Module Overview

Forecasting and Stochastic Models

Following on from Times Series Analysis 1, this module provides further understanding of time-domain and frequency-domain analyses of univariate and multivariate time series methods, with coverage of the most recently developed techniques in the field.  An important topic in Business Analytics, the module develops the theoretical knowledge and the practical implementation skills of different techniques. The module also covers the criteria where different approaches apply.

Module Code


ECTS Credits


*Curricular information is subject to change

Regression Analysis and Forecasting

Exponential Smoothing Methods

Stationary and Non-Stationary Times Series Models, The General ARIMA Model

Intervention Analysis and Outlier Detection

Transfer Function Models

Time Series Regression and GARCH Models

Learning will occur in a combination of lectures, practical laboratory sessions and tutorials.

  1. Lectures: Teach concepts.
  2. Discussions: Encourage understanding.
  3. Projects: Apply concepts to problems.
  4. Labs: Provide hands-on experience.
  5. Case studies: Illustrate real-world applications

Module Content & Assessment
Assessment Breakdown %
Other Assessment(s)100