The goal of this project was to conduct a simulation of the stock market to figure out which trading strategy would be most effective. A neural network program was designed to analyze stock market patterns for the prediction of trends. A six-week simulation was completed using three different trading techniques: day trading, position trading, and trading guided by neural network. The returns of the three methods were strategies are as follows: 64.38% for Neural Network, 61.69% for position trading, and 48.64% for day trading. In comparison, S&P 500 only gained 5.65% for the same period of time. This project gave the student insight into how the stock market works so that he could make informed trading decisions in the future.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Rambacher, Calvin

Subject

• Computing
• Project-Based Learning

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-121222-092352
• 82451

Mot-clé

• Stock Market

Advisor

• Tang, Dalin

Year

• 2022

UN Sustainable Development Goals

• 8 - Decent Work and Economic Growth

Date created

• 2022-12-12

Resource type

• Interactive Qualifying Project

Source

• E-project-121222-092352

Rights statement

• In Copyright

Dernière modification

• 2022-12-21