Research On Prediction Of Stock Price Fluctuation By Financial Index

Since the establishment of Shanghai stock exchange in 1990,China's stock market has gone through a stage of shock development,gradual standardization and marketization.However,on the whole,the fluctuation of stock price has the characteristics of large range and high frequency,which makes the stock market risky and unstable.Stock price fluctuations within a certain range can promote the national economy,but too frequent and violent fluctuations will make investors do not know how to make investment decisions,and even affect the stability of the entire economy.In this context,it is particularly important to explore the rule of stock price fluctuations and make predictions on stock price fluctuations.As the main information source of the stock market and the important basis for investors to make investment decisions,the financial index data of listed companies are very representative.It will be of practical significance to add the financial index data reflecting the intrinsic value of the company into the prediction of stock price fluctuations.This paper firstly sorts out relevant domestic and foreign literatures on the prediction of stock price volatility,and then analyzes the factors affecting the stock price volatility,and selects the financial indicators that can represent the intrinsic value of the company as the influencing factors.Combined with relevant theoretical basis,this paper analyzes the mechanism of financial indicators on stock price fluctuations and the selection of major financial indicators.Based on the csi 300 manufacturing listed companies,for example,choose the profit ability,debt paying ability,development ability and the ability to operate the 14 financial indicators,the innovative will profit ability,debt paying ability,development capacity index and operation ability index constructed by financial index system for evaluating company standards,rating on the operating performance of listed companies,select high-quality companies as the research object of this article.BP neural network was used to train the model,and the prediction test was carried out according to the out of sample data.Through comparative analysis,the prediction effect of BP neural network before principal component analysis is compared with that after principal component analysis,and the conclusion is drawn.The research findings are as follows: first,the stock market in China can be predicted;Second,the financial indicators of the listed companies in the csi 300 manufacturing industry selected in this paper can predict the stock price fluctuations through BP neural network.Third,in the construction of prediction model,pca-bp neural network improves the accuracy and efficiency of prediction,reduces the error of prediction,and is a better method to predict stock price fluctuations.Fourthly,investors can score and rank the operating status of listed companies by building a comprehensive evaluation system of financial indicators composed of profitability,debt paying ability,development ability and operating ability,so as to have a more objective understanding of the operating status of listed companies and make investment decisions.