wardbradt / Sentimental-Stock-Prediction

Analyzes the sentiment of SEC quarterly earnings reports to predict future stock prices

Home Page:https://wardbradt.github.io/Sentimental-Stock-Prediction/

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Sentimental Stock Prediction

Example Usage

Firstly, you must set quandl.ApiConfig.api_key at the top of sentimental.py to your quandl API key.

You can get a key here.

from sentimental import generate_earnings_day_reports

# can be any stock ticker
ticker = "NVDA"
generate_earnings_day_reports(ticker)

Now when you view index.html, you will be able to view the visualization for your ticker.

To Do:

  • Find a better way to find the discussion/ overview section of each report than the current implementation in find_overview_str
  • Fix price axis scaling

About

Analyzes the sentiment of SEC quarterly earnings reports to predict future stock prices

https://wardbradt.github.io/Sentimental-Stock-Prediction/

License:GNU General Public License v3.0


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