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Assessment of the probability of bankruptcy of companies using discriminant analysis and neural networks

Authors: Tymoshchuk, Oksana L.; Dorundiak, Kseniia M.;

Assessment of the probability of bankruptcy of companies using discriminant analysis and neural networks

Abstract

The models of discriminant analysis and artificial neural networks for forecasting and calculating the probability of bankruptcy of companies are investigated. The definition and essence of the term "bankruptcy", the main causes of the financial crisis of Ukrainian companies and statistical data reflecting the dynamics of bankruptcies of Ukrainian companies in recent years are analyzed. A model of an artificial neural network of the perceptron type was developed and a comparative analysis with models of Ukrainian economists was made using examples of financial analysis of several well-known Ukrainian companies. The advantages and problems of application of the considered models, as well as their practical importance in the current economic conditions, are analyzed.

Исследованы модели дискриминантного анализа и искусственных нейронных сетей для прогнозирования и вычисления вероятности банкротства предприятий. Проанализированы определение и сущность термина "банкротство", основные причины кризисного финансового состояния предприятий Украины и статистические данные, отражающие динамику банкротств украинских предприятий за 1999–2017 гг. Разработана модель искусственной нейронной сети типа персептрон и проведен компаративный анализ с моделями отечественных экономистов на примере анализа финансового состояния нескольких известных украинских предприятий. Оценены достоинства и проблемы применения рассмотренных моделей, а также их практическая значимость в современных условиях хозяйствования.

Досліджено моделі дискримінантного аналізу та штучних нейронних мереж для прогнозування й обчислення ймовірності банкрутства підприємств. Проаналізовано визначення та сутність терміна "банкрутство", основні причини кризового фінансового стану підприємств України та статистичні дані, які відображають динаміку банкрутств українських підприємств протягом 1999–2017 рр. Розроблено модель штучної нейронної мережі типу перцептрон та проведено компаративний аналіз з моделями вітчизняних економістів на прикладі аналізу фінансового стану декількох відомих українських підприємств. Оцінено переваги та проблеми застосування розглянутих моделей, а також їх практичну значущість у сучасних умовах господарювання.

Related Organizations
Keywords

industrial company; forecasting; probability of bankruptcy; discriminant analysis; neural network, предприятие; прогнозирование; вероятность банкротства; дискриманантний анализ; нейронная сеть, підприємство; прогнозування; ймовірність банкрутства; дискріманантний аналіз; нейронна мережа

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Top 10%
Average
gold