Bankruptcy

One of the major challenges faced by major firms is the risk of financial instability and ultimately financial bankruptcy. Hence, the main objective of this paper is to predict bankruptcy based on real Earning management models and the accrual Earning management of companies admitted to the Tehran Stock Exchange. The research method is descriptive-applied and is a correlation study. The time domain of research was between 1382 and 1395, with a sample of 110 companies (65 bankrupt and 65 non-bankrupt companies) selected from the list of companies admitted to the Tehran Stock Exchange. Logistic regression model was used to test the research hypotheses. In general, the findings of the research hypothesis test show that the predictive power of bankruptcy models based on real profit management models and accruals management of companies accepted in Tehran Stock Exchange is significant. Therefore, it can be stated that the amount of real earning management and accrual earnings management affect the bankruptcy of the investigated companies.

The main purpose of this research is to explain why and how the stock liquidity affects the default risk of petrochemical and petroleum products companies listed in Tehran Stock Exchange. The study used experimental data and parametric tests in order to estimate the relationship between stock liquidity and default risk through information efficiency and corporate governance roles of stock liquidity. The present research is applied in terms of purpose and is a descriptive-correlative study. All data required regarding the stock liquidity, price, trading volume and days, stockholder ownerships, etc., were extracted from Rahavard Novin database software. To investigate the relationship between variables, the multivariate regression analysis model using OLS method was applied in Eviews platform. The empirical findings showed that there is a significantly negative relationship between stock liquidity and default risk of petrochemical and petroleum product companies listed in TSE and also stock liquidity can affect the default risk through reducing the information asymmetry in the stock pricing process and strengthen the corporate governance. These results could provide visible signals based on the realities of the market in order to improve models to assess and predict the risk of default and lead managers and decision makers of suppliers, customers, partners and stakeholders, to conclude more flexible contracts with petrochemical and petroleum products companies and ultimately better mitigate business risks.

In a volatile economic environment, financial decision making is always associated with risk. Bankruptcy, as one of the most important risks, has a significant impact on the interests of the firm's stakeholders, so presenting appropriate bankruptcy forecasting patterns is of the utmost importance. In this study, after reviewing the theoretical literature and selecting the financial ratios used in previous bankruptcy prediction models as the variable input of the initial model, the financial ratios were adjusted based on the price index and then, using the LARS algorithm, the ratios that have the highest ability to differentiate between bankrupt and non-bankrupt firms were identified, and finally, using the SVM and Naive Bayesian algorithms, the final bankruptcy prediction model was developed. For this purpose, the data of 50 companies listed in Tehran Stock Exchange who had experienced bankruptcy for at least one year from 2008 to 2018 under Article 141 of the Commercial Code were used. The results show that the adjusted financial ratios based on the price index in the model presented by SVM algorithm can be a very good predictor for bankruptcy of companies with an accuracy of 99.4%.

In this research, the relationship between accruals quality and bankruptcy of companies has been studied. According to Dechow et al.'s (1995) model, the quality of accruals was measured, and according to the Shirata model (1998), bankruptcy was examined. Operations were considered as the control variables. The research hypothesis was tested using a multivariate regression model and a combined data method. The study's statistical sample consists of 197 companies listed on the Tehran Stock Exchange from 2011 to 2019. The results showed a significant and negative relationship between the quality of accruals and bankruptcy of the companies. It means that in bankruptcy, the use of earnings management through optional accruals reduces the quality of accruals. The results indicate that size, return on assets, and audit quality all significantly impact the quality of accruals. Besides, the leverage, life, and operating cash flow have a significant and negative effect on accruals' quality. However, the ratio of market value to book value does not significantly affect the quality of accruals.