Title

The Effect of Corporate Financial Data on Stock Value Fluctuation

Author(s)

Matthew M. Breivik

School Name

Spring Valley High School

Grade Level

10th Grade

Presentation Topic

Consumer Science

Presentation Type

Non-Mentored

Written Paper Award

1st Place

Abstract

The purpose of this experiment was to find different financial values that affected a business’s stock prices. It was hypothesized that when different financial data sets were studied statistically then a trend could be determined to accurately predict stock fluctuation. Fifty different stocks were studied over a period of 8 years. The raw information was gathered and recorded, then converted to percent change. The reason for this conversion was because of such a large difference between different stock prices percentages had to be looked at or the values would be so widely dispersed that no statistical test would be able to accurately provide a conclusion. These percentages were then recorded as well. Then a series of one-way ANOVA tests were conducted on the percent change in price to percent change in the financial data set, since there were six data sets six different ANOVAs were done. Some of the different data sets showed no correlation between price change and the financial data sets, while other showed that there was indeed a correlation, whether direct or indirect, however all of the correlations were very weak. With a confidence interval of 95% the conclusion was reached that the hypothesis was supported, however, because the hypothesis was to simply find a trend, or rather which data sets were showing correlation, it is not taken into account how weak the correlation is when stating whether or not the hypothesis was supported.

Start Date

4-11-2015 11:45 AM

End Date

4-11-2015 12:00 PM

COinS
 
Apr 11th, 11:45 AM Apr 11th, 12:00 PM

The Effect of Corporate Financial Data on Stock Value Fluctuation

The purpose of this experiment was to find different financial values that affected a business’s stock prices. It was hypothesized that when different financial data sets were studied statistically then a trend could be determined to accurately predict stock fluctuation. Fifty different stocks were studied over a period of 8 years. The raw information was gathered and recorded, then converted to percent change. The reason for this conversion was because of such a large difference between different stock prices percentages had to be looked at or the values would be so widely dispersed that no statistical test would be able to accurately provide a conclusion. These percentages were then recorded as well. Then a series of one-way ANOVA tests were conducted on the percent change in price to percent change in the financial data set, since there were six data sets six different ANOVAs were done. Some of the different data sets showed no correlation between price change and the financial data sets, while other showed that there was indeed a correlation, whether direct or indirect, however all of the correlations were very weak. With a confidence interval of 95% the conclusion was reached that the hypothesis was supported, however, because the hypothesis was to simply find a trend, or rather which data sets were showing correlation, it is not taken into account how weak the correlation is when stating whether or not the hypothesis was supported.