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// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © loxx

//@version=5
indicator("Three-Pole Super Smoother w/ EMA-Deviation-Corrected Stepping [Loxx]", 
     shorttitle = "TPSSEMADCS [Loxx]", 
     overlay = true, 
     timeframe="", 
     timeframe_gaps = true)
     
import loxx/loxxexpandedsourcetypes/3

greencolor = #2DD204
redcolor = #D2042D 

_ssf3(src, length) =>
    arg = math.pi / length
    a1 = math.exp(-arg)
    b1 = 2 * a1 * math.cos(1.738 * arg)
    c1 = math.pow(a1, 2)
    coef4 = math.pow(c1, 2)
    coef3 = -(c1 + b1 * c1)
    coef2 = b1 + c1
    coef1 = 1 - coef2 - coef3 - coef4
    src1 = nz(src[1], src)
    src2 = nz(src[2], src1)
    src3 = nz(src[3], src2)
    ssf = 0.0
    ssf := coef1 * src + coef2 * nz(ssf[1], src1) + coef3 * nz(ssf[2], src2) + coef4 * nz(ssf[3], src3)
    ssf
    
_corEmaDev(avg, price, period)=>
    ema0 = 0., ema1 = 0., corr = 0.
    alpha = 2.0 / (1.0 + period)
    ema0 := ta.ema(price, period)
    ema1 := ta.ema(price*price, period)
    _deviation = math.max(math.sqrt(period * (ema1 - ema0 * ema0) / math.max(period - 1, 1)), 0.0)
    v1 = math.pow(_deviation, 2)
    v2 = math.pow(nz(corr[1]) - avg, 2) 
    c = (v2 < v1 or v2 == 0) ? 0 : 1 - v1 / v2
    corr := nz(corr[1]) + c * (avg - nz(corr[1]))
    corr

smthtype = input.string("Kaufman", "Heiken-Ashi Better Smoothing", options = ["AMA", "T3", "Kaufman"], group=  "Source Settings")

srcoption = input.string("Close", "Source", group= "Source Settings", 
     options = 
     ["Close", "Open", "High", "Low", "Median", "Typical", "Weighted", "Average", "Average Median Body", "Trend Biased", "Trend Biased (Extreme)", 
     "HA Close", "HA Open", "HA High", "HA Low", "HA Median", "HA Typical", "HA Weighted", "HA Average", "HA Average Median Body", "HA Trend Biased", "HA Trend Biased (Extreme)",
     "HAB Close", "HAB Open", "HAB High", "HAB Low", "HAB Median", "HAB Typical", "HAB Weighted", "HAB Average", "HAB Average Median Body", "HAB Trend Biased", "HAB Trend Biased (Extreme)"])

per = input.int(14, "Period", group= "Basic Settings")
colorbars = input.bool(false, "Color bars?", group= "UI Options")

kfl=input.float(0.666, title="* Kaufman's Adaptive MA (KAMA) Only - Fast End", group = "Moving Average Inputs")
ksl=input.float(0.0645, title="* Kaufman's Adaptive MA (KAMA) Only - Slow End", group = "Moving Average Inputs")
amafl = input.int(2, title="* Adaptive Moving Average (AMA) Only - Fast", group = "Moving Average Inputs")
amasl = input.int(30, title="* Adaptive Moving Average (AMA) Only - Slow", group = "Moving Average Inputs")

haclose = request.security(ticker.heikinashi(syminfo.tickerid), timeframe.period, close)
haopen = request.security(ticker.heikinashi(syminfo.tickerid), timeframe.period, open)
hahigh = request.security(ticker.heikinashi(syminfo.tickerid), timeframe.period, high)
halow = request.security(ticker.heikinashi(syminfo.tickerid), timeframe.period, low)
hamedian = request.security(ticker.heikinashi(syminfo.tickerid), timeframe.period, hl2)
hatypical = request.security(ticker.heikinashi(syminfo.tickerid), timeframe.period, hlc3)
haweighted = request.security(ticker.heikinashi(syminfo.tickerid), timeframe.period, hlcc4)
haaverage = request.security(ticker.heikinashi(syminfo.tickerid), timeframe.period, ohlc4)


float src = switch srcoption
	"Close" => loxxexpandedsourcetypes.rclose()
	"Open" => loxxexpandedsourcetypes.ropen()
	"High" => loxxexpandedsourcetypes.rhigh()
	"Low" => loxxexpandedsourcetypes.rlow()
	"Median" => loxxexpandedsourcetypes.rmedian()
	"Typical" => loxxexpandedsourcetypes.rtypical()
	"Weighted" => loxxexpandedsourcetypes.rweighted()
	"Average" => loxxexpandedsourcetypes.raverage()
    "Average Median Body" => loxxexpandedsourcetypes.ravemedbody()
	"Trend Biased" => loxxexpandedsourcetypes.rtrendb()
	"Trend Biased (Extreme)" => loxxexpandedsourcetypes.rtrendbext()
	"HA Close" => loxxexpandedsourcetypes.haclose(haclose)
	"HA Open" => loxxexpandedsourcetypes.haopen(haopen)
	"HA High" => loxxexpandedsourcetypes.hahigh(hahigh)
	"HA Low" => loxxexpandedsourcetypes.halow(halow)
	"HA Median" => loxxexpandedsourcetypes.hamedian(hamedian)
	"HA Typical" => loxxexpandedsourcetypes.hatypical(hatypical)
	"HA Weighted" => loxxexpandedsourcetypes.haweighted(haweighted)
	"HA Average" => loxxexpandedsourcetypes.haaverage(haaverage)
    "HA Average Median Body" => loxxexpandedsourcetypes.haavemedbody(haclose, haopen)
	"HA Trend Biased" => loxxexpandedsourcetypes.hatrendb(haclose, haopen, hahigh, halow)
	"HA Trend Biased (Extreme)" => loxxexpandedsourcetypes.hatrendbext(haclose, haopen, hahigh, halow)
	"HAB Close" => loxxexpandedsourcetypes.habclose(smthtype, amafl, amasl, kfl, ksl)
	"HAB Open" => loxxexpandedsourcetypes.habopen(smthtype, amafl, amasl, kfl, ksl)
	"HAB High" => loxxexpandedsourcetypes.habhigh(smthtype, amafl, amasl, kfl, ksl)
	"HAB Low" => loxxexpandedsourcetypes.hablow(smthtype, amafl, amasl, kfl, ksl)
	"HAB Median" => loxxexpandedsourcetypes.habmedian(smthtype, amafl, amasl, kfl, ksl)
	"HAB Typical" => loxxexpandedsourcetypes.habtypical(smthtype, amafl, amasl, kfl, ksl)
	"HAB Weighted" => loxxexpandedsourcetypes.habweighted(smthtype, amafl, amasl, kfl, ksl)
	"HAB Average" => loxxexpandedsourcetypes.habaverage(smthtype, amafl, amasl, kfl, ksl)
    "HAB Average Median Body" => loxxexpandedsourcetypes.habavemedbody(smthtype, amafl, amasl, kfl, ksl)
	"HAB Trend Biased" => loxxexpandedsourcetypes.habtrendb(smthtype, amafl, amasl, kfl, ksl)
	"HAB Trend Biased (Extreme)" => loxxexpandedsourcetypes.habtrendbext(smthtype, amafl, amasl, kfl, ksl)
	=> haclose

avg2 = _ssf3(src, per)
val = _corEmaDev(avg2, src, per)

goLong_pre = ta.crossover(val, val[1])
goShort_pre = ta.crossunder(val, val[1])

contSwitch = 0
contSwitch := nz(contSwitch[1])
contSwitch := goLong_pre ? 1 : goShort_pre ? -1 : contSwitch

goLong = goLong_pre and ta.change(contSwitch)
goShort = goShort_pre and ta.change(contSwitch)

plot(val,"Corrected super smoother", color = contSwitch == 1  ? greencolor : redcolor, linewidth = 3)

barcolor(colorbars ? contSwitch == 1 ? greencolor : redcolor : na)

Code: Select all

//@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)