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Using this data constructed below and the linear regression line produced when estimating the parameters associated with the capital asset pricing model for Asset Y, complete the tasks in the pictures below.  data constructed Year T Excess return on Asset Y

Using this data constructed below and the linear regression line produced when estimating the parameters associated with the capital asset pricing model for Asset Y, complete the tasks in the pictures below.  data constructed Year T Excess return on Asset Y

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Using this data constructed below and the linear regression line produced when estimating the parameters associated with the capital asset pricing model for Asset Y, complete the tasks in the pictures below. 

data constructed

Year T

Excess return on Asset Y

Excess return on Market Xt

X2 t

Xt Yt

1

19.2

11

121

211.2

2

44.8

22.2

492.84

994.56

3

7.1

0.8

0.64

5.68

4

12.5

5.6

31.36

70

5

15.7

6.9

47.61

108.33

 

 

 

∑X2t = 693.45

∑ Xt Yt = 1389.77

 

Task Two Complete the values in the table below: X (X minus the mean of X) Sum (X minus the mean of X)¹ Calculate the standard errors for the estimated parameters: Standard error of (B₁) = Standard error of (Bo) vΣ(Χ. – Χ.)2 X² Σ(Χ.)2 ΤΧΣ(Χ -Χ.)2 Task Three Calculate a t-statistic for each of the coefficients. Using a 0.05 level of significance, decide if you can reject the null hypothesis for each estimated parameter. Once you have completed the above tasks, put the content together in a narrative I
Transcribed Image Text:Task Two Complete the values in the table below: X (X minus the mean of X) Sum (X minus the mean of X)¹ Calculate the standard errors for the estimated parameters: Standard error of (B₁) = Standard error of (Bo) vΣ(Χ. – Χ.)2 X² Σ(Χ.)2 ΤΧΣ(Χ -Χ.)2 Task Three Calculate a t-statistic for each of the coefficients. Using a 0.05 level of significance, decide if you can reject the null hypothesis for each estimated parameter. Once you have completed the above tasks, put the content together in a narrative I
Asset Y, complete the tasks below. You will recall that you are interested in the following: E(R) - rf B(E(Rm) - rf) Bo+B1(X) Y These are the hypotheses: equals E(R) - rf equals E(Rm) - rf equals & the estimate of riskiness Actual value for excess return for Asset Ho B₁ = 0 versus H₂ B₁ 0 Ho: Po = 0 versus H₂ : Bo 0 Task One Using the data from the previous activity, complete the table below: Excess return on Market X Fitted value for excess return for Asset Y Sum Calculate the sample variance. Estimated residual squared
Transcribed Image Text:Asset Y, complete the tasks below. You will recall that you are interested in the following: E(R) - rf B(E(Rm) - rf) Bo+B1(X) Y These are the hypotheses: equals E(R) - rf equals E(Rm) - rf equals & the estimate of riskiness Actual value for excess return for Asset Ho B₁ = 0 versus H₂ B₁ 0 Ho: Po = 0 versus H₂ : Bo 0 Task One Using the data from the previous activity, complete the table below: Excess return on Market X Fitted value for excess return for Asset Y Sum Calculate the sample variance. Estimated residual squared
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