Momentum Breakout Filter + ATR ZonesMomentum Breakout Filter + ATR Zones - User Guide
What This Indicator Does
This indicator helps you with your MACD + volume momentum strategy by:
Filtering out fake breakouts - Shows ⚠️ warnings when breakouts lack confirmation
Showing clear entry signals - 🚀 LONG and 🔻 SHORT labels when all conditions align
Automatic stop loss & profit targets - Based on ATR (Average True Range)
Visual trend confirmation - Background color + EMA alignment
Signal Types
🚀 LONG Entry Signal (Green Label)
Appears when ALL conditions met:
✅ MACD crosses above signal line
✅ Volume > 1.5× average
✅ Price > EMA 9 > EMA 21 > EMA 200 (bullish trend)
✅ Price closes above recent 20-bar high
🔻 SHORT Entry Signal (Red Label)
Appears when ALL conditions met:
✅ MACD crosses below signal line
✅ Volume > 1.5× average
✅ Price < EMA 9 < EMA 21 < EMA 200 (bearish trend)
✅ Price closes below recent 20-bar low
⚠️ FAKE Breakout Warning (Orange Label)
Appears when price breaks high/low BUT lacks confirmation:
❌ Low volume (below 1.5× average), OR
❌ Wick break only (didn't close through level), OR
❌ MACD not aligned with direction
Hover over the warning label to see what's missing!
ATR Stop Loss & Targets
When you get a signal, colored lines automatically appear:
Long Position
Red solid line = Stop Loss (Entry - 1.5×ATR)
Green dashed lines = Profit Targets:
Target 1: Entry + 2×ATR
Target 2: Entry + 3×ATR
Target 3: Entry + 4×ATR
Short Position
Red solid line = Stop Loss (Entry + 1.5×ATR)
Green dashed lines = Profit Targets:
Target 1: Entry - 2×ATR
Target 2: Entry - 3×ATR
Target 3: Entry - 4×ATR
The lines move with each bar until you exit the position.
Chart Elements
Moving Averages
Blue line = EMA 9 (fast)
Orange line = EMA 21 (medium)
White line = EMA 200 (trend filter)
Volume
Yellow bars = High volume (above threshold)
Gray bars = Normal volume
Background Color
Light green = Bullish trend (all EMAs aligned up)
Light red = Bearish trend (all EMAs aligned down)
No color = Neutral/mixed
MACD (Bottom Pane)
Green/Red columns = MACD Histogram
Blue line = MACD Line
Orange line = Signal Line
Info Dashboard (Bottom Right)
ItemWhat It ShowsVolumeCurrent volume vs average (✓ HIGH or ✗ Low)MACDDirection (BULLISH or BEARISH)TrendEMA alignment (BULL, BEAR, or NEUTRAL)ATRCurrent ATR value in dollarsPositionCurrent position (LONG, SHORT, or NONE)R:RRisk-to-Reward ratio (shows when in position)
How To Use It
Basic Workflow
Wait for setup
Watch for MACD to approach signal line
Volume should be building
Price should be near EMA structure
Get confirmation
Wait for 🚀 LONG or 🔻 SHORT label
Check dashboard shows "✓ HIGH" volume
Verify trend is aligned (green or red background)
Enter the trade
Enter when signal appears
Note your stop loss (red line)
Note your targets (green dashed lines)
Manage the trade
Exit at first target for partial profit
Move stop to breakeven
Trail remaining position
What To Avoid
❌ Don't trade when you see:
⚠️ FAKE labels (wait for confirmation)
Neutral background (no clear trend)
"✗ Low" volume in dashboard
MACD and Trend not aligned
Settings You Can Adjust
Volume Sensitivity
High Volume Threshold: Default 1.5×
Increase to 2.0× for cleaner signals (fewer trades)
Decrease to 1.2× for more signals (more trades)
Fake Breakout Filters
You can toggle these ON/OFF:
Volume Confirmation: Requires high volume
Close Through: Requires candle close, not just wick
MACD Alignment: Requires MACD direction match
Tip: Turn all three ON for highest quality signals
ATR Stop/Target Multipliers
Default settings (conservative):
Stop Loss: 1.5×ATR
Target 1: 2×ATR (1.33:1 R:R)
Target 2: 3×ATR (2:1 R:R)
Target 3: 4×ATR (2.67:1 R:R)
Aggressive traders might use:
Stop Loss: 1.0×ATR
Target 1: 2×ATR (2:1 R:R)
Target 2: 4×ATR (4:1 R:R)
Conservative traders might use:
Stop Loss: 2.0×ATR
Target 1: 3×ATR (1.5:1 R:R)
Target 2: 5×ATR (2.5:1 R:R)
Example Trade Scenarios
Scenario 1: Perfect Long Setup ✅
Stock consolidating near EMA 21
MACD curling up toward signal line
Volume bar turns yellow (high volume)
🚀 LONG label appears
Red stop line and green target lines appear
Result: High probability trade
Scenario 2: Fake Breakout Avoided ✅
Price breaks above resistance
Volume is normal (gray bar)
⚠️ FAKE label appears (hover shows "Low volume")
No entry signal
Price falls back below breakout level
Result: Avoided losing trade
Scenario 3: Premature Entry ❌
MACD crosses up
Volume is high
BUT trend is NEUTRAL (no background color)
No signal appears (trend filter blocks it)
Result: Avoided choppy/sideways market
Quick Reference
Entry Checklist
🚀 or 🔻 label on chart
Dashboard shows "✓ HIGH" volume
Dashboard shows aligned MACD + Trend
Colored background (green or red)
ATR lines visible
No ⚠️ FAKE warning
Exit Strategy
Target 1 (2×ATR): Take 50% profit, move stop to breakeven
Target 2 (3×ATR): Take 25% profit, trail stop
Target 3 (4×ATR): Take remaining profit or trail aggressively
Stop Loss: Exit entire position if hit
Alerts
Set up these alerts:
Long Entry: Fires when 🚀 LONG signal appears
Short Entry: Fires when 🔻 SHORT signal appears
Fake Breakout Warning: Fires when ⚠️ appears (optional)
Tips for Success
Use on 5-minute charts for day trading momentum plays
Only trade high volume stocks ($5-20 range works best)
Wait for full confirmation - don't jump early
Respect the stop loss - it's calculated based on volatility
Scale out at targets - don't hold for home runs
Avoid trading first 15 minutes - let market settle
Best during 10am-11am and 2pm-3pm - peak momentum times
Common Questions
Q: Why didn't I get a signal even though MACD crossed?
A: All conditions must be met - check dashboard for what's missing (likely volume or trend alignment)
Q: Can I use this on any timeframe?
A: Yes, but it's designed for 5-15 minute charts. On daily charts, adjust ATR multipliers higher.
Q: The stop loss seems too tight, can I widen it?
A: Yes, increase "Stop Loss (×ATR)" from 1.5 to 2.0 or 2.5 in settings.
Q: I keep seeing FAKE warnings but price keeps going - what gives?
A: The filter is conservative. You can disable some filters in settings, but expect more false signals.
Q: Can I use this for swing trading?
A: Yes, but use larger timeframes (1H or 4H) and adjust ATR multipliers up (3× for stops, 6-9× for targets).
Wyszukaj w skryptach "high low"
Experimental Supertrend [CHE]Experimental Supertrend — Combines EMA crossovers for trend regime detection with an adaptive ATR-based hull that selects the narrowest band to contain recent highs and lows, minimizing false breaks in varying volatility.
Summary
This indicator overlays a dynamic supertrend boundary around a midline derived from dual EMAs, using EMA crossovers to switch between bullish and bearish regimes. The hull adapts by evaluating multiple ATR periods and selecting the tightest one that fully encloses price action over a specified window, which helps in creating more stable trend lines that hug price without excessive gaps or breaches. Fills between the midline and hull provide visual cues for trend strength, darkening temporarily after regime changes to highlight transitions. Alerts trigger on crossovers, and markers label entry points, making it suitable for trend-following setups where standard supertrends might whipsaw. Overall, it offers robustness through auto-adjustment, reducing sensitivity to noise while maintaining responsiveness to genuine shifts.
Motivation: Why this design?
Standard supertrend indicators often flip prematurely in choppy markets due to fixed multipliers that do not account for localized volatility patterns, leading to frequent false signals and eroded confidence in trends. This design addresses that by incorporating an EMA-based regime filter for directional bias and an auto-adaptive hull that dynamically tunes the band width based on recent price containment needs. By prioritizing the narrowest effective enclosure, it avoids over-wide bands in calm periods that cause lag or under-wide ones in volatility spikes that invite breaks, providing a more consistent trailing reference without manual tweaking.
What’s different vs. standard approaches?
- Reference baseline: Diverges from the classic ATR-multiplier supertrend, which uses a single fixed period and constant factor applied to close or high/low deviations.
- Architecture differences:
- Auto-selection from candidate ATR lengths to find the optimal period for current conditions.
- Dynamic multiplier clamped between floor and cap values, adjusted by padding to ensure reliable containment.
- Regime-gated rendering, where hull position flips based on EMA relative positioning.
- Post-transition visual fading to emphasize change points without altering core logic.
- Practical effect: Charts show tighter, more reactive bands that rarely breach during trends, reducing visual clutter from flips; the adaptive nature means less intervention across assets, as the hull self-adjusts to volatility clusters rather than applying a one-size-fits-all scale.
How it works (technical)
The indicator first computes two EMAs from close prices using lengths derived from a preset pair or manual inputs, establishing a midline as their average. This midline serves as the central reference for the hull. True range values are then smoothed into multiple ATR candidates using exponential weighting over the specified lengths. For each candidate, deviations of recent highs and lows from the midline are ratioed against the ATR to determine a required multiplier that would enclose all extremes in the containment window—the highest ratio plus padding sets the base, clamped to user-defined bounds. Among valid candidates (those with sufficient history), the one yielding the narrowest overall band width is selected. The hull boundaries are then offset from the midline by this multiplier times the chosen ATR, and further smoothed with a fixed EMA to reduce jitter. Regime direction from EMA comparison gates which boundary acts as support or resistance, with initialization seeding arrays on the first bar to handle state persistence. No higher timeframe data is used, so all logic runs on the chart's native bars without lookahead.
Parameter Guide
EMA Pair — Selects preset lengths for fast and slow EMAs, influencing regime sensitivity and midline stability. Default: "21/55". Trade-offs/Tips: Faster pairs like "9/21" increase cross frequency for scalping but raise false signals; slower like "50/200" smooths for swings, potentially missing early turns. Use Manual for fine control.
Manual Fast — Sets fast EMA length when Manual mode is active; shorter values make regime switches quicker. Default: 21. Trade-offs/Tips: Lower than 10 risks over-reactivity; pair with slow at least double for clear separation.
Manual Slow — Sets slow EMA length when Manual mode is active; longer values anchor the midline more firmly. Default: 55. Trade-offs/Tips: Above 100 adds lag in trends; balance with fast to avoid perpetual neutrality.
ATR Lengths (comma-separated) — Defines candidate periods for ATR smoothing; more options allow finer auto-selection. Default: "7,10,14,21,28,35". Trade-offs/Tips: Fewer candidates speed computation but may miss optimal fits; keep under 10 for efficiency.
Containment Window — Number of recent bars the hull must fully enclose highs/lows of; larger windows favor stability. Default: 50. Trade-offs/Tips: Shorter (under 20) adapts faster to breaks but increases breach risk; longer smooths but delays response.
Min Multiplier Floor — Lowest allowed multiplier for hull width; prevents overly tight bands in low volatility. Default: 0.5. Trade-offs/Tips: Raise to 0.75 for conservative enclosures; too low allows pinches that flip easily.
Max Multiplier Cap — Highest allowed multiplier; caps expansion in spikes to avoid wide, lagging bands. Default: 1.0. Trade-offs/Tips: Lower to 0.75 tightens overall; higher permits more room but risks detachment from price.
Padding (+) — Adds buffer to the auto-multiplier for safer containment without exact touches. Default: 0.05. Trade-offs/Tips: Increase to 0.10 in gappy markets; minimal values hug closer but may still breach on outliers.
Fill Between (Mid ↔ Supertrend) — Toggles shaded area between midline and active hull for trend visualization. Default: true. Trade-offs/Tips: Disable for cleaner charts; pairs well with transparency tweaks.
Base Fill Transparency (0..100) — Sets default opacity of fills; higher values make them subtler. Default: 80. Trade-offs/Tips: Under 50 overwhelms price action; adjust with darken boost for emphasis.
Darken on Trend Change — Enables temporary opacity increase after regime shifts to spotlight transitions. Default: true. Trade-offs/Tips: Off for steady visuals; on aids spotting reversals in real-time.
Darken Fade Bars — Duration in bars for the darken effect to ramp back to base; longer prolongs highlight. Default: 8. Trade-offs/Tips: Shorter (4-6) for fast-paced charts; longer holds attention on changes.
Darken Boost at Change (Δ transp) — Intensity of opacity reduction at crossover; higher values make shifts more prominent. Default: 50. Trade-offs/Tips: Cap at 70 to avoid blackout; tune down if fades obscure details.
Show Supertrend Line — Displays the active hull boundary as a line. Default: true. Trade-offs/Tips: Hide for fill-only views; linewidth fixed at 3 for visibility.
Show EMA Cross Markers — Places circles and labels at crossover points for entry cues. Default: true. Trade-offs/Tips: Disable in clutter; labels show "Buy"/"Sell" at absolute positions.
Alert: EMA Cross Up (Long) — Triggers notification on bullish crossover. Default: true. Trade-offs/Tips: Pair with filters; once-per-bar frequency.
Alert: EMA Cross Down (Short) — Triggers notification on bearish crossover. Default: true. Trade-offs/Tips: Use for exits; ensure broker integration.
Show Debug — Reveals internal diagnostics like selected ATR details (if implemented). Default: false. Trade-offs/Tips: Enable for troubleshooting selections; minimal overhead.
Reading & Interpretation
Bullish regime shows a green line below price as support, with upward fill from midline; bearish uses red line above as resistance, downward fill. Crossovers flip the active boundary, marked by tiny green/red circles and "Buy"/"Sell" labels at the hull level. Fills start at base transparency but darken sharply at changes, fading over the specified bars to signal fresh momentum. If the hull rarely breaches during trends, containment is effective; frequent touches without flips indicate tight adaptation. Debug mode (when enabled) overlays text or plots for selected length and multiplier, helping verify auto-choices.
Practical Workflows & Combinations
- Trend following: Enter long on green "Buy" label above prior low structure; confirm with higher high. Trail stops along the green hull line, tightening as fills stabilize post-fade.
- Exits/Stops: Conservative exit on opposite crossover or hull breach; aggressive hold until fade completes if volume supports. Use darken boost as a volatility cue—high delta suggests waiting for confirmation.
- Multi-asset/Multi-TF: Defaults suit forex/stocks on 15m-4h; for crypto, widen containment to 75 for gaps. Layer on volume oscillator for cross filters; avoid on low-liquidity assets where ATR candidates skew.
Behavior, Constraints & Performance
Closed-bar logic ensures signals confirm at bar end, with live bars updating hull adaptively but no repaints since no future data or security calls are used. Arrays persist ATR states across bars, initialized once with candidates parsed from string. Small fixed loops (over 6 lengths max, inner up to 50) run per bar, capped by max_bars_back=500 for history needs. Resources stay low with 500 labels/lines limits, but dense charts may hit on markers. Known limits include initial lag until containment history builds (50+ bars), potential wide bands on gaps, and suboptimal selections if candidates omit ideal lengths.
Sensible Defaults & Quick Tuning
Start with "21/55" pair, 50-window, 0.5-1.0 multipliers, and 80% transparency for balanced responsiveness on daily charts. For too many flips, raise min floor to 0.75 or add lengths like "42"; for sluggishness, shorten window to 30 or pick faster pair. In high-vol environments, boost padding to 0.10; for smoother visuals, extend fade bars to 12.
What this indicator is—and isn’t
This is a visualization and signal layer for trend regime and adaptive boundaries, aiding entry/exit timing in directional markets. It is not a standalone system—pair with price structure, risk sizing, and broader context. Not predictive of turns, just reactive to containment and crosses.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Happy trading
Chervolino
USDJPY Fair Value Gap + Session Strategy🎯 Overview
This strategy combines Fair Value Gaps (FVGs) with session-based order flow analysis, specifically optimized for USDJPY. It identifies price inefficiencies left behind by institutional order flow during high-volatility trading sessions, offering a modern alternative to traditional lagging indicators.
🔬 What Are Fair Value Gaps?
Fair Value Gaps represent areas where aggressive institutional buying or selling created "gaps" in the market structure:
Bullish FVG: Price moves up so aggressively that it leaves unfilled buy orders behind
Bearish FVG: Price moves down so quickly that it leaves unfilled sell orders behind
Research shows approximately 80% of FVGs get "filled" (price returns to the gap) within 20-60 bars, making them highly predictable trading zones.
(see the generated image above)
(see the generated image above)
FVG Detection Logic:
text
// Bullish FVG: Gap between high and current low
bullishFVG = low > high and high > high
// Bearish FVG: Gap between low and current high
bearishFVG = high < low and low < low
🌏 Session-Based Trading
Why Sessions Matter for USDJPY
(see the generated image above)
Tokyo Session (00:00-09:00 UTC)
Highest volatility during first hour (00:00-01:00 UTC)
Average movement: 51-60 pips
Best for breakout strategies
London/NY Overlap (13:00-16:00 UTC)
Maximum liquidity and institutional participation
Tightest spreads and most reliable FVG formations
Optimal for continuation trades
Monday Premium Effect
USDJPY moves 120+ pips on Mondays due to weekend positioning
Enhanced FVG formation during session opens
📊 Strategy Components
(see the generated image above)
1. Fair Value Gap Detection
Identifies bullish and bearish FVGs automatically
Age limit: FVGs expire after 20 bars to avoid stale setups
Size filter: Minimum gap size to filter out noise
2. Session Filtering
Tokyo Open focus: Trades during first hour of Asian session
London/NY Overlap: Captures high-liquidity institutional flows
Weekend gap strategy: Enhanced signals on Monday opens
3. Volume Confirmation
Requires 1.5x average volume spike
Confirms institutional participation
Reduces false signals
4. Trend Alignment
50 EMA filter ensures trades align with higher timeframe trend
Long trades above EMA, short trades below
Prevents costly counter-trend trades
5. Risk Management
2:1 Risk/Reward minimum ensures profitability with 40%+ win rate
Percentage-based stops adapt to USDJPY volatility (0.3% default)
Configurable position sizing
🎯 Entry Conditions
(see the generated image above)
Long Entry (BUY)
✅ Bullish FVG detected in previous bars
✅ Price returns to FVG zone during active trading session
✅ Volume spike above 1.5x average
✅ Price above 50 EMA (trend confirmation)
✅ Bullish candle closes within FVG zone
✅ Trading during Tokyo open OR London/NY overlap
Short Entry (SELL)
✅ Bearish FVG detected in previous bars
✅ Price returns to FVG zone during active trading session
✅ Volume spike above 1.5x average
✅ Price below 50 EMA (trend confirmation)
✅ Bearish candle closes within FVG zone
✅ Trading during Tokyo open OR London/NY overlap
📈 Expected Performance
Backtesting Results (Based on Similar Strategies):
Win Rate: 44-59% (profitable due to high R:R ratio)
Average Winner: 60-90 pips during London/NY sessions
Average Loser: 30-40 pips (tight stops at FVG boundaries)
Risk/Reward: 2:1 minimum, often 3:1 during strong trends
Best Performance: Monday Tokyo opens and Wednesday London/NY overlaps
Why This Works for USDJPY:
90% correlation with US-Japan bond yield spreads
High volatility provides sufficient pip movement
Heavy institutional/central bank participation creates clear FVGs
Consistent volatility patterns across trading sessions
⚙️ Configurable Parameters
Session Settings:
Trade Tokyo Session (Enable/Disable)
Trade London/NY Overlap (Enable/Disable)
FVG Settings:
FVG Minimum Size (Filter small gaps)
Maximum FVG Age (20 bars default)
Show FVG Markers (Visual display)
Volume Settings:
Use Volume Filter (Enable/Disable)
Volume Multiplier (1.5x default)
Volume Average Period (20 bars)
Trend Settings:
Use Trend Filter (Enable/Disable)
Trend EMA Period (50 default)
Risk Management:
Risk/Reward Ratio (2.0 default)
Stop Loss Percentage (0.3% default)
🎨 Visual Indicators
🟡 Yellow Line: 50 EMA trend filter
🟢 Green Triangles: Long entry signals
🔴 Red Triangles: Short entry signals
🟢 Green Dots: Bullish FVG zones
🔴 Red Dots: Bearish FVG zones
🟦 Blue Background: Tokyo open session
🟧 Orange Background: London/NY overlap
📊 Recommended Settings
Optimal Timeframes:
Primary: 5-minute charts (scalping)
Secondary: 15-minute charts (swing trading)
Parameter Optimization:
Conservative: Stop Loss 0.2%, R:R 2:1, Volume 2.0x
Balanced: Stop Loss 0.3%, R:R 2:1, Volume 1.5x (default)
Aggressive: Stop Loss 0.4%, R:R 1.5:1, Volume 1.2x
Risk Management:
Maximum 1-2% of account per trade
Daily loss limit: Stop after 3-5 consecutive losses
Use fixed percentage position sizing
⚠️ Important Considerations
Avoid Trading During:
Major news events (BOJ interventions, NFP, FOMC)
Holiday periods with reduced liquidity
Low volatility Asian afternoon sessions
When US-Japan yield differential narrows sharply
Best Practices:
Limit to 2-3 trades per session maximum
Always respect the 50 EMA trend filter
Never risk more than planned per trade
Paper trade for 2-4 weeks before live implementation
Track performance by session and day of week
🚀 How to Use
Add the script to your USDJPY chart
Set timeframe to 5-minute or 15-minute
Adjust parameters based on your risk tolerance
Enable strategy alerts for automated notifications
Wait for visual signals (triangles) to appear
Enter trades according to your risk management rules
📚 Strategy Foundation
This strategy is based on:
Smart Money Concepts (SMC): Institutional order flow tracking
Market Microstructure: Understanding how FVGs form in electronic trading
Quantified Risk Management: Statistical edge through proper R:R ratios
Session Liquidity Patterns: Exploiting predictable volatility cycles
T3 ATR [DCAUT]█ T3 ATR
📊 ORIGINALITY & INNOVATION
The T3 ATR indicator represents an important enhancement to the traditional Average True Range (ATR) indicator by incorporating the T3 (Tilson Triple Exponential Moving Average) smoothing algorithm. While standard ATR uses fixed RMA (Running Moving Average) smoothing, T3 ATR introduces a configurable volume factor parameter that allows traders to adjust the smoothing characteristics from highly responsive to heavily smoothed output.
This innovation addresses a fundamental limitation of traditional ATR: the inability to adapt smoothing behavior without changing the calculation period. With T3 ATR, traders can maintain a consistent ATR period while adjusting the responsiveness through the volume factor, making the indicator adaptable to different trading styles, market conditions, and timeframes through a single unified implementation.
The T3 algorithm's triple exponential smoothing with volume factor control provides improved signal quality by reducing noise while maintaining better responsiveness compared to traditional smoothing methods. This makes T3 ATR particularly valuable for traders who need to adapt their volatility measurement approach to varying market conditions without switching between multiple indicator configurations.
📐 MATHEMATICAL FOUNDATION
The T3 ATR calculation process involves two distinct stages:
Stage 1: True Range Calculation
The True Range (TR) is calculated using the standard formula:
TR = max(high - low, |high - close |, |low - close |)
This captures the greatest of the current bar's range, the gap from the previous close to the current high, or the gap from the previous close to the current low, providing a comprehensive measure of price movement that accounts for gaps and limit moves.
Stage 2: T3 Smoothing Application
The True Range values are then smoothed using the T3 algorithm, which applies six exponential moving averages in succession:
First Layer: e1 = EMA(TR, period), e2 = EMA(e1, period)
Second Layer: e3 = EMA(e2, period), e4 = EMA(e3, period)
Third Layer: e5 = EMA(e4, period), e6 = EMA(e5, period)
Final Calculation: T3 = c1×e6 + c2×e5 + c3×e4 + c4×e3
The coefficients (c1, c2, c3, c4) are derived from the volume factor (VF) parameter:
a = VF / 2
c1 = -a³
c2 = 3a² + 3a³
c3 = -6a² - 3a - 3a³
c4 = 1 + 3a + a³ + 3a²
The volume factor parameter (0.0 to 1.0) controls the weighting of these coefficients, directly affecting the balance between responsiveness and smoothness:
Lower VF values (approaching 0.0): Coefficients favor recent data, resulting in faster response to volatility changes with minimal lag but potentially more noise
Higher VF values (approaching 1.0): Coefficients distribute weight more evenly across the smoothing layers, producing smoother output with reduced noise but slightly increased lag
📊 COMPREHENSIVE SIGNAL ANALYSIS
Volatility Level Interpretation:
High Absolute Values: Indicate strong price movements and elevated market activity, suggesting larger position risks and wider stop-loss requirements, often associated with trending markets or significant news events
Low Absolute Values: Indicate subdued price movements and quiet market conditions, suggesting smaller position risks and tighter stop-loss opportunities, often associated with consolidation phases or low-volume periods
Rapid Increases: Sharp spikes in T3 ATR often signal the beginning of significant price moves or market regime changes, providing early warning of increased trading risk
Sustained High Levels: Extended periods of elevated T3 ATR indicate sustained trending conditions with persistent volatility, suitable for trend-following strategies
Sustained Low Levels: Extended periods of low T3 ATR indicate range-bound conditions with suppressed volatility, suitable for mean-reversion strategies
Volume Factor Impact on Signals:
Low VF Settings (0.0-0.3): Produce responsive signals that quickly capture volatility changes, suitable for short-term trading but may generate more frequent color changes during minor fluctuations
Medium VF Settings (0.4-0.7): Provide balanced signal quality with moderate responsiveness, filtering out minor noise while capturing significant volatility changes, suitable for swing trading
High VF Settings (0.8-1.0): Generate smooth, stable signals that filter out most noise and focus on major volatility trends, suitable for position trading and long-term analysis
🎯 STRATEGIC APPLICATIONS
Position Sizing Strategy:
Determine your risk per trade (e.g., 1% of account capital - adjust based on your risk tolerance and experience)
Decide your stop-loss distance multiplier (e.g., 2.0x T3 ATR - this varies by market and strategy, test different values)
Calculate stop-loss distance: Stop Distance = Multiplier × Current T3 ATR
Calculate position size: Position Size = (Account × Risk %) / Stop Distance
Example: $10,000 account, 1% risk, T3 ATR = 50 points, 2x multiplier → Position Size = ($10,000 × 0.01) / (2 × 50) = $100 / 100 points = 1 unit per point
Important: The ATR multiplier (1.5x - 3.0x) should be determined through backtesting for your specific instrument and strategy - using inappropriate multipliers may result in stops that are too tight (frequent stop-outs) or too wide (excessive losses)
Adjust the volume factor to match your trading style: lower VF for responsive stop distances in short-term trading, higher VF for stable stop distances in position trading
Dynamic Stop-Loss Placement:
Determine your risk tolerance multiplier (typically 1.5x to 3.0x T3 ATR)
For long positions: Set stop-loss at entry price minus (multiplier × current T3 ATR value)
For short positions: Set stop-loss at entry price plus (multiplier × current T3 ATR value)
Trail stop-losses by recalculating based on current T3 ATR as the trade progresses
Adjust the volume factor based on desired stop-loss stability: higher VF for less frequent adjustments, lower VF for more adaptive stops
Market Regime Identification:
Calculate a reference volatility level using a longer-period moving average of T3 ATR (e.g., 50-period SMA)
High Volatility Regime: Current T3 ATR significantly above reference (e.g., 120%+) - favor trend-following strategies, breakout trades, and wider targets
Normal Volatility Regime: Current T3 ATR near reference (e.g., 80-120%) - employ standard trading strategies appropriate for prevailing market structure
Low Volatility Regime: Current T3 ATR significantly below reference (e.g., <80%) - favor mean-reversion strategies, range trading, and prepare for potential volatility expansion
Monitor T3 ATR trend direction and compare current values to recent history to identify regime transitions early
Risk Management Implementation:
Establish your maximum portfolio heat (total risk across all positions, typically 2-6% of capital)
For each position: Calculate position size using the formula Position Size = (Account × Individual Risk %) / (ATR Multiplier × Current T3 ATR)
When T3 ATR increases: Position sizes automatically decrease (same risk %, larger stop distance = smaller position)
When T3 ATR decreases: Position sizes automatically increase (same risk %, smaller stop distance = larger position)
This approach maintains constant dollar risk per trade regardless of market volatility changes
Use consistent volume factor settings across all positions to ensure uniform risk measurement
📋 DETAILED PARAMETER CONFIGURATION
ATR Length Parameter:
Default Setting: 14 periods
This is the standard ATR calculation period established by Welles Wilder, providing balanced volatility measurement that captures both short-term fluctuations and medium-term trends across most markets and timeframes
Selection Principles:
Shorter periods increase sensitivity to recent volatility changes and respond faster to market shifts, but may produce less stable readings
Longer periods emphasize sustained volatility trends and filter out short-term noise, but respond more slowly to genuine regime changes
The optimal period depends on your holding time, trading frequency, and the typical volatility cycle of your instrument
Consider the timeframe you trade: Intraday traders typically use shorter periods, swing traders use intermediate periods, position traders use longer periods
Practical Approach:
Start with the default 14 periods and observe how well it captures volatility patterns relevant to your trading decisions
If ATR seems too reactive to minor price movements: Increase the period until volatility readings better reflect meaningful market changes
If ATR lags behind obvious volatility shifts that affect your trades: Decrease the period for faster response
Match the period roughly to your typical holding time - if you hold positions for N bars, consider ATR periods in a similar range
Test different periods using historical data for your specific instrument and strategy before committing to live trading
T3 Volume Factor Parameter:
Default Setting: 0.7
This setting provides a reasonable balance between responsiveness and smoothness for most market conditions and trading styles
Understanding the Volume Factor:
Lower values (closer to 0.0) reduce smoothing, allowing T3 ATR to respond more quickly to volatility changes but with less noise filtering
Higher values (closer to 1.0) increase smoothing, producing more stable readings that focus on sustained volatility trends but respond more slowly
The trade-off is between immediacy and stability - there is no universally optimal setting
Selection Principles:
Match to your decision speed: If you need to react quickly to volatility changes for entries/exits, use lower VF; if you're making longer-term risk assessments, use higher VF
Match to market character: Noisier, choppier markets may benefit from higher VF for clearer signals; cleaner trending markets may work well with lower VF for faster response
Match to your preference: Some traders prefer responsive indicators even with occasional false signals, others prefer stable indicators even with some delay
Practical Adjustment Guidelines:
Start with default 0.7 and observe how T3 ATR behavior aligns with your trading needs over multiple sessions
If readings seem too unstable or noisy for your decisions: Try increasing VF toward 0.9-1.0 for heavier smoothing
If the indicator lags too much behind volatility changes you care about: Try decreasing VF toward 0.3-0.5 for faster response
Make meaningful adjustments (0.2-0.3 changes) rather than small increments - subtle differences are often imperceptible in practice
Test adjustments in simulation or paper trading before applying to live positions
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Responsiveness Characteristics:
The T3 smoothing algorithm provides improved responsiveness compared to traditional RMA smoothing used in standard ATR. The triple exponential design with volume factor control allows the indicator to respond more quickly to genuine volatility changes while maintaining the ability to filter noise through appropriate VF settings. This results in earlier detection of volatility regime changes compared to standard ATR, particularly valuable for risk management and position sizing adjustments.
Signal Stability:
Unlike simple smoothing methods that may produce erratic signals during transitional periods, T3 ATR's multi-layer exponential smoothing provides more stable signal progression. The volume factor parameter allows traders to tune signal stability to their preference, with higher VF settings producing remarkably smooth volatility profiles that help avoid overreaction to temporary market fluctuations.
Comparison with Standard ATR:
Adaptability: T3 ATR allows adjustment of smoothing characteristics through the volume factor without changing the ATR period, whereas standard ATR requires changing the period length to alter responsiveness, potentially affecting the fundamental volatility measurement
Lag Reduction: At lower volume factor settings, T3 ATR responds more quickly to volatility changes than standard ATR with equivalent periods, providing earlier signals for risk management adjustments
Noise Filtering: At higher volume factor settings, T3 ATR provides superior noise filtering compared to standard ATR, producing cleaner signals for long-term analysis without sacrificing volatility measurement accuracy
Flexibility: A single T3 ATR configuration can serve multiple trading styles by adjusting only the volume factor, while standard ATR typically requires multiple instances with different periods for different trading applications
Suitable Use Cases:
T3 ATR is well-suited for the following scenarios:
Dynamic Risk Management: When position sizing and stop-loss placement need to adapt quickly to changing volatility conditions
Multi-Style Trading: When a single volatility indicator must serve different trading approaches (day trading, swing trading, position trading)
Volatile Markets: When standard ATR produces too many false volatility signals during choppy conditions
Systematic Trading: When algorithmic systems require a single, configurable volatility input that can be optimized for different instruments
Market Regime Analysis: When clear identification of volatility expansion and contraction phases is critical for strategy selection
Known Limitations:
Like all technical indicators, T3 ATR has limitations that users should understand:
Historical Nature: T3 ATR is calculated from historical price data and cannot predict future volatility with certainty
Smoothing Trade-offs: The volume factor setting involves a trade-off between responsiveness and smoothness - no single setting is optimal for all market conditions
Extreme Events: During unprecedented market events or gaps, T3 ATR may not immediately reflect the full scope of volatility until sufficient data is processed
Relative Measurement: T3 ATR values are most meaningful in relative context (compared to recent history) rather than as absolute thresholds
Market Context Required: T3 ATR measures volatility magnitude but does not indicate price direction or trend quality - it should be used in conjunction with directional analysis
Performance Expectations:
T3 ATR is designed to help traders measure and adapt to changing market volatility conditions. When properly configured and applied:
It can help reduce position risk during volatile periods through appropriate position sizing
It can help identify optimal times for more aggressive position sizing during stable periods
It can improve stop-loss placement by adapting to current market conditions
It can assist in strategy selection by identifying volatility regimes
However, volatility measurement alone does not guarantee profitable trading. T3 ATR should be integrated into a comprehensive trading approach that includes directional analysis, proper risk management, and sound trading psychology.
USAGE NOTES
This indicator is designed for technical analysis and educational purposes. T3 ATR provides adaptive volatility measurement but has limitations and should not be used as the sole basis for trading decisions. The indicator measures historical volatility patterns, and past volatility characteristics do not guarantee future volatility behavior. Market conditions can change rapidly, and extreme events may produce volatility readings that fall outside historical norms.
Traders should combine T3 ATR with directional analysis tools, support/resistance analysis, and other technical indicators to form a complete trading strategy. Proper backtesting and forward testing with appropriate risk management is essential before applying T3 ATR-based strategies to live trading. The volume factor parameter should be optimized for specific instruments and trading styles through careful testing rather than assuming default settings are optimal for all applications.
Keltner Channel Enhanced [DCAUT]█ Keltner Channel Enhanced
📊 ORIGINALITY & INNOVATION
The Keltner Channel Enhanced represents an important advancement over standard Keltner Channel implementations by introducing dual flexibility in moving average selection for both the middle band and ATR calculation. While traditional Keltner Channels typically use EMA for the middle band and RMA (Wilder's smoothing) for ATR, this enhanced version provides access to 25+ moving average algorithms for both components, enabling traders to fine-tune the indicator's behavior to match specific market characteristics and trading approaches.
Key Advancements:
Dual MA Algorithm Flexibility: Independent selection of moving average types for middle band (25+ options) and ATR smoothing (25+ options), allowing optimization of both trend identification and volatility measurement separately
Enhanced Trend Sensitivity: Ability to use faster algorithms (HMA, T3) for middle band while maintaining stable volatility measurement with traditional ATR smoothing, or vice versa for different trading strategies
Adaptive Volatility Measurement: Choice of ATR smoothing algorithm affects channel responsiveness to volatility changes, from highly reactive (SMA, EMA) to smoothly adaptive (RMA, TEMA)
Comprehensive Alert System: Five distinct alert conditions covering breakouts, trend changes, and volatility expansion, enabling automated monitoring without constant chart observation
Multi-Timeframe Compatibility: Works effectively across all timeframes from intraday scalping to long-term position trading, with independent optimization of trend and volatility components
This implementation addresses key limitations of standard Keltner Channels: fixed EMA/RMA combination may not suit all market conditions or trading styles. By decoupling the trend component from volatility measurement and allowing independent algorithm selection, traders can create highly customized configurations for specific instruments and market phases.
📐 MATHEMATICAL FOUNDATION
Keltner Channel Enhanced uses a three-component calculation system that combines a flexible moving average middle band with ATR-based (Average True Range) upper and lower channels, creating volatility-adjusted trend-following bands.
Core Calculation Process:
1. Middle Band (Basis) Calculation:
The basis line is calculated using the selected moving average algorithm applied to the price source over the specified period:
basis = ma(source, length, maType)
Supported algorithms include EMA (standard choice, trend-biased), SMA (balanced and symmetric), HMA (reduced lag), WMA, VWMA, TEMA, T3, KAMA, and 17+ others.
2. Average True Range (ATR) Calculation:
ATR measures market volatility by calculating the average of true ranges over the specified period:
trueRange = max(high - low, abs(high - close ), abs(low - close ))
atrValue = ma(trueRange, atrLength, atrMaType)
ATR smoothing algorithm significantly affects channel behavior, with options including RMA (standard, very smooth), SMA (moderate smoothness), EMA (fast adaptation), TEMA (smooth yet responsive), and others.
3. Channel Calculation:
Upper and lower channels are positioned at specified multiples of ATR from the basis:
upperChannel = basis + (multiplier × atrValue)
lowerChannel = basis - (multiplier × atrValue)
Standard multiplier is 2.0, providing channels that dynamically adjust width based on market volatility.
Keltner Channel vs. Bollinger Bands - Key Differences:
While both indicators create volatility-based channels, they use fundamentally different volatility measures:
Keltner Channel (ATR-based):
Uses Average True Range to measure actual price movement volatility
Incorporates gaps and limit moves through true range calculation
More stable in trending markets, less prone to extreme compression
Better reflects intraday volatility and trading range
Typically fewer band touches, making touches more significant
More suitable for trend-following strategies
Bollinger Bands (Standard Deviation-based):
Uses statistical standard deviation to measure price dispersion
Based on closing prices only, doesn't account for intraday range
Can compress significantly during consolidation (squeeze patterns)
More touches in ranging markets
Better suited for mean-reversion strategies
Provides statistical probability framework (95% within 2 standard deviations)
Algorithm Combination Effects:
The interaction between middle band MA type and ATR MA type creates different indicator characteristics:
Trend-Focused Configuration (Fast MA + Slow ATR): Middle band uses HMA/EMA/T3, ATR uses RMA/TEMA, quick trend changes with stable channel width, suitable for trend-following
Volatility-Focused Configuration (Slow MA + Fast ATR): Middle band uses SMA/WMA, ATR uses EMA/SMA, stable trend with dynamic channel width, suitable for volatility trading
Balanced Configuration (Standard EMA/RMA): Classic Keltner Channel behavior, time-tested combination, suitable for general-purpose trend following
Adaptive Configuration (KAMA + KAMA): Self-adjusting indicator responding to efficiency ratio, suitable for markets with varying trend strength and volatility regimes
📊 COMPREHENSIVE SIGNAL ANALYSIS
Keltner Channel Enhanced provides multiple signal categories optimized for trend-following and breakout strategies.
Channel Position Signals:
Upper Channel Interaction:
Price Touching Upper Channel: Strong bullish momentum, price moving more than typical volatility range suggests, potential continuation signal in established uptrends
Price Breaking Above Upper Channel: Exceptional strength, price exceeding normal volatility expectations, consider adding to long positions or tightening trailing stops
Price Riding Upper Channel: Sustained strong uptrend, characteristic of powerful bull moves, stay with trend and avoid premature profit-taking
Price Rejection at Upper Channel: Momentum exhaustion signal, consider profit-taking on longs or waiting for pullback to middle band for reentry
Lower Channel Interaction:
Price Touching Lower Channel: Strong bearish momentum, price moving more than typical volatility range suggests, potential continuation signal in established downtrends
Price Breaking Below Lower Channel: Exceptional weakness, price exceeding normal volatility expectations, consider adding to short positions or protecting against further downside
Price Riding Lower Channel: Sustained strong downtrend, characteristic of powerful bear moves, stay with trend and avoid premature covering
Price Rejection at Lower Channel: Momentum exhaustion signal, consider covering shorts or waiting for bounce to middle band for reentry
Middle Band (Basis) Signals:
Trend Direction Confirmation:
Price Above Basis: Bullish trend bias, middle band acts as dynamic support in uptrends, consider long positions or holding existing longs
Price Below Basis: Bearish trend bias, middle band acts as dynamic resistance in downtrends, consider short positions or avoiding longs
Price Crossing Above Basis: Potential trend change from bearish to bullish, early signal to establish long positions
Price Crossing Below Basis: Potential trend change from bullish to bearish, early signal to establish short positions or exit longs
Pullback Trading Strategy:
Uptrend Pullback: Price pulls back from upper channel to middle band, finds support, and resumes upward, ideal long entry point
Downtrend Bounce: Price bounces from lower channel to middle band, meets resistance, and resumes downward, ideal short entry point
Basis Test: Strong trends often show price respecting the middle band as support/resistance on pullbacks
Failed Test: Price breaking through middle band against trend direction signals potential reversal
Volatility-Based Signals:
Narrow Channels (Low Volatility):
Consolidation Phase: Channels contract during periods of reduced volatility and directionless price action
Breakout Preparation: Narrow channels often precede significant directional moves as volatility cycles
Trading Approach: Reduce position sizes, wait for breakout confirmation, avoid range-bound strategies within channels
Breakout Direction: Monitor for price breaking decisively outside channel range with expanding width
Wide Channels (High Volatility):
Trending Phase: Channels expand during strong directional moves and increased volatility
Momentum Confirmation: Wide channels confirm genuine trend with substantial volatility backing
Trading Approach: Trend-following strategies excel, wider stops necessary, mean-reversion strategies risky
Exhaustion Signs: Extreme channel width (historical highs) may signal approaching consolidation or reversal
Advanced Pattern Recognition:
Channel Walking Pattern:
Upper Channel Walk: Price consistently touches or exceeds upper channel while staying above basis, very strong uptrend signal, hold longs aggressively
Lower Channel Walk: Price consistently touches or exceeds lower channel while staying below basis, very strong downtrend signal, hold shorts aggressively
Basis Support/Resistance: During channel walks, price typically uses middle band as support/resistance on minor pullbacks
Pattern Break: Price crossing basis during channel walk signals potential trend exhaustion
Squeeze and Release Pattern:
Squeeze Phase: Channels narrow significantly, price consolidates near middle band, volatility contracts
Direction Clues: Watch for price positioning relative to basis during squeeze (above = bullish bias, below = bearish bias)
Release Trigger: Price breaking outside narrow channel range with expanding width confirms breakout
Follow-Through: Measure squeeze height and project from breakout point for initial profit targets
Channel Expansion Pattern:
Breakout Confirmation: Rapid channel widening confirms volatility increase and genuine trend establishment
Entry Timing: Enter positions early in expansion phase before trend becomes overextended
Risk Management: Use channel width to size stops appropriately, wider channels require wider stops
Basis Bounce Pattern:
Clean Bounce: Price touches middle band and immediately reverses, confirms trend strength and entry opportunity
Multiple Bounces: Repeated basis bounces indicate strong, sustainable trend
Bounce Failure: Price penetrating basis signals weakening trend and potential reversal
Divergence Analysis:
Price/Channel Divergence: Price makes new high/low while staying within channel (not reaching outer band), suggests momentum weakening
Width/Price Divergence: Price breaks to new extremes but channel width contracts, suggests move lacks conviction
Reversal Signal: Divergences often precede trend reversals or significant consolidation periods
Multi-Timeframe Analysis:
Keltner Channels work particularly well in multi-timeframe trend-following approaches:
Three-Timeframe Alignment:
Higher Timeframe (Weekly/Daily): Identify major trend direction, note price position relative to basis and channels
Intermediate Timeframe (Daily/4H): Identify pullback opportunities within higher timeframe trend
Lower Timeframe (4H/1H): Time precise entries when price touches middle band or lower channel (in uptrends) with rejection
Optimal Entry Conditions:
Best Long Entries: Higher timeframe in uptrend (price above basis), intermediate timeframe pulls back to basis, lower timeframe shows rejection at middle band or lower channel
Best Short Entries: Higher timeframe in downtrend (price below basis), intermediate timeframe bounces to basis, lower timeframe shows rejection at middle band or upper channel
Risk Management: Use higher timeframe channel width to set position sizing, stops below/above higher timeframe channels
🎯 STRATEGIC APPLICATIONS
Keltner Channel Enhanced excels in trend-following and breakout strategies across different market conditions.
Trend Following Strategy:
Setup Requirements:
Identify established trend with price consistently on one side of basis line
Wait for pullback to middle band (basis) or brief penetration through it
Confirm trend resumption with price rejection at basis and move back toward outer channel
Enter in trend direction with stop beyond basis line
Entry Rules:
Uptrend Entry:
Price pulls back from upper channel to middle band, shows support at basis (bullish candlestick, momentum divergence)
Enter long on rejection/bounce from basis with stop 1-2 ATR below basis
Aggressive: Enter on first touch; Conservative: Wait for confirmation candle
Downtrend Entry:
Price bounces from lower channel to middle band, shows resistance at basis (bearish candlestick, momentum divergence)
Enter short on rejection/reversal from basis with stop 1-2 ATR above basis
Aggressive: Enter on first touch; Conservative: Wait for confirmation candle
Trend Management:
Trailing Stop: Use basis line as dynamic trailing stop, exit if price closes beyond basis against position
Profit Taking: Take partial profits at opposite channel, move stops to basis
Position Additions: Add to winners on subsequent basis bounces if trend intact
Breakout Strategy:
Setup Requirements:
Identify consolidation period with contracting channel width
Monitor price action near middle band with reduced volatility
Wait for decisive breakout beyond channel range with expanding width
Enter in breakout direction after confirmation
Breakout Confirmation:
Price breaks clearly outside channel (upper for longs, lower for shorts), channel width begins expanding from contracted state
Volume increases significantly on breakout (if using volume analysis)
Price sustains outside channel for multiple bars without immediate reversal
Entry Approaches:
Aggressive: Enter on initial break with stop at opposite channel or basis, use smaller position size
Conservative: Wait for pullback to broken channel level, enter on rejection and resumption, tighter stop
Volatility-Based Position Sizing:
Adjust position sizing based on channel width (ATR-based volatility):
Wide Channels (High ATR): Reduce position size as stops must be wider, calculate position size using ATR-based risk calculation: Risk / (Stop Distance in ATR × ATR Value)
Narrow Channels (Low ATR): Increase position size as stops can be tighter, be cautious of impending volatility expansion
ATR-Based Risk Management: Use ATR-based risk calculations, position size = 0.01 × Capital / (2 × ATR), use multiples of ATR (1-2 ATR) for adaptive stops
Algorithm Selection Guidelines:
Different market conditions benefit from different algorithm combinations:
Strong Trending Markets: Middle band use EMA or HMA, ATR use RMA, capture trends quickly while maintaining stable channel width
Choppy/Ranging Markets: Middle band use SMA or WMA, ATR use SMA or WMA, avoid false trend signals while identifying genuine reversals
Volatile Markets: Middle band and ATR both use KAMA or FRAMA, self-adjusting to changing market conditions reduces manual optimization
Breakout Trading: Middle band use SMA, ATR use EMA or SMA, stable trend with dynamic channels highlights volatility expansion early
Scalping/Day Trading: Middle band use HMA or T3, ATR use EMA or TEMA, both components respond quickly
Position Trading: Middle band use EMA/TEMA/T3, ATR use RMA or TEMA, filter out noise for long-term trend-following
📋 DETAILED PARAMETER CONFIGURATION
Understanding and optimizing parameters is essential for adapting Keltner Channel Enhanced to specific trading approaches.
Source Parameter:
Close (Most Common): Uses closing price, reflects daily settlement, best for end-of-day analysis and position trading, standard choice
HL2 (Median Price): Smooths out closing bias, better represents full daily range in volatile markets, good for swing trading
HLC3 (Typical Price): Gives more weight to close while including full range, popular for intraday applications, slightly more responsive than HL2
OHLC4 (Average Price): Most comprehensive price representation, smoothest option, good for gap-prone markets or highly volatile instruments
Length Parameter:
Controls the lookback period for middle band (basis) calculation:
Short Periods (10-15): Very responsive to price changes, suitable for day trading and scalping, higher false signal rate
Standard Period (20 - Default): Represents approximately one month of trading, good balance between responsiveness and stability, suitable for swing and position trading
Medium Periods (30-50): Smoother trend identification, fewer false signals, better for position trading and longer holding periods
Long Periods (50+): Very smooth, identifies major trends only, minimal false signals but significant lag, suitable for long-term investment
Optimization by Timeframe: 1-15 minute charts use 10-20 period, 30-60 minute charts use 20-30 period, 4-hour to daily charts use 20-40 period, weekly charts use 20-30 weeks.
ATR Length Parameter:
Controls the lookback period for Average True Range calculation, affecting channel width:
Short ATR Periods (5-10): Very responsive to recent volatility changes, standard is 10 (Keltner's original specification), may be too reactive in whipsaw conditions
Standard ATR Period (10 - Default): Chester Keltner's original specification, good balance between responsiveness and stability, most widely used
Medium ATR Periods (14-20): Smoother channel width, ATR 14 aligns with Wilder's original ATR specification, good for position trading
Long ATR Periods (20+): Very smooth channel width, suitable for long-term trend-following
Length vs. ATR Length Relationship: Equal values (20/20) provide balanced responsiveness, longer ATR (20/14) gives more stable channel width, shorter ATR (20/10) is standard configuration, much shorter ATR (20/5) creates very dynamic channels.
Multiplier Parameter:
Controls channel width by setting ATR multiples:
Lower Values (1.0-1.5): Tighter channels with frequent price touches, more trading signals, higher false signal rate, better for range-bound and mean-reversion strategies
Standard Value (2.0 - Default): Chester Keltner's recommended setting, good balance between signal frequency and reliability, suitable for both trending and ranging strategies
Higher Values (2.5-3.0): Wider channels with less frequent touches, fewer but potentially higher-quality signals, better for strong trending markets
Market-Specific Optimization: High volatility markets (crypto, small-caps) use 2.5-3.0 multiplier, medium volatility markets (major forex, large-caps) use 2.0 multiplier, low volatility markets (bonds, utilities) use 1.5-2.0 multiplier.
MA Type Parameter (Middle Band):
Critical selection that determines trend identification characteristics:
EMA (Exponential Moving Average - Default): Standard Keltner Channel choice, Chester Keltner's original specification, emphasizes recent prices, faster response to trend changes, suitable for all timeframes
SMA (Simple Moving Average): Equal weighting of all data points, no directional bias, slower than EMA, better for ranging markets and mean-reversion
HMA (Hull Moving Average): Minimal lag with smooth output, excellent for fast trend identification, best for day trading and scalping
TEMA (Triple Exponential Moving Average): Advanced smoothing with reduced lag, responsive to trends while filtering noise, suitable for volatile markets
T3 (Tillson T3): Very smooth with minimal lag, excellent for established trend identification, suitable for position trading
KAMA (Kaufman Adaptive Moving Average): Automatically adjusts speed based on market efficiency, slow in ranging markets, fast in trends, suitable for markets with varying conditions
ATR MA Type Parameter:
Determines how Average True Range is smoothed, affecting channel width stability:
RMA (Wilder's Smoothing - Default): J. Welles Wilder's original ATR smoothing method, very smooth, slow to adapt to volatility changes, provides stable channel width
SMA (Simple Moving Average): Equal weighting, moderate smoothness, faster response to volatility changes than RMA, more dynamic channel width
EMA (Exponential Moving Average): Emphasizes recent volatility, quick adaptation to new volatility regimes, very responsive channel width changes
TEMA (Triple Exponential Moving Average): Smooth yet responsive, good balance for varying volatility, suitable for most trading styles
Parameter Combination Strategies:
Conservative Trend-Following: Length 30/ATR Length 20/Multiplier 2.5, MA Type EMA or TEMA/ATR MA Type RMA, smooth trend with stable wide channels, suitable for position trading
Standard Balanced Approach: Length 20/ATR Length 10/Multiplier 2.0, MA Type EMA/ATR MA Type RMA, classic Keltner Channel configuration, suitable for general purpose swing trading
Aggressive Day Trading: Length 10-15/ATR Length 5-7/Multiplier 1.5-2.0, MA Type HMA or EMA/ATR MA Type EMA or SMA, fast trend with dynamic channels, suitable for scalping and day trading
Breakout Specialist: Length 20-30/ATR Length 5-10/Multiplier 2.0, MA Type SMA or WMA/ATR MA Type EMA or SMA, stable trend with responsive channel width
Adaptive All-Conditions: Length 20/ATR Length 10/Multiplier 2.0, MA Type KAMA or FRAMA/ATR MA Type KAMA or TEMA, self-adjusting to market conditions
Offset Parameter:
Controls horizontal positioning of channels on chart. Positive values shift channels to the right (future) for visual projection, negative values shift left (past) for historical analysis, zero (default) aligns with current price bars for real-time signal analysis. Offset affects only visual display, not alert conditions or actual calculations.
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Keltner Channel Enhanced provides improvements over standard implementations while maintaining proven effectiveness.
Response Characteristics:
Standard EMA/RMA Configuration: Moderate trend lag (approximately 0.4 × length periods), smooth and stable channel width from RMA smoothing, good balance for most market conditions
Fast HMA/EMA Configuration: Approximately 60% reduction in trend lag compared to EMA, responsive channel width from EMA ATR smoothing, suitable for quick trend changes and breakouts
Adaptive KAMA/KAMA Configuration: Variable lag based on market efficiency, automatic adjustment to trending vs. ranging conditions, self-optimizing behavior reduces manual intervention
Comparison with Traditional Keltner Channels:
Enhanced Version Advantages:
Dual Algorithm Flexibility: Independent MA selection for trend and volatility vs. fixed EMA/RMA, separate tuning of trend responsiveness and channel stability
Market Adaptation: Choose configurations optimized for specific instruments and conditions, customize for scalping, swing, or position trading preferences
Comprehensive Alerts: Enhanced alert system including channel expansion detection
Traditional Version Advantages:
Simplicity: Fewer parameters, easier to understand and implement
Standardization: Fixed EMA/RMA combination ensures consistency across users
Research Base: Decades of backtesting and research on standard configuration
When to Use Enhanced Version: Trading multiple instruments with different characteristics, switching between trending and ranging markets, employing different strategies, algorithm-based trading systems requiring customization, seeking optimization for specific trading style and timeframe.
When to Use Standard Version: Beginning traders learning Keltner Channel concepts, following published research or trading systems, preferring simplicity and standardization, wanting to avoid optimization and curve-fitting risks.
Performance Across Market Conditions:
Strong Trending Markets: EMA or HMA basis with RMA or TEMA ATR smoothing provides quicker trend identification, pullbacks to basis offer excellent entry opportunities
Choppy/Ranging Markets: SMA or WMA basis with RMA ATR smoothing and lower multipliers, channel bounce strategies work well, avoid false breakouts
Volatile Markets: KAMA or FRAMA with EMA or TEMA, adaptive algorithms excel by automatic adjustment, wider multipliers (2.5-3.0) accommodate large price swings
Low Volatility/Consolidation: Channels narrow significantly indicating consolidation, algorithm choice less impactful, focus on detecting channel width contraction for breakout preparation
Keltner Channel vs. Bollinger Bands - Usage Comparison:
Favor Keltner Channels When: Trend-following is primary strategy, trading volatile instruments with gaps, want ATR-based volatility measurement, prefer fewer higher-quality channel touches, seeking stable channel width during trends.
Favor Bollinger Bands When: Mean-reversion is primary strategy, trading instruments with limited gaps, want statistical framework based on standard deviation, need squeeze patterns for breakout identification, prefer more frequent trading opportunities.
Use Both Together: Bollinger Band squeeze + Keltner Channel breakout is powerful combination, price outside Bollinger Bands but inside Keltner Channels indicates moderate signal, price outside both indicates very strong signal, Bollinger Bands for entries and Keltner Channels for trend confirmation.
Limitations and Considerations:
General Limitations:
Lagging Indicator: All moving averages lag price, even with reduced-lag algorithms
Trend-Dependent: Works best in trending markets, less effective in choppy conditions
No Direction Prediction: Indicates volatility and deviation, not future direction, requires confirmation
Enhanced Version Specific Considerations:
Optimization Risk: More parameters increase risk of curve-fitting historical data
Complexity: Additional choices may overwhelm beginning traders
Backtesting Challenges: Different algorithms produce different historical results
Mitigation Strategies:
Use Confirmation: Combine with momentum indicators (RSI, MACD), volume, or price action
Test Parameter Robustness: Ensure parameters work across range of values, not just optimized ones
Multi-Timeframe Analysis: Confirm signals across different timeframes
Proper Risk Management: Use appropriate position sizing and stops
Start Simple: Begin with standard EMA/RMA before exploring alternatives
Optimal Usage Recommendations:
For Maximum Effectiveness:
Start with standard EMA/RMA configuration to understand classic behavior
Experiment with alternatives on demo account or paper trading
Match algorithm combination to market condition and trading style
Use channel width analysis to identify market phases
Combine with complementary indicators for confirmation
Implement strict risk management using ATR-based position sizing
Focus on high-quality setups rather than trading every signal
Respect the trend: trade with basis direction for higher probability
Complementary Indicators:
RSI or Stochastic: Confirm momentum at channel extremes
MACD: Confirm trend direction and momentum shifts
Volume: Validate breakouts and trend strength
ADX: Measure trend strength, avoid Keltner signals in weak trends
Support/Resistance: Combine with traditional levels for high-probability setups
Bollinger Bands: Use together for enhanced breakout and volatility analysis
USAGE NOTES
This indicator is designed for technical analysis and educational purposes. Keltner Channel Enhanced has limitations and should not be used as the sole basis for trading decisions. While the flexible moving average selection for both trend and volatility components provides valuable adaptability across different market conditions, algorithm performance varies with market conditions, and past characteristics do not guarantee future results.
Key considerations:
Always use multiple forms of analysis and confirmation before entering trades
Backtest any parameter combination thoroughly before live trading
Be aware that optimization can lead to curve-fitting if not done carefully
Start with standard EMA/RMA settings and adjust only when specific conditions warrant
Understand that no moving average algorithm can eliminate lag entirely
Consider market regime (trending, ranging, volatile) when selecting parameters
Use ATR-based position sizing and risk management on every trade
Keltner Channels work best in trending markets, less effective in choppy conditions
Respect the trend direction indicated by price position relative to basis line
The enhanced flexibility of dual algorithm selection provides powerful tools for adaptation but requires responsible use, thorough understanding of how different algorithms behave under various market conditions, and disciplined risk management.
Orderflow Label with OffsetThis Pine Script automatically displays orderflow labels on the chart to visualize the current market structure and potential breakout or reversal zones.
It compares the current candle’s high and low with those of the previous cycle (e.g., 90 minutes) and places descriptive labels that highlight possible bullish or bearish behavior.
Functionality & Logic (Step-by-step explanation)
Inputs:
cycleLength: Defines the duration of one “cycle” in minutes (for example, 90 minutes).
labelXOffset: Moves the label a few bars to the right, so it doesn’t overlap the current candle.
labelStyleOffset: Controls whether labels appear pointing to the right or left side of the chart.
Previous Cycle:
The script uses request.security to retrieve the high and low from the previous cycle timeframe.
These act as reference points (similar to key levels or market structure highs/lows).
Current Candle:
The script reads the current bar’s high, low, and close values for comparison.
Orderflow Conditions:
bullSupport: The current high and close are both above the previous high → bullish breakout (strong continuation).
bullReject: The high breaks above the previous high but closes below → bullish rejection / possible top.
bearRes: The low and close are both below the previous low → bearish breakdown (continuation to downside).
bearReclaim: The low goes below the previous low but closes above → bearish reclaim / possible reversal.
Label Logic:
Before creating a new label, the previous one is deleted (label.delete(flowLbl)) to avoid clutter.
The label’s X position is shifted using xPos = bar_index + labelXOffset.
The style (left/right) is set based on the user’s preference.
Displayed Labels:
🟢 Bullish Breakout → price closes above the previous cycle high.
🟠 Bullish Rejection → fake breakout or possible top.
🔴 Bearish Breakdown → price closes below the previous cycle low.
🟡 Bearish Reclaim → failed breakdown or potential trend reversal.
⚪ Neutral (Wait) → no clear signal, advises patience and watching for setups (like CHoCH or FVGs).
Visual Behavior:
The labels appear slightly to the right of the bar for better visibility.
The color and text alignment dynamically adjust depending on whether the label is pointing left or right.
Universal Breakout Strategy [KedArc Quant]Description:
A flexible breakout framework where you can test different logics (Prev Day, Bollinger, Volume, ATR, EMA Trend, RSI Confirm, Candle Confirm, Time Filter) under one system.
Choose your breakout mode, and the strategy will handle entries, exits, and optional risk management (ATR stops, take-profits, daily loss guard, cooldowns).
An on-chart info table shows live mode values (like Prev High/Low, Bollinger levels, RSI, etc.) plus P&L stats for quick analysis.
Use it to compare which breakout style works best on your instrument and timeframe, whether intraday, swing, or positional trading
🔑 Why it’s useful
* Flexibility: Switch between breakout strategies without loading different indicators.
* Clarity: On-chart info table displays current mode, relevant indicator levels, and live strategy P&L stats.
* Testing efficiency: Quickly A/B test different breakout styles under the same backtest environment.
* Transparency: Every trade is rule-based and displayed with entry/exit markers.
🚀 How it helps traders
* Lets you experiment with breakout strategies quickly without loading multiple scripts.
* Helps identify which breakout method fits your instrument & timeframe.
* Gives clear on-chart visual + statistical feedback for confident decision-making.
⚙️ Input Configuration
* Breakout Mode → choose which strategy to test:
* *Prev Day* → breakouts of yesterday’s High/Low.
* *Bollinger* → Upper/Lower BB pierce.
* *Volume* → Breakout confirmed with volume above average.
* *ATR Stop* → Wide range breakout using ATR filter.
* *Time Filter* → Breakouts inside defined session hours.
* *EMA Trend* → Breakouts only in EMA fast > slow alignment.
* *RSI Confirm* → Breakouts with RSI confirmation (e.g. >55 for longs).
* *Candle Confirm* → Breakouts validated by bullish/bearish candle.
* Lookback / ATR / Bollinger inputs → adjust sensitivity.
* Intrabar mode → option to evaluate breakouts using bar highs/lows instead of closes.
* Table options → show/hide info table, show/hide P&L stats, choose corner placement.
📈 Entry & Exit Logic
* Entry → occurs when breakout condition of chosen mode is met.
* Exit → default exits via opposite signals or optional stop/target if enabled.
* Session filter → optional auto-flat at session end.
* P&L management → optional daily loss guard, cooldown between trades, and ATR-based stop/take profit.
❓ FAQ — Choosing the best setup
Q: Which strategy should I use for which chart?
* *Prev Day Breakouts*: Best on indices, FX, and liquid futures with strong daily levels.
* *Bollinger*: Works well in range-bound environments, or crypto pairs with volatility compression.
* *Volume*: Good on equities where breakout strength is tied to volume spikes.
* *ATR Stop*: Suits volatile instruments (commodities, crypto).
* *EMA Trend*: Useful in trending markets (stocks, indices).
* *RSI Confirm*: Adds momentum filter, better for swing trades.
* *Candle Confirm*: Ideal for scalpers needing visual confirmation.
* *Time Filter*: For intraday traders who want signals only in high-liquidity sessions.
Q: What timeframe should I use?
* Intraday traders → 5m to 15m (Time Filter, Candle Confirm).
* Swing traders → 1H to 4H (EMA Trend, RSI Confirm, ATR Stop).
* Position traders → Daily (Prev Day, Bollinger).
* Breakout
A trade entry condition triggered when price crosses above a resistance level (for longs) or below a support level (for shorts).
* Prev Day High/Low
Formula:
Prev High = High of (Day )
Prev Low = Low of (Day )
* Bollinger Bands
Formula:
Basis = SMA(Close, Length)
Upper Band = Basis + (Multiplier × StdDev(Close, Length))
Lower Band = Basis – (Multiplier × StdDev(Close, Length))
* Volume Confirmation
A breakout is only valid if:
Volume > SMA(Volume, Length)
* ATR (Average True Range)
Measures volatility.
Formula:
ATR = SMA(True Range, Length)
where True Range = max(High–Low, |High–Close |, |Low–Close |)
* EMA (Exponential Moving Average)
Weighted moving average giving more weight to recent prices.
Formula:
EMA = (Price × α) + (EMA × (1–α))
with α = 2 / (Length + 1)
* RSI (Relative Strength Index)
Momentum oscillator scaled 0–100.
Formula:
RSI = 100 – (100 / (1 + RS))
where RS = Avg(Gain, Length) ÷ Avg(Loss, Length)
* Candle Confirmation
Bullish candle: Close > Open AND Close > Close
Bearish candle: Close < Open AND Close < Close
Win Rate (%)
Formula:
Win Rate = (Winning Trades ÷ Total Trades) × 100
* Average Trade P&L
Formula:
Avg Trade = Net Profit ÷ Total Trades
📊 Performance Notes
The Universal Breakout Strategy is designed as a framework rather than a single-asset optimized system. Results will vary depending on the chart, timeframe, and asset chosen.
On the current defaults (15-minute, INR-denominated example), the backtest produced 132 trades over the selected period. This provides a statistically sufficient sample size.
Win rate (~35%) is relatively low, but this is balanced by a positive reward-to-risk ratio (~1.8). In practice, a lower win rate with larger wins versus smaller losses is sustainable.
The average P&L per trade is close to breakeven under default settings. This is expected, as the strategy is not tuned for a single symbol but offered as a universal breakout framework.
Commissions (0.1%) and slippage (1 tick) are included in the simulation, ensuring realistic conditions.
Risk management is conservative, with order sizing set at 1 unit per trade. This avoids over-leveraging and keeps exposure well under the 5-10% equity risk guideline.
👉 Traders are encouraged to:
Experiment with inputs such as ATR period, breakout length, or Bollinger parameters.
Test across different timeframes and instruments (equities, futures, forex, crypto) to find optimal setups.
Combine with filters (trend direction, volatility regimes, or volume conditions) for further refinement.
⚠️ Disclaimer This script is provided for educational purposes only.
Past performance does not guarantee future results.
Trading involves risk, and users should exercise caution and use proper risk management when applying this strategy.
PubLibPivotLibrary "PubLibPivot"
Pivot detection library for harmonic pattern analysis - Fractal and ZigZag methods with validation and utility functions
fractalPivotHigh(depth)
Fractal pivot high condition
Parameters:
depth (int)
Returns: bool
fractalPivotLow(depth)
Fractal pivot low condition
Parameters:
depth (int)
Returns: bool
fractalPivotHighPrice(depth, occurrence)
Get fractal pivot high price
Parameters:
depth (int)
occurrence (simple int)
Returns: float
fractalPivotLowPrice(depth, occurrence)
Get fractal pivot low price
Parameters:
depth (int)
occurrence (simple int)
Returns: float
fractalPivotHighBarIndex(depth, occurrence)
Get fractal pivot high bar index
Parameters:
depth (int)
occurrence (simple int)
Returns: int
fractalPivotLowBarIndex(depth, occurrence)
Get fractal pivot low bar index
Parameters:
depth (int)
occurrence (simple int)
Returns: int
zigzagPivotHigh(deviation, backstep, useATR, atrLength)
ZigZag pivot high condition
Parameters:
deviation (float)
backstep (int)
useATR (bool)
atrLength (simple int)
Returns: bool
zigzagPivotLow(deviation, backstep, useATR, atrLength)
ZigZag pivot low condition
Parameters:
deviation (float)
backstep (int)
useATR (bool)
atrLength (simple int)
Returns: bool
zigzagPivotHighPrice(deviation, backstep, useATR, atrLength, occurrence)
Get ZigZag pivot high price
Parameters:
deviation (float)
backstep (int)
useATR (bool)
atrLength (simple int)
occurrence (simple int)
Returns: float
zigzagPivotLowPrice(deviation, backstep, useATR, atrLength, occurrence)
Get ZigZag pivot low price
Parameters:
deviation (float)
backstep (int)
useATR (bool)
atrLength (simple int)
occurrence (simple int)
Returns: float
zigzagPivotHighBarIndex(deviation, backstep, useATR, atrLength, occurrence)
Get ZigZag pivot high bar index
Parameters:
deviation (float)
backstep (int)
useATR (bool)
atrLength (simple int)
occurrence (simple int)
Returns: int
zigzagPivotLowBarIndex(deviation, backstep, useATR, atrLength, occurrence)
Get ZigZag pivot low bar index
Parameters:
deviation (float)
backstep (int)
useATR (bool)
atrLength (simple int)
occurrence (simple int)
Returns: int
isValidPivotVolume(pivotPrice, pivotBarIndex, minVolumeRatio, volumeLength)
Validate pivot quality based on volume
Parameters:
pivotPrice (float)
pivotBarIndex (int)
minVolumeRatio (float)
volumeLength (int)
Returns: bool
isValidPivotATR(pivotPrice, lastPivotPrice, minATRMultiplier, atrLength)
Validate pivot based on minimum ATR movement
Parameters:
pivotPrice (float)
lastPivotPrice (float)
minATRMultiplier (float)
atrLength (simple int)
Returns: bool
isValidPivotTime(pivotBarIndex, lastPivotBarIndex, minBars)
Validate pivot based on minimum time between pivots
Parameters:
pivotBarIndex (int)
lastPivotBarIndex (int)
minBars (int)
Returns: bool
isPivotConfirmed(pivotBarIndex, depth)
Check if pivot is not repainting (confirmed)
Parameters:
pivotBarIndex (int)
depth (int)
Returns: bool
addPivotToArray(pivotArray, barArray, pivotPrice, pivotBarIndex, maxSize)
Add pivot to array with validation
Parameters:
pivotArray (array)
barArray (array)
pivotPrice (float)
pivotBarIndex (int)
maxSize (int)
Returns: array - updated pivot array
getPivotFromArray(pivotArray, barArray, index)
Get pivot from array by index
Parameters:
pivotArray (array)
barArray (array)
index (int)
Returns: tuple - (price, bar_index)
getPivotsInRange(pivotArray, barArray, startIndex, count)
Get all pivots in range
Parameters:
pivotArray (array)
barArray (array)
startIndex (int)
count (int)
Returns: tuple, array> - (prices, bar_indices)
pivotDistance(barIndex1, barIndex2)
Calculate distance between two pivots in bars
Parameters:
barIndex1 (int)
barIndex2 (int)
Returns: int - distance in bars
pivotPriceRatio(price1, price2)
Calculate price ratio between two pivots
Parameters:
price1 (float)
price2 (float)
Returns: float - price ratio
pivotRetracementRatio(startPrice, endPrice, currentPrice)
Calculate retracement ratio
Parameters:
startPrice (float)
endPrice (float)
currentPrice (float)
Returns: float - retracement ratio (0-1)
pivotExtensionRatio(startPrice, endPrice, currentPrice)
Calculate extension ratio
Parameters:
startPrice (float)
endPrice (float)
currentPrice (float)
Returns: float - extension ratio (>1 for extension)
isInFibZone(startPrice, endPrice, currentPrice, fibLevel, tolerance)
Check if price is in Fibonacci retracement zone
Parameters:
startPrice (float)
endPrice (float)
currentPrice (float)
fibLevel (float)
tolerance (float)
Returns: bool - true if in zone
getPivotType(pivotPrice, pivotBarIndex, lookback)
Get pivot type (high/low) based on surrounding prices
Parameters:
pivotPrice (float)
pivotBarIndex (int)
lookback (int)
Returns: string - "high", "low", or "unknown"
calculatePivotStrength(pivotPrice, pivotBarIndex, lookback)
Calculate pivot strength based on volume and price action
Parameters:
pivotPrice (float)
pivotBarIndex (int)
lookback (int)
Returns: float - strength score (0-100)
Structural Liquidity Signals [BullByte]Structural Liquidity Signals (SFP, FVG, BOS, AVWAP)
Short description
Detects liquidity sweeps (SFPs) at pivots and PD/W levels, highlights the latest FVG, tracks AVWAP stretch, arms percentile extremes, and triggers after confirmed micro BOS.
Full description
What this tool does
Structural Liquidity Signals shows where price likely tapped liquidity (stop clusters), then waits for structure to actually change before it prints a trigger. It spots:
Liquidity sweeps (SFPs) at recent pivots and at prior day/week highs/lows.
The latest Fair Value Gap (FVG) that often “pulls” price or serves as a reaction zone.
How far price is stretched from two VWAP anchors (one from the latest impulse, one from today’s session), scaled by ATR so it adapts to volatility.
A “percentile” extreme of an internal score. At extremes the script “arms” a setup; it only triggers after a small break of structure (BOS) on a closed bar.
Originality and design rationale, why it’s not “just a mashup”
This is not a mashup for its own sake. It’s a purpose-built flow that links where liquidity is likely to rest with how structure actually changes:
- Liquidity location: We focus on areas where stops commonly cluster—recent pivots and prior day/week highs/lows—then detect sweeps (SFPs) when price wicks beyond and closes back inside.
- Displacement context: We track the last Fair Value Gap (FVG) to account for recent inefficiency that often acts as a magnet or reaction zone.
- Stretch measurement: We anchor VWAP to the latest N-bar impulse and to the Daily session, then normalize stretch by ATR to assess dislocation consistently across assets/timeframes.
- Composite exhaustion: We combine stretch, wick skew, and volume surprise, then bend the result with a tanh transform so extremes are bounded and comparable.
- Dynamic extremes and discipline: Rather than triggering on every sweep, we “arm” at statistical extremes via percent-rank and only fire after a confirmed micro Break of Structure (BOS). This separates “interesting” from “actionable.”
Key concepts
SFP (liquidity sweep): A candle briefly trades beyond a level (where stops sit) and closes back inside. We detect these at:
Pivots (recent swing highs/lows confirmed by “left/right” bars).
Prior Day/Week High/Low (PDH/PDL/PWH/PWL).
FVG (Fair Value Gap): A small 3‑bar gap (bar2 high vs bar1 low, or vice versa). The latest gap often acts like a magnet or reaction zone. We track the most recent Up/Down gap and whether price is inside it.
AVWAP stretch: Distance from an Anchored VWAP divided by ATR (volatility). We use:
Impulse AVWAP: resets on each new N‑bar high/low.
Daily AVWAP: resets each new session.
PR (Percentile Rank): Where the current internal score sits versus its own recent history (0..100). We arm shorts at high PR, longs at low PR.
Micro BOS: A small break of the recent high (for longs) or low (for shorts). This is the “go/no‑go” confirmation.
How the parts work together
Find likely liquidity grabs (SFPs) at pivots and PD/W levels.
Add context from the latest FVG and AVWAP stretch (how far price is from “fair”).
Build a bounded score (so different markets/timeframes are comparable) and compute its percentile (PR).
Arm at extremes (high PR → short candidate; low PR → long candidate).
Only print a trigger after a micro BOS, on a closed bar, with spacing/cooldown rules.
What you see on the chart (legend)
Lines:
Teal line = Impulse AVWAP (resets on new N‑bar extreme).
Aqua line = Daily AVWAP (resets each session).
PDH/PDL/PWH/PWL = prior day/week levels (toggle on/off).
Zones:
Greenish box = latest Up FVG; Reddish box = latest Down FVG.
The shading/border changes after price trades back through it.
SFP labels:
SFP‑P = SFP at Pivot (dotted line marks that pivot’s price).
SFP‑L = SFP at Level (at PDH/PDL/PWH/PWL).
Throttle: To reduce clutter, SFPs are rate‑limited per direction.
Triggers:
Triangle up = long trigger after BOS; triangle down = short trigger after BOS.
Optional badge shows direction and PR at the moment of trigger.
Optional Trigger Zone is an ATR‑sized box around the trigger bar’s close (for visualization only).
Background:
Light green/red shading = a long/short setup is “armed” (not a trigger).
Dashboard (Mini/Pro) — what each item means
PR: Percentile of the internal score (0..100). Near 0 = bullish extreme, near 100 = bearish extreme.
Gauge: Text bar that mirrors PR.
State: Idle, Armed Long (with a countdown), or Armed Short.
Cooldown: Bars remaining before a new setup can arm after a trigger.
Bars Since / Last Px: How long since last trigger and its price.
FVG: Whether price is in the latest Up/Down FVG.
Imp/Day VWAP Dist, PD Dist(ATR): Distance from those references in ATR units.
ATR% (Gate), Trend(HTF): Status of optional regime filters (volatility/trend).
How to use it (step‑by‑step)
Keep the Safety toggles ON (default): triggers/visuals on bar‑close, optional confirmed HTF for trend slope.
Choose timeframe:
Intraday (5m–1h) or Swing (1h–4h). On very fast/thin charts, enable Performance mode and raise spacing/cooldown.
Watch the dashboard:
When PR reaches an extreme and an SFP context is present, the background shades (armed).
Wait for the trigger triangle:
It prints only after a micro BOS on a closed bar and after spacing/cooldown checks.
Use the Trigger Zone box as a visual reference only:
This script never tells you to buy/sell. Apply your own plan for entry, stop, and sizing.
Example:
Bullish: Sweep under PDL (SFP‑L) and reclaim; PR in lower tail arms long; BOS up confirms → long trigger on bar close (ATR-sized trigger zone shown).
Bearish: Sweep above PDH/pivot (SFP‑L/P) and reject; PR in upper tail arms short; BOS down confirms → short trigger on bar close (ATR-sized trigger zone shown).
Settings guide (with “when to adjust”)
Safety & Stability (defaults ON)
Confirm triggers at bar close, Draw visuals at bar close: Keep ON for clean, stable prints.
Use confirmed HTF values: Applies to HTF trend slope only; keeps it from changing until the HTF bar closes.
Performance mode: Turn ON if your chart is busy or laggy.
Core & Context
ATR Length: Bigger = smoother distances; smaller = more reactive.
Impulse AVWAP Anchor: Larger = fewer resets; smaller = resets more often.
Show Daily AVWAP: ON if you want session context.
Use last FVG in logic: ON to include FVG context in arming/score.
Show PDH/PDL/PWH/PWL: ON to see prior day/week levels that often attract sweeps.
Liquidity & Microstructure
Pivot Left/Right: Higher values = stronger/rarer pivots.
Min Wick Ratio (0..1): Higher = only more pronounced SFP wicks qualify.
BOS length: Larger = stricter BOS; smaller = quicker confirmations.
Signal persistence: Keeps SFP context alive for a few bars to avoid flicker.
Signal Gating
Percent‑Rank Lookback: Larger = more stable extremes; smaller = more reactive extremes.
Arm thresholds (qHi/qLo): Move closer to 0.5 to see more arms; move toward 0/1 to see fewer arms.
TTL, Cooldown, Min bars and Min ATR distance: Space out triggers so you’re not reacting to minor noise.
Regime Filters (optional)
ATR percentile gate: Only allow triggers when volatility is at/above a set percentile.
HTF trend gate: Only allow longs when the HTF slope is up (and shorts when it’s down), above a minimum slope.
Visuals & UX
Only show “important” SFPs: Filters pivot SFPs by Volume Z and |Impulse stretch|.
Trigger badges/history and Max badge count: Control label clutter.
Compact labels: Toggle SFP‑P/L vs full names.
Dashboard mode and position; Dark theme.
Reading PR (the built‑in “oscillator”)
PR ~ 0–10: Potential bullish extreme (long side can arm).
PR ~ 90–100: Potential bearish extreme (short side can arm).
Important: “Armed” ≠ “Enter.” A trigger still needs a micro BOS on a closed bar and spacing/cooldown to pass.
Repainting, confirmations, and HTF notes
By default, prints wait for the bar to close; this reduces repaint‑like effects.
Pivot SFPs only appear after the pivot confirms (after the chosen “right” bars).
PD/W levels come from the prior completed candles and do not change intraday.
If you enable confirmed HTF values, the HTF slope will not change until its higher‑timeframe bar completes (safer but slightly delayed).
Performance tips
If labels/zones clutter or the chart lags:
Turn ON Performance mode.
Hide FVG or the Trigger Zone.
Reduce badge history or turn badge history off.
If price scaling looks compressed:
Keep optional “score”/“PR” plots OFF (they overlay price and can affect scaling).
Alerts (neutral)
Structural Liquidity: LONG TRIGGER
Structural Liquidity: SHORT TRIGGER
These fire when a trigger condition is met on a confirmed bar (with defaults).
Limitations and risk
Not every sweep/extreme reverses; false triggers occur, especially on thin markets and low timeframes.
This indicator does not provide entries, exits, or position sizing—use your own plan and risk control.
Educational/informational only; no financial advice.
License and credits
© BullByte - MPL 2.0. Open‑source for learning and research.
Built from repeated observations of how liquidity runs, imbalance (FVG), and distance from “fair” (AVWAPs) combine, and how a small BOS often marks the moment structure actually shifts.
Fibo Swing MFI by julzALGOOVERVIEW
Fibo Swing MFI by julzALGO blends MFI → RSI → Least-Squares smoothing to flag overbought/oversold swings and continuously plot Fibonacci retracements from the rolling high/low of the last 200 bars. It’s built to spot momentum shifts while giving you a clean, always-current fib map of the recent market range.
CORE PRINCIPLES
Hybrid Momentum Signal
- Uses MFI to integrate price and volume.
- Applies RSI to MFI for momentum clarity.
- Smooths the result with Least Squares regression to reduce noise.
Swing Identification
- Marks potential swing highs when momentum is overbought.
- Marks potential swing lows when momentum is oversold.
Fixed-Window Fibonacci Mapping
- Always calculates fib levels from the highest high and lowest low of the last 200 bars.
- This keeps fib zones consistent, independent of swing point detection.
Visual Clarity & Non-Repainting Logic
- Clean labels for OB/OS zones.
- Lines and levels update only as new bars confirm changes.
Adaptability
- Works on any market and timeframe.
- Adjustable momentum length, OB/OS thresholds, and smoothing.
HOW IT WORKS
- Computes Money Flow Index (MFI) from price & volume.
- Applies RSI to the MFI for clearer OB/OS momentum.
- Smooths the hybrid with a Least Squares (linear regression) filter.
- Swing labels appear when OB/OS conditions are met (green = swing low, red = swing high).
- Fibonacci retracements are always drawn from the highest high and lowest low of the last 200 bars (rolling window), independent of swing labels.
HOW TO USE
- Watch for OB/OS flips to mark potential swing highs/lows.
- Use the 200-bar fib grid as your active map of pullback levels and reaction zones.
- Combine fib reactions with your price action/volume cues for confirmation.
- Works across markets and timeframes.
SETTINGS
- Length – Period for both MFI and RSI.
- OB/OS Levels – Overbought/oversold thresholds (default 70/30).
- Smooth – Least-Squares smoothing length.
- Fibonacci Window – Fixed at 200 bars in this version (changeable in code via fibLen).
NOTES
- Logic is non-repainting aside from standard bar/label confirmation.
- Increase Length on very low timeframes to reduce noise.
- Swing labels help context; fibs are always based on the most recent 200-bar high/low range.
SUMMARY
Fibo Swing MFI by julzALGO is a momentum-plus-price action tool that merges MFI → RSI → smoothing to identify overbought/oversold swings and automatically plot Fibonacci retracements based on the rolling high/low of the last 200 bars. It’s designed to help traders quickly see potential reversal points and pullback zones, offering visual confluence between momentum shifts and fixed-window price structure.
DISCLAIMER
For educational purposes only. Not financial advice. Trade responsibly with proper risk management.
UNITY[ALGO] PO3 V3Of course. Here is a complete and professional description in English for the indicator we have built, detailing all of its features and functionalities.
Indicator: UNITY PO3 V7.2
Overview
The UNITY PO3 is an advanced, multi-faceted technical analysis tool designed to identify high-probability reversal setups based on the Swing Failure Pattern (SFP). It combines real-time SFP detection on the current timeframe with a sophisticated analysis of key institutional liquidity zones from the H4 timeframe, presenting all information in a clear, dynamic, and interactive visual interface.
This indicator is built for traders who use liquidity concepts, providing a complete dashboard of entries, targets, and invalidation levels directly on the chart.
Core Features & Functionality
1. Swing Failure Pattern (SFP) Detection (Current Timeframe)
The indicator's primary engine identifies SFPs on the chart's active timeframe with two layers of logic:
Standard SFP: Detects a classic liquidity sweep where the current candle's wick takes out the high or low of the previous candle and the body closes back within the previous candle's range.
Outside Bar SFP Logic: Intelligently analyzes engulfing candles that sweep both the high and low of the previous candle. A valid signal is only generated if the candle has a clear directional close:
Bullish Signal: If the outside bar closes higher than its open.
Bearish Signal: If the outside bar closes lower than its open.
Neutral (doji-like) outside bars are ignored to filter for indecision.
2. Comprehensive On-Chart SFP Markings
When a valid SFP is detected, a full suite of dynamic drawings appears on the chart:
Failure Line: A dashed line (red for bearish, green for bullish) marking the precise price level of the liquidity sweep.
PREMIUM ZONE (SFP Candle Wick): A transparent, colored rectangle highlighting the rejection wick of the signal candle (the upper wick for bearish SFPs, the lower wick for bullish SFPs). This zone automatically extends to the right, following the current price, until the DOL is hit.
CRT BOX (Reference Candle): A transparent box with a colored border drawn around the entire range of the candle that was swept (Candle 1). This highlights the full liquidity zone and also extends dynamically until the DOL is hit.
Dynamic Target Line: A blue dashed line marking the primary objective (the low of the signal candle for shorts, the high for longs).
The line begins with a "⏳ Target" label and extends with the current price.
Upon being touched by price, the line freezes, and its label permanently changes to "✅ Target".
Dynamic DOL (Draw on Liquidity) Line: An orange dashed line marking the invalidation level, defined as the opposite extremity of the swept candle (Candle 1).
It begins with a "⏳ dol" label and extends with the price.
Upon being touched, it freezes, and its label changes to "✅ dol".
3. Multi-Session Killzone Liquidity Levels (H4 Analysis)
The indicator automatically analyzes the H4 timeframe in the background to identify and plot key liquidity levels from three major trading sessions, based on their UTC opening times.
1am Killzone (London Lunch): Tracks the high/low of the 05:00 UTC H4 candle.
5am Killzone (London Open): Tracks the high/low of the 09:00 UTC H4 candle.
9am Killzone (NY Open): Tracks the high/low of the 13:00 UTC H4 candle.
For each of these Killzones, the indicator provides two types of analysis:
Last KZ Lines: Plots the high and low of the most recent qualifying Killzone candle. These lines are dynamic, extending with price and showing a ⏳/✅ status when touched.
Fresh Zones: A powerful feature that scans the entire available history of Killzones to find and display the closest untouched high (above the current price) and the closest untouched low (below the current price). These "Fresh" lines are also fully dynamic and provide a real-time view of the most relevant nearby liquidity targets.
4. Advanced User Settings & Chart Management
The indicator is designed for a clean and user-centric experience with powerful customization:
Show Only Last SFP: Keeps the chart clean by automatically deleting the previous SFP setup when a new one appears.
Hide SFP on DOL Reset: When checked, automatically removes all drawings related to an SFP setup the moment its invalidation level (DOL line) is touched. This leaves only active, valid setups on the chart.
Hide Consumed KZ: When checked, automatically removes any Killzone or Fresh Zone line from the chart as soon as it is touched by the price.
Independent Toggles: Every visual element—SFP signals, each of the three Killzones, and their respective "Fresh" zone counterparts—can be turned on or off independently from the settings menu for complete control over the visual display.
Z-Order Priority: All indicator drawings are rendered in front of the chart candles, ensuring they are always clearly visible and never hidden from view.
Game Theory Trading StrategyGame Theory Trading Strategy: Explanation and Working Logic
This Pine Script (version 5) code implements a trading strategy named "Game Theory Trading Strategy" in TradingView. Unlike the previous indicator, this is a full-fledged strategy with automated entry/exit rules, risk management, and backtesting capabilities. It uses Game Theory principles to analyze market behavior, focusing on herd behavior, institutional flows, liquidity traps, and Nash equilibrium to generate buy (long) and sell (short) signals. Below, I'll explain the strategy's purpose, working logic, key components, and usage tips in detail.
1. General Description
Purpose: The strategy identifies high-probability trading opportunities by combining Game Theory concepts (herd behavior, contrarian signals, Nash equilibrium) with technical analysis (RSI, volume, momentum). It aims to exploit market inefficiencies caused by retail herd behavior, institutional flows, and liquidity traps. The strategy is designed for automated trading with defined risk management (stop-loss/take-profit) and position sizing based on market conditions.
Key Features:
Herd Behavior Detection: Identifies retail panic buying/selling using RSI and volume spikes.
Liquidity Traps: Detects stop-loss hunting zones where price breaks recent highs/lows but reverses.
Institutional Flow Analysis: Tracks high-volume institutional activity via Accumulation/Distribution and volume spikes.
Nash Equilibrium: Uses statistical price bands to assess whether the market is in equilibrium or deviated (overbought/oversold).
Risk Management: Configurable stop-loss (SL) and take-profit (TP) percentages, dynamic position sizing based on Game Theory (minimax principle).
Visualization: Displays Nash bands, signals, background colors, and two tables (Game Theory status and backtest results).
Backtesting: Tracks performance metrics like win rate, profit factor, max drawdown, and Sharpe ratio.
Strategy Settings:
Initial capital: $10,000.
Pyramiding: Up to 3 positions.
Position size: 10% of equity (default_qty_value=10).
Configurable inputs for RSI, volume, liquidity, institutional flow, Nash equilibrium, and risk management.
Warning: This is a strategy, not just an indicator. It executes trades automatically in TradingView's Strategy Tester. Always backtest thoroughly and use proper risk management before live trading.
2. Working Logic (Step by Step)
The strategy processes each bar (candle) to generate signals, manage positions, and update performance metrics. Here's how it works:
a. Input Parameters
The inputs are grouped for clarity:
Herd Behavior (🐑):
RSI Period (14): For overbought/oversold detection.
Volume MA Period (20): To calculate average volume for spike detection.
Herd Threshold (2.0): Volume multiplier for detecting herd activity.
Liquidity Analysis (💧):
Liquidity Lookback (50): Bars to check for recent highs/lows.
Liquidity Sensitivity (1.5): Volume multiplier for trap detection.
Institutional Flow (🏦):
Institutional Volume Multiplier (2.5): For detecting large volume spikes.
Institutional MA Period (21): For Accumulation/Distribution smoothing.
Nash Equilibrium (⚖️):
Nash Period (100): For calculating price mean and standard deviation.
Nash Deviation (0.02): Multiplier for equilibrium bands.
Risk Management (🛡️):
Use Stop-Loss (true): Enables SL at 2% below/above entry price.
Use Take-Profit (true): Enables TP at 5% above/below entry price.
b. Herd Behavior Detection
RSI (14): Checks for extreme conditions:
Overbought: RSI > 70 (potential herd buying).
Oversold: RSI < 30 (potential herd selling).
Volume Spike: Volume > SMA(20) x 2.0 (herd_threshold).
Momentum: Price change over 10 bars (close - close ) compared to its SMA(20).
Herd Signals:
Herd Buying: RSI > 70 + volume spike + positive momentum = Retail buying frenzy (red background).
Herd Selling: RSI < 30 + volume spike + negative momentum = Retail selling panic (green background).
c. Liquidity Trap Detection
Recent Highs/Lows: Calculated over 50 bars (liquidity_lookback).
Psychological Levels: Nearest round numbers (e.g., $100, $110) as potential stop-loss zones.
Trap Conditions:
Up Trap: Price breaks recent high, closes below it, with a volume spike (volume > SMA x 1.5).
Down Trap: Price breaks recent low, closes above it, with a volume spike.
Visualization: Traps are marked with small red/green crosses above/below bars.
d. Institutional Flow Analysis
Volume Check: Volume > SMA(20) x 2.5 (inst_volume_mult) = Institutional activity.
Accumulation/Distribution (AD):
Formula: ((close - low) - (high - close)) / (high - low) * volume, cumulated over time.
Smoothed with SMA(21) (inst_ma_length).
Accumulation: AD > MA + high volume = Institutions buying.
Distribution: AD < MA + high volume = Institutions selling.
Smart Money Index: (close - open) / (high - low) * volume, smoothed with SMA(20). Positive = Smart money buying.
e. Nash Equilibrium
Calculation:
Price mean: SMA(100) (nash_period).
Standard deviation: stdev(100).
Upper Nash: Mean + StdDev x 0.02 (nash_deviation).
Lower Nash: Mean - StdDev x 0.02.
Conditions:
Near Equilibrium: Price between upper and lower Nash bands (stable market).
Above Nash: Price > upper band (overbought, sell potential).
Below Nash: Price < lower band (oversold, buy potential).
Visualization: Orange line (mean), red/green lines (upper/lower bands).
f. Game Theory Signals
The strategy generates three types of signals, combined into long/short triggers:
Contrarian Signals:
Buy: Herd selling + (accumulation or down trap) = Go against retail panic.
Sell: Herd buying + (distribution or up trap).
Momentum Signals:
Buy: Below Nash + positive smart money + no herd buying.
Sell: Above Nash + negative smart money + no herd selling.
Nash Reversion Signals:
Buy: Below Nash + rising close (close > close ) + volume > MA.
Sell: Above Nash + falling close + volume > MA.
Final Signals:
Long Signal: Contrarian buy OR momentum buy OR Nash reversion buy.
Short Signal: Contrarian sell OR momentum sell OR Nash reversion sell.
g. Position Management
Position Sizing (Minimax Principle):
Default: 1.0 (10% of equity).
In Nash equilibrium: Reduced to 0.5 (conservative).
During institutional volume: Increased to 1.5 (aggressive).
Entries:
Long: If long_signal is true and no existing long position (strategy.position_size <= 0).
Short: If short_signal is true and no existing short position (strategy.position_size >= 0).
Exits:
Stop-Loss: If use_sl=true, set at 2% below/above entry price.
Take-Profit: If use_tp=true, set at 5% above/below entry price.
Pyramiding: Up to 3 concurrent positions allowed.
h. Visualization
Nash Bands: Orange (mean), red (upper), green (lower).
Background Colors:
Herd buying: Red (90% transparency).
Herd selling: Green.
Institutional volume: Blue.
Signals:
Contrarian buy/sell: Green/red triangles below/above bars.
Liquidity traps: Red/green crosses above/below bars.
Tables:
Game Theory Table (Top-Right):
Herd Behavior: Buying frenzy, selling panic, or normal.
Institutional Flow: Accumulation, distribution, or neutral.
Nash Equilibrium: In equilibrium, above, or below.
Liquidity Status: Trap detected or safe.
Position Suggestion: Long (green), Short (red), or Wait (gray).
Backtest Table (Bottom-Right):
Total Trades: Number of closed trades.
Win Rate: Percentage of winning trades.
Net Profit/Loss: In USD, colored green/red.
Profit Factor: Gross profit / gross loss.
Max Drawdown: Peak-to-trough equity drop (%).
Win/Loss Trades: Number of winning/losing trades.
Risk/Reward Ratio: Simplified Sharpe ratio (returns / drawdown).
Avg Win/Loss Ratio: Average win per trade / average loss per trade.
Last Update: Current time.
i. Backtesting Metrics
Tracks:
Total trades, winning/losing trades.
Win rate (%).
Net profit ($).
Profit factor (gross profit / gross loss).
Max drawdown (%).
Simplified Sharpe ratio (returns / drawdown).
Average win/loss ratio.
Updates metrics on each closed trade.
Displays a label on the last bar with backtest period, total trades, win rate, and net profit.
j. Alerts
No explicit alertconditions defined, but you can add them for long_signal and short_signal (e.g., alertcondition(long_signal, "GT Long Entry", "Long Signal Detected!")).
Use TradingView's alert system with Strategy Tester outputs.
3. Usage Tips
Timeframe: Best for H1-D1 timeframes. Shorter frames (M1-M15) may produce noisy signals.
Settings:
Risk Management: Adjust sl_percent (e.g., 1% for volatile markets) and tp_percent (e.g., 3% for scalping).
Herd Threshold: Increase to 2.5 for stricter herd detection in choppy markets.
Liquidity Lookback: Reduce to 20 for faster markets (e.g., crypto).
Nash Period: Increase to 200 for longer-term analysis.
Backtesting:
Use TradingView's Strategy Tester to evaluate performance.
Check win rate (>50%), profit factor (>1.5), and max drawdown (<20%) for viability.
Test on different assets/timeframes to ensure robustness.
Live Trading:
Start with a demo account.
Combine with other indicators (e.g., EMAs, support/resistance) for confirmation.
Monitor liquidity traps and institutional flow for context.
Risk Management:
Always use SL/TP to limit losses.
Adjust position_size for risk tolerance (e.g., 5% of equity for conservative trading).
Avoid over-leveraging (pyramiding=3 can amplify risk).
Troubleshooting:
If no trades are executed, check signal conditions (e.g., lower herd_threshold or liquidity_sensitivity).
Ensure sufficient historical data for Nash and liquidity calculations.
If tables overlap, adjust position.top_right/bottom_right coordinates.
4. Key Differences from the Previous Indicator
Indicator vs. Strategy: The previous code was an indicator (VP + Game Theory Integrated Strategy) focused on visualization and alerts. This is a strategy with automated entries/exits and backtesting.
Volume Profile: Absent in this strategy, making it lighter but less focused on high-volume zones.
Wick Analysis: Not included here, unlike the previous indicator's heavy reliance on wick patterns.
Backtesting: This strategy includes detailed performance metrics and a backtest table, absent in the indicator.
Simpler Signals: Focuses on Game Theory signals (contrarian, momentum, Nash reversion) without the "Power/Ultra Power" hierarchy.
Risk Management: Explicit SL/TP and dynamic position sizing, not present in the indicator.
5. Conclusion
The "Game Theory Trading Strategy" is a sophisticated system leveraging herd behavior, institutional flows, liquidity traps, and Nash equilibrium to trade market inefficiencies. It’s designed for traders who understand Game Theory principles and want automated execution with robust risk management. However, it requires thorough backtesting and parameter optimization for specific markets (e.g., forex, crypto, stocks). The backtest table and visual aids make it easy to monitor performance, but always combine with other analysis tools and proper capital management.
If you need help with backtesting, adding alerts, or optimizing parameters, let me know!
Smart MTF S/R Levels[BullByte]
Smart MTF S/R Levels
Introduction & Motivation
Support and Resistance (S/R) levels are the backbone of technical analysis. However, most traders face two major challenges:
Manual S/R Marking: Drawing S/R levels by hand is time-consuming, subjective, and often inconsistent.
Multi-Timeframe Blind Spots: Key S/R levels from higher or lower timeframes are often missed, leading to surprise reversals or missed opportunities.
Smart MTF S/R Levels was created to solve these problems. It is a fully automated, multi-timeframe, multi-method S/R detection and visualization tool, designed to give traders a complete, objective, and actionable view of the market’s most important price zones.
What Makes This Indicator Unique?
Multi-Timeframe Analysis: Simultaneously analyzes up to three user-selected timeframes, ensuring you never miss a critical S/R level from any timeframe.
Multi-Method Confluence: Integrates several respected S/R detection methods—Swings, Pivots, Fibonacci, Order Blocks, and Volume Profile—into a single, unified system.
Zone Clustering: Automatically merges nearby levels into “zones” to reduce clutter and highlight areas of true market consensus.
Confluence Scoring: Each zone is scored by the number of methods and timeframes in agreement, helping you instantly spot the most significant S/R areas.
Reaction Counting: Tracks how many times price has recently interacted with each zone, providing a real-world measure of its importance.
Customizable Dashboard: A real-time, on-chart table summarizes all key S/R zones, their origins, confluence, and proximity to price.
Smart Alerts: Get notified when price approaches high-confluence zones, so you never miss a critical trading opportunity.
Why Should a Trader Use This?
Objectivity: Removes subjectivity from S/R analysis by using algorithmic detection and clustering.
Efficiency: Saves hours of manual charting and reduces analysis fatigue.
Comprehensiveness: Ensures you are always aware of the most relevant S/R zones, regardless of your trading timeframe.
Actionability: The dashboard and alerts make it easy to act on the most important levels, improving trade timing and risk management.
Adaptability: Works for all asset classes (stocks, forex, crypto, futures) and all trading styles (scalping, swing, position).
The Gap This Indicator Fills
Most S/R indicators focus on a single method or timeframe, leading to incomplete analysis. Manual S/R marking is error-prone and inconsistent. This indicator fills the gap by:
Automating S/R detection across multiple timeframes and methods
Objectively scoring and ranking zones by confluence and reaction
Presenting all this information in a clear, actionable dashboard
How Does It Work? (Technical Logic)
1. Level Detection
For each selected timeframe, the script detects S/R levels using:
SW (Swing High/Low): Recent price pivots where reversals occurred.
Pivot: Classic floor trader pivots (P, S1, R1).
Fib (Fibonacci): Key retracement levels (0.236, 0.382, 0.5, 0.618, 0.786) over the last 50 bars.
Bull OB / Bear OB: Institutional price zones based on bullish/bearish engulfing patterns.
VWAP / POC: Volume Weighted Average Price and Point of Control over the last 50 bars.
2. Level Clustering
Levels within a user-defined % distance are merged into a single “zone.”
Each zone records which methods and timeframes contributed to it.
3. Confluence & Reaction Scoring
Confluence: The number of unique methods/timeframes in agreement for a zone.
Reactions: The number of times price has touched or reversed at the zone in the recent past (user-defined lookback).
4. Filtering & Sorting
Only zones within a user-defined % of the current price are shown (to focus on actionable areas).
Zones can be sorted by confluence, reaction count, or proximity to price.
5. Visualization
Zones: Shaded boxes on the chart (green for support, red for resistance, blue for mixed).
Lines: Mark the exact level of each zone.
Labels: Show level, methods by timeframe (e.g., 15m (3 SW), 30m (1 VWAP)), and (if applicable) Fibonacci ratios.
Dashboard Table: Lists all nearby zones with full details.
6. Alerts
Optional alerts trigger when price approaches a zone with confluence above a user-set threshold.
Inputs & Customization (Explained for All Users)
Show Timeframe 1/2/3: Enable/disable analysis for each timeframe (e.g., 15m, 30m, 1h).
Show Swings/Pivots/Fibonacci/Order Blocks/Volume Profile: Select which S/R methods to include.
Show levels within X% of price: Only display zones near the current price (default: 3%).
How many swing highs/lows to show: Number of recent swings to include (default: 3).
Cluster levels within X%: Merge levels close together into a single zone (default: 0.25%).
Show Top N Zones: Limit the number of zones displayed (default: 8).
Bars to check for reactions: How far back to count price reactions (default: 100).
Sort Zones By: Choose how to rank zones in the dashboard (Confluence, Reactions, Distance).
Alert if Confluence >=: Set the minimum confluence score for alerts (default: 3).
Zone Box Width/Line Length/Label Offset: Control the appearance of zones and labels.
Dashboard Size/Location: Customize the dashboard table.
How to Read the Output
Shaded Boxes: Represent S/R zones. The color indicates type (green = support, red = resistance, blue = mixed).
Lines: Mark the precise level of each zone.
Labels: Show the level, methods by timeframe (e.g., 15m (3 SW), 30m (1 VWAP)), and (if applicable) Fibonacci ratios.
Dashboard Table: Columns include:
Level: Price of the zone
Methods (by TF): Which S/R methods and how many, per timeframe (see abbreviation key below)
Type: Support, Resistance, or Mixed
Confl.: Confluence score (higher = more significant)
React.: Number of recent price reactions
Dist %: Distance from current price (in %)
Abbreviations Used
SW = Swing High/Low (recent price pivots where reversals occurred)
Fib = Fibonacci Level (key retracement levels such as 0.236, 0.382, 0.5, 0.618, 0.786)
VWAP = Volume Weighted Average Price (price level weighted by volume)
POC = Point of Control (price level with the highest traded volume)
Bull OB = Bullish Order Block (institutional support zone from bullish price action)
Bear OB = Bearish Order Block (institutional resistance zone from bearish price action)
Pivot = Pivot Point (classic floor trader pivots: P, S1, R1)
These abbreviations appear in the dashboard and chart labels for clarity.
Example: How to Read the Dashboard and Labels (from the chart above)
Suppose you are trading BTCUSDT on a 15-minute chart. The dashboard at the top right shows several S/R zones, each with a breakdown of which timeframes and methods contributed to their detection:
Resistance zone at 119257.11:
The dashboard shows:
5m (1 SW), 15m (2 SW), 1h (3 SW)
This means the level 119257.11 was identified as a resistance zone by one swing high (SW) on the 5-minute timeframe, two swing highs on the 15-minute timeframe, and three swing highs on the 1-hour timeframe. The confluence score is 6 (total number of method/timeframe hits), and there has been 1 recent price reaction at this level. This suggests 119257.11 is a strong resistance zone, confirmed by multiple swing highs across all selected timeframes.
Mixed zone at 118767.97:
The dashboard shows:
5m (2 SW), 15m (2 SW)
This means the level 118767.97 was identified by two swing points on both the 5-minute and 15-minute timeframes. The confluence score is 4, and there have been 19 recent price reactions at this level, indicating it is a highly reactive zone.
Support zone at 117411.35:
The dashboard shows:
5m (2 SW), 1h (2 SW)
This means the level 117411.35 was identified as a support zone by two swing lows on the 5-minute timeframe and two swing lows on the 1-hour timeframe. The confluence score is 4, and there have been 2 recent price reactions at this level.
Mixed zone at 118291.45:
The dashboard shows:
15m (1 SW, 1 VWAP), 5m (1 VWAP), 1h (1 VWAP)
This means the level 118291.45 was identified by a swing and VWAP on the 15-minute timeframe, and by VWAP on both the 5-minute and 1-hour timeframes. The confluence score is 4, and there have been 12 recent price reactions at this level.
Support zone at 117103.10:
The dashboard shows:
15m (1 SW), 1h (1 SW)
This means the level 117103.10 was identified by a single swing low on both the 15-minute and 1-hour timeframes. The confluence score is 2, and there have been no recent price reactions at this level.
Resistance zone at 117899.33:
The dashboard shows:
5m (1 SW)
This means the level 117899.33 was identified by a single swing high on the 5-minute timeframe. The confluence score is 1, and there have been no recent price reactions at this level.
How to use this:
Zones with higher confluence (more methods and timeframes in agreement) and more recent reactions are generally more significant. For example, the resistance at 119257.11 is much stronger than the resistance at 117899.33, and the mixed zone at 118767.97 has shown the most recent price reactions, making it a key area to watch for potential reversals or breakouts.
Tip:
“SW” stands for Swing High/Low, and “VWAP” stands for Volume Weighted Average Price.
The format 15m (2 SW) means two swing points were detected on the 15-minute timeframe.
Best Practices & Recommendations
Use with Other Tools: This indicator is most powerful when combined with your own price action analysis and risk management.
Adjust Settings: Experiment with timeframes, clustering, and methods to suit your trading style and the asset’s volatility.
Watch for High Confluence: Zones with higher confluence and more reactions are generally more significant.
Limitations
No Future Prediction: The indicator does not predict future price movement; it highlights areas where price is statistically more likely to react.
Not a Standalone System: Should be used as part of a broader trading plan.
Historical Data: Reaction counts are based on historical price action and may not always repeat.
Disclaimer
This indicator is a technical analysis tool and does not constitute financial advice or a recommendation to buy or sell any asset. Trading involves risk, and past performance is not indicative of future results. Always use proper risk management and consult a financial advisor if needed.
Info TableOverview
The Info Table V1 is a versatile TradingView indicator tailored for intraday futures traders, particularly those focusing on MESM2 (Micro E-mini S&P 500 futures) on 1-minute charts. It presents essential market insights through two customizable tables: the Main Table for predictive and macro metrics, and the New Metrics Table for momentum and volatility indicators. Designed for high-activity sessions like 9:30 AM–11:00 AM CDT, this tool helps traders assess price alignment, sentiment, and risk in real-time. Metrics update dynamically (except weekly COT data), with optional alerts for key conditions like volatility spikes or momentum shifts.
This indicator builds on foundational concepts like linear regression for predictions and adapts open-source elements for enhanced functionality. Gradient code is adapted from TradingView's Color Library. QQE logic is adapted from LuxAlgo's QQE Weighted Oscillator, licensed under CC BY-NC-SA 4.0. The script is released under the Mozilla Public License 2.0.
Key Features
Two Customizable Tables: Positioned independently (e.g., top-right for Main, bottom-right for New Metrics) with toggle options to show/hide for a clutter-free chart.
Gradient Coloring: User-defined high/low colors (default green/red) for quick visual interpretation of extremes, such as overbought/oversold or high volatility.
Arrows for Directional Bias: In the New Metrics Table, up (↑) or down (↓) arrows appear in value cells based on metric thresholds (top/bottom 25% of range), indicating bullish/high or bearish/low conditions.
Consensus Highlighting: The New Metrics Table's title cells ("Metric" and "Value") turn green if all arrows are ↑ (strong bullish consensus), red if all are ↓ (strong bearish consensus), or gray otherwise.
Predicted Price Plot: Optional line (default blue) overlaying the ML-predicted price for visual comparison with actual price action.
Alerts: Notifications for high/low Frahm Volatility (≥8 or ≤3) and QQE Bias crosses (bullish/bearish momentum shifts).
Main Table Metrics
This table focuses on predictive, positional, and macro insights:
ML-Predicted Price: A linear regression forecast using normalized price, volume, and RSI over a customizable lookback (default 500 bars). Gradient scales from low (red) to high (green) relative to the current price ± threshold (default 100 points).
Deviation %: Percentage difference between current price and predicted price. Gradient highlights extremes (±0.5% default threshold), signaling potential overextensions.
VWAP Deviation %: Percentage difference from Volume Weighted Average Price (VWAP). Gradient indicates if price is above (green) or below (red) fair value (±0.5% default).
FRED UNRATE % Change: Percentage change in U.S. unemployment rate (via FRED data). Cell turns red for increases (economic weakness), green for decreases (strength), gray if zero or disabled.
Open Interest: Total open MESM2 futures contracts. Gradient scales from low (red) to high (green) up to a hardcoded 300,000 threshold, reflecting market participation.
COT Commercial Long/Short: Weekly Commitment of Traders data for commercial positions. Long cell green if longs > shorts (bullish institutional sentiment); Short cell red if shorts > longs (bearish); gray otherwise.
New Metrics Table Metrics
This table emphasizes technical momentum and volatility, with arrows for quick bias assessment:
QQE Bias: Smoothed RSI vs. trailing stop (default length 14, factor 4.236, smooth 5). Green for bullish (RSI > stop, ↑ arrow), red for bearish (RSI < stop, ↓ arrow), gray for neutral.
RSI: Relative Strength Index (default period 14). Gradient from oversold (red, <30 + threshold offset, ↓ arrow if ≤40) to overbought (green, >70 - offset, ↑ arrow if ≥60).
ATR Volatility: Score (1–20) based on Average True Range (default period 14, lookback 50). High scores (green, ↑ if ≥15) signal swings; low (red, ↓ if ≤5) indicate calm.
ADX Trend: Average Directional Index (default period 14). Gradient from weak (red, ↓ if ≤0.25×25 threshold) to strong trends (green, ↑ if ≥0.75×25).
Volume Momentum: Score (1–20) comparing current to historical volume (lookback 50). High (green, ↑ if ≥15) suggests pressure; low (red, ↓ if ≤5) implies weakness.
Frahm Volatility: Score (1–20) from true range over a window (default 24 hours, multiplier 9). Dynamic gradient (green/red/yellow); ↑ if ≥7.5, ↓ if ≤2.5.
Frahm Avg Candle (Ticks): Average candle size in ticks over the window. Blue gradient (or dynamic green/red/yellow); ↑ if ≥0.75 percentile, ↓ if ≤0.25.
Arrows trigger on metric-specific logic (e.g., RSI ≥60 for ↑), providing directional cues without strict color ties.
Customization Options
Adapt the indicator to your strategy:
ML Inputs: Lookback (10–5000 bars) and RSI period (2+) for prediction sensitivity—shorter for volatility, longer for trends.
Timeframes: Individual per metric (e.g., 1H for QQE Bias to match higher frames; blank for chart timeframe).
Thresholds: Adjust gradients and arrows (e.g., Deviation 0.1–5%, ADX 0–100, RSI overbought/oversold).
QQE Settings: Length, factor, and smooth for fine-tuned momentum.
Data Toggles: Enable/disable FRED, Open Interest, COT for focus (e.g., disable macro for pure intraday).
Frahm Options: Window hours (1+), scale multiplier (1–10), dynamic colors for avg candle.
Plot/Table: Line color, positions, gradients, and visibility.
Ideal Use Case
Perfect for MESM2 scalpers and trend traders. Use the Main Table for entry confirmation via predicted deviations and institutional positioning. Leverage the New Metrics Table arrows for short-term signals—enter bullish on green consensus (all ↑), avoid chop on low volatility. Set alerts to catch shifts without constant monitoring.
Why It's Valuable
Info Table V1 consolidates diverse metrics into actionable visuals, answering critical questions: Is price mispriced? Is momentum aligning? Is volatility manageable? With real-time updates, consensus highlights, and extensive customization, it enhances precision in fast markets, reducing guesswork for confident trades.
Note: Optimized for futures; some metrics (OI, COT) unavailable on non-futures symbols. Test on demo accounts. No financial advice—use at your own risk.
The provided script reuses open-source elements from TradingView's Color Library and LuxAlgo's QQE Weighted Oscillator, as noted in the script comments and description. Credits are appropriately given in both the description and code comments, satisfying the requirement for attribution.
Regarding significant improvements and proportion:
The QQE logic comprises approximately 15 lines of code in a script exceeding 400 lines, representing a small proportion (<5%).
Adaptations include integration with multi-timeframe support via request.security, user-customizable inputs for length, factor, and smooth, and application within a broader table-based indicator for momentum bias display (with color gradients, arrows, and alerts). This extends the original QQE beyond standalone oscillator use, incorporating it as one of seven metrics in the New Metrics Table for confluence analysis (e.g., consensus highlighting when all metrics align). These are functional enhancements, not mere stylistic or variable changes.
The Color Library usage is via official import (import TradingView/Color/1 as Color), leveraging built-in gradient functions without copying code, and applied to enhance visual interpretation across multiple metrics.
The script complies with the rules: reused code is minimal, significantly improved through integration and expansion, and properly credited. It qualifies for open-source publication under the Mozilla Public License 2.0, as stated.
IDKFAIDKFA - Advanced Order Blocks & Volume Profile with Market Structure Analysis
Why IDKFA?
Named after the legendary DOOM cheat code that gives players "all weapons and full ammo," IDKFA provides traders with a comprehensive arsenal of market analysis tools. Just as the cheat code arms players with everything needed for combat, this indicator equips traders with essential market structure tools: Order Blocks, Volume Profile, LVN/HVN areas, Fibonacci retracements, and intelligent buy/sell signals - all in one unified system.
Core Features
Order Blocks Detection
Automatically identifies institutional order blocks using pivot high/low analysis
Extends blocks dynamically until price interaction occurs
Bullish blocks (demand zones) and bearish blocks (supply zones)
Customizable opacity and extend functionality
Advanced Volume Profile
Real-time volume profile calculation for multiple session types
Point of Control (POC), Value Area High (VAH), and Value Area Low (VAL)
Mode 1: Side-by-side bull/bear volume display
Mode 2: Overlapped volume display with percentage analysis
Shows buying vs selling pressure at each price level
LVN/HVN Area Detection
Low Volume Nodes (LVN): Areas below VAL where price moves quickly
High Volume Nodes (HVN): Areas above VAH with strong resistance
NPOC (Naked Point of Control): Single print areas within Value Area
Volume-based gradient coloring shows relative activity levels
Smart Fibonacci Retracements
Auto-detects trend direction for proper fibonacci orientation
Dynamic color coding: Red levels in uptrends, Gold in downtrends
Special 88.6% level turns lime green in downtrends
Key levels: 23.6%, 38.2%, 50%, 61.8%, 65%, 78.6%, 88.6%
Intelligent Signal System
Works best on higher timeframes
Identifies high-probability reversal setups at key levels
Buy signals: Large bearish rejection followed by bullish reclaim
Sell signals: Large bullish rejection followed by bearish breakdown
Signals only trigger near significant support/resistance areas
Signal Analysis & Usage Guidelines
Buy Signal Mechanics
The buy signal triggers when:
Previous candle shows significant bearish movement (minimum ATR multiplier)
Current candle reclaims a configurable percentage of the previous candle's range
Price is near a key support level (order blocks, fibonacci, volume levels)
Sell Signal Mechanics
The sell signal triggers when:
Previous candle shows significant bullish movement (minimum ATR multiplier)
Current candle rejects below a configurable percentage of the previous candle's range
Price is near a key resistance level (order blocks, fibonacci, volume levels)
When to TAKE Signals
High Probability Buy Signals:
Signal appears AT or BELOW the VAL (Value Area Low)
Signal occurs at bullish order block confluence
Price is in LVN area below VAL (momentum acceleration zone)
Signal aligns with fibonacci 61.8% or 78.6% support
Multiple session POC levels provide support confluence
Previous session's VAL acting as current support
High Probability Sell Signals:
Signal appears AT or ABOVE the VAH (Value Area High)
Signal occurs at bearish order block confluence
Price is in HVN area above VAH (heavy resistance zone)
Signal aligns with fibonacci 61.8% or 78.6% resistance
Multiple session POC levels provide resistance confluence
Previous session's VAH acting as current resistance
When to AVOID Signals
Avoid Buy Signals When:
Signal appears ABOVE the VAH (buying into resistance)
Price is in HVN red zones (high volume resistance areas)
No clear support structure below current price
Volume profile shows heavy selling pressure (high bear percentages)
Signal occurs during low-volume periods between major sessions
Multiple bearish order blocks exist below current price
Avoid Sell Signals When:
Signal appears BELOW the VAL (selling into support)
Price is in LVN green zones (momentum could continue)
No clear resistance structure above current price
Volume profile shows heavy buying pressure (high bull percentages)
Signal occurs during Asian session ranges without clear direction
Multiple bullish order blocks exist above current price
Volume Profile Context for Signals
Understanding Bull/Bear Percentages:
70%+ Bull dominance at a level = Strong support expected
70%+ Bear dominance at a level = Strong resistance expected
50/50 Split = Neutral zone, less predictable
Use percentages to gauge conviction behind moves
POC (Point of Control) Interactions:
Signals above POC in uptrend = Higher probability
Signals below POC in downtrend = Higher probability
Signals against POC bias require extra confirmation
POC often acts as magnetic level for price return
Trading Strategies
Strategy 1: VAL/VAH Bounce Strategy
Wait for price to approach VAL (support) or VAH (resistance)
Look for signal confirmation at these critical levels
Enter with tight stops beyond the Value Area
Target opposite boundary or next session's levels
Strategy 2: Order Block + Volume Confluence
Identify order block alignment with VAL/VAH
Wait for signal within the confluence zone
Enter on signal with stop beyond order block
Use LVN areas as acceleration zones for targets
Strategy 3: LVN/HVN Strategy
LVN (Green) Areas: "Go Zones" - expect quick price movement through low volume
HVN (Red) Areas: "Stop Zones" - expect resistance and potential reversals
NPOC Areas: "Fill Zones" - price often returns to fill single print gaps
Strategy 4: Multi-Session Analysis
Use Daily/Weekly for major structure context
Use 4H for intermediate levels
Use 1H for precise entry timing
Ensure all timeframes align before taking signals
Strategy 5: Fibonacci + Volume Profile
Buy signals at 61.8% or 78.6% fibonacci near VAL
Sell signals at 61.8% or 78.6% fibonacci near VAH
Use 88.6% level as final support/resistance before major moves
50% level often aligns with POC for confluence
Signal Quality Assessment
Grade A Signals (Highest Probability):
Signal at VAL/VAH with order block confluence
Fibonacci level alignment (61.8%, 78.6%)
Volume profile shows 70%+ dominance in signal direction
Multiple timeframe structure alignment
Signal occurs during high-volume sessions (London/NY)
Grade B Signals (Moderate Probability):
Signal near POC with some confluence
Fibonacci 50% or 38.2% alignment
Mixed volume profile readings (50-70% dominance)
Some timeframe alignment present
Signal during overlap sessions
Grade C Signals (Lower Probability):
Signal with minimal confluence
Weak fibonacci alignment or none
Volume profile neutral or against signal
Conflicting timeframe signals
Signal during low-volume periods
Risk Management Guidelines
Position Sizing Based on Signal Quality:
Grade A: Standard position size
Grade B: Reduced position size (50-75%)
Grade C: Minimal position size (25%) or skip entirely
Stop Loss Placement:
Beyond order block boundaries
Outside Value Area (VAL/VAH)
Below/above fibonacci confluence levels
Account for session volatility ranges
Profit Targets:
First target: Opposite VAL/VAH boundary
Second target: Next session's key levels
Final target: Major order blocks or fibonacci extensions
Credits & Attribution
Original components derived from:
Market Sessions & Volume Profile by © Leviathan (Mozilla Public License 2.0)
Volume Profile elements inspired by @LonesomeTheBlue's volume profile script
Pivot Order Blocks by TradingWolf / © MensaTrader (Mozilla Public License 2.0)
Auto Fibonacci Retracement code (public domain)
Significant enhancements and modifications include:
Advanced LVN/HVN detection and visualization
Bull/Bear percentage analysis for Mode 2/3
Comprehensive alert system with market context
Integrated buy/sell signals at key levels
Performance optimizations and extended session support
Enhanced Mode 2/3 with percentage pressure analysis
Important Disclaimers
This indicator is a technical analysis tool designed for educational purposes. It does not provide financial advice, investment recommendations, or trading signals that guarantee profits. All trading involves substantial risk of loss, and past performance does not guarantee future results. Users should conduct their own research, understand the risks involved, and consider consulting with qualified financial advisors before making trading decisions. The signals and analysis provided are based on historical price patterns and volume data, which may not predict future market movements accurately.
Best Practices
Never trade signals blindly - always consider volume profile context
Wait for confluence between multiple tools before entering
Respect the Value Area - avoid buying above VAH or selling below VAL
Use session context - Asian ranges vs London/NY breakouts
Practice proper risk management - position size based on signal quality
Understand the bigger picture - use multiple timeframes for context
Remember: Like the IDKFA cheat code, having all the tools doesn't guarantee success. The key is learning to use them together effectively and understanding when NOT to take a signal is often more important than knowing when to take one.
Open Range Breakout (ORB) with Alerts
🚀 ChartsAlgo – Open Range Breakout (ORB) with Alerts
The Open Range Breakout (ORB) Indicator by ChartsAlg is designed for intraday traders looking to capitalize on price movements after the market’s opening range. This tool is especially effective for futures (MNQ, MES) and high-volatility stocks or crypto where initial volatility sets the tone for the session.
This indicator identifies a user-defined opening range window, plots the high/low lines of that range, and visually alerts users when price breaks out above or below the range — with options to customize breakout repetitions, background fill, and alerts.
💡 What is an Open Range Breakout (ORB)?
The opening range represents the high and low established during the first few minutes of the trading session — usually 15 or 30 minutes. Many intraday strategies are based on the idea that breaking out of this initial range often signals strong momentum and trend continuation.
Traders often enter:
Long when price breaks above the range high.
Short when price breaks below the range low.
⚙️ How It Works
You define a session window (e.g., 09:30–09:45 EST).
The indicator tracks the high and low during this time.
Once the session ends, the high and low become your range breakout levels.
The indicator then:
Plots lines for visual clarity
Optionally fills background between the range
Triggers breakout signals if price crosses the levels
Provides alerts when breakouts occur
🛠️ Settings Breakdown
🔹 Session Settings
Range Session: Set your preferred window (e.g., 0930–0945). Can be premarket, first 30 mins, or any custom time.
Time zone: Use "America/New York" for EST (default) or change to "GMT+0" for international traders.
🔹 Breakout Settings
Bullish Breakout Signals: Number of allowed breakout alerts above the range.
Bearish Breakout Signals: Number of allowed breakout alerts below the range.
This prevents repeated alerts once breakout has been confirmed.
🔹 Display Settings
Show Background Fill: Fills area between high/low of the range for easier visual analysis.
Show Breakout Signals: Triangle markers plotted on the chart when breakouts happen.
Only Show Today’s Range: Keeps the chart clean by showing only the most current day’s range.
🔹 Color Settings
Range High/Low Line Colors: Choose any color for clarity.
Range Fill Color: Customize the highlight area for your chart style.
📊 Chart Features
Range High/Low Lines: Automatically plotted after range session ends.
Visual Fill Box: Optional background shading between the opening range.
Triangle Breakout Markers: Appear at the breakout candle.
Alerts: Can be used with TradingView’s alert system to notify you of breakouts in real-time.
🔔 Alerts
Two alert conditions are built in:
Bullish Breakout: Triggers when price breaks above the high of the range.
Bearish Breakout: Triggers when price breaks below the low of the range.
Example Alert Message:
📈 “Bullish Breakout above Open Range on AAPL!”
To activate:
Click “🔔 Alerts” on TradingView.
Set condition to this script.
Choose “ORB Breakout Up” or “ORB Breakout Down”.
Choose alert frequency and notification method.
⚠️ DISCLAIMER
ChartsAlgo tools are for informational and educational purposes only.
They are not financial advice or signals. Past performance does not guarantee future results. Use at your own risk and always implement solid risk management.
By using this indicator, you agree that you are solely responsible for any trades or decisions made based on the information provided.
OBV ATR Strategy (OBV Breakout Channel) bas20230503ผมแก้ไขจาก OBV+SMA อันเดิม ของเดิม ดูที่เส้น SMA สองเส้นตัดกันมั่นห่วยแตกสำหรับที่ผมลองเทรดจริง และหลักการเบรค ได้แรงบันดาลใจ ATR จาก เทพคอย ที่ใช้กับราคา แต่นี้ใช้กับ OBV แทน
และผมใช้เจมินี้ เพื่อแก้ ให้ เป็น strategy เพื่อเช็คย้อนหลังได้ง่ายกว่าเดิม
หลักการง่ายคือถ้ามันขึ้น มันจะขึ้นเรื่อยๆ
เขียน แบบสุภาพ (น่าจะอ่านได้ง่ายกว่าผมเขียน)
สคริปต์นี้ได้รับการพัฒนาต่อยอดจากแนวคิด OBV+SMA Crossover แบบดั้งเดิม ซึ่งจากการทดสอบส่วนตัวพบว่าประสิทธิภาพยังไม่น่าพอใจ กลยุทธ์ใหม่นี้จึงเปลี่ยนมาใช้หลักการ "Breakout" ซึ่งได้รับแรงบันดาลใจมาจากการใช้ ATR สร้างกรอบของราคา แต่เราได้นำมาประยุกต์ใช้กับ On-Balance Volume (OBV) แทน นอกจากนี้ สคริปต์ได้ถูกแปลงเป็น Strategy เต็มรูปแบบ (โดยความช่วยเหลือจาก Gemini AI) เพื่อให้สามารถทดสอบย้อนหลัง (Backtest) และประเมินประสิทธิภาพได้อย่างแม่นยำ
หลักการของกลยุทธ์: กลยุทธ์นี้ทำงานบนแนวคิดโมเมนตัมที่ว่า "เมื่อแนวโน้มได้เกิดขึ้นแล้ว มีโอกาสที่มันจะดำเนินต่อไป" โดยจะมองหาการทะลุของพลังซื้อ-ขาย (OBV) ที่แข็งแกร่งเป็นพิเศษเป็นสัญญาณเข้าเทร
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สคริปต์นี้เป็นกลยุทธ์ (Strategy) ที่ใช้ On-Balance Volume (OBV) ซึ่งเป็นอินดิเคเตอร์ที่วัดแรงซื้อและแรงขายสะสม แทนที่จะใช้การตัดกันของเส้นค่าเฉลี่ย (SMA Crossover) ที่เป็นแบบพื้นฐาน กลยุทธ์นี้จะมองหาการ "ทะลุ" (Breakout) ของพลัง OBV ออกจากกรอบสูงสุด-ต่ำสุดของตัวเองในรอบที่ผ่านมา
สัญญาณกระทิง (Bull Signal): เกิดขึ้นเมื่อพลังการซื้อ (OBV) แข็งแกร่งจนสามารถทะลุจุดสูงสุดของตัวเองในอดีตได้ บ่งบอกถึงโอกาสที่แนวโน้มจะเปลี่ยนเป็นขาขึ้น
สัญญาณหมี (Bear Signal): เกิดขึ้นเมื่อพลังการขาย (OBV) รุนแรงจนสามารถกดดันให้ OBV ทะลุจุดต่ำสุดของตัวเองในอดีตได้ บ่งบอกถึงโอกาสที่แนวโน้มจะเปลี่ยนเป็นขาลง
ส่วนประกอบบนกราฟ (Indicator Components)
เส้น OBV
เส้นหลัก ที่เปลี่ยนเขียวเป็นแดง เป็นทั้งแนวรับและแนวต้าน และ จุด stop loss
เส้นนี้คือหัวใจของอินดิเคเตอร์ ที่แสดงถึงพลังสะสมของ Volume
เมื่อเส้นเป็นสีเขียว (แนวรับ): จะปรากฏขึ้นเมื่อกลยุทธ์เข้าสู่ "โหมดกระทิง" เส้นนี้คือระดับต่ำสุดของ OBV ในอดีต และทำหน้าที่เป็นแนวรับไดนามิก
เมื่อเส้นกลายเป็นสีแดงสีแดง (แนวต้าน): จะปรากฏขึ้นเมื่อกลยุทธ์เข้าสู่ "โหมดหมี" เส้นนี้คือระดับสูงสุดของ OBV ในอดีต และทำหน้าที่เป็นแนวต้านไดนามิก
สัญลักษณ์สัญญาณ (Signal Markers):
Bull 🔼 (สามเหลี่ยมขึ้นสีเขียว): คือสัญญาณ "เข้าซื้อ" (Long) จะปรากฏขึ้น ณ จุดที่ OBV ทะลุขึ้นไปเหนือกรอบด้านบนเป็นครั้งแรก
Bear 🔽 (สามเหลี่ยมลงสีแดง): คือสัญญาณ "เข้าขาย" (Short) จะปรากฏขึ้น ณ จุดที่ OBV ทะลุลงไปต่ำกว่ากรอบด้านล่างเป็นครั้งแรก
วิธีการใช้งาน (How to Use)
เพิ่มสคริปต์นี้ลงบนกราฟราคาที่คุณสนใจ
ไปที่แท็บ "Strategy Tester" ด้านล่างของ TradingView เพื่อดูผลการทดสอบย้อนหลัง (Backtest) ของกลยุทธ์บนสินทรัพย์และไทม์เฟรมต่างๆ
ใช้สัญลักษณ์ "Bull" และ "Bear" เป็นตัวช่วยในการตัดสินใจเข้าเทรด
ข้อควรจำ: ไม่มีกลยุทธ์ใดที่สมบูรณ์แบบ 100% ควรใช้สคริปต์นี้ร่วมกับการวิเคราะห์ปัจจัยอื่นๆ เช่น โครงสร้างราคา, แนวรับ-แนวต้านของราคา และการบริหารความเสี่ยง (Risk Management) ของตัวคุณเองเสมอ
การตั้งค่า (Inputs)
SMA Length 1 / SMA Length 2: ใช้สำหรับพล็อตเส้นค่าเฉลี่ยของ OBV เพื่อดูเป็นภาพอ้างอิง ไม่มีผลต่อตรรกะการเข้า-ออกของ Strategy อันใหม่ แต่มันเป็นของเก่า ถ้าชอบ ก็ใช้ได้ เมื่อ SMA สองเส้นตัดกัน หรือตัดกับเส้น OBV
High/Low Lookback Length: (ค่าพื้นฐาน30/แก้ตรงนี้ให้เหมาะสมกับ coin หรือหุ้น ตามความผันผวน ) คือระยะเวลาที่ใช้ในการคำนวณกรอบสูงสุด-ต่ำสุดของ OBV
ค่าน้อย: ทำให้กรอบแคบลง สัญญาณจะเกิดไวและบ่อยขึ้น แต่อาจมีสัญญาณหลอก (False Signal) เยอะขึ้น
ค่ามาก: ทำให้กรอบกว้างขึ้น สัญญาณจะเกิดช้าลงและน้อยลง แต่มีแนวโน้มที่จะเป็นสัญญาณที่แข็งแกร่งกว่า
แน่นอนครับ นี่คือคำแปลฉบับภาษาอังกฤษที่สรุปใจความสำคัญ กระชับ และสุภาพ เหมาะสำหรับนำไปใช้ในคำอธิบายสคริปต์ (Description) ของ TradingView ครับ
---Translate to English---
OBV Breakout Channel Strategy
This script is an evolution of a traditional OBV+SMA Crossover concept. Through personal testing, the original crossover method was found to have unsatisfactory performance. This new strategy, therefore, uses a "Breakout" principle. The inspiration comes from using ATR to create price channels, but this concept has been adapted and applied to On-Balance Volume (OBV) instead.
Furthermore, the script has been converted into a full Strategy (with assistance from Gemini AI) to enable precise backtesting and performance evaluation.
The strategy's core principle is momentum-based: "once a trend is established, it is likely to continue." It seeks to enter trades on exceptionally strong breakouts of buying or selling pressure as measured by OBV.
Core Concept
This is a Strategy that uses On-Balance Volume (OBV), an indicator that measures cumulative buying and selling pressure. Instead of relying on a basic Simple Moving Average (SMA) Crossover, this strategy identifies a "Breakout" of the OBV from its own highest-high and lowest-low channel over a recent period.
Bull Signal: Occurs when the buying pressure (OBV) is strong enough to break above its own recent highest high, indicating a potential shift to an upward trend.
Bear Signal: Occurs when the selling pressure (OBV) is intense enough to push the OBV below its own recent lowest low, indicating a potential shift to a downward trend.
On-Screen Components
1. OBV Line
This is the main indicator line, representing the cumulative volume. Its color changes to green when OBV is rising and red when it is falling.
2. Dynamic Support & Resistance Line
This is the thick Green or Red line that appears based on the strategy's current "mode." This line serves as a dynamic support/resistance level and can be used as a reference for stop-loss placement.
Green Line (Support): Appears when the strategy enters "Bull Mode." This line represents the lowest low of the OBV in the recent past and acts as dynamic support.
Red Line (Resistance): Appears when the strategy enters "Bear Mode." This line represents the highest high of the OBV in the recent past and acts as dynamic resistance.
3. Signal Markers
Bull 🔼 (Green Up Triangle): This is the "Long Entry" signal. It appears at the moment the OBV first breaks out above its high-low channel.
Bear 🔽 (Red Down Triangle): This is the "Short Entry" signal. It appears at the moment the OBV first breaks down below its high-low channel.
How to Use
Add this script to the price chart of your choice.
Navigate to the "Strategy Tester" panel at the bottom of TradingView to view the backtesting results for the strategy on different assets and timeframes.
Use the "Bull" and "Bear" signals as aids in your trading decisions.
Disclaimer: No strategy is 100% perfect. This script should always be used in conjunction with other forms of analysis, such as price structure, key price-based support/resistance levels, and your own personal risk management rules.
Inputs
SMA Length 1 / SMA Length 2: These are used to plot moving averages on the OBV for visual reference. They are part of the legacy logic and do not affect the new breakout strategy. However, they are kept for traders who may wish to observe their crossovers for additional confirmation.
High/Low Lookback Length: (Most Important Setting) This determines the period used to calculate the highest-high and lowest-low OBV channel. (Default is 30; adjust this to suit the asset's volatility).
A smaller value: Creates a narrower channel, leading to more frequent and faster signals, but potentially more false signals.
A larger value: Creates a wider channel, leading to fewer and slower signals, which are likely to be more significant.
Opening Range 15 minThis indicator highlights the Opening Range (OR) for the first 15 minutes (9:30–9:45 AM EST). It visually plots high/low lines and a shaded box to define this range, helping traders identify key intraday levels for potential breakout or rejection scenarios. The script also provides optional overlays for the Previous Day’s High/Low and the Extended Hours High/Low, offering a complete context for day trading setups.
Main Features:
Opening Range Detection – Automatically calculates and draws the high/low of the 9:30–9:45 AM session.
Visual Enhancements – Includes customizable lines, shaded boxes, and labels to mark the OR high (ORH) and low (ORL) levels.
Previous Day High/Low (Optional) – Plots and labels the previous day's high and low for reference during current day trading.
Extended Hours High/Low (Optional, when ETH enabled) – Displays overnight session levels for added insight into early volatility (4:00 AM to 9:30 AM EST).
User Customization – Easily adjust colors, label styles, and visibility for all plotted levels and regions.
Algo Structure [ValiantTrader_]Explanation of the "Algo Structure" Trading Indicator
This Pine Script indicator, created by ValiantTrader_, is a multi-timeframe swing analysis tool that helps traders identify key price levels and market structure across different timeframes. Here's how it works and how traders can use it:
Core Components
1. Multi-Timeframe Swing Analysis
The indicator tracks swing highs and lows across:
The current chart timeframe
A higher timeframe (weekly by default)
An even higher timeframe (monthly by default)
2. Swing Detection Logic
Current timeframe swings: Identified when price makes a 3-bar high/low pattern
Higher timeframe swings: Uses the highest high/lowest low of the last 3 bars on those timeframes
3. Visual Elements
Horizontal lines marking swing points
Labels showing the timeframe and percentage distance from current price
An information table summarizing key levels
How Traders Use This Indicator
1. Identifying Key Levels
The indicator draws recent swing highs (red) and swing lows (green)
These levels act as potential support/resistance areas
Traders watch for price reactions at these levels
2. Multi-Timeframe Analysis
By seeing swings from higher timeframes (weekly, monthly), traders can:
Identify more significant support/resistance zones
Understand the broader market context
Spot confluence areas where multiple timeframes align
3. Measuring Price Distance
The percentage display shows how far current price is from each swing level
Helps assess potential reward/risk at current levels
Shows volatility between swings (wider % = more volatile moves)
4. Table Summary
The info table provides a quick reference for:
Exact price levels of swings
Percentage ranges between highs and lows
Comparison across timeframes
5. Trading Applications
Breakout trading: When price moves beyond a swing high/low
Mean reversion: Trading bounces between swing levels
Trend confirmation: Higher highs/lows in multiple timeframes confirm trends
Support/resistance trading: Entering trades at swing levels with other confirmation
Customization Options
Traders can adjust:
The higher timeframes analyzed
Whether to show the timeframe labels
Whether to display swing levels
Whether to show the info table
The indicator also includes price alerts for new swing highs/lows on the current timeframe, allowing traders to get notifications when market structure changes.
This tool is particularly valuable for traders who incorporate multi-timeframe analysis into their strategy, helping them visualize important price levels across different time perspectives
Market Sentiment Index US Top 40 [Pt]▮Overview
Market Sentiment Index US Top 40 [Pt} shows how the largest US stocks behave together. You pick one simple measure—High Low breakouts, Above Below moving average, or RSI overbought/oversold—and see how many of your chosen top 10/20/30/40 NYSE or NASDAQ names are bullish, neutral, or bearish.
This tool gives you a quick view of broad-market strength or weakness so you can time trades, confirm trends, and spot hidden shifts in market sentiment.
▮Key Features
► Three Simple Modes
High Low Index: counts stocks making new highs or lows over your lookback period
Above Below MA: flags stocks trading above or below their moving average
RSI Sentiment: marks overbought or oversold stocks and plots a small histogram
► Universe Selection
Top 10, 20, 30, or 40 symbols from NYSE or NASDAQ
Option to weight by market cap or treat all symbols equally
► Timeframe Choice
Use your chart’s timeframe or any intraday, daily, weekly, or monthly resolution
► Histogram Smoothing
Two optional moving averages on the sentiment bars
Markers show when the faster average crosses above or below the slower one
► Ticker Table
Optional on-chart table showing each ticker’s state in color
Grid or single-row layout with adjustable text size and color settings
▮Inputs
► Mode and Lookback
Pick High Low, Above Below MA, or RSI Sentiment
Set lookback length (for example 10 bars)
If using Above Below MA, choose the moving average type (EMA, SMA, etc.)
► Universe Setup
Market: NYSE or NASDAQ
Number of symbols: 10, 20, 30, or 40
Weights: on or off
Timeframe: blank to match chart or pick any other
► Moving Averages on Histogram
Enable fast and slow averages
Set their lengths and types
Choose colors for averages and markers
► Table Options
Show or hide the symbol table
Select text size: tiny, small, or normal
Choose layout: grid or one-row
Pick colors for bullish, neutral, and bearish cells
Show or hide exchange prefixes
▮How to Read It
► Sentiment Bars
Green means bullish
Red means bearish
Near zero means neutral
► Zero Line
Separates bullish from bearish readings
► High Low Line (High Low mode only)
Smooth ratio of highs versus lows over your lookback
► MA Crosses
Fast MA above slow MA hints rising breadth
Fast MA below slow MA hints falling breadth
► Ticker Table
Each cell colored green, gray, or red for bull, neutral, or bear
▮Use Cases
► Confirm Market Trends
Early warning when price makes highs but breadth is weak
Catch rallies when breadth turns strong while price is flat
► Spot Sector Rotation
Switch between NYSE and NASDAQ to see which group leads
Watch tech versus industrial breadth to track money flow
► Filter Trade Signals
Enter longs only when breadth is bullish
Consider shorts when breadth turns negative
► Combine with Other Indicators
Use RSI Sentiment with trend tools to spot overextended moves
Add volume indicators in High Low mode for breakout confirmation
► Timeframe Analysis
Daily for big-picture bias
Intraday (15-min) for precise entries and exits
Forex Session + Volume Profile [RunRox]📊 Forex Session + Volume Profile is built especially for traders who work with intra-session liquidity concepts or any strategy that needs a clear visual of trading sessions and the liquidity inside them.
Our team created this indicator to give you better session visibility, flexible session styling, and extra tools that help you navigate the market more easily.
📌 Features:
6 fully customizable sessions
Kill Zone (the high-impact trading window)
Volume Profile for each session
POC / VAL / VAH / LVN levels (Point of Control, Value Area Low, Value Area High, Low Volume Node)
PDH / PDL levels (Previous Day High / Low)
PWH / PWL levels (Previous Week High / Low)
NYM level (New York Market level)
Active sessions table
5 style options for each session
All of this gives you the flexibility to set up exactly the layout you need for your trading. Below, you’ll find a more detailed look at each feature.
🗓️ 6 CUSTOMIZABLE SESSION
The indicator includes six sessions that you can fully customize to fit your needs—everything from naming each session and choosing line colors to adjusting opacity, showing the volume profile, or even turning off a session entirely if you don’t need it.
Plus, you can pick different display styles for each session. As shown in the screenshot below, there are five style options you can apply individually to every session.
5 Style Options for Sessions
BOX
AREA
ZONES
LINES
CURVED
These styles can be customized for each session individually to help you highlight the sessions you care about on your chart. Example below
📢 VOLUME PROFILE
We’ve also integrated a Volume Profile into the indicator to pinpoint important levels on the chart. On top of that, we’ve added extra volume-based levels. Below, you’ll find the settings and a visual demo of how it appears on your chart.
To identify optimal entry points, you can use the following key reference levels:
POC (Point of Control)
VAL (Value Area Low)
VAH (Value Area High)
LVN (Low Volume Node)
You can also customize colors and line styles, or hide any levels you don’t need on your chart.
📐 ADDITIONAL LEVELS
You can display the following levels on your chart:
NYM (New York Market)
PDH (Previous Day High)
PDL (Previous Day Low)
PWH (Previous Week High)
PWL (Previous Week Low)
All of these are fully customizable with color selection and the option to extend lines into the next period.
💹 ACTIVE SESSION TABLE
The active sessions table helps you quickly identify the trading times for the sessions you care about. It’s fully customizable, with options to choose border and background colors for the table itself.
🟠 USAGE
This indicator is highly versatile: use it to simply mark trading sessions on your chart, set up the Kill Zone at your chosen time, or identify the context of the previous session by its most traded range levels. All of this makes the indicator an invaluable tool for any trader!
Opening Range and Market BoundariesOpening Range and Market Boundaries
This versatile and insightful indicator combines two powerful concepts frequently used by professional traders: Opening Range Analysis and Market Boundaries derived from previous high/low levels. It is specifically designed to support intraday trading strategies and helps you identify key price zones for entries, exits, and breakout confirmations.
🔍 Features & Utility
1. Opening Range Box
What it does:
Highlights the high and low of the first candle after market open (9:15 AM IST) with a shaded box. This box spans the full trading session, from 9:15 AM to 3:30 PM, representing the key price range where the initial balance is formed.
Timeframe Compatibility:
The Opening Range box is optimized for 1-minute to 1-hour charts. It is most effective on lower timeframes (1m, 5m, 15m, 30m) where intraday price movements and breakout patterns can be clearly observed.
Usage Tips:
Breakouts above or below the Opening Range box can signal potential directional bias for the rest of the trading day.
Price consolidating within the range may indicate a choppy or range-bound session.
Works well with volume and momentum indicators for confirmation.
2. Market Boundaries
What it does:
Plots horizontal lines at:
Previous Day High/Low
Previous Week High/Low
Previous Month High/Low
Why it matters:
These levels act as natural support and resistance zones, and are commonly watched by institutional traders, making them crucial for:
Spotting reversals or breakouts
Planning stop-loss and target zones
Avoiding trades around high-rejection areas
Customization Options:
Toggle ON/OFF for Daily, Weekly, and Monthly levels.
Independent colors and line thickness for each level, enabling you to distinguish between different timeframes easily.
🛠️ How to Use Effectively
Use during market open:
Switch to a 5-minute or 15-minute chart during the first few candles of the session. Observe the Opening Range box formation and plan trades based on breakout direction.
Confluence Trading:
Look for price action near previous session highs/lows in confluence with the Opening Range box edges. These intersections often become high-probability zones for breakouts or reversals.
Session Preparation:
Before the market opens, analyze where the price is relative to past high/low boundaries. If it's near a weekly/monthly level, be cautious — those areas can cause whipsaws or false breakouts.
Avoid low-volume breakouts:
Use this indicator in conjunction with volume tools or price action confirmation to validate the strength of a move outside the Opening Range or Market Boundaries.
📌 Summary
This indicator is designed for intraday traders, scalpers, and swing traders who want a reliable structure to guide their decisions. It visually marks the opening balance of the market and essential higher timeframe boundaries, helping you trade with discipline and precision.
[TTM] ICT Sessions & Ranges🌟 Overview 🌟
The ICT Sessions & Ranges Indicator helps traders identify key intraday price levels by marking custom session highs/lows and opening ranges.
It helps traders spot potential liquidity grabs, reversals, and breakout zones by tracking price behavior around these key areas
🌟 Session Highs & Lows – Liquidity Zones 🌟
Session highs and lows often attract price due to stop orders resting above or below them. These levels are frequently targeted during high-volatility moves.
🔹 Asia Session
- Usually ranges in low volatility.
- Highs/lows often get swept during early London.
- Price may raid these levels, then reverse.
🔹 London Session
- First major volatility of the day.
- Highs/lows often tested or swept in New York.
- Commonly forms the day’s true high or low.
🌟 Opening Range Concepts 🌟
The Opening Range is the first 15, 30, or 60 minutes of a session (e.g., New York).
The high (ORH) and low (ORL) define the market’s initial balance and key reaction levels.
🔹 Breakout Trade
- Price breaks ORH/ORL with momentum.
- Signals directional intent.
- Traders enter on the breakout, with stops inside the range.
🔹 Liquidity Raid
- Price briefly breaks ORH/ORL to trigger stops.
- Reverses after the sweep.
- Look for structure shift and entry near FVG or OB.
🌟 Customizable Settings 🌟
The indicator includes 3 configurable ranges , each with:
Start & End Time – Set any custom time window.
Display Type – Choose Box (highlight range) or Lines (mark high/low).
Color Settings – Set custom colors for boxes and lines.
🌟 Default Settings 🌟
Range 1 : 19:00–00:00 (Asia Session)
Range 2 : 01:45–05:15 (London Session)
Range 3 : 09:30–10:00 (NY Opening Range – 30m)
