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dc.contributor.authorKremen, Viktoriia
dc.contributor.authorBrychko, Maryna
dc.date.accessioned2020-07-09T09:05:06Z-
dc.date.available2020-07-09T09:05:06Z-
dc.date.created2019-11-25
dc.date.issued2019-11-25
dc.identifier.citationKremen V. Logit and probit model for prediction the financial health of insurance company / Kremen Viktoriia, Brychko Maryna // Business Risk in Changing Dynamics of Global Village 2 : Monograph. — Nysa : Publishing House of University of Applied Sciences in Nysa, 2019. — P. 223–232. — (Business & tourism).
dc.identifier.isbn978-83-65881-19-9
dc.identifier.urihttp://elartu.tntu.edu.ua/handle/lib/32273-
dc.format.extent223-232
dc.language.isoen
dc.publisherPublishing House of University of Applied Sciences in Nysa
dc.relation.ispartofBusiness Risk in Changing Dynamics of Global Village 2, 2019
dc.relation.urihttps://forinsurer.com/ratings/Nonlife
dc.relation.urihttp://eprints.ucm.es/6836/1/0412.pdf
dc.relation.urihttps://nfp.gov.ua/ua/Ohliad-rynkiv.html
dc.relation.urihttps://smida.gov.ua/db/emitent
dc.subjectinsurance company
dc.subjectprediction the financial health
dc.subjectlogit and probit model
dc.subjectregression
dc.titleLogit and probit model for prediction the financial health of insurance company
dc.typeBook Chapter
dc.rights.holder© Publishing House of University of Applied Sciences in Nysa, 2019
dc.rights.holder© Ternopil Ivan Puluj National Technical University, 2019
dc.format.pages10
dc.relation.referencesen1. Anghelache, С., and Armeanu, D. Application of Discriminant Analysis on Romanian Insurance Market. Theoretical and Applied Economics, 2008. 11 (528). Pp. 51−62.
dc.relation.referencesen2. Barr, Richard S., and Thomas F. Siems. Bank failure prediction using DEA to measure management quality. Interfaces in computer science and operations research. Springer, Boston, MA, 1997. Pp. 341-365.
dc.relation.referencesen3. Forinsurer [Online]. – Available at: https://forinsurer.com/ratings/Nonlife
dc.relation.referencesen4. Hanweck, Gerald A. Predicting bank failure. No. 19. Board of Governors of the Federal Reserve System (US), 1977.
dc.relation.referencesen5. Martin, D. Early warning of bank failure: A logit regression approach. Journal of banking & finance, 1977. 1.3. Pp. 249-276.
dc.relation.referencesen6. Martіnez Z. D., Menеndez J. F., Vargas J. S. Algorithm versus Discriminant Analysis. An Application to the Prediction of Insolvency in Spanish Non-life Insurance Companies. Documentos 232 de trabajo de la Facultad de Ciencias Económicas y Empresariales [Online]. – Available at: http://eprints.ucm.es/6836/1/0412.pdf
dc.relation.referencesen7. National Commission for Regulation of Financial Services Markets of Ukraine [Online]. – Available at: https://nfp.gov.ua/ua/Ohliad-rynkiv.html
dc.relation.referencesen8. Prymak, Ju.R. Suchasni ukrajinsjki ta mizhnarodni metody analizu finansovoji stijkosti bankivsjkoji ustanovy. Mizhnarodnyj naukovyj zhurnal, 2016. 9. Pp. 115−122
dc.relation.referencesen9. Stock Market Infrastructure Development Agency of Ukraine [Online]. – Available at: https://smida.gov.ua/db/emitent.
dc.relation.referencesen10. Tatom, J., and Houston, R. Predicting failure in the commercial banking industry. Networks Financial Institute Working Paper, 2011. Working Paper. 27.
dc.identifier.citationenKremen V., Brychko M. (2019) Logit and probit model for prediction the financial health of insurance company. Business Risk in Changing Dynamics of Global Village 2 : Monograph (Nysa), pp. 223-232.
dc.contributor.affiliationKyiv National University of Technologies and Design, Kyiv, Ukraine
dc.contributor.affiliationSumy State University, Sumy, Ukraine
dc.citation.spage223
dc.citation.epage232
Vyskytuje se v kolekcích:Business Risk in Changing Dynamics of Global Village 2: Monograph



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