Kreditni rizik

Kreditni rizik jest rizik nepodmirenja obveza, odnosno mogućnost da se uložena sredstva neće pravodobno i/ili u potpunosti vratiti te da se neće vraćati planiranom dinamikom. Kreditni rejting predstavlja mišljenje o kreditnom riziku u narednom periodu i podrazumijeva procjenu sposobnosti i spremnosti dužnika da pravovremeno i u potpunosti podmiruje svoje obveze prema kreditorima. Promjena kreditnog rejtinga reflektira procjenu o poboljšanju ili pogoršanju kreditne kvalitete dužnika. Glavni cilj ovog rada jest modeliranje kreditnog rizika financijskih institucija procjenom vjerojatnosti promjene rejtinga i prognoziranjem vjerojatnosti defaulta, odnosno stanja neispunjavanja dužnikovih novčanih obveza, u jednom ili više narednih perioda. Polazeći od klasifikacije rizičnosti dužnika na rejting skali, pokazan je put od opaženih promjena kreditnog rejtinga do procijenjenih vjerojatnosti prijelaza i dana procjena za odstupanje od stvarnih prijelaznih stopa. Zbog međuovisnosti dužnika koji tvore portfelj, poseban je naglasak stavljen na normalni model s pragom s jednim parametrom unutar kojeg možemo na konzistentan način modelirati zavisne migracije. Obzirom da je vremenska stabilnost prijelaznih matrica jedan od ključnih elemenata za procjenu kreditnog rizika, sljedeći korak bio je predstaviti statističke testove o homogenosti i ilustrirati ih konkretnim primjerima. Potom smo analizirali višeperiodne prijelaze među kreditnim razredima, oslanjajući se na teoriju Markovljevih lanaca i bootstrap istih, dok je u konačnici uzeta u obzir i promjena u sastavu i rizičnosti kreditnog portfelja izazvana rejting migracijama.Credit risk is the risk that the counterparty will not settle its liability i.e. the possibility that invested funds will not be recovered in full or within the planned schedule. Credit rating is a forward-looking opinion about credit risk and an assessment of the ability and willingness of an issuer to meet its financial obligations in full and on time. A change in a rating reflects the assessment that the obligor’s credit quality has improved (upgrade) or deteriorated (downgrade). The main goal of this graduate thesis is modeling credit risk of financial institutions by assessing the rating migration probabilities and predicting the probability of default, i.e. of obligor’s failure to meet the legal obligations or conditions of debt repayment, in one or more upcoming periods. Starting from classification of debtor’s riskiness on rating scale, the way from the observed data to the estimated transition probabilities is shown and estimates for the standard deviations of the transition rates are given. Due to interdependencies of borrowers that compose a portfolio, particular emphasis is placed on framework of a threshold normal model with a single parameter which allows us to model dependent rating migrations in consistent way. Regarding time stability of transition matrices, which is one of the major issues for credit risk estimation, next step was to present statistical tests of homogeneity and give proper illustration by an example. Afterwards, multiperiod rating transitions are discussed, relying on Markov chain theory and bootstrap methods for Markov chains. Finally, the change of the composition and riskiness of a credit portfolio caused by rating migrations is considered