Module overview
Financial Econometrics 2 builds on Financial Econometrics 1 and provides you with more skills to undertake empirical research in finance. Lectures will introduce important topics such as unit roots, stationarity, VAR models as well as a broad range of volatility models. You get also get the chance to conduct your own empirical research through EViews software in the tutorials which will take place in labs.
Linked modules
Pre-requisite: MANG2074
Aims and Objectives
Learning Outcomes
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- analyse financial data and solve complex problems
- use an econometric software package (EViews)
- critically evaluate statistical models and forecasting tools
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- econometric modelling
- analyse financial data
- forecasting of financial time series
Transferable and Generic Skills
Having successfully completed this module you will be able to:
- collect and analyse quantitative data
Syllabus
Classical time series analysis
Deterministic trends
Cyclicality
Seasonality
ARIMA models
Box-Jenkins approach
Forecasting
Out-of-sample properties
Structural breaks
Testing for structural breaks
Endogenous and exogenous tests
Vector autoregression (VAR)
Short-term dynamics
Lag specification
Forecasting
Co-integration and long-term equilibrium
Johansen procedure
Structural breaks in long-term equilibrium
Vector error correction models (VECM)
Speed of adjustment
Short and long-term dynamics
Modelling conditional volatility
ARCH model
GARCH model
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.
| Type | Hours |
|---|---|
| Follow-up work | 24 |
| Lecture | 24 |
| Wider reading or practice | 22 |
| Tutorial | 10 |
| Revision | 60 |
| Preparation for scheduled sessions | 10 |
| Total study time | 150 |
Resources & Reading list
Textbooks
Greene, W.H. (2000). Econometric analysis. Prentice Hall International Inc.
Marno Verbeek (2012). A Guide to Modern Econometrics. Wiley and Sons.
Chris Brooks (2014). Introductory Econometrics for Finance. Cambridge University Press.
Assessment
Formative
This is how we’ll give you feedback as you are learning. It is not a formal test or exam.
In-class activitiesSummative
This is how we’ll formally assess what you have learned in this module.
| Method | Percentage contribution |
|---|---|
| Examination | 50% |
| Project | 50% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
| Method | Percentage contribution |
|---|---|
| Examination | 100% |
Repeat
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
| Method | Percentage contribution |
|---|---|
| Project | 50% |
| Examination | 50% |
Repeat Information
Repeat type: Internal & External