Designing an evaluation model for credit rating of Islamic securities with a Adaptive Neuro-Fuzzy network approach

Subject Areas : Financial engineering

Mohammad  Shabani varnami ¹ (Department of financial management, Aliabad Katoul branch, Islamic Azad University, Aliabad Katoul, Iran)
Hosein  Didehkhani ² (Department of Financial engineering, Aliabad Katoul branch, Islamic Azad University, Aliabad Katoul, Iran,)
Ali  khozain ³ (Department of Accounting, Aliabad Katoul branch, Islamic Azad University, Aliabad Katoul, Iran)
arash  naderian ⁴ (Department of Accounting, Aliabad Katoul branch, Islamic Azad University, Aliabad Katoul, Iran)

Received: 2020-02-29 Accepted : 2020-07-16 Published : 2021-03-21

Keywords: fuzzy logic, Neural network, Credit rating, Islamic securities, Adaptive Neuro-Fuzzy Network,

Abstract :

The purpose of this research is designing a credit rating model for issuers and tools for financing Islamic securities in the Iranian capital market. To do this, three major steps were taken. The first step was to identify the evaluation criteria or the risks associated with the Islamic securities, which was carried out by the experts and a review of theoretical basics. The second step, is modeling of Islamic securities using adaptive-network-based fuzzy approach in which the mean error of the training of all main and subset models was below the threshold. The third step is to apply adaptive fuzzy neural network modeling in credit rating of Islamic securities. In order to do this, the issuer’s ranking was used in the first stage and the results of the research showed that the issuer of the government had the least risk and private companies had the highest risk. In the second stage, for ranking financial instruments, the results showed that for issuer of government, treasury bonds had the lowest risk and forward bonds had the highest risk. For the issuer of state-owned companies, the forward bonds had the highest risk and lease bonds had the lowest risk.