HPotter

Kaufman Moving Average Adaptive (KAMA)

Everyone wants a short-term, fast trading trend that works without large
losses. That combination does not exist. But it is possible to have fast
trading trends in which one must get in or out of the market quickly, but
these have the distinct disadvantage of being whipsawed by market noise
when the market is volatile in a sideways trending market. During these
periods, the trader is jumping in and out of positions with no profit-making
trend in sight. In an attempt to overcome the problem of noise and still be
able to get closer to the actual change of the trend, Kaufman developed an
indicator that adapts to market movement. This indicator, an adaptive moving
average (AMA), moves very slowly when markets are moving sideways but moves
swiftly when the markets also move swiftly, change directions or break out of
a trading range.
从常用脚本中删除 添加到常用脚本
////////////////////////////////////////////////////////////
//  Copyright by HPotter v1.0 11/07/2014
// Everyone wants a short-term, fast trading trend that works without large
// losses. That combination does not exist. But it is possible to have fast
// trading trends in which one must get in or out of the market quickly, but
// these have the distinct disadvantage of being whipsawed by market noise
// when the market is volatile in a sideways trending market. During these
// periods, the trader is jumping in and out of positions with no profit-making
// trend in sight. In an attempt to overcome the problem of noise and still be
// able to get closer to the actual change of the trend, Kaufman developed an
// indicator that adapts to market movement. This indicator, an adaptive moving
// average (AMA), moves very slowly when markets are moving sideways but moves
// swiftly when the markets also move swiftly, change directions or break out of
// a trading range.
////////////////////////////////////////////////////////////
study(title="Kaufman Moving Average Adaptive (KAMA)", shorttitle="Kaufman Moving Average Adaptive (KAMA)", overlay = true)
Length = input(21, minval=1)
xPrice = close
xvnoise = abs(xPrice - xPrice[1])
nfastend = 0.666
nslowend = 0.0645
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")

评论

For those that want to use with pinescript v3:

nAMA = 0.0
nAMA := nz(nAMA) + nsmooth * (xPrice - nz(nAMA))
+8 回复
HPotter hexelbyte
@hexelbyte, Thank you. It will very helpful for other.
+1 回复
Many Thanks !
+1 回复
HPotter Mirandole
You are welcome.
回复
this is one of the best, thank you potter
回复
Mtrade85 Mtrade85
@Mtrade85, And may I ask, which time frames does KAMA work better, can we use it on daily, weekly periods with confidence too ?
+1 回复
HPotter Mtrade85
@Mtrade85, You are welcome.
回复
beautiful..! thank you
回复
HPotter Kharis
@Kharis, You are welcome
回复
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