Fractal Dimension Adaptive Moving Average (D-AMA)
etfhq.com/blog/2012/...oving-average-d-ama/
Overall the D-AMA produced results that were near identical to that of the FRAMA but the D-AMA is a slightly faster average.
It is very difficult to pick between the FRAMA and the D-AMA but becuase the FRAMA offers a slightly longer trade duration it the best Moving Average we have tested so far.
Overall the D-AMA produced results that were near identical to that of the FRAMA but the D-AMA is a slightly faster average.
It is very difficult to pick between the FRAMA and the D-AMA but becuase the FRAMA offers a slightly longer trade duration it the best Moving Average we have tested so far.
//@version=2
study("Fractal Dimension Adaptive Moving Average",shorttitle="D-AMA",overlay=true)
price=input(hl2)
len=input(defval=126,minval=1)
fast=input(defval=1,minval=1)
slow=input(defval=30,minval=1)
change=abs(price-price[len])
len1 = len/2
H1 = highest(high,len1)
L1 = lowest(low,len1)
N1 = (H1-L1)/len1
H2 = highest(high,len)[len1]
L2 = lowest(low,len)[len1]
N2 = (H2-L2)/len1
H3 = highest(high,len)
L3 = lowest(low,len)
N3 = (H3-L3)/len
dimen1 = (log(N1+N2)-log(N3))/log(2)
diff = iff(N1>0 and N2>0 and N3>0,dimen1,nz(dimen1[1]))
volatility=sum(diff,len)
ER=change/volatility
fastestSC=(2/(fast+1))
slowestSC=(2/(slow+1))
SC=pow(ER*(fastestSC-slowestSC)+slowestSC,2)
out=nz(out[1])+SC*(price-nz(out[1]))
plot(out,color=teal,title="D-AMA",linewidth=2)