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http://itmozg.ru/resume/show/?id=572d5c129f5255221bb43c3f
Using the original SSA codes from the ALGLIB site, I programmed the indicator program with a forecast and an expert for MQL5. AlglibSSA.dll is connected to them, so the programs are not on the market. Who is interested - contact please.
Studies related to search for the fractal behavior of financial data suggest that behind the seemingly chaotic behavior of economic time series there are hidden stable mechanisms of participants' collective behavior. These mechanisms can lead to the emergence of price dynamics on the exchange, which can define and describe specific properties of price series. When applied to trading, one could benefit from the indicators which can efficiently and reliably estimate the fractal parameters in the scale and time frame, which are relevant in practice.
After the upgrade of the MATLAB package in 2015, it is necessary to consider a modern way of creating DLL libraries. The article uses a sample predictive indicator to illustrate the peculiarities of linking MetaTrader 5 and MATLAB using modern 64-bit versions of the platforms, which are utilized nowadays. With the entire sequence of connecting MATLAB considered, MQL5 developers will be able to create applications with advanced computational capabilities much faster, avoiding «pitfalls».
The article considers the ideology and methodology of building a recommendatory system for time-efficient trading by combining the capabilities of forecasting with the singular spectrum analysis (SSA) and important machine learning method on the basis of Bayes' Theorem.
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
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 make
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
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