Corporate Default Prediction Model: Evidence from the Indian Industrial Sector (Record no. 133678)

MARC details
000 -LEADER
fixed length control field 02072nas a2200205Ia 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 240802c99999999xx |||||||||||| ||und||
022 ## - INTERNATIONAL STANDARD SERIAL NUMBER
International Standard Serial Number 0972-2629
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name H, Shilpa Shetty
9 (RLIN) 120278
245 #0 - TITLE STATEMENT
Title Corporate Default Prediction Model: Evidence from the Indian Industrial Sector
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Name of publisher, distributor, etc. Vision
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Date of publication, distribution, etc. 2024
300 ## - PHYSICAL DESCRIPTION
Extent 344-360
520 ## - SUMMARY, ETC.
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.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Financial Distress
9 (RLIN) 120279
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Indian Industrial Sector
9 (RLIN) 120280
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Insolvency and Bankruptcy
9 (RLIN) 120281
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element COVID-19
9 (RLIN) 118594
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Vincent, Theresa Nithila
9 (RLIN) 120282
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1177/09722629211036207">https://doi.org/10.1177/09722629211036207</a>
999 ## - SYSTEM CONTROL NUMBERS (KOHA)
Koha biblionumber 133678
Holdings
Withdrawn status Lost status Damaged status Not for loan Home library Current library Date acquired Serial Enumeration / chronology Total Checkouts Barcode Date last seen Price effective from Koha item type
        Dr VKRV Rao Library Dr VKRV Rao Library 02/08/2024 Vol. 28, No. 3   AI331 02/08/2024 02/08/2024 Article Index