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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | SCALABLE ALGORITHMS FOR REAL-TIME ANALYTICS IN FINANCIAL MARKETS: HARNESSING BIG DATA POWER |
| Authors Name: | Mrs. Ayesha Sultana , Mrs. Asma Sultana |
| Download E-Certificate: | Download |
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IJNRD_216779
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| Published Paper Id: | IJNRD2403578 |
| Published In: | Volume 9 Issue 3, March-2024 |
| DOI: | |
| Abstract: | In the rapidly evolving landscape of financial markets, the ability to process vast amounts of data in real-time has become paramount. This paper explores the realm of scalable algorithms for real-time analytics in financial markets, emphasizing the utilization of big data technologies to extract actionable insights. The challenges posed by the velocity, volume, and variety of financial data are elucidated, highlighting the necessity for scalable solutions capable of handling massive datasets with minimal latency. Various algorithmic approaches tailored for real-time analytics, including machine learning, deep learning, natural language processing, and data mining techniques, are discussed. Integration of advanced technologies such as cloud computing and distributed computing frameworks is examined to achieve scalability and parallel processing capabilities, crucial for handling the immense computational demands of real-time financial analytics. Additionally, the significance of data preprocessing and feature engineering in optimizing algorithm performance is emphasized. The deployment of real-time analytics platforms in financial institutions, encompassing algorithmic trading, risk management, fraud detection, and portfolio optimization, is showcased to illustrate the practical applications and benefits of scalable algorithms. By leveraging cutting-edge technologies and algorithmic innovations, financial institutions can gain a competitive edge, navigate volatile market conditions, and capitalize on emerging opportunities with agility and precision. |
| Keywords: | Scalable algorithms, Real-time analytics, financial markets, big data, Algorithmic trading, Data processing, Machine learning, High-frequency trading, Market analysis, Computational finance |
| Cite Article: | "SCALABLE ALGORITHMS FOR REAL-TIME ANALYTICS IN FINANCIAL MARKETS: HARNESSING BIG DATA POWER", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 3, page no.f680-f687, March-2024, Available :http://www.ijnrd.org/papers/IJNRD2403578.pdf |
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| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2403578 Registration ID: 216779 Published In: Volume 9 Issue 3, March-2024 DOI (Digital Object Identifier): Page No: f680-f687 Country: -, -, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2403578 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2403578 |
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ISSN: 2456-4184
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