What is the filter?
In signal processing, the function of a filter is to remove unwanted parts of the signal, such as random noise, or to extract useful parts of the signal, such as the components lying within a certain frequency range.

Ok. Why digital?
A digital filter uses a digital processor to perform numerical calculations on sampled values of the signal. The processor may be a general-purpose computer such as a PC, or a specialized DSP (Digital Signal Processor) chip.

Too complicated. Do I know the filter?
Yes of course:
- Simple Moving Average (SMA) is a average value of a last sequence in series of data. It is an example DF with Finite Impulse Response FIR also known as non-recursive filters.
- Triangle and Weighted Moving Average are calculated as SMA but elements in the series have different weights. Triangle (TMA) has maximum weight in the middle. Weighted (WMA) has minimum weights in the middle.
- Exponential MA is calculated as: Y[i] = Y[i-1] + (X[i] - Y[i-1]) * Alpha Where X is input data. Y is output data. Alpha is a coefficient that defines the smoothness of the indicator line. This is an example of DF as IIR filter.
- Momentum, ROC, MACD, TRIX and others - digital filters as well.

So what we are talking about! We know those filters!
Most of indicators used in Technical Analysis (TA) are regular linear digital filters (DF). Practically all of them have inside themselves moving averages parts (which are low pass filters). We can say now that the DF is a part of any TA. DFs are well investigated. There are methods of calculating of DF by calculatios, by weights coefficients or by the impulse response.

What is AT&CF?
It is Adaptive Trend & Cycles Following indicators.

What is FATL and SATL?

FATL (Fast Adaptive Trend Line)– is formed with the digital filter of the low frequency LPF-1. Filter LPF–1 serves to suppress noises of high frequency and market cycles with very short periods of oscillation that can be considered as noise.

SATL (Slow Adaptive Trend Line)– is formed with the digital filter of the low frequency LPF-2. Filter LPF–2 serves to suppress noises and market cycles with longer periods of oscillation.

Filters of low frequency LPF–1 and LPF–2 provide attenuation in the stop band with no less than 40 dB and absolutely don't distort the amplitude and phase of entry discontinuous price series in the pass band (bandwidth).

These properties of the digital filters provide significantly improved (in comparison with simple moving average) noise suppression that in its turn allows reducing sharply the probability of appearance "false" signals for purchase and sell.

There are no analogues to FATL and SATL among widely known technical instruments. These are not moving "average", but just the adaptive lines estimates of the short term and long-term trends. Unlike moving "average", FATL and SATL have no any phase delay with regard to current prices.

What is RFTL (Reference Fast Trend Line) and RSTL (Reference Slow Trend Line)?
RFTL and RSTL are support "slow" trend line are digital filters response of LPF 1 and LPF 2 to the entry discontinuous series taken with delays. Support lines of RFTL and RSTL are analogues to simple moving "average" in the sense of their delay in relation to the current prices.

Indicators of FTLM (Fast Trend Line Momentum) and STLM (Slow Trend Line Momentum) show the tempo of change (fall or growth) of FATL and SATL and are calculated similarly to indicator Momentum by formulas:
FTLM(k) = FATL(k) – RFTL(k),
STLM(k) = SATL(k) – RSTL(k).

Main difference of FTLM and STLM from classical technical instrument Momentum is that for its calculation not the close prices but smoothed (leveled) in the result of filtration values of the trend line are used. In the result FTLM and STLM turn out more leveled (smoothed) and regular functions than the classical instrument Momentum, and therefore have more forecasting value.

During computation the classical indicators Momentum requirement is often not fulfilled and it leads to unavoidable distortions in the spectrum of the entering signal. Specialists in the digital processing of the signals name these distortions aliasing that is frequencies overlay or ambiguity. This ambiguity leads to strong irregularity and chaos in the classical technical indicator Momentum.

A set of the technical instruments of the method contains two more new oscillators. They are indexes of RBCI and PCCI.
RBCI (Range Bound Channel Index) – is calculated by means of the channel (bandwidth) filter (CF).
PCCI Index (Perfect Commodity Channel Index) – is a perfect commodity channel index.
It has some outer similarity in the calculating method with commodity channel index CCI by D. Lambert. Indeed, CCI index is calculated as normalized difference between current price and its moving average and PCCI – as the difference between closing price and its mathematical expectation represented by the FATL value. Here lies more than in comparison with CCI the perfection of PCCI. PCCI index– is a normalized for its standard deviation high frequency component of the currency rate volatility.

Attached Images

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i need DIGITAL SYSTEM of forex

Does anyone have or would be able to code a MTF Low Pass Filter. I was thinking of something simular to the N4 TF HAS Bar used in the Steinz method or Forex Freedom Bars.

I find the Low Pass Filter very useful for finding trends on on the higher time frames and finding entries in the lower time frames. If you was to be able to visually see all the time frames in one indicator. Perhaps D1,H4,H1,M30,M15,M5. I believe you would better able to pick tops and bottoms off the on counter trend's dips and rallys.