Matt Babcock
Dr. Emre Yetgin
IS 251.03
20 October 2015
Stock Price Analysis
The company I chose to do this project on is The Coca-Cola Co. (ticker symbol: KO). I chose
Coca-Cola because I am familiar with their products, and consume them quite regularly. Also, while
choosing this company, which is in the Dow 30, I was thinking of commodities and competitors to
hopefully correlate with Coca-Cola. Just by looking at a can of Coke or a bottle of Powerade, I could tell
the main commodities used in their products. Also, I know Coke really only has a few major competitors,
so I was expecting their relationships to be somehow intertwined as they are part of an oligopoly on the
soda and sports drink market. Another reason that Coke intrigued me was because they are constantly
running commercials on television and sponsoring all sorts of events. They sponsor everything from eSports to the Special Olympics, so they really are an interesting and reputable company.
Coca Cola serves over a billion beverages each day, but it wasn’t always so massive. The original
Coca-Cola drink was invented in 1886 and bought by a man by the name of Asa Candler in 1889. Asa
went on to incorporate the company in 1892. With the introduction of the Coca-Cola bottle in the early
1900’s, Coke’s popularity increased rapidly. This gave them the ability to buy and start many other
different brands, in not only soda, but other beverages as well. Today, some of their most famous brands
are Coke, Vitamin Water, Sprite, Powerade, and Fanta.
Coca-Cola’s relevance in the beverage market is goliath, and they have many brands under their
belt. They produce in such quantities and are so well-known that they can basically undercut any new
player trying to enter into the beverage market. This essentially allows Coke to only be in competition
with a few other competitors. The barriers to entry are high, and the demand for the beverages Coke
produces seems to always be there. Even if demand for soda goes down because people are trying to be
healthier, the demand for sports drinks will likely rise because health and physical activity are correlated.
This leads one to believe that Coca-Cola can overcome nearly any difficulty it will face and is therefore a
relatively stable investment.
The main competitor that Coca-Cola has is PepsiCo (ticker symbol: PEP). They are in fierce
competition and are the combined suppliers of beverages to nearly all fast food restaurants and also a lot
of major sit-down chains. Coca Cola is the supplier to more restaurants but Pepsi is a very close second
and is working to steal more and more of Coke’s business. These two companies are closely related so I
decided to include PepsiCo as a competitor to Coke in my model. A second competitor I chose to include
was Dr. Pepper Snapple Group (ticker symbol: DPS). I included them because they are another one of the
major companies in the beverage group. Although, they are a little less known in the United States, their
global presence is strong and they are a real competitor.
After choosing the companies to include, I thought through the commodities necessary to create
many of the beverages that Coca-Cola handles. I looked at the back of several cans and bottles from
beverages Coke produces and realized that the main commodities used are aluminum and sugar. They
use aluminum to produce their canned beverages, and they also use sugar in many of their drinks. Sugar
was really a difficult one to decide on because they use corn syrup as opposed to real sugar in many of
their drinks. However, I decided that the price of real sugar impacts them enough based on the quantities
they need to use, as many of their drinks do include genuine sugar.
Some other items I chose to include were the 10 Year Treasury bond-Rate, the Federal Funds
Rate, and the volume of trades. These are somewhat generic variables that would be included on many
models because they have a rather direct impact on stock price. The 10 Year Treasury bond rate often
changes from month to month and could be a possible predictor of stock price, and although the Federal
Funds Rate is more stable, it may also play a role. The volume of trades is important because if lots of
trades are made, the price of the stock is going to have a tendency to change.
Two of the more abstract variables I included were the Consumer Sentiment Rate and the News.
The Consumer Sentiment Rate is collected by the University of Michigan, and indicates the health of the
economy as proposed by consumers. This variable seemed odd to include at first, but it is pretty vital in a
successful model. The news was another abstract variable I included, because it was up to my
interpretation. Coca-Cola is very popular so they made it into the news on a near-daily basis. I gathered
the news from both Morningstar and Google Finance News, and interpreted it myself. I rated the news on
a scale of integers from -3 to 3. -3 meant that the news was horrendous, and 3 meant that the news was
extraordinary. This variable was determined based on my opinion of the news, and whether or not I
thought it was going to bring down or raise the stock prices.
After taking all these variables and running my regression, I found some very interesting results.
The first thing I noticed was that my R squared had an approximate value of .71. This means that a
significant amount of the variability in stock prices can be explained by the variables which I included.
After analyzing R squared, I decided to take a look at my p-values and coefficients. The coefficients were
what I was expecting, but I was quite surprised by the fact that Volume, News, 10 Year Treasury Bonds,
and the Federal Funds Rate did not play a major role in predicting the closing price of KO.
On the contrast, all commodities, all competitors, and Consumer Sentiment were significant
predictors of stock price. The biggest predictor, and smallest p-value was PepsiCo, with a p-value of
approximately 3.99x10^ (-37). This was what I was initially expecting to be the biggest predictor because
of how close Coke and Pepsi are related, and was pleased with the results. Because of the relationship
between these two companies, I decided to graph the closing prices of Coke and the closing prices of
Pepsi (Graph Below).
KO vs. PEP
120
100
80
60
40
20
1
15
29
43
57
71
85
99
113
127
141
155
169
183
197
211
225
239
253
267
281
295
309
323
337
351
365
379
0
After checking all of the p-values, I went on to compare the actual closing prices of KO and the
prices which my model had predicted (Graph Below). The values were surprisingly close and overall my
model seemed to do its job by predicting prices with a standard error of around .77.
Predicted vs. Actual
46
44
42
40
38
36
1
19
37
55
73
91
109
127
145
163
181
199
217
235
253
271
289
307
325
343
361
379
34
Finally, I began using my predicted stock prices to determine whether to buy, sell, or hold the
stock. I came to a conclusion by seeing how my predicted stock price related to the actual stock price. If
predicted was higher I recommended buy, if predicted was lower I recommended sell, and if they were
equal I recommended hold. I put a buffer to compensate for some of my error in the predicted values.
Overall, I ended up with my recommendations being correct about 50.3% of the time. This number is not
huge, but at least it is better than 50%. This model may have had some limitations, but overall I ended up
with my first ever stock prediction model being a success, and I learned a lot about the market in the
process.
Sources
Historical Stock and Commodities
http://www.google.com/finance/historical?q=NYSE%3AKO&ei=P7ElVsG4AsTNeZ3Ss9AK
http://www.google.com/finance/historical?q=NYSE%3APEP&ei=cLElVuCpO4XCed_wg7gM
http://www.google.com/finance/historical?q=NYSE%3ADPS&ei=pbElVomLM43De_j5hJgB
http://www.google.com/finance/historical?q=INDEXDJX%3ADJUSAL&ei=77ElVqm5Ls6_e7vuiaAB
http://www.indexmundi.com/commodities/?commodity=sugar
News
https://inside.loyola.edu Morningstar (KO): Through Anywhere Apps
http://www.google.com/finance/company_news?q=NYSE%3AKO&ei=iLIlVsjhK463e6u6gugM
Fed Funds, Treasury Bonds, and Consumer Sentiment
https://research.stlouisfed.org/fred2/series/DGS10/downloaddata
https://research.stlouisfed.org/fred2/series/UMCSENT/#
https://research.stlouisfed.org/fred2/series/FEDFUNDS
Miscellaneous
http://deutch4macys.blogspot.com/2011/02/brief-history.html
http://www.businessinsider.com/restaurants-that-serve-coke-vs-pepsi-2013-12