John Ehlers Indicators

Ehlers Zero Lag Exponential Moving Average (ZLEMA)

The Zero Lag Exponential Moving Average (ZLEMA) is a technical analysis indicator used in financial markets to smooth price data while minimizing the inherent lag of standard exponential moving averages (EMAs), achieving this by applying an adjustment to the input price series that compensates for the estimated delay in trend response. The ZLEMA was developed by John F. Ehlers and Ric Way and introduced in their 2010 article "Zero Lag (Well, Almost)" published in Technical Analysis of Stocks & Commodities magazine. The ZLEMA is calculated by first estimating the lag factor as (period - 1) / 2, where period is the user-defined lookback length (typically 9 to 50 bars). The input data is then adjusted by subtracting the price from the lagged period and doubling the current price, yielding an adjusted series: adjusted = 2 × close - close[lag]. Finally, a standard EMA is applied to this adjusted series over the specified period, resulting in the ZLEMA value that tracks price changes more closely than a conventional EMA. This method effectively shifts the EMA forward in time, reducing delay without eliminating smoothing entirely, though the exact lag compensation assumes a linear trend approximation. In practice, the ZLEMA is employed for trend-following strategies, such as generating buy signals when price crosses above the indicator or using dual ZLEMA lines (short and long periods) for crossover confirmations. Its key advantages include enhanced responsiveness to recent price action and reduced whipsaws in volatile conditions, making it suitable for intraday and swing trading. However, in sideways or choppy markets, the ZLEMA can produce more false signals due to its sensitivity, and it requires computational resources for real-time implementation in trading platforms. Overall, it represents an evolution in moving average design, prioritizing timeliness while preserving noise reduction for informed decision-making in technical analysis.

more information found here: Zero lag exponential moving average — Grokipedia

Also:
It is using percent of various types of ATR (Average True Range) or STD (Standard deviation) as a filtering option. It is done in order to fix one of the weak points of using fixed (pips) step size: different time frames tend to have different results for fixed step size (ie: higher time frames become almost without steps and lower time frames still have those steps for same setting). Percent of ATR or STD usage fixes that and makes it a sort of adaptive. The rest is the same: if the average does not change for more than the required step, the value of the average remains the same. Otherwise, it is changed in order to reflect the nearest value based on the required steps.

PS) Adding Mladen Rakic's regular mt5 version.

Ehlers Reverse Ema

John F. Ehlers introduced Reverse EMA in Sep, 2017.
Function:
In “The Reverse EMA Indicator” in Sep 2017, John Ehlers presented very interesting filtering technique based on a Z-transform of the exponential moving average. It is a causal forward and backward EMA indicator that could be used in real trading. It has double smoothing at the high end of the spectrum to reduce aliased components and is able to mitigate the impact of spectral dilation at the low end. The author described the indicator as having unique flexibility in that it could display trend or cycle information by varying the alpha parameter and do this with very low lag. This version uses a standard ema period instead of alpha.

Signals are:
* inpEmaPeriodT --> Ehlers Reverse EMA fast line (Trend line period)
* inpEmaPeriodC --> Ehlers Reverse EMA slow line (Cycle line period)

Coloring options available:
* Lines color on slope change
* Lines color on zero cross
* Lines color on trend crossing cycle

Dsl Ehlers Zero Lag Macd

Uses:
The Zero Lag Exponential Moving Average (ZLEMA) is a technical analysis indicator used in financial markets to smooth price data while minimizing the inherent lag of standard exponential moving averages (EMAs), achieving this by applying an adjustment to the input price series that compensates for the estimated delay in trend response. The ZLEMA was developed by John F. Ehlers and Ric Way and introduced in their 2010 article "Zero Lag (Well, Almost)" published in Technical Analysis of Stocks & Commodities magazine. The ZLEMA is calculated by first estimating the lag factor as (period - 1) / 2, where period is the user-defined lookback length (typically 9 to 50 bars). The input data is then adjusted by subtracting the price from the lagged period and doubling the current price, yielding an adjusted series: adjusted = 2 × close - close[lag]. Finally, a standard EMA is applied to this adjusted series over the specified period, resulting in the ZLEMA value that tracks price changes more closely than a conventional EMA. This method effectively shifts the EMA forward in time, reducing delay without eliminating smoothing entirely, though the exact lag compensation assumes a linear trend approximation. In practice, the ZLEMA is employed for trend-following strategies, such as generating buy signals when price crosses above the indicator or using dual ZLEMA lines (short and long periods) for crossover confirmations. Its key advantages include enhanced responsiveness to recent price action and reduced whipsaws in volatile conditions, making it suitable for intraday and swing trading. However, in sideways or choppy markets, the ZLEMA can produce more false signals due to its sensitivity, and it requires computational resources for real-time implementation in trading platforms. Overall, it represents an evolution in moving average design, prioritizing timeliness while preserving noise reduction for informed decision-making in technical analysis.
more information found here: Zero lag exponential moving average — Grokipedia

Also: Super Smoother DSL From Mladen Rakic:

DSL (Discontinued Signal Line) indicators
What is the DSL Discontinued Signal Line?
A lot of indicators are using signal lines in order to determine the trend (or some desired state of the indicator) easier. The idea of the signal line is easy: comparing the value to its smoothed (slightly lagging) state, the idea of current momentum/state is made.

Discontinued signal line is inheriting that simple signal line idea, and it is extending it: instead of having one signal line, more lines depending on the current value of the indicator.

"Signal" line is calculated the following way:

1. When a certain level is crossed into the desired direction, the Super Smoother of that value is calculated for the desired signal line
2. When that level is crossed into the opposite direction, the previous "signal" line value is simply "inherited" and it becomes a kind of a level

This way it becomes a combination of signal lines and levels that are trying to combine both the good from both methods.
In simple terms, DSL uses the concept of a signal line and betters it by inheriting the previous signal line's value & makes it a level.

Hull Alma with floating levels

Arnaud Legoux Moving Average Definition:
The Arnaud Legoux Moving Average (ALMA) is different from other moving averages because of its specific design to use Gaussian distribution that is shifted with a calculated offset in order for the average to be biased towards more recent days, instead of more evenly centered on the window. Built on the generalized Moving Average Framework, ALMA is able to use various indicators in conjunction with its own capabilities and run on multiple time frames, with the inclusion of custom bar types.

History:
The Arnaud Legoux Moving Average (ALMA) indicator was developed by both Arnaud Legoux and Dimitrios Douzis-Loukas while trying to create a new and improved moving average that would showcase advanced smoothness and responsiveness in comparison to other moving averages at the time of its development. Legoux claimed the ALMA moving average was inspired significantly by the Gaussian Filter and often compares his developed moving average to the Hull Moving Average (HMA), which is said to be outperformed by the ALMA in effectiveness and smoothness.

Calculations:

1. To calculate the Arnaud Legoux Moving Average (ALMA) you’ll first need to compute a weighted sum of the window's size using your input series and weights given by a Gaussian function with a peak value determined by the offset, and a width determined by sigma.
2. This weighted sum is then divided by the total sum of the weights.

Incorporated a Hull moving average variation that allows speed adjusting of the hull moving average. The "speed" can be controlled through a HMA Speed parameter: the lower the value the slower the HMA. I am not exactly sure whose idea it was to modify the speed, (think it was someone from this forum) but was a good idea imho. The original Hull moving average has a "speed" value of 2.

Also comes with floating levels if levels greater than zero.

ps) know this has nothing to do with Ehlers but didn't want to start a new thread for one indicator.