Mean Clustering Estimation Method for Analyzing Financial Derivatives Profitability in Biotechnological Firms

Abstract

This study develops a mean clustering estimation method to analyze the financial profitability of financial derivatives in biotechnological firms, providing a critical tool for navigating post-pandemic economic landscapes. By leveraging secondary data sourced from world development indicators and various websites focused on green financial management, this research examines the interplay between financial derivatives and economic performance in the biotechnology sector. Utilizing eviews software, the study employs advanced analytical techniques including descriptive statistics, correlation coefficients, and regression tests to evaluate the relationships between economic indicators and financial outcomes. The analysis extends to unit root and histogram graphical tests to assess the impacts of green financial management during and after the COVID-19 pandemic. Key economic variables such as GDP, per capita income, and working capital are scrutinized to determine their correlation with the profitability of financial derivatives. The findings indicate a potentially negative impact of green financial strategies on economic development within the biotechnological industry post-pandemic, suggesting a need for recalibrated financial management approaches to enhance profitability and sustainability in this sector.