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Determinants of the probability of default: the case of the internationally listed shipping corporations

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  • Agata Lozinskaia
  • Andreas Merikas
  • Anna Merika
  • Henry Penikas

Abstract

In this study, we use a sample of 192 listed shipping companies and employ a logit model in order to investigate the determinants of the probability of default. We enhance our analysis by isolating not only the cases of company liquidations but also those cases where companies had to change their legal status due to warning liquidity signals. Our key findings are in line with prior research and moreover we depict a changing trend in the marginal effects of relevant variables, on the probability of default. We further show, through an empirical application, how the obtained results can be used in a managerial decision-making process and in a bank credit underwriting process in order to assess the creditworthiness of a shipping company.

Suggested Citation

  • Agata Lozinskaia & Andreas Merikas & Anna Merika & Henry Penikas, 2017. "Determinants of the probability of default: the case of the internationally listed shipping corporations," Maritime Policy & Management, Taylor & Francis Journals, vol. 44(7), pages 837-858, October.
    • Handle: RePEc:taf:marpmg:v:44:y:2017:i:7:p:837-858
    DOI: 10.1080/03088839.2017.1345018
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    1. Kavussanos, Manolis G. & Tsouknidis, Dimitris A., 2016. "Default risk drivers in shipping bank loans," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 94(C), pages 71-94.
    2. Andreou, Panayiotis C. & Louca, Christodoulos & Panayides, Photis M., 2014. "Corporate governance, financial management decisions and firm performance: Evidence from the maritime industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 63(C), pages 59-78.
    3. Jinlan Ni & Wikil Kwak & Xiaoyan Cheng & Guan Gong, 2014. "The Determinants of Bankruptcy for Chinese Firms," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 17(02), pages 1-22.
    4. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure - Reply," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 123-127.
    5. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
    6. Johnsen, Thomajean & Melicher, Ronald W., 1994. "Predicting corporate bankruptcy and financial distress: Information value added by multinomial logit models," Journal of Economics and Business, Elsevier, vol. 46(4), pages 269-286, October.
    7. 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.
    8. Mitroussi, K. & Abouarghoub, W. & Haider, J.J. & Pettit, S.J. & Tigka, N., 2016. "Performance drivers of shipping loans: An empirical investigation," International Journal of Production Economics, Elsevier, vol. 171(P3), pages 438-452.
    9. Jianguo Chen & Ben R. Marshall & Jenny Zhang & Siva Ganesh, 2006. "Financial Distress Prediction in China," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 9(02), pages 317-336.
    10. Nico Dewaelheyns & Cynthia Van Hulle, 2006. "Corporate Failure Prediction Modeling: Distorted by Business Groups' Internal Capital Markets?," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 33(5‐6), pages 909-931, June.
    11. Hernandez Tinoco, Mario & Wilson, Nick, 2013. "Financial distress and bankruptcy prediction among listed companies using accounting, market and macroeconomic variables," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 394-419.
    12. Ran Barniv & Anurag Agarwal & Robert Leach, 2002. "Predicting Bankruptcy Resolution," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 29(3‐4), pages 497-520, April.
    13. Merika, Anna & Theodoropoulou, Sotiria & Triantafyllou, Anna & Laios, Alexandros, 2015. "The relationship between business cycles and capital structure choice: The case of the international shipping industry," The Journal of Economic Asymmetries, Elsevier, vol. 12(2), pages 92-99.
    14. Pompe, Paul P.M. & Bilderbeek, Jan, 2005. "The prediction of bankruptcy of small- and medium-sized industrial firms," Journal of Business Venturing, Elsevier, vol. 20(6), pages 847-868, November.
    15. Stephen X. Gong & Heng-Qing Ye & Yvonne Yiyi Zeng, 2013. "Impacts of the recent financial crisis on ship financing in Hong Kong: a research note," Maritime Policy & Management, Taylor & Francis Journals, vol. 40(1), pages 1-9, January.
    16. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    17. Ran Barniv & Anurag Agarwal & Robert Leach, 2002. "Predicting Bankruptcy Resolution," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 29(3&4), pages 497-520.
    18. Grammenos, C.Th. & Nomikos, N.K. & Papapostolou, N.C., 2008. "Estimating the probability of default for shipping high yield bond issues," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 44(6), pages 1123-1138, November.
    19. Alexandros M. Goulielmos & Mariniki Psifia, 2006. "Shipping finance: time to follow a new track?," Maritime Policy & Management, Taylor & Francis Journals, vol. 33(3), pages 301-320, July.
    20. Kavussanos, Manolis G. & Tsouknidis, Dimitris A., 2014. "The determinants of credit spreads changes in global shipping bonds," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 55-75.
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    Cited by:

    1. Alexandridis, George & Kavussanos, Manolis G. & Kim, Chi Y. & Tsouknidis, Dimitris A. & Visvikis, Ilias D., 2018. "A survey of shipping finance research: Setting the future research agenda," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 164-212.
    2. Anna Burova & Henry Penikas & Svetlana Popova, 2021. "Probability of Default Model to Estimate Ex Ante Credit Risk," Russian Journal of Money and Finance, Bank of Russia, vol. 80(3), pages 49-72, September.
    3. Rita Bužinskienė & Vera Gelashvili, 2024. "The Economic and Financial Health of Lithuanian Logistics Companies," Risks, MDPI, vol. 12(6), pages 1-19, June.
    4. Mark Clintworth & Dimitrios Lyridis & Evangelos Boulougouris, 2023. "Financial risk assessment in shipping: a holistic machine learning based methodology," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 25(1), pages 90-121, March.
    5. Michal Pavlicko & Jaroslav Mazanec, 2022. "Minimalistic Logit Model as an Effective Tool for Predicting the Risk of Financial Distress in the Visegrad Group," Mathematics, MDPI, vol. 10(8), pages 1-22, April.

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