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

• Authors: Waqas Hamid , Md-Rus Rohani
• Languages of publication: EN

Abstracts

EN

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.

Keywords

EN

Financial distress; bankruptcy; logit regression; O-score model; financial distress; emerging market; Pakistan

Discipline

• ECONOMICS: ECONOMICS

• Publisher: Prague Development Center, Czech Republic
• Journal: Business and Economic Horizons
• Year: 2018
• Volume: Volume 14
• Issue: Issue 2
• Pages: 389-401

Dates

published

2018-02-22

Contributors

author

Waqas Hamid

• School of Economics Finance and Banking, University Utara Malaysia, Malaysia

author

Md-Rus Rohani

• School of Economics Finance and Banking, University Utara Malaysia, Malaysia

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