Default Probability Prediction with Static Merton-D-Vine Copula Model
Václav Klepáč
Additional contact information
Václav Klepáč: Mendel University in Brno, Czech Republic
European Journal of Business Science and Technology, 2015, vol. 1, issue 2, 104-113
Abstract:
We apply standard Merton and enhanced Merton-D-Vine copula model for the measurement of credit risk on the basis of accounting and stock market data for 4 companies from Prague Stock Exchange, in the midterm horizon of 4 years. Basic Merton structural credit model is based on assumption that firm equity is European option on company assets. Consequently enhanced Merton model take in account market data, dependence between daily returns and its volatility and helps to evaluate and project the credit quality of selected companies, i.e. correlation between assets trajectories through copulas. From our and previous results it is obvious that basic Merton model significantly underestimates actual level, i.e. offers low probabilities of default. Enhanced model support us with higher simulated probability rates which mean that capturing of market risk and transferring it to credit risk estimates is probably a good way or basic step in enhancing Merton methodology.
Keywords: Merton model; default risk; d-vine copula; probability; ARMA-GARCH (search for similar items in EconPapers)
JEL-codes: C15 C53 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://ejobsat.cz/doi/10.11118/ejobsat.v1i2.30.html (text/html)
http://ejobsat.cz/doi/10.11118/ejobsat.v1i2.30.pdf (application/pdf)
free of charge
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:men:journl:v:1:y:2015:i:2:p:104-113
DOI: 10.11118/ejobsat.v1i2.30
Access Statistics for this article
European Journal of Business Science and Technology is currently edited by Svatopluk Kapounek
More articles in European Journal of Business Science and Technology from Mendel University in Brno, Faculty of Business and Economics Contact information at EDIRC.
Bibliographic data for series maintained by Ivo Andrle ().