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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

A smart, experimental market analysis toolkit that stitches together AI‑powered sentiment scoring, core fundamental metrics, and analyst trend data to generate rough buy/hold/sell suggestions. It pulls from real‑time news, checks company fundamentals, and merges multiple signals into a single, easy‑to‑read snapshot.

  • Updated Aug 29, 2025
  • Python

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