The present paper examines the impact of herding behavior on market capitalization in the Egyptian stock market before and after the disclosure of environmental-social-governance scores (ESG Score Index). This line of thought and research contributes to the literature on the interrelationships between ESG factors and market dynamics. Consequently, the evolving landscape of how to sustain investments in emerging markets like Egypt can be enlightened. Two main hypotheses were tested in the paper. The first hypothesis is on the expected significant impact of herding behaviour on market capitalization. The second hypothesis is on the expected positive impact of ESG on the relationship between herding behaviour and market capitalization. Panel data analysis using data extracted from financial statements of 22 Egyptian EGX 30 companies, over the period 2018-2023 will be used. This is to control for the cross-section and time characteristics of the research sample. The empirical findings reveal a positive significant effect of herding behavior on market capitalization before disclosing ESG scores. Another finding is that after the implementation of mandatory ESG disclosure, the relationship between herding behavior and market capitalization is strengthened. Moreover, it is empirically evident that companies with higher ESG performance attract more investments and higher valuations. The importance of ESG in shaping investment decision-making, enhancing transparency, and market dynamics has important policy implications.

Continuous developments vitally impact the commercial and financial areas, and one of the most important technologies is artificial intelligence (AI). Despite financial aspects facing a lot of challenges due to using AI, there are many opportunities that should be explored. The main purpose of this study is to explore the effect of using artificial intelligence on the financial performance of banks in Egypt. The study's objective was accomplished by using a quantitative approach, and data analysis was done using path analysis. This study demonstrates how banks can use AI technologies to enhance their liquidity and profitability, and hence, financial performance consequently increases the trust of stakeholders. This study provides thorough insights that can help organizations and policymakers effectively utilize AI technology for improved financial performance. The study's findings have significant real-world repercussions for banks and their financial performance. Finally, this study provides recommendations for future research and practical implications that lead to more improvement in both academic and professional fields. تؤثر التطورات المستمرة بشكل حيوي على المجالات التجارية والمالية، وأحد أهم التقنيات هو الذكاء الاصطناعي (AI). وعلى الرغم من أن الجوانب المالية تواجه الكثير من التحديات بسبب استخدام الذكاء الاصطناعي، إلا أن هناك العديد من الفرص التي يجب استكشافها، والغرض الرئيسي من هذه الدراسة هو استكشاف تأثير استخدام الذكاء الاصطناعي على الأداء المالي للبنوك في مصر، وقد تم تحقيق هدف الدراسة باستخدام نهج كمي، وقد تم إجراء تحليل البيانات باستخدام تحليل المسار. توضح هذه الدراسة كيف يمكن للبنوك استخدام تقنيات الذكاء الاصطناعي لتعزيز سيولتها وربحيتها، ومن ثم فإن الأداء المالي يزيد من ثقة أصحاب المصلحة، تقدم هذه الدراسة رؤية شاملة يمكن أن تساعد المؤسسات وصانعي السياسات على استخدام تقنية الذكاء الاصطناعي بشكل فعال لتحسين الأداء المالي، ولنتائج هذه الدراسة تداعيات واقعية كبيرة على البنوك وأدائها المالي،وأخيرًا، تقدم هذه...

Purpose: This paper investigates the relationship between CaHR and firm financial profitability applying to the Egyptian stock market. Methodology: OLS regression analysis is conducted to explain the 2 models used for a sample of (10) Egyptian Companies during the period between 2013 to 2021. The main hypothesis is tested H₁: There is no a statistically significant relationship between CaHR and firm profitability. Findings: The independent variables (CaHR, Lev) have a negative effect on ROA-ROE, and the independent variables (size, AG) have a positive effect on ROA-ROE, but all independent variables have a statistically significant relationship on ROA-ROE, and thus the study's main hypothesis was rejected. Research limitations: The paper opens the area for future research by using a distinct dataset that includes the time period during and after the COVID-19 epidemic to capture the impact of covid-19 on the firm liquidity and profitability.

Research Objectives: Research targets is explaining the idea of herding-behavior and how to measure it as well as explore the association between herding-behavior and stock market returns in the Egyptian Stock Exchange to better understand the behavior of investors and how it influences stock market. Research Hypothesis: The key assumption tested in this research is: There is no statistically significant relationship between herding-behavior and stock market return. Research Approaches: The study employs both inductive and deductive methods, analyzing annual financial statement data from 22 companies in the index of EGX 30 in Egyptian Stock market between 2018 and 2023. Descriptive statistics of the variables are followed by Skewness and Kurtosis tests. A correlation test between the variables is conducted, alongside heteroskedasticity, multivariate normality, and multicollinearity tests. Therefore, regression analysis is employed to generate the study models and evaluate the hypothesis. Research Results: The study found that Herding-behavior has a positive impact on the Stock market return.