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Open Access Article
1 - Modeling the Factors Affecting the Capital Structure in Companies Listed on the Tehran Stock Exchange, the Approach of Bayesian Averaging Model
Zahra Talebi Mohammad Sokhanvar Tahereh AkhoondzadehThe capital structure, meaning the way the company is financed, affects the value of the company, the relationship between the components of the capital structure, which is a mixture of bonds and stocks for financing, has a significant effect on the performance results MoreThe capital structure, meaning the way the company is financed, affects the value of the company, the relationship between the components of the capital structure, which is a mixture of bonds and stocks for financing, has a significant effect on the performance results of companies, the aim of the research is to model the factors affecting the capital structure in companies listed on the Tehran Stock Exchange (the approach of Bayesian averaging (BMA), This research is practical in terms of purpose and correlational in terms of nature. In order to achieve the goal of the research, 175 companies were selected from among the companies admitted to the Tehran Stock Exchange during the years 1390 to 1400 by systematic elimination method and considered as the main sample.In order to identify the most important variables affecting the capital structure, the BMA model has been used. Based on this, 61 identified variables affecting the capital structure were included in the Bayesian averaging model. These variables were divided into two categories of internal and external factors. Based on previous probabilities, 17 variables were identified as important variables on capital structure. Among these variables, 10 intra-company variables (type of ownership; net operating profit; current ratio; total assets turnover ratio; interest rate coverage ratio; debt-to-equity ratio; beta per share; accrual profit management; financial distress and tax) and 7 external variables (inflation, exchange rate, budget deficit, business climate index, economic resilience index, sanctions index, capital market depth) were effective on the capital structure Manuscript profile -
Open Access Article
2 - Explaining the Financial Factors Affecting Turnaround from the insolvency of Companies Listed on the Tehran’s Stock Exchange
kazem harounkolai Seyedali Nabavi chashmi ghodratolah barzegar iman dadashiThe aim of this paper is explaining the financial factors affecting turnaround from the insolvency. For explaining financial affecting turnaround from insolvency 54 variables were selected from relevant studies. The information of 200 cases of distressed companies which MoreThe aim of this paper is explaining the financial factors affecting turnaround from the insolvency. For explaining financial affecting turnaround from insolvency 54 variables were selected from relevant studies. The information of 200 cases of distressed companies which were under recovery from distress was extracted between 2001 and 2017. Appropriate statistical methods for the process of refining variables have been performed through paired mean comparison tests as well as exploratory factor analysis using main components. Then, by filtering the variables using audit analysis and in the form of linear combinations, audit functions were formed. The results showed that the financial ratios of current liabilities to total assets, net profits to sales and sales to current assets have the most power to explain the companies’ turnaround. Manuscript profile -
Open Access Article
3 - Design a Model for Measuring the Dynamics Volatility Connectedness of Tehran Stock Exchange and Global Markets
Nasser Gholami Teymor Mohammadi abdolrasoul ghasemiThe aim of this article is to measure the dynamics connectedness of Tehran stock market with stock exchanges of selected countries from the Middle East and China, oil and gold markets, the dollar index and the euro-dollar and yuan-dollar. To this end, a variance decompo MoreThe aim of this article is to measure the dynamics connectedness of Tehran stock market with stock exchanges of selected countries from the Middle East and China, oil and gold markets, the dollar index and the euro-dollar and yuan-dollar. To this end, a variance decomposition approach has been used to measure connectedness of markets between January 2008 and the end of July 2019. The findings show that the variance of forecast errors in most of markets are due to the shocks of those markets themselves. The Qatari Stock Exchange has a significant impact on Saudi and UAE stock exchanges. As the time horizon increases, Brent's oil market will be more influential than other markets, and this market will be more affected by the stock exchanges of the Arab countries and the Shanghai Composite. According to the results, investing in the Tehran Stock Exchange and the yuan-dollar exchange rate due to insignificant dynamics connectedness with other markets is recommended to hedge risk. Manuscript profile -
Open Access Article
4 - Investigating the relationship between oil price and Iran's stock market index with an emphasis on political uncertainty and the Corona pandemic: Using wavelet transform approach
nasim amin kharazian roya aleemran Rasoul baradaran hassanzadeh Amir Ali farhangThe purpose of this research is to investigate the relationship between crude oil prices and the stock market index of Iran in the period from September 2009 to December 2020. For this purpose, by using wavelet coherence approach based on continuous wavelet transform, t MoreThe purpose of this research is to investigate the relationship between crude oil prices and the stock market index of Iran in the period from September 2009 to December 2020. For this purpose, by using wavelet coherence approach based on continuous wavelet transform, the relationship between the yield pair series of Brent crude oil price-total stock index, WTI oil price-total stock index and OPEC oil price-total index of Tehran Stock Exchange has been investigated .The results of this research show that the dependence between the above pair of time series increases with the increase of uncertain conditions such as the increase of sanctions, the withdrawal of the United States from the JCPOA, and the corona pandemic in the medium and long term. Therefore, investors can adjust their investment portfolio in the long and medium term based on the conditions governing the country and their investment goals. Manuscript profile -
Open Access Article
5 - Explanation of Financial Variables Effective in Predicting Turnaround: An Artificial Intelligence Approach
Kazem Harounkolai Ghodratolah BarzegarThe main aim of the research was to identify the financial variables that are effective in predicting turnaround of the listed companies in the Tehran Stock Exchange and to predict turnaround by using artificial intelligence method. For this purpose, the information of MoreThe main aim of the research was to identify the financial variables that are effective in predicting turnaround of the listed companies in the Tehran Stock Exchange and to predict turnaround by using artificial intelligence method. For this purpose, the information of 173 Distress Companies that came out of distress and turnaround was extracted during 1383 to 1399. Artificial Intelligence approach was used to analyze the data. In this approach, by using Lars and Relief Feature Selection Algorithms, 10 out of 54 financial variables which were effective in turnaround of companies were identified and then, the Learning Algorithm of Support Vector Machine and Decision Tree were used to evaluate the accuracy of the results of the identified variables in predicting turnaround. The results showed that Lars Feature Selection Method and Vector Machine Algorithm Support have better performance in predicting the time to exit from distress as compared to the Relief Feature Selection Method and Decision Tree Algorithm. Also, regardless of feature selection methods, support vector learning machine has a higher predictive power as compared to decision tree. Manuscript profile -
Open Access Article
6 - Evaluation of Nominal Wage Rigidities' Sensitivity in Dynamic Stochasic General Equilibrium by Considering the Stock Price Bubbles
Kiomars sohaili shahram fatahi narges rahmanianiThe main goal of this study is to introduce a general stochastic dynamic equilibrium model with sensitivity analysis for the wage rigidity in Iran's economy using the seasonal data from 1995-2014. The results showed, capital market dynamics influence the real sector of MoreThe main goal of this study is to introduce a general stochastic dynamic equilibrium model with sensitivity analysis for the wage rigidity in Iran's economy using the seasonal data from 1995-2014. The results showed, capital market dynamics influence the real sector of Iranian economy. The monetary policy shock has a significant impact on macroeconomic variables and stock prices. The volatilities in stock prices helps to explain the Iranian business cycles. In the case of bubble in asset prices, credit constraint in firms was decreased and their opportunity cost decreases and causes a downward pressure on the marginal costs and finally inflation decreases. By assuming wage rigidity, possibility of wage adjustment with regard to monetary shock decreases and the reaction of labour and labour supply is been more strict. And changes in production is slower than when the wage perfect flexibility exist. Based on the results, using of the model with wage rigidity in order to better simulate the real world is suggested. Manuscript profile -
Open Access Article
7 - The Application of GMDH Neural Network Approachin Forecasting the Price of Soybean Meal in Merchendis Stock Exchange
علی اکبر باغستانی سعید یزدانی مجید احمدیانAbstract Livestock and poultry industry has depended much on soybean meal. This dependence has led to fluctuations in the price of this product and therefore, forces market participants to follow the sensitivity and accuracy. These fluctuations created serious concerns MoreAbstract Livestock and poultry industry has depended much on soybean meal. This dependence has led to fluctuations in the price of this product and therefore, forces market participants to follow the sensitivity and accuracy. These fluctuations created serious concerns about the supply and price of soybean meal. So, this study, using monthly and weekly data of Soybean prices in the exchange market, tried to forecast soybean price. So Soybean Meal price has predicted with neural network GMDH algorithm and ARIMA. The results based on the root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MPAE) showed that the GMDH algorithm, has a better ability to predict the price accurately. Manuscript profile -
Open Access Article
8 - The Effect of Financial Development on Energy Consumption by Using the Generalized Method of Moment
مرتضی خورسندی تیمور محمدی محمد مهدی خزایی عارف بهروزAbstract In this study, the effect of financial development has examined on energy consumption by using the Generalized Method of Moment (GMM) in two groups of developing countries during 1993-2011 period. The first group includes 14 oil-producing developing countries MoreAbstract In this study, the effect of financial development has examined on energy consumption by using the Generalized Method of Moment (GMM) in two groups of developing countries during 1993-2011 period. The first group includes 14 oil-producing developing countries and the second group includes 19 non-oil-producing developing countries. For each group of countries, two separate models were estimated, the first model by using banking sector variable, and the second model estimated by using capital market variable. The results showed that, GDP per capita in the non-oil-producing countries compared with oil-producing countries has a greater positive effect on per capita consumption of energy. The oil-producing price variable compared with the Non-Oil-Producing developing countries has a greater negative effect on per capita consumption of energy. The ratio of domestic credit variable to private sector (% of GDP) in non-oil-producing developing countries 0.02% and in oil-producing developing countries is 0.009 percent .Comparison of the effects of domestic bank credit variable to the private sector ( as a percentage of GDP) on per capita consumption of energy in the two groups of countries reflects the higher efficiency of the banking sector in the non-oil-producing countries .On the other hand, variable rate of turnover of shares traded in the non-oil-producing developing countries is -0.003 percent and in oil-producing developing countries is -0.009 percent .Statistical analysis of the variable of capital market of shares traded in both developing oil-producing and non-oil-producing developing countries also shows that the effect of capital market development in energy consumption in oil-producing developing countries is more negative and smaller than the non-oil-producing developing countries Manuscript profile -
Open Access Article
9 - بررسی رابطه همبستگی شرطی بین بازارهای مالی ایران با تأکید بر اثر حافظه بلندمدت و عدم تقارن
شهرام فتاحی مرتضی سحاب خدا مرادی میثاق ایوتوند -
Open Access Article
10 - ارائه شاخصی جدید برای انعکاس رفتار بازار سهام با استفاده از رویکرد تحلیل شبکههای پیچیده
هادی اسماعیل پور تیمور محمدی محمد فقهی کاشانی عباس شاکری -
Open Access Article
11 - Investigating the Correlation Between Crude Oil Prices and the Stock Market in Iran: A multivariate GARCH approach and wavelet
Nasim Amin Roya Aleemran Rasoul Baradaran Hassanzadeh Amir Ali FarhangAbstract The purpose of this article is to investigate the correlation between TEPIX index and Brent oil prices in the weekly period from September 2009 to December 2016. In this regard, the DCC-GARCH and CWT approachs have been used. The results show the correlation b MoreAbstract The purpose of this article is to investigate the correlation between TEPIX index and Brent oil prices in the weekly period from September 2009 to December 2016. In this regard, the DCC-GARCH and CWT approachs have been used. The results show the correlation between the two indicators changes under the influence of economic and political conditions of society. Also, this situation is affected by the corona pandemic conditions from February 2020 to May 2020, so that in this period the correlation between the two indicators is negative and in the period before and after this period is positive. The results of the wavelet approach also show the dependence between the market pairs under study is low in the short term and higher in some periods in the medium and long term. Therefore, investors should invest in these two markets, depending on the time horizon and the economic and political conditions. Manuscript profile -
Open Access Article
12 - تاثیر منابع تامین مالی بر رشد شرکتهای کوچک و متوسط پذیرفته شده در بورس اوراق بهادار تهران
مریم گلقندشتی محمد ابراهیم آقا بابایی -
Open Access Article
13 - Providing a Pattern of the Impact of Political Connection and Corporate Governance on Banks Performance in Financial Crisis Condition
مهدی ذوالفقاری سید علی واعظ محمد خدامرادیThe aim of the present study is to investigate and provide a model of the impact of political connection and corporate governance on banks' performance in the financial crisis condition. In order to achieve the objectives of the research, the information of 10 banks lis MoreThe aim of the present study is to investigate and provide a model of the impact of political connection and corporate governance on banks' performance in the financial crisis condition. In order to achieve the objectives of the research, the information of 10 banks listed on Tehran Stock Exchange, which were selected for a ten-year territory (from the beginning of 2010 to the end of 2019), was extracted and necessary statistical tests were performed on them. In order to test the research hypotheses, multivariate linear regression based on panel data and a combination of cross-sectional and temporal series has been used. Research has shown that in times of financial crisis, political communication has a positive and significant effect on return on assets and the ratio of TobinsQ in exemplary banks; negative and significant in the context of financial crises in banks Sample; and in times of financial crisis, corporate governance has a positive and significant effect on return of assets and the TobinsQ ratio of the sample banks. Manuscript profile -
Open Access Article
14 - Data mining of Iranian stock market by modeling complex network filtering based on MST
Hadi Esmaeilpour MoghadamAbstract One of the most important problems in modern finance is finding efficient ways to summarize and visualize stock market data. Modeling the filtering of complex networks in the stock market allows this to be achieved by reducing the market size, obtaining reliab MoreAbstract One of the most important problems in modern finance is finding efficient ways to summarize and visualize stock market data. Modeling the filtering of complex networks in the stock market allows this to be achieved by reducing the market size, obtaining reliable information with less disturbance. Since stock price changes are not independent of each other, the study of the correlation between stock price changes provides a better understanding of market performance for investors. Stock market analysis based on complex networks allows studying the correlation of stock prices. In this paper, using the stock market data in the Tehran Stock Exchange, the Iranian stock market network is created by the threshold method, and then the network filtering is based on MST. The results show that the filtration modeling of Iran's stock market network based on the MST can form a subset of the stock market that follows the performance of the entire market with a significant reduction in size and has a similar degree of diversification with the entire market. These analyzes provide a more in-depth insight into the structure of the stock market while reducing the size. Manuscript profile
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