Predicting financial distress: Applicability of O-score and logit model for Pakistani firms

Predicting financial distress have significant importance in corporate finance as it serves as an effective early warning system for the related stakeholders.The study applies the most admired financial distress prediction O-score model and compares its predictive accuracy with estimated logit model...

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Main Authors: Waqas, Hamid, Md Rus, Rohani
Format: Article
Language:English
Published: Prague Development Center 2018
Subjects:
Online Access:https://repo.uum.edu.my/id/eprint/24348/1/BEH%20%2014%202%202018%20%20389-401.pdf
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author Waqas, Hamid
Md Rus, Rohani
author_facet Waqas, Hamid
Md Rus, Rohani
author_sort Waqas, Hamid
collection UUM
description Predicting financial distress have significant importance in corporate finance as it serves as an effective early warning system for the related stakeholders.The study applies the most admired financial distress prediction O-score model and compares its predictive accuracy with estimated logit model. The study estimates logit model by including the profitability ratios, liquidity ratios, leverage ratios, and cash flow ratios. This study filled the gap by using the cash flow ratios to predict financial distress for Pakistani listed firms. The sample for the estimation model consists of 290 firms with 45 distressed and 245 healthy firms for the period 2006-2016 and covers all sectors of Pakistan Stock Exchange. The study provides important insights on the role of different financial ratio in predicting financial distress and shows that estimated logit model produces higher accuracy rate in predicting financial distress.
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spelling uum-243482018-07-01T02:15:30Z https://repo.uum.edu.my/id/eprint/24348/ Predicting financial distress: Applicability of O-score and logit model for Pakistani firms Waqas, Hamid Md Rus, Rohani HG Finance Predicting financial distress have significant importance in corporate finance as it serves as an effective early warning system for the related stakeholders.The study applies the most admired financial distress prediction O-score model and compares its predictive accuracy with estimated logit model. The study estimates logit model by including the profitability ratios, liquidity ratios, leverage ratios, and cash flow ratios. This study filled the gap by using the cash flow ratios to predict financial distress for Pakistani listed firms. The sample for the estimation model consists of 290 firms with 45 distressed and 245 healthy firms for the period 2006-2016 and covers all sectors of Pakistan Stock Exchange. The study provides important insights on the role of different financial ratio in predicting financial distress and shows that estimated logit model produces higher accuracy rate in predicting financial distress. Prague Development Center 2018 Article PeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/24348/1/BEH%20%2014%202%202018%20%20389-401.pdf Waqas, Hamid and Md Rus, Rohani (2018) Predicting financial distress: Applicability of O-score and logit model for Pakistani firms. Business and Economic Horizons, 14 (2). pp. 389-401. ISSN 18045006 http://doi.org/10.15208/beh.2018.28 doi:10.15208/beh.2018.28 doi:10.15208/beh.2018.28
spellingShingle HG Finance
Waqas, Hamid
Md Rus, Rohani
Predicting financial distress: Applicability of O-score and logit model for Pakistani firms
title Predicting financial distress: Applicability of O-score and logit model for Pakistani firms
title_full Predicting financial distress: Applicability of O-score and logit model for Pakistani firms
title_fullStr Predicting financial distress: Applicability of O-score and logit model for Pakistani firms
title_full_unstemmed Predicting financial distress: Applicability of O-score and logit model for Pakistani firms
title_short Predicting financial distress: Applicability of O-score and logit model for Pakistani firms
title_sort predicting financial distress applicability of o score and logit model for pakistani firms
topic HG Finance
url https://repo.uum.edu.my/id/eprint/24348/1/BEH%20%2014%202%202018%20%20389-401.pdf
work_keys_str_mv AT waqashamid predictingfinancialdistressapplicabilityofoscoreandlogitmodelforpakistanifirms
AT mdrusrohani predictingfinancialdistressapplicabilityofoscoreandlogitmodelforpakistanifirms