Abstract
Singular Spectrum Analysis (SSA) is a nonparametric approach that can be used to decompose a time series as trends, oscillations and noise. In online applications, the SSA algorithm must be recalculated for each new sample available. The so called Causal SSA have been used in this context. In this manuscript, an alternative version of online SSA, the Recursive SSA, is proposed as a technical indicator. Based on a “forgetting factor” parameter, it is possible to control the amount of previous samples that are used in the SSA algorithm. This functionality may confer adaptive and hybrid features, thereby providing a crucial characteristic to technical indicators. The Recursive SSA technical trading rules (SSA-TTR) are applied to the DJIA time-series and compared against popular technical indicators. The results show the advantages of SSA-TTR over the popular ones.
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