Accuracy Analysis of Financial Distress Prediction Models for Companies on the IDX WatchlistBoard in2020-2022 Period
Dublin Core
Title
Accuracy Analysis of Financial Distress Prediction Models for Companies on the IDX WatchlistBoard in2020-2022 Period
Subject
Financial Distress, WatchlistBoard IDX, Altman, Grover,Zmijewski, Springate
Description
The research aims to examine the accuracy level of the Altman, Grover, Zmijewski, and Springatefinancial distress prediction models, to determine the most accurate financial distress prediction model in analyzing companies on the IDX WatchlistBoard criteria 5 or 8 between 2020 and 2022. Thisstudyemploysaquantitativemethodwithdescriptiveanalyticaltechniques. Data testingutilizestheKruskal-WallisOne-Way ANOVAtestduetothecomparisonofmorethantwopredictionmodelsandthenon-normaldistributionofthedata. A totalof44samples,purposivelyselectedfromthepopulationof55listedissuerswithintheDPK-BEI, wereused. TheresearchfindingsrevealnosignificantdifferencesintheaccuracyamongtheAltman,Grover,Zmijewski,andSpringatemodels.Thisisevidencedbytheaccuracyresultsbasedonthenumberofcorrectpredictionsfromeachmodel.Zmijewskiemergesasthemostaccuratemodelwitha 67%accuracyrate,followedbyAltmanandGroverat65%each,andSpringatewiththelowestaccuracyat60%.
Creator
Erdina Renaganis Anastasia1*,Fahrul Riza
Source
https://dinastipub.org/DIJEFA/article/view/2151/1471
Publisher
Bunda Mulia University
Date
07January2024
Contributor
Erdina Renaganis Anastasia
Format
PDF
Language
English
Type
Text
Files
Collection
Citation
Erdina Renaganis Anastasia1*,Fahrul Riza, “Accuracy Analysis of Financial Distress Prediction Models for Companies on the IDX WatchlistBoard in2020-2022 Period,” Repository Horizon University Indonesia, accessed March 13, 2025, https://repository.horizon.ac.id/items/show/5868.