SCALABLE ALGORITHMS FOR REAL-TIME ANALYTICS IN FINANCIAL MARKETS: HARNESSING BIG DATA POWER

SCALABLE ALGORITHMS FOR REAL-TIME ANALYTICS IN FINANCIAL MARKETS: HARNESSING BIG DATA POWER

Registration ID: IJNRD_216779

Published ID: IJNRD2403578

DOI: Click Here to Get

Mrs. Ayesha Sultana , Mrs. Asma Sultana

Scalable algorithms, Real-time analytics, financial markets, big data, Algorithmic trading, Data processing, Machine learning, High-frequency trading, Market analysis, Computational finance

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.

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"SCALABLE ALGORITHMS FOR REAL-TIME ANALYTICS IN FINANCIAL MARKETS: HARNESSING BIG DATA POWER", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 3, page no.f680-f687, March-2024, Available :https://ijnrd.org/papers/IJNRD2403578.pdf

Volume 9 Issue 3, March-2024

Pages : f680-f687

Paper Reg. ID: IJNRD_216779

Published Paper Id: IJNRD2403578

Downloads: 000121179

Research Area: Engineering

Country: -, -, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2403578.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2403578

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

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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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

Call For Paper - Volume 10 | Issue 8 | August 2025

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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world. IJNRD will provide an opportunity for practitioners and educators of engineering field to exchange research evidence, models of best practice and innovative ideas.

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