https://github.com/The-Swarm-Corporation/Open-Aladdin
An open source risk-management tool built for stock and security risk analysis
https://github.com/The-Swarm-Corporation/Open-Aladdin
blackrock finance real-time-ai risk-analysis risk-management stock-analysis wall-street xgboost
Last synced: 2 months ago
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An open source risk-management tool built for stock and security risk analysis
- Host: GitHub
- URL: https://github.com/The-Swarm-Corporation/Open-Aladdin
- Owner: The-Swarm-Corporation
- License: mit
- Created: 2024-10-14T21:33:41.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2025-06-30T23:12:16.000Z (3 months ago)
- Last Synced: 2025-07-06T05:48:29.674Z (3 months ago)
- Topics: blackrock, finance, real-time-ai, risk-analysis, risk-management, stock-analysis, wall-street, xgboost
- Language: Python
- Homepage: https://discord.com/servers/agora-999382051935506503
- Size: 2.18 MB
- Stars: 24
- Watchers: 1
- Forks: 6
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
- License: LICENSE
Awesome Lists containing this project
- awesome-swarms-list - Open-Aladdin
README
# open-aladdin
[](https://discord.gg/agora-999382051935506503) [](https://www.youtube.com/@kyegomez3242) [](https://www.linkedin.com/in/kye-g-38759a207/) [](https://x.com/kyegomezb)
open-aladdin is an open-source risk analysis and portfolio management system inspired by BlackRock's Aladdin platform. It aims to provide comprehensive risk assessment and management tools for stocks, securities, and other market instruments.
## Table of Contents
- [Features](#features)
- [Installation](#installation)
- [Usage](#usage)
- [Contributing](#contributing)
- [License](#license)
## Features
- **Comprehensive Risk Analysis**: Assess risk for a wide range of financial instruments including stocks, bonds, derivatives, and more.
- **Real-Time Data Processing**: Continuously update risk assessments based on market changes.
- **Advanced Machine Learning Models**: Utilize state-of-the-art ML algorithms for predictive analytics and risk forecasting.
- **Customizable Risk Metrics**: Calculate and track various risk measures including VaR, Expected Shortfall, and custom metrics.
- **Portfolio Optimization**: Tools for constructing and rebalancing portfolios based on risk-return profiles.
- **Interactive Dashboards**: Visualize risk data and portfolio performance through customizable dashboards.
- **API Integration**: Easy integration with external data sources and other financial systems.
## Installation
To install open-aladdin, run the following command:
```bash
pip install open-aladdin
```
## Usage
## Example
```python
from open_aladdin.main import fetch_stock_data, AdvancedRealTimeRiskAssessment
import time
if __name__ == "__main__":
# Example usage
# from data_integration import fetch_stock_data
tickers = [
"AAPL",
"GOOGL",
"MSFT",
"AMZN",
"^GSPC",
] # Including S&P 500 for market returns
historical_data = {
ticker: fetch_stock_data(ticker) for ticker in tickers
}
risk_assessor = AdvancedRealTimeRiskAssessment(historical_data)
risk_assessor.start_continuous_training()
try:
# Run for a while to allow some training iterations
time.sleep(60)
# Perform risk assessment
risk_results = risk_assessor.run_risk_assessment(
forecast_horizon=4
) # 1-year forecast
# Output results
risk_assessor.output_results(risk_results, "json")
risk_assessor.output_results(risk_results, "csv")
# Print some results
for ticker, measures in risk_results.items():
print(f"\nRisk Assessment for {ticker}:")
for measure, value in measures.items():
if isinstance(value, list):
print(
f"{measure}: [showing first 5 values] {value[:5]}"
)
else:
print(f"{measure}: {value:.4f}")
finally:
# Ensure we stop the continuous training when done
risk_assessor.stop_continuous_training()
```
For more detailed usage examples and API documentation, please visit our [User Guide](docs/user_guide.md).
## Contributing
We welcome contributions from the community! If you'd like to contribute to open-aladdin, please follow these steps:
1. Fork the repository
2. Create your feature branch (`git checkout -b feature/AmazingFeature`)
3. Commit your changes (`git commit -m 'Add some AmazingFeature'`)
4. Push to the branch (`git push origin feature/AmazingFeature`)
5. Open a Pull Request
Please read our [Contributing Guidelines](CONTRIBUTING.md) for more details on our code of conduct, and the process for submitting pull requests.
## License