Stock price trend prediction method
A forecasting method and price forecasting technology, applied in instrumentation, finance, data processing applications, etc., can solve problems such as errors
Pending Publication Date: 2019-05-14
CHONGQING UNIVERSITY OF SCIENCE AND TECHNOLOGY
View PDF0 Cites 0 Cited by
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Especially the recurrent neural network, because of its memory function in time, has been widely used in stock price prediction in recent years, but there are still shortcomings in the application. The fluctuation of stock price is affected by many factors, and each factor The degree of influence on the stock market is different, so there will be large errors in the stock price prediction based only on the cyclic neural network
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 moreImage
Smart Image Click on the blue labels to locate them in the text.
Smart ImageViewing Examples
Examples
Experimental program
Comparison scheme
Effect test
Embodiment Construction
[0051] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the following will be described in detail in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, and are not intended to limit the invention.
[0052] This embodiment provides a stock price trend prediction method, please refer to figure 1 shown, including the following steps:
[0053] S11: Obtain multiple sets of real stock characteristic data of the target stock for multiple trading days from a certain moment before the current moment to the current moment.
[0054] In this embodiment, each set of stock characteristic data includes characteristic values corresponding to various stock characteristics. In this embodiment, stock characteristics include the opening price op, closing price cls, highest price hig, lowe...
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
Login to View More Abstract
The invention discloses a stock price trend prediction method. The method comprises: firstly, a stock price prediction model is constructed based on an LSTM recurrent neural network model to predict astock price; introducing a fuzzy comprehensive evaluation algorithm; the prediction result of the stock price is evaluated; prediction results of important attributes in the main stock prices are highlighted; Enabling models more reliable, the final prediction result is more accurate; According to the method disclosed by the invention, the memory function of the recurrent neural network is utilized; According to the method, the influence of the current influence factor on the stock price change at the next moment or after longer time is captured, then the stock price predicted by the recurrent neural network is comprehensively evaluated through the fuzzy comprehensive evaluation algorithm, the importance of main factors is highlighted, and the finally predicted stock price trend has higher precision.
Description
technical field [0001] The invention relates to the technical field of stock price forecasting, and more specifically, relates to a stock price trend forecasting method. Background technique [0002] Today's stock market is not only faced with the problem of large and complex market data, but also the challenge of low prediction accuracy. In this environment, if you can predict stock prices more accurately than your competitors, it will mean that you may create millions of RMB or even more transactions per second. Therefore, how to improve the accuracy of stock price prediction has become a technical problem that people need to solve urgently. [0003] At present, the methods of analyzing the trend of stock price changes are mainly divided into two categories: fundamental analysis and technical analysis. Fundamental analysis is a qualitative analysis method. By analyzing factors such as the operating status of the macro economy, major national policies, and the company's f...
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
Login to View More IPC IPC(8): G06Q40/04
Inventor 李作进何昌隆陈刘奎周伟邹开其
Owner CHONGQING UNIVERSITY OF SCIENCE AND TECHNOLOGY