Financial Modelling

The details
Essex Business School
Colchester Campus
Postgraduate: Level 7
Sunday 17 January 2021
Friday 26 March 2021
21 September 2020


Requisites for this module



Key module for

MRESN30012 Finance,
MSC L11412 Financial Econometrics,
MSC N34212 Financial Engineering and Risk Management,
MSC N3G312 Finance and Data Analytics

Module description

The purpose of this module is to provide an introduction to core topics in financial econometrics that are useful in financial research. It is a relatively technical course that will suit students with some econometrics background who are comfortable with technical material. While practically oriented, it involves some theoretical econometric material. If you are not comfortable with technical econometric material it is not for you.

Module aims

The main aims of the module are:

1. To enable students to understand and acquire the skills and techniques necessary to understand and critically evaluate the research areas covered;

2. To enable students to develop and apply those skills and techniques in coursework.

Module learning outcomes

On successful completion of the module, students will be able to:

1. Have a technical understanding of the following methods using appropriate software: OLS, time series methods, hypothesis testing techniques, VARs, SUR, ARCH, GARCH and MGARCH, non-stationarity and cointegration, tests of the EMH, predictability of asset returns, long-horizon regressions, time variation in returns, point and density forecasting and forecast evaluation.
2. Be familiar with appropriate econometric software and be able to implement financial applications using the methods listed above.
3. Be able to report and explain econometric methods and be able to interpret the meaning of results of financial econometric exercises.

Module information

Skills for Your Professional Life (Transferable Skills)

The course will deliver skills that will be useful in your future professional life including:

1. Written Communication (through coursework).

2. Research Skills (a key objective in this module).

3. Critical Thinking.

4. Digital and Technical Fluency (using econometric software).

5. Data and Analytics.

Learning and teaching methods

The main learning and teaching methods are the lectures and online material supporting those lectures and the exercises. There are additional contact hours with lecturers outside the classroom available to students. In academic year 2020-2021 the delivery is likely to be different and involve online learning.


  • (2009) Palgrave Handbook of Econometrics, London: Palgrave Macmillan UK.
  • Diebold, Francis X. (2008) Elements of forecasting, Mason, OH: South-Western.
  • Taylor, Stephen. (c2005) Asset price dynamics, volatility, and prediction, Princeton, N.J.: Princeton University Press.
  • Campbell, John Y; Lo, Andrew W.; MacKinlay, Archie Craig. (c1997) The econometrics of financial markets, Princeton, N.J.: Princeton University Press.
  • Diebold, Francis X. (c1998) Elements of forecasting, Cincinnati, Ohio: South-Western College.
  • Brooks, Chris. (2019) Introductory econometrics for finance, Cambridge, United Kingdom: Cambridge University Press.

The above list is indicative of the essential reading for the course. The library makes provision for all reading list items, with digital provision where possible, and these resources are shared between students. Further reading can be obtained from this module's reading list.

Assessment items, weightings and deadlines

Coursework / exam Description Deadline Weighting
Coursework   Take home assignment    50% 
Coursework   Take home assignment - 2     50% 

Overall assessment

Coursework Exam
100% 0%


Coursework Exam
100% 0%
Module supervisor and teaching staff
Prof Simon Price, email:
Simon Price & Lazaros Symeonidis



External examiner

Dr Nikolaos Papanikolaou
Bournemouth University
Senior Lecturer in Accounting & Finance
Available via Moodle
Of 1207 hours, 10 (0.8%) hours available to students:
1197 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s).


Further information
Essex Business School

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