Question 14 (22 points) ) Listen The Coronavirus Pandemic (2019-2021) wreaked havoc on supply chains in many business areas, including a shortage of silicon which is impacting the manufacturing of computer chips. You are a senior strategy analyst for Intel (INTC) Corporation. Your company's CEO recalls a 20-day period in the early fall of 2010 when silicon production was stifled by labor unrest. The CEO asks you to retrieve the company's stock prices for that period as well as the closing stock prices for. IBM, Cisco (CSCO), GE, as well as the Dow-Jones Industrial average (DJIA)-all for comparison purposes. The data is shown in Figure 3. Figure 3 DJ Industrials Date IBM INTC CSCO GE Index\f1:05:21 rem 9/24/2010 $134.11 $19.42 $22.09 $16.66 10860.26 9/27/2010 $134.65 $19.24 $22.11 $16.43 10812.04 9/28/2010 $134.89 $19.51 $21.86 $16.44 10858.14 9/29/2010 $135.48 $19.24 $21.87 $16.36 10835.28 9/30/2010 $134.14 $19.20 $21.90 $16.25 10788.05 10/1/2010 $135.64 $19.32 $21.91 $16.36 10829.68 Though you possess this historical data, your CEO has asked you to review it from a forecasting standpoint to provide stock price prediction, in advance of a quarterly earnings call with shareholders. Based on the random and short-duration of stock data, you will take a simple exponential smoothing forecasting approach. 1. (10 points) Due to the predictive nature of the DJIA, you develop a simple exponential smoothing forecast to compare with the actual closing value of the index over the 20-day period. Figure 4 below shows this comparison, visually. Data Point 15 on the chart shows the forecast and actual close of the DJIA on 9/24/2010. Estimate the residual for this day (9/24/2010) based on a smoothing constant of .03. Figure 4 Data Analysis Chart 10900 108004010) based on a smoothing constant Figure 4 Data Analysis Chart 10900 10800 10700 10600 10500 Value 10400 10300 10200 10100 10000 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Data Point Actual Forecast 2. (12 points) Figure 5 shows a summary of the error metrics based on three differer smoothing constants: 0.1, 0.3, and 0.5. The impetus for this work assigned by yourData Point Actual Forecast 2. (12 points) Figure 5 shows a summary of the error metrics based on three different smoothing constants: 0.1, 0.3, and 0.5. The impetus for this work assigned by your CEO was to determine the best smoothing constant for forecasting stock prices given the current computer chip shortage. Based on the results in Table 5, which smoothing constant will you select for the current forecasting effort? Explain your reasoning. Intuitively speaking, why is the chosen smoothing constant the logical choice over the other two given your simple exponential smoothing forecasting approach? Figure 5 DJ Industrials IBM INTC CSCO GE Index MAD (0.3) 1.54931 0.26775 0.2726 02215 80.884883 MSE(0.3) 2.958295 0.09797 0.1251 0.0715 9257.687 MAPE (0.3) 0.011774 0.01427 0.0127 0.0137 0.0075756 MAD (0.1) 2.752193 0.44175 0.4653 0.4258 146.74624\f