auga

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  BA stock easily Visualized with Auga

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  Googles stock candlestick

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  We're able use what we learned in graph theory class to the stock data!

Inspiration

We are part of Oberlin's Quantitative Investing Team of Oberlin College's Investment Club. People continuously leave our club because they find it too hard to contribute, so we want to make it as easy as possible to do stock research without using a Bloomberg terminal. Additionally, we spend too much time organizing data for Machine learning without doing any machine learning ourselves. By being able to select exactly what we want, we are able to get to developing models better.

What it does

Auga(in the book series Eragon, its 'eye' in the dragon language) is a tool where you can input stock and get the past five years of stock data for it. You can create your own formulas and your own plots to in the back end.

Ultimately, its a tool that's easy to pick up, but has a very high skill ceiling as you have all of the data that even the most experienced professionals use.

How we built it

we use Python-flask for the front end, and python for the backend. Pandas and Iex finance are how we process the data.

Challenges we ran into

we tried using OMNISCI, but their product isn't built for stock charts. this makes implementations difficult.

Accomplishments that we're proud of

We have 5 years of stock data, we learned how to make embedded visualizations as well as querying APIs. A lot of us learned flask for the first time, which opened many doors toward python development.

What we learned

we learned how to make a front-end. We learned how to make embedded visualizations, API queries en masse, and data manipulation.

What's next for auga

Continued development during club time! Extended user feedback to create a better user experinece. Jupyter hooks with the embedded, as well as hosting on a server.

Built With

• html
• python