Regression Statistics 0.9942 0.9883 Multiple R R Square Adjusted R Square Std Err Model Observations 0.9882 61.9556 251

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Regression Statistics 0 9942 0 9883 Multiple R R Square Adjusted R Square Std Err Model Observations 0 9882 61 9556 251 1 (46.95 KiB) Viewed 24 times

Regression Statistics 0 9942 0 9883 Multiple R R Square Adjusted R Square Std Err Model Observations 0 9882 61 9556 251 2 (65.03 KiB) Viewed 24 times

Regression Statistics 0 9942 0 9883 Multiple R R Square Adjusted R Square Std Err Model Observations 0 9882 61 9556 251 3 (82.98 KiB) Viewed 24 times

Regression Statistics 0.9942 0.9883 Multiple R R Square Adjusted R Square Std Err Model Observations 0.9882 61.9556 251 1 ANOVA df SS MS F Regression 80,327,675.2 2 2677589.7 3 6975.62 Residual 247 948108.16 3838.4946 81,275,783.3 Total 250 Coefficient 8 Sid Err Term 1 Star P-value Lower 95% Upper 95% 2590.97 7.22 358,88 0.00 2576.53 2605.9105 0.87 0.06 13.87 0.00 0.7518 0.9882 Intercept Price Today Price Yesterday Price Yesterday 2 0.12 0.06 1.85 0.06 0.0018 0.2382 -0.000047 0.000018 -2.52 0.01 0.000083 0.000011

The model you made is: Price tomorrow = 2,590.97 +0.87*(Price Today) +0.12*(Price Yesterday) - 0.000047"(Price Yesterday)2 To make this model work, you have to modify the data a little bit. Your modified "Price Today" = $600. Your modified "Price Yesterday" is $598. v) What is your predicted "Price Tomorrow"? The predicted "price tomorrow" is 3167.92 vi) Assuming the “Price Tomorrow" has a 95% confidence interval of Price tomorrow +/- 2*(Std Err Model), what is the confidence interval? The confidence interval would be [3046.4882, 3289.3518) vii) If you want to short the stock, it needs to be below $3,100.00. What is the probability the stock tomorrow will meet this requirement? NCDF(0,Stock Price(short), Price Tomorrow, Std Err Model) The probability would be about 13.79% viti) Based upon this info, would you want try to short the stock tomorrow? ix) A boss heard you made a model and it "looked great!" They want to know to the dollar what the stock price will be tomorrow. Is your model good enough to give a price down to the dollar? I Why not? (HINT HINT HINT)

xi) If today's price was $3,163.00. And your estimated price for tomorrow is in xv, would you suggest to your boss that they buy or sell Amazon stock at tomorrows close? (remember, if tomorrow's price is higher, sell.) So, your boss took your advice. xii) If tomorrow's price at close is $3,200.00, is that within your confidence interval in vi? xiii) Suppose your boss bought 100,000 stock today at $3,163.00 per stock and sold them tomorrow at $3,200 per stock. How much money did your boss just make? xiv) As a way to thank you for your service, your boss gives you a 5% commission when they sell stock and it makes money, how much did you just make? xv) So, after your windfall, you want to reinvest that money into something. Potentially more AMAZON stocks. Today's end price for the stock is $3,200. When you translate this into you coded data, your new price today is $637. Price yesterday is now $600. Using your regression model above, what is your predicted stock price for tomorrow? xvi) Because you have so much more money to invest, you are still interested in possibly shorting the stock. Given that today's stock price is $3,200, any closing stock price $3,199 and below makes you money. What is the probability that the stock price drops below $3,199? NCDF(0,Stock Price(short), Price Tomorrow, Std Err Model) xvii) Would you short the stock?