Advanced: Performance & Numerical Methods
Last reviewed: by Options Analysis Suite Research.
The Advanced hub covers the computational and numerical layer that drives every analytic on the platform: GPU-accelerated Monte Carlo, FFT pricing, adaptive numerical integration, validation methodology, and the model-vs-method distinction that underpins pricing-engine selection. These pages are written for users who want to understand the why and how behind the numbers.
Pages in this section
- Performance & Computational Methods - Technical details on computational methods: GPU-accelerated Monte Carlo, FFT pricing, adaptive numerical integration, and performance benchmarks.
- Numerical Controls & Customization - Configure numerical precision settings. Monte Carlo paths, binomial tree steps, FFT grid points, and convergence tolerances.
- Validation & Diagnostics - Model Accuracy Testing - How to validate options pricing model outputs. Put-call parity checks, convergence testing, Greeks verification, and diagnostic tools.
- Models vs Methods - Conceptual Overview - Understand the difference between pricing models (Black-Scholes, Heston) and numerical methods (Monte Carlo, FFT, PDE) in options pricing.
- Market Data Integration Guide - Market data integration guide. Real-time options quotes, historical volatility data, dividend yields, and interest rate feeds.
This page is part of the Options Analysis Suite documentation hub.