Rough volatility dynamics in commodity markets

Battle Count: 70

Highly relevant for quantitative trading desks dealing with commodity derivatives. The paper provides a practical framework for pricing and calibrating vanilla futures options on WTI Crude Oil using rough volatility models. The automatic calibration of futures term structure and Samuelson effect treatment are directly applicable to trading systems. The time-dependent correlation extension improves smile fitting. However, the computational cost and the finding that classical models nearly match rough models (with extreme parameters) may limit practical adoption.

High complexity due to: (1) fractional Brownian motion simulation requiring Hybrid/Hybrid Quadratic schemes, (2) nested calibration procedure with sequential bisection for forward variance curve, (3) Monte Carlo simulation with dual mesh approach for short maturities, (4) surrogate optimization followed by local refinement, (5) handling of fictitious spot price and automatic futures calibration, (6) Samuelson effect modeling via mean reversion speed. Requires expertise in stochastic calculus, fractional processes, and numerical methods.

The paper provides detailed mathematical formulations, calibration procedures, and parameter tables. However, no code repository is provided. Implementation requires MATLAB R2024b with Global Optimization Toolbox, Monte Carlo simulation of fractional Brownian motion (Hybrid Scheme), and access to NYMEX WTI Crude Oil futures options data. The nested calibration scheme and dual mesh approach are described but not trivially reproducible without significant effort.