Module Identifier ECM1000  
Module Title EMPIRICAL METHODS IN FINANCE  
Academic Year 2003/2004  
Co-ordinator Dr Mark J Rhodes  
Semester Semester 1 (Taught over 2 semesters)  
Course delivery Lecture   12 Hours  
  Seminars / Tutorials   5 Hours  
  Other   5 Hours Computer Classes  

Learning outcomes

The module is an advanced level study of econometrics. On completion of this module students should be able to: Critically evaluate
(1) The use of classical linear regression in estimation and inference,
(2) The consequences of the failure of the classical regression assumptions, their diagnosis, consequences and solutions,
(3) The specification, estimation and properties of dynamic time series models, including those with dynamic error structures,
(4) The specification, estimation and properties of simultaneous equation regression models,
(5) The implications of unit roots in time series and the importance of cointegration, (6) the use of single and multiple equation estimation techniques and
(7) The advantages and shortcomings of panel data and the techniques for estimation of panel data models and their application.

Aims

The module is an advanced level study of econometrics. We will examine the uses of econometrics in the study of financial institutions and markets. Building from basic principles in finance and statistics we will discuss the practical application, both in the interpretation of empirical results in finance and the use of computers to estimate original models.

Reading Lists

Books
** Essential Reading
Brooks, C (2002) Introductory Econometrics for Finance Cambridge University Press
Copeland, T E and Weston, J F (1992) Financial Theory and Corporate Policy Addison Wesley
Newbold, P (1995) Statistics for Business and Economics 4th Edition. Prentice Hall
Enders, W (1995) Applied Econometric Time Series Wiley
Greene, W H (2002) Econometric Analysis 5th Edition. Prentice Hall

Notes

This module is at CQFW Level 7