Time selection admission method based on machine learning, and terminal equipment

Abstract

The invention is suitable for the technical field of computers, and provides a time selection admission method based on machine learning, and terminal equipment. The method comprises the following steps that: inputting the preset index data of each stock into a preset stock picking model, and outputting a stock combination; independently obtaining the feature data of each stock in the stock combination, wherein the feature data of the stock comprises the stock market transaction data of the stock or the technical index data of the stock; and inputting the feature data of each stock in the stock combination into a long short-term memory which finished being pre-trained, and outputting a price prediction result about each stock in the stock combination. By use of the method, the whole prediction process fully considers the behavior characteristics of a financial market, a deviation between the prediction result and the subsequent practical price tendency of the stock is effectively reduced, a user can more reasonably carry out the investment behaviors of stock selection and time selection admission on the basis of the predict prediction result, and the investment risk of the user iseffectively lowered.

Description

technical field [0001] The invention belongs to the field of computer technology, and in particular relates to a machine learning-based timing investment method and terminal equipment. Background technique [0002] Stock prices fluctuate in real time. In the process of stock trading, stock selection and purchase behaviors are often based on people's subjective decisions or when stock prices fall. Such stock selection behaviors are not based on subsequent stock prices. It is made by forecasting the trend, so there may be greater investment risks. In order to construct and adopt an appropriate investment portfolio strategy to achieve a relatively stable and rational investment method, the application of machine learning technology in the field of securities investment, especially in the selection of investment portfolio and the determination of the timing of entering the market, has been received. The widespread attention of researchers, which is based on the prediction of st...

AI Technical Summary

Problems solved by technology

[0004] In view of this, the embodiment of the present invention provides a machine learning-based time selection method and terminal equipment to solve the problem that the calculation process of the existing machine learning-based forecasting model does not fully consider the behavioral characteristics of the financial market, resulting in stock selection and There is a large deviation between the forecast results of stock selection at the right time and the subsequent actual price trend of the stock

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