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Corporate Default Prediction Model: Evidence from the Indian Industrial Sector (Record no. 130246)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02095nam a22001817a 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 241114b |||||||| |||| 00| 0 eng d |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Shilpa Shetty H. |
| 245 ## - TITLE STATEMENT | |
| Title | Corporate Default Prediction Model: Evidence from the Indian Industrial Sector |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | p344-360 |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. biblio.abstract | The unprecedented pandemic COVID-19 has impacted businesses across the globe. A significant jump in the credit default risk is expected. Credit default is an indicator of financial distress experienced by the business. Credit default often leads to bankruptcy filing against the defaulting company. In India, the Insolvency and Bankruptcy Code (IBC) is the law that governs insolvency and bankruptcy. As reported by the Insolvency and Bankruptcy Board of India (IBBI), the number of companies filing for bankruptcy under IBC is on a rise, and the industrial sector has witnessed the maximum number of bankruptcy filings. The present article attempts to develop a credit default prediction model for the Indian industrial sector based on a sample of 164 companies comprising an equal number of defaulting and nondefaulting companies. A total of 120 companies are used as training samples and 44 companies as the testing samples. Binary logistic regression analysis is employed to develop the model. The diagnostic ability of the model is tested using receiver operating characteristic curve, area under the curve and annual accuracy. According to the study, return on assets, current ratio, debt to total assets ratio, sales to working capital ratio and cash flow to total assets ratio is statistically significant in predicting default. The findings of the study have significant implications in lending and investment decisions. |
| 654 ## - SUBJECT ADDED ENTRY--FACETED TOPICAL TERMS | |
| Subject | <a href="Banrulptcy">Banrulptcy</a> |
| -- | <a href="Credit Default">Credit Default</a> |
| -- | <a href="IBC">IBC</a> |
| -- | <a href="Inida">Inida</a> |
| -- | <a href="Financial Ratios">Financial Ratios</a> |
| -- | <a href="Logistic">Logistic</a> |
| -- | <a href="Regression">Regression</a> |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Theresa Nithila Vincent |
| 773 0# - HOST ITEM ENTRY | |
| Host Biblionumber | 80316 |
| Host Itemnumber | 110092 |
| Place, publisher, and date of publication | New Delhi Sage Publications |
| Title | Vision: The Journal of Business Perspectives |
| International Standard Serial Number | 0972-2629 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Journal Article |
| 773 0# - HOST ITEM ENTRY | |
| -- | JP351 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| -- | ddc |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Location (home branch) | Sublocation or collection (holding branch) | Date acquired | Koha issues (times borrowed) | Piece designation (barcode) | Koha date last seen | Price effective from | Koha item type |
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| Dewey Decimal Classification | SNDT Juhu | SNDT Juhu | 14/11/2024 | JP351.4 | 14/11/2024 | 14/11/2024 | Journal Article |