نشریه تحقیقات مالی
پیاپی 71 (پاییز 1402)

Financial markets are considered to be a kind of complex network due to the interaction and interrelationship of its various actors. Therefore, the development of stock communication networks is an important issue for discovering potential connections between different companies. Therefore, the purpose of this research is to investigate and analyze the communication structure of companies in the capital market based on price, return, and trading volume of stock with a network approach.
 
This study employs a quantitative research methodology, specifically focusing on network analysis. The data were collected in the period between 2017 and 2021 and analyzed using the network analysis method and with the help of Excel 2021, SPSS 26, UCINET 6, and its complementary package NetDraw. In addition to the general analysis and review of the price, returns, and trading volume of the stock correlation network, the performance of each node in the network was also investigated using micro-indices. Centrality is one of the most important micro-concepts of network analysis, which examines the influence and importance of people in the network. Also, it was studied with three indices of degree, betweenness, and closeness of centrality of network nodes.
 
The results indicated that as the correlation basis expands, there is a decrease in communication between different companies along with an increase in irregularity. The higher the correlation basis, the less likely it is to be affected by a common variable or interaction, which will reduce the correlation between stocks. In addition, there are companies in the communicative network that are in a better position than the rest. They may have higher connections, faster access to information, and greater influence over other units' price changes. As a result, these companies can play a decisive and leading role, or in other words, the role of key and influential actors in the governing structure. Also, the results showed that in the second period of 2021 compared to the first period, communication networks were much more erratic and scattered.
 
Considering the importance of capital market communication networks and the decisive role of key companies, relationship pattern analysis helps to increase transparency, reduce risk, and, consequently, improve decision-making, policy-making, portfolio optimization, etc by revealing the network structure of the capital market. The results of this research can lead to a better understanding of the forces that create the communication structure of companies and enable policymakers to make better decisions. Therefore, all users are suggested to pay attention to the communication structure governing the companies in the capital market and the role and impact of their position on the advancement of the company's goals in their decisions and to consider this communication structure and the way power is distributed.

Today, there is widespread acceptance and emphasis on the role, function, and importance of regulation across all economic sectors, as encapsulated by theories of "regulation" and "regulatory governance." Within various economic sectors, banking regulation has been identified as particularly critical due to its inherent fragility. In addition, pursuing liberalization of financial and banking services, by deregulation and eliminating the current contradictory regulations, is found to be vital. The establishment of the World Trade Organization (WTO), as an entity for the expansion of free trade, including financial and banking services, is based on the same fundamentals. In this study, we seek to determine whether Iran's existing banking regulations could potentially hinder its accession to the WTO. Our investigation also tries to ascertain whether the WTO's legal framework mandates the adoption of specific levels of banking regulation. Ultimately, taking a broader perspective, we aim to describe and analyze the compatibility between these two seemingly contradictory concepts—regulation and liberalization.

In this article, which constitutes a qualitative legal study, we employed an analytical-descriptive approach as our research methodology. While the predominant approach in the first two parts is the descriptive method, the third part has a complete analytical approach. From a goal-oriented viewpoint, while our first two parts can be described as implied research, the last part has a fundamental approach.

The research outcomes reveal that Iran's current banking regulatory framework does not pose a barrier to its potential membership in the international organization. Specifically, while regulations more stringent than those established by the Basel Committee may hinder accession, the absence of such strict measures or non-compliance with Basel standards is not viewed as a hindrance. Additionally, it's noteworthy that the organization's legal framework does not mandate the adoption of any specific level of regulation, providing flexibility in this regard. The research findings also indicate that regulation can follow different types of objectives (including pursuing domestic goals, maintaining domestic and international financial stability, and liberalizing financial services trade) hence there is no conceptual contradiction between these two mentioned notions.

Our analysis uncovered no conflicts between the concepts of regulation and liberalization, either in terms of their conceptual compatibility or within the legal framework of the World Trade Organization. The lack of exact compliance between Iran’s banking regulations and the standards of the Basel Committee, will not act as an obstacle to the country’s accession to the World Trade Organization

Corporate financial policies are used as tools to maximize shareholders’ wealth. Liquidity risk is one of the main systematic risks affecting the equity cost of capital. This study is to investigate the relationship between dividends and the components of systematic risk of liquidity to discover the influence on the named risk.
 
In this study, the Amihud measure of liquidity and the liquidity-adjusted capital asset pricing model were used to measure and decompose the components of liquidity risk. The decomposed measures of liquidity risk included 1) the covariance of stock illiquidity and market illiquidity, 2) the covariance of stock returns and market illiquidity, and 3) the covariance of stock illiquidity and Market returns.
 
Findings showed that, according to the theoretical expectation, the covariance of stock returns and market illiquidity and the covariance of stock illiquidity and market return increase when managers distribute more dividends. The results also indicated that contrary to the theoretical expectations, the covariance of stock illiquidity and market illiquidity increases by dividend distribution. In addition, according to the findings, dividends can be used to manage the liquidity risk of equity leading to lower costs of capital and higher shareholders’ wealth. Mismanagement of this type of risk can destroy the liquidity risk effect of dividends i.e. dividends should be used to affect the appropriate channel of dividend risk or appropriate covariance. Based on the results of this study, Under conditions of low liquidity or market recession, dividend growth can boost the stock return and enhance liquidity to some extent. However, in an illiquid market, despite its positive impact on stock returns, dividend growth cannot significantly increase the liquidity of the stocks.
 
The dividend policy of the previous year can reduce the comprehensive measure of liquidity risk for the next one and thereby reduce the expected return of investors. Since the comprehensive measure is multi-dimensional, to investigate separately the effect of dividend distribution on dimensions of liquidity risk, , , and  were investigated as components of liquidity beta. The results showed that dividends have a positive effect on the covariance of stock returns with market illiquidity ( ) and the covariance of stock illiquidity with market returns ( ), but contrary to theoretical expectations, they positively impact the covariance of stock illiquidity with market illiquidity ( ). Therefore, the channel of the effect of dividends on liquidity risk is  and . Indeed, within a market characterized by high illiquidity, companies offering generous dividends can potentially achieve higher returns. i.e., the covariance of stock returns and market illiquidity increases by dividend growth, and the risk component related to  will be decreased. During a market recession, companies that offer high dividends tend to encounter reduced illiquidity. This means that the covariance between the stock's illiquidity and the market return increases, leading to a decrease in the risk component associated with β^4. However, the results proved that in a market with high illiquidity, companies with high dividends cannot experience less illiquidity and reduce the risk dimension related to  liquidity.

Both on micro and macro scales, the exchange rate and its dynamics play a pivotal role as influential variables in the economy. They can affect most economic, social, and cultural variables through various channels and change their behaviors. Given the importance of the exchange rate as a key variable in the Iranian economy, extensive studies have been conducted on the exchange rate and the associated concerns regarding exchange rate volatility. The rate affects many of the government's economic policies. In addition, since housing costs constitute the main household expenses in Iran, problems and limitations in providing housing can have a significant impact on the spread of social dissatisfaction. The purpose of this study is to investigate the effect of exchange rate instability on the housing price index in Iran. Therefore, analyzing the relationship between the exchange rate market and the housing market can help policymakers and economic decision-makers adopt appropriate policies in the foreign exchange market and housing sector.

In this study, the GARCH method was initially used to estimate the volatility of the exchange rate. Next, to investigate the effect of exchange rate instability on the housing price index from 1991 to 2020, the GMM time-series method was employed. Due to the dynamic nature of the model in this study and the need to establish conditions for generalized moment estimators, the use of this method seems appropriate. The GMM method is used for linear time-series models to ensure the conditions of moment estimators and incidental properties.

The results showed that the volatility of the exchange rate has a negative and significant effect on housing prices. Also, it was found that the interruption of the housing price index, oil revenues, inflation rate, liquidity, and urbanization all exert a notable and positive influence on housing prices. Additionally, the study's findings revealed a significant and adverse effect of variables such as interest rate, gold market return, and stock market return on housing prices within Iran's economy. The results of the tests used demonstrated that the estimation model is in a suitable condition in terms of statistical indicators.

Exchange rate volatility is of the parameters affecting housing prices. Accordingly, this study concludes that exchange rate volatility harms the housing price index in Iran. It is recommended that the central bank adopt appropriate currency policies to reduce volatility in the currency market and its effect on parallel markets, including the housing market. The results of estimating the coefficients of control variables are consistent and in line with the theoretical and empirical literature. Variables such as inflation rate, liquidity, and urbanization have a positive and significant effect on the housing price index. With an increase in liquidity, the housing price index in the Iranian economy increases, indicating that expansionary monetary policies have significant effects on the housing market in Iran.

Investors, in their pursuit to maximize expected returns, minimize risks in their stock portfolios, and achieve the desired benefits, require suitable methods and criteria to select stocks for their portfolios and allocate capital. One of the most important things in stock portfolio optimization is the use of a suitable optimization algorithm. The function of the multi-objective portfolio optimization model is quadratic. Quadratic functions are a special class of nonlinear programming problems in which the objective function is quadratic and the constraints are linear. Common algorithms for quadratic programming require certain parameters with fixed values. Such algorithms are extensively employed for solving real-world problems, particularly in financial contexts. The major objective of this research is to apply the inner point mathematical algorithm to optimize the stock portfolio and to use this algorithm to address the multi-objective portfolio optimization problem. With the GlueVaR risk measurement criterion, the problem of portfolio optimization takes into account the two objectives of maximizing returns during the research period and reducing investment risk, reassuring investors to make better and more accurate decisions about the final object of this research.

The necessary information for this study was provided by 50 active companies listed on the Tehran Stock Exchange. However, due to the availability of their daily prices during the study period, the final number of companies considered was reduced to 33. The inner point mathematical approach was utilized to optimize the model with the dual objectives of increasing efficiency and reducing risk. To demonstrate the effectiveness and capability of the algorithm in solving the problem of two-objective optimization, its output was compared with other risk measurement criteria such as variance, and value at risk (VaR). The investment risk in the stock portfolio was also calculated using the GlueVaR criterion. Comparing conditional (CVaR) was also done. The GlueVaR criterion has the advantage over the other criteria since it takes the investor's attitude toward risk into account. This advantage formed the basis of the calculation method in this research according to the mentioned algorithm.

According to the research, value at risk (VaR) and conditional value at risk (CVaR) perform better than other variance risk measures in the portfolio optimization model with the GlueVaR risk measure and the internal point optimization method for determining the most effective border. Additionally, when applied to optimization problems, the internal point method discovers the optimal point with fewer iterations, providing strong evidence of the algorithm's effectiveness.

Based on the current findings, it is evident that the internal point algorithm is effective in resolving stock portfolio optimization issues. Additionally, the GlueVaR risk measurement criterion outperforms VaR, variance, and CVaR for most investors with diverse risk and return preferences

During project management, certain risks need to be effectively mitigated. While risks are an inevitable part of every project, their perception, analysis, and management help organizations achieve goals. Risk management is now an important part of project management and has a specific function for improving the efficiency of implementing the project, saving prices, and improving the profitability of projects. Theories have demonstrated risk management as an influential and scientific management instrument to decrease risk levels. Accordingly, investigating the new methods of eliminating financial risk and financial risk management of projects is necessary to develop and improve risk management.
 
In this study, the related models and variables were introduced to identify the factors influencing project financing risk. Subsequently, general criteria were derived from the examined models and their associated variables. The study samples were drawn from experts and professionals within Iranian mining companies who had direct involvement in the subject matter. Variables were identified using the content analysis method, which involved utilizing MAXQDA software for theoretical and qualitative data analysis.
 
Financing methods, social risk, contractor risk, construction risk, political risk, design risk, legal risk, financial risk, management risk, customer risk, and sub-contracts are the categories governing the current research. Each item is composed of one or several concepts that represent “features,” “conditions,” and the current or desirable “situation” of the item in the country. Another important point is the synchronicity of “description” and “prescription” in secondary or pivotal items of the research. It means that the constituted items not only represent the descriptive meaning that reflects the description of the current or the desirable situation but also represent the prescriptive meaning. The highest-ranking item is "financing methods," with 99 allocated codes. Following that is "financial risk" in the second rank, with 86 codes, and "management risk" secures the third rank with 26 codes. Ultimately, the categorized items can be approached through a model. Therefore, one of the most important results of the country's economic enterprise challenges is the lack of proper modeling for the financing method. A specific model should be created for financing, based on the risk and return of financing. In addition, it should be noted that the structure used to finance the project in one country may not be effective due to the differences in its laws and conditions, while it is used effectively in another country. according to the conditions of each project and the host country of the project.
 
In this study, the influential items or factors affecting project financing risk are investigated. The results of the study showed that financing methods, social risks, contractor risks, construction risks, political risks, designing risks, legal risks, financial risks, management risks, customer risks, and secondary contracts have influential impacts on project financing risk. After project formation and establishment, project financing emerges as a key determinant. Effectively managing a project to successfully achieve its goals within defined time, cost, and quality parameters demands a holistic understanding of the project's stakeholders and its environmental context. Contract frameworks dictate how foreign companies can leverage their financial capabilities to execute operations within different countries.

Ever since Harry Markowitz's groundbreaking paper on the mean-variance model was published in 1952, numerous efforts have been dedicated to exploring the applications and advancements of classical models. Following the development of financial markets, active portfolio optimization has become one of the most important topics in finance. This study aimed to examine active portfolio management, a critical and delicate choice for investors, particularly concerning overall portfolio risk. The determination of an optimal stock portfolio that offers both a substantial return rate and controlled risk is consistently a subject of keen interest for analysts, investors, and even portfolio managers.
 

Many methods have been developed to measure investment risk, and the price of risky assets changes rapidly and randomly due to the complexity of the financial market. A random interval is a suitable tool for describing uncertainty with randomness and imprecision. Given the uncertainty in financial markets, this study used stochastic intervals to describe the returns of risky assets and the tail sequence risk, called the interval-valued conditional value at risk (ICVaR). The interval value in this model is an extension of the classic portfolio model, which can comprehensively reflect the complexity of the financial market and the risk-taking behavior of investors.
 

Following the findings from the real data of 10 out of 30 large corporates listed on the Tehran Stock Exchange, the ICVaR model is interpretable and compatible with the practical scenario and can be used to choose the optimal portfolio at different levels of risk and depending on the risk-taking degree of the investor. The present study used the portfolio optimization approach under a new criterion of ICVaR through the closing price, the highest price, and the lowest price on each trading day. In this model, the return range of the risky asset is taken as a random variable with an interval value. Besides, CVaR with an interval value is used to describe the risk instead of the variance at a certain level of return.
 

Uncertainties induced by asset transactions affect the predictions of investment plans. To address such challenging uncertainties in this study, a stable stochastic optimization approach was presented based on the range of optimal solutions produced by the proposed model to determine different operational options. Finally, the model developed in this study showed that investors’ subjective risk preference or aversion can be described by observing the principle of portfolio diversification, which reflects an innovation different from the classic portfolio model. Furthermore, the worst possible case was optimized in all scenarios in the model by robust optimization. The findings indicated that a narrower range corresponds to a higher level of risk aversion among investors.