Study On The Synergy Prediction Model Of Listed Companie

Recently,with the accelerating pace of merger and acquisition, failure casese of M&Amerged in endlessly. the prediction of synergy is the core issue of the M&A research. Inaddition,predictng the synergy accurately can reduce the risk of M&A,so as to reduce theblindness and randomness in M&A. Generally we use the diversification in stock returnsand performance to predict synergy. However there are so many problems in the twomethods. So research of the article is how to predict synergy accurately, and the article useBP neural network build a listed companies synergy forecasting model. Prior to providethe basis for accurate prediction of synergy.Firstly,this article describes the meaning and context. From M&A motivation andsynergy calculated two aspects study the relevant articles at home and abroad, find out theproblems in the past articles, and defines the content and framework of this article.Secondly, based on the theoretical research of the concept and types of M&A, thisarticle deeply analyses M&A motivation at home and abroad,and describes the concept,source and types of synergy.Thirdly, this article makes a synergy value model by many variation of financialindexes and principal component analysis (PCA). Prior to use the model to calculatesynergy relative value. And as the output value of BP neural network.Fourthly,by analysing various factor. we define six factors of synergy,and establisha synergy factor indicators. By BP neural network technology to fit the M&A synergyand its influencing factors, In addition,we also build a BP neural network predictionmodel which use synergy as dependent variable and use the impact synergy factors asindependent variables.At last, we use the method of empirical research to study27M&A samples in Listedcompanies occurred in2002to2008. The results show that the prediction model of BPneural network can predict merger synergies accurately.