Kaufman Adaptive Moving Average (KAMA) - Multi TF - synapticEx

Developed by Perry Kaufman, Kaufman's Adaptive Moving Average ( KAMA ) is a moving average designed to account for market noise or volatility .

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study(title="Kaufman Adaptive Moving Average", shorttitle="KAMA", overlay=true)
length = input(14, minval=1) 
fastMA = input(2, minval=1)
slowMA = input(30, minval=1)
src = input(title="Source", type=source, defval=close)
tf = input(title="Resolution", type=resolution, defval = "current")

volatility = sum(abs(src-src[1]), length)
change = abs(src-src[length-1])
er = iff(volatility != 0, change/volatility, 0)

fastSC = 2/(fastMA+1)
slowSC = 2/(slowMA+1)
sc = pow((er*(fastSC-slowSC))+slowSC, 2)

kama = nz(kama[1])+(sc*(hl2-nz(kama[1])))

kamaR = security(tickerid, tf == "current" ? period : tf, kama)
plot(kamaR, color=white, title="KAMA", trackprice=false, style=line)


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