Artificial intelligence stock system application method

Abstract

The invention relates to an artificial intelligence stock system application method, and relates to the technical field of stock transaction, and the method comprises the steps: training a rise and fall prediction model, predicting a stock prediction data set in a next period, screening growth situation stock data, classifying the stock data, analyzing a user preference field, and correspondingly pushing information. According to the artificial intelligence stock system, the stock in the corresponding field can be pushed to the user, so that the buyed stock can correspond to the field understood by the user, the user can better understand the stock data to judge holding or selling, and the possibility that the user benefits is increased.

Description

technical field

[0001] The present application relates to the field of stock trading, in particular to an application method of an artificial intelligence stock system. Background technique

[0002] China's stock market has made great achievements after years of development. As an important part of China's securities market, the stock market plays an important role in China's economic development and social stability.

[0003] my country's small and medium investors are an important part of China's stock market, but many market information in my country's stock market is not disclosed in a timely manner, and the acquisition of information requires high time and economic costs. The screening and buying system came into being. In the current stock automatic screening and buying system, usually only the profit of the stock is used as the primary push condition. When using this kind of automatic screening and buying system, users can only use the expected growth rate to optimize ...

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