Corporate Financial Distress Prediction in China – A Robustness Testing of ZCHINA-Score Model

Chen, Xiao (2014) Corporate Financial Distress Prediction in China – A Robustness Testing of ZCHINA-Score Model. Masters thesis, INTI International University.

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Abstract

Prior to 1990s, the application of financial distress prediction for companies in China is rather limited. Later in post 1990s, the popularity of Z-Score Model soared as a movement was initiated among Chinese researchers to adapt and to apply Altman Z-score model towards local Chinese companies. Poor prediction result experienced by the initial movement has prompted the original author of Altman z-score model, Edward I. Altman to team up with two Chinese scholars (Zhang and Yen, 2010) to develop an entirely new financial distress prediction model, known as the Zchina-Score Model, specifically for China’s companies. This study is to investigate the robustness of Zchina-Score Model towards current financial data as well as its robustness towards financial data from different industries. The empirical results of this study concludes that generally the Zchina-score model is a robust model for business stakeholders to refer to when making business decision. However, the prediction accuracy varies in different industries, which business stakeholders should be aware of when using this model. The result also implies that the Zchina-score model should be modified for each homogenous industry to achieve better prediction accuracy.

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