Energy Risk Management in
Natural Gas and Electricity

Module 9: Parametric VaR

​

• Overview of the standardized market risk approach

• Linear and non-linear portfolios

• Volatility Estimation

• Value at Risk

• Parametric Models

  • Normal VaR

  • Delta-Normal VaR

  • t-student distribution

  • lognormal distribution

• Linear model

• Quadratic model

• Expected Shortfall

• Stress Testing

  • Identification and validation of the stressful period

  • Stress Period Review

  • Stress Testing in energy companies

• Exercise 9: Delta-Normal estimation, VaR Lognormal and T-Student in R

• Exercise 10: Expected Shortfall in R

​

Module 10: Historical Simulation and Monte Carlo

​

• VaR Historical Simulation

  • Adjust for volatility

  • Bootstrapping

• VaR Monte Carlo simulation

  • Electricity price simulation

  • mean reversion

  • diffusion hops

  • Ornstein-Uhlenbeck process

  • Simulation with multiple risk factors

  • Variance Reduction Methods

• Normal Multivariate Distribution

• Multivariate T-Student Distribution

• VaR Monte Carlo based on Gaussian copula

• VaR Monte Carlo based on t-student copula

• Exercise 11: VaR estimation: using Monte Carlo Simulation and Historical Simulation with R and Excel with Visual Basic

• Exercise 12: Historical Simulation Backtesting in Python

• Exercise 14: VaR using Gaussian copula and tStudent in R

​

Module 11: Electric Power Derivatives in Europe and Spain

​

• Introduction to derivatives

  • European Energy Exchange (EEX)

  • Trading

  • Over the Counter (OTC)

  • European Commodity Clearing (ECC)

  • Spots and Derivatives

  • Markets and Contracts

• Hedging Electricity Using Power Futures

• Hedging Renewable Energy using Power Futures

• Hedging Strategies

• The Iberian Electricity Market (MIBEL)

• Iberian electricity market

• OMIP Regulated Market operator in Spain and Portugal

• OMIClear Clearing House,

• Auction mechanisms

• OTC Market vs Organized Market

• Acquisition of energy from Spanish distributors

• CESUR auction for the calculation of the TUR

• Descending Price Watch Auctions

• Definition and structure of last resort fees

• Cost of energy in the TUR

• MEFF, Derivatives Market of Spanish Stock Exchanges and Markets (BME)

• BME Clearing

• Base Load

• Peak Load

• contract term

• Nominal Base and Mini contracts

• Delivery period

• Forwards, Futures and Swaps

  • Forward Contracts

  • Future Contracts

  • Swaps

  • Commodity Forward Curves

• investment assets

• Consumption assets and convenience performance

• The market price of risk

• “Plain Vanilla” Options

• The Put–Call Parity

• Strategies with options

• Black's Futures Price Model

• Option Pricing Formulas

• Hedging Options: Greek

• Monitoring and real management of:

  • delta

  • gamma

  • theta

  • vega

  • elasticity

• Implied Volatilities and the “Volatility Smile”

• swaptions

• American, Bermudan and Asian Options

• American and Bermudan Options

• Asian Options

• exotic options

• Exercise 15: Electricity option pricing

• Exercise 16: Estimating Greek delta, gamma, theta, and vega in Python

• Exercise 17: Black Scholes model and assumptions

• Exercise 18: Implied volatility

• Exercise 19: Tree pricing methods for vanilla options

• Exercise 20: Monte Carlo Simulation

• Exercise 21: Pricing of exotic options

• Exercise 22: Variance reduction techniques in pricing with Monte Carlo

​

Module 12: Hedging and price risk management

​

• A portfolio perspective

• Measuring the value and risk of the portfolio

• Cash Flow at Risk

• Spot, forward and options markets

• Forward Prices

• Elementary Option Contracts

• option prices

• Valuation of fuel and energy resources

• fixed price contracts

• Black-Scholes option pricing model

• Hedging versus speculation

• Portfolio risk management

• Exposures to price risk

• Implications of Volatility and Correlation for Value and Risk

• Price risk coverage

• Hedging efficiency of electricity futures in the Spanish market

• Measure the effectiveness of hedges

  • Hedging ability of naïve

  • Minimum variance

  • partially predictable

  • BEKK_T hedge ratios

• Exercise 23: Hedging strategies with futures and swaps in electricity contracts

• Exercise 24: Hedging strategies with options, call, floor in electricity contracts

• Exercise 25: Analysis of the effectiveness of coverage of electricity contracts

​

Module 14: Tests for the use of Econometric Models

​

• Review of assumptions of econometric models

• Review of the coefficients and standard errors of the models

• Model reliability measures

• Error management

• not normal

• heteroscedasticity

• Outliers

• autocorrelation

• Using Correlation to detect bivariate collinearity

• Detection of multivariate collinearity in linear regression

• Exercise 26: Non-stationary series detection, cointegration and outliers

• Exercise 27: Measuring Collinearity, Heteroscedasticity, and Serial Autocorrelation

​

Module 15: Forecasting of electricity spot price models and Load consumption

​

• Econometric and machine learning spot price modeling

• Electricity spot price forecasting

• Data required

• Model Specifications

• Univariate models

  • RA

  • MA

  • ARIMA

  • SARIMA

  • ARCH

  • GARCH

• Multivariate Models

  • VAR Vector Autoregressive Models

  • ARCH models

  • GARCH models

  • GARCH Models Multivariate Copulas

  • VEC Error Correction Vector Model

  • Johansen's method

• Machine Learning Models

  • Supported Vector Machine

  • neural network

  • Multivariate Adaptive Regression Splines

  • Random Forest Regression

• deep learning

  • Recurrent Neural Networks RNN

  • Elman Neural Network

  • Jordan Neural Network

  • Basic structure of RNN

  • Long short term memory LSTM

  • temporary windows

  • Development and validation sample

  • Regression

  • Sequence modeling

• Gaussian Process Regression

• Exercise 28: Pricing with Random Forest Regression

• Exercise 29: Forecasting prices Gaussian Process Regression

• Exercise 30: Pricing model with Bayesian Support Vector Machine

• Exercise 31: Forectasting consumption Load SARIMA VAR and VEC

• Exercise 32: Load consumption forecasting with RNN LSTM

​

Module 16: Climate risk management in the electricity industry

​

• Climate: critical factor in the energy industry

• The effect of weather on prices

• econometric models

• Box Cox

• ARCH and GARCH

• price prediction

• Volatility

• Meteorological financial instruments

• weather derivatives

• Market requirements for weather financial instruments

• Exercise 33: Determination of Prices using climatic variables, using neural networks and deep learning

​

Module 17: Advanced Model of electricity prices

​

• production and consumption

• Spot price characteristics

• Load Characteristics

• Physical electricity retail

• electricity financial trading

• Price components derived from the P&L function

  • Price component and the correlation price component

  • Risk premium

  • RAROC

  • Hurdle Rate

  • Market Economic Capital

• Portfolio and individual client perspective

  • Portfolio-level pricing

  • marginal risk

  • Betas

  • Volume limits for defined price contracts

  • Model Description

  • Breakdown of the spot model into different processes

  • SARIMA

  • Deterministic spot and load models

  • daily stochastic models

  • hourly stochastic models

• Spike, seasonality and reversion to the mean

• Model estimation and selection process

  • deterministic functions

  • Daily autoregressive vector model

  • Gaussian copula approach for residuals

  • Hourly spot price vector autoregressive model

• Hourly load autoregressive process

• simulation approach

• Results of price components

• volume risk

• Portfolio Analysis

• customer analysis

• Exercise 34: Electricity contract pricing

• Exercise 35: Price component and the correlation price component

• Exercise 36: Ornstein–Uhlenbeck process with mean reversion and jump diffusion

• Exercise 37: Volume and Price Risk

• Exercise 38: Estimation of Risk Premiums

• Exercise 39: Estimation of RAROC and Hurdle Rate