AMS4322 - Financial Time Series for Business Intelligence

Year of Study:3 - 4
Credit Units: 3
Duration: 45hours
Prerequisites: AMS2320 Business Regression Analysis or with the Instructor’s permission and upon endorsement of the relevant Chairperson or Programme Director.
Module Description
This module aims to introduce sophisticated statistical techniques and models for analysing time series data and forecasting. Topics selected include basic time series forecasting, stochastic time series modelling and advanced techniques used in time series analysis. Students apply time series analysis techniques with the use of information technology to analyse practical business problems. Students are also required to present their findings to their peers and professors in a professional manner.
Learning Outcomes
Upon completion of this module, students should be able to:

  1. understand the fundamental principles of time series, smoothing, stochastic time series models and advanced time series analysis techniques;

  2. apply relevant statistical knowledge and techniques for forecasting;

  3. formulate forecasting problems, apply techniques with the use of computer software to analyse time series data, and interpret and present the results in a scientific and concise manner; and

  4. work effectively in a team and solve problems logically, analytically, critically and independently.