Kaufman Adaptive Moving Average — Indicator by jacobnie2008

From Stockcharts.com:
"Developed by Perry Kaufman, Kaufman's Adaptive Moving Average (KAMA) is a moving average designed to account for market noise or volatility. KAMA will closely follow prices when the price swings are relatively small and the noise is low. KAMA will adjust when the price swings widen and follow prices from a greater distance. This trend-following indicator can be used to identify the overall trend, time turning points and filter price movements."

This is different from other users' KAMA's because it allows the user to adjust more parameters that can adjust the indicator in more precise ways without needing to change the source code.

Open-source script

In true TradingView spirit, the author of this script has published it open-source, so traders can understand and verify it. Cheers to the author! You may use it for free, but reuse of this code in a publication is governed by House Rules. You can favorite it to use it on a chart.

Disclaimer

The information and publications are not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations supplied or endorsed by TradingView. Read more in the Terms of Use.

Want to use this script on a chart?

study(title="Kaufman Adaptive Moving Average", shorttitle="Kaufman Adaptive Moving Average", overlay = true)
Length = input(10, minval=1)
xPrice = close
xvnoise = abs(xPrice - xPrice[1])
Fastend = input(4)
Slowend = input(30)
nfastend = 2/(Fastend + 1)
nslowend = 2/(Slowend + 1)
nsignal = abs(xPrice - xPrice[Length])
nnoise = sum(xvnoise, Length)
nefratio = iff(nnoise != 0, nsignal / nnoise, 0)
nsmooth = pow(nefratio * (nfastend - nslowend) + nslowend, 2) 
nAMA = nz(nAMA[1]) + nsmooth * (xPrice - nz(nAMA[1]))
plot(nAMA, color=blue, title="KAMA")