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Objective: The stock market and the foreign exchange rate market have been sensitive segments of the financial market. These two markets are rapidly affected by fluctuations and business cycles in the economy and quickly reflect the economic change. At the same time, turmoil in one or both markets raises concerns among market policymakers. We also address the question of whether the national currency can be strengthened through the stock market.Methods: This study examines the stock market price on the value of the national currency of Iran using stock-oriented models and the Markov switching method in the period 1995 to 2021. In this study, the non-linear Markov switching method was used to estimate the model, and the LR- test method was used to check the linearity or non-linearity of the models. Akaike's test has also been used to determine the number of Markov switching regimes.Results: The research results show that for every one percent increase in stock prices, the exchange rate has decreased by 0.21 percent. Therefore, the results indicate the approval of stock-oriented models in the Iranian economy. In other words, the capital market is one of the determinants of the exchange rate.Conclusions: According to this model, lower stock prices reduce the wealth of domestic investors, which leads to lower demand for money with lower interest rates. Lower interest rates cause capital outflows to overseas markets, assuming other conditions remain stable, causing the domestic currency to depreciate and the exchange rate to rise.

Objective: Recent literature emphasizing the importance of income distribution for pollution. The GINI index is the most common indicator for measuring income inequality in previous studies. The new literature has focused on relative redistribution, which is quantified by the GINI coefficientis defined as the difference between the GINI based on market income and GINI based on disposable income. Thus, this study relies on the redistributive effect of taxes and transfers and its impact on carbon dioxide emissions.Methods: The study is conducted using aggregated data from oil-exporting countries including Canada, the United States, the UK, Mexico, the Netherlands, Russia, and China between 2010 and 2020 by using a simultaneous equations system consisting of two equations so that economic growth and pollution emission are as endogenous variables. Elative redistribution, good governance, oil income, trade openness, and CO2 emission are the exogenous variables. Results: Based on model estimates, income inequality, good governance, and oil income have a positive and significant impact on economic growth over the years studied, while inequalities in human development and population growth rates have a negative impact. Economic growth and trade openness also have a negative and significant impact on the spread of pollutionConclusion: Taxes and transfer payments, as redistribution tools can stimulate economic growth. Relative redistribution as a more equitable way can lead to increased economic growth and economic growth reduces carbon dioxide emissions. Therefore, providing an appropriate standard of income inequality can help to better understand and formulate effective policies for income equality.

Industrial development depends on planning and formulation of strategy and systematic policies. The purpose of this research is to analysis phase of conventional strategies in order to progress of Iran’s industry in the international atmosphere. The statistical community of this study is included of experts and academic pundits. To do this at first identification of significant conventional industry’s strategy was determined. six strategies was founded and then was specified, using the criticality of each phase’s approach. According to data analysis, efficiency of technology transfer on industrial progress is more than other elements. On the second rank, domestic and foreign investment’s strategies, development of parent industries, development of infrastructure industries and designing strategy and industrial policies and finally government support strategies has been placed at the lowest level that means third rank. Therefore technology transfer plan was recognized as the most important strategy and specially it should be considered as the strongest strategy for developing industry. The insight that this model offers to managers and decision makers of the country’s industry can help them to plane strategy for developing.

Objective Using a quantitative approach and a systematic methodology, advanced structural equation modelling techniques were applied to test the research hypotheses. In a possible sample of 98 experts and activists of entrepreneurship in Sistan and Baluchistan province, the observations were collected using a standard 32-items tool based on Likert scale. After screening the raw data, covariance-based confirmatory factor analysis was used to evaluate the validity, reliability and fittingness of the research model, and the hypotheses were tested in the form of a structural model. The results of convergent and divergent validity tests showed that the two indicators of the research model has validity. Also, the reliability tests indicated the generalizability of the research results at 85%. Also, all the research hypotheses were confirmed.Objective Using a quantitative approach and a systematic methodology, advanced structural equation modelling techniques were applied to test the research hypotheses. In a possible sample of 98 experts and activists of entrepreneurship in Sistan and Baluchistan province, the observations were collected using a standard 32-items tool based on Likert scale.

The optimal portfolio selection is vital for investment. The risk of portfolio Selection and return is the most critical concern of investment companies and private investors. According to modern portfolio theory, diversification should cover the risk. This theory is based on the normality of assets return. Experimental findings indicate that the assets return non-normality. Higher moments are sed to upgrade traditional models with the primary presumption of a normal distribution in recent years. This study uses a higher moment and the entropy for diversification and selects a portfolio given a non-normality assumption. It is essential to use up-to-date information to increase the model's efficiency, and accordingly, we used the rolling window for new price information. For the financial information method, we use the total index return in the last five working days and weigh the shares of the banking, insurance, and leasing industries on the next working day and evaluate this for three years. Python, math, and NumPy libraries were used to analyze the data. The results show that a much higher moment model can provide better portfolio selection results in most cases.

The purpose of this study was to design and formulate strategic liquidity management strategies in the banking industry. In this research, in order to combine qualitative and quantitative data, a sequential integrated exploratory method will be used, according to the classification model with emphasis on qualitative data. Therefore, according to its objectives, the present study is part of applied research and in terms of the research process is part of descriptive and exploratory research that was conducted in two parts: qualitative and quantitative. The statistical population of the present study was the qualitative part of the managers of the Welfare Bank. The sampling method was to achieve theoretical saturation and 25 people were selected as the sample size. Therefore, a survey was used to collect information and according to the data collection, two types of tools were used to review documents, interviews, and questionnaires, and the evaluation method of the questionnaire was performed with a 5-point Likert scale. The Cronbach's alpha questionnaire was used. SWOT analysis was used to analyze the data. The results showed that the Welfare Bank has many opportunities to develop appropriate liquidity management strategies. As it was observed, the chart stretches towards the opportunities and strengths of the offensive situation, which requires strategic planning to use the strengths and opportunities, and 11 strategies were developed for this purpose.

Objective: To identify the components affecting the behavior of investors and to develop a measurement model using a confirmatory factor analysis approach.Method: This is a correlational paper to identifythe dimensions and structures affecting investor behavior first using TOPSIS technique and then with first-order confirmatory factor analysis and second-order factor analysis. The statistical population includes people who have been active in the Tehran Stock Exchange for at least two years with asample of 327. The sampling method is convenience nonprobability sampling. The data was collected through a researcher-made questionnaire. The expert approval and Cronbach's alpha coefficient were used to assess the content validity. Findings: the current paperidentified seven factors as effective factors on investor behavior according to the theoretical literature and research background using TOPSIS technique. In the next stage, the research findings using the confirmatory factor analysis approach indicate that the two factors of investor financial literacy and investor personality traits have the most effective role in investor behavior. Also, the factors of higher expected returns, rules and regulations, security, profitability, position and location of investment are the next effective priorities on the behavior of investors.

The role of the capital market is fundamental and decisive in the economy of all countries [6]. Studies show that in the capital market, prices are determined based on macroeco-nomic variables[2]. Accordingly, In this study is to provide a model for measuring the impact of economic policy uncertainty (EPU) on information asymmetryn.The research method is applied and has been made to present a model for measuring the effect of EPU on information asymmetry in the EVIEWS12 and MATLAB2021 software environment. The research time period is determined from 2011 to 2020 and 101 companies are selected based on the applied restrictions to estimate the model. In this study, 40 variables affecting EPU are entered into the According to the results of BMA, the most important variables affecting the EPU is provided[2]. Based on the principal components approach, the EPU index is calculated using the most important variables affecting this variable. Then, with the GARCH model, the uncertainty part of the EPU index is extracted, and finally, using the powerful nonlinear TVPFAVAR model, the shock caused by the EPU variable on the information asymmetry indices in the research period is analyzed. The results show that the shock caused by the fluctuation of the variable of EPU has increased the index of information asymmetry in recent years. Based on the results, EPU shock on the index of information asymmetry has had a stronger effect on in the short and long term information asymmetry than the medium term.

EXTENDED ABSTRACT INTRODUCTION In the oil market, the price of oil depends on the international supply and demand of oil. In general, the factors affecting the price of oil can be divided into two main groups: fundamental factors and non-fundamental factors. Oil has both physical and commodity aspects as well as assets. Changes in fundamental and non-fundamental factors lead to changes in oil prices. Supply and demand are among the fundamental factors and risks and uncertainties, psychological, political, and geopolitical factors, stock exchange and speculation activities in oil financial markets, etc., which cause sudden changes in oil prices are among the non-fundamental factors. One of the signs of the existence of uncertainty in an economic system is high fluctuation in economic variables. The interaction between oil performance and macroeconomics has long attracted attention in the economic literature. Attention to this issue dates back to the 1970s. The 1970s and early 1980s were marked by sharp jumps in oil prices. Adverse oil supply shocks are often considered the main source of macroeconomic fluctuations and stagflation in that period (Blinder & Rudd, 2008).The present study differs from other studies in two ways compared to other studies. In internal studies, uncertainty related to variables is mainly measured through the conditional heterogeneous variance pattern. The data is an indicator of uncertainty in this study based on the method of Baker et al. (2016) and based on the media. When analyzing economic phenomena in a regression framework, economic theory seldom provides distinct information about the functional form of the relationship between the dependent variable and its independent variables. The simple properties of regression functions – such as models that are linear in parameters – are widely used in experimental applications, as they facilitate both econometric estimation and the economic interpretation of estimated regression parameters. However, the assumption about the functional form of the regression function leads to an error of incorrect parameter specification, which can lead to incorrect economic results and recommendations. In recent years, the rapidly growing literature on nonparametric econometric methods has been a solution to the problems of parametric specification error in econometric regression models. Nonparametric regression methods do not require the researcher to assume and determine a functional form for the relationship between explanatory variables and dependent variables. Thus, the functional form is determined by the data instead of the researcher making arbitrary decisions. In this aspect, the present study is different from other studies. Therefore, in the present study, considering the role and importance of OPEC in the oil supply and demand and oil prices and its effect on the growth and production of wealth in the world, factors affecting the determination of OPEC oil prices with emphasis on economic policy uncertainty as a representative of non-fundamental factors affecting oil prices, are investigated for a selection of OPEC member countries from 2003-2017 using non-parametric regression. METHODOLOGY The methodology must be clearly stated and described in sufficient detail or with sufficient references. The author should concisely summarize the research framework, and the research methods applied in the study. The summary should include the identification of valid data sources used in the research.The statistical population in this study is OPEC member countries and the data consist of 6 cross sections between the years 2003-2017. The data were extracted from World Bank reports, the OPEC Database[1], the Economic Policy Uncertainty Database[2], the World Bank Database[3], and the OECD website[4].The variables of the OPEC real oil price model are dependent and independent including uncertainty of economic policy, industry value added index, real interest rate index, oil rents, renewable energy, and oil price expectations.                                                                  FINDINGS  By using the kernel regression: local linear estimator, the extent and direction of the effect of global economic policy uncertainty on oil prices is estimated. The table of meanings of the studied variables is given in Appendix One. The results show that the alternative energy index and the interest rate index are fixed with a durable interruption. Also, according to the diagram shown in Appendix 2, in most of the countries studied, the value-added index of the industrial sector, affects the real price of oil by interruption.In this section, using the findings of kernel regression: local linear estimator in Stata software, the research hypotheses are examined as follows:Uncertainty in global economic policy has a positive and significant effect on oil prices.Among the influential factors in oil prices, economic policy uncertainty has the greatest effect. Table 1. Core regression: Local linear estimator for 6 OPEC countriesSource: Resarch ResultLocal-linear regressionKernel: epanechnikovBandwidth: cross-validationNumber of obs      =           327 R-squared           =          0.9678Log opEstimateMeanLog op 4.210966EffectLog un Ope L rr Or L ind  L re 0.3522596 0.420129 -0.0003032 0.0209778 0.0169741 -1.228478 Based on the table, the results show that there is a positive and significant relationship between oil prices and economic policy uncertainty. In terms of the effect on oil prices, the Alternative Energy at -1.2, the Oil Price Expectations at 0.42, and then the Economic Policy Uncertainty at 0.35 have the most effect, respectively.According to the findings, it can be concluded that for a one percent change in the economic policy uncertainty index, the variable of oil price will change by 0.35 percent. For one unit change in the oil price expectations index, oil prices increase by 42%. The real interest rate with a period of 0.03 percent reduces the real price of OPEC oil; For one unit change in the oil rent index, OPEC oil price increases by 2 percent, and the value added of the industrial sector with a lag increases to the rate of 1.6 percent of the price of oil; the index of alternative and new energies with a lag leads to a decrease in oil prices by 12 percent. CONCLUSION The present study aims to investigate the effect of economic policy uncertainty on oil prices in selected OPEC countries. In determining the price of oil, fundamental factors including factors related to oil supply and demand, and non-fundamental factors including financial market conditions, speculation, and geopolitics are effective. Given that the countries under study are selected from OPEC and the production and sales quotas are determined by OPEC, factors such as the value added of the industrial sector in each country, alternative energy sources, oil rents, and oil price expectations are among the fundamental factors and the US Federal Reserve real interest rate and economic policy uncertainty are among the non-fundamental factors. Estimation of the model by nonparametric method shows that renewable energy has the greatest effect on oil prices so as the quota of renewable energy in the energy supply increases, OPEC oil prices will fall due to declining demand. The added value of the industrial sector has a positive and significant effect on oil prices. Because of the increase in industrial activities, the oil demand has increased and this will lead to an increase in oil prices. Oil rents have a positive and significant effect on oil prices as the difference between income from oil sales and oil extraction costs. Considering that the income from oil sales is due to the determination of oil production and sales quotas as well as oil prices in OPEC member countries, by reducing oil extraction costs the profitability of the oil industry has increased, and through increasing oil speculation, its prices increase. Oil price expectations, like market expectations for any commodity, affect prices. Expectations of rising oil prices will lead to higher oil prices due to increased precautionary oil demand. According to the research findings, an increase in the Federal Reserve's real interest rate will lead to a decrease in oil prices. On the one hand, raising interest rates increases the cost of maintaining oil on board, and on the other hand, it reduces the net present value of future profits, thus increasing oil supply. Rising interest rates on the Federal Reserve will reduce the price of savings bonds, treasury bills, and stocks. Thus, the profitability of speculative activities in the savings bond market leads to the transfer of cash flow from commodity exchanges such as oil and its derivatives and agricultural products to the savings bond and treasury markets. As a result, oil prices fall. The emergence and spread of economic policy uncertainty will lead to higher oil prices. Since oil has assets in addition to physical and commodity aspects, with the increase of economic policy uncertainty, the possibility of restricting the future supply of oil, as well as increasing precautionary demand and speculation of oil, increases the price of oil. Therefore, the unique situation of OPEC member countries means that the uncertainty of global economic policies is not the most important factor affecting oil prices, and the development of alternative energies has a much greater effect on oil prices, and this necessitates a change in policy and precise planning in oil-rich countries to use alternative energies and produce oil products instead of selling crude. Although the general policies of the system in the field of energy, the diversity of energy resources, and the replacement of exports of oil and gas and petrochemical products with exporting crude oil and natural gas have been emphasized, despite the development of a national energy strategy document in the country, operational and monitoring of its realization should be prepared in a suitable time horizon. [1] https://www.opec.org/opec_web/en/[2] https://www.policyuncertainty.com/[3] https://data.worldbank.org/[4] https://www.oecd.org/

Objective:Examining brand experience, value congruence,and customer engagement for tourism brand productivity.Given the significant effects that brand productivity in the tourism industry can have on a country's prosperity and economic progress, the primary objective of this research is to develop and empirically examine a conceptual model that elucidates the complex relationships among brand experience dimensions,brand value congruence, customer-brand identification, and brand productivity.Furthermore, the study investigates the moderating role of customer-brand engagement within this framework.Methods:The statistical population for this research comprises the tourists visiting the city of Isfahan.Given that the population is unlimited, a sample size of 400 participants was selected based on Cochran's formula, and the sampling method used was convenience sampling.The data was collected through a structured questionnaire.First, the validity and reliability of the measurement scales were assessed. Content validity and convergent validity were established, and the reliability was confirmed through Cronbach's alpha and composite reliability calculations. The results of these assessments were satisfactory. For data analysis, the researchers employed structural equation modeling techniques, utilizing SPSS25 and SmartPLS3.0 software.Results: Sensory experience, effective experience, behavioral experience, intellectual experience and brand value congruence have a positive and significant effect on customer-brand identification.Customer-brand identification has a positive and significant effect on brand productivity.customer-rand engagement can moderate the effect of brand-customer value congruence on customer-brand identification.Conclusions:The results of this research will help the authorities to promote and improve brand productivity in the tourism industry by focusing on customer-brand engagement, brand value congruence and customer-brand identification,and considering different dimensions of customer experiences.

The most important policymaker entity in the bank-centered economy of Iran is central bank of Islamic Republic of Iran which has always been trying to manage and improve macroeconomic indicators by applying monetary policies. However, investigation of Iran's economy after four decades shows that this country has always suffered from double-digit inflation rates and 15000-fold liquidity throughout this period, while GDP of Iran has grown only by two times during this period. This paper tries to evaluate the effect of monetary policies of central bank on macroeconomic indicators by analytical-descriptive and library method via combining system dynamics and fuzzy multi-criteria decision-making using Vensim and Super Decision software. Monetary policy instruments in this re-search include foreign exchange rate, deposits interest rate, facilities interest rate, required reserve ratio, and open market operations. Further, the macroeconomic indicators include inflation, liquidity, national foreign exchange value, and eco-nomic growth. The results indicated that the most important macroeconomic indi-cators in the country according to economic experts are "national foreign ex-change value" and "inflation". The most important tool for monetary policies of central bank is "foreign exchange rate". Indeed, in order to improve the economic misery index, this bank should take measures to improve the national foreign exchange value, then manage inflation and liquidity, and eventually adjust the banking interest rate

This paper aims to investigate the portfolio optimization under various market risk conditions using copula dependence and extreme value approaches. According to the modern portfolio theory, diversifying investments in assets that are less correlated with one another allows investors to assume less risk. In many models, asset returns are assumed to follow a normal distribution. Consequently, the linear correlation coefficient explains the dependence between financial assets, and the Markowitz mean-variance optimization model is used to calculate efficient asset portfolios. In this regard, monthly data-driven information on the top 30 companies from 2011 to 2021 was the subject to consideration. In addition, extreme value theory was utilized to model the asset return distribution. Using Gumbel’s copula model, the dependence structure of returns has been analyzed. Distribution tails were modeled utilizing extreme value theory. If the weights of the investment portfolio are allocated according to Gumbel’s copula model, a risk of 2.8% should be considered to obtain a return of 3.2%, according to the obtained results.

It is well documented that using linear models to forecast plenty of financial observations due to their nonlinearity is not satisfactory. Therefore, in this paper, the technical analysis indicators are forecasted using Neural Network Auto-Regressive model with eXogenous inputs (NNARX). Then the effect of different factors (economic, systematic risk, company's properties and corporate governance) on their forecasting error (eRSI, eMA1, eMA2 and eMACD) was investigated. For this purpose, required data were collected using the removal sampling method for 323 companies listed on the Tehran Stock Exchange from 2014-2020. In addition, the mean absolute percentage error (MAPE) was applied to measure the error of forecasting technical analysis indicators. NNARX and dynamic panel data models (GMM) were used to study the effective factors on the error of forecasting technical analysis indicators. Results indicated that the error of forecasting technical analysis indicators is less than 0.1 and has sound accuracy. Also, the company's size and corporate governance indicators didn't significantly affect the error of forecasting technical analysis indicators. In addition, financial leverage doesn't significantly affect eRSI and eMACD but has a significant inverse effect on eMA1 and eMA2. On the other hand, return on assets has a significant inverse effect on eRSI, eMA1, eMA2 and eMACD. Also, economic recession and prosperity, inflation fluctuations, exchange rate fluctuations and systemic risk have a significant positive effect on eRSI, eMA1, eMA2 and eMACD.

Stock prices are influenced by economic, technological, psychological and geopolitical factors. A review of the literature in this field shows that stochastic approaches, trend analysis and econometrics have been used to demonstrate stock market dynamics and price forecasting. However, these techniques cannot provide a comprehensive overview of market dynamics. Because they ignore the temporal relationship between these factors and are unable to understand their cumulative effects on prices. By integrating chaos theory and continuous data mining based on price acceleration, this study has eliminated these gaps by inventing a new price forecasting method called dynamic stock market recognition simulator and combining two methods: one is delay structures. Or gives time intervals to the data set, and the other is the method of selecting new variables for the market environment. The results showed that the method used can be used to predict the long-term stock price using a small data set with small dimensions.

The main aim of this study was to identify and analyze the effect of social capital on entrepreneurial activities of Fars province specialized companies in Iran to improve their status. This descriptive research was accomplished using survey and required data was collected through questionnaire. Stratified random sampling was used and sample size was estimated to be 380 rural women. The validity and reliability of the questionnaire was confirmed by the viewpoints of professors as well as conducting a pilot study, calculating the Cronbach's alpha coefficient, respectively. Based on the results of path analysis, social capital and social networks activities had a direct and significant effect on entrepreneurial activities. Business plan writing skill, creativity, entrepreneurial motivation, family communication, supportive policies, educational-counseling policies, and business environments also had a direct and significant effect on social capital. Creativity, entrepreneurial motivation, family communication and educational policies had a direct and significant effect on social networking activities, as well. Enhancing the ability of entrepreneurs to start and continue entrepreneurial activities, paying attention to the role of social networks and their interacting as well as considering social capital as a link between business networks by identifying entrepreneurial opportunities and providing resources and facilities are essential in this regard.