A Stock Price Trend Prediction Method Based on Quantum Mechanics and Social Networks

A price trend forecasting, social networking technology, applied in forecasting, instrumentation, finance, etc., can solve the problem that position and momentum cannot be determined at the same time

Active Publication Date: 2016-08-24
XI AN JIAOTONG UNIV
View PDF2 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, according to the Heisenberg uncertainty principle, microscopic particles have uncertainty, and its position and momentum cannot be determined at the same time, so it can only be described in a probabilistic way

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
  • A Stock Price Trend Prediction Method Based on Quantum Mechanics and Social Networks
  • A Stock Price Trend Prediction Method Based on Quantum Mechanics and Social Networks
  • A Stock Price Trend Prediction Method Based on Quantum Mechanics and Social Networks

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0130] The invention is used to predict the stock price of Apple (AAPL), a listed company in the United States. The microblog data comes from the Twitter website. Twitter users are also investors and close followers of AAPL stocks, and they have mutual concern (follow) relationship with attention. In the present invention, the data from December 2009 to November 2011 are used, and some sampling points are predicted on a daily basis in combination with historical information.

[0131] Utilize the present invention to complete the implementation steps of AAPL stock stock price prediction as follows (work flow sees figure 2 ):

[0132] The first step is to search for relevant Weibo and investor information according to the keyword "$AAPL" through the API provided by Twitter. For example, through keyword search, the investor with the id 29242868 posted on Weibo at 2011-08-09 18:32:36 "$aapl get in now good news 3rd qtr great and 4 qtr even better, 300%increasein rev in last 90...

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 trend prediction method based on the quantum mechanics and the social network. The micro particle characteristics of an individual investor affective decision in the social network are fully considered, the wave function and the operator of the individual decision in the network are defined, the influence relation between individuals in the social network is simulated by a segmented infinite potential well, the emotion of a single investor is predicted by a schrodinger equation and is overlaid by the emotion in the social network, the stock price variation trend is described, and the quantum mechanics model of the social network can be used for effectively improving the stock price trend prediction accuracy. The stock price trend prediction method based on the quantum mechanics and the social network has an important theoretical significance and economic value.

Description

technical field [0001] The invention relates to the fields of quantum mechanics, social network analysis and stock price trend prediction, and specifically relates to predicting stock price trends by using quantum mechanics models by collecting and analyzing massive stock-related information in social networks. Background technique [0002] The analysis and forecasting of stock price trends has a long history. Fundamental analysis, technical analysis, etc. are all classic analysis methods, including CAPM, APT model, average line theory, K-line diagram analysis method, etc. On the basis of stock analysis results, researchers mainly use statistical methods such as regression analysis to establish mathematical models to predict stock price trends. [0003] It is a new research direction since 2000 to analyze the relationship between relevant news in news media (such as financial articles, financial magazines, local newspapers, etc.) and stock price trends. One of the more fam...

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 Patents(China)
IPC IPC(8): G06Q10/04G06Q40/06
Inventor 李倩
Owner XI AN JIAOTONG 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