Members in our team have spent multiple years learning about to finance to be able to make sound investment choices. Being financially sound is a pre-requisite to be able to do what you want without having to worry about what's going to be on the table tomorrow. We want everyone to be able to think about the long term instead of tomorrow

What it does

Scrapes analysts ratings and tries to predict the historical accuracy of multiple analysts on each stock. The stocks where analysts have been historically very accurate and are predicting an increase in price are the stocks we reccommned

How I built it

Scraped data from Factset using pyautogui and manually controlling the computer because financial data was extremely expensive to get otherwise. Running the images collected on autoML

Challenges I ran into

Images are not the best way to do this. We had to clean the data in several unique ways to make it work

Accomplishments that I'm proud of

Our creativity in figuring out how to source the data from a graphical interface into images

What I learned

how to use autoML and its limitations

What's next for PriceX

  • improve UI to provide more details about ETA and specific profit expected
  • integrate certain parts of code
  • turn data from images to csv through relative positions of pixels

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