Advances in Mathematical Finance and Application (AMFA)

The goal of investors in forming a stock portfolio is to obtain the highest return for bearing the lowest risk and portfolio optimization is one of the most complicated problems in the field of finance and investment. It is an NP-hard problem, and in general there is no definite method in polynomial time to find an exact solution for it. In this research, to solve the problem of choosing the optimal stock portfolio, the multi-criteria decision making method has been used under conditions of uncertainty. In order to implement the algorithm and evaluate it, the monthly returns of the Tehran Stock Exchange indices were used between 2018 and 2013. The results can be examined from two different perspectives. From an analytical and technical point of view, the results can be discussed. From a technical point of view, presenting a new technique for doing things can give the capital market participants the confidence that they can choose a stock portfolio using a new tool. From an analytical point of view, the existence of decision making algorithms in providing the optimal portfolio is a new step that can be used in the combination of fundamental analysis and the use of dynamic stock portfolio.

Two policies of carbon tax are considered by many countries for reduce carbon emissions. First policy emphasized on tax and second policy notice subsidy for carbon emission control. The results show that according to conditions, two policies can effective on reducing carbon emissions and technology development. A carbon tax Policy is needed to reduce carbon emissions in logistics systems. The purpose of this paper is to present effect of carbon tax policies for logistics in Iran pulp and paper industry. The research method is descriptive and data collection is survey, Samples consists two groups. The first group are experts for proposing possible Policy and deter-mining evaluation indices and selecting the appropriate Policy. The second group are managers in pulp and paper company for choose an appropriate Policy. Effect of factors on carbon tax was determined by experts’ interviews and fuzzy mean. Two suitable policies that covers the fossil fuels, were selected for simulation by VENSIM software. We considered 10 years for test and 10 years for simulation. Results showed both policies affect pollution reduction, reducing the fossil fuels consumption, reduction of emissions and increase innovation in the logistics system. The second policy that is carrying out carbon tax is more effective than the first policy which paying subsidies to reduce emissions.

The equitable distribution of income is considered as a development indicator in countries. Thus it is required to identify factors impacting the equitable distribution of income to make suitable policies to improve it. The present study aims to determine the optimal inflation rate in order to minimize income inequality by using the dynamic stochastic general equilibrium (DSGE) method in Iran during 1997-2017. The results revealed the optimal inflation rate to be 3.74%. An increase or reduction in the optimal inflation rate of 3.74% enhances income inequality. Thus, the government should target the inflation rate in its policies to achieve minimum inequality. Hence, inequality fluctuations (rises and declines) will be probable.

Several research investigations have indicated that asset returns exhibit notable skewness and kurtosis, which have a substantial impact on the utility function of investors. Additionally, it has been observed that Average Value-at-Risk (AVaR) provides a more accurate estimation of risk compared to variance. This study focuses on the computational challenge associated with portfolio optimization in an uncertain context, employing the Mean-AVaR-skewness-kurtosis paradigm.The uncertainty around the total return is con-sidered and analyzed in the context of the challenge of selecting an optimal portfolio. The concepts of Value-at-Risk (VaR), Average Value-at-Risk (AVaR), skewness, and kurtosis are initially introduced to describe uncertain variables. These concepts are then further explored to identify and analyse relevant aspects within specific distributions. The outcomes of this study will convert the existing models into deterministic forms and uncertain mean-AVaR-skewness-kurtosis optimization models for portfolio selection. These models are designed to cater to the demands of investors and mitigate their apprehensions.

Systemic risk is a type of financial instability that disrupts the functioning of the financial system and affects economic growth. The present study was developed with the aim of presenting a systemic risk warning model based on the entropy criterion in the financial markets of Iran. In terms of direction, the present research is of applied type and in terms of explanatory purpose, and the data collection method is library method. The statistical population of the country's financial markets research includes the capital market, money market, etc., and the time frame of this research is the data related to variables affecting systemic risk in the years 1998 to 2022. In this research, firstly, the identified criteria and indicators affecting systemic risk were ranked using Shannon entropy, Rennie entropy, and Tsallis entropy, and then systemic risk was measured with the MES criterion. The results of this research show that the most systemic risk is caused by the variable of banks' debt to the central bank, and the two variables of government debt and the ratio of government debt to GDP also have the highest systemic risk. According to the general theory of systems and the effectiveness and influence of financial markets on each other, the government and policy makers of the economic and financial sectors must take the necessary measures in order to create a systemic supervisory institution.

Resource management is a part of project management and its ultimate goal is to achieve maximum efficiency with the lowest level of inventory. Resource management is built around optimization and increased efficiency. In this paper, inventory optimization is done using fuzzy approach and statistical averaging methods are used to solve fuzzy multi-objective linear programming problems. These methods have been used to form a goal function of fuzzy multi-objective linear programming problems. First, in order to optimize inventory and find the weight of each product in Isfahan Steel Company, a model of fuzzy multi-objective linear programming problem is estimated. The highest weight of products is related to commodity ingots and the lowest weight related to other products. The Fuzzy Multi-Objective Linear Programming Estimation Model has compared the statistical methods with the Chondrasen method. The results show that this method has the capacity to optimize the amount of inventory, reduce storage costs and reduce interest costs due to working capital.

The main goal of this article is to Investigating Factors Affecting the Financial Wealth of Insurance Companies in Iran. The method of this article is descriptive in terms of practical purpose and library data collection method. The data collection tool in this article was a standard questionnaire that was adapted from Masoumi et al.'s questionnaire and model. The statistical population of the research is all the experts in the country's insurance industry. The results of this article showed that the country's insurance industry experts, including university professors and senior managers of Iran Insurance Company, agree with these four main risks in the Financial Wealth model . However, these four main risks are not enough for the model of Financial Wealth . In the final, the optimal pattern of financial wealth in the Iranian insurance company includes four main pillars, which include 6 basic and general contain asset/liability mismatch risk, reinvestment risk, exchange rate risk, international market risk, life insurance account separation risk from non-life insurance account, life insurance account investment risk risks in the insurance industry each of the basic and general risks of the insurance industry also has several risks and sub-categories.