Research: Prediction of Growth Stocks Using Machine Learning Algorithms
Awards: Somers Science Fair 2022 Participant
Mentor: Manyar Raza
Research Location: Yonkers, NY
Being active in the stock market is one of the most sophisticated ways that people generate income. However, depending on the type of investments made, there are different levels of risks involved. This is where machine learning comes into play and could aid in professional investors making higher gains in the stock market. Some intended methods that will be utilized for this research are the integration of certain characteristics that are reliably measured in growth stocks. These are key attributes and variables that will be used for these graphs and models that will be formulated. Some of these characteristics include high price-to-earnings ratio (P/E), possessing a higher growth rate than the average stock market, paying little to no dividends, and generating substantial revenues through capital gains. Another intended method that may be used for this research are certain classifiers, one of them being Linear Regressions. This is a very commonly used technique for data analysis and forecasting. It essentially uses the characteristics of growth stocks as independent variables to predict the relations between those variables and certain trends and patterns that occur in the stock market. The accuracy of the classifier is directly proportional to the amount of data provided to the classifier and the attributes selected. After conducting this research, it is expected to successfully aid professional investors in making accurate predictions in the stock market.