Stock price prediction method, server, and storage medium

A forecasting method and price forecasting technology, which is applied in the field of artificial intelligence, can solve the problems of low stock price accuracy and does not consider the time distance of historical stock data, so as to achieve the effect of improving the accuracy rate

Inactive Publication Date: 2019-03-15
SUN YAT SEN UNIV
View PDF0 Cites 19 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] At present, in the forecasting of stock prices, only the K-line chart model is often used to predict the stock price, or the intraday trend of the stock price is only quantified based on the intraday transaction data of the stock, without considering the time distance of the historical stock data , the impact on the stock price prediction results, which lead to the low accuracy of the predicted stock price

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Stock price prediction method, server, and storage medium
  • Stock price prediction method, server, and storage medium
  • Stock price prediction method, server, and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0037] It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0038] The present invention provides a stock price prediction method, by assigning greater weight to the historical stock data that is closer to the time point of the price prediction result, and generating the price prediction result based on the deep neural network model according to the historical stock data, the prediction is improved. Accuracy of the obtained stock price.

[0039] Such as figure 1 as shown, figure 1 It is a schematic diagram of the hardware operating environment of the embodiment terminal involved in the embodiment solution of the present invention;

[0040] The terminal in this embodiment of the present invention may be a server, or a stock price forecasting device.

[0041] Such as figure 1 As shown, the terminal may include: a processor 1001 , such as a CPU, a memory 1002 , and a communic...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a stock price prediction method, comprising the following steps: acquiring historical stock data of a target stock and preprocessing the historical stock data; Assigning time weights to the pre-processed historical stock data according to the time order of the historical stock data, the time weights being positively correlated with the time order; Based on a pre-constructeddepth neural network model, a price prediction result of the target stock is obtained according to the historical stock data given a time weight. The invention also discloses a server and a computer-readable storage medium. The present invention improves the accuracy of the predicted stock price by giving greater weight to the historical stock data which is closer to the time point of the price predicting result and generating the price predicting result based on the depth neural network model according to the historical stock data.

Description

technical field [0001] The invention relates to the field of artificial intelligence, in particular to a method for predicting stock prices, a server and a computer-readable storage medium. Background technique [0002] At present, in the forecasting of stock prices, only the K-line chart model is often used to predict the stock price, or the intraday trend of the stock price is only quantified based on the intraday transaction data of the stock, without considering the time distance of the historical stock data , the impact on the stock price prediction results, all of which lead to the low accuracy of the stock price forecast. Contents of the invention [0003] The main purpose of the present invention is to provide a stock price prediction method, server and computer-readable storage medium, which improves the accuracy of stock price prediction. [0004] To achieve the above object, the present invention provides a method for predicting stock prices, the method for pre...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06Q40/04G06N3/08G06N3/04
CPCG06N3/08G06Q40/04G06N3/045
Inventor 任江涛何佳俊
Owner SUN YAT SEN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap