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  3. Time Series Analysis and Forecasting

Time Series Analysis and Forecasting (ECOM30004)

Undergraduate level 3Points: 12.5On Campus (Parkville)

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Overview

Availability
Semester 2
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Normally topics will include current techniques used in forecasting in finance, accounting and economics such as regression models, Box-Jenkins, ARIMA models, vector autoregression, causality analysis, cointegration and forecast evaluation, and ARCH models. 

Intended learning outcomes

On successful completion of this subject, students should be able to:

  • Apply the Box-Jenkins methodology for identifying stationary and non-stationary univariate forecasting models;
  • Apply VAR/VECM models to analyse relationships between economic and financial time series; and
  • Apply ARCH models to analyse and forecast the volatility of financial time series.

Generic skills

On successful completion of this subject, students should have improved the following generic skills:

  • Evaluation of ideas, views and evidence;
  • Synthesis of ideas, views and evidence;
  • Strategic thinking;
  • Critical thinking;
  • Accessing economic and other information;
  • Summary and interpretation of information;
  • Application of Windows software;
  • Statistical reasoning;
  • Problem solving skills; and
  • Written communication.

Last updated: 6 December 2024