Application of the Surface Division Method to Segregate Investments in Capital Markets for Shares‘ Portfolio
Grzegorz Przekota
European Research Studies Journal, 2020, vol. XXIII, issue Special 1, 883-896
Abstract:
Purpose: One of the fundamental issues in capital markets is the sustainability of the price trend. There are many methods of identifying a trend. The article will test a characteristic based on The Surface Division Method. Design/Methodology/Approach: The Surface Division Method is a method that allows for the division of time series into categories due to the reinforcement of the trend, random walk or return to the mean. This fact can be used to segregate investments and choose the right strategy. Findings: The Surface Division Method is a promising method of segregating investments. It is easy to interpret and allows to better describe the shaping of time series values. Practical Implications: The presented investment strategy gave significantly better results than the passive strategy. Originality/value: The Surface Division Method is a new method of data analysis. The application for segregation of investments was made here for the first time. The method is worth developing as it presents a different view than the classical methods based on variance.
Keywords: SDM method; portfolio; capital market; time series; trend. (search for similar items in EconPapers)
JEL-codes: C15 C22 G11 G17 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://www.ersj.eu/journal/1799/download (application/pdf)
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:ers:journl:v:xxiii:y:2020:i:special1:p:883-896
Access Statistics for this article
More articles in European Research Studies Journal from European Research Studies Journal
Bibliographic data for series maintained by Marios Agiomavritis ().