NDLI: Predicting Firms' Financial Distress: An Empirical Analysis Using the F-Score Model

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Predicting Firms' Financial Distress: An Empirical Analysis Using the F-Score Model

Content Provider	MDPI
Author	Rahman, Mahfuzur Sa, Cheong Masud, Abdul Kaium
Copyright Year	2021
Description	Financial performance of firms is very important to bankers, shareholders, potential investors, and creditors. The inability of firms to meet their liabilities will affect all its stakeholders and will result in negative consequences in the wider economy. The objective of the study is to explore the applicability of a distress prediction model which uses the F-Score and its components to identify firms which are at high risk of going into default. The study incorporates a prediction model and vast literature to address the research questions. The sample of the study is collected from publicly listed firms of the United States. In total, 81 financially distressed firms wereextracted from the UCLA-LoPucki Bankruptcy Research Database during 2009–2017. This study found that the relationship of the F-Score and probability of firms going into financial distress is significant. This study also demonstrated that firms which are at risk of distress tend to record a negative cash flow from operations (CFO) and showed a greater decline in return on assets (ROA) in the year prior to default. This study extends the existing literature by supporting a model which has not been widely used in the area of financial distress predictions.
Starting Page	199
e-ISSN	19118074
DOI	10.3390/jrfm14050199
Journal	Journal of Risk and Financial Management
Issue Number	5
Volume Number	14
Language	English
Publisher	MDPI
Publisher Date	2021-05-01
Access Restriction	Open
Subject Keyword	Journal of Risk and Financial Management Applied Ethics F-score Bankruptcy Prediction Financial Distress Prediction Logistic Regression Accounting-based Bankruptcy
Content Type	Text
Resource Type	Article

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