it in their master thesis. This module also covers the learning outcomes highlighted in the Chartered Financial Analyst (CFA) Institute Quantitative Methods syllabus at levels 1-3.

LEARNING OUTCOMES AND SKILLS DEVELOPED

Upon completion of the module, you will have knowledge and understanding of:

• the nature of econometrics and economic data
• probability, descriptive statistics and inference
• how to run a simple and multiple linear regression and draw inference connecting the statistical results with economic theory
• the violations of the basic assumptions of simple and multiple regression models. How these can be detected and tackled and what are the consequences for the estimates
• time series analysis; why stationarity of the variables is important
• the use of STATA software to estimate linear models

Quantitative Methods in Finance is based on the following content and lecture programme:

1. Review of introductory statistics (probability, descriptive statistics, inference) (covered in the Flying Start Programme)
2. Simple Regression Analysis – Estimation
3. Simple Regression Analysis – Inference
4. Multiple Regression Analysis: Estimation and Inference
5. Multiple Regression Analysis with Qualitative Information: Binary (or Dummy) Variables
6. Heteroskedasticity
7. Basic Regression Analysis with Time Series Data
8. Further Issues in Using OLS with Time Series Data
9. Serial Correlation in Time Series Regressions
10. Stationarity tests