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Asymptotics of Ruin Probabilities for Perturbed Discrete Time Risk ProcessesPrimeFaces.cw("AccordionPanel","widget_formSmash_some",{id:"formSmash:some",widgetVar:"widget_formSmash_some",multiple:true}); PrimeFaces.cw("AccordionPanel","widget_formSmash_all",{id:"formSmash:all",widgetVar:"widget_formSmash_all",multiple:true});
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PrimeFaces.cw("AccordionPanel","widget_formSmash_responsibleOrgs",{id:"formSmash:responsibleOrgs",widgetVar:"widget_formSmash_responsibleOrgs",multiple:true}); 2014 (English)In: Modern Problems in Insurance Mathematics / [ed] Dmitrii Silvestrov, Anders Martin-Löf, Springer, 2014, p. 95-112Chapter in book (Refereed)
##### Abstract [en]

##### Place, publisher, year, edition, pages

Springer, 2014. p. 95-112
##### Series

EAA Series, ISSN 1869-6929
##### National Category

Probability Theory and Statistics
##### Research subject

Mathematical Statistics
##### Identifiers

URN: urn:nbn:se:su:diva-95469DOI: 10.1007/978-3-319-06653-0_7ISBN: 978-3-319-06652-3 (print)ISBN: 978-3-319-06653-0 (print)OAI: oai:DiVA.org:su-95469DiVA, id: diva2:660274
#####

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Available from: 2013-10-29 Created: 2013-10-29 Last updated: 2016-04-28Bibliographically approved
##### In thesis

We consider the problem of approximating the infinite time horizon ruin probabilities for discrete time risk processes. The approach is based on asymptotic results for non-linearly perturbed discrete time renewal equations. Under some moment conditions on the claim distributions, the approximations take the form of exponential asymptotic expansions with respect to the perturbation parameter. We show explicitly how the coefficients of these expansions can be computed as functions of the coefficients of the expansions of local characteristics for perturbed risk processes.

1. Asymptotic Expansions for Perturbed Discrete Time Renewal Equations$(function(){PrimeFaces.cw("OverlayPanel","overlay660387",{id:"formSmash:j_idt1459:0:j_idt1467",widgetVar:"overlay660387",target:"formSmash:j_idt1459:0:parentLink",showEvent:"mousedown",hideEvent:"mousedown",showEffect:"blind",hideEffect:"fade",appendToBody:true});});

2. Perturbed discrete time stochastic models$(function(){PrimeFaces.cw("OverlayPanel","overlay918673",{id:"formSmash:j_idt1459:1:j_idt1467",widgetVar:"overlay918673",target:"formSmash:j_idt1459:1:parentLink",showEvent:"mousedown",hideEvent:"mousedown",showEffect:"blind",hideEffect:"fade",appendToBody:true});});

doi
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