Building a hybrid logistics model to identify hidden defaults in the financial statements of companies
Abstract
В данной работе рассмотрены подходы к построению моделей оценки кредитного риска. Целью работы является изучение количественных методов оценки кредитных рисков. В ходе исследования были обработаны и систематизированы финансовые данные компаний, проведён анализ и синтез данных, применены экономико-математические и статистические подходы. Описан процесс создания гибридной логистической модели множественного упорядоченного выбора, которая представляет собой систему из двух эконометрических моделей (линейной вероятностной модели и логит-модели). Полученные результаты как инструмент макропруденциального контроля имеют практическую значимость при проведении анализа реального сектора на микроданных.
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