Paper Details
Title Predicting Financial Bankruptcy of Five Manufacturing Sectors in Pakistan Using Logistic Regression
AuthorsEHSAN UL HASSAN, ZAEMAH BT. ZAINUDDIN and SABARIAH BT. NORDIN
Abstract

Financial distress is a debatable issue among the researchers especially in developing economies. This study investigates the significant financial indicators for five manufacturing sectors listed on Pakistan Stock Exchange (PSX). Sample consists of 35 bankrupt and 156 non-bankrupt companies from textile, cement, sugar, technology and communication and power generation and distribution sectors. Study uses two data sets from 2005 to 2013 for estimation sample and 2014 to 2016 for holdout sample. Logistic regression analysis comprises of sixteen financial ratios under respective indicators i.e. profitability, liquidity, leverage, asset efficiency and size. Findings of the study reveal six significant financial ratios for each indicator i.e. return on equity (ROE), quick ratio, current ratio, shareholder’s equity to total assets, sales to current assets and natural log of total assets. Results show overall model accuracy of 89.6 percent for estimation sample while 92.2 percent for holdout sample which indicates model consistency with better financial distress prediction power in the context of Pakistan. Keywords: Financial Distress Prediction, Pakistan Stock Exchange, Bankruptcy, Financial Soundness, Logistic Regression.

Pages 268-277
Volume 7
Issue 1
Part 3
File Name Download (1082)
DOI/AUN 10.30543/7-1(2018)-25

Facebook