Re-estimation and comparisons of alternative accounting based bankruptcy prediction models for Indian companies

Background The suitability and performance of the bankruptcy prediction models is an empirical question. The aim of this paper is to develop a bankruptcy prediction model for Indian manufacturing companies on a sample of 208 companies consisting of an equal number of defaulted and non-defaulted firms. Out of 208 companies, 130 are used for estimation sample, and 78 are holdout for model validation. The study reestimates the accounting based models such as Altman EI (Journal of Finance 23: 19189–209, 1968) Z-Score, Ohlson JA (Journal of Accounting Research 18:109–131, 1980) Y-Score and Zmijewski ME (Journal of Accounting Research 22:59–82, 1984) X-Score model. The paper compares original and re-estimated models to explore the sensitivity of these models towards the change in time periods and financial conditions. Methods Multiple Discriminant Analysis (MDA) and Probit techniques are employed in the estimation of Z-Score and X-Score models, whereas Logit technique is employed in the estimation of Y-Score and the newly proposed models. The performance of all the original, re-estimated and new proposed models are assessed by predictive accuracy, significance of parameters, long-range accuracy, secondary sample and Receiver Operating Characteristic (ROC) tests. Results The major findings of the study reveal that the overall predictive accuracy of all the three models improves on estimation and holdout sample when the coefficients are re-estimated. Amongst the contesting models, the new bankruptcy prediction model outperforms other models. Conclusions The industry specific model should be developed with the new combinations of financial ratios to predict bankruptcy of the firms in a particular country. The study further suggests the coefficients of the models are sensitive to time periods and financial condition. Hence, researchers should be cautioned while choosing the models for bankruptcy prediction to recalculate the models by looking at the recent data in order to get higher predictive accuracy. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Singh, Bhanu Pratap [verfasserIn] Mishra, Alok Kumar

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2016

Schlagwörter:	Bankruptcy prediction Indian manufacturing companies MDA Logit Probit Unstable coefficient Predictive accuracy Receiver operating characteristic Long range accuracy

Anmerkung:	© The Author(s). 2016

Übergeordnetes Werk:	Enthalten in: Financial innovation - Heidelberg : SpringerOpen, 2015, 2(2016), 1 vom: 09. Juni
Übergeordnetes Werk:	volume:2 ; year:2016 ; number:1 ; day:09 ; month:06

Links:	Volltext

DOI / URN:	10.1186/s40854-016-0026-9

Katalog-ID:	SPR03793046X

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allfields	10.1186/s40854-016-0026-9 doi (DE-627)SPR03793046X (SPR)s40854-016-0026-9-e DE-627 ger DE-627 rakwb eng Singh, Bhanu Pratap verfasserin aut Re-estimation and comparisons of alternative accounting based bankruptcy prediction models for Indian companies 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2016 Background The suitability and performance of the bankruptcy prediction models is an empirical question. The aim of this paper is to develop a bankruptcy prediction model for Indian manufacturing companies on a sample of 208 companies consisting of an equal number of defaulted and non-defaulted firms. Out of 208 companies, 130 are used for estimation sample, and 78 are holdout for model validation. The study reestimates the accounting based models such as Altman EI (Journal of Finance 23: 19189–209, 1968) Z-Score, Ohlson JA (Journal of Accounting Research 18:109–131, 1980) Y-Score and Zmijewski ME (Journal of Accounting Research 22:59–82, 1984) X-Score model. The paper compares original and re-estimated models to explore the sensitivity of these models towards the change in time periods and financial conditions. Methods Multiple Discriminant Analysis (MDA) and Probit techniques are employed in the estimation of Z-Score and X-Score models, whereas Logit technique is employed in the estimation of Y-Score and the newly proposed models. The performance of all the original, re-estimated and new proposed models are assessed by predictive accuracy, significance of parameters, long-range accuracy, secondary sample and Receiver Operating Characteristic (ROC) tests. Results The major findings of the study reveal that the overall predictive accuracy of all the three models improves on estimation and holdout sample when the coefficients are re-estimated. Amongst the contesting models, the new bankruptcy prediction model outperforms other models. Conclusions The industry specific model should be developed with the new combinations of financial ratios to predict bankruptcy of the firms in a particular country. The study further suggests the coefficients of the models are sensitive to time periods and financial condition. Hence, researchers should be cautioned while choosing the models for bankruptcy prediction to recalculate the models by looking at the recent data in order to get higher predictive accuracy. Bankruptcy prediction (dpeaa)DE-He213 Indian manufacturing companies (dpeaa)DE-He213 MDA (dpeaa)DE-He213 Logit (dpeaa)DE-He213 Probit (dpeaa)DE-He213 Unstable coefficient (dpeaa)DE-He213 Predictive accuracy (dpeaa)DE-He213 Receiver operating characteristic (dpeaa)DE-He213 Long range accuracy (dpeaa)DE-He213 Mishra, Alok Kumar aut Enthalten in Financial innovation Heidelberg : SpringerOpen, 2015 2(2016), 1 vom: 09. Juni (DE-627)827572417 (DE-600)2824759-0 2199-4730 nnns volume:2 year:2016 number:1 day:09 month:06 https://dx.doi.org/10.1186/s40854-016-0026-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2 2016 1 09 06
spelling	10.1186/s40854-016-0026-9 doi (DE-627)SPR03793046X (SPR)s40854-016-0026-9-e DE-627 ger DE-627 rakwb eng Singh, Bhanu Pratap verfasserin aut Re-estimation and comparisons of alternative accounting based bankruptcy prediction models for Indian companies 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2016 Background The suitability and performance of the bankruptcy prediction models is an empirical question. The aim of this paper is to develop a bankruptcy prediction model for Indian manufacturing companies on a sample of 208 companies consisting of an equal number of defaulted and non-defaulted firms. Out of 208 companies, 130 are used for estimation sample, and 78 are holdout for model validation. The study reestimates the accounting based models such as Altman EI (Journal of Finance 23: 19189–209, 1968) Z-Score, Ohlson JA (Journal of Accounting Research 18:109–131, 1980) Y-Score and Zmijewski ME (Journal of Accounting Research 22:59–82, 1984) X-Score model. The paper compares original and re-estimated models to explore the sensitivity of these models towards the change in time periods and financial conditions. Methods Multiple Discriminant Analysis (MDA) and Probit techniques are employed in the estimation of Z-Score and X-Score models, whereas Logit technique is employed in the estimation of Y-Score and the newly proposed models. The performance of all the original, re-estimated and new proposed models are assessed by predictive accuracy, significance of parameters, long-range accuracy, secondary sample and Receiver Operating Characteristic (ROC) tests. Results The major findings of the study reveal that the overall predictive accuracy of all the three models improves on estimation and holdout sample when the coefficients are re-estimated. Amongst the contesting models, the new bankruptcy prediction model outperforms other models. Conclusions The industry specific model should be developed with the new combinations of financial ratios to predict bankruptcy of the firms in a particular country. The study further suggests the coefficients of the models are sensitive to time periods and financial condition. Hence, researchers should be cautioned while choosing the models for bankruptcy prediction to recalculate the models by looking at the recent data in order to get higher predictive accuracy. Bankruptcy prediction (dpeaa)DE-He213 Indian manufacturing companies (dpeaa)DE-He213 MDA (dpeaa)DE-He213 Logit (dpeaa)DE-He213 Probit (dpeaa)DE-He213 Unstable coefficient (dpeaa)DE-He213 Predictive accuracy (dpeaa)DE-He213 Receiver operating characteristic (dpeaa)DE-He213 Long range accuracy (dpeaa)DE-He213 Mishra, Alok Kumar aut Enthalten in Financial innovation Heidelberg : SpringerOpen, 2015 2(2016), 1 vom: 09. Juni (DE-627)827572417 (DE-600)2824759-0 2199-4730 nnns volume:2 year:2016 number:1 day:09 month:06 https://dx.doi.org/10.1186/s40854-016-0026-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2 2016 1 09 06
allfields_unstemmed	10.1186/s40854-016-0026-9 doi (DE-627)SPR03793046X (SPR)s40854-016-0026-9-e DE-627 ger DE-627 rakwb eng Singh, Bhanu Pratap verfasserin aut Re-estimation and comparisons of alternative accounting based bankruptcy prediction models for Indian companies 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2016 Background The suitability and performance of the bankruptcy prediction models is an empirical question. The aim of this paper is to develop a bankruptcy prediction model for Indian manufacturing companies on a sample of 208 companies consisting of an equal number of defaulted and non-defaulted firms. Out of 208 companies, 130 are used for estimation sample, and 78 are holdout for model validation. The study reestimates the accounting based models such as Altman EI (Journal of Finance 23: 19189–209, 1968) Z-Score, Ohlson JA (Journal of Accounting Research 18:109–131, 1980) Y-Score and Zmijewski ME (Journal of Accounting Research 22:59–82, 1984) X-Score model. The paper compares original and re-estimated models to explore the sensitivity of these models towards the change in time periods and financial conditions. Methods Multiple Discriminant Analysis (MDA) and Probit techniques are employed in the estimation of Z-Score and X-Score models, whereas Logit technique is employed in the estimation of Y-Score and the newly proposed models. The performance of all the original, re-estimated and new proposed models are assessed by predictive accuracy, significance of parameters, long-range accuracy, secondary sample and Receiver Operating Characteristic (ROC) tests. Results The major findings of the study reveal that the overall predictive accuracy of all the three models improves on estimation and holdout sample when the coefficients are re-estimated. Amongst the contesting models, the new bankruptcy prediction model outperforms other models. Conclusions The industry specific model should be developed with the new combinations of financial ratios to predict bankruptcy of the firms in a particular country. The study further suggests the coefficients of the models are sensitive to time periods and financial condition. Hence, researchers should be cautioned while choosing the models for bankruptcy prediction to recalculate the models by looking at the recent data in order to get higher predictive accuracy. Bankruptcy prediction (dpeaa)DE-He213 Indian manufacturing companies (dpeaa)DE-He213 MDA (dpeaa)DE-He213 Logit (dpeaa)DE-He213 Probit (dpeaa)DE-He213 Unstable coefficient (dpeaa)DE-He213 Predictive accuracy (dpeaa)DE-He213 Receiver operating characteristic (dpeaa)DE-He213 Long range accuracy (dpeaa)DE-He213 Mishra, Alok Kumar aut Enthalten in Financial innovation Heidelberg : SpringerOpen, 2015 2(2016), 1 vom: 09. Juni (DE-627)827572417 (DE-600)2824759-0 2199-4730 nnns volume:2 year:2016 number:1 day:09 month:06 https://dx.doi.org/10.1186/s40854-016-0026-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2 2016 1 09 06
allfieldsGer	10.1186/s40854-016-0026-9 doi (DE-627)SPR03793046X (SPR)s40854-016-0026-9-e DE-627 ger DE-627 rakwb eng Singh, Bhanu Pratap verfasserin aut Re-estimation and comparisons of alternative accounting based bankruptcy prediction models for Indian companies 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2016 Background The suitability and performance of the bankruptcy prediction models is an empirical question. The aim of this paper is to develop a bankruptcy prediction model for Indian manufacturing companies on a sample of 208 companies consisting of an equal number of defaulted and non-defaulted firms. Out of 208 companies, 130 are used for estimation sample, and 78 are holdout for model validation. The study reestimates the accounting based models such as Altman EI (Journal of Finance 23: 19189–209, 1968) Z-Score, Ohlson JA (Journal of Accounting Research 18:109–131, 1980) Y-Score and Zmijewski ME (Journal of Accounting Research 22:59–82, 1984) X-Score model. The paper compares original and re-estimated models to explore the sensitivity of these models towards the change in time periods and financial conditions. Methods Multiple Discriminant Analysis (MDA) and Probit techniques are employed in the estimation of Z-Score and X-Score models, whereas Logit technique is employed in the estimation of Y-Score and the newly proposed models. The performance of all the original, re-estimated and new proposed models are assessed by predictive accuracy, significance of parameters, long-range accuracy, secondary sample and Receiver Operating Characteristic (ROC) tests. Results The major findings of the study reveal that the overall predictive accuracy of all the three models improves on estimation and holdout sample when the coefficients are re-estimated. Amongst the contesting models, the new bankruptcy prediction model outperforms other models. Conclusions The industry specific model should be developed with the new combinations of financial ratios to predict bankruptcy of the firms in a particular country. The study further suggests the coefficients of the models are sensitive to time periods and financial condition. Hence, researchers should be cautioned while choosing the models for bankruptcy prediction to recalculate the models by looking at the recent data in order to get higher predictive accuracy. Bankruptcy prediction (dpeaa)DE-He213 Indian manufacturing companies (dpeaa)DE-He213 MDA (dpeaa)DE-He213 Logit (dpeaa)DE-He213 Probit (dpeaa)DE-He213 Unstable coefficient (dpeaa)DE-He213 Predictive accuracy (dpeaa)DE-He213 Receiver operating characteristic (dpeaa)DE-He213 Long range accuracy (dpeaa)DE-He213 Mishra, Alok Kumar aut Enthalten in Financial innovation Heidelberg : SpringerOpen, 2015 2(2016), 1 vom: 09. Juni (DE-627)827572417 (DE-600)2824759-0 2199-4730 nnns volume:2 year:2016 number:1 day:09 month:06 https://dx.doi.org/10.1186/s40854-016-0026-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2 2016 1 09 06
allfieldsSound	10.1186/s40854-016-0026-9 doi (DE-627)SPR03793046X (SPR)s40854-016-0026-9-e DE-627 ger DE-627 rakwb eng Singh, Bhanu Pratap verfasserin aut Re-estimation and comparisons of alternative accounting based bankruptcy prediction models for Indian companies 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2016 Background The suitability and performance of the bankruptcy prediction models is an empirical question. The aim of this paper is to develop a bankruptcy prediction model for Indian manufacturing companies on a sample of 208 companies consisting of an equal number of defaulted and non-defaulted firms. Out of 208 companies, 130 are used for estimation sample, and 78 are holdout for model validation. The study reestimates the accounting based models such as Altman EI (Journal of Finance 23: 19189–209, 1968) Z-Score, Ohlson JA (Journal of Accounting Research 18:109–131, 1980) Y-Score and Zmijewski ME (Journal of Accounting Research 22:59–82, 1984) X-Score model. The paper compares original and re-estimated models to explore the sensitivity of these models towards the change in time periods and financial conditions. Methods Multiple Discriminant Analysis (MDA) and Probit techniques are employed in the estimation of Z-Score and X-Score models, whereas Logit technique is employed in the estimation of Y-Score and the newly proposed models. The performance of all the original, re-estimated and new proposed models are assessed by predictive accuracy, significance of parameters, long-range accuracy, secondary sample and Receiver Operating Characteristic (ROC) tests. Results The major findings of the study reveal that the overall predictive accuracy of all the three models improves on estimation and holdout sample when the coefficients are re-estimated. Amongst the contesting models, the new bankruptcy prediction model outperforms other models. Conclusions The industry specific model should be developed with the new combinations of financial ratios to predict bankruptcy of the firms in a particular country. The study further suggests the coefficients of the models are sensitive to time periods and financial condition. Hence, researchers should be cautioned while choosing the models for bankruptcy prediction to recalculate the models by looking at the recent data in order to get higher predictive accuracy. Bankruptcy prediction (dpeaa)DE-He213 Indian manufacturing companies (dpeaa)DE-He213 MDA (dpeaa)DE-He213 Logit (dpeaa)DE-He213 Probit (dpeaa)DE-He213 Unstable coefficient (dpeaa)DE-He213 Predictive accuracy (dpeaa)DE-He213 Receiver operating characteristic (dpeaa)DE-He213 Long range accuracy (dpeaa)DE-He213 Mishra, Alok Kumar aut Enthalten in Financial innovation Heidelberg : SpringerOpen, 2015 2(2016), 1 vom: 09. Juni (DE-627)827572417 (DE-600)2824759-0 2199-4730 nnns volume:2 year:2016 number:1 day:09 month:06 https://dx.doi.org/10.1186/s40854-016-0026-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2034 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2 2016 1 09 06
language	English
source	Enthalten in Financial innovation 2(2016), 1 vom: 09. Juni volume:2 year:2016 number:1 day:09 month:06
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topic_facet	Bankruptcy prediction Indian manufacturing companies MDA Logit Probit Unstable coefficient Predictive accuracy Receiver operating characteristic Long range accuracy
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author	Singh, Bhanu Pratap
spellingShingle	Singh, Bhanu Pratap misc Bankruptcy prediction misc Indian manufacturing companies misc MDA misc Logit misc Probit misc Unstable coefficient misc Predictive accuracy misc Receiver operating characteristic misc Long range accuracy Re-estimation and comparisons of alternative accounting based bankruptcy prediction models for Indian companies
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topic_title	Re-estimation and comparisons of alternative accounting based bankruptcy prediction models for Indian companies Bankruptcy prediction (dpeaa)DE-He213 Indian manufacturing companies (dpeaa)DE-He213 MDA (dpeaa)DE-He213 Logit (dpeaa)DE-He213 Probit (dpeaa)DE-He213 Unstable coefficient (dpeaa)DE-He213 Predictive accuracy (dpeaa)DE-He213 Receiver operating characteristic (dpeaa)DE-He213 Long range accuracy (dpeaa)DE-He213
topic	misc Bankruptcy prediction misc Indian manufacturing companies misc MDA misc Logit misc Probit misc Unstable coefficient misc Predictive accuracy misc Receiver operating characteristic misc Long range accuracy
topic_unstemmed	misc Bankruptcy prediction misc Indian manufacturing companies misc MDA misc Logit misc Probit misc Unstable coefficient misc Predictive accuracy misc Receiver operating characteristic misc Long range accuracy
topic_browse	misc Bankruptcy prediction misc Indian manufacturing companies misc MDA misc Logit misc Probit misc Unstable coefficient misc Predictive accuracy misc Receiver operating characteristic misc Long range accuracy
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title	Re-estimation and comparisons of alternative accounting based bankruptcy prediction models for Indian companies
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title_full	Re-estimation and comparisons of alternative accounting based bankruptcy prediction models for Indian companies
author_sort	Singh, Bhanu Pratap
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author_browse	Singh, Bhanu Pratap Mishra, Alok Kumar
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doi_str_mv	10.1186/s40854-016-0026-9
title_sort	re-estimation and comparisons of alternative accounting based bankruptcy prediction models for indian companies
title_auth	Re-estimation and comparisons of alternative accounting based bankruptcy prediction models for Indian companies
abstract	Background The suitability and performance of the bankruptcy prediction models is an empirical question. The aim of this paper is to develop a bankruptcy prediction model for Indian manufacturing companies on a sample of 208 companies consisting of an equal number of defaulted and non-defaulted firms. Out of 208 companies, 130 are used for estimation sample, and 78 are holdout for model validation. The study reestimates the accounting based models such as Altman EI (Journal of Finance 23: 19189–209, 1968) Z-Score, Ohlson JA (Journal of Accounting Research 18:109–131, 1980) Y-Score and Zmijewski ME (Journal of Accounting Research 22:59–82, 1984) X-Score model. The paper compares original and re-estimated models to explore the sensitivity of these models towards the change in time periods and financial conditions. Methods Multiple Discriminant Analysis (MDA) and Probit techniques are employed in the estimation of Z-Score and X-Score models, whereas Logit technique is employed in the estimation of Y-Score and the newly proposed models. The performance of all the original, re-estimated and new proposed models are assessed by predictive accuracy, significance of parameters, long-range accuracy, secondary sample and Receiver Operating Characteristic (ROC) tests. Results The major findings of the study reveal that the overall predictive accuracy of all the three models improves on estimation and holdout sample when the coefficients are re-estimated. Amongst the contesting models, the new bankruptcy prediction model outperforms other models. Conclusions The industry specific model should be developed with the new combinations of financial ratios to predict bankruptcy of the firms in a particular country. The study further suggests the coefficients of the models are sensitive to time periods and financial condition. Hence, researchers should be cautioned while choosing the models for bankruptcy prediction to recalculate the models by looking at the recent data in order to get higher predictive accuracy. © The Author(s). 2016
abstractGer	Background The suitability and performance of the bankruptcy prediction models is an empirical question. The aim of this paper is to develop a bankruptcy prediction model for Indian manufacturing companies on a sample of 208 companies consisting of an equal number of defaulted and non-defaulted firms. Out of 208 companies, 130 are used for estimation sample, and 78 are holdout for model validation. The study reestimates the accounting based models such as Altman EI (Journal of Finance 23: 19189–209, 1968) Z-Score, Ohlson JA (Journal of Accounting Research 18:109–131, 1980) Y-Score and Zmijewski ME (Journal of Accounting Research 22:59–82, 1984) X-Score model. The paper compares original and re-estimated models to explore the sensitivity of these models towards the change in time periods and financial conditions. Methods Multiple Discriminant Analysis (MDA) and Probit techniques are employed in the estimation of Z-Score and X-Score models, whereas Logit technique is employed in the estimation of Y-Score and the newly proposed models. The performance of all the original, re-estimated and new proposed models are assessed by predictive accuracy, significance of parameters, long-range accuracy, secondary sample and Receiver Operating Characteristic (ROC) tests. Results The major findings of the study reveal that the overall predictive accuracy of all the three models improves on estimation and holdout sample when the coefficients are re-estimated. Amongst the contesting models, the new bankruptcy prediction model outperforms other models. Conclusions The industry specific model should be developed with the new combinations of financial ratios to predict bankruptcy of the firms in a particular country. The study further suggests the coefficients of the models are sensitive to time periods and financial condition. Hence, researchers should be cautioned while choosing the models for bankruptcy prediction to recalculate the models by looking at the recent data in order to get higher predictive accuracy. © The Author(s). 2016
abstract_unstemmed	Background The suitability and performance of the bankruptcy prediction models is an empirical question. The aim of this paper is to develop a bankruptcy prediction model for Indian manufacturing companies on a sample of 208 companies consisting of an equal number of defaulted and non-defaulted firms. Out of 208 companies, 130 are used for estimation sample, and 78 are holdout for model validation. The study reestimates the accounting based models such as Altman EI (Journal of Finance 23: 19189–209, 1968) Z-Score, Ohlson JA (Journal of Accounting Research 18:109–131, 1980) Y-Score and Zmijewski ME (Journal of Accounting Research 22:59–82, 1984) X-Score model. The paper compares original and re-estimated models to explore the sensitivity of these models towards the change in time periods and financial conditions. Methods Multiple Discriminant Analysis (MDA) and Probit techniques are employed in the estimation of Z-Score and X-Score models, whereas Logit technique is employed in the estimation of Y-Score and the newly proposed models. The performance of all the original, re-estimated and new proposed models are assessed by predictive accuracy, significance of parameters, long-range accuracy, secondary sample and Receiver Operating Characteristic (ROC) tests. Results The major findings of the study reveal that the overall predictive accuracy of all the three models improves on estimation and holdout sample when the coefficients are re-estimated. Amongst the contesting models, the new bankruptcy prediction model outperforms other models. Conclusions The industry specific model should be developed with the new combinations of financial ratios to predict bankruptcy of the firms in a particular country. The study further suggests the coefficients of the models are sensitive to time periods and financial condition. Hence, researchers should be cautioned while choosing the models for bankruptcy prediction to recalculate the models by looking at the recent data in order to get higher predictive accuracy. © The Author(s). 2016
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title_short	Re-estimation and comparisons of alternative accounting based bankruptcy prediction models for Indian companies
url	https://dx.doi.org/10.1186/s40854-016-0026-9
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