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*** NOTE: This is a repost with updated scripts to workaround the recent script engine changes ****
As the volatility rises, all Adaptive Moving Averages (AMA) become more sensitive and adapt faster to the price changes. As the volatility decreases, they slow down significantly compared to normal EMA . 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 Kaufman's Efficiency Ratio as the smoothing constant.
- Adaptive RSI . This adapts standard RSI to a smoothing constant.
- Tushar Chande's Variable Index Dynamic Average ( VIDYA ). This uses a pivotal smoothing constant, which is fixed, and varies the speed by using a factor based on the relative volatility to increase or decrease the value of SC .
For reference, I have plotted an EMA (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.
As the volatility rises, all Adaptive Moving Averages (AMA) become more sensitive and adapt faster to the price changes. As the volatility decreases, they slow down significantly compared to normal EMA . 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 Kaufman's Efficiency Ratio as the smoothing constant.
- Adaptive RSI . This adapts standard RSI to a smoothing constant.
- Tushar Chande's Variable Index Dynamic Average ( VIDYA ). This uses a pivotal smoothing constant, which is fixed, and varies the speed by using a factor based on the relative volatility to increase or decrease the value of SC .
For reference, I have plotted an EMA (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.
// // @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[0]-close[1]) 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[1], close)+smooth*(close-nz(kama[1], close)) plot( kama, color=green, linewidth=3)
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unelma
i only see the script for KAMA here, where is VIDYA ?
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everget
unelma
@unelma, here is VIDYA
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unelma
can you link me the adaptive rsi? I cant find it. thanks
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everget
unelma
@unelma, here is Adaptive RSI
+1
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RV1458
I ony see the script for Kaufman's AMA here. Where's the script for the other two?
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AlexandreFF
Great job master thanks again
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LazyBear
Vidya/KAMA are pointing to wrong AMAs, because, looks like, TV doesn't keep the alignment intact when publishing. Just match the colors to identify the correct AMA.
+4
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RV1458
LazyBear
@LazyBear, I ony see the script for Kaufman's AMA here. Where's the script for the other two?
+3
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everget
RV1458
@RV1458, see
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everget
RV1458
@RV1458, here is Adaptive RSI
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