Identifying and Explaining the Factors Affecting the Fiscal Discipline of Companies Accepted in Tehran Stock Exchange Using Artificial Neural Network

Fiscal discipline provides a mechanism for maintaining financial health and a favorable vision for listed companies by matching revenue and expenses with goal achievement programs (GAP), which, if realized, can ensure the success of these companies. Thus, this study was carried out aimed to identify and explain the factors affecting the fiscal discipline of companies listed on the Tehran Stock Exchange. The present study is considered as an applied research in terms of purpose and as a descriptive survey research in terms of method. In this study, population is listed companies that 114 companies have been selected as a sample using systematic sampling method. Analysis of research data was done using Artificial Neural Network (ANN) and two-layer perceptron and Matlab software. The results show that the most important factors affecting fiscal discipline include financial health, financial stability, debt growth rate, capital expenditures, profitability, and firm value and information uncertainty of companies.