#Stochastic-volatility
Showing 7 of 7 repositories tagged #stochastic-volatility, ranked by stars
Python implementation of pricing analytics and Monte Carlo simulations for stochastic volatility models including log-normal SV model, Heston
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.
R Finance packages not listed in the Empirical Finance Task View
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.
Low-latency options pricing engine in Rust. BSM, Black-76, Heston, Bates (stochastic vol + jumps), Local Vol (Dupire). Analytic Greeks, fast IV solver (Halley), monotone cubic spline surfaces. Parallel batch pricing via Rayon.
Q-Variance Challenge: Can any continuous-time stochastic-volatility model reproduce q-variance?