Impact of Quantitative and Qualitative Parameters on Stock Performance
Abstract: Stocks belonging to publicly traded companies is a topic which in society is mystified and by some considered to be an unpredictable phenomenon where you either make an economic loss or gain seemingly by chance. Despite this, there are numerous fields of work where the sole purpose is to predict the movement of stocks in order to maximize economic gain. The purpose of this report was to research whether or not these movements actually can be predicted by the usage of regression analysis. A regression model was constructed where the response variable used was the rate of change of a certain stock over 30 days and numerous different qualitative and quantitative parameters were used as regressors. This full model was then evaluated and improved in order to refine its construction and results yielded in order to present the best possible model. When researching and optimizing the model, it was found that several parameters turned out to be statistically significant for the model. The model itself did however come with some uncertainties in the form of a low R-squared value, meaning that despite the significance of said parameters, it contained a high amount of unrepresented variance.
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