heston

Financial Derivatives Calculator with 171+ Models (Options Calculator)

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.

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.

Quant. Research project - Cutting-Edge project (In collaboration with Milliman & University of Paris-Saclay)

The project aims to compare the effectiveness of the Heston model and WGAN-GP in modeling financial time series data.

Heston model implementation with Monte Carlo simulation for stochastic volatility pricing.Implementation of the Heston Stochastic Volatility Model in Python along with it's Monte Carlo Simulation

Sixteen option pricers over six stochastic models including Heston, Bates, SABR and rough Bergomi, spanning analytic, lattice, finite-difference, COS Fourier and Monte Carlo methods.

Derivatives pricing library: Black-Scholes-Merton (16 Greeks), Monte Carlo with variance reduction, Asian/Barrier/Lookback/Digital exotics, Heston (Fourier pricing, QE simulation, SPX calibration), rough Bergomi (hybrid scheme). 1,013 tests, QuantLib-validated, 97% coverage.

Rust library for option pricing: Binomial, Black-Scholes, Heston and intrinsic value, with Least Squares Monte Carlo and random-forest regression for American exercise.

Heston stochastic-volatility calibration for option pricing, comparing classical optimization and deep-learning methods on SPX implied-volatility data.

Numerical derivatives-pricing and model-validation core: Monte Carlo, finite-difference PDEs, Greeks, and SABR/Heston calibration, each challenged against closed forms and QuantLib, with an SR 26-2-style validation report.

High-performance options Greeks engine — Black-Scholes/Heston, AVX2-vectorised pricing, Google Benchmark suite

Python volatility-surface research engine for SPY option-chain cleaning, SABR/Heston calibration, robustness testing, cross-snapshot validation, and failure-mode analysis.

FFT, Monte Carlo, and finite difference

Dynamic Collar Hedging — PFE ECE Paris × EY Paris. Multi-models pricing (Black-Scholes, Heston, Hull-White, SABR), Greeks engine, backtesting, FastAPI + React.

Options pricing done to a quant standard: Black-Scholes + full Greeks, implied-vol solver, binomial/American, Monte-Carlo, exotics (Asian/Barrier/American-LSM), Heston stochastic vol (Fourier + MC) and an SVI surface — validated to ~1e-10 against published references. With a Streamlit dashboard.

Crypto options pricing and volatility-surface engine: Black-Scholes/Heston/Merton/SABR, Gatheral SVI calibration, model-free no-arbitrage checks, and mispricing signals netted against costs.

Construire un pricer, puis prouver qu'il est juste : convergence CRR mesurée (pente -0,98), tableau 1 de Longstaff-Schwartz répliqué 20/20 (puts bermudéens, transcription verrouillée par tests), couverture des IC Monte Carlo vérifiée (94-96 %), Heston contre sa formule. Aucune donnée de marché, 15 tests fermés.

Deep Hedging under market frictions.