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            <name>Title</name>
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                <text>Faculty Publications</text>
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    <name>Conference Paper</name>
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          <name>Creator</name>
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              <text>Kafila; Hari Krishna, Somanchi; Kulshrestha, Nitin; Singh Sidhu, Kawerinder; Budiharjo, Roy; Inumula, Krishna Murthy</text>
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          <name>Title</name>
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              <text>The Impact of AI on High-Frequency Trading: A New Paradigm in Share Market Dynamics</text>
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          <name>Date</name>
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              <text>01-01-2025</text>
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              <text>2025 International Conference on Pervasive Computational Technologies, ICPCT 2025;pp.452-458</text>
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              <text>&lt;a href="https://doi.org/10.1109/ICPCT64145.2025.10940362" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/ICPCT64145.2025.10940362&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105002861705?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105002861705?origin=resultslist&lt;/a&gt;</text>
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              <text>Kafila, Sr University, School of Business, Telangana, Warangal, India; Hari Krishna S., Vignana Bharathi Institute of Technology, Department of Business Management, Aushpur Village, Ghatkesar Mandal, Telangana State, 501301, India; Kulshrestha N., Christ Deemed to Be University, Commerce Finance and Accountancy, Uttar Pradesh, Ghaziabad, India; Singh Sidhu K., Uttaranchal University, Uttaranchal Institute of Management, Uttarakhand, Dehradun, India; Budiharjo R., Telkom University, Accounting, School of Economics and Business, West Java, Bandung, 40257, Indonesia; Inumula K.M., Symbiosis International (Deemed University), Symbiosis Institute of International Business (SIIB), Maharashtra, Pune, 411057, India</text>
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              <text>A fresh approach in financial trading has emerged as a result of the significant shifts in the dynamics of global share markets brought about by the incorporation of artificial intelligence (AI) into high-frequency trading (HFT). In order to analyse large datasets in real-time, perform trades in microseconds, and AI-driven Deep learning, machine learning, and natural language processing are all examples of things that HFT uses to help people make the best choices they can in markets that have to change all the time. This change will help people make better decisions, and sellers will be able to respond quickly to changes in the market. Individuals can trade faster, better, and for greater amounts of cash with it than ever before. AI does have some problems when used in HFT, though. It can make the market less stable, lead to legal problems, and make it more diligently to be fair and honest. The amount of money, how well markets work, along with the way risks are handled are all changed by AI. It also discusses about how AI changes HFT. This study talks about the pros and cons of HFT powered by AI. Along with the way shares are sold, it also hints at how it might change future rules.  2025 IEEE.</text>
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              <text>AI; ML; Precision; Share Market; Trading</text>
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          <name>Publisher</name>
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              <text>Institute of Electrical and Electronics Engineers Inc.</text>
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              <text>ISBN: 979-833150868-5;</text>
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              <text>Restricted Access; Hardcopy may be available in the library</text>
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              <text>online</text>
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