Comparative Analysis of Corporate Distress Prediction Models: A Dynamic Performance Evaluation Framework

Mohammad Mahdi Mousavi () and Jamal Ouenniche ()
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Mohammad Mahdi Mousavi: The University of Edinburgh Business School
Jamal Ouenniche: The University of Edinburgh Business School

No 4006251, Proceedings of International Academic Conferences from International Institute of Social and Economic Sciences

Abstract: In practice, investors, portfolio managers, and regulators continuously assess and monitor the performance of corporations. Such assessment and monitoring exercise is typically performed using a variety of tools including prediction models of distress. With the enormous number of prediction models, a strand of literature has focused on comparing the performance of alternative distress prediction models. In this research, we explore dynamic modelling and prediction frameworks of corporate distress and propose new ones. A dynamic evaluation framework is also proposed to assess the relative performance of these dynamic models in predicting corporate distress using a sample of UK firms listed on the London Stock Exchange (LSE).

Keywords: Distress Prediction Models; Dynamic Framework (search for similar items in EconPapers)
JEL-codes: G19 G33 (search for similar items in EconPapers)
Pages: 1 page
Date: 2016-08
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Published in Proceedings of the Proceedings of the 24th International Academic Conference, Barcelona, Aug 2016, pages 257-257

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Persistent link: https://EconPapers.repec.org/RePEc:sek:iacpro:4006251

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