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

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. According to the findings, it is concluded that bank's grant facilities to government and non-government sectors and non-bank credit institutions will increase the industry index and stock price index. In the case of some stock companies, the government even needs to take some actions itself and manage the bankrupt enterprises by granting facilities and improve their status on the stock market. Also, according to the research findings, the growth of automotive industry results in the growth of the financial index, and for this purpose, policymakers should pay particular attention to the automotive industry. Finally, given the results of this study, longer periods of time for future research and the use of other predictive methods as well as artificial intelligence are emphasized.
Introduction Investors and managers of the stock market make use of stock indices in order to achieve a good picture of the process of this market and the ability to evaluate past and, in some cases, to predict the future. A more detailed analysis of the price trend in stock markets requires indices with a variety of functions. As a result, today a wide variety of indices are calculated and published in the Iranian Stock Exchange. The methods of calculating the indices have undergone several changes in the direction of more efficiency and providing a more precise representation of the stock trading process. Naturally, there are a bulk of factors involved in shaping the information and views of the parties to the market and, ultimately, the stock prices of the companies. Some part of these factors is indigenous and some other is due to the status of variables outside the scope of the domestic economy of the company. Accordingly, the factors affecting stock prices are wide. On the other hand, each country's economic development depends on the money and capital markets in each country's economy. Given the importance of capital market in equipping community savings towards economic activities, identifying variables that affect the stock price index is quintessential. In this research, we have been trying to fill this gap in the financial literature of our country. Despite the fact that most previous research voluntarily selected a number of variables and examined their effects on the stock price index, in this research, optimal and effective variables in types of stock index is derived using the genetic function approximation. This research investigates the factors affecting price index, financial index, industry index, price index and cash returns, which is, in this regard, innovative compared to other studies.
Case study The data of the statistical population was collected from the Central Bank website from 1997 to 2014. Since there are a lot of factors affecting Tehran Stock Exchange index. These factors include exports, current account balance, capital account balance, monetary and credit variables, payments and receipts of government and stock transactions, energy sector, manufacturing and mining sector, housing and construction sector, transportation, and agricultural sector. Modeling was performed for the factors influencing the stock price index, stock price and cash return index, financial index, and industry index to determine the variables effective on all types of stock market indices.
Materials and Methods Using the genetic function approximation algorithm and running the MSmodeling software, modeling was performed for factors influencing the stock price index, stuck price index and cash return, financial index, industry index to determine which of the 108 independent variables are effective on the types of stock indices. An independent variable is added to the model and the optimal regression model is presented until no significant change, based on R2 or LOF criteria, is observed in the final model.
Discussion and Results In a nutshell, it can be postulated that monetary and credit variables have been effective on stock price index and stock return, industry index, and stock price index, in which an increase in liquidity in the society leads to a decrease in the price index and stock return in the stock market. Banking grants to government and non-government sectors and non-bank credit institutions have boosted the industry's index in the stock market. The monetary base and the facilities granted by banks to government and non-government sectors as well as short-term investment deposits also affected the stock price index. Furthermore, the effective stock variables are effective on a variety of indices. This means that the increase in the number of buyers in the stock market has reduced the price index and stock returns. The increase in the number of shares traded and the buyer in the stock market increases the financial index. The variables of the number of traded shares, the value of transactions and the number of buyers increased the industry index and the stock price index.
Conclusion According to the findings, it is concluded that bank's grant facilities to government and non-government sectors and non-bank credit institutions will increase the industry index and stock price index. In the case of some stock companies, the government even needs to take some actions itself and manage the bankrupt enterprises by granting facilities and improve their status on the stock market. Also, according to the research findings, the growth of automotive industry results in the growth of the financial index, and for this purpose, policymakers should pay particular attention to the automotive industry. Finally, given the results of this study, longer periods of time for future research and the use of other predictive methods as well as artificial intelligence are emphasized.