Regression Analysis of Samsung Stock Prices

Running head: STATISTICS ASSIGNMENT
STATISTICS ASSIGNMENT
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1STATISTICS ASSIGNMENT
Table of Contents
Data..................................................................................................................................................2
Calculations/Interpretations.............................................................................................................2
Graphs/Charts..................................................................................................................................4
Summary/Conclusion/Findings.......................................................................................................5
Sources.............................................................................................................................................6
Appendix..........................................................................................................................................7

2STATISTICS ASSIGNMENT
Data
The study analysis includes historical monthly closing prices of Samsung, Google and
Apple. Furthermore it includes the quarterly historical GDP growth of South Korea. The data of
closing prices were obtained from yahoo finance and the GDP of South Korea was obtained from
the OECD website (OECD, 2018). It is of interest to model the closing price of Samsung. The
factors considered are the GDP growth of South Korea, since Samsung is a South Korean
company and stock prices are believed to be positively associated with macro-economic statistics
(Gay, 2016). Aside from the software and hardware relationship that exists between Google and
Samsung , they share ad revenue and have in agreements for patent co-licensing as well as
collaboration in projects, setting standards of mobile security and computing as per Kristina
Zuchhi (2018) on her article in Investopedia. Hence their performance are anticipated to be
related. Additionally Apple being one of the primary competitors of Samsung, their performance
in the market is also expected to have an explanatory impact on the price of Samsung. The data
converts monthly prices to quarterly and spans from May of 2013 to February of 2018. The data
was then used to fit a regression model with Samsung closing prices as dependent and closing
price of Google and Apple as well as GDP of South Korea as independent variable.
Calculations/Interpretations
The goodness of fit statistic of the regression analysis on the data shows that model has
R-squared vale 0.518, that is model explains 51.8% of the variation in the quarterly closing price
of Samsung. The factor adjusted R-squared value was found to be 0.4277 that is for. This value