Open Access Open Access  Restricted Access Subscription Access

Adaptive Models for Tail of Distributions

O.S Adesina, D.A Agunbiade, O. Ibhadode

Abstract



Modelling tails of distributions can performed with models such as Weibull, Frechet and Gumbel distribution, it can also be modelled with generalized extreme value (GEV); a model which combines the three models. The limitation of GEV model is that it is not sufficient to model some levels of fat tail distributions. To identify the strength of GEV, Simulation study was carried out using both Generalized Pareto distributions (GPD) and GEV models with maximum likelihood estimate (MLE), and comparison was drawn between the models. Empirical results revealed that GPD model is sufficient to model fat tail distributions well irrespective of the data points, On the other hand, GEV models thin tail distribution better than GPD. GPD was modelled using electrical energy dataset and obtained tail risk, while GEV was used to model daily foreign exchange data.

Keywords


Extreme Value Theory, tail risk, Peak Over Threshold, foreign exchange, electrical energy

Full Text:

PDF


Disclaimer/Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information.