Assessing Financial Distress and Predicting Stock Prices of Automotive Sector: Robustness of Altman Z-score

Amit Sareen and Sudhi Sharma

Vision, 2022, vol. 26, issue 1, 11-24

Abstract: After the advent of a new economic policy, the stock market had shown exponential growth. The world’s financial markets have become a global financial village via the free flow of capital from one market to another. This provides breadth and depth in the stock market. On the other hand, with the dawn of globalization, the market has become cointegrated and thus more vulnerable to financial shocks. Thus, as a rational investor, catching early signs of financial distress and predicting stock prices is the challenge. This study considers the Altman Z -score to predict the financial distress and stock prices with special reference to the automotive sector in India. The study has been conducted in two parts: the first part focuses on analysing the financial distress of the automotive sector under the face of the financial crisis and GST regime. Thus, this study has been conducted in four window periods. The second part of the study deals with predicting the prices of auto stocks by panel data modelling for the period from 2000 to 2020. Using econometric-based growth curves, the study analyses that the automotive sector is affected by the financial crisis and the GST regime. Lastly, with the application of the panel data static-based fixed effects model, it has been analysed that EBITDA/TA and MV/TL are the significant ratios to predict the stock prices.

Keywords: Altman Z Score; Automotive Sector; Stock Prices; GST; Panel Data; Fixed Effect Model (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:vision:v:26:y:2022:i:1:p:11-24

DOI: 10.1177/0972262921990923

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