Firm dynamics and bankruptcy processes: A new theoretical model

Abstract

This paper introduces a theoretical model that relates firm dynamics to bankruptcy processes on both univariate and multivariate bases. The distinctiveness of the study lies in the estimation of default using a framework where firm dynamics are linked to the bankruptcy process itself. The structure builds on theoretical relations among the constructs viewed from a perspective sufficiently wide to demonstrate value addition and dilution. The univariate‐based estimation results indicate that the variables determined via the model successfully differentiate distressed firms from non‐distressed and other firms, although the evidence from the multivariate analysis facilitate a 90%+ correct distressed/non‐distressed classification rate for both 1‐ and 2‐year periods. The findings provide a road map for selecting the most appropriate default prediction variables and identifying the role of each in the prediction process. The prediction accuracy of the model does not depend solely upon statistical techniques but also reflects each variable's theoretical underpinning. The model is shown to be useful for firm rating in general and credit approval decisions in particular.

Evaluation of the effectiveness of anti-crisis management of municipal unitary enterprises of the housing and communal sector in the territory of the Sverdlovsk region

“…Рассмотрим ещё одну известную четырёхфакторную модель, созданную в 1972 году, модель Лиса [23] (6). Значение указывающее на вероятность банкротства компании находится в диапазоне ниже 0.037 [24]: Z = 0,063*K1 + 0,092*K2 + 0,057*K3 + 0,001*K4, Методы прогнозирования, рассмотренные выше, находят своё применение в различных сферах и отраслях экономики.…”

“…Примечена наличием зоны неопределённости модель Р. Таффлера[23] (7), разработанная в 1977 году, эта неопределённость находится в диапазоне между 0,2 и 0,3, снижение показателя ниже этой зоны, указывает на вероятность наступления банкротства компании[25].…”

A dynamic performance evaluation of distress prediction models

“…An early warning system of corporate failure events (e.g., bankruptcy and financial distress) has such economic benefits for stakeholders (e.g., managers, investors, auditors, and regulators) that many models from the fields of probability and statistics, operational research, and artificial intelligence have been designed to predict them—for a comprehensive classification of distress prediction models, the reader is referred to Abdou and Pointon (2011), Adnan Aziz and Dar (2010), and Demyanyk and Hasan (2010). Among other corporate events, predicting financial distress of a company as the prior phase of bankruptcy has received extensive attention in recent corporate failure studies (e.g., Çelik et al, 2021; Fich & Slezak, 2008; Geng et al, 2015; Hernandez Tinoco & Wilson, 2013; Hwang et al, 2013; Laitinen & Suvas, 2016; Mousavi & Lin, 2020; Wanke et al, 2015; Zhao & Huchzermeier, 2019).…”