Location
Presentation- College of Science and Mathematics
Document Type and Release Option
Thesis Presentation (Restricted to Georgia Southern)
Faculty Mentor
Dr. Kyle Bradford
Faculty Mentor Email
kbradford@georgiasouthern.edu
Presentation Year
2021
Start Date
26-4-2021 12:00 AM
End Date
30-4-2021 12:00 AM
Keywords
Georgia Southern University, Honors Symposium, Presentation
Description
Predicting stock prices is perhaps one of the most tantalizing applications of mathematical statistics. Despite the Efficient Market Hypothesis’ (EMH) assertion that consistent predictions of stock price movements are impossible, it has done little in the way of deterring people’s efforts. One area of growing interest is the use of various Machine Learning (ML) techniques to forecast stock price direction. In that spirit, this study aims to refute the EMH through the implementation of a Support Vector Regression (SVR) model. Using optimized hyperparameters and k-fold cross validation to assess the model’s overall performance, the results suggest that our model does have a certain predictive power.
Academic Unit
College of Science and Mathematics
Stock Price Prediction Using Support Vector Regression
Presentation- College of Science and Mathematics
Predicting stock prices is perhaps one of the most tantalizing applications of mathematical statistics. Despite the Efficient Market Hypothesis’ (EMH) assertion that consistent predictions of stock price movements are impossible, it has done little in the way of deterring people’s efforts. One area of growing interest is the use of various Machine Learning (ML) techniques to forecast stock price direction. In that spirit, this study aims to refute the EMH through the implementation of a Support Vector Regression (SVR) model. Using optimized hyperparameters and k-fold cross validation to assess the model’s overall performance, the results suggest that our model does have a certain predictive power.
Comments
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