A New Trend-Following Indicator: Using SSA to Design Trading Rules

被引：16

作者：

Rodrigues Leles, Michel Carlo ^{[1
,2
]}

Mozelli, Leonardo Amaral ^{[1
]}

Guimaraes, Homero Nogueira ^{[3
]}

机构：

[1] Univ Fed Sao Joao del Rei, CELTA Ctr Studies Elect Engn & Automat, Campus Alto Paraopeba,Rod MG 443 Km 7, BR-36420000 Ouro Branco, MG, Brazil

[2] Univ Fed Minas Gerais, Grad Program Elect Engn, Av Antonio Carlos 6627, BR-31270901 Belo Horizonte, MG, Brazil

[3] Univ Fed Minas Gerais, Dept Elect Engn, Av Antonio Carlos 6627, BR-31270901 Belo Horizonte, MG, Brazil

来源：

FLUCTUATION AND NOISE LETTERS | 2017年 / 16卷 / 02期

关键词：

Singular Spectrum Analysis; Technical Analysis; trend-following trading rules; SINGULAR SPECTRUM ANALYSIS; TECHNICAL ANALYSIS; PROFITABILITY; MARKETS;

D O I：

10.1142/S021947751750016X

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

Singular Spectrum Analysis (SSA) is a non-parametric approach that can be used to decompose a time-series as trends, oscillations and noise. Trend-following strategies rely on the principle that financial markets move in trends for an extended period of time. Moving Averages (MAs) are the standard indicator to design such strategies. In this study, SSA is used as an alternative method to enhance trend resolution in comparison with the traditional MA. New trading rules using SSA as indicator are proposed. This paper shows that for the Down Jones Industrial Average (DJIA) and Shangai Securities Composite Index (SSCI) time-series the SSA trading rules provided, in general, better results in comparison to MA trading rules.

引用

页数：16

共 17 条

[1]

Alexandrov T, 2009, REVSTAT-STAT J, V7, P1

[2] SIMPLE TECHNICAL TRADING RULES AND THE STOCHASTIC PROPERTIES OF STOCK RETURNS [J].