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Comprehensively state the criteria and process of selecting appropriate models for time series
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- The forecasting staff for the Prizer Corporation has developed a model to predict sales of its air-cushioned-ride snowmobiles. The model specifies that sales S vary jointly with disposable personal income Y and the population between ages 15 and 40, Z, and inversely with the price of the snowmobiles P. Based on past data, the best estimate of this relationship is S=kYZP where k has been estimated (with past data) to equal 100. If Y=11,000,Z=1,200, and P=20,000, what value would you predict for S? What happens if P is reduced to $17,500? How would you go about developing a value for k? What are the potential weaknesses of this model?Identify and briefly describe the two general forecasting approaches.A researcher has a sample of 6 annual observations {94, 104, 102, 99, 111 and 107} for the CPI in country Z for the period 2015 to 2020, and wants to forecast CPI for the years 2021, 2022 and 2023. The researcher uses 3 different forecasting models: A, B and C. Model A is an AR(1) model with no drift and with an estimated autoregressive coefficient = 0.7. Model B is a MA(1) model with no constant and with an estimated MA coefficient = -0.4 (note the minus !). Model C is a random walk model with no drift. The error terms over the 2015-2020 period were estimated to have the values: {3, -1, 2, 4, -3, 1}. a. Compute the 2021, 2022 and 2023 forecasted values for the consumer price index based on the three models. Show the formulas and the details of your calculations, and explain all the related symbols. b. Suppose that the actual values of the CPI over the 2021, 2022 and 2023 were {108, 114, 105}. Calculate the Root mean square error of the three model forecasts over the 2021-2023…
- The type of economic indicator that can best be used for business forecasting is the:The forecasting staff for the Prizer Corporation has developed a model to predict sales of its air-cushioned-ride snowmobiles. The model specifies that sales S vary jointly with disposable personal income Y and the population between ages 15 and 40, Z, and inversely with the price of the snowmobiles P. Based on past data, the best estimate of this relationship isS = k (YZ/ P)where k has been estimated (with past data) to equal 100.a. If Y = $11,000, Z = $1,200, and P = $20,000, what value would you predict for S?b. What happens if P is reduced to $17,500?c. How would you go about developing a value for k?d. What are the potential weaknesses of this model?The use of quarterly data to develop the forecasting model Yt = a +bYt-1 is an example of which forecasting technique?
- Choose one of the following forecasting methods discussed in this chapter: last-value, averaging, moving-average, or exponential smoothing. Identify the conditions when the method is most appropriate to use and give an example of an application of this method.Historical demand for Peeps is as displayed in the table. Month Demand January 11 February 18 March 31 April 39 May 44 June 53 July 67 August 82 September 96 Develop forecasts from June through October using these techniques: Holt's method with alpha=0.2 and beta=0.1. For Holt's model, the level and trend for May are assumed to be 44 and 12. Judge which forecast method is the best based on MAD.Name two coincident indicators used in forecasting
- Based on annual data from 2000-2010, the Gadget Company estimates that sales are growing according to a linear trend: Q = 50,000 + 200t where t is time and t = 0 in 2000. a. Forecast sales for 2013. b. Do you see any problems with this forecasting method?Qualitative methods of forecasting include:a) sales force composite. b) jury of executive opinion.c) consumer market survey. d) exponential smoothing.e) all except (d).A local moving company has collected data on the number of moves they have been asked to perform over the past two years. Moving is highly seasonal, so the owner/operator, who is both burly and highly educated, decides to apply the multiplicative seasonal method to forecast the number of customers for the coming year. The equation for the trend line of yearly sales is Ft = 16 + 60t. Please forecast demand for each quarter in Year 3. (Round the forecasts to whole numbers and show all calculations). Complete the table below and forecast the sales of Year 3 by quarter. Year 1 Year 2 Year 3 Quarter Demand Seasonal Index Quarter Demand Seasonal Index Average Seasonal Index Forecast 1 20 1 27 2 40 2 45 3 45 3 55 4 31 4 41 Total Average