EMA-Deviation-Corrected T3 [Loxx]EMA-Deviation-Corrected T3 is a T3 moving average that uses EMA deviation correcting to produce signals. This comes via the beloved genius Mladen.
The origin of the correcting algorithm can be attributed to Dr. Alexander Uhl, who developed a method to filter the moving average and identify signals. Originally, this method utilized standard deviation as a measure to correct the average values.
However, the current indicator in question employs a modified version of the correcting method. Instead of using standard deviation for calculation, it uses EMA deviation, which stands for Exponential Moving Average deviation. The idea behind using EMA deviation is two-fold:
Efficiency: EMA deviation can be calculated faster than standard deviation, resulting in more efficient code execution.
Signal Reduction: Surprisingly, this modified "correcting" approach generates fewer signals compared to using standard deviation. This is because EMA deviation is more responsive to price changes, making the correcting process less sensitive to whipsaws or false signals.
What is T3?
The T3 moving average, short for "Tim Tillson's Triple Exponential Moving Average," is a technical indicator used in financial markets and technical analysis to smooth out price data over a specific period. It was developed by Tim Tillson, a software project manager at Hewlett-Packard, with expertise in Mathematics and Computer Science.
The T3 moving average is an enhancement of the traditional Exponential Moving Average (EMA) and aims to overcome some of its limitations. The primary goal of the T3 moving average is to provide a smoother representation of price trends while minimizing lag compared to other moving averages like Simple Moving Average (SMA), Weighted Moving Average (WMA), or EMA.
To compute the T3 moving average, it involves a triple smoothing process using exponential moving averages. Here's how it works:
Calculate the first exponential moving average (EMA1) of the price data over a specific period 'n.'
Calculate the second exponential moving average (EMA2) of EMA1 using the same period 'n.'
Calculate the third exponential moving average (EMA3) of EMA2 using the same period 'n.'
The formula for the T3 moving average is as follows:
T3 = 3 * (EMA1) - 3 * (EMA2) + (EMA3)
By applying this triple smoothing process, the T3 moving average is intended to offer reduced noise and improved responsiveness to price trends. It achieves this by incorporating multiple time frames of the exponential moving averages, resulting in a more accurate representation of the underlying price action.
Included
Bar coloring
Signals
Alerts
Loxx's Expanded Source Types
Corrected
EMA-Deviation-Corrected Super Smoother [Loxx]This indicator is using the modified "correcting" method. Instead of using standard deviation for calculation, it is using EMA deviation and is applied to Ehlers' Super Smoother.
What is EMA-Deviation?
By definition, the Standard Deviation (SD, also represented by the Greek letter sigma σ or the Latin letter s) is a measure that is used to quantify the amount of variation or dispersion of a set of data values. In technical analysis we usually use it to measure the level of current volatility.
Standard Deviation is based on Simple Moving Average calculation for mean value. This version is not doing that. It is, instead, using the properties of EMA to calculate what can be called a new type of deviation, and since it is based on EMA. It is similar to Standard Deviation, but on a first glance you shall notice that it is "faster" than the Standard Deviation and that makes it useful when the speed of reaction to volatility is expected from any code or trading system.
What is Ehlers Super Smoother?
The Super Smoother filter uses John Ehlers’s “Super Smoother” which consists of a a Two-pole Butterworth filter combined with a 2-bar SMA (Simple Moving Average) that suppresses the 22050 Hz Nyquist frequency: A characteristic of a sampler, which converts a continuous function or signal into a discrete sequence.
Things to know
The yellow and fuchsia thin line is the original Super Smoother
The green and red line is the Corrected Super Smoother
When the original Super Smoother crosses above the Corrected Super Smoother line, its a long, when it crosses below, its a short
Included
Alerts
Signals
Bar coloring
Corrected JMA [Loxx]This indicator uses the Juirk Moving Average to calculate price deviations from the JMA and if the changes are not significant, then the value is "flattened". That way we can easily see both trends and potential chop zones. This uses the regular JMA as a trigger.
What is Jurik Volty used in the Juirk Filter?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
Included:
Bar coloring
Corrected Moving AverageThis moving average was originally developed by professor Andreas Uhl in 2005 (The paper in German: www.buero-uhl.de). Here is the guy himself: wavelab.at
The strength of the CMA is that the current value of the time series must exceed the current volatility-dependent threshold, so that the filter increases or falls, avoiding false signals in weak phases.
The straight line of CMA can be used for a ranging market identification
Uhl MA Crossover SystemToday proposed indicator is based on the corrected moving average, an indicator originally proposed by Andreas Uhl professor at Salzburg University. This moving average is not the most well known, which is a pity since its design is extremely elegant.
The corrected moving average (CMA) is an adaptive moving average based on exponential averaging and aim to correct common problems of classical moving averages such as crosses occurring during sideway markets, more details will be introduced in the calculation section. The CMA aim to act as a slow moving average in a moving average crossover system.
Here a new fast adaptive moving average named corrected trend step (CTS) based on the CMA is introduced in order to provide a full moving average crossover system based on A. Uhl design.
To Andreas Uhl
Calculation And Understanding The CTS
Even if the code is quite compact, the original idea behind the CMA can be blurry for some users, however it is actually relatively simple to understand. The CMA is based on exponential averaging and a smoothing variable is therefore required, in the CMA the calculation of the smoothing variable is based on the squared distance between the precedent CMA output and a simple moving average, and the rolling variance, where the rolling variance act as threshold.
The CTS work the same way but instead of using the squared error between a simple moving average and the previous CMA output, we use the squared error between the closing price and the previous CTS output, this allow the CTS to better fit with the closing price. As said before the rolling variance act as threshold, if the squared error is lower than the rolling variance this mean that the CTS is close to the price, which can indicate a sideway market, therefore we should filter the entirety of the current price, therefore on sideways market the CTS is equal to the precedent value of the CTS.
In trending/volatile markets we expect the price to go away from the CTS, thus having an high squared error, if the squared error is greater than the rolling variance, the smoothing variable is equal to 1 - variance/squared error , here variance/squared error < 1 since the squared error is greater than the rolling variance ( remember that the smoothing variable need to be in a (0,1) range ), however if the squared error is way higher than variance this ratio will be small, which would return a non reactive output, but thats not what we want ! This is why we subtract 1 by this ratio in order to make the CTS more reactive instead of less reactive.
In case the squared error is greater than the rolling variance during sideway markets we would not expect a huge difference anyway, that is squared error ≈ variance and therefore:
1 - variance/squared error ≈ 1 - 1/1 ≈ 1 - 1 ≈ 0
This is a beautiful way to make an adaptive moving average, the CMA is not a flashy indicator, but when we look at the details behind the design we can only get amazed, or maybe that its just me, truly a great adaptive moving average.
The System
length control the filtering amount of both moving averages, with higher values of length returning larger filtering amount. Mult multiply the rolling variance by an user selected value, this also allow a greater amount of filtering.
The CTS act as a fast moving average while the CMA act as a slow moving average.
Here the indicator with length = 200, we can see how a sideway market who could have generated a large amount of signals don't affect our system.
Unlike classical crossovers systems where the slow moving average will rarely produce a cross with the fast moving average and price at the same time, the Uhl system can actually do that:
Conclusion
A moving average crossover system based on the corrected moving average proposed by Andreas Uhl has been presented, a new moving average that aim to produce good fits with the price has been created especially for this system. The logic behind the CMA has also been explained. A possible strategy analysis could be presented in the future.
In conclusion i would say the CMA is a bit underrated, in a field where arrows, signals, alerts are the only things appreciated by peoples, original content is slowly dying, this actually make today technical indicators have a pretty bad academic reputations. I'am afraid that today haiku master is Uhl rather than me, i hope to see more indicators from him in the future.
Thanks for reading !
Original paper: www.buero-uhl.de
