| Since the fortieth anniversary of reform and opening up,people's living standards have been improving with the development of economy.People's demand for wealth accumulation and growth has become more and more urgent.With the vigorous development of financial markets and the improvement of people's cultural level,stock investment has become a popular way of wealth growth.But nowadays,the financial market is growing,the amount of information is huge,and the sources of information are various.Obviously,the traditional artificial analysis and prediction of stock investment can not meet the investors' requirements for returns and timeliness.Investors are more inclined to look for products with high returns and high returns to invest,but at the same time,they hope to minimize the investment risk.Therefore,the choice of investment strategy and the stock investment relying on technical means become very important.In recent years,with the rise of artificial intelligence,machine learning as the core field of artificial intelligence has been further improved,especially the tremendous success of machine learning algorithm in computer vision,speech recognition,expert system and other fields,which makes people also expect that the financial field can improve the performance of market forecasting through machine learning method.This paper mainly discusses how to choose a more appropriate investment strategy in the process of investment,and the application of machine learning in the field of stock quantitative investment.In this paper,the CART algorithm is used to select the characteristic factors according to the quantified investment strategy,and then the prediction model is constructed.Finally,compared with the results of the traditional model,it is easy to find that the results of the model based on decision tree are better than those of the traditional model.It proves that the model based on decision tree has stronger prediction ability and can select the best quality more effectively Stock. |
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