heston-model

Collection of notebooks about quantitative finance, with interactive python code.

OptionStratLib is a comprehensive Rust library for options trading and strategy development across multiple asset classes.

Fourier-transform pricing, Monte Carlo validation, and calibration of European options under stochastic-volatility models in Python

Quant Option Pricing - Exotic/Vanilla: Barrier, Asian, European, American, Parisian, Lookback, Cliquet, Variance Swap, Swing, Forward Starting, Step, Fader

High-performance quantitative finance in Rust and Python — 130+ stochastic processes, option pricing, calibration, fixed income, risk & copulas, with SIMD/GPU acceleration.

Python Financial ENGineering (PyFENG package in PyPI.org)

A model free Monte Carlo approach to price and hedge American options equiped with Heston model, OHMC, and LSM

Option pricing with various models (Black-Scholes, Heston, Merton jump diffusion, etc) and methods (Monte Carlo, finite difference, Fourier).

Quantitative finance and derivative pricing

Option pricing function for the Heston model based on the implementation by Christian Kahl, Peter Jäckel and Roger Lord. Includes Black-Scholes-Merton option pricing and implied volatility estimation. No Financial Toolbox required.

A UI-friendly program calculating Black-Scholes options pricing with advanced algorithms incorporating option Greeks, IV, Heston model, etc. Reads input from users, files, databases, and real-time, external market feeds (e.g. APIs).

Modelling the implicit volatility, using multi-factor statistical models.

Vollab (Volatility Laboratory) is a python package for testing out different approaches to volatility modelling within the field of mathematical finance.

Implementation of option pricing models using Numba that performs better. This entire project has utilized as little libraries as possible, even though certain models have their own Machine Learning Model with assessment and performance.

Custom Neuron Decision-Making and Visual Workflow Orchestration Quantitative

Open-source quantitative finance models in Python: option pricing and Greeks, volatility surfaces, deep hedging, portfolio construction and Monte Carlo. Every model runs on free data, with the full write-up on davidariasfinance.com

Low-latency options pricing engine in Rust. BSM, Black-76, Heston, Bates (jumps), Local Vol (Dupire), Monte Carlo (Euler/Andersen QE). Adaptive Gauss-Kronrod CF pricers, full analytic Greeks, forward-mode AD (incl. jump sensitivities), Halley IV solver, LM/DE global calibration, no-arbitrage repair, Rayon parallelism. CI + clippy, 0 warnings.

Stochastic volatility models and their application to Deribit crypro-options exchange

Arbitrage-free volatility surface construction with SVI & Heston calibration. Python toolkit for options pricing and risk management.

Closed-form solutions and fast calibration & simulation for SABR-based models with mean-reverting stochastic volatility