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http://dx.doi.org/10.15722/jds.20.10.202210.61

Predicting Financial Distress Distribution of Companies  

VU, Giang Huong (Hanoi Open University)
NGUYEN, Chi Thi Kim (Hanoi University of Business and Technology)
PHAM, Dang Van (Hanoi University of Business and Technology)
TRAN, Diu Thi Phuong (Academy of Finance)
VU, Toan Duc (Central Capital)
Publication Information
Journal of Distribution Science / v.20, no.10, 2022 , pp. 61-66 More about this Journal
Abstract
Purpose: Predicting the financial distress distribution of an enterprise is important to warn enterprises about their future. Predicting the possibility of financial distress helps companies have action plans to avoid the possibility of bankruptcy. In this study, the author conducted a forecast of the financial distress distribution of enterprises. Research design, data and methodology: The forecasting method is based on Logit and Discriminant analysis models. The data was collected from companies listed on Vietnam Stock Exchange from 2012 to 2020. In which there are both companies suffer from financial distress and non-financial distress. Results: The forecast analysis results show that the Logistic model has better predictability than the Discriminant analysis model. At the same time, the results also indicate three main factors affecting the financial distress of enterprises at all three research stages: (1) Liquidity, (2) Interest payment, and (3) firm size. In addition, at each stage, the impact of factors on financial distress differs. Conclusions: From the results of this study, the author also made several recommendations to help companies better control company operations to avoid falling into financial distress. Adjustments to current assets, debt, and company expansion considerations are the most important factors for companies.
Keywords
Financial Distress Distribution; Financial distress; Forecasting; Logit; Discriminant Analysis;
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