Research On The Application Of BP Neural Network Model Based On Particle Swarm Optimization In Quantitative Investment

Quantitative investment in the capital market of developed countries has always been an important way for financial institutions to obtain profits.Under the background of unstable market and changeable policy,quantitative trading can avoid market sentiment and make rational investment so that investors can get better returns or exit stop loss in time.Since the third information revolution,artificial intelligence,as a new frontier of information technology,has been gradually applied to all walks of life.The financial industry is also very sensitive to this.Financial technology has become a hot spot of development,among which the quantitative investment modeling guided by artificial intelligence technology has also received a lot of attention.Artificial intelligence technology integrates a variety of advanced algorithm technology,with a high degree of intelligence,which can provide strong technical support for the improvement of related industries,which makes people pay more and more attention to the research of artificial intelligence technology.Compared with other algorithms,AI does not attach importance to deduction,but rather to induction.Because of the characteristics of this algorithm,artificial intelligence technology can effectively analyze and integrate all kinds of empirical data,so that it can form a model with generalization ability.Firstly,this paper summarizes the traditional quantitative modeling techniques,such as trend judgment quantitative investment strategy,and introduces the principle of artificial neural network algorithm.On this basis,we download the daily data of A-share and financial futures market through wind database,train BP neural network,get the level and weight of neural network,and determine the input and output factor indicators,then input the latest data to the trained neural network for operation,get the investment income of the model,and make a reasonable comparison with theoverall market,so as to Judge whether artificial intelligence quantitative investment technology improves the investment results.At the same time,in the actual operation process,it is also found that under the influence of technical conditions,it is difficult to realize automatic transaction processing in the last trading.Therefore,in the design of automatic trading program,only artificial intelligence algorithm can be used to predict the rise and fall of stock price the next day.This also reserved some space for the follow-up study.