Real Options and Simulation in Energy Markets - DPH4 

CPE Credits Awarded: 16
Categories: Trading, Derivatives, Hedging and Risk Management, Global Association of Risk Professionals (GARP) Approved Course

Course Date Duration Venue Price Registration Deadline Register
09 Nov 2022 2 Days Calgary, Canada Country: ca
$ (USD)2,620.00+5%GST
30 Sep 2022


Real Options and Simulation in Energy markets is a two-day energy trading course presented by the energy training experts at Mennta Energy Solutions. This course is an advanced course for energy practitioners interested in enhancing their applied knowledge of best practices in valuation, hedging and risk management of long term contracts and physical assets. This highly interactive workshop uses practical case studies, Excel exercises and group discussions to reinforce the concepts presented in the lectures.

The course introduces the models and strategies used to value, hedge and manage the risk of derivatives and physical assets in leading energy trading organizations. Delegates learn about the practical applications of the models and strategies from the point of view of the users of those models, not the quantitative developers.

The course explores the embedded optionality and trading strategies to optimize storage, transportation (ground and marine) assets and long term contracts in gas, power and oil markets. Cross commodity spread strategies are explored in the context of power generation and oil refinery operations. The course also covers the valuation, hedging and optimization of natural gas, LNG and refined product storage strategies in contango and backwardated markets.

Delegates learn how to apply Monte Carlo simulation (stochastic forward curve models, Least-Squares Monte Carlo) and binomial/trinomial trees for physical asset valuation and hedging. Case studies show how to incorporate operational constraints in the analysis.

Please note: a laptop and up-to-date version of Office would be an advantage in order to engage in market data; however it is not essential.


Recommended: DPH1, DPH2, DPH3 (optional), PRM and NAGP or equivalent knowledge.


- Market risk managers
- Quantitative analysts
- Asset-based traders
- Commercial analytics teams
- Structured product teams
- Fundamental analysts
- Chief risk officers
- Middle office personnel
- Credit risk managers
- Risk consultants
- IT specialists


Day 1

401: Valuation and Hedging of Physical assets and Long Term Contracts as real options

-    Types of real options:  volume, timing, cross-commodity and location
-    Commodity trading: Transformation in time, space and form
-    Case study: Optionality in LNG trading
-    Main differences between real options vs. standard options
-    Intrinsic vs. extrinsic value of real options
-    Optimization and re-optimization: Rolling intrinsic and spot-based trading
-    Position management and monetization Strategies
-    Risk-equivalent position mapping of real options

402: Energy Price Behavior: Overview of forward curve models

-    Forward curve behavior in oil, gas and power markets
-    Review of spot price models: Geometric Brownian Motion (GBM), GBM with mean reversion and mean reverting jump diffusion (MRJD)
-    Multi-factor and multi-commodity models: Structured Monte Carlo (Cholesky-based) vs. Principal component analysis (PCA).
-    Excel exercises with PCA and structured Monte Carlo Simulation.
-    Case study: Destination option analysis and valuation with Monte Carlo

403: Transporting Commodities: Transformation in space

-    Pipeline and Transportation Options
-    Understanding locational basis relationships in energy markets
-    Using basis swaps to fix prices; hedge transportation and transmission
-    Case Study: To flow or not to flow: Natural gas locational basis trading
-    Firm capacity, Firm Recallable Capacity, and Interruptible services.
-    Cargo arbitrage with destination options: Position reports, delta-hedging and valuations
-    Congestion Revenue Rights (CRR) and Financial Transmission Rights (FTR)

404: Storing commodities: Transformation in time

-    Storage optimization in Contango and Backwardated markets
-    Natural Gas Storage: Time Spreads and Trading Strategies
-    Hedging and trading strategies for storage assets
-    Intrinsic value calculation of Storage using Excel’s Solver
-    Extrinsic value calculation and strip of spread options
-    Case study: Storage hedging and operational risk

Day 2

405: Blending commodities: Transformation in form

-    Optionality in production processes
-    Case study: Power generation
-    Valuation of generation assets as strips of spread options
-    Earnings at Risk for a power plant under different hedging strategies
-    Spark Spreads and Heat Rate Forwards and Options
-    Refineries and crack spreads
-    Case study: Hedging, Monetization and Speculation with Crack Spreads
-    LNG Liquefaction, Storage, Regasification and Trading: Transformation in space, time and form

406: Market, Credit and Operational Risk Policies and Metrics for Physical Assets

-    Risk appetite, risk tolerance and limits
-    Market Risk and Hedge Policy
-    Market risk metrics for assets: Value at Risk vs. Flow ‘at-risk’ metrics (e.g. CFaR, GMaR and EaR)
-    Case study: Gross earnings at risk for a power plant
-    Credit risk and exposure measurement: Current Exposures vs. Potential future exposures (PFE)
-    Operational risk in assets
-    Case study: Introducing outages and pricing outage insurance

407: Volumetric Risk: Supply and Demand side considerations

-    Key sources of volume risk in oil, gas and power markets
-    Volumetric risk and Operational Risk
-    Unplanned Outage Insurance
-    Case study: Hedging storage contracts and operational risk
-    Possible problems when hedging physical exposures with financial forwards
-    Hedging Volumetric Risk: Weather Derivatives and Multiple-trigger contracts
-    Prepayment deals and force majeure events

408: Optimization, Backwards induction methods and early exercise decisions

-    Dispatch rules and plant optimization under perfect foresight
-    Case study: Battery storage optimization and valuation with simulation
-    Binomial and trinomial trees. Step-by-step example
-    Forest of trees and swing contracts
-    Introduction to Least-squares Monte Carlo Simulation and applications
-    Case study: Pricing an American option with Longstaff-Schwartz method


DR CARLOS BLANCO is an expert in energy, commodity, and financial risk management and modeling. He has been a faculty member of Mennta Energy Solutions 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).

GARP rgbMennta Energy Solutions is registered with GARP as an Approved Provider of Continuing Professional Development (CPD) credits. Mennta Energy Solutions has determined that this program qualifies for 16 GARP CPD credit hours. If you are a Certified FRM or ERP, please record this activity in your Credit Tracker at

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Mennta Energy Solutions (formerly The Oxford Princeton Programme, Inc.) is not affiliated with Princeton University, Oxford University, or Oxford University Press.