Modeling a Variety of Indices of Iranian Stock Exchange Using Genetic Function Approximation Algorithm

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HASHEMITABAR MAHMOUD; DADRASMOGHADAM AMIR; HOSSEINI SEYED MEHDI; MORADI EBRAHIM

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Journal: PUBLIC MANAGEMENT RESEARCHES Year:2017 | Volume:10 | Issue:37 Page(s): 107-128

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Title

Modeling a Variety of Indices of Iranian Stock Exchange Using Genetic Function Approximation Algorithm

Author(s)

HASHEMITABAR MAHMOUD | DADRASMOGHADAM AMIR | HOSSEINI SEYED MEHDI | MORADI EBRAHIM | Issue Writer Certificate

Keywords

stock price indexQ1

stock price index and cash returnQ1

financial indexQ1

industry indexQ2

Generic Function Algorithm (GFA)Q1

Abstract

The most important issues in the stock market are stock indices. The main topic of this research is modeling the factors affecting stock price index, stock price and stock return index, financial index, and industry index in Iran's Stock Exchange. For this purpose, data of 112 macroeconomic and stock variables from 1997 to 2014 were used. Modeling has been done using the genetic function approximation algorithm. Using MSmodeling software has been modeled for the factors affecting the stock price index, the price index and cash returns of the stock exchange, the financial index, the industry index were used to determining 108 independent variables are effective on the types of stock indexes. The results indicate that the granting facilities of banks lead to an increase in the industry index in the stock market. The monetary base and the bank's facilities and short-term investment deposit are also effective on the stock price index. Moreover, the variables of the number of shares traded, the value of transactions, and the number of buyers increases the industry index and the stock price index.

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APA: Copy

HASHEMITABAR, MAHMOUD, DADRASMOGHADAM, AMIR, HOSSEINI, SEYED MEHDI, & MORADI, EBRAHIM. (2017). Modeling a Variety of Indices of Iranian Stock Exchange Using Genetic Function Approximation Algorithm. PUBLIC MANAGEMENT RESEARCHES, 10(37 ), 107-128. SID. https://sid.ir/paper/222100/en

Vancouver: Copy

HASHEMITABAR MAHMOUD, DADRASMOGHADAM AMIR, HOSSEINI SEYED MEHDI, MORADI EBRAHIM. Modeling a Variety of Indices of Iranian Stock Exchange Using Genetic Function Approximation Algorithm. PUBLIC MANAGEMENT RESEARCHES[Internet]. 2017;10(37 ):107-128. Available from: https://sid.ir/paper/222100/en

IEEE: Copy

MAHMOUD HASHEMITABAR, AMIR DADRASMOGHADAM, SEYED MEHDI HOSSEINI, and EBRAHIM MORADI, “Modeling a Variety of Indices of Iranian Stock Exchange Using Genetic Function Approximation Algorithm,” PUBLIC MANAGEMENT RESEARCHES, vol. 10, no. 37 , pp. 107–128, 2017, [Online]. Available: https://sid.ir/paper/222100/en

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