Media information tensor supervised learning-based stock price fluctuation prediction system and method

A technology of media information and supervised learning, applied in instrumentation, product evaluation, finance, etc., can solve problems such as low accuracy of stock price fluctuation prediction

Inactive Publication Date: 2017-11-24
SOUTHWESTERN UNIV OF FINANCE & ECONOMICS
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Problems solved by technology

[0005] The purpose of the present invention is to overcome the deficiencies of the prior art, to provide a stock price fluctuation prediction system and method based on media information tensor supervised learning, to solve the problem of low accuracy in the existing stock price fluctuation prediction

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  • Media information tensor supervised learning-based stock price fluctuation prediction system and method
  • Media information tensor supervised learning-based stock price fluctuation prediction system and method

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[0047] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0048] The invention predicts the stock price fluctuation based on the media information, especially based on the media information tensor supervised learning algorithm, and provides decision-making for the financial market.

[0049] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The following examples are used to illustrate the present invention, ...

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Abstract

The invention discloses a stock price fluctuation prediction system and method based on media information tensor supervised learning. According to the media information, a tensor is constructed, and a supervised learning algorithm is used to predict stock price fluctuations. The present invention has the following advantages: (1) Starting from the three-dimensional attribute information of market transaction information, investor emotional information, and media news information, it includes both quantitative and qualitative sources of information, including official news information and social media information, thus making it more comprehensive analyze the relationship between Internet media and the stock market; (2) use tensor to represent the media information space, so as to record the relationship between different dimensions of information; (3) the tensor supervised learning algorithm realizes the computer learning algorithm from the vector An extension to tensors.

Description

technical field [0001] The invention relates to a stock price fluctuation prediction system and method, in particular to a stock price fluctuation prediction system and method based on media information tensor supervised learning. Background technique [0002] With the development of information technology, Internet media has gradually become the mainstream media form. Especially with the rise of social media such as blogs, Weibo, social news, Wikipedia and online forums, their media influence is increasing day by day. Massive information and fissile communication make Internet media have a decisive impact on the stock market. [0003] In the prior art, when predicting stock price fluctuations, most of the quantitative information in Internet media, such as stock trading prices, is considered, while qualitative information, such as company news, is ignored, resulting in inaccurate stock price fluctuation predictions. [0004] When combining different latitude information t...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/02G06Q40/04
CPCG06Q30/0278G06Q40/04
Inventor 李庆蒋李灵
Owner SOUTHWESTERN UNIV OF FINANCE & ECONOMICS
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