Provide a Earnings Management forecasting model using ant colony and particle swarm algorithm algorithms

This study aims to use two ant colony algorithm and particle swarm algorithm to predict earning management and determine which algorithm has more explanatory power.To achieve the research goal, 163 companies have been selected by systematic elimination method in the period 2013-2019. The data are panel and thirteen variables have been considered to examine the models. Finally, eight variables have been identified as effective and tests have been performed using Python software. The results show that earnings management can be predicted with more than 97% accuracy by both algorithms, but the ability to predict the particle swarm model in accrual earnings management is higher, however ant colony algorithm has more power in predicting real earnings management.