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The University of Southampton

MANG2074 Financial Econometrics 1

Module Overview

Financial Econometrics 1 provides you with the necessary skills to undertake quantitative research in finance. Lectures will introduce a broad range of topics (e.g. regression). However, you will discover that by understanding and applying some basic concepts various issues can be analysed in a similar manner. In particular, we will introduce basic theoretical concepts developed in statistics and econometrics. Understanding the main theoretical methods is essential to appreciate the analytical tools and their applications to finance. Tutorials take place in labs where you will be able to conduct your own research via the software EViews. The module introduces empirical methods used in finance and is a prerequisite for Financial Econometrics 2 in the 2nd semester.

Aims and Objectives

Learning Outcomes

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

  • the basic theory of financial econometrics
  • the role empirical research has in finance and the limitations of such research
  • analyse financial data
Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

  • demonstrate quantitative skills in evaluating numerical data and answer complex problems
  • some specific applications of such financial theory
  • use an econometrics software package (Eviews)
Transferable and Generic Skills

Having successfully completed this module you will be able to:

  • demonstrate skills in utilizing analysis software
  • collect and analyse quantitative data


Structure of linear models Functional forms Log linear models Quadratic models Lags Dummy variables Exploring data Descriptive statistics Outliers Missing data Regression analysis Ordinary least squares (OLS) estimator Classical OLS assumption Statistical significance Specification tests Testing for violation of assumptions and their implications • Heteroskedasticity Autocorrelation Multicollinearity Endogeneity

Learning and Teaching

Teaching and learning methods

Weekly lectures will provide an overview of the main issues arising in the module. Weekly classes will supplement the lectures which will support student learning by providing opportunities for you to attempt, and gain feedback on, numerical and problem-solving exercises. This will include access to computer labs to conduct primary research via EViews software as well as in the Bloomberg suite to access and analyse real-time financial data.

Wider reading or practice22
Follow-up work24
Preparation for scheduled sessions10
Total study time150

Resources & Reading list

Marno Verbeek (2012). A Guide to Modern Econometrics. 

Chris Brooks (2014). Introductory Econometrics for Finance. 

Greene, W.H. (2000). Econometric analysis. 



In-class activities


MethodPercentage contribution
Project  (3000 words) 100%


MethodPercentage contribution
Project  (3000 words) 100%


MethodPercentage contribution
Project  (3000 words) 100%

Repeat Information

Repeat type: Internal & External


Costs associated with this module

Students are responsible for meeting the cost of essential textbooks, and of producing such essays, assignments, laboratory reports and dissertations as are required to fulfil the academic requirements for each programme of study.

In addition to this, students registered for this module typically also have to pay for:

Printing and Photocopying Costs

There will be additional costs for printing.


Recommended texts for this module may be available in limited supply in the University Library and students may wish to purchase the core/recommended text as appropriate.

Please also ensure you read the section on additional costs in the University’s Fees, Charges and Expenses Regulations in the University Calendar available at

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