Voici le code, si qq’un veut essayer de le traduire [merci]
//@version=4
// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © RedKTrader
study(“Comp_Ratio_MA”, shorttitle = “CoRa Wave”, overlay = true, resolution =””)
// ======================================================================
// Compound Ratio Weight MA function
// Compound Ratio Weight is where the weight increases in a “logarithmicly linear” way (i.e., linear when plotted on a log chart) – similar to compound ratio
// the “step ratio” between weights is consistent – that’s not the case with linear-weight moving average (WMA), or EMA
// another advantage is we can significantly reduce the “tail weight” – which is “relatively” large in other MAs and contributes to lag
//
// Compound Weight ratio r = (A/P)^1/t – 1
// Weight at time t A = P(1 + r)^t
// = Start_val * (1 + r) ^ index
// Note: index is 0 at the furthest point back — num periods = length -1
//
f_adj_crwma(source, length, Start_Wt, r_multi) =>
numerator = 0.0, denom = 0.0, c_weight = 0.0
//Start_Wt = 1.0 // Start Wight is an input in this version – can also be set to a basic value here.
End_Wt = length // use length as initial End Weight to calculate base “r”
r = pow((End_Wt / Start_Wt),(1 / (length – 1))) – 1
base = 1 + r * r_multi
for i = 0 to length -1
c_weight := Start_Wt * pow(base,(length – i))
numerator := numerator + source[i] * c_weight
denom := denom + c_weight
numerator / denom
// ====================================================================== ==
data = input(title = “Source”, type = input.source, defval = hlc3)
length = input(title = “length”, type = input.integer, defval = 20, minval = 1)
r_multi = input(title = “Comp Ratio Multiplier”, type = input.float, defval = 2.0, minval = 0, step = .1)
smooth = input(title = “Auto Smoothing”, type = input.bool, defval = true, group = “Smoothing”)
man_smooth = input(title = “Manual Smoothing”, type = input.integer, defval = 1, minval = 1, step = 1, group = “Smoothing”)
s = smooth ? max(round(sqrt(length)),1) : man_smooth
cora_raw = f_adj_crwma(data, length, 0.01, r_multi)
cora_wave = wma(cora_raw, s)
c_up = color.new(color.aqua, 0)
c_dn = color.new(#FF9800 , 0)
cora_up = cora_wave > cora_wave[1]
plot(cora_wave, title=”Adjustible CoRa_Wave”, color = cora_up ? c_up : c_dn, linewidth = 3)
.
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