19. (30 marks) Given the following time series dataset for X over a 48-month period. The dataset consists of monthly obs

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19 30 Marks Given The Following Time Series Dataset For X Over A 48 Month Period The Dataset Consists Of Monthly Obs 1 (146.02 KiB) Viewed 22 times

19. (30 marks) Given the following time series dataset for X over a 48-month period. The dataset consists of monthly observations. We are interested in deasonalising the data using 12 monthly seasonal indexes. Month Data X Month Month Data X Month Data X Data X 103 Jan, 2013 81 Jan, 2014 Jan, 2015 122 Jan, 2016 170 Feb, 2013 102 Feb, 2014 Feb, 2015 115 120 53 Feb, 2016 196 Mar, 2013 42 Mar, 2014 Mar, 2015 88 Mar, 2016 125 Apr, 2013 40 Apr, 2014 46 Apr, 2015 63 Apr, 2016 111 May, 2013 53 May, 2014 104 May, 2015 154 May, 2016 110 Jun, 2013 61 Jun, 2014 96 Jun, 2015 141 Jun, 2016 131 Jul, 2013 78 Jul, 2014 81 Jul, 2015 107 Jul, 2016 150 Aug, 2013 58 Aug, 2014 70 Aug, 2015 100 Aug, 2016 124 Sep, 2013 41 Sep, 2014 50 Sep, 2015 78 Sep, 2016 103 Oct, 2013 19 Oct, 2014 35 Oct, 2015 61 Oct, 2016 102 Nov, 2013 18 Nov, 2014 54 Nov, 2015 92 Nov, 2016 102 Dec, 2013 38 Dec, 2014 57 Dec, 2015 70 Dec, 2016 101 (a) Calculate the 12 un-normalised monthly seasonal indexes for this dataset. (b) Calculate the 12 normalised monthly seasonal indexes for this dataset. (c) Fit a linear trend line to the deseasonalised data using the least squares method. Assuming t = 1 for Jan, 2013, t = 2 for Feb, 2013, etc. (d) Provide 2 unadjusted forecasts for the months of Jan, 2017 and Feb, 2017.
Provide 2 adjusted forecasts for the months of Jan, 2017 and Feb, 2017.