During my graduate studies at Golden Gate University, I completed an analysis on five of the top tech companies’ stocks share prices since going public for trading. This was part of an individual project that I completed that used the skills I developed in both the R and Python programming languages. Due to previous experience in Python prior to taking a course in data analysis in Python and R, I chose to execute this project in Python under a Jupyter notebook. The five companies that were analyzed were Apple, Amazon, Meta, Alphabet, and Microsoft.
For clarification terms, at the time of this research conducted between March and May 2022, Meta, Inc.’s ticker symbol was still under the former term “FB”, when it originally did business as Facebook, Inc. Additionally, Google’s stock symbol, GOOGL, while doing business as Alphabet, Inc., is the share symbol for Alphabet shareholders who also vote on certain company and stock-related decisions. This was done as a result of a 2015 restructuring of the company then known as Google, when its services as a company became a subsidiary of Alphabet, Inc.
It was understood that the five companies I chose all went public at different times and with various forms of investment in their own economic climates. Apple, for example, went public in December 1980, but Meta, Inc., then doing business as Facebook, Inc., began trading on the Nasdaq in May 2012 despite underperformance in its first quarter on the market. There is a lot that can be compared between Meta’s stock and the other four companies’ stocks that it has faced competition with over the years.
I used Python and did an analysis of the data in the form of understanding the content of the columns and descriptive statistics. After analyzing the data that was being used for each of the five companies that I researched, some data science practices were used in the forms of correlation analysis as well as time series analysis to evaluate the many changes that each of these stocks’ share prices have grown over time. For this article, I will only look at the rolling averages in time series analysis; more can be found in the repository.
Overall, it can be seen that each one of the five companies’ stocks experienced to some degree exponential growth. There was even a small peak in the late 1990s because of the dotcom bubble, when the Worldwide Web was taken advantage of by companies to mark their digital footprints in the then-small Internet universe. Of the three companies (Amazon, Apple, Microsoft) who were on the market at the time, Amazon saw some growth where it experienced some of its best accomplishments as a company that at the time was within five years of its founding.
For all stocks with the exception of Facebook (which began in 2012), the mid-to-late 2000s saw stock prices see significant positive growth in per-share price. Based on some key stakeholder decisions and products released to consumers, the level of exponential growth is not significant for each of the five companies. Of the five companies that saw massive growth from the late 2000s onward, Google and Amazon saw the most growth in their share prices as they skyrocketed after 2010.
Between c. 2015 and 2020, Google, now doing business as Alphabet, Inc., saw its stock share price fall victim to the rise in Amazon’s performance in the market. Major investments by shareholders in Amazon and the results from Prime subscribers and offers, as well as having their own streaming services, has caused this massive rise for Amazon. The COVID-19 pandemic and stay-at-home restrictions resulting in ordering from home resulted in higher revenues and in founder and then-CEO Jeff Bezos to be the wealthiest man in the world at that time. Despite falling in second place to Amazon at the start of the pandemic, Alphabet’s share price still saw a significant rise but not at the rapid rate that Amazon has since experienced.
Time series analysis was used on all five tech stocks. Below is an image from Amazon’s share price since going public. There are rolling averages every 7, 30, 90, and 120 trading days with the changes between said periods. Additionally, I ran some basic linear regression modeling for analysis of variance (ANOVA) to see how far or close each of the stocks were to constant or exponential growth.
We will take a look at Amazon’s share price since going public. As mentioned before, its share price experienced a small increase back in the late 1990s from the dotcom bubble. Below we see the sample code created to get the rolling average compared to the actual period since Amazon went public to trade its shares.
Here, there are massive climbs that Amazon’s share price took after 2015. The fact that there are vertical lines with an indefinite slope value that grow larger and larger because of the rolling averages just shows the amount of growth the price of its shares experienced, as well as the sharp declines and upward rebounds. Instead of looking at the stock’s price day-to-day, looking at its price over the last 7, 30, 90, and 120 trading days shows the overall trend of its share price.
Click here to go directly to the GitHub repository for source code and additional information which also includes the analysis of variance in comparing between these five companies’ stocks’ share prices over time.
Click below to view the report, as well as to see the time series and correlation analyses for the other tech companies.
MATTHEW CHIN 