quarterpastten/Sentiment-Analysis-and-Stock-Prices
A Deep Learning Sentiment Analysis on News Headlines using FinBERT (Python)
This project helps financial analysts and traders understand if there's a connection between financial news headlines and stock price movements. It takes raw financial news headlines and corresponding stock prices, then processes them to produce sentiment scores for each headline and analyzes their correlation with stock prices over time. This is for someone who wants to explore the relationship between market sentiment from news and stock performance.
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Use this if you are a financial analyst or trader interested in exploring historical correlations between specific news sentiment and stock price changes.
Not ideal if you need a predictive model for stock prices or real-time sentiment analysis for immediate trading decisions.
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Apr 03, 2023
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