Investigating impact of Enterprise Risk Management (ERM) on the bankruptcy risk, using weed and particles swarm optimization algorithms

Enterprise risk management has a high impact on the improvement of a high-risk an organized culture of an organization in such a way, that it creates a transparent responsibility in relation to the enterprise risks like bankruptcy risk. Risk management operations, shift from a controlling role toward operative role and coordinator of risk management activities in such a way that the risks are clearly accepted by those who are responsible for decision making in the risk. Therefore, in this study has been paid to the assessment of Enterprise Risk Management (ERM) effect on bankruptcy risk using weed optimization and particles swarm optimization algorithms. To do this research a sample of 107 enterprises which are accepted in Tehran Stock Exchange are selected using sampling method. This study has been done in Tehran stock exchange in the period of 1392-1397. Multivariable regression using data panel and optimized algorithm is the implemented statistical method in this research. The result of this research shows that weed optimization and particles swarm optimization algorithms are capable of predicting bankruptcy risk using elements of ERM. In addition, comparing these two methods of optimization, particles swarm optimization is more efficient in the prediction of bankruptcy risk using ERM variable