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 is an MACD indicator with the ability to use zeror lag moving average instead of exponential moving average. I also added different background color when histogram is over or under center line, MACD Leader, Laguerre filter and dots to indicate when Leader line crosses macd line. Good luck traders!
A study of moving averages that utilizes different tricks I've learned to optimize them. Included is Bollinger Bands, Guppy (GMMA) and Super Guppy.
The method used to make it MtF should be more precise and smoother than regular MtF methods that use the security function. For intraday timeframes, each number represents each hour, with 24 equal to 1 day. For daily,...
Adopted to Pine from www.prorealcode.com
I haven't yet understood the details of the algorithm but it matches the original Jurik's RSX one to one.
Jurik's RSX is a "noise free" version of RSI, with no added lag. To learn more about this indicator see www.jurikres.com
A different version of ZERO LAG EMA indicator by John Ehlers and Ric Way...
In this cover, Zero Lag EMA is calculated without using the PREV function.
The main purpose is that to provide BUY/SELL signals earlier than classical EMA's.
You can see the difference of conventional and Zero Lag EMA in the chart.
The red line is classical EMA and the blue colored...
I inspired myself from the MACD to present a different oscillator aiming to show more reactive/predictive information. The MACD originally show the relationship between two moving averages by subtracting one of fast period and another one of slow period. In my indicator i will use a similar concept, i will subtract a quadratic least squares moving...
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 reducing...
A quadratic regression is the process of finding the equation that best fits a set of data.This form of regression is mainly used for smoothing data shaped like a parabola.
Because we can use short/midterm/longterm periods we can say that we use a Quadratic Least Squares Moving Average or a Moving Quadratic Regression.
Like the Linear Regression (LSMA) a...
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
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...
This is Guppy MA i customized for myself based on two scripts of GMMA from JustUncleL and NeoButane.
Its features are:
1. Besides standard EMA you can chose all kinds of exotic moving average types ike ALMA (my favorite), HullMA, ZeroLag EMA, VWMA, KAMA etc...
2. Two types of coloring scheme - depends on volatility try one that's best fit.
3. Multiple sets of...
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...
Fast smooth indicators that produce early signals can sound utopic but mathematically its not a huge deal, the effect of early outputs based on smooth inputs can be seen on differentiators crosses, this is why i propose this indicator that aim to return extra fast signals based on a slightly modified max-min normalization method. The indicator...
This is my most successful strategy to date! Please enjoy and join the Open Source movement by sharing your code and ideas online!
The strategy is based on Ehlers idea that any indicator can be turned into a signal-producing trade system through smoothing and other filtering processes.
In fact, I'm using his Zero Lag EMA (ZLEMA) as a baseline...
Ujanja uses Zero Lag EMA combined with Hull Moving Average for smoothing purposes. It is a less aggressive. It is only to be used with huge volume , huge momentum and high volatility to get trend analysis... It doesn't repaint at all.
Advised use :
Trades highly volatile Crypto currencies, stocks as well as Gold .
It is only to be used with huge momentum and...