STD-Filtered N-Pole Gaussian Fil…: Free TradingView Indicator (Pine Script)

Add It to Your TradingView Chart

1Copy the scriptPress Copy script above, or the copy button on the code below.
2Open the Pine EditorOpen a TradingView chart and choose Pine Editor at the bottom of the screen.
3Paste over the templateCreate a new indicator, select all of the template text and paste. Press Save and give it a name.
4Add it to the chartPress Add to chart, then adjust the settings with the gear icon next to its name.

Source Code

152 lines of Pine Script v5 from Standard Deviation Filtering.txt, published under MPL-2.0 (file header). Keep the author's credit and licence lines when you reuse it.

Standard Deviation Filtering.txt

// 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("STD-Filtered,N-Pole Gaussian Filter [Loxx]",
     shorttitle="STDFNPGF [Loxx]",
     overlay = true)
     
import loxx/loxxexpandedsourcetypes/4

greencolor = #2DD204  
redcolor = #D2042D 

//factorial calc
fact(int n)=>
    float a = 1
    for i = 1 to n 
        a *= i
    a

//alpha calc
_alpha(int period, int poles)=>
    w = 2.0 * math.pi / period
    float b = (1.0 - math.cos(w)) / (math.pow(1.414, 2.0 / poles) - 1.0)
    float a = - b + math.sqrt(b * b + 2.0 * b)
    a
    
//n-pole calc
_npolegf(float src, int period, int order)=>
    coeffs = matrix.new<float>(order + 1, 3, 0.)
    float a = _alpha(period, order)
    for r = 0 to order 
        out = nz(fact(order) / (fact(order - r) * fact(r)), 1)
        matrix.set(coeffs, r, 0, out)
        matrix.set(coeffs, r, 1, math.pow(a, r))
        matrix.set(coeffs, r, 2, math.pow(1.0 - a, r))
    float filt = src * matrix.get(coeffs, order, 1)
    int sign = 1
    for r = 1 to order 
        filt += sign * matrix.get(coeffs, r, 0) * matrix.get(coeffs, r, 2) * nz(filt[r])
        sign *= -1
    filt

//std filter
_filt(float src, int len, float filter)=>
    float price = src
    float filtdev = filter * ta.stdev(src, len)
    price := math.abs(price - price[1]) < filtdev ? price[1] : price
    price
    
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)"])

period = input.int(25,'Period', group = "Basic Settings")
order = input.int(5,'Order', group = "Basic Settings", minval = 1)

filterop = input.string("Gaussian Filter", "Filter Options", options = ["Price", "Gaussian Filter", "Both", "None"], group=  "Filter Settings")
filter = input.float(1, "Filter Devaitions", minval = 0, group= "Filter Settings")
filterperiod = input.int(10, "Filter Period", minval = 0, group= "Filter Settings")

colorbars = input.bool(true, "Color bars?", group = "UI Options")
showSigs = input.bool(true, "Show signals?", 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

src := filterop == "Both" or filterop == "Price" and filter > 0 ? _filt(src, filterperiod, filter) : src

out = _npolegf(src, period, order)

out := filterop == "Both" or filterop == "Gaussian Filter" and filter > 0 ? _filt(out, filterperiod, filter) : out

sig = nz(out[1])

state = 0
if (out > sig) 
    state := 1
if (out < sig) 
    state := -1

pregoLong = out > sig and (nz(out[1]) < nz(sig[1]) or nz(out[1]) == nz(sig[1]))
pregoShort = out < sig and (nz(out[1]) > nz(sig[1]) or nz(out[1]) == nz(sig[1]))

contsw = 0
contsw := nz(contsw[1])
contsw := pregoLong ? 1 : pregoShort ? -1 : nz(contsw[1])

goLong = pregoLong and nz(contsw[1]) == -1
goShort = pregoShort and nz(contsw[1]) == 1 

var color colorout = na
colorout := state == -1 ? redcolor : state == 1 ? greencolor : nz(colorout[1])

plot(out, "N-Pole GF", color = colorout, linewidth = 3)
barcolor(colorbars ? colorout : na)

plotshape(showSigs and goLong, title = "Long", color = color.yellow, textcolor = color.yellow, text = "L", style = shape.triangleup, location = location.belowbar, size = size.tiny)
plotshape(showSigs and goShort, title = "Short", color = color.fuchsia, textcolor = color.fuchsia, text = "S", style = shape.triangledown, location = location.abovebar, size = size.tiny)

alertcondition(goLong, title = "Long", message = "STD-Filtered, N-Pole Gaussian Filter [Loxx]: Long\nSymbol: {{ticker}}\nPrice: {{close}}")
alertcondition(goShort, title = "Short", message = "STD-Filtered, N-Pole Gaussian Filter [Loxx]: Short\nSymbol: {{ticker}}\nPrice: {{close}}")

Overview

Sources include regular prices and several Heiken Ashi variants, and Heiken Ashi smoothing can use AMA, T3 or Kaufman averages. The filter period and number of poles are adjustable, and the filter can be applied to price, to the Gaussian output, to both, or to neither. Bars can be colored and signals shown. It uses a Heiken Ashi request for some sources.

N-pole Gaussian filter with adjustable order
Standard deviation filter on price or output
Heiken Ashi source variants
Optional bar coloring and signal markers

Details

Published by

rajatjpatel on GitHub

Code credit

loxx, as written in the script's header

Type

Indicator, Pine Script v5

Draws

On the price chart

Markets

Any symbol

Timeframes

Any timeframe

Risk Notes

No repainting, lookahead or stacked entries were found in its code or README. That says nothing about how well it works: test it first.

File

Standard Deviation Filtering.txt

Repository

github.com/rajatjpatel/pine. See its other scripts in the library

Settings

The inputs you can change from the gear icon on the chart. Defaults are the author's.

Setting	Type	Default	Variable
Heiken-Ashi Better Smoothing	`string`	`Kaufman`	`smthtype`
Source	`string`	`Close`	`srcoption`
Period	`int`	`25`	`period`
Order	`int`	`5`	`order`
Filter Options	`string`	`Gaussian Filter`	`filterop`
Filter Devaitions	`float`	`1`	`filter`
Filter Period	`int`	`10`	`filterperiod`
Color bars?	`bool`	`true`	`colorbars`
Show signals?	`bool`	`true`	`showSigs`
* Kaufman's Adaptive MA (KAMA) Only - Fast End	`float`	`0.666`	`kfl`
* Kaufman's Adaptive MA (KAMA) Only - Slow End	`float`	`0.0645`	`ksl`
* Adaptive Moving Average (AMA) Only - Fast	`int`	`2`	`amafl`

Show all 13 settings

Setting	Type	Default	Variable
* Adaptive Moving Average (AMA) Only - Slow	`int`	`30`	`amasl`

Third-party code. ForexR did not write, test or endorse this script, and the summary above was generated automatically from its code and README. Indicators describe the past, and a strategy's backtest can look better than live trading, especially when a script repaints. Check it in the Strategy Tester and on a demo account before you rely on it.

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