Stock prediction method which combines news corpus and stock market transaction data

A technology for transaction data and forecasting methods, applied in natural language data processing, forecasting, data processing applications, etc., can solve problems affecting investors' professional judgment, information redundancy, etc., and achieve automation and precision, and improve accuracy. Effect

Inactive Publication Date: 2018-10-12
SUN YAT SEN UNIV +1
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  • Description
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AI Technical Summary

Problems solved by technology

This will cause excessive redundancy of information and affect the professional judgment of investors

Method used

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  • Stock prediction method which combines news corpus and stock market transaction data
  • Stock prediction method which combines news corpus and stock market transaction data
  • Stock prediction method which combines news corpus and stock market transaction data

Examples

Experimental program
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Embodiment 1

[0038] like Figure 1-4 As shown, a stock prediction method combining news corpus and stock market transaction data includes the following steps:

[0039] S1: Obtain and preprocess the stock news document collection to obtain the word vector of the document collection;

[0040] S2: Obtain stock transaction data for preprocessing, obtain normalized transaction data and daily classification labels;

[0041] S3: Use the GRU neural network and the attention mechanism to encode the document to obtain the document set vector;

[0042] S4: The document vector and transaction data are spliced, and then input into the GRU neural network in chronological order for prediction, and the trend prediction result of the stock for the next day is obtained.

[0043] In this embodiment, the stock transaction data collected from Yahoo Finance webpage from January 1, 2008 to November 30, 2017 and the stock news data collected from Reddit WorldNews Channel are used.

[0044] The specific process...

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PUM

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Abstract

The invention provides a stock prediction method which combines news corpus and stock market transaction data. The method makes full use of a large amount of corpus information of a network and breaksthe traditional boundary of a single analysis data source. Through a deep learning model, the stock market news corpus can be analyzed in batches, and the importance of corpus for prediction can be judged automatically, thus the automation and precision of network information analysis are realized. Modeling is performed on news corpus and transaction data through deep learning, and the relationship between different data is comprehensively analyzed according to different information from many aspects. The influence of stock market information on the stock price, the persistence of the stock market information and the investor's psychological factor are grasped, so that the stock market forecast accuracy is further improved; and the word vector, a GRU neural network, an attention mechanismand other in-depth learning cutting-edge technology are used, so that the implementation of science into the industry is realized, and scientific and technological innovation is achieved.

Description

technical field [0001] The invention relates to the field of stock market forecasting, and more specifically, relates to a stock forecasting method combining news corpus and stock market transaction data. Background technique [0002] In today's era of stock speculation by all people, the vast majority of people will have been exposed to stock market investment. The rise of capital has driven the stock market again and again. In order to maximize their profits, stock market investors will try to predict the trend of the stock market. However, due to the instability and variability of the stock market, this task has become impossible for ordinary investors. Traditional stock market forecasting methods are based on comprehensive analysis of market, policy and investor psychology by professional analysts. This traditional predictive analysis relies too much on the subjective judgment of analysts, and requires analysts to have rich practical experience and industry accumulati...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q40/04G06F17/30G06F17/27G06K9/62
CPCG06Q10/04G06Q40/04G06F40/289G06F18/24147
Inventor 朱俊祺印鉴高静
Owner SUN YAT SEN UNIV
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