{"id":26506346,"url":"https://github.com/netbr3ak/stockscorepro","last_synced_at":"2026-05-04T12:34:58.143Z","repository":{"id":282280065,"uuid":"948054184","full_name":"NetBr3ak/StockScorePro","owner":"NetBr3ak","description":"StockScorePro is a clear, intelligent, and data-driven investment tool that evaluates stocks based on their current price relative to their 50-day moving average. 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It identifies attractive investment opportunities by evaluating price stability, closeness to average pricing, and potential undervaluation. 💰📊\n\nThis tool is ideal when you have a specific list of companies you'd like to invest in long-term. You manually enter your favorite companies' stock tickers directly into the script, and StockScorePro will take care of the analysis for you.\n\n---\n\n## 🚀 **How Does StockScorePro Work?**\n\nStockScorePro evaluates each stock using three clear indicators:\n\n- **Stability 🧘**:  \n  *How stable has the stock’s average price been recently?*  \n  **Example:** If a stock’s average price has barely changed in recent days, it scores close to 1 (very stable).\n\n- **Closeness 🎯**:  \n  *How close is the current stock price to its 50-day average?*  \n  **Example:** If a stock’s current price matches its 50-day average, the Closeness score is 1 (perfect match).\n\n- **ExtraValue ✨**:  \n  *Is the stock priced below its 50-day average, potentially offering extra value?*  \n  **Example:** A stock trading 5% below its average receives a 5% bonus (ExtraValue score: 1.05).\n\nThese indicators combine into a single **OverallScore 🏅**, making it easy for you to spot attractive investment opportunities quickly.\n\n---\n\n## 🛠️ **Installation \u0026 Quick Start**\n\nFollow these simple steps to start using StockScorePro:\n\n### **1. Install Required Libraries**\n\n```bash  \npip install yfinance pandas numpy  \n```\n\n### **2. Customize the List of Companies**\n\n- Open the `stockscorepro.py` file.\n- Find the list named `tickers`.\n- Replace the provided tickers with your preferred long-term investment companies.\n\n### **3. Run StockScorePro**\n\nSave your changes and run the script:\n\n```bash  \npython stockscorepro.py  \n```\n\nYou will be prompted to enter your monthly investment amount (e.g., 1500).\n\n---\n\n## 🔍 **Example Results**\n\nWhen you run StockScorePro, you'll get clear results like this:\n\n```bash  \nEvaluation results (higher OverallScore indicates a potentially better investment):\n\n    Company  LatestPrice  50DayAverage  PriceDifferencePercent  Stability  Closeness  ExtraValue  OverallScore\n      Apple        145.3          150.0                  -0.031      0.980      0.920       1.031          0.930\n  Microsoft        290.5          289.0                   0.005      0.995      0.990       1.000          0.985\n       Nike        120.2          125.0                  -0.038      0.970      0.880       1.038          0.886\n\nProposed investment distribution based on your monthly budget:\n\n    Company  InvestmentFraction  InvestmentAmount\n      Apple              0.332             996.00\n  Microsoft              0.352            1056.00\n       Nike              0.316             948.00\n\nAnalysis completed on: 2025-03-13 15:45:30  \n```\n\n---\n\n## 📌 **Why Use StockScorePro?**\n\n- ✅ **Clear \u0026 Practical**: Easily identify attractive stocks without complicated analysis.\n- ✅ **Data-Driven**: Make decisions using reliable market information.\n- ✅ **Time Efficient**: Quickly evaluate multiple stocks simultaneously.\n- ✅ **Optimized Investment**: Automatically distribute your capital efficiently.\n\n---\n\n## ⚠️ **Important Disclaimer**\n\nStockScorePro is intended for educational purposes. Always do additional research before investing. Investing involves risk, and past performance does not guarantee future returns.\n\n---\n\n## 📩 **Contact \u0026 Contribution**\n\nGot feedback or questions? Feel free to reach out and help improve StockScorePro!\n\n💡 **Happy Investing!** 🚀🌟\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnetbr3ak%2Fstockscorepro","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnetbr3ak%2Fstockscorepro","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnetbr3ak%2Fstockscorepro/lists"}