Roman Korotchenko / Seller

An analogue of the Stochastic oscillator based on algorithms of singular spectrum analysis (SSA) SSA is an effective method to handle non-stationary time series with unknown internal structure. It is used for determining the main components (trend, seasonal and wave fluctuations), smoothing and noise reduction. The method allows finding previously unknown series periods and make forecasts on the basis of the detected periodic patterns. Indicator signals are identical to signals of the original i

SSACD - Singular Spectrum Average Convergence/Divergence This is an analogue of the MACD indicator based on the Caterpillar-SSA ( Singular Spectrum Analysis ) method. Limited version of the SSACD Forecast indicator. Limitations include the set of parameters and their range. Specificity of the method The Caterpillar-SSA is an effective method to handle non-stationary time series with unknown internal structure. The method allows to find the previously unknown periodicities of the series and mak

This indicator extracts a trend from a price series and forecasts its further development. Algorithm is based on modern technique of Singular Spectral Analysis ( SSA ). SSA is used for extracting the main components (trend, seasonal and wave fluctuations), smoothing and eliminating noise. It does not require the series to be stationary, as well as the information on presence of periodic components and their periods. It can be applied both for trend and for another indicators. Features of the m