# 🚀 MeridianAlgo Smart Trader
**Ultra-Accurate AI Stock Analysis with Universal GPU Support**
[](https://badge.fury.io/py/meridianalgo-smarttrader)
[](https://www.python.org/downloads/)
[](https://opensource.org/licenses/MIT)
[](https://github.com/MeridianAlgo/In-Python)
Professional-grade stock analysis powered by ensemble machine learning with universal GPU acceleration. Features advanced volatility spike detection and real-time technical analysis.
## ✨ Key Features
- 🎯 **Ultra-Accurate Predictions**: Ensemble ML models (LSTM + Transformer + XGBoost)
- 🔥 **Universal GPU Support**: AMD • Intel • NVIDIA • Apple Silicon
- ⚡ **Volatility Spike Detection**: Predict market turbulence before it happens
- 📊 **Real-time Analysis**: Live market data with technical indicators
- 🎨 **Clean Output**: Simplified, essential information only
- 🚀 **Easy Integration**: Simple Python API and CLI
## 🚀 Quick Start
### Installation
```bash
pip install meridianalgo-smarttrader
```
### Command Line Usage
```bash
# Analyze Apple stock
smart-trader AAPL
# Custom parameters
smart-trader TSLA --days 90 --epochs 15
# Show GPU information
smart-trader --gpu-info
```
### Python API Usage
```python
from meridianalgo import SmartTrader, analyze_stock
# Simple analysis
result = analyze_stock('AAPL')
print(f"Current: ${result['current_price']:.2f}")
print(f"Tomorrow: ${result['predictions'][0]:.2f}")
# Advanced usage
trader = SmartTrader(verbose=True)
analysis = trader.analyze('TSLA', days=60, epochs=10)
# Check volatility spike risk
vol_risk = analysis['volatility_spike']['spike_probability']
if vol_risk > 60:
print("⚠️ High volatility spike risk detected!")
```
## 📊 Sample Output
```
🚀 AAPL Analysis
Device: CPU (8 threads)
┌────────────┬──────────┬──────────────────┐
│ Metric │ Value │ Info │
├────────────┼──────────┼──────────────────┤
│ Current │ $213.96 │ Real-time │
│ Day +1 │ $216.45 │ +1.2% │
│ Day +2 │ $218.30 │ +2.0% │
│ Day +3 │ $215.80 │ +0.9% │
│ Confidence │ 84% │ Model reliability│
│ Vol Risk │ 23% │ ✅ Low risk │
└────────────┴──────────┴──────────────────┘
```
## 🔥 Universal GPU Support
Smart Trader automatically detects and optimizes for your GPU:
| Vendor | Technology | Status |
|--------|------------|--------|
| 🟢 NVIDIA | CUDA | ✅ Supported |
| 🔴 AMD | ROCm/DirectML | ✅ Supported |
| 🔵 Intel | XPU | ✅ Supported |
| 🍎 Apple | MPS | ✅ Supported |
### GPU Setup
```bash
# NVIDIA GPU
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121
# AMD GPU (Windows)
pip install torch-directml
# Intel GPU
pip install intel-extension-for-pytorch
# Apple Silicon (automatic)
pip install torch torchvision torchaudio
```
## ⚡ Volatility Spike Detection
Smart Trader's advanced algorithm analyzes historical volatility patterns to predict future market turbulence:
```python
from meridianalgo import detect_volatility_spikes
import yfinance as yf
# Get stock data
data = yf.Ticker('AAPL').history(period='1y')
# Detect volatility spikes
spike_info = detect_volatility_spikes(data)
print(f"Spike Probability: {spike_info['spike_probability']:.1f}%")
print(f"Expected in: {spike_info['expected_spike_days']} days")
print(f"Risk Level: {spike_info['risk_level']}")
```
## 🎯 Advanced Features
### Ensemble Models
- **LSTM**: Captures long-term dependencies
- **Transformer**: Attention-based pattern recognition
- **XGBoost**: Gradient boosting for robustness
### Technical Indicators
- RSI (Relative Strength Index)
- MACD (Moving Average Convergence Divergence)
- Bollinger Bands
- Volume analysis
### Risk Management
- Volatility spike prediction
- Market regime detection
- Confidence scoring
- Position sizing recommendations
## 📈 Performance
| Metric | CPU | GPU |
|--------|-----|-----|
| Training Time (10 epochs) | ~2-3 seconds | ~0.5-1 seconds |
| Batch Size | 32 | 64+ |
| Memory Usage | 2-4 GB RAM | GPU VRAM |
| Accuracy | High | Higher |
## 🛠️ Development
### Local Installation
```bash
git clone https://github.com/MeridianAlgo/In-Python.git
cd In-Python
pip install -e .
```
### Running Tests
```bash
pytest tests/
```
### Building Package
```bash
python setup.py sdist bdist_wheel
twine upload dist/*
```
## 📚 Documentation
- [GPU Setup Guide](GPU_SETUP_GUIDE.md)
- [API Reference](docs/api.md)
- [Examples](examples/)
- [Contributing](CONTRIBUTING.md)
## 🤝 Contributing
We welcome contributions! Please see our [Contributing Guide](CONTRIBUTING.md) for details.
## 📄 License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## 🔗 Links
- **PyPI**: https://pypi.org/project/meridianalgo/
- **GitHub**: https://github.com/MeridianAlgo/In-Python
- **Documentation**: https://meridianalgo.github.io/In-Python/
- **Issues**: https://github.com/MeridianAlgo/In-Python/issues
## 🏆 About MeridianAlgo
MeridianAlgo specializes in advanced financial AI solutions. Our mission is to democratize professional-grade trading tools through cutting-edge machine learning and universal GPU acceleration.
---
**Made with ❤️ by MeridianAlgo**
*Empowering traders with AI-driven insights*
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"description": "# \ud83d\ude80 MeridianAlgo Smart Trader\r\n\r\n**Ultra-Accurate AI Stock Analysis with Universal GPU Support**\r\n\r\n[](https://badge.fury.io/py/meridianalgo-smarttrader)\r\n[](https://www.python.org/downloads/)\r\n[](https://opensource.org/licenses/MIT)\r\n[](https://github.com/MeridianAlgo/In-Python)\r\n\r\nProfessional-grade stock analysis powered by ensemble machine learning with universal GPU acceleration. Features advanced volatility spike detection and real-time technical analysis.\r\n\r\n## \u2728 Key Features\r\n\r\n- \ud83c\udfaf **Ultra-Accurate Predictions**: Ensemble ML models (LSTM + Transformer + XGBoost)\r\n- \ud83d\udd25 **Universal GPU Support**: AMD \u2022 Intel \u2022 NVIDIA \u2022 Apple Silicon\r\n- \u26a1 **Volatility Spike Detection**: Predict market turbulence before it happens\r\n- \ud83d\udcca **Real-time Analysis**: Live market data with technical indicators\r\n- \ud83c\udfa8 **Clean Output**: Simplified, essential information only\r\n- \ud83d\ude80 **Easy Integration**: Simple Python API and CLI\r\n\r\n## \ud83d\ude80 Quick Start\r\n\r\n### Installation\r\n\r\n```bash\r\npip install meridianalgo-smarttrader\r\n```\r\n\r\n### Command Line Usage\r\n\r\n```bash\r\n# Analyze Apple stock\r\nsmart-trader AAPL\r\n\r\n# Custom parameters\r\nsmart-trader TSLA --days 90 --epochs 15\r\n\r\n# Show GPU information\r\nsmart-trader --gpu-info\r\n```\r\n\r\n### Python API Usage\r\n\r\n```python\r\nfrom meridianalgo import SmartTrader, analyze_stock\r\n\r\n# Simple analysis\r\nresult = analyze_stock('AAPL')\r\nprint(f\"Current: ${result['current_price']:.2f}\")\r\nprint(f\"Tomorrow: ${result['predictions'][0]:.2f}\")\r\n\r\n# Advanced usage\r\ntrader = SmartTrader(verbose=True)\r\nanalysis = trader.analyze('TSLA', days=60, epochs=10)\r\n\r\n# Check volatility spike risk\r\nvol_risk = analysis['volatility_spike']['spike_probability']\r\nif vol_risk > 60:\r\n print(\"\u26a0\ufe0f High volatility spike risk detected!\")\r\n```\r\n\r\n## \ud83d\udcca Sample Output\r\n\r\n```\r\n\ud83d\ude80 AAPL Analysis\r\nDevice: CPU (8 threads)\r\n\r\n\u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2510\r\n\u2502 Metric \u2502 Value \u2502 Info \u2502\r\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\r\n\u2502 Current \u2502 $213.96 \u2502 Real-time \u2502\r\n\u2502 Day +1 \u2502 $216.45 \u2502 +1.2% \u2502\r\n\u2502 Day +2 \u2502 $218.30 \u2502 +2.0% \u2502\r\n\u2502 Day +3 \u2502 $215.80 \u2502 +0.9% \u2502\r\n\u2502 Confidence \u2502 84% \u2502 Model reliability\u2502\r\n\u2502 Vol Risk \u2502 23% \u2502 \u2705 Low risk \u2502\r\n\u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518\r\n```\r\n\r\n## \ud83d\udd25 Universal GPU Support\r\n\r\nSmart Trader automatically detects and optimizes for your GPU:\r\n\r\n| Vendor | Technology | Status |\r\n|--------|------------|--------|\r\n| \ud83d\udfe2 NVIDIA | CUDA | \u2705 Supported |\r\n| \ud83d\udd34 AMD | ROCm/DirectML | \u2705 Supported |\r\n| \ud83d\udd35 Intel | XPU | \u2705 Supported |\r\n| \ud83c\udf4e Apple | MPS | \u2705 Supported |\r\n\r\n### GPU Setup\r\n\r\n```bash\r\n# NVIDIA GPU\r\npip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121\r\n\r\n# AMD GPU (Windows)\r\npip install torch-directml\r\n\r\n# Intel GPU\r\npip install intel-extension-for-pytorch\r\n\r\n# Apple Silicon (automatic)\r\npip install torch torchvision torchaudio\r\n```\r\n\r\n## \u26a1 Volatility Spike Detection\r\n\r\nSmart Trader's advanced algorithm analyzes historical volatility patterns to predict future market turbulence:\r\n\r\n```python\r\nfrom meridianalgo import detect_volatility_spikes\r\nimport yfinance as yf\r\n\r\n# Get stock data\r\ndata = yf.Ticker('AAPL').history(period='1y')\r\n\r\n# Detect volatility spikes\r\nspike_info = detect_volatility_spikes(data)\r\n\r\nprint(f\"Spike Probability: {spike_info['spike_probability']:.1f}%\")\r\nprint(f\"Expected in: {spike_info['expected_spike_days']} days\")\r\nprint(f\"Risk Level: {spike_info['risk_level']}\")\r\n```\r\n\r\n## \ud83c\udfaf Advanced Features\r\n\r\n### Ensemble Models\r\n- **LSTM**: Captures long-term dependencies\r\n- **Transformer**: Attention-based pattern recognition \r\n- **XGBoost**: Gradient boosting for robustness\r\n\r\n### Technical Indicators\r\n- RSI (Relative Strength Index)\r\n- MACD (Moving Average Convergence Divergence)\r\n- Bollinger Bands\r\n- Volume analysis\r\n\r\n### Risk Management\r\n- Volatility spike prediction\r\n- Market regime detection\r\n- Confidence scoring\r\n- Position sizing recommendations\r\n\r\n## \ud83d\udcc8 Performance\r\n\r\n| Metric | CPU | GPU |\r\n|--------|-----|-----|\r\n| Training Time (10 epochs) | ~2-3 seconds | ~0.5-1 seconds |\r\n| Batch Size | 32 | 64+ |\r\n| Memory Usage | 2-4 GB RAM | GPU VRAM |\r\n| Accuracy | High | Higher |\r\n\r\n## \ud83d\udee0\ufe0f Development\r\n\r\n### Local Installation\r\n\r\n```bash\r\ngit clone https://github.com/MeridianAlgo/In-Python.git\r\ncd In-Python\r\npip install -e .\r\n```\r\n\r\n### Running Tests\r\n\r\n```bash\r\npytest tests/\r\n```\r\n\r\n### Building Package\r\n\r\n```bash\r\npython setup.py sdist bdist_wheel\r\ntwine upload dist/*\r\n```\r\n\r\n## \ud83d\udcda Documentation\r\n\r\n- [GPU Setup Guide](GPU_SETUP_GUIDE.md)\r\n- [API Reference](docs/api.md)\r\n- [Examples](examples/)\r\n- [Contributing](CONTRIBUTING.md)\r\n\r\n## \ud83e\udd1d Contributing\r\n\r\nWe welcome contributions! Please see our [Contributing Guide](CONTRIBUTING.md) for details.\r\n\r\n## \ud83d\udcc4 License\r\n\r\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\r\n\r\n## \ud83d\udd17 Links\r\n\r\n- **PyPI**: https://pypi.org/project/meridianalgo/\r\n- **GitHub**: https://github.com/MeridianAlgo/In-Python\r\n- **Documentation**: https://meridianalgo.github.io/In-Python/\r\n- **Issues**: https://github.com/MeridianAlgo/In-Python/issues\r\n\r\n## \ud83c\udfc6 About MeridianAlgo\r\n\r\nMeridianAlgo specializes in advanced financial AI solutions. Our mission is to democratize professional-grade trading tools through cutting-edge machine learning and universal GPU acceleration.\r\n\r\n---\r\n\r\n**Made with \u2764\ufe0f by MeridianAlgo**\r\n\r\n*Empowering traders with AI-driven insights*\r\n",
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