CPR and FIST

Inspiration

Nowadays, there are not many free stock trading prediction algorithms for intraday and short-term trading. In order to make one accesible to the public, we created a user friendly platform that predicts and suggests BUY-SELL-HOLD signals for publicly traded securities in NYSE and NASDAQ.

What it does

Our back-end performs financial analysis and trend analysis on each equity and uses a weighted-average rating system to predict whether to BUY, SELL, or HOLD a particular stock. The financial analysis includes calculating the Moving Average Convergence-Divergence (MACD), Bollinger Bands, SMA-Crossover, among others. The results are stored in a database and displayed on a website with a clean user-interface.

How we built it

The back-end prediction algorithm is written using Python. The historical data of each stock and the ratings are stored in MongoDB. Flask, Node.js, HTML/CSS/Bootstrap is used to present the data from MongoDB in a seamless interface.

Challenges we ran into

We ran into slight problems while using Flask and JavaScript. The problems were solved quickly. The project went smoothly due to the efficiency of all team members.

Accomplishments that we're proud of

Our prediction algorithm was a complete success. We were also able to successfully populate tables in our front end from our database. These tables display our predictions in a clean fashion. We were able to create a free real-time stock graph for users (real-time price feeds cost upwards of $500 per month)

What we learned

We learned a lot about full-stack development after working with a back-end Python code, using Flask to submit GET and POST requests, using MongoDB to store data, using NodeJS/HTML/CSS/Bootstrap to create a front-end web application to present the contents of the database. We also learned how to take a very complex idea with many moving parts and allow them to communicate and work with each other.

What's next for CPR and FIST

Cleaning up the user-interface after hosting our website.

Built With

Submitted to

HackRU XII
- Winner Best Use of MongoDB

Created by

I wrote the trading algorithms and database management algorithms for the intra-day trading side, along with the live minute by minute chart. I also created the notification system using Twilio API. Most of my work consisted of Python, MongoDB and Twilio.

Peri Akiva
I wrote the trading and prediction algorithm using Python and my knowledge of the financial markets. I also wrote the queries for MongoDB using PyMongo. All of my work was primarly Back-end/Python and MongoDB.

Subramhanya Shankar
Logan and I worked on the front end of this project. He contributed majority of the code while mentoring me through his implementations. I helped with styling and also debugged issues, when possible.

Nick2Hair
I wrote the node/express server that pulls data from MongoDB to render on the front end. I also designed wrote the frontend using React and Bootstrap.

Logan May

Updates

Peri Akiva started this project — Apr 23, 2017 12:50 AM EDT

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