This project highlights time series analysis of historical stock prices and sentimental analysis of news headlines.
The historical stock prices dataset has been extracted from https://finance.yahoo.com/ and the news headlines data is used from https://bit.ly/36fFPI6.
I have used Auto-ARIMA model to make stock market prices predictions using the historical stock prices data. In the sentiment analysis model, I have made use of different machine learning algorithms-Random Forest Regressor, LightGBM, Adaboost and Xgboost- to make the predictions.
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This project is a part of The Sparks Foundation GRIP internship which highlights time series analysis of historical stock prices and sentimental analysis of news headlines.
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