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Predicting financial distress in non-financial sector of Pakistan using PCA and logit
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Predicting financial distress in non-financial sector of Pakistan using PCA and logit
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Journal Article
Predicting financial distress in non-financial sector of Pakistan using PCA and logit
2024
Overview
Purpose
This study aims to develop a robust predictive model for anticipating financial distress within Pakistani companies, providing a crucial tool for proactive economic turbulence management.
Design/methodology/approach
To achieve this objective, the study examines a comprehensive data set comprising nonfinancial firms listed on the Pakistan Stock Exchange from 2005 to 2022. It investigates 23 financial ratios categorized under profitability, liquidity, leverage, asset efficiency, size and growth.
Findings
The study reveals that financial ratio indices are more effective in forecasting financial distress compared to individual ratios. These indices achieve impressive accuracy rates, ranging from a robust 93.90% in the first year leading up to bankruptcy to a commendable 73.71% in the fifth year. Furthermore, the research identifies profitability, liquidity, leverage, asset efficiency, size and growth as pivotal indicators for financial distress prediction.
Originality/value
This research underscores the utility and practicality of financial ratio indices, offering a comprehensive perspective on risk assessment and management. In conclusion, this pioneering study provides valuable insights into financial distress prediction, highlighting the enhanced information capture made possible by financial ratio indices. It equips stakeholders in the Pakistan Stock Exchange with an effective means to proactively address financial risks.
