Machine Learning-Based Intelligent Risk Management and Arbitrage System for Fixed Income Markets: Integrating High-Frequency Trading Data and Natural Language Processing

Authors

  • Ming Wei Washington University in St. Louis
  • Yanli Pu Finance University of Illinois at Urbana Champaign
  • Qi Lou Tian Yuan Law Firm
  • Yida Zhu Rutgers Business School
  • Zeyu Wang University of Toronto

DOI:

https://doi.org/10.5281/zenodo.13858262

ARK:

https://n2t.net/ark:/40704/JIEAS.v2n5a09

Keywords:

Machine Learning, Fixed Income Markets, Risk Management, Arbitrage Detection

Abstract

This paper introduces risk management and competitive advantage in fixed-income trading, machine learning, high-volume trading (HFT), and natural language processing (NLP). The system integrates advanced analytics and deep learning techniques to improve decision-making, providing real-time risk assessment and detection arbitrage. The main innovations include combining HFT data, which captures the random product of microstructure dynamics, and NLP, which removes the agreement from the non-disordered text, such as financial information and management information. The system employs a hierarchical model, using gradient-boosting machines and neural networks to capture complex temporal dependencies. Results from rigorous testing and real-time performance evaluations show significant improvements in forecasting accuracy, risk management, and correlation analysis. Different compared to traditional methods. The system's adaptability in various business conditions underscores its ability to improve business stability and liquidity. In addition, ethical decision-making and management are addressed through AI-declared processes, making decision-making more transparent. This research demonstrates the transformative potential of integrating AI technology in the fixed-income industry, supporting better and more informed business strategies.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

Author Biographies

Ming Wei, Washington University in St. Louis

Finance, Washington University in St. Louis , MO, USA.

Yanli Pu, Finance University of Illinois at Urbana Champaign

Finance University of Illinois at Urbana Champaign, IL, USA.

Qi Lou, Tian Yuan Law Firm

Tian Yuan Law Firm, Hang Zhou, China.

Yida Zhu, Rutgers Business School

Financial Analysis, Rutgers Business School, NJ, USA.

Zeyu Wang, University of Toronto

Computer Science, University of Toronto, Toronto, Canada.

References

Singh, B., Abilasha, N., & Swarna, C. (2024, February). Real-Time Market Sentiment Analysis Using Natural Language Processing and ML. In 2024 IEEE International Conference on Computing, Power and Communication Technologies (IC2PCT) (Vol. 5, pp. 1585-1588). IEEE.

Chaudhari, H., Gandhi, A., Gabhane, V., & Magar, H. (2024, January). Multi-Asset Portfolio Management System: Integrating Diverse Investments for Optimal Returns and Risk Mitigation. In 2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS) (pp. 1164-1167). IEEE.

Ancy, S. G., & Praveenchandar, J. (2024, June). An Effective Machine Learning Algorithm for Forecasting the Market Value of a House. In 2024, 3rd International Conference on Applied Artificial Intelligence and Computing (ICAAIC) (pp. 1567-1574). IEEE.

Ahamed, F., Biswal, S., Nanda, S. S., Pundir, S., Soubhari, T., & Boggavarapu, S. (2023, September). Intelligent Unmanned AI Detection Model for Financial Volatility in Stock Exchange. In 2023 6th International Conference on Contemporary Computing and Informatics (IC3I) (Vol. 6, pp. 1422-1426). IEEE.

Uğur, Ö., Kalay, T., Demirel, O., & Yıldırım, S. (2022, December). Leveraging the power of Natural Language Processing for Financial Intelligence System. In 2022 3rd International Informatics and Software Engineering Conference (IISEC) (pp. 1-4). IEEE.

Li, S., Xu, H., Lu, T., Cao, G., & Zhang, X. (2024). Emerging Technologies in Finance: Revolutionizing Investment Strategies and Tax Management in the Digital Era. Management Journal for Advanced Research, 4(4), 35-49.

Shi J, Shang F, Zhou S, et al. Applications of Quantum Machine Learning in Large-Scale E-commerce Recommendation Systems: Enhancing Efficiency and Accuracy[J]. Journal of Industrial Engineering and Applied Science, 2024, 2(4): 90-103.

Wang, S., Zheng, H., Wen, X., & Fu, S. (2024). DISTRIBUTED HIGH-PERFORMANCE COMPUTING METHODS FOR ACCELERATING DEEP LEARNING TRAINING. Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online), 3(3), 108-126.

Zhang, M., Yuan, B., Li, H., & Xu, K. (2024). LLM-Cloud Complete: Leveraging Cloud Computing for Efficient Large Language Model-based Code Completion. Journal of Artificial Intelligence General Science (JAIGS) ISSN: 3006-4023, 5(1), 295-326.

Lei, H., Wang, B., Shui, Z., Yang, P., & Liang, P. (2024). Automated Lane Change Behavior Prediction and Environmental Perception Based on SLAM Technology. arXiv preprint arXiv:2404.04492.

Wang, B., He, Y., Shui, Z., Xin, Q., & Lei, H. (2024). Predictive Optimization of DDoS Attack Mitigation in Distributed Systems using Machine Learning. Applied and Computational Engineering, 64, 95-100.

Wang, B., Zheng, H., Qian, K., Zhan, X., & Wang, J. (2024). Edge computing and AI-driven intelligent traffic monitoring and optimisation. Applied and Computational Engineering, 77, 225-230.

Xu, Y., Liu, Y., Xu, H., & Tan, H. (2024). AI-Driven UX/UI Design: Empirical Research and Applications in FinTech. International Journal of Innovative Research in Computer Science & Technology, 12(4), 99-109.

Liu, Y., Xu, Y., & Song, R. (2024). Transforming User Experience (UX) through Artificial Intelligence (AI) in interactive media design. Engineering Science & Technology Journal, 5(7), 2273-2283.

Zhang, P. (2024). A STUDY ON THE LOCATION SELECTION OF LOGISTICS DISTRIBUTION CENTERS BASED ON E-COMMERCE. Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online), 3(3), 103-107.

Zhang, P., & Gan, L. I. U. (2024). Optimise Vehicle Scheduling for Joint Distribution in the Logistics Park based on Priority. Journal of Industrial Engineering and Applied Science, 2(4), 116-121.

Li, H., Wang, S. X., Shang, F., Niu, K., & Song, R. (2024). Applications of Large Language Models in Cloud Computing: An Empirical Study Using Real-world Data. International Journal of Innovative Research in Computer Science & Technology, 12(4), 59-69.

Ping, G., Wang, S. X., Zhao, F., Wang, Z., & Zhang, X. (2024). Blockchain-Based Reverse Logistics Data Tracking: An Innovative Approach to Enhance E-Waste Recycling Efficiency.

Xu, H., Niu, K., Lu, T., & Li, S. (2024). Leveraging artificial intelligence for enhanced risk management in financial services: Current applications and prospects. Engineering Science & Technology Journal, 5(8), 2402-2426.

Shi, Y., Shang, F., Xu, Z., & Zhou, S. (2024). Emotion-Driven Deep Learning Recommendation Systems: Mining Preferences from User Reviews and Predicting Scores. Journal of Artificial Intelligence and Development, 3(1), 40-46.

Wang, Shikai, Kangming Xu, and Zhipeng Ling. "Deep Learning-Based Chip Power Prediction and Optimization: An Intelligent EDA Approach." International Journal of Innovative Research in Computer Science & Technology 12.4 (2024): 77-87.

Ping, G., Zhu, M., Ling, Z., & Niu, K. (2024). Research on Optimizing Logistics Transportation Routes Using AI Large Models. Applied Science and Engineering Journal for Advanced Research, 3(4), 14-27.

Shang, F., Shi, J., Shi, Y., & Zhou, S. (2024). Enhancing E-Commerce Recommendation Systems with Deep Learning-based Sentiment Analysis of User Reviews. International Journal of Engineering and Management Research, 14(4), 19-34.

Xu, H., Li, S., Niu, K., & Ping, G. (2024). Utilising Deep Learning to Detect Fraud in Financial Transactions and Tax Reporting. Journal of Economic Theory and Business Management, 1(4), 61-71.

Xu, K., Zhou, H., Zheng, H., Zhu, M., & Xin, Q. (2024). Intelligent Classification and Personalized Recommendation of E-commerce Products Based on Machine Learning. arXiv preprint arXiv:2403.19345.

Zheng, H., Xu, K., Zhou, H., Wang, Y., & Su, G. (2024). Medication Recommendation System Based on Natural Language Processing for Patient Emotion Analysis. Academic Journal of Science and Technology, 10(1), 62-68.

Zheng, H.; Wu, J.; Song, R.; Guo, L.; Xu, Z. Predicting Financial Enterprise Stocks and Economic Data Trends Using Machine Learning Time Series Analysis. Applied and Computational Engineering 2024, 87, 26–32,

Zhan, X., Shi, C., Li, L., Xu, K., & Zheng, H. (2024). Aspect category sentiment analysis based on multiple attention mechanisms and pre-trained models. Applied and Computational Engineering, 71, 21-26.

Liu, B., Zhao, X., Hu, H., Lin, Q., & Huang, J. (2023). Detection of Esophageal Cancer Lesions Based on CBAM Faster R-CNN. Journal of Theory and Practice of Engineering Science, 3(12), 36-42.

Liu, B., Yu, L., Che, C., Lin, Q., Hu, H., & Zhao, X. (2024). Integration and performance analysis of artificial intelligence and computer vision based on deep learning algorithms. Applied and Computational Engineering, 64, 36-41.

Zhao, F., Zhang, M., Zhou, S., & Lou, Q. (2024). Detection of Network Security Traffic Anomalies Based on Machine Learning KNN Method. Journal of Artificial Intelligence General science (JAIGS) ISSN: 3006-4023, 1(1), 209-218.

Yang, M., Huang, D., Zhang, H., & Zheng, W. (2024). AI-Enabled Precision Medicine: Optimizing Treatment Strategies Through Genomic Data Analysis. Journal of Computer Technology and Applied Mathematics, 1(3), 73-84.

Wen, X., Shen, Q., Zheng, W., & Zhang, H. (2024). AI-Driven Solar Energy Generation and Smart Grid Integration A Holistic Approach to Enhancing Renewable Energy Efficiency. International Journal of Innovative Research in Engineering and Management, 11(4), 55-55.

Lou, Q. (2024). New Development of Administrative Prosecutorial Supervision with Chinese Characteristics in the New Era. Journal of Economic Theory and Business Management, 1(4), 79-88.

Zhou, S., Yuan, B., Xu, K., Zhang, M., & Zheng, W. (2024). THE IMPACT OF PRICING SCHEMES ON CLOUD COMPUTING AND DISTRIBUTED SYSTEMS. Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online), 3(3), 193-205.

Sun, J., Wen, X., Ping, G., & Zhang, M. (2024). Application of News Analysis Based on Large Language Models in Supply Chain Risk Prediction. Journal of Computer Technology and Applied Mathematics, 1(3), 55-65.

Huang, D., Yang, M., Wen, X., Xia, S., & Yuan, B. (2024). AI-Driven Drug Discovery: Accelerating the Development of Novel Therapeutics in Biopharmaceuticals. Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online), 3(3), 206-224.

Liu, Y., Tan, H., Cao, G., & Xu, Y. (2024). Enhancing User Engagement through Adaptive UI/UX Design: A Study on Personalized Mobile App Interfaces.

Xu, K., Zheng, H., Zhan, X., Zhou, S., & Niu, K. (2024). Evaluation and Optimization of Intelligent Recommendation System Performance with Cloud Resource Automation Compatibility.

Zhao, F., Li, H., Niu, K., Shi, J., & Song, R. (2024). Application of deep learning-based intrusion detection system (IDS) in network anomaly traffic detection.

Downloads

Published

2024-10-01

How to Cite

[1]
M. Wei, Y. Pu, Q. Lou, Y. Zhu, and Z. Wang, “Machine Learning-Based Intelligent Risk Management and Arbitrage System for Fixed Income Markets: Integrating High-Frequency Trading Data and Natural Language Processing”, Journal of Industrial Engineering & Applied Science, vol. 2, no. 5, pp. 56–67, Oct. 2024.

Issue

Section

Articles

ARK