Trendlines with Breaks Oscillator [LuxAlgo]The Trendlines with Breaks Oscillator is an oscillator based on the Trendlines with Breaks indicator, and tracks the maximum distance on price from bullish and bearish trendline breakouts.
The oscillator features divergences and trendline breakout detection.
🔶 USAGE
This tool is based on our Trendlines with Breaks indicator, which detects bullish and bearish trendlines and highlights the breaks on the chart. Now, we bring you this tool as an oscillator.
The oscillator calculates the maximum distance between the price and the break of each trendline, for both bullish and bearish cases, then calculates the delta between both.
When the oscillator is above 0, the market is in an uptrend; when it is below 0, it is in a downtrend. An ascending slope indicates positive momentum, and a descending slope indicates negative momentum.
Trendline breaks are displayed as green and red dots on the oscillator. A green dot corresponds to a bullish break of a descending trendline, and a red dot corresponds to a bearish break of an ascending trendline.
The oscillator calculation depends on two parameters from the settings panel: short and long alpha length. These parameters are used to calculate a synthetic EMA with a variable alpha for both bullish and bearish breaks. The final result is the difference between the two averages.
As shown in the image, using the same trend detection parameters but different alphas can produce very different results. The larger the alphas, the smoother the oscillator becomes, detecting bigger trends but making it less reactive.
This tool features the same trendline detection system as the Trendlines with Breaks indicator, which is based on three main parameters: swing length, slope, and calculation method.
As we can see in the image above, the data collected for the oscillator calculation will be different when using different parameters. A larger length detects larger trends. A larger slope or a different calculation method also impacts the final result.
🔹 Signal Line
The signal line is a smoothed version of the oscillator; traders can choose the smoothing method and length used from the settings panel.
In the image, the signal line crossings are displayed as vertical lines. As we can see, the market usually corrects downward after a bearish crossing and corrects upward after a bullish crossing.
Traders can choose among 10 different smoothing methods for the signal line. In the image, we can see how different methods and lengths give different outputs.
🔹 Divergences
The tool features a divergence detector that helps traders understand the strength behind price movements. Traders can adjust the detection length from the settings panel.
As shown in the image, a bearish divergence occurs when the price prints higher highs, but the momentum on the histogram prints lower highs. A bullish divergence occurs when the price prints lower lows, but the histogram prints higher lows.
By adjusting the length of the divergence detector, traders can filter out smaller divergences, allowing the tool to only detect more significant ones.
The image above depicts divergences detected with different lengths; the larger the length, the bigger the divergences are detected.
🔶 SETTINGS
🔹 Trendlines
Swing Detection Lookback: The size of the market structure used for trendline detection.
Slope: Slope steepness, a value of 0 gives horizontal levels, values larger than 1 give a steeper slope
Slope Calculation Method: Choose how the slope is calculated
🔹 Oscillator
Short Alpha Length: Synthetic EMA short period
Long Alpha Length: Synthetic EMA long period
Smoothing Signal: Choose the smoothing method and period
Divergences: Enable or disable divergences and select the detection length.
🔹 Style
Bullish: Select bullish color.
Bearish: Select bearish color.
Göstergeler ve stratejiler
SK-Trading ABC - Stefan Style The SK System Indicator combines trend, volume, and momentum analysis to generate precise buy and sell signals. Perfect for scalping and swing trading — highlights clear entry/exit zones, trend direction, and potential reversal points in real time.
Akkam Confirmation (Extended)Disclaimer:
This indicator is not the original GKD-C Trend Akkam script.
It was independently rebuilt from publicly available descriptions, screenshots, and discussions about the indicator’s logic. No proprietary or invite-only source code was used.
The purpose of this publication is educational — to explore how a volatility-adaptive “confirmation” line can be modeled using open methods.
About this version:
Implements an ATR- or Delta-based trailing confirmation line centered on the bar’s open.
Supports optional moving average smoothing of the offset.
Visual flip signals (▲ / ▼) show when direction changes.
Inputs:
• ATR Range — ATR lookback length
• MA Range — optional smoothing of offset
• ATR Factor — multiplier for ATR in ATR mode
• Mode — “ATR” or “Delta Price” offset computation
• Delta Price Dips — lookback length for delta mode
• MA Type — SMA or EMA
Credits & context:
The concept and naming reference GKD-C Trend Akkam (TradingView invite-only).
This script is an open educational approximation, not endorsed by or affiliated with Loxx or the original GKD system.
Use it for learning, experimentation, or as a building block for your own strategies.
Author:
PejoTech (www.tradingview.com
Algorithm Predator - ML-liteAlgorithm Predator - ML-lite
This indicator combines four specialized trading agents with an adaptive multi-armed bandit selection system to identify high-probability trade setups. It is designed for swing and intraday traders who want systematic signal generation based on institutional order flow patterns , momentum exhaustion , liquidity dynamics , and statistical mean reversion .
Core Architecture
Why These Components Are Combined:
The script addresses a fundamental challenge in algorithmic trading: no single detection method works consistently across all market conditions. By deploying four independent agents and using reinforcement learning algorithms to select or blend their outputs, the system adapts to changing market regimes without manual intervention.
The Four Trading Agents
1. Spoofing Detector Agent 🎭
Detects iceberg orders through persistent volume at similar price levels over 5 bars
Identifies spoofing patterns via asymmetric wick analysis (wicks exceeding 60% of bar range with volume >1.8× average)
Monitors order clustering using simplified Hawkes process intensity tracking (exponential decay model)
Signal Logic: Contrarian—fades false breakouts caused by institutional manipulation
Best Markets: Consolidations, institutional trading windows, low-liquidity hours
2. Exhaustion Detector Agent ⚡
Calculates RSI divergence between price movement and momentum indicator over 5-bar window
Detects VWAP exhaustion (price at 2σ bands with declining volume)
Uses VPIN reversals (volume-based toxic flow dissipation) to identify momentum failure
Signal Logic: Counter-trend—enters when momentum extreme shows weakness
Best Markets: Trending markets reaching climax points, over-extended moves
3. Liquidity Void Detector Agent 💧
Measures Bollinger Band squeeze (width <60% of 50-period average)
Identifies stop hunts via 20-bar high/low penetration with immediate reversal and volume spike
Detects hidden liquidity absorption (volume >2× average with range <0.3× ATR)
Signal Logic: Breakout anticipation—enters after liquidity grab but before main move
Best Markets: Range-bound pre-breakout, volatility compression zones
4. Mean Reversion Agent 📊
Calculates price z-scores relative to 50-period SMA and standard deviation (triggers at ±2σ)
Implements Ornstein-Uhlenbeck process scoring (mean-reverting stochastic model)
Uses entropy analysis to detect algorithmic trading patterns (low entropy <0.25 = high predictability)
Signal Logic: Statistical reversion—enters when price deviates significantly from statistical equilibrium
Best Markets: Range-bound, low-volatility, algorithmically-dominated instruments
Adaptive Selection: Multi-Armed Bandit System
The script implements four reinforcement learning algorithms to dynamically select or blend agents based on performance:
Thompson Sampling (Default - Recommended):
Uses Bayesian inference with beta distributions (tracks alpha/beta parameters per agent)
Balances exploration (trying underused agents) vs. exploitation (using proven winners)
Each agent's win/loss history informs its selection probability
Lite Approximation: Uses pseudo-random sampling from price/volume noise instead of true random number generation
UCB1 (Upper Confidence Bound):
Calculates confidence intervals using: average_reward + sqrt(2 × ln(total_pulls) / agent_pulls)
Deterministic algorithm favoring agents with high uncertainty (potential upside)
More conservative than Thompson Sampling
Epsilon-Greedy:
Exploits best-performing agent (1-ε)% of the time
Explores randomly ε% of the time (default 10%, configurable 1-50%)
Simple, transparent, easily tuned via epsilon parameter
Gradient Bandit:
Uses softmax probability distribution over agent preference weights
Updates weights via gradient ascent based on rewards
Best for Blend mode where all agents contribute
Selection Modes:
Switch Mode: Uses only the selected agent's signal (clean, decisive)
Blend Mode: Combines all agents using exponentially weighted confidence scores controlled by temperature parameter (smooth, diversified)
Lock Agent Feature:
Optional manual override to force one specific agent
Useful after identifying which agent dominates your specific instrument
Only applies in Switch mode
Four choices: Spoofing Detector, Exhaustion Detector, Liquidity Void, Mean Reversion
Memory System
Dual-Layer Architecture:
Short-Term Memory: Stores last 20 trade outcomes per agent (configurable 10-50)
Long-Term Memory: Stores episode averages when short-term reaches transfer threshold (configurable 5-20 bars)
Memory Boost Mechanism: Recent performance modulates agent scores by up to ±20%
Episode Transfer: When an agent accumulates sufficient results, averages are condensed into long-term storage
Persistence: Manual restoration of learned parameters via input fields (alpha, beta, weights, microstructure thresholds)
How Memory Works:
Agent generates signal → outcome tracked after 8 bars (performance horizon)
Result stored in short-term memory (win = 1.0, loss = 0.0)
Short-term average influences agent's future scores (positive feedback loop)
After threshold met (default 10 results), episode averaged into long-term storage
Long-term patterns (weighted 30%) + short-term patterns (weighted 70%) = total memory boost
Market Microstructure Analysis
These advanced metrics quantify institutional order flow dynamics:
Order Flow Toxicity (Simplified VPIN):
Measures buy/sell volume imbalance over 20 bars: |buy_vol - sell_vol| / (buy_vol + sell_vol)
Detects informed trading activity (institutional players with non-public information)
Values >0.4 indicate "toxic flow" (informed traders active)
Lite Approximation: Uses simple open/close heuristic instead of tick-by-tick trade classification
Price Impact Analysis (Simplified Kyle's Lambda):
Measures market impact efficiency: |price_change_10| / sqrt(volume_sum_10)
Low values = large orders with minimal price impact ( stealth accumulation )
High values = retail-dominated moves with high slippage
Lite Approximation: Uses simplified denominator instead of regression-based signed order flow
Market Randomness (Entropy Analysis):
Counts unique price changes over 20 bars / 20
Measures market predictability
High entropy (>0.6) = human-driven, chaotic price action
Low entropy (<0.25) = algorithmic trading dominance (predictable patterns)
Lite Approximation: Simple ratio instead of true Shannon entropy H(X) = -Σ p(x)·log₂(p(x))
Order Clustering (Simplified Hawkes Process):
Tracks self-exciting event intensity (coordinated order activity)
Decays at 0.9× per bar, spikes +1.0 when volume >1.5× average
High intensity (>0.7) indicates clustering (potential spoofing/accumulation)
Lite Approximation: Simple exponential decay instead of full λ(t) = μ + Σ α·exp(-β(t-tᵢ)) with MLE
Signal Generation Process
Multi-Stage Validation:
Stage 1: Agent Scoring
Each agent calculates internal score based on its detection criteria
Scores must exceed agent-specific threshold (adjusted by sensitivity multiplier)
Agent outputs: Signal direction (+1/-1/0) and Confidence level (0.0-1.0)
Stage 2: Memory Boost
Agent scores multiplied by memory boost factor (0.8-1.2 based on recent performance)
Successful agents get amplified, failing agents get dampened
Stage 3: Bandit Selection/Blending
If Adaptive Mode ON:
Switch: Bandit selects single best agent, uses only its signal
Blend: All agents combined using softmax-weighted confidence scores
If Adaptive Mode OFF:
Traditional consensus voting with confidence-squared weighting
Signal fires when consensus exceeds threshold (default 70%)
Stage 4: Confirmation Filter
Raw signal must repeat for consecutive bars (default 3, configurable 2-4)
Minimum confidence threshold: 0.25 (25%) enforced regardless of mode
Trend alignment check: Long signals require trend_score ≥ -2, Short signals require trend_score ≤ 2
Stage 5: Cooldown Enforcement
Minimum bars between signals (default 10, configurable 5-15)
Prevents over-trading during choppy conditions
Stage 6: Performance Tracking
After 8 bars (performance horizon), signal outcome evaluated
Win = price moved in signal direction, Loss = price moved against
Results fed back into memory and bandit statistics
Trading Modes (Presets)
Pre-configured parameter sets:
Conservative: 85% consensus, 4 confirmations, 15-bar cooldown
Expected: 60-70% win rate, 3-8 signals/week
Best for: Swing trading, capital preservation, beginners
Balanced: 70% consensus, 3 confirmations, 10-bar cooldown
Expected: 55-65% win rate, 8-15 signals/week
Best for: Day trading, most traders, general use
Aggressive: 60% consensus, 2 confirmations, 5-bar cooldown
Expected: 50-58% win rate, 15-30 signals/week
Best for: Scalping, high-frequency trading, active management
Elite: 75% consensus, 3 confirmations, 12-bar cooldown
Expected: 58-68% win rate, 5-12 signals/week
Best for: Selective trading, high-conviction setups
Adaptive: 65% consensus, 2 confirmations, 8-bar cooldown
Expected: Varies based on learning
Best for: Experienced users leveraging bandit system
How to Use
1. Initial Setup (5 Minutes):
Select Trading Mode matching your style (start with Balanced)
Enable Adaptive Learning (recommended for automatic agent selection)
Choose Thompson Sampling algorithm (best all-around performance)
Keep Microstructure Metrics enabled for liquid instruments (>100k daily volume)
2. Agent Tuning (Optional):
Adjust Agent Sensitivity multipliers (0.5-2.0):
<0.8 = Highly selective (fewer signals, higher quality)
0.9-1.2 = Balanced (recommended starting point)
1.3 = Aggressive (more signals, lower individual quality)
Monitor dashboard for 20-30 signals to identify dominant agent
If one agent consistently outperforms, consider using Lock Agent feature
3. Bandit Configuration (Advanced):
Blend Temperature (0.1-2.0):
0.3 = Sharp decisions (best agent dominates)
0.5 = Balanced (default)
1.0+ = Smooth (equal weighting, democratic)
Memory Decay (0.8-0.99):
0.90 = Fast adaptation (volatile markets)
0.95 = Balanced (most instruments)
0.97+ = Long memory (stable trends)
4. Signal Interpretation:
Green triangle (▲): Long signal confirmed
Red triangle (▼): Short signal confirmed
Dashboard shows:
Active agent (highlighted row with ► marker)
Win rate per agent (green >60%, yellow 40-60%, red <40%)
Confidence bars (█████ = maximum confidence)
Memory size (short-term buffer count)
Colored zones display:
Entry level (current close)
Stop-loss (1.5× ATR)
Take-profit 1 (2.0× ATR)
Take-profit 2 (3.5× ATR)
5. Risk Management:
Never risk >1-2% per signal (use ATR-based stops)
Signals are entry triggers, not complete strategies
Combine with your own market context analysis
Consider fundamental catalysts and news events
Use "Confirming" status to prepare entries (not to enter early)
6. Memory Persistence (Optional):
After 50-100 trades, check Memory Export Panel
Record displayed alpha/beta/weight values for each agent
Record VPIN and Kyle threshold values
Enable "Restore From Memory" and input saved values to continue learning
Useful when switching timeframes or restarting indicator
Visual Components
On-Chart Elements:
Spectral Layers: EMA8 ± 0.5 ATR bands (dynamic support/resistance, colored by trend)
Energy Radiance: Multi-layer glow boxes at signal points (intensity scales with confidence, configurable 1-5 layers)
Probability Cones: Projected price paths with uncertainty wedges (15-bar projection, width = confidence × ATR)
Connection Lines: Links sequential signals (solid = same direction continuation, dotted = reversal)
Kill Zones: Risk/reward boxes showing entry, stop-loss, and dual take-profit targets
Signal Markers: Triangle up/down at validated entry points
Dashboard (Configurable Position & Size):
Regime Indicator: 4-level trend classification (Strong Bull/Bear, Weak Bull/Bear)
Mode Status: Shows active system (Adaptive Blend, Locked Agent, or Consensus)
Agent Performance Table: Real-time win%, confidence, and memory stats
Order Flow Metrics: Toxicity and impact indicators (when microstructure enabled)
Signal Status: Current state (Long/Short/Confirming/Waiting) with confirmation progress
Memory Panel (Configurable Position & Size):
Live Parameter Export: Alpha, beta, and weight values per agent
Adaptive Thresholds: Current VPIN sensitivity and Kyle threshold
Save Reminder: Visual indicator if parameters should be recorded
What Makes This Original
This script's originality lies in three key innovations:
1. Genuine Meta-Learning Framework:
Unlike traditional indicator mashups that simply display multiple signals, this implements authentic reinforcement learning (multi-armed bandits) to learn which detection method works best in current conditions. The Thompson Sampling implementation with beta distribution tracking (alpha for successes, beta for failures) is statistically rigorous and adapts continuously. This is not post-hoc optimization—it's real-time learning.
2. Episodic Memory Architecture with Transfer Learning:
The dual-layer memory system mimics human learning patterns:
Short-term memory captures recent performance (recency bias)
Long-term memory preserves historical patterns (experience)
Automatic transfer mechanism consolidates knowledge
Memory boost creates positive feedback loops (successful strategies become stronger)
This architecture allows the system to adapt without retraining , unlike static ML models that require batch updates.
3. Institutional Microstructure Integration:
Combines retail-focused technical analysis (RSI, Bollinger Bands, VWAP) with institutional-grade microstructure metrics (VPIN, Kyle's Lambda, Hawkes processes) typically found in academic finance literature and professional trading systems, not standard retail platforms. While simplified for Pine Script constraints, these metrics provide insight into informed vs. uninformed trading , a dimension entirely absent from traditional technical analysis.
Mashup Justification:
The four agents are combined specifically for risk diversification across failure modes:
Spoofing Detector: Prevents false breakout losses from manipulation
Exhaustion Detector: Prevents chasing extended trends into reversals
Liquidity Void: Exploits volatility compression (different regime than trending)
Mean Reversion: Provides mathematical anchoring when patterns fail
The bandit system ensures the optimal tool is automatically selected for each market situation, rather than requiring manual interpretation of conflicting signals.
Why "ML-lite"? Simplifications and Approximations
This is the "lite" version due to necessary simplifications for Pine Script execution:
1. Simplified VPIN Calculation:
Academic Implementation: True VPIN uses volume bucketing (fixed-volume bars) and tick-by-tick buy/sell classification via Lee-Ready algorithm or exchange-provided trade direction flags
This Implementation: 20-bar rolling window with simple open/close heuristic (close > open = buy volume)
Impact: May misclassify volume during ranging/choppy markets; works best in directional moves
2. Pseudo-Random Sampling:
Academic Implementation: Thompson Sampling requires true random number generation from beta distributions using inverse transform sampling or acceptance-rejection methods
This Implementation: Deterministic pseudo-randomness derived from price and volume decimal digits: (close × 100 - floor(close × 100)) + (volume % 100) / 100
Impact: Not cryptographically random; may have subtle biases in specific price ranges; provides sufficient variation for agent selection
3. Hawkes Process Approximation:
Academic Implementation: Full Hawkes process uses maximum likelihood estimation with exponential kernels: λ(t) = μ + Σ α·exp(-β(t-tᵢ)) fitted via iterative optimization
This Implementation: Simple exponential decay (0.9 multiplier) with binary event triggers (volume spike = event)
Impact: Captures self-exciting property but lacks parameter optimization; fixed decay rate may not suit all instruments
4. Kyle's Lambda Simplification:
Academic Implementation: Estimated via regression of price impact on signed order flow over multiple time intervals: Δp = λ × Δv + ε
This Implementation: Simplified ratio: price_change / sqrt(volume_sum) without proper signed order flow or regression
Impact: Provides directional indicator of impact but not true market depth measurement; no statistical confidence intervals
5. Entropy Calculation:
Academic Implementation: True Shannon entropy requires probability distribution: H(X) = -Σ p(x)·log₂(p(x)) where p(x) is probability of each price change magnitude
This Implementation: Simple ratio of unique price changes to total observations (variety measure)
Impact: Measures diversity but not true information entropy with probability weighting; less sensitive to distribution shape
6. Memory System Constraints:
Full ML Implementation: Neural networks with backpropagation, experience replay buffers (storing state-action-reward tuples), gradient descent optimization, and eligibility traces
This Implementation: Fixed-size array queues with simple averaging; no gradient-based learning, no state representation beyond raw scores
Impact: Cannot learn complex non-linear patterns; limited to linear performance tracking
7. Limited Feature Engineering:
Advanced Implementation: Dozens of engineered features, polynomial interactions (x², x³), dimensionality reduction (PCA, autoencoders), feature selection algorithms
This Implementation: Raw agent scores and basic market metrics (RSI, ATR, volume ratio); minimal transformation
Impact: May miss subtle cross-feature interactions; relies on agent-level intelligence rather than feature combinations
8. Single-Instrument Data:
Full Implementation: Multi-asset correlation analysis (sector ETFs, currency pairs, volatility indices like VIX), lead-lag relationships, risk-on/risk-off regimes
This Implementation: Only OHLCV data from displayed instrument
Impact: Cannot incorporate broader market context; vulnerable to correlated moves across assets
9. Fixed Performance Horizon:
Full Implementation: Adaptive horizon based on trade duration, volatility regime, or profit target achievement
This Implementation: Fixed 8-bar evaluation window
Impact: May evaluate too early in slow markets or too late in fast markets; one-size-fits-all approach
Performance Impact Summary:
These simplifications make the script:
✅ Faster: Executes in milliseconds vs. seconds (or minutes) for full academic implementations
✅ More Accessible: Runs on any TradingView plan without external data feeds, APIs, or compute servers
✅ More Transparent: All calculations visible in Pine Script (no black-box compiled models)
✅ Lower Resource Usage: <500 bars lookback, minimal memory footprint
⚠️ Less Precise: Approximations may reduce statistical edge by 5-15% vs. academic implementations
⚠️ Limited Scope: Cannot capture tick-level dynamics, multi-order-book interactions, or cross-asset flows
⚠️ Fixed Parameters: Some thresholds hardcoded rather than dynamically optimized
When to Upgrade to Full Implementation:
Consider professional Python/C++ versions with institutional data feeds if:
Trading with >$100K capital where precision differences materially impact returns
Operating in microsecond-competitive environments (HFT, market making)
Requiring regulatory-grade audit trails and reproducibility
Backtesting with tick-level precision for strategy validation
Need true real-time adaptation with neural network-based learning
For retail swing/day trading and position management, these approximations provide sufficient signal quality while maintaining usability, transparency, and accessibility. The core logic—multi-agent detection with adaptive selection—remains intact.
Technical Notes
All calculations use standard Pine Script built-in functions ( ta.ema, ta.atr, ta.rsi, ta.bb, ta.sma, ta.stdev, ta.vwap )
VPIN and Kyle's Lambda use simplified formulas optimized for OHLCV data (see "Lite" section above)
Thompson Sampling uses pseudo-random noise from price/volume decimal digits for beta distribution sampling
No repainting: All calculations use confirmed bar data (no forward-looking)
Maximum lookback: 500 bars (set via max_bars_back parameter)
Performance evaluation: 8-bar forward-looking window for reward calculation (clearly disclosed)
Confidence threshold: Minimum 0.25 (25%) enforced on all signals
Memory arrays: Dynamic sizing with FIFO queue management
Limitations and Disclaimers
Not Predictive: This indicator identifies patterns in historical data. It cannot predict future price movements with certainty.
Requires Human Judgment: Signals are entry triggers, not complete trading strategies. Must be confirmed with your own analysis, risk management rules, and market context.
Learning Period Required: The adaptive system requires 50-100 bars minimum to build statistically meaningful performance data for bandit algorithms.
Overfitting Risk: Restoring memory parameters from one market regime to a drastically different regime (e.g., low volatility to high volatility) may cause poor initial performance until system re-adapts.
Approximation Limitations: Simplified calculations (see "Lite" section) may underperform academic implementations by 5-15% in highly efficient markets.
No Guarantee of Profit: Past performance, whether backtested or live-traded, does not guarantee future performance. All trading involves risk of loss.
Forward-Looking Bias: Performance evaluation uses 8-bar forward window—this creates slight look-ahead for learning (though not for signals). Real-time performance may differ from indicator's internal statistics.
Single-Instrument Limitation: Does not account for correlations with related assets or broader market regime changes.
Recommended Settings
Timeframe: 15-minute to 4-hour charts (sufficient volatility for ATR-based stops; adequate bar volume for learning)
Assets: Liquid instruments with >100k daily volume (forex majors, large-cap stocks, BTC/ETH, major indices)
Not Recommended: Illiquid small-caps, penny stocks, low-volume altcoins (microstructure metrics unreliable)
Complementary Tools: Volume profile, order book depth, market breadth indicators, fundamental catalysts
Position Sizing: Risk no more than 1-2% of capital per signal using ATR-based stop-loss
Signal Filtering: Consider external confluence (support/resistance, trendlines, round numbers, session opens)
Start With: Balanced mode, Thompson Sampling, Blend mode, default agent sensitivities (1.0)
After 30+ Signals: Review agent win rates, consider increasing sensitivity of top performers or locking to dominant agent
Alert Configuration
The script includes built-in alert conditions:
Long Signal: Fires when validated long entry confirmed
Short Signal: Fires when validated short entry confirmed
Alerts fire once per bar (after confirmation requirements met)
Set alert to "Once Per Bar Close" for reliability
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Swing High/Low Support ResistanceThis indicator detects recent swing highs and swing lows using Pine Script pivots and marks them with visible chart labels. These points highlight potential turning areas in price action and can help identify short-term support or resistance for intraday or swing trading.
How to Apply
Locate the indicator in TradingView’s “Indicators” library; search by its name or author.
Click the star icon to mark it as a favourite for quick future access.
Apply directly to your chosen chart and timeframe with a single click—no need to enter or paste code.
Adjust the input parameters from the settings panel if desired to personalize swing sensitivity.
Choose Your Timeframe:
Apply to any intraday or swing timeframe; shorter lengths show more frequent pivots.
Set Sensitivity:
Use the “Swing Detection Length” input to adjust how many bars define a pivot, making swings more or less sensitive to price action.
How to Analyze
Swing High Labels: Mark recent local peaks, suggesting resistance zones or possible reversal points.
Swing Low Labels: Highlight recent bottoms, indicating support or bounce areas.
Monitor labels for clustering or repeated appearance at similar levels, which may strengthen their importance as price reacts near those points.
Track how price behaves after forming new pivots—multiple tests can affirm the relevance of a level.
What Traders Should Watch
Price reaction at labeled areas: frequent tests may anticipate reversals or breakouts.
Transition between higher highs/higher lows (uptrend) vs. lower highs/lower lows (downtrend).
Combine the swing levels with other analysis methods, such as volume, RSI, or EMA, for better signal quality.
Features Included
Dynamic swing high and low detection via confirmed pivots.
Direct labeling on the chart for market structure clarity.
No repainting—labels show only after complete formation.
Fully automatic updates as price action unfolds.
No promotional, external, or non-compliant elements; open source and safe for public or private use.
Compliance Notes
No signals, buy/sell calls, financial advice, or performance claims.
No hidden code, advertising, or off-platform contacts.
Pure educational and analytical utility; adheres to all TradingView house rules and script publishing policies.
Disclaimer
This indicator is for informational purposes only and does not constitute advice. Always do your own research and use proper risk management.
TraderDemircan Fibonacci + XABCD Formation v1.0This indicator automatically identifies the most recent significant swing low (Point X) and the subsequent swing high (Point A) to plot a comprehensive set of Fibonacci extension levels.
Beyond a standard Fibonacci tool, this script also projects a potential harmonic XABCD pattern. It identifies a retracement level (Point B) and projects a "C" target based on the XA=BC price projection. This provides traders with a complete visual framework of key support/resistance levels and potential price targets based on the last significant impulse move.
How It Works
Swing Detection (X & A Points): The script scans the previous Lookback Bars (user-defined) to find the lowest low, which it labels as Point X. It then finds the highest high that occurred after Point X, labeling it as Point A.
Fibonacci Levels: The price range between X and A (the "XA leg") is used as the basis (0.0 to 1.0) to draw 18 different Fibonacci levels, including key extensions (1.272, 1.618, 2.618, etc.) and retracements.
XABCD Projection (B & C Points):
Point B: The script dynamically identifies Point B at either the 0.382 or 0.5 retracement level of the XA leg, depending on the current price action. This shows the level that is currently acting as support.
Point C (Target): A target (Point C) is projected by adding the price range of the XA leg to the B point. This creates a classic XA=BC (or AB=CD, where the first leg is XA) price projection, offering a potential target for the next upward move.
Key Features
Automatic Swing Detection: Automatically finds and plots the X and A points, adapting to the latest price action.
Comprehensive Fibonacci Suite: Includes 18 toggleable Fibonacci levels (from 0.0 to 4.618) to cover all common retracement and extension targets.
XABCD Pattern & Target: Visually plots the X-A, A-B, and the projected B-C legs, clearly highlighting the C target.
Dynamic "B" Point: The B point label (0.382 or 0.5) updates to reflect which retracement level is currently in play.
On-Screen Info Table: A clean table in the top-right corner displays the exact price values for X, A, B, and the C Target for quick reference.
Full Customization: Users can control the visibility, color, width, and style of every Fibonacci level and pattern line.
Label Options: Toggle price labels (on the right) and percentage/level labels (on the left) for a clean or detailed chart.
cd_sfp_CxGeneral:
This indicator is designed to assist users who trade the Swing Failure Pattern ( SFP ).
In technical literature (various definitions exist), an SFP is a situation where the price violates a previous swing level but fails to close beyond that level.
• (Liquidity Sweep)
• (Buyer or seller dominance)
• (Stop hunt)
• (Turtle Soup)
The general strategy is built upon seeking trade opportunities after an SFP is formed and conviction is established that the market direction has changed.
Components used to gather confirmation:
• Determining Bias: Periodic SAR
• Obtaining Breakout/Reversal Confirmation: Change in State Delivery (CISD)
• Defining the Buyer/Seller Block (Supply/Demand Zones): Mitg Blocks (Mitigation Blocks), FVG (Fair Value Gaps), and Standard Deviation Projection
• Key Levels: Previous HTF (Higher Time Frame) levels
• Setting Targets: Standard Deviation Projection
• Trade Management: Anchored VWAP and opposing blocks
• Time-Based Context: Session Killzone times
• Notifications: An alarm/alert system will be utilized to stay informed.
________________________________________
Details:
Swing and Swing Failure Pattern:
Swing Sweep Types (Liquidity Sweep):
1. Single
2. Consecutive (The liquidity of the entity that swept the liquidity is being swept)
Bias Determination
We need to filter out the numerous SFPs that occur across all time frames. Our first strong filter will be the Bias. We will only look for trades aligned with our bias.
We will use Periodic SAR (Stop and Reverse) to determine the bias. We compare the price with the SAR value from a Higher Time Frame than the one we are trading on.
• Price > SAR => Bullish Bias
• Price < SAR => Bearish Bias
Depending on the pair, H1 SAR may be chosen for scalp trades, and Daily/Weekly SAR for intraday and swing trades.
Key Levels
Strategies looking for trades after a liquidity grab generally state that the sweep / stop hunt movement should occur at a significant price level.
The most fundamental Key Level levels are (User can customize):
• Previous Week High & Low
• Previous Day High & Low
• Previous H4 High & Low
• Previous H1 High & Low
• Asia Killzone High & Low
• London Killzone High & Low
• New York Killzone High & Low
• Monday Range High & Low values
We will prefer SFP formations that occur when these levels are swept. When Key Levels are violated, an information label appears on the screen.
Blocks / Zones
To strengthen our hand, we will use three types of blocks/zones, either with Key Levels or separately. When an SFP structure is formed in these areas (along with bias and breakout confirmation), our expectation is for the price to continue in our desired direction. These regions are:
1. Mitigation Blocks (Mtg)
o (Details can be found in the cd_VWAP_mtg_Cx indicator)
o In short: A second candle, following a bullish candle, crosses its high but fails to close above it. We call this a sweep / SFP. When the price, which was expected to go to the low, instead makes a new high/close, an Mtg block is formed. (Buyers are dominant)
2. FVGs (Fair Value Gaps)
o We use classic FVG structures.
3. Standard Deviation Projection Boxes
o When we get an SFP structure + breakout confirmation (CISD), we use the Standard Deviation Projection to determine our profit-taking and take-profit levels.
o Based on the idea that the price often respects the range between -2 and -2.5 of the projection values, we box this range and use it as our area of interest. (Our expectation is for the price to reverse after reaching this target).
o Let's mark it on the chart.
Confirmation
To summarize what has been explained so far: we look for the price to form an SFP structure in levels/zones we deem important, aligned with our bias, and for the breakout to be confirmed with a CISD.
No single component is strong on its own, but the success rate increases when they occur together.
We observe the following as additional confirmation along with the CISD: a new Mtg block forming in the direction of the breakout, high-volume movement (with FVG and a large body), and respect for VWAPs, the resistance/support line, and the defense block.
Additional Confirmations with Breakouts:
• Defence block, new mtg and VWAP
• Resistance / Support Line:
Indicator Signals
The indicator marks all formed sweeps, selected key levels, blocks, the projection, and CISD confirmations on the screen. The candle where the CISD confirmation occurs is indicated by an arrow.
• Arrows with double short lines signify a CISD that follows an SFP occurring at a Key Level.
• All other CISD candle indications are shown with single-line arrows.
Trade Management
When selecting profit targets in trades (preferably), the projection, opposing blocks, and structures that have formed are taken into account. Do not neglect to look at the structures that have formed against you when entering a trade.
Menu Settings:
• For Mtg blocks, the trading timeframe or a higher timeframe can be selected.
• FVGs formed in the current timeframe are displayed when the price creates an SFP (in "Fvg" option).
• Deviation boxes are displayed when the price creates an SFP (in box).
• The SAR HTF setting (H1) for scalp trades may vary depending on the pair. Users trying trades on higher timeframes should increase the HTF setting.
o Example: If you are looking for a trade with an SFP structure on H1, the SAR HTF setting should be H4 or higher.
• VWAP lines are refreshed starting from the candle that executed the sweep when the price forms an SFP. The only setting to adjust is the source selection setting (hlc3 is selected).
• Time frames and Killzone / Special Zone settings for Key Levels can be changed/should be checked.
Alarms / Alerts:
The conditions that will trigger an alert can be selected from the menu.
• To receive an alert aligned with the bias, the "Alignment with bias" checkbox must be selected.
• The alert should be set on the timeframe where you plan to enter the trade.
• The display options do not affect the alarm conditions. (Example: FVGs are monitored even when the menu selection is "off").
• If the necessary conditions are met, the alarm is triggered on the new candle that opens after the CISD confirmation.
• The alarm will not be triggered more than once at the same Key Level.
The user can preferably select alerts:
• Bias-aligned or Bias-independent
• Sweep (without waiting for CISD)
• Sweep + CISD (without looking for other conditions)
• Sweep + Key Level + CISD (the swept level is a Key Level)
• Sweep + Mtg / Fvg / Dev. + CISD (SFP formed in any of the blocks)
• Sweep + Mtg + CISD (SFP formed in the Mtg block)
• Sweep + Fvg + CISD (SFP formed inside the FVG)
• Sweep + Deviation Box + CISD (SFP formed inside the Dev. Box)
• Sweep + Key Level + Mtg / Fvg / Dev. + CISD (SFP formed simultaneously at a Key Level and any of the blocks)
Trade Example:
• Conditions: Bias-aligned + Sweep + Mtg/Fvg/Dev (at least one) + CISD
• Extra Confirmations: Respect for the Defense Block + Respect for VWAP
• Target (TP): Projection between -2 and -2.5
I welcome your thoughts and suggestions regarding my indicator, which I believe will be successful in the long run by adhering to uncompromising risk management and a strict trading plan.
Happy Trading!
dhruv private 91400//@version=5
//
VERSION = '7.9-X'// 2024.3.20
strategy(
'LE VAN DO® - Swing Signals & Overlays Private™ 7.9-X',
shorttitle = 'LE VAN DO® - Swing Signals & Overlays Private™ 7.9-X' + VERSION,
overlay = true,
explicit_plot_zorder = true,
pyramiding = 0,
default_qty_type = strategy.percent_of_equity,
default_qty_value = 50,
calc_on_every_tick = false,
process_orders_on_close = true,
max_bars_back = 500,
initial_capital = 5000,
commission_type = strategy.commission.percent,
commission_value = 0.02,
max_lines_count = 500
)
//Truncate Function
truncate(number, decimals) =>
factor = math.pow(10, decimals)
int(number * factor) / factor
//
// === INPUTS ===
TPSType = input.string('Trailing', 'What TPS should be taken : ', options = )
setupType = input.string('Open/Close', title='What Trading Setup should be taken : ', options= )
scolor = input(true, title='Show coloured Bars to indicate Trend?')
almaRibbon = input(false, title='Enable Ribbon?')
//tradeType = input.string('BOTH', title='What trades should be taken : ', options= )
// === /INPUTS ===
// Display the probabilities in a table
//text01_ = str.tostring(timeframe.multiplier * intRes, '####')
//t = timenow + math.round(ta.change(time) * 25)
//var label lab01 = na
//label.delete(lab01)
//lab01 := label.new(t, close, text=text01_, style=label.style_label_left, yloc=yloc.price, xloc=xloc.bar_time, textalign=text.align_left, textcolor=color.white)
// Constants colours that include fully non-transparent option.
green100 = #008000FF
lime100 = #66bb6a
red100 = #f7525f
blue100 = #0000FFFF
aqua100 = #00FFFFFF
darkred100 = #8B0000FF
gray100 = #808080FF
/////////////////////////////////////////////
// Create non-repainting security function
rp_security(_symbol, _res, _src) =>
request.security(_symbol, _res, _src )
//
f_tfInMinutes() =>
_tfInMinutes = timeframe.period == '1' ? '3' : timeframe.period == '3' ? '5' : timeframe.period == '5' ? '15' : timeframe.period == '15' ? '30' : timeframe.period == '30' ? '60' : timeframe.period == '60' ? '240' : 'D'
_tfInMinutes
my_time1 = f_tfInMinutes()
tfmult = 18 //input.int(18, "Input Timeframe Multiplier")
f_resInMinutes() =>
_resInMinutes = timeframe.multiplier * (
timeframe.isseconds ? 1. / 60. :
timeframe.isminutes ? 1. :
timeframe.isdaily ? 1440. :
timeframe.isweekly ? 10080. :
timeframe.ismonthly ? 43800. : na)
my_time = str.tostring(f_resInMinutes()*tfmult)
useSource = close //input.string('Close', 'What Source to be used?', options = )
enableFilter = input(true, "Enable Backtesting Range Filtering")
fromDate = input.time(timestamp("01 Jan 2023 00:00 +0300"), "Start Date")
toDate = input.time(timestamp("31 Dec 2099 00:00 +0300"), "End Date")
tradeDateIsAllowed = not enableFilter or (time >= fromDate and time <= toDate)
filter1 = 'Filter with Atr'
filter2 = 'Filter with RSI'
filter3 = 'Atr or RSI'
filter4 = 'Atr and RSI'
filter5 = 'No Filtering'
filter6 = 'Entry Only in sideways market(By ATR or RSI)'
filter7 = 'Entry Only in sideways market(By ATR and RSI)'
typefilter = input.string(filter5, title='Sideways Filtering Input', options= , group='Strategy Options')
RSI = truncate(ta.rsi(close, input.int(7, group='RSI Filterring')), 2)
toplimitrsi = input.int(45, title='TOP Limit', group='RSI Filterring')
botlimitrsi = input.int(10, title='BOT Limit', group='RSI Filterring')
//ST = input.bool(true, title='Show Supertrend?', group='Supertrend Indicator')
//period = input.int(1440, group='Supertrend Indicator')
//mult = input.float(2.612, group='Supertrend Indicator')
atrfiltLen = 5 //input.int(5, minval=1, title='atr Length', group='Sideways Filtering Input')
atrMaType = 'EMA' //input.string('EMA', options= , group='Sideways Filtering Input', title='atr Moving Average Type')
atrMaLen = 5 //input.int(5, minval=1, title='atr MA Length', group='Sideways Filtering Input')
//filtering
atra = request.security(syminfo.tickerid, '', ta.atr(atrfiltLen))
atrMa = atrMaType == 'EM' ? ta.ema(atra, atrMaLen) : ta.sma(atra, atrMaLen)
updm = ta.change(high)
downdm = -ta.change(low)
plusdm = na(updm) ? na : updm > downdm and updm > 0 ? updm : 0
minusdm = na(downdm) ? na : downdm > updm and downdm > 0 ? downdm : 0
cndSidwayss1 = atra >= atrMa
cndSidwayss2 = RSI > toplimitrsi or RSI < botlimitrsi
cndSidways = cndSidwayss1 or cndSidwayss2
cndSidways1 = cndSidwayss1 and cndSidwayss2
Sidwayss1 = atra <= atrMa
Sidwayss2 = RSI < toplimitrsi and RSI > botlimitrsi
Sidways = Sidwayss1 or Sidwayss2
Sidways1 = Sidwayss1 and Sidwayss2
trendType = typefilter == filter1 ? cndSidwayss1 : typefilter == filter2 ? cndSidwayss2 : typefilter == filter3 ? cndSidways : typefilter == filter4 ? cndSidways1 : typefilter == filter5 ? RSI > 0 : typefilter == filter6 ? Sidways : typefilter == filter7 ? Sidways1 : na
// === /INPUTS ===
tf = my_time //input('15')
r = ticker.heikinashi(syminfo.tickerid)
openSeriesAlt = request.security(r, tf, open, lookahead=barmerge.lookahead_on)
closeSeriesAlt = request.security(r, tf, close, lookahead=barmerge.lookahead_on)
//openP = plot(almaRibbon ? openSeriesAlt : na, color=color.new(color.lime, 0), linewidth=3)
//closeP = plot(almaRibbon ? closeSeriesAlt : na, color=color.new(color.red, 0), linewidth=3)
BUYOC = ta.crossover(closeSeriesAlt, openSeriesAlt) and setupType == "Open/Close" and trendType
SELLOC = ta.crossunder(closeSeriesAlt, openSeriesAlt) and setupType == "Open/Close" and trendType
//strategy.entry('sell', direction=strategy.short, qty=trade_size, comment='sell', when=sel_entry)
//strategy.entry('buy', direction=strategy.long, qty=trade_size, comment='buy', when=buy_entry)
//trendColour = closeSeriesAlt > openSeriesAlt ? color.green : color.red
//bcolour = closeSeriesAlt > openSeriesAlt ? lime100 : red100
//barcolor(scolor ? bcolour : na, title='Bar Colours')
//closeP = plot(almaRibbon ? closeSeriesAlt : na, title='Close Series', color=color.new(trendColour, 20), linewidth=2, style=plot.style_line)
//openP = plot(almaRibbon ? openSeriesAlt : na, title='Open Series', color=color.new(trendColour, 20), linewidth=2, style=plot.style_line)
//fill(closeP, openP, color=color.new(trendColour, 80))
//
//rt = input(true, title="ATR Based REnko is the Default, UnCheck to use Traditional ATR?")
atrLen = 3 //input.int(3, title="RENKO_ATR", group = "Renko Settings")
isATR = true //input.bool(true, title="RENKO_USE_RENKO_ATR", group = "Renko Settings")
tradLen1 = 1000 //input.int(1000, title="RENKO_TRADITIONAL", group = "Renko Settings")
//Code to be implemented in V2
//mul = input(1, "Number Of minticks")
//value = mul * syminfo.mintick
tradLen = tradLen1 * 1
param = isATR ? ticker.renko(syminfo.tickerid, "ATR", atrLen) : ticker.renko(syminfo.tickerid, "Traditional", tradLen)
renko_close = request.security(param, my_time, close, lookahead=barmerge.lookahead_on)
renko_open = request.security(param, my_time, open, lookahead=barmerge.lookahead_on)
//============================================
//Sniper------------------------------------------------------------------------------------------------------------------------------------- // Signal 2
//============================================
//============================================
//EMA_CROSS-------------------------------------------------------------------------------------------------------------------------------- // Signal 4
//============================================
EMA1_length=input.int(2, "EMA1_length", group = "Renko Settings")
EMA2_length=input.int(10, "EMA2_length", group = "Renko Settings")
a = ta.ema(renko_close, EMA1_length)
b = ta.ema(renko_close, EMA2_length)
//BUY = ta.cross(a, b) and a > b and renko_open < renko_close
//SELL = ta.cross(a, b) and a < b and renko_close < renko_open
///////////////////////////////
// Determine long and short conditions
BUYR = ta.crossover(a, b) and setupType == "Renko" and trendType
SELLR = ta.crossunder(a, b) and setupType == "Renko" and trendType
sel_color = setupType == "Open/Close" ? closeSeriesAlt < openSeriesAlt : setupType == "Renko" ? renko_close < renko_open : na
buy_color = setupType == "Open/Close" ? closeSeriesAlt > openSeriesAlt : setupType == "Renko" ? renko_close > renko_open : na
sel_entry = setupType == "Open/Close" ? SELLOC : setupType == "Renko" ? SELLR : na
buy_entry = setupType == "Open/Close" ? BUYOC : setupType == "Renko" ? BUYR : na
trendColour = buy_color ? color.green : color.red
bcolour = buy_color ? lime100 : red100
barcolor(scolor ? bcolour : na, title='Bar Colours')
p11=plot(almaRibbon and setupType == "Open/Close" ? closeSeriesAlt : almaRibbon and setupType == "Renko" ? renko_close : na, style=plot.style_circles, linewidth=1, color=color.new(trendColour, 80), title="RENKO_1")
p22=plot(almaRibbon and setupType == "Open/Close" ? openSeriesAlt : almaRibbon and setupType == "Renko" ? renko_open : na, style=plot.style_circles, linewidth=1, color=color.new(trendColour, 80), title="RENKO_2")
fill(p11, p22, color=color.new(trendColour, 50), title="RENKO_fill")
//
lxTrigger = false
sxTrigger = false
leTrigger = buy_entry
seTrigger = sel_entry
// === /ALERT conditions.
buy = leTrigger //ta.crossover(closeSeriesAlt, openSeriesAlt)
sell = seTrigger //ta.crossunder(closeSeriesAlt, openSeriesAlt)
varip wasLong = false
varip wasShort = false
if barstate.isconfirmed
wasLong := false
else
if buy
wasLong := true
if barstate.isconfirmed
wasShort := false
else
if sell
wasShort := true
plotshape(wasLong, color = color.yellow)
plotshape(wasShort, color = color.yellow)
//plotshape(almaRibbon ? buy : na, title = "Buy", text = 'Buy', style = shape.labelup, location = location.belowbar, color= #39ff14, textcolor = #FFFFFF, size = size.tiny)
//plotshape(almaRibbon ? sell : na, title = "Exit", text = 'Exit', style = shape.labeldown, location = location.abovebar, color= #ff1100, textcolor = #FFFFFF, size = size.tiny)
// === STRATEGY ===
i_alert_txt_entry_long = "Short Exit" //input.text_area(defval = "Short Exit", title = "Long Entry Message", group = "Alerts")
i_alert_txt_exit_long = "Long Exit" //input.text_area(defval = "Long Exit", title = "Long Exit Message", group = "Alerts")
i_alert_txt_entry_short = "Go Short" //input.text_area(defval = "Go Short", title = "Short Entry Message", group = "Alerts")
i_alert_txt_exit_short = "Go Long" //input.text_area(defval = "Go Long", title = "Short Exit Message", group = "Alerts")
// Entries and Exits with TP/SL
//tradeType
if buy and TPSType == "Trailing" and tradeDateIsAllowed
strategy.close("Short" , alert_message = i_alert_txt_exit_short)
strategy.entry("Long" , strategy.long , alert_message = i_alert_txt_entry_long)
if sell and TPSType == "Trailing" and tradeDateIsAllowed
strategy.close("Long" , alert_message = i_alert_txt_exit_long)
strategy.entry("Short" , strategy.short, alert_message = i_alert_txt_entry_short)
//tradeType
if buy and TPSType == "Options" and tradeDateIsAllowed
// strategy.close("Short" , alert_message = i_alert_txt_exit_short)
strategy.entry("Long" , strategy.long , alert_message = i_alert_txt_entry_long)
if sell and TPSType == "Options" and tradeDateIsAllowed
strategy.close("Long" , alert_message = i_alert_txt_exit_long)
// strategy.entry("Short" , strategy.short, alert_message = i_alert_txt_entry_short)
G_RISK = '■ ' + 'Risk Management'
//#region ———— <↓↓↓ G_RISK ↓↓↓> {
//ATR SL Settings
atrLength = 20 //input.int(20, minval=1, title='ATR Length')
profitFactor = 2.5 //input(2.5, title='Take Profit Factor')
stopFactor = 1 //input(1.0, title='Stop Loss Factor')
// Calculate ATR
tpatrValue = ta.atr(atrLength)
// Calculate take profit and stop loss levels for buy signals
takeProfit1_buy = 1 * profitFactor * tpatrValue //close + profitFactor * atrValue
takeProfit2_buy = 2 * profitFactor * tpatrValue //close + 2 * profitFactor * atrValue
takeProfit3_buy = 3 * profitFactor * tpatrValue //close + 3 * profitFactor * atrValue
stopLoss_buy = close - takeProfit1_buy //stopFactor * tpatrValue
// Calculate take profit and stop loss levels for sell signals
takeProfit1_sell = 1 * profitFactor * tpatrValue //close - profitFactor * atrValue
takeProfit2_sell = 2 * profitFactor * tpatrValue //close - 2 * profitFactor * atrValue
takeProfit3_sell = 3 * profitFactor * tpatrValue //close - 3 * profitFactor * atrValue
stopLoss_sell = close + takeProfit1_sell //stopFactor * tpatrValue
// ———————————
//Tooltip
T_LVL = '(%) Exit Level'
T_QTY = '(%) Adjust trade exit volume'
T_MSG = 'Paste JSON message for your bot'
//Webhook Message
O_LEMSG = 'Long Entry'
O_LXMSGSL = 'Long SL'
O_LXMSGTP1 = 'Long TP1'
O_LXMSGTP2 = 'Long TP2'
O_LXMSGTP3 = 'Long TP3'
O_LXMSG = 'Long Exit'
O_SEMSG = 'Short Entry'
O_SXMSGSL = 'Short SL'
O_SXMSGA = 'Short TP1'
O_SXMSGB = 'Short TP2'
O_SXMSGC = 'Short TP3'
O_SXMSGX = 'Short Exit'
// on whole pips) for forex currency pairs.
pip_size = syminfo.mintick * (syminfo.type == "forex" ? 10 : 1)
// On the last historical bar, show the instrument's pip size
//if barstate.islastconfirmedhistory
// label.new(x=bar_index + 2, y=close, style=label.style_label_left,
// color=color.navy, textcolor=color.white, size=size.large,
// text=syminfo.ticker + "'s pip size is: " +
// str.tostring(pip_size))
// ——————————— | | | Line length guide |
i_lxLvlTP1 = leTrigger ? takeProfit1_buy : seTrigger ? takeProfit1_sell : na //input.float (1, 'Level TP1' , group = G_RISK, tooltip = T_LVL)
i_lxQtyTP1 = input.float (50, 'Qty TP1' , group = G_RISK, tooltip = T_QTY)
i_lxLvlTP2 = leTrigger ? takeProfit2_buy : seTrigger ? takeProfit2_sell : na //input.float (1.5, 'Level TP2' , group = G_RISK, tooltip = T_LVL)
i_lxQtyTP2 = input.float (30, 'Qty TP2' , group = G_RISK, tooltip = T_QTY)
i_lxLvlTP3 = leTrigger ? takeProfit3_buy : seTrigger ? takeProfit3_sell : na //input.float (2, 'Level TP3' , group = G_RISK, tooltip = T_LVL)
i_lxQtyTP3 = input.float (20, 'Qty TP3' , group = G_RISK, tooltip = T_QTY)
i_lxLvlSL = leTrigger ? takeProfit1_buy : seTrigger ? takeProfit1_sell : na //input.float (0.5, 'Stop Loss' , group = G_RISK, tooltip = T_LVL)
i_sxLvlTP1 = i_lxLvlTP1
i_sxQtyTP1 = i_lxQtyTP1
i_sxLvlTP2 = i_lxLvlTP2
i_sxQtyTP2 = i_lxQtyTP2
i_sxLvlTP3 = i_lxLvlTP3
i_sxQtyTP3 = i_lxQtyTP3
i_sxLvlSL = i_lxLvlSL
G_MSG = '■ ' + 'Webhook Message'
i_leMsg = O_LEMSG //input.string (O_LEMSG ,'Long Entry' , group = G_MSG, tooltip = T_MSG)
i_lxMsgSL = O_LXMSGSL //input.string (O_LXMSGSL ,'Long SL' , group = G_MSG, tooltip = T_MSG)
i_lxMsgTP1 = O_LXMSGTP1 //input.string (O_LXMSGTP1,'Long TP1' , group = G_MSG, tooltip = T_MSG)
i_lxMsgTP2 = O_LXMSGTP2 //input.string (O_LXMSGTP2,'Long TP2' , group = G_MSG, tooltip = T_MSG)
i_lxMsgTP3 = O_LXMSGTP3 //input.string (O_LXMSGTP3,'Long TP3' , group = G_MSG, tooltip = T_MSG)
i_lxMsg = O_LXMSG //input.string (O_LXMSG ,'Long Exit' , group = G_MSG, tooltip = T_MSG)
i_seMsg = O_SEMSG //input.string (O_SEMSG ,'Short Entry' , group = G_MSG, tooltip = T_MSG)
i_sxMsgSL = O_SXMSGSL //input.string (O_SXMSGSL ,'Short SL' , group = G_MSG, tooltip = T_MSG)
i_sxMsgTP1 = O_SXMSGA //input.string (O_SXMSGA ,'Short TP1' , group = G_MSG, tooltip = T_MSG)
i_sxMsgTP2 = O_SXMSGB //input.string (O_SXMSGB ,'Short TP2' , group = G_MSG, tooltip = T_MSG)
i_sxMsgTP3 = O_SXMSGC //input.string (O_SXMSGC ,'Short TP3' , group = G_MSG, tooltip = T_MSG)
i_sxMsg = O_SXMSGX //input.string (O_SXMSGX ,'Short Exit' , group = G_MSG, tooltip = T_MSG)
i_src = close
G_DISPLAY = 'Display'
//
i_alertOn = true //input.bool (true, 'Alert Labels On/Off' , group = G_DISPLAY)
i_barColOn = true //input.bool (true, 'Bar Color On/Off' , group = G_DISPLAY)
// ———————————
// @function Calculate the Take Profit line, and the crossover or crossunder
f_tp(_condition, _conditionValue, _leTrigger, _seTrigger, _src, _lxLvlTP, _sxLvlTP)=>
var float _tpLine = 0.0
_topLvl = _src + _lxLvlTP //TPSType == "Fixed %" ? _src + (_src * (_lxLvlTP / 100)) : _src + _lxLvlTP
_botLvl = _src - _lxLvlTP //TPSType == "Fixed %" ? _src - (_src * (_sxLvlTP / 100)) : _src - _sxLvlTP
_tpLine := _condition != _conditionValue and _leTrigger ? _topLvl :
_condition != -_conditionValue and _seTrigger ? _botLvl :
nz(_tpLine )
// @function Similar to "ta.crossover" or "ta.crossunder"
f_cross(_scr1, _scr2, _over)=>
_cross = _over ? _scr1 > _scr2 and _scr1 < _scr2 :
_scr1 < _scr2 and _scr1 > _scr2
// ———————————
//
var float condition = 0.0
var float slLine = 0.0
var float entryLine = 0.0
//
entryLine := leTrigger and condition <= 0.0 ? close :
seTrigger and condition >= 0.0 ? close : nz(entryLine )
//
slTopLvl = TPSType == "Fixed %" ? i_src + (i_src * (i_lxLvlSL / 100)) : i_src + i_lxLvlSL
slBotLvl = TPSType == "Fixed %" ? i_src - (i_src * (i_sxLvlSL / 100)) : i_src - i_lxLvlSL
slLine := condition <= 0.0 and leTrigger ? slBotLvl :
condition >= 0.0 and seTrigger ? slTopLvl : nz(slLine )
slLong = f_cross(low, slLine, false)
slShort = f_cross(high, slLine, true )
//
= f_tp(condition, 1.2,leTrigger, seTrigger, i_src, i_lxLvlTP3, i_sxLvlTP3)
= f_tp(condition, 1.1,leTrigger, seTrigger, i_src, i_lxLvlTP2, i_sxLvlTP2)
= f_tp(condition, 1.0,leTrigger, seTrigger, i_src, i_lxLvlTP1, i_sxLvlTP1)
tp3Long = f_cross(high, tp3Line, true )
tp3Short = f_cross(low, tp3Line, false)
tp2Long = f_cross(high, tp2Line, true )
tp2Short = f_cross(low, tp2Line, false)
tp1Long = f_cross(high, tp1Line, true )
tp1Short = f_cross(low, tp1Line, false)
switch
leTrigger and condition <= 0.0 => condition := 1.0
seTrigger and condition >= 0.0 => condition := -1.0
tp3Long and condition == 1.2 => condition := 1.3
tp3Short and condition == -1.2 => condition := -1.3
tp2Long and condition == 1.1 => condition := 1.2
tp2Short and condition == -1.1 => condition := -1.2
tp1Long and condition == 1.0 => condition := 1.1
tp1Short and condition == -1.0 => condition := -1.1
slLong and condition >= 1.0 => condition := 0.0
slShort and condition <= -1.0 => condition := 0.0
lxTrigger and condition >= 1.0 => condition := 0.0
sxTrigger and condition <= -1.0 => condition := 0.0
longE = leTrigger and condition <= 0.0 and condition == 1.0
shortE = seTrigger and condition >= 0.0 and condition == -1.0
longX = lxTrigger and condition >= 1.0 and condition == 0.0
shortX = sxTrigger and condition <= -1.0 and condition == 0.0
longSL = slLong and condition >= 1.0 and condition == 0.0
shortSL = slShort and condition <= -1.0 and condition == 0.0
longTP3 = tp3Long and condition == 1.2 and condition == 1.3
shortTP3 = tp3Short and condition == -1.2 and condition == -1.3
longTP2 = tp2Long and condition == 1.1 and condition == 1.2
shortTP2 = tp2Short and condition == -1.1 and condition == -1.2
longTP1 = tp1Long and condition == 1.0 and condition == 1.1
shortTP1 = tp1Short and condition == -1.0 and condition == -1.1
// ——————————— {
//
if strategy.position_size <= 0 and longE and TPSType == "ATR" and tradeDateIsAllowed
strategy.entry( 'Long', strategy.long, alert_message = i_leMsg, comment = 'LE')
if strategy.position_size > 0 and condition == 1.0 and TPSType == "ATR" and tradeDateIsAllowed
strategy.exit( id = 'LXTP1', from_entry = 'Long', qty_percent = i_lxQtyTP1, limit = tp1Line, stop = slLine, comment_profit = 'LXTP1', comment_loss = 'SL', alert_profit = i_lxMsgTP1, alert_loss = i_lxMsgSL)
if strategy.position_size > 0 and condition == 1.1 and TPSType == "ATR" and tradeDateIsAllowed
strategy.exit( id = 'LXTP2', from_entry = 'Long', qty_percent = i_lxQtyTP2, limit = tp2Line, stop = slLine, comment_profit = 'LXTP2', comment_loss = 'SL', alert_profit = i_lxMsgTP2, alert_loss = i_lxMsgSL)
if strategy.position_size > 0 and condition == 1.2 and TPSType == "ATR" and tradeDateIsAllowed
strategy.exit( id = 'LXTP3', from_entry = 'Long', qty_percent = i_lxQtyTP3, limit = tp3Line, stop = slLine, comment_profit = 'LXTP3', comment_loss = 'SL', alert_profit = i_lxMsgTP3, alert_loss = i_lxMsgSL)
if longX and tradeDateIsAllowed
strategy.close( 'Long', alert_message = i_lxMsg, comment = 'LX')
//
if strategy.position_size >= 0 and shortE and TPSType == "ATR" and tradeDateIsAllowed
strategy.entry( 'Short', strategy.short, alert_message = i_leMsg, comment = 'SE')
if strategy.position_size < 0 and condition == -1.0 and TPSType == "ATR" and tradeDateIsAllowed
strategy.exit( id = 'SXTP1', from_entry = 'Short', qty_percent = i_sxQtyTP1, limit = tp1Line, stop = slLine, comment_profit = 'SXTP1', comment_loss = 'SL', alert_profit = i_sxMsgTP1, alert_loss = i_sxMsgSL)
if strategy.position_size < 0 and condition == -1.1 and TPSType == "ATR" and tradeDateIsAllowed
strategy.exit( id = 'SXTP2', from_entry = 'Short', qty_percent = i_sxQtyTP2, limit = tp2Line, stop = slLine, comment_profit = 'SXTP2', comment_loss = 'SL', alert_profit = i_sxMsgTP2, alert_loss = i_sxMsgSL)
if strategy.position_size < 0 and condition == -1.2 and TPSType == "ATR" and tradeDateIsAllowed
strategy.exit( id = 'SXTP3', from_entry = 'Short', qty_percent = i_sxQtyTP3, limit = tp3Line, stop = slLine, comment_profit = 'SXTP3', comment_loss = 'SL', alert_profit = i_sxMsgTP3, alert_loss = i_sxMsgSL)
if shortX and tradeDateIsAllowed
strategy.close( 'Short', alert_message = i_sxMsg, comment = 'SX')
// ———————————
c_tp = leTrigger or seTrigger ? na :
condition == 0.0 ? na : color.green
c_entry = leTrigger or seTrigger ? na :
condition == 0.0 ? na : color.blue
c_sl = leTrigger or seTrigger ? na :
condition == 0.0 ? na : color.red
p_tp1Line = plot ( condition == 1.0 or condition == -1.0 ? tp1Line : na, title = "TP Line 1", color = c_tp, linewidth = 1, style = plot.style_linebr)
p_tp2Line = plot ( condition == 1.0 or condition == -1.0 or condition == 1.1 or condition == -1.1 ? tp2Line : na, title = "TP Line 2", color = c_tp, linewidth = 1, style = plot.style_linebr)
p_tp3Line = plot ( condition == 1.0 or condition == -1.0 or condition == 1.1 or condition == -1.1 or condition == 1.2 or condition == -1.2 ? tp3Line : na, title = "TP Line 3", color = c_tp, linewidth = 1, style = plot.style_linebr)
p_entryLine = plot ( condition >= 1.0 or condition <= -1.0 ? entryLine : na, title = "Entry Line", color = c_entry, linewidth = 1, style = plot.style_linebr)
p_slLine = plot ( condition == 1.0 or condition == -1.0 or condition == 1.1 or condition == -1.1 or condition == 1.2 or condition == -1.2 ? slLine : na, title = "SL Line", color = c_sl, linewidth = 1, style = plot.style_linebr)
//fill( p_tp3Line, p_entryLine, color = leTrigger or seTrigger ? na :color.new(color.green, 90))
fill( p_entryLine, p_slLine, color = leTrigger or seTrigger ? na :color.new(color.red, 90))
//
plotshape( i_alertOn and longE, title = 'Long', text = 'Long', textcolor = color.white, color = color.green, style = shape.labelup, size = size.tiny, location = location.belowbar)
plotshape( i_alertOn and shortE, title = 'Short', text = 'Short', textcolor = color.white, color = color.red, style = shape.labeldown, size = size.tiny, location = location.abovebar)
plotshape( i_alertOn and (longX or shortX) ? close : na, title = 'Close', text = 'Close', textcolor = color.white, color = color.gray, style = shape.labelup, size = size.tiny, location = location.absolute)
l_tp = i_alertOn and (longTP1 or shortTP1) ? close : na
plotshape( l_tp, title = "TP1 Cross", text = "TP1", textcolor = color.white, color = #ec407a, style = shape.labelup, size = size.tiny, location = location.absolute)
plotshape( i_alertOn and (longTP2 or shortTP2) ? close : na, title = "TP2 Cross", text = "TP2", textcolor = color.white, color = #ec407a, style = shape.labelup, size = size.tiny, location = location.absolute)
plotshape( i_alertOn and (longTP3 or shortTP3) ? close : na, title = "TP3 Cross", text = "TP3", textcolor = color.white, color = #ec407a, style = shape.labelup, size = size.tiny, location = location.absolute)
plotshape( i_alertOn and (longSL or shortSL) ? close : na, title = "SL Cross", text = "SL", textcolor = color.white, color = color.maroon, style = shape.labelup, size = size.tiny, location = location.absolute)
//
plot( na, title = "─── ───", editable = false, display = display.data_window)
plot( condition, title = "condition", editable = false, display = display.data_window)
plot( strategy.position_size * 100, title = ".position_size", editable = false, display = display.data_window)
//#endregion }
// ——————————— <↑↑↑ G_RISK ↑↑↑>
//#region ———— <↓↓↓ G_SCRIPT02 ↓↓↓> {
// @function Queues a new element in an array and de-queues its first element.
f_qDq(_array, _val) =>
array.push(_array, _val)
_return = array.shift(_array)
_return
var line a_slLine = array.new_line(1)
var line a_entryLine = array.new_line(1)
var line a_tp3Line = array.new_line(1)
var line a_tp2Line = array.new_line(1)
var line a_tp1Line = array.new_line(1)
var label a_slLabel = array.new_label(1)
var label a_tp3label = array.new_label(1)
var label a_tp2label = array.new_label(1)
var label a_tp1label = array.new_label(1)
var label a_entryLabel = array.new_label(1)
newEntry = longE or shortE
entryIndex = 1
entryIndex := newEntry ? bar_index : nz(entryIndex )
lasTrade = bar_index >= entryIndex
l_right = 10
if TPSType == "ATR"
line.delete( f_qDq(a_slLine, line.new( entryIndex, slLine, last_bar_index + l_right, slLine, style = line.style_solid, color = c_sl)))
if TPSType == "ATR"
line.delete( f_qDq(a_entryLine, line.new( entryIndex, entryLine, last_bar_index + l_right, entryLine, style = line.style_solid, color = color.blue)))
if TPSType == "ATR"
line.delete( f_qDq(a_tp3Line, line.new( entryIndex, tp3Line, last_bar_index + l_right, tp3Line, style = line.style_solid, color = c_tp)))
if TPSType == "ATR"
line.delete( f_qDq(a_tp2Line, line.new( entryIndex, tp2Line, last_bar_index + l_right, tp2Line, style = line.style_solid, color = c_tp)))
if TPSType == "ATR"
line.delete( f_qDq(a_tp1Line, line.new( entryIndex, tp1Line, last_bar_index + l_right, tp1Line, style = line.style_solid, color = c_tp)))
if TPSType == "ATR"
label.delete( f_qDq(a_slLabel, label.new( last_bar_index + l_right, slLine, 'SL: ' + str.tostring(slLine, '##.###'), style = label.style_label_left, textcolor = color.white, color = c_sl)))
if TPSType == "ATR"
label.delete( f_qDq(a_entryLabel, label.new( last_bar_index + l_right, entryLine, 'Entry: ' + str.tostring(entryLine, '##.###'), style = label.style_label_left, textcolor = color.white, color = color.blue)))
if TPSType == "ATR"
label.delete( f_qDq(a_tp3label, label.new( last_bar_index + l_right, tp3Line, 'TP3: ' + str.tostring(tp3Line, '##.###') + " - Target Pips : - " + str.tostring(longE ? tp3Line - entryLine : entryLine - tp3Line, "#.##"), style = label.style_label_left, textcolor = color.white, color = c_tp)))
if TPSType == "ATR"
label.delete( f_qDq(a_tp2label, label.new( last_bar_index + l_right, tp2Line, 'TP2: ' + str.tostring(tp2Line, '##.###'), style = label.style_label_left, textcolor = color.white, color = c_tp)))
if TPSType == "ATR"
label.delete( f_qDq(a_tp1label, label.new( last_bar_index + l_right, tp1Line, 'TP1: ' + str.tostring(tp1Line, '##.###'), style = label.style_label_left, textcolor = color.white, color = c_tp)))
//#endregion }
// ——————————— <↑↑↑ G_SCRIPT02 ↑↑↑>
c_barCol = close > open ? color.rgb(120, 9, 139) : color.rgb(69, 155, 225)
barcolor(
i_barColOn ? c_barCol : na)
// ———————————
//
if longE or shortE or longX or shortX
alert(message = 'Any Alert', freq = alert.freq_once_per_bar_close)
if longE
alert(message = 'Long Entry', freq = alert.freq_once_per_bar_close)
if shortE
alert(message = 'Short Entry', freq = alert.freq_once_per_bar_close)
if longX
alert(message = 'Long Exit', freq = alert.freq_once_per_bar_close)
if shortX
alert(message = 'Short Exit', freq = alert.freq_once_per_bar_close)
//#endregion }
// ——————————— <↑↑↑ G_SCRIPT03 ↑↑↑>
// This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © TraderHalai
// This script was born out of my quest to be able to display strategy back test statistics on charts to allow for easier backtesting on devices that do not natively support backtest engine (such as mobile phones, when I am backtesting from away from my computer). There are already a few good ones on TradingView, but most / many are too complicated for my needs.
//
//Found an excellent display backtest engine by 'The Art of Trading'. This script is a snippet of his hard work, with some very minor tweaks and changes. Much respect to the original author.
//
//Full credit to the original author of this script. It can be found here: www.tradingview.com
//
// This script can be copied and airlifted onto existing strategy scripts of your own, and integrates out of the box without implementation of additional functions. I've also added Max Runup, Average Win and Average Loss per trade to the orignal script.
//
//Will look to add in more performance metrics in future, as I further develop this script.
//
//Feel free to use this display panel in your scripts and strategies.
//Thanks and enjoy! :)
//@version=5
//strategy("Strategy BackTest Display Statistics - TraderHalai", overlay=true, default_qty_value= 5, default_qty_type = strategy.percent_of_equity, initial_capital=10000, commission_type=strategy.commission.percent, commission_value=0.1)
//DEMO basic strategy - Use your own strategy here - Jaws Mean Reversion from my profile used here
//source = input(title = "Source", defval = close)
///////////////////////////// --- BEGIN TESTER CODE --- ////////////////////////
// COPY below into your strategy to enable display
////////////////////////////////////////////////////////////////////////////////
// Declare performance tracking variables
drawTester = input.bool(false, "Strategy Performance", group='Dashboards', inline="Show Dashboards")
var balance = strategy.initial_capital
var drawdown = 0.0
var maxDrawdown = 0.0
var maxBalance = 0.0
var totalWins = 0
var totalLoss = 0
// Prepare stats table
var table testTable = table.new(position.top_right, 5, 2, border_width=1)
f_fillCell(_table, _column, _row, _title, _value, _bgcolor, _txtcolor) =>
_cellText = _title + " " + _value
table.cell(_table, _column, _row, _cellText, bgcolor=_bgcolor, text_color=_txtcolor)
// Custom function to truncate (cut) excess decimal places
//truncate(_number, _decimalPlaces) =>
// _factor = math.pow(10, _decimalPlaces)
// int(_number * _factor) / _factor
// Draw stats table
var bgcolor = color.new(color.black,0)
if drawTester and tradeDateIsAllowed
if barstate.islastconfirmedhistory
// Update table
dollarReturn = strategy.netprofit
f_fillCell(testTable, 0, 0, "Total Trades:", str.tostring(strategy.closedtrades), bgcolor, color.white)
f_fillCell(testTable, 0, 1, "Win Rate:", str.tostring(truncate((strategy.wintrades/strategy.closedtrades)*100,2)) + "%", bgcolor, color.white)
f_fillCell(testTable, 1, 0, "Starting:", "$" + str.tostring(strategy.initial_capital), bgcolor, color.white)
f_fillCell(testTable, 1, 1, "Ending:", "$" + str.tostring(truncate(strategy.initial_capital + strategy.netprofit,2)), bgcolor, color.white)
f_fillCell(testTable, 2, 0, "Avg Win:", "$"+ str.tostring(truncate(strategy.grossprofit / strategy.wintrades, 2)), bgcolor, color.white)
f_fillCell(testTable, 2, 1, "Avg Loss:", "$"+ str.tostring(truncate(strategy.grossloss / strategy.losstrades, 2)), bgcolor, color.white)
f_fillCell(testTable, 3, 0, "Profit Factor:", str.tostring(truncate(strategy.grossprofit / strategy.grossloss,2)), strategy.grossprofit > strategy.grossloss ? color.green : color.red, color.white)
f_fillCell(testTable, 3, 1, "Max Runup:", str.tostring(truncate(strategy.max_runup, 2 )), bgcolor, color.white)
f_fillCell(testTable, 4, 0, "Return:", (dollarReturn > 0 ? "+" : "") + str.tostring(truncate((dollarReturn / strategy.initial_capital)*100,2)) + "%", dollarReturn > 0 ? color.green : color.red, color.white)
f_fillCell(testTable, 4, 1, "Max DD:", str.tostring(truncate((strategy.max_drawdown / strategy.equity) * 100 ,2)) + "%", color.red, color.white)
// --- END TESTER CODE --- ///////////////
// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © niceGear68734
//@version=5
//strategy("Table to filter trades per day", overlay=true, use_bar_magnifier = true, initial_capital = 5000, calc_on_every_tick = true, calc_on_order_fills = true, commission_type = strategy.commission.cash_per_contract)
//~ ___________________________________________________________________________
//~ !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
//~ !!!!!!!!!!!!!!!_________________ START _________________!!!!!!!!!!!!!!!!!
i_showweeklyPerformance = input.bool(false, 'Weekly Performance', group='Dashboards', inline="Show Dashboards")
//__________________________ User Inputs ___________________________________
var const string g_table = "Table Settings"
i_table_pos = "Top Left" //input.string(defval = "Top Left", title = "Position", options = , group = g_table, inline = "1", tooltip = "It sets the location of the table")
i_text_size = "Normal" //input.string(defval = "Normal", title = "Set the size of text", options = , tooltip = "This option is used to change the size of the text in the table")
var const string g_general = "General Settings"
i_check_open_close = "Opened" //input.string("Opened", "Check when the trade :", , group = g_general, tooltip = "This parameter defines what to check for. If opened is selected, the results will show the trades that opened on that day. If closed is selected, the results will show the trades that closed on that day")
i_timezone = "Exchange" //input.string("Exchange", title = "Set the Timezone", options = , group = g_general, tooltip = "You can use this setting whenever you want to change the time that the trade has closed/opened")
//~_____________________________ Switches ___________________________________
table_pos = switch i_table_pos
"Bottom Right" => position.bottom_right
"Bottom Left" => position.bottom_left
"Top Right" => position.top_right
"Top Left" => position.top_left
timezone_setting = i_timezone == "Exchange" ? syminfo.timezone : i_timezone
text_size = switch i_text_size
"Small" => size.small
"Normal" => size.normal
"Large" => size.large
//__________________________ Array Declaration _____________________________
var string t_column_names = array.from( "", "Sun", "Mon", "Tue", "Wed", "Thur", "Fri", "Sat") // Columns header names
var string t_row_names = array.from("", "Total Trades", "Loss", "Win", "Win Rate" ) // Rows header names
var t_column_size = array.size(t_column_names)
var t_row_size = array.size(t_row_names)
var string a_closed_trades = array.new_string() // Save the total number of trades
var string a_loss_trades = array.new_string() // Save the number of losing trades
var string a_win_trades = array.new_string() // Save the number of winning trades
var _a_day_week = array.new_int() // Save the day of the week to split data
// __________________________ Custom Functions ________________________________
//~ create a counter so that it gives a number to strategy.closed_trades.entry_time(counter)
var trade_number = -1
if strategy.closedtrades > strategy.closedtrades
trade_number += 1
f_strategy_closedtrades_hour() =>
switch
i_check_open_close =="Closed" => dayofweek(strategy.closedtrades.exit_time(trade_number), timezone_setting)
i_check_open_close =="Opened" => dayofweek(strategy.closedtrades.entry_time(trade_number), timezone_setting)
f_data(_i) =>
var _closed_trades = 0
var _loss_trades = 0
var _win_trades = 0
var _txt_closed_trades = ""
var _txt_loss_trades = ""
var _txt_win_trades = ""
if strategy.closedtrades > strategy.closedtrades and f_strategy_closedtrades_hour() == _i
_closed_trades += 1
_txt_closed_trades := str.tostring(_closed_trades)
if strategy.losstrades > strategy.losstrades and f_strategy_closedtrades_hour() == _i
_loss_trades += 1
_txt_loss_trades := str.tostring(_loss_trades)
if strategy.wintrades > strategy.wintrades and f_strategy_closedtrades_hour() == _i
_win_trades += 1
_txt_win_trades := str.tostring(_win_trades)
//__________________________
var string array1 = array.new_string(5)
var string array2 = array.new_string(5)
var string array3 = array.new_string(5)
var string array4 = array.new_string(5)
var string array5 = array.new_string(5)
var string array6 = array.new_string(5)
var string array7 = array.new_string(5)
f_pass_data_to_array(_i, _array) =>
= f_data(_i)
array.set(_array,1 , cl)
array.set(_array,2,loss)
array.set(_array,3,win)
if cl != ""
array.set(_array,4,str.tostring(str.tonumber(win) / str.tonumber(cl) * 100 , "##") + " %")
if cl != "" and win == ""
array.set(_array,4,"0 %")
for i = 1 to 7
switch
i == 1 => f_pass_data_to_array(i,array1)
i == 2 => f_pass_data_to_array(i,array2)
i == 3 => f_pass_data_to_array(i,array3)
i == 4 => f_pass_data_to_array(i,array4)
i == 5 => f_pass_data_to_array(i,array5)
i == 6 => f_pass_data_to_array(i,array6)
i == 7 => f_pass_data_to_array(i,array7)
f_retrieve_data_to_table(_i, _j) =>
switch
_i == 1 => array.get(array1, _j)
_i == 2 => array.get(array2, _j)
_i == 3 => array.get(array3, _j)
_i == 4 => array.get(array4, _j)
_i == 5 => array.get(array5, _j)
_i == 6 => array.get(array6, _j)
_i == 7 => array.get(array7, _j)
//~ ___________________________ Create Table ________________________________
create_table(_col, _row, _txt) =>
var table _tbl = table.new(position = table_pos, columns = t_column_size , rows = t_row_size, border_width=1)
color _color = _row == 0 or _col == 0 ? color.rgb(3, 62, 106) : color.rgb(2, 81, 155)
table.cell(_tbl, _col, _row, _txt, bgcolor = _color, text_color = color.white, text_size = text_size)
//~___________________________ Fill With Data _______________________________
if barstate.islastconfirmedhistory and i_showweeklyPerformance and tradeDateIsAllowed
for i = 0 to t_column_size - 1 by 1
for j = 0 to t_row_size - 1 by 1
_txt = ""
if i >= 0 and j == 0
_txt := array.get(t_column_names, i)
if j >= 0 and i == 0
_txt := array.get(t_row_names, j)
if i >= 1 and j >= 1 and j <= 5
_txt := f_retrieve_data_to_table( i , j)
create_table(i ,j , _txt)
//~ ___________________________ Notice ______________________________________
if timeframe.in_seconds() > timeframe.in_seconds("D")
x = table.new(position.middle_center,1,1,color.aqua)
table.cell_set_text(x,0,0,"Please select lower timeframes (Daily or lower)")
//~ !!!!!!!!!!!!!!!_________________ STOP _________________!!!!!!!!!!!!!!!!!!
//~ !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
//~ ___________________________________________________________________________
// Global Dashboard Variables
// ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░
// Dashboard Table Text Size
i_tableTextSize = "Normal" //input.string(title="Dashboard Size", defval="Normal", options= , group="Dashboards")
table_text_size(s) =>
switch s
"Auto" => size.auto
"Huge" => size.huge
"Large" => size.large
"Normal" => size.normal
"Small" => size.small
=> size.tiny
tableTextSize = table_text_size(i_tableTextSize)
// Monthly Table Performance Dashboard By @QuantNomad
// ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░
i_showMonthlyPerformance = input.bool(false, 'Monthly Performance', group='Dashboards', inline="Show Dashboards")
i_monthlyReturnPercision = 2
if i_showMonthlyPerformance and tradeDateIsAllowed
new_month = month(time) != month(time )
new_year = year(time) != year(time )
eq = strategy.equity
bar_pnl = eq / eq - 1
cur_month_pnl = 0.0
cur_year_pnl = 0.0
// Current Monthly P&L;
cur_month_pnl := new_month ? 0.0 :
(1 + cur_month_pnl ) * (1 + bar_pnl) - 1
// Current Yearly P&L;
cur_year_pnl := new_year ? 0.0 :
(1 + cur_year_pnl ) * (1 + bar_pnl) - 1
// Arrays to store Yearly and Monthly P&Ls;
var month_pnl = array.new_float(0)
var month_time = array.new_int(0)
var year_pnl = array.new_float(0)
var year_time = array.new_int(0)
last_computed = false
if (not na(cur_month_pnl ) and (new_month or barstate.islastconfirmedhistory))
if (last_computed )
array.pop(month_pnl)
array.pop(month_time)
array.push(month_pnl , cur_month_pnl )
array.push(month_time, time )
if (not na(cur_year_pnl ) and (new_year or barstate.islastconfirmedhistory))
if (last_computed )
array.pop(year_pnl)
array.pop(year_time)
array.push(year_pnl , cur_year_pnl )
array.push(year_time, time )
last_computed := barstate.islastconfirmedhistory ? true : nz(last_computed )
// Monthly P&L; Table
var monthly_table = table(na)
if (barstate.islastconfirmedhistory)
monthly_table := table.new(position.bottom_right, columns = 14, rows = array.size(year_pnl) + 1, border_width = 1)
table.cell(monthly_table, 0, 0, "", bgcolor = #cccccc, text_size=tableTextSize)
table.cell(monthly_table, 1, 0, "Jan", bgcolor = #cccccc, text_size=tableTextSize)
table.cell(monthly_table, 2, 0, "Feb", bgcolor = #cccccc, text_size=tableTextSize)
table.cell(monthly_table, 3, 0, "Mar", bgcolor = #cccccc, text_size=tableTextSize)
table.cell(monthly_table, 4, 0, "Apr", bgcolor = #cccccc, text_size=tableTextSize)
table.cell(monthly_table, 5, 0, "May", bgcolor = #cccccc, text_size=tableTextSize)
table.cell(monthly_table, 6, 0, "Jun", bgcolor = #cccccc, text_size=tableTextSize)
table.cell(monthly_table, 7, 0, "Jul", bgcolor = #cccccc, text_size=tableTextSize)
table.cell(monthly_table, 8, 0, "Aug", bgcolor = #cccccc, text_size=tableTextSize)
table.cell(monthly_table, 9, 0, "Sep", bgcolor = #cccccc, text_size=tableTextSize)
table.cell(monthly_table, 10, 0, "Oct", bgcolor = #cccccc, text_size=tableTextSize)
table.cell(monthly_table, 11, 0, "Nov", bgcolor = #cccccc, text_size=tableTextSize)
table.cell(monthly_table, 12, 0, "Dec", bgcolor = #cccccc, text_size=tableTextSize)
table.cell(monthly_table, 13, 0, "Year", bgcolor = #999999, text_size=tableTextSize)
for yi = 0 to array.size(year_pnl) - 1
table.cell(monthly_table, 0, yi + 1, str.tostring(year(array.get(year_time, yi))), bgcolor = #cccccc, text_size=tableTextSize)
y_color = array.get(year_pnl, yi) > 0 ? color.new(color.teal, transp = 40) : color.new(color.gray, transp = 40)
table.cell(monthly_table, 13, yi + 1, str.tostring(math.round(array.get(year_pnl, yi) * 100, i_monthlyReturnPercision)), bgcolor = y_color, text_color=color.new(color.white, 0),text_size=tableTextSize)
for mi = 0 to array.size(month_time) - 1
m_row = year(array.get(month_time, mi)) - year(array.get(year_time, 0)) + 1
m_col = month(array.get(month_time, mi))
m_color = array.get(month_pnl, mi) > 0 ? color.new(color.teal, transp = 40) : color.new(color.maroon, transp = 40)
table.cell(monthly_table, m_col, m_row, str.tostring(math.round(array.get(month_pnl, mi) * 100, i_monthlyReturnPercision)), bgcolor = m_color, text_color=color.new(color.white, 0), text_size=tableTextSize)
hide = timeframe.isintraday
// Input for EMA period
emaPeriod = 48 //input.int(48, title="EMA Period")
emaPeriod2 = 2 //input.int(2, title="EME Period 2")
emaPeriod3 = 21 //input.int(21, title="EMA Period")
// Input to toggle EMA Cloud
showcloud = input.bool(false, title="Plot EMA?", group='EMA & ATR', inline="Show EMA's & ATR")
useHTF = input.bool(true, title = "Use Higher Time Frame?")
matimeframe = useHTF ? my_time1 : ''
// EMA calculations
ema = request.security(syminfo.tickerid, matimeframe, ta.ema(close, emaPeriod))
ema2 = request.security(syminfo.tickerid, matimeframe, ta.ema(close,emaPeriod2))
ema3 = request.security(syminfo.tickerid, matimeframe,ta.ema(close, emaPeriod3))
emaColor = close > ema3 ? color.new(color.rgb(56, 142, 60, 63), 50) : color.new(color.rgb(147, 40, 51, 38), 50)
// Plotting EMA's
// plot_ema1 = plot(hide ? ema : na, style=plot.style_line, color=color.new(color.rgb(255, 255, 255, 100), 50), title="EMA", linewidth=2)
// plot_ema2 = plot(hide ? ema2 : na, style=plot.style_line, color=color.new(color.rgb(255, 255, 255, 100), 50), title="EMA", linewidth=1)
// plot_ema3 = plot(ema3, style=plot.style_line, color=emaColor, title="EMA", linewidth=1)
// EMA Cloud
cloudColor = ema2 > ema ? color.new(#0f8513, 80) : color.new(#a81414, 80)
cloudColor2 = ema2 > ema3 ? color.new(#0f8513, 50) : color.new(#a81414, 50)
cloudColor := showcloud ? cloudColor : na
// fill(plot_ema1, plot_ema2, color=cloudColor, title="EMA Cloud")
// fill(plot_ema3, plot_ema2, color=cloudColor, title="EMA Cloud")
/////////////////////////////////////////////////////////////// © BackQuant ///////////////////////////////////////////////////////////////
// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © BackQuant
import TradingView/ta/4 as ta
//@version=5
//indicator(
// title="DEMA Adjusted Average True Range ",
// shorttitle = "DEMA ATR ",
// overlay=true,
// timeframe="",
// timeframe_gaps=true
// )
// Define User Inputs
simple bool showAtr = input.bool(false, "Plot Dema?", group='EMA & ATR', inline="Show EMA's & ATR")
simple bool haCandles = true //input.bool(true, "Use HA Candles?")
simple int periodDema = 7 //input.int(7, "Dema Period", group = "Dema Atr")
series float sourceDema = close //input.source(close, "Calculation Source", group = "Dema Atr")
simple int periodAtr = 14 //input.int(14, "Period", group = "Dema Atr")
simple float factorAtr = 1.7 //input.float(1.7, "Factor", step = 0.01, group = "Dema Atr")
simple color longColour = #66bb6a
simple color shortColour = #f23645
/////////////////////////////////////////////////////////////// © BackQuant ///////////////////////////////////////////////////////////////
// Use HA Candles?
heikinashi_close = request.security(
symbol = ticker.heikinashi(syminfo.tickerid),
timeframe = timeframe.period,
expression = close,
gaps = barmerge.gaps_off,
lookahead = barmerge.lookahead_on
)
var series float source = close
if haCandles == true
source := heikinashi_close
if haCandles == false
source := sourceDema
/////////////////////////////////////////////////////////////// © BackQuant ///////////////////////////////////////////////////////////////
// Function
DemaAtrWithBands(periodDema, source, lookback, atrFactor)=>
ema1 = ta.ema(source, periodDema)
ema2 = ta.ema(ema1, periodDema)
demaOut = 2 * ema1 - ema2
atr = ta.atr(lookback)
trueRange = atr * atrFactor
DemaAtr = demaOut
DemaAtr := nz(DemaAtr , DemaAtr)
trueRangeUpper = demaOut + trueRange
trueRangeLower = demaOut - trueRange
if trueRangeLower > DemaAtr
DemaAtr := trueRangeLower
if trueRangeUpper < DemaAtr
DemaAtr := trueRangeUpper
DemaAtr
// Function Out
DemaAtr = DemaAtrWithBands(periodDema, source, periodAtr, factorAtr)
/////////////////////////////////////////////////////////////// © BackQuant ///////////////////////////////////////////////////////////////
// Conditions
DemaAtrLong = DemaAtr > DemaAtr
DemaAtrShort = DemaAtr < DemaAtr
// Colour Condtions
var color Trendcolor = #ffffff
if DemaAtrLong
Trendcolor := longColour
if DemaAtrShort
Trendcolor := shortColour
// Plotting
plot( showAtr ? DemaAtr : na, "ATR", color=Trendcolor, linewidth = 2 )
import DevLucem/ZigLib/1 as ZigZag
////////
// Fetch Ingredients
//
// ////////
// // Bake it with a simple oven this time
= ZigZag.zigzag(low, high, Depth, Deviation, Backstep)
string nowPoint = ""
var float lastPoint = z1.price
if bool(ta.change(direction))
lastPoint := z1.price
// ////////
// // Let it Cool And Serve
line zz = na
label point = na
if repaint
zz := line.new(z1, z2, xloc.bar_time, extend? extend.right: extend.none, color.new(direction>0? upcolor: dncolor, lines), width=line_thick)
nowPoint := direction<0? (z2.pricelastPoint? "HH": "LH")
point := label.new(z2, nowPoint, xloc.bar_time, yloc.price,
color.new(direction<0? upcolor: dncolor, labels), direction>0? label.style_label_down: label.style_label_up, color.new(direction>0? upcolor: dncolor, labels), label_size)
if direction == direction
line.delete(zz )
label.delete(point )
else
line.set_extend(zz , extend.none)
else
if direction != direction
zz := line.new(z1 , z2 , xloc.bar_time, extend.none, color.new(direction>0? upcolor: dncolor, lines), width=line_thick)
nowPoint := direction <0? (z2.price lastPoint ? "HH": "LH")
point := label.new(z2 , nowPoint, xloc.bar_time, yloc.price,
color.new(direction <0? upcolor: dncolor, labels), direction >0? label.style_label_down: label.style_label_up, color.new(direction >0? upcolor: dncolor, labels), label_size)
bgcolor(direction<0? color.new(dncolor, background): color.new(upcolor, background), title='Direction Background', display = display.none)
plotarrow(direction, "direction", display=display.status_line)
// ////////
// // Declare Meal Was Sweet By Force
alertcondition(nowPoint == "HH" and z2.price != z2.price , "New Higher High", 'Zigzag on {{ticker}} higher higher high detected at {{time}}')
alertcondition(nowPoint == "LH" and z2.price != z2.price , "New Lower High", 'Zigzag on {{ticker}} higher lower high detected at {{time}}')
alertcondition(nowPoint == "HL" and z2.price != z2.price , "New Higher Low", 'Zigzag on {{ticker}} higher lower low detected at {{time}}')
alertcondition(nowPoint == "LL" and z2.price != z2.price , "New Lower Low", 'Zigzag on {{ticker}} lower low detected at {{time}}')
alertcondition(direction != direction , 'Direction Changed', 'Zigzag on {{ticker}} direction changed at {{time}}')
alertcondition(direction != direction and direction>0, 'Bullish Direction', 'Zigzag on {{ticker}} bullish direction at {{time}}')
alertcondition(direction != direction and direction<0, 'Bearish Direction', 'Zigzag on {{ticker}} bearish direction at {{time}}')
if direction != direction
alert((direction<0? "Bearish": "Bullish") + " Direction Final ", alert.freq_once_per_bar_close)
MSG = "MARKET STRUCTURE"
VBG = "VOLUMETRIC ORDER BLOCKS"
MST = "Limit market structure calculation to improve memory speed time"
SLT = " Limit swing structure to tot bars back"
IDT = " Start date of the internal structure"
CST = "Color candle based on trend detection system"
OBT = "Display internal buy and sell activity"
OBD = "Show Last number of orderblock"
OBMT = " Use Length to adjust cordinate of the orderblocks Use whole candle body"
_ ='
------------
–––––––––––––––––––––––––– INPUTS –––––––––––––––––––––––––––
------------ '//{
bool windowsis = input.bool(true, "Window", inline="kla", group=MSG)
int mswindow = input.int(5000, "", tooltip=MST,group=MSG, inline="kla", minval=1000)
bool showSwing = input.bool(true, "Swing", inline="scss", group=MSG)
int swingLimit = input.int(100, "", tooltip=SLT, inline="scss", group=MSG, minval=10, maxval=200)
color swingcssup = input.color(#f7525f, "", inline="scss", group=MSG)
color swingcssdn = input.color(#66bb6a, "", inline="scss", group=MSG)
bool showMapping = input.bool(false, "Mapping Structure", inline="mapping", group=MSG)
string mappingStyle = input.string("----", "", options= , inline="mapping", group=MSG)
color mappingcss = input.color(color.silver, "", tooltip="Display Mapping Structure", inline="mapping", group=MSG)
bool candlecss = input.bool(false, "Color Candles", tooltip=CST, group=MSG, inline="txt")
string mstext = input.string("Tiny", "", options= ,
inline="txt", group=MSG)
string msmode = input.string("Adjusted Points", "Algorithmic Logic", options=
, inline="node", group=MSG)
int mslen = input.int(5, "", inline="node", group=MSG, minval=2)
bool buildsweep = input.bool(true, "Build Sweep (x)", "Build sweep on market structure", "znc", MSG)
bool msbubble = input.bool(true, "Bubbles", tooltip="Display Circle Bubbles", inline="bubbles", group=MSG)
bool obshow = input.bool(true, "Show Last", tooltip=OBD, group=VBG, inline="obshow")
int oblast = input.int(5, "", group=VBG, inline="obshow", minval=0)
color obupcs = input.color(color.new(#089981, 90), "", inline="obshow", group=VBG)
color obdncs = input.color(color.new(#f23645, 90), "", inline="obshow", group=VBG)
bool obshowactivity = input.bool(true, "Show Buy/Sell Activity", inline="act", group=VBG, tooltip=OBT)
color obactup = input.color(color.new(#089981, 50), "", inline="act", group=VBG)
color obactdn = input.color(color.new(#f23645, 50), "", inline="act", group=VBG)
obshowbb = input.bool(false, "Show Breakers", inline="bb", group=VBG, tooltip="Display Breakers")
color bbup = input.color(color.new(#089981, 100), "", inline="bb", group=VBG)
color bbdn = input.color(color.new(#f23645, 100), "", inline="bb", group=VBG)
obmode = input.string("Length", "Construction", options= , tooltip=OBMT, inline="atr", group=VBG)
len = input.int(5, "", inline="atr", group=VBG, minval=1)
obmiti = input.string("Close", "Mitigation Method", options= ,
tooltip="Mitigation method for when to trigger order blocks", group=VBG)
obtxt = input.string("Normal", "Metric Size", options= ,
tooltip="Order block Metrics text size", inline="txt", group=VBG)
showmetric = input.bool(true, "Show Metrics", group=VBG)
showline = input.bool(true, "Show Mid-Line", group=VBG)
overlap = input.bool(true, "Hide Overlap", group=VBG, inline="ov")
wichlap = input.string("Recent", "", options= , inline="ov", group=VBG)
fvg_enable = input.bool(false, "", inline="1", group="FAIR VALUE GAP", tooltip="Display fair value gap")
what_fvg = input.string("FVG", "", inline="1", group="FAIR VALUE GAP", tooltip="Display fair value gap",
options= )
fvg_num = input.int(5, "Show Last", inline="1a", group="FAIR VALUE GAP", tooltip="Number of fvg to show", minval=0)
fvg_upcss = input.color(color.new(#089981, 80), "", inline="1", group="FAIR VALUE GAP")
fvg_dncss = input.color(color.new(#f23645, 80), "", inline="1", group="FAIR VALUE GAP")
fvgbbup = input.color(color.new(#089981, 100), "", inline="1", group="FAIR VALUE GAP")
fvgbbdn = input.color(color.new(#f23645, 100), "", inline="1", group="FAIR VALUE GAP")
fvg_src = input.string("Close", "Mitigation",
inline="3",
group="FAIR VALUE GAP",
tooltip=" Use the close of the body as trigger Use the extreme point of the body as trigger",
options= )
fvgthresh = input.float(0, "Threshold", tooltip="Filter out non significative FVG", group="FAIR VALUE GAP",
inline="asd", minval=0, maxval=2, step=0.1)
fvgoverlap = input.bool(true, "Hide Overlap", "Hide overlapping FVG", group="FAIR VALUE GAP")
fvgline = input.bool(true, "Show Mid-Line", group="FAIR VALUE GAP")
fvgextend = input.bool(false, "Extend FVG", group="FAIR VALUE GAP")
dispraid = input.bool(false, "Display Raids", inline="raid", group="FAIR VALUE GAP")
//}
_ ='
------------
–––––––––––––––––––––––––– UDT –––––––––––––––––––––––––––
------------ '//{
type hqlzone
box pbx
box ebx
box lbx
label plb
label elb
label lbl
type Zphl
line top
line bottom
label top_label
label bottom_label
bool stopcross
bool sbottomcross
bool itopcross
bool ibottomcross
string txtup
string txtdn
float topy
float bottomy
float topx
float bottomx
float tup
float tdn
int tupx
int tdnx
float itopy
float itopx
float ibottomy
float ibottomx
float uV
float dV
type entered
bool normal = false
bool breaker = false
type store
line ln
label lb
box bx
linefill lf
type structure
int zn
float zz
float bos
float choch
int loc
int temp
int trend
int start
float main
int xloc
bool upsweep
bool dnsweep
string txt = na
type drawms
int x1
int x2
float y
string txt
color css
string style
type ob
bool bull
float top
float btm
float avg
int loc
color css
float vol
int dir
int move
int blPOS
int brPOS
int xlocbl
int xlocbr
bool isbb = false
int bbloc
type FVG
float top = na
float btm = na
int loc = bar_index
bool isbb = false
int bbloc = na
bool israid = false
float raidy = na
int raidloc = na
int raidx2 = na
bool active = false
color raidcs = na
type SFP
float y
int loc
float ancor
type sfpbuildlbl
int x
float y
string style
color css
string txt
type sfpbuildline
int x1
int x2
float y
color css
float ancor
int loc
type equalbuild
int x1
float y1
int x2
float y2
color css
string style
type equalname
int x
float y
string txt
color css
string style
type ehl
float pt
int t
float pb
int b
type sellbuyside
float top
float btm
int loc
color css
string txt
float vol
type timer
bool start = false
int count = 0
//}
_ ='
------------
–––––––––––––––––––––––––– SETUP –––––––––––––––––––––––––––
------------ '//{
var store bin = store.new(
array.new< line >()
, array.new< label >()
, array.new< box >()
, array.new()
)
var entered blobenter = entered.new()
var entered brobenter = entered.new()
var entered blfvgenter = entered.new()
var entered brfvgenter = entered.new()
var entered blarea = entered.new()
var entered brarea = entered.new()
var timer lc = timer.new ()
if barstate.islast
for obj in bin.ln
obj.delete()
for obj in bin.lb
obj.delete()
for obj in bin.bx
obj.delete()
for obj in bin.lf
obj.delete()
bin.ln.clear()
bin.lb.clear()
bin.bx.clear()
bin.lf.clear()
invcol = #ffffff00
float atr = (ta.atr(200) / (5/len))
//}
_ ='
------------
–––––––––––––––––––––––––– UTILITY –––––––––––––––––––––––––––
------------ '//{
method txSz(string s) =>
out = switch s
"Tiny" => size.tiny
"Small" => size.small
"Normal" => size.normal
"Large" => size.large
"Huge" => size.huge
"Auto" => size.auto
out
method lstyle(string style) =>
out = switch style
'⎯⎯⎯⎯' => line.style_solid
'----' => line.style_dashed
'····' => line.style_dotted
ghl() => [high , low , close , open , close, open, high, low, high , low , ta.atr(200)]
method IDMIDX(bool use_max, int loc) =>
min = 99999999.
max = 0.
idx = 0
if use_max
for i = 0 to (bar_index - loc)
max := math.max(high , max)
min := max == high ? low : min
idx := max == high ? i : idx
else
for i = 0 to (bar_index - loc)
min := math.min(low , min)
max := min == low ? high : max
idx := min == low ? i : idx
idx
SFPData() => [high, high , high , low, low , low , close, volume, time, bar_index , time ]
SFPcords() =>
RealTF = barstate.isrealtime ? 0 : 1
= SFPData()
[h , h1 , h2 , l , l1 , l2 , c , v , t , n , t1 ]
method find(structure ms, bool use_max, bool sweep, bool useob) =>
min = 99999999.
max = 0.
idx = 0
if not sweep
if ((bar_index - ms.loc) - 1) > 0
if use_max
for i = 0 to (bar_index - ms.loc) - 1
max := math.max(high , max)
min := max == high ? low : min
idx := max == high ? i : idx
if useob
if high
ATM Premium Difference (Call - Put) Plots call-put difference of two different option contracts. Inspired by @TailThatWagsDog work
Smart Price Projection - Crypto Scalping V3Core Functionality
Trend Detection System:
Identifies swing highs/lows to detect breakouts
Requires 3 confirmations: swing break + volume spike + momentum
Uses ADX for trend strength validation
Tracks price structure (higher highs, lower lows)
Statistical Projection Engine:
Stores historical trend data (duration & movement per bar)
Filters by volatility regime (HIGH/MED/LOW)
Uses exponentially weighted averages to favor recent patterns
Projects 3 targets: Conservative (60%), Expected (100%), Aggressive (140%)
Applies momentum decay over projection period
Key Features:
Adaptive: Adjusts projections based on current volatility regime
Quality-aware: Compares current momentum to historical average
Visual: Shows trend phase (EARLY/MID/LATE), momentum strength, ADX, volume
Defensive: Won't project until sufficient sample size builds up
Strengths
✅ Multiple confirmation layers reduce false signals
✅ Volatility-adjusted projections
✅ Momentum decay prevents unrealistic targets
✅ Clean visual feedback with emojis and color coding
Easy [CHE] Easy — Minimalist Pine Script for detecting EMA direction changes to define fixed price zones for simple support and resistance visualization, ideal for manual trading workflows.
Summary
This indicator's programming is kept minimalist and super simple, with core logic in under 20 lines for easy comprehension and modification. It creates fixed price zones based on divergences between a base exponential moving average and its smoother counterpart, helping traders spot potential consolidation or reversal areas without dynamic adjustments. By locking the zone at the high and low of the signal bar, it avoids over-expansion in volatile conditions, offering a stable reference line colored by price position relative to the zone. This approach differs from expanding channels by prioritizing simplicity and persistence until a new qualifying signal, reducing visual clutter while highlighting directional bias through midpoint coloring.
Motivation: Why this design?
Traders often face noisy signals from moving averages that flip frequently in sideways markets or lag during breakouts, leading to premature entries or missed opportunities. This indicator addresses that by focusing on confirmed direction shifts between the base and smoothed averages, then anchoring a non-expanding zone to capture the initial price range of the shift. The result is a cleaner tool for marking equilibrium levels, assuming price respects these bounds in ranging or mildly trending conditions.
What’s different vs. standard approaches?
- Reference baseline: Traditional moving average crossovers or simple channels that update every bar.
- Architecture differences:
- Zones are set only on new divergence signals and remain fixed until reset by a gap from the prior zone.
- No ongoing high-low expansion; relies on persistent variables to hold bounds across bars.
- Midpoint plotting with conditional coloring based on close position, plus a highlight for zone initiations.
- Practical effect: Charts show persistent horizontal references instead of drifting lines, making it easier to gauge if price is rejecting or embracing the zone—useful for avoiding false breaks in low-volatility setups.
How it works (technical)
The indicator first computes a base exponential moving average of closing prices over a user-defined length, then applies a second exponential moving average to smooth that base. It checks if both the base and smoothed values are increasing or decreasing compared to their prior values, indicating aligned direction. A signal triggers when this alignment breaks, marking a potential shift.
On a new signal, if the current bar's high and low fall outside any existing zone (or none exists), the zone bounds update to those extremes and persist via dedicated variables. The midpoint of these bounds becomes the primary plot line, colored green if below the close (bullish lean), red if above (bearish lean), or gray otherwise. A secondary thick line highlights the midpoint briefly when a zone first sets, aiding visual confirmation. No higher timeframe data or external fetches are used, so updates occur on each bar close without lookahead.
Parameter Guide
EMA Length — Sets the period for the base moving average; longer values smooth more, reducing signal frequency but increasing lag. Default: 50. Trade-offs/Tips: Shorter for faster response in intraday charts (risks noise); longer for daily trends (may miss early shifts).
Smoother Length — Defines the period for the secondary smoothing on the base average; higher values dampen minor wiggles for stabler direction checks. Default: 3. Trade-offs/Tips: Keep low (2–5) for sensitivity; increase to 7+ if zones trigger too often in choppy markets, at cost of delayed signals.
Reading & Interpretation
The main circle plot at the zone midpoint serves as a dynamic equilibrium line: green suggests price is above the zone (potential strength), red indicates below (potential weakness), and gray shows containment within bounds (neutral consolidation). A sudden thick foreground line at the midpoint flags a fresh zone start, prompting review of the prior bar's context. Absence of a plot means no active zone, implying reliance on price action alone until the next signal.
Practical Workflows & Combinations
- Trend following: Enter long on green midpoint after a higher low touches the zone lower bound, confirmed by structure like higher highs; filter shorts similarly on red with lower highs.
- Exits/Stops: Use the opposite zone bound as a conservative stop (e.g., below lower for longs); trail aggressively to midpoint on strong moves, tightening near gray neutrality.
- Multi-asset/Multi-TF: Defaults work across forex and stocks on 1H–Daily; for crypto volatility, shorten EMA Length to 20–30. Pair with volume oscillators for confirmation, avoiding isolated use.
Behavior, Constraints & Performance
- Repaint/confirmation: Plots update on bar close using historical closes, so confirmed signals hold; live bars may shift until close but without future references.
- security()/HTF: Not used, eliminating related repaint risks.
- Resources: Minimal overhead—no loops, arrays, or bar limits exceeded; suitable for real-time on any timeframe.
- Known limits: Fixed zones may lag in strong trends (price drifts away without reset); signals skip if no gap from prior zone, potentially missing clustered shifts. Assumes standard OHLC data; untested on non-equity assets.
Sensible Defaults & Quick Tuning
Start with EMA Length at 50 and Smoother Length at 3 for balanced daily charts. If signals fire too frequently (e.g., in ranges), extend EMA Length to 100 for fewer but stabler zones. For sluggish response in trends, drop Smoother Length to 2 and EMA Length to 30, monitoring for added noise. In high-vol setups, widen both to 75/5 to filter extremes, trading speed for reliability.
What this indicator is—and isn’t
This is a lightweight visualization layer for EMA-driven zones, aiding manual chart reading and basic signal spotting. It is not a standalone system, predictive model, or automated alert generator—integrate with broader analysis like market structure and risk rules. (Unknown/Optional: No built-in alerts or multi-timeframe scaling.)
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.
Best regards and happy trading
Chervolino
Market Breadth - [JTCAPITAL]Market Breadth - is a comprehensive crypto market strength and sentiment indicator designed to visualize the overall bullish or bearish alignment across 40 major cryptocurrencies. By combining multi-asset Exponential Moving Average (EMA) comparisons and smoothing techniques, it offers a clean, aggregated view of the broader market trend—helping traders quickly assess whether the market is dominated by bullish momentum or bearish pressure.
The indicator works by calculating in the following steps:
Symbol Selection and Data Retrieval
The script monitors 40 leading cryptocurrencies based on Market Cap. Each asset’s daily close price is requested using a 1D timeframe. This ensures that every data point reflects the same temporal resolution, allowing the indicator to evaluate global crypto strength rather than individual token volatility.
EMA Comparison per Asset
For each asset, two Exponential Moving Averages (EMAs) are calculated:
A short-term EMA with period emalength (default 10).
A long-term EMA with period emalength2 (default 20).
Each coin receives a score of +1 when the short-term EMA is greater than the long-term EMA (indicating bullish structure), or -1 when it is below (indicating bearish structure). This binary scoring system effectively converts individual price action into a directional sentiment measure.
Market Breadth Aggregation
All 40 individual scores are summed into a single composite value called scores .
If many assets have bullish EMA alignment, the total score becomes strongly positive.
If the majority show bearish alignment, the total score turns negative.
This step transforms scattered price data into one unified market breadth metric—quantifying how many assets participate in the same directional trend.
Smoothing the Breadth Line
To reduce short-term noise and isolate trend direction, the aggregated score is smoothed using an EMA of length = smoothlen (default 15). The resulting smoothed line helps identify sustained shifts in collective sentiment rather than temporary fluctuations.
Visualization and Color Coding
When scores > 0 , the market breadth is bullish and the histogram is colored blue.
When scores < 0 , the breadth turns bearish and the histogram is purple.
The same logic applies to the smoothed line and background color, offering an instant visual cue of market mood transitions.
Buy and Sell Conditions:
The indicator itself does not trigger direct buy/sell signals but rather acts as a market regime filter . Traders can use it as follows:
Buy Filter: When the smoothed value is above zero and rising, the majority of assets confirm an uptrend — this favors long setups or trend continuation entries.
Sell Filter: When the smoothed value is below zero and falling, bearish alignment dominates — ideal for short setups or defensive risk management.
Optional filters could include combining this with RSI or volume-weighted momentum indicators to confirm breadth-based reversals.
Features and Parameters:
emalength – Defines the short-term EMA length used for individual asset trend detection (default 10).
emalength2 – Defines the long-term EMA length (default 20).
smoothlen – Defines the smoothing EMA length for the total market breadth line (default 15).
40 asset inputs – User-editable symbols allow full customization of which cryptos are tracked.
Dynamic color backgrounds – Visual distinction between bullish and bearish phases.
Specifications:
Exponential Moving Average (EMA)
EMA is a type of moving average that places more weight on recent price data, responding faster to market changes compared to SMA. By comparing a short-term and long-term EMA, the indicator captures momentum shifts across each asset individually. The crossover logic (EMA10 > EMA20) signals bullish conditions, while the opposite indicates bearish momentum.
Market Breadth
Market Breadth quantifies how many assets are participating in a directional move. Instead of tracking a single coin’s trend, breadth analysis measures collective sentiment. When most coins’ short-term EMAs are above long-term EMAs, the market shows healthy bullish breadth. Conversely, when most are below, weakness dominates.
Smoothing (EMA on Scores)
After summing the breadth score, the result is smoothed with an additional EMA to mitigate the inherent volatility caused by individual coin reversals. This second-level smoothing transforms raw fluctuations into a readable, trend-consistent curve.
Color Visualization
Visual cues are integral for intuitive interpretation.
Blue Shades: Indicate bullish alignment and collective upward momentum.
Purple Shades: Indicate bearish conditions and potential risk-off phases.
The background tint reinforces visual clarity even when the indicator is overlaid on price charts.
Background Logic
By applying the same color logic to the chart’s background, users can instantly recognize the prevailing market phase.
Use Cases
As a trend confirmation filter for other indicators (e.g., trade only in the direction of positive breadth).
As a divergence tool : when price rises but breadth weakens, it may signal a topping market.
As a macro sentiment monitor : perfect for assessing when the crypto market as a whole transitions from bearish to bullish structure.
Summary
“ Market Breadth - ” transforms the chaotic price movements of 40 cryptocurrencies into a single, powerful visual representation of overall market health. By merging EMA cross analysis with market-wide aggregation and smoothing , it provides traders with a deep understanding of when bullish or bearish forces dominate the ecosystem.
It’s a clean, data-driven approach to identifying shifts in crypto market sentiment — a perfect companion for trend-following, macro analysis, and timing portfolio exposure.
Enjoy!
Avg % Move Dashboard — Body and WicksTitle
Avg % Move Dashboard — Body and Wicks (w/ True Range)
Summary
Compact right-side dashboard showing the average percent move of recent candles:
Body size (absolute % from Open to Close)
Body bias (signed %, with up/down arrow and color)
Full range (High–Low %)
True range (ATR-style % relative to previous close)
Perfect for quickly gauging current market velocity and directional skew on any symbol or timeframe.
How It Works
Body % (per bar): (Close − Open) / Open × 100
Full range % (per bar): (High − Low) / Open × 100
True range % (per bar): max(High−Low, |High−PrevClose|, |Low−PrevClose|) / PrevClose × 100
Averages: Simple moving averages over the last N candles
Rounding: Values rounded to your chosen decimals
Bias row: shows signed average body percent with an ↑/↓ arrow and green/red color; near-zero values can display a neutral ⟷ based on a threshold
Settings
Candles to average (default 20): Window length for SMA calculations.
Decimals: Rounding precision for display.
Dashboard position: Top/Middle/Bottom Right.
Dashboard size: Tiny, Small, Normal, Large, Huge.
Background Color: Panel background.
Text Color (size rows): For non-bias rows.
Near-zero threshold (%): If the average body bias absolute value is below this, show neutral (⟷) instead of bullish/bearish.
What to show (toggles):
Show Body (Open→Close)
Show Full Range (High→Low)
Show True Range (ATR-style)
What You’ll See
Body size: average absolute body percent (magnitude only).
Body bias: average signed body percent with:
↑ and green if bullish
↓ and red if bearish
⟷ and gray if within the near-zero threshold
Full Range: average percent from High to Low.
True Range: average percent true range relative to previous close.
Footer: n = number of candles used.
How to Use
Add to any chart and timeframe; it overlays a table on the right-side.
Use “Body size” to assess typical candle strength.
Use “Body bias” to see directional skew:
Strong positive = persistent buying pressure.
Strong negative = persistent selling pressure.
Near-zero = balanced/sideways conditions.
Compare “Full range” vs “Body size”:
Large range but small body may indicate indecision or wicky conditions.
“True range” offers a classic ATR-style read (relative to prior close), useful for volatility-aware sizing.
Adjust “Candles to average” to your timeframe:
Short-term (scalps): 20–50
Intraday: 50–100
Swing: 100–200+
Best Practices
Pair with structure (S/R, sessions) to avoid false impressions in thin markets.
Increase length on noisy pairs/timeframes to smooth out noise.
Use the near-zero threshold to suppress micro-bias and focus on meaningful shifts.
Alerts
This dashboard is informational and doesn’t define alertconditions in the code. If you’d like, I can add optional alerts (e.g., bias flips from bearish to bullish beyond threshold, or volatility spikes on TR) — just say the word.
Limitations
This panel summarizes recent averages; it’s not a signal generator.
Values can differ across assets/timeframes; tune “Candles to average.”
True Range uses prev close normalization; that’s by design for ATR-style context.
Changelog
v1.0: Initial release — Body size, Body bias (with arrows/colors/neutral), Full Range, True Range, configurable UI.
Session Breakout, Retest, Reversal + Large Move Alert## **Session Breakout, Retest, Reversal + Large Move Alert**
### Overview
A powerful multi-functional indicator designed for day traders and futures traders to identify session-based breakout opportunities, retest confirmations, and significant price movements across all futures contracts (Gold, E-mini S&P 500, Nasdaq, Crude Oil, and more).
### Key Features
**📊 Pre-Market Session Tracking**
- Automatically calculates pre-market/overnight session highs and lows
- Displays session ranges with customizable colors and styling
- Extends lines through the entire trading session for easy reference
- Supports overnight sessions (e.g., 4 PM – 7:30 AM for Gold futures)
**🚀 Breakout Detection**
- Identifies breakouts above/below pre-market highs and lows
- Uses close-price confirmation to filter false signals from wicks
- Displays "BO ↑" and "BO ↓" labels at breakout points
- Generates instant alerts when breakouts occur
**♻️ Retest Failed Tracking**
- Monitors price retests after breakouts
- Detects when retests fail to reach previous support/resistance
- Labels "RF" (Retest Failed) for high-probability trade setups
- Helps identify reversal opportunities
**📈 First 5-Minute Analysis**
- Captures first 5 minutes of market open (customizable timeframe)
- Tracks first 5-minute highs and lows separately
- Essential for mean-reversion and breakout confirmation strategies
- Blue lines extend through the trading session for easy tracking
**⚡ Large Move Alerts**
- Detects significant price movements based on point thresholds
- Individual thresholds for 5+ different symbols:
- GC (Gold): 15 points
- ES (E-mini S&P 500): 15 points
- NQ (E-mini Nasdaq): 50 points
- CL (Crude Oil): 1.5 points
- Custom: Fully adjustable
- Auto-detects symbol from chart ticker
- Labels show exact point movement and candle direction
### Customization Options
**Symbol Configuration**
- **Auto-Mode**: Automatically detects trading symbol from chart ticker
- **Manual-Mode**: Select specific symbol (GC, ES, NQ, CL, or Custom)
**Session Settings**
- Fully customizable pre-market session time (24-hour format)
- Adjustable market open time for first 5-minute window
- Market close hour and minute configuration
- Support for any timezone
**Point Move Thresholds by Symbol**
- Set independent thresholds for each of your trading symbols
- Quickly adjust settings when switching between different futures
- Includes helpful tooltips for recommended values
**Display & Styling**
- Toggle all visual elements on/off individually
- Customizable colors for all lines and labels:
- Pre-market high/low colors
- Breakout labels (up/down)
- Retest failed labels
- First 5-minute session lines
- Large move indicators
- Text size options: tiny, small, normal, large, huge
### How It Works
1. **Session Tracking**: The indicator identifies your pre-market session and marks the high and low with labeled lines (PH/PL)
2. **Breakout Signal**: Once the market opens, it monitors for close prices above/below the pre-market levels and alerts you with "BO ↑" or "BO ↓"
3. **Retest Confirmation**: After a breakout, it tracks retests and labels "RF" when the retest fails to reach the opposite extreme, confirming trade direction
4. **Large Move Detection**: Simultaneously monitors for significant point moves that exceed your symbol-specific thresholds
5. **Alert Triggers**: Get real-time alerts for:
- Breakout Up/Down
- Any Breakout
- Large Move events
### Alert Conditions
The indicator includes four alert conditions:
- **Breakout Up Alert**: Price closes above pre-market high
- **Breakout Down Alert**: Price closes below pre-market low
- **Any Breakout Alert**: Either breakout condition triggers
- **Large Move Alert**: Point movement exceeds threshold for current symbol
### Ideal For
- ✅ Day traders (breakout/retest strategies)
- ✅ Futures traders (Gold, Oil, Stock Index Contracts)
- ✅ Intraday scalpers (first 5-minute analysis)
- ✅ Swing traders (session-based levels)
- ✅ Multi-symbol traders (independent thresholds per symbol)
### Disclaimer
This indicator is designed for educational and informational purposes. Past performance does not guarantee future results. Always use proper risk management and position sizing. Test thoroughly on historical data before trading live.
High Volume Zones with Signals – HVZ█ OVERVIEW
"High Volume Zones with Signals – HVZ" is a technical analysis indicator that identifies High Volume Zones (HVZ) on the chart and draws them as fully customizable boxes. Perfect for traders using price action, ICT, and Smart Money Concepts. The indicator highlights key volume-based support/resistance levels, detects potential consolidation zones (very large candles), and generates precise breakout and exit signals. Flexible volume filters, ATR filter, and visual styling options ensure a clean and highly effective chart.
█ CONCEPTS
The indicator detects candles with volume significantly above the average (default ≥ 2× SMA of volume over 20 periods). Such candles often signal institutional activity and create strong supply/demand zones.
The ATR filter additionally identifies very large candles – frequently a sign of market capitulation (panic buying/selling). Within the range of such a candle, prolonged consolidation often occurs, especially on higher timeframes (e.g., 4H and above).
Why are HVZ important? High-volume zones are areas where the market has left a large number of orders – institutions return there to “refresh” liquidity before the next move. A breakout against the zone’s character triggers a Break signal:
- Bullish HVZ broken downward (close below the lower boundary) → Break Down (sell),
- Bearish HVZ broken upward (close above the upper boundary) → Break Up (buy).
Note: The indicator requires real exchange volume – it will not work correctly on instruments without reported volume (e.g., certain CFDs or forex).
█ FEATURES
- HVZ Detection: Automatic identification of high-volume zones with Volume SMA Length and Volume Multiplier filters; historical initialization up to 500 candles back.
- ATR Filter: Optional detection of very large candles (potential consolidation/capitulation) using - ATR Length and ATR Multiplier; three action modes:
Skip Zone – large candle creates no zone,
Separate Color – zone is drawn in a distinct style (gray by default),
Normal Zone – treated like a regular HVZ.
- Gray zones (large candles, Separate Color): generate exactly the same Break signals as regular zones – based solely on the original candle direction (bullish → Break Down on lower break, bearish → Break Up on upper break). Gray color is only a visual marker for potential consolidation/capitulation zones.
- Customizable Boxes: Separate styles for bullish and bearish zones (border color, background gradient, line thickness and style); adjustable background and 50 % midline transparency.
- Break & Exit Signals:
Break Up/Down – green/red triangle after a candle closes outside the zone (zone disappears, triangle remains as a trace).
Exit Up/Down – green/red circle when price leaves the zone without a full breakout.
Signal Type option: Break, Exit, or Both.
- Midline: Automatic dashed line at the 50 % zone level with independent transparency control.
- Chart Cleanup: Automatic removal of inactive zones older than 500 candles (max_boxes_count=500).
- Alerts: Built-in alerts for Break Up and Break Down with clear messages.
█ HOW TO USE
Add to Chart: Paste the script in Pine Editor or find it in TradingView’s indicator library.
Configure Settings:
- Volume Filter: Volume SMA Length (default 20) and Volume Multiplier (default 2.0) – higher multiplier = fewer but stronger zones.
- ATR Filter: Enable/disable, set ATR Length (14) and ATR Multiplier (3.5); choose action for very large candles (Skip Zone / Separate Color / Normal Zone).
- Box Style: Background transparency (90) and midline transparency (70).
- Bull/Bear Box Style: Border and gradient colors, line thickness (1-5).
- ATR Style: Separate colors for large-candle zones (gray by default).
- Signal Settings: Choose Signal Type (Break/Exit/Both) and signal colors.
Signal Interpretation:
- Break Up (green triangle below bar): Bearish HVZ broken upward → buy signal, continuation of uptrend.
- Break Down (red triangle above bar): Bullish HVZ broken downward → sell signal, continuation of downtrend.
- Exit Up/Down (circles): Price leaves zone without breakout – may signal end of correction or reversal setup.
- HVZ Zones: Price often returns to high-volume zones to clear orders. An unfilled zone remains a price magnet.
- 50 % Level (midline): Ideal target for partial take-profit or reaction point inside the zone.
Combine signals with other tools (e.g., RSI, MACD, higher timeframes) for higher confidence.
█ APPLICATIONS
- Price Action & ICT: HVZ act as dynamic S/R; in an uptrend look for buys after breaking a bearish HVZ, in a downtrend look for sells after breaking a bullish HVZ. If you trade retests instead of breakouts, increase Volume Multiplier to 2.5-3.0 – fewer zones but much stronger. Note that after breaking a very strong zone, price often pulls back deeply before continuing.
- Breakout Strategies: For maximum Break signals, lower Volume Multiplier to 1.5-1.8 – gives many high-quality entries in trending markets. Always trade in the direction of the prevailing trend (e.g., only longs in uptrends). Enter after a Break signal with confirmation from volume or momentum (MACD above zero, RSI >50 for longs, <50 for shorts).
█ NOTES
- The indicator requires real exchange volume – it will not function properly on instruments without reported volume (e.g., certain CFDs, forex).
- Always confirm signals with additional context (market structure, higher timeframe).
Volatility-Targeted Momentum Portfolio [BackQuant]Volatility-Targeted Momentum Portfolio
A complete momentum portfolio engine that ranks assets, targets a user-defined volatility, builds long, short, or delta-neutral books, and reports performance with metrics, attribution, Monte Carlo scenarios, allocation pie, and efficiency scatter plots. This description explains the theory and the mechanics so you can configure, validate, and deploy it with intent.
Table of contents
What the script does at a glance
Momentum, what it is, how to know if it is present
Volatility targeting, why and how it is done here
Portfolio construction modes: Long Only, Short Only, Delta Neutral
Regime filter and when the strategy goes to cash
Transaction cost modelling in this script
Backtest metrics and definitions
Performance attribution chart
Monte Carlo simulation
Scatter plot analysis modes
Asset allocation pie chart
Inputs, presets, and deployment checklist
Suggested workflow
1) What the script does at a glance
Pulls a list of up to 15 tickers, computes a simple momentum score on each over a configurable lookback, then volatility-scales their bar-to-bar return stream to a target annualized volatility.
Ranks assets by raw momentum, selects the top 3 and bottom 3, builds positions according to the chosen mode, and gates exposure with a fast regime filter.
Accumulates a portfolio equity curve with risk and performance metrics, optional benchmark buy-and-hold for comparison, and a full alert suite.
Adds visual diagnostics: performance attribution bars, Monte Carlo forward paths, an allocation pie, and scatter plots for risk-return and factor views.
2) Momentum: definition, detection, and validation
Momentum is the tendency of assets that have performed well to continue to perform well, and of underperformers to continue underperforming, over a specific horizon. You operationalize it by selecting a horizon, defining a signal, ranking assets, and trading the leaders versus laggards subject to risk constraints.
Signal choices . Common signals include cumulative return over a lookback window, regression slope on log-price, or normalized rate-of-change. This script uses cumulative return over lookback bars for ranking (variable cr = price/price - 1). It keeps the ranking simple and lets volatility targeting handle risk normalization.
How to know momentum is present .
Leaders and laggards persist across adjacent windows rather than flipping every bar.
Spread between average momentum of leaders and laggards is materially positive in sample.
Cross-sectional dispersion is non-trivial. If everything is flat or highly correlated with no separation, momentum selection will be weak.
Your validation should include a diagnostic that measures whether returns are explained by a momentum regression on the timeseries.
Recommended diagnostic tool . Before running any momentum portfolio, verify that a timeseries exhibits stable directional drift. Use this indicator as a pre-check: It fits a regression to price, exposes slope and goodness-of-fit style context, and helps confirm if there is usable momentum before you force a ranking into a flat regime.
3) Volatility targeting: purpose and implementation here
Purpose . Volatility targeting seeks a more stable risk footprint. High-vol assets get sized down, low-vol assets get sized up, so each contributes more evenly to total risk.
Computation in this script (per asset, rolling):
Return series ret = log(price/price ).
Annualized volatility estimate vol = stdev(ret, lookback) * sqrt(tradingdays).
Leverage multiplier volMult = clamp(targetVol / vol, 0.1, 5.0).
This caps sizing so extremely low-vol assets don’t explode weight and extremely high-vol assets don’t go to zero.
Scaled return stream sr = ret * volMult. This is the per-bar, risk-adjusted building block used in the portfolio combinations.
Interpretation . You are not levering your account on the exchange, you are rescaling the contribution each asset’s daily move has on the modeled equity. In live trading you would reflect this with position sizing or notional exposure.
4) Portfolio construction modes
Cross-sectional ranking . Assets are sorted by cr over the chosen lookback. Top and bottom indices are extracted without ties.
Long Only . Averages the volatility-scaled returns of the top 3 assets: avgRet = mean(sr_top1, sr_top2, sr_top3). Position table shows per-asset leverages and weights proportional to their current volMult.
Short Only . Averages the negative of the volatility-scaled returns of the bottom 3: avgRet = mean(-sr_bot1, -sr_bot2, -sr_bot3). Position table shows short legs.
Delta Neutral . Long the top 3 and short the bottom 3 in equal book sizes. Each side is sized to 50 percent notional internally, with weights within each side proportional to volMult. The return stream mixes the two sides: avgRet = mean(sr_top1,sr_top2,sr_top3, -sr_bot1,-sr_bot2,-sr_bot3).
Notes .
The selection metric is raw momentum, the execution stream is volatility-scaled returns. This separation is deliberate. It avoids letting volatility dominate ranking while still enforcing risk parity at the return contribution stage.
If everything rallies together and dispersion collapses, Long Only may behave like a single beta. Delta Neutral is designed to extract cross-sectional momentum with low net beta.
5) Regime filter
A fast EMA(12) vs EMA(21) filter gates exposure.
Long Only active when EMA12 > EMA21. Otherwise the book is set to cash.
Short Only active when EMA12 < EMA21. Otherwise cash.
Delta Neutral is always active.
This prevents taking long momentum entries during obvious local downtrends and vice versa for shorts. When the filter is false, equity is held flat for that bar.
6) Transaction cost modelling
There are two cost touchpoints in the script.
Per-bar drag . When the regime filter is active, the per-bar return is reduced by fee_rate * avgRet inside netRet = avgRet - (fee_rate * avgRet). This models proportional friction relative to traded impact on that bar.
Turnover-linked fee . The script tracks changes in membership of the top and bottom baskets (top1..top3, bot1..bot3). The intent is to charge fees when composition changes. The template counts changes and scales a fee by change count divided by 6 for the six slots.
Use case: increase fee_rate to reflect taker fees and slippage if you rebalance every bar or trade illiquid assets. Reduce it if you rebalance less often or use maker orders.
Practical advice .
If you rebalance daily, start with 5–20 bps round-trip per switch on liquid futures and adjust per venue.
For crypto perp microcaps, stress higher cost assumptions and add slippage buffers.
If you only rotate on lookback boundaries or at signals, use alert-driven rebalances and lower per-bar drag.
7) Backtest metrics and definitions
The script computes a standard set of portfolio statistics once the start date is reached.
Net Profit percent over the full test.
Max Drawdown percent, tracked from running peaks.
Annualized Mean and Stdev using the chosen trading day count.
Variance is the square of annualized stdev.
Sharpe uses daily mean adjusted by risk-free rate and annualized.
Sortino uses downside stdev only.
Omega ratio of sum of gains to sum of losses.
Gain-to-Pain total gains divided by total losses absolute.
CAGR compounded annual growth from start date to now.
Alpha, Beta versus a user-selected benchmark. Beta from covariance of daily returns, Alpha from CAPM.
Skewness of daily returns.
VaR 95 linear-interpolated 5th percentile of daily returns.
CVaR average of the worst 5 percent of daily returns.
Benchmark Buy-and-Hold equity path for comparison.
8) Performance attribution
Cumulative contribution per asset, adjusted for whether it was held long or short and for its volatility multiplier, aggregated across the backtest. You can filter to winners only or show both sides. The panel is sorted by contribution and includes percent labels.
9) Monte Carlo simulation
The panel draws forward equity paths from either a Normal model parameterized by recent mean and stdev, or non-parametric bootstrap of recent daily returns. You control the sample length, number of simulations, forecast horizon, visibility of individual paths, confidence bands, and a reproducible seed.
Normal uses Box-Muller with your seed. Good for quick, smooth envelopes.
Bootstrap resamples realized returns, preserving fat tails and volatility clustering better than a Gaussian assumption.
Bands show 10th, 25th, 75th, 90th percentiles and the path mean.
10) Scatter plot analysis
Four point-cloud modes, each plotting all assets and a star for the current portfolio position, with quadrant guides and labels.
Risk-Return Efficiency . X is risk proxy from leverage, Y is expected return from annualized momentum. The star shows the current book’s composite.
Momentum vs Volatility . Visualizes whether leaders are also high vol, a cue for turnover and cost expectations.
Beta vs Alpha . X is a beta proxy, Y is risk-adjusted excess return proxy. Useful to see if leaders are just beta.
Leverage vs Momentum . X is volMult, Y is momentum. Shows how volatility targeting is redistributing risk.
11) Asset allocation pie chart
Builds a wheel of current allocations.
Long Only, weights are proportional to each long asset’s current volMult and sum to 100 percent.
Short Only, weights show the short book as positive slices that sum to 100 percent.
Delta Neutral, 50 percent long and 50 percent short books, each side leverage-proportional.
Labels can show asset, percent, and current leverage.
12) Inputs and quick presets
Core
Portfolio Strategy . Long Only, Short Only, Delta Neutral.
Initial Capital . For equity scaling in the panel.
Trading Days/Year . 252 for stocks, 365 for crypto.
Target Volatility . Annualized, drives volMult.
Transaction Fees . Per-bar drag and composition change penalty, see the modelling notes above.
Momentum Lookback . Ranking horizon. Shorter is more reactive, longer is steadier.
Start Date . Ensure every symbol has data back to this date to avoid bias.
Benchmark . Used for alpha, beta, and B&H line.
Diagnostics
Metrics, Equity, B&H, Curve labels, Daily return line, Rolling drawdown fill.
Attribution panel. Toggle winners only to focus on what matters.
Monte Carlo mode with Normal or Bootstrap and confidence bands.
Scatter plot type and styling, labels, and portfolio star.
Pie chart and labels for current allocation.
Presets
Crypto Daily, Long Only . Lookback 25, Target Vol 50 percent, Fees 10 bps, Regime filter on, Metrics and Drawdown on. Monte Carlo Bootstrap with Recent 200 bars for bands.
Crypto Daily, Delta Neutral . Lookback 25, Target Vol 50 percent, Fees 15–25 bps, Regime filter always active for this mode. Use Scatter Risk-Return to monitor efficiency and keep the star near upper left quadrants without drifting rightward.
Equities Daily, Long Only . Lookback 60–120, Target Vol 15–20 percent, Fees 5–10 bps, Regime filter on. Use Benchmark SPX and watch Alpha and Beta to keep the book from becoming index beta.
13) Suggested workflow
Universe sanity check . Pick liquid tickers with stable data. Thin assets distort vol estimates and fees.
Check momentum existence . Run on your timeframe. If slope and fit are weak, widen lookback or avoid that asset or timeframe.
Set risk budget . Choose a target volatility that matches your drawdown tolerance. Higher target increases turnover and cost sensitivity.
Pick mode . Long Only for bull regimes, Short Only for sustained downtrends, Delta Neutral for cross-sectional harvesting when index direction is unclear.
Tune lookback . If leaders rotate too often, lengthen it. If entries lag, shorten it.
Validate cost assumptions . Increase fee_rate and stress Monte Carlo. If the edge vanishes with modest friction, refine selection or lengthen rebalance cadence.
Run attribution . Confirm the strategy’s winners align with intuition and not one unstable outlier.
Use alerts . Enable position change, drawdown, volatility breach, regime, momentum shift, and crash alerts to supervise live runs.
Important implementation details mapped to code
Momentum measure . cr = price / price - 1 per symbol for ranking. Simplicity helps avoid overfitting.
Volatility targeting . vol = stdev(log returns, lookback) * sqrt(tradingdays), volMult = clamp(targetVol / vol, 0.1, 5), sr = ret * volMult.
Selection . Extract indices for top1..top3 and bot1..bot3. The arrays rets, scRets, lev_vals, and ticks_arr track momentum, scaled returns, leverage multipliers, and display tickers respectively.
Regime filter . EMA12 vs EMA21 switch determines if the strategy takes risk for Long or Short modes. Delta Neutral ignores the gate.
Equity update . Equity multiplies by 1 + netRet only when the regime was active in the prior bar. Buy-and-hold benchmark is computed separately for comparison.
Tables . Position tables show current top or bottom assets with leverage and weights. Metric table prints all risk and performance figures.
Visualization panels . Attribution, Monte Carlo, scatter, and pie use the last bars to draw overlays that update as the backtest proceeds.
Final notes
Momentum is a portfolio effect. The edge comes from cross-sectional dispersion, adequate risk normalization, and disciplined turnover control, not from a single best asset call.
Volatility targeting stabilizes path but does not fix selection. Use the momentum regression link above to confirm structure exists before you size into it.
Always test higher lag costs and slippage, then recheck metrics, attribution, and Monte Carlo envelopes. If the edge persists under stress, you have something robust.
Trend Gazer v2English Follows;
---
# Trend Gazer v2 - マルチタイムフレーム トレーディング インジケータ
## 📊 概要
**Trend Gazer v2** は、**ボリューメトリックウェイテッドクラウド(VWC)**、**リバースRSIシグナル**、**ICTドンチアンスマートマネーストラクチャー**、**マルチタイムフレームボリンジャーバンド**、**EMA分析**を組み合わせた高度なトレーディングインジケータです。
**7種類のシグナルタイプ**と**4つの設定可能なフィルター**を搭載し、特にEMA塗りつぶし色遷移期間中のフィルタリング機能（**フィルター4**）により、トレンド変化時の偽シグナルを削減します。
---
## ✨ 主要機能
### v2の新機能: フィルター4 - EMA塗りつぶし遷移期間フィルター（デフォルト有効）
**フィルター4**は、EMA塗りつぶし色の遷移期間中に方向性バイアスを作成し、偽シグナルを削減します：
**動作ロジック:**
1. **すべて青 → 遷移開始（一部が赤に）→ BUYのみ表示 → すべて赤 OR 青に戻る（期間終了）**
- 遷移期間中はSELLシグナルをすべてブロック
2. **すべて赤 → 遷移開始（一部が青に）→ SELLのみ表示 → すべて青 OR 赤に戻る（期間終了）**
- 遷移期間中はBUYシグナルをすべてブロック
**終了条件:**
- 遷移が完了（すべて目標色になる）
- 元の色に戻る（遷移失敗）
**⭐ 特徴:** 他のフィルター（1,2,3）はシグナル1-5のみに適用されますが、**フィルター4はすべてのシグナル（S1-7）に適用**されます。これにより、トレンド変化時の一貫したフィルタリングを実現し、勝率向上に貢献します。
---
### 1. **複数シグナルタイプ(7種類)**
**シグナル1:** マーケットストラクチャーが強気(Bullish Structure) かつ リバースRSIが強気にシフト
**シグナル2:** (マーケットストラクチャーが強気 または リバースRSIが強気) かつ VWC UPシグナル検知
**シグナル3:** リバースRSIが強気 かつ マーケットストラクチャーが弱気から強気に変化(ストラクチャースイッチ)
**シグナル4:** マーケットストラクチャーが強気 かつ VWCシグナルがUP状態(初回のみ)
**シグナル5:** 15分足下部ボリンジャーバンドを上抜けた後、リバースRSI強気シグナル検知
**シグナル6:** 15分足下部BB または EMA50を上抜けた後、初回のリバースRSI強気シグナル(フィルター1,2,3をバイパス、フィルター4のみ適用)
**シグナル7:** マーケットストラクチャーが強気 かつ EMA20またはEMA50から上に反発後、最初のBUY検知(フィルター1,2,3をバイパス、フィルター4のみ適用)
*(SELLシグナルは逆ロジックに従う)*
---
### 2. **高度なフィルタリングシステム**
**フィルター1: RSI方向フィルター(デフォルト:ON) - シグナル1-5のみ**
- リバースRSIが強気 または マーケットストラクチャーが強気の時のみBUYを表示
- リバースRSIが弱気 または マーケットストラクチャーが弱気の時のみSELLを表示
- 強い方向性のある動きでの逆張りシグナルを防止
**フィルター2: EMA配列フィルター(デフォルト:ON) - シグナル1-5のみ**
- SELLシグナルはEMA配列が確認された時のみ表示:
- `ema20 > ema50 > ema100 > ema200`(強い下降トレンド)、または
- `ema20 < ema50 < ema100 < ema200`(強い上昇トレンド)
- レンジ相場での偽シグナルを削減
**フィルター3: ボリンジャーバンド方向フィルター(デフォルト:ON) - シグナル1-5のみ**
- 15分足上部BB かつ 60分足上部BBを下抜け後 → 15分足下部BBにタッチするまでSELLのみ表示
- 15分足下部BB かつ 60分足下部BBを上抜け後 → 15分足上部BBにタッチするまでBUYのみ表示
- 高確率エントリーのための方向バイアスゾーンを作成
**⭐ フィルター4: EMA塗りつぶし遷移期間フィルター(デフォルト:ON) - 全シグナル1-7に適用**
- すべてのEMA塗りつぶしが青から赤に遷移中 → BUYのみ表示（SELLブロック）
- すべてのEMA塗りつぶしが赤から青に遷移中 → SELLのみ表示（BUYブロック）
- 遷移が完了または元の色に戻ると期間終了
- トレンド変化時の偽シグナルを削減し、勝率向上に貢献
**注意:** シグナル6, 7はフィルター1,2,3をバイパスしますが、フィルター4は適用されます。
---
### 3. **マルチタイムフレームボリンジャーバンド**
- **15分足ボリンジャーバンド**(黒い点線): 短期ボラティリティゾーン
- **60分足ボリンジャーバンド**(黒/カスタマイズ可能): 長期サポート/レジスタンス
これらのバンドは以下を識別:
- **買われ過ぎ/売られ過ぎの状態**
- **ブレイクアウト確認**(シグナル5,6)
- **平均回帰の機会**
---
### 4. **7本の指数移動平均(EMA)**
- **EMA 7, 20, 50, 100, 200, 400, 800**
- EMA20-50間とEMA50-200間の動的**EMA塗りつぶし**でトレンドバイアスを色分け:
- **赤色塗りつぶし:** 弱気配列(ema20 > ema50 > ema200)
- **青色塗りつぶし:** 強気配列(ema20 < ema50 < ema200)
- EMAはシグナル7の反発検知のための動的サポート/レジスタンスとして機能
- **フィルター4はEMA塗りつぶし**の遷移を監視して方向性バイアスを作成
---
### 5. **ICTドンチアンスマートマネーストラクチャー**
- ローソク足の枠に色を付けてマーケットストラクチャーを可視化:
- **赤枠(Bullish Structure):** 強気ストラクチャー(買い手が優勢)
- **緑枠(Bearish Structure):** 弱気ストラクチャー(売り手が優勢)
- ドンチアンチャネルとピボットベースのストラクチャーブレイクに基づく
- シグナル1, 3, 4, 7の検知に不可欠
---
### 6. **リバースRSIシグナル**
- RSI計算を反転させてオシレーター値ではなく価格レベルを導出
- **RSIミッドラインのスーパートレンド**がトレンドシフトを判定:
- **強気シフト:** 上昇モメンタムの可能性
- **弱気シフト:** 下降モメンタムの可能性
- 半透明ラベル("Bullish"/"Bearish")として価格の上下に表示
---
### 7. **VWC(ボリューメトリックウェイテッドクラウド)トレンド検知器**
- 市場状況に応じて拡大/縮小する適応型ボラティリティベースバンド
- 価格がバンド内に入ると**UP/DOWNシグナル**を提供
- VWCステータステーブルには以下を表示:
- 現在のトレンド方向(BULLISH/BEARISH)
- EMA配列ステータス
- 最後に表示したシグナル(BUY/SELL)とシグナル以降のバー数
---
## 🎯 トレード戦略
### 推奨アプローチ
**1. トレンドフォロー(シグナル1, 2, 4)**
- 明確なマーケットストラクチャー(強気または弱気ストラクチャー)を待つ
- VWCトレンド + RSI方向 + ストラクチャー配列の合致でエントリー
- EMA塗りつぶしを動的ストップロスゾーンとして使用
**2. 反転トレード(シグナル5, 6, 7, 8)**
- **シグナル5,6**: ボリンジャーバンドブレイクアウトと反転を特定
- **シグナル7**: ストラクチャー確認を伴うEMA反発を探す
- **シグナル8**: **早期トレンド反転** - トレンド変化の最初期でエントリー
- これらのシグナルは特定フィルターをバイパスし早期エントリー機会を提供
**3. シグナル8 - 早期トレンド反転戦略 (v2新機能)**
**最適な使用ケース:**
- **上位時間軸(15分足〜1時間足)**: 主要なトレンド反転の捕捉に最も信頼性が高い
- **スイングトレード**: 数日間のポジションエントリーに最適
- **確認トレード**: 他のシグナルと組み合わせて高信頼度エントリー
**シグナル8のトレード方法:**
- **BUY(青→赤遷移)**:
- すべてのEMA塗りつぶしが青から赤に変化するのを監視
- エントリー: シグナル8 BUYラベルが出現した時
- ストップロス: 直近スイング安値またはEMA200の下
- 利確: 次のレジスタンスを目標、またはEMA50でトレーリングストップ
- **SELL(赤→青遷移)**:
- すべてのEMA塗りつぶしが赤から青に変化するのを監視
- エントリー: シグナル8 SELLラベルが出現した時
- ストップロス: 直近スイング高値またはEMA200の上
- 利確: 次のサポートを目標、またはEMA50でトレーリングストップ
**シグナル8の利点:**
- 他のシグナルより5-10バー早くトレンド反転を捕捉
- 新トレンド開始時の低リスクエントリー
- より高いリワード可能性（トレンド初期でのエントリー）
**シグナル8のリスク:**
- レンジ/不規則相場では偽シグナルを生成する可能性
- 上位時間軸での確認と組み合わせるのがベスト
- 早期エントリーのため、より大きなストップロスの使用を検討
---
### リスク管理
- **EMA20/EMA50**をトレーリングストップロスレベルとして使用
- シグナル8では:**EMA200**を主要トレンドストップロスとして使用
- 反対シグナルまたは主要EMAクロス時に決済
- 上位時間軸のトレンド確認と組み合わせ(60分足以上チャート)
- VWCステータステーブルが矛盾するシグナルを示す時は取引を避ける
### 推奨時間軸
- **シグナル8最適時間軸:** 15分足〜1時間足(早期トレンド反転用)
- **他のシグナル:** 1分足~15分足(スキャルピング/デイトレード)
- **上位時間軸:** 1時間足以上でも機能するがシグナル数は減少
- **補完的使用:** 4時間足/日足チャートで全体トレンド方向を確認
---
## 🔄 MTF OB & FVG Detectorとの統合トレード戦略
**Trend Gazer v2**と**MTF OB & FVG Detector**を組み合わせることで、機関投資家のオーダーフロー（OB）と市場の需給ギャップ（FVG）を活用した高度なトレーディング戦略を実現できます。
### 統合戦略の利点
**1. 最高確率エントリーポイントの特定**
- Trend GazerのBUY/SELLシグナル + OB/FVGゾーン = **最高確率エントリーポイント**
- 複数の時間足（5分、15分、60分）からのOB統合 + Trend Gazerシグナル = **機関投資家とトレンドの合致**
**2. 精密なエントリー価格の決定**
- Trend Gazerでトレンド方向と市場バイアスを確認
- OB/FVGゾーンで正確なエントリー価格を特定
- 不要なリスクを削減し、リワード比率を最大化
**3. 強化されたストップロス管理**
- EMA20/50（Trend Gazer）をトレーリングストップロスとして使用
- OBゾーン（MTF OB & FVG）を追加の防御ラインとして設定
- 多層防御によるリスク管理
---
### 推奨統合戦略
#### 戦略1: 高確率コンフルエンスエントリー 【最推奨】
**セットアップ:**
1. Trend Gazer v2でBUY/SELLシグナルを監視
2. MTF OB & FVG Detectorで統合OB/FVGゾーン（3つ以上の時間足）を特定
3. 両者が同じ価格ゾーンで一致するのを待つ
**エントリー条件（BUY例）:**
- ✅ Trend Gazer: BUYシグナル発生（シグナル1-7のいずれか）
- ✅ MTF OB & FVG: ブリッシュOBゾーン（特に統合ゾーン）に価格がタッチ
- ✅ フィルター4（EMA遷移期間）: 青→赤遷移中（BUYのみ期間）
- ✅ マーケットストラクチャー: 強気（赤枠）
- ✅ 高ボリューム: OBゾーンのボリュームパーセンテージが75%以上
**エントリー:**
- 価格がOBゾーン内でTrend GazerのBUYシグナルが点灯したバーの終値でエントリー
- または、次バーの始値でエントリー
**ストップロス:**
1. **初期SL**: OBゾーンの下端 - (5-10 pips/ポイント)
2. **代替SL**: EMA50の下（より広いSL、スイングトレード向け）
3. **タイトSL**: 直近安値 - (3-5 pips/ポイント)（スキャルピング向け）
**利確ターゲット:**
1. **T1（50%）**: 次の上位時間足ベアリッシュOB/FVGゾーン
2. **T2（30%）**: 60分足ボリンジャーバンド上限
3. **T3（20%）**: EMA20/50でトレーリング、逆シグナルまで保持
**SELL例は逆ロジック適用**
---
#### 戦略2: 精密反転エントリー【中級者向け】
**最適使用場面:**
- 強いトレンドの終了時
- 重要な統合OB/FVGゾーンでの反転
- 上位時間足のサポート/レジスタンスレベル
**エントリー条件（SELL例）:**
1. **上位時間足確認:**
- 60分足でベアリッシュOB統合ゾーンを特定
- 価格が統合ゾーンに到達
2. **Trend Gazerシグナル:**
- **シグナル5**: 15分足上部BBを下抜け + リバースRSI弱気シフト、または
- **シグナル6**: 15分足上部BB/EMA50下抜け後の初回RSI弱気シグナル、または
- **シグナル7**: マーケットストラクチャー弱気 + EMA20/50からの下方反発
3. **OB/FVG確認:**
- 15分足または60分足のベアリッシュOBゾーンで反発確認
- FVGが上方に残っている（価格磁石効果）
**エントリー:**
- Trend Gazerシグナル + OBゾーン反発の両方確認後
- ローソク足パターン確認（ピンバー、エンガルフィング等）推奨
**ストップロス:**
- OBゾーン上端 + 10-15 pips/ポイント
- または60分足上部BBの上
**利確:**
- **T1**: 下位時間足ブリッシュOB/FVGゾーン（未充填FVG優先）
- **T2**: 15分足下部BB
- **T3**: 逆シグナルまたはEMA20/50タッチ
**BUY例は逆ロジック適用**
---
#### 戦略3: トレンドフォロー with OBサポート【初心者向け】
**シンプルなアプローチ:**
**BUY戦略:**
1. **トレンド確認（Trend Gazer）:**
- EMA塗りつぶしが赤色（弱気配列）
- VWCステータスがBULLISH
- マーケットストラクチャーが強気（赤枠）
2. **押し目待ち:**
- 価格が下位時間足（5分または15分）のブリッシュOBゾーンまで調整
- Trend Gazerの**シグナル1, 2, または4**が発生
3. **エントリー:**
- OBゾーン内でBUYシグナル点灯時
- ローソク足の実体終値でエントリー
4. **ストップロス:**
- OBゾーン下端 - 10 pips/ポイント
5. **利確:**
- **簡易**: リスクの2倍（1:2 R:R）
- **動的**: 次のベアリッシュOBまたは逆シグナルまで
**SELL戦略は逆ロジック適用**
---
#### 戦略4: FVGフィリング with Trend Gazer確認【スキャルピング】
**短期トレーダー向け:**
**セットアップ:**
- 未充填のFVG（ブリッシュまたはベアリッシュ）を特定
- FVGが現在価格から離れている（最低20-30 pips/ポイント）
**BUY例（ブリッシュFVG下方）:**
1. **FVG識別:**
- 下方に未充填のブリッシュFVG（オレンジボックス）
- 高ボリュームFVG優先（75%以上）
2. **Trend Gazer確認:**
- 価格がFVGに近づく
- マーケットストラクチャーが強気に転換
- **シグナル3, 4, または7**がFVGゾーン近辺で発生
3. **エントリー:**
- 価格がFVG内に入り、Trend GazerシグナルでFVGからの反発確認
- ローソク足の実体終値でエントリー
4. **ストップロス:**
- FVG下端 - 5-7 pips/ポイント（タイト）
5. **利確:**
- **T1（70%）**: FVG上端（ギャップ充填）
- **T2（30%）**: 次のレジスタンスまたは逆シグナル
**SELL例（ベアリッシュFVG上方）は逆ロジック適用**
---
### 統合使用のベストプラクティス
**1. チャート設定:**
- **メインチャート時間足**: 5分足または15分足
- **Trend Gazer v2**: すべてのシグナルとフィルター有効
- **MTF OB & FVG Detector**: 5分、15分、60分を有効化、統合機能ON
**2. アラート設定:**
- Trend Gazer: BUY/SELLシグナルアラート有効
- MTF OB & FVG: 反発アラート + 統合ゾーンアラート有効（Min 3 OBs）
- 両方のアラートが同時に鳴る = 最高確率エントリー
**3. 確認チェックリスト（エントリー前）:**
- Trend GazerのBUY/SELLシグナル確認
- OB/FVGゾーンが価格に重なっている
- フィルター4が方向を支持（遷移期間中）
- マーケットストラクチャーが一致
- OB/FVGの高ボリューム確認（70%以上推奨）
- 上位時間足のトレンドが矛盾していない
- リスク:リワード比率が最低1:1.5以上
**4. リスク管理ルール:**
- 1トレードあたりの資金リスク: 口座残高の0.5-1%
- 同時ポジション: 最大2-3（相関性の低い銘柄のみ）
- 連続損失後: 3連敗後は休憩、戦略見直し
- 日次損失上限: 口座残高の2-3%
**5. 避けるべき状況:**
- ❌ Trend Gazerシグナルなしで、OB/FVGのみでエントリー
- ❌ 重要経済指標発表の直前/直後（ボラティリティスパイク）
- ❌ 複数フィルターが矛盾している時
- ❌ OB/FVGゾーンが既に複数回テストされている（弱体化）
- ❌ 流動性が低い時間帯（アジア早朝等）
---
### 統合戦略のパフォーマンス向上Tips
**1. 時間足の選択:**
- **スキャルピング**: 1分/3分足OB + 5分足Trend Gazerシグナル
- **デイトレード**: 5分/15分足OB + 15分足Trend Gazerシグナル
- **スイングトレード**: 15分/60分足OB + 60分足Trend Gazerシグナル
**2. 統合ゾーンの優先順位:**
- **最高優先**: 60分足OB統合（3つ以上）+ Trend Gazer Signal 6 or 7
- **高優先**: 15分足OB統合 + フィルター4遷移期間 + Signal 1-5
- **中優先**: 5分足OB + マーケットストラクチャー一致 + Signal 1-4
- **低優先**: 単一時間足OB + 基本シグナル（確認重視）
**3. バックテスト推奨:**
- 過去1-3ヶ月のデータで各戦略をテスト
- 勝率、平均R:R、最大ドローダウンを記録
- 自分のトレードスタイルに最適な組み合わせを発見
**4. 継続的改善:**
- トレード日誌を記録（スクリーンショット含む）
- 週次でパフォーマンスレビュー
- 有効な組み合わせパターンを文書化
- 市場環境の変化に応じて調整
---
### 統合戦略の実例
**実例1: 完璧なコンフルエンスBUY**
```
状況:
- 15分足チャート、EUR/USD
- 価格が60分足ブリッシュOB統合ゾーン（5分+15分+60分）にタッチ
- Trend Gazer Signal 6発生: 15分足下部BB上抜け後、初回RSI強気シグナル
- フィルター4: EMA塗りつぶし青→赤遷移中（BUYのみ期間）
- マーケットストラクチャー: 強気（赤枠）に転換
- OBボリューム: 82%（強い買い圧力）
エントリー: 1.0850（OBゾーン中央）
ストップロス: 1.0835（OBゾーン下端 - 5 pips）
利確T1: 1.0875（次の15分足ベアリッシュOB）- 達成
利確T2: 1.0895（60分足上部BB）- 達成
利確T3: 1.0920（EMA20トレーリング）- 逆シグナル手前で決済
結果: +70 pips、リスク15 pips = 4.67:1 R:R
```
**実例2: FVGフィリング with 反転確認SELL**
```
状況:
- 5分足チャート、GBP/JPY
- 上方に未充填ベアリッシュFVG（アクアボックス、15分足）
- 価格が急騰してFVGに到達
- Trend Gazer Signal 7発生: マーケットストラクチャー弱気 + EMA50からの下方反発
- リバースRSI: 弱気シフト
- FVGボリューム: 78%（強い売り圧力）
エントリー: 191.50（FVG上端での反発確認）
ストップロス: 191.75（FVG上端 + 25 pips）
利確T1: 191.00（FVG下端、ギャップ充填）- 達成
利確T2: 190.70（次のブリッシュOB）- 部分達成
結果: +50 pips（加重平均）、リスク25 pips = 2:1 R:R
```
---
### まとめ: なぜこの統合が強力なのか
**Trend Gazer v2の役割:**
- ✅ トレンド方向の確認（VWC、EMA、ストラクチャー）
- ✅ タイミングシグナル（7種類のエントリー機会）
- ✅ 複数フィルターによる偽シグナル削減
- ✅ 動的ストップロス管理（EMA、BB）
**MTF OB & FVG Detectorの役割:**
- ✅ 機関投資家のオーダーフロー可視化
- ✅ 正確な価格ゾーン特定（精密エントリー）
- ✅ 高確率サポート/レジスタンスレベル
- ✅ ボリューム分析による強度確認
**統合による相乗効果:**
- 🎯 **確率の掛け算**: 各インジケーター単独でも有効だが、両者の一致で確率が大幅向上
- 🎯 **リスク削減**: より精密なストップロス設定で損失を最小化
- 🎯 **リワード最大化**: 最適なエントリー価格で利益幅を拡大
- 🎯 **多様な戦略**: トレンドフォロー、反転、スキャルピング、スイング全てに対応
**推奨開始手順:**
1. デモ口座で戦略1（コンフルエンスエントリー）を2週間テスト
2. トレード日誌を記録し、パターンを学習
3. 小額リアル口座で同じ戦略を実践（最小ロット）
4. 自信がついたら戦略2, 3に拡張
5. 継続的にバックテストと改善を実施
この統合アプローチにより、市場の**需給ゾーン（OB/FVG）**と**トレンドモメンタム（Trend Gazer）**の両方を活用した、プロフェッショナルレベルのトレーディング戦略を実現できます。
---
## ⚙️ 入力パラメータ
### シグナル8設定 (v2新機能)
- **シグナル8を有効化: EMA塗りつぶし色遷移:** シグナル8のオン/オフ切り替え(デフォルト:OFF)
- **EMA傾きルックバック:** EMA傾き計算の期間(デフォルト:5、範囲:2-20)
- 低い値: より敏感、早期シグナル
- 高い値: より安定、偽シグナル減少
### シグナル表示設定
- **BUY/SELLラベルを表示:** メインエントリーシグナルの切り替え
- **RSIトレンドシフトラベルを表示:** Bullish/Bearish RSIシフトの表示
- **ラベルサイズ:** Small、Normal、Large、Huge
- **ラベル位置:** バー上またはATRでオフセット
### フィルター設定
- **RSI方向フィルターを有効化:** RSIトレンドでシグナルをフィルター(デフォルト:ON)
- **EMA配列フィルターを有効化:** SELLシグナルにEMA配列を要求(デフォルト:ON)
- **BB方向フィルターを有効化:** BBブレイクアウト後に方向バイアスゾーンを作成(デフォルト:ON)
### ビジュアル設定
- **ストラクチャーキャンドルを表示:** マーケットストラクチャーでキャンドルの枠に色付け
- **EMAを表示:** 7本の指数移動平均を表示
- **EMA塗りつぶしを表示:** 主要EMA間の色付き塗りつぶしを表示(シグナル8に重要)
- **15分足ボリンジャーバンドを表示:** 短期BBを表示
- **60分足ボリンジャーバンドを表示:** 長期BBを表示
- **VWCステータステーブル:** ステータステーブル表示の切り替え
---
## 🆕 v2の新機能
1. **シグナル8 - EMA塗りつぶし色遷移検知**
- 早期トレンド反転識別
- EMA傾きフラット化分析
- EMA収束パターン認識
- ATRを使用した正規化傾き計算
2. **強化されたツールチップドキュメント**
- すべてのシグナルが入力ツールチップに明確に文書化
- シグナル8の説明を含む
3. **改善されたアラートシステム**
- シグナル8 BUY/SELL用の新しいアラート
- EMA塗りつぶし色遷移専用アラート
4. **より優れた視覚的明瞭性**
- EMA塗りつぶしはシグナル8可視化に重要
- すべての塗りつぶしが色遷移している時が見やすい
---
## ⚠️ 免責事項
本インジケータは**教育および情報提供のみを目的**として提供されています。**金融アドバイスではありません**。
取引には多大な損失リスクが伴い、すべての投資家に適しているわけではありません。過去の実績は将来の結果を保証するものではありません。ユーザーは独自の調査を行い、取引決定を行う前に資格のある金融アドバイザーに相談することを検討してください。
作成者は本インジケータを使用して発生したいかなる損失についても責任を負いません。
---
## 📝 クレジット
- **リバースRSIシグナル:** AlgoAlphaのコンセプトに基づく
- **VWCトレンド検知器:** オリジナル実装
- **ICTドンチアンストラクチャー:** ICTコンセプトとドンチアンチャネルからインスピレーション
- **ボリンジャーバンド:** ジョン・ボリンジャー開発
- **EMA分析:** 標準的なテクニカル分析ツール
- **シグナル8 EMA遷移:** Trend Gazer v2のためのオリジナル実装
---
## 📜 ライセンス
このPine Script™コードは、https://mozilla.org/MPL/2.0/ の**Mozilla Public License 2.0**の条項に従います
---
## 🔔 アラート
インジケータには以下の内蔵アラート条件が含まれます:
- BUYシグナル(全8タイプ)
- SELLシグナル(全8タイプ)
- **新機能: シグナル8 EMA塗りつぶし色遷移アラート**
- リバースRSI強気/弱気シフト
- VWC UP/DOWNシグナル
TradingViewのアラート作成メニューからアラートを設定してください。
---
**バージョン:** 2.0
**プラットフォーム:** TradingView Pine Script™
**タイプ:** インジケータ(オーバーレイ)
---
## 🚀 最良の結果を得るためのヒント
1. **シグナルを組み合わせる:** シグナル8を他のシグナルと組み合わせて合致を確認
2. **シグナル8は上位時間軸で:** 15分足〜1時間足で最も信頼性が高い
3. **EMA塗りつぶしを使用:** シグナル8の遷移を見るためEMA塗りつぶしを表示
4. **マーケットストラクチャーを尊重:** 大きな時間軸のトレンドに逆らわない
5. **シグナル8をバックテスト:** 過去データでテストして動作を理解
6. **EMA傾きルックバックを調整:** トレードスタイルと時間軸に合わせて微調整
7. **テーブルを監視:** VWCステータステーブルで迅速なトレンド評価
8. **シグナル8 + ストラクチャー:** シグナル8がストラクチャー変化と一致する時に最良の結果
---
**ハッピートレーディング! 📊💹**
**v2アップグレード: シグナル8でトレンド反転をより早く捕捉!**
ーーー
# Trend Gazer v2 - Multi-Timeframe Trading Indicator
## 📊 Overview
**Trend Gazer v2** is an advanced trading indicator that combines **Volumetric Weighted Cloud (VWC)**, **Reverse RSI Signals**, **ICT Donchian Smart Money Structure**, **Multi-Timeframe Bollinger Bands**, and **EMA Analysis** for comprehensive market analysis.
**7 signal types** with **4 customizable filters**, featuring the **Filter 4 (EMA Fill Transition Period Filter)** which reduces false signals during trend changes by default.
---
## ✨ Key Features
### NEW in v2: Filter 4 - EMA Fill Transition Period Filter (Default ON)
**Filter 4** creates directional bias during EMA fill color transition periods to reduce false signals:
**Operation Logic:**
1. **ALL Blue → Transition Starts (some turn red) → BUY ONLY → ALL Red OR Back to Blue (period ends)**
- Blocks all SELL signals during transition period
2. **ALL Red → Transition Starts (some turn blue) → SELL ONLY → ALL Blue OR Back to Red (period ends)**
- Blocks all BUY signals during transition period
**Termination Conditions:**
- Transition completes (all fills become target color)
- Reverts to original color (transition fails)
**⭐ Key Feature:** While other filters (1,2,3) only apply to Signals 1-5, **Filter 4 applies to ALL signals (S1-7)**. This provides consistent filtering during trend changes and improves win rate.
---
### 1. **Multiple Signal Types (7 Types)**
**Signal 1:** Market Structure is Bullish (Bullish Structure) AND Reverse RSI shifts to Bullish
**Signal 2:** (Market Structure is Bullish OR Reverse RSI is Bullish) AND VWC UP signal detected
**Signal 3:** Reverse RSI is Bullish AND Market Structure changes from Bearish to Bullish (Structure Switch)
**Signal 4:** Market Structure is Bullish AND VWC Signal is in UP state (first time only)
**Signal 5:** Reverse RSI Bullish signal detected AFTER breaking above 15min Lower Bollinger Band
**Signal 6:** First Reverse RSI Bullish signal AFTER breaking above 15min Lower BB OR EMA50 (Bypasses Filter 1,2,3, Filter 4 still applies)
**Signal 7:** Market Structure is Bullish AND price bounces from EMA20 or EMA50, then first BUY detected (Bypasses Filter 1,2,3, Filter 4 still applies)
*(SELL signals follow inverse logic)*
---
### 2. **Advanced Filtering System**
**Filter 1: RSI Direction Filter (Default: ON) - Signals 1-5 Only**
- Only displays BUY when Reverse RSI is Bullish OR Market Structure is Bullish
- Only displays SELL when Reverse RSI is Bearish OR Market Structure is Bearish
- Prevents counter-trend signals in strong directional moves
**Filter 2: EMA Order Filter (Default: ON) - Signals 1-5 Only**
- SELL signals only appear when EMA alignment is confirmed:
- `ema20 > ema50 > ema100 > ema200` (Strong downtrend), OR
- `ema20 < ema50 < ema100 < ema200` (Strong uptrend)
- Reduces false signals during choppy/ranging markets
**Filter 3: Bollinger Band Direction Filter (Default: ON) - Signals 1-5 Only**
- After breaking below 15min Upper BB AND 60min Upper BB → Only SELL signals until touching 15min Lower BB
- After breaking above 15min Lower BB AND 60min Lower BB → Only BUY signals until touching 15min Upper BB
- Creates directional bias zones for high-probability entries
**⭐ Filter 4: EMA Fill Transition Period Filter (Default: ON) - ALL Signals 1-7**
- During ALL EMA fills transitioning blue→red → Show BUY only (block SELL)
- During ALL EMA fills transitioning red→blue → Show SELL only (block BUY)
- Period ends when transition completes OR reverts to original color
- Reduces false signals during trend changes and improves win rate
**Note:** Signals 6, 7 bypass Filters 1,2,3 but Filter 4 still applies.
---
### 3. **Multi-Timeframe Bollinger Bands**
- **15-Minute Bollinger Bands** (Black dotted lines): Short-term volatility zones
- **60-Minute Bollinger Bands** (Black/customizable): Longer-term support/resistance
These bands identify:
- **Overbought/Oversold Conditions**
- **Breakout Confirmations** (Signal 5 & 6)
- **Mean Reversion Opportunities**
---
### 4. **7 Exponential Moving Averages (EMA)**
- **EMA 7, 20, 50, 100, 200, 400, 800**
- Dynamic **EMA Fills** between EMA20-50 and EMA50-200 with color-coded trend bias:
- **Red Fill:** Bearish alignment (ema20 > ema50 > ema200)
- **Blue Fill:** Bullish alignment (ema20 < ema50 < ema200)
- EMAs act as dynamic support/resistance for Signal 7 bounce detection
- **Filter 4 monitors EMA fills** to create directional bias during transitions
---
### 5. **ICT Donchian Smart Money Structure**
- Colors candle borders to visualize market structure:
- **RED Border (Bullish Structure):** Bullish structure (buyers in control)
- **GREEN Border (Bearish Structure):** Bearish structure (sellers in control)
- Based on Donchian channels and pivot-based structure breaks
- Critical for Signal 1, 3, 4, and 7 detection
---
### 6. **Reverse RSI Signals**
- Inverts RSI calculations to derive price levels rather than oscillator values
- **Supertrend on RSI Midline** determines trend shifts:
- **Bullish Shift:** Potential upward momentum
- **Bearish Shift:** Potential downward momentum
- Displayed as semi-transparent labels ("Bullish"/"Bearish") above/below price
---
### 7. **VWC (Volumetric Weighted Cloud) Trend Detector**
- Adaptive volatility-based bands that expand/contract with market conditions
- Provides **UP/DOWN signals** when price enters the bands
- VWC Status Table displays:
- Current trend direction (BULLISH/BEARISH)
- EMA alignment status
- Last displayed signal (BUY/SELL) and bars since signal
---
## 🎯 Trading Strategy
### Recommended Approach
**1. Trend Following (Signals 1, 2, 4)**
- Wait for clear market structure (Bullish or Bearish Structure)
- Enter on confluence of VWC trend + RSI direction + Structure alignment
- Use EMA fills as dynamic stop-loss zones
**2. Reversal Trading (Signals 5, 6, 7, 8)**
- **Signal 5 & 6**: Identify Bollinger Band breakouts and reversals
- **Signal 7**: Look for EMA bounces with structure confirmation
- **Signal 8**: **EARLY TREND REVERSAL** - Enter at the very beginning of trend changes
- These signals bypass certain filters for early entry opportunities
**3. Signal 8 - Early Trend Reversal Strategy (NEW in v2)**
**Best Use Cases:**
- **Higher Timeframes (15m-1H)**: Most reliable for catching major trend reversals
- **Swing Trading**: Perfect for multi-day position entries
- **Confirmation Trading**: Use with other signals for high-confidence entries
**How to Trade Signal 8:**
- **BUY (Blue→Red transition)**:
- Watch for all EMA fills turning from blue to red
- Entry: When Signal 8 BUY label appears
- Stop Loss: Below recent swing low or EMA200
- Take Profit: Target next resistance or use trailing stop with EMA50
- **SELL (Red→Blue transition)**:
- Watch for all EMA fills turning from red to blue
- Entry: When Signal 8 SELL label appears
- Stop Loss: Above recent swing high or EMA200
- Take Profit: Target next support or use trailing stop with EMA50
**Signal 8 Advantages:**
- Catches trend reversals 5-10 bars BEFORE other signals
- Lower risk entry at the start of new trends
- Higher reward potential (entering at trend inception)
**Signal 8 Risks:**
- May produce false signals in choppy/ranging markets
- Best combined with higher timeframe confirmation
- Consider using larger stop losses due to early entry
---
### Risk Management
- Use **EMA20/EMA50** as trailing stop-loss levels
- For Signal 8: Use **EMA200** as major trend stop-loss
- Exit on opposite signal or when price crosses major EMA
- Combine with higher timeframe trend confirmation (60min+ chart)
- Avoid trading when VWC Status Table shows conflicting signals
### Timeframe Recommendations
- **Signal 8 Best Timeframes:** 15min to 1H (for early trend reversal)
- **Other Signals:** 1-minute to 15-minute charts (scalping/day trading)
- **Higher timeframes:** Works on 1H+ but may produce fewer signals
- **Complementary:** Use 4H/Daily chart for overall trend direction
---
## 🔄 Integrated Trading Strategy with MTF OB & FVG Detector
Combining **Trend Gazer v2** with **MTF OB & FVG Detector** creates a powerful trading approach that leverages institutional order flow (OB) and market supply-demand imbalances (FVG) alongside trend momentum.
### Benefits of Integration
**1. Highest Probability Entry Points**
- Trend Gazer BUY/SELL signals + OB/FVG zones = **Highest probability entry points**
- Multi-timeframe OB confluence (5m, 15m, 60m) + Trend Gazer signals = **Institutional + trend alignment**
**2. Precise Entry Price Determination**
- Trend Gazer confirms trend direction and market bias
- OB/FVG zones pinpoint exact entry prices
- Reduces unnecessary risk and maximizes reward ratios
**3. Enhanced Stop Loss Management**
- Use EMA20/50 (Trend Gazer) as trailing stop loss levels
- Set OB zones (MTF OB & FVG) as additional defensive lines
- Multi-layer risk protection
---
### Recommended Integration Strategies
#### Strategy 1: High-Probability Confluence Entry 【MOST RECOMMENDED】
**Setup:**
1. Monitor Trend Gazer v2 for BUY/SELL signals
2. Identify combined OB/FVG zones (3+ timeframes) on MTF OB & FVG Detector
3. Wait for both to align at the same price zone
**Entry Conditions (BUY example):**
- ✅ Trend Gazer: BUY signal triggered (any Signal 1-7)
- ✅ MTF OB & FVG: Price touches Bullish OB zone (especially combined zones)
- ✅ Filter 4 (EMA Transition Period): Blue→Red transition active (BUY-only period)
- ✅ Market Structure: Bullish (red border)
- ✅ High Volume: OB zone volume percentage ≥75%
**Entry:**
- Enter at close of bar when Trend Gazer BUY signal appears within OB zone
- Or enter at open of next bar
**Stop Loss:**
1. **Initial SL**: OB zone lower edge - (5-10 pips/points)
2. **Alternative SL**: Below EMA50 (wider SL, for swing trades)
3. **Tight SL**: Below recent low - (3-5 pips/points) (for scalping)
**Take Profit Targets:**
1. **T1 (50%)**: Next higher timeframe Bearish OB/FVG zone
2. **T2 (30%)**: 60min Bollinger Band upper limit
3. **T3 (20%)**: Trail with EMA20/50, hold until opposite signal
**SELL example follows inverse logic**
---
#### Strategy 2: Precise Reversal Entry 【INTERMEDIATE】
**Best Use Cases:**
- End of strong trends
- Reversals at significant combined OB/FVG zones
- Higher timeframe support/resistance levels
**Entry Conditions (SELL example):**
1. **Higher Timeframe Confirmation:**
- Identify Bearish OB confluence zone on 60min chart
- Price reaches confluence zone
2. **Trend Gazer Signals:**
- **Signal 5**: Break below 15min upper BB + Reverse RSI bearish shift, OR
- **Signal 6**: First RSI bearish signal after breaking 15min upper BB/EMA50, OR
- **Signal 7**: Market Structure bearish + bounce down from EMA20/50
3. **OB/FVG Confirmation:**
- Confirm bounce at 15min or 60min Bearish OB zone
- FVG remains above (price magnet effect)
**Entry:**
- Enter after confirming both Trend Gazer signal + OB zone bounce
- Candlestick pattern confirmation recommended (pin bar, engulfing, etc.)
**Stop Loss:**
- Above OB zone upper edge + 10-15 pips/points
- Or above 60min upper BB
**Take Profit:**
- **T1**: Lower timeframe Bullish OB/FVG zone (unfilled FVG preferred)
- **T2**: 15min lower BB
- **T3**: Until opposite signal or EMA20/50 touch
**BUY example follows inverse logic**
---
#### Strategy 3: Trend Following with OB Support 【BEGINNER-FRIENDLY】
**Simple Approach:**
**BUY Strategy:**
1. **Trend Confirmation (Trend Gazer):**
- EMA fills are red (bullish alignment)
- VWC Status shows BULLISH
- Market Structure is Bullish (red border)
2. **Wait for Pullback:**
- Price retraces to lower timeframe (5m or 15m) Bullish OB zone
- Trend Gazer **Signal 1, 2, or 4** triggers
3. **Entry:**
- Enter when BUY signal appears within OB zone
- Enter at candle body close
4. **Stop Loss:**
- Below OB zone lower edge - 10 pips/points
5. **Take Profit:**
- **Simple**: 2x risk (1:2 R:R)
- **Dynamic**: Until next Bearish OB or opposite signal
**SELL Strategy follows inverse logic**
---
#### Strategy 4: FVG Filling with Trend Gazer Confirmation 【SCALPING】
**For Short-Term Traders:**
**Setup:**
- Identify unfilled FVG (Bullish or Bearish)
- FVG should be away from current price (minimum 20-30 pips/points)
**BUY Example (Bullish FVG below):**
1. **FVG Identification:**
- Unfilled Bullish FVG below current price (Orange box)
- Prefer high-volume FVG (75%+)
2. **Trend Gazer Confirmation:**
- Price approaches FVG
- Market Structure turns Bullish
- **Signal 3, 4, or 7** triggers near FVG zone
3. **Entry:**
- Price enters FVG and Trend Gazer signal confirms bounce from FVG
- Enter at candle body close
4. **Stop Loss:**
- Below FVG lower edge - 5-7 pips/points (tight)
5. **Take Profit:**
- **T1 (70%)**: FVG upper edge (gap fill)
- **T2 (30%)**: Next resistance or opposite signal
**SELL Example (Bearish FVG above) follows inverse logic**
---
### Best Practices for Integrated Usage
**1. Chart Setup:**
- **Main Chart Timeframe**: 5min or 15min
- **Trend Gazer v2**: All signals and filters enabled
- **MTF OB & FVG Detector**: Enable 5m, 15m, 60m; Combine Overlapping OBs = ON
**2. Alert Configuration:**
- Trend Gazer: BUY/SELL signal alerts enabled
- MTF OB & FVG: Bounce alerts + Combined Zone alerts enabled (Min 3 OBs)
- Both alerts firing simultaneously = Highest probability entry
**3. Pre-Entry Checklist:**
- Trend Gazer BUY/SELL signal confirmed
- OB/FVG zone overlaps with price
- Filter 4 supports direction (during transition period)
- Market Structure aligns
- OB/FVG high volume confirmed (70%+ recommended)
- Higher timeframe trend doesn't conflict
- Risk:Reward ratio minimum 1:1.5
**4. Risk Management Rules:**
- Risk per trade: 0.5-1% of account balance
- Concurrent positions: Maximum 2-3 (low-correlation pairs only)
- After consecutive losses: Pause after 3 losses, review strategy
- Daily loss limit: 2-3% of account balance
**5. Situations to Avoid:**
- ❌ Entering with OB/FVG alone, without Trend Gazer signal
- ❌ Immediately before/after major economic releases (volatility spikes)
- ❌ When multiple filters contradict each other
- ❌ OB/FVG zones tested multiple times (weakened)
- ❌ Low liquidity periods (Asian early morning, etc.)
---
### Performance Enhancement Tips
**1. Timeframe Selection:**
- **Scalping**: 1m/3m OB + 5m Trend Gazer signals
- **Day Trading**: 5m/15m OB + 15m Trend Gazer signals
- **Swing Trading**: 15m/60m OB + 60m Trend Gazer signals
**2. Confluence Zone Priority:**
- **Highest**: 60min OB confluence (3+) + Trend Gazer Signal 6 or 7
- **High**: 15min OB confluence + Filter 4 transition period + Signal 1-5
- **Medium**: 5min OB + Market Structure alignment + Signal 1-4
- **Low**: Single timeframe OB + basic signal (require more confirmation)
**3. Backtesting Recommended:**
- Test each strategy on 1-3 months of historical data
- Record win rate, average R:R, maximum drawdown
- Discover optimal combinations for your trading style
**4. Continuous Improvement:**
- Keep trade journal (with screenshots)
- Weekly performance review
- Document effective combination patterns
- Adjust to changing market conditions
---
### Real-World Examples
**Example 1: Perfect Confluence BUY**
```
Situation:
- 15min chart, EUR/USD
- Price touches 60min Bullish OB confluence zone (5m+15m+60m)
- Trend Gazer Signal 6: First RSI bullish signal after 15min lower BB breakout
- Filter 4: EMA fills transitioning blue→red (BUY-only period)
- Market Structure: Turns Bullish (red border)
- OB Volume: 82% (strong buying pressure)
Entry: 1.0850 (OB zone middle)
Stop Loss: 1.0835 (OB zone lower edge - 5 pips)
Take Profit T1: 1.0875 (Next 15min Bearish OB) - Hit
Take Profit T2: 1.0895 (60min upper BB) - Hit
Take Profit T3: 1.0920 (EMA20 trailing) - Closed before opposite signal
Result: +70 pips, Risk 15 pips = 4.67:1 R:R
```
**Example 2: FVG Filling with Reversal Confirmation SELL**
```
Situation:
- 5min chart, GBP/JPY
- Unfilled Bearish FVG above (Aqua box, 15min)
- Price surges to reach FVG
- Trend Gazer Signal 7: Market Structure bearish + downward bounce from EMA50
- Reverse RSI: Bearish shift
- FVG Volume: 78% (strong selling pressure)
Entry: 191.50 (bounce confirmed at FVG upper edge)
Stop Loss: 191.75 (FVG upper edge + 25 pips)
Take Profit T1: 191.00 (FVG lower edge, gap fill) - Hit
Take Profit T2: 190.70 (Next Bullish OB) - Partially hit
Result: +50 pips (weighted average), Risk 25 pips = 2:1 R:R
```
---
### Summary: Why This Integration is Powerful
**Trend Gazer v2's Role:**
- ✅ Trend direction confirmation (VWC, EMA, Structure)
- ✅ Timing signals (7 types of entry opportunities)
- ✅ Multiple filters reduce false signals
- ✅ Dynamic stop loss management (EMA, BB)
**MTF OB & FVG Detector's Role:**
- ✅ Institutional order flow visualization
- ✅ Precise price zone identification (exact entries)
- ✅ High-probability support/resistance levels
- ✅ Volume analysis for zone strength confirmation
**Synergy from Integration:**
- 🎯 **Probability Multiplication**: Each indicator is effective alone, but alignment dramatically increases probability
- 🎯 **Risk Reduction**: More precise stop loss placement minimizes losses
- 🎯 **Reward Maximization**: Optimal entry prices expand profit potential
- 🎯 **Strategy Diversity**: Applicable to trend-following, reversals, scalping, and swing trading
**Recommended Getting Started:**
1. Test Strategy 1 (Confluence Entry) on demo account for 2 weeks
2. Keep trade journal and learn patterns
3. Practice same strategy on small real account (minimum lot)
4. Expand to Strategies 2, 3 as confidence grows
5. Continuously backtest and improve
This integrated approach enables professional-level trading strategies that combine market **supply-demand zones (OB/FVG)** with **trend momentum (Trend Gazer)**.
---
## ⚙️ Input Parameters
### Signal 8 Settings (NEW in v2)
- **Enable Signal 8: EMA Fill Color Transition:** Toggle Signal 8 on/off (Default: OFF)
- **EMA Slope Lookback:** Period for EMA slope calculation (Default: 5, Range: 2-20)
- Lower values: More sensitive, earlier signals
- Higher values: More stable, fewer false signals
### Signal Display Settings
- **Show BUY/SELL Labels:** Toggle main entry signals
- **Show RSI Trend Shift Labels:** Display Bullish/Bearish RSI shifts
- **Label Size:** Small, Normal, Large, Huge
- **Label Position:** On bar or offset by ATR
### Filter Settings
- **Enable RSI Direction Filter:** Filter signals by RSI trend (Default: ON)
- **Enable EMA Order Filter:** Require EMA alignment for SELL signals (Default: ON)
- **Enable BB Direction Filter:** Create directional bias zones after BB breakouts (Default: ON)
### Visual Settings
- **Show Structure Candles:** Color candle borders by market structure
- **Show EMAs:** Display 7 exponential moving averages
- **Show EMA Fills:** Display colored fills between key EMAs (critical for Signal 8)
- **Show 15min Bollinger Bands:** Display short-term BB
- **Show 60min Bollinger Bands:** Display longer-term BB
- **VWC Status Table:** Toggle status table display
---
## 🆕 What's New in v2
1. **Signal 8 - EMA Fill Color Transition Detection**
- Early trend reversal identification
- EMA slope flattening analysis
- EMA convergence pattern recognition
- Normalized slope calculation using ATR
2. **Enhanced Tooltip Documentation**
- All signals now clearly documented in input tooltips
- Signal 8 explanation included
3. **Improved Alert System**
- New alerts for Signal 8 BUY/SELL
- Dedicated alert for EMA fill color transitions
4. **Better Visual Clarity**
- EMA fills now critical for Signal 8 visualization
- Easy to see when all fills are transitioning colors
---
## ⚠️ Disclaimer
This indicator is provided for **educational and informational purposes only**. It is **not financial advice**.
Trading involves substantial risk of loss and is not suitable for all investors. Past performance does not guarantee future results. Users should conduct their own research and consider consulting with a qualified financial advisor before making any trading decisions.
The author is not responsible for any losses incurred using this indicator.
---
## 📝 Credits
- **Reverse RSI Signals:** Based on concepts by AlgoAlpha
- **VWC Trend Detector:** Original implementation
- **ICT Donchian Structure:** Inspired by ICT concepts and Donchian channels
- **Bollinger Bands:** Developed by John Bollinger
- **EMA Analysis:** Standard technical analysis tool
- **Signal 8 EMA Transition:** Original implementation for Trend Gazer v2
---
## 📜 License
This Pine Script™ code is subject to the terms of the **Mozilla Public License 2.0** at mozilla.org
---
## 🔔 Alerts
The indicator includes built-in alert conditions for:
- BUY signals (all 8 types)
- SELL signals (all 8 types)
- **NEW: Signal 8 EMA Fill Color Transition alerts**
- Reverse RSI Bullish/Bearish shifts
- VWC UP/DOWN signals
Configure alerts via TradingView's alert creation menu.
---
**Version:** 2.0
**Platform:** TradingView Pine Script™
**Type:** Indicator (Overlay)
---
## 🚀 Tips for Best Results
1. **Combine Signals:** Use Signal 8 with other signals for confluence
2. **Signal 8 on Higher TF:** Most reliable on 15m-1H timeframes
3. **Use EMA Fills:** Keep EMA fills visible to see Signal 8 transitions
4. **Respect Market Structure:** Don't fight the trend on larger timeframes
5. **Backtest Signal 8:** Test on historical data to understand its behavior
6. **Adjust EMA Slope Lookback:** Fine-tune for your trading style and timeframe
7. **Watch the Table:** The VWC Status Table provides quick trend assessment
8. **Signal 8 + Structure:** Best results when Signal 8 aligns with Structure change
---
**Happy Trading! 📊💹**
**v2 Upgrade: Catch trend reversals EARLIER with Signal 8!**
FC Session & Levels: Killzone, FVG, BB, OB, MAs, VWAP, Zizag FibFC Session & Levels – Ultimate Multi-Tool Trading Indicator
All-in-one professional-grade indicator combining session analysis, key levels, institutional concepts, and trend tools for futures, forex, crypto, and stocks.
Core Features
Real-time Session High/Low tracking for Asia, London, NY AM/PM, MOC
Dynamic Daily Pivot Points with R1–R3 / S1–S3 levels
Configurable Opening Range Breakout (ORB) 15-min high/low from NY open
Smart VWAP, EMA/SMA crosses, Trend Cloud (EMA38/62)
CHoCH (Change of Character) detection with dotted breakout lines
Fair Value Gaps (FVG) with volume & ATR filtering
Advanced ZigZag + Fibonacci Retracement/Extension levels
Institutional Order Blocks & Breaker Blocks with mitigation tracking
How to Use – Step-by-Step Instructions
1. Add to Chart
Open TradingView → Indicators → Search " FC Session & Levels "
Add to any chart (works on all timeframes, best on 1m–1H)
2. Configure Time Zone
Set Time Zone to UTC-5 (Standard Time) or UTC-4 (Daylight Saving)
NYT sessions auto-adjust
3. Enable Sessions
Toggle: Asia, London, NY AM, NY PM, MOC
Each draws high/low lines + optional labels
Colors fully customizable
4. Pivot & Pre-Market Levels
Daily Pivot (PP) + R1–R3 / S1–S3 auto-calculated
Pre-Day High/Low (purple) & Pre-Week High/Low (blue)
Daily Open line (cyan)
Extend future lines with Extend Future
5. Opening Range Breakout (ORB)
Enable ORB 15min High/Low
Set start: 9:30 AM , end: 9:45 AM (NYT)
Lines extend ± N bars (default 5)
Great for breakout entries
6. VWAP & Moving Averages
Toggle VWAP , MA9/20 cross , MA50/100/200
Trend Cloud : EMA38 (fast) vs EMA62 (slow) → bullish/bearish fill
7. CHoCH – Change of Character
Detects swing breaks with 20-bar lookback
Draws dotted line from swing point to breakout
Labels: "CHoCH" in green (bull) or red (bear)
8. Fair Value Gaps (FVG)
Detects gaps > 0.5× ATR with volume > 1.2× avg
Draws semi-transparent boxes + midline
Max 10 FVGs , auto-expire after 50 bars
9. ZigZag + Fibonacci
ZigZag period: 15 (adjustable)
Auto-draws 0.236, 0.382, 0.5, 0.618, 0.786 levels
Labels show ratio + price
Extends to right on last leg
10. Order Blocks & Breaker Blocks
Detects institutional zones using swing + volume
Filters by size (0–30%) and volume multiplier
Shows last 5 Bull / 5 Bear OBs
Breaker Blocks : when OB is broken → becomes supply/demand
Mitigation tracking : 50%, Close, or Wick
Strength score (0–100) → stronger = bolder color
11. Statistics Dashboard
Toggle Show Statistics Table
Displays: Total OBs, Breakers, Bull/Bear counts
Position: Top/Bottom, Left/Right
12. Alerts
Bullish OB Formation
Bearish OB Formation
Breaker Block Formation
Polarity Change (▲/▼)
Best Practices & Tips
Use on 1m, 3m, 5m, 15m for intraday
Combine ORB + CHoCH for high-probability breakouts
Wait for FVG retest in direction of trend
Strong OBs (>70 strength) = high confluence zones
Use Pre-Week H/L for weekly bias
MOC session (15:50–16:00) = final 10min imbalance
Customization Options
Colors : All lines, boxes, labels
Opacity : Pivot (0–100%), FVG, OB
Line Width : OB/Breaker lines
Display Mode : Boxes, Lines, or Both
Labels : Session, FVG, CHoCH, Polarity
Author : futurescall @ fcalgobot.com . discord.gg
Credit: @LuxAlgo for BB, OB . Zigzag base on @LonesomeTheBlue
Commodity Channel Index Trend | DextraOverview
A smart, noise-filtered CCI that transforms chaotic oscillations into clear trend states. Instead of flipping constantly, CCI Trend locks into bullish or bearish mode only when momentum truly breaks out — using hysteresis to eliminate false signals.
Instant visual feedback via fully colored candles:
- Emerald Green = Bullish trend locked
- Hot Pink = Bearish trend locked
How It Works
1. Calculates standard CCI using EMA and price deviation
2. Triggers trend only when CCI exits the neutral zone
3. Locks the state until CCI breaks the opposite threshold
4. Updates CCI line color and candle appearance in real time
The Ultimate Price Action & SMC Toolkit: Delta Zones, MTF IndicaThis is an All-in-One Pine Script indicator that seamlessly combines three advanced trading concepts:
Delta Zones (Wick Pressure): Uses Standard Deviation to identify extreme buying/selling pressure within the candlestick wicks, signaling potential stop hunts or liquidity absorption. These are plotted as critical Buy/Sell Boxes.
Multi-Timeframe (MTF) Indicators: Confirms signals using popular indicators (RSI, CCI, Stochastic) calculated from a separate, user-selected Timeframe or the current chart timeframe. This adds a crucial layer of context and momentum confirmation.
Smart Money Concepts (SMC): Automatically detects and plots Orderblocks (OBs) and Breaker Blocks based on confirmed Market Structure Breaks (MSB). This helps locate high-probability Supply and Demand zones.
Key Features:
Integrated plotting for combined indicator signals.
Flexible MTF selection for all standard oscillators.
Automatic Swing High/Low detection for SMC analysis.
Comprehensive Alert system for Delta Pressure, Orderblocks, and Breaker Zones.
Option 2: Focusing on SMC and Flow (Concise)
Title: "SMC Delta Flow: Advanced Orderblock, Breaker, and Wick Reversal Zones with MTF Filter."
Description:
An essential tool for sophisticated SMC traders. This indicator provides high-precision zones:
Smart Money Blocks: Plots Orderblocks and Breaker Blocks following Market Structure Shifts (MSS). Includes a "Chop Control" feature to invalidate re-used or weak Breakers.
Delta Reversal Zones: Pinpoints candles showing extreme high-deviation wick pressure. Use these zones to confirm reversals and identify precise entry points where liquidity was captured.
MTF Confirmation: Incorporates configurable Multi-Timeframe (MTF) RSI, CCI, and Stochastic indicators to act as a momentum filter or confirmation tool.
Add this indicator to unify your analysis of Liquidity, Market Structure, and Momentum on a single chart!
SMC, SmartMoneyConcepts, Orderblock, BreakerBlock, MTF, MultiTimeframe, Delta, Wick, Liquidity, PriceAction, RSI, Stochastic, CCI
Tactical Holding [SwissAlgo]Tactical Holding
A visual framework for managing long-term positions across market cycles
--------------------------------------------------------------
Purpose
Instead of holding a fixed position through all market conditions , you can use this framework to adjust your exposure tactically . By reducing positions during distribution phases and accumulating during favorable accumulation zones, you may end up holding more units of the asset over complete market cycles - even if you temporarily exit or reduce exposure during unfavorable periods. This approach aims to help you compound your holdings by taking advantage of market volatility rather than simply enduring it.
--------------------------------------------------------------
Recommended Settings
Timeframe : Weekly (1W) chart
Chart Type : Standard candlesticks (select 'Bar' type Candles)
This indicator is designed for higher timeframe analysis. While it can be applied to other timeframes, the logic and signal generation are optimized for weekly charts to filter out short-term noise and focus on major market cycles.
--------------------------------------------------------------
Key Features
♦ Market State Classification
The indicator aims to categorize potential market conditions into five color-coded states based on technical confluences:
* Bull (bright green): Multiple bullish indicators align
* Bull Retrace (teal): Bullish structure with temporary weakness
* Bull ⇆ Bear Reversal (yellow): Transitional phase between trends
* Bear (bright red): Multiple bearish indicators align
* Bear Retrace (Pale Red/Maroon): Bearish structure with temporary strength
♦ Visual Elements
* Candles change color based on the current market state
* A 50-period EMA tracks with the same color coding, providing visual trend context
* Small arrow markers appear when specific pattern conditions are met (zones for potential distribution or accumulation)
* A legend table (toggle on/off) explains the color system
* A label shows the current state name on the chart
♦ Pattern Recognition
The system monitors for two types of potential entry/exit zones:
1. State transition patterns after periods of market regime consistency
2. RSI divergence patterns (when price and momentum move in opposite directions)
♦ Customization
* Toggle the legend table visibility through settings
* All calculations are transparent and use standard technical analysis methods
--------------------------------------------------------------
How It Works
Think of this indicator as a traffic light system for your portfolio:
♦ Green zones suggest the asset might be in an environment where long-term holders historically have remained invested
Bright green (Bull) : Multiple technical indicators align in a potentially strong bullish phase
Pale green (Bull Retrace) : Bullish structure remains intact, but momentum shows temporary weakness - often a pullback within an uptrend
♦ Red zones suggest conditions where long-term holders might consider reducing exposure or waiting for better entry points
Dark red (Bear) : Multiple technical indicators align in a potentially strong bearish phase
Pale red (Bear Retrace) : Bearish structure remains intact but shows temporary strength - often a bounce within a downtrend
♦ Yellow zones indicate the market is in transition between bull and bear regimes - a time for increased attention as the trend direction becomes uncertain
The system doesn't predict future prices. Instead, it helps you understand the current technical environment by doing the heavy lifting of analyzing multiple indicators at once and presenting them in a simple visual format.
Example: During the 2022 crypto bear market, the indicator would have displayed extended red periods, signaling defensive conditions for holders. When accumulation arrows appeared in late 2022-early 2023, it highlighted potential re-entry zones as the technical regime transitioned back toward green, before the 2024 recovery.
--------------------------------------------------------------
Who This Is For
♦ Long-term investors who want to hold assets through cycles but prefer a systematic approach to position sizing and timing rather than buying and never selling .
♦ Portfolio managers looking for a visual tool to help determine when to increase or decrease exposure to specific assets based on technical regime changes.
♦ Swing traders on higher timeframes who want to align their positions with the broader market structure rather than fighting the trend.
This is not designed for:
* Day traders or scalpers
* Those seeking exact entry/exit prices
* Automated trading systems (this is a visual decision-support tool)
--------------------------------------------------------------
Understanding the Visuals
When you apply Tactical Holding to a chart, you'll see:
1. Colored candles - Instantly see what market regime the asset is in
2. Colored EMA line (thick line) - Provides a dynamic support/resistance reference that changes color with market conditions
3. Small arrows (↑ ↓) - Mark bars where specific technical patterns complete
4. State label - Shows current market classification
5. Legend table (top right) - Quick reference guide for the color system
6. Warning banner (top center) - Reminds you to use weekly charts
The visual design prioritizes clarity over complexity. You should be able to glance at a chart and immediately understand the current technical environment.
--------------------------------------------------------------
Important Limitations
This indicator cannot:
* Predict future price movements
* Guarantee profitable trades
* Work equally well on all assets or timeframes
* Replace your own research and risk management
Technical considerations:
* Divergence detection has a 3-bar confirmation lag (by design, to avoid false signals)
* State transitions require multiple technical confirmations, which may cause delayed reactions to rapid market changes
* The system is reactive, not predictive - it responds to price action after it occurs
* Performance varies significantly between trending assets (like Solana) and stable assets (like Apple)
--------------------------------------------------------------
Practical Application
Consider using this indicator as one component of a broader investment framework:
♦ Understanding Position Context:
The color-coded states can help frame your thinking about current holdings:
Bull: Technical conditions that have historically been associated with sustained uptrends
Bull Retrace: Pullbacks within an overall bullish structure- these periods may offer opportunities to evaluate entry points or reassess existing positions
Reversal (Yellow): Transitional phases where the trend direction is unclear - periods that may warrant closer monitoring
Bear Retrace: Temporary strength within an overall bearish structure - rallies that historically have often faded
Bear: Technical conditions that have historically been associated with sustained downtrends
♦ Interpreting Signal Arrows:
Arrow markers indicate when specific technical pattern conditions have been met. These are observation points, not instructions:
A signal appearing doesn't mean immediate action is required
Treat arrows as prompts for further analysis rather than automatic triggers
Consider the broader context: fundamentals, your investment timeline, risk tolerance, and overall market conditions
Signals show when historical technical patterns have formed - not whether those patterns will lead to the same outcomes as in the past
The framework is designed to organize information visually, not to tell you what to do. Your investment decisions should incorporate this technical perspective alongside other factors relevant to your situation.
--------------------------------------------------------------
Technical Methodology
For transparency, the indicator uses:
* RSI (14) with a 14-period SMA to assess momentum direction
* MACD (12,26,9) to confirm trend strength and histogram momentum
* Stochastic RSI with K and D line crossovers for additional confirmation
* 50-period EMA as the primary trend filter
* Linear regression-based slope analysis to detect flat/transitional periods
* Pivot-based divergence detection following standard technical analysis principles
All calculations use publicly available technical analysis formulas. Nothing is hidden or proprietary beyond the specific combination and weighting of these standard tools.
--------------------------------------------------------------
Disclaimer
This indicator is an educational and analytical tool only. It is not financial advice.
* Trading and investing involve substantial risk of loss
* Past performance of any technical system does not indicate future results
* No indicator can predict market movements with certainty
* Always conduct your own research and consult with qualified financial professionals
* Never invest more than you can afford to lose
* The creators of this indicator are not responsible for any trading losses
* This tool is not affiliated with, endorsed by, or connected to TradingView, 3Commas, or any other trading platform
* Use of this indicator is at your own risk
Risk Management: Regardless of what any indicator shows, always use proper position sizing, stop losses, and risk management appropriate to your personal financial situation.
This indicator provides a framework for analysis. Your decisions, research, and risk management determine your results.
Mickey's Breaker Engine⚡ Breaker Engine | Auto Retest + Smart R:R Targets
A precision-grade breaker-block detection system built for traders who live and breathe clean structure.
This indicator automatically detects Breaker Candles, confirms them, marks their zones, and executes intelligent retest-based entry logic — complete with Stop-Loss and Risk-to-Reward (R:R) tracking up to 3R (or any custom ratio).
🧠 Core Concept
A Breaker Block is a structural shift where price violates liquidity from a failed order block and flips the zone’s polarity — turning a former supply into demand (or vice-versa).
This script identifies those setups automatically, confirms them only after a valid structure break, and waits for a clean retest to trigger a trade signal.
🚀 Key Features
⚙️ Smart Zone Detection
Detects both Bullish Breakers and Bearish Breakers.
Zones are drawn precisely using the breaker’s middle candle body (or full wick range if enabled).
Fully configurable transparency, width, and extension for better visual context.
🎯 Auto Retest Entry Logic
Entry triggers only on a clean retest, not on immediate breakout.
Includes logical filters to ensure retests are structurally valid and not overlapping candles.
Works in any timeframe or market — crypto, forex, indices, or commodities.
💡 Dynamic Risk–Reward Tracking
Automatically plots 1R, 2R, 3R, ...R targets based on your defined stop range.
Risk is calculated from entry to zone boundary or ATR offset.
Each target label appears precisely when hit.
Targets automatically stop updating once Stop-Loss is triggered.
🧱 Visual Clarity
BUY 🟢 / SELL 🔴 bubbles at entries.
SL ❌ marker when stop is hit.
🎯 1R / 2R / 3R labels dynamically plotted when each reward level is reached.
Non-overlapping placement using ATR-based spacing.
⚡ Real-Time Alerts - Instant alerts for:
✅ “Breaker BUY” – Clean retest confirmed (Long setup)
✅ “Breaker SELL” – Clean retest confirmed (Short setup)
❌ “Breaker BUY SL” – Stop hit for Long
❌ “Breaker SELL SL” – Stop hit for Short
🧩 Customization Panel
| Setting | Description |
| :-------------------------- | :------------------------------------------------------------------------------ |
| **ATR Length** | Controls volatility-based offset sizing. |
| **Entry / SL Offset × ATR** | Adjusts label spacing and dynamic positioning. |
| **Risk-Reward Ratio** | Define default R:R (e.g. 1:3). |
| **Multiple Retests** | Enable if you want the same breaker zone to allow multiple retests/entries. |
| **Banner Design** | Control opacity, extension, and wick usage for the breaker block visualization. |
| **Color Controls** | Choose your BUY/SELL/SL bubble colors to match your chart theme. |
⚙️ Underlying Logic (At a Glance)
Pattern Detection:
Identifies a 5-bar sequence that forms a valid Breaker Candle (the middle bar flips structure).
Confirmation:
Requires a follow-through candle to validate a real liquidity break.
Zone Registration:
Stores the breaker zone’s body range in arrays for tracking.
Clean Retest Entry:
Waits for price to retest the zone from the opposite side and close cleanly inside.
Stop Loss / Target Projection:
Defines stop loss just beyond the zone and plots up to 3 × reward targets dynamically.
Monitoring & Alerts:
Tracks each setup independently until either an R-target or SL is reached.
💬 Recommended Usage
Works best with market-structure traders, smart-money concepts, or liquidity-based systems.
Combine it with an external displacement confirmation or BOS/CHOCH tool for best precision.
Ideal for backtesting breaker-based R:R consistency or forward-testing retest entries.
Compatible with any asset / timeframe.
🧭 Disclaimer
This script is for educational and analytical purposes only.
It is not financial advice and should not be used to make trading decisions without independent confirmation or risk management.
Always test on demo data before deploying live.
VWAP + Volume Spikes See Where Smart Money ExhaustsVolume tells the truth. VWAP tells the bias. This script shows both — live.
If you trade intraday momentum, reversals, or liquidity sweeps, this indicator is built for you.
It shows where volume spikes hit extreme levels, anchored around VWAP and its dynamic bands, so you can instantly spot capitulation or hidden absorption.
🎯 What This Indicator Does
✅ Plots VWAP — session-anchored, updates automatically
✅ Adds dynamic VWAP bands — standard deviation envelopes showing volatility context
✅ Highlights volume spikes — colored candles + background for abnormal prints
✅ Includes alerts — “Volume Spike”, “VWAP Cross”, or a combined alert with direction
✅ Clean visual design — instantly readable in fast markets
It’s your visual orderflow radar — whether you’re trading gold, indices, or small caps.
🔍 Why It Works
Institutions build and unwind positions around VWAP.
Retail often chases volume… this script shows you when that volume becomes too extreme.
A spike above VWAP near resistance? → Likely distribution.
A spike below VWAP near support? → Likely capitulation.
Combine volume exhaustion + VWAP context, and you’ll see market turning points form before most indicators react.
⚙️ Inputs You Can Tune
Bands lookback: adjusts how reactive the VWAP bands are
Band width (σ): set how tight or wide your deviation envelope is
Volume baseline length: controls how “abnormal” a spike must be
Spike threshold: multiplier vs. average volume
Toggle color-coding, bands, and labels
Default settings work well across 1m–15m intraday charts and 1h–4h swing frames.
💡 How Traders Use It
1️⃣ Fade Parabolics:
When a green spike candle pierces upper VWAP band on high volume → smart money unloading.
Look for rejection and short into VWAP.
2️⃣ Catch Capitulations:
When a red spike candle dumps below lower VWAP band → panic selling.
Watch for stabilization and long back to VWAP.
3️⃣ VWAP Rotation Plays:
Alerts for price crossing VWAP help you spot shift in intraday control.
Above VWAP = buyers in charge.
Below VWAP = sellers in charge.
🧠 Best Practices
Pair it with Volume Profile or Delta/Flow tools to confirm exhaustion.
Don’t chase — wait for spike confirmation + reversal candle.
Use it on liquid tickers (NASDAQ, SPY, GOLD, BTC, etc.).
Great for Dux-style small-cap shorts or index pullbacks.
🔔 Alerts Ready
Choose from:
Volume Spike (single-bar explosion)
VWAP Cross Up/Down (trend shift confirmation)
One Combined Alert (any signal, includes ticker, price, and volume)
Set once — get real-time push notifications, Telegram, or webhook signals.
📊 My Favorite Setups
US100 / NASDAQ: fade rallies above VWAP + spike
Gold / Silver: trade reversals from VWAP bands
Small caps: short back-side after volume climax
ES, DAX, Oil: scalp VWAP rotation with confluence
❤️ Support This Work
I release free and premium scripts weekly — combining smart money concepts, VWAP tools, and volume analytics.
👉 Follow me on TradingView for more indicators and setups.
👉 Comment “🔥” if you want me to post the multi-timeframe VWAP + Volume Pressure version next.
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