This is an FTLM digital filter with a smoothing algorithm, also it shows candle formations in the histogram. The candles help to spot turning points as they get squeezed.
The ZerolagHATEMA and ZerolagTEMA were presented by Sylvain Vervoort in “THE QUEST FOR RELIABLE CROSSOVERS” Technical Analysis of Stocks & Commodities, May 2008. The Zerolag HATEMA is based on a TEMA that uses Heikin-Ashi candles as input series. In a second step Sylvain Vervoort applied zero-lag techniques to the HATEMA to compensate for its lag. For further details, please read the article by Sylvain Vervoort.
This indicator does not depend on the selected input series, as it uses open, high, low and close of each candle. As a consequence this indicator may not be used with any other input series than price.
The Zerolag TEMA and Zerolag HATEMA were presented by Sylvain Vervoort in “THE QUEST FOR RELIABLE CROSSOVERS” Technical Analysis of Stocks & Commodities, May 2008. The Zerolag TEMA is a version of the triple smoothed moving average which is less smooth, but more responsive to market movements. For further details read article by Sylvain Vervoort.
Sylvain Vervoort suggested to use the typical price as input series for the Zerolag TEMA. I have not hardcoded the typical price as input series. Please select the typical price as input series via the indicator dialogue box.
These are the 2 pole and 3 pole Super Smoother Filters, which are derived from digital Butterworth Filters. They were first described by John F. Ehlers in his book "Cybernetic Analysis for Stocks and Futures". I have ported them from Easy Language to NinjaTrader.
The chart shows that the 2 pole super smoother filter (firebrick) gives a better approximation for price while the 3 pole filter (blue) offers superior smoothing.
To emulate the original SuperSmoother presented by John F. Ehlers, please select the PriceType "Median" as Input Series.
The Sine Weighted Moving Average (SWMA) is a FIR filter that applies weights to each bar of the lookback period in the shape of the bulge in a sine curve from 0 to pi. As a consequence the middle prices of the lookback period have the greatest weight.
The sine weighted moving average is quite similar to a triangular moving average.
I have coded it because it comes as a default moving average with other software packages and has been requested by users.
This is a four element Adaptive Laguerre Filter as described by John Ehlers in his paper "Time Warp - Without Space Travel".
The Laguerre Filter is a smoothing filter based on Laguerre polynomials. Its first term is an EMA, which is then further smoothened with a damping factor. The damping factor may take any value between 0 and 1. When the damping factor is set to 0, the Laguerre Filter becomes a finite impulse response (FIR) filter. When the damping factor is set to a value close to 1, the filter becomes dramatically smoother, but will have a significant lag.
The Adaptive Laguerre Filter is based on the simple Laguerre Filter, but uses a variable damping factor. The damping factor is adjusted such that low frequency components are delayed more than high frequency components. The resulting filter is an adaptive moving average and can be compared to the Kaufman Adaptive Moving Average (KAMA) or the Variable Index Dynamic Average (VIDYA).
This is a four element Laguerre Filter as described by John Ehlers in his paper "Time Warp - Without Space Travel".
The Laguerre Filter is a smoothing filter based on Laguerre polynomials. Its first term is an EMA, which is then further smoothened with a damping factor. The damping factor may take any value between 0 and 1. When the damping factor is set to 0, the Laguerre Filter becomes a finite impulse response (FIR) filter. When the damping factor is set to a value close to 1, the filter becomes dramatically smoother, but will have a significant lag.
The indicator that can be downloaded here is a four element Laguerre Filter. I have replaced the damping factor with a synthetic lookback period which allows for adjusting smoothness and lag. A lookback period of 1 corresponds to a simple 4-period triangular moving average.
LaguerreFilter(1) = TMA(4)
When the synthetic lookback period is increased, the filter becomes smoother but has a slower response to price changes.
You may set the number of poles in the filter to 1,2,3 or 4. A 1-pole filter will have a better approximation to price, whereas the 4-pole filter has superior smoothing.
To emulate the original Gaussian filter presented by John F. Ehlers, please select the PriceType "Median" as Input Series.
This is the ThinkorSwim version of the LowPassCycle indicator. It is set to stlm2 emulation settings and it seems to work well on these settings. It does have problems painting correctly on lower settings. Feel free to update or modify the code.