Generalized stock price prediction method based on multitask asymmetric proximity support vector machine

A support vector machine and price forecasting technology, applied in forecasting, instrumentation, finance, etc., can solve the problems of ignoring cross-correlation information and data set distribution characteristics, poor forecasting accuracy and robustness, etc., to improve flexibility, improve The effect of generalizing performance and improving prediction accuracy

Inactive Publication Date: 2021-03-26
XIAN UNIV OF POSTS & TELECOMM
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The purpose of this application is to solve the problem of poor prediction accuracy and robustness due to the large limitations of existing stock market forecasting methods due to the neglect of cross-correlation information between stock indexes and the distribution characteristics of data sets

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
  • Generalized stock price prediction method based on multitask asymmetric proximity support vector machine
  • Generalized stock price prediction method based on multitask asymmetric proximity support vector machine
  • Generalized stock price prediction method based on multitask asymmetric proximity support vector machine

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0037] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.

[0038] Such as figure 1 As shown, the generalized stock price prediction method based on multi-task asymmetric proximity support vector machine proposed by this application, the basic implementation steps are as follows:

[0039] Step 1: Download and preprocess the market data of several stock indexes on the trading day before the forecast date to obtain a data set; each stock index is a separate learning task;

[0040] Step 2: Construct an asymmetric square ε insensitive loss function, and adjust the parameters appropriately so that the loss function can better adapt to ...

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 provides a generalized stock price prediction method based on a multitask asymmetric proximity support vector machine, and solves the problems of poor prediction precision and robustnesscaused by relatively high limitation due to neglect of cross-correlation information among stock indexes and distribution characteristics of a data set in an existing stock market prediction method.The prediction method mainly comprises the following steps: obtaining and preprocessing a plurality of stock trading day quotation data to obtain a data set; constructing an asymmetric square epsiloninsensitive loss function, and adjusting hyper-parameters to enable the hyper-parameters to better adapt to the distribution characteristics of the data set; establishing a generalized mathematical optimization model for stock price prediction based on the multitask learning asymmetric proximity support vector machine according to the multitask learning hypothesis; converting an original planningproblem of a generalized stock price prediction model based on the multitask learning asymmetric proximity support vector machine into a dual planning problem according to a KKT condition; and solvingthe dual planning to obtain a decision function of the stock price prediction model.

Description

technical field [0001] The application relates to a data processing method suitable for forecasting commercial and financial trend information, and specifically relates to a stock price forecasting method. Background technique [0002] The stable development of the stock market is the focus of attention of the national government and investors, and the analysis of the running trend of the stock market index and the fluctuation of stock prices has become a widely discussed topic in the academic and financial circles. So far, scholars at home and abroad have done a lot of research on stock market forecasting. However, due to the characteristics of the stock market itself, such as complex nonlinearity, high dimensionality, noise sensitivity, and instability, it is particularly important to conduct reasonable and accurate volatility prediction analysis. difficulty. [0003] The existing stock market prediction methods are mainly divided into three categories: market technical a...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06Q40/04G06Q10/04G06Q10/06
CPCG06Q10/04G06Q10/067G06Q40/04
Inventor 吴青张恒昌高小凤王凡
Owner XIAN UNIV OF POSTS & TELECOMM
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products