Published products
The indicator detects the beginning of a new trend not directly, but by comparing two forecast values based on the available history. Its action is based on the assumption that the predicted (historically normal) price and the real price differ due to the appearance of "new" force (unbalanced impact on the market), which usually leads to a significant market correction in an unstable market. The indicator does not track market stability, so it is recommended to use other methods to control vol
The indicator is built on a principle similar to neural networks, and it calculates a multidimensional polynomial. When you install it on a chart or make changes to the indicator's parameters, or when you switch the chart period, the indicator is initially initialized. During initialization, not only the entire period of the chart is recalculated, but also the indicator is self-trained. The indicator's parameters include Sensitivity, Forecast, and degree of harmonization. The indicator theoretic
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Advanced harmonic filter is a reliable and smart utility that uses an author's algorithm to process continuous data and present them in the form of harmonic oscillations. The utility can identify regularities and patterns in the input data, which are then used to generate output data that is most similar to the input data. This makes it a powerful tool to use with other indicators to predict future trends and identify Elliott waves on selected intervals. The utility is most effective when us
Advanced harmonic filter is a reliable and smart utility that uses an author's algorithm to process continuous data and present them in the form of harmonic oscillations. The utility can identify regularities and patterns in the input data, which are then used to generate output data that is most similar to the input data. This makes it a powerful tool to use with other indicators to predict future trends and identify Elliott waves on selected intervals. The utility is most effective when us
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Thread indicator is calculating possible values for the upcoming periods. It is built by author’s system, with ability to learn. Input data ( recommended interval ): Sensitivity to oscillatory motion (integer value, 0 - 8) increase of value shifts priority of calculation towards high-frequency vibrations (increase loads the system) Shift of diagram (integer value, 0 - 8) shifts output of indicator to the right Diagram forecast (integer value, maximum 10) defies the number of periods calculated
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