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Discrete wavelet transform

The Discrete wavelet transform indicator is an enhanced implementation of the numerical and functional analysis for MetaTrader 4, the discrete wavelet transform method (DWT). The specific feature of DWT is the way the wavelet is represented in the form of a discrete signal (sample). DWT is widely used for filtering and preliminary processing of data, for analyzing the state and making forecasts for the stock and currency markets, for recognizing patterns, processing and synthesizing various signals, for example, speech and medical signals, for solving the problems of image compression and processing, in learning neural networks and in many other cases.

The Discrete wavelet transform indicator is a filter, which is used for finding optimal market entry and exit points in trending conditions. It allows for more accurate forecasting and analysis of the current and emerging trend.

Discrete wavelet transform includes several methods for filtering the analyzed signal.
  • 1. Haar (haar)
  • 2. Daubechies (db1, db2, db3, db4, db5, db6, db7, db8, db9, db10)
  • 3. Coiflet (coif1, coif2, coif3, coif4, coif5)
  • 4. Biorthogonal (bior11, bior13, bior15, bior22, bior24 и др)
  • 5. Reverse Biorthogonal (rbior11, rbior13, rbior15, rbior22, bior24 и др)

as well as the calculation options and final filter presentation variants

  • 1. DWT is discrete wavelet transform
  • 2. MODWT is discrete wavelet transform with overlap
  • 3. SWT is stationary wavelet transform

Filters differ in basic functions, wavelet transform coefficients, as well as calculation methods (mainly iterative). Each filter has its own characteristics in the time and frequency space. The use of different filters allows identifying certain properties of the analyzed signal.

The number of wavelets used in signal analysis determines the level of decomposition. The accuracy of the signal presentation decreases on higher levels of decomposition, but the possibility of filtering the signal at a higher quality with better noise removal and efficient compression increases.


Adjustable Parameters

  • type - calculation type (0-DWT, 1-MODWT, 2-SWT);
  • filter - filter type;
  • indicator - indicator used for transform (0-1);
  • length - indicator length;
  • J - the level of decomposition.
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The AT Forex Indicator MT4 is a sophisticated trading tool designed to provide traders with a comprehensive analysis of multiple currency pairs. This   powerful indicator   simplifies the complex nature of the forex market, making it accessible for both novice and experienced traders. AT Forex Indicator uses   advanced algorithms   to detect trends, patterns and is an essential tool for traders aiming to enhance their forex trading performance. With its robust features, ease of use, and reliabl
PZ Mean Reversion MT4
PZ TRADING SLU
2.33 (3)
Indicateur unique qui met en œuvre une approche professionnelle et quantitative pour signifier le trading de réversion. Il capitalise sur le fait que le prix dévie et revient à la moyenne de manière prévisible et mesurable, ce qui permet des règles d'entrée et de sortie claires qui surpassent largement les stratégies de trading non quantitatives. [ Installation Guide | Update Guide | Troubleshooting | FAQ | All Products ] Des signaux de trading clairs Étonnamment facile à échanger Couleurs et
Reversal Sniper is designed to find the extreme reversals of the price. Indicator collects data of Cycle Sniper Indicator. NOTE: REVERSAL SNIPER Indicator is made for Cycle Sniper Users as an additional tool.  However, it can be used by the traders who look for finding out strong reversal levels. Indicator works on all timeframes and all instruments. Reversal  Sniper  Checks: Harmonic Patterns RSI Zig Zag and Harmonic Swings Cycle Sniper Indicator's Buy / Sell Signals The complex algo i
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Biwavelet is an indicator for harmonic forecast of the market based on one-dimensional wavelet transform functions. Wavelet transforms are one of the main tools of digital algorithmic trading. This is due to their ability to analyze and predict processes occurring in two independent basic dimensions - price and time. Wavelets have significant advantages over the Fourier transform, because wavelet transform allows evaluating not only the frequency spectrum of the price signal, but also the time a
The ARIMA Trend Forecaster indicator is designed for analyzing and forecasting the trend component of a financial instrument based on the integrated ARIMA autoregressive model. The ARIMA methodology aims at identifying the presence of unit roots and the order of time series integration. In financial markets, autoregressive models are used for working with price time series to predict future price points. The ARIMA Trend Forecaster indicator using all the advantages of the ARIMA method allows to
MultiTrendLines - мультивалютный индикатор для автоматизации графического анализа трендовых линий. Позволяет быстро выполнять трудоемкий анализ трендовой ситуации на рынке. Использует точные математические алгоритмы выделения ключевых точек рынка для извлечения трендовой струкртуры инструмента. За счет применения корреляционных сигналов можно улучшить симметричную оценку поведения инструмента. Включает в себя возможность точно задавать необходимый уровень глубины и угла трендовой линии. Основной
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Version 3.0 2018.02.20
1. Added the eighth level of decomposition
2. Added new filter type - Reverse Biorthogonal (rbior)
3. Added two new indicators for transform
4. Extended filter families (filter order)
- Daubechies - db1, db2, db3, db4, db5, db6, db7, db8, db9, db10;
- Coiflet - coif1, coif2, coif3, coif4, coif5;
- Biorthogonal - bior11, bior13, bior15, bior22, bior24, bior31, bior33, bior35, bior37, bior39, bior44, bior55, bior68;
- Reverse Biorthogonal - rbior11, rbior13, rbior15, rbior22, rbior24, rbior31, rbior33, rbior35, rbior37, rbior39, rbior44, rbior55, rbior68.
5. Extended the range of possible values for the time series length parameter