📈 Stock Market Prediction App

An AI-powered stock price prediction web application using LightGBM machine learning and real-time Yahoo Finance data.

✨ Features

• Real-time Stock Data - Live prices from Yahoo Finance API
• AI Price Predictions - Next-day price predictions using LightGBM
• Multi-Stock Support - Track 10+ popular stocks (AAPL, GOOGL, MSFT, TSLA, etc.)
• Technical Indicators - RSI, MACD, ATR, Moving Averages, Volatility
• Smart Caching - Built-in rate limiting and caching to prevent API blocks
• Modern UI - Clean, responsive web interface

🚀 Quick Start

Prerequisites

• Python 3.10+
• pip

Installation

# Clone the repository
git clone https://github.com/muhammadtihame/StockMarketPredictionApp.git
cd StockMarketPredictionApp

# Install dependencies
pip install -r requirements.txt

# Run the app
python app.py

Open your browser and navigate to http://127.0.0.1:5000

🧠 Model Architecture

Training Details

The model was trained using LightGBM Regressor on historical AAPL stock data.

Parameter	Value
Algorithm	LightGBM Regressor
Estimators	3,000
Learning Rate	0.01
Max Depth	6
Num Leaves	48
Subsample	0.75
Column Sample	0.75
Early Stopping	100 rounds

Feature Engineering (16 Features)

Category	Features
Price Lags	close_lag_1, close_lag_2, close_lag_3, close_lag_5
Volume	volume_lag_1
Moving Averages	ma7, ma21, ma50
Price/MA Ratios	price_ma7, price_ma21
Returns	return_1, return_5
Volatility	volatility_20
Technical Indicators	rsi_14, macd, atr_14

Model Performance

• Directional Accuracy: ~53-55% (predicting up/down movement)
• Target: Next-day percentage return prediction

📁 Project Structure

StockMarketPredictionApp/
├── app.py                  # Flask backend
├── lgbm_aapl_model.pkl     # Trained LightGBM model
├── target_scaler.pkl       # RobustScaler for target
├── requirements.txt        # Python dependencies
├── static/
│   └── style.css           # CSS styling
└── templates/
    └── index.html          # Frontend template

🔌 API Endpoints

Endpoint	Method	Description
/	GET	Main web interface
/api/stocks	GET	Get all popular stock quotes
/api/predict/<symbol>	GET	Get prediction for a stock
/api/health	GET	Health check endpoint
/api/clear-cache	GET	Clear cached data

Example API Response

{
  "success": true,
  "data": {
    "symbol": "AAPL",
    "company_name": "Apple Inc.",
    "current_price": 185.50,
    "predicted_price": 186.25,
    "price_change": 0.75,
    "price_change_pct": 0.40,
    "prediction_date": "2026-01-16",
    "indicators": {
      "rsi_14": 55.32,
      "macd": 0.0012,
      "ma7": 184.20,
      "ma21": 182.50,
      "ma50": 180.10,
      "volatility": 1.25,
      "atr": 2.85
    }
  }
}

🛠️ Tech Stack

• Backend: Flask 3.0
• ML Framework: LightGBM 4.2
• Data Processing: Pandas, NumPy
• Data Source: Yahoo Finance API
• Scaling: Scikit-learn RobustScaler

⚠️ Disclaimer

This application is for educational purposes only. Stock market predictions are inherently uncertain, and this tool should not be used as the sole basis for investment decisions. Always consult with a qualified financial advisor before making investment choices.

📄 License

MIT License - feel free to use and modify for your own projects.

👨‍💻 Author

Muhammad Tihame

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