fariborz avazzadeh fath

The main goal of this research is to develop a model for an integrated reporting framework with an Islamic approach. First, the researcher determined the framework's structure and components using theoretical foundations. Then, the structure and components of the framework were modified and finalized by the experts with the knowledge base. A structured form of the components was used twice to judge 32 experts in integrative reporting. The final model was determined by combining the Delphi technique with fuzzy logic and nonlinear data analysis. This template includes 7 Guidelines and 8 Content elements. In the Islamic section, several principles were determined as a guideline and several components were set to contribute to the content of the Islamic part of the report.

Many researchers proved that hybrid models have better results in comparison with independent models. A combination of different methods could enhance the accuracy of time series prediction. Hence, this research used the hybrid of three methods of chaos theory, multi-layer perceptron and metaheuristic algorithm to increase the power of the model forecasting. Artificial neural networks have properly considered complex nonlinear relations and are good comprehensive approximators. Multi-objective evolutionary algorithms such as multi-objective particle swarm optimization are good at solving multi-objective optimization issues. This algorithm organized the combination of parent and children populations by elitist strategy, decreased the messy comparing factors to improve the solution variety and avoided to use of niche factors. Chaos theory controls the complexities of stochastic systems. So, this research offers Tehran Stock Exchange Index (TSEI) prediction by a hybrid model of chaos theory, multi-layer perceptron and metaheuristic algorithm. The results show that in perceptron-based mode, RMSE measures are gradually increased in all intervals. The continuous decrease of RMSE shows that the perceptron-based model could show consistency with the whole data flow. This matter could offer a better learning and consistency process by perceptron-based models to predict stock prices, as this type of learning could apply more experiences for forecasting future behaviour in order to change the system content.

The purpose of this research was to provide a model for predicting time series of financial information based on the Lyapunov representation of information using chaos theory. This research is applied in its purpose, which is conducted using a quantitative approach. The research ranks as descriptive-causal accounting research based on actual information in companies' financial statements. The research method is the "post-event" type and was carried out using chaos theory and Saida's method based on the Lyapunov view. The findings showed that during the ADF test, the null hypothesis was rejected at a level of less than 5% type 1 error and 95% confidence, and it shows that the data is not static. During the substitution analysis test and its significance level, the behavior of the time series of the main financial information is significantly different compared to their substitutes. The obtained value was calculated to describe the production process of all data sets for μ = 2, ApEnMax equal to 0.65 and rMax equal to 0.32, and for μ = 3, ApEnMax equal to 0.6 and rMax equal to 0.44. The value of the Lyapunov profile in stability at a certain point is less than zero and in the limited cycle of stability is equal to zero and in chaos, it is greater than zero and smaller than ∞, and in noise it is equal to ∞. The results show that higher returns, encourage investors to invest and increase the flow of capital. It is believed that companies' stock returns are a function of systematic risk, and systematic risk represents the changes in the return rate of a share compared to the changes in the return rate of the entire stock market.

Considering the issue of selecting an optimal and desirable stock portfolio, which all investors, both individual and institutional, face.

The purpose of the current research is to present trading systems with innovation based on neural networks and metaheuristic algorithms grounded in technical analysis. Therefore, the criteria affecting stock selection in technical analysis have been examined. Consequently, from among the companies listed on the Tehran Stock Exchange during the years 2011 to 2021, 135 companies were selected as samples through a systematic elimination method and analyzed using a combination of innovative neural network methods and metaheuristic algorithms.

The results have shown that such a trading system produces comparable or better results compared to Buy & Hold and other trading systems for a wide range of stocks even over relatively longer periods.

For future work, it is planned to focus on combining more technical parameters and using convolutional neural networks (CNN) or other deep neural network models.

The purpose of the current research is to examine the effect of underreaction and overreaction on the risk distribution of the Iranian capital market. The current research is a post-event descriptive and applied type in terms of purpose. The target statistical population is all active and accepted companies in Tehran Stock Exchange, whose shares were traded in Tehran Stock Exchange from 2010 to 2019, and the statistical sample was selected based on the method of systematic elimination of 182 companies. In order to collect the required data and financial information, primary and secondary data such as reports of financial statements and audited financial statements of stock companies for a period of 10 years have been used and analyzed by Eviews9 software. For the inferential analysis of the variables, various statistical tests were used, including the Limer and Hausman F test, regression test, and panel data. The results of the research showed that there is a positive and significant relationship between underreaction and overreaction with Iran's capital market risk. In other words, incorrect pricing leads to underreaction or overreaction in stock prices from the psychological deviation of the investor, such as the investor's misunderstanding of the company's profit.

Integrated report as the last type of report in the evolution of reporting, although it tries to expand the content of information by integrating financial and non-financial information, it has not been able to provide the information required by Islamic societies. The integrated Islamic report can be different in terms of framework, content, format and credibility compared to the international framework of integrated reporting. The focus of this research is only on the content part, because the purpose of this research is to determine the content elements of the integrated Islamic report and their components. Focusing on the second dimension of the integrated Islamic accountability model of Kumaraldin and Madaziz (2019), i.e. accountability to what, and examining theoretical sources and previous studies and establishing the international framework of integrated reporting, first the elements of the content of the integrated Islamic report and the component The values of each of them were determined. Then, using the Delphi technique, the components were subjected to the judgment of 32 experts in two consecutive rounds. In order for the model to be more reliable, the components approved by the experts were put to a public survey using a questionnaire. After analyzing the data obtained from the judgment of 393 people, using spss software, the content elements and their components were determined and ranked. The content of the integrated Islamic report includes 18 Islamic components that are not present in the international integrated report.

The purpose of this research is to first examine the necessity of preparing a theoretical framework and integrated reporting with an Islamic approach and then determine the goal, approach, audience and scope of an integrated report with an Islamic approach. This research has been done in two separate parts. In the first part, the opinions of 32 experts in integrated reporting were received in successive rounds and analyzed using the fuzzy Delphi technique. In the second part, the results obtained from the first part were exposed to a public survey. The opinions received from 393 respondents were analyzed using SPSS software. The results show the necessity of preparing a theoretical framework and an integrated report with an Islamic approach by organizations. Also, the results showed that integrated reporting with an Islamic approach should pay attention to more audiences than international integrated reporting. The purpose of this research is to first examine the necessity of preparing a theoretical framework and integrated reporting with an Islamic approach and then determine the goal, approach, audience and scope of an integrated report with an Islamic approach. This research has been done in two separate parts. In the first part, the opinions of 32 experts in integrated reporting were received in successive rounds and analyzed using the fuzzy Delphi technique. In the second part, the results obtained from the first part were exposed to a public survey. The opinions received from 393 respondents were analyzed using SPSS software.

It is very important to choose an efficient monitoring system to assess the financial distress of banks, therefore, one of the most important monitoring systems used to assess the financial distress of banks is the CAMELS monitoring system. Which includes six indicators; Capital adequacy, asset quality, management quality, revenue quality, liquidity, market risk sensitivity. Therefore, in this study, the criterion of financial helplessness of banks is CAMELS indicators. Initially, 17 banks listed on the Tehran Stock Exchange in the fiscal year 1399 were ranked and divided into healthy and helpless financial groups by CAMELS indicators. Then, models, Data Envelopment Analysis and logistic Regression were used to predict the financial distress of banks. Then, with the pairwise comparison test (T), the prediction accuracy of both models was investigated. In logistic regression method, binary model with ForwardlR method was used. And in data envelopment analysis method, SBM model with different application was used. The results showed that the overall accuracy of the logistic regression model is higher than the data envelopment analysis model in assessing financial distress and also the CAMELS monitoring system can be a good assessor for banks' financial distress.

Organizations differ in terms of goals, environment, technology, complexity, etc., and this differentiation requires the use of different tools and models. Therefore, patterns are a function of the type of organization. In this study, the discussed research models include the four models of historical cost, Flemholtz, replacement cost, and Low and Schwartz as dependent variables, and the indicators of the same model as independent variables.

This research was descriptive (non-experimental) and survey tools including a questionnaire collected the required information. The study's statistical population includes pharmaceutical companies, including companies active in the production of drugs, and electronic tools such as the facilities of the Press Line site have been used in data collection.

The research findings indicate that the nature and structure of institutions significantly impact the efficiency of human resource accounting models. Observing the appropriateness of the model type with the institution's nature is undeniable and necessary.

Among the four common human resource accounting models that have been studied in this study, including historical cost models, Flamholtz, full replacement cost, and Lev and Schwartz, the Flamholtz model was the most consistent one with the environment of pharmaceutical companies.

The main purpose of this study is to investigate the impact of economic uncertainty criteria on tax management in accepted companies in the Tehran Stock Exchange. In this study, we used three criteria of tax management including tax avoidance, tax evasion and Tax aggression, as well as measuring economic macro-variables uncertainty from four criteria of GDP, inflation, exchange rates and interest rates using the Arch and Garch indexes. To this end, three hypotheses have formulated to investigate this issue and the data of 108 company members Tehran Stock Exchange have collected and analyzed for the period of 2011-2018. The research regression model has investigated and tested using Fama Macbeth two-step method. The final results show that the economic uncertainty criteria (GDP growth, inflation rate, exchange rate and interest rate) have a positive and significant impact on all three criteria of tax management namely tax avoidance, tax evasion and Tax aggression.

Empirical evidence shows that companies are trying to reduce or defer their income taxes. This study examines aggressive tax policy as a tool for tax reduction. The present study seeks to provide empirical evidence to compare the performance of linear methods such as correlation-based methods and relief with other models before reducing the variables in predicting the criteria of bold tax policy of companies listed on the Tehran Stock Exchange. The usefulness of correlation and relief methods for selecting optimal predictor variables was also evaluated and compared. For this purpose, data related to 108 companies for the period between 1389 to 1397 were reviewed and tested using the panel data method. The results indicate that there is a significant difference between estimating all research variables and using variable reduction methods. The results also show that the usefulness of Relief method in modeling the factors affecting aggressive tax policy is more than the correlation method. In addition, the results showed that the uncertainty of macroeconomic variables has a positive and significant effect and factors of audit quality, product market competition, and the characteristics of CEOs have a significant negative effect on aggressive tax policy.

The purpose of this study is to investigate the effect of CEO's power measures on tax management in listed companies in the Tehran Stock Exchange. In this study to evaluate the tax management, three scales which are tax avoidance, tax evasion and tax aggression is used. The data of 108 companies listed in Tehran Stock Exchange from 2010 to 2017 are sellected. The regression model of the research is tested by panel data. The results show that the CEO's power has a negative and significant effect on tax management by using all three measures. That is, powerfull CEO's due to thier stock ownership, expertise, experience, more independence, have long term investment horizons, worry about tax penalties and also in order to prevent damaging to their reputation and to prevent increasing the transaction costs in tax management and non-tax cost, do less tax management. It is suggested that users always pay attention to this point in their investment decisions that decreasing of tax management leads to increasing liquidity risk and investment risk too.  </em></strong>