📊 QuantVision — AI-Powered Stock Analysis & Trading Dashboard

QuantVision is an end-to-end quantitative finance platform that combines machine learning, technical analysis, and interactive visualization to analyze financial markets and generate actionable trading insights.

The system integrates real-time analytics, predictive modeling, and an interactive dashboard to simulate a professional-grade trading research environment.

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🚀 Key Highlights

• 📈 Interactive stock dashboard built with Streamlit
• 🤖 Machine Learning-based price direction prediction
• 📊 Advanced technical indicators (RSI, MACD, Bollinger Bands)
• 🔍 Pattern recognition (Head & Shoulders, Double Bottom, etc.)
• 📉 Trend analysis with support & resistance levels
• 💬 AI-powered chatbot for financial insights
• ⚡ Modern UI with real-time visualizations (Plotly)

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🧠 System Architecture

The project is structured as a modular pipeline:

1. Data Collection
2. Feature Engineering
3. Indicator & Pattern Analysis
4. Machine Learning Model Prediction
5. Visualization via Dashboard
6. User Interaction via AI Chatbot

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🎯 Use Case

QuantVision simulates a quantitative trading research tool, enabling users to:

• Analyze stock behavior
• Detect technical patterns
• Evaluate market risk
• Generate predictive signals
• Interact with AI for insights

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📊 Dashboard Preview

🎥 Demo Video

Watch QuantVision in action:

QuantVision.Stock.Analysis.-.Google.Chrome.2026-03-19.00-48-53.mp4

🤖 Machine Learning Model

• Model: Classification (Up/Down Prediction)

• Features:

  • Price returns (1D, 3D, 5D, 10D)
  • Moving averages & ratios
  • Volatility (ATR)
  • Volume-based features
  • Momentum indicators

• Output:

  • Direction (UP / DOWN)
  • Confidence Score
  • Model Accuracy

⚠️ Risk Analysis Engine

QuantVision evaluates market risk using:

• RSI overbought/oversold signals
• MACD trend confirmation
• Trend direction analysis

Risk levels:

• 🔴 High Risk
• 🟡 Medium Risk
• 🟢 Low Risk

💬 AI Financial Assistant

An integrated chatbot allows users to:

• Ask stock-related questions
• Get indicator-based insights
• Understand trends and predictions

Example queries:

• "Will AAPL go up tomorrow?"
• "Is TSLA high risk?"

▶️ Run the Dashboard

streamlit run app/dashboard.py

⭐ Why This Project Stands Out

• Combines Quantitative Finance + Machine Learning + UI Engineering
• Simulates a real-world trading analytics platform
• Demonstrates end-to-end system design