Inspiration
All of us love to monitor the global business ecosystem and we personally invest our money into publically traded companies. We noticed that in today’s "buzzy" day and age, the everyday investor can't afford 20+ hours to understand a company’s financial health and the intricacies of their business model. As a result, popularity and public sentiment are driving the stock market. The “buzz” surrounding a company is slowly becoming more important than the behind-the-scene changes to supply chain or restructuring that affects profit. Take Tesla, whose volatile stock prices can be partially attributed to the eccentricness of Elon Musk.
What it does
BuzzLine gathers historical data and uses machine learning to determine the correlation between “buzz” and the stock price of a specific company. BuzzLine's analysis will help aid your decision in whether you should buy, sell, or hold.
How we built it
Used two APIs, Python, and Front-end tools
Challenges we ran into
EVERYTHING
Accomplishments that we're proud of
Learning and completing our first finished and working project.
What we learned
Servers, Python
What's next for BuzzLine
Using our data and machine learning to output a "credit score" for stock, indicating to the user on whether to buy, hold, or sell the stock.
Built With
- alphavantageapi
- css
- html
- javascript
- newsapi
- python
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