Explosive: Heston Model of Volatility in Python

Explosive is a Python library for working with the Heston Model of Volatility in the field of quantitative finance. This library provides a set of tools and functions to simulate, calibrate, and analyze the Heston Model, a widely-used mathematical model for describing the dynamics of financial asset prices with stochastic volatility.

Features

Simulation: Generate paths of asset prices and corresponding volatilities based on the Heston Model.
Calibration: Calibrate the model to market data, finding the optimal parameters to match observed option prices or implied volatilities.
Pricing: Calculate option prices and Greeks (Delta, Gamma, Vega, Theta) using the Heston Model.
Analysis: Analyze model outputs, including statistical metrics and risk measures.

Getting Started

Installation:

Install Explosive using pip:
```
pip install explosive
```

Usage:

Import the library and start using the Heston Model functions in your Python code:

from explosive import HestonModel

# Create a HestonModel instance
heston = HestonModel()

# Simulate asset price and volatility paths
paths = heston.simulate_paths(...)

# Calibrate the model to market data
calibrated_params = heston.calibrate(...)

# Price options using the calibrated model
option_price = heston.price_option(...)

# Analyze model outputs and risk measures
statistics = heston.analyze(...)

Documentation:

For detailed documentation and examples, refer to the Explosive Documentation.
Contributing:

Contributions are welcome! If you'd like to contribute to the development of Explosive, please follow our Contributing Guidelines.
License:

Explosive is distributed under the MIT License. See the LICENSE file for more information.

Example

# Sample code for simulating Heston Model paths
from explosive import HestonModel

# Create a HestonModel instance
heston = HestonModel()

# Simulate asset price and volatility paths
paths = heston.simulate_paths(
    initial_price=100,
    mean_reversion=0.1,
    long-term_volatility=0.2,
    volatility_of_volatility=0.3,
    correlation=-0.5,
    maturity=1.0,
    num_time_steps=252,
    num_paths=1000
)

# Visualize the simulated paths
import matplotlib.pyplot as plt

for path in paths:
    plt.plot(path)

plt.xlabel("Time Steps")
plt.ylabel("Asset Price")
plt.title("Heston Model Simulated Paths")
plt.show()

Acknowledgments

This library was inspired by the groundbreaking work of Steven L. Heston and the broader quantitative finance community.

Support

If you have any questions, bug reports, or feature requests, please open an issue on our GitHub repository.