DocumentCode :
2431381
Title :
Using Monte Carlo Simulation with Crystal Ball to Improve Mergers & Acquisitions Decision
Author :
Bao-Cheng, He ; Shu-Zhi, Yao ; Hong-Mei, Sun ; Hai-Gang, Wang
Author_Institution :
Sch. of Manage., Shaanxi Univerisity of Sci., Xi´´an, China
fYear :
2010
fDate :
7-9 May 2010
Firstpage :
1592
Lastpage :
1595
Abstract :
Mergers & Acquisitions (M&A) is an important way to expand the enterprises´ scale and improve their core competitiveness, but M&A decision is a big challenge for the manager, especially in the highly uncertain environment. The main approach to value M&A by traditional financial theory is discounted cash flow (DCF) model. DCF models are used for M&A evaluation by most companies, presumably because they are straightforward to apply and because they are intuitively appealing. However DCF method fails to consider the value of managerial flexibility. Real option analysis (ROA) offers a superior way of capturing the value of flexibility, while ROA can´t effectively deal with the volatility of parameters in itself, because there are typically no historical returns for the underlying asset and no current market prices. This paper uses Monte Carlo Simulation with Crystal Ball to settle the parameters volatility problems in ROA. The case study further proves that it can improve M&A decision effectively under highly uncertain circumstances.
Keywords :
Monte Carlo methods; corporate acquisitions; financial management; DCF model; M&A decision; M&A evaluation; Monte Carlo simulation; crystal ball; discounted cash flow; enterprise scale; financial theory; managerial flexibility; mergers & acquisitions decision; parameters volatility problem; real option analysis; Analytical models; Biological system modeling; Companies; Crystals; Investments; Monte Carlo methods; Predictive models; Crystal Ball; Mergers & Acquisitions; Monte Carlo Simulation; Real option Analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
E-Business and E-Government (ICEE), 2010 International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-0-7695-3997-3
Type :
conf
DOI :
10.1109/ICEE.2010.403
Filename :
5592410
Link To Document :
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