Calibrating Trees to the Market Price of Options
In this article, published in Energy Risk Magazine's Masterclass Series, we outline an approach for calibrating a local volatility surface single factor model to market prices of average price (Asian) options.
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Application of Multi-Factor Multi-Commodity Modeling Framework to Value Complex Spread Options
In this article published in Energy Risk Magazine’s Masterclass series, we describe how the MFMC model can be used as the basis of a Monte Carlo simulation for the valuation of complicated spread options that depend on a basket of energy prices.
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Application of Multi-Factor Multi-Commodity Model for Cargo Dispatch Optimisation
In this article published in Energy Risk Magazine’s Masterclass series, we describe the use of the multi-factor multi-commodity (MFMC) model in determining the optimal location for shipping a cargo, specifically the delivery of LNG.
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Multi-Factor Multi-Commodity Models & Parameter Estimation Processes
This article published in Energy Risk Magazine’s Masterclass series, discusses a general multi factor multi commodity (MFMC) model and the process for estimating parameters from historical data.
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Risks & Hedging Techniques for Swing Contracts
The main features of swing contracts which make them difficult to value and risk manage are the constraints on the quantity of, for example, gas which can be taken. In this article, published in Energy Risk Magazine’s Masterclass series, we discuss risks & hedging techniques for swing contacts with take-or-pay, make-up & carry-forward features.
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Measuring & Capturing Value in the Flexibility of Gas Swing Contracts
In this article, published in Energy Risk Magazine’s Masterclass Series, we outline the key features of typical swing contracts, describe how the value in these contracts can be determined, and also how the constraints on the contract impact the optimal exercise strategy.
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Risk Analysis of Swing Contracts
Swing-based contracts allow the holder to choose within limits the quantity of the underlying energy they wish to receive.
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Valuation of Swing Contracts
In this article we outline a methodology for the pricing of swing type contracts, which applies the technique to a gas sales agreement (GSA). The performance of an analysis of the GSA is left to a future article. The term swing refers to the flexibility in the quantity of energy that the holder of the swing option can receive.
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Derivatives on the Forward Curve
In this article, we show how very general European-style derivatives can be priced and extend the analysis to path-dependent and American-style options.
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Valuation & Risk Management of Gas Supply Agreements & Power Station Based Contracts
Power generation based contracts such as Gas Supply Agreements and Virtual Power Stations have embedded path dependent optionality.
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The Many Shapes of Volatility
Perhaps the main advantage of the forward curve modelling approach is the flexibility the user has in choosing both the number and form of the volatility functions.
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Analysis for Achievement
Here we concentrate on valuations of products that do yield analytical tractability,and so do have closed-form solutions. Analytical pricing, if achievable, is important for a number of reasons.
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Extending Mean-Reversion Jump Diffusion
But some energy prices, electricity being the classic example, often exhibit sudden,unexpected and discontinuous changes. A model such as that mentioned above struggles to capture this type of behaviour (see EPRM December 2000, page 26).
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Jumping the Gaps
Energy prices often exhibit sudden, unexpected and discontinuous changes. Jump behaviour – ‘spiking’or ‘gapping’, is driven in many cases by fluctuations in demand and low elasticity of supply, reflecting rigidities in the transportation and transmission system and limited inventories.
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Spot Simulation Processing
We recently showed how to estimate parameters for a mean reverting spot price model applied to energy markets (see EPRM November 2000, page 24). Here we extend that analysis to the pricing of a wide range of energy derivatives using spot price models.
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Making the Most of Mean Reversion
In this article we analyse this so-called mean reversion,which was first described by Vasicek (1977) for modelling interest-rate dynamics, and which has subsequently been widely adapted. some long-term level,and not drift off to higher and higher values.
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Which Var for Energy Derivatives
Value-at-risk (Var) answers a fundamental question facing all energy risk managers: What is the most I can lose in a chosen number of days with chosen likelihood?
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