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Automatic stock selection method based on big data of news

A big data and news technology, applied in the field of information retrieval, can solve problems such as automatic stock selection without industry attention

Inactive Publication Date: 2017-08-08
MINNAN NORMAL UNIV
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Problems solved by technology

The existing scheme focuses on the analysis of the characteristics of individual stocks, and does not automatically select stocks from the perspective of industry attention

Method used

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  • Automatic stock selection method based on big data of news
  • Automatic stock selection method based on big data of news

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Embodiment Construction

[0013] Below, the present invention will be further described in detail in combination with the main process of the present invention and the flow chart of the execution algorithm.

[0014] Keywords: emotional glossary, industry glossary. Emotional vocabulary refers to the vocabulary in the emotional vocabulary list, including positive vocabulary and negative vocabulary. Industry Glossary A glossary compiled from common keywords in each industry. The above emotional glossary and industry glossary come from the "Professional Chinese Financial Dictionary", which the applicant has compiled into a volume.

[0015] For example, positive words include: success, excellence, uniqueness, leadership, progress, innovation, etc. Negative words include failure, loss, inadequacy, bad review, recall, downturn, etc.

[0016] Industry vocabulary, for example, in the banking industry, common keywords are interest, loan, China Banking Regulatory Commission, central bank, interest rate, credit...

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Abstract

The invention relates to an automatic stock selection method based on big data of news. According to the technical scheme, firstly, emotional vocabularies and industry vocabularies which come from a professional Chinese Financial Dictionary are stored in a storage; internet financial news are acquired in real time through RSS and updated every half hour; news text content of the day is analyzed through a server, text analysis of the news content comprises two sub-sections: 1) emotional dimension analysis of the news content: emotional tendency of the news content is obtained through calculation; 2) industry dimension analysis of the news content: industry attention embodied by the news content is obtained through calculation. The stock ranking is calculated by use of the emotional tendency and the industry attention, and a plurality of stocks ranking in the top are selected as investment objects. Vocabularies with emotional dimension indexes and industry attention indexes in the news are filtered and counted, and more information having influence on stock prices is mined at multiple angles.

Description

technical field [0001] The invention relates to the field of information retrieval, specifically an automatic stock selection method based on news big data. Background technique [0002] Now, quantitative investment is playing an increasingly important role in asset management. Everyone has begun to use computer equipment to use historical stock volume and price data as a data resource, and verify it through mathematical models for quantitative investment in stocks. The existing scheme focuses on the analysis of the characteristics of individual stocks, and does not automatically select stocks from the perspective of industry attention. Because the news orientation will also have a certain early warning effect on the trend of stock data ("this invention adopts lexical statistical analysis method to mine the emotional tendency of news and complete automatic stock selection"). Simply put, the emotional orientation of news content can be divided into two situations: positive e...

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Application Information

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IPC IPC(8): G06F17/30G06F17/27G06Q40/04
CPCG06F16/951G06F40/205G06Q40/04
Inventor 张铁军
Owner MINNAN NORMAL UNIV
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