4 year seasonality - % (Daily TF)

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Inspired by the work done by crasher (can be found here:
Improvement of my earlier adaptation (can be found here:

This script projects the average % change of the selected security in the past 4 years.
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study("Cycle Seasonality - % (Daily TF)")

Period = input(title="Period Cycle", type=integer , defval=264)
Seasonlength = input(title="Season length", type=integer, defval=66)
Smoothing = input(title="SMA (smoothing)", type=integer, defval=5)

LBP = Period / Seasonlength

lastyear = (close - close[1*Period/LBP]) / close[1*Period/LBP]
twoyearsago = (close[1*Period] - close[1*Period + Period/LBP]) / close[1*Period + Period/LBP]
threeyearsago = (close[2*Period] - close[2*Period + Period/LBP]) / close[2*Period + Period/LBP]
fouryearsago = (close[3*Period] - close[3*Period + Period/LBP]) / close[3*Period + Period/LBP]

cum = (lastyear+twoyearsago+threeyearsago+fouryearsago)/4

smacum = sma(cum, Smoothing)

scolor = smacum >= 0 ? green : red

plot(smacum*10, color=scolor, offset = 264, style=columns)
nice work on the seasonal indicators. im having a little trouble setting up the inputs. can you explain what period length and sma smoothing represent in a little more detail? thx!
Yeah I like the idea but there is something that is confusing me.
Now the columns represent how much the instrument won or lost in % over the past four years. But what if I want to think of it as a small seasonal chart or price cycle. In other words, over those last four years on average when did the instrument see a bottom and when did it see a top. How do I do that?
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