Managing energy risk : an integrated view on power and other energy markets /

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Mathematical techniques for trading and risk management. Managing Energy Risk closes the gap between modern techniques from financial mathematics and the practical implementation for trading and risk management. It takes a multi-commodity approach that covers the mutual influences of the markets for...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Burger, Markus
Otros Autores: Graeber, Bernhard, Schindlmayr, Gero
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Chichester, England ; Hoboken, NJ : John Wiley & Sons, ©2007.
Colección:Wiley finance series.
Temas:
Energy industries > Risk management.
Industries énergétiques > Gestion du risque.
TECHNOLOGY & ENGINEERING > Power Resources > Electrical.
Energiemarkt
Finanzmathematik
Mathematisches Modell
Acceso en línea:Texto completo
Texto completo
Tabla de Contenidos:
  • 1. Energy Markets
  • 2. Energy Derivatives
  • 3. Commodity Price Models
  • 4. Fundamental Market Models
  • 5. Electricity Retail Products
  • 6. Risk Management.
  • 1. Energy Markets
  • 1.1. The oil market
  • 1.1.1. Consumption, production and reserves
  • 1.1.2. Crude oil trading
  • 1.1.3. Refined oil products
  • 1.2. The natural gas market
  • 1.2.1. Consumption, production and reserves
  • 1.2.2. Natural gas trading
  • 1.2.3. Price formulas with oil indexation
  • 1.2.4. Liquefied natural gas
  • 1.3. The coal market
  • 1.3.1. Consumption, production and reserves
  • 1.3.2. Coal trading
  • 1.3.3. Freight
  • 1.3.4. Coal subsidies in Germany: BAFA-indexed prices
  • 1.4. The electricity market
  • 1.4.1. Consumption and production
  • 1.4.2. Electricity trading
  • 1.4.3. Products in the electricity markets
  • 1.4.4. Energy exchanges
  • 1.5. The emissions market
  • 1.5.1. Kyoto Protocol
  • 1.5.2. EU emissions trading scheme
  • 1.5.3. Flexible mechanisms
  • 1.5.4. Products and market places
  • 1.5.5. Emissions trading in North America
  • 2. Energy Derivatives
  • 2.1. Forwards, futures and swaps
  • 2.1.1. Forward contracts
  • 2.1.2. Futures contracts
  • 2.1.3. Swaps
  • 2.2. "Plain vanilla" options
  • 2.2.1. The put-call parity and option strategies
  • 2.2.2. Black's futures price model
  • 2.2.3. Option pricing formulas
  • 2.2.4. Hedging options: the "Greeks"
  • 2.2.5. Implied volatilities and the "volatility smile"
  • 2.2.6. Swaptions
  • 2.3. American and Asian options
  • 2.3.1. American options
  • 2.3.2. Asian options
  • 2.4. Commodity bonds and loans
  • 2.5. Multi-underlying options
  • 2.5.1. Basket options
  • 2.5.2. Spread options
  • 2.5.3. Quanto and composite options
  • 2.6. Spot price options
  • 2.6.1. Pricing spot price options
  • 2.6.2. Caps and floors
  • 2.6.3. Swing options
  • 2.6.4. Virtual storage
  • 3. Commodity Price Models
  • 3.1. Forward curves and the market price of risk
  • 3.1.1. Investment assets
  • 3.1.2. Consumption assets and convenience yield
  • 3.1.3. Contango, backwardation and seasonality
  • 3.1.4. The market price of risk
  • 3.1.5. Derivatives pricing and the risk-neutral measure
  • 3.2. Commodity spot price models
  • 3.2.1. Geometric Brownian motion
  • 3.2.2. The one-factor Schwartz model
  • 3.2.3. The Schwartz-Smith model
  • 3.3. Stochastic forward curve models
  • 3.3.1. One-factor forward curve models
  • 3.3.2. A two-factor forward curve model
  • 3.3.3. A multi-factor exponential model
  • 3.4. Electricity price models
  • 3.4.1. The hourly forward curve
  • 3.4.2. The SMaPS model
  • 3.4.3. Regime-switching model
  • 3.5. Multi-commodity models
  • 3.5.1. Regression analysis
  • 3.5.2. Correlation analysis
  • 3.5.3. Cointegration
  • 3.5.4. Model building.
  • 4. Fundamental Market Models
  • 4.1. Fundamental price drivers in electricity markets
  • 4.1.1. Demand side
  • 4.1.2. Supply side
  • 4.1.3. Interconnections
  • 4.2. Economic power plant dispatch
  • 4.2.1. Thermal power plants
  • 4.2.2. Hydro power plants
  • 4.2.3. Optimisation methods
  • 4.3. Methodological approaches
  • 4.3.1. Merit order curve
  • 4.3.2. Optimisation models
  • 4.3.3. System dynamics
  • 4.3.4. Game theory
  • 4.4. Relevant system information for electricity market modelling
  • 4.4.1. Demand side
  • 4.4.2. Supply side
  • 4.4.3. Transmission system
  • 4.4.4. Historical data for backtesting
  • 4.4.5. Information sources
  • 4.5. Application of electricity market models
  • 4.6. Gas market models
  • 4.6.1. Demand side
  • 4.6.2. Supply side
  • 4.6.3. Transport
  • 4.6.4. Storage
  • 4.6.5. Portfolio optimisation
  • 4.6.6. Formulation of the market model
  • 4.6.7. Application of gas market models
  • 4.7. Market models for oil, coal, and CO2 markets
  • 5. Electricity Retail Products
  • 5.1. Interaction of wholesale and retail markets
  • 5.2. Retail products
  • 5.2.1. Common full service contracts
  • 5.2.2. Indexed contracts
  • 5.2.3. Partial delivery contracts
  • 5.2.4. Portfolio management
  • 5.2.5. Supplementary products
  • 5.3. Sourcing
  • 5.3.1. Business-to-business (B2B)
  • 5.3.2. Business-to-consumer (B2C)
  • 5.3.3. Small accounts
  • 5.3.4. Municipalities and reseller
  • 5.4. Load forecasting
  • 5.5. Risk premium
  • 5.5.1. Price validity period
  • 5.5.2. Balancing power
  • 5.5.3. Credit risk
  • 5.5.4. Price-volume correlation
  • 5.5.5. Strict risk premiums
  • 5.5.6. Hourly price profile risk
  • 5.5.7. Volume risk
  • 5.5.8. Operational risk
  • 5.5.9. Risk premium summary
  • 6. Risk Management
  • 6.1. Market price exposure
  • 6.1.1. Delta position
  • 6.1.2. Variance minimising hedging
  • 6.2. Value-at-Risk and further risk measures
  • 6.2.1. Definition of Value-at-Risk
  • 6.2.2. Parameters of the Value-at-Risk measure
  • 6.2.3. Computation methods
  • 6.2.4. Liquidity-adjusted Value-at-Risk
  • 6.2.5. Estimating volatilities and correlations
  • 6.2.6. Backtesting
  • 6.2.7. Further risk measures
  • 6.3. Credit risk
  • 6.3.1. Legal risk
  • 6.3.2. Quantifying credit risk
  • 6.3.3. Credit rating.

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