Effects of Social Media on Stock Prices

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Introduction
It is with no doubt that social media which has grown to be a landmark of the evolution in
communication of the 21st century and communication media in general, has become an integral
part of the everyday life of almost any person. For instance, a Facebook post by a banker in some
place in South Africa can be instantly accessed from anywhere in the world that has an internet
connection. Generally, social media opinions by persons spread in astonishingly high and so are
news components in the digital world of today. The unrestricted freedom that has been brought
about by the adoption of digital revolution in communication begs the question as to what are the
effects of the freedom of expression that underlay the whole idea of social media (Ranco,
Caldarelli, Aleksovski, Grčar, & Mozetič, 2015).
Human are sentimental creatures, well at least many of them. As such an idea or just a statement
made by an individual is most likely going to influence a reaction of another individual regarding
the topic in focus (QuantPedia, 2017). Statistical studies on the effect of consumer reviews on
the willingness of other buyers to purchase an item indicate that, “...consumers tend to trust the
thoughts of other consumers more than they do trust the word of producers concerning the
product” (Render, 2018). The case of consumer reviews has been applied to stock purchasing
also where information influences stock investment (Jegadeesh & Titman, 2001). As to who
bears the brute part of negative or reaps the positive outcomes of sentiments expressed all over
media remains a key question.
Information and stock
Stock and information are often correlated in which new information is posited to affect stock
prices. An argument that,“... a basic tenet of financial economics is that asset prices change in

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response to unexpected fundamental information” (Boudoukh, Feldman, Kogan, & Richardson,
2013) sums it perfectly well and forms the basis of this papers objective.
The objective
Information media forms a medium for fast information channeling and access. It is therefore a
basic supposition of this paper that the more access to information there is, the more volatile the
stock prices of a firm are likely to be. In this case the analysis will focus on technical and
sentimental analysis to predict stock of the tech giant Apple.
Basics
There are lots of sources of information out there, the main task underlies as to how to obtain the
relevant information and from credible. For this task, we scrape tweets relating to the apple firm
for the closing period of 2018 to 2019 and analyze different technical information such as stock
forecasting using moving average and exponential smoothing then use the information to
compare how the predicted stock is predicted by sentiment confidence if at all sentiments predict
stock prices. This study uses forecasting methods such as the “TA (Technical analysis
algorithms” and predictive algorithms i.e. OLS regression in machine learning to address the
paper’s objective.
Technical analysis and prediction
In this section we analyze the performance of Apple’s stock using the “Technical analysis”
package in python. The main focus will be on: forecasting the stock prices which will show if
prices will go up or down in the future, examining the trend to understand the volume and price
trend of the stock, momentum to understand the buying pressure where the prices rise if there is
buying pressure and falls when there is selling pressure, daily returns, money flow and KST

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Oscillator (KST), Chaikin Money Flow to measure the amount of Money Flow Volume over the
trading period.
The graphs below show basic trends of different stock performance.
Opening stock prices

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After conducting a forecasting of Apple’s stock prices using both moving averages and
exponential smoothening in “ta” library we note that the stock prices show an upward trend at
the start of January but is forecasted to drop sharply after the close of march 2019.