Module
Applied Econometrics 2
Module description
Summary:
In thismodule you will beintroduced 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.
Additional Information:
Internationalisation
Since econometrics relies on mathematical and statistical tools, the course content is relevant internationally.
Sustainability
All of the lecture material is available on ELE (Exeter Learning Environment)
Employability
Students acquire the ability to analyse financial data and understand the foundations of economic 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: | Applied Econometrics 2 |
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Module code: | BEEM012 |
Module level: | M |
Academic year: | 2023/4 |
Module lecturers: |
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Module credit: | 15 |
ECTS value: | 7.5 |
Pre-requisites: | None |
Co-requisites: | None |
Duration of module: |
Duration (weeks) - term 2: 11 |
Module aims
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 economic 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. apply econometric methods to theoretical economic/financial models.
- 2. apply modern econometric techniques in the analysis of economic/financial data.
ILO: Discipline-specific skills
- 3. analyse and solve theoretical and applied economic/financial questions.
- 4. formulate the hypothesis of interest, derive the necessary tools to test this hypothesis and interpret the results.
- 6. apply knowledge of financial econometrics to real-world problems
ILO: Personal and key skills
- 6. learn programming concepts necessary to solve empirical problems
- 7. approach empirical questions with firm foundations in theory
- 8. develop confidence in identifying, tackling and solving research problems independently
Learning activities and teaching methods (given in hours of study time)
Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
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32 | 118 | 0 |
Details of learning activities and teaching methods
Category | Hours of study time | Description |
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Contact hours | 22 | Lectures |
10 | Tutorials |
Formative assessment
Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
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In-class problems and assignments | 3 hours each | 1-8 | Oral or written |
Summative assessment (% of credit)
Coursework | Written exams | Practical exams |
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50 | 50 | 0 |
Details of summative assessment
Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
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Empirical Project | 50 | 2500 words (10-12 sides of A4) | 1-2, 5-8 | Oral or written |
Written examination | 50 | 1.5 hours | 1-4 | Written |
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Details of re-assessment (where required by referral or deferral)
Original form of assessment | Form of re-assessment | ILOs re-assessed | Timescale for re-assessment |
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Empirical Project | Empirical Project (2,500 words) 50% | 1-2, 5-8 | July |
Written Exam | Written Exam (1.5 hours) 50% | Written Exam (1.5 hours) 50% | August |
Syllabus plan
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Linear time series analysis.
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Unit root processes.
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Cointegration.
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Multivariate Models
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Volatility Models
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Nonlinear models including Markov-switching and threshold models.
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The predictability of asset returns.
Indicative learning resources - Basic reading
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?
Yes
Origin date
16/07/2014
Last revision date
21/01/2021