درخت حوزه‌های تخصصی

Development of e-banking has empirically modified the structure and characters of banks’ performance, efficiency, risk and challenges which have also been articulately recognized based on the international best practices. E-banking brazenly accelerates and restructures financial transactions via enhancing technology and expanding the banking services in comparison with conventional banking. Accordingly, online access to the banks’ products, financial statements, payment services and even credit scoring has considerably improved banks-customers relationships in the context of lending and borrowing practice, deposit composition, investment opportunities, trade finance options as well as account management diversification. The impact of recent e-banking developments is statistically evaluated for Iran’s banking network via Dynamic Panel Data approach. The findings highlight that the ratio of ATMs and Electronic Cards transactions to banks' assets negatively-significantly influence the profitability due to higher substitution ratio with the other payment instruments and maintenance cost. The ratio of online branch transactions to the banks' assets negatively-insignificantly affects the profitability owing to the rapid increase in the NPLs and loan/loss expenses which has consequently shrunk Shared Revenues over the past 10 years. SWIFT-branches have positively-significantly enhanced the banks internal-secured cash flow while contemporaneously improves fund efficiency, banks’ services fees, and ultimately profit margin.

Technical analysis is constituted as an approach in the market analysis which is based on the study of pricing behavior and shares size in the past and price determination and its procedure in the future. Algorithmic transactions are growing rapidly in order to automate business strategies, given the arrival of computer-based technologies and the rapid processing of bulky information. Trading systems combine input information and ultimately identify the time of purchase and sale by forming one signal. In this paper, the training system is a kind of fuzzy inference system that combines fuzzified RSI and SO signals from technical analysis. The system’s trade rules database (selling, buying, and holding) would be calculated based on an optimization process using PSO. This optimization process should be repeated at certain intervals to keep the system up to date. This process is called the corrective property of systems. The findings on the overall index in the period 2001/3/21-2019/3/20 indicate that the system having optimized training on training data has an average daily return of /0027, risk-taking of /0065 and the daily sharp ratio of /42. Concerning the index of return and sharp ratio, the findings reveal that the system outperforms the signals and the market performance.

Corporate investment decisions are determined by a variety of factors, including various managerial measures, including overconfidence of managers, which are important determinants of corporate investment decisions. Most corporate executives prefer internal financing, but if internal resources are not sufficient to meet this need, they use external resources with the least degree of information asymmetry. The purpose of this study was to investigate the effect of managerial overconfidence on investment and the moderating effect of the internal financing method is on their relationship. The study consisted of listed companies in Tehran Stock Exchange during the period 2011 to 2016 and using a systematic elimination sampling method, 97 companies were selected. To investigate the research hypotheses, EVIEWS software and panel data regression method was used. The results of the research showed that managers’ overconfidence has a positive and significant effect on investment as well as underinvestment, but internal financing does not have a significant effect on the relationship between the overconfidence of managers and investment as well over-investment. But the effect of internal financing on the relationship between managers’ overconfidence and underinvestment was a significant positive. Finally, it became clear that internal financing had a significant negative impact on investment and over-investment.

Banking and insurance industries are the strategic pillars of every country's economy and play a key role in the economy of countries. Without financial and insurance institutions, the financial sector of the country will be no longer effective. Therefore, determining the factors affecting the returns and performance of these institutions seems necessary.  So, in this research, the efficiency and effectiveness of financial and insurance institutions and their influential factors in 18 banks and listed insurance companies in Tehran Stock Exchange were studied. To do this, the data of selected financial and insurance institutions during the period of 2009-2016 were extracted using Rahavard Novin softwareand the model was estimated using the data panel method and Eviews9.0. Before estimating the model, using the unitroot test of the Dickey Fuller, the variables stationary property were checked and confirmed,and the Jarque-Bera testwas approved for the normal distribution of variables. The results of the model estimation showed that at a significant level of 5%, the size of financial and insurance institutions, financial leverage, and the concentration ratio on their performance and returns had a positive effect, and this effect was statistically significant at 5% significancy. Also, credit risk has a negative effect on the performance and returns of these institutions and this effect is statistically significant at 5% significancy. The effect of the volume of state ownership on the performance and returns of financial and insurance institutions is negative, but this effect is not statistically significant for the returns of these institutions.