The prediction of financial market based on BP neural network is used to maximize the income of investment

Abstract

In the financial market, investors often buy and sell volatile assets to maximize returns. We can use statistical and mathematical tools, mathematical models and computer technology to trade and get excess return ratio. Firstly, we established a price prediction model based on BP neural network, trained the network through the trading prices of bitcoin and gold before 2016, and then predicted the price of the next day every day from September 11, 2016 to September 10, 2021. Through the comparison with the real value and the horizontal comparison of other models, the prediction effect of this model is good. Then, the programming model is used to maximize the benefits in the next day as the objective function, and the constraints are that the amount after the transaction cannot be negative and there is no gold trading in part of the time. Considering the risk in the final transaction model, the planning model is established to find the optimal investment scheme at this time. Finally, the daily investment plan and the final total value are $3886.8.