Assignment

Question 1

Solution

Dependent Variable: RP_MS
Method: Least Squares
Date: 09/19/18   Time: 15:21
Sample: 1998M01 2008M12
Included observations: 132
Variable	Coefficient	Std. Error	t-Statistic	Prob.
C	0.006098	0.007747	0.787109	0.432651
RP_MKT	1.318947	0.16079	8.202908	1.98E-13
R-squared	0.341064	Mean dependent var	0.005881
Adjusted R-squared	0.335995	S.D. dependent var	0.109224
S.E. of regression	0.089003	Akaike info criterion	-1.98527
Sum squared resid	1.029792	Schwarz criterion	-1.94159
Log likelihood	133.0275	Hannan-Quinn criter.	-1.96752
F-statistic	67.28771	Durbin-Watson stat	2.34505
Prob(F-statistic)	1.98E-13

RP_MS= 0.006098 + 1.318947 RP_MKT                         

 S.E     (0.0077)    (0.1608)

R-squared = 0.341064

Some screenshots:

Question 2

Solution

The RP_MKT has increased by 1% and so the RP_MS increases by 1.32 %

(as RP_MS= 0.006098 + 1.318947 RP_MKT                          )

Question 3

Solution

We assume as α = 0.05. Following hypothesis Ho: α’ = 0 & H1: α’ <> 0. We know that if p< α we reject the null hypothesis

t = (α – α’)/SE(α’) = (0.0061 -0)/0.0077= 0.72

α’ (t=0.72) does not lie in the rejection side and so null hypothesis is accepted.

Question 4

Answer:

We assume as α = 0.05. Following hypothesis Ho: Bi = 0 & H1: Bj <> 0. We know that if p< α we reject the null hypothesis

t = (Bi– Bj)/SE(Bj) = (1.319 -0)/0.161= 8.2

Since t  is now in the rejection region so we reject the Null Hypothesis.

Question 5

Answer:

We assume as α = 0.05. Following hypothesis Ho: Bi >1 & H1: Bj <= 1. We know that if p< α we reject the null hypothesis

t = (Bi– Bj)/SE(Bj) = (1.319 – 1)/0.161= 1.98

Since t is now in the rejection region so we reject the Null Hypothesis as shown in the below figure:

Question 6

Answer: The r squared  = 0.411. this can be interpreted as 34.11 % variations with respect to (Y) RP_MS over the mean value.  

Question 7

Answer:

Y=B_i + B_j+e

r_j – r_f = α’ + B_j (r_m – r_j)

• rj  – 0.000025 = 0.0061 + 1.3159 (0.0215*7% – 0.000025)
•  rj  – 0.000025 = 0.0061 + 0.029
• rj  = 0.0347 = 3.47 %

Question 8

Answer:

Dependent Variable: RP_GE
Method: Least Squares
Date: 09/19/18   Time: 15:47
Sample: 1998M01 2008M12
Included observations: 132
Variable	Coefficient	Std. Error	t-Statistic	Prob.
C	-0.00117	0.004759	-0.24519	0.806692
RP_MKT	0.89926	0.098782	9.103512	1.33E-15
R-squared	0.38931	Mean dependent var	-0.00131
Adjusted R-squared	0.384612	S.D. dependent var	0.069702
S.E. of regression	0.054679	Akaike info criterion	-2.95964
Sum squared resid	0.388672	Schwarz criterion	-2.91596
Log likelihood	197.3363	Hannan-Quinn criter.	-2.94189
F-statistic	82.87393	Durbin-Watson stat	2.239423
Prob(F-statistic)	1.33E-15

RP_GE = -0.00117+ 0.89926 RP_MKT

 S.E: =        (0.0048)   (0.0988)

R-square = 0.38931

Dependent Variable: RP_GM
Method: Least Squares
Date: 09/19/18   Time: 15:51
Sample: 1998M01 2008M12
Included observations: 132
Variable	Coefficient	Std. Error	t-Statistic	Prob.
C	-0.01155	0.009743	-1.18547	0.237992
RP_MKT	1.261411	0.202223	6.237709	5.77E-09
R-squared	0.230355	Mean dependent var	-0.01176
Adjusted R-squared	0.224435	S.D. dependent var	0.127106
S.E. of regression	0.111937	Akaike info criterion	-1.52672
Sum squared resid	1.628896	Schwarz criterion	-1.48304
Log likelihood	102.7635	Hannan-Quinn criter.	-1.50897
F-statistic	38.90901	Durbin-Watson stat	2.062907
Prob(F-statistic)	5.77E-09

RP_GM = -0.0155 + 1.2614 RP_MKT

S.E           (0.0097)  (0.2022)

R-squared = 0.2303

Dependent Variable: RP_IBM
Method: Least Squares
Date: 09/19/18   Time: 15:53
Sample: 1998M01 2008M12
Included observations: 132
Variable	Coefficient	Std. Error	t-Statistic	Prob.
C	0.005851	0.006091	0.960574	0.33855
RP_MKT	1.188208	0.126433	9.397948	2.52E-16
R-squared	0.404548	Mean dependent var	0.005656
Adjusted R-squared	0.399967	S.D. dependent var	0.090347
S.E. of regression	0.069985	Akaike info criterion	-2.46604
Sum squared resid	0.636722	Schwarz criterion	-2.42237
Log likelihood	164.7589	Hannan-Quinn criter.	-2.4483
F-statistic	88.32143	Durbin-Watson stat	2.171986
Prob(F-statistic)	2.52E-16

RP_IBM = 0.0058 + 1.1882 RP_MKT

S.E        (0.0061)     (0.1264)

R-square = 0.4045

Dependent Variable: RP_DISNEY
Method: Least Squares
Date: 09/19/18   Time: 15:55
Sample: 1998M01 2008M12
Included observations: 132
Variable	Coefficient	Std. Error	t-Statistic	Prob.
C	-0.00115	0.005956	-0.19298	0.847279
RP_MKT	0.897838	0.123627	7.262477	3.11E-11
R-squared	0.288621	Mean dependent var	-0.0013
Adjusted R-squared	0.283149	S.D. dependent var	0.080824
S.E. of regression	0.068432	Akaike info criterion	-2.51093
Sum squared resid	0.608775	Schwarz criterion	-2.46725
Log likelihood	167.7212	Hannan-Quinn criter.	-2.49318
F-statistic	52.74358	Durbin-Watson stat	2.426356
Prob(F-statistic)	3.11E-11

RP_DISNEY = -0.00115 + 0.89783 RP_MKT
  S.E                (0.00595)      (0.1236)

R-square = 0.288621

Dependent Variable: RP_MEX
Method: Least Squares
Date: 09/19/18   Time: 15:57
Sample: 1998M01 2008M12
Included observations: 132
Variable	Coefficient	Std. Error	t-Statistic	Prob.
C	0.00788	0.004322	1.823133	0.070581
RP_MKT	0.413969	0.089713	4.614357	9.33E-06
R-squared	0.140736	Mean dependent var	0.007812
Adjusted R-squared	0.134126	S.D. dependent var	0.053367
S.E. of regression	0.049659	Akaike info criterion	-3.15223
Sum squared resid	0.320585	Schwarz criterion	-3.10855
Log likelihood	210.0471	Hannan-Quinn criter.	-3.13448
F-statistic	21.29229	Durbin-Watson stat	2.348331
Prob(F-statistic)	9.33E-06

RP_MEX = 0.00788 + 0.413969 RP_MKT

S.E              (0.0043)    (0.0897)

R-square = 0.140736

Appendix:

Eviews output