Abstract
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.
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