Conventional and Neural Network Target-Matching Methods Dynamics : The information technology mergers and acquisitions market in the USA. / Anagnostopoulos, Ioannis; Rizeq, Anas.

In: Intelligent Systems in Accounting, Finance and Management, Vol. 28, No. 2, 02.06.2021, p. 97-118.

Research output: Contribution to journalArticlepeer-review

E-pub ahead of print

Abstract

In this paper, we explore, apply, and compare two types of target screening classification techniques—the NN and the traditional logistic regression (LR) M&A forecasting techniques—in terms of successful target prediction in the IT M&A market for the USA. We provide for a demonstration of the growing prospects of the use of an NN to systematize feature engineering from raw time series, in a more methodical way as a result of the strategic change in the types of digital commodities that decision-makers demand. In that respect, and within the context of M&As, predicting which companies will become takeover targets and the ability to discriminate between high‑ and low-quality targets is very important for managers and financiers, as well as for regulators and competition market committees. Our findings provide valuable insights to guide managers in financial and other organizations to improve their performance through suitable target (or nontarget) screening methods.
Original languageEnglish
Pages (from-to)97-118
Number of pages22
JournalIntelligent Systems in Accounting, Finance and Management
Volume28
Issue number2
Early online date2 Jun 2021
DOIs
Publication statusE-pub ahead of print - 2 Jun 2021
This open access research output is licenced under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

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