particle aggregation algorithm

Credit ratings are an overall judgment of an issuer’s ability and willingness to meet its financial obligations in accordance with the terms of those obligations. Since this overall judgment is based on a complex, in-depth analysis of quantitative as well as qualitative information of the rated firm, Therefore, it is sensitive to the published information of the company. Independent auditors, meanwhile, play an important role in ensuring that financial information is free from material misstatement. Thus, the purpose of this study is to investigate the characteristics of an independent auditor on the credit rating using a particle aggregation algorithm. Therefore, to achieve the research goal, with 101 sample companies in a period of 9 years from 2011 to 2019 were collected and Credit rating was measured by the emerging market score model and auditor characteristics were measured by the size and expertise of the auditor in the industry. The research hypothesis was analyzed using the least squares optimization method of perturbation sentences using particle aggregation optimization (PSO) algorithm. The statistical test related to the results indicates a significant relationship between the characteristics of the independent auditor and the credit rating.