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@article{Noven:2018:10.21314/JEM.2018.179,
author = {Noven, R and Veraart, A and Gandy, A},
doi = {10.21314/JEM.2018.179},
journal = {Journal of Energy Markets},
pages = {1--24},
title = {A latent trawl process model for extreme values},
url = {http://dx.doi.org/10.21314/JEM.2018.179},
volume = {11},
year = {2018}
}

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TY  - JOUR
AB  - This paper presents a new model for characterising temporaldependence in exceedancesabove a threshold.  The model is based on the class of trawl processes, which are stationary,infinitely  divisible  stochastic  processes.   The  model  for  extreme  values  is  constructed  byembedding a  trawl  process  in  a hierarchical  framework,  which  ensures that  the marginaldistribution  is  generalised  Pareto,  as  expected  from  classical  extreme  value  theory.   Wealso consider a modified version of this model that works witha wider class of generalisedPareto distributions,  and has the advantage of  separating  marginal  and temporal  depen-dence  properties.   The  model  is  illustrated  by  applicationsto  environmental  time  series,and it is shown that the model offers considerable flexibilityin capturing the dependencestructure of extreme value data
AU  - Noven,R
AU  - Veraart,A
AU  - Gandy,A
DO  - 10.21314/JEM.2018.179
EP  - 24
PY  - 2018///
SN  - 1756-3607
SP  - 1
TI  - A latent trawl process model for extreme values
T2  - Journal of Energy Markets
UR  - http://dx.doi.org/10.21314/JEM.2018.179
UR  - http://arxiv.org/abs/1511.08190
UR  - http://hdl.handle.net/10044/1/63333
VL  - 11
ER  -

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