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Machine Learning for Prediction and Analysis of Public Financial Data

The U.S. Securities and Exchange Commission requires publicly traded companies to file reports of their financial statements every quarter. Our project utilized this data along with daily stock price information for nine different companies to create an interactive web application. Users can input financial data on the front-end, and our machine learning algorithms will cluster companies with similar stock trends and make predictions on the future value of the queried stock.

Team Members: 

Rajat Ahuja

Casey Hu

Seungjun Lee

Aaron North

State Street