RicardoSantos

[RS]Log Channel V0

EXPERIMENTAL: logarithm based channel.
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study("[RS]Log Channel V0", overlay=true)
smooth = input(title='ma smooth', type=integer, defval=4)
length = input(title='l', type=integer, defval=6)
src = input(title='src', type=source, defval=hl2)

logc = log(sqrt(src))
lower = sma(close - logc*0.5, smooth)
upper = sma(lower + logc, smooth)
midline = avg(lower,upper)

smooth_upper = upper*0.25 + highest(upper, length)*0.75
smooth_lower = lower*0.25 + lowest(lower, length)*0.75
smooth_midline = avg(smooth_upper, smooth_lower)

plot(midline, color=lime)
plot(lower, style=circles, color=lower == smooth_lower ? na : falling(lower, 1) ? na : lime, linewidth=2)
plot(upper, style=circles, color=upper == smooth_upper ? na : rising(upper, 1)  ? na : red, linewidth=2)

plot(smooth_midline, color=red)
plot(smooth_lower, color=black)
plot(smooth_upper, color=black)
Nice work as always.

I know this is perhaps moot but you can use a logarithm property to evaluate logc = log(sqrt(src)) = log((src)^(0.5)) = 0.5 * log(src), since: log(a^b) = b * log(a) rule. That way you do not have to apply sqrt(src) before applying log().

** This is not to be patronizing. Just a flashback to my Numerical Analysis classes from college back in the day of optimizing algorithm calculations, reducing calculation complexity and time.
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thx, thats nice to know :p i never attended college, and not a particular focused math person either, so just playing around with it.
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tradearcher PRO RicardoSantos
No worries. Hope that helps. I like the visual perspectives that your indicators create. Keep on keeping on. =)
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snapshot

snapshot

interesting usage :)
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