A. Appendix
A.5 The presence of fat tail confirm heteroscedasticity of the GARCH process
4. Data analysis
Zones of discriminations:
Z>2.6 -“Safe”Zone
1.1 < Z < 2. 6 -“Grey”Zone Z < 1.1 -“Distress”Zone
The concept of CAMELS’standard, It consists of six dimensions. Each dimension can be measured through different ratios. These ratios along with their measures are1grouped2inTable 4.
4.2 Asset quality (AQ) dimension
Three ratios are examined: Total loans / total assets; Loan Loss Reserve;
Non-performing loan to Total loan.
Table 9shows test method(Variables Entered/Removed method).
Table 10shows3model summary between Z score and Total Loan to Total Assets, it indicates that Loan to Assets ratio interpret 88% of changes in Z score by positive causal relation = 11.45 point, at significance level 0.0001, seeTables 11–13 indicates that the best ratio can measure Assets Quality is Total Loan to Total Assets.
However both provision of non-performing loan to net loans and Non-Performing Loan to Total Loan ratios are excluded because they have high multi collinearity statistics. (They are highly correlated with each other).
Model Unstandardized
Coefficients
Standardized Coefficients t Sig.
B Std. Error Beta
1 T.Liabilities/T.Assets 8.898 .554 .888 16.051 .000
2 T.Liabilities/T.Assets 7.267 .918 .725 7.918 .000
Equity/ total assets ratio 6.586 2.997 .201 2.197 .031
aDependent Variable: Z Score
bLinear Regression through the Origin
Table 7.
Coefficientsa,bof the test between Z score and capital adequacy dimension.
Model Beta In t Sig. Partial Correlation Collinearity Statistics Tolerance
1 Equity/ total assets ratio .201c 2.197 .031 .257 .346
Source the researcher from data analysis.
aDependent Variable: Z Score
bLinear Regression through the Origin
cPredictors in the Model: T.Liabilities/T.Assets
Table 8.
Excluded Variablesa,b.
Variables Entered/Removeda,b
Model Variables Entered Variables Removed Method
1 T.Loan /T.Assets . Stepwise (Criteria: Probability-of-F-to-enter<
= .050, Probability-of-F-to-remove>= .100).
Source researcher from data analysis to Assets ratio interpret 88% of changes in Z score at significance level 0.0001.
aDependent Variable: Z Score.
bLinear Regression through the Origin.
Table 9.
Test method.
3 Loan means Islamic finance portfolio in Assets side of the bank
4.3 Management efficiency dimension
Four ratios are examined including: Cost to Income; Finance Cost /Total Assets;
ROE. Market price (absolute value is used). The researcher could not find
Model R R Squareb Adjusted R Square Std. Error of the Estimate
1 .886a .786 .783 3.41686937
Source researcher from data analysis.
aPredictors: Total Loan /Total Assets
bFor regression through the origin (the no-intercept model), R Square measures the proportion of the variability in the dependent variable about the origin explained by regression. This CANNOT be compared to R Square for models which include an intercept.
Table 10.
Model Summary between Z score and Assets Quality dimension.
ANOVAa,b
Model Sum of Squares df Mean Square F Sig.
1 Regression 2956.514 1 2956.514 253.235 .000c
Residual 805.575 69 11.675
Total 3762.089d 70
Source researcher from data analysis.
aDependent Variable: Z Score
bLinear Regression through the Origin
cPredictors: T.Loan /T.Assets
dThis total sum of squares is not corrected for the constant because the constant is zero for regression through the origin.
Table 11.
The significance of the model.
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 T.Loan /T.Assets 11.454 .720 .886 15.913 .000
Source researcher from data analysis.
Table 12shows that total loan to total assets positively on Z score.
aDependent Variable: Z Score.
bLinear Regression through the Origin.
Table 12.
Individual effect of independent variables: Coefficients.a,b
Model Beta
In
t Sig. Partial Correlation
Collinearity Statistics Tolerance 1 provision of non-performing loan /net loans .030c .536 .594 .065 .970
Non-Performing Loan /T.Loan .082c 1.226 .224 .147 .688 Source researcher from data analysis.
aDependent Variable: Z Score
bLinear Regression through the Origin
cPredictors in the Model: T.Loan /T.Assets
Table 13.
Excluded Variablesa,b.
employees number, so that she excluded Profit per Employee (PPE) and replaced with Market Price, however it did not use before in previous reviewed studied as efficient management indicator.
Table 14shows the model Summary which indicates that share market price plus constant interpret 28% of Z score changes (Table 15). AndTable 16shows excluded variables (ratios) from the model between Z score and management efficiency Dimension (Table 17).
According toTable 16: Z score = 1.36 + 1.05 share market price.
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .289a .083 .078 4.86709490
Source researcher from data analysis.
aPredictors: (Constant), share Market Price
bDependent Variable: Z Score
Table 14.
Model Summarybbetween Z score and management efficiency Dimension.
Model Sum of Squares df Mean Square F Sig.
1 Regression 358.058 1 358.058 15.115 .000b
Residual 3932.310 166 23.689
Total 4290.368 167
Source researcher from data analysis.
aDependent Variable: Z Score
bPredictors: (Constant), Market Price
Table 15.
ANOVA.atest between Z score and management efficiency Dimension.
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) 1.355 .683 1.985 .049
Share Market Price 1.051 .270 .289 3.888 .000
Source researcher from data analysis.
aDependent Variable: Z Score
Table 16.
Coefficientsa.
Model Beta In t Sig. Partial Correlation Collinearity Statistics Tolerance
1 Finance Cost /Total Assets -.025b .338 .736 .026 .999
Return on Equities .061b .820 .413 .064 .997
Total Cost /Total Income .086b 1.122 .264 .087 .941
Earnings Per Share -.082b 1.093 .276 .085 .976
Source researcher from data analysis.
aDependent Variable: Z Score
bPredictors in the Model: (Constant), Market Price
Table 17.
Excluded Variablesafrom the model between Z score and management efficiency Dimension.
4.4 Liquidity dimension
Three ratios are examined using step wise method,they are: Quick Ratio,Net loan to Total Assets;Net Loan/total DepositsTable 18shows model Summary,it indicates that Net Loan to Total Assets ratio interpret 89% of changes in Z score.Tables 19and 20show significance of the test at 0.0001 level.), andTable 21shows excluded variables(ratios) from the model between Z score and Liquidity dimension in camel model those are include Quick ratio,and current ratio. So that, these ratios should excluded from banks evaluation methods in the future.
4.5 Earnings dimension
Three ratios are used return on Equity (ROE), return on Assets (ROA), Earning Per share (EPS).Table 22shows the variables tested as indicators of Earning Dimension in Camel model,Table 23shows the model between Earning Dimension and Z score, andTable 24shows significant of the model between Z score and
Model R R Squareb Adjusted R Square Std. Error of the Estimate
1 .896a .803 .800 3.27566281
Source researcher from data analysis.
aPredictors: Net Loan/Total Assets
bFor regression through the origin (the no-intercept model), R Square measures the proportion of the variability in the dependent variable about the origin explained by regression. This CANNOT be compared to R Square for models which include an intercept.
Table 18.
Model summary between Z score and Liquidity Dimension.
Model Sum of Squares df Mean Square F Sig.
1 Regression 3021.721 1 3021.721 281.615 .000c
Residual 740.368 69 10.730
Total 3762.089d 70
Source researcher from data analysis.
Table 19shows significance of the test.
aDependent Variable: Z Score
bLinear Regression through the Origin
cPredictors: Net Loan/Total Assets
dThis total sum of squares is not corrected for the constant because the constant is zero for regression through the origin.
Table 19.
ANOVAa,b.
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 Net Loan/Total Assets 12.499 .745 .896 16.781 .000
Source researcher from analysis.
Table 20shows significant individual variable (net loan to Total assets ratio) effect on Z score.
aDependent Variable: Z Score
bLinear Regression through the Origin
Table 20.
Coefficientsa,bof the test between Z score and Liquidity Dimension.
Earning Dimension ratios, butTable 25shows significance of individual variable, it indicate that only Earnings Per share (EPS) as Earning indicator affects positively and significantly on Z score. However EPS did not use previously as Earning indi- cator in reviewed studies. The results ofTables 23and25show that only Earning per share can affect negatively on Z score at 1% level, however there is no signifi- cant effect of ROE&ROA on Z score.
Model Beta In t Sig. Partial
Correlation
Collinearity Statistics Tolerance 1 liquid assets / current
liabilities
.012c .193 .848 .023 .798
Liquid Assets/Total Deposits .119c 1.730 .088 .205 .585 Source the researcher from data analysis.
aDependent Variable: Z Score
bLinear Regression through the Origin
cPredictors in the Model: Net Loan/Total Assets
Table 21.
Excluded Variablesa,bfrom the model between Z score and Liquidity dimension in camel model.
Model Sum of Squares df Mean Square F Sig.
1 Regression 451.655 3 150.552 3.526 .020b
Residual 2818.162 66 42.699
Total 3269.817 69
Source the researcher from data analysis.
Table 24shows significant of the model between Z score and Earning Dimension ratios.
aDependent Variable: Z Score
bPredictors: (Constant), Earning Per Share in dollar, Return on Assets, Return on Equity
Table 24.
ANOVAatest between Z score and Earning Dimension ratios.
Model Variables Entereda Variables
Removed
Method
1 Earnings Per Share in dollar, Return on Assets, Return on Equityb
. Enter
Source the researcher from data analysis.
aDependent Variable: Z Score
bAll requested variables entered.
Table 22.
Variables entered/Removed.
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .372a .138 .099 6.53448
Source the researcher from data analysis.
aPredictors: (Constant), Earning Per Share in dollar, Return on Assets, Return on Equity
Table 23.
Model summary between Z score and Earning Dimension ratios.
4.6 Sensitivity dimension
Only one ratio (provision/gross Loan) is used to measure sensitivity effect on Z scoreTable 26shows model summary, between Z score and sensitivity ratio which indicates that provision to Gross loan ratio interpret 34% of changes in Z score.
Table 27shows significance of the test (0.004) (Table 28).
4.7 External factors analysis
The researcher used three economic factors as explanatory variables of Z score in Islamic banks, including gross domestic Product Growth rate (GDP), Inflation rate, and exchange rate in Dollar.Table 29indicates that exchange rate causes69% of changes in Z score,Table 30shows significance of the model, The result of
Table 31shows that exchange rate affect negatively on Z score in Islamic banks at
Model Unstandardized
Coefficients
Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) 4.340 1.554 2.793 .007
Return on Assets 121.732 132.351 .181 .920 .361
Return on Equity 5.350 22.077 .052 .242 .809
Earnings Per Share in dollar 2.860 .992 .384 2.883 .005
Source the researcher from data analysis.
Table 25shows significance of individual variable.
aDependent Variable: Z Score
Table 25.
Coefficients.aof the test between Z score and Earning Dimension ratios.
Model Sum of Squares df Mean Square F Sig.
1 Regression 439.498 1 439.498 9.127 .004c
Residual 3322.591 69 48.153
Total 3762.089d 70
Table 27shows significance of the test.
aDependent Variable: Z Score
bLinear Regression through the Origin
cPredictors: provision/Gross loan (PGL)
dThis total sum of squares is not corrected for the constant because the constant is zero for regression through the origin.
Table 27.
ANOVAa,b.
Model R R Squareb Adjusted R Square Std. Error of the Estimate
1 .342a .117 .104 6.93927225
Source the researcher from data analysis.
aPredictors: provision /Gross loan (PGL)
bFor regression through the origin (the no-intercept model), R Square measures the proportion of the variability in the dependent variable about the origin explained by regression. This CANNOT be compared to R Square for models which include an intercept.
Table 26.
Model summary between Z score and Sensitivity Dimension.
significance level .1%,Table 32shows excluded variables (GDP & inflation rate) from the model. According toTable 32the study can demonstrate there is no causal relation between that inflation rate, GDP and Z score. This result go in contrast with Zeitun [2] he stated that GDP was found to be positively related to banks perfor- mance, while inflation negatively related to the banks performance.
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .699a .489 .481 4.95918
Source the researcher from data analysis.
aPredictors: (Constant), exchange rate in Dollar
Table 29.
Model summary between Z score and economic factors.
Model Unstandardized
Coefficients
Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) 8.486 .837 10.138 .000
exchange rate in Dollar 3.442 .427 .699 8.059 .000
Source the researcher from data analysis.
aDependent Variable: Z Score.
Table 31.
Coefficientsasignificance of the model between Z score and exchange rate.
Model Sum of Squaresa df Mean Square F Sig.
1 Regression 1597.460 1 1597.460 64.955 .000b
Residual 1672.356 68 24.593
Total 3269.817 69
Source the researcher from data analysis.
aDependent Variable: Z Score
bPredictors: (Constant), exchange rate in Dollar
Table 30.
ANOVAatest between Z score and economic factors.
Model Unstandardized
Coefficients
Standardized Coefficients t Sig.
B Std. Error Beta
1 provision/ Gross loan (PGL) 23.147 7.662 .342 3.021 .004
Table 28shows individual variable significance.
Source researcher from data analysis.
aDependent Variable: Z Score
bLinear Regression through the Origin
Table 28.
Coefficientsa,bof the test between Z score and Sensitivity Dimension.