Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Balaji, K. Title A name given to the resource Revolutionizing High-Frequency Trading: The Impacts of Financial Technology and Data Science Innovations Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Machine Learning and Modeling Techniques in Financial Data Science;pp.103-123 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3693-8186-1.ch004" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3693-8186-1.ch004</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105007279710?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105007279710?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Balaji K., Christ University, Bengaluru, India Description An account of the resource This paper provides a comprehensive review of various High- Frequency Trading (HFT) strategies and the cutting- edge technologies that underpin them. It explores the latest advancements in financial data science, machine learning, and AI, highlighting their transformative role in reshaping modern trading practices. The paper delves into the algorithmic approaches employed by HFT firms and stock exchanges, including predictive analytics, time- series analysis, pattern recognition, sentiment analysis, and risk management techniques. Through a series of case studies, the paper examines successful implementations of HFT technologies at global exchanges such as the NYSE, NASDAQ, LSE, TSE, and Euronext. It also considers the regulatory and ethical implications of HFT, emphasizing the need for balance between technological innovation, market stability, and fairness. By analyzing these advancements, the paper sheds light on the future trajectory of HFT and its broader impact on financial markets. 2025 by IGI Global Scientific Publishing. All rights reserved. Publisher An entity responsible for making the resource available IGI Global Relation A related resource ISBN: 979-836938188-5; 979-836938186-1; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online