stochastic-volatility

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

High-performance quantitative finance in Rust — 120+ stochastic processes, option pricing, calibration, fixed income, risk & copulas, with SIMD/GPU acceleration and Python bindings.

Vanilla and exotic option pricing library to support quantitative R&D. Focus on pricing interesting/useful models and contracts (including and beyond Black-Scholes), as well as calibration of financial models to market data.

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).

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.

R Finance packages not listed in the Empirical Finance Task View

Bayesian Estimation of Heteroskedastic Structural Vector Autoregressions with Markov-Switching and Time-Varying Identification of the Structural Matrix

Financial analysis and demonstration of the classic algorithmic trading method, pair trading. This analysis compares the portfolio's growth with the underlying assets value and volatility over time.

Q-Variance Challenge: Can any continuous-time stochastic-volatility model reproduce q-variance?

List of books on time series analysis, with links to code where available

High-fidelity synthetic financial data generator using Heston Stochastic Volatility and Jump Diffusion.

A repo which deals with Computational Methods in Mathematics, mainly applied in the context of Mathematical Finance, even though it can be applied to almost any domain where you need Probability, Partial Differential Equations, Stochastic Differential Equations, Characteristic Functions, Lévy Processes, Stochastic Volatility, FFT, etc.

Stochastic Volatility Estimated by MCMC (Markov Chain Monte Carlo) Method

TVP-GVAR-FSVM model proposed in "Measuring international uncertainty using global vector autoregressions with drifting parameters"

Joint calibration of stochastic volatility models on SPX and VIX options, with the notebooks and diagnostics behind each fit.

ADI finite difference solver for European options under the Heston stochastic volatility model

R Time series packages not included in CRAN Task View: Time Series Analysis

Python framework for simulating and estimating Bayesian nonlinear pricing models with regime-switching and adaptive volatility filters.