Team leader's Slack

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Inspiration Edit later

This web application was inspired by the recent volatile events in the stock market. Trying to make sense of a seemingly random data set is a daunting task, but the more complex we can make this algorithm, the better chance we may have to predict it!

What it does

Trendi uses historical data pulled from Yahoo Finance to create metrics about stocks and the industry categories to which they belong, including a Stability Coefficient, variance, and upward/downward market trends.

How we built it

The concept started with general end goals for an app which would create recommendations for its user. The process involved deciding what the algorithm (python script) would do and how it would do it. After iterations, we are happy to present a few findings and metrics we have been able to pull from the data. We are displaying the findings on a React web application.

Challenges we ran into

Coding projects always have their own set of challenges. We unfortunately only had two people working on this project after half the team dropped the day before. We also had no experience with Python or ReactJS, so learning on the fly was a fun and interesting challenge.

Accomplishments that we're proud of

We are very proud that the algorithm was able to recognize times of extreme market trajectory and that it was able to rank stocks on a volatility metric which made sense in the grand scheme of its actual performance, balanced for different prices. We are proud that the look of the site feels clean and simple like a tech/stock company would have it. For not having used the technology for more than a day, we are incredibly pleased with what we have to share with you.

What we learned

We learned a lot about the nuts and bolts (and pitfalls) of Python and ReactJS. We also learned how intricate the stock market tracking game is, opening our minds to future opportunities of expanding the algorithm for larger scope and application and more accurate predictions.

What's next for Trendi

We hope that the future of Trendi would include refining and optimization of the algorithm to reflect and predict even the most volatile market conditions. I with that we had a bigger team, which would've meant having a deployed website and maybe live reading of the data from whichever source we decided. We could create more metrics within the algorithm and test which combinations of them make the best predictors in the long run. The long term goal might be to have a mobile app which would alert you when you should buy or sell a "watched" stock based on the algorithm's current understanding of the market, and maybe even partnering with one of the big boys, like RobinHood!