Belmont University Research Symposium (BURS)

Technology Stock Predictive Analysis Using Statistical Modeling & Machine Learning

Publication Date

Spring 4-18-2022


Sciences and Mathematics, College of


Math and Computer Science, Department of

BURS Faculty Advisor

Dr. Daniel C. Biles

Presentation Type

Oral Presentation


Within the S&P 500, technology stocks (or tech stocks) are often the leading indicator for the index, the stock market, and the economy. Utilizing statistical modeling and various predictive analytic and machine learning methods such as: simple linear regression, polynomial regression, k-nearest neighbors (KNN), support vector machines (SVM), and random forests to, as accurately as possible, predict the percent change in price of the some of the top tech stocks of 2021 over a 6-month period.

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