The goal of this project is to create and compare several different stock prediction models and find a correlation between the predictions and volatility for each stock. The models were created using the historical data, DJI index, and moving averages. The most accurate prediction model had an average of 5.3 days spent within a prediction band. A correlation of -0.0438 was found between that model and a measure of volatility, indicating that more prediction days means lower volatility.

• 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

• Cintron, Laura C.

Subject

• Learning
• Project-Based Learning
• Innovation
• Industry
• Computing

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-050521-235953
• 22601

Mot-clé

• Moving Average
• Fourier Series
• Dow Jones Industrial Index
• Volatility
• Stock Market
• Stock Prediction

Advisor

• Humi, Mayer

Year

• 2021

UN Sustainable Development Goals

• 8 - Decent Work and Economic Growth
• 9 - Industry, Innovation and Infrastructure

Date created

• 2021-05-05

Resource type

• Major Qualifying Project

Major

• Mathematical Sciences

Rights statement

• In Copyright