Energy and Commodities Quant: Modeling, Derivatives, and Risk Analytics
Bisette, Vincent
Synopsis "Energy and Commodities Quant: Modeling, Derivatives, and Risk Analytics"
Reactive Publishing Energy and Commodities Quant: Modeling, Derivatives, and Risk Analytics provides a precise, modern blueprint for quantitative analysis across volatile physical and financial commodity markets. Designed for quants, risk managers, and computational finance professionals, this comprehensive text bridges the gap between high-level financial engineering theory and production-grade market execution. Energy and commodity dynamics present unique mathematical challenges, from extreme mean reversion and structural spikes to complex spatial basis relationships and physical delivery constraints. This book delivers a rigorous treatment of the mathematical frameworks required to model, price, and hedge complex exposures across power, natural gas, crude oil, and refined products. Key Topics CoveredStochastic Price Dynamics: Formulate single- and multi-factor mean-reverting processes, jump-diffusion models, and regime-switching frameworks to capture commodity price shocks and seasonal volatility curves. Yield Curves & Storage Option Dynamics: Model forward curves, convenience yields, seasonal carry structures, and the valuation of physical storage and transport assets. Derivatives Pricing & Structuring: Master numerical methods for vanilla and exotic options, including Asian options, swing contracts, crack spreads, spark spreads, and volumetric hedges. Risk Analytics & Portfolio Optimization: Implement Value at Risk (VaR), Expected Shortfall (CVaR), stress testing, and counterparty credit risk (CVA/DVA) tailored to illiquid and non-normally distributed markets. Algorithmic & Computational Execution: Translate mathematical formulations into high-performance computational models designed for real-time risk simulation and portfolio hedging. Target AudienceThis book is essential reading for quantitative analysts, risk managers, financial engineers, commodity traders, and graduate students in computational finance seeking an actionable, mathematically sound reference for modern commodity markets.
