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
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...
In general gaussian related indicators are built by using the gaussian function in one way or another, for example a gaussian filter is built by using a truncated gaussian function as filter kernel (kernel refer to the set weights) and has many great properties, note that i say truncated because the gaussian function is not supposed to be finite. In general the...
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 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...
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...
The term "shapeshifting" is more appropriate when used with something with a shape that isn't supposed to change, this is not the case of a moving average whose shape can be altered by the length setting or even by an external factor in the case of adaptive moving averages, but i'll stick with it since it describe the purpose of the proposed moving average pretty...
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...
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.
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 :...
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...
I already estimated the least-squares moving average numerous times, one of the most elegant ways was by rescaling a linear function to the price by using the z-score, today i will propose a new smoother (FLSMA) based on the line rescaling approach and the inverse fisher transform of a scaled moving average error with the goal to provide an...
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...
An adaptive filtering technique allowing permanent re-evaluation of the filter parameters according to price volatility. The construction of this filter is based on the formula of moving ordinary least squares or lsma , the period parameter is estimated by dividing the true range with its highest. The filter will react faster during high volatility periods and...
The ability to reduce lag while keeping a good level of stability has been a major challenge for smoothing filters in technical analysis. Stability involve many parameters, one of them being overshoots. Overshoots are a common effect induced by low-lagging filters, they are defined as the ability of a signal output to exceed a target input. This...