Energy Risk/Technical paper
Applying modern portfolio theory to optimal gas purchasing
Yijun Du and Xiaorui Hu present a general framework for applying modern portfolio theory to optimal natural gas procurements. They show that successful natural gas procurement involves determining the optimal allocation between fixed-price and floating…
Project risk: improving Monte Carlo value-at-risk
Cashflows from projects and other structured deals can be as complicated as we are willing to allow, but the complexities of Monte Carlo project modelling need not complicate value-at-risk calculation. Here, Andrew Klinger imports least-squares valuation…
Asian basket spreads and other exotic averaging options
Giuseppe Castellacci and Michael Siclari of OpenLink introduce a class of exotic options that simultaneously generalises both Asian and basket options. They develop approximate analytic models for real-time pricing of complex instruments that average…
A decision model for selling park and loan services
The park and loan model is useful for gas storages and pipelines. The concept can be applied to many ‘when to sell’-type decisions. Here, Huagang ‘Hugh’ Li considers selling park and loan services as a financial and statistical decision on revenue and…
The front-month proxy hedge
The front-month proxy hedge is a correlation-based hedge that seeks to neutralise the aggregate sensitivity of a portfolio to a futures curve by converting the individual futures hedges into a single hedge with respect to only the front-month contract…
Weather option pricing with transaction costs
The weather derivatives market is becoming more liquid, and dynamic hedging of weather options with weather swaps is now possible, though limited by transaction costs. Here Stephen Jewson investigates the effect of such hedging on option pricing
A joint state-space model for spot and futures power
Portfolio-wide risk management requires a model that accounts correctly for correlations between the spot asset and various futures products. Kjetil Kåresen and Egil Husby discuss a joint multi-factor model for power spot and futures prices and show how…
Estimating oil price volatility: a Garch model
Nikolai Sidorenko, Michael Baron and Michael Rosenberg present a general framework for modelling energy price volatility. These models explain the volatility persistence and clustering present in many commodity prices. In addition, they can incorporate…
Risk and reward at the speed of light: a new electricity price model
Samuel Bodily and Michel Del Buono propose a new electricity price model. The mean-reverting proportional volatility model matches important characteristics of power price dynamics where others, such as geometric Brownian motion, fall short
Exploring option pricing with mean-reversion jump diffusion
Yijun Du explores option pricing with a mean-reversion and jump-diffusion – or MJ – model, using Monte Carlo simulation. We find that jumps can increase the call price, a higher mean-reversion rate lowers the call price and the time to maturity has…
Modelling weather-sensitive electrical loads
Here Véronique Bugnion, Aram Sogomonian and Glen Swindle introduce a new methodology for forecasting and jointly simulating temperature and electrical load
Mean-reverting smiles
Commodity markets such as crude oil exhibit mean reversion as well as option smiles. David Beaglehole and Alain Chebanier meet this challenge, constructing a model suitable for pricing exotic options in these markets
At the end of the tail
When fat tails are present, extreme value theory provides a framework for estimating value-at-risk at higher confidence levels with greater accuracy than traditional Var methods. Naveen Andrews and Mark Thomas explain