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Quantitative analysis

Cutting edge: Visualising value-at-risk

Risk transparency is an important yet elusive goal of any risk management process. One challenge is to understand the diversification effects of the portfolio elements. Wentao Zhao and Kevin Kindall introduce a graphical technique based on value-at-risk…

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…

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…

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

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