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The Lila distribution and its applications in risk modelling

Bertrand K. Hassani () and Wei Yang ()
Additional contact information
Bertrand K. Hassani: Centre d'Economie de la Sorbonne, Grupo Santander, https://centredeconomiesorbonne.univ-paris1.fr
Wei Yang: Risk methodology, Santander UK plc

Documents de travail du Centre d'Economie de la Sorbonne from Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne

Abstract: Risk date sets tend to have heavy-tailed, sometimes bi-modal, empirical distributions, especially in operational risk, market risk and customers behaviour data sets. To capture these observed “unusual” features, we construct a new probability distribution and call it the lowered-inside-leveraged-aside (Lila) distribution as it transfers the embedded weight of data from the body to the tail. This newly constructed distribution can be viewed as a parametric distribution with two peaks. It is constructed through the composition of a Sigmoid-shaped continuous increasing differentiable function with cumulative distribution functions of random variables. Examples and some basic properties of the Lila distribution are illustrated. As an application, we fit a Lila distribution to a set of generated data by using the quantile distance minimisation method (alternative methodologies have been tested too, such as maximum likelihood estimation)

Keywords: probability distribution; parametric distribution; multimodal distribution; operational risk; market risk; pseudo bi-modal distribution (search for similar items in EconPapers)
JEL-codes: C13 C16 G21 G32 (search for similar items in EconPapers)
Pages: 25 pages
Date: 2016-10
New Economics Papers: this item is included in nep-ecm and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:mse:cesdoc:16068

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