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Prediction method based on high-dimensional data structure relations

A prediction method and high-dimensional data technology, applied in network data retrieval, data processing applications, network data indexing, etc., can solve problems such as lack of effective prediction models for complex data structures

Inactive Publication Date: 2018-03-27
TIANJIN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Lack of effective predictive models for complex data structures such as tensors

Method used

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  • Prediction method based on high-dimensional data structure relations
  • Prediction method based on high-dimensional data structure relations
  • Prediction method based on high-dimensional data structure relations

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Embodiment Construction

[0018] In order to make the purpose, technical solution and advantages of the present invention clearer, the implementation manners of the present invention will be further described in detail below.

[0019] Embodiments of the present invention collect different information sources and explore their interaction effects to predict stock prices, such as news expression and author sentiment news, investor sentiment and characteristics. Embodiments of the present invention use Natural Language Process (NLP) to teach a computer how to read and understand the information and sentiment of an article. The working nature of embodiments of the present invention is a combination of machine learning (ML) and financial applications. In fact, machine learning does not provide a simple path to feasibility or improved execution, it is not a magic black box, but provides a powerful and principled framework for trading optimization through data. What the embodiments of the present invention t...

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Abstract

The invention discloses a prediction method based on high-dimensional data structure relations. The prediction method comprises the following steps of obtaining posts and replies of a Sina share postbar and an Eastern Fortune share post bar through a crawler technology and obtaining specific news of Baidu's advanced search; conducting natural semantic processing on the posts and news to obtain features and combining with formula calculations to obtain technical indicator features; constructing a tensor of the three features, and reconstructing the tensor by high-order singular value decomposition to achieve the purpose of denoising and strengthening the relationship between various factors; obtaining tensor information bodies of the above steps every day, and reconstructing data by a reconstruction algorithm proposed by us by using the correspondence relationship with lifting price information to obtain a new tensor sequence, wherein the information bodies that have the similar levelof lifting or the same direction of lifting are similar through reconstruction restrictions; conducting optimized tensor ridge regression for the new tensor sequence; using a regression prediction asa secondary trading system.

Description

technical field [0001] The invention relates to the field of high-dimensional data structures, in particular to a prediction method based on high-dimensional data structure relationships. Background technique [0002] Stock market forecasting has long been a particularly active area of ​​research. The efficient market hypothesis (EMH) shows that stock market prices are mainly affected by factors such as news, stock market sentiment, company performance (such as return on assets, leverage ratio), etc., because stock market efficiency causes existing stock prices to always incorporate and reflect all relevant information. Two interesting examples are United Airlines which recently lost $300 million in market value due to the “relocation” incident, and Huishan Dairy which lost 90% of its market value due to a bearish report from Muddy Waters. In both cases, the power of the event itself and the power of the online discussion to drive the final outcome speaks to the market valu...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06K9/62G06Q40/04
CPCG06F16/951G06Q40/04G06F18/2136G06F18/22
Inventor 李岳楠张桐喆苏育挺井佩光
Owner TIANJIN UNIV
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