Smart Money Tracker [JOAT]Smart Money Tracker
Introduction
The Smart Money Tracker is an open-source indicator that combines institutional order flow concepts including Fair Value Gaps (FVG), Order Blocks (OB), Breaker Blocks, Liquidity Sweeps, Market Structure Breaks, and Displacement patterns. This mashup creates a comprehensive Smart Money Concepts (SMC) analysis system designed to identify where institutional traders are positioning themselves and how they manipulate price to accumulate or distribute positions.
The indicator addresses a fundamental market reality: institutional traders with large capital cannot simply buy or sell at market prices without moving the market against themselves. They must use sophisticated techniques including liquidity sweeps, gap creation, and order block manipulation. By tracking these institutional footprints simultaneously, this tool helps retail traders align with smart money rather than becoming their liquidity.
Chart showing FVG zones, Order Blocks, liquidity sweeps, and market structure on 15M timeframe
Why This Mashup Exists
This indicator combines six Smart Money Concepts that reveal different aspects of institutional behavior:
Fair Value Gaps (FVG): Inefficient price delivery zones where institutions moved price quickly
Order Blocks (OB): Last opposite-direction move before impulse, showing accumulation/distribution
Breaker Blocks: Failed Order Blocks that signal potential trend reversal
Liquidity Sweeps: Stop hunts where institutions trigger retail stops before real move
Market Structure: Break of Structure (BOS) and Change of Character (CHoCH) patterns
Displacement: Strong institutional moves with high volume and large candles
Each concept reveals different institutional tactics: FVGs show where they moved fast, Order Blocks show where they accumulated, Breaker Blocks show failed accumulation, Liquidity Sweeps show stop hunts, Market Structure shows control shifts, and Displacement shows strong directional intent. Together, they create a complete picture of institutional order flow that no single concept can provide.
The mashup is justified because these concepts work together in institutional trading sequences: institutions sweep liquidity, create FVGs during displacement, leave Order Blocks at accumulation zones, and break market structure when taking control. Tracking all simultaneously reveals the complete institutional playbook.
Core Components Explained
1. Fair Value Gap (FVG) Detection
FVGs occur when price moves so quickly that it leaves an unfilled gap:
// Bullish FVG: Current low > high from 2 bars ago
bullishFVG = low > high and close > high
fvgTop = low
fvgBottom = high
fvgSize = ((fvgTop - fvgBottom) / fvgBottom) * 100
// Bearish FVG: Current high < low from 2 bars ago
bearishFVG = high < low and close < low
fvgTop = low
fvgBottom = high
fvgSize = ((fvgTop - fvgBottom) / fvgBottom) * 100
FVG significance:
Represents inefficient price delivery - institutions moved too fast
Price often returns to "fill" these gaps before continuing
Larger FVGs (> 0.5%) are more significant
FVGs act as support/resistance zones
Multiple unfilled FVGs suggest strong directional intent
The indicator draws boxes for FVGs and tracks when they get "mitigated" (price returns to fill them). Timeframe-adaptive limits prevent clutter (fewer boxes on higher timeframes).
2. Order Block Identification
Order Blocks mark where institutions accumulated or distributed positions:
// Bullish Order Block
// Two consecutive bearish candles + strong bullish candle with high volume
bullishOB = close < open and
close < open and
close > open and
volume > volumeMA * 1.5
obHigh = high
obLow = low
// Bearish Order Block
// Two consecutive bullish candles + strong bearish candle with high volume
bearishOB = close > open and
close > open and
close < open and
volume > volumeMA * 1.5
Order Block characteristics:
Last opposite-direction move before strong impulse
Represents institutional accumulation (bullish OB) or distribution (bearish OB)
Often provides support/resistance on retests
Volume confirmation ensures institutional participation
Stronger OBs have larger candles and higher volume
The indicator draws solid boxes for Order Blocks and tracks their strength based on volume and candle size. Timeframe-adaptive filtering ensures only significant OBs are displayed.
3. Breaker Block Detection
Breaker Blocks are failed Order Blocks that signal potential reversals:
// Track last bullish and bearish Order Block levels
var float lastBullOBHigh = na
var float lastBearOBLow = na
if bullishOB
lastBullOBHigh := high
if bearishOB
lastBearOBLow := low
// Breaker Bull: Price breaks above failed bearish OB
breakerBull = not na(lastBearOBLow) and
close > lastBearOBLow and
close <= lastBearOBLow
// Breaker Bear: Price breaks below failed bullish OB
breakerBear = not na(lastBullOBHigh) and
close < lastBullOBHigh and
close >= lastBullOBHigh
Breaker Block significance:
Failed Order Blocks often become strong support/resistance in opposite direction
Indicate institutional position reversal
High-probability reversal zones when combined with other SMC signals
Often mark major trend changes
The indicator marks Breaker Blocks with "BB" labels and tracks them as potential reversal zones.
4. Liquidity Sweep Analysis
Liquidity Sweeps identify stop hunts before real moves:
lookbackBars = 20
// Recent highs and lows (liquidity pools)
recentHigh = ta.highest(high, lookbackBars)
recentLow = ta.lowest(low, lookbackBars)
// Liquidity Sweep High (stop hunt above recent high)
liquiditySweepHigh = high > recentHigh and
close < recentHigh and
volume > volumeMA * 1.5
// Liquidity Sweep Low (stop hunt below recent low)
liquiditySweepLow = low < recentLow and
close > recentLow and
volume > volumeMA * 1.5
// Strong sweeps have higher volume
strongSweep = volume > volumeMA * 2.5
Liquidity Sweep characteristics:
Price briefly exceeds recent high/low to trigger stops
Closes back inside range - "fake breakout"
High volume confirms institutional participation
Often precedes strong moves in opposite direction
"Strong" sweeps (very high volume) are more reliable
The indicator places "LIQ" and "STRONG LIQ" labels precisely at sweep tips (above bars for high sweeps, below bars for low sweeps) with timeframe-adaptive spacing to prevent overlap.
5. Market Structure Analysis
Market structure tracks control shifts between buyers and sellers:
// Break of Structure (BOS)
// Price breaks beyond previous swing high/low in trend direction
bullishBOS = close > ta.highest(high , 20) and trend == bullish
bearishBOS = close < ta.lowest(low , 20) and trend == bearish
// Change of Character (CHoCH)
// Price breaks structure against trend - potential reversal
bullishCHoCH = close > ta.highest(high , 20) and trend == bearish
bearishCHoCH = close < ta.lowest(low , 20) and trend == bullish
Market Structure significance:
BOS confirms trend continuation
CHoCH signals potential trend reversal
Helps identify when institutional control shifts
Provides context for other SMC signals
The indicator marks BOS and CHoCH with labels and uses them to determine overall market bias.
6. Displacement Detection
Displacement identifies strong institutional moves:
atr = ta.atr(14)
// Displacement: Large candle (> 2x ATR) with climax volume
displacement = math.abs(close - open) > atr * 2 and
volume > volumeMA * 3.0
bullishDisplacement = displacement and close > open
bearishDisplacement = displacement and close < open
Displacement characteristics:
Very large candles relative to ATR
Climax volume (> 3x average)
Indicates strong institutional directional intent
Often creates FVGs
Signals potential trend acceleration
The indicator marks displacement with "DISP" labels and uses them to identify high-conviction institutional moves.
Example showing all SMC concepts: FVGs, Order Blocks, Breaker Blocks, and liquidity sweeps
Timeframe-Adaptive System
The indicator automatically adjusts based on timeframe to prevent clutter:
// Higher timeframes (2H+): Fewer boxes, larger minimum sizes
if timeframe >= 120 minutes:
maxFVGs = 12
maxOBs = 10
minFVGSize = 0.5%
minOBSize = 0.8%
labelSpacing = 15 bars
// Medium timeframes (1H): Moderate filtering
else if timeframe >= 60 minutes:
maxFVGs = 15
maxOBs = 12
minFVGSize = 0.4%
minOBSize = 0.6%
labelSpacing = 12 bars
// Lower timeframes (15M): More boxes, smaller minimum sizes
else:
maxFVGs = 20-25
maxOBs = 15-20
minFVGSize = 0.3%
minOBSize = 0.4%
labelSpacing = 8-10 bars
This ensures the indicator remains useful across all timeframes without overwhelming the chart.
SMC Confluence Dashboard
The dashboard (top-right position) displays:
Market Bias: Bullish/Bearish/Neutral based on structure
Active FVGs: Count of unfilled Fair Value Gaps
Active OBs: Count of untested Order Blocks
Recent Sweeps: Liquidity sweeps in last 50 bars
Structure: Last BOS or CHoCH type
Displacement: Recent displacement direction
SMC Score: Overall confluence (0-10)
SMC Score calculation:
SMC Score Components:
- Significant FVG present: +2 points
- Strong Order Block present: +2 points
- Breaker Block active: +1 point
- Recent liquidity sweep: +2 points
- Displacement in direction: +3 points
Total: 0-10 points
Visual Elements
FVG Boxes: Green (bullish) and red (bearish) boxes, removed when mitigated
Order Block Boxes: Solid green/red boxes with strength-based transparency
Breaker Block Labels: "BB" markers at breaker zones
Liquidity Sweep Labels: "LIQ" and "STRONG LIQ" at sweep tips
Displacement Labels: "DISP" markers on displacement candles
Structure Labels: "BOS" and "CHoCH" at structure breaks
Mitigation Markers: Small circles when FVGs get filled
Dashboard: Top-right table with SMC metrics
How Components Work Together
The mashup reveals institutional trading sequences:
Sequence 1 - Accumulation:
1. Liquidity Sweep triggers retail stops
2. Order Block forms as institutions accumulate
3. Displacement occurs as institutions push price
4. FVG created during fast move
5. BOS confirms trend direction
Sequence 2 - Reversal:
1. Multiple liquidity sweeps fail to extend trend
2. Order Block fails, becomes Breaker Block
3. CHoCH signals control shift
4. Opposite-direction displacement
5. New trend structure forms
Example: Price sweeps below recent lows (liquidity sweep), then strongly reverses with high volume (displacement), leaving a bullish FVG. A bullish Order Block forms at the reversal zone. Price breaks above previous structure (BOS). SMC Score reaches 9/10, signaling strong bullish institutional setup.
Input Parameters
FVG Settings:
Show FVGs: Toggle FVG boxes (default: enabled)
Min FVG Size: Minimum gap size % (default: 0.3%)
Max FVG Boxes: Limit displayed boxes (default: timeframe-adaptive)
Show Mitigation: Mark when FVGs get filled (default: enabled)
Order Block Settings:
Show Order Blocks: Toggle OB boxes (default: enabled)
Min OB Strength: Minimum volume multiplier (default: 1.5x)
Max OB Boxes: Limit displayed boxes (default: timeframe-adaptive)
OB Lookback: Bars to track OBs (default: 100)
Liquidity Settings:
Show Liquidity Sweeps: Toggle sweep labels (default: enabled)
Lookback Bars: Period for liquidity pools (default: 20)
Strong Sweep Threshold: Volume multiplier (default: 2.5x)
Label Spacing: Minimum bars between labels (default: timeframe-adaptive)
Structure Settings:
Show Structure: Toggle BOS/CHoCH labels (default: enabled)
Show Breaker Blocks: Toggle BB labels (default: enabled)
Show Displacement: Toggle DISP labels (default: enabled)
Structure Sensitivity: Swing detection period (default: 20)
Display Options:
Show Dashboard: Toggle SMC dashboard (default: enabled)
Timeframe Adaptive: Auto-adjust limits (default: enabled)
Remove Extensions: Don't extend boxes right (default: enabled)
Color Theme: Choose color scheme
How to Use This Indicator
Step 1: Identify Market Structure
Check for recent BOS or CHoCH. BOS suggests trend continuation, CHoCH suggests potential reversal.
Step 2: Look for Liquidity Sweeps
Liquidity sweeps often precede strong moves in opposite direction. "STRONG LIQ" sweeps are particularly significant.
Step 3: Identify Order Blocks
Look for Order Blocks in the direction of intended trade. OBs often provide high-probability entry zones on retests.
Step 4: Check for FVGs
Unfilled FVGs act as magnets - price often returns to fill them. Can be used for entry targets or profit-taking zones.
Step 5: Watch for Displacement
Displacement signals strong institutional intent. When displacement occurs from an Order Block, it confirms the zone's validity.
Step 6: Monitor Breaker Blocks
Failed Order Blocks (Breaker Blocks) often mark major reversals. These are high-probability reversal zones.
Step 7: Review SMC Score
Check dashboard SMC Score. Scores above 7 indicate strong institutional confluence.
Best Practices
Use on 15-minute to 4-hour timeframes for optimal SMC signal quality
Liquidity sweeps followed by displacement are extremely high-probability setups
Order Block retests with FVG confluence provide excellent risk:reward entries
Wait for price to return to Order Blocks rather than chasing displacement
Multiple unfilled FVGs in same direction suggest strong institutional intent
Breaker Blocks combined with CHoCH signal major trend reversals
Higher timeframe SMC signals are more reliable than lower timeframe
Use SMC Score as filter - focus on setups with 7+ score
Combine with traditional support/resistance for additional confirmation
Indicator Limitations
Not all FVGs get filled - some remain unfilled in strong trends
Order Blocks don't always provide support/resistance on retest
Liquidity sweeps can be followed by additional sweeps (multiple stop hunts)
Timeframe-adaptive filtering may hide some valid signals
Requires understanding of Smart Money Concepts for effective use
Visual elements can clutter chart even with adaptive limits
SMC concepts work best in trending markets, less effective in ranges
Institutional behavior patterns can change over time
No SMC system eliminates false signals entirely
Technical Implementation
Built with Pine Script v6 using:
Box management system with automatic cleanup
Timeframe-adaptive limits and filtering
Anti-overlap logic for all labels with dynamic spacing
FVG mitigation tracking with visual markers
Order Block strength calculation based on volume and size
Liquidity pool identification with sweep detection
Market structure tracking with BOS/CHoCH logic
Displacement detection using ATR and volume
Real-time SMC confluence scoring
Comprehensive dashboard with all SMC metrics
The code is fully open-source and can be modified to adjust thresholds, visual preferences, and filtering criteria.
Originality Statement
This indicator is original in its comprehensive SMC integration approach. While individual concepts (FVG, Order Blocks, Breaker Blocks, Liquidity Sweeps, Market Structure, Displacement) are established Smart Money Concepts, this mashup is justified because:
It tracks all major SMC concepts simultaneously in one indicator
Timeframe-adaptive system prevents clutter while maintaining functionality
Anti-overlap logic ensures clean visual presentation
SMC confluence scoring quantifies institutional setup quality
Integration reveals complete institutional trading sequences
Enhanced visual elements (precise label positioning, mitigation markers) improve usability
Each SMC concept reveals different institutional behavior: FVGs show fast moves, Order Blocks show accumulation, Breaker Blocks show failed accumulation, Liquidity Sweeps show stop hunts, Market Structure shows control shifts, and Displacement shows strong intent. The mashup's value lies in presenting these complementary institutional footprints simultaneously, allowing traders to identify complete institutional trading sequences rather than isolated signals.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss and is not suitable for all investors.
Smart Money Concepts are analytical frameworks based on observations of institutional trading patterns. They do not guarantee that institutions are actually trading at identified zones, nor do they predict future institutional behavior. Market conditions change, and patterns that worked historically may not work in the future.
The SMC Score is a mathematical calculation based on current market structure, not a prediction of future price movement. High SMC scores do not ensure profitable trades. Order Blocks, FVGs, and other SMC zones can fail to provide support/resistance. Liquidity sweeps can be followed by additional sweeps.
Always use proper risk management, including stop losses and position sizing appropriate for your account size and risk tolerance. Never risk more than you can afford to lose. Consider consulting with a qualified financial advisor before making investment decisions.
The author is not responsible for any losses incurred from using this indicator. Users assume full responsibility for all trading decisions made using this tool.
-Made with passion by officialjackofalltrades Indicator
Advanced Divergence Hunter [JOAT]Advanced Divergence Hunter
Introduction
The Advanced Divergence Hunter is an open-source multi-oscillator indicator that simultaneously tracks divergences across six different momentum indicators: RSI, MACD, Stochastic RSI, CCI, MFI, and Williams %R. This mashup creates a comprehensive divergence detection system designed to identify momentum exhaustion and potential reversals by analyzing when multiple oscillators simultaneously show divergence from price action.
The indicator addresses a critical limitation of single-oscillator divergence detection: false signals. By requiring confluence across multiple oscillators using different calculation methods, this tool significantly reduces false divergence signals and highlights only the most reliable momentum exhaustion patterns that occur when price and momentum fundamentally disconnect across multiple measurement frameworks.
Chart showing multiple divergence signals across oscillators with dashboard on 1H timeframe
Why This Mashup Exists
This indicator combines six oscillators that detect divergences using fundamentally different methodologies:
RSI: Momentum oscillator based on average gains vs losses
MACD: Trend-following momentum using EMA convergence/divergence
Stochastic RSI: Stochastic calculation applied to RSI for enhanced sensitivity
CCI (Commodity Channel Index): Measures deviation from statistical mean
MFI (Money Flow Index): Volume-weighted RSI showing buying/selling pressure
Williams %R: Momentum indicator measuring overbought/oversold using highest high/lowest low
Each oscillator responds to different market dynamics: RSI tracks momentum speed, MACD shows trend strength changes, Stochastic RSI catches early shifts, CCI identifies statistical extremes, MFI incorporates volume, and Williams %R uses price extremes. When multiple oscillators show divergence simultaneously, it indicates genuine momentum exhaustion rather than noise from a single calculation method.
The mashup is justified because these oscillators use distinct mathematical approaches (rate of change, moving average convergence, stochastic, statistical deviation, volume-weighted, price extremes) that respond to different aspects of price movement. Confluence across multiple methods provides significantly higher reliability than any single divergence signal.
Example showing all six oscillators with divergence markers and alignment indicators
Core Components Explained
1. RSI Divergence Detection
Standard RSI calculation with pivot-based divergence logic:
rsi = ta.rsi(close, 14)
// Identify swing points
pivotHigh = ta.pivothigh(rsi, 5, 5)
pivotLow = ta.pivotlow(rsi, 5, 5)
// Regular Bullish Divergence
// Price: Lower Low, RSI: Higher Low
bullDiv = priceLow < prevPriceLow AND rsiLow > prevRSILow
// Regular Bearish Divergence
// Price: Higher High, RSI: Lower High
bearDiv = priceHigh > prevPriceHigh AND rsiHigh < prevRSIHigh
2. MACD Histogram Divergence
MACD histogram divergences often lead price divergences:
= ta.macd(close, 12, 26, 9)
// Histogram divergence detection
// Bullish: Price LL, Histogram HL
// Bearish: Price HH, Histogram LH
The indicator plots MACD histogram with enhanced visualization and tracks divergences separately from RSI.
3. Stochastic RSI Divergence
More sensitive than regular RSI, catches early momentum shifts:
stochRSI = ta.stoch(rsi, rsi, rsi, 14)
// K and D line divergences
// Often diverges before regular RSI
Stochastic RSI K and D lines are plotted, and divergences on both lines are tracked independently.
4. CCI Divergence Detection
CCI measures price deviation from statistical mean:
cci = ta.cci(close, 20)
// CCI divergences indicate statistical exhaustion
// Bullish: Price LL, CCI HL
// Bearish: Price HH, CCI LH
CCI divergences are particularly reliable at extreme levels (> +100 or < -100).
5. MFI Divergence (Volume-Weighted)
MFI incorporates volume, making divergences more significant:
// Calculate typical price
typicalPrice = (high + low + close) / 3
// Money flow with volume
rawMoneyFlow = typicalPrice * volume
// MFI calculation
mfi = 100 - (100 / (1 + positiveFlow / negativeFlow))
// Volume divergences often lead price
// Bullish: Price LL, MFI HL (buying pressure increasing)
// Bearish: Price HH, MFI LH (selling pressure increasing)
MFI divergences are weighted more heavily in the confluence system because they incorporate volume.
6. Williams %R Divergence
Williams %R uses highest high and lowest low:
williamsR = -100 * (ta.highest(high, 14) - close) / (ta.highest(high, 14) - ta.lowest(low, 14))
// Divergences at extreme levels (-80 to -100 or -20 to 0)
// Bullish: Price LL, Williams %R HL
// Bearish: Price HH, Williams %R LH
Williams %R divergences are most reliable when oscillator is in extreme zones.
Divergence Confluence System
The indicator tracks divergences across all six oscillators and calculates confluence:
Divergence Confluence Score:
- Single oscillator divergence: 1 point
- Two oscillators: 2 points
- Three oscillators: 4 points
- Four oscillators: 7 points
- Five oscillators: 11 points
- All six oscillators: 15 points (MEGA divergence)
Divergence classification:
Weak Divergence: 1-2 oscillators (score 1-2)
Moderate Divergence: 3 oscillators (score 4)
Strong Divergence: 4 oscillators (score 7)
Very Strong Divergence: 5 oscillators (score 11)
MEGA Divergence: All 6 oscillators (score 15)
The dashboard displays which oscillators are showing divergence and the total confluence score.
Oscillator Alignment Analysis
Beyond divergences, the indicator tracks oscillator alignment:
Alignment Score:
- RSI in healthy range (40-60 bull, 60-40 bear): +1
- MACD histogram direction: +1
- Stochastic RSI position: +1
- CCI direction: +1
- MFI level: +1
- Williams %R position: +1
Total Alignment: 0-6 points
Alignment interpretation:
5-6 aligned: Strong momentum consensus
3-4 aligned: Moderate momentum
0-2 aligned: Weak or conflicting momentum
Enhanced Dashboard System
The indicator features an 11-row dashboard showing:
Row 1: Overall momentum direction (BULL/BEAR/NEUTRAL)
Row 2: Divergence confluence score with color coding
Row 3: RSI value and divergence status
Row 4: MACD histogram status
Row 5: Stochastic RSI K value
Row 6: CCI value and status
Row 7: MFI value and divergence status
Row 8: Williams %R value
Row 9: Momentum strength (0-100)
Row 10: Oscillator alignment (X/6 aligned)
Row 11: Active divergences count
Dashboard showing divergence confluence with individual oscillator breakdown
Visual Elements
Oscillator Lines: All six oscillators plotted with distinct colors
Divergence Labels: "DIV" markers at divergence points, sized by confluence
Confluence Markers: Large diamond shapes for MEGA divergences (6/6)
Background Zones: Color-coded backgrounds for extreme conditions
Overbought/Oversold Lines: Reference levels for each oscillator
Zero/Midpoint Lines: Centerline references
Histogram Bars: MACD histogram with gradient coloring
Dashboard: Comprehensive table with all oscillator readings
How Components Work Together
The mashup creates layered divergence analysis:
Layer 1 - Individual Detection: Each oscillator independently detects divergences
Layer 2 - Confluence Calculation: System counts how many oscillators show divergence
Layer 3 - Weighting: Volume-based divergences (MFI) weighted more heavily
Layer 4 - Alignment Check: Verifies overall oscillator consensus
Layer 5 - Extreme Zones: Identifies when divergences occur at statistical extremes
Layer 6 - Signal Generation: Produces graded signals based on confluence strength
Example scenario: Price makes higher high, but RSI, MACD, Stochastic RSI, and MFI all make lower highs (4/6 divergence). CCI and Williams %R are in extreme overbought zones. Confluence score is 7 (Strong Divergence), and dashboard shows 4 active divergences. This signals high-probability bearish reversal setup.
Input Parameters
Oscillator Settings:
RSI Length: Period for RSI (default: 14)
MACD Settings: Fast 12, Slow 26, Signal 9
Stochastic RSI Length: Period for Stoch RSI (default: 14)
CCI Length: Period for CCI (default: 20)
MFI Length: Period for MFI (default: 14)
Williams %R Length: Period for Williams %R (default: 14)
Divergence Settings:
Pivot Lookback: Bars for pivot detection (default: 5)
Min Confluence: Minimum oscillators for signal (default: 3)
Show All Divergences: Display single-oscillator divergences (default: disabled)
Show Only Strong: Display only 4+ confluence (default: enabled)
Display Options:
Show Dashboard: Toggle dashboard (default: enabled)
Show Oscillators: Toggle oscillator plots (default: enabled)
Show Background Zones: Toggle extreme zone coloring (default: enabled)
Dashboard Position: Top-right, bottom-right, etc.
How to Use This Indicator
Step 1: Monitor Divergence Confluence
Watch the dashboard divergence score. Wait for 3+ oscillators showing divergence (score 4+) before considering reversal trades.
Step 2: Check Oscillator Extremes
Divergences are most reliable when oscillators are in extreme zones (RSI > 70 or < 30, MFI > 80 or < 20, etc.).
Step 3: Verify Alignment
Check oscillator alignment score. Low alignment (0-2) with high divergence confluence suggests strong reversal potential.
Step 4: Identify MEGA Divergences
When all 6 oscillators show divergence (MEGA), it signals extremely high probability reversal setup. These are rare but very reliable.
Step 5: Confirm with Price Action
Wait for price action confirmation (reversal candlestick patterns, trendline breaks) before entering trades based on divergences.
Step 6: Use for Exit Signals
If holding trend-following position and strong divergence appears, consider taking profits or tightening stops.
Best Practices
Use on 15-minute to 4-hour timeframes for optimal divergence reliability
Wait for 3+ oscillator confluence before acting on divergence signals
MEGA divergences (6/6) are rare but extremely reliable - don't ignore them
MFI divergences are particularly significant because they incorporate volume
Divergences in strong trends often lead to pullbacks, not full reversals
Combine with support/resistance levels for precise entry timing
Hidden divergences signal trend continuation, regular divergences signal reversal
Multiple consecutive divergences increase reversal probability
Use oscillator alignment to gauge overall momentum health
Indicator Limitations
Divergences can persist for extended periods before reversal occurs
Strong trends can continue despite multiple oscillator divergences
Pivot-based detection means divergences are confirmed with lag
False divergences can occur in choppy, ranging markets
MEGA divergences are rare - waiting only for these may miss opportunities
Oscillator calculations vary in sensitivity - some may diverge prematurely
Requires understanding of each oscillator's characteristics
No divergence system eliminates false signals entirely
Performance varies across different markets and volatility regimes
Technical Implementation
Built with Pine Script v6 using:
Six independent oscillator calculations
Pivot-based divergence detection for each oscillator
Confluence scoring algorithm with weighted components
Oscillator alignment tracking system
Enhanced 11-row dashboard with real-time updates
Dynamic background zones for extreme conditions
Anti-overlap logic for divergence labels
Gradient coloring for MACD histogram
The code is fully open-source and can be modified to adjust oscillator parameters, confluence thresholds, and visual preferences.
Originality Statement
This indicator is original in its multi-oscillator divergence confluence approach. While individual oscillators (RSI, MACD, Stochastic RSI, CCI, MFI, Williams %R) are established tools, this mashup is justified because:
It tracks divergences across six oscillators using fundamentally different calculations
The confluence scoring system quantifies divergence strength across multiple methods
Integration of volume-weighted divergence (MFI) with price-based oscillators
Oscillator alignment analysis provides momentum consensus measurement
Enhanced dashboard presents complex multi-oscillator data clearly
MEGA divergence detection identifies extremely rare, high-probability setups
Each oscillator contributes unique divergence information: RSI shows momentum speed divergence, MACD shows trend strength divergence, Stochastic RSI catches early divergences, CCI shows statistical divergence, MFI shows volume-weighted divergence, and Williams %R shows price extreme divergence. The mashup's value lies in identifying when multiple independent calculation methods simultaneously show momentum exhaustion, significantly reducing false signals.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss and is not suitable for all investors.
Divergence indicators are analytical tools that identify potential momentum exhaustion, not guarantees of reversals. Divergences can persist for extended periods, and strong trends can continue despite multiple divergence signals. Past divergence performance does not guarantee future results.
The confluence score is a mathematical calculation based on current oscillator readings, not a prediction of future price movement. High confluence scores do not ensure profitable trades. Market conditions change, and divergence patterns that worked historically may not work in the future.
Always use proper risk management, including stop losses and position sizing appropriate for your account size and risk tolerance. Never risk more than you can afford to lose. Consider consulting with a qualified financial advisor before making investment decisions.
The author is not responsible for any losses incurred from using this indicator. Users assume full responsibility for all trading decisions made using this tool.
-Made with passion by officialjackofalltrades Indicator
Multi-Timeframe Strength Scanner [JOAT]Multi-Timeframe Strength Scanner
Introduction
The Multi-Timeframe Strength Scanner is an open-source indicator that combines higher timeframe trend analysis with current timeframe momentum indicators to create a comprehensive market strength assessment system. This mashup integrates ADX (Average Directional Index), Donchian Channels, VWAP (Volume Weighted Average Price), RSI divergence detection, and multi-timeframe EMA analysis into a unified scanner that identifies when trend strength aligns across multiple timeframes.
The indicator addresses a critical trading challenge: signals that look strong on one timeframe often fail because higher timeframes are moving in the opposite direction. By analyzing 15-minute, 1-hour, and 4-hour timeframes simultaneously while monitoring current timeframe momentum, this tool helps traders avoid counter-trend trades and identify high-probability setups where multiple timeframes align.
Chart showing multi-timeframe alignment dashboard and strength indicators on 15M timeframe
Why This Mashup Exists
This indicator combines five analytical frameworks that address different aspects of trend strength:
ADX Analysis: Measures trend strength regardless of direction using directional movement
Donchian Channels: Identifies breakouts and trend continuation using price extremes
VWAP: Shows institutional average price and volume-weighted fair value
RSI Divergence: Detects momentum exhaustion at current timeframe swing points
Multi-Timeframe EMAs: Confirms trend direction across 15M, 1H, and 4H timeframes
Each component serves a specific purpose: ADX quantifies trend strength, Donchian Channels identify breakout momentum, VWAP reveals institutional positioning, RSI divergences warn of reversals, and multi-timeframe EMAs ensure directional alignment. Together, they create a strength scanner that filters out weak, counter-trend setups and highlights only those with multi-timeframe confirmation.
The mashup is justified because these components use fundamentally different data (directional movement, price extremes, volume-weighted averages, momentum oscillators, moving averages) that respond to different market conditions. When they align, it indicates genuine trend strength rather than temporary momentum.
Core Components Explained
1. ADX Trend Strength System
ADX (Average Directional Index) measures trend strength on a scale of 0-100:
= ta.dmi(adxLength, adxLength)
// Trend strength classification
strongTrend = adx > adxThreshold // Default: 20
veryStrongTrend = adx > 40
extremeTrend = adx > 60
// Direction determination
bullishTrend = plus > minus
bearishTrend = minus > plus
ADX interpretation:
ADX < 20: Weak trend or ranging market - avoid trend-following strategies
ADX 20-40: Moderate trend strength - standard trend-following viable
ADX 40-60: Strong trend - high-probability trend continuation
ADX > 60: Extreme trend - potential exhaustion or very strong momentum
The indicator plots ADX as a line with color coding:
Green: Strong bullish trend (ADX > 20, +DI > -DI)
Red: Strong bearish trend (ADX > 20, -DI > +DI)
Gray: Weak trend or ranging (ADX < 20)
2. Donchian Channel Breakout System
Donchian Channels track the highest high and lowest low over a specified period:
donchianLength = 20 // Configurable
upperChannel = ta.highest(high, donchianLength)
lowerChannel = ta.lowest(low, donchianLength)
midChannel = (upperChannel + lowerChannel) / 2
Breakout signals:
Bullish Breakout: Close above upper channel = new 20-bar high
Bearish Breakout: Close below lower channel = new 20-bar low
Channel Position: Price near upper channel = bullish strength, near lower = bearish strength
The indicator uses Donchian breakouts to confirm trend strength. When price breaks out of the channel with strong ADX, it signals high-momentum trend continuation.
3. VWAP Analysis
VWAP (Volume Weighted Average Price) calculates the average price weighted by volume:
vwap = ta.vwap(hlc3)
// Position analysis
aboveVWAP = close > vwap // Bullish positioning
belowVWAP = close < vwap // Bearish positioning
// Distance from VWAP
vwapDistance = ((close - vwap) / vwap) * 100
VWAP significance:
Institutional traders use VWAP as benchmark for execution quality
Price above VWAP = buyers in control, institutions paying premium
Price below VWAP = sellers in control, institutions getting discount
Large distance from VWAP = potential mean reversion opportunity
VWAP acts as dynamic support/resistance level
The indicator plots VWAP with dynamic coloring based on price position and uses it for trend confirmation.
4. RSI Divergence Detection
The indicator detects divergences using pivot-based analysis:
rsi = ta.rsi(close, 14)
// Identify swing points
pivotHigh = ta.pivothigh(rsi, 5, 5)
pivotLow = ta.pivotlow(rsi, 5, 5)
// Compare current pivot with previous pivot
bullishDivergence = price makes lower low AND rsi makes higher low
bearishDivergence = price makes higher high AND rsi makes lower high
Divergence types:
Regular Bullish: Price LL, RSI HL - momentum improving, potential reversal up
Regular Bearish: Price HH, RSI LH - momentum deteriorating, potential reversal down
Hidden Bullish: Price HL, RSI LL - trend continuation signal in uptrend
Hidden Bearish: Price LH, RSI HH - trend continuation signal in downtrend
Divergences are marked with "DIV" labels and used to warn of potential trend exhaustion or continuation.
5. Multi-Timeframe EMA Analysis
The indicator analyzes trend direction across three higher timeframes:
// Request higher timeframe data
htf15mEMA = request.security(syminfo.tickerid, "15", ta.ema(close, 21))
htf1hEMA = request.security(syminfo.tickerid, "60", ta.ema(close, 21))
htf4hEMA = request.security(syminfo.tickerid, "240", ta.ema(close, 21))
// Determine trend direction
htf15mBullish = close > htf15mEMA
htf1hBullish = close > htf1hEMA
htf4hBullish = close > htf4hEMA
// Count aligned timeframes
bullishCount = (htf15mBullish ? 1 : 0) + (htf1hBullish ? 1 : 0) + (htf4hBullish ? 1 : 0)
bearishCount = (!htf15mBullish ? 1 : 0) + (!htf1hBullish ? 1 : 0) + (!htf4hBullish ? 1 : 0)
Alignment classification:
STRONG BULL: All 3 timeframes bullish (3/3 alignment)
BULL: 2 out of 3 timeframes bullish
MIXED: Timeframes conflicting (1-1-1 or 2-1 split)
BEAR: 2 out of 3 timeframes bearish
STRONG BEAR: All 3 timeframes bearish (3/3 alignment)
Example showing multi-timeframe alignment dashboard with all three timeframes bullish
Strength Scoring System
The indicator calculates a comprehensive strength score (0-100) by evaluating:
Strength Score Components:
- ADX Strength: Up to 25 points (ADX > 40 = 25, ADX > 20 = 15, ADX < 20 = 0)
- ADX Direction: Up to 15 points (+DI > -DI = 15 for bull, -DI > +DI = 15 for bear)
- Donchian Position: Up to 15 points (breakout = 15, near channel = 10, mid-channel = 5)
- VWAP Position: Up to 15 points (above VWAP = 15 for bull, below = 15 for bear)
- MTF Alignment: Up to 20 points (3/3 = 20, 2/3 = 13, 1/3 = 7)
- RSI Level: Up to 10 points (healthy range = 10, extreme = 5, divergence = -5)
Score interpretation:
80-100: Extremely strong trend - high-probability continuation
60-79: Strong trend - favorable for trend-following
40-59: Moderate trend - selective trend trades
20-39: Weak trend - caution, potential reversal
0-19: Very weak or counter-trend - avoid trend-following
The dashboard displays the strength score with color coding and individual component breakdown.
Visual Elements
ADX Line: Main trend strength indicator with dynamic coloring
+DI/-DI Lines: Directional movement indicators
ADX Threshold: Horizontal line at 20 (configurable)
Donchian Channels: Upper, middle, and lower channel lines
VWAP Line: Volume-weighted average price with dynamic coloring
Divergence Labels: "DIV" markers at RSI divergence points
Strength Bars: Background coloring based on strength score
Dashboard: Comprehensive table showing:
- Current strength score
- ADX value and direction
- Donchian position
- VWAP position
- MTF alignment (15M, 1H, 4H status)
- RSI level
- Overall trend classification
Chart showing strength dashboard with component breakdown and visual indicators
How Components Work Together
The mashup creates a layered strength analysis:
Layer 1 - Trend Strength: ADX quantifies how strong the trend is
Layer 2 - Breakout Momentum: Donchian Channels identify momentum surges
Layer 3 - Institutional Positioning: VWAP shows where smart money is positioned
Layer 4 - Momentum Health: RSI divergences warn of exhaustion
Layer 5 - Multi-Timeframe Confirmation: HTF EMAs ensure directional alignment
Layer 6 - Synthesis: Strength score combines all factors into actionable metric
Example scenario: ADX is 45 (Layer 1), price breaks above Donchian upper channel (Layer 2), trading above VWAP (Layer 3), no RSI divergence (Layer 4), and all three higher timeframes are bullish (Layer 5). The strength score reaches 90 (Layer 6), signaling extremely strong bullish trend with high continuation probability.
Input Parameters
ADX Settings:
ADX Length: Period for ADX calculation (default: 14)
ADX Threshold: Minimum ADX for strong trend (default: 20)
Show +DI/-DI: Toggle directional indicators (default: enabled)
Donchian Settings:
Donchian Length: Period for channel calculation (default: 20)
Show Channels: Toggle channel display (default: enabled)
Breakout Sensitivity: Threshold for breakout signals (default: close beyond channel)
VWAP Settings:
Show VWAP: Toggle VWAP line (default: enabled)
VWAP Reset: Session, Week, Month, or Never (default: Daily)
Distance Alert: Alert when price moves X% from VWAP (default: 2%)
RSI Settings:
RSI Length: Period for RSI calculation (default: 14)
Show Divergences: Toggle divergence markers (default: enabled)
Pivot Lookback: Bars for pivot detection (default: 5)
Multi-Timeframe Settings:
HTF 1: First higher timeframe (default: 15 minutes)
HTF 2: Second higher timeframe (default: 1 hour)
HTF 3: Third higher timeframe (default: 4 hours)
EMA Length: Period for HTF EMAs (default: 21)
Min Alignment: Minimum timeframes aligned for signal (default: 2/3)
Display Options:
Show Dashboard: Toggle strength score table (default: enabled)
Show Strength Bars: Toggle background coloring (default: enabled)
Dashboard Position: Top-right, top-left, bottom-right, bottom-left
Color Theme: Choose between multiple color schemes
How to Use This Indicator
Step 1: Check Multi-Timeframe Alignment
Review the dashboard MTF section. Look for 2/3 or 3/3 alignment in your intended trade direction. Avoid trades when timeframes are mixed or opposing.
Step 2: Verify ADX Strength
Ensure ADX is above 20 (preferably above 30) for trend-following trades. ADX below 20 suggests ranging market where trend strategies underperform.
Step 3: Confirm Donchian Position
Check if price is near or breaking through Donchian channels. Breakouts with strong ADX signal high-momentum moves.
Step 4: Assess VWAP Position
For long trades, prefer price above VWAP. For short trades, prefer price below VWAP. Large distances from VWAP may indicate overextension.
Step 5: Check for Divergences
Look for RSI divergence warnings. If divergence appears with extreme strength score, consider taking profits or tightening stops.
Step 6: Review Strength Score
Use the overall strength score as final filter. Scores above 70 indicate strong trend conditions favorable for trend-following. Scores below 40 suggest caution.
Best Practices
Use on 5-minute to 1-hour timeframes for optimal multi-timeframe analysis
Wait for 2/3 or 3/3 MTF alignment before entering trend trades
Strong ADX (> 30) with MTF alignment produces highest-probability setups
Donchian breakouts with ADX > 25 often lead to sustained moves
VWAP acts as dynamic support/resistance - use for entry refinement
RSI divergences in strong trends often lead to pullbacks, not reversals
Strength score above 80 suggests strong trend continuation potential
Avoid trading when strength score is below 40 unless counter-trend trading
Combine with price action and key levels for precise entries
Indicator Limitations
ADX is lagging indicator - trend strength confirmed after move has started
Donchian breakouts can produce false signals in choppy markets
VWAP resets daily, may not reflect longer-term institutional positioning
Multi-timeframe analysis requires sufficient data history
Strength score is mathematical calculation, not prediction of future movement
Strong trends can reverse suddenly despite high strength scores
Divergences can persist for extended periods in strong trends
Higher timeframe data may repaint on lower timeframes
Requires understanding of trend analysis concepts for effective use
Technical Implementation
Built with Pine Script v6 using:
DMI/ADX calculation with directional indicators
Donchian Channel calculation with breakout detection
VWAP calculation with session reset options
Pivot-based RSI divergence detection
request.security() for multi-timeframe EMA analysis
Comprehensive strength scoring algorithm
Dynamic dashboard with component breakdown
Background coloring based on strength levels
The code is fully open-source and can be modified to adjust timeframes, thresholds, and scoring weights.
Originality Statement
This indicator is original in its multi-timeframe strength integration approach. While individual components (ADX, Donchian Channels, VWAP, RSI divergence, EMAs) are established tools, this mashup is justified because:
It combines trend strength measurement with multi-timeframe directional confirmation
The strength scoring system quantifies trend quality across multiple dimensions
Multi-timeframe analysis prevents counter-trend trades on lower timeframes
Integration of volume-weighted analysis (VWAP) with momentum indicators
Divergence detection provides early warning within trend strength context
Comprehensive dashboard presents complex multi-timeframe data clearly
Each component contributes unique information: ADX measures trend strength, Donchian identifies breakout momentum, VWAP shows institutional positioning, RSI divergences warn of exhaustion, and MTF EMAs ensure alignment. The mashup's value lies in filtering out weak, counter-trend setups and highlighting only those with genuine multi-timeframe strength confirmation.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss and is not suitable for all investors.
Trend strength indicators are lagging tools that confirm trends after they've begun. Strong trends can reverse suddenly, and high strength scores do not guarantee trend continuation. Multi-timeframe analysis does not eliminate the risk of losses.
The strength score is a mathematical calculation based on current market data, not a prediction of future price movement. Past trend strength does not guarantee future performance. Market conditions change, and trends that appear strong can reverse without warning.
Always use proper risk management, including stop losses and position sizing appropriate for your account size and risk tolerance. Never risk more than you can afford to lose. Consider consulting with a qualified financial advisor before making investment decisions.
The author is not responsible for any losses incurred from using this indicator. Users assume full responsibility for all trading decisions made using this tool.
-Made with passion by officialjackofalltrades Indicator
Harmonic Confluence Wave Detector [JOAT]Harmonic Confluence Wave Detector
Introduction
The Harmonic Confluence Wave Detector is an open-source oscillator-based indicator that combines WaveTrend, Money Flow Index (MFI), RSI, MACD, and Stochastic RSI into a unified momentum analysis system. This mashup creates a multi-layered oscillator framework designed to identify momentum shifts, overbought/oversold conditions, and divergence patterns across multiple timeframes and calculation methods.
The indicator addresses a common trading challenge: single oscillators can give conflicting or premature signals. By synthesizing five different momentum calculations that use distinct mathematical approaches, this tool provides confluence-based signals that occur when multiple momentum indicators align, significantly reducing false signals compared to using any single oscillator alone.
Chart showing WaveTrend oscillator, MACD histogram, and multi-signal system on 1H timeframe
Why This Mashup Exists
This indicator combines five oscillators that complement each other through different calculation methodologies:
WaveTrend: Smoothed momentum oscillator based on price deviation from exponential moving average
Money Flow Index (MFI): Volume-weighted RSI showing buying/selling pressure
RSI: Classic momentum oscillator measuring speed and magnitude of price changes
MACD: Trend-following momentum indicator showing relationship between two EMAs
Stochastic RSI: Stochastic calculation applied to RSI for enhanced sensitivity
Each oscillator has unique strengths: WaveTrend excels at identifying wave-like momentum cycles, MFI incorporates volume for institutional flow analysis, RSI provides reliable overbought/oversold readings, MACD shows trend strength and direction, and Stochastic RSI catches early momentum shifts. Together, they create a comprehensive momentum picture that no single oscillator can provide.
The mashup is justified because these oscillators use fundamentally different calculations (price-based, volume-weighted, moving average convergence, stochastic) that respond to different market conditions. When they align, it indicates genuine momentum shift rather than noise.
Core Components Explained
1. WaveTrend Oscillator (Primary Signal Generator)
WaveTrend is the primary oscillator, calculated using this methodology:
// Calculate exponential average of HLC3
esa = ta.ema(hlc3, channelLength)
// Calculate deviation
d = ta.ema(abs(hlc3 - esa), channelLength)
// Calculate channel index
ci = (hlc3 - esa) / (0.015 * d)
// Apply smoothing to create WaveTrend 1
wt1 = ta.ema(ci, averageLength)
// Create WaveTrend 2 as simple moving average of WT1
wt2 = ta.sma(wt1, 4)
WaveTrend oscillates around zero, with:
Values above +60: Overbought zone
Values above +80: Extreme overbought
Values below -60: Oversold zone
Values below -80: Extreme oversold
Crossovers between WT1 and WT2: Momentum shift signals
The indicator plots WT1 and WT2 as lines with dynamic coloring based on momentum direction and strength.
2. Money Flow Index (MFI) - Volume-Weighted Momentum
MFI calculation incorporates both price and volume:
// Calculate typical price
typicalPrice = (high + low + close) / 3
// Calculate raw money flow
rawMoneyFlow = typicalPrice * volume
// Separate positive and negative money flow
positiveFlow = close > close ? rawMoneyFlow : 0
negativeFlow = close < close ? rawMoneyFlow : 0
// Sum over MFI period
positiveSum = sum(positiveFlow, mfiLength)
negativeSum = sum(negativeFlow, mfiLength)
// Calculate MFI
mfi = 100 - (100 / (1 + positiveSum / negativeSum))
MFI ranges from 0-100, with readings above 80 indicating buying pressure and below 20 indicating selling pressure. The indicator plots MFI as a line and uses it for confluence scoring.
3. RSI - Classic Momentum Oscillator
Standard RSI calculation over 14 periods (configurable):
RSI > 70: Overbought
RSI < 30: Oversold
RSI > 65 with other bearish signals: Potential reversal
RSI < 35 with other bullish signals: Potential reversal
RSI provides reliable baseline momentum readings and is used for divergence detection.
4. MACD - Trend Momentum Indicator
MACD uses standard 12/26/9 settings:
= ta.macd(close, 12, 26, 9)
The indicator displays MACD histogram with enhanced width (linewidth 8) for visibility. Histogram color changes based on:
Green: Positive and increasing (bullish momentum)
Light green: Positive but decreasing (weakening bulls)
Red: Negative and decreasing (bearish momentum)
Light red: Negative but increasing (weakening bears)
MACD histogram provides visual confirmation of momentum strength and direction.
5. Stochastic RSI - Enhanced Sensitivity
Stochastic calculation applied to RSI values:
stochRSI = ta.stoch(rsi, rsi, rsi, 14)
Stochastic RSI oscillates between 0-100 and is more sensitive than regular RSI, catching momentum shifts earlier. The indicator plots both K and D lines for crossover analysis.
Example showing all oscillators with divergence markers and signal labels
Multi-Signal System
The indicator generates six tiers of signals based on confluence strength:
BUY Signals:
BUY: WT1 crosses above WT2 in oversold zone (WT1 < -40)
STRONG BUY: BUY + volume above average + MACD histogram positive
MEGA BUY: STRONG BUY + WT1 < -60 (extreme oversold) + RSI < 35
ULTRA BUY: MEGA BUY + MFI < 30 + Stoch RSI oversold + bullish divergence
SELL Signals:
SELL: WT1 crosses below WT2 in overbought zone (WT1 > 40)
STRONG SELL: SELL + volume above average + MACD histogram negative
MEGA SELL: STRONG SELL + WT1 > 60 (extreme overbought) + RSI > 65
ULTRA SELL: MEGA SELL + MFI > 70 + Stoch RSI overbought + bearish divergence
Signal labels appear on chart with size proportional to signal strength (tiny for BUY/SELL, normal for ULTRA).
Divergence Detection System
The indicator detects divergences across multiple oscillators:
RSI Divergence:
Bullish: Price makes lower low, RSI makes higher low
Bearish: Price makes higher high, RSI makes lower high
WaveTrend Divergence:
Bullish: Price makes lower low, WT1 makes higher low
Bearish: Price makes higher high, WT1 makes lower high
MACD Divergence:
Bullish: Price makes lower low, MACD histogram makes higher low
Bearish: Price makes higher high, MACD histogram makes lower high
Divergences are marked with bright orange/yellow "D" labels (color.rgb(255, 200, 0)) with black text for maximum visibility. When multiple oscillators show divergence simultaneously, it signals strong momentum exhaustion and potential reversal.
Confluence Scoring System
The indicator calculates a real-time confluence score (0-100) by evaluating:
Confluence Components:
- WaveTrend Position: Up to 25 points (extreme zones add more weight)
- WaveTrend Momentum: Up to 15 points (WT1-WT2 relationship)
- RSI Level: Up to 15 points (extreme readings add weight)
- MFI Level: Up to 15 points (volume pressure confirmation)
- MACD Histogram: Up to 15 points (trend momentum)
- Stochastic RSI: Up to 10 points (early momentum detection)
- Divergence Presence: Up to 5 points (any divergence detected)
The dashboard displays the current confluence score with color coding:
Green (80-100): Strong bullish confluence
Light green (60-79): Moderate bullish confluence
Yellow (40-59): Neutral/mixed signals
Light red (20-39): Moderate bearish confluence
Red (0-19): Strong bearish confluence
Visual Elements
WaveTrend Lines: WT1 (blue) and WT2 (orange) with dynamic coloring
Overbought/Oversold Zones: Horizontal lines at +60/-60 and +80/-80
Zero Line: Reference line at 0
MACD Histogram: Large bars (linewidth 8) with gradient coloring
MFI Line: Purple line showing volume-weighted momentum
RSI Line: Green line with overbought/oversold reference levels
Stochastic RSI: K (blue) and D (red) lines
Signal Labels: BUY/SELL markers with size based on signal strength
Divergence Labels: Bright orange "D" markers at divergence points
Dashboard: Top-right table showing confluence score and oscillator readings
Chart demonstrating signal hierarchy from BUY to ULTRA BUY with divergence markers
How Components Work Together
The mashup creates a layered momentum analysis:
Layer 1 - Primary Momentum: WaveTrend identifies wave cycles and crossover signals
Layer 2 - Volume Confirmation: MFI validates moves with volume-weighted pressure
Layer 3 - Baseline Momentum: RSI provides reliable overbought/oversold context
Layer 4 - Trend Strength: MACD histogram shows underlying trend momentum
Layer 5 - Early Detection: Stochastic RSI catches momentum shifts before other oscillators
Layer 6 - Exhaustion Signals: Divergences across oscillators indicate momentum exhaustion
Example scenario: WT1 crosses above WT2 in oversold zone (Layer 1), MFI shows buying pressure increasing (Layer 2), RSI is below 35 (Layer 3), MACD histogram turns positive (Layer 4), Stochastic RSI crosses up (Layer 5), and RSI shows bullish divergence (Layer 6). This generates an ULTRA BUY signal with 90+ confluence score.
Input Parameters
WaveTrend Settings:
Channel Length: Period for EMA calculation (default: 10)
Average Length: Smoothing period for WT1 (default: 21)
Overbought Level: Upper threshold (default: 60)
Oversold Level: Lower threshold (default: -60)
Extreme OB Level: Extreme upper threshold (default: 80)
Extreme OS Level: Extreme lower threshold (default: -80)
Oscillator Settings:
RSI Length: Period for RSI calculation (default: 14)
MFI Length: Period for MFI calculation (default: 14)
MACD Fast: Fast EMA period (default: 12)
MACD Slow: Slow EMA period (default: 26)
MACD Signal: Signal line period (default: 9)
Stochastic RSI Length: Period for Stoch RSI (default: 14)
Signal Settings:
Show Signals: Toggle signal labels (default: enabled)
Show Divergences: Toggle divergence markers (default: enabled)
Volume Confirmation: Require volume for STRONG signals (default: enabled)
Min Confluence for Signals: Minimum score to display signals (default: 60)
Display Options:
Show Dashboard: Toggle confluence score table (default: enabled)
Show MACD Histogram: Toggle MACD display (default: enabled)
Show MFI Line: Toggle MFI display (default: enabled)
Show RSI Line: Toggle RSI display (default: enabled)
Show Stochastic RSI: Toggle Stoch RSI display (default: enabled)
Color Theme: Choose between multiple color schemes
How to Use This Indicator
Step 1: Monitor WaveTrend Oscillator
Watch for WT1/WT2 crossovers in extreme zones. Crossovers in oversold zone (< -60) suggest bullish reversals, crossovers in overbought zone (> 60) suggest bearish reversals.
Step 2: Check Confluence Score
Review the dashboard. Scores above 70 indicate strong momentum alignment. Higher scores generally produce more reliable signals.
Step 3: Identify Signal Strength
Pay attention to signal labels. ULTRA signals have highest probability but occur less frequently. STRONG signals offer good balance between frequency and reliability.
Step 4: Look for Divergences
Divergence markers indicate momentum exhaustion. When divergences appear with extreme oscillator readings, reversal probability increases significantly.
Step 5: Confirm with MACD Histogram
Check MACD histogram direction and strength. Large histogram bars confirm strong momentum, shrinking bars suggest momentum loss.
Step 6: Validate with Volume (MFI)
Ensure MFI supports the move. Bullish signals with rising MFI are stronger, bearish signals with falling MFI are stronger.
Best Practices
Use on 15-minute to 4-hour timeframes for optimal signal quality
Wait for STRONG or MEGA signals rather than acting on every BUY/SELL
Divergences work best when combined with extreme oscillator readings
Multiple oscillator divergences (RSI + WT + MACD) are most reliable
Use confluence score as filter - avoid signals below 60 score
MACD histogram size indicates momentum strength - larger bars = stronger moves
MFI divergence from price often precedes reversals (volume leads price)
Combine with price action and support/resistance for best results
Indicator Limitations
Oscillators can remain overbought/oversold longer than expected in strong trends
Divergences can persist for multiple bars before reversal occurs
Multiple signals in choppy markets can lead to whipsaws
Confluence score is mathematical calculation, not prediction of future movement
ULTRA signals are rare - waiting only for these may miss opportunities
Volume data quality varies across markets and can affect MFI reliability
Stochastic RSI is very sensitive and can generate premature signals
No indicator combination eliminates false signals entirely
Requires understanding of oscillator behavior for effective interpretation
Technical Implementation
Built with Pine Script v6 using:
Custom WaveTrend calculation with dual-line system
Proper MFI formula with volume-weighted money flow
Multi-oscillator divergence detection with pivot analysis
Confluence scoring algorithm with weighted components
Enhanced MACD histogram visualization (linewidth 8)
Dynamic color gradients for momentum visualization
Anti-overlap logic for signal labels
Real-time dashboard with oscillator readings
The code is fully open-source and can be modified to adjust oscillator weights, signal thresholds, and visual preferences.
Originality Statement
This indicator is original in its multi-oscillator integration approach. While individual components (WaveTrend, MFI, RSI, MACD, Stochastic RSI) are established oscillators, this mashup is justified because:
It combines five oscillators using fundamentally different calculation methods
The tiered signal system (BUY to ULTRA) provides graduated confidence levels
Multi-oscillator divergence detection catches momentum exhaustion across different timeframes
Confluence scoring quantifies momentum alignment across all oscillators
Volume integration through MFI adds institutional flow perspective
Enhanced visualization (large MACD histogram, bright divergence markers) improves usability
Each oscillator contributes unique information: WaveTrend provides wave-cycle analysis, MFI incorporates volume, RSI offers reliable baseline, MACD shows trend strength, and Stochastic RSI catches early shifts. The mashup's value lies in identifying when these different momentum calculations align, significantly reducing false signals compared to any single oscillator.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss and is not suitable for all investors.
Oscillator-based indicators are lagging tools that analyze past price data. They do not predict future price movement. Overbought conditions can persist in strong uptrends, and oversold conditions can persist in strong downtrends. Divergences can continue for extended periods before reversals occur.
The confluence score is a mathematical calculation, not a guarantee of trade success. High confluence scores do not ensure profitable trades. Past signal performance does not guarantee future results. Market conditions change, and oscillator behavior varies across different market regimes.
Always use proper risk management, including stop losses and position sizing appropriate for your account size and risk tolerance. Never risk more than you can afford to lose. Consider consulting with a qualified financial advisor before making investment decisions.
The author is not responsible for any losses incurred from using this indicator. Users assume full responsibility for all trading decisions made using this tool.
-Made with passion by officialjackofalltrades Indicator
Precision Pivot Confluence Engine [JOAT]Precision Pivot Confluence Engine
Introduction
The Precision Pivot Confluence Engine is an open-source technical indicator that combines Central Pivot Range (CPR) analysis with Smart Money Concepts (SMC), multi-oscillator divergence detection, and institutional order flow patterns. This mashup integrates multiple proven methodologies into a unified confluence system designed to identify high-probability trading zones where institutional and retail liquidity intersect.
The indicator is built for traders who understand that no single signal provides consistent edge, but multiple confirming factors working together can significantly improve trade selection. By synthesizing CPR levels, Fair Value Gaps, Order Blocks, liquidity sweeps, and divergence patterns, this tool helps identify structural market inflection points.
Chart showing CPR levels, FVG zones, Order Blocks, and divergence signals on 4H timeframe
Why This Mashup Exists
This indicator combines five distinct analytical frameworks that complement each other:
CPR Analysis: Identifies key pivot levels where institutional algorithms and retail traders make decisions
Smart Money Concepts: Tracks Fair Value Gaps, Order Blocks, and Breaker Blocks showing institutional positioning
Divergence Detection: Uses RSI, MACD, and Stochastic RSI to identify momentum exhaustion
Liquidity Analysis: Detects liquidity sweeps where stop hunts occur before reversals
Volume Confirmation: Validates moves with volume analysis and delta calculations
Each component addresses a different aspect of market structure. CPR provides static reference levels, SMC reveals dynamic institutional behavior, divergences show momentum shifts, liquidity sweeps identify stop hunts, and volume confirms genuine moves versus noise. Together, they create a multi-dimensional view of market conditions.
Core Components Explained
1. Enhanced CPR System
The Central Pivot Range system calculates Daily and Weekly pivot levels using the formula:
Pivot = (High + Low + Close) / 3
BC (Bottom Central) = (High + Low) / 2
TC (Top Central) = (Pivot - BC) + Pivot
The indicator analyzes CPR width to determine market regime:
Narrow CPR (width < 0.5%): Indicates compression and potential breakout conditions
Wide CPR (width > 1.5%): Suggests ranging market with less directional conviction
Price position relative to CPR: Above both Daily and Weekly pivots = bullish structure, below = bearish structure
CPR levels act as magnetic zones where price tends to react. The indicator tracks distance from pivots to identify overextension and mean reversion opportunities.
2. Smart Money Concepts Integration
Fair Value Gaps (FVG):
Bullish FVG occurs when current low > high from 2 bars ago, leaving an unfilled gap
Bearish FVG occurs when current high < low from 2 bars ago
The indicator calculates FVG size as percentage of price and filters for significant gaps (> 0.3%) to avoid noise. FVGs represent inefficient price delivery where institutions moved price quickly, often returning to fill these gaps later.
Order Blocks (OB):
Bullish OB: Two consecutive bearish candles followed by strong bullish candle with high volume
Bearish OB: Two consecutive bullish candles followed by strong bearish candle with high volume
Order Blocks mark the last opposite-direction move before a strong impulse, indicating where institutions accumulated or distributed positions.
Breaker Blocks:
Failed Order Blocks that get violated become Breaker Blocks, signaling potential trend reversal. The indicator tracks the last bullish and bearish OB levels and alerts when price breaks through them.
Liquidity Sweeps:
The indicator identifies when price briefly exceeds recent highs/lows (20-bar lookback) but closes back inside the range. These "stop hunts" often precede reversals as institutions trigger retail stops before moving price in the intended direction.
Example showing FVG zones, Order Blocks, and liquidity sweep markers
3. Multi-Oscillator Divergence System
The indicator simultaneously tracks divergences across three oscillators:
RSI Divergence:
Bullish: Price makes lower low, RSI makes higher low (momentum improving despite price weakness)
Bearish: Price makes higher high, RSI makes lower high (momentum deteriorating despite price strength)
MACD Divergence:
Tracks histogram divergences using the same pivot-based logic
Stochastic RSI Divergence:
More sensitive than RSI, catches early momentum shifts
The indicator uses a 5-bar pivot lookback to identify swing highs/lows and compares current pivots with previous pivots to detect divergences. When multiple oscillators show divergence simultaneously, it signals strong momentum exhaustion.
4. Volume Analysis Engine
Volume MA Comparison: Identifies high volume (> 1.5x MA) and climax volume (> 3x MA)
Volume Delta: Cumulative difference between buying volume (green candles) and selling volume (red candles)
Delta Trend: Compares current delta to 20-period MA to identify institutional accumulation or distribution
Volume Confirmation: Validates bullish moves with high volume + rising delta, bearish moves with high volume + falling delta
5. Confluence Scoring System
The indicator calculates a real-time confluence score (0-100) by weighting each component:
Confluence Score Components:
- CPR Position: Up to 15 points (bullish above pivots, bearish below)
- SMC Signals: Up to 10 points (FVG + OB + Breaker + Liquidity Sweeps)
- Divergence: Up to 10 points (single oscillator = 5, multiple = 10)
- Volume: Up to 10 points (confirmed volume = 7, climax = additional 3)
- Trend Alignment: Up to 5 points (price vs key MAs)
Scores above 70 indicate strong confluence for potential trades. The dashboard displays individual component scores for transparency.
Visual Elements
CPR Lines: Daily Pivot (yellow), TC/BC (yellow transparent), Weekly Pivot (yellow circles)
FVG Boxes: Green boxes for bullish FVGs, red boxes for bearish FVGs
Order Block Boxes: Solid green/red boxes marking institutional zones
Breaker Block Labels: "BB" markers when Order Blocks fail
Liquidity Sweep Labels: "LIQ" and "STRONG LIQ" positioned at sweep tips
Divergence Labels: "D" markers at divergence pivot points
Dashboard: Top-right table showing confluence score and component breakdown
How Components Work Together
The mashup creates a layered analysis approach:
Layer 1 - Structure: CPR levels define key zones where reactions are likely
Layer 2 - Institutional Behavior: SMC concepts show where smart money is positioned
Layer 3 - Momentum: Divergences indicate when current trend is losing steam
Layer 4 - Confirmation: Volume validates whether moves are genuine or false
Layer 5 - Synthesis: Confluence score combines all factors into actionable signal
Example scenario: Price approaches Daily Pivot (Layer 1) where a bullish Order Block exists (Layer 2), RSI shows bullish divergence (Layer 3), and volume delta is rising (Layer 4). The confluence score jumps to 85 (Layer 5), signaling high-probability long setup.
Input Parameters
CPR Settings:
Show Daily CPR: Toggle daily pivot levels (default: enabled)
Show Weekly CPR: Toggle weekly pivot levels (default: enabled)
CPR Width Threshold: Defines narrow vs wide CPR (default: 0.5% / 1.5%)
Smart Money Concepts:
Show FVG: Display Fair Value Gap boxes (default: enabled)
Show Order Blocks: Display Order Block boxes (default: enabled)
Show Breaker Blocks: Display Breaker Block labels (default: enabled)
Show Liquidity Sweeps: Display liquidity sweep markers (default: enabled)
FVG Min Size: Minimum gap size to display (default: 0.3%)
Lookback Bars: Bars to scan for liquidity levels (default: 20)
Divergence Detection:
Show Divergences: Toggle divergence labels (default: enabled)
RSI Length: Period for RSI calculation (default: 14)
Pivot Lookback: Bars for pivot detection (default: 5)
Volume Analysis:
Show Volume Analysis: Toggle volume indicators (default: enabled)
Volume MA Length: Period for volume moving average (default: 20)
High Volume Multiplier: Threshold for high volume (default: 1.5x)
Climax Volume Multiplier: Threshold for climax volume (default: 3.0x)
Display Options:
Show Dashboard: Toggle confluence score table (default: enabled)
Max FVG Boxes: Limit displayed FVG boxes (default: 20)
Max OB Boxes: Limit displayed Order Block boxes (default: 15)
Label Spacing: Minimum bars between labels to prevent overlap (default: 10-15)
How to Use This Indicator
Step 1: Identify Market Structure
Check CPR position and width. Narrow CPR suggests breakout potential, wide CPR suggests range-bound conditions.
Step 2: Look for SMC Confluence
Identify FVGs, Order Blocks, and recent liquidity sweeps. These zones often provide high-probability entry areas.
Step 3: Check for Divergences
Look for divergence labels at swing points. Multiple oscillator divergences increase signal strength.
Step 4: Confirm with Volume
Ensure volume supports the move. Rising delta + high volume confirms bullish moves, falling delta + high volume confirms bearish moves.
Step 5: Review Confluence Score
Check the dashboard. Scores above 70 indicate strong confluence. Individual component scores show which factors are contributing.
Step 6: Wait for Price Action Confirmation
The indicator identifies zones and conditions, but wait for price action confirmation (candlestick patterns, breakouts, etc.) before entering trades.
Best Practices
Use on 15-minute to 4-hour timeframes for optimal signal quality
Combine with proper risk management - indicator shows zones, not exact entries
Pay attention to confluence score - higher scores generally indicate better setups
Watch for FVG fills and Order Block retests as entry triggers
Liquidity sweeps followed by reversal often provide excellent risk:reward entries
Divergences work best when combined with SMC zones or CPR levels
Volume confirmation is critical - avoid low-volume signals
Indicator Limitations
Does not provide exact entry/exit signals - requires trader interpretation
Can generate false signals in choppy, low-volume conditions
Multiple visual elements may clutter chart - adjust display settings as needed
Divergences can persist longer than expected - price can continue trending despite divergence
FVGs and Order Blocks don't always get retested - not every zone provides entry opportunity
Confluence score is a guide, not a guarantee - high scores can still result in losing trades
Requires understanding of SMC concepts and CPR analysis for effective use
Performance varies across different markets and timeframes
Technical Implementation
Built with Pine Script v6 using:
Custom CPR calculations with width analysis
Box and label management with anti-overlap logic
Persistent variables for tracking Order Blocks and Breaker Blocks
Pivot-based divergence detection across multiple oscillators
Volume delta calculation with cumulative tracking
Real-time confluence scoring system
Dynamic dashboard with component breakdown
The code is fully open-source and can be modified to suit individual trading styles and preferences.
Originality Statement
This indicator is original in its integration approach. While individual components (CPR, FVG, Order Blocks, RSI divergence, volume analysis) are established concepts, this mashup is justified because:
It synthesizes five distinct methodologies that address different market aspects
The confluence scoring system provides quantitative measurement of setup quality
Anti-overlap logic and timeframe-adaptive filtering reduce visual clutter
Component integration creates layered analysis not available in individual indicators
The combination helps identify zones where multiple institutional and technical factors align
Each component contributes unique information: CPR provides static structure, SMC reveals dynamic institutional behavior, divergences show momentum shifts, liquidity analysis identifies stop hunts, and volume confirms genuine moves. The mashup's value lies in presenting these complementary perspectives simultaneously with a unified scoring system.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss and is not suitable for all investors.
Technical indicators are tools for analysis, not crystal balls. Past performance and backtested results do not guarantee future performance. Market conditions change, and strategies that worked historically may not work in the future.
The confluence score is a mathematical calculation based on current market data, not a prediction of future price movement. High confluence scores do not guarantee profitable trades. Users must conduct their own analysis and risk assessment before making trading decisions.
Always use proper risk management, including stop losses and position sizing appropriate for your account size and risk tolerance. Never risk more than you can afford to lose. Consider consulting with a qualified financial advisor before making investment decisions.
The author is not responsible for any losses incurred from using this indicator. Users assume full responsibility for all trading decisions made using this tool.
-Made with passion by officialjackofalltrades Indicator
Institutional Confluence Mapper [JOAT]Institutional Confluence Mapper (ICM)
Introduction
The Institutional Confluence Mapper is an open-source multi-factor analysis tool that combines five analytical modules into a unified confluence scoring system. It synthesizes institutional trading concepts including Relative Rotation analysis, Smart Money flow detection, Liquidity zone mapping, Session-based timing, and Volatility regime classification.
Rather than relying on a single indicator, ICM evaluates market conditions through multiple lenses simultaneously, presenting a clear confluence score (0-100%) that reflects the alignment of various market factors.
This script is fully open-source under the Mozilla Public License 2.0.
Originality and Purpose
This indicator is NOT a random mashup of existing indicators. It is an original implementation that creates a unified institutional analysis framework:
Why Multiple Modules? Most retail traders struggle because they rely on single indicators that provide conflicting signals. Institutional traders evaluate markets through multiple frameworks simultaneously. ICM bridges this gap by providing a unified view of complementary analysis methods.
The Confluence Scoring System: Each module contributes to a weighted confluence score (0-100%). Scores above 65% indicate bullish confluence; below 35% indicates bearish confluence.
How Components Work Together:
RRG (Relative Rotation) determines macro bias - is this asset outperforming or underperforming its benchmark?
Institutional Flow confirms smart money activity - are institutions accumulating or distributing?
Volatility Regime determines strategy selection - trend-follow or mean-revert?
Liquidity Detection identifies key levels - where are the stop hunts happening?
Session Analysis optimizes timing - when should you trade?
The Five Core Modules
1. Relative Rotation Momentum Matrix (RRG)
Compares the current symbol against a benchmark (default: SPY) using the JdK RS-Ratio methodology with double-smoothed EMA. Assets rotate through four quadrants:
LEADING: Outperforming with positive momentum (strongest bullish)
WEAKENING: Outperforming but losing momentum
LAGGING: Underperforming with negative momentum (strongest bearish)
IMPROVING: Underperforming but gaining momentum
2. Institutional Flow Analysis
Analyzes volume patterns to detect smart money activity:
Volume Z-Score measures how unusual current volume is
Buy/Sell pressure estimation based on candle structure
Unusual volume detection highlights institutional activity
3. Volatility Regime System
Uses ATR percentile ranking to classify market conditions:
COMPRESSION: Low volatility (ATR < 20th percentile) - potential breakout
EXPANSION: High volatility (ATR > 80th percentile) - trending
TRENDING_BULL/BEAR: Directional trends based on EMA alignment
RANGING: Sideways consolidation
4. Liquidity Detection
Identifies institutional liquidity targets using swing point analysis:
Swing highs/lows are tracked and displayed as dashed lines
Purple dashed lines mark resistance/sell-side liquidity
Teal dashed lines mark support/buy-side liquidity
Gold diamonds appear when liquidity sweeps are detected (potential reversals)
5. Session Momentum Profiler
Tracks trading sessions based on your selected timezone:
Asian Session: 7PM - 4AM EST
London Session: 3AM - 12PM EST
New York Session: 9:30AM - 4PM EST
London/NY Overlap: 8AM - 12PM EST (peak liquidity)
Visual Elements
Main Dashboard (Top-Right):
BIAS: Overall direction with confluence percentage
RRG: Current quadrant and momentum
FLOW: Smart money bias and volume status
REGIME: Market condition and volatility percentile
SESSION: Active trading session and current time
LIQUIDITY: Active zones and grab signals
SIGNAL: Actionable recommendation
Chart Elements:
Gold Diamond: Liquidity grab (potential reversal point)
Teal Dashed Line: Support / Buy-side liquidity zone
Purple Dashed Line: Resistance / Sell-side liquidity zone
EMA 21/55/200: Trend structure with cloud fill
Volatility Bands: ATR-based channels
How to Use
Step 1: Check the BIAS row for overall market direction
Step 2: Check REGIME to understand market conditions
Step 3: Identify key levels using liquidity zones and EMAs
Step 4: Wait for confluence above 65% (bullish) or below 35% (bearish)
Step 5: Look for gold diamond signals at key levels
Best Setups
Bullish: Confluence >65%, RRG in LEADING/IMPROVING, bullish flow, price near teal support zone.
Bearish: Confluence <35%, RRG in LAGGING/WEAKENING, bearish flow, price near purple resistance zone.
Reversal: Gold diamond appears after price sweeps a liquidity zone.
Key Input Parameters
Benchmark Symbol: Compare against (default: SPY)
RS-Ratio/Momentum Lookback: RRG calculation periods
Volume Analysis Period: Flow detection lookback
Swing Length: Liquidity zone detection
ATR Period/Rank Period: Regime classification
Timezone: Session detection timezone
Alerts
Liquidity Grab Bull: Bullish sweep detected
Liquidity Grab Bear: Bearish sweep detected
High Confluence Bull: Confluence above 70%
High Confluence Bear: Confluence below 30%
Best Practices
Use on 1H, 4H, or Daily timeframes for reliable signals
Combine with price action for confirmation
Respect the regime - don't fight strong trends
Trade during London/NY overlap for best liquidity
Wait for high confluence scores before entering
Always use proper risk management
Limitations
Works best on liquid markets with sufficient volume
Session features optimized for forex/crypto markets
RRG requires a valid benchmark symbol
No indicator predicts the future - use proper risk management
Disclaimer
This indicator is for educational and informational purposes only. It is not financial advice. Trading involves substantial risk of loss. Past performance does not guarantee future results.
-Made with passion by officialjackofalltrades
Indicator
TurboRSI Pro [JOAT]TurboRSI Pro - Multi-Length RSI Ensemble with Dynamic Momentum Analysis
Introduction
TurboRSI Pro is an open-source indicator that reimagines the classic RSI by calculating multiple RSI lengths simultaneously and combining them into a single, more reliable momentum reading. Instead of relying on a single RSI period that may lag or produce false signals, this indicator creates an ensemble of RSI values across a configurable range, providing a smoother and more robust momentum assessment.
The indicator is designed for traders who want deeper insight into momentum conditions without the noise that comes from single-period oscillators.
Originality and Purpose
This indicator is NOT a simple RSI with different settings. It is an original implementation that solves a fundamental problem with traditional RSI:
The Problem with Single-Period RSI: Traditional RSI uses a single lookback period (typically 14). The issue is that different market conditions favor different RSI lengths. A 14-period RSI might work well in one market phase but produce false signals in another. There's no "perfect" RSI length that works in all conditions.
The Multi-Length Solution: TurboRSI Pro calculates RSI across a range of lengths (default: 10 to 20) simultaneously, then averages all values to create a composite reading. This ensemble approach filters out period-specific noise while preserving genuine momentum shifts. When multiple RSI lengths agree, the signal is more reliable.
OB/OS Strength Percentage: The indicator tracks how many individual RSI lengths are in overbought or oversold territory. When 100% of lengths are overbought, it's a much stronger signal than when only 50% are. This percentage-based approach is original to this indicator and provides conviction assessment.
Candle Heatmap Innovation: An optional feature colors price bars based on deviation from a 200-bar linear regression line. This shows when price is statistically overextended (HOT/COLD) independent of RSI, providing another layer of analysis.
How the components work together:
Multi-length RSI ensemble provides a more robust momentum reading than single-period RSI
OB/OS Strength percentages quantify how many timeframes agree on the momentum condition
Dynamic channels expand/contract based on momentum strength across all calculated lengths
Candle heatmap adds statistical price deviation context independent of RSI
Core Concept: Multi-Length RSI Ensemble
Traditional RSI uses a single lookback period (typically 14). The problem is that different market conditions favor different RSI lengths. TurboRSI Pro solves this by:
Calculating RSI across a range of lengths (default: 10 to 20)
Averaging all RSI values to create a composite reading
Tracking how many individual RSI lengths are in overbought or oversold territory
Displaying this information as "OB Strength" and "OS Strength" percentages
This approach filters out noise while preserving genuine momentum shifts.
How the Multi-Length RSI Works
The calculation uses an efficient array-based approach:
int N = maxLength - minLength + 1
float diff = nz(srcInput - srcInput )
for i = 0 to N - 1
int len = minLength + i
float alpha = 1.0 / len
float numRma = alpha * diff + (1 - alpha) * array.get(numArr, i)
float denRma = alpha * math.abs(diff) + (1 - alpha) * array.get(denArr, i)
float rsiVal = denRma != 0 ? 50 * numRma / denRma + 50 : 50
avgRSI += rsiVal
Each RSI length is calculated using the RMA (Running Moving Average) formula, then all values are averaged. The result is a composite RSI that responds to momentum changes while filtering out period-specific noise.
Visual Components
1. Multi-Length RSI Line
The main oscillator line displays the averaged RSI value with a gradient color:
Green gradient when RSI is above 50 (bullish momentum)
Red gradient when RSI is below 50 (bearish momentum)
Color intensity increases as RSI approaches extreme levels
2. Dynamic Channels
Two adaptive channel lines track momentum extremes:
Upper Channel: Expands when multiple RSI lengths enter overbought territory
Lower Channel: Expands when multiple RSI lengths enter oversold territory
Channel width indicates momentum strength across all calculated lengths
3. Candle Heatmap
An optional feature that colors price bars based on deviation from a linear regression line:
Red/Orange bars: Price is significantly above the regression line (overextended to upside)
Blue bars: Price is significantly below the regression line (overextended to downside)
Yellow bars: Price is near the regression line (neutral)
The heatmap uses a 200-bar regression calculation to identify when price has deviated significantly from its statistical trend.
4. Reference Lines
Standard RSI reference levels are displayed:
80 and 20: Extreme overbought/oversold
70 and 30: Standard overbought/oversold thresholds
50: Neutral momentum line
5. Background Zones
Shaded areas indicate the percentage of RSI lengths in extreme territory:
Green shading from bottom: Percentage of lengths in overbought
Red shading from top: Percentage of lengths in oversold
Dashboard Panel
The dashboard displays real-time analysis in a 7-row table:
RSI Value: Current composite RSI reading (large text for visibility)
Momentum: Current state - OVERBOUGHT, OVERSOLD, BULLISH, BEARISH, or NEUTRAL
OB Strength: Percentage of RSI lengths currently above the overbought threshold
OS Strength: Percentage of RSI lengths currently below the oversold threshold
Heat Level: Current price deviation state - HOT, WARM, NEUTRAL, COOL, or COLD
Trend Bias: Overall trend assessment based on RSI level and channel direction
Optional Stochastic RSI
When enabled, an additional Stochastic RSI line is plotted. This applies the stochastic formula to the RSI itself, providing another layer of momentum analysis. The Stochastic RSI is more sensitive to short-term momentum shifts.
Input Parameters
RSI Settings:
Min RSI Length: Starting length for the RSI range (default: 10)
Max RSI Length: Ending length for the RSI range (default: 20)
Source: Price source for calculation (default: ohlc4)
Overbought: Upper threshold (default: 70)
Oversold: Lower threshold (default: 30)
Candle Heatmap:
Enable Heatmap: Toggle bar coloring on/off (default: enabled)
Regression Length: Lookback for linear regression calculation (default: 200)
Display:
Show Dashboard: Toggle the information panel (default: enabled)
Show Dynamic Channels: Toggle channel lines (default: enabled)
Show Stochastic RSI: Toggle additional Stoch RSI line (default: disabled)
Colors:
Bullish: Color for bullish conditions (default: teal)
Bearish: Color for bearish conditions (default: red)
Neutral: Color for neutral conditions (default: gray)
How to Use TurboRSI Pro
Identifying Momentum Shifts:
Watch for RSI crossing above 50 for bullish momentum confirmation
Watch for RSI crossing below 50 for bearish momentum confirmation
Use the gradient color to quickly assess momentum direction
Using OB/OS Strength:
When OB Strength reaches 100%, all RSI lengths are overbought - strong reversal potential
When OS Strength reaches 100%, all RSI lengths are oversold - strong bounce potential
Partial readings (e.g., 50%) indicate mixed conditions across timeframes
Heatmap Analysis:
HOT readings combined with high RSI suggest overextension - caution for longs
COLD readings combined with low RSI suggest oversold conditions - watch for reversal
Use heatmap divergence from RSI for additional confirmation
Channel Interpretation:
Expanding upper channel with rising RSI confirms strong bullish momentum
Expanding lower channel with falling RSI confirms strong bearish momentum
Channel contraction suggests momentum is weakening
Alert Conditions
Six alert conditions are available:
RSI Overbought: RSI crosses above overbought threshold
RSI Oversold: RSI crosses below oversold threshold
RSI Bullish Cross: RSI crosses above 50
RSI Bearish Cross: RSI crosses below 50
All RSI Overbought: Every RSI length is in overbought territory
All RSI Oversold: Every RSI length is in oversold territory
Best Practices
Use on higher timeframes (1H, 4H, Daily) for more reliable signals
Combine with price action analysis - RSI confirms, it does not predict
Pay attention to OB/OS Strength percentages for conviction assessment
The heatmap works best on assets with clear trending behavior
Adjust min/max RSI lengths based on your trading style - wider range for smoother signals
Limitations
Like all oscillators, can remain in overbought/oversold territory during strong trends
The heatmap regression may lag during rapid price movements
Multi-length calculation requires more processing than single RSI
Best suited for swing trading and position trading timeframes
Technical Notes
This indicator is written in Pine Script v6 and uses:
Array-based calculations for efficient multi-length RSI computation
Linear regression for heatmap deviation analysis
Gradient coloring for intuitive visual feedback
State management for dynamic channel calculations
The source code is open and available for review and modification.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Trading involves substantial risk of loss. Past performance does not guarantee future results. Always conduct your own analysis and use proper risk management.
-Made with passion by officialjackofalltrades Indicator
RSI Fibonacci Flow [JOAT]RSI Fibonacci Flow - Advanced Fibonacci Retracement with RSI Confluence
Introduction
RSI Fibonacci Flow is an open-source overlay indicator that combines automatic Fibonacci retracement levels with RSI momentum analysis to identify high-probability trading zones. The indicator automatically detects swing highs and lows, draws Fibonacci levels, and generates confluence signals when RSI conditions align with key Fibonacci zones.
This indicator is designed for traders who use Fibonacci retracements but want additional confirmation from momentum analysis before entering trades.
Originality and Purpose
This indicator is NOT a simple mashup of RSI and Fibonacci tools. It is an original implementation that creates a synergistic relationship between two complementary analysis methods:
Why Combine RSI with Fibonacci? Fibonacci retracements identify WHERE price might reverse, but they don't tell you WHEN. RSI provides the timing component by showing momentum exhaustion. When price reaches the Golden Zone (50%-61.8%) AND RSI shows oversold conditions, the probability of a successful bounce increases significantly.
Original Confluence Scoring System: The indicator calculates a 0-5 confluence score that weights multiple factors: Golden Zone presence (+2), entry zone presence (+1), RSI extreme alignment (+1), RSI divergence (+1), and strong RSI momentum (+1). This scoring system is original to this indicator.
Automatic Pivot Detection: Unlike manual Fibonacci tools, this indicator automatically detects swing highs and lows using a configurable pivot algorithm, then draws Fibonacci levels accordingly. The pivot detection uses a center-bar comparison method that checks if a bar's high/low is the highest/lowest within the specified depth on both sides.
Dynamic Trend Awareness: The indicator determines trend direction based on pivot sequence (last pivot was high or low) and adjusts Fibonacci orientation accordingly. In uptrends, 0% is at swing low; in downtrends, 0% is at swing high.
Each component serves a specific purpose:
Fibonacci levels identify potential reversal zones based on natural price ratios
RSI provides momentum context to filter out low-probability setups
Confluence scoring quantifies setup quality for position sizing decisions
Automatic pivot detection removes subjectivity from level placement
Core Concept: RSI-Fibonacci Confluence
The most powerful trading setups occur when multiple factors align. RSI Fibonacci Flow identifies these moments by:
Automatically detecting price pivots and drawing Fibonacci levels
Tracking which Fibonacci zone the current price occupies
Monitoring RSI for overbought/oversold conditions
Generating signals when RSI extremes coincide with key Fibonacci levels
Scoring confluence strength on a 0-5 scale
When price reaches the Golden Zone (50%-61.8%) while RSI shows oversold conditions in an uptrend, the probability of a bounce increases significantly.
Fibonacci Levels Explained
The indicator draws nine Fibonacci levels based on the most recent swing:
0% (Swing Low/High): The starting point of the move
23.6%: Shallow retracement - often seen in strong trends
38.2%: First significant support/resistance level
50%: Psychological midpoint of the move
61.8% (Golden Ratio): The most important Fibonacci level
78.6%: Deep retracement - last defense before trend failure
100% (Swing High/Low): The end point of the move
127.2% (TP1): First extension target for take profit
161.8% (TP2): Second extension target for take profit
The Golden Zone
The area between 50% and 61.8% is highlighted as the "Golden Zone" because:
It represents the optimal retracement depth for trend continuation
Institutional traders often place orders in this zone
It offers favorable risk-to-reward ratios
Price frequently bounces from this area in healthy trends
When price enters the Golden Zone, the indicator highlights it with a semi-transparent box and optional background coloring.
Pivot Detection System
The indicator uses a configurable pivot detection algorithm:
pivotDetect(float src, int len, bool isHigh) =>
int halfLen = len / 2
float centerVal = nz(src , src)
bool isPivot = true
for i = 0 to len - 1
if isHigh
if nz(src , src) > centerVal
isPivot := false
break
else
if nz(src , src) < centerVal
isPivot := false
break
isPivot ? centerVal : float(na)
This identifies swing highs and lows by checking if a bar's high/low is the highest/lowest within the specified depth on both sides.
Visual Components
1. Fibonacci Lines
Horizontal lines at each Fibonacci level:
Solid lines for major levels (0%, 50%, 61.8%, 100%)
Dashed lines for secondary levels (23.6%, 38.2%, 78.6%)
Dotted lines for extension levels (127.2%, 161.8%)
Color-coded for easy identification
Configurable line width
2. Fibonacci Labels
Price labels at each level showing:
Fibonacci percentage
Actual price at that level
Golden Zone label highlighted
TP1 and TP2 labels for targets
3. Golden Zone Box
A semi-transparent box highlighting the 50%-61.8% zone:
Gold colored border and fill
Extends from swing start to current bar (or beyond if extended)
Provides clear visual of the optimal entry zone
4. ZigZag Lines
Connecting lines between detected pivots:
Cyan for moves from low to high
Orange for moves from high to low
Helps visualize market structure
Configurable line width
5. Pivot Markers
Small labels at detected swing points:
"HH" (Higher High) at swing highs
"LL" (Lower Low) at swing lows
Helps track market structure
6. Entry Signals
BUY and SELL labels when confluence conditions are met:
BUY: RSI oversold + price in entry zone + uptrend + positive momentum
SELL: RSI overbought + price in entry zone + downtrend + negative momentum
Labels include "RSI+FIB" to indicate confluence
Confluence Scoring System
The indicator calculates a confluence score from 0 to 5:
+2 points: Price is in the Golden Zone (50%-61.8%)
+1 point: Price is in the entry zone (38.2%-61.8%)
+1 point: RSI is oversold in uptrend OR overbought in downtrend
+1 point: RSI divergence detected (bullish or bearish)
+1 point: Strong RSI momentum (change > 2 points)
Confluence ratings:
STRONG (4-5): Multiple factors align - high probability setup
MODERATE (2-3): Some factors align - proceed with caution
WEAK (0-1): Few factors align - wait for better setup
Dashboard Panel
The 10-row dashboard provides comprehensive analysis:
RSI Value: Current RSI reading (large text)
RSI State: OVERBOUGHT, OVERSOLD, BULLISH, BEARISH, or NEUTRAL
Fib Trend: UPTREND or DOWNTREND based on last pivot sequence
Price Zone: Current Fibonacci zone (e.g., "GOLDEN ZONE", "38.2% - 50%")
Price: Current close price (large text)
Confluence: Score rating with numeric value (e.g., "STRONG (4/5)")
Nearest Fib: Closest key Fibonacci level with price
TP1 (127.2%): First take profit target price
TP2 (161.8%): Second take profit target price
Input Parameters
Pivot Detection:
Pivot Depth: Bars to look back for swing detection (default: 10)
Min Deviation %: Minimum price move to confirm pivot (default: 1.0)
RSI Settings:
RSI Length: Period for RSI calculation (default: 14)
Source: Price source (default: close)
Overbought: Upper threshold (default: 70)
Oversold: Lower threshold (default: 30)
Fibonacci Display:
Show Fib Lines: Toggle Fibonacci lines (default: enabled)
Show Fib Labels: Toggle price labels (default: enabled)
Show Golden Zone Box: Toggle zone highlight (default: enabled)
Line Width: Thickness of Fibonacci lines (default: 2)
Extend Fib Lines: Extend lines into future (default: enabled)
ZigZag:
Show ZigZag: Toggle connecting lines (default: enabled)
ZigZag Width: Line thickness (default: 2)
Signals:
Show Entry Signals: Toggle BUY/SELL labels (default: enabled)
Show TP Levels: Toggle take profit in dashboard (default: enabled)
Show RSI-Fib Confluence: Toggle confluence analysis (default: enabled)
Dashboard:
Show Dashboard: Toggle information panel (default: enabled)
Position: Choose corner placement
Colors:
Bullish: Color for bullish elements (default: cyan)
Bearish: Color for bearish elements (default: orange)
Neutral: Color for neutral elements (default: gray)
Golden Zone: Color for Golden Zone highlight (default: gold)
How to Use RSI Fibonacci Flow
Identifying Entry Zones:
Wait for price to retrace to the 38.2%-61.8% zone
Check if RSI is approaching oversold (for longs) or overbought (for shorts)
Look for STRONG confluence rating in the dashboard
Enter when BUY or SELL signal appears
Setting Take Profit Targets:
TP1 at 127.2% extension for conservative target
TP2 at 161.8% extension for aggressive target
Consider scaling out at each level
Using the Price Zone:
"BELOW 23.6%" - Price hasn't retraced much; wait for deeper pullback
"23.6% - 38.2%" - Shallow retracement; strong trend continuation possible
"38.2% - 50%" - Good entry zone for trend trades
"GOLDEN ZONE" - Optimal entry zone; highest probability
"61.8% - 78.6%" - Deep retracement; trend may be weakening
"78.6% - 100%" - Very deep; trend reversal possible
"ABOVE/BELOW 100%" - Trend has likely reversed
Confluence Trading Strategy:
Only take trades with confluence score of 3 or higher
STRONG confluence (4-5) warrants larger position size
MODERATE confluence (2-3) warrants smaller position size
WEAK confluence (0-1) - wait for better setup
Alert Conditions
Ten alert conditions are available:
RSI-Fib BUY Signal: Strong bullish confluence detected
RSI-Fib SELL Signal: Strong bearish confluence detected
Price in Golden Zone: Price enters 50%-61.8% zone
New Pivot High: Swing high detected
New Pivot Low: Swing low detected
RSI Overbought: RSI crosses above overbought threshold
RSI Oversold: RSI crosses below oversold threshold
Bullish Divergence: Potential bullish RSI divergence
Bearish Divergence: Potential bearish RSI divergence
Strong Confluence: Confluence score reaches 4 or higher
Understanding Trend Direction
The indicator determines trend based on pivot sequence:
UPTREND: Last pivot was a low after a high (expecting move up)
DOWNTREND: Last pivot was a high after a low (expecting move down)
Fibonacci levels are drawn accordingly:
In uptrend: 0% at swing low, 100% at swing high
In downtrend: 0% at swing high, 100% at swing low
Bar Coloring
When confluence features are enabled:
Cyan bars on strong bullish signals
Orange bars on strong bearish signals
Gold-tinted bars when price is in Golden Zone
Best Practices
Use on 1H timeframe or higher for more reliable pivots
Adjust Pivot Depth based on timeframe (higher for longer timeframes)
Wait for price to enter Golden Zone before considering entries
Confirm RSI is in favorable territory before trading
Use extension levels (127.2%, 161.8%) for realistic profit targets
Combine with support/resistance and candlestick patterns
Higher confluence scores indicate higher probability setups
Limitations
Pivot detection has inherent lag (must wait for confirmation)
Fibonacci levels are subjective - different swings produce different levels
Works best in trending markets with clear swings
RSI can remain overbought/oversold in strong trends
Not all Golden Zone entries will be successful
The source code is open and available for review and modification.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Trading involves substantial risk of loss. Past performance does not guarantee future results. Fibonacci levels are not guaranteed support/resistance - they are probability zones based on historical price behavior. Always conduct your own analysis and use proper risk management.
- Made with passion by officialjackofalltrades :D
Indicator
Red Bull Wings [JOAT]RED BULL WINGS - Bullish-Only Institutional Overlay
Introduction and Purpose
RED BULL WINGS is an open-source overlay indicator that combines five distinct bullish detection methods into a single composite scoring system. The core problem this indicator solves is that individual bullish signals (patterns, volume, zones, trendlines) often disagree or fire in isolation. A bullish engulfing pattern means little if volume is weak and price is far from support. Traders need confluence across multiple dimensions to identify high-probability setups.
This indicator addresses that by scoring each bullish component separately, then combining them into a weighted WINGS score (0-100) that reflects overall bullish conviction. When multiple components align, the score rises; when they disagree, the score stays low.
Why These Five Modules Work Together
Each module measures a different aspect of bullish market structure:
1. Module A - Bullish Candlestick Engine - Detects classic reversal patterns (engulfing, marubozu, hammer, 3-bar cluster). These patterns identify WHERE buyers are stepping in.
2. Module B - PVSRA Volume Climax - Measures spread x volume to detect institutional participation. This tells you WHETHER smart money is involved.
3. Module C - Demand Zone Detection - Identifies and tracks order block zones where buyers previously overwhelmed sellers. This shows you WHERE institutional support exists.
4. Module D - Trendline Channel - Builds dynamic support/resistance from pivot points. This reveals the STRUCTURE of the current trend.
5. Module E - Ichimoku Assist - Optional filter using Tenkan/Kijun cross, cloud position, and Chikou confirmation. This provides TREND PERMISSION context.
The combination works because:
Patterns alone can fail without volume confirmation
Volume alone means nothing without price structure context
Zones alone are static without pattern/volume triggers
Trendlines alone miss the micro-level entry timing
When 3+ modules agree, the probability of a valid bullish setup increases significantly
How the Calculations Work
Module A - Pattern Detection:
Bullish Engulfing - Current bullish bar completely engulfs prior bearish bar:
bool engulfingCond = isBullish() and
isBearish() and
open <= close and
close >= open and
bodySize() > bodySize()
Marubozu - Strong body with minimal wicks (body >= 1.8x average, wick ratio < 20%):
float wickRatio = candleRange() > 0 ? (upperWick() + lowerWick()) / candleRange() : 0
bool marubozuCond = isBullish() and
bodySize() >= bodySizeAvg * i_maruMult and
wickRatio < i_wickRatioMax
Hammer - Long lower wick (>= 2.5x body), close in upper third, volume confirmation:
bool hammerWick = lowerWick() >= i_hammerWickMult * bodySize()
bool hammerClose = close >= low + (candleRange() * 0.66)
bool hammerVol = volume >= i_pvsraRisingMult * volAvg
3-Bar Cluster - Three consecutive bullish closes with increasing prices and volume spike:
bool threeBarBullish = isBullish() and isBullish() and isBullish()
bool increasingCloses = close > close and close > close
bool volSpike3Bar = volume >= i_pvsraRisingMult * volAvg or
volume >= i_pvsraRisingMult * volAvg
Module B - PVSRA Volume Analysis:
Uses spread x volume to detect climax conditions:
float spreadVol = candleRange() * volume
float maxSpreadVol = ta.highest(spreadVol, ADJ_PVSRA_LOOKBACK)
bool volClimax = volume >= i_pvsraClimaxMult * volAvg or spreadVol >= maxSpreadVol
bool volRising = volume >= i_pvsraRisingMult * volAvg and volume < i_pvsraClimaxMult * volAvg
Volume only scores when the candle is bullish, preventing false signals on bearish volume spikes.
Module C - Demand Zone Detection:
Identifies zones using a two-candle structure:
// Small bearish candle A followed by larger bullish candle B
bool candleA_bearish = isBearish()
bool candleB_bullish = isBullish()
bool newZoneCond = candleA_bearish and candleB_bullish and
candleB_size >= i_zoneSizeMult * candleA_size
Zones are drawn as rectangles and tracked for retests. Score increases when price is near or inside an active zone, with bonus points for rejection candles.
Module D - Trendline Channel:
Builds dynamic channel from confirmed pivot points:
float ph = ta.pivothigh(high, i_pivotLeft, i_pivotRight)
float pl = ta.pivotlow(low, i_pivotLeft, i_pivotRight)
Pivots are stored and connected to form upper/lower channel lines. The indicator detects breakouts when price closes beyond the channel with volume confirmation.
Module E - Ichimoku Assist:
Standard Ichimoku calculations with bullish scoring:
float tenkan = (ta.highest(high, i_tenkanLen) + ta.lowest(low, i_tenkanLen)) / 2
float kijun = (ta.highest(high, i_kijunLen) + ta.lowest(low, i_kijunLen)) / 2
bool tkCross = ta.crossover(tenkan, kijun)
bool priceAboveCloud = close > cloudTop
bool chikouAbovePrice = chikou > close
Module F - WINGS Composite Score:
All module scores are combined using adjustable weights:
float WINGS_score = 100 * (nW_pattern * S_pattern +
nW_volume * S_vol +
nW_zone * S_zone +
nW_trend * S_trend +
nW_ichi * S_ichi)
Default weights: Pattern 30%, Volume 25%, Zone 20%, Trend 15%, Ichimoku 10%.
Signal Thresholds
WATCH (30-49) - Interesting bullish context forming, not yet actionable
MOMENTUM (50-74) - Strong bullish conditions, multiple modules agreeing
LIFT-OFF (75+) - High-confidence bullish confluence across most modules
WINGS Badge (Dashboard)
The right-side panel displays:
WINGS Score - Current composite score (0-100)
Pattern - Active pattern name and strength, or neutral placeholder
Volume - Normal / Rising / CLIMAX status
Zone - ACTIVE if price is near a demand zone
Trend - Channel position or BREAK status
Ichimoku - OFF / Weak / Bullish / STRONG
Status - Overall signal level (Neutral / WATCH / MOMENTUM / LIFT-OFF)
Input Parameters
Module Toggles:
Enable Bullish Patterns (true) - Toggle pattern detection
Enable PVSRA Volume (true) - Toggle volume analysis
Enable Order Blocks (true) - Toggle demand zone detection
Enable Trendlines (true) - Toggle pivot channel
Enable Ichimoku Assist (false) - Toggle Ichimoku filter (off by default for performance)
Enable Visual Effects (false) - Toggle labels, trails, and visual elements
LIVE MODE (false) - Enable intrabar signals (WARNING: signals may repaint)
Pattern Engine:
Pattern Lookback (5) - Bars for body size averaging
Marubozu Body Multiplier (1.8) - Minimum body size vs average
Hammer Wick Multiplier (2.5) - Minimum lower wick vs body
Max Wick Ratio (0.2) - Maximum wick percentage for marubozu
Volume / PVSRA:
PVSRA Lookback (10) - Period for volume averaging
Climax Multiplier (2.0) - Volume threshold for climax detection
Rising Volume Multiplier (1.5) - Volume threshold for rising detection
Order Blocks:
Zone Size Multiplier (2.0) - Minimum bullish candle size vs bearish
Zone Extend Bars (200) - How far zones project forward
Max Zones (12) - Maximum active zones displayed
Remove Zone on Close Below (true) - Delete broken zones
Trendlines:
Pivot Left/Right Bars (3/3) - Pivot detection sensitivity
Min Slope % (0.25) - Minimum trendline angle
Max Trendlines (5) - Maximum pivot points stored
Trendline Projection Bars (60) - Forward projection distance
Ichimoku:
Tenkan Length (9) - Conversion line period
Kijun Length (26) - Base line period
Senkou B Length (52) - Leading span B period
Displacement (26) - Cloud displacement
WINGS Score:
Weight: Pattern (0.30) - Pattern contribution to score
Weight: Volume (0.25) - Volume contribution to score
Weight: Zone (0.20) - Zone contribution to score
Weight: Trend (0.15) - Trendline contribution to score
Weight: Ichimoku (0.10) - Ichimoku contribution to score
Lift-Off Threshold (75) - Score required for LIFT-OFF signal
Momentum Watch Threshold (50) - Score required for MOMENTUM signal
Visuals:
Signal Cooldown (8) - Minimum bars between labels
Show WINGS Score Badge (true) - Toggle dashboard
Show Wing Combos (true) - Show DOUBLE/MEGA WINGS streaks
Red Background Wash (true) - Tint chart background
Show Lift-Off Trails (false) - Toggle golden trail visuals
How to Use This Indicator
For Bullish Entry Identification:
1. Monitor the WINGS badge for score changes
2. Wait for MOMENTUM (50+) or LIFT-OFF (75+) signals
3. Check which modules are contributing (Pattern + Volume + Zone = stronger)
4. Use demand zones and trendlines as structural reference for entries
For Confluence Confirmation:
1. Use alongside your existing analysis
2. LIFT-OFF signals indicate multiple bullish factors aligning
3. Low scores (< 30) suggest weak bullish context even if one factor looks good
For Zone-Based Trading:
1. Watch for price approaching active demand zones
2. Look for pattern + volume confirmation at zone retests
3. Zone score increases with successful retests
For Trendline Analysis:
1. Monitor the pivot-based channel for trend structure
2. Breakouts with volume confirmation trigger TREND BREAK alerts
3. Price inside channel with bullish patterns = trend continuation setup
1M and lower timeframes:
Alerts Available
LIFT-OFF - High-confidence bullish confluence
MOMENTUM - Strong bullish conditions
Zone Retest - Bullish rejection from demand zone
Trendline Break - Breakout with volume confirmation
Individual patterns (Engulfing, Marubozu, Hammer, 3-Bar Cluster)
Volume Climax - Institutional volume spike
DOUBLE WINGS / MEGA WINGS - Consecutive lift-off signals
Repainting Behavior
By default, the indicator uses confirmed bars only (barstate.isconfirmed), meaning signals appear after the bar closes and do not repaint. However:
LIVE MODE - When enabled, signals can appear intrabar but may disappear if conditions change before bar close. A warning label displays when LIVE MODE is active.
Trendlines - Pivot detection requires lookback bars, so the most recent trendline segments may adjust as new pivots confirm. This is inherent to pivot-based analysis.
Demand Zones - Zones are created on confirmed bars and do not repaint, but they can be removed if price closes below the zone bottom (configurable).
Live Mode with 'Enable Visual Effect' turned off in settings:
Limitations
This is a bullish-only indicator. It does not detect bearish setups or provide short signals.
The WINGS score is a confluence measure, not a prediction. High scores indicate favorable conditions, not guaranteed outcomes.
Pattern detection uses simplified logic. Not all candlestick nuances are captured.
Volume analysis requires reliable volume data. Results may vary on instruments with inconsistent volume reporting.
Ichimoku calculations add processing overhead. Disable if not needed.
Demand zones are based on a specific two-candle structure. Other valid zones may not be detected.
Trendlines use linear regression between pivots. Curved or complex channels are not supported.
Timeframe Recommendations
15m-1H: More frequent signals, useful for intraday analysis. Higher noise.
4H-Daily: Best balance of signal quality and frequency for swing trading.
Weekly: Fewer but more significant signals for position trading.
Adjust lookback periods and thresholds based on your timeframe. Shorter timeframes may benefit from shorter lookbacks.
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. The source code is fully visible and can be studied to understand how each module works.
This indicator does not constitute financial advice. The WINGS score and signals do not guarantee profitable trades. Past performance does not guarantee future results. Always use proper risk management, position sizing, and stop-losses. Test thoroughly on your preferred instruments and timeframes before using in live trading.
- Made with passion by officialjackofalltrades
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Prism Band Dynamics [JOAT]Prism Band Dynamics - Bollinger-Style Bands with Force Detection
Introduction and Purpose
Prism Band Dynamics is an open-source overlay indicator that creates dynamic Bollinger-style bands with an innovative "force detection" system. The core problem this indicator solves is that standard Bollinger Bands show volatility but don't indicate directional momentum. When all three band components (upper, lower, basis) move in the same direction, it indicates strong directional force that standard bands don't highlight.
This indicator addresses that by detecting when all band components align directionally, providing a clear signal of market force.
Why Force Detection Matters
Standard Bollinger Bands expand and contract based on volatility, but they don't tell you about directional momentum. Force detection adds this dimension:
1. Bullish Force - Upper band, lower band, AND basis all moving up together. This indicates strong upward momentum where even the lower support level is rising.
2. Bearish Force - Upper band, lower band, AND basis all moving down together. This indicates strong downward momentum where even the upper resistance level is falling.
3. Neutral - Mixed movement indicates consolidation or uncertainty.
How Force Detection Works
bool upperUp = upper > upper
bool lowerUp = lower > lower
bool basisUp = basis > basis
int forceFull = if upperUp and lowerUp and basisUp
1 // Bullish force
else if upperDn and lowerDn and basisDn
-1 // Bearish force
else
0 // Neutral
Additional Features
Squeeze Detection - Identifies when band width contracts below threshold, often preceding large moves
Gradient Fills - Color intensity reflects force strength
Direction Change Arrows - Visual markers when force direction shifts
Dashboard Information
Force - Current force status (BULLISH/BEARISH/NEUTRAL)
Position - Price location within bands (Upper/Mid/Lower Zone)
Band Width - Current width percentage with expansion/contraction label
Volatility - Squeeze status (SQUEEZE/NORMAL)
Force Count - Bars since last force change
How to Use This Indicator
For Trend Following:
1. Enter long when force turns BULLISH
2. Enter short when force turns BEARISH
3. Exit or reduce when force turns NEUTRAL
For Squeeze Breakouts:
1. Watch for SQUEEZE status in dashboard
2. Prepare for breakout in either direction
3. Enter when force confirms direction after squeeze
For Mean Reversion:
1. Only trade mean-reversion when force is NEUTRAL
2. Avoid fading moves when force is active
3. Use band touches as entry points during neutral force
Input Parameters
Length (20) - Period for basis and standard deviation
Multiplier (2.0) - Standard deviation multiplier for bands
MA Type (SMA) - Basis calculation method
Squeeze Threshold (0.5) - Band width percentage for squeeze detection
Timeframe Recommendations
4H-Daily: Cleanest force signals
1H: Good balance of signals and reliability
15m: More signals but more noise
Limitations
Force detection can lag during rapid reversals
Squeeze breakouts can fail (false breakouts)
Works best in markets with clear trending/ranging phases
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes.
This indicator does not constitute financial advice. Force detection does not guarantee trend continuation. Always use proper risk management.
- Made with passion by officialjackofalltrades
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Eclipse Multi-Oscillator [JOAT]Eclipse Multi-Oscillator - Unified Momentum Confluence System
Introduction and Purpose
Eclipse Multi-Oscillator is an open-source indicator that combines four classic oscillators (RSI, Stochastic, CCI, and Williams %R) into a single unified view with confluence detection. The core problem this indicator solves is oscillator disagreement: traders often see RSI oversold while Stochastic is neutral, or CCI overbought while Williams %R is mid-range. This creates confusion about the true momentum state.
This indicator addresses that by displaying all four oscillators together and counting how many agree on overbought or oversold conditions, providing a clear confluence score that cuts through the noise.
Why These Four Oscillators Work Together
Each oscillator measures momentum differently, and their combination provides a more complete picture:
1. RSI (Relative Strength Index) - Measures the magnitude of recent price changes. Best at identifying momentum exhaustion.
2. Stochastic - Compares closing price to the high-low range. Best at identifying where price is within its recent range.
3. CCI (Commodity Channel Index) - Measures price deviation from statistical mean. Best at identifying unusual price movements.
4. Williams %R - Similar to Stochastic but inverted. Provides confirmation of Stochastic readings.
When 3 or more of these oscillators agree on overbought or oversold, the signal is significantly more reliable than any single oscillator alone.
How Confluence Scoring Works
The indicator counts how many oscillators are in extreme territory:
int obCount = 0
if rsi > rsiOB
obCount += 1
if stochK > stochOB
obCount += 1
if cci > cciOB
obCount += 1
if willRScaled > stochOB
obCount += 1
bool strongOverbought = obCount >= 3
bool strongOversold = osCount >= 3
The confluence score ranges from -4 (all oversold) to +4 (all overbought), with 0 being neutral.
Signal Types
Strong Oversold - 3+ oscillators below oversold threshold (potential bounce)
Strong Overbought - 3+ oscillators above overbought threshold (potential pullback)
OB/OS Exit - RSI leaving extreme zone with Stochastic confirmation (potential reversal)
Divergence - Price makes new high/low while RSI does not (potential reversal warning)
Dashboard Information
RSI/Stoch K/CCI/Will %R - Current values with zone status (OB/OS/MID)
Confluence - Overall bias (STRONG OS, STRONG OB, Lean Bull/Bear, Neutral)
OB Count - How many oscillators are overbought (0-4)
OS Count - How many oscillators are oversold (0-4)
How to Use This Indicator
For Reversal Trading:
1. Wait for Strong Oversold (3+ oscillators agree)
2. Look for bullish candlestick pattern or support level
3. Enter long with stop below recent low
4. Take profit when confluence returns to neutral or overbought
For Trend Confirmation:
1. Check confluence direction matches your trade bias
2. Avoid longs when confluence is strongly overbought
3. Avoid shorts when confluence is strongly oversold
For Divergence Trading:
1. Watch for "D" labels indicating RSI divergence
2. Bullish divergence at support = potential long
3. Bearish divergence at resistance = potential short
Input Parameters
RSI Length (14) - Period for RSI calculation
Stochastic K/D Length (14/3) - Periods for Stochastic
CCI Length (20) - Period for CCI
Williams %R Length (14) - Period for Williams %R
OB/OS Thresholds - Customizable levels for each oscillator
Timeframe Recommendations
15m-1H: Good for intraday momentum analysis
4H-Daily: Best for swing trading confluence
Very short timeframes may produce noisy signals
Limitations
All oscillators can remain in extreme territory during strong trends
Confluence does not predict direction, only identifies extremes
Divergence detection is simplified and may miss some patterns
Works best in ranging or moderately trending markets
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. The source code is fully visible and can be studied.
This indicator does not constitute financial advice. Oscillator confluence does not guarantee reversals. Past performance does not guarantee future results. Always use proper risk management.
- Made with passion by officialjackofalltrades
Indicator
Aurora Volatility Bands [JOAT]Aurora Volatility Bands - Dynamic ATR-Based Envelope System
Introduction and Purpose
Aurora Volatility Bands is an open-source overlay indicator that creates multi-layered volatility envelopes around price using ATR (Average True Range) calculations. The core problem this indicator solves is that static bands (like fixed percentage envelopes) fail to adapt to changing market conditions. During high volatility, static bands are too tight; during low volatility, they're too wide.
This indicator addresses that by using ATR-based dynamic bands that automatically expand during volatile periods and contract during quiet periods, providing contextually appropriate support/resistance levels at all times.
Why These Components Work Together
The indicator combines three analytical approaches:
1. Triple-Layer Band System - Inner (1x ATR), Outer (2x ATR), and Extreme (3x ATR) bands provide graduated levels of significance
2. Volatility State Detection - Compares current ATR to historical average to classify market regime
3. Multiple MA Types - Allows customization of the center line calculation method
These components complement each other:
The triple-layer system gives traders multiple reference points - inner bands for normal moves, outer for significant moves, extreme for rare events
Volatility state detection tells you WHEN bands are expanding or contracting, helping anticipate breakouts or mean-reversion
MA type selection lets you match the indicator to your trading style (faster EMA vs smoother SMA)
How the Calculation Works
The bands are calculated using ATR multiplied by configurable factors:
float atr = ta.atr(atrPeriod)
float innerUpper = centerMA + (atr * innerMult)
float outerUpper = centerMA + (atr * outerMult)
float extremeUpper = centerMA + (atr * extremeMult)
Volatility state is determined by comparing current ATR percentage to its historical average:
float atrPercent = (atr / close) * 100
float avgAtrPercent = ta.sma(atrPercent, volatilityLookback)
float volatilityRatio = atrPercent / avgAtrPercent
bool isExpanding = volatilityRatio > 1.2 // 20%+ above average
bool isContracting = volatilityRatio < 0.8 // 20%+ below average
Signal Types
Band Touch - Price reaches inner, outer, or extreme bands
Mean Reversion - Price returns to center after touching outer/extreme bands
Breakout - Sustained move beyond outer bands during volatility expansion
Dashboard Information
Volatility - Current state (EXPANDING/CONTRACTING/NORMAL)
Vol Ratio - Current volatility vs average (e.g., 1.5x = 50% above average)
ATR - Current ATR value
ATR % - ATR as percentage of price
Zone - Current price position (EXTREME HIGH/UPPER ZONE/CENTER ZONE/etc.)
Position - Price position as percentage within band structure
Width - Total band width as percentage of price
Using SMA in settings:
How to Use This Indicator
For Mean-Reversion Trading:
1. Wait for price to touch outer or extreme bands
2. Check that volatility state is NORMAL or CONTRACTING (not expanding)
3. Look for reversal candlestick patterns at the band
4. Enter toward center MA with stop beyond the band
For Breakout Trading:
1. Wait for volatility state to show EXPANDING
2. Look for price closing beyond outer bands
3. Enter in direction of breakout
4. Use the band as trailing stop reference
For Volatility Analysis:
1. Monitor volatility ratio for regime changes
2. CONTRACTING often precedes large moves (squeeze)
3. EXPANDING confirms trend strength
Using VWMA and Mean Reversion Signal/MR:
Input Parameters
ATR Period (14) - Period for ATR calculation
Inner/Outer/Extreme Multipliers (1.0/2.0/3.0) - Band distance from center
MA Type (EMA) - Center line calculation method
MA Period (20) - Period for center line
Volatility Comparison Period (20) - Lookback for volatility state
Timeframe Recommendations
15m-1H: Good for intraday mean-reversion
4H-Daily: Best for swing trading and breakout identification
Weekly: Useful for position trading and major level identification
Limitations
ATR-based bands lag during sudden volatility spikes
Mean-reversion signals can fail in strong trends
Breakout signals may whipsaw in ranging markets
Works best on liquid instruments with consistent volatility patterns
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. The source code is fully visible and can be studied to understand how each component works.
This indicator does not constitute financial advice. Band touches do not guarantee reversals. Past performance does not guarantee future results. Always use proper risk management, position sizing, and stop-losses.
- Made with passion by officialjackofalltrades Indicator
Entropy Balance Oscillator [JOAT]
Entropy Balance Oscillator - Chaos Theory Edition
Overview
Entropy Balance Oscillator is an open-source oscillator indicator that applies chaos theory concepts to market analysis. It calculates market entropy (disorder/randomness), balance (price position within range), and various chaos metrics to identify whether the market is in an ordered, chaotic, or balanced state. This helps traders understand market regime and adjust their strategies accordingly.
What This Indicator Does
The indicator calculates and displays:
Entropy - Measures market disorder using return distribution analysis
Balance - Price position within the high-low range, normalized to -1 to +1
Lyapunov Exponent - Estimates sensitivity to initial conditions (chaos indicator)
Hurst Exponent - Measures long-term memory in price series (trend persistence)
Strange Attractor - Simulated attractor points for visualization
Bifurcation Detection - Identifies potential regime change points
Chaos Index - Combined entropy and volatility score
Market Phase - Classification as CHAOS, ORDER, or BALANCED
How It Works
Entropy is calculated using return distribution:
calculateEntropy(series float price, simple int period) =>
// Calculate returns and their absolute values
// Sum absolute returns for normalization
// Apply Shannon entropy formula: -sum(p * log(p))
float entropy = 0.0
for i = 0 to array.size(returns) - 1
float prob = math.abs(array.get(returns, i)) / sumAbs
if prob > 0
entropy -= prob * math.log(prob)
entropy
Balance measures price position within range:
calculateBalance(series float high, series float low, series float close, simple int period) =>
float range = high - low
float position = (close - low) / (range > 0 ? range : 1)
float balance = ta.ema(position, period)
(balance - 0.5) * 2 // Normalize to -1 to +1
Lyapunov Exponent estimates chaos sensitivity:
lyapunovExponent(series float price, simple int period) =>
float sumLog = 0.0
for i = 1 to period
float ratio = price > 0 ? math.abs(price / price ) : 1.0
if ratio > 0
sumLog += math.log(ratio)
lyapunov := sumLog / period
Hurst Exponent measures trend persistence:
H > 0.5: Trending/persistent behavior
H = 0.5: Random walk
H < 0.5: Mean-reverting behavior
Signal Generation
Phase changes and extreme conditions generate signals:
Chaos Phase: Normalized entropy exceeds chaos threshold (default 0.7)
Order Phase: Normalized entropy falls below order threshold (default 0.3)
Extreme Chaos: Entropy exceeds 1.5x chaos threshold
Extreme Order: Entropy falls below 0.5x order threshold
Bifurcation: Variance exceeds 2x average variance
Dashboard Panel (Top-Right)
Market Phase - Current phase (CHAOS/ORDER/BALANCED)
Entropy Level - Normalized entropy value
Balance - Current balance reading (-1 to +1)
Chaos Index - Combined chaos score percentage
Volatility - Current price volatility
Lyapunov Exp - Lyapunov exponent value
Hurst Exponent - Hurst exponent value
Chaos Score - Overall chaos assessment
Status - Current market status
Visual Elements
Entropy Line - Main oscillator showing normalized entropy
Entropy EMA - Smoothed entropy for trend reference
Balance Area - Filled area showing balance direction
Chaos/Order Thresholds - Horizontal dashed lines
Lyapunov Line - Step line showing Lyapunov exponent
Strange Attractor - Circle plots showing attractor points
Phase Space - Line showing phase space reconstruction
Phase Background - Background color based on current phase
Extreme Markers - X-cross for extreme chaos, diamond for extreme order
Bifurcation Markers - Circles at potential regime changes
Input Parameters
Entropy Period (default: 20) - Period for entropy calculation
Balance Period (default: 14) - Period for balance calculation
Chaos Threshold (default: 0.7) - Threshold for chaos phase
Order Threshold (default: 0.3) - Threshold for order phase
Lyapunov Exponent (default: true) - Enable Lyapunov calculation
Hurst Exponent (default: true) - Enable Hurst calculation
Strange Attractor (default: true) - Enable attractor visualization
Bifurcation Detection (default: true) - Enable bifurcation detection
Suggested Use Cases
Identify market regime for strategy selection (trend-following vs mean-reversion)
Watch for phase changes as potential trading environment shifts
Use Hurst exponent to assess trend persistence
Monitor chaos index for volatility regime awareness
Avoid trading during extreme chaos phases
Timeframe Recommendations
Best on 1H to Daily charts. Chaos metrics require sufficient data for meaningful calculations.
Limitations
Chaos theory concepts are applied as analogies, not rigorous mathematical implementations
Lyapunov and Hurst calculations are simplified approximations
Strange attractor visualization is conceptual
Bifurcation detection uses variance as proxy
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always use proper risk management.
- Made with passion by officialjackofalltrades
Indicator
Velocity Divergence Radar [JOAT]
Velocity Divergence Radar - Momentum Physics Edition
Overview
Velocity Divergence Radar is an open-source oscillator indicator that applies physics concepts to market analysis. It calculates price velocity (rate of change), acceleration (rate of velocity change), and jerk (rate of acceleration change) to provide a multi-dimensional view of momentum. The indicator also includes divergence detection and force vector analysis.
What This Indicator Does
The indicator calculates and displays:
Velocity - Rate of price change over a configurable period, smoothed with EMA
Acceleration - Rate of velocity change, showing momentum shifts
Jerk (3rd Derivative) - Rate of acceleration change, indicating momentum stability
Force Vectors - Volume-weighted acceleration representing market force
Kinetic Energy - Calculated as 0.5 * mass (volume ratio) * velocity squared
Momentum Conservation - Tracks momentum relative to historical average
Divergence Detection - Identifies when price and velocity diverge at pivots
How It Works
Velocity is calculated as smoothed rate of change:
calculateVelocity(series float price, simple int period) =>
float roc = ta.roc(price, period)
float velocity = ta.ema(roc, period / 2)
velocity
Acceleration is the change in velocity:
calculateAcceleration(series float velocity, simple int period) =>
float accel = ta.change(velocity, period)
float smoothAccel = ta.ema(accel, period / 2)
smoothAccel
Jerk is the change in acceleration:
calculateJerk(series float acceleration, simple int period) =>
float jerk = ta.change(acceleration, period)
float smoothJerk = ta.ema(jerk, period / 2)
smoothJerk
Force is calculated using F = m * a (mass approximated by volume ratio):
calculateForceVector(series float mass, series float acceleration) =>
float force = mass * acceleration
float forceDirection = math.sign(force)
float forceMagnitude = math.abs(force)
Signal Generation
Signals are generated based on velocity behavior:
Bullish Divergence: Price makes lower low while velocity makes higher low
Bearish Divergence: Price makes higher high while velocity makes lower high
Velocity Cross: Velocity crosses above/below zero line
Extreme Velocity: Velocity exceeds 1.5x the upper/lower zone threshold
Jerk Extreme: Jerk exceeds 2x standard deviation
Force Extreme: Force magnitude exceeds 2x average
Dashboard Panel (Top-Right)
Velocity - Current velocity value
Acceleration - Current acceleration value
Momentum Strength - Combined velocity and acceleration strength
Radar Score - Composite score based on velocity and acceleration
Direction - STRONG UP/SLOWING UP/STRONG DOWN/SLOWING DOWN/FLAT
Jerk - Current jerk value
Force Vector - Current force magnitude
Kinetic Energy - Current kinetic energy value
Physics Score - Overall physics-based momentum score
Signal - Current actionable status
Visual Elements
Velocity Line - Main oscillator line with color based on direction
Velocity EMA - Smoothed velocity for trend reference
Acceleration Histogram - Bar chart showing acceleration direction
Jerk Area - Filled area showing jerk magnitude
Vector Magnitude - Line showing combined vector strength
Radar Scan - Oscillating pattern for visual effect
Zone Lines - Upper and lower threshold lines
Divergence Labels - BULL DIV / BEAR DIV markers
Extreme Markers - Triangles at velocity extremes
Input Parameters
Velocity Period (default: 14) - Period for velocity calculation
Acceleration Period (default: 7) - Period for acceleration calculation
Divergence Lookback (default: 10) - Bars to scan for divergence
Radar Sensitivity (default: 1.0) - Zone threshold multiplier
Jerk Analysis (default: true) - Enable 3rd derivative calculation
Force Vectors (default: true) - Enable force analysis
Kinetic Energy (default: true) - Enable energy calculation
Momentum Conservation (default: true) - Enable momentum tracking
Suggested Use Cases
Identify momentum direction using velocity sign and magnitude
Watch for divergences as potential reversal warnings
Use acceleration to detect momentum shifts before price confirms
Monitor jerk for momentum stability assessment
Combine force and kinetic energy for conviction analysis
Timeframe Recommendations
Works on all timeframes. Higher timeframes provide smoother readings; lower timeframes show more granular momentum changes.
Limitations
Physics analogies are conceptual and not literal market physics
Divergence detection uses pivot-based lookback and may lag
Force calculation uses volume ratio as mass proxy
Kinetic energy is a derived metric, not actual energy
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always use proper risk management.
- Made with passion by officialjackofalltrades
Indicator
Indicator
Ocean Master [JOAT]Ocean Master QE - Advanced Oceanic Market Analysis with Quantum Flow Dynamics
Overview
Ocean Master QE is an open-source overlay indicator that combines multiple analytical techniques into a unified market analysis framework. It uses ATR-based dynamic channels, volume-weighted order flow analysis, multi-timeframe correlation (quantum entanglement concept), and harmonic oscillator calculations to provide traders with a comprehensive view of market conditions.
What This Indicator Does
The indicator calculates and displays several key components:
Dynamic Price Channels - ATR-adjusted upper, middle, and lower channels that adapt to current volatility conditions
Order Flow Analysis - Separates buying and selling volume pressure to calculate a directional delta
Smart Money Index - Volume-weighted order flow metric that highlights potential institutional activity
Harmonic Oscillator - Weighted combination of 10 Fibonacci-period EMAs (5, 8, 13, 21, 34, 55, 89, 144, 233, 377) to identify trend direction
Multi-Timeframe Correlation - Measures price correlation across 1H, 4H, and Daily timeframes
Wave Function Analysis - Momentum-based state detection that identifies when price action becomes decisive
How It Works
The core channel calculation uses ATR with a configurable quantum sensitivity factor:
float atr = ta.atr(i_atrLength)
float quantumFactor = 1.0 + (i_quantumSensitivity * 0.1)
float quantumATR = atr * quantumFactor
upperChannel := ta.highest(high, i_length) - (quantumATR * 0.5)
lowerChannel := ta.lowest(low, i_length) + (quantumATR * 0.5)
midChannel := (upperChannel + lowerChannel) * 0.5
Order flow is calculated by separating volume into buy and sell components based on candle direction:
The harmonic oscillator weights shorter EMAs more heavily using inverse weighting (1/1, 1/2, 1/3... 1/10), creating a responsive yet smooth trend indicator.
Signal Generation
Confluence signals require multiple conditions to align:
Bullish: Harmonic oscillator crosses above zero + positive Smart Money Index + positive Order Flow Delta
Bearish: Harmonic oscillator crosses below zero + negative Smart Money Index + negative Order Flow Delta
Dashboard Panel (Top-Right)
Bias - Current market direction based on price vs mid-channel
Entanglement - Multi-timeframe correlation score (0-100%)
Wave State - COLLAPSED (decisive) or SUPERPOSITION (uncertain)
Volume - Current volume relative to 20-period average
Volatility - ATR as percentage of price
Smart Money - Volume-weighted order flow reading
Visual Elements
Ocean Depth Layers - Gradient fills between channel levels representing different price zones
Channel Lines - Upper (surface), middle, and lower (seabed) dynamic levels
Divergence Markers - Triangle shapes when harmonic oscillator crosses zero
Confluence Labels - BULL/BEAR labels when multiple factors align
Suggested Use Cases
Identify trend direction using the harmonic oscillator and channel position
Monitor order flow for potential institutional activity
Use multi-timeframe correlation to confirm trade direction across timeframes
Watch for confluence signals where multiple factors align
Input Parameters
Length (default: 14) - Base period for channel and indicator calculations
ATR Length (default: 14) - Period for ATR calculation
Quantum Depth (default: 3) - Complexity factor for calculations
Quantum Sensitivity (default: 1.5) - Channel width multiplier
Timeframe Recommendations
Works on all timeframes. Higher timeframes (4H, Daily) provide smoother signals; lower timeframes require faster reaction times and may produce more noise.
Limitations
Multi-timeframe requests add processing overhead
Order flow estimation is based on candle direction, not actual order book data
Correlation calculations require sufficient historical data
Open-Source and Disclaimer
This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always use proper risk management and conduct your own analysis before trading.
- Made with passion by officialjackofalltrades
Indicator
