Do traditional financial distress prediction models predict the early warning signs of financial distress?

dc.contributor.authorAshraf, Sumaira
dc.contributor.authorFélix, Elisabete G.S.
dc.contributor.authorSerrasqueiro, Zélia
dc.date.accessioned2020-02-11T11:05:36Z
dc.date.available2020-02-11T11:05:36Z
dc.date.issued2019
dc.description.abstractPurpose: This study aims to compare the prediction accuracy of traditional distress prediction models for the firms which are at an early and advanced stage of distress in an emerging market, Pakistan, during 2001–2015. Design/methodology/approach: The methodology involves constructing model scores for financially distressed and stable firms and then comparing the prediction accuracy of the models with the original position. In addition to the testing for the whole sample period, comparison of the accuracy of the distress prediction models before, during, and after the financial crisis was also done. Findings: The results indicate that the three-variable probit model has the highest overall prediction accuracy for our sample, while the Z-score model more accurately predicts insolvency for both types of firms, i.e., those that are at an early stage as well as those that are at an advanced stage of financial distress. Furthermore, the study concludes that the predictive ability of all the traditional financial distress prediction models declines during the period of the financial crisis. Originality/value: An important contribution is the widening of the definition of financially distressed firms to consider the early warning signs related to failure in dividend/bonus declaration, quotation of face value, annual general meeting, and listing fee. Further, the results suggest that there is a need to develop a model by identifying variables which will have a higher impact on the financial distress of firms operating in both developed and developing markets.por
dc.description.sponsorshipThis paper is financed by National Funds of the FCT–Portuguese Foundation for Science and Technology within the project “UID/ECO/04007/2019”.por
dc.identifier.authoremailexecutive.sumaira@gmail.com
dc.identifier.authoremailefelix@uevora.pt
dc.identifier.authoremailzelia@ubi.pt
dc.identifier.citationAshraf, S., Félix, E.G.S. and Serrasqueiro, Z., 2019. Do traditional financial distress prediction models predict the early warning signs of financial distress? Journal of Risk and Financial Management, 12(2), 1-17.por
dc.identifier.doihttps://doi.org/10.3390/jrfm12020055por
dc.identifier.scientificarea256por
dc.identifier.urihttps://doi.org/10.3390/jrfm12020055
dc.identifier.urihttp://hdl.handle.net/10174/26891
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherJournal of Risk and Financial Managementpor
dc.rightsopenAccesspor
dc.subjectfinancial distresspor
dc.subjectemerging marketpor
dc.subjectprediction modelspor
dc.subjectZ-scorepor
dc.subjectlogit analysispor
dc.subjectprobit modelpor
dc.titleDo traditional financial distress prediction models predict the early warning signs of financial distress?por
dc.typearticlepor

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Página inicial.pdf
Size:
204.64 KB
Format:
Adobe Portable Document Format

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
3.89 KB
Format:
Item-specific license agreed upon to submission
Description: