Financial Economics
Ahmad Agheli; Seyyed Ali Paytakhti Oskooe; Nader Mehregan; Monireh Dizaji
Abstract
1- INTRODUCTION
Considering the role of the capital market in the economy of countries and studying the performance of this market has a particular importance. One of the factors that affect the performance of the capital market is the decisions made regarding the financial structure of companies’ ...
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1- INTRODUCTION
Considering the role of the capital market in the economy of countries and studying the performance of this market has a particular importance. One of the factors that affect the performance of the capital market is the decisions made regarding the financial structure of companies’ performance in this market. Today, in fact, the credit rating of companies is largely dependent on their financial structure, or in other words, their capital structure, and in fact, the basis of production and service provision depends on the way financial funds are provided and used. On the other hand, the financial structure of each company is an early warning regarding the number of financial resources of the company, and it is necessary to determine the factors affecting their financial structure in the strategic planning of companies. Many variables affect the financial structures of stock companies, among which we can mention financing with Islamic instruments. Sukuk is one of the important financial instruments and conforms with the Islamic Shari'ah, which provide an alternative source of funding, especially for large (very active) companies, and more efficient sources compared to conventional bonds.
2- THEORETICAL FRAMEWORK
In financial field, the way in which the company invests is called financial structure. Financial structure, or in other words capital structure, describes the long-term capital financing of a company, which represents debt and equity, and is a type of permanent financing that supports the growth of the company and related assets. One of the most important functions of the Islamic financial system is to facilitate financial flow and guide it towards the most efficient type of investment, and as a facilitator of financial flow, it gives producers the opportunity to move economic resources with greater speed and accuracy by relying on monetary and financial resources. The existence of these types of financial instruments increases capital efficiency and optimal allocation of resources in companies. Since Islamic financing can lead to global financial stability and economic growth; Therefore, wider access to financial services improves social participation and increases market power, and ultimately strengthens protective laws and solves problems and issues of financial development, and increases profitability and improves the financing process of companies.
3- METHODOLOGY
This research is considered as applied research in terms of its objective; Because it examines the relationships between variables, the subject of the research is the Tehran Stock Exchange Organization in terms of location, and the time scope of the research is from the fiscal year 2010 to 2019 by using the annual data of the companies. The 83 companies were selected as the statistical sample used in the research. In order to estimate the effects of the variables, the panel data technique with Johnssen's approach is used. In this research, the variable of financial structure is used as dependent variable and the variables of ejare sukuk, murabaha sukuk, sode sukuk, istisna sukuk and mosharekat sukuk are used as explanatory variables.
4- RESULTS & DISCUSSION
According to the empirical results of this study, all new Islamic financing instruments had a positive effect on the financial structure index (ratio of capital to assets). In the long run, ejare sukuk, murabaha sukuk, sode sukuk, istisna sukuk and mosharekat sukuk explain 7.06, 20.32, 0.07, 3.32 and 0.84 percent respectively, of the changes in the financial structure index.
5- CONCLUSIONS & SUGGESTIONS
The present study investigates effectiveness of the financial structure of listed companies from new Islamic financing instruments (Sukuk) by using the panel data technique with the Johanssen approach. For this purpose, the data of 83 listed companies on the Tehran Stock Exchange has been used during the years 2010 to 2019. According to the research results, instruments had a positive effect on the financial structure index (ratio of capital to assets). Accordingly, the issue of sukuk can significantly improve the financial structure of companies. Companies should use a complete combination of modern financing tools (Sukuk) to achieve benefits such as increasing liquidity, increasing shareholders' wealth and increasing diversity in financing sources.
Siab Mamipour; Ziba Sasanian Asl
Abstract
Financial markets are sensitive to exchange rate fluctuations of the Iran’s economy. Changes in the foreign exchange market affect household, businesses, and government spendings. Exchange rate management policy helps stock market to be protected from the effects of exchange rates. As for investment ...
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Financial markets are sensitive to exchange rate fluctuations of the Iran’s economy. Changes in the foreign exchange market affect household, businesses, and government spendings. Exchange rate management policy helps stock market to be protected from the effects of exchange rates. As for investment strategies, investors can invest without considering the exchange rate in the short run investments, but exposure to asymmetric exchange rate is very important in long run.
This study explores the asymmetric exchange rate exposure of stock returns building upon the capital asset pricing model (CAPM) framework, using monthly returns of Iranian industry indices. In accordance with the existing literature, industry returns are subject to lagged exposure effects, but the asymmetries vary across industries, which could be due to the discrepancies of trade balance and ownership of certain industries.
Furthermore, the dynamic multipliers depict that industry returns quickly respond to changes in the exchange rate and correct the disequilibrium within a short time, making the long run exposure to be symmetric or very small (Cuestas & Tang, 2015).
Methodology
The main aim of this study is, hence, to investigate the asymmetric exchange rate exposure of stock returns in the Iranian stock market at the industry level. Specifically, we introduce the conventional CAPM for measuring exchange rate exposure. We construct the dynamic nonlinear model to investigate both the long run and short run asymmetric exposure effects, which is carried out by means of estimating a nonlinear autoregressive distributed lag (NARDL) model introduced by Shin and Greenwood-Nimmo (2014).
Building upon the CAPM structure, this paper contributes to a growing literature on the analysis of exchange rate exposure of Iran's stock market on the following grounds. First, compared to linear regression models, the NARDL model demonstrates its competence and efficiency in estimating the exchange rate exposure. The disparities in the exposure effect depend on the ownership of these companies and the expansion of their global operations. Second, industry returns strongly and quickly respond to exchange rate changes in the very short run, while most of the long run exposures are symmetric or very small.
In fact, this paper studies the effects of positive and negative shocks of exchange rate on the return of various industries in stock market based on CAPM model and NARDL approach to estimate parameters during the period of April 2012 to March 2015.
To evaluate the efficiency of asymmetric effects of exchange rate on active industries in Tehran stock market, first exchange rates decompose to positive and negative shocks and then its asymmetric effects on stock market is analyzed using NARDL model. To do it, we use the Wald test for the symmetry or asymmetry effects of positive and negative exchange rate on return of active industries in the short run and long run.
Results and Discussion
The results indicate that most industries of stock market are under the influence of positive and negative shocks of exchange rate and these effects are different for industries. Hence, the effects of positive and negative exchange rate shocks for the industries such as agriculture, textile, rubber, engineering, leather, communication, steel products, radio, chemical materials, and multi-disciplinary industries are symmetric while the effect of exchange rate shocks on return of industries like bank, automobile, basic metals, publishing and printing, electrical devices, computer , tool medical, cement, finance, non finance, investments, paper, non-metallic minerals, and machinery industries are asymmetric in short run, and for industries of ceramic tiles, they are asymmetric in the long run. Additionally, in industries like mass production, oil, transport, coal, drugs, wood, sugar, food ingredients except sugar, they are asymmetric in the short run and long run.
Thus, the results of this study can be useful for investors and shareholders in predicting the short and long term effects of exchange rate shocks on the stock prices.
Therefore, it can be argued that sudden shocks exchange rate can affect about 70 percent of returns of active industries in Tehran Stock market. Therefore, avoiding sudden shocks and maintaining relative stability in exchange market are the main suggestions for policymakers. Also, given that the exchange rate shocks are exogenous variables for firm managers, investors should further evaluate the performance of companies and their profitability, and consider long run vision in analysis and making decisions.
Mohammad Rasool Chopani; Farzaneh Nassirzadeh; Mahdi saehi
Abstract
Earnings per share is one of the most important financial statistics, mostly used in the evaluation of profitability, the risk associated with earning, and the stock price. In many countries, the importance of this measure is to the extent that it is considered as one of the principal scales in determining ...
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Earnings per share is one of the most important financial statistics, mostly used in the evaluation of profitability, the risk associated with earning, and the stock price. In many countries, the importance of this measure is to the extent that it is considered as one of the principal scales in determining the stock price and is widely used in stock evaluation models. Thus, to predict the earnings per share, different algorithms have been used, some of which make use of the statistical models and some smart models.
The studies recently conducted on the precision of smart models show that in comparison to the statistical models, the smart models have performed better in classification and finding of an efficient solution. Thus, those investors using these models will find the investment opportunities much more efficiently. Therefore, regarding this necessity, this study has compared the errors of such models as Support Vector Estimator, Minimum Degree Estimator, and Fuzzy Neural Network (which are among the smart models having the lowest error rates) in predicting the earnings per share for the firms enlisted in Tehran Stock Exchange during the years of 2005 to 2012.
Research Methodology
In this research, nineteen different independent variables have been used in the three financial, fundamental, and macro groups. The relationships between the first group of variables and the earnings per share in the paper by Zhang et al. (2004), and the relationship between the second group of variables and the earnings per share in the papers by Lexian et al. (1390, 2011) and Brid (2001) have been confirmed. The dependent variable in this research is the annual earnings per share. Therefore, the current research tries to find a model, which has the highest precision in predicting the earnings per share, using the independent variables, either individually or in groups.
The selected sample in this research include 171 firms in 27 active industries, during the years of 2005 to2012, through random sampling and using cluster sampling from among the active firms in Tehran Stock Exchange.
After being collected and standardized, the data was classified into training and experimental data, using the K-Fold Cross-Validation method. The percentage of training data to the experimental data is assumed as 30-70 or 20-80; in this research, the 20-80 composition has been employed. In this research, the amount of K has been determined as 10.
Then, the main process of modeling is conducted in a way that the prevalent patterns and relations between the data (independent and dependent variables) are extracted, using the techniques of Support Vector Estimator, Minimum Degree Estimator, and Fuzzy Neural Network. In this stage, the training data are used for modeling. After extracting the data patterns, the precision of the proposed model is estimated, using the experimental data, and finally, to explore the models’ precision, such error measures as mean square error (MSE), Median Absolute Deviation (MAD), and determination coefficient have been used.
Research Findings:
The results show that when all the fundamental and financial variables are used simultaneously, the precision of the estimator model is highest. When the fundamental variables are used in LARS, the MSE and MAD are 3.505 and 306.301 respectively. When the financial variables are used in LARS, the MSE and MAD are 0.921 and 206.669 respectively, and finally, when all the variables are used in LARS, the MSE and MAD are 3.414 and 392.081 respectively. The obtained results have been presented in sum in the following table.
Conclusion
In this research, the models have been evaluated annually; the models have been conducted on each year, and the results have been compared with each other. Finally, the average annual errors have been considered as the basis of determining a more precise model in every state. Exploring the models’ final error the Minimum Degree Estimator model predict the earnings better than the Fuzzy Neural Network and Support Vector Estimator. Also, exploring the average errors for the Minimum Degree Estimator model shows that using the financial variables has resulted in the increase in the predicting capabilities of this model.
Keyword: Tehran stock exchange, Earning per share, Support vector regression, Least angel regression, Adaptive neuro Fuzzy Inference system.
Hossein Sadeghi; Parisa Rahimi; Yunes Salmani
Abstract
Abstract
Financial distress caused by internal (Governance) and external (macroeconomic) factors can lead to a waste of resources. On the other hand, with the knowledge of the effectiveness of macroeconomic factors and Governance in financial distress, financial managers will be able to take appropriate ...
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Abstract
Financial distress caused by internal (Governance) and external (macroeconomic) factors can lead to a waste of resources. On the other hand, with the knowledge of the effectiveness of macroeconomic factors and Governance in financial distress, financial managers will be able to take appropriate actions to prevent financial distress. Investors also identify suitable opportunities to invest their own capital at minimum risk.
This study analyses the impact of macroeconomic and the Governance factors on Financial Distress in manufacturing companies listed in Tehran Stock Exchange during the period from 1382 to 1386, by using of panel Logit.
The results show that, firstly; of corporate governance factors; high levels of activity background, leverage ratio and ownership concentration increases the probability of financial distress and high levels of the firm size, agency costs, and Current Ratio reduce it.
Income and economic growth of firms reduce the probability of financial distress and inflation increases it. Secondly, the role of macroeconomic factors in health and financial distress of firms is far greater than the governance factors.
Mohammad Javad Saei; Mohammad Ali Bagherpour Velashani; Seyyed Naser Mosavi Baigi
Abstract
Abstract
The purpose of this study is investigation of the effect of restated information on the prediction of earnings. The sample comprised 1603 firm-year observations for the period 2001 to 2008, which represents 70% of all companies listed in Tehran stock exchange (TSE).The T-test results indicate ...
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Abstract
The purpose of this study is investigation of the effect of restated information on the prediction of earnings. The sample comprised 1603 firm-year observations for the period 2001 to 2008, which represents 70% of all companies listed in Tehran stock exchange (TSE).The T-test results indicate that,there is a significant difference between primary and restated figures. In addition, restated information increases the ability (power) of Sloan earnings prediction modeland reduces the errors of firm’s ordering based on Shannon entropy & GRA model, which implies that restated figures are more useful than primary ones in this model of earning prediction.
The results show that the use of restated figures by users and researchers could conclude to more powerful predictions. Therefore strongly suggest that financial database software should expand to supply this kind of information.
Mahmoud Mousavi Shiri; Sadegh Bafandeh Imandoust; Mohammad Bolandraftar Pasikhani
Abstract
Due to the effects of companies’ financial distress on stakeholders, financial distress prediction models have been one of the most attractive scopes in financial research. In recent years, after the global financial crisis, the number of bankrupt companies has risen. Since companies' financial distress ...
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Due to the effects of companies’ financial distress on stakeholders, financial distress prediction models have been one of the most attractive scopes in financial research. In recent years, after the global financial crisis, the number of bankrupt companies has risen. Since companies' financial distress is the first stage of bankruptcy, using financial ratios for predicting financial distress have attracted too much attention of the academics as well as economic and financial institutions.
Although in recent years studies on predicting companies’ financial distress in Iran have been increased, but most efforts have exploited traditional statistical methods; and just a few studies have used nonparametric methods. Recent studies demonstrate machine learning techniques outperform traditional statistical methods.
In the present study k-Nearest Neighbor classification method, derived from the field of data mining, is employed to predict financial distress of Tehran Stock Exchange listed companies during 2005-2008. Experimental results show that k-Nearest Neighbor is able to predict corporate financial distress with high accuracy.
Houshang Taghizadeh; Mir Vahid Pourrabbi
Abstract
In this paper, the efficiency of Cement industry firms Listed on Tehran Stock Exchange is evaluated, by using data envelopment analysis. The survey population includes 23 firms using Tehran stock exchange data. In this paper, inputs and outputs of DEA are determined through selecting the most important ...
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In this paper, the efficiency of Cement industry firms Listed on Tehran Stock Exchange is evaluated, by using data envelopment analysis. The survey population includes 23 firms using Tehran stock exchange data. In this paper, inputs and outputs of DEA are determined through selecting the most important criteria. Inputs include: cost of fuel (gasoline, mazut and …), cost of natural gas, cost of electricity and cost of water. Outputs include net sells, increasing (decreasing) on finished products, increasing (decreasing) on products in process, and the benefits of investments. On basis of existing data the efficiency of each firm was calculated using DEAP2 software. At last, the most efficient firms were introduced as patterns. Through comparison inefficient firms could come closer to patterns and reach the efficiency level.
Mohammad Reza shoorvarzy; Hadi Ghavami; Hamid Hosseinpour
Abstract
In the bubble, State of Stock erchange the stock valuation of companies based on their actual performance and price are not taken as an indicator of performance can not show it.
The present study investigated the relationship between clarity and price bubbles companies incidence of Tehran Stock Exchange ...
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In the bubble, State of Stock erchange the stock valuation of companies based on their actual performance and price are not taken as an indicator of performance can not show it.
The present study investigated the relationship between clarity and price bubbles companies incidence of Tehran Stock Exchange during the years 2008 to 2010, by using the continuity and independence tests (chi-square) and binary logistic regression is. These tests on 70 companies of which are chosen amony 400 companies has been implemented. Hazrabtda research companies in real returns on a daily basis using specialized software such as the securities and exchange process or and software to deviseane wRA and then collected by Excel software, the initial processing was done on them and these data were used for the test sequence spss environment. The first hypothesis of the study is Hbabdar clarity in companies, The results indicate that significant differences exist in the clarity of information on companies Hbabdar And clarity (distributed) information between the companies is average. The second hypothesis is also investigating transparency in companies Ghyrhbabdar The results indicated that there was no significant difference in the clarity and transparency of information Ghyrhbabdar companies (distribution) information between the companies is very high. The third hypothesis of the continuity test result Sindicate that there is a relation between the openness and clarity of price information and occurrence of bubbles in companies and in companies Ghyrhbabdar Hbabdar average clarity of informationis is very much.
mehdi moradi; amin Rostami
Abstract
In this study, the relationship between the some of corporate governance mechanisms and corporate financial performance after Initial Public Offerings (IPOs) in Tehran Stock Exchange (TSE), based on data from 70 companies during the years 1381–1387 (2003–2009) are examined. Corporate governance mechanisms ...
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In this study, the relationship between the some of corporate governance mechanisms and corporate financial performance after Initial Public Offerings (IPOs) in Tehran Stock Exchange (TSE), based on data from 70 companies during the years 1381–1387 (2003–2009) are examined. Corporate governance mechanisms includes Ownership structure (i.e., Institutional ownership, Managerial ownership), and Board composition (i.e., the percentage of Non executive director or Board independence, and CEO duality) in order to evaluation of the, return on asset and Tobin’s Q is used. Statistical method used to test hypotheses is panel data approach.
Findings show that institutional ownership and managerial ownership are positively related with firm performance after going public. Moreover, the percentage of non executive director improves firm performance. However, there is no relationship between CEO duality and firm performance.
Saei Mohammad Javad; Ali Esmaeili; Akbar Bagheri
Abstract
This study examines the relationship of "book value" and "net income" with the value of companies (Stock Prices). The results are consistent with previous study for “strong companies”, but in “weak companies" the relationship of two criteria with the value of companies is almost the same. Although, ...
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This study examines the relationship of "book value" and "net income" with the value of companies (Stock Prices). The results are consistent with previous study for “strong companies”, but in “weak companies" the relationship of two criteria with the value of companies is almost the same. Although, the "book value" have a higher relationship with the value of the firm, but the difference isn't significant
