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Review Article Open Access December 27, 2023

Leveraging Machine Learning Techniques for Predictive Analysis in Merger and Acquisition (M&A)

KishanKumar Routhu 1, Vasu Velaga 2, Chethan Sriharsha Moore 3, Suneel Babu Boppana 4, Purna Chandra Rao Chinta 3 and Krishna Madhav Jha 5
1
ADP, Openstack Architect, USA
2
Cintas Corporation, SAP Functional Analyst, USA
3
Microsoft, Support Escalation Engineer, USA
4
iSite Technologies, Project Manager, USA
5
Topbuild Corp, Sr Business Analyst, USA
Publihed in: Open Journal of Agricultural Research (Volume 3, Issue 1, 2023)
Page(s): 56-71
DOI: 10.31586/jaibd.2023.1215
Received
July 08, 2023
Revised
October 19, 2023
Accepted
December 22, 2023
Published
December 27, 2023
Keywords
Machine Learning, Merger and Acquisition, Predictive Analysis, ML Techniques in Predictive Analysis, Predictive Analysis in Merger and Acquisition (M& A)
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright: Copyright © The Author(s), 2023. Published by Scientific Publications
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Cite This Article

APA Style
Routhu, K. , Routhu, K. Velaga, V. , Velaga, V. Moore, C. S. , Moore, C. S. Boppana, S. B. , Boppana, S. B. Chinta, P. C. R. , & Chinta, P. C. R. (2023). Leveraging Machine Learning Techniques for Predictive Analysis in Merger and Acquisition (M&A). Open Journal of Agricultural Research, 3(1), 56-71. https://doi.org/10.31586/jaibd.2023.1215
ACS Style
Routhu, K. ; Routhu, K. Velaga, V. ; Velaga, V. Moore, C. S. ; Moore, C. S. Boppana, S. B. ; Boppana, S. B. Chinta, P. C. R. ; Chinta, P. C. R. Leveraging Machine Learning Techniques for Predictive Analysis in Merger and Acquisition (M&A). Open Journal of Agricultural Research 2023 3(1), 56-71. https://doi.org/10.31586/jaibd.2023.1215
Chicago/Turabian Style
Routhu, KishanKumar, KishanKumar Routhu. Vasu Velaga, Vasu Velaga. Chethan Sriharsha Moore, Chethan Sriharsha Moore. Suneel Babu Boppana, Suneel Babu Boppana. Purna Chandra Rao Chinta, and Purna Chandra Rao Chinta. 2023. "Leveraging Machine Learning Techniques for Predictive Analysis in Merger and Acquisition (M&A)". Open Journal of Agricultural Research 3, no. 1: 56-71. https://doi.org/10.31586/jaibd.2023.1215
AMA Style
Routhu K, Routhu KVelaga V, Velaga VMoore CS, Moore CSBoppana SB, Boppana SBChinta PCR, Chinta PCR. Leveraging Machine Learning Techniques for Predictive Analysis in Merger and Acquisition (M&A). Open Journal of Agricultural Research. 2023; 3(1):56-71. https://doi.org/10.31586/jaibd.2023.1215 
@Article{ojar1215,
AUTHOR = {Routhu, KishanKumar and Velaga, Vasu and Moore, Chethan Sriharsha and Boppana, Suneel Babu and Chinta, Purna Chandra Rao and Jha, Krishna Madhav},
TITLE = {Leveraging Machine Learning Techniques for Predictive Analysis in Merger and Acquisition (M&A)},
JOURNAL = {Open Journal of Agricultural Research},
VOLUME = {3},
YEAR = {2023},
NUMBER = {1},
PAGES = {56-71},
URL = {https://www.scipublications.com/journal/index.php/JAIBD/article/view/1215},
ISSN = {2769-8874},
DOI = {10.31586/jaibd.2023.1215},
ABSTRACT = {M&A is a strategic concept of business growth through consolidation, gaining market access, increasing strategic positions, and increasing operational efficiency. To understand the dynamics of M&A, this paper looks at aspects such as targeted firm identification, evaluation, bidding for the target firm, and post-acquisition integration. All forms of M&A, including horizontal, vertical, conglomerate, and acquisitions, are discussed in terms of goals and values, including synergy, cost reduction, competitive advantages, and access to better technology. However, issues such as cultural assimilation, adhesion to regulations, and calculating an inaccurate value are also resolved. The paper then goes deeper to provide insight into how predictive analytics applies to M&A, using ML to improve decision-making with forecasting benefits. Including healthcare, education, and construction industries, the presented predictive models using regression analysis, neural networks, and ensemble techniques help to make decisions. Through time series and real-time data, PDA enables sound M&A strategies, effective risk management and smooth integration.},
}
%0 Journal Article
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%A Velaga, Vasu
%A Moore, Chethan Sriharsha
%A Boppana, Suneel Babu
%A Chinta, Purna Chandra Rao
%A Jha, Krishna Madhav
%D 2023
%J Open Journal of Agricultural Research

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%V 3
%N 1
%P 56-71

%T Leveraging Machine Learning Techniques for Predictive Analysis in Merger and Acquisition (M&A)
%M doi:10.31586/jaibd.2023.1215
%U https://www.scipublications.com/journal/index.php/JAIBD/article/view/1215

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AU  - Boppana, Suneel Babu
AU  - Chinta, Purna Chandra Rao
AU  - Jha, Krishna Madhav
TI  - Leveraging Machine Learning Techniques for Predictive Analysis in Merger and Acquisition (M&A)
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AB  - M&A is a strategic concept of business growth through consolidation, gaining market access, increasing strategic positions, and increasing operational efficiency. To understand the dynamics of M&A, this paper looks at aspects such as targeted firm identification, evaluation, bidding for the target firm, and post-acquisition integration. All forms of M&A, including horizontal, vertical, conglomerate, and acquisitions, are discussed in terms of goals and values, including synergy, cost reduction, competitive advantages, and access to better technology. However, issues such as cultural assimilation, adhesion to regulations, and calculating an inaccurate value are also resolved. The paper then goes deeper to provide insight into how predictive analytics applies to M&A, using ML to improve decision-making with forecasting benefits. Including healthcare, education, and construction industries, the presented predictive models using regression analysis, neural networks, and ensemble techniques help to make decisions. Through time series and real-time data, PDA enables sound M&A strategies, effective risk management and smooth integration.
DO  - Leveraging Machine Learning Techniques for Predictive Analysis in Merger and Acquisition (M&A)
TI  - 10.31586/jaibd.2023.1215
ER  -