محمدحسین قائمی

One of the most important effective elements in economic growth is the efficiency of manufacturing units. Therefore, measuring the efficiency of firms is necessary in order to increase efficiency in future planning courses. In the current research, using Stochastic Frontier Production Function, the efficiency of firms in Tehran Stock Exchange has been measured. In the above method, the efficient frontier is determined by using the Trans log production function, and the efficiency of each firm measured by the efficient frontier. The most important superiority of Stochastic Frontier Production Function is to specify the role of random and environmental elements (out of firm authorities) and inter-organizational elements (in-firm authorities) to assess the inefficiency of firms as compared to other methods. Thus, 105 firms were selected using maximum likelihood method in 2008-2017 to evaluate the research model. Results indicated that the minerals industry and cement industry with the averages of 53% and 90% had the least and most efficiency values, respectively. Separating the inefficiency values showed that the food industry and chemicals industry had the least and most inefficiency resulting from the firm authorities as 33.6% and 95.2%, respectively. According to research results, financial analysts and investors are recommended to rank the efficiency and assess the performance based on the firm authorities. Due to the importance of efficiency measurement in operational auditing, the auditors are recommended to use the current research model to assess the firm’s efficiency. Also, Organization of Industries and Mines is suggested to tackle the obstacles after identifying the elements out of firm authorities which affect the inefficiency in the firms.

Market participants use different tools basically technical or fundamental analysis to have a higher return in constructing a well-maintained portfolio. Examining the efficiency of technical strategies in creating a portfolio is the main objective of this study. Technical analysis is based on using historical trading data to launch selling and buying rules that maximize return and still control risks of loss. We use the adjusted trading data of 50 active stocks in the Tehran Stock Exchange as our sample which includes daily trading data from 2008 to 2019. We construct two types of portfolio; strategy-based portfolio versus random one. Then we calculate abnormal returns of each type of portfolio, applying the Monte-Carlo technique. Using Independent-Samples T-Test to compare means of the abnormal returns, our findings show that there is a significant positive abnormal return for both strategies applied in constructing a portfolio (0.057 and 0.062 mean difference for the first and second strategy, respectively), confirming the higher efficiency of applying technical strategies in portfolio management. Therefore, it is suggested to have and apply a strategy or combination of strategies for trading as an active participant, instead of constructing, rebalancing and maintaining one’s portfolio only by chance, since there will be undesirable results in the long-run.

One of the most important effective factors in the economic growth is the increased efficiency of manufacturing sectors. Thus, it is necessary to review and measure the efficiency of business units from a variety of dimensions to plan the increase of efficiency in future courses. One of these dimensions is the economics to scale (ES) referring to the concept of enhanced earnings due to the increased manufacturing unit, which may be of an increasing, fixed or decreasing trend. ES can be measured through economic production functions. This paper has applied Translog production function to measure corporates' ES. Therefore, data of 105 manufacturing corporates have been collected during 2008-2017. With regard to linearity between independent variables, the elastic net regression method has been used. Results indicate that some industries are of increasing economics to scale trend and some have a decreasing ES. Results can be applied in order to plan and determine the appropriate production level in the management accounting of corporates.