Advanced Techniques for Intraday Liquidity Management
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Abstract
Intraday liquidity management has become a critical focus for financial institutions as they navigate the complex interplay of regulatory requirements, operational efficiency, and market dynamics. Advanced techniques in this domain leverage cutting-edge technologies, data analytics, and strategic frameworks to optimize liquidity usage while mitigating associated risks. This study explores innovative approaches such as real-time liquidity monitoring, predictive modeling, and algorithmic fund allocation. Additionally, the role of blockchain technology and artificial intelligence in enhancing transparency, reducing settlement times, and improving decision-making processes is discussed. The research underscores the importance of collaborative infrastructures, regulatory alignment, and stress testing to ensure resilience in high-frequency trading environments. By employing these advanced techniques, financial institutions can achieve enhanced liquidity control, reduced costs, and greater stability, contributing to a more robust financial ecosystem.
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References
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• Siddagoni, Mahaveer Bikshapathi, Sandhyarani Ganipaneni, Sivaprasad Nadukuru, Om Goel, Niharika Singh, Prof. (Dr.) Arpit Jain. 2023. Leveraging Agile and TDD Methodologies in Embedded Software Development. Iconic Research And Engineering Journals Volume 7, Issue 3, Pages 457-477.
• Hrishikesh Rajesh Mane, Vanitha Sivasankaran Balasubramaniam, Ravi Kiran Pagidi, Dr. S P Singh, Prof. (Dr.) Sandeep Kumar, Shalu Jain. "Optimizing User and Developer Experiences with Nx Monorepo Structures." Iconic Research And Engineering Journals Volume 7 Issue 3:572-595.
• Sunny Jaiswal, Nusrat Shaheen, Dr Umababu Chinta, Niharika Singh, Om Goel, Akshun Chhapola. (2024). Modernizing Workforce Structure Management to Drive Innovation in U.S. Organizations Using Oracle HCM Cloud. International Journal of Research Radicals in Multidisciplinary Fields, ISSN: 2960-043X, 3(2), 269–293. Retrieved from https://www.researchradicals.com/index.php/rr/article/view/129.
• Jaiswal, S., Shaheen, N., Mangal, A., Singh, D. S. P., Jain, S., & Agarwal, R. (2024). Transforming Performance Management Systems for Future-Proof Workforce Development in the U.S. Journal of Quantum Science and Technology (JQST), 1(3), Apr(287–304). Retrieved from https://jqst.org/index.php/j/article/view/121.
• Bhardwaj, Abhijeet, Nagender Yadav, Jay Bhatt, Om Goel, Prof. (Dr.) Punit Goel, and Prof. (Dr.) Arpit Jain. 2024. Leveraging SAP BW4HANA for Scalable Data Warehousing in Large Enterprises. Integrated Journal for Research in Arts and Humanities 4(6): 143-163. https://doi.org/10.55544/ijrah.4.6.13.
• Abhijeet Bhardwaj, Pradeep Jeyachandran, Nagender Yadav, Prof. (Dr) MSR Prasad, Shalu Jain, Prof. (Dr) Punit Goel. (2024). Best Practices in Data Reconciliation between SAP HANA and BI Reporting Tools. International Journal of Research Radicals in Multidisciplinary Fields, ISSN: 2960-043X, 3(2), 348–366. Retrieved from https://www.researchradicals.com/index.php/rr/article/view/133.
• Abhijeet Bhardwaj, Nagender Yadav, Jay Bhatt, Om Goel, Prof.(Dr.) Arpit Jain, Prof. (Dr) Sangeet Vashishtha. (2024). Optimizing SAP Analytics Cloud (SAC) for Real-time Financial Planning and Analysis. International Journal of Multidisciplinary Innovation and Research Methodology, ISSN: 2960-2068, 3(3), 397–419. Retrieved from https://ijmirm.com/index.php/ijmirm/article/view/144.
• Bhardwaj, Abhijeet, Jay Bhatt, Nagender Yadav, Priya Pandey, S. P. Singh, and Punit Goel. 2024. Implementing Integrated Data Management for Multi-system SAP Environments. International Journal of Research in Modern Engineering and Emerging Technology (IJRMEET) 12(11):1–10. https://www.ijrmeet.org.
• Bhardwaj, A., Jeyachandran, P., Yadav, N., Singh, N., Goel, O., & Chhapola, A. (2024). Advanced Techniques in Power BI for Enhanced SAP S/4HANA Reporting. Journal of Quantum Science and Technology (JQST), 1(4), Nov(324–344). Retrieved from https://jqst.org/index.php/j/article/view/126.
• Bhardwaj, A., Yadav, N., Bhatt, J., Goel, O., Goel, P., & Jain, A. (2024). Enhancing Business Process Efficiency through SAP BW4HANA in Order-to-Cash Cycles. Stallion Journal for Multidisciplinary Associated Research Studies, 3(6), 1–20. https://doi.org/10.55544/sjmars.3.6.1.
• Das, A., Gannamneni, N. K., Jena, R., Agarwal, R., Vashishtha, P. (Dr) S., & Jain, S. (2024). “Implementing Low-Latency Machine Learning Pipelines Using Directed Acyclic Graphs.” Journal of Quantum Science and Technology (JQST), 1(2):56–95. Retrieved from https://jqst.org/index.php/j/article/view/8.
• Mane, Hrishikesh Rajesh, Shyamakrishna Siddharth Chamarthy, Vanitha Sivasankaran Balasubramaniam, T. Aswini Devi, Sandeep Kumar, and Sangeet. "Low-Code Platform Development: Reducing Man-Hours in Startup Environments." International Journal of Research in Modern Engineering and Emerging Technology 12(5):107. Retrieved from www.ijrmeet.org.
• Mane, H. R., Kumar, A., Dandu, M. M. K., Goel, P. (Dr.) P., Jain, P. A., & Shrivastav, E. A. "Micro Frontend Architecture With Webpack Module Federation: Enhancing Modularity Focusing On Results And Their Implications." Journal of Quantum Science and Technology (JQST) 1(4), Nov(25–57). Retrieved from https://jqst.org.
• Kar, Arnab, Ashish Kumar, Archit Joshi, Om Goel, Dr. Lalit Kumar, and Prof. (Dr.) Arpit Jain. 2024. Distributed Machine Learning Systems: Architectures for Scalable and Efficient Computation. International Journal of Worldwide Engineering Research 2(11): 139-157.
• Mali, A. B., Khan, I., Dandu, M. M. K., Goel, P. (Dr) P., Jain, P. A., & Shrivastav, E. A. (2024). Designing Real-Time Job Search Platforms with Redis Pub/Sub and Machine Learning Integration. Journal of Quantum Science and Technology (JQST), 1(3), Aug(184–206). Retrieved from https://jqst.org/index.php/j/article/view/115.