Blockchain-Integrated AI Strategies for Cross-Border High-Frequency Trading: Optimizing Liquidity and Reducing Transaction Costs

Ling Ran

No knz94_v1, OSF Preprints from Center for Open Science

Abstract: This paper examines the evolving landscape of cross-border trading enabled by blockchain technology and artificial intelligence (AI). It explores the mechanisms through which blockchain decentralizes trading infrastructure, enhances transaction transparency, and eliminates intermediaries to reduce operational costs. AI integration is analyzed in the context of high-frequency trading, focusing on real-time data processing, algorithmic decision-making, and smart contract automation. The discussion addresses technical and regulatory barriers, including algorithmic failures, cyber threats, jurisdictional discrepancies, and integration complexity. The paper evaluates the resulting shifts in market liquidity, compliance strategies, fraud mitigation, and overall trading efficiency. The convergence of blockchain and AI is framed as a paradigm shift in financial technology infrastructures, with both opportunities and limitations in scalability, regulation, and cost of deployment. The findings suggest a potential for optimized trade execution and autonomous risk-adjusted decision systems under constrained legal and technical environments.

Date: 2025-04-23
New Economics Papers: this item is included in nep-mst and nep-pay
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Persistent link: https://EconPapers.repec.org/RePEc:osf:osfxxx:knz94_v1

DOI: 10.31219/osf.io/knz94_v1

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