Research Methods in Financial Econometrics

The details
Essex Business School
Colchester Campus
Postgraduate: Level 8
Thursday 03 October 2024
Friday 13 December 2024
28 February 2024


Requisites for this module



Key module for

MPH N30024 Finance,
MPH N30048 Finance,
MPHDN30036 Finance,
MPHDN30048 Finance,
MPHDN30072 Finance,
MPHDN30084 Finance,
MPHDN300FA Finance,
MPHDN300FJ Finance,
MPHDN300PA Finance,
MPHDN300PJ Finance,
MSD N30012 Finance,
MSD N30024 Finance,
PHD N30036 Finance,
PHD N30048 Finance,
PHD N30072 Finance,
PHD N30084 Finance,
PHD N300FA Finance,
PHD N300FJ Finance,
PHD N300PA Finance,
PHD N300PJ Finance

Module description

The aim of this module is to provide first year PhD students, registered for a PhD in either Finance or Econometrics in Essex Business School, with an up-to-date and rigorous introduction to a range of state-of-the art methods used in the published financial econometrics literature.

This module aims to introduce students to the core methodology and empirical practice of modern financial econometrics. This will involve developing relevant statistical and mathematical skills, together with the ability to apply these methods to real data using industry-standard software and to interpret their results

Module aims

The aims of this module are:

  • To develop and transmit knowledge of recent advancements in the financial econometrics literature through examining key papers that are closely tied to the research interests of our academic staff.

  • To provide training in relevant econometric techniques required to perform robust research in financial econometrics, and to illustrate the use of these techniques in practice.

  • To provide students with hands on experience of implementing the methods commonly employed in the financial econometrics literature through a series of lectures and associated workshops and computer practical sessions. 

  • To provide training in the use of the relevant computing software. 

Module learning outcomes

By the end of this module, students will be expected to be able to:

  1. Have an understanding of the relevant econometric techniques appropriate for performing both theoretical and empirical analysis in financial econometrics.

  2. Have developed knowledge on the use of industry standard statistical software, being able to use this software to perform advanced statistical techniques on either user-imported or pseudo-data.

  3. Be able to critically evaluate contributions made by recent papers in the financial econometrics literature, and to replicate or develop further the findings outlined in these papers

Module information

This module will be run over the autumn term. The module will consist of 10 weeks of lecture plus workshop (group based) and/or computer lab based teaching around a number of specific advanced topics in financial econometrics. Each topic will be delivered by a particular member of EBS staff who undertakes research in that area (broadly defined).

The selection of topics covered will vary from year-to-year depending on staff availability and will also be designed to reflect the interests and chosen areas of doctoral research of that year's cohort of students. Likely topics include: Advanced unit root and cointegration methods; Detecting rational bubbles in financial price data; Predictive regression methods for forecasting stock returns; Econometrics of asset pricing models; Machine learning and `big data' methods in finance; Cross sectional and panel data methods in finance.

Students will be asked to read key published journal articles (which will vary from year to year, all of which will be accessible on-line using their university ID and password) relevant to each topic which will be central to the teaching delivery. Associated lecture notes will be provided for each topic covered.

Learning and teaching methods

This module will be delivered via:

  • One 2-hour lecture per week
  • One 2-hour lab per week


This module does not appear to have a published bibliography for this year.

Assessment items, weightings and deadlines

Coursework / exam Description Deadline Coursework weighting

Exam format definitions

  • Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
  • In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
  • In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
  • In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary, for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.

Your department will provide further guidance before your exams.

Overall assessment

Coursework Exam
100% 0%


Coursework Exam
100% 0%
Module supervisor and teaching staff
Prof Robert Taylor, email:
Professor Rob Taylor, Dr Ilias Chronopoulos, Christos Argyropoulos, Dr Efthymios Nikolakopoulos & Dr Ali Ozbekler



External examiner

No external examiner information available for this module.
Available via Moodle
No lecture recording information available for this module.


Further information
Essex Business School

* Please note: due to differing publication schedules, items marked with an asterisk (*) base their information upon the previous academic year.

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