M&A Short-Term Performance Based on Elman Neural Network Model: Evidence from 2006 to 2019 in China

Based on the event study method, this paper conducts the analysis on the short-term performance of 1302 major mergers and acquisitions (M&A) in China from 2006 to 2019 and takes the cumulative abnormal return (CAR) as the measurement index. After comparing the five abnormal return (AR) calculati...

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Bibliographic Details
Published inComplexity (New York, N.Y.) Vol. 2020; no. 2020; pp. 1 - 15
Main Authors Xiao, Ming, Li, Ge, Yang, Xionghui
Format Journal Article
LanguageEnglish
Published Cairo, Egypt Hindawi Publishing Corporation 2020
Hindawi
Hindawi Limited
Subjects
Acquisitions & mergers
Capital markets
Neural networks
Securities markets
Stock exchanges
Stockholders
China
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Summary:Based on the event study method, this paper conducts the analysis on the short-term performance of 1302 major mergers and acquisitions (M&A) in China from 2006 to 2019 and takes the cumulative abnormal return (CAR) as the measurement index. After comparing the five abnormal return (AR) calculation models, it is found that the commonly used market model method and the market adjustment method have statistical defects while the Elman feedback neural network model is capable of good nonlinear prediction ability. The study shows that M&A can create considerable short-term performance for Chinese listed company shareholders. The CAR in window period reached 14.45% with a downward trend, which is the win-win result achieved through the cooperation between multiple parties and individuals driven by their respective rights and interests in the current macro-microeconomic environment in China.
ISSN:1076-2787
1099-0526
DOI:10.1155/2020/8811273