Risk assessment for enterprise merger and acquisition via multiple classifier fusion

Abstract

This paper aims to solve the problem of Risk assessment for enterprise merger and acquisition (M&A), which is an important problem in modern company management. Firstly, we design an index system to assess risks of enterprise M&A behavior, and six risks are considered: 1) Systemic risk, 2) Law risk, 3) Financial risk, 4) Intermediary risk, 5) Integrated risk, and 6) Information risk. Furthermore, 18 indexes are chosen to cover these six aspects. Secondly, we illustrate how to utilize the proposed risk assessment in the decision system for enterprise M&A risk assessment. We separate the M&A risk assessment process to three steps, that is, 1) Before M&A, and 2) In M&A, and 3) After M&A. Particularly, after the risk assessment process, there are three decisions for enterprise managers, that is, 1) implement the original M&A plan, 2) modify the original M&A plan, and 3) refuse it. Thirdly, we propose the multiple classifier fusion based risk assessment algorithm, which aims to effectively combine the six support vector machines. To relax the limitation of the SVM classifier, we introduce the fuzzy theory in the multiple classifier fusion algorithm, and the category label assignment is determined by utilizing a maximum membership rule. Finally, we conduct an experiment to make performance evaluation by constructing a dataset which includes the M&A data of 200 enterprises, among which 185 enterprises are used as training dataset and others are regarded as testing dataset. Using ROC curve, MAE and MAPE as evaluation criterions, performance of the proposed method is compared with single SVM scheme. Experimental results demonstrate that combining multiple the SVM classifiers together, accuracy of M&A risk assessment is greatly enhanced.

Improving AdaBoost Classifier to Predict Enterprise Performance after COVID-19

“…A cluster analysis and a correspondence analysis could be applied to explore the mutual relationships among the selected categories for each country [17]. Duan et al (2019) considered six criteria to evaluate and classify the risks of an enterprise. The risk criteria included financial risk, intermediary risk, integrated risk, systemic risk, legal risk and information risk.…”

“…The mean absolute error (MAE) and mean absolute percentage error (MAPE) receiver operating characteristics (ROC) were selected as the evaluation criteria for evaluating the prediction ability of this method. Compared with the traditional single SVM classifier, their method could deliver a very high predictive performance [18]. Hu et al (2019) had arranged some historical annual data from the Taiwanese tourism bureau.…”

Mergers and Acquisitions Risk Modeling

“…Also important are the risk of conflicts between shareholders of the companies, the risk of losing key employees of the target company who do not agree with the deal. Duan et al (2019) separate the M&A risk assessment process to three steps, that is: before M&A, in M&A and after M&A. They assign the greatest importance to the stage of carrying out integration procedures.…”