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everget
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Add repo
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‎.gitignore

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# Logs
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logs
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*.log
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npm-debug.log*
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yarn-debug.log*
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yarn-error.log*
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# Runtime data
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pids
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*.pid
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*.seed
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*.pid.lock
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# Directory for instrumented libs generated by jscoverage/JSCover
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lib-cov
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# Coverage directory used by tools like istanbul
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coverage
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# nyc test coverage
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.nyc_output
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# Grunt intermediate storage (http://gruntjs.com/creating-plugins#storing-task-files)
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.grunt
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# Bower dependency directory (https://bower.io/)
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bower_components
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# node-waf configuration
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.lock-wscript
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# Compiled binary addons (https://nodejs.org/api/addons.html)
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build/Release
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# Dependency directories
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node_modules/
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jspm_packages/
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__docs__/
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# TypeScript v1 declaration files
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typings/
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# Optional npm cache directory
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*.log
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*.tgz
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.npm
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# Optional eslint cache
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.eslintcache
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# Optional REPL history
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.node_repl_history
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# Output of 'npm pack'
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*.tgz
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# Yarn Integrity file
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.yarn-integrity
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# dotenv environment variables file
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.env
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# next.js build output
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.next
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.idea
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.vscode
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.DS_Store

‎scripts/build.js

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‎scripts/updatePineScriptVersion.js

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‎src/channels/acceleration_bands.pine

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//@version=3
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// Copyright (c) 2018-present, Alex Orekhov (everget)
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// Acceleration Bands indicator script may be freely distributed under the MIT license.
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study(title="Acceleration Bands", shorttitle="ABANDS", overlay=true)
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length = input(title="Length", type=integer, defval=20)
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factor = input(title="Factor", type=float, defval=0.001, step=0.0001)
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src = input(title="Source", type=source, defval=close)
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mult = 4 * factor * 1000 * (high - low) / (high + low)
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upperBandSrc = high * (1 + mult)
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upperBand = sma(upperBandSrc, length)
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basis = sma(src, length)
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lowerBandSrc = low * (1 - mult)
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lowerBand = sma(lowerBandSrc, length)
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upperBandPlot = plot(upperBand, title="Upper", linewidth=1, color=#138484, transp=0)
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plot(basis, title="Basis", linewidth=1, color=#741b47, transp=0)
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lowerBandPlot = plot(lowerBand, title="Lower", linewidth=1, color=#138484, transp=0)
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fill(upperBandPlot, lowerBandPlot, title="Background", color=color(#ffd966, 84))

‎src/movings/adaptive_laguerre_filter.pine

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//@version=3
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// Copyright (c) 2018-present, Alex Orekhov (everget)
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// Adaptive Laguerre Filter indicator script may be freely distributed under the MIT license.
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study("Adaptive Laguerre Filter", shorttitle="ALF", overlay=true)
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length = input(title="Length", type=integer, defval=20, minval=1)
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medianLength = input(title="Median Length", type=integer, defval=5, minval=1)
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src = input(title="Source", type=source, defval=close)
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sort(src, i) =>
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min = -10000.0
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for j = 0 to i - 1
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min_local = 10000.0
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for l = 0 to medianLength - 1
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if (nz(src[l]) <= min)
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continue
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min_local := min(min_local, max(min, nz(src[l])))
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if min_local != 10000
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min := min_local
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min
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median(src, length) =>
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result = 0.0
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if length % 2 == 0
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result := (sort(src, length / 2) + sort(src, length / 2 + 1)) / 2
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else
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result := sort(src, ceil(length / 2))
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diff = 0.0
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HH = 0.0
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LL = 0.0
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alpha = 0.0
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L0 = 0.0
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L1 = 0.0
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L2 = 0.0
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L3 = 0.0
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alf = 0.0
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diff := abs(src - nz(alf[1]))
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HH := diff
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LL := diff
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for i = 0 to length - 1
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if nz(diff[i]) > HH
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HH := nz(diff[i])
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if nz(diff[i]) < LL
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LL := nz(diff[i])
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alpha := HH - LL != 0 ? median((diff - LL) / (HH - LL), medianLength) : nz(alpha[1])
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L0 := alpha * src + (1 - alpha) * nz(L0[1])
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L1 := -(1 - alpha) * L0 + nz(L0[1]) + (1 - alpha) * nz(L1[1])
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L2 := -(1 - alpha) * L1 + nz(L1[1]) + (1 - alpha) * nz(L2[1])
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L3 := -(1 - alpha) * L2 + nz(L2[1]) + (1 - alpha) * nz(L3[1])
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alf := (L0 + 2 * L1 + 2 * L2 + L3) / 6
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plot(alf, title="ALF", linewidth=2, color=#741b47, transp=0)

‎src/movings/adaptive_moving_average.pine

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//@version=3
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// Copyright (c) 2018-present, Alex Orekhov (everget)
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// Adaptive Moving Average indicator script may be freely distributed under the MIT license.
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study("Adaptive Moving Average", shorttitle="AMA", overlay=true)
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length = input(title="Length", type=integer, defval=14, minval=1)
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fastLength = input(title="Fast MA Length", type=integer, defval=2, minval=1)
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slowLength = input(title="Slow MA Length", type=integer, defval=30, minval=1)
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showKAMA = input(title="Show KAMA ?", type=bool, defval=true)
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src = input(title="Source", type=source, defval=close)
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kama(src, length, fastLength, slowLength) =>
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change = abs(nz(src[1]) - nz(src[length]))
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volatility = sum(abs(src - nz(src[1])), length)
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// Efficiency Ratio
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ER = iff(volatility != 0, change / volatility, 0)
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fastSC = 2 / (fastLength + 1)
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slowSC = 2 / (slowLength + 1)
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// Smoothing constant
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SC = pow((ER * (fastSC - slowSC)) + slowSC, 2)
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kama = 0.0
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kama := SC * src + (1 - SC) * nz(kama[1])
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ama(src, length, fastLength, slowLength) =>
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pds = length + 1
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fastSC = 2 / (fastLength + 1)
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slowSC = 2 / (slowLength + 1)
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MLTP = abs((src - lowest(low, pds)) - (highest(high, pds) - src)) / (highest(high, pds) - lowest(low, pds))
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SSC = MLTP * (fastSC - slowSC) + slowSC
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ama = 0.0
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ama := nz(ama[1]) + (SSC * SSC) * (src - nz(ama[1]))
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plot(showKAMA ? kama(src, length, fastLength, slowLength) : na, title="KAMA", linewidth=2, color=#e69138, transp=0)
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plot(ama(src, length, fastLength, slowLength), title="AMA", linewidth=2, color=#741b47, transp=0)

‎src/movings/adaptive_rsi.pine

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//@version=3
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// Copyright (c) 2018-present, Alex Orekhov (everget)
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// Adaptive RSI indicator script may be freely distributed under the MIT license.
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study(title="Adaptive RSI", shorttitle="ARSI", overlay=true)
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length = input(title="Length", type=integer, defval=14, minval=1)
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src = input(title="Source", type=source, defval=close)
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alpha = abs(rsi(src, length) / 100 - 0.5) * 2
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arsi = 0.0
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arsi := alpha * src + (1 - alpha) * nz(arsi[1])
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plot(arsi, title="ARSI", color=#741b47, linewidth=2, transp=0)

‎src/movings/ahrens_moving_average.pine

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//@version=3
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// Copyright (c) 2018-present, Alex Orekhov (everget)
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// Ahrens Moving Average indicator script may be freely distributed under the MIT license.
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study("Ahrens Moving Average", shorttitle="AhMA", overlay=true)
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length = input(title="Length", type=integer, defval=9, minval=1)
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src = input(title="Source", type=source, defval=close)
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ahma = 0.0
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ahma := nz(ahma[1]) + (src - (nz(ahma[1]) + nz(ahma[length])) / 2) / length
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plot(ahma, title="AhMA", linewidth=2, color=#6d1e7f, transp=0)

‎src/movings/moving_geometric_mean.pine

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//@version=3
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// Copyright (c) 2018-present, Alex Orekhov (everget)
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// Geometric Mean indicator script may be freely distributed under the MIT license.
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study("Geometric Mean", shorttitle="GM", overlay=true)
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length = input(title="Length", type=integer, defval=14, minval=1)
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src = input(title="Source", type=source, defval=close)
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// https://en.wikipedia.org/wiki/Nth_root_algorithm
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// https://en.wikipedia.org/wiki/Nth_root
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// http://www.calculator.net/root-calculator.html?cvar3=14&cvar4=5&ctype=3&x=77&y=23
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// https://www.rapidtables.com/calc/math/Root_Calculator.html
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// https://rosettacode.org/wiki/Nth_root#JavaScript
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precision = 0.00001
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nthRoot(value, degree) =>
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x0 = 1
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xk = ((degree - 1) * x0 + value / pow(x0, degree - 1)) / degree
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xkDelta = (value / (pow(x0, degree - 1)) - x0) / degree
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for i = 0 to 99999
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if abs(xkDelta) <= precision
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break
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xkDelta := (value / (pow(xk, degree - 1)) - xk) / degree
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xk := xk + xkDelta
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xk
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gm(src, length) =>
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prod = 1.0
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for i = 0 to length - 1
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prod := prod * (na(src[i]) ? 1 : src[i])
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nthRoot(prod, length)
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plot(gm(src, length), title="GM", linewidth=2, color=#6d1e7f, transp=0)

‎src/movings/moving_harmonic_mean.pine

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//@version=3
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// Copyright (c) 2018-present, Alex Orekhov (everget)
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// Harmonic Mean indicator script may be freely distributed under the MIT license.
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study("Harmonic Mean", shorttitle="HM", overlay=true)
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length = input(title="Length", type=integer, defval=14, minval=1)
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src = input(title="Source", type=source, defval=close)
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hm(src, length) =>
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sum = 0.0
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for i = 0 to length - 1
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sum := sum + 1 / (na(src[i]) ? 1 : src[i])
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length / sum
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plot(hm(src, length), title="HM", linewidth=2, color=#6d1e7f, transp=0)

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