Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Financial time series prediction method, server and device

A technology for financial time series and forecasting methods, applied in the field of financial time series forecasting methods, servers and devices, can solve problems affecting the accuracy of financial time series forecasting, selection of financial derivatives market features, high data noise, etc., and achieve accurate model accuracy. The effect of improving the degree of accuracy, improving the accuracy, reducing the noise and redundancy

Inactive Publication Date: 2018-11-23
SHANDONG NORMAL UNIV
View PDF0 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Due to the high noise and high redundancy of financial derivatives market data, these search strategies cannot effectively select the features of the financial derivatives market, which in turn affects the accuracy of financial time series forecasting

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 more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Financial time series prediction method, server and device
  • Financial time series prediction method, server and device
  • Financial time series prediction method, server and device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0064] It should be pointed out that the following detailed description is exemplary and intended to provide further explanation to the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0065] It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combinations thereof.

[0066] figure 1 It is a flow chart of a financial time series forecasting method of the present invention.

[...

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

No PUM Login to View More

Abstract

The invention discloses a financial time series prediction method, a server and a device. The financial time series prediction method comprises the following steps: establishing a financial time series prediction model by using a feature subset of the financial time series, a time window of the financial time series, and a financial time series classifier as three populations of a roulette cooperative co-evolutionary algorithm and finding the optimal value of the three populations; inputting the financial time series into the financial time series prediction model and outputting a prediction result. The financial time series prediction method improves the accuracy of financial time series predictions.

Description

technical field [0001] The invention belongs to the field of financial time series data processing, and in particular relates to a financial time series prediction method, server and device. Background technique [0002] Financial time series is a kind of time series data, which has strong timeliness. The data has strong dependence before and after, and the order cannot be adjusted. It is generally two-dimensional data. With the development of computer science and technology, some methods based on data mining and machine learning, such as neural networks and support vector machines, have also been widely used in the financial derivatives market. Compared with traditional technical analysis methods, machine learning algorithms The big data processing capability can give full play to the advantages of technical analysis, make a variety of technical indicators as features, and use machine learning algorithms to filter features and predict the market price trend of financial der...

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
no application Login to View More
IPC IPC(8): G06K9/62G06Q40/04
CPCG06Q40/04G06F18/2411G06F18/214
Inventor 骆超姜志朋
Owner SHANDONG NORMAL UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com