Fat tails
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Source: Risk magazine
Despite the remarkable advances made over the past 25 years, David Rowe argues the industry’s existing risk models are not fit for purpose when it comes to stress testing and analysis of tail risk
Published online only
Source: Risk magazine
Models of US and UK equity markets show players expect fresh outbreak of crisis
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More Fat tails articles
Published online only
Source: Risk magazine
Financial institutions are more aware of the risks posed by high-impact events since the crisis, but the question is how to encapsulate these in models. Zari Rachev, Boryana Racheva-Iotova and Stoyan Stoyanov discuss three approaches for capturing fat...
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Source: Risk magazine
Cross-asset quadratic Gaussian models have been limited in the scale of their implementation by the difficulty in ensuring the correct drift conditions to omit arbitrage. Here, Paul McCloud shows how to exploit the symmetries of the functional form to...
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Source: Operational Risk & Regulation
For operational risk managers to really make a difference to their firms' fortunes, they must be willing to get their hands dirty and face facts, no matter how scary the facts may be, says Sergio Scandizzo, in the second of a two-part series
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Source: Asia Risk
Klaus Bocker and Claudia Kluppelberg 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 value-at-risk (VAR) can...
Published online only
Source: Risk magazine
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....
Published online only
Source: Energy Risk
On a distribution curve, a fat-tailed distribution has a greater-than-normal chance of a big positive or negative realisation.
Published online only
Source: Energy Risk
The property of a statistical distribution to have more occurrences far away from the mean than would be predicted by a normal distribution. Also referred to as ‘fat tails’.
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