ETC5550 - Applied forecasting - Monash University

There is a more recent version of this academic item available.

Overview

Reliable forecasts of business and economic variables must often be obtained against a backdrop of structural change in markets and the economy. This unit introduces methods suitable for forecasting in these circumstances including the decomposition of time series, exponential smoothing methods, ARIMA modelling, and regression with autocorrelated disturbances. You can … For more content click the Read More button below.

Reliable forecasts of business and economic variables must often be obtained against a backdrop of structural change in markets and the economy. This unit introduces methods suitable for forecasting in these circumstances including the decomposition of time series, exponential smoothing methods, ARIMA modelling, and regression with autocorrelated disturbances. You can expect to enhance their computer skills with exercises using R.

Offerings

S1-01-CLAYTON-ON-CAMPUS

Requisites

Prerequisite

FIT5197

6 CP

Statistical data modelling

ETC2410

6 CP

Introductory econometrics

Introductory econometrics

Introductory econometrics

ETF2121

6 CP

Data analysis in business

ETF5910

6 CP

Introductory applied econometrics

ETF5912

6 CP

Data analysis in business

Prohibition

Rules

Enrolment Rule

Contacts

Chief Examiner(s)

Professor Rob Hyndman

Teaching approach

Problem-based learning

Assessment

1 - Within semester assessment

2 - Examination

Scheduled and non-scheduled teaching activities

Lectures

Tutorials

Workload requirements

Workload

Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled learning activities and independent study. Independent study may include associated readings, assessment and preparation for scheduled activities. The unit requires on average three/four hours of scheduled activities per week. Scheduled activities may include a combination of teacher directed learning, peer directed learning and online engagement.

Learning resources

Required resources

Technology resources