درخت حوزه‌های تخصصی

Neurotransmitters are the chemical messengers nerve cells use to transmit signals to target cells. Neurotransmitters affect the behavioral aspects of investors' performance. Therefore, this study investigated neurotransmitters' effect on individual investors' behavior by using structural equation modeling. To achieve this goal, exploratory and confirmatory factor analysis has been used. The study is applied research and utilizes a survey methodology. The required data were collected through the distribution of questionnaires among 315 individual investors. This study was done in the Tehran stock exchange's second and third seasons of 2023. According to the research, neurotransmitters through eight components of adrenaline or epinephrine, noradrenaline or norepinephrine, dopamine, serotonin, GABA (gamma-aminobutyric add), acetylcholine, glutamate, and endorphins affect the behavior of individual investors. Based on the second-order confirmatory factor analysis, the GABA component (0.39) has the highest impact, and adrenaline or epinephrine (0.25) has the least effect on the behavior of individual investors. The findings indicate the necessity of redefining rationality and considering its effects on investors' decisions and behavior.

Climate change and infectious diseases have emerged as two of the most significant challenges facing the world and its economic systems today. Recent studies have increasingly focused on understanding how phenomena such as the COVID-19 pandemic and the climate change crisis—including rising greenhouse gas emissions and uncertainties in climate policy—affect macroeconomic variables and capital markets. Many experts assert that climate change poses a serious threat to human civilization. In light of these pressing concerns, this paper examines the impact of Climate Policy Uncertainty (CPU) and Infectious Disease Risk (IDR) on the Islamic Dow Jones Index (IDJ). To achieve this, the study utilizes monthly data spanning from January 2016 to March 2021 and employs a Structural Vector Autoregressive (SVAR) model. Additionally, Contour Plot graphs are applied to estimate the interaction effects on the IDJ. The findings reveal contrasting impacts of the CPU and IDR indices on the IDJ. Specifically, an increase in the CPU index leads to higher utilization of the Earth's resources for producing goods and services by companies included in the index, resulting in a positive effect. Conversely, a rise in the IDR index exacerbates economic recession, thereby causing a decline in the IDJ.

The correct understanding of behavioral factors affecting individual investment decisions in the stock market is one of the main goals of this research. This accurate knowledge will increase the efficiency of the market, and the financial resources will be adequately equipped and allocated. Finally, it will save resources in this market. Therefore, the current research seeks to investigate and test the effect of risk aversion based on the past performance of stocks in the financial behavior of investors. In this research, a regression model was used to test the hypotheses. The statistical population of this research is all the firms accepted in the Tehran Stock Exchange over 7 years, from 2016 to 2022. Considering the research period, the total number of data points is 980 years—firm (observation). Also, in this research, the stock price was used to evaluate the variable of past stock performance, which has not been paid attention to in past behavioral financial research due to its importance for investors' decision-making. The analysis of the research hypotheses showed that risk aversion has a positive relationship with investors' decision-making. In addition, the study of research data indicates that the past performance of stocks has a positive moderating role in the relationship between risk aversion and investors' decision-making.

Nowadays, insurance is considered as an integral part of the financial system of every country. Insurance companies as important financial institutions in the capital market, in addition to risk coverage, play the role of financial intermediaries. As for-profit institutions, these companies must achieve profitability by implementing these two roles. For this purpose, this study aims to identify the factors that determine the profitability of Iran's insurance industry between 2011-3 and 2022-3 on a seasonal basis using the TVP-DMA model. The results showed that financial leverage variables, exchange rate, and insurance premium growth are, respectively, the most influential variables affecting the performance of Iran's insurance industry. Additionally, the results show that the manner and probability of these variables influencing the performance of the insurance industry over time is not constant and is influenced by factors such as the JCPOA agreement, withdrawal from the JCPOA, the continuation of the privatization process, the elimination of value-added tax in the insurance industry, and the change in the articles of association insurance companies, notification of the establishment of the general natural disaster insurance fund and the use of the capital market capacities of the insurance industry.

Bank facilities can be categorized into large-scale and non-large-scale facilities based on their value and in compliance with banking regulations. Given the significant share of large-scale facilities in the country's total credit portfolio, the exposure to a limited number of borrowers, primarily major corporations, and their subsequent direct and indirect effects on the banking system and the economy, this paper investigates the credit concentration risk associated with large-scale facilities. Using the Herfindahl-Hirschman Index (HHI), the degree of name concentration in the allocation of large-scale facilities among beneficiaries was measured, and its impact on the default rate of these facilities was estimated using a Generalized Method of Moments (GMM) model for 15 banks listed on the Tehran Stock Exchange during the period 2022-2024. Additionally, the share of large-scale facilities in the total loans granted by each bank (as another concentration measure) was included in the model, along with the loans-to-deposits ratio and the capital adequacy ratio as control variables. The model results indicate stickiness and a statistically significant impact of the lagged default rate of large-scale facilities. It was observed that name concentration in the allocation of large-scale facilities has a negative effect on the default rate of these facilities. However, the share of large-scale facilities in total loans, as an alternative concentration measure, did not exhibit a statistically significant effect on their default rate. Furthermore, the loans-to-deposits ratio, which serves as an indicator of banks’ liquidity and resource management performance, had a significant negative effect. Additionally, an improvement in the capital adequacy ratio led to a statistically significant reduction in the default rate of large-scale facilities.

This paper develops a stylized New Keynesian DSGE model with imperfect banking competition and fiscal constraints to evaluate the welfare effects of different Central Bank Digital Currency (CBDC) designs. The model compares five monetary regimes: a conventional baseline, retail account-based CBDC, retail token-based CBDC, wholesale CBDC, and a hybrid CBDC. Results show that a retail, interest-bearing, account-based CBDC delivers the highest welfare gain, equivalent to a permanent 11.13% increase in consumption, driven by lower transaction costs, greater banking sector competition, and reduced labor tax distortions. A hybrid CBDC generates a moderate welfare gain of 6.04%, while the token-based and wholesale designs offer only marginal improvements. The analysis reveals that the welfare impact of CBDC adoption is highly sensitive to its design features, particularly the utility it provides, the interest rate spread, and the degree of competition it induces in the banking sector. These findings underscore the complexity of CBDC policymaking, where trade-offs between efficiency, inclusion, and financial sector dynamics must be carefully balanced. Policy recommendations emphasize prioritizing user-friendly, account-based CBDC frameworks, enhancing interoperability with existing systems, and adopting a gradual, flexible approach that aligns with country-specific fiscal and financial structures.

The concept of moral hazard has a relation with risk shifting and asset portfolio. The banking background focuses on sources and types of risk shifting. However, moral hazard problem has provided a brief analysis of the incentive of risk shifting. The present study aims to figure out the model for Iranian banking system during 2000-2024 in order to determine the dominant risk shifting behavior. Risk shifting can cause conflicts between shareholders, depositors and creditors. Risk shifting can also be related to the risk taking behavior in banking systems. Accepting risk by one party can lead to risk transfers to other parties. Therefore, the present study aims to figure out whether the risk changes are related to capital ratio and other structures of balance sheet in banking system, using the deposit and non-depository debt ratio in order to reach the risk transfer rates to depositors and other parties. The results showed that the type of risk shifting is deposit side in Iranian banking system and shareholders tend to shift risks to depositors. Return on equity seems to be the suitable variable increasing the moral hazard behavior and risk shifting. Thus, profitable banks have powerful signals for risk transfer. However, large banks supported by the Central Bank and Government show more risk shifting behaviors, the incentives of which can be detected in the banking system and decreased by regulation and supervision.

The tourism industry, as one of the important drivers of economic growth, plays a significant role in improving the performance of financial markets and enhancing the efficiency of related sectors, which has been considered in many studies. This study aimed to analyze the impact of macroeconomic factors on the stock returns of the tourism industry in five selected countries: France, Spain, Turkey, Malaysia, and Iran, during the years 1999 to 2023, using panel data and the generalized moments (GMM) approach, which allows for the examination of dynamic effects and control for country effects. The findings showed that economic growth and the added value of the service sector have a positive and significant impact on the stock returns of the tourism industry, while exchange rate fluctuations, inflation, and interest rates significantly reduce stock returns in some countries such as Iran and Turkey, which have more unstable economies. Also, the effects of external shocks such as the Covid-19 pandemic and economic sanctions on Iran have been observed to be significant and negative on the stock returns of this industry. Governance index, as a key institutional variable, also plays an effective role in strengthening the stock returns of the tourism industry and can moderate the negative effects of economic factors and external shocks. Comparative analysis between selected countries reveals structural differences in the intensity and direction of the impact of macroeconomic and institutional factors, which shows the importance of economic conditions, quality of governance and crisis management in each country. Based on these results, strengthening sustainable economic policies, improving governance indicators and managing external risks are recommended as key strategies to increase the efficiency of the tourism industry and develop related financial markets.