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Inspiration
We chose to do this as we wanted to develop an application that would be able to provide users with a deep analysis of any inputted stock, better equipping beginners in investing.
What it does
Uses a LLM to provide scores based on stock history, current price, P/E ratio, all time highs and lows, and the stock company's value as a company amongst several other factors.
How we built it
We used react, tailwind, next, and shadcn for our front end; express, mongoose, and mongodb for backend. We also used two API's, OpenAI and Polygon.io.
Challenges we ran into
Staying awake and running around campus for the scavenger hunt, only for there to be no second place prize.
Accomplishments that we're proud of
That we completed this in 24 hours.
What we learned
Do not do the scavenger hunt.
What's next for HooStocks
Polish the front end, finish authentication, and include more factors into the analytic process.
Built With
- express.js
- mongodb
- mongoose
- next
- openai
- polygon
- react
- shadcn
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