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https://idr.l4.nitk.ac.in/jspui/handle/123456789/14539
Title: | An Exploratory Analysis of Financial Distress and Default – A Study of Select Indian Companies |
Authors: | Shridev |
Supervisors: | K. R, Suprabha |
Keywords: | School of Management;Financial factors;Corporate governance;Altman Z Score;Logistic Regression |
Issue Date: | 2019 |
Publisher: | National Institute of Technology Karnataka, Surathkal |
Abstract: | The issue of non-performing assets is one of the biggest issues faced by the Indian banking industry in the recent past. The default is due to the financial distress which is built over a period of time. The model to understand and the financial distress would be helpful to solve this issue. This study examines whether the financial default can be predicted using the financial and non-financial factors using the sample Indian companies. The four main categories of financial ratios are profitability, liquidity, activity and leverage ratios. The non-financial variables considered are company age, proportion of independent directors to the total, promoter shareholding, duality in leadership, board size, institutional and non-institutional variables. Multiple regression was applied to study the impact of financial ratios on financial distress. Logistic regression analysis was applied to study the impact of non-financial factors on financial distress. The investors or potential investors can benefit from these findings on financial distress prediction because these findings would enable them to better assess the probability of the companies experiencing financial distress in the near future. One financial distress model which included financial factors and another financial distress model which included non-financial factors were constructed in the method section. Based on these two models, the present study developed a financial distress prediction model, which used not only financial factors but also non-financial factors. Further, the event study methodology was adopted to the stock market announcement on financial distress. The investors or potential investors and lenders can benefit from these findings on financial distress prediction because these findings would enable them to better assess the probability of the companies going to experience financial distress in the near future. |
URI: | http://idr.nitk.ac.in/jspui/handle/123456789/14539 |
Appears in Collections: | 1. Ph.D Theses |
Files in This Item:
File | Description | Size | Format | |
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145083HM14F04.pdf | 2.9 MB | Adobe PDF | View/Open |
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