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The University of Southampton

MANG6297 Advanced Time Series Modelling

Module Overview

The module offers a comprehensive introduction to Advanced Time Series Modelling. You will learn various analytical tools to enable you to analyse financial data. The module expects prior skills in data analysis covered by the module Quantitative Finance (MANG6299) in the 1st semester. In addition, Students on the MSc Risk and Finance can choose this module but they will need to have taken MANG6003 Quantitative Methods in the first semester if they wish to do so.

Aims and Objectives

Learning Outcomes

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

  • econometric modelling;
  • forecasting of financial time series;
  • competence in using an econometric software package (STATA).
Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

  • analyse financial data;
  • evaluate model fit;
  • assess out-of-sample properties;
  • interpret statistical output;
  • relate forecasts to strategic decisions;
  • critically evaluate statistical models and forecasting tools.
Transferable and Generic Skills

Having successfully completed this module you will be able to:

  • analyse financial data;
  • develop quantitative models.


The module will introduce methods developed in time series analysis and apply these methods to financial data. The module will stress the relationship between finance, econometrics and statistics. The module will be also offered as an option on other programmes (i.e. MSc International Financial Markets, MSc International Banking and Financial Studies). The module will use comparative case studies and will analyse financial data in different settings (countries, industries and governance mechanism). Topics: Classical time series analysis • Deterministic trends • Cyclicality • Seasonality ARIMA models • Box-Jenkins approach • Forecasting • Out-of-sample properties Structural breaks • Testing for structural breaks • Endogenous and exogenous tests Vector autoregression (VAR) • Short-term dynamics • Lag specification • Forecasting Co-integration and long-term equilibrium • Johansen procedure • Structural breaks in long-term equilibrium Vector error correction models (VECM) • Speed of adjustment • Short and long-term dynamics Modelling conditional volatility • ARCH model • GARCH model Multivariate time series modelling • Panel vector autoregression • Panel co-integration

Learning and Teaching

Teaching and learning methods

Teaching methods include: The module will be taught by a mixture of methods ranging from guided background reading, lectures, group work and the exploration of mini case studies and datasets. The lecturer will draw upon market developments current at the time of the course. The lecturer will introduce the concepts, and you will have the opportunity to practice and apply the methods discussed. We will do a step-by-step analysis of different financial data (stock market data, firm and industry-specific data). Learning activities include: • EVIEWS based exercises in class • A group assignment • Discussion of findings in class There will be many opportunities for you to gain feedback from your tutor and/or peers about your level of understanding and knowledge prior to any formal summative assessment such as coursework or examinations. In particular, class exercises and short presentations in class will provide an opportunity for feedback from peers and tutors.

Independent Study126
Total study time150

Resources & Reading list

Hayashi, F. (2000). Econometrics. 

Asterious, G. and S. Hall (2011). Applied Econometrics. 

Greene, W.H. (2000). Econometric Analysis. 

Wooldridge, J.M. (2009). Introductory Econometrics. 

Chiang, A.C. (1984). Fundamental Methods of Mathematical Economics. 

Campbell, J.Y., Lo, A.W. & A.C. MacKinlay (1997). The Econometrics of Financial Markets. 

Enders, W. (2014). Applied Econometric Time Series. 



Homework Exercises


MethodPercentage contribution
Individual Coursework 100%


MethodPercentage contribution
Individual Coursework 100%


MethodPercentage contribution
Individual Coursework 100%

Repeat Information

Repeat type: Internal & External


Costs associated with this module

Students are responsible for meeting the cost of essential textbooks, and of producing such essays, assignments, laboratory reports and dissertations as are required to fulfil the academic requirements for each programme of study.

In addition to this, students registered for this module typically also have to pay for:

Books and Stationery equipment

Students are expected to buy the core text.


Recommended texts for this module may be available in limited supply in the University Library and students may wish to purchase the mandatory/additional reading text as appropriate.

Please also ensure you read the section on additional costs in the University’s Fees, Charges and Expenses Regulations in the University Calendar available at

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