درخت حوزه‌های تخصصی

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.

one of the most important financial and investment issues is Portfolio selection, that seeks to allocate a predetermined capital (wealth) over one or multiple periods between assets and stocks in such a way that the wealth of investor (portfolio owner) is maximized and, Simultaneously, its risk minimized. In the paper, we first propose a mathematical programming model for Portfolio selection to maximize the minimum amount of Sharpe ratios of the portfolio in all periods (max-min problem). Then, due to the uncertain property of the input parameters of such a problem, a robust possibilistic programming model (based on necessity theory) has been developed, which is capable of adjusting the robust degree of output decisions to the uncertainty of the parameters. The proposed model was tested on 27 companies active in the Tehran stock market. In the end, the results of the model demonstrated the good performance of the robust possibilistic programming model.