Module code: ECOM031

Module provider


Module Leader

DUMITRU A Dr (Economics)

Number of Credits


ECT Credits



FHEQ Level 7

JACs code


Module cap (Maximum number of students)


Module Availability

Semester 2

Overall student workload

Independent Study Hours: 128

Lecture Hours: 22

Seminar Hours: 11

Assessment pattern

Assessment type Unit of assessment Weighting
Coursework COURSEWORK - 2500 WORD REPORT 25%
Examination EXAMINATION - 2 HOURS 75%

Alternative Assessment

Not applicable

Prerequisites / Co-requisites


Module overview

Introduction to modern econometric techniques used in the analysis of financial time series. Topics include ARIMA models, ARCH & GARCH and Stochastic Volatility models, estimating and testing the CAPM, fractional integration and nonlinear models.

Module aims

examine a variety of econometric techniques developed to analyse financial data series and use appropriate software to apply these techniques to estimate models of actual financial data 

Learning outcomes

Attributes Developed
Understand and critically evaluate models of asset return processes C
Build models of ARCH and GARCH processes using appropriate software PT
Analyse dynamic models with changing regimes C
Estimate and test models of financial data using appropriate computer software PT

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

Module content

Indicative content includes:

Asset return processes: stationarity, random walks, tests for unit roots
Conditional volatility: ARCH, GARCH, GARCH-M and E-GARCH models
Stochastic volatility models
Estimating and testing the Capital Asset Pricing Model
Long term memory and fractional integration in stock market returns
Non-linear models including SETAR, STAR, Markov models of regime switching

Methods of Teaching / Learning

The learning and teaching strategy is designed to:

The lectures provide an understanding of a variety of econometric techniques used in modelling the characteristic features of financial data series. The classes give experience in applying appropriate software to estimate and critically assess different models of financial data series.

The learning and teaching methods include:

1 hour lecture per week x 11 weeks
1 hour class per week x 11 weeks

Assessment Strategy

The assessment strategy is designed to provide students with the opportunity to demonstrate

knowledge of different econometric techniques used with financial data series
the practical ability to build and assess appropriate econometric models using actual data

Thus, the summative assessment for this module consists of:

A take-home piece of coursework (2500 words) requiring students to build and assess an appropriate model of a stock return series for an assigned country using computer software. Deadline around week 8
A two-hour examination covering the econometric techniques discussed in the lectures, scheduled in weeks 13-15.

Formative assessment and feedback

Classes to provide verbal feedback on the exercises which teach the use of software to build models of financial data series and help prepare students for the coursework.

Reading list


Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2017/8 academic year.