Designing Prediction Model of Financial Restatements Using Neural-Genetic Simulation Algorithm

Advances in Mathematical Finance and Applications

مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 10 تیر 1402

نوع مقاله: Research Paper

شناسه دیجیتال (DOI): 10.22034/amfa.2023.1973028.1824

نویسندگان

sasan MEHRANI¹؛ akbar rahimi poor^{* 2}

¹a Associate Professor of Accounting, University of Tehran, Tehran, Iran

²Ph.D. Student in Accounting, Tehran University Alborz Campus, Tehran, Iran.

چکیده

The increased number of restatements in recent years has increased the worries about the quality of financial reporting among the beneficiary groups. The pres-ence of prior period adjustments and, subsequently, the financial restatements have a negative impact on the relatedness and reliability of the financial state-ments. The present study is aimed to present an appropriate criterion for predict-ing the financial restatements based on the Beneish model (1999) and its indices in companies admitted to the Tehran Stock & Exchange between 2009 and 2020. For this purpose, a total of 265 companies were selected considering the limita-tions. Also, the model estimation was performed using Beneish's primary model, a meta-heuristic neural network model, and optimization through genetic pro-gramming. As indicated by the obtained results based on the confusion matrix, the efficiency of the proposed model derived from the enhanced Beneish model (1999) with a genetic algorithm had a total prediction accuracy of 73.21%, which was the highest prediction power compared to the Beneish Model (1999)

کلیدواژه‌ها

Prediction؛ Financial Restatement؛ Beneish Model؛ Meta-Heuristic Models