IDEAS home Printed from https://ideas.repec.org/a/ora/journl/v1y2017i1p385-393.html
   My bibliography  Save this article

Estimation Of The Probability Of Default Based On Relevant Economic And Financial Indicators

Author

Listed:
  • Luminita Gabriela Istrate

    (Academia de Studii Economice din Bucuresti Facultatea de Contabilitate si Informatica de Gestiune)

  • Bogdan Stefan Ionescu

Abstract

The credit risk is one of the main banking activity risks, with direct impact on the bank performance. Approaches based on internal rating models introduced by the Basel II agreement allow banks to use their own estimates for credit risk quantification, with direct effect on capital adequacy. This study aims to develop a scoring model for quantifying the probability of default dependent on the non-performing loans rate evolution based on quantitative information and determination of the power of prediction to determine non-reimbursement situations. Also, it was considered the determination of some qualitative variables impacting on the reimbursement capacity of companies. The financing sources, in essence, in-house or attracted, condition the profitability of any business and influence the financial position of the company, both in the short and long term. This study aims at an understanding of the inter-conditioning relationship between the financing sources, profitability and default risk. The estimation of the default probability is the first step to determining and assessing the credit risk. Major issues in the estimation of the default probability are generated by the limitation of the required information. The approach based on internal rating models relies on the accuracy of the default probability estimation.

Suggested Citation

  • Luminita Gabriela Istrate & Bogdan Stefan Ionescu, 2017. "Estimation Of The Probability Of Default Based On Relevant Economic And Financial Indicators," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 385-393, July.
  • Handle: RePEc:ora:journl:v:1:y:2017:i:1:p:385-393
    as

    Download full text from publisher

    File URL: http://anale.steconomiceuoradea.ro/volume/2017/n1/37.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Castro, Vítor, 2013. "Macroeconomic determinants of the credit risk in the banking system: The case of the GIPSI," Economic Modelling, Elsevier, vol. 31(C), pages 672-683.
    2. Edward I. Altman & Brooks Brady & Andrea Resti & Andrea Sironi, 2005. "The Link between Default and Recovery Rates: Theory, Empirical Evidence, and Implications," The Journal of Business, University of Chicago Press, vol. 78(6), pages 2203-2228, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bogdan POPA & Jenica POPESCU, 2023. "New Approaches to Financial and Bankruptcy Risk," Finante - provocarile viitorului (Finance - Challenges of the Future), University of Craiova, Faculty of Economics and Business Administration, vol. 1(25), pages 8-13, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Katuka, Blessing, 2017. "Credit risk dynamics in listed local banks in Zimbabwe (2009-2013)," MPRA Paper 92687, University Library of Munich, Germany, revised 2017.
    2. Wang, Hong & Forbes, Catherine S. & Fenech, Jean-Pierre & Vaz, John, 2020. "The determinants of bank loan recovery rates in good times and bad – New evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 177(C), pages 875-897.
    3. Trueck, Stefan & Rachev, Svetlozar T., 2008. "Rating Based Modeling of Credit Risk," Elsevier Monographs, Elsevier, edition 1, number 9780123736833.
    4. Andrea Cipollini & Giuseppe Missaglia, 2008. "Measuring bank capital requirements through Dynamic Factor analysis," Center for Economic Research (RECent) 010, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    5. Bank for International Settlements, 2005. "The role of ratings in structured finance: issues and implications," CGFS Papers, Bank for International Settlements, number 23, december.
    6. Santiago Forte & Lidija Lovreta, 2015. "Time†Varying Credit Risk Discovery in the Stock and CDS Markets: Evidence from Quiet and Crisis Times," European Financial Management, European Financial Management Association, vol. 21(3), pages 430-461, June.
    7. Muhammad Waqas & Nudrat Fatima & Aryan Khan & Muhammad Arif, 2017. "Determinants of Non-performing Loans: A Comparative Study of Pakistan, India, and Bangladesh," International Journal of Finance & Banking Studies, Center for the Strategic Studies in Business and Finance, vol. 6(1), pages 51-68, January.
    8. Meng-Jou Lu & Cathy Yi-Hsuan Chen & Wolfgang Karl Härdle, 2017. "Copula-based factor model for credit risk analysis," Review of Quantitative Finance and Accounting, Springer, vol. 49(4), pages 949-971, November.
    9. Helmut Elsinger & Alfred Lehar & Martin Summer, 2006. "Risk Assessment for Banking Systems," Management Science, INFORMS, vol. 52(9), pages 1301-1314, September.
    10. repec:onb:oenbwp:y::i:152:b:1 is not listed on IDEAS
    11. Fathi, Abid & Nader, Naifar, 2007. "Price Calibration of basket default swap: Evidence from Japanese market," MPRA Paper 6013, University Library of Munich, Germany.
    12. Hwang, Ruey-Ching & Chu, Chih-Kang & Yu, Kaizhi, 2020. "Predicting LGD distributions with mixed continuous and discrete ordinal outcomes," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1003-1022.
    13. Rösch, Daniel & Scheule, Harald, 2009. "The Empirical Relation between Credit Quality, Recovery and Correlation," Hannover Economic Papers (HEP) dp-418, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    14. Tomas Konecny & Jakub Seidler & Aelta Belyaeva & Konstantin Belyaev, 2017. "The Time Dimension of the Links Between Loss Given Default and the Macroeconomy," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 67(6), pages 462-491, October.
    15. Martin Guth, 2022. "Predicting Default Probabilities for Stress Tests: A Comparison of Models," Papers 2202.03110, arXiv.org.
    16. Isma il Tijjani Idris & Sabri Nayan, 2017. "A Pooled Mean Group Approach to the Joint Effects of Oil Price Changes and Environmental Risks on Non-Performing Loans: Evidence from Organisation of the Petroleum Exporting the Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 7(3), pages 345-351.
    17. Jochen Güntner & Benjamin Karner, 2023. "The bond agio premium," Economics working papers 2023-13, Department of Economics, Johannes Kepler University Linz, Austria.
    18. Ismail Tijjani Idris & Sabri Nayan, 2016. "The Moderating Role of Loan Monitoring on the Relationship between Macroeconomic Variables and Non-performing Loans in Association of Southeast Asian Nations Countries," International Journal of Economics and Financial Issues, Econjournals, vol. 6(2), pages 402-408.
    19. Alain Monfort & Fulvio Pegoraro & Jean-Paul Renne & Guillaume Roussellet, 2021. "Affine Modeling of Credit Risk, Pricing of Credit Events, and Contagion," Management Science, INFORMS, vol. 67(6), pages 3674-3693, June.
    20. Giesecke, Kay & Longstaff, Francis A. & Schaefer, Stephen & Strebulaev, Ilya, 2011. "Corporate bond default risk: A 150-year perspective," Journal of Financial Economics, Elsevier, vol. 102(2), pages 233-250.
    21. Maalaoui Chun, Olfa & Dionne, Georges & François, Pascal, 2014. "Credit spread changes within switching regimes," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 41-55.

    More about this item

    Keywords

    probability of default; financial performance; credit risk; qualitative variables; macroeconomic environment; credit scoring;
    All these keywords.

    JEL classification:

    • J08 - Labor and Demographic Economics - - General - - - Labor Economics Policies

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ora:journl:v:1:y:2017:i:1:p:385-393. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catalin ZMOLE (email available below). General contact details of provider: https://edirc.repec.org/data/feoraro.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.