(i) Part 1 Report (Individual): Students should formulate responses to the relevant questions indicated in Part 1 (for the task undertaken by their group) in the form of a short preliminary report. Although presentation will be important and will be assessed strict report format (Executive Summary, Introduction, Body etc.) is not required. However, all workings (spreadsheets, computer output), detailed methodological descriptions and references should be contained in the appendices. The report for Part 1 should be around 1500 – 2000 words and no longer than 6 x 1½ spaced 12 point typed pages excluding cover page, executive summary, references, and appendices.
Part 1 consists of some preliminary data identification, analysis and provision of basic forecasts and will be done individually by each member of the group. Each student is required to submit their response to Part 1 through Turnitin on the unit website by 11 pm, Sunday 22nd April.
Both major task options involve choosing appropriate data for the task. The choice of appropriate data needs to be justified and relevant data selection is part of the assessment process. In both cases, forecasts for the relevant target variable will be related to forecasts for variables potentially available through ABS and RBA websites. Often in forecasting and other research that available data will not perfectly match the situation. The forecaste
esearcher needs to make a judgment on suitable data that approximate the exact variable (s) needed.
A: Forecasting task A: You can only select one of the forecasting tasks
Suppose you are employed by a firm which markets interior trim insurance to new car owners. The insurance can only be provided on new cars and is valid for a 12-month period after which the policy lapses and cannot be renewed. The insurance covers things like stain removal from upholstery and minor repairs from scratches and other blemishes. You have been asked to predict the likely potential market for this insurance service for a 12-month period. This insurance is a new product/service and will be launched in March 2018 with a comprehensive marketing campaign.
As the insurance is a new product/service, there is no historical data on insurance sales available. One approach being considered by the insurance company is to forecast the sales of relevant new vehicles and to assume a certain proportion of new cars sold will opt for the insurance. This will allow relevant forecasts for new insurance policy sales to be generated.
ently the firm is considering either offering the same insurance policy for all passenger vehicles (excluding trucks and utilities) or offering separate insurance policies for normal passenger vehicles and SUV type vehicles. You have been assigned the task of analysing relevant time series and providing forecasts for the relevant period. Your group will also need to provide recommendations to management on possible outcomes associated with the proposed segmentation outlined above. In addition to providing forecasts, you are also required to outline relevant considerations due to changing economic circumstances and other environmental factors.
Part 1: Individual (15%) Due: 11 pm, Sunday 22nd April
(a) Identify a relevant time series for the total number of new vehicles sold in Australia (for at least the last 10 years) which may be useful in generating the forecasts required by the insurance company. Justify your choice of time series.
(Data should be available on relevant Australian government websites such as the Reserve Bank (RBA) or Australian Bureau of Statistics (ABS). It may also be available on relevant governmental department websites or through relevant trade organisations and/or commercial data
1. Provide a line chart of the relevant time series for approximately the last 10 years.
1. Comment in general on the characteristics of the time series line chart. What systematic components are evident in the time series?
1. Outline the economic and environmental factors or circumstances which are likely to have influenced the characteristics or components of the time series identified in (ii)? Will these factors or circumstances apply to the relevant forecasting period?
(b) Apply an appropriate method to smoothe (remove randomness) from the time series chosen in (a) to help further identify the relevant systematic components.
(i) From the results of the above smoothing, provide a time series line chart comparing the original time series with the generated smoothed values.
(ii) Does the line chart generated in (b (i)) suggest any re-evaluation or modification (if at all) to your answer to (a.(ii))? Explain.
(iii) Using the results of the smoothing method you applied, provide numerical estimates for the underlying systematic components (for example, if a trend is observed provide a relevant trend equation and/or if seasonality is observed provide estimates of the seasonal relatives or indexes).
(c) Provide at least one appropriate time series model for the time series you selected in (a) and provide relevant monthly forecasts for total new vehicle sales in Australia for April -18 to Mar-19. Justify your choice of model.