Price prediction of target of mergers and acquisitions based on genetic-algorithm BP neural network

In order to predict the price of candidates in acquisition and evaluate its feasibility, this paper puts forward a model of price prediction of candidates based on genetic-algorithm and BP neural network. The model is trained by the data of market deals which were made in the past. The result of simulation and test indicates that average error of prediction is percent 11.03. It can be as the reference of evaluating the feasibility of mergers & acquisitions. More index and training samples should be increased to improve the model.