Design And Implementation Of Stock Market Browsing And Analysis System Based On Node.js Technology

The financial market plays a very important role in the country's economic and social development.Stock trading is not only a corporate financing model,but also an increasing number of individual investors' financial management methods.The existing stock systems in the domestic market are basically C/S architecture,with cumbersome installation processes,difficult data synchronization,and products that are too specialized,most of which have complex interfaces and functions,which cannot meet the needs of investors at different levels.For new investors,in addition to the basic stock market browsing function,there are also needs for communication and learning,intelligent stock selection,and the use of computers for data analysis to help them make intelligent decisions.Therefore,the current stock software is gradually being transformed into a comprehensive integrated stock software service platform of 'quotes+social platform+intelligent analysis+information browsing'based on quotation browsing.In response to the needs of primary investors in the stock market,this article combines new Internet technologies to design and implement a stock market browsing and analysis system based on Node.js's B/S architecture.The core of Node.js is based on the event-driven asynchronous I/O model.This mechanism significantly improves the concurrency of the server.Therefore,node.js has become a popular server technology in recent years.The front-end of the system uses the popular Vue.js framework,page component development and front-end and back-end separation mode greatly improve development efficiency.Due to the complex structure of the stock data,based on design MongoDB storage mode,with the Json format avoids Node.js type conversion,data in persistent storage.Combined Echarts framework and H5 Canvas technology,through multiple charts intuitive visual interface to show the user a variety of data as well as details of the stock market tracking.Stock data includes real-time data,minute K-line data,daily,monthly,and annual K-line data,company industry information,indicator data MACD,RSI,KDJ,etc.;market conditions include rankings,dragon and tiger lists,leading stocks,leading sectors Etc.On the one hand,the system uses Redis database for stock data caching,and on the other hand,socket.io instant messaging technology is used to enable the server to actively push messages or stock data to the client to ensure real-time performance.In addition,this article also mainly introduces the social platform module,early warning module,intelligent stock selection,self-selected stock management and other functions to facilitate users to browse market data and learn stock knowledge.Taking into account the intelligence of the system and focusing on data analysis,it not only supports investors to freely change indicator parameters according to trading styles and export data for local analysis,this article also proposes a MACD indicator optimization model based on machine learning,to a certain extent,which alleviates the problems of traditional MACD indicator lag and frequent false signals when stock prices fluctuate.The early warning module can send reminders of buying and selling to users in a timely manner.At the same time,it realized a combined stock price prediction model based on ARIMA and LSTM neural network,and provided reasonable suggestions to investors through advanced computer technology.This article also optimizes the design from the aspects of performance and security,including database connection pool,load balancing,browser caching,etc.;and defends against common XSS,CSRF,SQL injection and other website attacks,such as Token authentication login and Md5+Salt method encrypts and stores user information as a security measure.