LazyBear

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
- MAMA: www.mesasoftware.com/papers/MAMA.pdf

List of my public indicators: bit.ly/1LQaPK8
List of my app-store indicators: blog.tradingview.com/?p=970


List of my free indicators: bit.ly/1LQaPK8
List of my indicators at Appstore: blog.tradingview.com/?p=970
Script de código abierto

Siguiendo el verdadero espíritu de TradingView, el autor de este script lo ha publicado en código abierto, para que los traders puedan entenderlo y verificarlo. ¡Un hurra por el autor! Puede utilizarlo de forma gratuita, aunque si vuelve a utilizar este código en una publicación, debe cumplir con lo establecido en las Normas internas. Puede añadir este script a sus favoritos y usarlo en un gráfico.

Exención de responsabilidad

La información y las publicaciones que ofrecemos, no implican ni constituyen un asesoramiento financiero, ni de inversión, trading o cualquier otro tipo de consejo o recomendación emitida o respaldada por TradingView. Puede obtener información adicional en las Condiciones de uso.

¿Quiere utilizar este script en un gráfico?
//
// @author LazyBear 
// 
// List of my public indicators: http://bit.ly/1LQaPK8 
// List of my app-store indicators: http://blog.tradingview.com/?p=970 
//
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")
bc=mama>fama?lime:red
barcolor(ebc?bc:na)