درخت حوزه‌های تخصصی

This study examines the criterion of value at risk from another perspective and presents a new type of mean-value at Risk model. To solve the portfolio optimization problem in Tehran Stock Exchange, we use NSGA II, MOACO, and MOABC algorithms and then compare the mean-pVaR model with the mean-SV model. Given that, finding the best answer is very important in meta-heuristic methods, we use the concept of dominance in the discussion of multi-objective optimization to find the best answers and show that, at low iterations, the performance of the NSGA II algorithm is better than the MOABC and MOACO algorithms in solving the portfolio optimization problem. As the iteration increases, the performance of the algorithms improves, but the rate of improvement is not the same, in a way, the performance of the MOABC algorithm is better than that of the NSGA II and MOACO algorithms. Then, to compare the performance of the “mean-percentage of Value at Risk” model and the “mean-semi variance” model, we examine both models in the standard mean-variance model and show that the mean-pVaR model, compared to the mean-SV model, Has better performance in stock portfolio optimization.

Purpose: Social capital plays an important role in the success of any organization, including the education organization. As a result, the purpose of this study was presenting a social capital management model in the general directorate of education in Kermanshah province with a grounded theory approach. Methodology: This research in terms of purpose was applied and in terms of implementation method was mixed (qualitative and quantitative). The research population in the qualitative part was experts and senior managers of education in Kermanshah province and in the quantitative part were the principals of primary schools in Kermanshah province. The sample size in the qualitative part was estimated according to the principle of theoretical saturation 11 people who were selected by purposive sampling method and in the quantitative part was estimated according to Krejcie and Morgan table 332 people who were selected by random cluster sampling method. The research instrument in the qualitative part was a semi-structured interview and in the quantitative part was a researcher-made questionnaire, whose psychometric indices was confirmed and for data analysis was used from the methods of coding in MAXQDA software and exploratory factor analysis in LISREL software. Findings: Findings showed that in the central category of social capital management in education, causal conditions including categories of organizational factors, social factors and individual factors, contextual conditions including categories of social bonds of employees, cultural and social commitments and sustainable social development, intervening conditions including categories of legal requirements and frameworks, civic participation networks, organizational policies and organizational culture, strategies including categories of knowledge management, organizational resilience, job turnover and organizational participation and outcomes including categories of organizational outcomes, individual outcomes and social outcomes. Other findings showed that the factor load of all sub-categories except sense of identity on causal conditions, all sub-categories except collective power on contextual conditions, all sub-categories except success and education on intervening conditions, all sub-categories on strategies and all sub-categories except human capital accumulation, social cohesion, organizational learning, organizational entrepreneurship and interpersonal trust on outcomes were confirmed. Conclusion: Regarded to the importance of identified categories and concepts for the social capital management in education, planning is essential to improve the categories through their concepts.