درخت حوزه‌های تخصصی

Successful trades in financial markets have to be conducted close to the key recurrent points. Researchers have recently developed diverse systems to help the identification of these points. Technical analysis is one of the most valid and all-purpose kinds of these systems. With its numerous rules, the technical analysis endeavors to create well-timed and correct signals so that these points are identified. However, one of the drawbacks of this system is its overdependence on human analysis and knowledge in selecting and applying these rules. Employing the three tools of genetic algorithm, fuzzy logic, and neural network, this study attempts to develop an intelligent trading system based on the recognized rules of the technical analysis. Indeed, the genetic algorithm will assist with the optimization of technical rules owing to computing complexities. The fuzzy inference will also help the recognition of the total current condition in the market. It is because a set of rules will be selected based on the market kind (trending or non-trending). Finally, the signal developed by every rule will be translated into a single result (buy, sell, or hold). The obtained results reveal that there is a statistically meaningful difference between a stock's buy and hold and the trading system proposed by this research. In other words, our proposed system displays an extremely higher profitability potential.

The purpose of this paper is to explore the impact of industry competitive intensity on brand performance that marketing capabilities and market-focused learning and organizational innovation have the mediator role. Survey of top firms of Tehran Stock Exchange for the last 4 years is explored. We used questionnaire for gathering data and 77 firms of 92 responded to the questionnaire . In order to test the validity of the questionnaire Dillon - Goldstein (cρ =0/70) coefficient used. AVE was used to assess the validity of indicators that show the validity of the questionnaire have been favorable .This study analyzed the data in two levels of descriptive and inferential statistics using Smart PLS ,Spss18, Excel2007. To calculate the significant path coefficient and to gain the test statistic T we used Astrab boot ( via insertion of the sampling method ). The results show that industry competitive intensity has a positive and significant effect on brand performance and all hypotheses were confirmed . The mediation effect of marketing capabilities and market-focused learning and organizational innovation was approved too.