مطالب مرتبط با کلیدواژه

Bankruptcy Risk


۱.

The Effect of Customers Concentration on Company Risks(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Customer concentration stock price Crash risk Bankruptcy Risk employment risk

حوزه های تخصصی:
تعداد بازدید : ۴۱۳ تعداد دانلود : ۲۱۳
The companies with major customers can supply a considerable source of cash flows by selling a large portion of their products to them. Since the lack of purchase, loss, or bankruptcy of major customers can result in a significant reduction in cash flows in the company, thus the risk is the companies with major customers is higher than other companies. Thus, the present study aimed to investigate the effect of customer concentration on company risks. For this purpose, the effect of customer concentration on three criteria of stock price crash risk, bankruptcy risk, and employment risk was studied. The research sample included 127 companies listed in the Tehran Stock Exchange during 2011-2018. Multivariate regression models with panel data were used by the random-effects method to test the research hypotheses. The research findings indicated that customer concentration has a significant positive effect on stock price crash risk, bankruptcy risk, and employment risk. In other words, stock price crash risk, bankruptcy risk, and employment risk are higher in the companies where the concentration of major customers is higher. 
۲.

Analyzing the performance of DEA models for bankruptcy prediction in the energy sector: with emphasis on Dynamic DEA approach(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Bankruptcy Risk Data Envelopment Analysis Bankruptcy Prediction Models Dynamic Data Envelopment Analysis

حوزه های تخصصی:
تعداد بازدید : ۱۱۳ تعداد دانلود : ۱۱۸
Predicting bankruptcy risk is one of the most critical issues in corporate financial decision-making. Investors always try to predict the bankruptcy of a firm to reduce the risk of losing their assets, so they are looking for ways by which they can predict the risk of bankruptcy. We predict the position of companies active in the oil and gas industry based on their financial health in the 2020 ranking of S&P global up to three years before 2020. This study uses three data envelopment analysis models (CCR, BCC, and DDEA) and the traditional Altman model for forecasting. We have shown that dynamic data envelopment analysis is a powerful tool for predicting bankruptcy risk.