Research And Implementation Of Intelligent Stock Quantitative Trading System For Private Equity Fund

After more than 30 years,China's securities market is still in the stage of rapid and vigorous development.The continuous deepening of the integration of computer technology and financial field promotes the development of capital market toward the direction of intelligence.In view of human beings' greed,fear and fluke psychology in investment,quantitative trading using mathematical and statistical knowledge for data analysis and on the basis of the data to support decision making,using computer technology to trading,overcome some of weaknesses of human nature,avoid the influence of subjective emotion investors,through a more rational and more standardized,more scientific investment,to achieve stable asset appreciation.With the rise of artificial intelligence in recent years,the research of predicting stock price trend by machine learning model also provides new development direction and power for the field of quantitative trading.This paper firstly abstracts the quantitative trading strategy mathematically,constructs the stock selection strategy through the multi-factor stock selection model and combines the idea of plate rotation,establishes the factor index as the standard for selecting the stock pool,and selects the qualified stocks from the stock data.Next build bull and bear market identification model to divide the bull and bear market,then build automatic quantitative trading process,including stock selection,transaction records detail acquisition,net asset value calculation,index and earnings several algorithms,formation algorithm according to the data to make investment decisions,according to the fixed rules operation when buying and selling stocks and calculate each index and the proceeds of full automatic quantitative trading process.Finally,design intelligent bull market interval quantitative back test algorithm.Using machine learning ideas to train the parameters of the trading strategy in bull market,get the parameters with the best performance,and generalize them to the following bull market interval for verification,optimize the trading strategy,evaluate the benefits and risks of the trading strategy,and improve the ability of the trading strategy to create income.In view of the limitation that traditional quantitative trading strategy has fixed parameters and cannot find stock selling points accurately,the basic idea of machine learning is integrated into the traditional quantitative trading strategy,and use algorithms to optimize the parameters in the trading strategy and perform back testing.Design of private equity fund intelligent stock quantitative trading system to seize private equity investment threshold is high,the characteristic,the pursuit of absolute excess returns to choose only overall in the stock market is on the rise of investment in the bull market range of steer clear of the stock market bearish,gloomy outlook bear territory,try to avoid into the bear market,in order to obtain higher returns.Compared with Shanghai and Shenzhen 300 index by back-test experiments results,realizing the private fund smart stock trading systems can range in bull market to make profit from a series of stock assets of optimal investment decisions,algorithm realized gain excess returns in the stock market investment,is the research of quantitative trading and its strategy to provide some reference value.