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Value-at-risk (VAR)

Enough’s enough

Brett Humphreys takes the guesswork out of determining how many simulations are needed to calculate value-at-risk

Getting stressed

To understand how much value can be lost from a position in the energy markets, we need to use measures other than value-at-risk. Brett Humphreys discusses methods for creating effective stress tests

Unsystematic credit risk

Although Basel has shifted its treatment of unsystematic credit risk from the first, capital rules pillar (where it was called the 'granularity adjustment') to the second, supervisory pillar of the forthcoming Accord, this issue is of great practical…

Unsystematic credit risk

Although Basel has shifted its treatment of unsystematic credit risk from the first, capital rules pillar (where it was called the ‘granularity adjustment’) to the second, supervisory pillar of the forthcoming Accord, this issue is of great practical…

Reaping integration rewards

In the October issue of Risk, Clive Davidson discussed the integration of ALM and ERM technology. Here, in a second article, he profiles the firms that have tackled this project and reviews the challenges, advantages and pitfalls of the integration…

Var too far

The energy industry has shown tremendous commitment to value-at-risk (Var) methodologies. But use of Var has been misguided, as James Ockenden discovers

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…

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…

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…

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…

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.

Analytical approach to credit risk modelling

The increasing popularity of VAR-based credit portfolio risk models has led to a growing recognition that Monte Carlo techniques are inadequate for economic capital calculations. Here, Michael Pykhtin and Ashish Dev present a new analytical alternative…

Op risk modelling evolves

Operational risk is devilishly difficult to model, but dealers and software vendors are making headway. Automated op risk reporting, profiling and sophisticated operational value-at-risk (VAR) modelling are finally beginning to catch-on in banks.

Dealers' VAR increases during 2001, says BofE report

Average value-at-risk (VAR) levels among leading dealers has increased over 2001, but despite increased vol across equity and rates markets post-September 11, large trading losses appear to have been avoided, according to the Bank of England’s Financial…

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