Iranian Journal of Finance

This study postulates the relationships between earning quality and investment efficiency among Tehran Stock Exchange-listed companies with an emphasis on the moderating role of board characteristics including independence, the duality of executives and the financial expertise of members. The research is applied in terms of purpose and takes a correlative-descriptive approach. The statistical population is comprised of TSE listed companies from 2008 to 2018 and, the final sample consisting of 78 companies was selected using systematic (purposeful) elimination. To test the hypotheses, two regression models were estimated using Ordinary Least Squares method through Eviews software. The empirical results revealed a positive and significant relationship between the quality of earning and investment efficiency in TSE publicly-traded companies. As well as, the board members' independence and financial background can significantly exaggerate such a relationship. Based on our findings, capital market legislators, regulators, and policymakers may reinforce the governance role of the board of directors in monitoring the behavior of firms, and as a result, increase the efficiency of allocating capital among companies listed in TSE and also in macroeconomic levels. The findings can persuade corporate shareholders to pay more attention to the degree of independence and expertise of their board of directors to gain more return on their investment opportunities.

Cash flow is one of the critical resources in the economic unit and the balance between available cash and cash needs is the most important factor in economic health. Since judgments of many stakeholders such as investors and shareholders about the position of the economic unit are based on liquidity situation, so predicting future cash flow is crucial. In this research, the impact of cash and accrual items on cash flow forecasts has been studied. Providing a proper model to predict operating cash flows and review some important characteristics of cash flow forecasting regression models, using a multilayer perceptron and determining the best model by using accrual regression model variables for predicting cash flows. For this purpose, 287 firms listed in Tehran Stock Exchange during 2008 to 2017 were studied; Linear and nonlinear regression, correlation coefficient and artificial neural network statistical methods have been used for data analysis and predictive power of powers was compared by using the sum of squared prediction error and coefficient of determination. Results showed that the accrual regression model can predict future cash flows better than other tested models and among corporate characteristics, the highest correlation belongs to sales volatility and firm size with accrual regression models. On the other hand, results of fitting different neural network models indicate that two structures with 8 and 11 hidden nodes are the best models to predict cash flows.

Tax avoidance is making use of legal loop holes to display an individual's financial situation as if it were lower than what it is in order to decrease the amount of income tax owed. Behavioral economics and taxation literature indicate that psychological factors can provide further insight on accountants' financial decisions. The literature claim that tax compliance can be influenced by an individual’s personality and beliefs. Therefore, in this research, the effects of psychological variables including Machiavellianism, emotional manipulation and moral foundations are examined on tax avoidance in accounting and finance professions. The aim of this study is to investigate the role of Machiavellianism and emotional manipulation as two negative attributes of human beings and moral foundations in tax avoidance in listed and unlisted firms. For this purpose, a sample consisting of 500 accountants and financial managers of listed and unlisted companies of Tehran stock exchange was selected. This study is an applied and descriptive survey. The hypotheses of the research have been analyzed by structural equation modeling using Lisrel software. The evidence of this study show that Machiavellianism has a positive and moral foundations have a negative effect on tax avoidance. But, this study doesn’t confirm any significant relation between emotional manipulation and tax avoidance. This paper also states that social and psychological variables  would  explain the tax avoidance phenomenon.

Networks are useful tools for presenting the relationships between financial institutions. During the previous years, many scholars have found that using single-layer networks cannot properly characterize and explain complex systems. The purpose of this research is to introduce a multiplex network in order to analyze, as accurately as possible, all aspects of communication between banks in capital market of Iran. In this article, each bank represents a node and three layers of return, trading volume and market Cap have been presented for analyzing the idea of multiplex networks. We have used the Granger causality method to determine the direction between nodes. For understanding the topology structure of these layers, different concepts have been used. The research findings show that the value layer topology has a significant similarity with the trading volume layer. Also according to the measure of centrality it can be seen that the centrality varies in different layers.

In order to survive in the modern world, organizations must be equipped with the mechanisms that not only maintain their competitive advantage, but also result in their progress and improvement. Prediction of banks’ performances is an important issue, and a poor performance in banks may primarily lead to their bankruptcy, thereby affecting national economics. The bank performance prediction model uses scientific and systematic approaches to diagnose the financial operations of institutes. According to a precise and strict evaluation, the model can detect the weakness of institutions in advance and provide early warning signals to related financial governments. In the present study, we have used three data mining models to predict the future performance of the banks accepted in Tehran Stock Exchange (TSE) and Iran Fara Bourse. Initially, 53 financial ratios were selected and, consequently, reduced to 28 using the fuzzy Delphi technique. The statistical population included 18 banks listed on TSE and Iran Fara Bourse, which   provided their financial statements during the period of 2011 to 2017. Data were collected from the Codal site based on 28 financial ratios using C4.5 decision tree, AdaBoost, and Naïve Bayes algorithm. According to the findings, the Naïve Bayes algorithm was the optimal predictive model with the accuracy of 88.89%.

One of the main causes of firms’ ineffectiveness is the absence or insufficiency of appropriate investment methods. This deficiency could also be attributed to an unfortunate selecting of an inappropriate investment methods which may ultimately endanger the firms’ prospect of survival. According to the firm life cycle theory, various firms demonstrate diverse behavior when provided with an investment opportunity. These responses are largely in accordance with the stage of the life cycle in which the firm resides in at that moment. In this research, the selection of the investment method appropriate for a firm has been studied following the premises of the life cycle theory. The target populations of this study were companies admitted to Tehran Stock Exchange. Systematic removal method was adopted to recruit a sample of 118 firms. The study period was 8 years (2011-2018).  Findings suggest that firms choose to invest in operational properties when they are at the stage of growth, maturity and decline. In other words, the capital under the companies’ authority and control were employed for the firms’ mainstream activities. However, such a link was not found at the introduction stage of their life cycle. This relation has been illustrated in various industries.