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news-sentiment

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In this work, the application of the Triple-Barrier Method and Meta-Labeling techniques are explored using XGBoost to develop a sentiment-based trading signal for the S&P 500 stock market index. The results indicate that sentiment data possess predictive power; however, substantial work remains before a fully implementable strategy can be realized.

  • Updated Feb 25, 2024
  • Jupyter Notebook

📈 Telegram bot that delivers comprehensive US stock analysis combining real-time technical data, AI-powered news sentiment, and fundamental metrics. Get dual-timeframe recommendations for day trading and long-term investing.

  • Updated Sep 30, 2025

AI-powered stock analysis & prediction system. Flask backend + yfinance + XGBoost classifier + VADER sentiment + Ridge forecasting. Real-time technicals, risk assessment, BUY/HOLD/SELL recommendations. Live news only. No API keys required.

  • Updated Jun 6, 2026
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