Bankruptcy Prediction Models: An Empirical Comparison
Arpita Agarwal1, Ity Patni2

1Arpita Agarwal, Department of Business Administration, Manipal University Jaipur, India.

2Ity Patni, Department of Business Administration, Manipal University Jaipur, India.

Manuscript received on 10 April 2019 | Revised Manuscript received on 17 April 2019 | Manuscript Published on 24 May 2019 | PP: 131-139 | Volume-8 Issue-6S3 April 2019 | Retrieval Number: F22230486S219/19©BEIESP

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Abstract: The study is intended to evaluate the significance of bankruptcy prediction models. The corporate bankruptcy prediction is an ongoing area of interest in the recent past for which efforts are put to compare five bankruptcy models named Springate, Ohlson, Zmijewski, Grover and Altman. The aim of this research is to identify the best model fit for bankruptcy prediction through comparative analysis in empirical application. Approach-Through an extensive literature review, this study provides a comprehensive analysis of the methodologies and empirical findings from these models in their applications across different bankrupted or likely to be bankrupted companies. Findings-Our empirical findings on the comparison between the bankruptcy prediction models suggests the investor that they might choose any significant model to analyze the companies performances but the Springate and Zmijewski models are found to be the best models which gives early predictions and can be used to avoid the loss for investing money in bankrupted companies. Originality- It is anticipated that this study will be the most extensive to-date review in this field of literature. This paper shed light on the problem of model choice in empirical bankruptcy prediction of corporates and suggesting some directions and scope for future research.

Keywords: Altman; Bankruptcy Prediction; Grover; Ohlson; Springate; Zmijewski.
Scope of the Article: Big Data Analytics and Business Intelligence