In this module you will be introduced to important concepts of time series econometrics and their usefulness in analysing financial/economic data. . It is designed to give you an understanding of why the specific econometric methods are used, to provide you with a working ability of applying modern econometric methods and illustrate their application in finance.
Since econometrics relies on mathematical and statistical tools, the course content is relevant internationally.
All of the lecture material is available on the ELE (Exeter Learning Environment).
Students acquire the ability to analyse financial data and understand the foundations of econometric theory. They also develop their technical expertise in a computer software tool, logical articulation of solutions for financial data questions, and their confidence in identifying, calculating and solving research problems. These valuable skills will help them for a career in business, international organisations, government, academia or banking.
Full module specification
|Module title:||Financial Econometrics|
BEEM102 Quantitative Research Techniques 1 or BEEM104 Quantitative Methods for Finance
|Duration of module:||
Duration (weeks) - term 2: |
The aim of the module is to introduce students to the fundamental techniques used in the analysis of financial data, and to provide the necessary econometric background to carry out empirical investigations.
Students will need a good command of module-specific skills to complete an empirical dissertation, and to succeed in a job after they graduate. Effective personal and discipline-specific skills will also help students to complete other modules in the programme.
ILO: Module-specific skills
- 1. An ability to apply econometric methods to theoretical financial models.
- 2. An ability to apply modern econometric techniques in the analysis of financial data.
ILO: Discipline-specific skills
- 3. An ability to analyse and solve theoretical and applied financial questions.
- 4. An ability to formulate the hypothesis of interest, derive the necessary tools to test this hypothesis and interpret the results.
- 5. A specialised knowledge of applied aspects of financial econometrics to enable him/her to carry out applied research or direct them towards an academic career.
ILO: Personal and key skills
- 6. A technical expertise in computing software, particularly econometric software, to tackle empirical problems.
- 7. A logical attitude towards the solution of financial questions.
- 8. Confidence in identifying, tackling and solving research problems.
Learning activities and teaching methods (given in hours of study time)
|Scheduled Learning and Teaching Activities||Guided independent study||Placement / study abroad|
Details of learning activities and teaching methods
|Category||Hours of study time||Description|
Summative assessment (% of credit)
|Coursework||Written exams||Practical exams|
Details of summative assessment
|Form of assessment||% of credit||Size of the assessment (eg length / duration)||ILOs assessed||Feedback method|
|Empirical Project||50||2500 words (10-12 sides of A4)|
|Written examination 50% 1.5 hours||50||1.5 hours|
1. Linear time series analysis.
2. Unit root processes.
4. Multivariate Models
5. Volatility Models
6. Nonlinear models including Markov-switching and threshold models.
7. The predictability of asset returns.
Indicative learning resources - Basic reading
C. Brooks (2014), Introductory Econometrics for Finance, 3rd edition, Cambridge
W. Enders (2004), Applied Econometric Time Series, 2nd edition, Wiley Series in Probability and Statistics.
P. H. Franses and D. van Dijk (2006), Non-linear Time Series Models in Empirical Finance, Cambridge.
J. Y. Campbell, A. W. Lo and A.C. MacKinlay (1996), The Econometrics of Financial Markets, Princeton University Press.
T. C. Mills (1999), The Econometric Modelling of Financial Time Series, 2nd edition, Cambridge.
Module has an active ELE page?
Last revision date