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Predicting corporate failure for listed shipping companies

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Maritime Economics & Logistics Aims and scope

Abstract

The shipping industry has unique financial characteristics: it is capital intensive, faces highly volatile freight rates and ship prices, and exhibits strong cyclicality and seasonality. It is a sector which has a unique corporate structure, as it is normally highly geared and relies extensively on debt financing. Shipping is also a conservative sector favouring traditional finance and tapping the global capital market much later than other industries. In this sense, the shipping industry deserves its own enquiry into its financial characteristics. This paper considers listed shipping companies worldwide in terms of their overall financial performance. While default against individual financial instruments can represent early phases of corporate failure, predicting overall failure at the firm level is worth investigating. This paper studies corporate failure and financial performance in globally listed shipping firms, examining the different characteristics of financial risks, and investigating how these characteristics vary over time. A new technique, the receiver-operating characteristic curve, is introduced to compare the overall accuracies of various models for predicting binary outcomes. The findings in respect of shipping finance for listed shipping companies can benefit both shipowners and investors.

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Notes

  1. See Charitou et al. (2004) and Grammenos et al. (2008) for examples.

  2. Indeed, when these factors are included in the same regression, with different possible combinations of measurement, it is found that none of the financial ratios—except for TD/TA—is significant.

  3. The ‘6-month before’ version includes ‘ship’ as an intercept dummy.

  4. This is mainly because the total correction rate does not discriminate between type I and type II errors, so the relationship between the total correction rate and the trade-off between type I and type II errors is quite independent over different cases.

  5. See Zweig and Campbell (1993) for a thorough illustration of the method.

  6. Recall that this optimal version predicted 76.5% of the true failed cases and 76.5% of the true survived cases according to its confusion matrix—see Table 4.

  7. The draws are conducted with the bootstrap technique.

  8. Thus, the Pareto ‘80-20 principle’ is followed when segmenting the sample.

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Acknowledgements

The authors would like to extend their gratitude to the journal’s reviewers for their in-depth comments, guidance and useful advice.

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Authors and Affiliations

  1. Cardiff Business School, Cardiff University, Colum Road, Cardiff, CF10 3EU, UK

    Jane Haider, Zhirong Ou & Stephen Pettit

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  1. Jane Haider
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  2. Zhirong Ou
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Correspondence to Stephen Pettit.

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Haider, J., Ou, Z. & Pettit, S. Predicting corporate failure for listed shipping companies. Marit Econ Logist 21, 415–438 (2019). https://doi.org/10.1057/s41278-018-0101-4

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