Commodity Markets & Derivatives: Trading & Managing Risk

3 day practical course providing comprehensive deep dives on both physical commodity market fundamentals and derivatives / derivatives hedging applications for each major commodity.

Major commodity categories covered include:

• Energy - crude oil, natural gas, LNG, electricity, coal, carbon credits
• Base metals - copper, aluminium, other
• Precious metals - gold, silver, platinum, palladium
• Agricultural commodities - corn, wheat, soybeans, coffee, cocoa, sugar, cotton, palm oil

Derivatives coverage includes:

• Forwards, futures, futures options and swaps
• Spread options, exchange options, TAPOs
• Exotic options
• Pricing and Greeks under Black, jump diffusion, univariate and multivariate Monte Carlo simulation and SABR models
• Volatility surfaces and futures curves seen across commodity markets
• Pricing of correlation-sensitive commodity derivatives
• Real options pricing of physical commodity assets - storage facilities, power plants and mining assets
• Quanto pricing - compo forwards and options
• Hedging strategies for commodity producers, consumers and investors
• Trading strategies - curve trading, volatility trading, relative value, inventory-driven arbitrage and commodity-sensitive equities

• Commodity producers
• Commodity consumers – raw materials purchase executives
• Commodity trading firm staff
• Analysts and portfolio managers at hedge funds and other asset management firms
• Quants
• Structures

• Deep dive understanding of major commodities markets - reserves, production, demand, inventory, producers, consumers.
• Comprehensive understanding of commodity derivatives, pricing approaches and risk management.
• How to use commodity derivatives to hedge for producers, consumers and investors as well as trading strategies

• Basic understanding of commodity markets and derivatives / derivatives pricing generally is helpful but not essential

Commodity Markets: Fundamentals & Price Formation

Commodity Market Overview

• Overview of energy, metals and agricultural commodities
• Physical vs financial markets
• Key exchanges and key exchange-traded contracts – CME, LME, ICE, SHFE, SGX
• Major participants – producers, consumers, trading firms and financial investors
• Case Study 1: Commodity-by-commodity market data and background. Trading volumes and major participants

Spot & Forward Price Formation

• Spot pricing dynamics and demand-supply drivers
• Inventory, storage, cost of carry and convenience yield
• Commodity forwards, futures, futures options and swaps
• Relationship between spot and forward prices
• Construction of forward curves
• Case Study 2: Construction of forward curve for WTI crude oil and comparison vs WTI crude oil futures curve
• Contango vs backwardation and forward curve interpretation
• Case Study 3: Crude oil forward curve in periods of market shocks – 2008, 2020
• Seasonality

Energy – Crude Oil

• Crude oil and exchanges
• Chemistry of oil
• Industry overview
• Exploration and production
• Refining and finished products
• Transportation and storage
• Seasonality
• Reserves
• ESG considerations
• Case Study 4: Deep dive crude oil market analysis. Reserves and production breakdown by company and country. Demand breakdown and outlook. Inventory analysis

Energy – Other

• Natural gas
• LNG
• Electricity
• Coal
• Carbon credits

Metals – Base Metals

• Copper, aluminium and other base metals
• Exchanges
• Case Study 5: Implications for copper markets from vehicle electrification
• Case Study 6: Implications for copper markets from growth in wind turbines
• Case Study 7: Deep dive copper and aluminium market analysis. Reserves and production breakdown by company and country. Demand breakdown and outlook. Inventory analysis

Metals – Precious Metals

• Gold, silver, platinum, palladium
• Case Study 8: Deep dive gold and silver market analysis. Reserves and production breakdown by company and country. Demand breakdown and outlook
• Precious metals vs bitcoin / crypto

Agricultural Commodities

• Weather risk and country risk
• Corn, wheat, soybeans, coffee, cocoa, sugar, cotton, palm oil
• Fertilisers and fertiliser swaps

Commodity Derivatives

• Recap – forwards, futures, futures options and swaps
• Spread options
• Exchange options
• Traded Average Price Options (TAPOs)
• Auto cancellable options
• Commodity structured products
• Physical vs financial optionality

Basic Option Pricing Models

• Black-Scholes and Black (1976) models. Why Black model is used more for pricing commodity futures options
• Implied volatility
• Greeks
• Case Study 9: Black model pricing, Greeks and scenario analysis for WTI crude oil futures options
• Mean reversion and seasonality in prices
• Jump diffusion models. Why these are relevant for commodity markets subject to supply shocks, geopolitics and storage constraints
• Case Study 10: Jump-diffusion model for pricing power futures, Greeks and scenario analysis

Volatility in Commodities

• Historical vs implied volatility
• Volatility term structure – relationship between implied volatility and expiration and what drives this
• Volatility skew and smile – relationship between implied volatility and strike / delta
• Why implied volatility is not constant across strikes / delta
• Case Study 11: Typical skew seen in energy, base metals, precious metals and agricultural commodities
• Volatility surface – 3-dimensional representation of how implied volatility varies across: (1) strike / delta; and (2) expiration
• Stochastic volatility models

Advanced Pricing Techniques

• Monte Carlo simulation – univariate and multivariate. Pricing of exotic options
• Case Study 12: Using univariate Monte Carlo to price Asian options on LME copper
• Correlation sensitive commodity derivatives including spread options, spark spread options and crack spread options. Margrabe’s model, Kirk’s approximation and Monte Carlo
• Case Study 13: Using Margrabe’s model, Kirk’s approximation and multivariate Monte Carlo to price crack spread option

Physical Asset Valuation – Real Options

• Valuation of storage facilities
• Valuation of power plants
• Case Study 14: Using crack spread option pricing to value a power plant
• Valuation of mining assets

Commodity Derivatives – Risk Management & Advanced Topics

Advanced Commodity Option Models

• Implied distribution
• Truncated distribution
• Volga-Vanna model
• SABR model. Objectives – generate realistic volatility surface fitted to implied volatility observed in traded options...
• Why SABR is generally better suited than Volga-Vanna for pricing commodity options
• Case Study 15: SABR model pricing, Greeks and scenario analysis for WTI crude oil futures options and comparison to Black model

Quanto Risk In Commodities

• Compo forwards
• Compo options
• Quanto pricing
• Case Study 16: Pricing Brent oil compo call for a UK investor

Risk Management & Hedging Strategies

• Delta hedging
• Case Study 17: P&L and position illustration for delta hedging LME copper futures options
• Proxy hedging
• Case Study 18: Hedging jet fuel price exposure for airline using crude oil futures as proxy hedge. Consideration of basis risks
• Correlation hedging
• Case Study 19: Using crack spread put options to hedge crack spread risk for oil refiner
• Quanto hedging
• Case Study 20: European investor hedging oil exposure in EUR
• Producer hedging
• Case Study 21: Hedging copper price exposure for copper miner
• Utility and power hedging
• Case Study 22: Hedging electricity price exposure for electric utility

Trading Strategies

• Curve trading (calendar spreads, roll yield)
• Volatility trading
• Relative value across commodities
• Inventory-driven arbitrage
• Commodity-sensitive equities
• Case Study 23: Assessing relative value between equities of commodity-sensitive companies and their primary underlying commodity exposure