Cutting Edge

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…

Component proponents

Principal component analysis is a widely used technique in finance but can be problematic when different data sets are grouped together. Christophe Pérignon and Christophe Villa show how to resolve this problem using a technique from biology called…

VAR you can rely on

Analytical and simulation-based methods often appear as rivals, but many real world problems are best served by judicious combinations of both approaches. In a first of a pair of computationally themed papers, Rabi De and Tanya Tamarchenko present a…

Calculating portfolio loss

For credit portfolios, analytical methods work best for tail risk, while Monte Carlo is used to model expected loss. However, products such as CDOs require a model for the entire distribution. Sandro Merino and Mark Nyfeler meet the challenge by…

Risk and probability measures

Although its drawbacks are well known, VAR has become institutionalised as the market risk measure of choice among trading firms and regulators. Now there is a growing feeling that a reappraisal is overdue, exemplified here by Phelim Boyle, Tak Kuen Siu…

A two-factor mean-reverting model

Commodity markets exhibit multi-factor behaviour as well as mean reversion. Building upon their previous paper, David Beaglehole and Alain Chebanier conclude the current Masterclass series by developing a two-factor mean-reverting model for crude oil…

The maturity effect on credit risk capital

In a mark-to-market approach to credit risk capital, ratings or spread volatility has the effect of making longer-maturity loans more capital-intensive. This is incorporated in the current Basel II proposals via a maturity adjustment factor. Arguing that…

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

Testing assumptions

In calculating value-at-risk forecasts for trading portfolios, distributional assumptions are asimportant as the choice of risk factors, but it is not easy to determine the source of errorwhen rejected forecasts occur. Here, Jeremy Berkowitz develops a…

Substitute hedging

Derivatives on assets that are difficult to trade are of growing importance. Pricing suchderivatives requires the use of utility theory and proxy assets for hedging. Here, VickyHenderson and David Hobson review the theory and discuss several topical…

Universal Barriers

As our survey in this issue shows, there is an increasing volume of barrier products traded in the forex options market. Here, Alexander Lipton and William McGhee discuss the pricing of barriers under various model frameworks, with particular focus on…

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

Honour your contribution

What is the best method for determining the risk contribution of a component in a portfolio? An exploration of the pros and cons of three important methods, showing that none dominates the others.

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