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Applied Econometrics 2

Module description


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.

Additional Information:


  • Since econometrics relies on mathematical and statistical tools, the course content is relevant internationally


  • All of the lecture material is available on ELE (Exeter Learning Environment)


  • 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
Module code:BEEM012
Module level:M
Academic year:2023/4
Module lecturers:
  • Mr Julian Dyer - Convenor
Module credit:15
ECTS value:






Duration of module: Duration (weeks) - term 2:


Module aims

The aim of the module is to introduce you to the fundamental techniques used in the analysis of financial data, and to provide the necessary economic background to carry out empirical investigations.

You 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 you 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
  • 5. 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 ActivitiesGuided independent studyPlacement / study abroad

Details of learning activities and teaching methods

CategoryHours of study timeDescription
Scheduled learning and teaching22Lectures
Scheduled learning and teaching10Tutorials
Guided independent study118Private study

Formative assessment

Form of assessmentSize of the assessment (eg length / duration)ILOs assessedFeedback method
In-class problems and assignments3 hours each1-8Oral or written

Summative assessment (% of credit)

CourseworkWritten examsPractical exams

Details of summative assessment

Form of assessment% of creditSize of the assessment (eg length / duration)ILOs assessedFeedback method
Empirical project proposal5<1 page of A41-2, 5-8Written
Empirical project502500 words (10-12 side of A4)1-2, 5-8Oral or written
Written examination451.5 hours1-4Written

Details of re-assessment (where required by referral or deferral)

Original form of assessmentForm of re-assessmentILOs re-assessedTimescale for re-assessment
Empirical project proposal<1 page of A41-2, 5-8Referral/deferral period
Empirical projectEmpirical project (2,500 words) 50%1-2, 5-8Referral/deferral period
Written examWritten exam (1.5 hours) 45%Written exam (1.5 hours) 50% Referral/deferral period

Re-assessment notes

Deferral – if you miss an assessment for certificated reasons judged acceptable by the Mitigation Committee, you will normally be either deferred in the assessment or an extension may be granted. The mark given for a re-assessment taken as a result of deferral will not be capped and will be treated as it would be if it were your first attempt at the assessment.

Referral – if you have failed the module overall (i.e., a final overall module mark of less than 50%) you will be required to redo the assessment(s) as necessary. If you are successful on referral, your overall module mark will be capped at 50%.

Syllabus plan

Whilst the module’s precise content may vary from year to year, it is envisaged that the syllabus will cover some or all of the following topics: 

  • Linear time series analysis
  • Unit root processes
  • Cointegration
  • Multivariate Models
  • Volatility Models
  • Nonlinear models including Markov-switching and threshold models
  • 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?


Indicative learning resources - Other resources


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