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

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  • Ran, Ling

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.

Suggested Citation

  • Ran, Ling, 2025. "Blockchain-Integrated AI Strategies for Cross-Border High-Frequency Trading: Optimizing Liquidity and Reducing Transaction Costs," OSF Preprints knz94_v1, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:knz94_v1
    DOI: 10.31219/osf.io/knz94_v1
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    References listed on IDEAS

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    1. Oliver Linton & Soheil Mahmoodzadeh, 2018. "Implications of High-Frequency Trading for Security Markets," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 237-259, August.
    2. Makarov, Igor & Schoar, Antoinette, 2020. "Trading and arbitrage in cryptocurrency markets," LSE Research Online Documents on Economics 100409, London School of Economics and Political Science, LSE Library.
    3. Makarov, Igor & Schoar, Antoinette, 2020. "Trading and arbitrage in cryptocurrency markets," Journal of Financial Economics, Elsevier, vol. 135(2), pages 293-319.
    4. Brian M. Weller, 2018. "Does Algorithmic Trading Reduce Information Acquisition?," The Review of Financial Studies, Society for Financial Studies, vol. 31(6), pages 2184-2226.
    5. Qian, Ling & Dong, Lianjie, 2025. "Convergence of Blockchain and AI in Global Finance: Cross-Border Payment Innovations and Adaptive Trading Algorithms," OSF Preprints 7qvk8_v1, Center for Open Science.
    6. Du, Yudai, 2025. "Singapore’s Fintech Revolution: Blockchain-Powered Cross-Border Settlements and AI-Enhanced Trading Ecosystems (2020-2023)," OSF Preprints fhg3z_v1, Center for Open Science.
    7. Yukun Liu & Aleh Tsyvinski & Xi Wu, 2022. "Common Risk Factors in Cryptocurrency," Journal of Finance, American Finance Association, vol. 77(2), pages 1133-1177, April.
    8. Larry Harris, 2013. "What to Do about High-Frequency Trading," Financial Analysts Journal, Taylor & Francis Journals, vol. 69(2), pages 6-9, March.
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