OPEN-SOURCE SCRIPT
RSI With Noise Elimination Technology (John Ehlers)

Indicator translation to Pinescript requested by cookie_crusher on Twitter. The "RSI With Noise Elimination Technology" (NET) is an indicator developed by John Elhers.
The indicator is simply a rolling Kendall rank correlation coefficient of a normalized momentum oscillator (a version of the RSI introduced by Elhers in the May 2018 issue of Stocks & Commodities). It can be interesting to note that the absolute value of this oscillator is equal to the efficiency ratio used in the Kaufman adaptive moving average (KAMA).
Even if both the normalized momentum oscillator and rolling Rank correlation are scale-invariant oscillators, they do not have the same behaviors when increasing their settings, that is the normalized momentum oscillator scale range will become lower while the Kendall correlation will stay close to 1/-1, here is a closed-form approximation of the mean of the absolute value of the normalized momentum oscillator absolute value (efficiency ratio):
E(er) ≈ 1/√p
Where E(er) is the mean of the efficiency ratio er while p is the period of the efficiency ratio, as such the scale of the normalized momentum oscillator will shrink with a higher period, maybe that both are not intended to be plotted at the same time but that's what the original code does.
It's still a coll indicator. The link to J. Elhers article is in the code.
The indicator is simply a rolling Kendall rank correlation coefficient of a normalized momentum oscillator (a version of the RSI introduced by Elhers in the May 2018 issue of Stocks & Commodities). It can be interesting to note that the absolute value of this oscillator is equal to the efficiency ratio used in the Kaufman adaptive moving average (KAMA).
Even if both the normalized momentum oscillator and rolling Rank correlation are scale-invariant oscillators, they do not have the same behaviors when increasing their settings, that is the normalized momentum oscillator scale range will become lower while the Kendall correlation will stay close to 1/-1, here is a closed-form approximation of the mean of the absolute value of the normalized momentum oscillator absolute value (efficiency ratio):
E(er) ≈ 1/√p
Where E(er) is the mean of the efficiency ratio er while p is the period of the efficiency ratio, as such the scale of the normalized momentum oscillator will shrink with a higher period, maybe that both are not intended to be plotted at the same time but that's what the original code does.
It's still a coll indicator. The link to J. Elhers article is in the code.
Skrip open-source
Dengan semangat TradingView yang sesungguhnya, penulis skrip ini telah menjadikannya sumber terbuka, sehingga para trader dapat meninjau dan memverifikasi fungsinya. Hormat untuk penulisnya! Meskipun anda dapat menggunakannya secara gratis, ingatlah bahwa penerbitan ulang kode tersebut tunduk pada Tata Tertib kami.
Check out the indicators we are making at luxalgo: tradingview.com/u/LuxAlgo/
"My heart is so loud that I can't hear the fireworks"
"My heart is so loud that I can't hear the fireworks"
Pernyataan Penyangkalan
Informasi dan publikasi tidak dimaksudkan untuk menjadi, dan bukan merupakan saran keuangan, investasi, perdagangan, atau rekomendasi lainnya yang diberikan atau didukung oleh TradingView. Baca selengkapnya di Persyaratan Penggunaan.
Skrip open-source
Dengan semangat TradingView yang sesungguhnya, penulis skrip ini telah menjadikannya sumber terbuka, sehingga para trader dapat meninjau dan memverifikasi fungsinya. Hormat untuk penulisnya! Meskipun anda dapat menggunakannya secara gratis, ingatlah bahwa penerbitan ulang kode tersebut tunduk pada Tata Tertib kami.
Check out the indicators we are making at luxalgo: tradingview.com/u/LuxAlgo/
"My heart is so loud that I can't hear the fireworks"
"My heart is so loud that I can't hear the fireworks"
Pernyataan Penyangkalan
Informasi dan publikasi tidak dimaksudkan untuk menjadi, dan bukan merupakan saran keuangan, investasi, perdagangan, atau rekomendasi lainnya yang diberikan atau didukung oleh TradingView. Baca selengkapnya di Persyaratan Penggunaan.