hestonpy

hestonpy is a Python package for pricing, calibrating and hedging options under stochastic volatility models, built around the Heston framework (with Black-Scholes and Bates also included). It's aimed at anyone who wants to simulate paths, price vanilla options, calibrate a model to a market smile, or explore optimal portfolio allocation under Heston dynamics, without having to reimplement the underlying numerical machinery from scratch.

Documentation: https://sarcasticmatrix.github.io/hestonpy/

Installation

hestonpy is available on PyPI:

pip install hestonpy

It requires Python 3.10+ and depends on numpy, scipy, pandas, matplotlib, tqdm and yfinance.

Features

• Models: Black-Scholes, Heston, and Bates (Heston with jumps)
• Simulation: Euler and Milstein discretization schemes for asset and variance paths
• Pricing: Monte Carlo, Fourier-transform, and Carr-Madan methods for European vanilla options
• Greeks & hedging: delta/vega computation and delta-vega hedging
• Calibration: fit model parameters to market implied volatility smiles and surfaces, with support for pulling option chain data from Yahoo Finance or user-supplied data
• SVI / SSVI: Stochastic Volatility Inspired parametrization for smiles and surfaces

Quick start

from hestonpy import Heston

model = Heston(
    spot=100,
    vol_initial=0.04,
    r=0.02,
    kappa=2.0,
    theta=0.04,
    drift_emm=0.0,
    sigma=0.3,
    rho=-0.7,
)

# Simulate asset price and variance paths
S, V, null_variance = model.simulate(
    time_to_maturity=1,
    scheme="milstein",
    nbr_points=252,
    nbr_simulations=10_000,
)

# Price a European call
price = model.call_price(strike=100, time_to_maturity=1)

Calibrating to a market smile:

from hestonpy import VolatilitySmile

smile = VolatilitySmile(...)  # see docs for constructing from market/Yahoo Finance data
calibrated_params = smile.calibration(...)

More worked examples (pricing, calibration, hedging, asset allocation) are available in the example/ directory of the repository.

Project layout

src/hestonpy/
├── models/         # Black-Scholes, Heston, Bates, calibration (SVI/SSVI)
├── option/         # Option and OptionsBook abstractions, market data fetching

Contributing

Contributions are welcome — see CONTRIBUTING.md and CONDUCT.md for guidelines.

License

hestonpy was created by Théophile Schmutz (@SarcasticMatrix). It is licensed under the MIT license — see LICENSE for details.