Question

Problem 2.2: Linear Regression. Suppose that I am trying to estimate Starbucks stock price with a linear regression model. The Day and Volume are being used as my X1 and X2. a) Calculate the forecast for November 1 if Volume is 8000 b) Should I be using both Day and Volume as predictors of stock price? (Use Regression result output below) c) Does the data truly have a downward trend? How could I prove it from the Regression result output? Starbucks Stock Price $86.36 $86.62 Volume (in 10003) 5,622 4,937 4,723 3,707 4,398 4,631 $86.45 $86.71 $86.29 $86.03 5,007 Date Day 10/11/2019 1 10/14/2019 2 10/15/2019 10/16/2019 10/17/2019 10/18/2019 6 10/21/2019 | 7 10/22/2019 8 10/23/20199 10/24/2019 10 10/25/2019 11 10/28/2019 12 10/29/2019 13 10/30/2019 14 10/31/2019 15 $85.35 $83.46 5,807 7,187 4,633 5,235 $82.74 $83.18 $83.38 6,653 5,699 8,731 14,009 $83.60 $84.13 $84.19 $84.56

Answer 1

a)

From the Given table, Just look at the Coefficient value for various data,

For Intercept, Coefficient is 86.32

For Day, Coefficient is -0.303

For Volume, Coefficient is 0.00016,

Hence, Regression Equation for Stock Price = Intercept -0.303*Day+0.00016*Volume,

As, for November 1, Day = 16 and Volume = 8000,

Hence, Stock Price = 86.32+(-0.303*16)+(0.00016*8000)

Stock Price =82.752

b)

Here, we will look at P value, as P value for Day is 0.002 less than 0.05 or alpha value, hence, it is statistically significant, or Day can be used as predictor of stock price, again, P value for Volume is 0.2525 that is more than alpha value or 0.05, hence, it is statistically insignificant and Volume is not predictor of stock price,

c)

Yes, the data has downward trend, here, looking at the coefficient value of Day that is here negative, hence, we can conclude that Day value will increase and Stock price will decrease, The Regression equation as follows: Stock Price = Intercept -0.303*Day+0.00016*Volume,