حسین پناهیان

Modeling the implementation of organizational ambidexterity as an organizational ability in alignment and efficiency in response to market demands and simultaneously adapting to environmental changes through innovation and discovery of new solutions can help improve the performance of the aforementioned organizations. The purpose of this research is to design a two-level organizational model in the branches of the Tejarat Bank of Isfahan province to identify the important indicators. in current research, the research method is a descriptive survey, and researcher-made questionnaires were designed based on the Fuzzy Dimetal method and the fuzzy network analysis process, these indicators have been prioritized by 36 senior employees of Isfahan Tejarat Bank using the combined technique of Fuzzy Dimetal and fuzzy network analysis process. based on the output of the above table, it indicates that the index of organizational managerial competence and loose relations, and finally attraction and employment were introduced as the most effective positive and negative indicators. the indicators of human resources of the organizational ambidexterity model, which mainly refers to the organizational and individual culture, indicate the influential role of the internals of individuals and organizations in the implementation of a new concept. In the strategic indicators, the existence of a flexible structure for the implementation of ambidexterity has been emphasized. From the aspect of social capital, the significant point is the high priority of the index of revision of social processes and components in the total indicators of ambidexterity in the organization. This means that in the initial stages of the implementation of dualism, it is necessary to review the processes and equipment to discover exploitation and exploration opportunities, plan to follow up on these opportunities at the same time, and formulate a model of ambidexterity in different parts of the bank.

The purpose of this study is to make investment decisions with the approach of data envelopment analysis and making decision on selection of optimal stock portfolio employing meta heuristic algorithms for multi-objective functions subject to real-life constraints. The statistical population of this research in capital decision-making and selection of the optimal capital composition is 183 of the selected companies of Tehran Stock Exchange, which were finally 42 companies as justified investment options. After measuring the risk and return of efficient companies, the real limitations of the budget, requirements and expectations of the investor, determination and composition of the investment were formulated as a multi-objective model. For optimal decision, the modified genetic meta heuristic algorithm and MATLAB software with dual operators were used. Elimination of the risk minimization function in sensitivity analysis improved the level of decision return but also led to more risk. Eliminating the maximizing return function improved decision-making risk but also reduced investment return. Elimination of investment requirements and expectations improved returns and increased investment risk, but more companies became involved in optimal investment.

There has not been presented any comprehensive index for Corporate Governance in spite of its crucial role in resolution and responsiveness. Although diverse methods have been sought for measuring the Corporate Governance in the previous studies, in this study, a comprehensive index is proposed for measuring Corporate Governance taking other indexes into account through mathematical equations. For testing the designed model’s functionality, a set of data related to 149 firms from 2014 to 2019 has been used jointly, too. To do so, a questionnaire, which asks the experts their idea about the weight and significance of the criteria of measuring the Corporate Governance of the firm, is made and distributed and the weight and significance of the criteria were determined through one method of multi-criteria decision model (Shannon Entropy). To measure the changeable hidden relationship which exists in this study of the Corporate Governance, provided with the measurement items, a confirmatory factorial analysis was taken, too; results show that the supposed model has been a proper index for Corporate Governance. This mixed index includes criteria such as the board of directors' size, independence, meetings, and its education, the CEO's permanence, the size, independence, financial specialty, financial experience, tenure and the meetings of the auditors hip committee, ownership concentration, organizational ownership, governmental ownership, deals with the dependent persons, the quality of the disclosure, proper information and weaknesses if the internal controls,

This study was an attempt to evaluate the progress of capital market efficiency in Iran. Optimal resource allocation and micro and macro investments play a key role in the capital market. The capital market's main task is to circulate capital and allocate resources efficiently and optimally. The main task of this market is to flow capital and allocate resources efficiently and optimally. Is there a regular pattern for determining the stock price? Market efficiency gains significance as it is important to know what factor or factors are effective in determining the price of the stock in the stock market or whether there is a regular pattern for determining the price of a stock. Thus, this study examined the efficiency of the capital market in Iran. In this regard, the researchers used the daily data of the total index of the Tehran Stock Exchange for 2008-2017. Artificial neural network and time series training tests were used to perform the test. The test results showed weak efficiency in the Tehran Stock Exchange and this inefficiency did not change significantly compared to the first period. In other words, in the Tehran Stock Market, one can predict returns using artificial intelligence.

Background: Many investment decisions are not only affected by economic indicators and rationality, but also categories such as work experience, social responsibility, risk, investor self-confidence, etc. affect investor’s behavior and their decisions. The main purpose of this study is to present a financial behavior model based on psychological and moral factors. Method: The present study was mixed. In the qualitative part, the Delphi technique was used. The statistical population of all experts and managers of brokerages, investment funds, investment portfolios, traders and analysts had professional qualifications and high experience, of which 12 people were considered as snowball technique as a sample. It was an interview tool and finally the data were analyzed by fuzzy Delphi method. In a small part, the descriptive-survey method was used. 287 members of the investor community were considered as a sample. A questionnaire was used to collect data. Finally, using AMOS software, confirmatory factor analysis and structural equation design were investigated. Results: Finally, the analysis model in this study was approved. Based on the importance of investors' behavior and the importance of moral and psychological characteristics in the capital market, it was shown that the expected return formed has a direct effect on the psychological characteristics of optimism, distrust, risk aversion and emotion, as well as ethics. It was also shown that psychological and moral characteristics affected turnover, trading volume, risk sharing, risk appetite. In addition, one of the most important results is a combination of behavioral factors (optimism, overconfidence, emotion, risk aversion and ethics) and market efficiency (trading volume, turnover, risk appetite and risk sharing). Conclusion: The obtained results indicate the effect of emotional and psychological and moral characteristics and characteristics on the behavior of investors and is important to drive the market towards rationality and on the other hand as a basis for designing investment strategies for investment managers.

Risk parity is perceived as one of the stock portfolio selection models that have received a lot of attention since the US financial crisis in 2008. The philosophy of this model is to allocate the same amount of portfolio risk between the constituent assets. In the present study, the combined portfolio selection model of relative robust risk parity is introduced, which uses the worst-case scenario approach on the covariance matrix parameter appearing in the robust risk model in portfolio robustness. According to historical data, several scenarios are considered for the covariance matrix. The objective function value of the hybrid model for each portfolio (feasible point) is the worst result (with most volatility) among the set of scenarios.  Finally, the model selects a portfolio for which the worst possible result has the least relative volatility. The research portfolio consists of 8 industries from Tehran Stock Exchange in the period 2011 to 2020. This portfolio has a higher Sharpe ratio than conventional models of mean-variance and weight parity, and is more resilient to market declines than the two models and produces less loss. Therefore, risk-averse investors are advised to use this stock portfolio selection model as a cover to face severe market declines.