Design And Implementation Of Stock Quantitative Backtesting System

In today's society,investment stocks are favored by more and more people,but the stock market is a highly complex market.The stock price trend is affected by many factors.In such a complicated situation,we want to accurately predict the trend of stocks.And getting excess benefits through trading is not an easy task.In the stock market,the disadvantages of insufficient investor resources are further magnified because investment institutions have their own access to information and intelligence.Then ordinary investors need to find an effective way to make up for the gap in information.The quantitative investment that has gradually developed in recent years has become the best choice.Based on the stock price forecast,this paper takes the back-test of stock quantification strategy as the core,and uses a data that ordinary irnvestors can obtain,and designs a stock quantback system for ordinary investors.The development requirements of the system are elaborated,and the design idea and overall architecture of the system are described.According to the demand,the stock quantification test system is designed as six functional modules:stock data download,stock basic information query,historical data backtest,result visualization,quantitative analysis tool and strategy parameter optimization.The detailed design and implementation of each module are introduced in turn..The stock data download module describes the acquisition of stock data sources and the storage of data in the database.When introducing the database storage of stock data,it describes the advantages of MongoDB database for storing stock data,and gives the table structure;stock basic information.The query module is responsible for the user to query the stock related information;the historical data backtest module is the core function of the system and is responsible for the implementation of the backtest function;the quantitative analysis tool provides technical support for the user to analyze a single stock;the strategy parameter optimization uses the GirdSearch method to optimize the selected strategy.Parameters to improve the performance of the strategy;the results visualization module is responsible for graphically presenting the results of the data backtesting and quantitative analysis tool modules.System functions were tested after all module implementations were completed.The system provides a certain reference for investors'decision-making in the stock market through the display and measurement of the backtest results of trading strategies.