I need the questions answered and show the calculations. This is for the company called GameStop which is a gaming company. I can afford 35.00 and that's it. I am a college student and I am pretty poor lol. The hardest part is just creating a graph and forecast the next year stock using regression analysis. This website will get you started..http://finance.yahoo.com/q?s=GME

Show all work. Thank You and happy holidays. A tutor did this assignment but for Apple which was NOT what I was asking for.

Please do for the company called GAMESTOP only....

a. For you to decide if a corporation's stock is a good buy or sell, you must forecast several key variables, including the stock price. i. Use historical prices (5 years of monthly data recommended) and forecast the stock price for the next year. Use regression analysis, and/or moving average, etc. to create your forecast. ii. Create a graph from the historical data and show your forecast on the same graph. You can add a trend line to the graph to help you with a forecast. Include the graph in your report. iii. You need to say specifically what the forecasted value of the stock price is. iv. You must address the question, \"Is this forecast reasonable?\" Must you amend your analysis to get a more reasonable forecast? a. For you to decide if a corporation's stock is a good buy or sell, you must forecast several key variables, including the stock price. i. Use historical prices (5 years of monthly data recommended) and forecast the stock price for the next year. Use regression analysis, and/or moving average, etc. to create your forecast. ii. Create a graph from the historical data and show your forecast on the same graph. You can add a trend line to the graph to help you with a forecast. Include the graph in your report. iii. You need to say specifically what the forecasted value of the stock price is. iv. You must address the question, \"Is this forecast reasonable?\" Must you amend your analysis to get a more reasonable forecast? Forecast by Moving Average Apple's stock is chosen to do the analysis, Moving Average gives average of past three values as forecast to the next period Moving Average 140 120 100 80 60 Value 40 20 0 f(x) = 1.43x + 33.1 Actual Forecast Linear (Forecast) Data Point In our case Forecasted Value Of Apple's stock for next month is by moving average is $ 117 and current price is $ 116 therefore Apple stock price is poised to increase next month,. Forecast by regression SUMMARY OUTPUT Regression Statistics Multiple R 0.881683 R Square 0.777365 Adjusted R Square 0.773592 Standard Error 12.39516 Observation s 61 ANOVA df Regression 1 Residual Total Intercept Time in Months 59 60 Coefficien ts 41.11788 1.293744 SS 31651.0 3 9064.76 1 40715.7 9 Standard Error 3.13544 4 0.09013 8 MS 31651. 03 F 206.00 77 Significan ce F 6.63E-21 153.64 t Stat 13.113 89 14.352 97 P-value 3.9E-19 6.63E21 Lower 95% 34.84387 1.113378 Upper 95% 47.391 89 1.4741 09 Lower 95.0% 34.843 87 1.1133 78 Upper 95.0% 47.391 89 1.4741 09 Regression equation St = 1.29*time in Months + 41.11 Apple's stock price by regression equation is $ 120.36 current price is $ 116 therefore Apple stock price is poised to increase next month. We can observe that R square value of regression model is 0.77 which implies 77% variation in Apple's stock can be explained with trend along the time, thus frequency of forecast is reasonable. Date 13/12/201 3/1/2011 1/2/2011 1/3/2011 1/4/2011 2/5/2011 1/6/2011 1/7/2011 1/8/2011 1/9/2011 ### ### ### 3/1/2012 1/2/2012 1/3/2012 2/4/2012 1/5/2012 1/6/2012 2/7/2012 1/8/2012 4/9/2012 ### ### ### 2/1/2013 1/2/2013 1/3/2013 1/4/2013 1/5/2013 3/6/2013 1/7/2013 1/8/2013 3/9/2013 ### ### ### 2/1/2014 3/2/2014 3/3/2014 1/4/2014 1/5/2014 2/6/2014 1/7/2014 1/8/2014 2/9/2014 ### ### ### 2/1/2015 2/2/2015 2/3/2015 1/4/2015 1/5/2015 1/6/2015 1/7/2015 3/8/2015 1/9/2015 ### ### ### Apple Adj Time in Months 42.90576 0 45.13511 1 46.98271 2 46.35753 3 46.57302 4 46.26708 5 44.6496 6 51.94023 7 51.18869 8 50.7218 9 53.84236 10 50.83885 11 53.87162 12 60.7193 13 72.1534 14 79.74995 15 77.67889 16 76.84754 17 77.68156 18 81.24107 19 88.86772 20 89.1162 21 79.52729 22 78.54318 23 71.41594 24 61.12567 25 59.58004 26 59.75012 27 59.76631 28 61.10623 29 53.87778 30 61.48667 31 66.63722 32 65.20522 33 71.48982 34 76.49787 35 77.17883 36 68.86693 37 72.82753 38 74.28065 39 81.66387 40 88.09158 41 90.52836 42 93.12936 43 100.3477 44 98.63445 45 105.7322 46 116.9376 47 108.5308 48 115.1972 49 126.8064 50 122.8283 51 123.539 52 129.1402 53 124.3326 54 120.2387 55 112.2794 56 109.8299 57 118.9907 58 118.3 59 116.17 60 ForecastMoving Average SUMMARY OUTPUT #N/A #N/A Regression Statistics 45.00786 Multiple R 0.881683 46.15845 R Square 0.777365 46.63775 Adjusted R 0.773592 46.39921 Standard Er 12.39516 45.8299 Observatio 61 47.61897 49.25951 ANOVA 51.28357 df SS MS F Significance F 51.91762 Regression 1 31651.03 31651.03 206.0077 6.63E-21 51.801 Residual 59 9064.761 153.64 52.85094 Total 60 40715.79 55.14326 62.24811 Coefficient Standard Er Stat t P-value Lower 95%Upper 95%Lower 95.0Upper 95.0% 70.87422 Intercept 41.11788 3.135444 13.11389 3.90E-19 34.84387 47.39189 34.84387 47.39189 76.52741 Time in Mo 1.293744 0.090138 14.35297 6.63E-21 1.113378 1.474109 1.113378 1.474109 78.09213 77.40266 Stock Price t = 61 120.0362 78.59006 82.59678 86.40833 85.83707 82.39555 76.49547 70.36159 64.04055 60.15194 59.69882 60.20755 58.25011 58.82356 60.66722 64.44304 67.77742 71.0643 75.05551 74.18121 72.95776 71.9917 76.25735 81.34537 86.76127 90.5831 94.66847 97.3705 101.5715 107.1014 110.4002 113.5552 116.8448 121.6106 124.3912 125.1692 125.6706 124.5705 118.9502 114.116 113.7 115.7068 117.8202 a. For you to decide if a corporation's stock is a good buy or sell, you must forecast several key variables, including the stock price. i. Use historical prices (5 years of monthly data recommended) and forecast the stock price for the next year. Use regression analysis, and/or moving average, etc. to create your forecast. ii. Create a graph from the historical data and show your forecast on the same graph. You can add a trend line to the graph to help you with a forecast. Include the graph in your report. iii. You need to say specifically what the forecasted value of the stock price is. iv. You must address the question, \"Is this forecast reasonable?\" Must you amend your analysis to get a more reasonable forecast? Forecast by Moving Average Apple's stock is chosen to do the analysis, Moving Average gives average of past three values as forecast to the next period Moving Average 140 120 100 80 60 Value 40 20 0 f(x) = 1.43x + 33.1 Actual Forecast Linear (Forecast) Data Point In our case Forecasted Value Of Apple's stock for next month is by moving average is $ 117 and current price is $ 116 therefore Apple stock price is poised to increase next month,. Forecast by regression SUMMARY OUTPUT Regression Statistics Multiple R 0.881683 R Square 0.777365 Adjusted R Square 0.773592 Standard Error 12.39516 Observation s 61 ANOVA df Regression 1 Residual Total Intercept Time in Months 59 60 Coefficien ts 41.11788 1.293744 SS 31651.0 3 9064.76 1 40715.7 9 Standard Error 3.13544 4 0.09013 8 MS 31651. 03 F 206.00 77 Significan ce F 6.63E-21 153.64 t Stat 13.113 89 14.352 97 P-value 3.9E-19 6.63E21 Lower 95% 34.84387 1.113378 Upper 95% 47.391 89 1.4741 09 Lower 95.0% 34.843 87 1.1133 78 Upper 95.0% 47.391 89 1.4741 09 Regression equation St = 1.29*time in Months + 41.11 Apple's stock price by regression equation is $ 120.36 current price is $ 116 therefore Apple stock price is poised to increase next month. We can observe that R square value of regression model is 0.77 which implies 77% variation in Apple's stock can be explained with trend along the time, thus frequency of forecast is reasonable. Date 13/12/201 3/1/2011 1/2/2011 1/3/2011 1/4/2011 2/5/2011 1/6/2011 1/7/2011 1/8/2011 1/9/2011 ### ### ### 3/1/2012 1/2/2012 1/3/2012 2/4/2012 1/5/2012 1/6/2012 2/7/2012 1/8/2012 4/9/2012 ### ### ### 2/1/2013 1/2/2013 1/3/2013 1/4/2013 1/5/2013 3/6/2013 1/7/2013 1/8/2013 3/9/2013 ### ### ### 2/1/2014 3/2/2014 3/3/2014 1/4/2014 1/5/2014 2/6/2014 1/7/2014 1/8/2014 2/9/2014 ### ### ### 2/1/2015 2/2/2015 2/3/2015 1/4/2015 1/5/2015 1/6/2015 1/7/2015 3/8/2015 1/9/2015 ### ### ### Apple Adj Time in Months 42.90576 0 45.13511 1 46.98271 2 46.35753 3 46.57302 4 46.26708 5 44.6496 6 51.94023 7 51.18869 8 50.7218 9 53.84236 10 50.83885 11 53.87162 12 60.7193 13 72.1534 14 79.74995 15 77.67889 16 76.84754 17 77.68156 18 81.24107 19 88.86772 20 89.1162 21 79.52729 22 78.54318 23 71.41594 24 61.12567 25 59.58004 26 59.75012 27 59.76631 28 61.10623 29 53.87778 30 61.48667 31 66.63722 32 65.20522 33 71.48982 34 76.49787 35 77.17883 36 68.86693 37 72.82753 38 74.28065 39 81.66387 40 88.09158 41 90.52836 42 93.12936 43 100.3477 44 98.63445 45 105.7322 46 116.9376 47 108.5308 48 115.1972 49 126.8064 50 122.8283 51 123.539 52 129.1402 53 124.3326 54 120.2387 55 112.2794 56 109.8299 57 118.9907 58 118.3 59 116.17 60 ForecastMoving Average SUMMARY OUTPUT #N/A #N/A Regression Statistics 45.00786 Multiple R 0.881683 46.15845 R Square 0.777365 46.63775 Adjusted R 0.773592 46.39921 Standard Er 12.39516 45.8299 Observatio 61 47.61897 49.25951 ANOVA 51.28357 df SS MS F Significance F 51.91762 Regression 1 31651.03 31651.03 206.0077 6.63E-21 51.801 Residual 59 9064.761 153.64 52.85094 Total 60 40715.79 55.14326 62.24811 Coefficient Standard Er Stat t P-value Lower 95%Upper 95%Lower 95.0Upper 95.0% 70.87422 Intercept 41.11788 3.135444 13.11389 3.90E-19 34.84387 47.39189 34.84387 47.39189 76.52741 Time in Mo 1.293744 0.090138 14.35297 6.63E-21 1.113378 1.474109 1.113378 1.474109 78.09213 77.40266 Stock Price t = 61 120.0362 78.59006 82.59678 86.40833 85.83707 82.39555 76.49547 70.36159 64.04055 60.15194 59.69882 60.20755 58.25011 58.82356 60.66722 64.44304 67.77742 71.0643 75.05551 74.18121 72.95776 71.9917 76.25735 81.34537 86.76127 90.5831 94.66847 97.3705 101.5715 107.1014 110.4002 113.5552 116.8448 121.6106 124.3912 125.1692 125.6706 124.5705 118.9502 114.116 113.7 115.7068 117.8202