Publication:
Analysis of sectoral credit default cycle dependency with wavelet networks: Evidence from Turkey

dc.contributor.authorsCifter, Atilla; Yilmazer, Sait; Cifter, Elif
dc.date.accessioned2022-03-12T17:37:17Z
dc.date.accessioned2026-01-11T16:39:45Z
dc.date.available2022-03-12T17:37:17Z
dc.date.issued2009
dc.description.abstractIn this paper, we investigate the relationship between industrial production and sectoral credit defaults (non-performing loans ratio) cycle by wavelet network analysis in Turkey over the period January 2001-November 2007. We use feedforward neural network based wavelet decomposition to analyze the contemporaneous connection between industrial production cycles and sectoral credit default cycles at different time scales between 2 and 64 months. The main findings for Turkey indicates that industrial production cycles effect the sectoral credit default cycles at different time scales and thus indicate that the creditors should consider the multiscale sectoral cycles in order to minimize credit default rates. (C) 2009 Elsevier B.V. All rights reserved.
dc.identifier.doi10.1016/j.econmod.2009.07.014
dc.identifier.eissn1873-6122
dc.identifier.issn0264-9993
dc.identifier.urihttps://hdl.handle.net/11424/229363
dc.identifier.wosWOS:000270646400024
dc.language.isoeng
dc.publisherELSEVIER SCIENCE BV
dc.relation.ispartofECONOMIC MODELLING
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectSectoral credit default cycles
dc.subjectBusiness cycles
dc.subjectWavelets
dc.subjectWavelet networks
dc.subjectMEASURING BUSINESS CYCLES
dc.subjectECONOMIC TIME-SERIES
dc.subjectREGRESSION RESIDUALS
dc.subjectEFFICIENT TESTS
dc.subjectHOMOSCEDASTICITY
dc.subjectINDEPENDENCE
dc.subjectNORMALITY
dc.subjectSLOVENIA
dc.subjectRISK
dc.titleAnalysis of sectoral credit default cycle dependency with wavelet networks: Evidence from Turkey
dc.typearticle
dspace.entity.typePublication
oaire.citation.endPage1388
oaire.citation.issue6
oaire.citation.startPage1382
oaire.citation.titleECONOMIC MODELLING
oaire.citation.volume26

Files