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A Singular Spectrum Analysis based Trend-Following Trading System

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Author(s):
Leles, Michel C. R. ; Cardoso, Adriano S. V. ; Moreira, Mariana G. ; Sbruzzi, Elton F. ; Nascimento, Cairo L., Jr. ; Guimaraesf, Homero N. ; IEEE
Total Authors: 7
Document type: Journal article
Source: 12TH ANNUAL IEEE INTERNATIONAL SYSTEMS CONFERENCE (SYSCON2018); v. N/A, p. 5-pg., 2018-01-01.
Abstract

A comparison between Moving Averages (MA) and two versions of Singular Spectrum Analysis (SSA) methodology - the Caterpillar and the Toeplitz - is presented. Caterpillar had already been studied in this manner but the same is not true for the Toeplitz SSA. Toeplitz SSA assumes the stationarity of the time-series, which means that the process needs to be mean-reverting. However, such assumption is not a necessary condition for the Caterpillar SSA. In this paper both approaches are applied to a trend estimation problem in order to be used as an indicator in trend-following technical rules design. Similarities and differences between these techniques are addressed. The obtained results suggest that, although SSA approaches provides more flexibility to achieve a desired trend resolution compared to the traditional MA, the Toeplitz SSA exhibit some issues that might put it off its use in this particular application. (AU)

FAPESP's process: 17/20248-8 - Employing computational intelligence techniques and Big Data analytics in a multi-agent system experiment of finance
Grantee:Michel Carlo Rodrigues Leles
Support Opportunities: Scholarships in Brazil - Post-Doctoral
FAPESP's process: 16/04992-6 - Employing computational intelligence techniques and Big Data analytics in a multi-agent system experiment of finance
Grantee:Cairo Lúcio Nascimento Júnior
Support Opportunities: Research Grants - eScience and Data Science Program - Regular Program Grants