Assessing the Efficiency of AI-Enhanced Algorithmic Trading in Developed vs. Developing Financial Markets

Author(s)	Ronit Gupta
Country	India
Abstract	This study assesses the efficiency of AI-enhanced algorithmic trading in developed and developing financial markets. It explores the influence of technological infrastructure, market liquidity, regulatory frameworks, and volatility on trading performance. Developed markets, characterized by advanced technology, high liquidity, and robust regulations, demonstrate superior trading efficiency, including faster execution speeds, reduced transaction costs, and enhanced stability. In contrast, developing markets face challenges such as slower technological adoption, lower liquidity, and inconsistent regulations, which hinder trading effectiveness. Comparative case studies of the U.S. equity market and the Indian stock market emphasize the former's efficiency and the latter's emerging potential. The findings suggest market-specific strategies and highlight the need for infrastructural improvements in developing markets to optimize AI's benefits.
Keywords	AI-enhanced algorithmic trading, financial markets, market efficiency, technological infrastructure, market liquidity, regulatory frameworks, developed markets, developing markets
Field	Business Administration
Published In	Volume 7, Issue 1, January-February 2025
Published On	2025-01-19
Cite This	Assessing the Efficiency of AI-Enhanced Algorithmic Trading in Developed vs. Developing Financial Markets - Ronit Gupta - IJFMR Volume 7, Issue 1, January-February 2025.

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