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.

Objective: This study aims to evaluate one of Algeria's key strategies for developing an entrepreneurial culture among university students in higher education, which is entrepreneurial education. It analyzes the number of files submitted by university students through the National Agency for the Support and Development of Entrepreneurship from 2013 to 2020, as well as the statistics on students who participated in the Entrepreneurship House from 2013 to 2019. Methods: The study evaluates entrepreneurial education as a strategy for fostering an entrepreneurial culture among university students in Algeria, based on the number of files submitted for establishing micro-enterprises at the National Agency for the Support and Development of Entrepreneurship. It also assesses the outcomes of activities promoting entrepreneurship by entrepreneurship centers in higher education institutions in 2019. Results: The statistics reveal that Algeria’s experience in teaching entrepreneurship in higher education is both recent and weak. This weakness is due to the limited role of educational programs in business plan preparation and their inability to keep up with scientific advancements. These programs also fail to equip students with the necessary knowledge, skills, and capabilities to start their own projects or invest in opportunities for small business creation. Conclusions: Developing an entrepreneurial culture in universities requires collaboration across various efforts. This includes the Entrepreneurship House, which connects students to the economic environment through awareness and training, university business incubators that provide support and funding, and student clubs and research labs that foster an entrepreneurial culture within the academic setting.

A developed financial system, which ensures the provision, allocation, and direction of resources toward productive economic sectors, is one of the key drivers of economic growth and development. On the other hand, given the low efficiency of various economic, productive, and social sectors, attention to total factor productivity (TFP) is fundamental for global competitiveness. Given resource constraints in the economy, improving this factor can enhance investment, optimize resource allocation, prioritize productive sectors, reduce costs, improve product quality, and increase value added in economic sectors. Accordingly, the present study aims to investigate the impact of credit on total factor productivity and the growth of value added in Iran’s economic sectors using the Panel ARDL approach and quarterly time series data from 2012Q1 to 2024Q4 (Persian calendar). The results indicate that real credit, real exchange rates, and real capital formation in machinery have a positive and direct impact on the growth of value added and total factor productivity in economic sectors. Specifically, credit in the industrial sector and exchange rates in the service sector exert the greatest influence on TFP and the growth of value added. Additionally, capital formation in machinery in the agricultural sector has the most significant impact on total factor productivity.

This study investigates the relationship between audit quality and earnings management, based on Loan Loss Provisions(LLPs), in 15 active banks listed on the Tehran Stock Exchange from 2010 to 2024. By analyzing data from these sample banks, this study evaluates the impact of various factors on Earnings Management Practices(EMP), including audit firm size, auditor tenure, and auditor specialization in the banking industry. The results indicate a significantly negative relationship between audit firm size and earnings management, suggesting that banks audited by larger firms are less likely to engage in earnings manipulation. Conversely, a positive and significant relationship was found between auditor tenure and earnings management, implying that prolongedauditor-client relationships may lead to a decline in auditor independence, thereby facilitating earnings management. Additionally, auditors with specialized knowledge in the banking sector demonstrate a greater ability to detect and mitigate opportunistic earnings management behaviors, contributing to a reduction in earnings manipulation within these banks

This research examines the performance of banks' Asset Liability Management (ALM) strategies using Data Envelopment Analysis (DEA) to improve bank efficiency and estimate the efficiency scores of emerging banks. ALM is an essential process for financial institutions to manage their assets and obligations effectively, ensuring profitability, liquidity, and risk oversight, while DEA offers a comprehensive methodology for evaluating and comparing the efficiency of Decision-Making Units (DMUs). By utilizing DEA in the context of ALM, this research seeks to uncover inefficiencies and recommend optimization strategies. The results reveal considerable differences in efficiency levels, underscoring potential improvement areas and best practices. This study adds to the existing literature by illustrating the practical use of DEA in ALM and providing actionable insights for banks to boost their performance

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.