Threshold Moving Approach with Logit Models for Bankruptcy Prediction

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F23%3A43921248" target="_blank" >RIV/62156489:43110/23:43921248 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1007/s10614-022-10244-8" target="_blank" >https://doi.org/10.1007/s10614-022-10244-8</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s10614-022-10244-8" target="_blank" >10.1007/s10614-022-10244-8</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Threshold Moving Approach with Logit Models for Bankruptcy Prediction

Popis výsledku v původním jazyce

This article focuses on the issue of the classification capability of logistic regression models in the area of bankruptcy prediction within two manufacturing sectors. Most authors undervalue the setting of a threshold for classification and use a standard dividing point. However, the results of this article show that for data that truly reflect the market situation, this standard threshold is inappropriate, as it leads to a high classification error for bankrupt companies, which are less represented in the dataset than active (healthy) companies. In order to find a suitable threshold, two criteria derived from empirically estimated ROC curves were used in this article, which made it possible to balance the error rate within the group of active and bankrupt companies.

Název v anglickém jazyce

Threshold Moving Approach with Logit Models for Bankruptcy Prediction

Popis výsledku anglicky

This article focuses on the issue of the classification capability of logistic regression models in the area of bankruptcy prediction within two manufacturing sectors. Most authors undervalue the setting of a threshold for classification and use a standard dividing point. However, the results of this article show that for data that truly reflect the market situation, this standard threshold is inappropriate, as it leads to a high classification error for bankrupt companies, which are less represented in the dataset than active (healthy) companies. In order to find a suitable threshold, two criteria derived from empirically estimated ROC curves were used in this article, which made it possible to balance the error rate within the group of active and bankrupt companies.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Computational Economics

ISSN

0927-7099

e-ISSN

1572-9974

Svazek periodika

61

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

22

Strana od-do

1251-1272

Kód UT WoS článku

000767698700001

EID výsledku v databázi Scopus

2-s2.0-85126106529