Research Conference 2024 | Sample Abstract
PLEASE EMAIL ALL ABSTRACT SUBMISSIONS TO:
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The following is an example of an abstract:
Using Calendar Correlation to Increase Investment Efficiency
Andrea Gibson and Joe Omojola
Southern University at New Orleans, New Orleans, LA 70126
Abstract
Correlation is a statistical measure that determines the level of relationship between two variables. The goal of this research is to determine calendar periods over which a trend in a particular stock correlate with each other and the frequency of their correlation. The objectives of this research are: (a) to collect data for assigned stocks and analyze the data, (b) to determine the trends (up or down) and their respective time frame and, (c) to determine time intervals over 10 years when trends in the same stock agree. Data was collected for a period of 10 years for 25 assigned stocks. Specifically, the period for up trends and down trends were determined for 10 years. The success rates of the up trends and down trends were then determined. They were determined by looking at the stock charts for the years 2008-2017 and recording all the up and down trends throughout those years. Then, looking at those trends one can determine if the dates of those trends correlate. Majority had a positive correlation while a few had a negative correlation. However, negative correlations can be used for buying put options. To test how accurate the research was, the year 2018 was used to determine if those predictions were accurate. In conclusion, the result show that one can determine the periods over which stock prices trends correlate and be able to use this knowledge to make profitable investment decisions. On average the predictions are about 49% accurate.