Predicting Share Prices of Colgate Palmolive Name of the University Author

Running Head: PREDICTING THE SHARE PRICES OF COLGATE PALMOLIVE
Predicting the Share Prices of Colgate Palmolive
Name of the Student
Name of the University
Author Note

PREDICTING THE SHARE PRICES OF COLGATE PALMOLIVE1
Table of Contents
Executive Summary.........................................................................................................................2
Description of the Data....................................................................................................................2
Variance Inflation Factor (VIF).......................................................................................................3
Residual Analysis............................................................................................................................4
Analysis of Variance........................................................................................................................5
Coefficient of Determination...........................................................................................................6
Hypothesis Tests..............................................................................................................................6
Coefficients......................................................................................................................................7
Prediction of Share Prices................................................................................................................8
Conclusion.......................................................................................................................................8
Appendix – VIF Values.................................................................................................................10

PREDICTING THE SHARE PRICES OF COLGATE PALMOLIVE2
Executive Summary
This report is aimed towards analyzing the data on the previous years in order to predict
the future changes in the share prices of the company Colgate Palmolive. Analysis has been
conducted on the stock market data of various products for 378 days spread over 2 years from
April 2016 to march 2018. Colgate Palmolive is the leading company across the globe popular
for manufacturing toothpaste and soap.
The data on the changes in the stock prices for 378 days spread over 2 years for the
company Colgate Palmolive is used to conduct the analysis. The relationship between the
changes in the stock prices with other independent factors have been established here with the
help of multiple regression model. The variance inflation factor (VIF) and analysis of variance
(ANOVA) have also been discussed along with the regression analysis and the coefficient of
determination (R2)
Description of the Data
There is data on 378 trading days available for a time period of two years starting from 4th
April 2016 to 26th March 2018. There are six input variables or independent variables that are
used to predict the dependent variable which is the future price of the shares for Colgate
Palmolive. The prices of different assets change each day and the changes in these prices are
recorded in the different columns of the dataset provided. The dataset contains the changes in the
prices of the following assets:
 Aluminum
 Gold
 The confidence of the Consumers

PREDICTING THE SHARE PRICES OF COLGATE PALMOLIVE3
 Interest rates of the 30-year treasury bond
 The index of the Standard and Poor 500 stock prices
 Changes in the share prices of Colgate Palmolive in the previous years.
The changes in the share prices of Colgate Palmolive are predicted with the help of the
change in price of the other assets mentioned above. It can be noted from the available dataset
that most of the change in the prices of the variables used to predict the future stock prices of
Colgate Palmolive are interaction variables. It can also be observed that the changes in the prices
given in the dataset lies between 0 and 1. This is because the original percentage change in the
prices is transformed to a new variable by ranking the prices, sorting them and then dividing
them by 378. Thus, 0 will indicate that there has been no change in price, 1 will indicate the
maximum increase in the price and 0.5 will indicate the median increase in the prices.
Variance Inflation Factor (VIF)
The existence of multi-collinearity in the data has to be checked before starting to analyze
the data. When there is very high correlation between two or more variables, the problem is
known as multi-collinearity. In the presence of multi-collinearity, it becomes difficult to fit a
model and obtain proper interpretation from it. The variance inflation factor (VIF) is calculated
to test for the presence of multi-collinearity between the variables in the dataset (Tinoco and
Wilson, 2013).
All the tests and analysis in this research is conducted by using the PHStat AddIn in MS
EXCEL. A value of VIF higher than 5 indicates the presence of multi-collinearity between the
variables. It can be seen from the values of the VIF statistics provided in the appendix section
that none of the VIF values are greater than 5. Thus, the problem of multi-collinearity does not