Iiuedu.eu

More documents

Recommendations

Info

28 School of Doctoral Studies (European Union) Journal2011Table 2. Pearson correlation coefficientX2 0.74X1 X2 X3 X4 X5 OLSIZE TLTA WCTA CLCA NITA FUTL CHIN NITL CACL RESIZE LEXRETURN LAGSIGMAX3 0.42 0.60X4 0.18 0.26 0.54X5 0.17 0.15 0.29 0.01*OLSIZE -0.04* 0.15 0.09 -0.08 -0.15TLTA -0.80 -0.86 -0.56 -0.35 -0.07 -0.07WCTA 0.31 -0.12 -0.11 -0.24 0.26 -0.17 0.24CLCA -0.90 -0.61 -0.37 -0.18 -0.23 0.08 0.67 -0.39NITA 0.51 0.68 0.91 0.55 0.20 0.12 -0.68 -0.18 -0.44FUTL 0.19 0.36 0.61 0.57 0.12 0.02* -0.43 -0.32 -0.20 0.56CHIN 0.06 0.09 0.29 0.16 0.09 0.01* -0.07 0.00* -0.07 0.33 0.10NITL 0.39 0.52 0.81 0.64 0.13 0.04* -0.59 -0.23 -0.37 0.86 0.69 0.28CACL 0.76 0.44 0.35 0.29 0.16 -0.15 -0.57 0.31 -0.77 0.39 0.28 0.07 0.51RESIZE 0.09 0.28 0.45 0.43 -0.07 0.76 -0.26 -0.27 -0.04* 0.48 0.30 0.10 0.40 -0.01*LEXRETURN 0.10 0.16 0.27 0.21 0.01* 0.15 -0.09 0.04* -0.09 0.29 0.03* 0.09 0.20 0.06 0.34LAGSIGMA 0.10 0.05 0.05 0.02* 0.03* 0.05 -0.06 0.03* -0.10 0.07 -0.04* 0.06 0.01* 0.04* 0.11 0.09TLMTA -0.34 -0.41 -0.67 -0.79 -0.07 0.10 0.54 0.28 0.30 -0.71 -0.56 -0.16 -0.73 -0.37 -0.51 -0.28 -0.08This table presents Pearson correlation coefficient. The coefficients that are marked with asterisk (*), are not significant but others are significant atthe 5% level or lower.The results of Pearson correlation coefficients showthat the most of coefficients between research variables aresignificant at the 5% level or better.Model EstimationThe regression results of models and In-sample andout-of-sample prediction metrics to compare the modelsare presented in Table 3. The estimation results of Altman(1968) model indicate that X1 (-0.12), X2 (-0.48) and X3(-0.52) have a negative and significant relationship withdependent variable (Failing) at the 1% level and X4 (0.01)has a positive relation with dependent variable at the 5%level but X5 has no significant relationship with dependentvariable. The F-statistic of this model (468.16) is significantat the 1% level.Altman (1968)modelPanel A: Model estimation resultsTable 3: The results of regression modelsOhlson (1980)modelZemijewsky(1984) modelShumway (2001)modelCombinedmodelIntercept 0.18** -12.87** -8.00** -16.94** -2.22**X1 -0.12** -0.95X2 -0.48** -13.40**X3 -0.52**X4 0.01*X5 0.00OLSIZE -0.14TLTA 14.58** 8.21** 17.75**WCTA -2.92CLCA -0.60School of Doctoral Studies (European Union) Journal - 2011
2011 Comparing Bankruptcy Prediction Models in Iran29Altman (1968)modelOhlson (1980)modelZemijewsky(1984) modelShumway (2001)modelCombinedmodelOENEG -0.17 1.73**NITA -1.40FUTL -2.60INTWO 3.79** 0.25CHIN -0.25NITL -3.21* -9.88* -0.91CACL -0.03 0.01RESIZE 0.01LEXRETURN -1.25LAGSIGMA -0.60TLMTAPanel B: In-sample prediction power metricAdj. R 2 51.25 Pse. R 2 83.21 72.71 76.07 87.83F stat. 468.16** LR stat. 904.61** 1272.92** 1083.25** 1384.16**Voung Z 11.48** 2.21* 4.81** 3.22**Panel C: Out-of-sample prediction power metricsRMSE 0.21 0.14 0.16 0.14 0.12MAE 0.14 0.03 0.06 0.05 0.03MAPE 4.96 1.64 2.69 2.05 1.41*, ** significant at the 5% and 1%, respectivelyIn the Ohlson (1980) model, TLTA (14.58) and thedummy variable of INTWO (3.79) are significant at the1% level and in Zemijewsky (1984) model TLTA (8.21)and NITL (-3.21) are significant at the 1% and 5% level,respectively. The results of Shumway (2001) modelindicates that TLTA (17.75) and NITL (-9.88) are significantat the 1% and 5% level respectively. Finally, our presentedmodel show that X2 (-13.40) and OENG (1.73) are bothsignificant at the 1% level.The results of likelihood ratio (LR) for Ohlson model(904.61), Zemijewsky model (1272.92), Shumway model(1083.25) and our presented combined model (1384.16)show that all models are significant at 1% level, generally.The In-sample prediction power (adjusted R2) of ourcombined model (87.83%) is higher than that of Altmanmodel (51.25%), Ohlson model (83.21%), Zemijewskymodel (72.71%) and Shumway model (76.07%). the resultsof Voung (1989) test show that the differences between theprediction power of combined model and Altman model(11.48), Ohlson model (2.21), Zemijewsky model (4.81)and Shumway model (3.22) are all significant at the 1%level.The results show that the root mean squared error(RMSE) of our combined model (0.12) is lower than thatof Altman model (0.21), Ohlson model (0.14), Zemijewskymodel (0.16) and Shumway model (0.14). The resultsalso indicate that the mean absolute error (mean absolutepercent error) of our combined model, 0.03 (1.41) is lowerthan (or equal to) that of Altman model, 0.14 (4.96), Ohlsonmodel, 0.03 (1.64), Zemijewsky model, 0.06 (2.69) andShumway model, 0.05 (2.05). Thus, the results indicate thatthe In-sample and out-of-sample prediction power of ourpresented model in predicting failed firms is higher than thatof other previous models. Thus, our logit type bankruptcyprediction model significantly outperforms other models.ConclusionIn this paper, we examine the predictive power of anumber of bankruptcy prediction models. The models usea range of different independent variables (accountinginformation and market and firm-characteristic data) anda range of different econometric specifications (multiplediscriminateanalysis, logit ‎, probit models). We find thatfirms are more likely to experience bankruptcy if theyhave relatively lower earnings before interest and tax tototal assets, a larger decline in net income, relatively lowworking capital to total assets, or high total liabilities tototal assets.We compare the empirical performance of a range ofbankruptcy prediction models using a series of in-sampleand out-of-sample performance metrics. Across all of theseEbrahimi K. A., Nikbakht N. - Comparing Bankruptcy Prediction Models in Iran
Page 1 and 2: Number 3Year 2011School of Doctoral
Page 3 and 4: 2011 School of Doctoral Studies (Eu
Page 6 and 7: 4 School of Doctoral Studies (Europ
Page 8 and 9: 6 School of Doctoral Studies (Europ
Page 10: 8 School of Doctoral Studies (Europ
Page 14 and 15: 12 School of Doctoral Studies (Euro
Page 21 and 22: 2011 Institutional Infrastructure a
Page 27 and 28: 2011 Comparing Bankruptcy Predictio
Page 29: 2011 Comparing Bankruptcy Predictio
Page 33 and 34: 2011 Comparing Bankruptcy Predictio
Page 35 and 36: 2011 The Relationship Between Servi
Page 41 and 42: 2011 Electronic Commerce, Automatio
Page 53 and 54: 2011 A Survey on the Assessment of
Page 67 and 68: 2011 Small Scale Supplier Satisfact
Page 81 and 82:
2011 Globalization and Energy Deman
Page 83 and 84:
Page 85 and 86:
Page 87 and 88:
2011 Overview and Analysis on Cyber
Page 89 and 90:
Page 91 and 92:
Page 93 and 94:
Page 95 and 96:
Page 97 and 98:
Page 99 and 100:
Page 101 and 102:
2011 The Impact of Computer Aided D
Page 103 and 104:
Page 105 and 106:
Page 107 and 108:
Page 109 and 110:
Page 111 and 112:
Page 113 and 114:
111 School of Doctoral Studies (Eur
Page 115 and 116:
2011 Enhanced Wellbeing Amongst Eng
Page 117 and 118:
Page 119 and 120:
Page 121 and 122:
Page 123 and 124:
2011 An Effective Neuroprotective T
Page 125 and 126:
Page 127 and 128:
Page 129 and 130:
Page 131 and 132:
Page 133 and 134:
Page 135 and 136:
Page 137 and 138:
2011 Metastatic Breast Cancer: An e
Page 139 and 140:
Page 141 and 142:
Page 143 and 144:
Page 145 and 146:
Page 147 and 148:
2011 Natural Gas Sweetening Process
Page 149 and 150:
Page 151 and 152:
Page 153 and 154:
Page 155 and 156:
Page 157 and 158:
Page 159 and 160:
157 School of Doctoral Studies (Eur
Page 161 and 162:
2011 Foreign Aid and Economic Devel
Page 163 and 164:
Page 165 and 166:
Page 167 and 168:
Page 169 and 170:
2011 Marcel Duchamp Artist’s Work
Page 171 and 172:
Page 173 and 174:
Page 175 and 176:
Page 177 and 178:
Page 179 and 180:
Page 181 and 182:
2011 The Effect of Islamic Azad Uni
Page 183 and 184:
Page 185 and 186:
Page 187 and 188:
2011 Service Failure and Recovery:
Page 189 and 190:
Page 191 and 192:
show all

Iiuedu.eu

Create successful ePaper yourself

Delete template?

Save as template?