ICM337-Econometric Analysis for Finance

Module Provider: ICMA Centre
Number of credits: 20 [10 ECTS credits]
Terms in which taught: Autumn term module
Non-modular pre-requisites:
Modules excluded:
Current from: 2023/4

Module Convenor: Prof Mike Clements
Email: m.p.clements@icmacentre.ac.uk

Module Co-convenor: Dr Lisa Schopohl
Email: l.schopohl@icmacentre.ac.uk

Type of module:

Summary module description:

This module equips you with the quantitative tools used by market participants. The module uses a mixture of (1) lectures where the theory and concepts are introduced and (2) seminars and workshops where we apply the knowledge to practical cases.

It is an introductory applied econometrics module with an emphasis on finance.


The aims and objectives of the module are to give students an introduction to econometrics so that they might understand the econometric techniques used in the finance research literature. Via illustrations from the empirical finance literature and using econometric, students then learn how to apply these techniques to real data. Emphasis is placed on practical applications of the techniques in the global financial markets.


Assessable learning outcomes:

By the end of the module, it is expected that students will be able to

  • Explain the standard approaches to model formulation, estimation and testing, and how to check the statistical validity of a model  

  • Formulate and apply econometric models to test financial theories and hypotheses

  • Interpret and analyse the results from estimated econometric models

  • Critically evaluate the use of econometrics in the published academic finance literature.

Additional outcomes:

The module aims to encourage the development of IT and data handling skills: in particular, the use of Python as the software to apply the econometric techniques to data, e.g. from Eikon and Bloomberg.

Outline content:

  1. Introduction to econometrics and simple regression assumptions

  2. Hypothesis Testing

  3. Multiple regression, t-ratios and over-reaction hypothesis

  4. Goodness of fit statistics and hedonic models

  5. Heteroscedasticity and autocorrelation

  6. Multicollinearity, functional form, normality,

  7. Seasonality, parameter stability tests

  8. Panel Data

  9. Conditional Variance models

  10. Large scale data modelling and analysis

Global context:

Throughout the module we will be using international financial datasets. The academic studies discussed in the module cover different countries and offer a global perspective.

Brief description of teaching and learning methods:

Core lectures supported by lab-based computer seminars and classroom-based tutor led discussion.

Contact hours:
  Autumn Spring Summer
Lectures 20
Seminars 14
Guided independent study:      
    Wider reading (independent) 10
    Wider reading (directed) 10
    Exam revision/preparation 22
    Advance preparation for classes 20
    Preparation for tutorials 32
    Revision and preparation 22
    Essay preparation 40
    Reflection 10
Total hours by term 200 0 0
Total hours for module 200

Summative Assessment Methods:
Method Percentage
Written exam 70
Written assignment including essay 30

Summative assessment- Examinations:

2 hour multiple-choice based examination.

The examination for this module will require a narrowly defined time window and is likely to be held in a dedicated exam venue.

Summative assessment- Coursework and in-class tests:

One group project which will include the estimation of econometric models and the use and interpretation of related techniques. The group project report should have a limit of 2,500 words.   The submission deadline is in Week 2 of the Spring term.

Formative assessment methods:

Practice MCQ tests via Blackboard.

Penalties for late submission:

The below information applies to students on taught programmes except those on Postgraduate Flexible programmes. Penalties for late submission, and the associated procedures, which apply to Postgraduate Flexible programmes are specified in the policy “Penalties for late submission for Postgraduate Flexible programmes”, which can be found here: https://www.reading.ac.uk/cqsd/-/media/project/functions/cqsd/documents/cqsd-old-site-documents/penaltiesforlatesubmissionpgflexible.pdf

The Support Centres will apply the following penalties for work submitted late:

  • where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of five working days;

  • where the piece of work is submitted more than five working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

The University policy statement on penalties for late submission can be found at: https://www.reading.ac.uk/cqsd/-/media/project/functions/cqsd/documents/cqsd-old-site-documents/penaltiesforlatesubmission.pdf

You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Assessment requirements for a pass:

50% weighted average mark

Reassessment arrangements:

By examination only, as part of the overall examination arrangements for the MSc programme. Re-sit examination to be taken in August/September.

Additional Costs (specified where applicable):

Required textbooks: 

Brooks, C. (2019). Introductory Econometrics for Finance, 4th Edition, Cambridge University Press, Cambridge (UK) £45 (but available as e-book via UoR Library)

Specialist equipment or materials: Calculator £15

Recommended Models:

1. Casio FX-83GTx or Casio FX-83GTPLUS 

2. Casio FX-85GTx or Casio FX-85GTPLUS

3. Casio FX-85MS

4. Texas Instruments BA II Plus

Last updated: 5 April 2023


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