| ---
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| title: Dynamic Allocation System
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| emoji: 📈
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| colorFrom: blue
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| colorTo: green
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| sdk: docker
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| app_file: app.py
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| pinned: false
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| ---
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| # Dynamic Portfolio Allocation System
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| A machine learning-based portfolio allocation system that combines supervised learning and reinforcement learning to generate dynamic stock allocation recommendations.
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| ## Technologies Used
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| - Python
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| - Streamlit
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| - Gradient Boosting Regression
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| - PPO Reinforcement Learning
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| - Plotly
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| - Scikit-learn
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| - Stable-Baselines3
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| ## Features
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| - Dynamic portfolio allocation
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| - Risk profile selection
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| - 5-day and 10-day investment horizons
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| - Cash reserve optimization
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| - Portfolio visualization
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| - PPO vs Equal Weight comparison
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| - Portfolio insights
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| - Download portfolio as CSV
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| ## Project Workflow
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| 1. Feature Engineering
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| 2. Gradient Boosting Return Prediction
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| 3. PPO Reinforcement Learning Allocation
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| 4. Portfolio Recommendation
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| 5. Interactive Dashboard
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| Developed as a Final Year Project. |
