Commodity Derivatives Markets, Instruments, and Hedging - Second course on Risk Management and Hedging in Energy, Metals, and Agricultural Markets - CDPH2
CPE Credits Awarded: 16
CDPH 2 builds on the concepts and instruments presented in the first course and focuses on the management and measurement of risks in commodity physical and derivatives portfolios, with particular emphasis on VaR and Stress tests and advanced hedging topics.
We will start with a review of Price Behavior, Probability and Statistics, and various Excel exercises with hands-on calculations of various risk statistics. The course also covers an introduction to Derivatives Pricing Models and relevant accounting rules such as IAS 39 and IFRS 7. Implied volatility and “Greeks” are presented using practical exercises. The course also covers analysis of structured products used by producers and end-users such as extendable swaps. Spot price models, Geometric Brownian Motion, and Mean-reverting models for pricing and risk analysis.
This highly interactive workshop uses practical case studies, Excel exercises, and group discussions to reinforce the concepts presented in the lectures.
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This course is ideal for:
- Producers, Integrated firms, Physical Traders, End-users, Marketers, Financial Institutions, Investment funds, Utilities, Co-operatives
- Market and credit risk managers
- Chief Risk Officers
- CFO, Treasurer, Analysts
- Back office and operations
- Audit and Accounting teams involved with derivatives activities
- IT departments servicing risk groups
Management teams: Metals, Agricultural, and Energy Markets
- Metals: Base Metals (Aluminum, Copper, Zinc), Precious Metals (Gold, Silver) and Ferrous Metals (Iron ore)
- Agriculture: Wheat, Corn, Biofuels, Cocoa, Coffee, Soybeans, Palm Oil, Sugar, Weather
- Energy – Crude Oil, Products, Natural Gas, Coal, LNG
Price Behavior, Probability, and Statistics
- Overview of price behavior; seasonality; mean reversion; spikes
- Spot vs. forward prices; price indices and market liquidity
- Building forward curves in illiquid commodity markets
- Volatility structure in commodity markets; spot vs. forwards
- Probability distributions; moments of a distribution.
- Calculating volatility and correlation.
- Case study: Excel exercises with hands-on calculations of various risk statistics
Commodity Derivatives Structures
- How to unbundle embedded risk structures in commodity contracts
- Building blocks: long vs. short; option types; volumes; strike price; exercise style; underlying; trigger event/contingency; payoff type
- Review of main derivatives structures: futures and forwards; fixed for floating and basis swaps; European and American options; basis swaps and options; exotic options
- Case study: Identifying hidden derivatives in long term supply contracts
Mark-to-Market vs. Mark-to-Model: Overview of Derivatives Pricing Models, Uses, Pros, and Cons
- Overview of IFRS 7 and FAS 157 and three "fair value" levels. Adding the liquidity dimension
- Closed-form solutions (formulas).
- Case study: Pricing an option using Black 76 in Excel.
- Monte Carlo simulation based models.
- Case study: Generating random paths in Excel.
- Binomial and trinomial trees.
- Case study: Pricing an American option.
- Counterparty Valuation Adjustments (CVA)
- Understanding option sensitivities through the "Greeks" Case study: calculating and visualizing "Greeks" in Excel
Analysis of Derivative Strategies
- Comprehensive analysis of the risk involved in various derivatives strategies
- Zero-cost and Three-way collars
- Case study: Lesson from China Aviation Oil misuse of Three-Way Collars
- Bull and bear spreads
- Volatility plays: straddles and strangles
- Exotic swaps: extendable, cancelable, double-up swaps
- Case study: OTC structured products for Australian and Thai sugar producers
Commodity Price Behaviour: Overview of spot price models
- Spot price models for commodity markets
- Understanding price processes; parameterization
- Geometric Brownian motion; uses and limitations
- Mean reversion; limit of variance ("terminal distribution"). Case study: Simulating a mean-reverting process in Excel.
- Jump diffusion and mean reverting with jumps price processes
- Case study: Implications of model choice for contract valuation
Market Risk Management for Commodity Trading
- Market risk and "risk factors"
- Understanding VaR and expected tail loss (ETL)
- Overview of methodologies: analytic, Monte Carlo and historical simulation
- Case study: interpretation of mining firms market risk disclosures
- Market risk limits
- Petroleum, mining, agriculture, freight and gas specific issues
- Case study: calculating VaR in a spreadsheet
Basis Risk and Derivatives in Commodity Markets
- Types of Understanding correlation.
- Seasonality and location based considerations.
- IAS 39 and FAS 133 and hedge effectiveness. ex-ante vs. ex-post tests
- Case study: Hedging strategy by airlines
- Minimum variance ratio using volatility and correlation analysis
- Pitfalls of correlation as a measure of dependence
- Case study: natural gas location basis risk
Stress Testing and Backtesting for Commodity Firms
- Designing and conducting stress tests for commodity markets
- Benefits of stress tests
- Standard & Poors liquidity risk survey and stress testing
- Integrating stress tests in the risk modeling process
- Stress tests for commodity markets
- Exercise: Stress tests and technical risk reviews
- Backtesting market risk models
DR CARLOS BLANCO is an expert in energy, commodity, and financial risk management and modeling. He has been a faculty member of the Oxford Princeton Programme since 2004, where he teaches the Derivatives Pricing Hedging and Risk Management Certificate Programme as well as courses on Counterparty Risk Management and Gas and Power Trading and Risk Management.
He has published over 100 articles on financial, energy, and commodity trading, hedging and risk management. He is the founder and managing director of a risk management advisory firm with clients in North America, Europe, Africa and Asia. Carlos is a former VP, Risk Solutions at Financial Engineering Associates. There, he worked over six years as an essential contributor in the development of the energy derivatives valuation and risk management models of the firm. He also provided leading-edge risk advisory and educational services to over 500 energy and commodity trading firms and financial institutions worldwide. He also managed the world-class support and professional services department within the firm. Prior to FEA, Carlos worked for a hedge fund in the Midwest and an asset management firm in Madrid, Spain. He is a former regional director of the Professional Risk Managers’ International Association (PRMIA).
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