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Stock market timing is a very difficult task because of the complexity of the market. Since there are various factors affecting the market and therefore it is not a simple task to predict future stock price and its trend. This paper aims to apply advanced tools and algorithms such as the artificial neural networks (ANN) to model nonlinear processes and predict future stock price and its trend. More specifically, this study explores the abilities of the ANN to enhance the effectiveness of the technical analysis indicators to predict stock trend signals. Using a sample of 50 companies in the Tehran Stock Exchange (TSE), the results indicate that the ANN is capable to predict the direction of the short term movement in the future stock price. After considering the transaction costs, the results confirm that there is not significant difference among the returns gained from the ANN method, buy and hold strategy, and the most profitable technical indicators in the market when the trend is increasing. While, the ANN model yields higher returns compared to buy and hold strategy in the market when the trend is decreasing. Nevertheless, in the case of decreasing trend, the finding confirms the trend indicators (moving averages) achieve the highest returns.

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Biodiesel is a renewable fuel that can be produced from vegetable or animal oil. The main benefit of using biodiesel is its capacity to lower exhaust emissions compared to diesel fuel. Over the last few years, numerous studies have been performed on biodiesel production and its effect to engine performance and emissions. However, in those studies; no attention has been paid in economic analysis of biodiesel usage in engines. In this investigation, various mixtures of biodiesel and diesel fuel have been tested on a four cylinders turbocharged diesel engine. The combustion reaction was determined by using the experimental data. Then, the mass flow rate of each exhaust emissions was calculated, using combustion reaction. The economic analysis was performed considering social cost of emissions, inlet fuel cost and the cost of engine power loss. Because of low diesel fuel price in Iran, the results were determined by ignoring the inlet fuel cost. The technical analysis was also performed considering the engine performance results. The results showed that the 10% and 15% biodiesel-diesel blends (B10 and B15) were more affordable than diesel fuel. The performance results of engine were also acceptable in these blends. The power loss was slight and the highest thermal efficiency was also observed in these blends. All biodiesel blends were more affordable than diesel in emissions economic analysis

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with due attention to importance of investment in stock exchange and special attention of governments to prospering of this part of economy , in this research we want to introduce the best method of investment between two specialized common methods namely fundamental analysis and technical analysis . It is claimed by the investigator that investment on base of fundamental analysis is more efficient than by technical analysis . Therefore average efficiency of each method should be accounted and then compare with each other . This investigation for purpose of objective is applying and for purpose of method is descriptive - comparative and by nature is post-happening and considers past quantitative information . The results show that efficiency of fundamental analysis is more than technical analysis through the two years period of study and it verify investigator claim . ` ` ` ` ` ` ` ` ` ` ` `