CRT INTRADAY + MTF (15M/30M-12H custom) Candle Range TheoryCRT INTRADAY + MTF (15M/30M–12H) — Candle Range Theory
This indicator plots previous completed range High/Low levels for multiple time blocks, based on Candle Range Theory (CRT).
It can display:
Previous Day High / Low (CRT DAY)
Previous block High / Low for: 15M, 30M, 1H, 2H, 3H, 4H, 5H, 6H, 7H, 8H, 9H, 10H, 11H, 12H
Each block has its own color / line style / width, and optional time separators to visually mark new periods.
How it works
When a new time block starts (e.g., new 4H candle), the indicator stores the High/Low of the previous completed block and extends those levels forward on the chart.
How to use
CRT levels are commonly used as:
intraday support/resistance
liquidity reference levels
targets and invalidation points
breakout / rejection confirmation zones
Typical approach:
Watch how price reacts when returning to the previous block range.
Use confluence with structure (BOS/CHOCH), volume, or your entry model.
Settings
Turn each timeframe ON/OFF (15M → 12H)
Enable/disable separators for each timeframe
Customize line colors, widths, and styles
Optional labels with configurable size
UTC Offset to align session/day boundaries with your preferred timezone
Notes
For performance, the MTF blocks are designed for lower timeframes (≤ 60 minutes).
This indicator is a visual reference tool and does not generate trade signals.
Recommended Confluence (Optional)
This CRT tool is designed to be used as a price reference framework. For higher-quality setups, combine CRT levels with confirmation tools such as:
Crypto Radar / multi-symbol market context (trend strength, market regime, relative performance)
SETUP HMTR (risk zones, extremes, pressure zones)
Structure & price action (breakout + retest, rejection, liquidity sweep)
A common workflow:
Start with market context (risk / regime)
Mark CRT levels (previous range highs/lows)
Wait for a Setup/confirmation signal + clean price reaction at CRT
Use CRT levels as targets / invalidation / S/R
Multitimeframe
ICT CISD+FVG+OBThis script is a high-performance ICT suite designed for traders who want a professional, "noise-free" chart. It identifies core institutional patterns—Order Blocks, Fair Value Gaps, and Changes in State of Delivery (CISD)—across multiple timeframes.
The script features a proprietary Proximity Cleanup Engine that automatically deletes old or broken levels, keeping your workspace focused only on price action that is currently tradeable. It strictly follows directional delivery rules for CISD and includes a 50-candle "freshness" limit to ensure you never have to manually clear old data from your past bars.
Core Features
Intelligent CISD: Only triggers Bullish CISD on green candles and Bearish CISD on red candles.
Proximity Filter: Automatically wipes away any levels that are "miles away" from the current price.
Clean Workspace: Removes broken session highs/lows and mitigated zones instantly.
Full Customization: Toggle visibility and colors for every component via the settings menu.
MTF Target Radar [Rulph]MTF Target Radar - Multi-Timeframe Target Clustering with Machine Learning
MTF Target Radar is an advanced target projection system that analyzes trendline breakouts across multiple timeframes (Daily to Biweekly) and clusters projected targets into high-probability zones. It dynamically calculates targets from actual breakout patterns and validates them through multi-timeframe confluence and machine learning, instead of using static support/resistance or fixed Fibonacci ratios.
The system continuously tracks cluster performance (Reached / Lost / Timeout) and uses this history to improve future predictions through a transparent k-Nearest Neighbors (k-NN) logic, providing explainable adjustments to cluster quality rather than black-box scores.
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WHY COMBINE MULTI-TIMEFRAME TARGETS?
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Most target projection methods rely on a single timeframe or on arbitrary geometric ratios. MTF Target Radar is designed around three core ideas:
1. Cross-timeframe validation : A target zone where multiple higher timeframes converge (e.g., 1D, 2D, 3D, 4D, 5D, 6D, 1W, 2W) indicates a structural price magnet, where several independent trend cycles agree on a probable area of exhaustion, continuation, or reversal.
2. Dynamic projection from real patterns : Targets are computed from the geometry of each breakout (distance from the trendline to the extreme of the pattern) instead of being fixed percentages from arbitrary swing points. This makes projected levels adaptive to the actual volatility and structure of each pattern.
3. Adaptive learning : The system learns which cluster characteristics (density, strength, distance, momentum, market regime, etc.) historically lead to successful outcomes and then gently adjusts future cluster qualities in that direction.
The result is a "target radar" where the most important zones stand out because they combine: multiple timeframes, favorable structure, and a positive historical profile with similar setups.
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COMPONENT 1: TRENDLINE BREAKOUT DETECTION
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For each enabled higher timeframe (up to 8), the indicator performs the same deterministic process:
1. Swing pivot detection
It finds swing highs and lows using a configurable pivot length (default 3 bars left and right), which defines local extremes for trendline construction.
2. Trendline construction
- For bullish breakout setups (upward target clusters), it connects two descending swing highs to form a bearish trendline.
- For bearish breakout setups (downward target clusters), it connects two ascending swing lows to form a bullish trendline.
3. Breakout detection
A breakout is confirmed when the close crosses and holds beyond the trendline in the opposite direction of the preceding trend (close above a descending line for long setups, or below an ascending line for short setups), which indicates that the previous trend structure has failed.
4. Target projection
The target is measured from the internal structure of the pattern, not guessed:
For bullish (upward) targets:
- The algorithm finds the lowest low between the second pivot and the breakout.
- It computes the vertical distance from the trendline value at that bar to this lowest low.
- This distance is then projected above the breakout level to obtain an initial target.
For bearish (downward) targets, the logic is mirrored using the highest high within the pattern range.
This makes each target a direct function of how "compressed" price was before breaking out, creating geometry-driven objectives that adapt to each pattern.
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COMPONENT 2: TARGET CLUSTERING
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All individual targets from active timeframes are merged into clusters, which represent zones where multiple projected levels overlap or lie very close to each other.
Clustering logic :
- All targets are sorted by price.
- Targets within a maximum distance (MAX_CLUSTER_DISTANCE, default 1.5% of price) are merged into a single cluster.
- A cluster must contain at least MIN_CLUSTER_SIZE targets (default 2) to be considered valid and plotted.
Cluster properties include:
- Center : the average target price within the cluster.
- Size : number of contributing targets; more targets imply stronger structural agreement.
- Spread : the price width between the lowest and highest targets in the cluster.
- Timeframe composition : which timeframes contributed (e.g., "1D, 2D, 3D, 1W").
A tight cluster where many timeframes converge is treated as a stronger and more precise target than scattered levels spread widely in price.
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COMPONENT 3: QUALITY SCORING SYSTEM
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Each cluster receives a base quality score from 0 to 1, computed as a weighted combination of four dimensions:
1. Density score (weight: 0.35)
- Based on how narrow the cluster is relative to volatility.
- Uses normalized spread: cluster_spread / ATR(14).
- A smaller normalized spread leads to a higher density score.
2. Strength score (weight: 0.35)
- Depends on the number of targets and their distribution across timeframes.
- Uses a log-scaled function of cluster size and a density factor so that adding more confluences yields diminishing but still meaningful improvements.
3. Reachability score (weight: 0.20)
- Based on the distance from current price to cluster center in percent terms.
- Closer clusters are easier to reach; very distant ones are penalized unless the market and trend strongly support extended moves.
4. Momentum score (weight: 0.10)
- Analyzes the last few candles (e.g., 5 bars) using candle bodies, wicks, and short-term rate of change to determine whether current price action supports moving into the cluster.
Base quality formula :
The base quality is a convex combination:
Q_base = 0.35 × Density + 0.35 × Strength + 0.20 × Reachability + 0.10 × Momentum, with additional multiplicative penalties when reachability is too low or the overall market regime contradicts the direction of the cluster.
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COMPONENT 4: MACHINE LEARNING ADJUSTMENT
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When the ML enhancement is enabled and there is enough history, the script uses an internal k-Nearest Neighbors approach to adjust cluster quality based on what worked or failed in the past.
Feature extraction :
For each cluster, the system extracts a feature vector including:
- Base quality, distance to target, volatility, trend strength (ADX), RSI value, volume ratio, recent momentum, cluster size, density, market regime, volume trend, timeframe consistency, and price acceleration.
Neighbor search :
- Only clusters with the same direction (up or down) and with finalized outcomes (reached, lost, or timeout) are considered.
- A Lorentzian distance metric is used: sum over all features of log(1 + |difference|) multiplied by per-feature weights, so that extreme outliers do not dominate.
Graduated success scoring :
Each historical cluster stores a continuous success_score, not just 0 or 1:
- Full success when the target zone is actually reached with reasonable timing.
- Partial credit when price comes very close but slightly misses the cluster or reaches only part of it.
- Penalties when the cluster times out or price moves away strongly.
ML adjustment of quality :
The script computes an ML_probability for the active cluster by aggregating neighbors' success_score values weighted by similarity and recency. This ML-derived probability is then mixed with the base quality:
Q_adjusted = Q_base × (1 − ML_weight) + ML_probability × ML_weight,
where ML_weight increases gradually with the amount and reliability of historical data and is capped so that ML cannot completely override the base structural logic.
Additionally, performance metrics such as recent accuracy, false positives, false negatives, and total predictions are tracked to adapt how much trust is placed in ML adjustments over time.
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COMPONENT 5: TIME-TO-TARGET PREDICTION
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When time prediction is enabled, the indicator estimates how many bars it may take for price to reach the cluster. This is an experimental feature designed for context, not as a hard promise.
Base estimate :
- Uses distance to cluster and current volatility as primary inputs.
- Time is scaled differently for various asset classes (e.g., crypto vs. equities), so that fast markets do not get unrealistic long estimates and slow markets do not get unrealistically short ones.
ML refinement :
If enough successful historical clusters with similar features are available, the script:
- Filters neighbors that actually reached their targets.
- Uses their real bars_to_reach values.
- Computes a weighted average to refine the time estimate.
The final time prediction is a blend of base estimate and ML-derived value, with a confidence measure derived from the number, similarity, and recency of matching examples.
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CLUSTER STATE MACHINE
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Each cluster goes through a simple and explicit state machine:
forming → active
Once cluster quality rises above the minimum threshold, it becomes active and is displayed on the chart.
active → reached
The cluster is marked as reached when price touches at least the first target in its internal list (TP1), using direction-sensitive logic (high >= TP1 for long clusters, low <= TP1 for short clusters).
active → lost
If the underlying targets are structurally invalidated (e.g., fewer than MIN_CLUSTER_SIZE remain due to market movement), the cluster becomes lost.
active → timeout
If age exceeds MAX_CLUSTER_AGE (default 40 bars) without reaching the target, the cluster is marked as timeout, so stale setups do not stay active indefinitely.
Final states (reached, lost, timeout) are recorded with snapshots of cluster features, bars_alive, bars_to_reach, and realized P&L percentage. These records feed back into the ML history.
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HOW TO USE MTF TARGET RADAR
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Basic workflow :
1. Enable the higher timeframes that are relevant to your trading style (e.g., 1D–6D + 1W for intraday or swing trading).
2. Set Min Quality Score (MIN_QUALITY) according to your risk tolerance:
- 0.3–0.4 for aggressive,
- 0.5–0.6 for balanced,
- 0.7+ for conservative setups.
3. Optionally enable ML and time prediction once enough history is accumulated.
4. Use the trend context block (if enabled) to see whether clusters align with the dominant trend or go against it.
Reading the chart :
- Green boxes above price = upward target clusters (long objectives).
- Red boxes below price = downward target clusters (short objectives).
- Box width shows the price range of the cluster; box position shows where price is expected to gravitate.
- Labels can include: contributing timeframes, cluster center, base quality, ML-adjusted quality, distance to target, and estimated time to target when enabled.
Example entry logic :
- For a long: price is below a strong green cluster, quality > 0.6, direction aligned with the current trend, and ML-adjusted quality is not significantly lower than base quality.
- Entry can be timed using your own triggers (breakouts, pullbacks, candlestick patterns), while the cluster defines the target area rather than the exact entry.
Example exit logic :
- Take profit as price enters the cluster zone.
- Scale out around cluster center or when realized move covers your planned R-multiple.
- Exit early if the cluster flips to "lost" or if an opposite-direction high-quality cluster appears and is closer than the current one.
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WHAT MAKES MTF TARGET RADAR ORIGINAL
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MTF Target Radar is not a simple overlay of trendlines and support/resistance; it implements a full pipeline: pattern-based target projection, cross-timeframe clustering, quality scoring, and machine learning feedback.
Key aspects of originality include:
- Multi-timeframe target clustering where zones are built from many independent breakouts instead of a single pattern.
- Quantified cluster quality combining density, strength, reachability, and momentum in a transparent scoring model.
- Graduated ML learning that uses continuous success scores and explainable k-NN, rather than opaque models.
- State machine tracking of each cluster's lifecycle with explicit rules for success, failure, and timeout.
- Optional time-to-target estimation that reuses the same ML history instead of guessing fixed time windows.
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CHART LEGEND
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- Green box above current price: bullish target cluster.
- Red box below current price: bearish target cluster.
- Historical clusters can be marked with symbols:
- ✓ for reached,
- ✗ for lost,
- ⏱ for timeout,
often accompanied by a diagonal line showing entry-to-target path and final P&L%.
- Optional trend context (LazyTrend/SuperTrend-style block):
- Green background: bullish regime.
- Red background: bearish regime.
- Neutral colors: sideways or mixed regime.
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Additional Resources (Optional) :
This description is complete and self-contained; no external materials are required to understand how the script works or how to use it. Any separate educational ideas or examples are optional and serve only as additional illustration.
Disclaimer: MTF Target Radar is a decision-support tool, not a standalone trading system. All trading involves risk, and past cluster performance does not guarantee future results. Always backtest and apply proper risk management.
~ The OracleCandle Identification Assistant 3000
Daily Candles M T W T F
Current Week
4h Candles 18 22 2 6 10 14
Current Week
Current Day (only reason i made it tbh)
enjoy
Photon Price Action Scanner [JOAT]Photon Price Action Scanner - Multi-Pattern Recognition with Adaptive Filtering
Introduction and Purpose
Photon Price Action Scanner is an open-source overlay indicator that automates the detection of 15+ candlestick patterns while filtering them through multiple confirmation layers. The core problem this indicator solves is pattern noise: raw candlestick pattern detection produces too many signals, most of which fail because they lack context. This indicator addresses that by combining pattern recognition with trend alignment, volume-weighted strength scoring, velocity confirmation, and an adaptive neural bias filter.
The combination of these components is not arbitrary. Each filter addresses a specific weakness in standalone pattern detection:
Trend alignment ensures patterns appear in favorable market structure
Volume-weighted strength filters out weak patterns with low conviction
Velocity confirmation identifies momentum behind the pattern
Neural bias filter adapts to recent price behavior to avoid counter-trend signals
What Makes This Indicator Original
While candlestick pattern scanners exist, this indicator's originality comes from:
1. Multi-Layer Filtering System - Patterns must pass through trend, strength, velocity, and neural bias filters before generating signals. This dramatically reduces false positives compared to simple pattern detection.
2. Adaptive Neural Bias Filter - A custom momentum-adjusted EMA that learns from recent price action using a configurable learning rate. This is not a standard moving average but an adaptive filter that accelerates during trends and smooths during consolidation.
3. Pattern Strength Scoring - Each pattern receives a strength score based on volume ratio and body size, allowing traders to focus on high-conviction setups rather than every pattern occurrence.
4. Smart Cooldown System - Prevents signal overlap by enforcing minimum bar spacing between pattern labels, keeping charts clean even when "Show All Patterns" is enabled.
How the Components Work Together
Step 1: Pattern Detection
The indicator scans for 15 candlestick patterns using precise mathematical definitions:
// Example: Bullish Engulfing requires the current bullish candle to completely
// engulf the previous bearish candle with a larger body
isBullishEngulfing() =>
bool pattern = close < open and close > open and
open <= close and close >= open and
close - open > open - close
pattern
// Example: Three White Soldiers requires three consecutive bullish candles
// with each opening within the previous body and closing higher
isThreeWhiteSoldiers() =>
bool pattern = close > open and close > open and close > open and
close < close and close < close and
open > open and open < close and
open > open and open < close
pattern
Step 2: Strength Calculation
Each detected pattern receives a strength score combining volume and body size:
float volRatio = avgVolume > 0 ? volume / avgVolume : 1.0
float bodySize = math.abs(close - open) / close
float baseStrength = (volRatio + bodySize * 100) / 2
This ensures patterns with above-average volume and large bodies score higher than weak patterns on low volume.
Step 3: Trend Alignment
Patterns are checked against the trend direction using an EMA:
float trendEMA = ta.ema(close, i_trendPeriod)
int trendDir = close > trendEMA ? 1 : close < trendEMA ? -1 : 0
Bullish patterns in uptrends and bearish patterns in downtrends receive priority.
Step 4: Neural Bias Filter
The adaptive filter uses a momentum-adjusted EMA that responds to price changes:
neuralEMA(series float src, simple int period, simple float lr) =>
var float neuralValue = na
var float momentum = 0.0
if na(neuralValue)
neuralValue := src
float error = src - neuralValue
float adjustment = error * lr
momentum := momentum * 0.9 + adjustment * 0.1
neuralValue := neuralValue + adjustment + momentum
neuralValue
The learning rate (lr) controls how quickly the filter adapts. Higher values make it more responsive; lower values make it smoother.
Step 5: Velocity Confirmation
Price velocity (rate of change) must exceed the average velocity for strong signals:
float velocity = ta.roc(close, i_trendPeriod)
float avgVelocity = ta.sma(velocity, i_trendPeriod)
bool velocityBull = velocity > avgVelocity * 1.5
Step 6: Signal Classification
Signals are classified based on how many filters they pass:
Strong Pattern : Pattern + strength threshold + trend alignment + neural bias + velocity
Ultra Pattern : Strong pattern + gap in same direction + velocity confirmation
Watch Pattern : Pattern detected but not all filters passed
Detected Patterns
Classic Reversal Patterns:
Bullish/Bearish Engulfing - Complete body engulfment with larger body
Hammer - Long lower wick (2x body), small upper wick, bullish context
Shooting Star - Long upper wick (2x body), small lower wick, bearish context
Morning Star - Three-bar bullish reversal with small middle body
Evening Star - Three-bar bearish reversal with small middle body
Piercing Line - Bullish candle closing above midpoint of previous bearish candle
Dark Cloud Cover - Bearish candle closing below midpoint of previous bullish candle
Bullish/Bearish Harami - Small body contained within previous larger body
Doji - Body less than 10% of total range (indecision)
Advanced Patterns (Optional):
Three White Soldiers - Three consecutive bullish candles with rising closes
Three Black Crows - Three consecutive bearish candles with falling closes
Tweezer Top - Equal highs with reversal candle structure
Tweezer Bottom - Equal lows with reversal candle structure
Island Reversal - Gap isolation creating reversal structure
Dashboard Information
The dashboard displays real-time analysis:
Pattern - Current detected pattern name or "SCANNING..."
Bull/Bear Strength - Volume-weighted strength scores
Trend - UPTREND, DOWNTREND, or SIDEWAYS based on EMA
RSI - 14-period RSI for momentum context
Momentum - 10-period momentum reading
Volatility - ATR as percentage of price
Neural Bias - BULLISH, BEARISH, or NEUTRAL from adaptive filter
Action - ULTRA BUY/SELL, BUY/SELL, WATCH BUY/SELL, or WAIT
Visual Elements
Pattern Labels - Abbreviated codes (BE=Engulfing, H=Hammer, MS=Morning Star, etc.)
Neural Bias Line - Adaptive trend line showing filter direction
Gap Boxes - Cyan boxes highlighting price gaps
Action Zones - Dashed boxes around strong pattern areas
Velocity Markers - Small circles when velocity confirms direction
Ultra Signals - Large labels for highest conviction setups
How to Use This Indicator
For Reversal Trading:
1. Wait for a pattern to appear at a key support/resistance level
2. Check that the Action shows "BUY" or "SELL" (not just "WATCH")
3. Confirm the Neural Bias aligns with your trade direction
4. Use the strength score to gauge conviction (higher is better)
For Trend Continuation:
1. Identify the trend using the Trend row in the dashboard
2. Look for patterns that align with the trend (bullish patterns in uptrends)
3. Ultra signals indicate the strongest continuation setups
For Filtering Noise:
1. Keep "Show All Patterns" disabled to see only filtered signals
2. Increase "Pattern Strength Filter" to see fewer, higher-quality patterns
3. Enable "Velocity Confirmation" to require momentum behind patterns
Input Parameters
Scan Sensitivity (1.0) - Overall detection sensitivity multiplier
Pattern Strength Filter (3) - Minimum strength score for strong signals
Trend Period (20) - EMA period for trend determination
Show All Patterns (false) - Display all patterns regardless of filters
Advanced Patterns (true) - Enable soldiers/crows/tweezer detection
Gap Analysis (true) - Enable gap detection and boxes
Velocity Confirmation (true) - Require velocity for strong signals
Neural Bias Filter (true) - Enable adaptive trend filter
Neural Period (50) - Lookback for neural bias calculation
Neural Learning Rate (0.12) - Adaptation speed (0.01-0.5)
Timeframe Recommendations
1H-4H: Best balance of signal frequency and reliability
Daily: Fewer but more significant patterns
15m-30m: More signals, requires tighter filtering (increase strength threshold)
Limitations
Pattern detection is mechanical and does not consider fundamental context
Neural bias filter may lag during rapid trend reversals
Gap detection requires clean price data without after-hours gaps
Strength scoring favors high-volume patterns, which may miss valid low-volume setups
- Made with passion by officialjackofalltrades
Market Structure MTF [HH/HL/LH/LL + CHoCH + BOS]Automatic market structure detection with pivot classification (HH/HL/LH/LL), Change of Character (CHoCH) and Break of Structure (BOS) signals. Multi-timeframe support allows overlaying higher timeframe structure on any chart.
█ OVERVIEW
This indicator automatically detects and classifies pivot points to visualize market structure. It identifies trend direction through the sequence of highs and lows, and signals potential reversals through Change of Character (CHoCH) and trend continuation through Break of Structure (BOS).
█ CONCEPTS
Market structure analysis is based on the relationship between consecutive pivot points:
Bullish Structure:
• HH (Higher High): A swing high that exceeds the previous swing high
• HL (Higher Low): A swing low that stays above the previous swing low
• Sequence: HH → HL → HH → HL confirms uptrend
Bearish Structure:
• LH (Lower High): A swing high that fails to exceed the previous swing high
• LL (Lower Low): A swing low that breaks below the previous swing low
• Sequence: LH → LL → LH → LL confirms downtrend
Structure Shifts:
• CHoCH (Change of Character): Signals when the expected sequence breaks, suggesting potential trend reversal
• BOS (Break of Structure): Confirms trend continuation when price breaks a pivot level in trend direction
█ FEATURES
• Automatic pivot detection using configurable lookback period
• Smart classification comparing each pivot to its predecessor
• CHoCH detection when trend sequence is violated
• BOS signals with anti-repetition filter to reduce noise in consolidation zones
• Multi-Timeframe (MTF) support to display higher timeframe structure
• Horizontal dashed lines marking HTF pivot levels
• Clean visual output with color-coded labels
█ SETTINGS
Structure Settings:
• Pivot Length: Number of bars on each side required to confirm a pivot (default: 5)
- Lower values (2-3) = more sensitive, detects minor swings
- Higher values (10-20) = less sensitive, only major structure
Multi-Timeframe:
• Show HTF Structure: Enable/disable higher timeframe overlay
• HTF Timeframe: Select the higher timeframe to display (D, W, M, etc.)
Visualization:
• Show Local Structure: Toggle visibility of current timeframe pivots
Filters:
• BOS Buffer: Minimum bars between BOS signals to avoid repetition
█ HOW TO USE
The indicator offers three visualization modes:
1. LOCAL STRUCTURE ONLY (default)
├─ Show Local Structure: ✓ Enabled
├─ Show HTF Structure: ✗ Disabled
└─ Use case: Analyze structure on the current timeframe only
2. HIGHER TIMEFRAME ONLY (recommended for clarity)
├─ Show Local Structure: ✗ Disabled
├─ Show HTF Structure: ✓ Enabled
├─ HTF Timeframe: Select desired TF (D, W, M)
└─ Use case: View higher TF context on lower TF charts without clutter
3. BOTH TIMEFRAMES (advanced)
├─ Show Local Structure: ✓ Enabled
├─ Show HTF Structure: ✓ Enabled
└─ Use case: See confluence between timeframes
⚠️ WARNING: This mode can make the chart visually crowded.
Recommended only for experienced users who need both layers simultaneously.
█ RECOMMENDED SETTINGS BY TIMEFRAME
| Chart TF | Pivot Length | Suggested HTF |
|----------|--------------|---------------|
| 1H | 10-15 | 4H or D |
| 4H | 5-10 | D or W |
| 1D | 5-7 | W |
| 1W | 3-5 | M |
The goal is to make pivots on lower timeframes represent equivalent time context.
█ VISUAL REFERENCE
Local Structure Labels:
• 🟩 Green (above): HH - Higher High
• 🟥 Red (above): LH - Lower High
• 🟩 Green (below): HL - Higher Low
• 🟥 Red (below): LL - Lower Low
• 🟧 Orange: CHoCH - Change of Character
• 🟦 Blue: BOS - Break of Structure
HTF Structure Labels:
• 🩵 Teal: HH/HL - Bullish HTF structure
• 🟫 Maroon: LH/LL - Bearish HTF structure
• 🟨 Yellow: CHoCH - HTF trend shift
• 🟦 Navy: BOS - HTF structure break
• ┈┈ Dashed lines mark HTF pivot price levels
█ INTERPRETATION GUIDELINES
Reading the sequence:
• Consistent HH + HL = Bullish bias, look for long opportunities
• Consistent LH + LL = Bearish bias, look for short opportunities
• CHoCH after trending sequence = Potential reversal, exercise caution
• BOS in trend direction = Trend continuation confirmed
Combining timeframes:
• HTF structure defines the primary bias
• Local structure provides entry timing
• Confluence (both TFs aligned) = Higher probability setups
█ LIMITATIONS
• Pivots are confirmed with a delay equal to the Pivot Length parameter
• In ranging markets, multiple CHoCH signals may appear (this is correct behavior - the market IS changing direction frequently)
• CHoCH signals potential reversal, not guaranteed reversal
• Works best on liquid markets with clean price action
█ TECHNICAL NOTES
• Uses ta.pivothigh() and ta.pivotlow() for pivot detection
• request.security() fetches higher timeframe data
• Anti-repetition logic prevents BOS signal clustering in consolidation
• All crossover/crossunder calculations are performed at global scope for consistency (Pine Script v6 compliance)
█ CREDITS
Developed for swing traders and position traders who use market structure for trend analysis and trade timing.
Feedback and suggestions are welcome.
Position and Leverage Size CalculatorThis script is assist you to see approximate position and leverage size while trading in prop firms.
Stochastic RSI 1 MonthThis is the standard SRSI indicator set to 1 month so I can see have multiple timeframes on the same chart which helps with seeing momentum swings.
Killzones [Tradeuminati]Killzones is a precise TradingView indicator designed to display the most important institutional trading windows (“Killzones”) based strictly on New York local time.
The indicator focuses on accurate session timing, automatic asset classification, and stable chart behavior without affecting price scale or candle colors.
🔹 Included Killzones (NY Local Time)
London Killzone
02:00 – 05:00
New York Killzone (AM)
Indices & Index CFDs: 09:30 – 11:00
All other assets (Forex, Crypto, Commodities such as Gold, DXY): 07:00 – 10:00
New York PM Killzone
14:00 – 15:00
🔹 Asset Logic (Fully Automatic & Locked)
- Indices and Index CFDs are detected automatically
- Forex, Crypto, Commodities (e.g. Gold/XAUUSD, DXY) always use the 07:00–10:00 New York Killzone
- Stocks (Equities) are completely excluded
→ no lines, no table, no status display
This ensures the indicator is purpose-built for intraday trading in highly liquid markets and intentionally not designed for stock charts.
🔹 Chart Visualization
- Vertical session lines are drawn statically at the start of each New York trading day
- Lines are not dependent on bar timestamps
- No distortion of the price scale
- Session lines are shown only on intraday timeframes below 4H
- Line color, width, and style are fully adjustable
🔹 Status Table (Top Right)
- Clear overview of all Killzones with start and end times
- Live status indicator (green/red) based on the real current time (timenow), not the last printed candle
- The table remains visible on all timeframes (except stocks)
🔹 Technical Highlights
- Pure New York time–based logic, independent of chart timezone
- No future-bar plotting
- Stable across different brokers and CFD feeds
- Does not interfere with other indicators or candle coloring
⚠️ Disclaimer
This indicator is intended for technical analysis only and does not constitute trading or investment advice.
Trend Bias Impulse Range Spread Aware TP SLThis indicator combines two simple concepts into one practical trade-planning workflow:
Trend Bias (SMA filter) decides direction only (LONG/SHORT).
Impulse Range (HH–LL over a lookback) decides position sizing logic only (how far TP/SL are placed).
The value is in how these parts work together to produce a complete and readable setup on-chart: Entry + Spread-aware SL + 3 Targets + Zones + TP hit tracking in one tool, so you don’t have to manually draw levels every time bias changes.
Calculations
Trend bias
SMA = sma(close, smaLen)
If close > SMA → LONG, else → SHORT
Impulse range (dynamic sizing unit)
impulseRange = highest(high, lenImpulse) - lowest(low, lenImpulse)
Entry / Setup generation
A new setup is created when:
bias flips (LONG↔SHORT), or
the previous setup is completed (TP3 reached or SL reached).
Entry is the close price on the setup bar. Levels stay fixed until the next setup.
Targets & Stop (range fractions)
TP1 = 0.382 × impulseRange
TP2 = 0.618 × impulseRange
TP3 = 0.786 × impulseRange
SL = levelRatio × impulseRange opposite to trade direction
Spread-aware adjustment (execution realism)
User input spreadPts shifts levels:
LONG: TPs − spread, SL + spread
SHORT: TPs + spread, SL − spread
Chart visuals
Lines: Entry, SL, TP1, TP2, TP3
Zones:
Entry→TP1 (first target block)
TP1→TP3 (profit zone)
Entry→SL (risk zone)
Table (top-right) shows all prices; ✅ appears only when TP levels are reached.
Inputs (UI translation)
Длина импульса = Impulse length (lenImpulse)
Длина SMA = SMA length (smaLen)
SL/TP множитель = SL multiplier (levelRatio)
Spread (пункты) = Spread in points (spreadPts)
Notes / limitations
Indicator only (not a strategy). No order placement. Always test on your symbol/timeframe and use risk management. For publication screenshots, keep symbol, timeframe, and script name visible in the chart header.
trend system algo [skyeye]System Overview The Structural Trend & Fibo Nexus is a comprehensive trading system designed to bridge the gap between discretionary technical analysis and quantitative risk management. It integrates Market Structure identification, Multi-Timeframe (MTF) Momentum, and automated Risk/Reward calculation into a single chart interface.
Core Features & Calculation Logic
1. Market Structure Identification (The Backbone)
Algorithm: Utilizes a filtered ZigZag algorithm. Unlike standard ZigZags, this script incorporates a Min Swing % filter and a Min Bars duration filter.
Logic: It identifies valid Higher Highs (HH) and Lower Lows (LL) only when price moves exceed a specific volatility threshold. This effectively filters out market noise.
Visuals:
Green Background: Indicates a Bullish Structure phase.
Red Background: Indicates a Bearish Structure phase.
2. Zero-Lag Momentum Layer (The Trigger)
Algorithm: A Two-Pole Gaussian Filter.
Logic: Gaussian filters offer superior smoothness compared to Simple or Exponential Moving Averages (SMA/EMA) while significantly reducing lag. This allows for faster reaction to trend reversals without the "whipsaw" effect of noisy moving averages.
MTF Dashboard: The table in the bottom-right corner monitors the Gaussian momentum across 5 timeframes (5m to 4h) in real-time, helping traders align with the dominant trend.
3. Quantitative Risk Engine (The Execution)
Auto-Calculation: When a valid trend reversal signal occurs (Structure Flip + Momentum Cross), the script automatically projects a trade setup.
Dynamic Stop Loss (SL): Calculated using the Average True Range (ATR). This ensures the stop loss adapts to the current market volatility (wider stops in volatile markets, tighter stops in calm markets).
Take Profit (TP) Targets: Automatically projects three fixed Reward-to-Risk (R:R) targets:
TP1: 1:1 R:R
TP2: 1:1.5 R:R
TP3: 1:2 R:R
Visuals: Draws colored boxes and dashed lines on the chart to visualize the potential PnL zones immediately upon signal generation.
Strategy Guide: The "Quant Nexus" Method
Step 1: Structural Bias Observe the background color.
Trade Long only when the background is Green.
Trade Short only when the background is Red.
Step 2: Trend Alignment Check the MTF Dashboard. Ideally, the H1 and H4 timeframes should match the color of your intended trade direction (Green for Long, Purple for Short).
Step 3: Signal Execution Wait for the entry signal (indicated by the Risk/Reward boxes appearing).
Entry: At the close of the signal candle.
Stop Loss: Place your SL at the level indicated by the "Stop Loss" label (based on ATR).
Take Profit: Scale out positions at TP1, TP2, and TP3 levels.
Settings Customization
ZigZag Config: Adjust Depth and Min Swing % to tune the sensitivity of market structure.
MTF Trends: Customize the Alpha to adjust the smoothness of the Gaussian line.
Quant Risk: Toggle Use ATR SL or adjust SL Multiplier to fit your risk appetite.
Disclaimer: This tool is for educational purposes only. Automated signals should always be verified with your own analysis.
(Chinese Translation / 中文說明)
系統概述 Structural Trend & Fibo Nexus 是一套綜合交易系統，旨在縮小主觀技術分析與量化風險管理之間的差距。它將市場結構識別、多週期 (MTF) 動能和自動風險/回報計算整合到單一圖表介面中。
核心功能與計算邏輯
1. 市場結構識別 (骨幹)
演算法： 使用經過過濾的 ZigZag 演算法。與標準 ZigZag 不同，本腳本結合了「最小波動百分比」和「最小 K 線數」過濾器。
邏輯： 僅當價格變動超過特定的波動率閾值時，才會識別有效的更高高點 (HH) 和更低低點 (LL)。這有效地過濾了市場雜訊。
視覺效果：
綠色背景： 表示看漲結構階段。
紅色背景： 表示看跌結構階段。
2. 零延遲動能層 (觸發器)
演算法： 雙極高斯濾波器 (Two-Pole Gaussian Filter)。
邏輯： 與簡單或指數移動平均線 (SMA/EMA) 相比，高斯濾波器提供了卓越的平滑度，同時顯著減少了延遲。這允許對趨勢反轉做出更快的反應，而不會產生嘈雜均線的「假突破」效應。
MTF 儀表板： 右下角的表格即時監控 5 個時間週期 (5m 至 4h) 的高斯動能，幫助交易者與主趨勢保持一致。
3. 量化風控引擎 (執行)
自動計算： 當有效的趨勢反轉信號出現（結構翻轉 + 動能交叉）時，腳本會自動投射交易計畫。
動態止損 (SL)： 使用 平均真實波幅 (ATR) 計算。這確保止損能適應當前的市場波動（波動大時止損較寬，平靜時止損較窄）。
止盈 (TP) 目標： 自動投射三個固定的風險回報比 (R:R) 目標：
TP1: 1:1 盈虧比
TP2: 1:1.5 盈虧比
TP3: 1:2 盈虧比
視覺效果： 在信號產生時，立即在圖表上繪製彩色方框和虛線，以視覺化潛在的盈虧區域。
策略指南：量化共振法
第一步：結構偏差 觀察背景顏色。
背景為 綠色 時，僅考慮做多。
背景為 紅色 時，僅考慮做空。
第二步：趨勢對齊 檢查 MTF 儀表板。理想情況下，H1 和 H4 時間週期應與您的預期交易方向顏色相符（做多為綠色，做空為紫色）。
第三步：信號執行 等待進場信號（由出現的風險/回報框指示）。
進場： 在信號 K 線收盤時。
止損： 將止損設置在「Stop Loss」標籤指示的位置（基於 ATR）。
止盈： 在 TP1、TP2 和 TP3 水平分批獲利了結。
設定自定義
ZigZag 設置： 調整 Depth 和 Min Swing % 以微調市場結構的靈敏度。
MTF 趨勢： 自定義 Alpha 以調整高斯線的平滑度。
量化風控： 切換 Use ATR SL 或調整 SL Multiplier 以符合您的風險偏好。
免責聲明：本工具僅供教育用途。自動信號應始終通過您自己的分析進行驗證。
BB6-MTF-OverlayBB6-MTF-Overlay (Multi-Bollinger Bands, MTF, Overlay)
BB6-MTF-Overlay is a Bollinger Bands overlay indicator that lets you display up to 6 independent BB sets on a single chart, with full MTF (higher timeframe) support.
It’s designed for fast multi-timeframe context—so you can see where price is relative to higher-timeframe BB levels (middle / ±1σ / ±2σ / ±3σ) while trading your current timeframe.
Key Features
Up to 6 Bollinger Band sets displayed simultaneously (overlay)
Per BB set: choose Local (current TF) or MTF (higher TF via security)
Per BB set: Gaps ON/OFF
ON: values may appear only at HTF update points (discontinuous)
OFF: HTF values are filled across lower TF bars (step-like)
Per BB set: Confirmed Bars Mode ON/OFF
ON: uses confirmed HTF values (minimizes repainting)
OFF: follows the in-progress HTF bar (useful for discretionary trading)
Per BB set: toggle visibility for Middle / ±σ1 / ±σ2 / ±σ3 independently
Custom sigma multipliers (e.g., 1.5σ, 0.6σ) for fine tuning
Separate switches for Calculation ON/OFF and Display ON/OFF
Turn off calculations to reduce load, or hide plots only
Typical Use Cases
Use higher timeframe (4H/D/W) BB middle and ±1σ as “structure walls” while executing on lower timeframe
Combine real-time tracking (e.g., 15m BB with Confirmed OFF) with stable HTF anchors (e.g., Daily/Weekly with Confirmed ON)
Keep ±2σ/±3σ OFF by default and enable them only when you need to check range expansion or extremes
Default Preset (Initial Settings)
BB1: 15m MTF (Confirmed Bars Mode OFF)
BB2: 4H MTF (Confirmed Bars Mode OFF)
BB3: Daily MTF (Confirmed Bars Mode ON)
BB4: Weekly MTF (Confirmed Bars Mode ON)
BB5: Monthly MTF (Confirmed Bars Mode ON)
BB6: Calculation OFF / Display OFF
For all active BB sets: σ1 ON by default, σ2 & σ3 OFF by default
Notes
With MTF + Confirmed OFF, band values will move until the higher timeframe bar closes (intended for discretionary use).
If the chart looks too busy, disable unused BB sets or turn off σ2/σ3.
📌 BB6-MTF-Overlay（ボリンジャーバンド6本・MTF対応・Overlay）
BB6-MTF-Overlay は、最大6セットのボリンジャーバンドを同時にチャート上へ重ねて表示できる、MTF（上位足参照）対応のBollinger Bandsインジケーターです。
🕒 15分／4時間／日足／週足／月足など、複数時間軸のボリンジャーを1つのチャートで確認できるため、環境認識（上位足の位置関係）＋現在足の判断をスムーズに行えます。
✨ 主な特徴
📈 最大6本のボリンジャーバンドを同時表示（Overlay）
🔁 各BBごとに Local（現在足） / MTF（上位足） を選択可能
🧩 各BBごとに ギャップON/OFF（上位足更新点のみ表示／階段状に埋める表示）を切替
✅ 各BBごとに 確定足モードON/OFF
ON：上位足確定値（リペイント最小）
OFF：進行中の上位足にも追随（裁量補助向け）
🎚️ 各BBごとに ミドル／±σ1／±σ2／±σ3 を個別に表示ON/OFF
🔧 σ値は自由入力（例：1.5σ、0.6σ など微調整可）
⚙️ 計算ON/OFFと表示ON/OFFを分離
表示だけ消す／計算ごと止めて軽くする、の両方に対応
🧠 想定する使い方（例）
🧱 上位足（4H/日足/週足）のミドル・±1σを「壁」として見て、今の足（5分/15分）での反発・抜けを判断
🏃 「15分BB（確定足OFF）」でリアルタイム追随しつつ、「日足/週足（確定足ON）」で大局の位置を固定して確認
🔍 σ2・σ3は普段OFF、必要なときだけONにしてレンジ幅・伸び代を確認
🧾 デフォルト設定（初期状態）
1️⃣ BB1：15分MTF（確定足モードOFF）
2️⃣ BB2：4時間MTF（確定足モードOFF）
3️⃣ BB3：日足MTF（確定足モードON）
4️⃣ BB4：週足MTF（確定足モードON）
5️⃣ BB5：月足MTF（確定足モードON）
6️⃣ BB6：計算OFF／表示OFF
🎛️ 初期表示は全BB共通で「1σのみON（2σ・3σはOFF）」
⚠️ 注意事項
🔄 MTFで「確定足モードOFF（追随）」を使用する場合、上位足が確定するまで値が動くため、見え方が変化します（裁量補助向け）。
🧹 表示本数が増えるとチャートが混み合うため、必要なBBだけ表示ONにする運用がおすすめです。
Hidden Div ALERT ONLY v1.9 1. This script detects **price-anchored hidden divergences** for trend continuation, not reversals.
2. It uses **price pivots** as the reference and reads **RSI at the exact pivot candle**.
3. **Hidden Bearish**: lower high in price with higher high in RSI → bearish trend continuation.
4. **Hidden Bullish**: higher low in price with lower low in RSI → bullish trend continuation.
5. A **RefLock mechanism** prevents small or noisy pivots from overwriting the main swing.
6. **Min/Max gap filters** ensure only valid swing structures are evaluated.
7. Optional **EMA, RSI range, and volume filters** help align signals with market context.
8. The script is **alert-only**, non-repainting, and optimized for **mobile use**.
9. Designed for **set-and-forget trading**, alerts trigger execution without watching the chart.
MACD Multitimeframe Histogram Color with shapesMACD Multitimeframe Histogram Color with Shapes
Overview
This indicator displays MACD status across 8 timeframes simultaneously in a single pane. Each timeframe is represented by a row of shapes that indicate both the MACD direction (above or below signal) and whether the histogram is expanding or contracting.
The visual encoding lets you quickly assess trend alignment across multiple timeframes without switching charts or cluttering your screen with multiple MACD panels.
How It Works
For each of the 8 configurable timeframes, the indicator calculates the standard MACD (fast MA minus slow MA) and signal line. It then determines:
Direction: Is MACD above or below the signal line?
Momentum: Is the histogram expanding (moving away from zero) or contracting (moving toward zero)?
Shapes indicate direction:
Circle: MACD above signal (bullish)
X Cross: MACD below signal (bearish)
Colors indicate momentum:
Bright green: Bullish and expanding
Dark green: Bullish but contracting
Bright red: Bearish and expanding
Dark red: Bearish but contracting
Each timeframe plots on its own horizontal level, with shorter timeframes at the bottom and longer timeframes at the top.
Settings
MACD Parameters:
Fast Length: Fast MA period (default 12)
Slow Length: Slow MA period (default 26)
Signal Smoothing: Signal line period (default 9)
Oscillator MA Type: SMA or EMA for MACD calculation
Signal Line MA Type: SMA or EMA for signal line
Colors:
Bullish Expansion Color
Bullish Contraction Color
Bearish Expansion Color
Bearish Contraction Color
Timeframes:
8 configurable timeframes (default: 5m, 10m, 15m, 30m, 1H, 2H, 4H, 1D)
Usage
Look for alignment across timeframes. When most or all timeframes show the same direction and are expanding, it suggests strong trend momentum. Mixed signals or contracting histograms across timeframes may indicate consolidation or potential reversal.
This works well as a confirmation tool alongside price action analysis or other indicators. The multi-timeframe view helps avoid taking trades against the higher timeframe trend.
Tip:
You can turn off as many MACDs as you want and it will resize. I usually use 4 - and keep them close together time wise. For the 5 minute chart, I use 5, 7, 9, 11 minutes. For something longer, like the hour chart, I will use 60 minutes, 75 minutes, 90 minutes, and 105 minutes (15 min intervals).
Trading Sessions IndicatorMulti-Session High/Low Indicator
Automatically plots clean session highs and lows for up to 5 customizable trading sessions.
• Individual colors per session
• Vertical line at session open
• Optional extension through New York
• Clean, lightweight, no clutter
Perfect for futures, forex, and session-based traders who rely on key intraday levels and liquidity.
Want to know more about my indicators? Want a custom indicator built? Join the Trader Circle Discord community by clicking the link below;
discord.gg
Set it once. Trade with clarity every day.
SULTAN NEXUS INTRADAY v2.2SULTAN NEXUS is a professional-grade intraday trading system that dynamically maps institutional supply and demand zones. It features a unique 3-layer MTF Guard system (H1, M15, M5) and an ATR-based risk calculator to provide a complete trading plan directly on your dashboard.
1. The Nexus Engine (Originality) SULTAN NEXUS does not use static pivot points. It calculates a dynamic "Market Range" over a user-defined lookback period. It then mathematically applies Zone Thickness % to identify the most critical areas where price is likely to react.
2. 3-Layer MTF Guards (How it works) To solve the problem of trading against the trend, we have implemented Triple-Timeframe Alignment.
H1 Guard: Ensures the macro trend is in your favor.
M15 Guard: Confirms medium-term momentum.
M5 Gate: Only opens the trade when the immediate price action aligns. If these timeframes conflict, the dashboard displays a "MTF CONFLICT" warning, keeping you out of low-probability trades.
3. Fixed RR Risk Dashboard This script provides a real-time trading plan:
Dynamic SL: Calculated using ATR padding to prevent "stop-hunting."
TP1 (Equilibrium): Automatically targets the 50% midpoint of the range.
TP2 (External Zone): Targets the opposing Supply or Demand zone for maximum Risk/Reward.
4. Filtering Noise We use an ADX Minimum Filter to ensure the market is trending before suggesting a signal. This prevents the indicator from giving "Buy/Sell" signals in a chop market.
How to Use:
Wait for price to enter a Green (Demand) or Red (Supply) zone.
Check the Status Dashboard. If it says "BUY NOW," the MTF Guards and ADX filters are aligned.
Follow the Entry, SL, and TP levels provided in the Buy/Sell Plan on the dashboard.
GateKeepers EMA-12GateKeepers — EMA 12
Multi-EMA Market Structure & Trend Context Framework
GateKeepers EMA 12 is a professional-grade market structure framework designed to reveal how price behaves across multiple time horizons simultaneously.
Instead of simplifying the market down to a single bias line or signal, EMA 12 provides a layered structural map—showing trend strength, compression, expansion, and transition in a way that is immediately readable and actionable.
This tool is built for traders who understand that structure comes before entries.
⸻
Why EMA 12 Exists
Markets rarely move in a straight line. They expand, contract, rotate, and transition long before entries appear.
GateKeepers EMA 12 was built to answer one core question:
Is the market structurally healthy enough to trade — or is it compressing, stalling, or transitioning?
By using a 12-EMA framework, EMA 12 exposes the internal rhythm of price that single-EMA tools cannot show.
⸻
What EMA 12 Helps You See
• EMA alignment and stacking across short, medium, and longer horizons
• Trend strength vs compression at a glance
• Early signs of trend exhaustion or transition
• Where pullbacks and continuation zones are most likely to form
• When overlapping EMAs warn of chop and low-quality conditions
When EMAs are cleanly stacked and expanding, conditions favor continuation.
When EMAs compress, overlap, or flatten, conditions favor patience.
⸻
How EMA 12 Fits Into the GateKeepers Ecosystem
GateKeepers tools are intentionally layered:
1. Structural context → EMA 12
2. Directional bias clarity → EMA v2
3. Volatility & regime awareness → ATR Badge
4. Execution confirmation → 3 Candle Reversal
EMA 12 serves as the structural foundation, helping traders understand what phase the market is in before applying bias, volatility filters, or entry confirmation.
⸻
Practical Use Cases
• Define market structure before looking for setups
• Identify high-probability pullback zones
• Avoid trading during EMA compression and indecision
• Improve patience and selectivity
• Pair with EMA v2 for simplified bias and ATR Badge for volatility context
EMA 12 does not tell you when to trade — it helps you understand whether trading makes sense at all.
⸻
Design Philosophy
• Context over signals
• Structure before execution
• Clean, readable visuals
• Built for rule-based, repeatable trading processes
⸻
What This Tool Is (and Isn’t)
• ✔ A market structure and trend context engine
• ✔ Designed for disciplined, process-driven traders
• ✘ Not a buy/sell indicator
• ✘ Not predictive on its own
GateKeepers EMA 12 helps traders slow down, see clearly, and engage the market with intent instead of impulse.
GateKeepers 3 Candle Reversals GateKeepers — 3 Candle Reversal
Price-Action Confirmation Module
GateKeepers 3 Candle Reversal is a price-action confirmation tool designed to work inside the GateKeepers ecosystem — not in isolation.
This indicator highlights clean three-candle reversal structures that often appear when momentum exhausts and control begins to shift. It is intentionally selective, marking only clear patterns that can be used to confirm bias, structure, or volatility context already defined by other GateKeepers tools.
How It Fits Into the GateKeepers Framework
GateKeepers tools are built around a simple hierarchy:
1. Context first (EMA v2 — trend & bias)
2. Conditions second (ATR Badge — volatility & regime)
3. Confirmation last (3 Candle Reversal — price action)
This indicator serves as the final check, helping you avoid premature entries and improve timing once conditions are already favorable.
Practical Use Cases
• Confirm pullbacks in trend after EMA bias is established
• Validate reversal attempts during volatility expansion
• Improve entry timing on structure retests or exhaustion zones
• Filter out noise by requiring visible price commitment
Design Philosophy
• No signal spam
• No lagging indicators
• No prediction
Only readable price behavior, expressed in a simple, repeatable form.
What This Tool Is (and Isn’t)
• ✔ A confirmation layer for disciplined traders
• ✔ Best paired with EMA, volatility, or structure tools
• ✘ Not a strategy
• ✘ Not meant to be traded blindly
When used within a rules-based process, GateKeepers 3 Candle Reversal helps traders act with intent instead of impulse.
SULTAN SMC PRO v1The SULTAN SMC PRO v9 is a comprehensive institutional trading framework. Unlike basic SMC scripts that simply plot boxes on every pivot, this script utilizes a custom Displacement Filter and ATR-based Volatility logic to separate low-probability noise from high-probability institutional moves.
Why this is NOT a simple Mashup:
This script integrates three distinct analytical layers that work in synergy:
Dynamic Mitigation Tracking: Every Order Block and FVG is monitored in real-time. The script calculates the "Mitigation Count" which helps traders understand the exhaustion of a zone—a feature not found in standard open-source SMC tools.
Breakout Strength Engine: We have implemented a proprietary logic that compares candle body size, volume, and ATR to label structure breaks as "(Real) 🔥" or "(Weak/Trap)". This prevents traders from entering on fakeouts.
Non-Repainting MTF Implementation: Using barmerge.lookahead_off, we provide a safe way to view Higher Timeframe (HTF) context without the risk of historical repainting.
How to use this script:
Step 1: Identify the institutional trend via the Dashboard.
Step 2: Look for a Liquidity Sweep (marked with ⚔️) near a HTF Supply/Demand zone.
Step 3: Confirm with a CHoCH that has a "(Real) 🔥" strength label.
Step 4: Enter at the FVG or Order Block mitigation.
Transparency & Credits
Built-in Functions: This script uses standard Pine Script™ pivot and security functions for data fetching.
Public Domain Concepts: The core concepts of BOS, CHoCH, and FVG are well-documented in the public domain.
Custom Improvements: The "Breakout Strength" algorithm and "Zone Volume" accumulation logic are original additions to this codebase to provide extra utility to the community.
Johnny's Calculated Brain## Overview
Johnny’s Calculated Brain is a real-time market context indicator designed to frame continuation and correction opportunities using higher timeframe structure.
It continuously evaluates price imbalance, volume participation, trend strength, and multi-timeframe alignment to help traders understand what type of market environment they are operating in. Continuation, pullback, or mean reversion, as price unfolds in real time.
This indicator provides context, not just execution.
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## Brain Zones
Brain Zones highlight areas where price moves with strong directional intent and imbalance in real-time, for simple continuation trades in the same direction, or reversal entries for corrections, also often leaving behind zones that price may 'later' react to as well.
These zones:
- Are calculated on a locked higher timeframe (default: 4H)
- Are non-repainting and historical
- Are volume weighted, reflecting participation strength
- Dim automatically once fully mitigated
Brain Zones are not buy or sell signals, in the real world, those types of indicators don't exist and don't work either. They represent areas of interest where continuation, correction, or rejection may occur depending on market conditions.
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## Real-Time Market Framing
Johnny’s Calculated Brain operates in real time and can be used to frame:
- Continuation trades
When trend strength and multi-timeframe alignment support further directional movement.
- Corrective / pullback trades
When price retraces into Brain Zones within an established trend.
- Mean-reversion conditions
When trend strength weakens and structure becomes balanced.
The indicator does not decide entries, it helps you decide which type of setup to look for and shows when that opportunity presents itself.
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## Dashboard
The dashboard provides higher-timeframe context at a glance.
ADX:
- Indicates whether the market is Trending or Ranging
- Color coded for clarity
MTF (Multi-Timeframe Alignment):
- Bullish → Higher timeframes aligned upward
- Bearish → Higher timeframes aligned downward
- Mixed → No clear alignment
This helps determine whether continuation or correction setups are more appropriate.
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## Highs & Lows (MTF)
Optional reference levels include:
- Daily High / Daily Low
- Weekly High / Weekly Low
- Monthly High / Monthly Low
These levels often act as liquidity targets, reaction zones, and structural boundaries that add confluence to Brain Zones.
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## Alerts
Alerts are designed to help you monitor multiple markets efficiently.
How to use alerts:
1. Create a watchlist of assets you are interested in (FX, Crypto, Indices, etc.)
2. Set a TradingView alert using the script’s alert conditions against the watchlist and select 'Johnny's Calculated Brain' as the indicator.
3. Ensure the chart timeframe is set to **4H**
4. Select **Once Per Bar Close** when creating the alert
When an alert triggers, it means a **new Brain Zone has formed** on the higher timeframe and a **potential opportunity may be present**.
They notify you of new structural developments and potential trade opportunities.
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## If You Cannot Use Alerts
If your TradingView membership does not allow automated alerts:
- Keep the indicator applied on your chart
- Monitor the chart on the 4H timeframe
- Watch for new Brain Zones forming visually (wait for H4 candle close)
- Treat newly formed zones as an area of potential trade opportunity
The indicator behaves the same with or without alerts.
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## Recommended Settings
It is strongly recommended to leave all settings at their default values.
The defaults are tuned for higher timeframe reliability, reduced noise, and balanced sensitivity.
Changing sensitivity does not guarantee better results, it simply changes how strict the Brain is.
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## How to Use
1. Start on a higher timeframe (4H recommended)
2. Wait for a new Brain Zone to form
- via alert notification, or
- visually on the chart
3. Check ADX (trend strength) and MTF alignment
4. Decide whether the market favors continuation or correction
5. Execute using your own strategy and risk management
This indicator is a decision support tool, not a blind buy/sell system.
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## Disclaimer
This script is for educational purposes only and does not constitute financial advice.
Always use proper risk management and your own judgment when trading.
[JF] Trading SessionsThis indicator outlines trading sessions. You are able to outline Asia, London and each New York sessions.
