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Assessment of a failure prediction model in the energy sector: a multicriteria discrimination approach with Promethee based classification

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  • Silvia Angilella
  • Maria Rosaria Pappalardo

Abstract

This study presents the implementation of a non-parametric multiple criteria decision aiding (MCDA) model, the Multi-group Hierarchy Discrimination (M.H.DIS) model, with the Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE), on a dataset of 114 European unlisted companies operating in the energy sector. Firstly, the M.H.DIS model has been developed following a five-fold cross validation procedure to analyze whether the model explains and replicates a two-group pre-defined classification of companies in the considered sample, provided by Bureau van Dijk's Amadeus database. Since the M.H.DIS method achieves a quite limited satisfactory accuracy in predicting the considered Amadeus classification in the holdout sample, the PROMETHEE method has been performed then to provide a benchmark sorting procedure useful for comparison purposes.

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  • Silvia Angilella & Maria Rosaria Pappalardo, 2021. "Assessment of a failure prediction model in the energy sector: a multicriteria discrimination approach with Promethee based classification," Papers 2102.07656, arXiv.org.
    • Handle: RePEc:arx:papers:2102.07656
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    3. Bompard, E.F. & Corgnati, S.P. & Grosso, D. & Huang, T. & Mietti, G. & Profumo, F., 2022. "Multidimensional assessment of the energy sustainability and carbon pricing impacts along the Belt and Road Initiative," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).

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