The Application of Altman s Z-Score Model in Determining the Financial Soundness of Healthcare Companies Listed in Kuwait Stock Exchange

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1 Available online at SCIENTIFIC RESEARCH GATE International Journal of Economic Papers, April 2018; 3 (1): 1 5 International Journal of Economic Papers The Application of Altman s Z-Score Model in Determining the Financial Soundness of Healthcare Companies Listed in Kuwait Stock Exchange Abstract Musaed S. AlAli 1 * 1. Assistant Professor, College of Business Studies, Department of Insurance and Banking, The Public Authority for Applied Education and Training (PAAET), Kuwait. Background: This study aims to examine the financial soundness of the companies listed in the healthcare sector in Kuwait stock exchange. Methods and Material: One of the risks investors face when investing in any company is the risk of bankruptcy, with leman brothers setting the best example for that matter. It has been well documented that such collapse does not come all of a sudden, but there are some signs that would indicate such scenario. One of the most used models for predicting financial distress for any company is Altman s Z-score model. Results and conclusion: This paper examines the financial distress risk for the healthcare companies listed in Kuwait stock exchange and examines their financial soundness against any bankruptcy threat. Key words: Altman, Z-score, Healthcare, Kuwait stock exhchange, Financial distress. Citation to This Article: AlAli M.S. The Application of Altman s Z-Score Model in Determining the Financial Soundness of Healthcare Companies Listed in Kuwait Stock Exchange. International Journal of Economic Papers, April 2018; 3 (1): Introduction While the healthcare sector in Kuwait stock market is not considered to be the largest sector in the market, it is a very vital sector for the economy since the companies listed in that sector are considered the main medical drugs and medical equipment s provider for both public and private hospitals and clinics in Kuwait. Forecasting any shortfalls in the company s financial situation would be very useful for both the customers of these companies since any fall will affect their supplies and for investors in these companies since they would lose their investments as a result of the financial difficulties the company might face. Elloumi and Gueyie [1] defined a company under a financial distress when having negative net income for two consecutive years. Ward et al. [2] defined a company under financial distress when having interest coverage ratio of less than one. While others like Almilia [3] stated that a company experiencing financial distress is when a company suffers from negative net operating income and is not paying dividends for one consecutive year. Altman [4] used financial ratios in his bankruptcy prediction model to produce an early warning system for the companies. VenkataRamana, et al. [5] used Altman Z-score model to examine the financial performance and predict the risk of bankruptcy for the Indian cement companies for the period They found that KCP Ltd and Kilogram Industries Ltd. experiencing poor financial performance or financial distress. Yet, Dalmia Bharat Ltd. is on the threshold of bankruptcy. This suggests the use of a model Altman bankruptcy for research is still applicable. As for most of the financial distress prediction models, Azhar and Ramesh [6] used Altman s Z-score and showed that the majority of companies in India do not have good financial health, thus they point out that there is an urgent need for their administration to examine and reduce the financial * Corresponding author: Musaed S. AlAli Address: ms.alali@paaet.edu.kw

2 difficulty of their companies. Maina and Sakwa [7] used Altman s z-model to examine the financial soundness of companies in Kenya and they were able to distinguish between companies with good financial position and companies that were in the danger zone. Altman [4] used the Multiple Discriminate Analysis (MDA). The discriminant analysis is a statistical technique that identifies some financial ratios that are considered the most important in influencing the value of an event, and then it develops it into a model with a view of making it easier to draw conclusions from an event. Subramanyam and Wild [8] concluded that financial analysis is a very useful tool that significantly assists business decision making. 2. Methodology Altman s Z-score model is constructed based on financial ratios, Husein and Pambekti [9] concluded that financial ratios founded in the company s financial statement are an efficient way to analyze the soundness of the company and can be used to anticipate future financial difficulties. Altman s Z-score is a linear combination of four or five financial ratios, weighted by coefficients. The coefficients were estimated by identifying a set of firms which had declared bankruptcy and then collecting a matched sample of firms which had survived, with matching by industry and approximate size (assets). While there are many Altman Z-score models for different types of companies, for example the 5 factor model is used for manufacturing companies and there is a model that is designed for banks, this paper uses Altman 4 factor model to measure the financial stress of the companies. This formula is used for the non-manufacturing and emerging companies (Altman, 4). The formula used is as follow; Z = 6.56 X X X X4 (Equation 1) Where; X1 = working capital (current assets (CA) current liabilities (CL)) / total assets (TA) X2 = retained earnings (RE) / total assets (TA) X3 = earnings before interest and tax (EBIT) / total assets (TA) X4 = total book equity (TE) / total liabilities (TL) The results obtained from the model is then compared to a benchmark that is set to determine the financial soundness of the company. The criteria used to interpret the Z-score model is; - Safe Zone if Z-score > 2.99 (risk free) - Gray Zone if 1.81 < Z-score < 2.99 (at risk) - Distress Zone if Z-score < 1.81 (bankruptcy) 3. Date and empirical results This paper is based on data collected from the annual reports of the Healthcare companies for the period spanning from 2013 to The annual reports were obtained from the Kuwait stock market website. When looking at the financial ratios for Yiaco as seen in table [1], it can be seen that the net working capital to total assets ratio has been improving during the study period. On the other hand, the retained earnings to total assets ratio went down from in 2013 to in 2016 due to the huge losses the company had in These 2015 losses can clearly be seen in EBIT to total assets ratio, where the company had a positive ratio in all years except in 2015, the ratio also shows a downward trend implying that the company is not generating profits as in previous years. The equity market value to total liabilities had the lowest number in 2015 due to the bad results the company had, but that ratio went up due to the increase in the company s share price from 142 fils (1 KWD = 1000 fils) in 2015 to 360 fils in Page 2

3 Table 1. Yiaco Financial Ratios Results X X X X When it comes to the ratios of the advanced technology company, it can be seen from table [2] that the company had a stable net working capital to total assets. The company had the highest ratio in the year 2015 but that ratio went down in 2016 due to the increase in the company s total assets. By looking at the retained earnings to total assets ratio, it can be seen that the ratio is showing a downtrend during the study period which gives a conclusion that the growth in total assets exceeded the growth of the retained earnings during this period. The company also showed its total assets size is growing faster than their EBIT s which suggests that the company is not utilizing its assets as it used to do in the past. The company s market capitalization to total liabilities ratio showed a downward trend during period under study despite having somewhat the same price for the period, which suggests that the company s total liabilities are increasing more than the increase in the stock price. Table 2. Advanced Technology Financial Ratios Results X X X X When calculating the z-score for the companies as seen in table [3], it can be seen that advanced technology company outperformed Yiaco in the first three years of the study but by the year 2016 they showed a very close results. Advanced Technology Company showed a z-score way above the threshold of 2.99 for the years 2013, 2014, and 2015, but that score went down below 2.99 in Even though advanced technology company had a z-score of above 2.99 for the first three years, there was a downward trend in their score. The reason behind this downtrend was the constant reduction in the market capitalization of the company to its total liabilities ratio. Table 3. Altman s Z-Score Healthcare Companies Listed in KSE Market Yiaco Advanced Technology Gray Gray Gray Free Gray Free Gray Free 2.99< =Free, 2.99> Gray>1.18, 1.18>High bankruptcy risk Yiaco s z-score has been in the gray area for the whole study period, with the year 2015 being their worst year due to the huge losses the encountered. Yiaco had the best z-score in the year 2016 thanks to the increase of net working capital to total assets ratio and market capitalization to total liabilities ratio. The increase in the company s share price had a big impact on the company s z-score. On the other hand, advanced technology while being in the safe zone for the first three years they slipped to the gray area in As to their position at the end of 2016, both companies are not in the bankruptcy risk free zone but it can be noted from figure (1) that Yiaco is showing an uptrend in their z-score but advanced technology is showing a downward trend. Page 3

4 Figure 1. Altman s Z-Score 4. Conclusion This study examined the financial soundness of the healthcare companies listed in the Kuwait stock exchange. These companies play a crucial role in the healthcare industry in the State of Kuwait. Having a healthy financial position would provide a peace of mind for both their shareholders and their customers. The results obtained from this study, showed that both companies are positioned in the gray area which means that they are facing bankruptcy risk. The outcomes from this study shows that Yiaco Company should pay more attention to their earning since their assets are growing at a faster rate than their profits. On the other hand Advanced Technology Company should pay more attention to the growth of their liabilities since the growth in their liabilities is exceeding the growth in their equity market value. References 1- Elloumi, Fathi and Gueyié, Jean Pierre. (2001) "Financial distress and corporate governance: an empirical analysis", Corporate Governance: The international journal of business in society, Vol. 1 Issue: 1, pp.15-23, 2- Ward, T. J., B. Foster and J. Woodroof (2006), Estimated Operating Cash Flow, Reported Cash Flow from Operating Activities, and Financial Distress, Advances in Quantitative Analysis of Finance and Accounting, Vol. 4, pp Almilia, L.S Prediction of Corporate Financial Distress by Multinominal Logit Analysis. Economic Institute of Perbanas, Surabaya. Indonesia. 4- Altman, E. (1968) Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy, Journal of Finance, Vol. 23, Pages VenkataRamana, N., Azash, S., and Ramakrishnaiah, K. (2012) Financial Performance and Predicting the Risk of Bankruptcy: A Case of Selected Cement Companies in India, International Journal of Public Administration and Management Research, Vol. 1, No. 1, Pages 40-56, October. 6- Azhar, Syed and Ramesh, B. (2017) Predicting Financial Insolvency of Listed Power Generation/Distribution Companies in India Using Z Score (December 14, 2017). IOSR Journal of Business and Management (IOSR-JBM) (2017). Available at SSRN: Page 4

5 7- Maina, F. & Sakwa, M. (2017). Understanding financial distress among listed firms in Nairobi stock exchange: a quantitative. Approach using the z-score multi-discriminant financial analysis model. University of Agriculture and Technology, Nairobi, Kenya. 8- Subramanyam, K.R. and Wild, J. (2013) Financial Statement Analysis, 11 th edition, N.Y.: McGraw-Hill/Irwin. 9- Husein, M. and Pambekti, G. (2014) Precision of models of Altman, Springate, Zmijewski, and Grover for predicting the financial distress, Journal of Economics, Business, and Accounting Ventura, Vol. 17, No. 3, Pages , December. Page 5