IDEAS home Printed from https://ideas.repec.org/a/spr/jglont/v9y2019i1d10.1186_s40497-019-0152-8.html
   My bibliography  Save this article

Estimating probabilities of default of different firms and the statistical tests

Author

Listed:
  • Amir Ahmad Dar

    (B S Abdur Rahman Crescent Institute of Science and Technology)

  • N. Anuradha

    (B S Abdur Rahman Crescent Institute of Science and Technology)

  • Shahid Qadir

    (Desh Bhagat University)

Abstract

The probability of default (PD) is the essential credit risks in the finance world. It provides an estimate of the likelihood that a borrower will be unable to meet its debt obligations. Purpose This paper computes the probability of default (PD) of utilizing market-based data which outlines their convenience for monetary reconnaissance. There are numerous models that provide assistance to analyze credit risks, for example, the probability of default, migration risk, and loss gain default. Every one of these models is vital for estimating credit risk, however, the most imperative model is PD, i.e., employed in this paper. Design/methodology/approach In this paper, the Black-Scholes Model for European Call Option (BSM-CO) is utilized to gauge the PD of the Jammu and Kashmir Bank, Bank of Baroda, Indian Overseas Bank, and Canara Bank. The information has been taken from a term of 5 years on a yearly premise from 2012 to 2016. This paper demonstrates how d2 in Black Scholes displayed help in assessing the PD of the various firms. Findings The fundamental findings of this paper are whether there are any mean contrasts between the mean differences of PD between the organizations utilizing ANOVA and the Tukey strategy.

Suggested Citation

  • Amir Ahmad Dar & N. Anuradha & Shahid Qadir, 2019. "Estimating probabilities of default of different firms and the statistical tests," Journal of Global Entrepreneurship Research, Springer;UNESCO Chair in Entrepreneurship, vol. 9(1), pages 1-15, December.
    • Handle: RePEc:spr:jglont:v:9:y:2019:i:1:d:10.1186_s40497-019-0152-8
    DOI: 10.1186/s40497-019-0152-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1186/s40497-019-0152-8
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1186/s40497-019-0152-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Ke Wang & Darrell Duffie, 2004. "Multi-Period Corporate Failure Prediction With Stochastic Covariates," Econometric Society 2004 Far Eastern Meetings 747, Econometric Society.
    2. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-470, May.
    3. M. Tudela & G. Young, 2005. "A Merton-Model Approach To Assessing The Default Risk Of Uk Public Companies," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 8(06), pages 737-761.
    4. Arindam Bandyopadhyay, 2006. "Predicting probability of default of Indian corporate bonds: logistic and Z-score model approaches," Journal of Risk Finance, Emerald Group Publishing, vol. 7(3), pages 255-272, May.
    5. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    6. Sreedhar T. Bharath & Tyler Shumway, 2008. "Forecasting Default with the Merton Distance to Default Model," The Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1339-1369, May.
    7. Jessen, Cathrine & Lando, David, 2015. "Robustness of distance-to-default," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 493-505.
    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. Amir Ahmad Dar & Shahid Qadir, 2019. "Distance to default and probability of default: an experimental study," Journal of Global Entrepreneurship Research, Springer;UNESCO Chair in Entrepreneurship, vol. 9(1), pages 1-12, December.
    2. Nora Gavira-Durón & Octavio Gutierrez-Vargas & Salvador Cruz-Aké, 2021. "Markov Chain K-Means Cluster Models and Their Use for Companies’ Credit Quality and Default Probability Estimation," Mathematics, MDPI, vol. 9(8), pages 1-14, April.

    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. Bhagat, Sanjai & Bolton, Brian & Lu, Jun, 2015. "Size, leverage, and risk-taking of financial institutions," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 520-537.
    2. Afik, Zvika & Arad, Ohad & Galil, Koresh, 2016. "Using Merton model for default prediction: An empirical assessment of selected alternatives," Journal of Empirical Finance, Elsevier, vol. 35(C), pages 43-67.
    3. Jackson, Richard H.G. & Wood, Anthony, 2013. "The performance of insolvency prediction and credit risk models in the UK: A comparative study," The British Accounting Review, Elsevier, vol. 45(3), pages 183-202.
    4. Mohammad Mahdi Mousavi & Jamal Ouenniche & Kaoru Tone, 2023. "A dynamic performance evaluation of distress prediction models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 756-784, July.
    5. Han-Hsing Lee & Kuanyu Shih & Kehluh Wang, 2016. "Measuring sovereign credit risk using a structural model approach," Review of Quantitative Finance and Accounting, Springer, vol. 47(4), pages 1097-1128, November.
    6. Marta Gómez-Puig & Simón Sosvilla-Rivero & Manish K. Singh, 2018. "“Incorporating creditors' seniority into contingent claim models:Application to peripheral euro area countries”," IREA Working Papers 201803, University of Barcelona, Research Institute of Applied Economics, revised Feb 2018.
    7. Singh, Manish K. & Gómez-Puig, Marta & Sosvilla-Rivero, Simón, 2015. "Bank risk behavior and connectedness in EMU countries," Journal of International Money and Finance, Elsevier, vol. 57(C), pages 161-184.
    8. Lanlan Liu & Dan Luo & Liang Han, 2019. "Default risk, state ownership and the cross-section of stock returns: evidence from China," Review of Quantitative Finance and Accounting, Springer, vol. 53(4), pages 933-966, November.
    9. Felipe Zurita L., 2008. "Bankruptcy Prediction for Chilean Companies," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 11(1), pages 93-116, April.
    10. Andrikopoulos, Panagiotis & Khorasgani, Amir, 2018. "Predicting unlisted SMEs' default: Incorporating market information on accounting-based models for improved accuracy," The British Accounting Review, Elsevier, vol. 50(5), pages 559-573.
    11. Wang, Peiwen & Chen, Minghua & Wu, Ji & Yan, Yuanyun, 2023. "Do peer effects matter in bank risk? Some cross-country evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
    12. Ahsan Habib & Mabel D' Costa & Hedy Jiaying Huang & Md. Borhan Uddin Bhuiyan & Li Sun, 2020. "Determinants and consequences of financial distress: review of the empirical literature," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(S1), pages 1023-1075, April.
    13. 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.
    14. Sigrist, Fabio & Leuenberger, Nicola, 2023. "Machine learning for corporate default risk: Multi-period prediction, frailty correlation, loan portfolios, and tail probabilities," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1390-1406.
    15. Maclachlan, Iain C, 2007. "An empirical study of corporate bond pricing with unobserved capital structure dynamics," MPRA Paper 28416, University Library of Munich, Germany.
    16. Carlson Mark A & King Thomas & Lewis Kurt, 2011. "Distress in the Financial Sector and Economic Activity," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 11(1), pages 1-31, June.
    17. Chengru Hu & Wei Jiang, 2019. "Managerial risk incentives and accounting conservatism," Review of Quantitative Finance and Accounting, Springer, vol. 52(3), pages 781-813, April.
    18. Charitou, Andreas & Dionysiou, Dionysia & Lambertides, Neophytos & Trigeorgis, Lenos, 2013. "Alternative bankruptcy prediction models using option-pricing theory," Journal of Banking & Finance, Elsevier, vol. 37(7), pages 2329-2341.
    19. Duc Hong Vo & Binh Ninh Vo Pham & Chi Minh Ho & Michael McAleer, 2019. "Corporate Financial Distress of Industry Level Listings in Vietnam," JRFM, MDPI, vol. 12(4), pages 1-17, September.
    20. Sim, Jaehun & Kim, Chae-Soo, 2019. "The value of renewable energy research and development investments with default consideration," Renewable Energy, Elsevier, vol. 143(C), pages 530-539.

    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:spr:jglont:v:9:y:2019:i:1:d:10.1186_s40497-019-0152-8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.