Ehlers MESA Adaptive Moving Average [LazyBear]

Another one to add to Ehlers collection.

The MESA Adaptive Moving Average ( MAMA ) adapts to price movement based on the rate of change of phase as measured by the Hilbert Transform Discriminator. This method features a fast attack average and a slow decay average so that composite average rapidly ratchets behind price changes and holds the average value until the next ratchet occurs. Consider FAMA (Following AMA) as the signal.

Here are some of the options:

Fill MAMA /FAMA region (ribbon mode):

Mark Crossovers:

The above options (along with the bar colors) allow this to be used as a standalone system.

BTW, John Ehlers calls MAMA , "Mother of all Adaptive Moving Averages", lemme know what you think :)

More info:
- MESA Adaptive Moving Average , Stocks and Commodities Magazine, August 2001

List of my public indicators:
List of my app-store indicators:

List of my free indicators:
List of my indicators at Appstore:
Script open-source

Nello spirito di condivisione promosso da TradingView, l'autore (al quale vanno i nostri ringraziamenti) ha deciso di pubblicare questo script in modalità open-source, così che chiunque possa comprenderlo e testarlo. Puoi utilizzarlo gratuitamente, ma il riutilizzo del codice è subordinato al rispetto del Regolamento. Per aggiungerlo al grafico, mettilo tra i preferiti.

Vuoi usare questo script sui tuoi grafici?
// @author LazyBear 
// List of my public indicators: 
// List of my app-store indicators: 
study("Ehlers MESA Adaptive Moving Average [LazyBear]", shorttitle="EMAMA_LB", overlay=true, precision=3)
src=input(hl2, title="Source")
fl=input(.5, title="Fast Limit")
sl=input(.05, title="Slow Limit")
sp = (4*src + 3*src[1] + 2*src[2] + src[3]) / 10.0
dt = (.0962*sp + .5769*nz(sp[2]) - .5769*nz(sp[4])- .0962*nz(sp[6]))*(.075*nz(p[1]) + .54)
q1 = (.0962*dt + .5769*nz(dt[2]) - .5769*nz(dt[4])- .0962*nz(dt[6]))*(.075*nz(p[1]) + .54)
i1 = nz(dt[3])
jI = (.0962*i1 + .5769*nz(i1[2]) - .5769*nz(i1[4])- .0962*nz(i1[6]))*(.075*nz(p[1]) + .54)
jq = (.0962*q1 + .5769*nz(q1[2]) - .5769*nz(q1[4])- .0962*nz(q1[6]))*(.075*nz(p[1]) + .54)
i2_ = i1 - jq
q2_ = q1 + jI
i2 = .2*i2_ + .8*nz(i2[1])
q2 = .2*q2_ + .8*nz(q2[1])
re_ = i2*nz(i2[1]) + q2*nz(q2[1])
im_ = i2*nz(q2[1]) - q2*nz(i2[1])
re = .2*re_ + .8*nz(re[1])
im = .2*im_ + .8*nz(im[1])
p1 = iff(im!=0 and re!=0, 360/atan(im/re), nz(p[1]))
p2 = iff(p1 > 1.5*nz(p1[1]), 1.5*nz(p1[1]), iff(p1 < 0.67*nz(p1[1]), 0.67*nz(p1[1]), p1))
p3 = iff(p2<6, 6, iff (p2 > 50, 50, p2))
p = .2*p3 + .8*nz(p3[1])
spp = .33*p + .67*nz(spp[1])
phase = atan(q1 / i1)
dphase_ = nz(phase[1]) - phase
dphase = iff(dphase_< 1, 1, dphase_)
alpha_ = fl / dphase
alpha = iff(alpha_ < sl, sl, iff(alpha_ > fl, fl, alpha_))
mama = alpha*src + (1 - alpha)*nz(mama[1])
fama = .5*alpha*mama + (1 - .5*alpha)*nz(fama[1])
pa=input(false, title="Mark crossover points")
plotarrow(pa?(cross(mama, fama)?mama<fama?-1:1:na):na, title="Crossover Markers")
fr=input(false, title="Fill MAMA/FAMA Region")
duml=plot(fr?(mama>fama?mama:fama):na, style=circles, color=gray, linewidth=0, title="DummyL")
mamal=plot(mama, title="MAMA", color=red, linewidth=2)
famal=plot(fama, title="FAMA", color=green, linewidth=2)
fill(duml, mamal, red, transp=70, title="NegativeFill")
fill(duml, famal, green, transp=70, title="PositiveFill")
ebc=input(false, title="Enable Bar colors")