A better version of Apirine's RS EMA by using a superior MA: Ehlers Super Smoother.
In January 2022 edition of TASC Vitaly Apirine introduced his Relative Strength Exponential Moving Average. A concept not entirely new, as Tushar Chande used a similar calculation for his VIDYA moving average. Both are based on the idea to change EMA length depending on the...
Level:2
Background
The third-order super smoother low-pass butterworth filter (3 pole) is a classic J.F Ehlers indicator.
Function
I have found many places where the algorithms are not uniform and some are even wrong. So, I did some research and wrote a low pass filter that I think is correctly defined. This indicator is often used as one of the basic...
A complimentary indicator to my Adaptive MA constructor. It calculates the difference between the two MA lines (inspired by the Moving Average Difference (MAD) indicator by John F. Ehlers). You can then further smooth the resulting curve. The parameters and options are explained here:
The difference is normalized by dividing the difference by twice its Root mean...
Adaptive Moving Averages are nothing new, however most of them use EMA as their MA of choice once the preferred smoothing length is determined. I have decided to make an experiment and separate length generation from smoothing, offering multiple alternatives to be combined. Some of the combinations are widely known, some are not. This indicator is based on my...
The 2 Pole and 3 Pole Super Smoother Filters were developed by John Ehlers and described in "Chapter 13: Super Smother" of his book Cybernetic Analysis for Stocks and Futures .
The 2 Pole Smoother is described as being a better approximation of price, whereas the 3 Pole Smoother has superior smoothing.
Library "Ehlers_Super_Smoother"
Provides the functions to...
The Deviation Scaled Super Smoother was created by John Ehlers and this is an excellent moving average that changes direction very quickly and can keep up with the current underlying trend. This indicator works by applying a Hann Windowed Moving Average to the stock's momentum and scaling that by the Root Mean Square and then using that value in the input for a ...
The Average Error Filter was created by John Ehlers and this is a variation of a Zero Lag Exponential Moving Average that uses a Super Smoother to filter out the noise and then uses a second Super Smoother of the difference between the current price and the filtered data. This works well as a trendline and does give out a few false signals like all indicators...
John Ehler's MESA Stochastic uses super smoothing to give solid signals. This indicator uses the same rules as every other Stochastic indicator so it would be worth looking into if you are not already familiar with reading a Stochastic. There are 4 different lengths displayed to give traders an edge on reading the market. This is a great tool to analyze waves and...
Level: 2
Background
John F. Ehlers introuced Super Smoother Filter in Jan, 2014.
Function
In “Predictive And Successful Indicators” in Jan, 2014, John Ehlers describes a new method for smoothing market data while reducing the lag that most other smoothing techniques have. And this is a very popular filter to eliminate noise of market signal.
Key Signal
Filt...
Description : This SwissArmyKnife - MultiPurposeIndicator allows user to modify the Directional index based on one of filtering tools proposed by John F.Ehlers .
Details of each filtering type can be read in Ehlers Technical Papers: "Swiss Army Knife Indicator" and/or his book "Cybernetics Analysis for Stock and Futures"
Disclaimer:
These study scripts was built...
Level: 2
Background
John F. Ehlers introuced Super Smooth Stochastic Indicator in Jan, 2014.
Function
In “Predictive And Successful Indicators” of in, 2014, John Ehlers presented another innovative way to eliminate noise from classic indicators and introduces some new smoothing indicators: the SuperSmoother filter, which is superior to moving averages for...
Level: 2
Background
John F. Ehlers introuced Three Pole Super Smoother in his "Cybernetic Analysis for Stocks and Futures" chapter 13 on 2004.
Function
The Super Smoother filter is formed by retaining the IIR part of a Butterworth digital filter. The order of Super Smoother filters can be increased indefinitely to increase the sharpness of the filter...
Level: 2
Background
John F. Ehlers introuced Two Pole Super Smoother in his "Cybernetic Analysis for Stocks and Futures" chapter 13 on 2004.
Function
The transfer response of the two-pole Super Smoother is almost identical to the transfer response of the Regularized filter. The difference between the two is that the characteristics of the Super Smoother are...
This is an experimental study designed to calculate polynomial regression for any order polynomial that TV is able to support.
This study aims to educate users on polynomial curve fitting, and the derivation process of Least Squares Moving Averages (LSMAs).
I also designed this study with the intent of showcasing some of the capabilities and potential applications...
The 2 Pole Super Smoother Filter was created by John Ehlers (Cycle Analytics For Traders pg 32) and this follows the price very closely and very useful because it is consistent with uptrends and falls sharply during a sudden downtrend so it should be able to help you stay more profitable. Buy when the indicator line turns green and sell when it turns red.
Let me...
This is an experimental study that calculates filter values at user defined sample rates.
This study is aimed to provide users with alternative functions for filtering price at custom sample rates.
First, source data is resampled using the desired rate and cycle offset. The highest possible rate is 1 bar per sample (BPS).
There are three resampling methods to...
The 2 Pole Super Smoother Filter was created by John Ehlers (Cybernetic Analysis For Stocks And Futures pg 202) and this one of his filters that follows the price very closely. I would recommend to change the default settings to what fits your trading style the best. Buy when the indicator line turns green and sell when it turns red.
Let me know if there are...
This is an experimental study built on the concept of using roofing filters on price data proposed by John Ehlers.
Roofing filters are a type of bandpass filter conventionally used in HF radio receivers in the first IF stage to limit the frequency spectrum passed on to later stages in the receiver.
The goal in applying roofing filters to a price signal is to...
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