
Energy Risk Management in
Natural Gas and Electricity
COURSE OBJECTIVE
Intensive course on risk management and pricing of electricity and Natural Gas with a wide range of concepts, methodologies, models, strategies, tools and exercises using real databases for pricing based on a competitive market such as energy.
Considering the financial risk management of an energy company, the main business risk is exposure to market prices.
The price of electricity is much more volatile than that of other commodities that are normally characterized by their extreme volatility. End user demand is highly dependent on weather and grid reliability is paramount. The possibility of extreme price movements increases trading risk in the electricity markets.
However, during the course we explain advanced models for pricing at the contract and pool level. Using VaR, betas, risk premiums, RAROC. Econometric models such as the autoregressive vector, SARIMA model and stochastic models.
We analyze pricing strategies in a competitive environment using game theory methodologies and dynamic oligopoly models. In addition, the risks of mispricing are explained.
We will explain what are the futures and energy derivatives in the markets of Spain and Europe. We will analyze how to create hedges using electricity and natural gas derivatives and how to statistically measure the effectiveness of hedges.
During the course we will show market risk models and methodologies such as Value at Risk VAR and Expected Shortfall, and historical simulation methodologies, Monte Carlo Simulation and parametric models.
We expose pricing models and electricity price forecasting using powerful econometric and machine learning tools. In addition, advanced probabilistic artificial intelligence models have been incorporated to help determine model uncertainty and provide confidence intervals on spot price projections. This will allow to know the uncertainty of the prices and of the income and profits.
Natural gas price risk management and natural gas pricing models are explained.
The course contains exercises in Python, R and Excel on pricing, risk premium, RAROC, Value at Risk and hurdle rate to reinforce participant learning.
WHO SHOULD ATTEND?
Officials from investment banks, electric power and Natural Gas companies, energy hedge funds, regulators, consultants and those interested in:
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Pricing of electricity and natural gas contracts
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Pricing of energy derivatives
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Commodity and energy risk management and analysis
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portfolio management
For a better understanding of the topics, it is recommended that the participant have knowledge of statistics.



Price: 7.900 €
Schedules:
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Europe: Mon-Fri, CEST 16-20 h
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America: Mon-Fri, CDT 18-21 h
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Asia: Mon-Fri, IST 18-21 h

Level: Advanced

Duration: 40 h

Material:
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Presentations PDF
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Exercises in Excel, R, Python y Jupyterlab
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The recorded video of the 30-hour course is delivered.

AGENDA
Energy Risk Management in Natural Gas and Electricity

Modular Agenda
ELECTRICAL ENERGY
Module 1: Retail gas and electricity markets
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Current energy crisis situation
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Ukraine-Russia War
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Inflation and geopolitical risk
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market indicators
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Evolution of retail electricity and natural gas markets
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Evolution of the demand for electricity and natural gas
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Evolution of the sale of electricity and natural gas
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The degree of loyalty in the electricity and natural gas sector
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Evolution of retail electricity and natural gas prices
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in the free market
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Consumer involvement in the retail market
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Energy consumer protection measures
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Actions of the CNMC, the European regulators and the European Commission regarding consumer protection and the retail market since 2020
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Recommendations and regulatory proposals
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Regulatory proposals
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Recommendations to marketers
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Consumer Recommendations
Module 2: Electricity price models
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Building blocks
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Building Block Dimensions
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Retail electrical products
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Guaranteed price products
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"Flip-the-switch" (FrS)
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Spot Price Products
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product usage time
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seasonal rate product
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Fixed invoice product
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Spot Price Products
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Real-time prices (RTP),
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Interruptible and Reducible Products (1IC)
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Risk Management Products
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cap price
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floor price
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Necklace Price
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weather coverage
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Calculation of the cost of products differentiated by risk: calculation of equilibrium prices
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Forward prices per hour
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Forward Retail Price
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Guaranteed price product
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Pricing of products differentiated by risk
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Value creation by sharing risk
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Bundling of value-added services with basic electricity
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Exercise 1: Spot price, equilibrium price, fixed price and price for time of use and renewal options
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Exercise 2: Derivatives Price, Cap, Floor and Collar
Module 3: Electricity price strategies
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Customer segmentation
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commercial segment
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industry segment
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residential segment
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Commercial strategies
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The role of pricing in a competitive market
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Consequences of incorrect pricing
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Customer expectations about prices
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Market models in the electric power industry
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Classic Oligopoly Models
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Oligopolistic market equilibria
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Games theory
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static games
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Dynamic games
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Bertrand and Cournot dynamical experiments
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Module 4: Risks in the energy market
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the energy cycle
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Exploration
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production or extraction
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Treatment
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Transport and storage
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Refinement
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Distribution
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Integrated and specialized companies
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Risks in the energy cycle
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Overview
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Market risk
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Credit risk Operational risks
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Liquidity risk
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Political and regulatory risk
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price risk
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Integrated vs specialized companies
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Common risk management tools
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Volatility and energy risk management
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Risks in renewable energy projects and their mitigation
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Project development risks
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Construction risks
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Resource risks
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Technical risks
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Market risks
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Regulatory risks
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Other operational risks
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Module 5: Market Risk Management in electricity companies
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Management of corporate risks in the electricity and energy market
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Objectives, roles and responsibilities
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Market Risk Appetite Framework
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business strategy
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business plans
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Risk Appetite
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risk tolerance
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Risk Capacity
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Market risk management policies and procedures
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Treasury management in energy companies
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Boundary setting
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Market risk management cycle: Identification, monitoring, measurement, control and monitoring of market risk
Module 6: Univariate and Multivariate Analysis of risk factors
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Univariate Analysis
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Yield Estimation
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arithmetic mean, median, geometric mean
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Outlier Review
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Measures of dispersion
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Shape measurements
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Sample Skewed
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Groeneveld's measure
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Moors's measure
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Fitting probability distributions
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Multivariate analysis:
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Arbitrage Pricing Theory
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Return models
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OLS regression
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Heteroskedasticity Treatment
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Outlier Treatment
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Robust Regression
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Principal Components (PCA)
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Multifactor model
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Industry or country factors
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Exercise 3: Treatment of time series, non-stationary series, heteroscedasticity, outliers, multicollinearity in factors.
Module 7: Power Purchase Agreements (PPAs)
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What is a PPA contract -
Bases of the agreement
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Types of PPAs for Generators
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Physical
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Synthetic or Financial
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Negotiation of a PPA
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Generation
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Consumption
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Pricing Structures
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Fixed annual baseload pricing structure
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Fixed, escalation and indexing
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Fixed Price Nominal PPA
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Fixed price with escalation (stepped)
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Fixed Price with inflation indexation
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Variable price, market discount with Caps and Floors
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Market discount with floor
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Market discount with necklace
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Collar and Reverse Collar
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Necklace
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Reverse Collar (VPPA only)
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hybrid structures
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Hybrid – % production
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Hybrid - over time
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clawback
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Volume Structures and Risk Allocation
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PPA Risk Mitigation
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EEX Futures, Asian Put Option
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Exercise 4: Pricing PPA using closed formulas
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Exercise 5: Pricing PPA using copulas
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Exercise 6: Quantifying volumetric and correlation risk
Module 8: Treatment of Volatility
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Performance Treatment
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Exponentially Weighted Moving Average (EWMA)
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GARCH Univariate Model
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GARCH Multivariate Model
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GARCH Extensions
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Evaluation of variance models
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In sample review with autocorrelation
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Out sample review with regression
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Use of intraday information
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GARCH Multivariate model with copulas
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Exercise 7: GARCH (1,1) volatility modeling in R
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Exercise 8: Volatility modeling GARCH copulas in R