This study is based on Back-propagation neural network theory to forecast Taiwan Top50 Exchange Tracker Fund (ETF50). Because ETF50 is composed of Taiwan Top 50 representative firms, this study applies the technical index of ETF50 and the top 20 of ETF50 stock indices as the inputs of the neural network. Our sample data is mainly separated into two parts, 356 records of training data and 100 records of testing data. After training the neural network, simulating the ETF50 price index and comparing with the mean square error, I choose the top 5 prediction modes. Besides, a speculative trading strategy is applied to evaluate the performance of the best return prediction model. Through my experiment, I found two points: 1. the neural network model proposed has good prediction capability; 2. neural network model applied with my speculative trading strategy can obtain higher return.