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#

news-sentiment

Here are 20 public repositories matching this topic...

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

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
  • HTML

News sentiment score trends as a Python API client and MCP tool. Positive/negative sentiment over time, weekly or daily series, growth percentages. Powered by trendsmcp.ai

  • Updated Mar 31, 2026
  • Python

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