Monetary & Financial Economics

Abstract ‎Investing in stocks offered on the stock exchange is one of the most lucrative investments in the financial and capital markets‏. However, stock price behavior is one of the most complex mechanisms that researchers have studied. This market always shows unpredictable, chaotic, and non-linear behavior because it is affected by economic, political, and industrial conditions. In this paper, we try to predict the closing price of the share in the coming days by using Multilayer Perceptron Neural Networks and Elman. The weights of the neural networks used in this work are optimized using the squirrel search algorithm, which increases the speed and accuracy of the neural networks. The results are evaluated by MSE, RMSE, MAE, and MAPE criteria. Also, the proposed method is compared with Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Grey Wolf Optimization (GWO), and Artificial Bee Colony (ABC) metaheuristic algorithms to show that the optimization of network weights using squirrel search algorithm averages 72% for Iran Telecommunication Companies, National Iranian Copper Industries, Pars International Products, Ghadir Holding and India Steel has better results than other methods. In comparison with the multilayer perceptron neural network with Elman neural network, Elman neural network has an average of 27% better results than the multilayer perceptron neural network.

Abstract The interaction between the stock market and the elements of the economic system has always been one of the important issues in Iran's economy On the other hand, considering that Iran is an oil exporting country, oil price changes have always been one of the important factors of economic fluctuations in Iran. These fluctuations affect the financial markets, especially the stock market. The main goal of this research is to investigate the effect of oil price fluctuations and economic policy uncertainty on stock returns in Iran. In this research, in order to investigate the relationships between variables, seasonal data during the period from 1392:1 to 1400:4 and the Autoregressive distributed lag model have been used. The research findings indicate that economic policy uncertainty has a negative and significant effect on stock returns in Iran. Also, the two variables of oil price fluctuations and real effective exchange rate have a positive and significant relationship with stock returns in Iran. On the other hand, economic policy uncertainty, interest rate and industrial production index have a negative and significant relationship with stock returns in Iran. Therefore, it is recommended to reduce the dependence of the country's budget on oil revenues, and also, the stock exchange organization should take the necessary measures to reduce the effects of economic policy uncertainty on the overall index of the stock exchange.

Abstract Purpose: The main purpose of this study is to investigate the effect of macroeconomic variables, economic sanctions and global commodity price index on the price index of banks and credit institutions in Iran's capital market.
Method: This study is using time series data with monthly frequency during the period of 1387-1400 and using the auto-regression approach with distribution breaks (ARDL) of the estimated model. Also, the edge test was used to test the convergence of the model.
Findings: The results of the model estimation indicate that in the dynamic model, the price index of the banks and credit institutions group is significantly affected by the examined variables, and based on the collocation test, the existence of a long-term relationship was also confirmed; That is, in the long term, the price index of the group of banks and credit institutions is significantly affected by the macroeconomic variables and the global price index of commodities. The results of the error correction model have shown that any imbalance in the model moves towards balance in the long term and it takes less than two years for the short-term balance error to be corrected and the model to return to its long-term balance.
Innovation: Previous studies to examine external factors have generally considered macroeconomic variables, while Iran's capital market is a commodity-oriented market, and on the other hand, Iran's economy is affected by economic sanctions, so in the current research, in addition to the impact of macroeconomic variables, the impact of economic sanctions And the global price index of commodities has been checked on the price index of the group of banks and credit institutions.