Insider trading remains a critical concern for the integrity and fairness of financial markets. This observational study aims to investigate patterns of insider trading in the Athens Stock Exchange (ASE) by analyzing abnormal stock price movements, trading volumes, and key financial disclosures. Utilizing data from a range of publicly traded companies on the ASE, the study applies statistical models and financial metrics to identify potential instances of insider trading. By focusing on periods preceding major announcements such as mergers, acquisitions, and earnings reports, the research highlights any irregular trading behaviors. The results are evaluated in the context of regulatory frameworks and market efficiency, offering insights into the effectiveness of existing surveillance mechanisms in detecting and deterring insider trading. This study contributes to the broader discourse on market transparency, providing policy recommendations aimed at enhancing the detection and prevention of illegal trading activities within the ASE.

This study, "Sectoral Analysis of Namibia's Economic Landscape," provides a detailed examination of the primary sectors driving the Namibian economy. Namibia's economic structure is characterized by its reliance on a few key sectors, including mining, agriculture, tourism, and manufacturing, each contributing significantly to the nation's GDP and employment. This analysis explores the performance, challenges, and growth prospects of these sectors, utilizing a combination of economic data, sectoral reports, and empirical research.

The mining sector, particularly uranium and diamond extraction, remains a cornerstone of Namibia's economy, contributing substantially to export revenues and foreign investment. Agriculture, with its focus on livestock and crop production, plays a vital role in rural livelihoods and food security. Tourism, leveraging Namibia's unique landscapes and biodiversity, has shown promising growth, despite global challenges and competition. The manufacturing sector, while smaller in scale, offers potential for diversification and value addition.

By employing a comprehensive approach that includes statistical analysis and sector-specific case studies, this study identifies key trends and challenges within each sector. It also evaluates the impacts of domestic policies, global market conditions, and technological advancements on sectoral performance. The findings highlight opportunities for sustainable development and economic diversification, providing policy recommendations aimed at enhancing sectoral resilience and growth.

The rapid advancement of technology has transformed the financial services sector, leading to the rise of fintech companies that leverage cutting-edge tools such as artificial intelligence (AI) and machine learning (ML) to offer innovative solutions. One area where fintech is particularly impactful is dynamic pricing, which involves adjusting prices in real-time based on market conditions, user behavior, and external factors. The ability to optimize pricing in response to fluctuating conditions is critical for maximizing profitability, improving customer satisfaction, and maintaining competitiveness. In this context, machine learning algorithms provide a powerful framework for making data-driven pricing decisions by learning from historical data and predicting future trends.

ZENODO DOI:- https://doi.org/10.5281/zenodo.14013976