EconPapers    
Economics at your fingertips  
 

Index Frequency-Based Contour Selection of Gray Wave Forecasting Model and Its Application in Shanghai Stock Market

Xingyuan Li (), Qifeng Tang and Shaojun Ning
Additional contact information
Xingyuan Li: East China University of Science and Technology
Qifeng Tang: Shanghai Zamplus Technology Co., Ltd
Shaojun Ning: Shanghai Zamplus Technology Co., Ltd

A chapter in Smart Service Systems, Operations Management, and Analytics, 2020, pp 283-291 from Springer

Abstract: Abstract Indexes reflect the mechanism of the stock market and the Gray Wave Forecasting Model (GWFM) which has been confirmed to be one of the most effective methods for forecasting. However, the previous method did not take into account the fact that the larger the index frequency is, the more likely this index is to appear in the future. According to the changing law of indexes, an index frequency-based contour selection of GWFM is put forward in this study where the classical uniformly spaced contour line is used twice to select the contour lines. Using this model, the fluctuation trend of Shanghai stock indexesShanghai stock market indexes is well predicted which demonstrated that this model has certain advantage over the original GWFM at forecasting stock indexes.

Keywords: Gray wave predicting; Index frequency-based contours; Shanghai stock market indexes (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-030-30967-1_26

Ordering information: This item can be ordered from
http://www.springer.com/9783030309671

DOI: 10.1007/978-3-030-30967-1_26

Access Statistics for this chapter

More chapters in Springer Proceedings in Business and Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-04-13
Handle: RePEc:spr:prbchp:978-3-030-30967-1_26