University of Zagreb. Faculty of Science. Department of Mathematics.
Abstract
U ovom diplomskom radu cilj je pružiti pristupačan uvod u temelje modeliranja kreditnog portfelja. Krećemo do osnovnih pojmova iz vjerojatnosti i statistike, a zatim postupno ulazimo u svijet upravljanja kreditnim rizikom kroz pojmove očekivanog i neočekivanog gubitka, gdje možemo vidjeti i bitnu ulogu korelacija, te distribucije gubitka i načina kako je dobiti. Zatim, krećemo s modeliranjem koreliranih defaulta pomoću dva pristupa. Uz teoretsku podlogu, upoznajemo i modele predstavnike tih pristupa. Također, specifikacijom uvodimo jednofaktorski (CreditMetricsTM /KMV), odnosno jednosektorski (CreditRisk+) model te nakon njihove usporedbe završavamo praktičnim primjerom.This thesis goal is to provide accessible introduction to the foundations of the credit portfolio modelling. We start from the basic concepts of probability and statistics, and then gradually enter the world of credit risk management through the terms of the expected and unexpected loss (where we first see the important role of the correlations), distribution loss and ways to get it. Then, we use two approaches to the modeling of correlated defaults and get introduced to representatives of these approaches. We also look in more detail at portfolios with uniform dependency structure, namely one-factor (CreditMetrics TM /KMV), respectively one-sector (CreditRisk+) models and after their comparison we conclude this thesis with working exampl
