{"id":26149238,"url":"https://github.com/himanshubhosale25/binance_trade_analysis","last_synced_at":"2026-04-24T10:02:43.035Z","repository":{"id":277035554,"uuid":"931121320","full_name":"HimanshuBhosale25/Binance_Trade_Analysis","owner":"HimanshuBhosale25","description":"This project analyzes 90 days of Binance trade data to rank accounts based on risk-adjusted performance. 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The goal is to **rank accounts based on risk-adjusted performance**, identifying the top 20 accounts that demonstrate both **profitability and stability**.\n\n📊 **Key Features**\n-------------------\n\n✔️ **Financial Metrics Calculation:** ROI, PnL, Sharpe Ratio, MDD, Win Rate, etc.\\\n✔️ **Risk-Aware Ranking System:** Prioritizes stable and consistent traders over high-risk ones.\\\n✔️ **Feature Engineering:** Extracts insights from trade data and assigns weighted scores.\\\n✔️ **Top 20 Accounts List:** Identifies the best-performing accounts based on calculated scores.\n\n🏗 **Project Structure**\n------------------------\n``` sh\n📂 Binance_Trade_Analysis/\n│── 📜 primetrade_analysis.ipynb   # Jupyter Notebook with full analysis\n│── 📜 Binance_Trade_Analysis_Report.pdf   # Final report detailing findings\n│── 📜 metrics_results.csv   # CSV file with calculated metrics\n│── 📜 README.md   # Project documentation (this file)\n```\n⚙️ **Methodology**\n------------------\n\n1️⃣ **Data Exploration \u0026 Cleaning** -- Loaded and processed the dataset, handled missing values.\\\n2️⃣ **Feature Engineering** -- Calculated key performance metrics like ROI, MDD, and Win Rate.\\\n3️⃣ **Ranking Algorithm** -- Developed a custom ranking system based on risk-adjusted metrics.\\\n4️⃣ **Scoring System** -- Assigned weights to different metrics to balance profitability and risk.\\\n5️⃣ **Evaluation \u0026 Insights** -- Identified the **top 20 best-performing accounts** based on the ranking.\n\n📌 **Findings \u0026 Challenges**\n----------------------------\n\n🔹 The biggest challenge was balancing **high profitability** with **risk mitigation**.\\\n🔹 Some accounts had **high profits but large drawdowns**, making them unstable.\\\n🔹 The final ranking prioritized **Win Rate \u0026 Sharpe Ratio** to ensure **consistent performance**.\\\n🔹 Testing different metric weightings helped **fine-tune the scoring system**.\n\n📂 **Deliverables**\n-------------------\n\n✅ **Jupyter Notebook** -- Full analysis and code implementation.\\\n✅ **CSV File** -- Contains calculated metrics for all accounts.\\\n✅ **Top 20 Accounts List** -- Best-performing accounts based on the ranking.\\\n✅ **Report** -- Summary of methodology, findings, and assumptions.\n\n🚀 **How to Use**\n-----------------\n\n1️⃣ Clone the repository:\n``` sh\ngit clone https://github.com/HimanshuBhosale25/Binance_Trade_Analysis.git\n```\n\n2️⃣ Open the Jupyter Notebook (`primetrade_analysis.ipynb`) and run the analysis.\\\n3️⃣ Check the `metrics_results.csv` file for calculated metrics.\\\n4️⃣ Read the report (`Binance_Trade_Analysis_Report.pdf`) for detailed insights.\n\n🏆 **Conclusion**\n-----------------\n\nThis project successfully provides a **structured and risk-aware ranking system** for Binance accounts, ensuring that top-performing traders are both **profitable and consistent**.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhimanshubhosale25%2Fbinance_trade_analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhimanshubhosale25%2Fbinance_trade_analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhimanshubhosale25%2Fbinance_trade_analysis/lists"}