Hello Pine//@version=6
indicator("Barcolor Test v6", overlay=true)
fastMA = ta.sma(close, 50)
slowMA = ta.sma(close, 200)
buySignal = ta.crossover(fastMA, slowMA)
sellSignal = ta.crossunder(fastMA, slowMA)
barcolor(buySignal ? color.new(color.green, 0) : sellSignal ? color.new(color.red, 0) : color.na)
Indikatoren und Strategien
52WH/last52WH/ATH/lastATHThis indicator determines and displays four values:
First, it determines the current 52-week high and displays it as a line and in a table at the top right with the name, date, and price.
Corresponding color markings are also displayed on the price scale.
Next, the 52-week high that is at least three months ago is determined.
The corresponding candle is also labeled with a date. This past high is also displayed as a line, on the price scale, and in the table.
Next, the current all-time high is determined and also displayed as a line, on the price scale, and in the table.
Finally, the current all-time high that was valid 3 months ago is determined and also displayed as a line, in the price scale, and in the table.
All display values can be switched on or off in the view, and the corresponding colors of the displays can also be freely selected.
Pin Bar_EMA34_kidumon
This indicator is pin bar with legs at ema34 which helps us catch order reversal trend.
Pin Bar_ EMA34 _kidumonPin Bar touches EMA34 - kidumon
pin bar candlestick reaction at ema34 shows strong rejection force, can catch reversal trend.
Fish OrbThis indicator marks and tracks the first 15-minute range of the New York session open (default 9:30–9:45 AM ET) — a critical volatility period for futures like NQ (Nasdaq).
It helps you visually anchor intraday price action to that initial opening range.
Core Functionality
1. Opening Range Calculation
It measures the High, Low, and Midpoint of the first 15 minutes after the NY market opens (default 09:30–09:45 ET).
You can change the window or timezone in the inputs.
2. Visual Overlays
During the 15-minute window:
A teal shaded box highlights the open range period.
Live white lines mark the current High and Low.
A red line marks the midpoint (mid-range).
These update in real-time as each bar forms.
3. Post-Window Behavior
When the 15-minute window ends:
The High, Low, and Midpoint are locked in.
The indicator draws persistent horizontal lines for those values.
4. Historical Days
You can keep today + a set number of previous days (configurable via “Previous Days to Keep”).
Older days automatically delete to keep charts clean.
5. Line Extension Control
Each day’s lines extend to the right after they form.
You can toggle “Stop Lines at Next NY Open”:
ON: Yesterday’s lines stop exactly at the next NY session open (09:30 ET).
OFF: Lines extend indefinitely across the chart.
SGM Gold Day Trading EMAsWhat it does
This tool plots four Exponential Moving Averages (EMAs) with practical default periods for gold intraday analysis: 9 (Momentum), 21 (Pullback), 50 (Trend Filter), and 200 (Macro). The goal is to provide a clear, multi-horizon structure so traders can quickly assess momentum, pullbacks, intermediate trend, and long-term bias on the same chart.
How it works (method)
Each line is a standard EMA computed on the close price.
The defaults map to common roles:
EMA 9 – Momentum: immediate changes in short-term flow.
EMA 21 – Pullback: typical retracement area within ongoing trends.
EMA 50 – Trend Filter: medium-term confirmation of direction.
EMA 200 – Macro: long-term bias and market context.
Optional dynamic color for EMA9/EMA21 highlights whether EMA9 ≥ EMA21 (green) or not (red). This is a visual aid only; it does not generate signals.
Originality & usefulness
The script focuses on clarity and control rather than automation. It combines a neutral, high-contrast palette with independent line thickness per EMA and an optional visual crossover mode. The configuration encourages disciplined analysis across time horizons without embedding opaque entry/exit logic.
Inputs & customization:
Periods: 9, 21, 50, 200 (all adjustable).
Colors: fully customizable for each EMA; optional crossover color mode for 9/21.
Line thickness: set individually per EMA to emphasize your primary reference.
How to use:
Add the script on any timeframe/asset (gold defaults are provided but not required).
Use EMA 200 for long-term bias; trade with caution against it.
Use EMA 50 to filter intermediate trend; prefer setups aligned with it.
Watch EMA 21 as a pullback reference within trends.
Use EMA 9 to gauge momentum around pullbacks/breakouts.
(Optional) Enable the crossover color to quickly see when momentum (9) is above/below pullback (21).
Notes & limitations:
This script does not produce buy/sell signals or alerts.
It is intended as a visual framework to support analysis and risk management.
Always validate with your own rules, risk controls, and market conditions.
RTACoreLibrary "RTACore"
Advanced multi-timeframe technical analysis framework for Pine Script
@author WavesUnchained
@build 2025-10-14 22:41:47
newFloatResult(value, context)
Create a successful Result with float value
Parameters:
value (float)
context (string)
newStringResult(value, context)
Create a successful Result with string value
Parameters:
value (string)
context (string)
newBoolResult(value, context)
Create a successful Result with boolean value
Parameters:
value (bool)
context (string)
newErrorResult(errorCode, errorMessage, floatFallback, stringFallback, boolFallback, context)
Create an error Result with fallback values
Parameters:
errorCode (string)
errorMessage (string)
floatFallback (float)
stringFallback (string)
boolFallback (bool)
context (string)
addResultTag(result, tag)
Add a tag to Result
Parameters:
result (Result)
tag (string)
newSignalResult(signalStrength, signalType)
Create a signal Result with trading-specific tags
Parameters:
signalStrength (float)
signalType (string)
newIndicatorResult(value, indicatorName)
Create an indicator calculation Result with indicator tag
Parameters:
value (float)
indicatorName (string)
newTimeframeResult(value, timeframe, context)
Create a timeframe-specific Result
Parameters:
value (float)
timeframe (string)
context (string)
newConfluenceResult(confluenceScore, confidenceLevel)
Create a confluence Result with confidence level
Parameters:
confluenceScore (float)
confidenceLevel (string)
newValidationResult(context)
Create a new validation result (starts as valid)
Parameters:
context (string)
newValidationSuccess(context)
Create a successful validation result
Parameters:
context (string)
newValidationFailure(errors, context)
Create a failed validation result with errors
Parameters:
errors (array)
context (string)
addValidationError(result, field, error)
Add an error to validation result
Parameters:
result (ValidationResult)
field (string)
error (string)
addValidationWarning(result, field, warning)
Add a warning to validation result
Parameters:
result (ValidationResult)
field (string)
warning (string)
addValidationCorrection(result, correction)
Add a correction to validation result
Parameters:
result (ValidationResult)
correction (string)
setValidationMode(result, mode)
Set validation mode
Parameters:
result (ValidationResult)
mode (string)
getValidationMode(result)
Get validation mode
Parameters:
result (ValidationResult)
incrementValidatedFields(result)
Increment validated fields counter
Parameters:
result (ValidationResult)
setValidationTotalFields(result, total)
Set total fields for validation
Parameters:
result (ValidationResult)
total (int)
calculateValidationScore(result)
Calculate and update validation score based on errors/warnings
Parameters:
result (ValidationResult)
newPerformanceProfile(functionName)
Create a new performance profile
Parameters:
functionName (string)
startTiming(profile)
Start timing a performance profile (simple)
Parameters:
profile (PerformanceProfile)
endTiming(profile, hadError)
End timing and update performance profile
Parameters:
profile (PerformanceProfile)
hadError (bool)
updateMemoryEstimate(profile, arrayElements)
Set estimated memory usage (array elements)
Parameters:
profile (PerformanceProfile)
arrayElements (int)
newHealthyStatus()
Create a new healthy status
setComponentHealth(status, component, isOK, message)
Set component health status
Parameters:
status (HealthStatus)
component (string)
isOK (bool)
message (string)
isHealthyOverall(status)
Quick health check - are all components OK?
Parameters:
status (HealthStatus)
getHealthSummary(status)
Get simple health summary
Parameters:
status (HealthStatus)
hasValidFloat(result)
Check if Result contains a valid float value
Parameters:
result (Result)
hasValidString(result)
Check if Result contains a valid string value
Parameters:
result (Result)
getFloat(result, fallback)
Get float value from Result with fallback
Parameters:
result (Result)
fallback (float)
getString(result, fallback)
Get string value from Result with fallback
Parameters:
result (Result)
fallback (string)
getBool(result, fallback)
Get boolean value from Result with fallback
Parameters:
result (Result)
fallback (bool)
hasResultTag(result, tag)
Check if Result has specific tag
Parameters:
result (Result)
tag (string)
getResultTags(result)
Get all tags from Result
Parameters:
result (Result)
setResultContext(result, context)
Set operation context for Result
Parameters:
result (Result)
context (string)
filterResultsByTag(results, tag)
Filter Results by tag (utility for arrays of Results)
Parameters:
results (array)
tag (string)
getAllResultTags(results)
Get all unique tags from array of Results
Parameters:
results (array)
newDefaultAnalysisConfig()
Create default analysis configuration
newAggressiveAnalysisConfig()
Create aggressive trading configuration
newConservativeAnalysisConfig()
Create conservative trading configuration
newDefaultTimeframeConfig()
Create default timeframe configuration
newIntradayTimeframeConfig()
Create intraday timeframe configuration
newSwingTimeframeConfig()
Create swing trading timeframe configuration
getConfigSummary(config)
Get configuration summary string
Parameters:
config (AnalysisConfig)
cloneAnalysisConfig(source)
Clone analysis configuration
Parameters:
source (AnalysisConfig)
newGenericAnalysis(analysisType, timeframe)
Create a new generic analysis result
Parameters:
analysisType (string)
timeframe (string)
newConsensusData()
Create empty consensus data
newNeutralSignal(reason)
Create a neutral signal result
Parameters:
reason (string)
newBuySignal(score, confidence, reason)
Create a buy signal result
Parameters:
score (float)
confidence (float)
reason (string)
newSellSignal(score, confidence, reason)
Create a sell signal result
Parameters:
score (float)
confidence (float)
reason (string)
newMultiTimeframeResult(config, tfConfig)
Create new multi-timeframe result
Parameters:
config (AnalysisConfig)
tfConfig (TimeframeConfig)
getAnalysisAction(analysis)
Get analysis action string
Parameters:
analysis (GenericAnalysis)
isBullish(analysis)
Check if analysis is bullish
Parameters:
analysis (GenericAnalysis)
isBearish(analysis)
Check if analysis is bearish
Parameters:
analysis (GenericAnalysis)
getSignalSummary(signal)
Get signal summary string
Parameters:
signal (SignalResult)
hasStrongConsensus(consensus)
Check if consensus is strong
Parameters:
consensus (ConsensusData)
getConsensusSummary(consensus)
Get consensus summary
Parameters:
consensus (ConsensusData)
isActionableSignal(signal)
Check if signal is actionable
Parameters:
signal (SignalResult)
getSignalColor(signal)
Get signal color for UI display
Parameters:
signal (SignalResult)
validateAnalysisConfig(config)
Validate analysis configuration
Parameters:
config (AnalysisConfig)
validateTimeframeConfig(config)
Validate timeframe configuration
Parameters:
config (TimeframeConfig)
validatePriceData(prices)
Validate price data array
Parameters:
prices (array)
sanitizeFloat(value, minVal, maxVal, defaultVal)
Sanitize numeric input
Parameters:
value (float)
minVal (float)
maxVal (float)
defaultVal (float)
sanitizeInt(value, minVal, maxVal, defaultVal)
Sanitize integer input
Parameters:
value (int)
minVal (int)
maxVal (int)
defaultVal (int)
sanitizeFloatArray(arr)
Sanitize array by removing invalid values
Parameters:
arr (array)
logError(message)
Log error message
Parameters:
message (string)
logWarning(message)
Log warning message
Parameters:
message (string)
safeExecute(operationName, condition)
Safe execute wrapper
Parameters:
operationName (string)
condition (bool)
shouldAllowOperation(errorCount, maxErrors)
Circuit breaker pattern
Parameters:
errorCount (int)
maxErrors (int)
retryOperation(maxRetries)
Retry mechanism
Parameters:
maxRetries (int)
atrDistance(value1, value2, atr)
Calculate ATR-normalized distance between two values
Parameters:
value1 (float)
value2 (float)
atr (float)
atrDistance(value, reference, atrLength)
Calculate ATR-normalized distance between values
Parameters:
value (float)
reference (float)
atrLength (simple int)
percentDistance(value1, value2)
Calculate percentage-based distance between two values
Parameters:
value1 (float)
value2 (float)
withinATRTolerance(value, reference, atr, multiplier)
Check if value is within ATR-based tolerance of reference
Parameters:
value (float)
reference (float)
atr (float)
multiplier (float)
withinATRTolerance(value, reference, multiplier)
Check if value is within ATR-based tolerance of reference
Parameters:
value (float)
reference (float)
multiplier (float)
withinPercentTolerance(value, reference, percentTolerance)
Check if value is within percentage tolerance of reference
Parameters:
value (float)
reference (float)
percentTolerance (float)
proximityScore(value, reference, maxDistance)
Get proximity score (0-1, where 1 = very close)
Parameters:
value (float)
reference (float)
maxDistance (float)
sortArrayByValue(values, sortOrder)
Efficient array sorting using Pine Script native sort
Note: Replaces inefficient bubble sort implementations found in modules
Parameters:
values (array)
sortOrder (string)
safeArrayAverage(values)
Safe array average with null handling
Parameters:
values (array)
formatTableHeader(title, width)
Create formatted header for display tables
Parameters:
title (string)
width (int)
formatTableRow(key, value, width)
Format table row with key-value pair
Parameters:
key (string)
value (string)
width (int)
formatTableFooter(width)
Close table formatting
Parameters:
width (int)
truncateText(txt, maxLength, suffix)
Truncate text to specified length
Parameters:
txt (string)
maxLength (int)
suffix (string)
padText(txt, width, padChar, align)
Pad text to specified width
Parameters:
txt (string)
width (int)
padChar (string)
align (string)
titleCase(txt)
Convert text to title case
Parameters:
txt (string)
joinStrings(strings, separator)
Join array of strings with separator
Parameters:
strings (array)
separator (string)
formatTimestamp(timestamp, format)
Format timestamp to readable date/time
Parameters:
timestamp (int)
format (string)
evictLRU(cache)
Evict least recently used entry
Parameters:
cache (CacheManager)
newRiskAssessment()
Create a default risk assessment
calculateRiskAssessment(signal, volatility, volumeLevel)
Calculate comprehensive risk assessment
Parameters:
signal (SignalResult)
volatility (float)
volumeLevel (float)
newPositionData()
Create new empty position data
getConservativeStrategy()
Create conservative strategy template
getAggressiveStrategy()
Create aggressive strategy template
newDefaultStrategy()
Create default balanced strategy template
getStandardATR()
Get standard ATR(14) - cached per bar
getATR(length)
Get custom ATR with specified length
Parameters:
length (simple int)
getATRTolerance(multiplier)
Get ATR-based tolerance for distance calculations
Parameters:
multiplier (float)
getStandardVolumeAverage()
Get standard volume average SMA(20) - cached per bar
getVolumeAverage(length)
Get custom volume average
Parameters:
length (int)
getVolumeRatio()
Get volume ratio (current vs average)
getVolumeConfirmation(threshold)
Get volume confirmation (above threshold)
Parameters:
threshold (float)
getStandardEMAs()
Get standard EMAs (21, 50, 200) - cached per bar
getEMA21()
Get individual standard EMAs
getEMA50()
getEMA200()
getEMATrendAlignment()
Get EMA trend alignment score
getStandardRSI()
Get standard RSI(14) - cached per bar
getRSILevels(overbought, oversold)
Get RSI with overbought/oversold levels
Parameters:
overbought (float)
oversold (float)
getStandardMACD()
Get standard MACD (12, 26, 9) - cached per bar
getMACDSignal()
Get MACD trend signal
getMomentumScore()
Get comprehensive momentum score
getTrendStrength()
Get trend strength (0-100)
getIndicatorSummary()
Get indicator calculation summary (for debugging)
newZoneDetectionConfig()
Create default zone configuration
newZoneDetection(upperBoundary, lowerBoundary, creationBar, zoneType)
Create new zone
Parameters:
upperBoundary (float)
lowerBoundary (float)
creationBar (int)
zoneType (string)
calculateZoneOverlap(zone1Upper, zone1Lower, zone2Upper, zone2Lower)
Calculate zone overlap ratio
Parameters:
zone1Upper (float)
zone1Lower (float)
zone2Upper (float)
zone2Lower (float)
isPriceTouchingZone(zone, currentPrice, touchTolerance)
Check if price is touching zone
Parameters:
zone (ZoneDetection)
currentPrice (float)
touchTolerance (float)
getZonesInRange(zones, minPrice, maxPrice)
Get zones within price range
Parameters:
zones (array)
minPrice (float)
maxPrice (float)
getNearestZones(zones, currentPrice)
Get nearest support and resistance zones
Parameters:
zones (array)
currentPrice (float)
processZoneDetection(zones, config)
Complete zone detection and management system
Parameters:
zones (array)
config (ZoneDetectionConfig)
processZoneDetectionEngine(zones, config)
Parameters:
zones (array)
config (ZoneDetectionConfig)
newChannelConfig()
calcKeltnerChannel(config)
Parameters:
config (ChannelConfig)
checkKeltnerTouch(upper, lower)
Parameters:
upper (float)
lower (float)
getKeltnerDepth(basis, upper, lower)
Parameters:
basis (float)
upper (float)
lower (float)
checkKeltnerBreakout(upper, lower)
Parameters:
upper (float)
lower (float)
calcDonchianChannel(config)
Parameters:
config (ChannelConfig)
checkDonchianTouch(upper, lower)
Parameters:
upper (float)
lower (float)
checkDonchianReentry(upper, lower)
Parameters:
upper (float)
lower (float)
getDonchianWidth(upper, lower)
Parameters:
upper (float)
lower (float)
calcBollingerBands(config)
Parameters:
config (ChannelConfig)
calcSqueezeRatio(bbStdev, kcMultiplier, kcAtr)
Parameters:
bbStdev (float)
kcMultiplier (float)
kcAtr (float)
detectSqueezeState(squeezeRatio)
Parameters:
squeezeRatio (float)
detectSqueezeBreak(squeezeRatio, kcUpper, kcLower)
Parameters:
squeezeRatio (float)
kcUpper (float)
kcLower (float)
getSqueezeIntensity(squeezeRatio)
Parameters:
squeezeRatio (float)
processChannelDetection(config)
Parameters:
config (ChannelConfig)
detectChannelSignals(state)
Parameters:
state (ChannelState)
detectQualityZones(state)
Parameters:
state (ChannelState)
getChannelSignalText(state)
Parameters:
state (ChannelState)
analyzeChannelTrend(state)
Parameters:
state (ChannelState)
getChannelConfluence(state)
Parameters:
state (ChannelState)
newVwapConfig()
newVwapAnchors()
calcSessionVwap()
getPreviousSessionVwap(sessionVwap)
Parameters:
sessionVwap (float)
updateVwapAnchors(anchors, config)
Parameters:
anchors (VwapAnchors)
config (VwapConfig)
calcAnchoredVwap(anchors, isHigh)
Parameters:
anchors (VwapAnchors)
isHigh (bool)
detectPriceCrosses(sessionVwap)
Parameters:
sessionVwap (float)
detectStructureCrosses(sessionVwap, anchoredHigh, anchoredLow)
Parameters:
sessionVwap (float)
anchoredHigh (float)
anchoredLow (float)
detectVwapCluster(sessionVwap, anchoredHigh, anchoredLow, config)
Parameters:
sessionVwap (float)
anchoredHigh (float)
anchoredLow (float)
config (VwapConfig)
canShowSignal(anchors, config, signalType)
Parameters:
anchors (VwapAnchors)
config (VwapConfig)
signalType (string)
updateSignalThrottle(anchors, signalType)
Parameters:
anchors (VwapAnchors)
signalType (string)
calcCrossStrength(sessionVwap, isPriceCross)
Parameters:
sessionVwap (float)
isPriceCross (bool)
calcClusterStrength(vwapsInCluster, priceInCluster, tolerance)
Parameters:
vwapsInCluster (bool)
priceInCluster (bool)
tolerance (float)
calcStructureStrength(sessionVwap, anchoredHigh, anchoredLow)
Parameters:
sessionVwap (float)
anchoredHigh (float)
anchoredLow (float)
analyzeVwapTrend(sessionVwap)
Parameters:
sessionVwap (float)
processVwapDetection(anchors, config)
Parameters:
anchors (VwapAnchors)
config (VwapConfig)
generateVwapSignals(state)
Parameters:
state (VwapState)
getVwapBias(state)
Parameters:
state (VwapState)
getVwapConfluence(state)
Parameters:
state (VwapState)
newZoneConfig()
newZoneState()
stringToFloats(s)
Parameters:
s (string)
calculateBias(config)
Parameters:
config (ZoneConfig)
createZone(top, bottom, isBull, isHTF)
Parameters:
top (float)
bottom (float)
isBull (bool)
isHTF (bool)
updateZoneStatus(zone)
Parameters:
zone (Zone)
detectFVGOverlap(zone)
Parameters:
zone (Zone)
scoreZone(zone, config)
Parameters:
zone (Zone)
config (ZoneConfig)
sortAndTrimZones(zones, config)
Parameters:
zones (array)
config (ZoneConfig)
adjustZoneVisibility(zones, config)
Parameters:
zones (array)
config (ZoneConfig)
calculateTargetsATR(base, stepsString, atrLength)
Parameters:
base (float)
stepsString (string)
atrLength (simple int)
calculateTargetsSigma(base, stepsString, sigmaLength)
Parameters:
base (float)
stepsString (string)
sigmaLength (int)
calculateTargetsLiquidity(isLong, config)
Parameters:
isLong (bool)
config (ZoneConfig)
detectZoneSignals(zones, bias, config)
Parameters:
zones (array)
bias (int)
config (ZoneConfig)
processZoneManagement(state, config)
Parameters:
state (ZoneState)
config (ZoneConfig)
findNearestZones(state)
Parameters:
state (ZoneState)
newVolumeConfig()
newVolumeState()
getPriceSource(config)
Parameters:
config (VolumeConfig)
isInSession(config)
Parameters:
config (VolumeConfig)
isNewSession(config)
Parameters:
config (VolumeConfig)
calculateWindow(config)
Parameters:
config (VolumeConfig)
calculateProfile(config, windowStart, windowLength)
Parameters:
config (VolumeConfig)
windowStart (int)
windowLength (int)
detectVolumeNodes(binVolumes, binPrices, totalVolume)
Parameters:
binVolumes (array)
binPrices (array)
totalVolume (float)
calculateVolumeChoppiness(config)
Calculate choppiness index for volume profile
Parameters:
config (VolumeConfig)
detectMarketRegime(state, config)
Detect market regime based on multiple factors
Parameters:
state (VolumeState)
config (VolumeConfig)
calculateAdaptiveParameters(state, config)
Calculate adaptive volume profile parameters
Parameters:
state (VolumeState)
config (VolumeConfig)
updateMarketConditions(state, config)
Update volume state with market conditions
Parameters:
state (VolumeState)
config (VolumeConfig)
applyAdaptiveConfig(config, state)
Apply adaptive parameters to profile calculation
Parameters:
config (VolumeConfig)
state (VolumeState)
getHTFPivots(config)
Parameters:
config (VolumeConfig)
checkPivotConfluence(price, config, pivotHigh1, pivotLow1, pivotHigh2, pivotLow2)
Parameters:
price (float)
config (VolumeConfig)
pivotHigh1 (float)
pivotLow1 (float)
pivotHigh2 (float)
pivotLow2 (float)
calculateMOST()
Calculate MOST (Moving Stop) indicator
calculateTrendFilters(config)
Parameters:
config (VolumeConfig)
findNearestNodes(hvnNodes, lvnNodes)
Parameters:
hvnNodes (array)
lvnNodes (array)
detectVolumeSignals(config, profile, trendBullish, htfConfluence)
Parameters:
config (VolumeConfig)
profile (VolumeProfile)
trendBullish (bool)
htfConfluence (bool)
calculateVolumeScore(profile, trendBullish)
Parameters:
profile (VolumeProfile)
trendBullish (bool)
processVolumeProfile(state, config)
Parameters:
state (VolumeState)
config (VolumeConfig)
newHTFConfig()
newHTFStackState()
getOptimalTimeframes(chartTF)
Parameters:
chartTF (string)
calculateChoppiness(length)
Parameters:
length (int)
detectTrendEMA(length, threshold)
Parameters:
length (simple int)
threshold (float)
detectTrendSupertrend(atrLength, multiplier)
Parameters:
atrLength (simple int)
multiplier (float)
detectTrendMOST(length, multiplier)
Parameters:
length (simple int)
multiplier (float)
analyzeTrendForTF(tf, config)
Parameters:
tf (string)
config (HTFConfig)
calculateStackConfluence(tfData, config)
Parameters:
tfData (array)
config (HTFConfig)
calculateAutoTuningParams(choppiness, stackStrength, config)
Parameters:
choppiness (float)
stackStrength (float)
config (HTFConfig)
detectStackSignals(state, prevState, config)
Parameters:
state (HTFStackState)
prevState (HTFStackState)
config (HTFConfig)
createStackPanel(state, config)
Parameters:
state (HTFStackState)
config (HTFConfig)
processHTFStack(state, config)
Parameters:
state (HTFStackState)
config (HTFConfig)
processHTFStackSignals(state, prevState, config)
Parameters:
state (HTFStackState)
prevState (HTFStackState)
config (HTFConfig)
newRedefiningTechnicalAnalysisCore(analysisConfig, timeframeConfig, strategy)
Initialize RedefiningTechnicalAnalysis Core Library
Note: This function requires valid config objects to be passed in
The configuration module must be used directly to create default configs
Parameters:
analysisConfig (AnalysisConfig)
timeframeConfig (TimeframeConfig)
strategy (StrategyTemplate)
performAnalysis(core, prices, volumes, timestamps)
Perform complete multi-timeframe analysis
Parameters:
core (RedefiningTechnicalAnalysisCore)
prices (array)
volumes (array)
timestamps (array)
generateSignal(core, analysisResult)
Generate trading signal from analysis results
Parameters:
core (RedefiningTechnicalAnalysisCore)
analysisResult (MultiTimeframeResult)
assessRisk(core, signal)
Assess risk for trading decision
Parameters:
core (RedefiningTechnicalAnalysisCore)
signal (SignalResult)
executeFullWorkflow(core)
Execute complete analysis workflow
Parameters:
core (RedefiningTechnicalAnalysisCore)
updateAnalysisConfig(core, newConfig)
Update analysis configuration
Parameters:
core (RedefiningTechnicalAnalysisCore)
newConfig (AnalysisConfig)
updateStrategy(core, newStrategy)
Update strategy template
Parameters:
core (RedefiningTechnicalAnalysisCore)
newStrategy (StrategyTemplate)
checkSystemHealth(core)
Perform system health check
Parameters:
core (RedefiningTechnicalAnalysisCore)
generateStatusReport(core)
Generate comprehensive status report
Parameters:
core (RedefiningTechnicalAnalysisCore)
enableDebugMode(core, enabled)
Enable debug mode
Parameters:
core (RedefiningTechnicalAnalysisCore)
enabled (bool)
setFeatureFlag(core, flag, enabled)
Set feature flag
Parameters:
core (RedefiningTechnicalAnalysisCore)
flag (string)
enabled (bool)
getFeatureFlag(core, flag, defaultValue)
Get feature flag
Parameters:
core (RedefiningTechnicalAnalysisCore)
flag (string)
defaultValue (bool)
resetLibraryState(core)
Reset library state
Parameters:
core (RedefiningTechnicalAnalysisCore)
getLibraryInfo()
Get library version information
quickAnalysis(config, tfConfig, strategy)
Quick analysis - simplified entry point
Parameters:
config (AnalysisConfig)
tfConfig (TimeframeConfig)
strategy (StrategyTemplate)
getQuickStatus(core)
Get quick status string
Parameters:
core (RedefiningTechnicalAnalysisCore)
Result
Generic Result type for safe operations with error handling and fallbacks
Fields:
floatValue (series float)
stringValue (series string)
boolValue (series bool)
intValue (series int)
isSuccess (series bool)
errorCode (series string)
errorMessage (series string)
floatFallback (series float)
stringFallback (series string)
boolFallback (series bool)
intFallback (series int)
operationContext (series string)
timestamp (series int)
tags (array)
ValidationResult
Comprehensive validation result with errors, warnings, and corrections
Fields:
isValid (series bool)
errors (array)
warnings (array)
corrections (array)
suggestions (array)
validationScore (series float)
validationMode (series string)
validatedFields (series int)
totalFields (series int)
validationContext (series string)
validationTime (series int)
PerformanceProfile
Simplified performance profiling for Pine Script limitations
Fields:
executionTimeMs (series float)
averageExecutionMs (series float)
executionCount (series int)
errorCount (series int)
cacheHits (series int)
cacheMisses (series int)
cacheHitRatio (series float)
estimatedArrayElements (series int)
hasHeavyCalculation (series bool)
lastOptimizationHint (series string)
performanceGrade (series string)
performanceScore (series float)
functionName (series string)
profileStartTime (series int)
HealthStatus
Simplified health status for Pine Script limitations
Fields:
isHealthy (series bool)
healthScore (series float)
healthGrade (series string)
issues (array)
warnings (array)
recommendations (array)
dataValidationOK (series bool)
calculationsOK (series bool)
memoryUsageOK (series bool)
errorCountSession (series int)
warningCountSession (series int)
lastHealthCheck (series int)
healthCheckVersion (series string)
AnalysisConfig
Comprehensive analysis configuration with factor weights, thresholds, and extensible options
Fields:
activeFactors (array)
factorWeights (map)
thresholds (map)
features (map)
tradingMode (series string)
consensusMode (series string)
riskProfile (series string)
minConfidence (series float)
signalStrength (series float)
requireConsensus (series bool)
minConsensusCount (series int)
parameters (map)
options (map)
flags (map)
configName (series string)
version (series string)
description (series string)
createdTime (series int)
lastModified (series int)
validation (ValidationResult)
TimeframeConfig
Multi-timeframe configuration with weights and adjustments
Fields:
timeframes (array)
weights (array)
autoDetectChartTF (series bool)
includeHigherTFs (series bool)
tfAdjustments (map)
tfSensitivity (map)
tfFeatures (map)
minTimeframes (series int)
consensusThreshold (series float)
consensusMethod (series string)
normalizeWeights (series bool)
adaptiveBias (series bool)
higherTFBias (series float)
tfConfigName (series string)
configTimestamp (series int)
validation (ValidationResult)
GenericAnalysis
Generic analysis result that all specific analysis types extend
Fields:
totalScore (series float)
confidence (series float)
action (series string)
strength (series string)
riskLevel (series string)
factorScores (map)
factorWeights (map)
factorSignals (map)
factorReasons (map)
analysisType (series string)
timeframeAnalyzed (series string)
analysisTimestamp (series int)
marketCondition (series string)
dataQuality (series float)
performance (PerformanceProfile)
validation (ValidationResult)
numericData (map)
textData (map)
flags (map)
ConsensusData
Multi-timeframe consensus analysis data
Fields:
agreementCount (series int)
totalTimeframes (series int)
agreementPercentage (series float)
hasStrongConsensus (series bool)
hasMajorityConsensus (series bool)
agreeingTimeframes (array)
disagreeingTimeframes (array)
tfScores (map)
tfActions (map)
consensusMode (series string)
consensusScore (series float)
consensusAction (series string)
consensusStrength (series string)
tfWeights (map)
weightedConsensus (series bool)
weightedScore (series float)
consensusQuality (series float)
consensusReliability (series string)
consensusWarnings (array)
SignalResult
Comprehensive trading signal result
Fields:
strongBuy (series bool)
buy (series bool)
neutral (series bool)
sell (series bool)
strongSell (series bool)
overallScore (series float)
confidence (series float)
primaryAction (series string)
signalStrength (series string)
signalReason (series string)
contributingFactors (array)
factorContributions (map)
triggerCondition (series string)
consensus (ConsensusData)
consensusLevel (series string)
hasConsensus (series bool)
riskLevel (series string)
riskRewardRatio (series float)
successProbability (series float)
signalTimestamp (series int)
urgency (series string)
validityPeriod (series int)
marketPhase (series string)
warningFlags (array)
metadata (map)
MultiTimeframeResult
Multi-timeframe analysis result container
Fields:
primaryAnalysis (GenericAnalysis)
tfResults (map)
consensus (ConsensusData)
aggregatedScore (series float)
confidenceScore (series float)
dominantAction (series string)
consensusStrength (series string)
analyzedTimeframes (array)
failedTimeframes (array)
failureReasons (map)
performance (PerformanceProfile)
validation (ValidationResult)
dataQualityScore (series float)
config (AnalysisConfig)
tfConfig (TimeframeConfig)
analysisTimestamp (series int)
DebugLogEntry
Debug log entry
Fields:
timestamp (series int)
level (series string)
module (series string)
function (series string)
message (series string)
context (series string)
data (map)
barIndex (series int)
timeframe (series string)
DebugLogger
Debug logger with configurable levels
Fields:
entries (array)
maxEntries (series int)
currentLevel (series string)
enabled (series bool)
enabledModules (array)
showTimestamp (series bool)
showBarIndex (series bool)
outputFormat (series string)
PerformanceMeasurement
Performance measurement
Fields:
name (series string)
startTime (series int)
endTime (series int)
duration (series float)
iterations (series int)
avgDuration (series float)
status (series string)
context (series string)
TraceEntry
Execution trace entry
Fields:
function (series string)
module (series string)
entryTime (series int)
exitTime (series int)
isEntry (series bool)
parameters (series string)
returnValue (series string)
depth (series int)
ExecutionTracer
Execution tracer
Fields:
traces (array)
currentDepth (series int)
maxDepth (series int)
enabled (series bool)
maxTraces (series int)
CacheEntry
Cache entry
Fields:
key (series string)
data (series string)
timestamp (series int)
ttl (series int)
accessCount (series int)
lastAccess (series int)
CacheManager
Cache manager
Fields:
name (series string)
entries (map)
maxEntries (series int)
defaultTTL (series int)
enabled (series bool)
hits (series int)
misses (series int)
evictions (series int)
RiskAssessment
Core risk assessment result
Fields:
riskLevel (series string)
riskScore (series float)
riskRewardRatio (series float)
successProbability (series float)
maxDrawdownExpected (series float)
positionRisk (series float)
portfolioExposure (series float)
correlationRisk (series float)
concentrationRisk (series float)
volatilityRisk (series float)
liquidityRisk (series float)
timeframeRisk (series float)
newsEventRisk (series float)
supportResistanceRisk (series float)
trendRisk (series float)
momentumRisk (series float)
volumeRisk (series float)
hasHighRisk (series bool)
hasExtremeRisk (series bool)
riskWarnings (array)
riskFactors (array)
recommendedPositionSize (series float)
stopLossDistance (series float)
takeProfitDistance (series float)
shouldAvoidTrade (series bool)
riskMitigationStrategy (series string)
assessmentTimestamp (series int)
assessmentMethod (series string)
performance (PerformanceProfile)
PositionData
Comprehensive position data
Fields:
hasPosition (series bool)
positionSide (series string)
positionSize (series float)
entryPrice (series float)
entryTimestamp (series int)
entryReason (series string)
unrealizedPnL (series float)
realizedPnL (series float)
maxUnrealizedGain (series float)
maxUnrealizedLoss (series float)
totalReturn (series float)
stopLossPrice (series float)
takeProfitPrice (series float)
riskAmount (series float)
riskRewardRatio (series float)
currentRisk (RiskAssessment)
barsInPosition (series int)
maxBarsAllowed (series int)
isTimedOut (series bool)
timeframe (series string)
hasExitSignal (series bool)
exitReason (series string)
exitScore (series float)
shouldExit (series bool)
exitUrgency (series string)
actionHistory (array)
timestampHistory (array)
reasonHistory (array)
sharpeRatio (series float)
maxDrawdown (series float)
winRate (series float)
avgHoldTime (series float)
StrategyTemplate
Base strategy template
Fields:
name (series string)
description (series string)
category (series string)
timeframes (array)
entryThreshold (series float)
entryConfidenceMin (series float)
requiredSignals (array)
excludeConditions (array)
exitThreshold (series float)
stopLossPercent (series float)
takeProfitPercent (series float)
maxBarsInTrade (series int)
maxPositionSize (series float)
basePositionSize (series float)
useVolatilityAdjustment (series bool)
useConfidenceAdjustment (series bool)
maxRiskPerTrade (series float)
maxDailyRisk (series float)
maxDrawdownLimit (series float)
useAdaptiveRisk (series bool)
requireConsensus (series bool)
minConsensusPercent (series float)
avoidNewsEvents (series bool)
requireVolume (series bool)
targetSharpeRatio (series float)
targetWinRate (series float)
targetRiskReward (series float)
parameters (map)
flags (map)
settings (map)
MetricDataPoint
Performance metric data point
Fields:
timestamp (series int)
value (series float)
name (series string)
unit (series string)
labels (map)
source (series string)
MetricStats
Metric statistics
Fields:
min (series float)
max (series float)
avg (series float)
sum (series float)
count (series int)
p50 (series float)
p95 (series float)
p99 (series float)
stdDev (series float)
firstTimestamp (series int)
lastTimestamp (series int)
MetricDataPointArray
Wrapper for array of metric data points (to avoid nested collections)
Fields:
dataPoints (array)
MetricsCollector
Metrics collector
Fields:
metrics (map)
stats (map)
maxDataPoints (series int)
retentionPeriod (series int)
autoCleanup (series bool)
enabled (series bool)
enabledMetrics (array)
lastCleanupTime (series int)
ComponentHealth
Component health status
Fields:
name (series string)
status (series string)
healthScore (series float)
lastCheckTime (series int)
warnings (array)
errors (array)
metrics (map)
lastError (series string)
errorCount (series int)
warningCount (series int)
isOperational (series bool)
SystemHealth
System health overview
Fields:
overallStatus (series string)
overallScore (series float)
healthyComponents (series int)
degradedComponents (series int)
unhealthyComponents (series int)
components (array)
systemWarnings (array)
systemErrors (array)
lastFullCheckTime (series int)
autoHealing (series bool)
healingAttempts (series int)
HealthAlert
Health alert
Fields:
level (series string)
component (series string)
message (series string)
timestamp (series int)
acknowledged (series bool)
category (series string)
ZoneDetection
Advanced zone data structure
Fields:
upper (series float)
lower (series float)
mid (series float)
height (series float)
score (series float)
quality (series string)
touchCount (series int)
lastTouchBar (series int)
creationBar (series int)
role (series int)
zoneType (series string)
isActive (series bool)
isBroken (series bool)
flipBar (series int)
flipRetestCount (series int)
flipBestQuality (series float)
flipScore (series float)
hasFlipped (series bool)
htfOverlap (series bool)
htfTimeframe (series string)
htfConfidence (series float)
retestQuality (series float)
volumeProfile (series float)
volatilityProfile (series float)
freshnessScore (series float)
successfulBounces (series int)
failedBreakouts (series int)
successRate (series float)
avgHoldTime (series float)
zoneBox (series box)
midLine (series line)
zoneLabel (series label)
flipLabel (series label)
ZoneDetectionConfig
Zone analysis configuration
Fields:
pivotPeriod (series int)
atrMultiplier (series float)
atrLength (series int)
maxZones (series int)
mergeThreshold (series float)
minTouchesForSignificance (series int)
weightTouches (series float)
weightFreshness (series float)
weightVolume (series float)
weightHTF (series float)
minWickPercent (series float)
maxBodyPercent (series float)
freshnessHalfLife (series int)
useHTFProjection (series bool)
htfTimeframe (series string)
htfPivotCount (series int)
htfProjectionMultiplier (series float)
ChannelConfig
Fields:
kcEmaLength (series int)
kcAtrLength (series int)
kcMultiplier (series float)
dcLength (series int)
bbLength (series int)
bbMultiplier (series float)
pivotLength (series int)
atrThreshold (series float)
minBarsPerLeg (series int)
minTouchCount (series int)
mergeThreshold (series float)
ChannelState
Fields:
kcUpper (series float)
kcLower (series float)
kcBasis (series float)
kcAtr (series float)
dcUpper (series float)
dcLower (series float)
dcMid (series float)
bbUpper (series float)
bbLower (series float)
bbBasis (series float)
bbStdev (series float)
squeezeRatio (series float)
isSqueezeActive (series bool)
isExpanding (series bool)
touchKcUpper (series bool)
touchKcLower (series bool)
touchDcUpper (series bool)
touchDcLower (series bool)
kcBreakoutUp (series bool)
kcBreakoutDown (series bool)
dcReentryUp (series bool)
dcReentryDown (series bool)
squeezeBreakUp (series bool)
squeezeBreakDown (series bool)
kcDepth (series float)
dcWidth (series float)
squeezeIntensity (series float)
ChannelSignal
Fields:
signalType (series string)
direction (series int)
strength (series float)
description (series string)
isQualitySignal (series bool)
VwapConfig
Fields:
pivotLeftBars (series int)
pivotRightBars (series int)
clusterTolerancePercent (series float)
minBarsBetweenSignals (series int)
crossThreshold (series float)
enableThrottling (series bool)
detectClusters (series bool)
VwapState
Fields:
sessionVwap (series float)
sessionVwapPrev (series float)
anchoredVwapHigh (series float)
anchoredVwapLow (series float)
hasAnchoredHigh (series bool)
hasAnchoredLow (series bool)
priceCrossUp (series bool)
priceCrossDown (series bool)
canShowPriceCross (series bool)
structureCrossUp (series bool)
structureCrossDown (series bool)
canShowStructureCross (series bool)
isClusterActive (series bool)
canShowCluster (series bool)
clusterTolerance (series float)
vwapsInCluster (series bool)
priceInCluster (series bool)
priceVwapPosition (series int)
priceVwapDistance (series float)
priceVwapDistancePercent (series float)
crossStrength (series float)
clusterStrength (series float)
structureStrength (series float)
VwapSignal
Fields:
signalType (series string)
direction (series int)
strength (series float)
description (series string)
isHighConfidence (series bool)
barIndex (series int)
VwapAnchors
Fields:
cumulativePV (series float)
cumulativeV (series float)
anchorPV_High (series float)
anchorV_High (series float)
hasHighAnchor (series bool)
anchorPV_Low (series float)
anchorV_Low (series float)
hasLowAnchor (series bool)
lastPriceCrossBar (series int)
lastStructureCrossBar (series int)
lastClusterBar (series int)
ZoneConfig
Fields:
htfTimeframe (series string)
useHTF (series bool)
maxZonesPerSide (series int)
rankFavorHTF (series bool)
rankFavorFVG (series bool)
rankFavorFresh (series bool)
showOnlyTopRank (series bool)
alphaTop (series int)
alphaRest (series int)
biasLength (series int)
biasBandMultiplier (series float)
targetMode (series string)
atrLength (series int)
atrSteps (series string)
sigmaLength (series int)
sigmaSteps (series string)
useSSL (series bool)
useFVGFills (series bool)
confirmMidline (series bool)
confirmBreak (series bool)
requireBias (series bool)
lazyTargets (series bool)
nearPercent (series float)
Zone
Fields:
top (series float)
bottom (series float)
mid (series float)
bornTime (series int)
isBull (series bool)
isHTF (series bool)
touched (series bool)
violated (series bool)
hasFVG (series bool)
score (series float)
rank (series int)
zoneBox (series box)
midLine (series line)
isActive (series bool)
ZoneState
Fields:
zonesTF (array)
zonesHTF (array)
bias (series int)
biasScore (series float)
biasRegime (series string)
vwapLevel (series float)
bandUpper (series float)
bandLower (series float)
targetLevels (array)
targetLines (array)
activeBullZones (series int)
activeBearZones (series int)
totalZones (series int)
avgZoneScore (series float)
longSignal (series bool)
shortSignal (series bool)
nearestBullZone (Zone)
nearestBearZone (Zone)
ZoneSignal
Fields:
signalType (series string)
sourceZone (Zone)
strength (series float)
description (series string)
confirmed (series bool)
barIndex (series int)
VolumeConfig
Fields:
profileMode (series string)
fixedLength (series int)
rollingLength (series int)
sessionString (series string)
binCount (series int)
valueAreaPercent (series float)
useHLC3 (series bool)
useHTF1 (series bool)
htfTimeframe1 (series string)
useHTF2 (series bool)
htfTimeframe2 (series string)
pivotLookback (series int)
pivotToleranceATR (series float)
enableAutoTuning (series bool)
vaPct_eff (series float)
epsATR_eff (series float)
adaptiveAlpha (series float)
choppinessLength (series int)
choppyThreshold (series float)
trendingThreshold (series float)
useMarketRegime (series bool)
enableLVNSignals (series bool)
enableVASignals (series bool)
maxRetestDistanceATR (series float)
useEMAFilter (series bool)
useSupertrendFilter (series bool)
useMOSTFilter (series bool)
showPOC (series bool)
showValueArea (series bool)
showNodes (series bool)
showSilhouette (series bool)
silhouetteOffset (series int)
silhouetteWidth (series int)
zoneOpacity (series int)
enableSessionSplits (series bool)
maxSessionCount (series int)
VolumeNode
Fields:
price (series float)
volume (series float)
nodeType (series string)
prominence (series float)
isSignificant (series bool)
VolumeProfile
Fields:
pocPrice (series float)
pocVolume (series float)
valueAreaHigh (series float)
valueAreaLow (series float)
totalVolume (series float)
windowStart (series int)
windowLength (series int)
windowHigh (series float)
windowLow (series float)
binVolumes (array)
binPrices (array)
hvnNodes (array)
lvnNodes (array)
nearestLVN (series float)
nearestHVN (series float)
htfConfluence (series bool)
pocLine (series line)
valueAreaBox (series box)
nodeBoxes (array)
silhouette (series polyline)
VolumeState
Fields:
currentProfile (VolumeProfile)
sessionProfiles (array)
trendBullish (series bool)
emaConfluence (series float)
supertrendBull (series bool)
mostBull (series bool)
choppiness (series float)
isChoppy (series bool)
isTrending (series bool)
marketRegime (series string)
vaPct_current (series float)
epsATR_current (series float)
smoothingFactor (series float)
longLVNSignal (series bool)
shortLVNSignal (series bool)
longVASignal (series bool)
shortVASignal (series bool)
volumeScore (series float)
passFilter (series bool)
inValueArea (series bool)
abovePOC (series bool)
pocRising (series bool)
nearLVN (series bool)
VolumeSignal
Fields:
signalType (series string)
direction (series int)
strength (series float)
description (series string)
triggerPrice (series float)
hasConfluence (series bool)
barIndex (series int)
HTFConfig
Fields:
timeframes (array)
tfWeights (array)
autoSelectTFs (series bool)
maxTimeframes (series int)
trendLength (series int)
trendThreshold (series float)
trendMethod (series string)
stackThreshold (series float)
requireAllTFs (series bool)
confluenceBonus (series float)
enableAutoTuning (series bool)
choppinessLength (series int)
choppyThreshold (series float)
trendingThreshold (series float)
showStackPanel (series bool)
panelPosition (series string)
panelRows (series int)
panelCols (series int)
showTooltips (series bool)
HTFTrendData
Fields:
timeframe (series string)
trendStrength (series float)
trendDirection (series string)
confidence (series float)
isValid (series bool)
weight (series float)
trendColor (series color)
HTFStackState
Fields:
tfData (array)
bullConfluence (series float)
bearConfluence (series float)
stackStrength (series float)
stackBias (series string)
choppiness (series float)
isChoppy (series bool)
isTrending (series bool)
marketRegime (series string)
vaPct_eff (series float)
epsATR_eff (series float)
adaptiveAlpha (series float)
bullStackSignal (series bool)
bearStackSignal (series bool)
stackBreakSignal (series bool)
stackTable (series table)
tfLabels (array)
strengthBars (array)
RedefiningTechnicalAnalysisCore
Main library state container
Fields:
analysisConfig (AnalysisConfig)
timeframeConfig (TimeframeConfig)
activeStrategy (StrategyTemplate)
lastAnalysis (MultiTimeframeResult)
lastSignal (SignalResult)
lastRisk (RiskAssessment)
currentPosition (PositionData)
isInitialized (series bool)
lastUpdateTime (series int)
currentTimeframe (series string)
globalPerformance (PerformanceProfile)
systemHealth (SystemHealth)
metricsCollector (MetricsCollector)
analysisCache (CacheManager)
calculationCache (CacheManager)
recentErrors (array)
recentWarnings (array)
errorCount (series int)
warningCount (series int)
debugLogger (DebugLogger)
debugMode (series bool)
extensionData (map)
featureFlags (map)
Moderate Value Screener (NASDAQ + NYSE + TSX v6 FINAL CLEAN)Moderate Value Screener (NASDAQ + NYSE + TSX v6 FINAL CLEAN)
Lucas' Money GlitchHere's a description you can use to publish your indicator to TradingView:
Title: Triple SuperTrend + RSI + Fib BB + Volume Oscillator
Short Description:
Advanced multi-indicator system combining three SuperTrends, RSI, Fibonacci Bollinger Bands, DEMA filter, and Volume Oscillator for precise trade entry and exit signals.
Full Description:
Overview
This comprehensive trading indicator combines multiple proven technical analysis tools to identify high-probability trade setups with built-in risk management through automated take profit levels.
Key Features
📊 Triple SuperTrend System
Uses three SuperTrend indicators with different ATR periods (10, 11, 12) and multipliers (1.0, 2.0, 3.0)
Requires all three SuperTrends to align before generating signals
Reduces false signals and confirms trend strength
📈 Volume Oscillator Filter
Calculates volume momentum using short and long-term moving averages
Requires volume oscillator to be above 20% threshold for trade entries
Ensures trades only occur during periods of strong volume activity
Displayed as a clean histogram in separate pane (green = bullish, red = bearish)
🎯 RSI Confirmation
7-period RSI must be above 50 for buy signals
RSI must be below 50 for sell signals
Prevents counter-trend entries
🌊 200 DEMA Trend Filter
Double Exponential Moving Average acts as major trend filter
Optional: Only buy above DEMA, only sell below DEMA
Can be toggled on/off based on trading style
📐 Fibonacci Bollinger Bands
Uses 2.618 Fibonacci multiplier (Golden Ratio)
200-period basis
Price touching bands triggers exit signals
Helps identify overextended moves
Entry Signals
BUY Signal (Green Triangle):
All three SuperTrends turn bullish simultaneously
RSI > 50
Price above 200 DEMA (if filter enabled)
Volume Oscillator > 20%
SELL Signal (Red Triangle):
All three SuperTrends turn bearish simultaneously
RSI < 50
Price below 200 DEMA (if filter enabled)
Volume Oscillator > 20%
Exit Signals
Automatic Exits Occur When:
Any of the three SuperTrends changes direction
Price touches Fibonacci Bollinger Band (upper or lower)
Take Profit target is reached (1.5x the distance from entry to ST1)
Exit Labels:
🟠 "TP" = Take Profit hit
🟡 "X" = SuperTrend change or BB touch
Visual Elements
Orange Line: Dynamic take profit level based on SuperTrend distance
Green/Red Lines: Three SuperTrend levels (varying opacity)
Purple Bands: Fibonacci Bollinger Bands with shaded area
Blue Line: 200 DEMA
Background Tint: Green when all bullish, red when all bearish
Volume Histogram: Separate pane showing volume oscillator
Dashboard Display
Real-time information table showing:
Current position status (Long/Short/Flat)
RSI value
Volume Oscillator percentage
Overall trend direction
Alert Conditions
Set up custom alerts for:
Buy signals
Sell signals
Take profit hits
Exit signals
Customizable Parameters
SuperTrend Settings:
Individual ATR periods and multipliers for each SuperTrend
Default: ST1(10,1.0), ST2(11,2.0), ST3(12,3.0)
Volume Oscillator:
Short length (default: 5)
Long length (default: 10)
Threshold percentage (default: 20%)
Toggle filter on/off
Other Filters:
RSI length (default: 7)
DEMA length (default: 200)
Fib BB length and multiplier
Take profit multiplier (default: 1.5x)
Best Use Cases
Trend following strategies
Swing trading
Day trading on higher timeframes (15min+)
Works on all markets: Stocks, Forex, Crypto, Futures
Notes
This is an indicator, not an automated strategy
Signals are for informational purposes only
Always practice proper risk management
Test on historical data before live trading
Works best in trending markets
Triple SuperTrend + RSI + Fib BB + Vol Osc Strategy✅ Key Features Implemented:
Three SuperTrend Indicators with different opacities:
ST1: 10 period, 1.0 multiplier (solid)
ST2: 11 period, 2.0 multiplier (40% transparent)
ST3: 12 period, 3.0 multiplier (70% transparent)
Signal Logic (no repainting):
BUY: All 3 SuperTrends turn green + RSI(7) > 50
SELL: All 3 SuperTrends turn red + RSI(7) < 50
EXIT: Any SuperTrend changes color OR price touches Fib BB
Fibonacci Bollinger Bands (200 SMA ± 2.618 × StdDev):
Purple bands with subtle fill
Gray dashed middle line
Visual Elements:
Green "BUY" labels below bars
Red "SELL" labels above bars
Yellow circle "EXIT" labels at candle tops
Green/red background tint when all STs align
Info dashboard showing real-time status
Alert Conditions for BUY, SELL, and EXIT
Position Tracking ensures only one signal per condition change
📊 Usage:
Copy the entire code and paste it into TradingView's Pine Editor, then click "Add to Chart". The indicator will display all three SuperTrends, Fibonacci Bollinger Bands, and generate signals according to your exact specifications.
The dashboard in the top-right corner shows the current status of each SuperTrend, RSI value, and whether you're in a position!RetryLH
Bridge Bands ATR (Overlay) ShaneHurst-Adaptive Volatility Bands
A fractal-inspired evolution of Bollinger and Keltner bands that adapts dynamically to both volatility and trend persistence.
This indicator estimates the Hurst exponent (H) — a measure of market memory — and adjusts a standard volatility band to lean in the direction of the prevailing trend.
When H > 0.5, markets exhibit persistence (trending behavior); the bands shift in the trend’s direction.
When H < 0.5, markets are mean-reverting; the bands flatten and recent extremes become potential fade zones.
Band width scales with recent volatility (σ), expanding in turbulent conditions and contracting during calm periods.
Key Features:
Adaptive offset using the Hurst exponent
Volatility-sensitive width for dynamic market regimes
EMA baseline with directional bias
Clear visual separation between trending and choppy phases
Inspired by Benoit Mandelbrot’s The Misbehavior of Markets and H.E. Hurst’s original work on long-term memory in time series.
Use it to identify regime shifts, trend-following entries, and volatility-adjusted stop levels.
Credit for this script goes to a number of people including Steve B, MichaalAngle, doc and joecat808. 500 day DEMA (double EMA) can be used as a longer term momentum line.
Cumulative Volume Delta Z Score [BackQuant]Cumulative Volume Delta Z Score
The Cumulative Volume Delta Z Score indicator is a sophisticated tool that combines the cumulative volume delta (CVD) with Z-Score normalization to provide traders with a clearer view of market dynamics. By analyzing volume imbalances and standardizing them through a Z-Score, this tool helps identify significant price movements and market trends while filtering out noise.
Core Concept of Cumulative Volume Delta (CVD)
Cumulative Volume Delta (CVD) is a popular indicator that tracks the net difference between buying and selling volume over time. CVD helps traders understand whether buying or selling pressure is dominating the market. Positive CVD signals buying pressure, while negative CVD indicates selling pressure.
The addition of Z-Score normalization to CVD makes it easier to evaluate whether current volume imbalances are unusual compared to past behavior. Z-Score helps in detecting extreme conditions by showing how far the current CVD is from its historical mean in terms of standard deviations.
Key Features
Cumulative Volume Delta (CVD): Tracks the net buying vs. selling volume, allowing traders to gauge the overall market sentiment.
Z-Score Normalization: Converts CVD into a standardized value to highlight extreme movements in volume that are statistically significant.
Divergence Detection: The indicator can spot bullish and bearish divergences between price and CVD, which can signal potential trend reversals.
Pivot-Based Divergence: Identifies price and CVD pivots, highlighting divergence patterns that are crucial for predicting price changes.
Trend Analysis: Colors bars according to trend direction, providing a visual indication of bullish or bearish conditions based on Z-Score.
How It Works
Cumulative Volume Delta (CVD): The CVD is calculated by summing the difference between buying and selling volume for each bar. It represents the net buying or selling pressure, giving insights into market sentiment.
Z-Score Normalization: The Z-Score is applied to the CVD to normalize its values, making it easier to compare current conditions with historical averages. A Z-Score greater than 0 indicates a bullish market, while a Z-Score less than 0 signals a bearish market.
Divergence Detection: The indicator detects regular and hidden bullish and bearish divergences between price and CVD. These divergences often precede trend reversals, offering traders a potential entry point.
Pivot-Based Analysis: The indicator uses pivot highs and lows in both price and CVD to identify divergence patterns. A bullish divergence occurs when price makes a lower low, but CVD fails to follow, suggesting weakening selling pressure. Conversely, a bearish divergence happens when price makes a higher high, but CVD doesn't confirm the move, indicating potential selling pressure.
Trend Coloring: The bars are colored based on the trend direction. Green bars indicate an uptrend (CVD is positive), and red bars indicate a downtrend (CVD is negative). This provides an easy-to-read visualization of market conditions.
Standard Deviation Levels: The indicator plots ±1σ, ±2σ, and ±3σ levels to indicate the degree of deviation from the average CVD. These levels act as thresholds for identifying extreme buying or selling pressure.
Customization Options
Anchor Timeframe: The user can define an anchor timeframe to aggregate the CVD, which can be customized based on the trader’s needs (e.g., daily, weekly, custom lower timeframes).
Z-Score Period: The period for calculating the Z-Score can be adjusted, allowing traders to fine-tune the indicator's sensitivity.
Divergence Detection: The tool offers controls to enable or disable divergence detection, with the ability to adjust the lookback periods for pivot detection.
Trend Coloring and Visuals: Traders can choose whether to color bars based on trend direction, display standard deviation levels, or visualize the data as a histogram or line plot.
Display Options: The indicator also allows for various display options, including showing the Z-Score values and divergence signals, with customizable colors and line widths.
Alerts and Signals
The Cumulative Volume Delta Z Score comes with pre-configured alert conditions for:
Z-Score Crossovers: Alerts are triggered when the Z-Score crosses the 0 line, indicating a potential trend reversal.
Shifting Trend: Alerts for when the Z-Score shifts direction, signaling a change in market sentiment.
Divergence Detection: Alerts for both regular and hidden bullish and bearish divergences, offering potential reversal signals.
Extreme Imbalances: Alerts when the Z-Score reaches extreme positive or negative levels, indicating overbought or oversold market conditions.
Applications in Trading
Trend Identification: Use the Z-Score to confirm bullish or bearish trends based on cumulative volume data, filtering out noise and false signals.
Reversal Signals: Divergences between price and CVD can help identify potential trend reversals, making it a powerful tool for swing traders.
Volume-Based Confirmation: The Z-Score allows traders to confirm price movements with volume data, providing more reliable signals compared to price action alone.
Divergence Strategy: Use the divergence signals to identify potential points of entry, particularly when regular or hidden divergences appear.
Volatility and Market Sentiment: The Z-Score provides insights into market volatility by measuring the deviation of CVD from its historical mean, helping to predict price movement strength.
The Cumulative Volume Delta Z Score is a powerful tool that combines volume analysis with statistical normalization. By focusing on volume imbalances and applying Z-Score normalization, this indicator provides clear, reliable signals for trend identification and potential reversals. It is especially useful for filtering out market noise and ensuring that trades are based on significant price movements driven by substantial volume changes.
This indicator is perfect for traders looking to add volume-based analysis to their strategy, offering a more robust and accurate way to gauge market sentiment and trend strength.
Metals vs DXY CorrelationThere's a growing interest in Gold and Metals in general - due to safe have demand - a lot of traders get blindsided by sudden consolidation and reversals while trading Gold or Silver. The key is to know that GC is closely related to DXY because large institutions and central banks hedge the two instruments. They are inversely correlated for the most part.
This indicator looks at price action applies Pearson correlation to find the strength in their "entanglement" and tells you if its is strongly, weakly or positively correlated.
It has helped me stay away from the markets when there's a strong inverse correlation because the price action can be very unpredictable.
Hopefully you find this useful.
Bull-Bear EfficiencyBull-Bear Efficiency
This indicator measures the directional efficiency of price movement across many historical entry points to estimate overall market bias. It is designed as a trend gauge rather than a timing signal.
Concept
For each historical bar (tau) and a chosen lookahead horizon (h), the script evaluates how efficiently price has traveled from that starting point to the endpoint. Efficiency is defined as the net price change divided by the total absolute movement that occurred along the path.
Formula:
E(tau,h) = ( Price - Price ) / ( Sum from i = tau+1 to tau+h of | Price - Price | )
This measures how "straight" the path was from the entry to the current bar:
If price moved steadily upward, the numerator and denominator are nearly equal, and E approaches +1 (efficient bullish trend).
If price moved steadily downward, E approaches -1 (efficient bearish trend).
If price chopped back and forth, the denominator grows faster than the numerator, and E approaches 0 (inefficient movement).
The algorithm computes this efficiency for many past starting points and multiple horizons, optionally normalizing by ATR to account for volatility. The efficiencies are then weighted by recency to emphasize more recent behavior.
From this, the script derives:
Bull = weighted average of positive efficiencies
Bear = weighted average of negative efficiencies (absolute value)
Net = Bull - Bear (net directional efficiency)
Interpretation
Bull, Bear, and Net quantify how coherently the market has been trending.
Bull near 1.0, Bear near 0.0, Net > 0 -> clean upward trends; long positions have been more efficient.
Bear near 1.0, Bull near 0.0, Net < 0 -> clean downward trends; short positions have been more efficient.
Bull and Bear both small or similar -> low-efficiency, range-bound environment.
Net therefore acts as a "trend coherence index" that measures whether price action is directionally organized or noisy.
Practical Use
Trend filter:
Apply trend-following systems only when Net is strongly positive or negative.
Avoid them when Net is near zero.
Regime change detection:
Crossings through zero often correspond to transitions between trending and ranging regimes.
Momentum loss detection:
If price makes new highs but Net or Bull weakens, it suggests trend exhaustion.
Settings Overview
Lookback: Number of historical bars considered as entry points (tau values).
Horizons: List of forward projection lengths (in bars) for measuring efficiency.
Recency Decay (lambda): Exponential weighting that emphasizes recent data.
Normalize by ATR: Adjusts "effort" to account for volatility changes.
Display Options: Toggle Bull, Bear, Net, or Signed Average (S). Customize line colors.
Notes
This indicator does not produce entry or exit signals.
It is a statistical tool that measures how efficiently price has trended over time.
High Net values indicate smooth, coherent trends.
Low or neutral Net values indicate noisy, directionless conditions.
Bollinger Band ToolkitBollinger Band Toolkit
An advanced, adaptive Bollinger Band system for traders who want more context, precision, and edge.
This indicator expands on the classic Bollinger Bands by combining statistical and volatility-based methods with modern divergence and squeeze detection tools. It helps identify volatility regimes, potential breakouts, and early momentum shifts — all within one clean overlay.
🔹 Core Features
1. Adaptive Bollinger Bands (σ + ATR)
Classic 20-period bands enhanced with an ATR-based volatility adjustment, making them more responsive to true market movement rather than just price variance.
Reduces “overreacting” during chop and avoids bands collapsing too tightly during trends.
2. %B & RSI Divergence Detection
🟢 Green dots: Positive %B divergence — price makes a lower low, but %B doesn’t confirm (bullish).
🔴 Red dots: Negative %B divergence — price makes a higher high, but %B doesn’t confirm (bearish).
✚ Red/green crosses: RSI divergence confirmation — momentum fails to confirm the price’s new extreme.
These signals highlight potential reversal or slowdown zones that are often invisible to the naked eye.
3. Bollinger Band Squeeze (with Volume Filter)
Yellow squares (■) show periods when Bollinger Bands are at their narrowest relative to recent history.
Volume confirmation ensures the squeeze only triggers when both volatility and participation contract.
Often marks the “calm before the storm” — breakout potential zones.
4. Multi-Timeframe Breakout Markers
Optionally displays breakouts from higher or lower timeframes using different colors/symbols.
Lets you see when a higher timeframe band break aligns with your current chart — a strong trend continuation signal.
5. Dual- and Triple-Band Visualization (±1σ, ±2σ, ±3σ)
Optional inner (±1σ) and outer (±3σ) bands provide a layered volatility map:
Price holding between ±1σ → stable range / mean-reverting behavior
Price riding near ±2σ → trending phase, sustained momentum
Price touching or exceeding ±3σ → volatility expansion or exhaustion zone
This triple-band layout visually distinguishes normal movement from statistical extremes, helping you read when the market is balanced, expanding, or approaching its limits.
⚙️ Inputs & Customization
Choose band type (SMA/EMA/SMMA/WMA/VWMA)
Adjust deviation multiplier (σ) and ATR multiplier
Toggle individual features (divergence dots, squeeze markers, inner bands, etc.)
Multi-timeframe and colour controls for advanced users
🧠 How to Use
Watch for squeeze markers followed by a breakout bar beyond ±2σ → volatility expansion signal.
Combine divergence dots with RSI or price structure to anticipate slowdowns or reversals.
Confirm direction using multi-timeframe breakouts and volume expansion.
💬 Why It Works
This toolkit transforms qualitative chart reading (tight bands, hidden divergence) into quantitative, testable conditions — giving you objective insights that can be backtested, coded, or simply trusted in live setups.
Previous Day High, Low, and Mid (Extended)This indicator shows the previous sessions high, low, and midpoint with extended lines for the trading session.
Previous Day High, Low, and MidThis indicator will draw out levels for the previous sessions highs and lows as well as the middle point between the two. Might not work with indices
Measured Pattern Move (Bulkowski) [SS]Hey everyone,
This is the Measured Pattern Move using Bulkowski's process for measured move calculation.
What the indicator does:
The indicator has the associated measured move across 20 of the most common and frequent Bulkowski patterns, including:
Double Bottom / Adam Eve Bottom
Double Top / Adam Eve Top
Inverse Head and Shoulders
Bear Flag
Bull Flag
Horn Bottom
Horon Top
Broadening Top
Descending Broadening Wedge
Broadening Bottoms
Broadening Tops
Cup and Handle
Inverted cup and handle
Diamond Bottom
Diamond Top
Falling Wedge
Rising Wedge
Pipe Bottom
Pipe Top
Head and Shoulders
It will calculate the measured move according to the Bulkowski process.
What is the Bulkowski Process?
Each move has an associated continuation percentage, which Bulkowski has studied, analyzed and concluded statistically.
For example, Double tops have a continuation percent of 54%. Bear flags, 47%. These are "constants" that are associated with the pattern.
Bulkowski applies them to the daily, but how I have formulated this, it can be used on all timeframes, and with the constant, it will correctly calculate the measured move of the pattern.
What this indicator DOES NOT DO
This indicator will not identify the pattern for you.
I tried this using Dynamic Time Warping (DTW) using my own pre-trained Bulkowski model in R. I was successfully able to get Pinescript to calculate DTW which was amazing! But applying it to all these patterns actually went over the execution time limit, which is understandable.
As such, you will need to identify the pattern yourself, then use this indicator to hilight the pattern and it will calculate the measured move based on the constant and the pattern range.
Let's look at some examples:
Use examples
Double bottom / adam eve bottom on SPY on the 1-Minute chart
Adam and Eve Double Bottom QQQ 1-Hour Chart
Adam Eve Double Bottom MSFT Daily Chart
Bearish Head and Shoulders Pattern MSFT Daily
You get the point.
How to use the indicator
To use the indicator, identify the pattern of interest to you.
Then, highlight the pattern using the indicator (it will ask you to select start time of the pattern and end time of the pattern). The indicator will then highlight the pattern and calculate the measured move, as seen in the examples above.
Best approaches
To make the most of the indicator, its best to draw out your pattern and wait for an actual break, the point of the break is usually the end of the pattern formation.
From here, you will then apply this indicator to calculate the expected up or down move.
Let me show you an example:
Here we see CME_MINI:ES1! has made an Adam bottom pattern. We know the Eve should be forming soon and it indeed does:
We mark the top of the pattern like so:
Then we use our Measured move indicator to calculate the measured move:
Measured move here for CME_MINI:ES1! is 6,510.
Now let's see....
Voila!
Selecting the Pattern
After you highlight the selected pattern, in the indicator settings, simply select the type of pattern it is, for example "head and shoulders" or "Broadening wedge", etc.
The indicator will then adjust its measurements to the appropriate constant and direction.
Concluding remarks
That is the indicator!
It is helpful for determining the actual projected move of a pattern on breakout.
Remember, it does not find the pattern for you , you are responsible for identifying the pattern. But this will calculate the actual TP of the pattern for you, without you having to do your own calculations.
I hope you find it useful, I actually use this indicator every day, especially on the lower timeframes!
And you will find, the more you use it, the better you get at recognizing significant patterns!
If you are not aware of these patterns, Bulkowski lists all of this information freely accessible on his website. I cannot link it here but you can just Google him and he has graciously made his information public and free!
That's it, I hope you enjoy and safe trades!
Disclaimer
This is not my intellectual property. The pattern calculations come from the work of Thomas Bulkowski and not myself. I simply coded this into an indicator using his publicly accessible information.
You can get more information from Bulkowski's official website about his work and patterns.
TOP GAINER V2
The "TOP GAINER" is a custom TradingView indicator designed to identify and trade high-potential momentum stocks, particularly top pre-market gainers with strong hype and volatility. It's tailored for day traders focusing on small-cap, low-float stocks that exhibit explosive price movements, allowing for quick entries and exits to capitalize on short-term pumps. This indicator combines technical signals (MACD, RSI, and EMA) with fundamental filters to spot setups in pre-market and early regular trading hours, ideally on a 5-minute chart for precise timing.
Key Features and How It Works
Scanning for Top Gainers: The indicator targets stocks that are among the day's top pre-market performers. It evaluates criteria like:
Price Range ($2–$20): Focuses on affordable stocks where you can buy a large number of shares with limited capital. Lower-priced stocks often have higher volatility, enabling them to double, triple, or more in a single session due to hype-driven momentum.
Pre-Market Gain (≥20%): Identifies stocks with significant upside from the pre-market open (4:00 AM ET), signaling strong early interest and potential for continuation.
High Volume (≥500,000 shares from pre-market open): Ensures liquidity and confirms genuine hype, as elevated pre-market volume often precedes big moves at market open.
Small Market Cap (<$500M): Prioritizes small-cap companies, which are more prone to rapid price swings from news, catalysts, or retail frenzy compared to large caps.
Low Float (<50M shares): Low-float stocks have fewer shares available for trading, making them susceptible to sharp rallies when demand surges (e.g., from social media buzz or short squeezes).
These criteria are displayed in a real-time table on the chart for quick scanning—green checkmarks (✅) indicate a match, red crosses (❌) show failures, and "N/A" appears if data is unavailable (e.g., for non-stocks).
Entry Signals (Buy Opportunities): Once a stock meets the filters, the indicator watches for bullish momentum during pre-market or at market open:
EMA Exit (default enabled): Sells when price crosses below a 40-period EMA (orange line), signaling a potential trend reversal. STRONGLY RECOMMEND TURNING THIS OFF
MACD Exit (default enabled, now using standard line/signal crossunder): Sells on a bearish MACD crossover for momentum-based exits.
Plots orange (EMA) or red (MACD) downward triangles above the bar for exits.
Built-in alerts notify you of buy and sell signals in real-time.
Why This Strategy?
This indicator is built for "hype trading" on volatile small-caps, where pre-market scanners highlight gappers, and the tool helps time entries post-open (e.g., on 5-min charts) to catch breakouts. Small floats and caps amplify moves— a 20%+ gainer with high volume can surge 50–200% intraday due to supply/demand imbalances. The $2–$20 range keeps it accessible: with $1,000, you could buy 500 shares of a $2 stock, turning a $1 gain into $500 profit. It's not for long-term investing but for scalping or swinging on daily catalysts like earnings, news, or memes.
Usage Tips
This tool streamlines spotting and trading "lotto plays" while providing visual and alert-based discipline for entries/exits.
Candle Range Theory Range FinderThe video below will explain how to use the indicator.
In a nutshell, it'll shows range candles after 2 strong closes below a prior day's low or above a prior day's high for a possible range candle to trade a reversal off of.
Red arrows are to be treated as a range where you may want to start to look for longs.
Green arrows show where a range where you may want to look for shorts.
Again, the video will make it clearer.
