genpark-heston-stochastic-volatility-cir-process-skill
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Heston two-factor stochastic volatility model with Cox-Ingersoll-Ross (CIR) variance and Feller condition checking
README.md
Heston Stochastic Volatility Simulator Skill
Two-factor coupled stochastic differential equation solver featuring CIR variance and correlated Brownian noise.
flowchart TD
Gaussian["Correlated Gaussians (Z1, Z2 with correlation ρ)"] --> Var["CIR Variance Step: dV = κ(θ - V)dt + ξ √V dW_V"]
Gaussian --> Price["Price Step: dS = μ S dt + √V S dW_S"]
Var --> Price
Var --> Feller["Feller Verification: 2κθ > ξ^2"]
Features
- 100% Python Standard Library: Full truncation Euler scheme for non-negative variance.
- Correlated Noise Injection: Cholesky decomposition of 2D Wiener processes.
- Feller Boundary Check: Automatic analytical positivity verification.
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