GRM 2010 GRM 2011

Abstract Details

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Title of Paper:
Predicting Banking Didstress in GCC Countries Using Emerging Market Z"-Sore Model: A Comparative Study
Paper Proposal Text :
Purpose - This paper analyses whether Altman Emerging Market (EM) Z”-score models, can predict bankruptcy and at the same time measuring the financial performance of Islamic banks in the GCC countries. The empirical analysis examines 13 Islamic banks in GCC countries – consists of 4 Islamic Banks in UAE, 3 Islamic banks in Bahrain, 2 Islamic banks in Qatar, 2 Islamic Banks in Saudi Arabia, and 2 Islamic Banks in Kuwait, during the period of 2005-2010. This is significant since the study also look at the impact of global financial crisis to the Islamic banks performance in this region.

Literature - Several bank failure prediction models have been developed since the mid 1970s. Most of the earlier models were built using classical statistical techniques, such as multivariate discriminant analysis (MDA). Later studies have also used neural networks, split-population survival time model, Bayesian belief networks, and isotonic separation. Some of these models have been routinely applied in the regulatory practices of banking agencies. Most of these models predict likely bank failures based on a set of high-level constructs called financial ratios, instead of low-level accounting variables. These financial ratios are usually constructed based on publicly available balance and income data that commercial banks are required to report to regulatory authorities on a regular basis. They are designed to reflect the soundness of a commercial bank in several aspects. Given the importance of the subject, extensive research has been devoted to the design and identification of such financial ratios in the last three decades. As a result, a large set of financial ratios has been identified and applied in regulatory practices. These financial ratios are believed to be more effective explanatory variables than the raw accounting data in the call reports in predicting and explaining bank failures (Zhao, Sinha, & Ge, 2009).
As such, the original Z-score bankruptcy model was as follows:
Z = 1.2X1 + 1.4X2 + 3.3X3 + 0.6X4 + 1.0X5.
X1 = working capital/total assets,
X2 = retained earnings/total assets,
X3 = earnings before interest and taxes/total assets,
X4 = market value equity/book value of total liabilities,
X5 = sales/total assets, and
The cut-off values for the z-score involve three zones that permit one to assess whether this model identifies the company as safe, in the gray area, or troubled. Any score greater than or equal 2.99 is considered safe, score between 1.82 and 2.98 is in the grey area, and finally any score below 1.81 is considered as a troubled company.
Some modification of the original Z-score can be seen in the Z”-score model for the non-manufacturing companies. In order to minimize the potential industry effect, Altman developed this model without X5 (sales/total assets). This model has been used by Altman to assess the financial health of non-US corporate. The Z”-score model is as follows:
Z" = 6.56 (X1)+ 3.26 (X2) + 6.72 (X3) + 1.05 (X4)
All of the coefficients for variables X1 to X4 are changed as are the group means and cut-off scores. Any score greater than or equal 2.6 is considered safe, score between 1.1 and 2.6 is in the grey area, and finally any score below 1.1 is considered as in a distressed area.

Methodology - The methodology that will be used in this study is based on the Z”-score model for emerging markets developed by Altman. Most of the previous studies has proved that EM Z”-score model has more than 80 percent of accuracy and confirmed that it is a robust tool and valuable in assessing and predicting the potential distress condition of companies. In this study, the EM Z”-score for each Islamic banks for the past six years calculated by examining the financial statements of each of these Islamic banks. These Z”-score then will then be compared with the Z”-score for the current year. By Applying the Emerging Market Z”-score, this study investigated whether EM Z”-Score model can predict the Islamic banks performance for a period of up to six years earlier. Altman, Hatzell and Peck (1995) have applied this enhanced Z”-score model to emerging markets corporate.

Research Limitations/ Recommendations – Islamic banking industry in GCC countries is still considered as small size, thus this has some effect on the number of samples as well as the maximum outcome of this study. It is recommended that, for future studies, the coefficient values of each ratio in this EM Z”-score model to be updated based on the inputs from the Islamic banking industry in GCC, thus giving some true value for better prediction of banking distress condition in the Gulf region.

Research Implications – The empirical results of this study can be used by banking regulators in monitoring the performance of Islamic banks in the GCC countries and at the same time reducing the effect of banks go bankrupt.

Keyword(s) – Banking distress, GCC countries, EM Z”-Score Model