SUSTAINABLE AND ETHICAL AI IN FINANCE: DEVELOPING GREEN SHARK ALGORITHMS FOR ECO-FRIENDLY TRADING

Abstract

This article addresses the growing computational demands of modern trading algorithms and the pressing need for sustainable practices by introducing "Green Shark Algorithms," a new class of trading systems engineered to emphasize energy efficiency, sustainability, and ethical investment principles. In response to the escalating energy consumption and environmental impact of traditional trading operations, this research proposes a comprehensive approach that merges technological optimization with responsible investing. The study specifically focuses on the Istanbul Stock Exchange (BIST), analyzing how these innovative algorithms can reduce energy usage, lower carbon footprints, and maintain robust financial performance.The development of Green Shark Algorithms involves optimizing algorithmic design and enhancing the efficiency of data center operations. By refining computational processes and leveraging energy-efficient technologies, these algorithms aim to significantly reduce the power demands of trading activities without compromising the speed or accuracy critical to financial markets. The research underscores the potential of these advancements to contribute to the broader sustainability goals of the financial industry by decreasing the environmental impact associated with high-frequency trading.In addition to technical innovations, the integration of Environmental, Social, and Governance (ESG) criteria into trading strategies is a central theme of this study. The inclusion of ESG factors within algorithmic decision-making frameworks ensures that trading activities align with ethical and sustainable investment practices. By prioritizing investments in companies with strong ESG performance, Green Shark Algorithms not only promote financial returns but also foster a more responsible approach to market participation, encouraging corporate behaviors that contribute positively to society and the environment.The findings suggest that the implementation of Green Shark Algorithms on the BIST can lead to a dual benefit: reduced energy consumption and enhanced sustainability in trading operations, coupled with financial performance that meets or exceeds traditional benchmarks. However, the research also highlights challenges, such as the need for reliable ESG data and the complexities of balancing energy efficiency with algorithmic precision.Future research directions include the exploration of advanced energy-efficient technologies, the refinement of ESG metrics for more accurate assessments, and the developmentof regulatory frameworks to support the adoption of sustainable trading practices. The Green Shark Algorithms represent a pivotal step toward reconciling the demands of modern trading with the imperatives of environmental stewardship and ethical investment, potentially reshaping the future of financial markets.