Applying the negative selection algorithm for merger and acquisition target identification theory and case study

Satyakama Paul, Andreas Janecek, Fernando Buarque De Lima Neto, Tshilidzi Marwala

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

In this paper, we propose a new methodology based on the Negative Selection Algorithm that belongs to the field of Computational Intelligence (specifically, Artificial Immune Systems - AIS) to identify takeover targets. Although considerable research based on customary statistical techniques and some contemporary Computational Intelligence techniques have been devoted to identify takeover targets, most of the existing studies are based upon multiple previous mergers and acquisitions. Contrary to previous research, the novelty of this proposal lies in the methodology's ability to suggest takeover targets for novice firms that are at the beginning of their merger and acquisition spree. We first discuss the theoretical perspective and then provide a case study with details for practical implementation, both capitalizing from unique generalization capabilities of AIS algorithms.

Original languageEnglish
Title of host publicationProceedings - 1st BRICS Countries Congress on Computational Intelligence, BRICS-CCI 2013
PublisherIEEE Computer Society
Pages609-616
Number of pages8
ISBN (Print)9781479931941
DOIs
Publication statusPublished - 2013
Event1st BRICS Countries Congress on Computational Intelligence, BRICS-CCI 2013 - Recife, Brazil
Duration: 8 Sept 201311 Sept 2013

Publication series

NameProceedings - 1st BRICS Countries Congress on Computational Intelligence, BRICS-CCI 2013

Conference

Conference1st BRICS Countries Congress on Computational Intelligence, BRICS-CCI 2013
Country/TerritoryBrazil
CityRecife
Period8/09/1311/09/13

Keywords

  • Artificial Immune System
  • Cosine similarity
  • Euclidean distance
  • M&A
  • Merger and Acquisition
  • Negative Selection Algorithm
  • Takeover target prediction

ASJC Scopus subject areas

  • Artificial Intelligence

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