Bankruptcy prediction of firms listed at the Nairobi Securities Exchange
Businesses are enterprises which produce goods or render services for profit motive. To be able to predict the financial soundness of a business has led to many research works. Financial ratios are a key indicator of financial soundness of a business. Financial ratios are a tool to determine the operational & financial efficiency of business undertakings. There exist a large number of ratios propounded by various authors. Altman developed a z-score model using ratios as its foundation. With the help of the Z- Score model, Altman could predict financial efficiency/bankruptcy up to 2-3 years in advance. The paper assesses the utility of statistical technique mostly termed as multiple discriminant analysis (MDA) in bankruptcy prediction of firms listed in Nairobi Stock Exchange in Kenya during the period of 2008 to 2012 and also delisted firms from NSE from the period of 1996 to 2012. The Capital Market Authority (CMA) has a regulatory responsibility to keep surveillance of firms listed in Nairobi Stock Exchange (NSE) with regards to capital, liquidity and other aspects with overall aim of ensuring financial stability of these firms. The expectation is therefore that the firms will be financially prudent and healthy which in turn will attract investors. There is therefore a need to critically assess the financial position of the listed firms and suggest ways of improving the performance of NSE. This study utilizes Altman’s (1993) Z”-score multi discriminant financial analysis model which provides the framework for gauging the financial performance of the firms. This is in addition to the use of the Statistical Package for Social Sciences software in support of the evidences from the Z-score model. The sample constituted selected firms listed in Nairobi Stock Exchange divided into five different sectors. The results of failed firms clearly stated that the model was intended for non-manufacturing firms since most of the failed firms that were classified in distress zone have scores of safe zone or grey zone. This is an indication that the model is not sufficient. Thus the study recommended that the NSE should make financial stability an integral driver of its policy framework.