Value-at-risk (VAR)

Valid Assumptions Required: aggregation

In the first article of this series, in which Brett Humphreys questions some of the assumptions and decisions that go into the calculation of value-at-risk, he focuses on portfolio aggregation.

Operational VAR: a closed-form approximation

Klaus Böcker and Claudia Klüppelberg investigate a simple loss distribution model for operational risk. They show that, when loss data is heavy-tailed (which in practice it is), a simple closed-form approximation for operational VAR can be obtained. They…

Time for multi-period capital models

Several financial institutions use single-period models to determine their credit portfolio lossdistribution, calculate their loss volatility and assign economic capital. Here, Kevin Thompson,Alistair McLeod, Panayiotis Teklos and Shobhit Gupta…

A Markovian approach to modelling correlated defaults

Vladyslav Putyatin, David Prieul and Svetlana Maslova unveil a simple dynamic binomial credit model with a Poissonian mixing distribution to satisfy the constraints faced by financial institutions assessing their credit exposure in a consistent manner…

The misdirected directive?

Germany's financial regulator, BaFin, tried to steal a march on its European rivals by implementing a new directive that should open the door to asset managers investing in new products and using over-the-counter derivatives. But did it get it wrong?

VAR: ready to explode?

The SEC plans to force US securities firms to tighten up their value-at-risk reporting. Its decision comes as VAR at the world’s leading financial services firms soared an average 25.8% last year. Who are the biggest risk-takers, and are risk managers…

Building scenarios

Kenji Fujii of UFJ Holdings looks at the benefits of using scenario analysis as a means of managing operational risk, and discusses UFJ Bank's scenario-based advanced measurement approach.

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