Options Pricing Python Packages

pyvolr

Modern Black-Scholes-Merton pricing, Greeks, and implied volatility for Python. Rust core. Drop-in replacement for the abandoned py_vollib.

qwed-finance

Deterministic verification layer for AI-generated financial decisions. Verifies math (NPV, IRR, Black-Scholes, YTM, VaR), compliance (AML/KYC via Z3), and banking schemas (ISO 20022, SWIFT) — fail-closed, proof-backed. Not execution. Verification.

calcbsimpvol

Calculate Black Scholes Implied Volatility - Vectorwise

polars-vol

polars plugin for volatility trading

nsedt

Library to collect NSE data in pandas dataframe

optionspricerlib

OptionsPricerLib is a Python library for pricing financial options using various european and american models. The library provides options pricing, implied volatility calculation, and the Greeks for options, covering models such as Barone-Adesi Whaley, Black-Scholes, Leisen-Reimer, Jarrow-Rudd, and Cox-Ross-Rubinstein.

oipd

OIPD computes the probabilities of an asset's future price as implied by the options market.

exotx

exotx provides a simple and user-friendly interface for pricing and analyzing financial derivatives using QuantLib's advanced numerical methods.

voltorch

Differentiable option pricing and volatility surfaces in PyTorch — Heston, Bates, Merton, Variance Gamma via Fourier-COS; SVI/SABR surfaces; rough Bergomi. Greeks from autograd, calibration by gradient descent.

langchain-quantoracle

63 deterministic quant computation tools for autonomous financial agents. Options, derivatives, risk, portfolio, statistics, crypto/DeFi, macro/FX, TVM. 1,000 free calls/day — no signup.

cftc-cot

Python library for downloading, storing, and unpacking official CFTC Commitments of Traders (COT) report archives.

cutebacktests

Backtesting framework for modern option strategies

ecofin

EcoFin is a quantitative economic library

bsm-pricer

European option pricing under Black-Scholes-Merton: prices, Greeks, implied volatility, and sensitivity surfaces. Typed, tested, NumPy-only — no SciPy, so it runs in a browser. The published document shows where the model breaks, generating a volatility smile and inverting it.