Analysis of algorithms to create profitable trades in the stock market

<p>"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.</p>

Name thesis:degree_name

Master of Science (MS) in Computer Science

Level thesis:degree_level

Thesis: EWU Only

Discipline thesis:degree_discipline

Computer Science

Year

2016

Author dc:creator

• Klinger, Nicholas P.

• Stocks--Prices--Mathematical models
• Stock price forecasting
• Stock exchanges
• Computer algorithms
• Computer Sciences
• Finance and Financial Management
• Theory and Algorithms

Statement dc:rights

• Access perpetually restricted to EWU users with an active EWU NetID

Repository record dc:identifier

https://dc.ewu.edu/theses/400

OAI identifier oai:identifier

oai:dc.ewu.edu:theses-1400