Document Type : Research Paper

Authors

• Gholamhossein Mahdavi ¹
• Kazem Goodarzi ²

¹ Associate Professor of Accounting, Shiraz University, Iran

² M. S. in Accounting, Shiraz University, Iran

Abstract

The purpose of this study is to introduce an artificial neural model for
predicting systematic risk of Saipa Company by using macro
economic variables. The net used in the study is a neural feedforward
network with backpropagation algorithms. Price Index in Tehran
Stock Exchange, Exchange Rate, Oil Price and Gold Price have been
considered as four input variables, and the systematic risk as the
output variable. The relevant data for each variable has been set
weekly and monthly, and based on the data, 80 different neural
networks were designed.
The results show that the optimal model for predicting weekly
systematic risk is a four- layer- model with the Root- Mean- Square
(RMS) of 0/033314. Furthermore, the optimal model for predicting
monthly systematic risk is a three- layer- model with the RMS of
0/065557.

Keywords

• Systematic Risk
• Artificial Neural Network
• Macro Economic Variables