UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 6 Issue 4
April-2019
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIRGD06028


Registration ID:
531617

Page Number

184-189

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Title

Algorithmic Trading Strategies with Big Data

Abstract

This research article explores the intersection of algorithmic buying and selling strategies and large information analytics, investigating the potential synergies which can revolutionize financial markets. In an era marked with the aid of unparalleled facts era, harnessing the strength of big information has grown to be vital for boosting buying and selling techniques and gaining a aggressive part. The observe delves into the improvement and optimization of algorithmic trading fashions that leverage enormous datasets, starting from marketplace expenses and buying and selling volumes to macroeconomic signs and social media sentiments. The studies employs a complete approach, combining quantitative evaluation and system mastering strategies to find hidden styles and correlations within the large datasets. Emphasis is placed on information the effect of massive information at the accuracy and efficiency of algorithmic buying and selling strategies, with a focus on hazard control and performance evaluation. Furthermore, the article explores the challenges and moral concerns associated with the use of large facts in economic markets. The findings of this studies make a contribution valuable insights to both academia and enterprise, supplying a roadmap for marketplace members to navigate the evolving landscape of algorithmic trading in the generation of big facts. Ultimately, the combination of sophisticated algorithms with giant datasets has the capability to reshape monetary markets, providing traders with progressive gear to make greater informed decisions and adapt to dynamic market situations.

Key Words

Algorithmic Trading Strategies, Big Data Analytics, Financial Markets, Machine Learning, Quantitative Analysis, High-Frequency Trading.

Cite This Article

"Algorithmic Trading Strategies with Big Data", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.184-189, April-2019, Available :http://www.jetir.org/papers/JETIRGD06028.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Algorithmic Trading Strategies with Big Data", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp184-189, April-2019, Available at : http://www.jetir.org/papers/JETIRGD06028.pdf

Publication Details

Published Paper ID: JETIRGD06028
Registration ID: 531617
Published In: Volume 6 | Issue 4 | Year April-2019
DOI (Digital Object Identifier): https://doi.org/10.5281/zenodo.10691972
Page No: 184-189
Country: -, -, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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