please solve three sub-parts by using data in pictures c. Perform a test and discuss your findings for whether the means are statistically different from zero for the excess stock returns and the three factor returns (Mkt_RF (this is called ‘the excess market return’), SMB, HML);d. Also compute the 95% confidence interval for the means of excess stock returns and the three factor returns;e. Calculate the correlation coefficient matrix between the excess stock return and the three factor returns (Mkt_RF, SMB, HML) and the NBER recession dummy; (d)Variableobsмeanstd. Err.[95% conf. Interval]ESR275.0013146.0052003-.0089231.e115523Mkt_RFSMB276e.0064e.0028e.0009e.0119276e.0019e.0020-0.0020e.0058HML2760.00120.0020-0.00270.0050(е)ESRMkt_RFSMBHMLUSRECESR1.0000Mkt_RF0.61391.0000SMB0.08850.28701.0000HML-0.0093-0.2046 -0.25181.0000USREC-0.1062-e.06680.0887e.04061.0000 (c). ttest ESR=0one-sample t testVariableObsMeanstd. Err. std. Dev. [95% conf. Interval]ESR275.0013146.0052003.8862379-.0089231.0115523mean = mean (ESR)Ho: mean = e0.2528degrees of freedom -274Ha: mean < eHa: mean !- eHa: mean > ePr(T < t) = 0.5997Pr(|T| > It|) - 0.8006Pr(T > t) = 0.4003. ttest Mkt_RF==0one-sample t testvariableobsMeanstd. Err. std. Dev.[95% conf. Interval]Mikt_RF276.0064127.0027987 .0464961.000903.0119223mean = mean (Mkt_RF)t = 2.2913Ho: mean = edegrees of freedom -275Ha: mean < eHa: mean I.eHa: mean > ePr(T < t) = 0.9886Pr(|T| > |t|) = 0.0227Pr(T > t) - 0.0114. ttest SMB0one-sample t testvariableObsMeanstd. Err.std. Dev.[95% conf. Interval1]SMB276.0019424.001981.03291-.0019574.0058421mean- mean (SMB)t0.9805HO: mean- edegrees of freedom-275Ha: mean ePr(IT| > Itl) - 0.3277Pr(T > t) - 0.1638. ttest HML0one-sample t testvariableObsMean std. Err. std. Dev. [95% conf. Interval]HML276.0011703.0019634.0326183-.0026949.0050355t. 0.5961mean- mean (HML)HO: mean- edegrees of freedon-275Ha: mean ePr(|T| > |t|) - 0.5516Ha: mean > ePr(T > t) - 0.2758Ha: mean

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Description: please solve three sub-parts by using data in pictures c. Perform a test and discuss your findings for whether the means are statistically different from zero for the excess stock returns and the three factor returns (Mkt_RF (this is called ‘the exc

One sample t test is used to determine whether the means are statistically different from zero. The…

Answered: c. Perform a test and discuss your…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

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please solve three sub-parts by using data in pictures

c. Perform a test and discuss your findings for whether the means are statistically different from zero for the excess stock returns and the three factor returns (Mkt_RF (this is called ‘the excess market return’), SMB, HML);

d. Also compute the 95% confidence interval for the means of excess stock returns and the three factor returns;

e. Calculate the correlation coefficient matrix between the excess stock return and the three factor returns (Mkt_RF, SMB, HML) and the NBER recession dummy;

(d)
Variable
obs
мean
std. Err.
[95% conf. Interval]
ESR
275
.0013146
.0052003
-.0089231
.e115523
Mkt_RF
SMB
276
e.0064
e.0028
e.0009
e.0119
276
e.0019
e.0020
-0.0020
e.0058
HML
276
0.0012
0.0020
-0.0027
0.0050
(е)
ESR
Mkt_RF
SMB
HML
USREC
ESR
1.0000
Mkt_RF
0.6139
1.0000
SMB
0.0885
0.2870
1.0000
HML
-0.0093
-0.2046 -0.2518
1.0000
USREC
-0.1062
-e.0668
0.0887
e.0406
1.0000

(c)
. ttest ESR=0
one-sample t test
Variable
Obs
Mean
std. Err. std. Dev. [95% conf. Interval]
ESR
275
.0013146
.0052003
.8862379
-.0089231
.0115523
mean = mean (ESR)
Ho: mean = e
0.2528
degrees of freedom -
274
Ha: mean < e
Ha: mean !- e
Ha: mean > e
Pr(T < t) = 0.5997
Pr(|T| > It|) - 0.8006
Pr(T > t) = 0.4003
. ttest Mkt_RF==0
one-sample t test
variable
obs
Mean
std. Err. std. Dev.
[95% conf. Interval]
Mikt_RF
276
.0064127
.0027987 .0464961
.000903
.0119223
mean = mean (Mkt_RF)
t = 2.2913
Ho: mean = e
degrees of freedom -
275
Ha: mean < e
Ha: mean I.e
Ha: mean > e
Pr(T < t) = 0.9886
Pr(|T| > |t|) = 0.0227
Pr(T > t) - 0.0114
. ttest SMB0
one-sample t test
variable
Obs
Mean
std. Err.
std. Dev.
[95% conf. Interval1]
SMB
276
.0019424
.001981
.03291
-.0019574
.0058421
mean- mean (SMB)
t
0.9805
HO: mean- e
degrees of freedom-
275
Ha: mean <e
Pr(T < t) - 0.8362
Ha: mean t. e
Ha: mean > e
Pr(IT| > Itl) - 0.3277
Pr(T > t) - 0.1638
. ttest HML0
one-sample t test
variable
Obs
Mean std. Err. std. Dev. [95% conf. Interval]
HML
276
.0011703
.0019634
.0326183
-.0026949
.0050355
t. 0.5961
mean- mean (HML)
HO: mean- e
degrees of freedon-
275
Ha: mean e
Pr(|T| > |t|) - 0.5516
Ha: mean > e
Pr(T > t) - 0.2758
Ha: mean <e
Pr(T < t) - 0.7242

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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