An interest in understanding the stock market led to us creating the project. It's difficult to find resources that help keep track of all the latest stock behavior, and there is a lack of a central hub to run simulations, extract latest social media sentiments and observe a proper breakdown of analyzed data. So, we thought we'd give it a try and come up with a user friendly app that helps users get an insight into the behavior of the stock market and help make smart decisions.

What it does

It runs stock data simulation based on user inputs of total amount of money to be invested in the selected stock market data and the date, provides latest real time twitter sentiment analysis on the company and a graphical breakdown of the changing sentiments, and a pie chart that effectively lists the different sentiments. The users will be able to easily keep track of the latest trends, and make smarter decisions.

How we built it

The front-end is built in Angular, Cordova and Ionic. It makes requests to the Python Flask server which servers the purpose of a microservice and spawns and runs a c++ simulation back-end. Sentiments from Twitter are extracted using Textblob.

Challenges we ran into

Integration of the c++ simulation back-end with Python, and researching stuff for the simulation. FRONT-END. A lot of small additional challenges, like parsing data and cleaning data which a lot of time.

Accomplishments that we're proud of

Building a completely functional application which is super user friendly and effectively achieves the purpose it was built for and more.

What we learned

A LOT about the stock market and financial market. Integration of different technologies and services. A lot about the languages themselves and program architecture.

What's next for Stock Hub

Predictions based on simulations and extraction of live sentiments.

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