سید محمدرضا داوودی

After closing, the multi-period portfolio can be corrected and revised at regular intervals. The philosophy behind using multi-period portfolio models is that investors often have a multi-period view of future changes in assets, which can be the result of technical and fundamental analysis or statistical model analysis. In conventional multi-period portfolio models, it is assumed that the forecast and correction time horizons are the same for all assets. However, one asset may be forecasted over a one-month horizon while another may be forecasted over a two-month horizon, and both may be revised in the future. The purpose of this study is to present a multi-period portfolio model in which assets have different time horizons for corrections or an asset may not be traded for the first few periods and then enter the correction stage. In this model, fuzzy variables defined in a credibility space are used to describe the return, and the credibility measure controls the risk. The model's objective function is to maximize the portfolio's ultimate wealth, and a constraint is used to control portfolio risk, in which the validity of the portfolio's ultimate wealth below a certain threshold is controlled at a certain level of confidence. A combination of particle swarm optimization and simulation is used to find the best solution. Finally, using a numerical example, the model is implemented on a portfolio with 6 assets and 4 monthly time steps on the Tehran Stock Exchange.

Designing trading systems with good returns is critical for capital market investors. Trading systems are often based on a combination of several tools to use their combined information. For the first time in Iran, the present study aimed to propose a pattern detection algorithm for a flag pattern based on Japanese candlestick charts and their arrangement. By recognizing the pattern and if the 4- and 10-day moving average is confirmed, a shopping position is developed, and the selling time is determined based on an optimized and dynamic process commensurate with price changes and the data scale. Our objective was to address the question of whether the returns resulting from this strategy have a more significant positive return compared to the purchase and maintenance strategy. The research sample included the daily information of 16 active companies of basic metals in Tehran Stock Exchange during 2007-2019, extracted from the database of Novin Rahavard software. Data analysis was performed in MATLAB software, and the obtained experimental evidence was described using t-test. According to the results, the research strategy had a higher performance in terms of returns and risks compared to the market.

Traders in the capital market always seek methods to make full use of available information and combine them to find the best buying and selling strategy. The present study uses a linear hybrid system to combine 106 signals from moving averages oscillators and RSI signals in the technical analysis along with two buy and sell bonds. In addition, the system has correctional property and modifies its parameters over time and according to new information. The result of the research on the Tehran Exchange overall index in the period 1380 to 1397 indicates that the system after the optimal training on training data has an average of daily returns of 0/0025, 0/0048 risk, and a daily Sharp ratio of 0/52, which is better than the individual performance of each signal and market performance in daily average return and sharp ratio criterion.

Purpose : The purpose of this study is to design and explain the development model of future managers based on talent management and personality types with the grounded theory approach in the headquarters of the National Social Security Organization. Method : This research was conducted with a qualitative-inductive approach and Strauss-Corbin's grounded theory method. The research tool was a semi-structured interview. Using the grounded theory method, the data obtained from interviews with 12 elites and qualified specialists of the Social Security Organization were analyzed in three open, axial, and selective coding stages. Findings : 19 general categories in the form of a paradigm model in which these factors include causal conditions (individual factors, organizational factors, lack of proper selection, knowledge and skills of employees), central phenomenon (future managers based on talent management and personality types), contextual conditions (Organizational context, Talent Selection, Talent utilization), intervening conditions (psychological (individual) factors, Individual factors, Management factors), and strategies (Talent sourcing, Empowerment of managers and employees, Proportion of job and employment, Succession, Foresight and Cognitive Strategy) and Consequences (Organizational results, Public satisfaction, Futurization). Conclusion : Conclusion: Recent developments in the field of human resources have made this field doubly important. Organizations try to employ the most specialized people at management levels, and therefore talent management, as a key king, examines the types of situations involved in this field. Proper use of talents leads to success and puts the organization on the right track.