This indicator can have a wide variety of usages, and since it is based on exponential averaging then the whole indicator can be made adaptive, thus ending up with a really promising tool. This indicator who can both smooth price and act as a trailing stop depending on user preferences, i tried to make it as reactive, stable and efficient as...
Source: Stocks and Commodities V38
Hooray! Another new John Ehlers indicator!
John claims this indicator is lag-less and uses the SPY on the Daily as an example.
This indicator is a slight modification of Reflex, which I have posted here
I think it's better for Stocks and ETFs than Reflex since it factors in long trends. It tends to keep you in winning trades...
The Hull moving average (HMA) developed by Alan Hull is one of the many moving averages that aim to reduce lag while providing effective smoothing. The HMA make use of 3 linearly weighted (WMA) moving averages, with respective periods p/2 , p and √p , this involve three convolutions, which affect computation time, a more efficient version exist...
Based on the exponential averaging method with lag reduction, this filter allow for smoother results thanks to a multi-poles approach. Translated and modified from the Non-Linear Kalman Filter from Mladen Rakic 01/07/19 www.mql5.com
length control the amount of smoothing, the poles can be from 1 to 3, higher...
Impulse responses can fully describe their associated systems, for example a linearly weighted moving average (WMA) has a linearly decaying impulse response, therefore we can deduce that lag is reduced since recent values are the ones with the most weights, the Blackman moving average (or Blackman filter) has a bell shaped impulse response, that is mid term values...
A derivation of the Kalman Filter.
Lower Gain values create smoother results.The ratio Smoothing/Lag is similar to any Low Lagging Filters.
The Gain parameter can be decimal numbers.
Kalman Smoothing With Gain = 20
For any questions/suggestions feel free to contact me
Perform forward-backward filtering using exponential averaging, thus providing a zero-phase exponential moving average. The output repaint and cannot be used as input for other indicators.
Length : moving average period
Src : data input of the moving average
Plot Color : the color of the displayed plot
Line Width : width of the plotted line
This script is a crossing of eleven different MA, with alerts and SL and TP.
The simplest is what works best.
SMA --> Simple
EMA --> Exponential
WMA --> Weighted
VWMA --> Volume Weighted
SMMA --> Smoothed
DEMA --> Double Exponential
TEMA --> Triple Exponential
HMA --> Hull
TMA --> Triangular
SSMA --> SuperSmoother filter
ZEMA --> Zero Lag Exponential
Based on ZeroLag EMA (original version by @Glaz).
Ideas and code from @yassotreyo and @albert.callisto.
Enhanced by Bill Strat @billstrat.
See you on twitter and telegram.
Last Update 11.09.2018
(BS - 1.0) Histogram with custom colors, crossovers and bars highlighting.
It is possible to use a wide variety of filters for the estimation of a least squares moving average, one of the them being the Kaufman adaptive moving average (KAMA) which adapt to the market trend strength, by using KAMA in an lsma we therefore allow for an adaptive low lag filter which might provide a smarter way to remove noise while preserving...
Remember that we can make filters by using convolution, that is summing the product between the input and the filter coefficients, the set of filter coefficients is sometime denoted "kernel", those coefficients can be a same value (simple moving average), a linear function (linearly weighted moving average), a gaussian function (gaussian filter), a...
This indicator is a collaboration between me and Himeyuri, i encourage you to check her profile and follow her www.tradingview.com
A lot of indicators include a "trigger" line, it can be a smoothed version of another input, in this case the trigger will generate signals from his crosses with the input. The purpose...
There can be many ways to make a simple moving average, you can either sum the current and the n-1 previous data points and divide the result by n , or you can do it more efficiently by first taking the cumulative sum of your data points, and subtracting the current cumulative sum result with the cumulative sum results n bars ago, then divide the result by n...
There are tons of filters, way to many, and some of them are redundant in the sense they produce the same results as others. The task to find an optimal filter is still a big challenge among technical analysis and engineering, a good filter is the Kalman filter who is one of the more precise filters out there. The optimal filter theorem state that :...
A user has asked for the Study/Indicator version of this Strategy .
If you encounter the error "loop....>100ms" simply toggle the eye icon to hide and unhide the indicator
The following is simply quoted from my previous post for your convenience: (obviously there won't be risk, Stop Loss, or Take profit parameters!)
The strategy is...
The Hull smoothing method aim to reduce the lag of a moving average by using a simple calculation involving smoothing with a moving average of period √p the subtraction of a moving average of period p/2 multiplied by 2 with another moving average of period p , however it is possible to extend this calculation by introducing more terms thus...