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We consider a class of fuzzy stochastic differential equations (FSDE), in which the integrands of the stochastic integrals are not adapted to the duration generated by a Wiener process. Such equations with randomness, fuzziness, and non-adapted processes can be applied in financial models. We discuss the existence and uniqueness of strong solutions. We consider a class of fuzzy stochastic differential equations (FSDE), in which the integrands of the stochastic integrals are not adapted to the duration generated by a Wiener process. Such equations with randomness, fuzziness, and non-adapted processes can be applied in financial models. We discuss the existence and uniqueness of strong solutions.

Objective: A study of the movement of the insurance industry returns shows that the movement of income returns was less than the movement of the insurance industry. The movements of lower income returns than the movements of paid losses of the insurance industry in the economy are due to various variables, including the management of the insurance industry, part of which is due to risk recognition. Which helps managers in the insurance industry, to the extent of tolerable and intolerable risks in the acceptance or non-acceptance of various swimming risks, and by managing them play an important role in marketing and increasing the demand for insurance and in general, In line with the optimal growth of the insurance industry. Methodology: This study, using generalized conditional autoregression models, ARIMA-GARCH / TARCH and beta coefficient, has evaluated the impact of risk on the return of the insurance industry in the Iranian economy during the period 1350-1398. Results: The results showed that there is a significant relationship between the study of the impact of risk on the return of Basma industry. Also in this research, systematic risk has been investigated using the beta coefficient method. Since the result of the impact of risk on the return on income of the insurance industry is 67%. Because the obtained beta coefficient is less than one and greater than zero. This result indicates that the income of the insurance industry is smaller than the general trend of market movement and risk aversion

So far, readabilityof disclosure concepts and the behavioral features of investors have not been addressed appropriatedly in Iran despite their importance and there is not even a suitable tool to measure it in the country. Therefore, it seems necessary to conduct research in Iran to introduce the concept of disclosure readability, its measurement and the impact of business strategy on the readabilityof disclosure of financial statements. Therefore, the current paper evaluated the effect of the type of business strategy on the readability of financial statements of companies listed on the Tehran Stock Exchange. This is an applied causal (post-event) correlational paper. The statistical population of the study is all companies listed on the Tehran Stock Exchange. Using the systematic elimination sampling method, 129 companies were selected as the research sample and were surveyed in a period of 5 years from 2015 to 2019. EViews 9 and regression were used to test the research hypotheses. The results show that the type of business strategy affects the readability of financial statements of companies listed on the Tehran Stock Exchange.

The main purpose of this study is to determine the real and dynamic relationship between returns and stock market fluctuations in different time horizons so that its key results can measure the predictive power of returns and stock market fluctuations in determining the level of economic activity of investors. Accurate measurement of these relationships helps investors predict stock market movements in the future and Develop, plan and implement their own investment strategies in each time horizon. In this research Maximal overlap discrete wavelet transform has been used to investigate the relationships between industries return fluctuations and stock main indices in different time horizons from 2011 to 2020 have been estimated. The results showed that the wavelet variance of the rate of return varies in different industries. The return of investment companies on various time scales is equal to the investment return of the banking industry. The variance of the total index is less on different time scales than the value of the cash index.

Banks play an important role in the growth and development of any economy. A profitable banking system enhances economic stability and efficiency to mitigate the impacts of sudden macroeconomic shocks. To be more efficient and profitable, banks need to recognize the factors underpinning their performance. Accrued liabilities are one of the factors that hinder the profitability of banks. There are several methods to assess banks' profitability with their own pros and cons. Among them, data envelopment analysis (DEA) has been recommended as one of the most common approaches to evaluate different efficiencies including cost efficiency, revenue efficiency, technical efficiency, and finally profitability. The availability of prices/weights of inputs and outputs provides financial managers with significant information for evaluating efficiencies and assists them in decision-making and strategy development processes. This study mainly aims to analyze banks' profitability by considering accrued liabilities resulting from undesirable factors, for which relevant data were collected from 33 branches of a commercial bank in Gilan province, Iran based on managerial and weak disposability. The results illustrated that only three branches were graded one in three dimensions of efficiency, namely technical, cost and revenue, and profitability. Besides, it was suggested that the lack of these efficiencies was not correlated with the branches' profitability.

In this paper, we use fuzzy numbers and possibility theory to model possibility. The purpose of this work is to determine the optimal investment model based on the neural network method for fuzzy LR, trapezoidal and triangular numbers in an optimal portfolio. It is listed on the Tehran Stock Exchange to maximize "returns" and reduce "risk" to find the optimal portfolio. Therefore, to achieve this goal, the problem of multi-objective nonlinear programming is addressed. Also, by substituting the mean-variance model and the standard mean deviation instead of the Markowitz mean-variance model, the selection of the optimal portfolio in the possible space is examined. Finally, after calculating the model of the possibility of fuzzy numbers, we reach the optimal stock portfolio, which can be used to set the stock portfolio that has the highest returns and the lowest risk.

The financial sector plays a central role in economic development and growth, and due to playing an intermediary role in allocating resources to all sectors of the economy, by reducing financing costs and encouraging savings and their efficient use, a major contribution. In the long-term economic growth of the government in oil-exporting countries, relying on oil revenues, it is possible to enter the financial markets extensively and make various changes in it. The main goal of policymakers from such changes is to stimulate economic growth. But studies in this area show that fiscal development does not necessarily lead to economic growth. However, in recent decades, the role of financial development in economic growth has been forgotten. Therefore, this study examines the impact of the development of financial institutions on economic growth. The statistical population of the present study consists of MENA member countries in the period 1980 to 2019. In order to conduct this research, due to the nonlinear relationship between the research variables, the PSTR model and Markov switching time series pattern have been used. Financial depth, accessibility and efficiency are also variables in the development of financial institutions that have been considered in this study. The results indicate that all three components of the financial institutions development index have a significant effect on the economic growth variable.

This study focuses on providing an intelligent credit risk management system of the bank in the presence of the macroeconomic indicators using a combined methodology of econometrics and artificial intelligence. In addition to the use of scientific documents and reports, the panel data related to the annual reports and datasets of stock exchange banks are analyzed by using the MATLAB programming environment. One of the most important results of the this paper is that the proposed approach has been based on the calculations made with the GARCH economic model in which the input values of the component "Inflation rate factor (A4)” have a weight of 0.943734 (equivalent to the membership function "High H"); the component "rate factor Bank deposit (B4)” has a weight of 0.959346 (equivalent to the "High H" membership function); the component “Unemployment rate factor (A3)” has a weight of 0.990343 (equivalent to the "High H" membership function); the component "Exchange Rate Factor (B2)" has a weight of 0.990413 (equivalent to the membership function "High H"); And the component "GDP growth rate factor (A1)” has a weight of 0.959256 (equivalent to the membership function of "high H"); This means that, 5.46 is within a range of 6, i.e. the target variable is exactly in the 91st position (the fifth level of the system output is excellent).

The increasing progress of technology has affected all aspects of human life. One of the new technologies for which various applications have been created today is virtual reality technology. Virtual reality seeks to create a sense of reality in an unreal environment. The aim of this research is the effect of virtual reality technology on the creation of customers' attitudes and understanding of property and service providers in the real estate consultant department in Shiraz. The statistical population includes all real estate clients and those who refer to the real estate sector in Shiraz, and since the population is considered, it is unlimited; The number of statistical sample is 384 people. In this research, the standard questionnair of Players and Ponsin (2020) were used to collect research data. Structural equation modeling approach and PLS3 software were used for data analysis. The results showed that virtual reality technology has a significant effect on creating the attitude and understanding of customers towards the property and the service provider in the real estate consultant sector. The combination of virtual reality technology with augmented reality is one of the measures that can significantly improve the attractiveness and efficiency of using virtual reality in the field of real estate.

The human resource management works closely with all the employees in the organization. An HRM must allow the employees to make constructive criticism when there is a need for it. The duty of organizing the company towards achieving their set goals lies in the hands of the HRM. A Human Resource management process can best be distinct as a tool which is utilized to collect, organize, present, keep and share applied information about the human resource of an organization. To this end, this research present a Throughput model framework that describes individuals' decision-making processes in an algorithmic HRM context. The model depicts how perceptions, judgments, and the use of information affect strategy selection, identifying how diverse strategies may be supported by the employment of certain decision-making algorithmic pathways. In focusing on concerns relating to the impact and acceptance of artificial intelligence (AI) integration in HRM, this research draws insights from multidisciplinary theoretical lenses, such as Al-augmented and HRM assimilation processes, AI-mediated social exchange, and the judgment and choice literature. Results highlight the use of algorithmic ethical positions in the adoption of AI for better HRM outcomes in terms of intelligibility and accountability of AI-generated HRM decision-making, which is often underexplored in existing research.

The financial anomalies, which have brought about challenges for the nature of efficient-market hypothesis, provide ample experimental evidence on the deviation of market from rationality. According to the efficient-market hy-pothesis, investors avail themselves of all the information available in the market, and then attempt a thorough and painstaking interpretation of it. The empirical evidence, however, reveals that most investors fail to imple-ment rigorous information processing, thereby rendering to a number of behavioral theories concerning market inefficiency and biased information processing. The current research sets out to identify and scrutinize the im-pact of the CEO’s perceptual biases in judgment and economic decision-making on the reporting quality of the firms listed on the Tehran Stock Ex-change. The Purpose of this study CEO Overconfidence and Overinvestment by Role of Economic moderators Tehran Stock Exchange (TSE). One hun-dred five companies were selected as the sample size by systematic removal sampling reviewed in 2012-2019. Due to its dichotomous dependent variable, this study uses probit regression to test the research hypotheses. The results indicated the significant positive effect of CEO overconfidence on overin-vestment. It was also noted that Exchange Rate strengthens the positive effect of CEO overconfidence on overinvestment. Based on these results, the CEO's decisions as a decision-maker in charge of any company, especially under inflationary conditions, can play a substantial role in future corporate investment levels. The findings reveal that the indices of the CEO’s percep-tual biases in judgment and economic decision-making exert a significantly negative effect on financial reporting reliability and competitiveness.

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.

The main drivers of value creation in a ‘brand community’ are social networking, community engagement, impression management, and brand use. Marketers are therefore interested in determining which factors affect the value creation practices. This study examines the impact of the Interactivity of Electronic Word of Mouth (EWOM) systems on value creation practices in a brand community, which in turn influences the loyalty of the customers. In this regard, a conceptual model was developed and tested by the researchers of the current study. The results indicate that perceptions of the users regarding the interactivity of EWOM systems, highly impact only three of the four value creation practices including community engagement practices, impression management practices, and brand use practices. Furthermore, the researchers found that collective value creation practices could significantly and directly enhance brand loyalty. Several theoretical contributions and managerial implications were also discussed