OPEN-SOURCE SCRIPT

Stock Booster 2.0

// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org/MPL/2.0/
// © fluxchart

//version=5
const bool DEBUG = false
const int maxDistanceToLastBar = 5000
const int labelCooldown = 8
const int KDELimit = 300

indicator("Stock Booster", overlay = true, max_labels_count = 500)

rsiLengthInput = input.int(14, minval = 1, title="RSI Length", group="RSI Settings")
rsiSourceInput = input.source(close, "Source", group="RSI Settings")

highPivotLen = input.int(21, "High Pivot Length", minval = 1, group = "Pivots", display = display.none)
lowPivotLen = input.int(21, "Low Pivot Length", minval = 1, group = "Pivots", display = display.none)
realPivotLabels = DEBUG ? input.bool(false, "[DBG] Real Pivot Labels", group = "Pivots") : false
kdePivotLabels = DEBUG ? input.bool(false, "[DBG] KDE Pivot Labels", group = "Pivots") : false

activationThresholdStr = input.string("Medium", "Activation Threshold", options = ["High", "Medium", "Low"], group = "KDE", tooltip = "Determines the amount of arrows shown. Higher options will result in more arrows being rendered.")
string KDEKernel = input.string("Gaussian", "Kernel", options=['Uniform', 'Gaussian', 'Sigmoid'], group = "KDE", tooltip = "The kernel function for KDE calculation. Gaussian is a commonly used kernel and is based on normal distribution.")
float KDEBandwidth = input.float(2.71828, "Bandwidth", group = "KDE", tooltip = "This setting sets the smoothness of the KDE function output.")
int KDEStep = input.int(100, "Nº Bins", minval = 1, group = "KDE", tooltip = "The number of elements the KDE Probability array will have. Higher settings will result in greater precision.")
activationThreshold = DEBUG ? input.float(0.25, "[DBG] Activation Threshold", group = "KDE") : 0.25
if not DEBUG
activationThreshold := (activationThresholdStr == "High" ? 0.4 : activationThresholdStr == "Medium" ? 0.25 : 0.15)
probMode = DEBUG ? input.string("Sum", '[DBG] Probability Mode', options = ["Sum", "Nearest"], group = "KDE") : "Sum"
minPadding = DEBUG ? input.bool(false, '[DBG] KDE Min Padding', group = "KDE") : false

tableEnabled = input.bool(true, "Dashboard", group = "Dashboard", display = display.none)
tableLocation = input.string("Top Right", "Position", options = ["Top Right", "Top Center", "Right Center", "Middle Center", "Left Center", "Bottom Center"], group = "Dashboard", display = display.none)
screenerColor = input.color(#1B1F2B, 'Background', group = 'Dashboard', display = display.none)
frameColor = input.color(color.rgb(255, 255, 255), 'Frame', group = 'Dashboard', display = display.none)
borderColor = input.color(color.rgb(255, 255, 255), 'Border', group = 'Dashboard', display = display.none)
textColorDB = input.color(color.white, 'Text', group = 'Dashboard', display = display.none)
fillBackgrounds = input.bool(true, "Fill Backgrounds", group = "Dashboard", display = display.none)

bearishColor = input.color(#f23646, "High Pivots", group = "Style", inline = "col", display = display.none)
neutralColor = input.color(color.gray, "Neutral", group = "Style", inline = "col", display = display.none)
bullishColor = input.color(#089981, "Low Pivots", group = "Style", inline = "col", display = display.none)
textColor = input.color(color.white, 'Text', group = 'Style', inline = "col", display = display.none)
RSILabelsEnabled = input.bool(true, "RSI Labels", group = "Style")
KDELabelsEnabled = input.bool(true, "KDE Labels", group = "Style")

rsi = ta.rsi(rsiSourceInput, rsiLengthInput)

getPosition (positionText) =>
if positionText == "Top Right"
position.top_right
else if positionText == "Top Center"
position.top_center
else if positionText == "Right Center"
position.middle_right
else if positionText == "Left Center"
position.middle_left
else if positionText == "Bottom Center"
position.bottom_center
else if positionText == "Middle Center"
position.middle_center

//#region KDE
gaussian (float distance, float bandwidth = 1.0) => 1.0 / math.sqrt(2.0 * math.pi) * math.pow(math.e, -0.5 * math.pow(distance / bandwidth, 2.0))
uniform (float distance, float bandwidth = 1.0) => (math.abs(distance) > bandwidth) ? 0.0 : 0.5
sigmoid (float distance, float bandwidth = 1.0) => 2.0 / math.pi * (1.0 / (math.pow(math.e, (distance / bandwidth)) + math.pow(math.e, -(distance / bandwidth))))

kde (array<float> arr, string kernel, float bandwidth, int steps) =>
arrSize = arr.size()
arrRange = arr.range()
arrMin = arr.min() - (minPadding ? (arrRange / 2.0) : 0)
stepCount = arrRange / steps

densityRange = array.new<float>(steps * 2)
for i = 0 to (steps * 2) - 1
densityRange.set(i, arrMin + i * stepCount)

xArr = array.new<float>()
yArr = array.new<float>()
for i = 0 to densityRange.size() - 1
float temp = 0
for j = 0 to arr.size() - 1
switch KDEKernel
"Gaussian" => temp += gaussian(densityRange.get(i) - arr.get(j), 1.0 / bandwidth)
"Uniform" => temp += uniform(densityRange.get(i) - arr.get(j), 1.0 / bandwidth)
"Sigmoid" => temp += sigmoid(densityRange.get(i) - arr.get(j), 1.0 / bandwidth)

xArr.push(densityRange.get(i))
yArr.push(1.0 / arrSize * temp)
[xArr, yArr]
//#endregion

//#region Pivots

prefixSum (array<float> arr, int l, int r) =>
arr.get(r) - (l == 0 ? 0 : arr.get(l - 1))

float MidKDEHigh = na
float MidKDELow = na

var array<float> KDEHighX = na
var array<float> KDEHighY = na
var array<float> KDEHighYSum = array.new<float>()

var array<float> KDELowX = na
var array<float> KDELowY = na
var array<float> KDELowYSum = array.new<float>()

highPivot = ta.pivothigh(highPivotLen, highPivotLen)
lowPivot = ta.pivotlow(lowPivotLen, lowPivotLen)

var highPivotRSIs = array.new<float>()
var lowPivotRSIs = array.new<float>()

if not na(highPivot)
if highPivotRSIs.size() > KDELimit
highPivotRSIs.remove(0)
highPivotRSIs.push(rsi[highPivotLen])

[KDEHighX1, KDEHighY1] = kde(highPivotRSIs, KDEKernel, KDEBandwidth, KDEStep)
KDEHighX := KDEHighX1
KDEHighY := KDEHighY1

KDEHighYSum.clear()
temp = 0.0
for i = 0 to KDEHighY.size() - 1
temp += KDEHighY.get(i)
KDEHighYSum.push(temp)

MidKDEHigh := array.get(KDEHighX, array.indexof(KDEHighY, array.max(KDEHighY)))

if not na(lowPivot)
if lowPivotRSIs.size() > KDELimit
lowPivotRSIs.remove(0)
lowPivotRSIs.push(rsi[lowPivotLen])

[KDELowX1, KDELowY1] = kde(lowPivotRSIs, KDEKernel, KDEBandwidth, KDEStep)
KDELowX := KDELowX1
KDELowY := KDELowY1

KDELowYSum.clear()
temp = 0.0
for i = 0 to KDELowY.size() - 1
temp += KDELowY.get(i)
KDELowYSum.push(temp)

MidKDELow := array.get(KDELowX, array.indexof(KDELowY, array.max(KDELowY)))
//#endregion

//#region KDE Optimization
f_lin_interpolate(float x0, float x1, float y0, float y1, float x) =>
y0 + (x - x0) * (y1 - y0) / (x1 - x0)

float lowProb = na
float maxLowProb = na
float highProb = na
float maxHighProb = na

if last_bar_index - maxDistanceToLastBar < bar_index
if highPivotRSIs.size() > 0
highXIndexL = array.binary_search_leftmost(KDEHighX, rsi)
highXIndexR = math.min(array.binary_search_rightmost(KDEHighX, rsi), KDEHighX.size() - 1)
nearestIndex = (math.abs(rsi - KDEHighX.get(highXIndexL)) < math.abs(rsi - KDEHighX.get(highXIndexR))) ? highXIndexL : highXIndexR
if probMode == "Nearest"
highProb := KDEHighY.get(nearestIndex)
maxHighProb := array.max(KDEHighY)
else if probMode == "Sum"
highProb := prefixSum(KDEHighYSum, 0, nearestIndex)

if lowPivotRSIs.size() > 0
lowXIndexL = array.binary_search_leftmost(KDELowX, rsi)
lowXIndexR = math.min(array.binary_search_rightmost(KDELowX, rsi), KDELowX.size() - 1)
nearestIndex = (math.abs(rsi - KDELowX.get(lowXIndexL)) < math.abs(rsi - KDELowX.get(lowXIndexR))) ? lowXIndexL : lowXIndexR
if probMode == "Nearest"
lowProb := KDELowY.get(nearestIndex)
maxLowProb := array.max(KDELowY)
else if probMode == "Sum"
lowProb := prefixSum(KDELowYSum, nearestIndex, KDELowYSum.size() - 1)

if DEBUG and barstate.islastconfirmedhistory
for i = 0 to KDELowX.size() - 1
curX = KDELowX.get(i)
curY = KDELowY.get(i)
log.info(str.tostring(curX) + " = " + str.tostring(curY))
log.info("High Y Sum " + str.tostring(KDEHighY.sum()))

diffToHighKDE = math.abs(rsi - MidKDEHigh)
diffToLowKDE = math.abs(rsi - MidKDELow)
//#endregion

//#region Draw Pivots
color curColor = na
if (not na(KDELowY)) and (not na(KDEHighY))
if probMode == "Nearest"
if math.abs(lowProb - maxLowProb) < activationThreshold / 50.0
curColor := bullishColor
if math.abs(highProb - maxHighProb) < activationThreshold / 50.0
curColor := bearishColor
else if probMode == "Sum"
if lowProb > KDELowY.sum() * (1.0 - activationThreshold)
curColor := bullishColor
else if highProb > KDEHighY.sum() * (1.0 - activationThreshold)
curColor := bearishColor
//barcolor(curColor)

atr = ta.atr(50)

plotarrow(curColor == bullishColor and barstate.isconfirmed ? 1 : na, "Bullish Arrows", color.new(bullishColor, 70), color.new(bullishColor, 70), minheight = 20, maxheight = 20)
plotarrow(curColor == bearishColor and barstate.isconfirmed ? -1 : na, "Bearish Arrows", color.new(bearishColor, 70), color.new(bearishColor, 70), minheight = 20, maxheight = 20)

plotarrow((na(curColor) and curColor[1] == bullishColor and barstate.isconfirmed) ? 1 : na, "Possible Bullish Pivot", bullishColor, bullishColor, minheight = 20, maxheight = 20)
plotarrow((na(curColor) and curColor[1] == bearishColor and barstate.isconfirmed) ? -1 : na, "Possible Bearish Pivot", bearishColor, bearishColor, minheight = 20, maxheight = 20)

alertcondition(na(curColor) and curColor[1] == bullishColor and barstate.isconfirmed, "Possible Bullish Pivot")
alertcondition(na(curColor) and curColor[1] == bearishColor and barstate.isconfirmed, "Possible Bearish Pivot")

if KDELabelsEnabled or RSILabelsEnabled
var lastBullishLabel = 0
if (na(curColor) and curColor[1] == bullishColor and barstate.isconfirmed) and (bar_index - lastBullishLabel) > labelCooldown
lastBullishLabel := bar_index
txt = ""
if RSILabelsEnabled and KDELabelsEnabled
txt := "RSI | " + str.tostring(rsi, "#") + " | " + str.tostring(lowProb * 100, "#.##") + "%"
else if RSILabelsEnabled
txt := "RSI | " + str.tostring(rsi, "#")
else
txt := str.tostring(rsi, "#") + "%"
label.new(bar_index, low, txt, yloc = yloc.belowbar, color = na, style = label.style_label_up, textcolor = textColor, force_overlay = true)

var lastBearishLabel = 0
if (na(curColor) and curColor[1] == bearishColor and barstate.isconfirmed) and (bar_index - lastBearishLabel) > labelCooldown
lastBearishLabel := bar_index
txt = ""
if RSILabelsEnabled and KDELabelsEnabled
txt := "RSI | " + str.tostring(rsi, "#") + " | " + str.tostring(highProb * 100, "#.##") + "%"
else if RSILabelsEnabled
txt := "RSI | " + str.tostring(rsi, "#")
else
txt := str.tostring(rsi, "#") + "%"
label.new(bar_index, low, txt, yloc = yloc.abovebar, color = na, style = label.style_label_down, textcolor = textColor, force_overlay = true)

if kdePivotLabels
txt = str.tostring(rsi, "#.##") + "\nHP -> " + str.tostring(highProb, "#.##") + "\nLP -> " + str.tostring(lowProb, "#.##") + "\n\nMHP -> " + str.tostring(maxHighProb, "#.##") + "\nMLP -> " + str.tostring(maxLowProb, "#.##")
if math.abs(lowProb - maxLowProb) < activationThreshold
label.new(bar_index, high, txt, yloc = yloc.belowbar, color = textColor, style = label.style_label_up, textcolor = color.black, force_overlay = true)
if math.abs(highProb - maxHighProb) < activationThreshold
label.new(bar_index, high, txt, yloc = yloc.abovebar, color = textColor, style = label.style_label_down, textcolor = color.black, force_overlay = true)

if realPivotLabels
if not na(highPivot)
txt = str.tostring(rsi[highPivotLen], "#.##") + "\nHP -> " + str.tostring(highProb[highPivotLen], "#.##") + "\nLP -> " + str.tostring(lowProb[highPivotLen], "#.##") + "\n\nMHP -> " + str.tostring(maxHighProb[highPivotLen], "#.##") + "\nMLP -> " + str.tostring(maxLowProb[highPivotLen], "#.##")
label.new(bar_index - highPivotLen, high, txt, yloc = yloc.abovebar, color = textColor, style = label.style_label_down, textcolor = color.black, force_overlay = true)
if not na(lowPivot)
txt = str.tostring(rsi[lowPivotLen], "#.##") + "\nHP -> " + str.tostring(highProb[lowPivotLen], "#.##") + "\nLP -> " + str.tostring(lowProb[lowPivotLen], "#.##") + "\n\nMHP -> " + str.tostring(maxHighProb[lowPivotLen], "#.##") + "\nMLP -> " + str.tostring(maxLowProb[lowPivotLen], "#.##")
label.new(bar_index - lowPivotLen, high, txt, yloc = yloc.belowbar, color = textColor, style = label.style_label_up, textcolor = color.black, force_overlay = true)
//#endregion

if tableEnabled
var table realtimeTable = table.new(getPosition(tableLocation), 2, 10, bgcolor = screenerColor, frame_width = 2, frame_color = frameColor, border_width = 1, border_color = borderColor)
// Header
table.merge_cells(realtimeTable, 0, 0, 1, 0)
table.cell(realtimeTable, 0, 0, "KDE Optimized RSI", text_color = textColorDB, bgcolor = screenerColor)

// RSI
table.cell(realtimeTable, 0, 1, "RSI", text_color = textColorDB, bgcolor = screenerColor)
table.cell(realtimeTable, 1, 1, str.tostring(rsi, "#"), text_color = textColorDB, bgcolor = screenerColor)

// KDE
table.cell(realtimeTable, 0, 2, (lowProb > highProb) ? "Bullish KDE" : "Bearish KDE", text_color = (lowProb > highProb) ? bullishColor : bearishColor, bgcolor = screenerColor)
table.cell(realtimeTable, 1, 2, str.tostring(nz(math.max(highProb, lowProb), 0) * 100, "#.##") + "%", text_color = textColorDB, bgcolor = screenerColor)
Chart patternsCycles

Open-source script

In true TradingView spirit, the author of this script has published it open-source, so traders can understand and verify it. Cheers to the author! You may use it for free, but reuse of this code in publication is governed by House rules. You can favorite it to use it on a chart.

Want to use this script on a chart?

Disclaimer