Team: 13
School: Eldorado High
Area of Science: Mathematics and Social Science
Proposal: Team number: 1056*
School: Eldorado High School
Area of Science: Mathematics & Economics
Project Title: C.A.S.H. M.O.N.E.Y
Initial Issue
Many people believe that the stock market is driven by company profits or other objective variables but it is the general consensus among top economists that the driving force of the stock market are the investors. They don’t follow predictable trends; rather, they are subject to the various psychological forces that influence all economic activities of humans. Thus, the only way to foresee future financial crises or market trends is through closely examining the collective views and thoughts of investors under a lens. The major roadblock in achieving this goal is the amount of data to be collected throughout the day and our inability to objectively classify psychological trends and its effects on the economy. This is how supercomputing and machine learning become necessary for this task; computers can collect and analyze vast amounts of data to produce objective results in real time.
The approach we plan to take is to develop a sentiment-analyzing machine learning model to examine historical articles and tweets to determine dynamic relationships between various sources and historical data. To test the final, mature model, the algorithm will be run under simulated circumstances that compares its predictions against historical data in real time to determine how well it fares against the market.
Team Members:
Nick Pasch
Tejas Kandath
William Waitkus
Nate Wolff
Sponsoring Teacher: Gary Bodman