BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//CREST - ECPv5.1.3//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:CREST
X-ORIGINAL-URL:https://crest.science
X-WR-CALDESC:Events for CREST
BEGIN:VTIMEZONE
TZID:Europe/Helsinki
BEGIN:DAYLIGHT
TZOFFSETFROM:+0200
TZOFFSETTO:+0300
TZNAME:EEST
DTSTART:20250330T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0300
TZOFFSETTO:+0200
TZNAME:EET
DTSTART:20251026T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Europe/Helsinki:20251001T140000
DTEND;TZID=Europe/Helsinki:20251001T150000
DTSTAMP:20260710T020455
CREATED:20250926T131421Z
LAST-MODIFIED:20250929T141618Z
UID:18383-1759327200-1759330800@crest.science
SUMMARY:Renata ALCOFORADO  (Federal University of Pernambuco & Chaire ACTIONS"
DESCRIPTION:Actuariat et Risque Contemporains\nTime : 14h00 – 15h00 \nDate : 01/10/2025 \nLieu : Salle 2012 \n  \nRenata ALCOFORADO (Federal University of Pernambuco & Chaire ACTIONS”  “Risk model with dependent frequency and severity for Liability and Housing Insurance” \nAbstract: \nA common assumption in classical risk theory is the independence between claim frequency and severity. However\, this often fails in practice\, especially when subtle or nonlinear dependencies are present. This study analyzes a real-world dataset comprising 15\,665 claims from housing and liability insurance contracts\, recorded between 01/01/2015 and 31/12/2019\, provided by an anonymous insurer. Unlike most literature focused on automobile insurance\, our data allow us to explore dependence in less-studied lines of business\, which pose unique challenges. We investigate the presence and nature of dependence between frequency and severity\, and how this relationship evolves over time and across insurance types. Our approach combines parametric and nonparametric methods: we fit Poisson-Inverse Gaussian\, Negative Binomial\, Weibull\, and Log-Normal distributions to the marginals\, and apply copula-based techniques to assess joint behavior. Using pseudo-observations\, we estimate empirical copulas\, visualize joint densities\, and perform statistical tests of independence and equality (KcopTest)\, which reveal a structural break in housing insurance in 2016. Results indicate strong positive dependence in liability insurance. In housing insurance\, we find near-independence in most years\, but a weak and significant negative dependence in 2016. Finally\, GAMLSS models confirm diverging patterns: in liability insurance\, severity increases with frequency; in housing insurance\, it decreases\, in contrast to findings by Garrido (2016). We discuss implications for pricing\, reserving\, and solvency assessment under dependence. \nReferences.\n[1] Garrido\, J.\, Genest\, C.\, and Schulz\, J. (2016). Generalized linear models for dependent\nfrequency and severity of insurance claims Insurance: Mathematics and Economics 70\, 205-215. \nOrganisateurs : Hillairet Caroline\, Olivier Lopez \nLieu : 2020 \nGENES-CREST – Salle t.b.a – 5 Av Henri Châtelier – 91120 Palaiseau \n  \n
URL:https://crest.science/event/renata-alcoforado-federal-university-of-pernambuco-chaire-actions/
CATEGORIES:Actuariat et Risques Contemporains,Finance-Insurance,Seminars
ATTACH;FMTTYPE=:
END:VEVENT
END:VCALENDAR