LazyBear

Ehlers Adaptive Cyber Cycle Indicator [LazyBear]

Another famous Ehlers indicator.

This is the adaptive version of Ehlers' Cyber Cycle (CC) (already published, check "More info" below). Idea behind making something "adaptive" is to calculate it using dynamic cycle period inputs instead of static setting. In adaptive cyber cycle, Ehlers uses the dominant cycle period as the length in computation of alpha.

According to Ehlers this should be more responsive than the non-adaptive version. Buy and sell signals should often occur one bar earlier than for the non-adaptive version.

I have the usual options in place. Check out plain CC for comparison.

More info:
- Cyber Cycle Indicator: - Cybernetic Analysis for Stocks and Futures (Ehlers)

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
Open-source script

In true TradingView spirit, the author of this script has published it open-source, so traders can understand and verify it. Cheers to the author! You may use it for free, but reuse of this code in a publication is governed by House Rules. You can favorite it to use it on a chart.

Disclaimer

The information and publications are not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations supplied or endorsed by TradingView. Read more in the Terms of Use.

Want to use this script on a chart?
//
// @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 Adaptive Cyber Cycle Indicator [LazyBear]", shorttitle="EACCI_LB", overlay=false, precision=3)
src=input(hl2, title="Source") 
a=input(.07, title="Alpha")
s = (src + 2*src[1] + 2*src[2] + src[3])/6.0
c = n<7?(src - 2*src[1] + src[2])/4.0:((1 - 0.5*a)*(1 - 0.5*a)*(s - 2*s[1] + s[2]) + 2*(1-a)*c[1] - (1 - a)*(1-a)*c[2])
q1 = (.0962*c + 0.5769*c[2] - 0.5769*c[4] - .0962*c[6])*(0.5+.08*nz(ip[1]))
I1 = c[3]
dp_ = iff(q1 != 0 and q1[1] != 0, (I1/q1 - I1[1]/q1[1]) / (1 + I1*I1[1]/(q1*q1[1])),0)
dp = iff(dp_ < 0.1, 0.1, iff(dp_ > 1.1, 1.1, dp_))
med(x,y,z) => (x+y+z) - min(x,min(y,z)) - max(x,max(y,z))
md = med(dp,dp[1], med(dp[2], dp[3], dp[4]))
dc = iff(md == 0, 15, 6.28318 / md + 0.5)
ip = .33*dc + .67*nz(ip[1])
p = .15*ip + .85*nz(p[1])
a1 = 2.0/(p + 1)
ac=nz(((1-0.5*a1)*(1-0.5*a)*(s-2*s[1]+s[2])+2*(1-a1)*ac[1]-(1-a1)*(1-a1)*ac[2]), (src-2*src[1]+src[2])/4.0)
t=ac[1]
fr=input(true, title="Fill Osc/Trigger region")
plot(0, color=gray, title="ZeroLine")
duml=plot(fr?(ac>t?ac:t):na, style=circles, linewidth=0, color=gray, title="Dummy")
cmil=plot(ac, title="AdaptiveCyberCycle",color=blue)
tl=plot(t, title="Trigger",color=green)
fill(cmil, duml, color=red, transp=50, title="NegativeFill")
fill(tl, duml, color=lime, transp=50, title="PositiveFill")
ebc=input(false, title="Color bars?")
bc=ebc?(ac>0? (ac>t?lime:(ac==t?gray:green)): (ac<t?red:orange)):na
barcolor(bc)