# 🚀 DERIVFLOW-FINANCE
**Advanced Derivatives Analytics Platform for Quantitative Finance**
[](https://badge.fury.io/py/derivflow-finance)
[](https://pypi.org/project/derivflow-finance/)
[](https://opensource.org/licenses/MIT)
[](https://pepy.tech/project/derivflow-finance)
**DERIVFLOW-FINANCE** is a comprehensive, professional-grade derivatives analytics platform built for quantitative finance professionals, researchers, and institutions. It provides advanced pricing models, risk analytics, and portfolio management tools with institutional-quality accuracy and performance.
## 🌟 **Key Features**
### 📊 **Advanced Pricing Models**
- **Multiple Methodologies**: Black-Scholes analytical, Binomial trees, Monte Carlo simulation
- **Exotic Options**: Barrier options (all variants), Asian options (arithmetic/geometric)
- **Stochastic Models**: Heston stochastic volatility model with calibration
- **Greeks Calculation**: Complete 1st, 2nd, and 3rd order Greeks with advanced sensitivities
### 💹 **Real-Time Market Data**
- **Live Data Integration**: Yahoo Finance API with intelligent caching
- **Options Chains**: Complete options data with implied volatilities
- **Historical Analytics**: Volatility calculation and risk-free rate extraction
- **Market Status**: Real-time market hours and trading status
### 📈 **Professional Risk Management**
- **Portfolio Analytics**: Multi-asset portfolio construction and valuation
- **VaR Calculation**: Parametric and Monte Carlo Value-at-Risk
- **Scenario Analysis**: Stress testing with custom scenarios
- **Hedging Optimization**: Delta hedging and risk minimization
### 🎨 **Interactive Visualizations**
- **3D Volatility Surfaces**: Professional volatility modeling with interpolation
- **Greeks Dashboards**: Interactive sensitivity analysis
- **Payoff Diagrams**: Option payoff and P&L visualization
- **Risk Charts**: Portfolio risk decomposition and analytics
## 🚀 **Quick Start**
### Installation
```bash
pip install derivflow-finance
```
### Basic Usage
```python
from derivflow import PricingEngine, GreeksCalculator, VolatilitySurface
# Price a European option
from derivflow.core import price_european_option
price = price_european_option(S=100, K=105, T=0.25, r=0.05, sigma=0.2, option_type='call')
print(f"Option Price: ${price:.2f}")
# Calculate Greeks
from derivflow.greeks import GreeksCalculator
calc = GreeksCalculator()
greeks = calc.calculate_greeks(S=100, K=105, T=0.25, r=0.05, sigma=0.2, option_type='call')
print(f"Delta: {greeks.delta:.4f}")
# Price exotic options
from derivflow.exotic import BarrierOptions, AsianOptions
# Barrier option
barrier = BarrierOptions()
result = barrier.price(S=100, K=105, H=95, T=0.25, r=0.05, sigma=0.2,
barrier_type='down_and_out', option_type='call')
print(f"Barrier Option: ${result.price:.4f}")
# Asian option with variance reduction
asian = AsianOptions()
result = asian.price(S=100, K=105, T=0.25, r=0.05, sigma=0.2,
option_type='call', asian_type='arithmetic')
print(f"Asian Option: ${result.price:.4f} ± {result.std_error:.4f}")
```
### Portfolio Risk Analytics
```python
from derivflow.portfolio import PortfolioRiskAnalyzer
# Create portfolio
portfolio = PortfolioRiskAnalyzer()
# Add positions
portfolio.add_stock_position('AAPL', quantity=100, current_price=150, volatility=0.25)
portfolio.add_option_position('AAPL', quantity=10, current_price=150,
strike=155, expiry=0.25, option_type='call', volatility=0.25)
# Calculate risk metrics
portfolio_value = portfolio.calculate_portfolio_value()
greeks = portfolio.calculate_portfolio_greeks()
var_95, es_95 = portfolio.calculate_var_parametric(0.95)
print(f"Portfolio Value: ${portfolio_value:,.2f}")
print(f"Portfolio Delta: {greeks['delta']:.2f}")
print(f"95% VaR: ${var_95:,.2f}")
```
### Volatility Surface Modeling
```python
from derivflow.volatility import create_sample_surface
# Create and build volatility surface
surface = create_sample_surface()
surface.build_surface()
# Get volatility smile
smile = surface.get_smile(expiry=0.25, num_points=10)
# Interpolate volatility
vol = surface.interpolate(strike=102, expiry=0.33)
print(f"Interpolated Volatility: {vol:.1%}")
```
## 🎯 **Advanced Features**
### Stochastic Volatility Models
```python
from derivflow.models import HestonModel
# Heston stochastic volatility
heston = HestonModel()
heston.set_parameters(v0=0.04, kappa=2.0, theta=0.04, sigma=0.3, rho=-0.7)
# Price with stochastic volatility
result = heston.price_option(S=100, K=105, T=0.25, r=0.05,
option_type='call', method='monte_carlo')
print(f"Heston Price: ${result.price:.4f}")
```
### Real-Time Market Data
```python
from derivflow.utils import AdvancedMarketData
# Get live market data
market_data = AdvancedMarketData()
price, timestamp = market_data.get_current_price('AAPL')
vol = market_data.get_historical_volatility('AAPL', days=30)
print(f"Current AAPL: ${price:.2f}")
print(f"30-day Volatility: {vol:.1%}")
```
## 📊 **Performance Benchmarks**
DERIVFLOW-FINANCE is optimized for institutional-grade performance:
- **Black-Scholes Pricing**: 4,000+ options per second
- **Monte Carlo Simulation**: 10,000 paths in <0.2 seconds
- **Asian Options**: 1,500x variance reduction with control variates
- **Greeks Calculation**: Complete sensitivity analysis in milliseconds
## 🎓 **Use Cases**
### **Investment Banking & Trading**
- Derivatives structuring and pricing
- Real-time risk management
- Volatility trading strategies
- Exotic products development
### **Academic Research**
- Financial engineering research
- Quantitative finance education
- PhD dissertations and papers
- Teaching materials and examples
### **Portfolio Management**
- Multi-asset portfolio construction
- Risk analytics and VaR calculation
- Hedging strategy optimization
- Stress testing and scenario analysis
### **Fintech Development**
- Pricing engines for trading platforms
- Risk management systems
- Regulatory compliance tools
- API development for financial services
## 🛠️ **Installation Options**
### Standard Installation
```bash
pip install derivflow-finance
```
### Development Installation
```bash
pip install derivflow-finance[dev]
```
### Full Installation (all features)
```bash
pip install derivflow-finance[visualization,testing,docs]
```
## 📚 **Documentation**
- **API Reference**: Complete function and class documentation
- **User Guide**: Step-by-step tutorials and examples
- **Theory Guide**: Mathematical foundations and model explanations
- **Examples**: Jupyter notebooks with real-world applications
## 🤝 **Contributing**
We welcome contributions from the quantitative finance community! Please see our [Contributing Guide](CONTRIBUTING.md) for details.
### Development Setup
```bash
git clone https://github.com/jeevanba273/derivflow-finance.git
cd derivflow-finance
pip install -e .[dev]
pytest tests/
```
## 📄 **License**
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## 🌟 **Acknowledgments**
- Built with modern Python scientific computing stack
- Inspired by quantitative finance research and industry best practices
- Designed for both academic research and commercial applications
## 📞 **Contact & Support**
- **Author**: Jeevan B A
- **Email**: jeevanba273@gmail.com
- **GitHub**: [@jeevanba273](https://github.com/jeevanba273)
- **Issues**: [GitHub Issues](https://github.com/jeevanba273/derivflow-finance/issues)
---
**⭐ Star this repository if DERIVFLOW-FINANCE helps your quantitative finance projects!**
**🚀 Built for the global quantitative finance community by Jeevan B A**
Raw data
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"description": "# \ud83d\ude80 DERIVFLOW-FINANCE\r\n\r\n**Advanced Derivatives Analytics Platform for Quantitative Finance**\r\n\r\n[](https://badge.fury.io/py/derivflow-finance)\r\n[](https://pypi.org/project/derivflow-finance/)\r\n[](https://opensource.org/licenses/MIT)\r\n[](https://pepy.tech/project/derivflow-finance)\r\n\r\n**DERIVFLOW-FINANCE** is a comprehensive, professional-grade derivatives analytics platform built for quantitative finance professionals, researchers, and institutions. It provides advanced pricing models, risk analytics, and portfolio management tools with institutional-quality accuracy and performance.\r\n\r\n## \ud83c\udf1f **Key Features**\r\n\r\n### \ud83d\udcca **Advanced Pricing Models**\r\n\r\n- **Multiple Methodologies**: Black-Scholes analytical, Binomial trees, Monte Carlo simulation\r\n- **Exotic Options**: Barrier options (all variants), Asian options (arithmetic/geometric)\r\n- **Stochastic Models**: Heston stochastic volatility model with calibration\r\n- **Greeks Calculation**: Complete 1st, 2nd, and 3rd order Greeks with advanced sensitivities\r\n\r\n### \ud83d\udcb9 **Real-Time Market Data**\r\n\r\n- **Live Data Integration**: Yahoo Finance API with intelligent caching\r\n- **Options Chains**: Complete options data with implied volatilities\r\n- **Historical Analytics**: Volatility calculation and risk-free rate extraction\r\n- **Market Status**: Real-time market hours and trading status\r\n\r\n### \ud83d\udcc8 **Professional Risk Management**\r\n\r\n- **Portfolio Analytics**: Multi-asset portfolio construction and valuation\r\n- **VaR Calculation**: Parametric and Monte Carlo Value-at-Risk\r\n- **Scenario Analysis**: Stress testing with custom scenarios\r\n- **Hedging Optimization**: Delta hedging and risk minimization\r\n\r\n### \ud83c\udfa8 **Interactive Visualizations**\r\n\r\n- **3D Volatility Surfaces**: Professional volatility modeling with interpolation\r\n- **Greeks Dashboards**: Interactive sensitivity analysis\r\n- **Payoff Diagrams**: Option payoff and P&L visualization\r\n- **Risk Charts**: Portfolio risk decomposition and analytics\r\n\r\n## \ud83d\ude80 **Quick Start**\r\n\r\n### Installation\r\n\r\n```bash\r\npip install derivflow-finance\r\n```\r\n\r\n### Basic Usage\r\n\r\n```python\r\nfrom derivflow import PricingEngine, GreeksCalculator, VolatilitySurface\r\n\r\n# Price a European option\r\nfrom derivflow.core import price_european_option\r\nprice = price_european_option(S=100, K=105, T=0.25, r=0.05, sigma=0.2, option_type='call')\r\nprint(f\"Option Price: ${price:.2f}\")\r\n\r\n# Calculate Greeks\r\nfrom derivflow.greeks import GreeksCalculator\r\ncalc = GreeksCalculator()\r\ngreeks = calc.calculate_greeks(S=100, K=105, T=0.25, r=0.05, sigma=0.2, option_type='call')\r\nprint(f\"Delta: {greeks.delta:.4f}\")\r\n\r\n# Price exotic options\r\nfrom derivflow.exotic import BarrierOptions, AsianOptions\r\n\r\n# Barrier option\r\nbarrier = BarrierOptions()\r\nresult = barrier.price(S=100, K=105, H=95, T=0.25, r=0.05, sigma=0.2, \r\n barrier_type='down_and_out', option_type='call')\r\nprint(f\"Barrier Option: ${result.price:.4f}\")\r\n\r\n# Asian option with variance reduction\r\nasian = AsianOptions()\r\nresult = asian.price(S=100, K=105, T=0.25, r=0.05, sigma=0.2, \r\n option_type='call', asian_type='arithmetic')\r\nprint(f\"Asian Option: ${result.price:.4f} \u00b1 {result.std_error:.4f}\")\r\n```\r\n\r\n### Portfolio Risk Analytics\r\n\r\n```python\r\nfrom derivflow.portfolio import PortfolioRiskAnalyzer\r\n\r\n# Create portfolio\r\nportfolio = PortfolioRiskAnalyzer()\r\n\r\n# Add positions\r\nportfolio.add_stock_position('AAPL', quantity=100, current_price=150, volatility=0.25)\r\nportfolio.add_option_position('AAPL', quantity=10, current_price=150, \r\n strike=155, expiry=0.25, option_type='call', volatility=0.25)\r\n\r\n# Calculate risk metrics\r\nportfolio_value = portfolio.calculate_portfolio_value()\r\ngreeks = portfolio.calculate_portfolio_greeks()\r\nvar_95, es_95 = portfolio.calculate_var_parametric(0.95)\r\n\r\nprint(f\"Portfolio Value: ${portfolio_value:,.2f}\")\r\nprint(f\"Portfolio Delta: {greeks['delta']:.2f}\")\r\nprint(f\"95% VaR: ${var_95:,.2f}\")\r\n```\r\n\r\n### Volatility Surface Modeling\r\n\r\n```python\r\nfrom derivflow.volatility import create_sample_surface\r\n\r\n# Create and build volatility surface\r\nsurface = create_sample_surface()\r\nsurface.build_surface()\r\n\r\n# Get volatility smile\r\nsmile = surface.get_smile(expiry=0.25, num_points=10)\r\n\r\n# Interpolate volatility\r\nvol = surface.interpolate(strike=102, expiry=0.33)\r\nprint(f\"Interpolated Volatility: {vol:.1%}\")\r\n```\r\n\r\n## \ud83c\udfaf **Advanced Features**\r\n\r\n### Stochastic Volatility Models\r\n\r\n```python\r\nfrom derivflow.models import HestonModel\r\n\r\n# Heston stochastic volatility\r\nheston = HestonModel()\r\nheston.set_parameters(v0=0.04, kappa=2.0, theta=0.04, sigma=0.3, rho=-0.7)\r\n\r\n# Price with stochastic volatility\r\nresult = heston.price_option(S=100, K=105, T=0.25, r=0.05, \r\n option_type='call', method='monte_carlo')\r\nprint(f\"Heston Price: ${result.price:.4f}\")\r\n```\r\n\r\n### Real-Time Market Data\r\n\r\n```python\r\nfrom derivflow.utils import AdvancedMarketData\r\n\r\n# Get live market data\r\nmarket_data = AdvancedMarketData()\r\nprice, timestamp = market_data.get_current_price('AAPL')\r\nvol = market_data.get_historical_volatility('AAPL', days=30)\r\n\r\nprint(f\"Current AAPL: ${price:.2f}\")\r\nprint(f\"30-day Volatility: {vol:.1%}\")\r\n```\r\n\r\n## \ud83d\udcca **Performance Benchmarks**\r\n\r\nDERIVFLOW-FINANCE is optimized for institutional-grade performance:\r\n\r\n- **Black-Scholes Pricing**: 4,000+ options per second\r\n- **Monte Carlo Simulation**: 10,000 paths in <0.2 seconds\r\n- **Asian Options**: 1,500x variance reduction with control variates\r\n- **Greeks Calculation**: Complete sensitivity analysis in milliseconds\r\n\r\n## \ud83c\udf93 **Use Cases**\r\n\r\n### **Investment Banking & Trading**\r\n\r\n- Derivatives structuring and pricing\r\n- Real-time risk management\r\n- Volatility trading strategies\r\n- Exotic products development\r\n\r\n### **Academic Research**\r\n\r\n- Financial engineering research\r\n- Quantitative finance education\r\n- PhD dissertations and papers\r\n- Teaching materials and examples\r\n\r\n### **Portfolio Management**\r\n\r\n- Multi-asset portfolio construction\r\n- Risk analytics and VaR calculation\r\n- Hedging strategy optimization\r\n- Stress testing and scenario analysis\r\n\r\n### **Fintech Development**\r\n\r\n- Pricing engines for trading platforms\r\n- Risk management systems\r\n- Regulatory compliance tools\r\n- API development for financial services\r\n\r\n## \ud83d\udee0\ufe0f **Installation Options**\r\n\r\n### Standard Installation\r\n\r\n```bash\r\npip install derivflow-finance\r\n```\r\n\r\n### Development Installation\r\n\r\n```bash\r\npip install derivflow-finance[dev]\r\n```\r\n\r\n### Full Installation (all features)\r\n\r\n```bash\r\npip install derivflow-finance[visualization,testing,docs]\r\n```\r\n\r\n## \ud83d\udcda **Documentation**\r\n\r\n- **API Reference**: Complete function and class documentation\r\n- **User Guide**: Step-by-step tutorials and examples\r\n- **Theory Guide**: Mathematical foundations and model explanations\r\n- **Examples**: Jupyter notebooks with real-world applications\r\n\r\n## \ud83e\udd1d **Contributing**\r\n\r\nWe welcome contributions from the quantitative finance community! Please see our [Contributing Guide](CONTRIBUTING.md) for details.\r\n\r\n### Development Setup\r\n\r\n```bash\r\ngit clone https://github.com/jeevanba273/derivflow-finance.git\r\ncd derivflow-finance\r\npip install -e .[dev]\r\npytest tests/\r\n```\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## \ud83c\udf1f **Acknowledgments**\r\n\r\n- Built with modern Python scientific computing stack\r\n- Inspired by quantitative finance research and industry best practices\r\n- Designed for both academic research and commercial applications\r\n\r\n## \ud83d\udcde **Contact & Support**\r\n\r\n- **Author**: Jeevan B A\r\n- **Email**: jeevanba273@gmail.com\r\n- **GitHub**: [@jeevanba273](https://github.com/jeevanba273)\r\n- **Issues**: [GitHub Issues](https://github.com/jeevanba273/derivflow-finance/issues)\r\n\r\n---\r\n\r\n**\u2b50 Star this repository if DERIVFLOW-FINANCE helps your quantitative finance projects!**\r\n\r\n**\ud83d\ude80 Built for the global quantitative finance community by Jeevan B A**\r\n",
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