Stock Return Analysis

Stock Analysis 1
STOCK RETURN ANALYSIS
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Stock Analysis 2
Stock Return Analysis
Task A: Downloading the Dataset
The data was obtained from the links provided by the lecturer.
Task B: Hypothesis Testing of Means and Variance equality
1. Returns Computation and Normality test
Jarque-Berra test of normality is based on the following hypothesis:
H0: X N (μ, σ 2); The series is normally distributed (Das and Imon 2016)
H1: The series is not normally distributed.
The test statics is given as:
JB= n
6 ( S2 + K2
4 )
Where:
S – the sample skewness
K- sample excess kurtosis (excess kurtosis minus 3)
n – the number of non-missing values in the data sample
The JB statistic has an asymptotic Chi-square distribution with two degrees of
freedom under the null hypothesis
JB χ v=2 ,α
2 v – is the degrees of freedom and α – significance level.
From excel calculations the following values are obtained for the Boeing and GD
stocks
Table 1: Jarque-Berra Normality Tests
Statistic Boeing GD
S -0.0522 -0.4964
K -1.3457 -0.9752
N 60 60
JB 4.5545 4.8414
χ v=2 , α =0.05
2
5.9915 5.9915
Source: Author (2019)

Stock Analysis 3
The calculated JB for Boeing return is 4.5545 less than 5.9915 implying that at
95% level of significance the Boeing return sampling distribution is normally
distributed. Similarly, the calculated JB for GD return is 4.8414 less than 5.9915
implying that at 95% level of significance the GD return sampling distribution is
normally distributed.
2. Hypothesis testing of a single population mean (μ)
The hypothesis testing takes the following steps.
Hypothesis under test:
Ho: μ = 2.8% against H1: μ ≠ 2.8%
Significance level = 0.05.
Test statistic: One sample t-tests given as
tcalc .= √n ( X−μ0 )
SD
Where: n = 60, X = 1.3321 (sample mean), μ0 =2.8, and SD = 5.2248 (sample
standard deviation). The tests statistic under null hypothesis is normally distributed
with zero mean and one standard deviation. The assumption of normality is satisfied
in (1) and the sample size is greater than 30 observations.
Excel Outputs for Test table 2
Table 1: Descriptive Statistics for t-tests on GD return
Statistic Value
Mean ( X ¿ 1.3321
Standard deviation (SD) 5.2248
N 60
Source: Author (2019)
Calculation: tcalc .= √60 ( 1.3321−2.8 )
5.2248 =−2.1762