A project to allow access to quick data-driven predictions of quarterly earnings call for security trading.

Daniel Trinh Priyadarsi Mishra Arjun Ankad

This project was designed to aid with simplicity in mind. It is designed to provide access to earnings call predictions for a given security. Of course, NO USER SHOULD TAKE THIS RECOMMENDATION AS SOUND FINANCIAL ADVICE. THIS IS FOR EDUCATIONAL PURPOSES. We were inspired to create this project because we saw a need to make quantitative trading analysis more accessible. And throughout the development of this project, we experienced how difficult it is to really get software deployed. We originally planned to have a complicated backend setup but were greatly limited by the available free APIs and easy to integrate databases. We ended up building the project using React for the easier Frontend development and a Python LSTM model for the intelligence behind the "advice". However, we ran into issues in connecting the two. Originally, we had not structured the Python file in a way where it could be invoked by the frontend, so we needed to restructure it. But it did end up working. However, we do believe there is of course more work to do!

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Currently, the project is deployed on Vercel. This may change in the future.

• Vercel - Frontend Hosting
• Heroku - To deploy on Heroku
• React JS - Frontend Framework
• Python 3 - Backend Language
• Flask - Backend Framework