Merger and Acquisition Decision Optimization

• Main Authors: Shun-Chang Yang, 楊順昌
• Other Authors: Chao-Chang Chiu
• Format: Others
• Language: en_US
• Published: 2002
• Online Access: http://ndltd.ncl.edu.tw/handle/22823205810113691808

碩士 === 元智大學 === 資訊管理學系 === 90 === When a manager decides to merge or acquisition the other enterprise, a traditional financial statement or financial index is an important reference to decision of mergence; however, the traditional financial statement and financial index cannot really reflect dynamic risks of the objective business. It leads to the price of mergence is more higher or doesn’t get benefits when a decision maker doesn’t estimate various uncertainties; finally, we may throw in more cost than ago to solve many problems of the company merged and then encumber with the merger. As a result, our research combine Discounted Cash flow (DCF) method with Monte Carlo Simulation to simulate a period of working varieties of the merged business by Simple Additive Weighting (SAW), such as the sales revenue or the operating cost. Then we compute the weight score of financial or nor-financial ratio of the weight which is decide by a manager and result an optimal merged combination which is fits in with the constraints by Genetic Algorithm. By doing this, we can help the decision maker evaluate the merger in advance and reach M&A portfolio optimization.