Research On The Stock Market By Big Data Method

The stock market is a very large and complex system.Its function is mainly to transfer,sell and circulate the issued shares,and its condition is closely related to the development of the national economy.In China,with the rapid rise of the national economy,the stock market is booming,more and more investors are investing in the stock market with the enthusiasm of the support of national construction and investment management.Therefore,the research on the stock market is of great significance.Although there have a lot of research work in this area,but most of the results are not satisfactory,the main shortcoming are mostly in the following two points: first,the level of information is limited and calculation of intake and storage level limit for a smaller amount of data supporting research;two,did not fully consider the impact of interest rate and internal rate of return.With the development of modern computer and Internet,we have the ability to overcome these two shortcomings and make better achievements in scientific research.This paper tries to construct three ways to explore the mysteries of the stock market from the view of enlarging the amount of data and paying attention to the interest rate and the rate of return and carrying out some empirical analysis.This article consists of five chapters.The first chapter introduces the significance and background of the stock and the big data method,dynamic related research,and explains the structure how the work to be carried out.The second chapter introduces the content and significance of behavioral finance,and the related research trends.Then,from the point of view of large data,machine learning and behavioral finance,we design an algorithm to define a kind of performance a random variable R of the yield status of the stock and conducts the relevant study.The discount to the historical data of the stock by using the designed algorithm to derive a sample based on R.According to the samples to make a empirical distribution,the empirical distribution establish the approximation of a sequence distribution,then gives an approximate analytical method for optimizing the distribution and generation of R.To demonstrate its significance based on,and reveals some problems for further study.The third chapter starts from the elimination of the interest rate and the internal rate of return of the perspective of the definition of a moving average value,establish a method to predict the stock price and stock index trend according to the length of the averagevalue,makes an empirical analysis of historical data in the past years based on the relevant basic knowledge.The fourth chapter first introduces the definition of Markov chain,an internal rate of return,set up an internal rate of return of discounted based on the historical data and the Markov chain prediction of stock and stock index trend,and to analyze the historical data.The fifth chapter is the conclusion and prospect,summarizes the description of the work,points out the shortcomings,and puts forward the problems to be further studied,and the author's future prospects.The work can provide some inspiration for the stock market,which can provide some inspiration for the further study of the stock market from the perspective of large data,machine learning and behavioral finance.