As the rises, all Adaptive Moving Averages (AMA) become more sensitive and adapt faster to the price changes. As the decreases, they slow down significantly compared to normal . This makes it an excellent choice for detecting ranging markets (look for horizontal lines).
I have included 3 AMAs here:
- Kaufman's AMA. This makes use of as the smoothing constant.
- Adaptive . This adapts standard to a smoothing constant.
- Tushar Chande's ( ). This uses a pivotal smoothing constant, which is fixed, and varies the speed by using a factor based on the relative to increase or decrease the value of SC .
For reference, I have plotted an (10). This uses a fixed smoothing constant.
This is my 25th indicators post (Yayy!), so decided to include a bunch of AMAs. Enjoy :)
Feel free to "Make mine" and use these in your charts. Appreciate any comments / feedback.
List of my indicators at Appstore: http://blog.tradingview.com/?p=970
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.
// // @author LazyBear // // v2 - updated the scripts to workaround function array indexing issues in the latest TV engine. // v1 - initial // study(title = "Kaufman Adaptive Moving Average [LazyBear]", shorttitle="KAMA2_LB", overlay=true) amaLength = input(10, title="Length") fastend=input(0.666) slowend=input(0.0645) diff=abs(close-close) signal=abs(close-close[amaLength]) noise=sum(diff, amaLength) efratio=noise!=0 ? signal/noise : 1 smooth=pow(efratio*(fastend-slowend)+slowend,2) kama=nz(kama, close)+smooth*(close-nz(kama, close)) plot( kama, color=green, linewidth=3)