Research Journal of Finance and Accounting www.iiste.org ISSN 2222-1697 (Paper) ISSN 2222-2847 (Online) Vol.9, No.6, 2018 94 Portability of Multiple Discriminant Analysis Prediction Model of Listed Firms: An Emerging Market Perspective Prince Gyimah 1* Williams Kwasi Boachie 1 1. University of Education, Winneba – Kumasi Campus Department of Accounting Studies Education. P. O. Box 1277, Tanoso, Kumasi – Ghana. Abstract This paper tests the portability of Altman’s (2000) Z-score model in predicting corporate failure of listed firms in an emerging market, Ghana. The study applies the model on financial statements of fifteen (15) firms listed on Ghana Stock Exchange (GSE) for 2013 fiscal year. The empirical result shows that 66.7 percent of the listed firms were misclassified as failed firms (Type II Error) and correctly classified 33.3 percent as success firms or safe zone firms. The study concludes that the Altman (2000) financial model is not portable in Ghana due to high type II error rate and this is calling more research for the use of non-financial models in predicting corporate failure in emerging markets. Keywords: Multiple Discriminant Analysis, Corporate failure, Altman Z-score, Listed firms, Ghana 1. Introduction Stakeholders such as shareholders, managers, employees, financial institutions, and investors are concerned about their organizational financial health. The ability to predict corporate financial distress is particularly significant to these stakeholders in order to take the necessary preventive measures. Also, corporate ethics and governance although have created a platform to prevent financial failure, an early prediction is essential for stakeholders especially investors that intend to protect their financial investments (Muntari, 2015; Muller et al., 2009). Several corporate failures have occurred in both developed and emerging markets, and thus corporate failure prediction model is crucial to serve as benchmark for organizations. In developed countries, companies such as WorldCom, Enron Corporation, Freddie, AIG, General Motors (GM), Xerox, Lehman Brothers are some of the companies that have collapsed. Emerging market like Ghana, companies that have collapsed include Ghana Airways, Bank for Housing and Construction, Gateway Broadcasting Services, Ghana Co-operative Bank, National Savings and Credit Bank (Appiah, 2011). A case of corporate failure that is still fresh in the minds of Ghanaians is the collapse of DKM, Noble Dreams Saving and Loans, and Ghana Commercial Bank that recently took over UT Bank and Capital Bank due to liquidity and solvency challenges. Thus, prediction of corporate failure can enable companies to reduce bankruptcy costs, avoid failure and help improve financial stability. This paper is timely in addressing the needs of companies in the Ghanaian economy. In Ghana, there have been some recent studies on corporate failure prediction, notably among is the corporate failure prediction study conducted by Appiah (2011) using Altman (1968) model. The results of Appiah (2011) indicated that the Altman (1968) prediction model is not applicable in Ghana in predicting the success and failure of companies. However, the revised model, Altman (2000) Z-score has not be tested in Ghana to find out whether it can be used by stakeholders as a benchmark in predicting failure or success of companies. This current paper intends to replicate Appiah (2011) to test the revised model, Altman’s (2000) model if it is portable among listed firms in Ghana. The results of the study can contribute to literature on the stability of listed companies in Ghana, and assist the general public and investors on the financial health of companies listed on Ghana Stock Exchange. The rest of the paper is presented as follows: Section 2 gives brief literature on corporate failure prediction models, Section 3 discusses the methods and multiple discriminant analysis model used for the study, Section 4 presents and discusses the empirical results, and finally Section 5 concludes the study. 2. Literature Review Corporate failure prediction is essential for mitigation negative economic cycles in an economy (Simic et al., 2012) and has become a significant concern for corporate governance. Empirical studies reveal that failure predictions of most businesses concentrate on financial data, but few considered other non-financial variables as being relevant. The contribution of Altman (1968); Altman, Haldeman, and Harayanan (1977); Beaver (1966); Deakin (1977);