With the recent financial crisis in America, investors have received much of the blame and have been tasked with improving investment techniques to prevent another recession of similar magnitude. Here we look to develop new methods for investing using algorithms that automate the process of deciding whether to buy, sell, or avoid a stock. These algorithms use both technical and fundamental data to improve investing success by removing the factor of human emotion from trading, reducing risk of loss due to greed. We ultimately find that with a careful application of technical and fundamental data, as well as a thorough understanding patterns in financial markets, it is possible to develop an automated trading strategy that can profitably trade stocks and currencies.
Worcester Polytechnic Institute
Interactive Qualifying Project
All authors have granted to WPI a nonexclusive royalty-free license to distribute copies of the work, subject to other agreements. Copyright is held by the author or authors, with all rights reserved, unless otherwise noted.
Electrical and Computer Engineering