2016
DOI: 10.1956/jge.v12i2.418
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Indicators of financial distress - An empirical study of Indian Textile sector

Abstract:  AbstractBusinesses across the globe faces challenges to ensure stability, growth and sustainability. Companies have to deal with changes in economic, social, cultural, political and technological environment. Companies failing to do may face financial distress causing default in payment of contractual obligations and erosion of shareholders wealth. In a business scenario where the stakeholders are many viz. shareholders, lenders, employees, government and society at large, protection of the interests of the … Show more

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Cited by 3 publications
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“…Various studies used neural networks in their study and demonstrated that it produced better results, an overall classifying accuracy of 83% one year prior to the collapse period (Neophytou & Charitou, 2004; K. Tam, 1991;Wilson & Sharda, 1994;and Fletcher & Goss, 1993) . Among the various models, the logit model gained much prominence and various studies used logit models in their study for bankruptcy prediction (Tserng et al, 2014 ;Sun et al, 2014;and Nair & Sachdeva, 2018).…”
Section: Literature Reviewmentioning
confidence: 99%
“…Various studies used neural networks in their study and demonstrated that it produced better results, an overall classifying accuracy of 83% one year prior to the collapse period (Neophytou & Charitou, 2004; K. Tam, 1991;Wilson & Sharda, 1994;and Fletcher & Goss, 1993) . Among the various models, the logit model gained much prominence and various studies used logit models in their study for bankruptcy prediction (Tserng et al, 2014 ;Sun et al, 2014;and Nair & Sachdeva, 2018).…”
Section: Literature Reviewmentioning
confidence: 99%
“…However the validity of these models remains to be examined. Most of the studies have focused on application of Altman's 'z'score model and Ohlson's 'o' score model to Indian companies, [Bardia, (2012), Sarbapriya Ray, (2011), Nair, (2015, Panda and Bahera, (2015)]. Discriminant Analysis and Logistic Regression are the preferred statistical methods used in Indian context.…”
Section: Research In Indiamentioning
confidence: 99%
“…Most of the studies focused on the application of existing models to Indian companies to identify sickness [Panda and Bahera, (2015), Nair, (2015) Nair, (2013, Bardia, (2012), Kumar and Kumar, (2012), Sarbapriya Ray, (2011), Reddy andReddy, (2010)]. Some studies have attempted to identify factors indicating distress in various sectors [Nair and Sachdeva, (2016) Thus, in the wake of the current crisis in the manufacturing sector, a model predicting distress in Indian companies is the need of the hour. An in-depth study of the manufacturing sector to identify early warning signals can add immense value to managers, investors and bankers alike.…”
mentioning
confidence: 99%