RajdeepBiswas/Stock_Market_Prediction_with_SnP500
This project would demonstrate the following capabilities: 1. Extraction Loading and Transformation of S&P 500 data and company fundamentals. 2. Exploratory and Time Series Data Analysis on top of the stock data. 3. Stock Screener based on fundamentals. 4. Stock Price Prediction using multiple and/or an ensemble of machine learning models.
This project helps financial traders and investors predict future stock prices and sector movements for S&P 500 companies. It takes historical daily trading data, dividend information, stock splits, and company fundamentals as input. The output is a prediction of whether a stock or sector will rise or fall, aiding in investment decisions.
No commits in the last 6 months.
Use this if you are a trader or investor looking for a system to help predict stock and sector price movements to inform your investment strategy.
Not ideal if you believe in the efficient-market hypothesis and think stock prices are inherently unpredictable.
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14
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7
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Sep 26, 2021
Commits (30d)
0
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