Business Finance
BUS660 Grand Canyon Forecasts and Error Analysis Spreadsheet

BUS660

Grand Canyon University

Question Description

What is the best model for forecasting and why? How do I determine what Alpha and Beta to use of the the Trending Adj Exponential smoothing model? I attached the assignment spreadsheets and the word doc instructions.

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Forecasting Case Study: New Business Planning Important Note: Students must access the “Entrepreneurship and the U.S. Economy” page of the Bureau of Labor Statistics website in order to complete this assignment. Scenario The generation of new business start-up is vital to the growth of the economy as it builds new jobs and creates new opportunities for the community. The Bureau of Labor Statistics tracks new business development and jobs created on the website for the United States Department of Labor. You have been tasked with forecasting economic growth and decline patterns for new businesses in the United States. Forecasting Access the “Entrepreneurship and the U.S. Economy” page of the Bureau of Labor Statistics website. Under the "Business establishment age" heading, the first chart reviews new businesses less than 1 year old during the March 1994 to March 2015 period. Click on the [Chart data] link below the chart: Once the chart data window opens, you will see the number of establishments that are less than 1 year old for each year during this period: Using the five most recent years and the "Forecasting Template" spreadsheet provided, complete the forecasts for the next two periods and provide updated Totals and Average Bias, median absolute deviation (MAD), mean squared error (MSE), and mean absolute percentage error (MAPE) for all four charts. Provide a Summary Page in Excel with a 500-750 word report on the analysis completed by the forecasting models. Include review of error, recommendations on the best forecasting model to use, and analysis of the business trend data for new business startup in the United States. 2 Forecasting Num pds Moving averages - 2 period moving average 2 Period 2011 2012 2013 2014 2015 Actuals Establishments 582,569.00 631,817.00 629,078.00 652,780.00 679,072.00 2016 2017 Forecast 665,926.00 672,499.00 Forecast Forecasts and Error Analysis Error Absolute Squared Abs % Err 607,193.00 630,447.50 640,929.00 Total Average 21,885.00 22,332.50 38,143.00 82,360.50 27,453.50 Bias 21,885.00 22,332.50 38,143.00 82,360.50 27,453.50 MAD 478,953,225.00 498,740,556.25 1,454,888,449.00 2,432,582,230.25 810,860,743.42 MSE 3.48% 3.42% 5.62% 12.52% 4.17% MAPE 672,499.00 Average (6,573.00) 6,573.00 17,967.50 22,349.50 Bias MAD 43,204,329.00 665,611,111.42 MSE 0.99% 3.34% MAPE Forecasting 700,000.00 680,000.00 660,000.00 before period 6 forecast after period 6 forecast Value 640,000.00 620,000.00 600,000.00 580,000.00 560,000.00 540,000.00 520,000.00 1 2 3 4 Time Establishments Forecast 5 Forecasting Num pds Moving averages - 3 period moving average 3 Period 2011 2012 2013 2014 2015 Actuals Establishments 582,569.00 631,817.00 629,078.00 652,780.00 679,072.00 2016 2017 Forecast 653,643.33 661,831.78 Forecast Forecasts and Error Analysis Error Absolute Squared Abs % Err 614,488.00 637,891.67 Total Average 38,292.00 38,292.00 1,466,277,264.00 5.87% 41,180.33 41,180.33 1,695,819,853.44 6.06% 79,472.33 79,472.33 3,162,097,117.44 11.93% 39,736.17 39,736.17 1,581,048,558.72 5.97% Bias MAD MSE MAPE 661,831.78 Average (8,188.44) 8,188.44 67,050,622.42 1.25% 16,495.94 24,684.39 881,435,237.93 3.66% Bias MAD MSE MAPE Forecasting 700,000.00 680,000.00 660,000.00 after period 6 forecast Value 640,000.00 620,000.00 600,000.00 580,000.00 560,000.00 540,000.00 520,000.00 1 2 3 4 Time Establishments Forecast 5 Forecasting Alpha Period 2011 2012 2013 2014 2015 0.7 Actuals Establishments 582,569.00 631,817.00 629,078.00 652,780.00 679,072.00 Exponential smoothing Forecast 582,569.00 582,569.00 617,042.60 625,467.38 644,586.21 Total Average Forecasts and Error Analysis Error Absolute Squared Abs % Err 0 0 0 0.00% 49,248.00 49,248.00 2,425,365,504.00 7.79% 12,035.40 12,035.40 144,850,853.16 1.91% 27,312.62 27,312.62 745,979,211.26 4.18% 34,485.79 34,485.79 1,189,269,436.04 5.08% 123,081.81 123,081.81 4,505,465,004.46 18.97% 24,616.36 24,616.36 901,093,000.89 3.79% Bias MAD MSE MAPE SE 38,753.34 Forecasting 700,000.00 680,000.00 660,000.00 Value 640,000.00 620,000.00 600,000.00 580,000.00 560,000.00 540,000.00 520,000.00 1 2 3 Time 582,569.00 582,569.00 4 Forecasting Trend adjusted exponential smoothing Alpha Beta 0.7 0.3 Actuals Period 2011 2012 2013 2014 2015 Establishments 582,569.00 631,817.00 629,078.00 652,780.00 679,072.00 Next period 674,028.87 Next period Forecasts and Error Analysis Smoothed Forecast, Ft 582,569.00 582,569.00 617,042.60 628,570.00 648,726.30 674,028.87 Total Average Smoothed Trend, Tt 679,148.51 Total Average 1,535.89 0.00 10,342.08 10,697.68 13,535.26 17,065.45 Forecast Including Trend, FITt 582,569.00 582,569.00 627,384.68 639,267.68 662,261.57 691,094.33 680,684.40 Error 0.00 49,248.00 1,693.32 13,512.32 16,810.43 Absolute 0.00 49,248.00 1,693.32 13,512.32 16,810.43 81,264.07 16,252.81 Bias 81,264.07 16,252.81 MAD SE (6,655.53) 74,608.54 12,434.76 Bias 6,655.53 87,919.60 14,653.27 MAD SE nalysis Forecasting 700,000.00 0.00 2,425,365,504.00 2,867,332.62 182,582,759.35 282,590,606.95 Abs % Err 0.00% 7.79% 0.27% 2.07% 2.48% 2,893,406,202.92 12.61% 578,681,240.58 2.52% MSE MAPE 31,055.90 44,296,044.40 0.99% 2,937,702,247.32 13.60% After forecast 489,617,041.22 2.27% MSE MAPE 54,200.57 680,000.00 660,000.00 640,000.00 Value Squared 620,000.00 600,000.00 580,000.00 560,000.00 540,000.00 520,000.00 1 2 3 4 Time Establishments Smoothed Forecast, Ft 4 thed Forecast, Ft 5 ...
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Final Answer

Hi,The value of alpha and eta is chosen such that the MAPE is minimum.It is generally checked using solver where we have to set the objective function of error being minimum and varying the two variables that is alpha and beta.Using this technique you can choose optimal value of alpha and beta.Otherwise,you can take value of alpha and beta manually by inputting different values so that the MAPE is shown to be minimum.I am attaching two files.One word file and other excel sheet where wrote the summary done in Excel.I think excel work was already done,so I included the writ up part.Let me know if you face any doubt.

The aim of the paper is to forecast the total establishment which is less than 1 year. In order
to predict the number of new establishments, different forecasting techniques were employed.
A line chart of the number of the establishment from 1994 till 2015 shows that the number of
establishments increased till 2006 which then started declining. Because of economic
recession, it seems that the number of new establishments started decreasing till 2010.
However, after 2010 new establishments again started to increase. The different forecasting
technique includes forecasting using two-period moving average, three-period moving
average, exponential smoothing and trend adjusted exponential smoothing method. The
forecasting technique is based on the most recent years (2011-2015) for forecasting the
number of establishments for next two period, i.e. 2016 and 2017.
Two-Period Moving Average
Forecasting using two-period moving average is based on predicting the new establishments
considering the average of the two most recent years. Using this metho...

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