cedardev-equity-derivatives 0.5.0

Equity derivatives analytics in Python (FST solver, Heston, vol surfaces).

cedardev-equity-derivatives

Equity derivatives analytics in Python.

v0.5.0 — Track A buildout: Black-Scholes, Heston, Carr-Madan FFT pricer, analytic & numerical Greeks, implied vol, SVI smile calibration, market curves. v0.4.0 — Track B: Fourier Space Time-stepping (FST) solver — six Lévy models with European, American, and barrier pricers.

Status

Companion to cedardev-fixed-income.

Track	Module	What's inside
A	cedardev.equity.models	BlackScholes, Heston (with char_function)
A	cedardev.equity.pricers	VanillaOption, CarrMadanPricer
A	cedardev.equity.greeks	bsm_greeks (analytic), numerical_greeks (FD)
A	cedardev.equity.vol	implied_vol, VolSurface, SVIParams
A	cedardev.equity.calibration	fit_svi_slice
A	cedardev.equity.market	DiscountCurve, DividendCurve, forward
B	cedardev.equity.solvers.fst	6 Lévy models, FSTEuropean, FSTAmerican, FSTBarrier

Installation

pip install cedardev-equity-derivatives

Optional extras:

pip install "cedardev-equity-derivatives[fft]"   # adds pyfftw
pip install "cedardev-equity-derivatives[dev]"   # pytest, ruff, mypy, build, twine
pip install "cedardev-equity-derivatives[docs]"  # mkdocs + mkdocs-material

Quick start — Track A

Black-Scholes with Greeks

from cedardev.equity.models import BlackScholes
from cedardev.equity.pricers import VanillaOption
from cedardev.equity.greeks import bsm_greeks

m = BlackScholes(spot=100, r=0.03, q=0.01, sigma=0.20)
opt = VanillaOption(strike=100, expiry=1.0, option_type="call")
print(opt.price(m))                              # 8.8273
print(bsm_greeks(m, K=100, T=1.0, option_type="call"))

Heston with Carr-Madan FFT

from cedardev.equity.models import Heston
from cedardev.equity.pricers import VanillaOption

heston = Heston(spot=100, r=0.03, q=0.01,
                v0=0.04, kappa=2.0, theta=0.04, sigma_v=0.5, rho=-0.7)
print(VanillaOption(100, 1.0, "call").price(heston))   # 8.2535
print(heston.feller_satisfied())                       # False -> watch v

Implied vol

from cedardev.equity.vol import implied_vol

iv = implied_vol(market_price=12.50, spot=100, K=95,
                 r=0.03, q=0.01, T=1.0, option_type="call")

SVI smile calibration

import numpy as np
from cedardev.equity.calibration import fit_svi_slice
from cedardev.equity.vol import svi_implied_vol
from cedardev.equity.market import DiscountCurve, DividendCurve, forward

F = forward(100, 1.0, DiscountCurve(0.03), DividendCurve(0.01))
K  = np.array([60, 80, 100, 120, 140])
iv = np.array([0.32, 0.26, 0.22, 0.21, 0.23])

fit = fit_svi_slice(K, iv, T=1.0, forward=F)
fit_iv = svi_implied_vol(fit, np.log(K / F), T=1.0)

Quick start — Track B (FST)

European under Variance Gamma

from cedardev.equity.solvers.fst import VarianceGamma, FSTEuropean

m = VarianceGamma(spot=100, r=0.03, q=0.01, sigma=0.2, nu=0.2, theta=-0.1)
print(FSTEuropean(m).price(100, 1.0, "call"))

American put under Merton jump diffusion

from cedardev.equity.solvers.fst import MertonJD, FSTAmerican

m = MertonJD(spot=100, r=0.05, q=0.0,
             sigma=0.15, lam=0.3, mu_j=-0.1, sigma_j=0.2)
am_put = FSTAmerican(m, n_grid=2 ** 13, n_time=300).price(100, 1.0, "put")

Up-and-out call under Kou (continuously monitored)

from cedardev.equity.solvers.fst import Kou, FSTBarrier

m = Kou(spot=100, r=0.03, q=0.01, sigma=0.15,
        lam=1.0, p=0.4, eta1=10.0, eta2=5.0)
uo = FSTBarrier(m, n_grid=2 ** 13, n_time=400) \
        .price(K=100, T=1.0, option_type="call",
               barrier=130, barrier_type="UO", monitoring="continuous")

Lévy catalog (Track B)

Model	Class	Parameters
Black-Scholes-Merton	BSMLevy	sigma
Merton (1976) jump-diffusion	MertonJD	sigma, lam, mu_j, sigma_j
Kou (2002) double-exponential	Kou	sigma, lam, p, eta1, eta2
Variance Gamma	VarianceGamma	sigma, nu, theta
Normal Inverse Gaussian	NIG	alpha, beta, delta
CGMY	CGMY	C, G, M, Y

All satisfy the risk-neutral martingale condition psi(-i) = r - q.

Repository layout

cedardev-equity-derivatives/
├── cedardev/
│   └── equity/
│       ├── models/          # BlackScholes, Heston       (Track A)
│       ├── pricers/         # VanillaOption, CarrMadan   (Track A)
│       ├── vol/             # implied vol, surface, SVI  (Track A)
│       ├── calibration/     # SVI slice fit              (Track A)
│       ├── greeks/          # analytic + numerical       (Track A)
│       ├── market/          # DiscountCurve, etc.        (Track A)
│       ├── utils/           # BSM helper formulas        (Track A)
│       ├── risk/            # placeholder for future
│       └── solvers/
│           └── fst/         # FST + 6 Levy models        (Track B)
├── tests/
├── pyproject.toml
├── README.md
├── LICENSE
└── CHANGELOG.md

Development

git clone https://github.com/cedardev-capital/cedardev-equity-derivatives.git
cd cedardev-equity-derivatives
pip install -e ".[dev]"
pytest                          # 98 tests
ruff check .
mypy cedardev

Citation

@software{cedardev_equity_derivatives,
  author  = {CedarDev Capital Management LLC},
  title   = {cedardev-equity-derivatives: Equity Derivatives Analytics in Python},
  year    = {2026},
  url     = {https://github.com/cedardev-capital/cedardev-equity-derivatives}
}

References

• Black, F., & Scholes, M. (1973). The Pricing of Options and Corporate Liabilities. JPE.
• Heston, S. (1993). A Closed-Form Solution for Options with Stochastic Volatility... RFS.
• Carr, P., & Madan, D. (1999). Option Valuation Using the Fast Fourier Transform. JCF.
• Albrecher, H., et al. (2007). The Little Heston Trap. Wilmott.
• Gatheral, J. (2004). A parsimonious arbitrage-free implied volatility parameterization (SVI).
• Surkov, V. (2009). Option Pricing using Fourier Space Time-stepping Framework. PhD thesis, U. Toronto. SSRN 1479738.

License

MIT — see LICENSE.

Disclaimer

This library is provided for research, education, and infrastructure prototyping. It is not a production trading system and carries no warranty. Use at your own risk.