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Date of Award
Thesis: EWU Only
Master of Science (MS) in Computer Science
"There are many different strategies to predict the stock market. When selecting a strategy to predict the stock market, that strategy must be robust and be able to handle unexpected events. This paper analyzes algorithms that are based on human psychology instead of just looking for patterns in the data. It also attempts to find optimal parameters for the algorithms and see if their performance will persist in the future and with trading costs. Finally, this paper looks at algorithms that are able to combine the signals of other algorithms and see how well they perform with and without trading costs"--Leaf iv.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Klinger, Nicholas P., "Analysis of algorithms to create profitable trades in the stock market" (2016). EWU Masters Thesis Collection. 400.