Ten weeks of data on the Commodity Futures Index are 7.35, 7.40, 7.55, 7.56, 7.60, 7.52, 7.52, 7.70, 7.62, and 7.55. a. Construct a time series plot. What type of pattern exists in the data? b. Compute the exponential smoothing forecasts for α = .2. c. Compute the exponential smoothing forecasts for α = .3.
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. Ten weeks of data on the Commodity Futures Index are
7.35, 7.40, 7.55, 7.56, 7.60, 7.52, 7.52, 7.70, 7.62, and 7.55.
a. Construct a time series plot. What type of pattern exists in the data?
b. Compute the exponential smoothing forecasts for α = .2.
c. Compute the exponential smoothing forecasts for α = .3.
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- For the hawkins company, the monthly percentages of all shipments received on timeover the past 12 months are 80, 82, 84, 83, 83, 84, 85, 84, 82, 83, 84, and 83.a. construct a time series plot. What type of pattern exists in the data?b. compare the three-month moving average approach with the exponential smoothing approach for a = .2. Which provides more accurate forecasts using MSe as themeasure of forecast accuracy?Consider the following time series data. Week 1 2 3 4 5 6 Value 18 13 16 11 17 14 Construct a time series plot. What type of pattern exist in the data? Develop a three-week moving average for this time series. Compute MSE and forecast for week 7. Use a = 0.2 to compute the exponential smoothing values for the time series. Compute MSE and forecast for week 7.Which of the following time series forecasting methods would not be used to forecast seasonal data?
- consider the following time series data.Month 1 2 3 4 5 6 7Value 24 13 20 12 19 23 15a. compute MSe using the most recent value as the forecast for the next period. Whatis the forecast for month 8?b. compute MSe using the average of all the data available as the forecast for the nextperiod. What is the forecast for month 8?c. Which method appears to provide the better forecast?After its move in 1990 to La Junta, Colorado, and its new initiatives, the DeBourgh Manufacturing Company began an upward climb of record sales. Suppose the figures shown here are the DeBourgh monthly sales figures from January 2001 through December 2009 (in $1,000s). a) Produce a time series plot. Are there any trends evident in the data? Does DeBourgh have a seasonal component to its sales? b) Deseasonalize the data using Multiplicative model with a 0.5 weighted moving average. Produce a time series plot of the deseasonalized data and add a trendline. c) Forecast the sales from January to December of the year 2010. d) Include a discussion of the general direction of sales and any seasonal tendencies that might be occurrinG Month 2001 2002 2003 2004 2005 2006 2007 2008 2009 January 139.7 165.1 177.8 228.6 266.7 431.8 381 431.8 495.3 February 114.3 177.8 203.2 254 317.5 457.2 406.4 444.5 533.4 March 101.6 177.8 228.6 266.7 368.3 457.2 431.8 495.3 635 April 152.4 203.2…The following ratio-to-moving averages for the seasonally adjusted series were found by the decomposition method applied on a time series representing quarterly sales for January 2018 to December 2020 period: a. Calculate the Seasonal Index for every quarter. b. If the trend is described by the trend line T^ = 1,000 + 30 t, what is the forecast for the fourth quarter of 2021?
- consider the following time series data.t 1 2 3 4 5 6 7yt10 9 7 8 6 4 4a. construct a time series plot. What type of pattern exists in the data?b. develop the linear trend equation for this time series.c. What is the forecast for t = 8?Using excel. For the Hawkins Company, the monthly percentages of all shipments received on time over the past 12 months are 80, 82, 84, 83, 83, 84, 85, 84, 82, 83, 84, and 83. a. Construct a time series plot. What type of pattern exists in the data? b. Compare the three-month moving average approach with the exponential smoothing approach for α=\alpha =α= .2. Which provides more accurate forecasts using MSE as the measure of forecast accuracy? c. What is the forecast for next month?Look at the four plots in Figure 14.2—the US unemployment rate, thedollar-pound exchange rate, the logarithm of the index of industrial production, and the percentage change in stock prices. Which of these seriesappears to be non-stationary? Which of them appears to resemble a randomwalk?
- Suppose the following are the seasonal indices for the first three quarters of the year for a quarterly series: Quarter Seasonal Index Q1 73.9 Q2 84.1 Q3 107.1 Remember that the seasonal indices should average 100 so you should be able to infer the seasonal index for Q4. Furthermore, suppose that the estimated coeffcients from a regression of the deseasonalized series on Time are given below: Coefficients Intercept 2,964 Time 50.7 What is the trend projection of the series for period 119? (please round your answer to 1 decimalThe dataset in the below table represents the 3-month profits (in million $) of real estate companythat operates over the period of time between 2014-2018. I II III 2014 15.6 20.4 29.4 2015 13.8 23.2 35 2016 17.8 19.4 30.6 2017 21.4 24.8 33.6 2018 18.4 27.2 34.2 Predict the expected value of company’s profit in summer 2019 which includes the effects of allthe components of time series. And comment on the results.Below you are given the first five values of a quarterly time series. The multiplicative model is appropriate and a four-quarter moving average will be used. Year Quarter Time Series Value Yt 1 1 36 2 24 3 16 2 4 20 1 44 An estimate of the combined trend-cycle component (T2Ct) for Quarter 3 of Year 1 (used for estimating the de-trended values), when a four-quarter moving average is used, is a. 24. b. 26. c. 28. d. 25.