Dual HTF EMAMulti-timeframe Exponential Moving Average (EMA) indicator plots two separate higher timeframe (HTF) EMAs of your choice. Displays four EMAs per HTF while providing optional background coloring (bullish/bearish). The background coloring occurs when two EMA's cross per HTF. User can select two of the four EMAs to determine the trend direction as they cross creating the background color.
User can configure timeframe, EMA lengths, EMA cross and background, source, and visibility; separately for each timeframe.
Default lengths are 9, 21, 50, 200 with source as closed and EMA cross background from EMA 1 and EMA 3. Also clear visual distinction using thick solid lines for HTF 1 and thin dashed lines for HTF 2.
Uses request.security() with gaps=barmerge.gaps_on to avoid staircase effects on lower timeframes.
This script is ideal for multi-timeframe analysis, helping traders align shorter-term price movements with broader trends from higher timeframes without cluttering the chart.
Analisis Trend
Market State Tracker🙏🏻 This is MST (Market State Tracker) , it’s main purpose is to tell whether it's better to take a predefined take-profit, or to expect a runner.
Unlike widely-known alternatives, this model is made with top state-space and innovation modelling tech, and it takes the necessary info ‘itself’ (not the derivatives) from the right places. In fancy terms it’s not even a model, it’s an ensemble of several models. If you want to get familiar with other work of mine like this, check UAT .
^^ compared with reverse-engineered Jurik Moving Average in moving window mode
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Main use case : take-profit engine. It tells whether to hold a position past its primary 1:1 Risk:Reward take-profit up to the opposite entry), or to close it right away at 1:1.
Alternative use case : market state operator. Alternatively the study can be used as a primary market-state operator that would actually define further strategies and actions. It’s very useful if your strategies are not market regime agnostic. Otherwise, use it only as the main use case tells.
Other use cases : anything that other mainstream studies are doing, but better* (proceed to the Tech Note in the end of the post): trend detection, price smoothing, crossovers, dynamic S&R etc.
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How to use:
The script has 2 studies, lower study (blue and red lines) and upper study (purple and gray lines).
...
Lower study is less variance & more bias option , in general it’s less preferred than upper study, but if none of your other system layers do not gauge directional info directly and you wanna keep it simply this way, this lower study is what you need.
Lower study states -> advised take-profit strategy:
When: negative gamma (red line) is above positive gamma (blue line), market is biased towards sell side, so shorts should be held up to the opposite entry, while longs should be closed asap after 1:1 Risk:Reward
When: positive gamma (blue line) is above negative gamma (red line), market is biased towards buy side, so longs should be held up to the opposite entry, while shorts should be closed asap after 1:1 Risk:Reward
...
Upper study is the preferred one in general because of its higher informational content. Most probably, if you’re already gaining directional info on your other system layers, this one will likely provide you information you don’t gain there. Here the purple line is the lead state estimate, and the gray line is the lagged state estimate, and current price = current bar POC or HLC3 (inferred POC).
Upper study states -> advised take-profit strategy:
When: current price > purple line > gray line, market is heavily biased towards buy side, so longs should be held up to the opposite entry, while shorts should be closed asap after 1:1 Risk:Reward
When: current price < purple line < gray line, market is heavily biased towards sell side, so shorts should be held up to the opposite entry, while longs should be closed asap after 1:1 Risk:Reward
When: purple line > gray line > current price, market is biased towards another buy wave, so longs should be held up to the opposite entry, while shorts should be closed asap after 1:1 Risk:Reward
When: purple line < gray line < current price, market is biased towards another sell wave, so shorts should be held up to the opposite entry, while longs should be closed asap after 1:1 Risk:Reward
All other price x purple line x gray line patterns are considered neutral, and both longs and shorts are done with minimal 1:1 Risk:Reward.
Important: if you trade based on current session activity, you have to track current states. If you trade based on previous session levels, you only need the last state of that session that originated the level.
Important 2: The script has a setting called “blend”. The differences between all 3 options provided there are extremely low, and moreover it doesn’t change the main part: location of crossovers. So I left it here because I genuinely don’t know yet which of these is the most primordial math option for the current context xd.
...
* now about this:
Tech note
In short: it gains all the information without touching artifacts with the best possible math that runs on O(1) time complexity.
The ‘final’ time complexity of the whole method is O(1), both in moving and expanding window modes.
The main short-term forecasting & innovations engine, I called it VAPM (Volume Acceleration Price Model) , is inspired by how prediction and NaN fills works on the lowest hardware level, processor cache etc. It’s based on splines , the most fundamental geometrical principles. This is the stuff you can run on FPGAs doing UHFT, not even HFT.
Based on lead/lag and negative/positive relationships with the VAPM forecasts, innovations are separated into 4 different streams.
Each stream of these 4 then discovers its own adaptive gain (limited by theoretical constraints of the exponential distribution each stream follows).
Then, 4 separate PVA (Position Velocity Acceleration) state-space models are run on POC estimate of each bar, using previously computed 4 different adaptive gains. Initial impulse response of the models was almost exactly matched with the Extended Beta(2, 2) Window, provided in UAT open access script (heck the code & description, it would worth it).
Then these 4 separate trackers are grouped pairwise and blended into 2, resulting in the lead/lag model.
Additionally, 4 adaptive gains are blended into 2 separate pos/neg models. I offer 3 blending options: max(), contraharmonic mean, and Log-Sum-Exp. The differences of outputs based on these 3 options are almost negligible.
All possible hidden issues like info leakage from previous finished expanding windows, or special cases of forecasts at the very few first datapoints, are taken into account and solved. The whole method has zero constants and zero pre-optimized or arbitrary values, everything based on fundamental math entities / objects.
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∞
BTC - Power Law 1.5: Dynamic 50/50 Decay OVERVIEW
Most Bitcoin models treat the asset as if it exists in a vacuum of infinite exponential growth. The classical Power Law (v1.0) was a groundbreaking start, but as Bitcoin matures into a multi-trillion dollar institutional asset, our models must account for the laws of physics and liquidity. The Power Law 1.5: Dynamic 50/50 Decay is a second-generation structural engine. It doesn't just draw a line; it calculates the structural "Center of Gravity" of Bitcoin’s adoption curve while accounting for the natural maturation (decay) of the network’s growth speed.
THE MATHEMATICAL BACKBONE: QUANTILE MEDIAN CALCULATION
The "Fair Value" line (blue) is derived using a Log-Log Linear Regression focused on the 50th percentile (Median). The script first transforms the price and the time (days since the Genesis Block) into a logarithmic scale. It then calculates a power-law constant by finding the Absolute Least Deviation across the entire historical dataset since 2011. Specifically, it uses the formula: Price = 10^(Intercept + Slope * log10(Days)) . To ensure the line is a true median, the script calculates the Median Offset of every historical price point from the raw regression line. By shifting the intercept by this median value, we guarantee that exactly 50% of all weekly bars fall above the curve and 50% fall below it, creating a robust, non-biased structural center.
THE ALPHA SHADOW: DYNAMIC EXPONENT PROJECTION
Unlike standard power-law projections that rely on a static slope, the "Alpha Shadow" (the projection extending from the blue backbone) utilizes a Time-Varying Exponent Model . The model acknowledges that Bitcoin's growth speed—the exponent 'b'—is a decaying function of time, reflecting the diminishing returns of a maturing asset. The script recalculated the Instantaneous Slope on every single bar using the formula: Future_Slope = Initial_Slope - (Decay_Rate * log10(Total_Days_from_Genesis)) . While the Decay Rate (default 0.045) serves as a structural sensitivity constant, its application ensures the growth speed is a dynamic variable rather than a fixed number. Each segment of the dashed green "Shadow" is a unique power-law arc calculated for its specific future time window. This ensures the projection isn't just a straight line drawn on a log chart, but a mathematically tethered curve that "feels" the weight of increasing market capitalization and respects the reality of global liquidity constraints as we approach 2029.
HOW TO READ THE CHART
• The Backbone (Solid Blue): This is the 50/50 Fair Value. When price is below this line, Bitcoin is structurally "cheap." When price is far above it, the asset is in a state of cyclical expansion.
• The Alpha Shadow (Green): This is the mathematical projection of the current curve into 2029. It shows the path of "Fair Value" as the network continues to mature.
• The Regime Audit (Dashboard): A real-time table in the middle-right of your chart provides an audit of the model's integrity, including the current slope (b) and the projected Fair Price for Jan 1, 2029.
WHY THIS IS "FRESH"
Most open-source Power Law scripts on TradingView utilize a Static Linear Regression —calculating a single constant slope that is applied equally to 2011 and 2029. Furthermore, common community models often rely on "Outer Band" fitting (connecting historical cycle peaks to cycle lows). While visually appealing, these methods can be highly sensitive to "Black Swan" outliers and often assume Bitcoin’s growth velocity is a permanent constant.
This script stands out by introducing a Maturation Framework . Instead of fitting to volatile extremes, we anchor the logic to a 50/50 Quantile Median , creating a backbone that is mathematically centered regardless of cyclical noise. By then applying a Dynamic Decay Factor to the growth exponent, we move away from the "static bands" approach and toward a model that respects the physical reality of a maturing, multi-trillion-dollar asset class. This provides a structurally grounded, institutional-grade view of Bitcoin’s trajectory that accounts for the diminishing returns inherent in global adoption.
DISCLAIMER
This script is for educational and macro-analytical purposes only. It does not constitute financial advice. The 2029 projection is a mathematical extrapolation based on historical data and decay constants; it is not a guarantee of future price action.
TAGS
bitcoin, powerlaw, macro, regression, fairvalue, btc, projection, quantitative, math, structural, Rob Maths, robmaths, Rob_Maths
Sector Rotation Dashboard (Beta)🎯 OVERVIEW
The Sector Rotation Indicator is a comprehensive real-time dashboard that tracks money flow across all 11 S&P 500 sector ETFs and 6 major macro assets. It automatically detects market regimes (Risk-On, Risk-Off, Tech-Led), flags anomalies, and shows you where institutional money is flowing.
Whether you're trading individual stocks, sector ETFs, or managing a portfolio, this indicator tells you:
• Which sectors are leading/lagging (ranked by relative strength)
• What market regime we're in (Risk-On, Risk-Off, Tech-Led, Mixed)
• Where the anomalies are (sectors behaving unexpectedly)
• How confident the signals are (based on cross-sector confirmation)
• What sector ETF the current chart ticker belongs to, if any (with rank and RS%)
🚧 BETA NOTICE
⚠️ This indicator is currently in BETA.
IMPORTANT - ETF Holdings Database:
• The 500+ stock-to-sector mappings are based on actual ETF holdings
• SPDR sector ETFs rebalance quarterly (3rd Friday of Mar/Jun/Sep/Dec)
• Holdings data requires MANUAL updating by the creator after each rebalance
• Users may experience DELAYS in data updates following rebalance dates
• Some newly added or removed stocks may be temporarily misclassified
📊 WHAT IT TRACKS
11 SPDR Sector ETFs:
• XLE (Energy) - Cyclical
• XLF (Financials) - Cyclical
• XLI (Industrials) - Cyclical
• XLY (Consumer Discretionary) - Cyclical
• XLB (Materials) - Cyclical
• XLK (Technology) - Growth
• XLC (Communication Services) - Growth
• XLV (Healthcare) - Defensive
• XLP (Consumer Staples) - Defensive
• XLU (Utilities) - Defensive
• XLRE (Real Estate) - Defensive
6 Macro Assets:
• GLD (Gold) - Safe Haven
• TLT (20+ Year Treasuries) - Safe Haven
• UUP (US Dollar Index) - Currency
• DBC (Commodities) - Risk/Inflation
• EEM (Emerging Markets) - Risk Appetite
• IBIT (Bitcoin) - Speculative
🔥 KEY FEATURES
1️⃣ Real-Time Sector Rankings
• All 11 sectors ranked by Relative Strength (RS) vs SPX
• Dual color coding: Background = RS, Text = Absolute performance
• Trend arrows showing momentum (↑↑, ↑, →, ↓, ↓↓)
• Rank change tracking with configurable alert threshold
2️⃣ Intelligent Regime Detection
• Risk-On: Cyclicals leading (XLE, XLF, XLI, XLY, XLB)
• Risk-Off: Defensives leading (XLV, XLP, XLU, XLRE)
• Tech-Led: Growth dominating (XLK, XLC)
• Mixed: No clear leadership
• High Volatility: Signals unreliable
3️⃣ Anomaly Detection System
• Flags sectors that jump/drop 3+ ranks
• Detects behavioral anomalies (e.g., Energy #1 in Risk-Off)
• High volatility warnings when multiple sectors show extreme moves
• Dynamic tooltips explain WHY each anomaly is flagged
4️⃣ Confidence Scoring
• Counts how many sectors confirm the current regime
• High (7+), Medium (5-6), Low (<5) confidence levels
• Shows exactly which sectors are confirming vs diverging
5️⃣ Current Ticker Classification
• Built-in database of 500+ stock tickers mapped to sector ETFs
• Shows your current chart's sector, rank, and RS
• Dual classification: ETF Holdings + TradingView (mismatch detection)
6️⃣ Macro Cross-Asset Flow
• Tracks 6 macro assets for broader market context
• Interprets flows: Risk-Off Flow, Risk-On Flow, Flight to Safety
• Equity outflow warnings when safe havens beat SPX significantly
7️⃣ Educational Tooltips
• Hover over ANY cell for detailed explanations
• Dynamic tooltips show live data + educational context
• Learn what drives each signal while you trade
📖 HOW TO READ THE DASHBOARD
Sector Panel:
• Green background = Outperforming SPX (positive RS)
• Red background = Underperforming SPX (negative RS)
• Green text = Positive absolute return
• Red text = Negative absolute return
• Δ column shows rank changes (⚠️ = significant move)
Interpretation Panel:
• ROTATION → Describes current sector movement pattern
• REGIME → Current market environment classification
• ALERT → Anomalies detected or "All Clear" status
• CONFIDENCE → Signal reliability score with breakdown
Macro Panel:
• Signal column: Strong > Bid > Neutral > Offered > Weak
• FLOW row: Summary of cross-asset money movement
⚙️ SETTINGS & RECOMMENDATIONS
PRIMARY TIMEFRAME (days) - Default: 20
Lookback period for RS calculation.
• 5-10 days: Day/swing traders - responsive but noisier
• 20 days: Most traders - good balance of signal vs noise ⭐
• 50 days: Position traders - smooth, confirms established trends
• 100+ days: Investors - major regime shifts only
Tip: Match to your typical holding period.
TREND TIMEFRAME (days) - Default: 5
Shorter lookback for momentum arrows (↑↑ ↑ → ↓ ↓↓).
• 3 days: Aggressive - more sensitive, more arrow changes
• 5 days: Most traders - catches momentum shifts without whipsaws ⭐
• 10 days: Conservative - smoother, fewer false reversals
Tip: Keep at 1/4 to 1/5 of Primary Timeframe.
ALERT THRESHOLD (ranks) - Default: 3
Minimum rank change to trigger ⚠️ anomaly alert.
• 2 ranks: Active traders - more alerts, catches smaller rotations
• 3 ranks: Most traders - significant moves only (e.g., #8→#5) ⭐
• 4-5 ranks: Swing/position - major disruptions only, high conviction
Tip: Lower = more alerts, Higher = fewer but stronger signals.
RECOMMENDED COMBINATIONS BY TRADING STYLE:
• Day Trading: Primary 10, Trend 3, Alert 2
• Swing Trading: Primary 20, Trend 5, Alert 3
• Position Trading: Primary 50, Trend 10, Alert 4
• Long-term Investing: Primary 100, Trend 20, Alert 5
OTHER SETTINGS:
• 44+ color and opacity controls for full customization
• Dark/Light theme support
• Compact view (Top 3 + Bottom 3) or Full view (all 11)
• Show/hide interpretation panel
🚨 BUILT-IN ALERTS
• Sector rotation changes (Cyclical ↔ Defensive)
• Regime changes (Risk-On ↔ Risk-Off ↔ Tech-Led)
• Large rank movements (configurable threshold)
• Equity outflow detection
• Safe haven bid alerts
• Global risk-on signals
💡 TRADING APPLICATIONS
For Stock Traders:
• See if your stock's sector is leading or lagging
• Avoid fighting the sector trend
• Find stocks in leading sectors for momentum plays
For Sector Rotators:
• Identify rotation early with rank change alerts
• Confirm regime with confidence scoring
• Spot anomalies that may signal turning points
For Portfolio Managers:
• Monitor risk-on/risk-off positioning
• Track cross-asset correlations
• Get early warning of defensive rotations
For Macro Traders:
• Cross-reference sector rotation with macro flows
• Identify flight-to-safety episodes
• Track inflation hedge positioning
📝 TECHNICAL NOTES
• Data Source: TradingView sector data + custom ETF holdings database
• ETF Holdings: 500+ tickers mapped to sector ETFs (manually maintained)
• Rebalancing: SPDR ETFs rebalance on 3rd Friday of Mar/Jun/Sep/Dec
• Best Timeframe: Daily recommended, works on all timeframes
• Performance: Optimized for minimal lag despite tracking 17 assets
• Pine Script: Version 6
⚠️ DATA UPDATE SCHEDULE:
The ETF holdings database is manually updated by the creator following each quarterly rebalance. Updates are typically completed within 1-2 weeks after the official rebalance date. During this period, some ticker classifications may be outdated. The indicator will fall back to TradingView's sector classification for any tickers not found in the database.
⚠️ DISCLAIMER
This indicator is currently in BETA. Features may change, and bugs may exist.
This indicator is for educational and informational purposes only. It does not constitute financial advice. Always do your own research and consider your risk tolerance before making trading decisions. Past performance does not guarantee future results.
True FVGsThis script highlights 3-candle Fair Value Gaps (FVGs) on your chart, showing areas where price moved quickly and left potential gaps in market structure. Bullish FVGs are shown with green boxes and suggest possible support, while bearish FVGs are shown with red boxes and suggest possible resistance. It also includes doji candles—very small-bodied candles that indicate indecision—so these patterns are not missed. The script displays the most recent 5 FVGs, making it easy to spot recent potential areas where price may react.
Ghost Protocol [Bit2Billions]📌 Ghost Protocol — RSI Percentile Momentum Engine
Ghost Protocol is a closed-source RSI momentum indicator built around a non-standard RSI calculation method designed to solve a core limitation of traditional RSI tools: fixed threshold bias.
Standard RSI uses static levels (30/70 or 20/80), which assume all markets, assets, and volatility regimes behave the same. In practice, this causes false signals, late divergences, and inconsistent momentum interpretation.
Ghost Protocol replaces fixed RSI thresholds with a percentile-ranked RSI distribution model, allowing momentum to be evaluated relative to its own historical behavior rather than absolute levels.
📌 Core Calculation Method (Non-Standard RSI Implementation)
Instead of interpreting RSI using fixed values, Ghost Protocol evaluates RSI using:
* A rolling RSI distribution
* Percentile ranking of RSI values within that distribution
* Volatility-aware normalization of momentum extremes
This means:
* “Overbought” and “oversold” conditions are defined by relative momentum rarity, not static numbers.
* RSI adapts automatically to different instruments and volatility regimes.
* Momentum signals remain consistent across markets without manual tuning.
This calculation method cannot be replicated using built-in RSI alone, as built-ins do not provide percentile-based RSI context or distribution awareness.
📌 How the Components Work Together
All modules in Ghost Protocol reference the same percentile-based RSI state:
1. Percentile RSI Core defines momentum pressure relative to historical distribution.
2. Divergence Detection compares price swings against percentile-ranked RSI swings, reducing false signals caused by static RSI levels.
3. Trend & Regime Filtering evaluates whether momentum is expanding, compressing, or exhausting based on percentile persistence rather than crossings.
4. Multi-Timeframe Alignment compares percentile RSI states across timeframes using normalized momentum, not raw RSI values.
Because every component references the same normalized RSI context, signals confirm or invalidate each other instead of conflicting.
📌 What Problem This Script Solves
Ghost Protocol is designed for traders who struggle with:
* RSI behaving differently across assets
* Fixed OB/OS levels failing in trending markets
* Divergences appearing too late or inconsistently
* Multiple RSI tools giving contradictory signals
* Manual RSI calibration per instrument
By using percentile-based RSI logic, Ghost Protocol provides:
* Consistent momentum interpretation
* Regime-aware RSI behavior
* Contextual divergence detection
* Cleaner, more reliable momentum structure
📌 How Traders Use Ghost Protocol
Ghost Protocol is not a signal generator.
Traders use it to:
* Identify momentum expansion vs exhaustion
* Evaluate divergence strength in context
* Confirm trend continuation or weakening pressure
* Align momentum across timeframes
All outputs are designed for decision context, not automated entries.
📌 Why This Script Is Original
Ghost Protocol does not modify RSI visually—it redefines how RSI is interpreted.
Originality comes from:
* Percentile-based RSI evaluation
* Distribution-aware momentum logic
* Contextual divergence validation
* Unified RSI state shared across all modules
This approach cannot be reproduced by stacking public RSI indicators or using built-in thresholds.
📌 Why This Script Is Invite-Only
Ghost Protocol is offered as a closed-source script because its value lies in the calculation model, not the visual elements.
The script replaces:
* Manual RSI tuning
* Multiple RSI variants
* Separate divergence tools
* Multi-timeframe RSI comparisons
This level of consistency and normalization requires proprietary logic and is therefore provided as an invite-only indicator.
📌 Key Components & Intent
#RSI Candles (Standard & Heikin-Ashi)
Purpose: clearer momentum transitions and divergence readability.
#Divergence Engine
Detects:
• Regular divergence
• Hidden divergence
• Ghost Candidate pre-divergence
Purpose: identify exhaustion before price confirmation.
#Adaptive RSI Zones
Zones adjust based on:
• Volatility
• Displacement
• Trend direction
Purpose: eliminate static OB/OS bias.
#RSI Ichimoku Cloud
Shows:
• Regime bias
• Momentum compression/expansion
• Equilibrium shifts
Purpose: identify internal RSI regime transitions.
#RSI Trendlines
Automatically maps momentum structure.
Purpose: remove manual RSI drawing.
#Relative Trend Index
Evaluates trend alignment across multiple timeframes.
📌 Dashboard Metrics (Contextual, Not Signal-Based)
Provides a consolidated view of:
• Volatility
• Volume
• VWAP vs price
• EMA sentiment and structure
• RSI and price OB/OS statistics
• Relative trend alignment
• ATR state and trailing stop context
Purpose: decision context, not trade automation.
📌 Visual Design & Usability
• Only real-time labels are displayed
• Historical clutter is hidden
• Consistent color and line hierarchy
• Clear distinction between divergence types and momentum states
This design supports institutional-style momentum reading, not signal spam.
📌 Summary
Ghost Protocol is a closed-source, invite-only RSI intelligence system built on original logic.
Its mashup structure is intentional, necessary, and justified, because it solves real RSI limitations that cannot be addressed by isolated tools.
This script delivers clear analytical value, coherent momentum interpretation, and a professional workflow worthy of a paid publication.
📌 Recommended Use
* Best on: 15m, 1H, 4H, Daily, Weekly
* Works across: crypto, forex, indices, liquid equities
* Pivot-style modules may show noise in illiquid markets
📌 Performance Notes
* Heavy modules may draw many objects → disable unused tools
* Refresh chart if buffer limits are approached
* Internal handling of TradingView object rules
📌 License
* Proprietary script © 2025
* Independently developed
* Redistribution, sharing, resale, or decompilation prohibited
* Similarities to public tools result only from shared market concepts
📌 Respect & Transparency
Built using widely-recognized RSI concepts, but extended with proprietary logic.
Developed with respect for the TradingView community.
Any overlaps can be addressed openly and constructively.
📌 Disclaimer
For educational and research use only.
Not financial advice.
Always test responsibly and manage risk.
📌 FAQs
* Source code is intentionally private
* Modules can be toggled
* Alerts can be configured manually
* Works on all major markets and timeframes
📌 About Ghost Trading Suite
Author: BIT2BILLIONS
Project: Ghost Trading Suite © 2025
Indicators: Ghost Matrix, Ghost Protocol, Ghost Cipher, Ghost Shadow
Strategies: Ghost Robo, Ghost Robo Plus
Pine Version: V6
The Ghost Trading Suite is designed to simplify and automate many aspects of chart analysis. It helps traders identify market structure, divergences, support and resistance levels, and momentum efficiently, reducing manual charting time.
The suite includes several integrated tools — such as Ghost Matrix, Ghost Protocol, Ghost Cipher, Ghost Shadow, Ghost Robo, and Ghost Robo Plus — each combining analytical modules for enhanced clarity in trend direction, volatility, pivot detection, and momentum tracking.
Together, these tools form a cohesive framework that assists in visualizing market behavior, measuring momentum, detecting pivots, and analyzing price structure effectively.
This project focuses on providing adaptable and professional-grade tools that turn complex market data into clear, actionable insights for technical analysis.
Crafted with 💖 by BIT2BILLIONS for Traders. That's All Folks!
📌 Changelog
v1.0 – Initial Release
* Added RSI Candles (Standard & Heiken-Ashi) for enhanced trend and divergence clarity.
* Implemented Divergence Engine to highlight both regular and hidden divergences automatically.
* Introduced Live Ghost Candidates to visualize forming divergence setups.
* Added Adaptive RSI Zones for dynamic overbought and oversold thresholds.
* Integrated Trend Index using percentile volatility sampling for directional bias.
* Added RSI Ichimoku Cloud for equilibrium and momentum zone visualization.
* Implemented RSI Trend Lines for auto support/resistance on RSI.
* Added Momentum Shift Visualization and real-time momentum tracking.
* Introduced Relative Trend Index for multi-timeframe trend strength analysis.
* Developed Dashboard Module displaying volatility, volume, EMA trends, RSI/price overbought-oversold percentages, relative trend, and ATR-based metrics.
V3 Multi-MA MTF Full (by RUG)This Multiple Moving Averages (MA) indicator lets you plot and compare several moving averages on the same chart to quickly read trend direction and momentum. You can configure up to 10 MAs, choosing each one’s type (for example, SMA or EMA), length (periods), and—most importantly—its own independent timeframe (for instance, a 9-period EMA on the daily timeframe while you’re viewing a 15-minute chart). This creates a clean “context layer” that blends short-, mid-, and long-term trends, helping you spot trend alignment, dynamic support/resistance zones, and key crossovers without constantly switching timeframes.
SilverHawk Flip Confirm (4-Step)This premium indicator identifies high-probability trend flips using a 4-step confirmation sequence (Sweep → Displacement → BOS → Retest/Hold) with zone-based filters.
Core logic & how it works:
- Step 1 (Sweep): price wicks through a recent Supply/Demand area or Order Block (ATR-buffered)
- Step 2 (Displacement): strong candle body (ATR size + min body %) after sweep
- Step 3 (BOS): price breaks previous swing high/low
- Step 4 (Retest + Hold): price retests the entry zone (OB or S&D area) without breaking opposite side
- Zone modes: Hybrid (S&D area + OB entry), Supply/Demand only, or Order Block only
- Non-repainting option (confirmed bars only)
- Timeout: max bars between steps to avoid stale setups
Features:
- Visual zones (boxes) for S&D areas & OBs (toggleable)
- Step labels (Sweep/Disp/BOS/Retest) on signal candles
- Small panel with current steps, confidence %, and perfect sequence reminder
- Alerts for full flip confirmation + individual steps
- Customizable zone padding, pivot lengths, ATR buffers
Settings:
- Zone Mode: Hybrid, Supply & Demand only, Order Block only
- Use Confirmed Bars Only: non-repainting toggle
- Max Bars Between Steps: timeout for sequence
- Pivot lengths for S&D and BOS
- ATR multipliers for sweep buffer, displacement, padding, retest tolerance
- Visuals: show zones/labels/panel
- Alerts: enable/disable full flip + step triggers
Best used on H1–D4 timeframes in Forex or indices for spotting trend reversals or continuations after liquidity sweeps. Combine with higher-timeframe structure and risk management.
Invite-only access. Educational tool only. Not financial advice. Trading involves risk.
SilverHawk HTF Alignment Panel ProThis premium dashboard displays multi-timeframe trend alignment, confidence score, regime, and risk assessment in a single, easy-to-read panel.
Core calculation & how it works:
- Trend direction: user-selectable engine (EMA cross, price vs EMA, Supertrend)
- Strength %: EMA spread relative to historical max
- Volume %: current RVOL vs average
- Volatility %: current ATR vs historical max
- Momentum %: RSI(14)
- Confidence %: weighted blend of strength, volume, volatility, momentum
- Regime: expansion (high vola + strength), compression (low vola + strength), normal
- Alignment %: agreement between chart TF trend + 2 higher TFs
- Gate: pass if at least 2 TFs align
- Risk Load: ATR relative to distance from slow EMA
- Quality (A/B/WAIT): final score based on confidence, alignment, risk, regime
Features:
- Color-coded table (bullish green, bearish red, neutral gray)
- Customizable location (top/bottom left/right)
- Optional info column explaining each metric
- Optional manual reference panel
- High-performance rendering (fixed rows/columns)
Settings:
- Dashboard Location: top-left/right, bottom-left/right
- Trend Engine: EMA Cross, Price vs EMA, Supertrend
- EMA lengths, Supertrend period/factor
- Lookbacks for strength, volume, volatility
- Weights for confidence calculation
- Style: header/row colors, text color, border
- Extras: show manual panel, show info column
Best used on H1–D1 timeframes in Forex or indices for quick multi-timeframe assessment and decision support. Combine with structure, volume confirmation and risk management.
Invite-only access. Educational tool only. Not financial advice. Trading involves risk.
PSAR Laboratory [DAFE]PSAR Laboratory : The Ultimate Adaptive Trailing Stop & Reversal Engine
23 Advanced Algorithms. Adaptive Acceleration. Smart Flip Logic. Parabolic SAR Reimagined.
█ PHILOSOPHY: WELCOME TO THE LABORATORY
The standard Parabolic SAR, created by the legendary J. Welles Wilder Jr., is a tool of beautiful simplicity. But in today's complex, algorithm-driven markets, its simplicity is its fatal flaw. Its fixed acceleration and rigid flip logic cause it to fail precisely when you need it most: it whipsaws in choppy conditions and gives back too much profit in strong trends.
The PSAR Laboratory was not created to be just another PSAR. It was engineered to be the definitive evolution of Wilder's original concept. This is not an indicator; it is a powerful, interactive research environment. It is a sandbox where you, the trader, can move beyond the static "one-size-fits-all" approach and forge a PSAR that is perfectly adapted to your specific market, timeframe, and trading style.
We have deconstructed the very DNA of the Parabolic SAR and rebuilt it from the ground up, infusing it with modern quantitative techniques. The result is an institutional-grade suite of 23 distinct, mathematically diverse algorithms that dynamically control every aspect of the PSAR's behavior.
█ WHAT MAKES THIS A "LABORATORY"? THE CORE INNOVATIONS
This tool stands in a class of its own. It is a collection of what could be 23 separate indicators, all seamlessly integrated into one powerful engine.
The 23 Algorithm Engine: This is the heart of the Laboratory. Instead of one rigid formula, you have a library of 23 unique mathematical engines at your command. These algorithms are not simple tweaks; they are complete re-imaginings of how the PSAR should behave, based on concepts from information theory, digital signal processing, fractal geometry, and institutional analysis.
Truly Adaptive Acceleration (AF): The standard PSAR's "gas pedal" (the AF) is dumb; it accelerates at a fixed rate. Our algorithms make it intelligent. The AF can now speed up in clean, trending environments to lock in profits, and automatically slow down in choppy, chaotic conditions to avoid whipsaws.
Advanced Flip Confirmation Logic: Say goodbye to noise-driven flips. You are no longer at the mercy of a single wick touching the SAR. The Laboratory provides multiple layers of flip confirmation, including requiring a bar close beyond the SAR, a volume spike to validate the reversal, or even a multi-bar confirmation .
Comprehensive Noise Filtering Core: In a revolutionary step, you can apply one of over 30 advanced signal processing filters directly to the SAR output itself. From ultra-low-lag filters like the Hull MA and DAFE Spectral Laguerre to adaptive filters like KAMA and FRAMA , you can surgically remove noise while preserving the responsiveness of the core signal.
Integrated Performance Engine: How do you know which of the 23 algorithms is best for your market? You test it. The built-in Performance Dashboard is a comprehensive backtesting and analytics engine that tracks every trade, providing real-time data on Win Rate, Profit Factor, Max Drawdown, and more. It allows you to scientifically validate your chosen configuration.
█ A GUIDED TOUR OF THE ALGORITHMS: 23 PATHS TO AN EDGE
b]These 23 algorithms are not simple settings; they are distinct mathematical philosophies for how a Parabolic SAR should adapt to the market. They are grouped into three primary categories: those that adapt the Acceleration Factor (AF) , those that enhance the Extreme Point (EP) detection, and those that redefine the Flip Logic .
CATEGORY A: ACCELERATION FACTOR (AF) ADAPTATION
These algorithms dynamically change the "gas pedal" of the PSAR.
1. Volatility-Scaled AF
Core Concept: Treats volatility as market friction. The PSAR should be more forgiving in high-volatility environments.
How It Works: It calculates a Volatility Ratio by comparing the short-term ATR to the long-term ATR. If current volatility is high (ratio > 1), it reduces the AF Step. If volatility is low (ratio < 1), it increases the AF Step to trail tighter.
Ideal Use Case: The best all-rounder. Excellent for any market, especially those with clear shifts between high and low volatility regimes (like indices and crypto).
2. Efficiency Ratio (ER) AF
Core Concept: The PSAR should accelerate aggressively in clean, efficient trends and slow down dramatically in choppy, inefficient markets.
How It Works: It uses Kaufman's Efficiency Ratio (ER), which measures the net directional movement versus the total price movement. A high ER (near 1.0) signifies a pure trend, triggering a high AF multiplier. A low ER (near 0.0) signifies chop, triggering a low AF multiplier.
Ideal Use Case: Markets that alternate between strong trends and sideways chop. It is exceptionally good at surviving ranging periods.
3. Shannon Entropy AF
Core Concept: Uses Information Theory to measure market disorder. The PSAR should be conservative in chaos and aggressive in order.
How It Works: It calculates the Shannon Entropy of recent price changes. High entropy means the market is unpredictable ("chaotic"), causing the AF to slow down. Low entropy means the market is organized and trending, causing the AF to speed up.
Ideal Use Case: Advanced traders looking for a mathematically pure way to distinguish between a tradable trend and random noise.
4. Fractal Dimension (FD) AF
Core Concept: Measures the "jaggedness" or complexity of the price path. A smooth path is a trend; a jagged, space-filling path is chop.
How It Works: It calculates the Fractal Dimension of the price series. An FD near 1.0 is a smooth line (high AF). An FD near 1.5 is a random walk (low AF).
Ideal Use Case: Visually identifying the moment a smooth trend begins to break down into chaotic, unpredictable movement.
5. ADX-Gated AF
Core Concept: Uses the classic ADX indicator to confirm the presence of a trend before allowing the PSAR to accelerate.
How It Works: If the ADX value is above a "Strong" threshold (e.g., 25), the AF accelerates normally. If the ADX is below a "Weak" threshold (e.g., 15), the AF is "frozen" and will not increase, preventing the SAR from tightening up in a non-trending market.
Ideal Use Case: For classic trend-following purists who trust the ADX as their primary regime filter.
6. Kalman AF Estimator
Core Concept: A sophisticated signal processing algorithm that predicts the "true" optimal AF by filtering out price "noise."
How It Works: It treats the PSAR's AF as a state to be estimated. It makes a prediction, then corrects it based on how far the actual price deviates. It's like a GPS constantly refining its position. The "Process Noise" input controls how fast it thinks the AF can change, while "Measurement Noise" controls how much it trusts the price data.
Ideal Use Case: Smooth, high-inertia markets like commodities or major forex pairs. It creates an incredibly smooth and responsive AF.
7. Volume-Momentum AF
Core Concept: A trend's acceleration is only valid if confirmed by both volume and price momentum.
How It Works: The AF will only increase if a new Extreme Point is made on above-average volume AND the Rate of Change (ROC) of the price is aligned with the trend's direction.
Ideal Use Case: Any market with reliable volume data (stocks, futures, crypto). It's excellent for filtering out low-conviction moves.
8. Garman-Klass (GK) AF
Core Concept: Uses a more advanced, statistically efficient measure of volatility (Garman-Klass, which uses OHLC data) to adapt the AF.
How It Works: It modulates the AF based on whether the current GK volatility is higher or lower than its historical average. Unlike the standard Volatility-Scaled algo, it tends to slow down more in high volatility and speed up less in low volatility, making it more conservative.
Ideal Use Case: Traders who want a volatility-adaptive model that is more focused on risk reduction during volatile periods.
9. RSI-Modulated AF
Core Concept: The RSI can identify points of potential trend exhaustion or strong momentum.
How It Works: If a trend is bullish but the RSI enters the "Overbought" zone, the AF slows down, anticipating a pullback. Conversely, if the RSI is in the strong momentum mid-range (40-60), the AF is boosted to trail more aggressively.
Ideal Use Case: Mean-reversion traders or those who want to automatically loosen their trail stop near potential exhaustion points.
10. Bollinger Squeeze AF
Core Concept: A Bollinger Band Squeeze signals a period of volatility compression, often preceding an explosive breakout.
How It Works: When the algorithm detects that the Bollinger Band Width is in a "Squeeze" (below a certain historical percentile), it boosts the AF in anticipation of a fast move, allowing the PSAR to catch the breakout quickly.
Ideal Use Case: Breakout traders. This algorithm primes the PSAR to be maximally responsive right at the moment a breakout is most likely.
11. Keltner Adaptive AF
Core Concept: Keltner Channels provide a robust measure of a trend's "normal" volatility channel.
How It Works: When price is trading strongly outside the Keltner Channel, it's considered a powerful trend, and the AF is boosted. When price falls back inside the channel, it's considered a consolidation or pullback, and the AF is slowed down.
Ideal Use Case: Trend followers who use channel breakouts as their primary confirmation.
12. Choppiness-Gated AF
Core Concept: Uses the Choppiness Index to quantify whether the market is trending or consolidating.
How It Works: If the Choppiness Index is below the "Trend" threshold (e.g., 38.2), the AF is boosted. If it's above the "Range" threshold (e.g., 61.8), the AF is significantly reduced.
Ideal Use Case: A more responsive alternative to the ADX-Gated algorithm for distinguishing between trending and ranging markets.
13. VIDYA-Style AF
Core Concept: Uses a Chande Momentum Oscillator (CMO) to create a variable-speed acceleration factor.
How It Works: The absolute value of the CMO is used to create a dynamic smoothing constant. Strong momentum (high absolute CMO) results in a faster, more responsive AF. Weak momentum results in a slower, smoother AF.
Ideal Use Case: Momentum traders who want their trailing stop's speed directly tied to the momentum of the price itself.
14. Hilbert Cycle AF
Core Concept: Uses Ehlers' Hilbert Transform to extract the dominant cycle period of the market and synchronizes the PSAR with it.
How It Works: It dynamically adjusts the AF based on the detected cycle period (shorter cycles = faster AF) and can also modulate it based on the current phase within that cycle (e.g., accelerate faster near cycle tops/bottoms).
Ideal Use Case: Markets with clear cyclical behavior, like commodities and some forex pairs.
CATEGORY B: EXTREME POINT (EP) ENHANCEMENT
These algorithms make the detection of new highs/lows more intelligent.
15. Volume-Weighted EP
Core Concept: A new high or low is more significant if it occurs on high volume.
How It Works: It can be configured to only accept a new EP if the volume on that bar is above average. It can also "weight" the EP by volume, pushing it further out on high-volume bars.
Ideal Use Case: Filtering out weak, low-conviction price probes in markets with reliable volume.
16. Wavelet Filtered EP
Core Concept: Uses wavelet decomposition (a signal processing technique) to separate the underlying trend from high-frequency noise.
How It Works: It calculates a smoothed, wavelet-filtered version of the price. A new EP is only registered if the actual high/low significantly exceeds this smoothed baseline, effectively ignoring minor noise spikes.
Ideal Use Case: Noisy markets where small, insignificant wicks can cause the AF to accelerate prematurely.
17. ATR-Validated EP
Core Concept: A new EP should represent a meaningful move, not just a one-tick poke.
How It Works: It requires a new high/low to exceed the previous EP by a minimum amount, defined as a multiple of the current ATR. This ensures only volatility-significant advances are counted.
Ideal Use Case: A simple, robust way to filter out "noise" EPs and slow down the AF's acceleration in choppy conditions.
18. Statistical EP Filter
Core Concept: A new EP is only valid if the price change that created it is statistically significant.
How It Works: It calculates the Z-Score of the bar's price change relative to recent history. A new EP is only accepted if its Z-Score exceeds a certain threshold (e.g., 1.5 sigma), meaning it was an unusually strong move.
Ideal Use Case: For quantitative traders who want to ensure their trailing stop only tightens in response to statistically meaningful price action.
CATEGORY C: FLIP LOGIC & CONFIRMATION
These algorithms change the very rules of when and why the PSAR reverses.
19. Dual-PSAR Gate
Core Concept: Uses two PSARs—one fast and one slow—to confirm a reversal.
How It Works: A flip signal for the main PSAR is only considered valid if both the fast (sensitive) PSAR and the slow (structural) PSAR have flipped. This acts as a powerful trend filter.
Ideal Use Case: An excellent method for reducing whipsaws. It forces the PSAR to wait for both short-term and longer-term momentum to align before signaling a reversal.
20. MTF Coherence PSAR
Core Concept: Do not flip against the higher timeframe macro trend.
How It Works: It pulls PSAR data from two higher timeframes. A flip is only allowed if the new direction does not contradict the trend on at least one (or both) of those higher timeframes. It also boosts the AF when all timeframes are aligned.
Ideal Use Case: The ultimate tool for multi-timeframe traders who want to ensure their entries and exits are in sync with the bigger picture.
21. Momentum-Gated Flip
Core Concept: A reversal is only valid if it is supported by a significant surge of momentum.
How It Works: A price cross of the SAR is not enough. The script also requires the Rate of Change (ROC) to exceed a certain threshold for a set number of bars, confirming that there is real force behind the reversal.
Ideal Use Case: Filtering out weak, drifting reversals and only taking signals that are initiated with explosive power.
22. Close-Only PSAR
Core Concept: Wicks are noise; the bar's close is the final decision.
How It Works: This algorithm modifies the flip logic to ignore wicks. A flip only occurs if one or more bars close beyond the SAR line.
Ideal Use Case: One of the most effective and simple ways to reduce false signals from volatile wicks. A fantastic default choice for any trader.
23. Ultimate PSAR Consensus
Core Concept: The highest conviction signal comes from the agreement of multiple, diverse mathematical models.
How It Works: This is the capstone algorithm. It runs a "vote" between a selection of the top-performing algorithms (e.g., Volatility-Scaled, Efficiency Ratio, Dual-PSAR). A flip is only signaled if a majority consensus is reached. It can even weight the votes based on each algorithm's recent performance.
Ideal Use Case: For traders who want the absolute highest level of confirmation and are willing to accept fewer, but more robust, signals.
█ PART II: THE NOISE FILTERING CORE - The Shield
This is a revolutionary feature that allows you to apply a second layer of signal processing directly to the SAR line itself, surgically removing noise before the flip logic is even considered.
FILTER CATEGORIES
Basic Filters (SMA, EMA, WMA, RMA): The classic moving averages. They provide basic smoothing but introduce significant lag. Best used for educational purposes.
Low-Lag Filters (DEMA, TEMA, Hull MA, ZLEMA): A family of filters designed to reduce the lag inherent in basic moving averages. The Hull MA is a standout, offering a superb balance of smoothness and responsiveness.
Adaptive Filters (KAMA, VIDYA, FRAMA): These are "smart" filters. They automatically adjust their smoothing level based on market conditions. They will be very smooth in choppy markets and become highly responsive in trending markets.
Advanced DSP & DAFE Filters: This is the pinnacle of signal processing.
Ehlers Filters (SuperSmoother, 2-Pole, 3-Pole): Based on the work of John Ehlers, these use digital signal processing techniques to remove high-frequency noise with minimal lag.
Gaussian & ALMA: These use a bell-curve weighting, giving the most importance to recent data in a smooth, non-linear fashion.
DAFE Spectral Laguerre: A proprietary, non-linear filter that uses a feedback loop and adapts its "gamma" based on volatility, providing exceptional tracking in all market conditions.
How to Choose a Filter
Start with "None": First, find an algorithm you like with no filtering to understand its raw behavior.
Introduce Low Lag: If you are getting too many whipsaws from noise, apply a short-length Hull MA (e.g., 5-8). This is often the best solution.
Go Adaptive: If your market has very distinct trend/chop regimes, try an Adaptive KAMA .
Maximum Purity: For the smoothest possible output with excellent responsiveness, use the DAFE Spectral Laguerre or Ehlers SuperSmoother .
█ THE VISUAL EXPERIENCE: DATA AS ART
The PSAR Laboratory is not just functional; it is beautiful. The visualization engine is designed to provide you with an intuitive, at-a-glance understanding of the market's state.
Algorithm-Specific Theming: Each of the 23 algorithms comes with its own unique, professionally designed color palette. This not only provides visual variety but allows you to instantly recognize which engine is active.
Dynamic Glow Effects: For many algorithms, the PSAR dots will emit a soft "glow." The brightness and color of this glow are not random; they are tied to a key metric of the active algorithm (e.g., trend strength, volatility, consensus), providing a subtle, visual cue about the health of the trend.
Adaptive Volatility Bands: Certain algorithms will display dynamic bands around the PSAR. These are not standard deviation bands; their width is controlled by the specific logic of the active algorithm, showing you a visual representation of the market's expected range or energy level.
Secondary Reference Lines: For algorithms like the Dual-PSAR or MTF Coherence, a secondary line will be plotted on the chart, giving you a clear visual of the underlying data (e.g., the slow PSAR, the HTF trend) that is driving the decision-making process.
█ THE MASTER DASHBOARD: YOUR MISSION CONTROL
The comprehensive dashboard is your unified command center for analysis and performance tracking.
Engine Status: See the currently selected Algorithm, the active Noise Filter, the Trend direction, and a real-time progress bar of the current Acceleration Factor (AF).
Algorithm-Specific Metrics: This is the most powerful section. It displays the key real-time data from the currently active algorithm. If you're using "Shannon Entropy," you'll see the Entropy score. If you're using "ADX-Gated," you'll see the ADX value. This gives you a direct, quantitative look under the hood.
Performance Readout: When enabled, this section provides a full breakdown of your backtesting results, including Win Rate, Profit Factor, Net P&L, Max Drawdown, and your current trade status.
█ DEVELOPMENT PHILOSOPHY
The PSAR Laboratory was born from a deep respect for Wilder's original work and a relentless desire to push it into the 21st century. We believe that in modern markets, static tools are obsolete. The future of trading lies in adaptation. This indicator is for the serious trader, the tinkerer, the scientist—the individual who is not content with a black box, but who seeks to understand, test, and refine their edge with surgical precision. It is a tool for forging, not just following.
The PSAR Laboratory is designed to be the ultimate tool for that evolution, allowing you to discover and codify the rules that truly fit you.
█ DISCLAIMER AND BEST PRACTICES
THIS IS A TOOL, NOT A STRATEGY: This indicator provides a sophisticated trailing stop and reversal signal. It must be integrated into a complete trading plan that includes risk management, position sizing, and your own contextual analysis.
TEST, DON'T GUESS: The power of this tool is its adaptability. Use the Performance Dashboard to rigorously test different algorithms and settings on your chosen asset and timeframe. Find what works, and build your strategy around that data.
START SIMPLE: Begin with the "Volatility-Scaled AF" algorithm, as it is a powerful and intuitive all-rounder. Once you are comfortable, begin experimenting with other engines.
RISK MANAGEMENT IS PARAMOUNT: All trading involves substantial risk. The backtesting results are hypothetical and do not account for slippage or psychological factors. Never risk more capital than you are prepared to lose.
"I don't think traders can follow rules for very long unless they reflect their own trading style. Eventually, a breaking point is reached and the trader has to quit or change, or find a new set of rules he can follow. This seems to be part of the process of evolution and growth of a trader."
— Ed Seykota, Market Wizard
Taking you to school. - Dskyz, Trade with Volume. Trade with Density. Trade with DAFE
Luminous Market Flux [Pineify]Luminous Market Flux - Dynamic Volatility Channel with Breakout Detection
The Luminous Market Flux indicator is a sophisticated volatility-based trading tool that combines dynamic channel analysis with breakout detection and squeeze identification. This indicator helps traders visualize market conditions by creating an adaptive envelope around price action, highlighting periods of compression (low volatility) and expansion (high volatility) while generating actionable buy and sell signals at key breakout moments.
Key Features
Dynamic volatility channel that adapts to changing market conditions using ATR-based calculations
Visual squeeze detection system that warns traders when volatility is contracting
Automatic breakout signal generation for both bullish and bearish scenarios
Luminous gradient fill that provides instant visual feedback on price position within the channel
Bar coloring feature that highlights strong volatility breakouts
Built-in alert conditions for automated trading notifications
How It Works
The indicator operates on three core calculation layers:
1. Baseline Calculation (Central Tendency)
The foundation uses a Running Moving Average (RMA) of the closing price over the specified Flux Length period. RMA was specifically chosen over SMA or EMA because it provides smoother trend detection similar to how RSI and ATR calculations work, reducing noise while maintaining responsiveness to genuine price movements.
2. Volatility Measurement
The channel width is determined by the Average True Range (ATR) multiplied by the Flux Expansion Factor. ATR captures the true volatility of the market by accounting for gaps and limit moves, making the channel responsive to actual market conditions rather than just closing price variations.
3. Squeeze Detection Logic
The indicator compares the current channel width against a 100-period simple moving average of historical channel widths. When the current range falls below 80% of this average, a squeeze condition is identified, signaling that volatility is compressing and a significant move may be imminent.
Trading Ideas and Insights
Breakout Trading: Enter long positions when price breaks above the upper flux channel with a BUY signal, and short positions when price breaks below the lower channel with a SELL signal. These breakouts indicate strong momentum in the direction of the move.
Squeeze Anticipation: When squeeze circles appear at the top of the chart, prepare for a potential explosive move. Squeezes often precede significant breakouts as the market coils before releasing energy in one direction.
Trend Confirmation: Use the bar coloring feature to confirm trend strength. Colored bars indicate that price is trading outside the volatility envelope, suggesting strong directional momentum.
Mean Reversion: When price is within the channel (no bar coloring), the gradient fill helps identify whether price is closer to the upper or lower boundary, potentially useful for mean-reversion strategies.
How Multiple Indicators Work Together
This indicator integrates several technical concepts into a cohesive system:
The RMA baseline provides the trend anchor, while the ATR-based envelope adapts to volatility conditions. These two components work together to create a channel that expands during volatile periods and contracts during quiet markets. The squeeze detection layer adds a third dimension by comparing current volatility to historical norms, alerting traders when the market is unusually quiet.
The visual elements reinforce this analysis: the gradient fill shows price position within the channel at a glance, bar coloring confirms breakout strength, and shape markers provide discrete entry signals. This multi-layered approach ensures traders receive consistent information across different visualization methods.
Unique Aspects
The "Luminous" visual design uses color gradients that dynamically shift based on price position, creating an intuitive heat-map effect within the channel
Unlike traditional Bollinger Bands that use standard deviation, this indicator uses ATR for volatility measurement, making it more responsive to actual price range movements
The squeeze detection compares current volatility to a longer-term average (100 periods), providing context-aware compression signals rather than arbitrary thresholds
Signal generation uses proper state tracking to ensure breakout signals only fire on the initial breakout, not on every bar during an extended move
How to Use
Add the indicator to your chart. It will overlay directly on price with the volatility channel visible.
Watch for BUY labels appearing below bars when price breaks above the upper channel - these indicate bullish breakout opportunities.
Watch for SELL labels appearing above bars when price breaks below the lower channel - these indicate bearish breakout opportunities.
Monitor for small circles at the top of the chart indicating squeeze conditions - prepare for potential breakouts when these appear.
Use the colored bars as confirmation of breakout strength - green bars confirm bullish momentum, red bars confirm bearish momentum.
Set up alerts using the built-in alert conditions to receive notifications for buy signals, sell signals, and squeeze warnings.
Customization
Flux Length (default: 20): Controls the lookback period for both the baseline and ATR calculations. Lower values create more responsive but noisier channels; higher values create smoother but slower-reacting channels.
Flux Expansion Factor (default: 2.0): Multiplier for the ATR value that determines channel width. Higher values create wider channels with fewer signals; lower values create tighter channels with more frequent signals.
Smooth Signal : Toggle for signal smoothing preference.
Bullish Energy : Customize the color for bullish breakouts and upper channel highlights.
Bearish Energy : Customize the color for bearish breakouts and lower channel highlights.
Compression/Neutral : Customize the color for squeeze indicators and neutral channel states.
Conclusion
The Luminous Market Flux indicator provides traders with a comprehensive volatility analysis tool that combines channel-based trend detection, squeeze identification, and breakout signaling into a single, visually intuitive package. By using ATR-based volatility measurement and RMA smoothing, the indicator adapts to changing market conditions while filtering out noise. Whether you are a breakout trader looking for momentum entries or a swing trader waiting for volatility expansion after compression periods, this indicator offers the visual clarity and signal precision needed to make informed trading decisions.
XAUUSD: Ultimate Sniper v6.0 [Order Flow & Macro]This indicator is a comprehensive trading system designed specifically for XAUUSD (Gold). It moves away from lagging indicators by combining real-time Macro-Economic sentiment, Regression Analysis, and Institutional Order Flow logic into a single professional interface.
### Core Strategy & Features: 1. Macro Correlation Filter: Gold has a strong inverse correlation with the USD (DXY) and Treasury Yields (US10Y). This script monitors them in the background. If DXY/US10Y are Bullish, Gold Buy signals are filtered out to prevent trading against the trend. 2. Linear Regression Channel: Defines the "Fair Value" of price. We only look for reversal trades when price hits the extreme Upper or Lower bands. 3. Order Flow Pressure (New): Analyzes the internal structure of each candle (Wick vs Body). A signal is only confirmed if the "Buying Pressure" or "Selling Pressure" within the candle supports the move (e.g. >50%). 4. RSI Divergence: Automatically spots Bullish and Bearish divergences to identify momentum exhaustion.
### ⚙️ Recommended Settings / Best Practices To get the best results, adjust the settings based on your trading style:
🏎️ SCALPING (1min - 5min Charts) * Goal: Quick entries, smaller targets, higher frequency. * DXY/US10Y Timeframe: Set to "15" or "30" (Reacts faster to macro changes). * Regression Length: 50 or 80 (Adapts to short-term trends). * RSI Length: 9 or 14.
🛡️ INTRADAY (15min - 1h Charts) - * Goal: Balanced trading, capturing the daily range. * DXY/US10Y Timeframe: Set to "60" (1 Hour). * Regression Length: 100 (Standard setting). * RSI Length: 14.
🦅 SWING TRADING (4h - Daily Charts) * Goal: Catching major trend reversals. * DXY/US10Y Timeframe: Set to "240" (4 Hours) or "D" (Daily). * Regression Length: 200 (Long-term trend baseline). * Channel Width: Increase to 2.5 or 3.0.
### How to Trade: - BUY Signal: Valid when the Dashboard shows "BEARISH" DXY/US10Y and the Live Pressure is "BUYERS". - SELL Signal: Valid when the Dashboard shows "BULLISH" DXY/US10Y and the Live Pressure is "SELLERS". - Risk Management: The script automatically calculates ATR-based Stop Loss (SL) and Take Profit (TP) levels.
Impulse Trend Levels [BOSWaves]Impulse Trend Levels - Momentum-Adaptive Trend Detection with Impulse-Driven Confidence Bands
Overview
Impulse Trend Levels is a momentum-aware trend identification system that tracks directional price movement through adaptive confidence bands, where band width dynamically adjusts based on impulse strength and freshness to reflect real-time conviction in the current trend direction.
Instead of relying on fixed moving average crossovers or static band multipliers, trend state, band positioning, and zone thickness are determined through impulse detection patterns, exponential decay modeling, and volatility-normalized momentum measurement.
This creates dynamic trend boundaries that reflect actual momentum intensity rather than arbitrary technical levels - contracting during fresh impulse conditions when trend conviction is high, expanding during impulse decay periods when directional confidence weakens, and incorporating momentum freshness calculations to reveal whether trends are accelerating or deteriorating.
Price is therefore evaluated relative to bands that adapt to momentum state rather than conventional static thresholds.
Conceptual Framework
Impulse Trend Levels is founded on the principle that meaningful trend signals emerge when price momentum intensity reaches significant thresholds relative to recent volatility rather than when price simply crosses moving averages.
Traditional trend-following methods identify directional changes through price-indicator crossovers, which often ignore the underlying momentum dynamics and conviction levels that sustain those moves. This framework replaces static-threshold logic with impulse-driven band construction informed by actual momentum strength and decay characteristics.
Three core principles guide the design:
Trend direction should be determined by volatility-normalized momentum breaches, not simple price crossovers alone.
Band width must adapt to impulse freshness, reflecting real-time confidence in the current trend.
Momentum decay modeling reveals whether trends are maintaining strength or losing conviction.
This shifts trend analysis from static indicator levels into adaptive, momentum-anchored confidence boundaries.
Theoretical Foundation
The indicator combines exponential moving average smoothing, mean absolute deviation measurement, impulse detection methodology, and exponential decay tracking.
An EMA-based trend baseline provides directional reference, while Mean Absolute Deviation (MAD) offers volatility-normalized scaling for momentum measurement. Impulse detection identifies significant price movements relative to recent volatility, triggering fresh momentum readings that decay exponentially over time. Band multipliers interpolate between tight and wide settings based on calculated impulse freshness.
Four internal systems operate in tandem:
Trend Baseline Engine : Computes EMA-smoothed price levels for directional reference and band anchoring.
Volatility Measurement System : Calculates MAD to provide adaptive scaling that normalizes momentum across varying market conditions.
Impulse Detection Logic : Identifies volatility-normalized price movements exceeding threshold levels, capturing momentum intensity and direction.
Decay-Based Confidence Modeling : Applies exponential decay to impulse readings, converting raw momentum into time-weighted freshness metrics that drive band adaptation.
This design allows trend confidence to reflect actual momentum behavior rather than reacting mechanically to price formations.
How It Works
Impulse Trend Levels evaluates price through a sequence of momentum-aware processes:
Baseline Calculation : EMA smoothing of open and close creates a directional trend reference that filters short-term noise.
Volatility Normalization : MAD calculation over a specified lookback provides dynamic scaling for momentum measurement.
Raw Impulse Detection : Price change over impulse lookback divided by MAD creates volatility-normalized momentum readings.
Threshold-Based Activation : When normalized momentum exceeds threshold (1.0), impulse registers with absolute magnitude and directional sign.
Exponential Decay Application : Between impulse events, stored impulse value decays exponentially via configurable decay rate.
Freshness Conversion : Decaying impulse transforms into freshness metric (0-100%) representing current momentum conviction.
Adaptive Band Construction : Band multiplier interpolates between minimum (fresh) and maximum (stale) settings based on freshness, then scales MAD to determine band width.
Trend State Logic : Price crossing above upper band triggers bullish state; crossing below lower band triggers bearish state; state persists until opposite breach.
Signal Generation : Trend state switches from bearish to bullish produce buy signals; bullish to bearish switches produce sell signals.
Retest Identification : Price touching inner band edge after signal buffer period marks retests, with cooldown periods preventing excessive plotting.
Together, these elements form a continuously updating trend framework anchored in momentum reality.
Interpretation
Impulse Trend Levels should be interpreted as momentum-anchored trend confidence boundaries:
Bullish Trend State (Cyan) : Established when price closes above adaptive upper band, indicating upward momentum breach with associated confidence level.
Bearish Trend State (Magenta) : Established when price closes below adaptive lower band, signaling downward momentum breach with directional conviction.
Trend Cloud : Visual gradient zone displays between outer and inner band edges, with opacity reflecting current trend state and confidence.
Band Width Dynamics : Tighter bands indicate fresh impulse (high confidence), wider bands indicate impulse decay (reduced confidence).
▲ Buy Signals : Green upward triangles mark bullish trend state initiations at crossovers above upper band.
▼ Sell Signals : Red downward triangles mark bearish trend state initiations at crossovers below lower band.
✦ Retest Markers : Small diamonds identify price retouching inner band edge after sufficient buffer period from initial signal.
Retest Extension Lines : Horizontal projections from retest points extend forward, marking potential support/resistance levels.
Colored Candles : Optional bar coloring reflects current trend state for immediate visual reference. Note: The original chart candles must be disabled in chart settings for the trend-colored candles to display properly.
Impulse freshness, band width dynamics, and momentum normalization outweigh isolated price movements.
Signal Logic & Visual Cues
Impulse Trend Levels presents two primary interaction signals:
Buy Signal (▲) : Green label appears when trend state switches from bearish to bullish via upper band crossover, suggesting momentum shift to upside.
Sell Signal (▼) : Red label displays when trend state switches from bullish to bearish via lower band crossunder, indicating momentum shift to downside.
Retest detection provides secondary confirmation when price revisits inner band boundaries after signal buffer cooldown expires.
Alert generation covers trend state switches (long/short), retest occurrences, and impulse freshness decay below 50% threshold for systematic monitoring.
Strategy Integration
Impulse Trend Levels fits within momentum-informed and adaptive trend-following approaches:
Momentum-Confirmed Entries : Use band crossovers as high-probability trend initiation points where volatility-normalized momentum exceeded threshold.
Freshness-Based Position Sizing : Scale exposure based on impulse freshness - larger positions during fresh impulse periods, reduced sizing as impulse decays.
Band-Width Risk Management : Expect wider price ranges when bands expand during decay, tighter ranges when bands contract during fresh impulse.
Retest-Based Re-entry : Use inner band retests as lower-risk entry opportunities within established trends after initial signal cooldown.
Cloud-Aligned Directional Bias : Favor trades aligning with current trend state rather than counter-trend positions.
Multi-Timeframe Momentum Confirmation : Apply higher-timeframe impulse trend state to filter lower-timeframe entry precision.
Technical Implementation Details
Core Engine : EMA-based baseline with MAD volatility measurement
Impulse Model : Volatility-normalized momentum detection with directional sign capture
Decay System : Exponential decay application (0.8-0.99 range) with freshness conversion
Band Construction : Linear interpolation between min/max multipliers scaled by MAD
Visualization : Gradient-filled cloud zones with bar coloring and signal labels
Signal Logic : State-switch detection with retest buffer and cooldown mechanisms
Performance Profile : Optimized for real-time execution across all timeframes
Optimal Application Parameters
Timeframe Guidance:
1 - 5 min : Micro-trend detection for scalping with responsive impulse settings
15 - 60 min : Intraday momentum tracking with balanced decay characteristics
4H - Daily : Swing-level trend identification with sustained impulse persistence
Suggested Baseline Configuration:
Trend Length : 19
Impulse Lookback : 5
Decay Rate : 0.99
MAD Length : 20
Band Min (Fresh) : 1.5
Band Max (Stale) : 1.9
Signal Buffer Period : 10
Show Trend Cloud : Enabled
Color Bars : Enabled (requires disabling original chart candles in chart settings)
Show Buy/Sell Signals : Enabled
These suggested parameters should be used as a baseline; their effectiveness depends on the asset's volatility profile, momentum characteristics, and preferred signal frequency, so fine-tuning is expected for optimal performance.
Parameter Calibration Notes
Use the following adjustments to refine behavior without altering the core logic:
Excessive signal noise : Increase Trend Length to demand smoother baseline crossovers or increase Impulse Lookback for less reactive momentum detection.
Missed momentum shifts : Decrease Impulse Lookback to capture shorter-term momentum changes or reduce Decay Rate to allow faster impulse fade.
Bands too tight/wide : Adjust Band Min and Band Max multipliers to modify confidence zone thickness across freshness spectrum.
Impulse decays too quickly : Increase Decay Rate toward 0.99 to sustain impulse readings longer between fresh events.
Impulse decays too slowly : Decrease Decay Rate toward 0.8 for faster momentum fade and more frequent band expansion.
Unstable volatility scaling : Increase MAD Length to smooth volatility measurement and reduce sensitivity to short-term spikes.
Too many retest markers : Increase retest cooldown period (55 bars hardcoded) or increase Signal Buffer Period to space out signals.
Adjustments should be incremental and evaluated across multiple session types rather than isolated market conditions.
Performance Characteristics
High Effectiveness:
Trending markets with clear momentum phases and directional persistence
Instruments with consistent volatility characteristics where MAD scaling normalizes effectively
Momentum continuation strategies entering on fresh impulse signals
Trend-following approaches benefiting from adaptive confidence measurement
Reduced Effectiveness:
Choppy, range-bound markets with frequent whipsaw crossovers
Extremely low volatility environments where impulse threshold becomes difficult to breach
News-driven or gapped markets with discontinuous momentum patterns
Mean-reversion dominant conditions where momentum breaches quickly reverse
Consolidation and sideways price action where trend-following methodologies inherently struggle due to lack of sustained directional movement
Integration Guidelines
Confluence : Combine with BOSWaves structure, volume analysis, or traditional trend indicators
Freshness Respect : Trust signals occurring during high impulse freshness periods with contracted bands
Decay Awareness : Reduce position sizing or tighten stops as impulse decays and bands widen
Retest Utilization : Treat inner band retests as continuation confirmation rather than reversal signals
State Discipline : Maintain directional bias aligned with current trend state until opposite band breach occurs
Disclaimer
Impulse Trend Levels is a professional-grade momentum and trend analysis tool. It uses volatility-normalized impulse detection with exponential decay modeling but does not predict future price movements. Results depend on market conditions, volatility characteristics, parameter selection, and disciplined execution. BOSWaves recommends deploying this indicator within a broader analytical framework that incorporates price structure, volume context, and comprehensive risk management.
FxShare - Trend MomentumThis one is just a clean background script. You can use it as an addition to your other indicators or if you just want:
a clean Trend Channel
a calm background
Momentum Strength meter panel.
It is based on our favorite accurate combo ATR, MACD and RSI mix . It has only one outside parameter for channel smoothing - 0-50 range. Use it, break it, improve it..
Supertrend + RSI + EMA + MACD - Fixed Single SignalMomentum trading with signals to add alerts and connect to API for Algo trading
Keltner-Aroon-EFI FlowKeltner-Aroon-EFI Flow (KAE)
KAE Flow is a quantitative composite indicator designed to identify dominant market trends by fusing three distinct dimensions of price action: Volatility, Trend Age, and Volume Pressure.
Unlike standard indicators that rely on a single data point (like a moving average crossover), KAE Flow aggregates three independent logic engines into a single normalized "Flow" score. This score is then smoothed using an Arnaud Legoux Moving Average (ALMA) to filter out noise while retaining responsiveness to genuine trend reversals.
This script operates strictly on the current chart timeframe, ensuring all signals are causal, non-repainting, and reliable for real-time analysis.
1. The Quantitative Engine (How it Works)
The indicator polls three separate components. Each component votes "1" (Bullish), "-1" (Bearish), or "0" (Neutral). These votes are averaged to create the raw signal.
K — Keltner Channels (Volatility Dimension)
Concept: Measures volatility expansion.
Logic: The script calculates Keltner Channels using an EMA center line and ATR bands.
Bullish (+1): Price closes above the Upper Channel.
Bearish (-1): Price closes below the Lower Channel.
This component ensures we only trade when price is breaking out of its expected volatility range.
A — Aroon (Trend Age Dimension)
Concept: Measures the strength and "freshness" of a trend.
Logic: We utilize the Aroon Up and Aroon Down metrics.
Bullish (+1): Aroon Up is greater than Aroon Down AND Aroon Up is > 70.
Bearish (-1): Aroon Down is greater than Aroon Up AND Aroon Down > 70.
This filters out weak or aging trends, ensuring the move has mathematical momentum.
E — Elder’s Force Index (Volume Dimension)
Concept: Measures volume-weighted price change.
Logic: We calculate the raw Force Index (Close - Close ) * Volume and smooth it with an EMA.
Bullish (+1): Smoothed EFI > 0.
Bearish (-1): Smoothed EFI < 0.
This component confirms that price movement is supported by actual volume flow (accumulation/distribution).
2. Signal Processing (ALMA Smoothing)
Raw aggregation can be noisy. The composite score is passed through an ALMA (Arnaud Legoux Moving Average) filter.
Why ALMA? It uses a Gaussian distribution to provide smoothness without the significant lag associated with SMA or EMA. This creates the "Flow" line that resists false flips during choppy consolidation.
3. How to Use
The indicator plots a signal line and dynamically colors the price bars and background to reflect the dominant bias.
Deep Blue (Bullish Flow): The KAE Score is > 0.1. All three engines (or the majority) are aligned bullishly. Traders typically look for long entries or hold existing long positions.
White (Bearish Flow): The KAE Score is < -0.1. The majority of engines detect bearish volatility and volume. Traders typically look for short entries.
Gray (Neutral): The score is between -0.1 and 0.1. The market is in equilibrium or transition. Trend-following strategies should be paused.
4. Configuration
Logic Engine: You can toggle individual components (K, A, or E) on or off to isolate specific market dimensions.
Smoothing: Adjust the ALMA Window and Offset to fine-tune the sensitivity of the signal line.
Lengths: Fully customizable periods for Keltner, Aroon, and EFI to adapt to different asset classes (e.g., Crypto vs. Forex).
Crypto Engine ProCrypto Engine Pro is a proprietary trend-structure and price-behavior indicator designed specifically for BTC and ETH markets.
It combines Price structure, dynamic trend midlines, and adaptive trend lines to help traders visually identify trend direction, momentum shifts, and structure breaks with clarity.
🔹 Key Features
📈 Dynamic Trend Detection
Identifies bullish and bearish phases using price structure and internal equilibrium levels.
📐 Trend Midline (Running)
Continuously updates based on the active trend, helping visualize balance and continuation zones.
🔺 Multi-Trend Line System
Primary structure line from previous trend extreme
Designed to reflect real market structure, not lagging signals
🎨 Trend-Based Visuals
Background color reflects active trend
Bar color changes on structure breaks relative to the main trend line
🔔 Trend Flip Alerts
Alerts on bullish and bearish structure flips
Helps traders stay aligned with dominant momentum
⚠️ Important Note
Crypto Engine Pro currently works only on BTC and ETH charts.
If applied to any other symbol, the indicator will display a restriction message and disable visuals.
🧠 Who Is This For?
Crypto traders focusing on BTC & ETH
Traders who prefer structure-based trend analysis
Those looking for visual clarity over cluttered indicators
📌 Usage Disclaimer
This indicator is a visual decision-support tool and should not be used as a standalone trading system.
Always combine with proper risk management and higher-timeframe context.
Version: Crypto Engine Pro
GOM Divine LevelsGOM Divine Levels is an advanced trading indicator that revolutionizes how you identify support and resistance levels. Developed with logic inspired by professional MT5 algorithms, this tool gives you a competitive edge in the markets.
✨ MAIN FEATURES:
🔍 Multi-Timeframe Detection:
Simultaneous analysis of 6 main timeframes (M5, M15, H1, H4, D1, W1)
Selective display according to your trading preferences
Real-time level updates
⚖️ Intelligent ATR Validation:
Level filtering based on ATR distance
Elimination of false signals and market "noise"
Adjustable parameters according to your trading style
🔄 Touch Detection System:
Automatic touch counting on each level
Variable line thickness according to level significance
The more a level is tested, the more significant it becomes
🎨 Professional Visualization:
Distinct color codes for supports (green) and resistances (red)
Clear labels with timeframe and level type
Lines extended across the entire chart for better visibility
⚠️ Complete Alert System:
Alerts for each timeframe and level type
Real-time notifications for trading opportunities
Configurable according to your specific needs
🛠️ CUSTOMIZABLE PARAMETERS:
Swing Detection: Adjust pivot sensitivity
ATR Validation: Control minimum and maximum distances
Touch System: Customize detection zone and line thickness
Display: Choose timeframes, colors, and labels
📈 FOR WHOM?
Beginner traders looking for clear levels
Experienced traders wanting to confirm their analysis
Scalpers using short timeframes
Long-term investors relying on higher timeframes
⚡ KEY ADVANTAGES:
Accuracy: Sophisticated algorithms for precise detection
Flexibility: Adaptable to all trading styles
Visibility: Clear and uncluttered interface
Reliability: Multiple level validations
Real-time: Instant updates
🔧 TECHNICAL SPECIFICATIONS:
Based on pivot detection (swing highs/lows)
Validation by dynamic ATR distance
Historical touch counting system
Compatible with all TradingView instruments
🚀 HOW TO USE:
Add the indicator to your chart
Configure desired timeframes
Adjust parameters according to the market
Trade on the most significant levels
Enable alerts to never miss opportunities
Join the traders who have already discovered the power of divine levels! Transform your technical analysis with GOM Divine Levels™.
IG ATR Risk PlannerOverview
The IG ATR Risk Planner is a professional risk management indicator that calculates position size, stop-loss, and take-profit levels using the Average True Range (ATR). It adapts to market volatility, helping traders maintain consistent discipline across different instruments and timeframes.
Key Features
Position Size Calculation: Automatically determines optimal position size based on account balance, risk percentage, and ATR stop distance.
Volatility-Based Stop-Loss: Calculates stop levels using ATR multipliers, ensuring stops are adjusted to market conditions.
Take-Profit Targets: Provides three customizable ATR-based profit targets (TP1, TP2, TP3).
Risk Parameters Table: Displays account size, risk %, multiplier, entry, stop, and targets in a clear on‑chart table.
Chart Labels: Entry, stop, and TP levels are visually marked for instant recognition.
Alerts: Integrated alerts for entry, stop, and profit targets.
Alerts Included (concise list)
Entry Long / Entry Short
Stop Long / Stop Short
TP1 Long / TP1 Short
TP2 Long / TP2 Short
TP3 Long / TP3 Short
Why Use This Indicator?
Risk management is the foundation of consistent trading. The IG ATR Risk Planner ensures every trade is backed by clear calculations, structured targets, and actionable alerts. Whether trading forex, stocks, or crypto, this tool helps you stay disciplined and professional.
Future Swing [BigBeluga]🔵 OVERVIEW
Future Swing is a swing-based projection tool that estimates the potential size and price target of the next swing move using historical swing behavior.
Instead of predicting direction randomly, it analyzes completed swing legs, measures their percentage moves, and projects a statistically derived swing target into the future.
The indicator combines swing structure, high/low zones, volume context, and a real-time dashboard to help traders anticipate where price may travel next.
🔵 CONCEPTS
Swing Detection — Swing highs and lows are identified using a configurable lookback length.
Swing Percentage Tracking — Each completed swing leg is converted into a percentage move and stored.
Statistical Projection — Future swing size is estimated using Average, Median, or Mode of past swing percentages.
Directional Awareness — Projections adapt automatically based on current swing direction.
🔵 FEATURES
Historical Swing Sampling —
• Uses a user-defined number of completed swings.
• More samples = smoother projection, fewer samples = faster adaptation.
Future Swing Projection —
• Dashed line projects the estimated swing target forward in time.
• Projection distance is visual-only and does not affect calculations.
High/Low Swing Zones —
• Upper and lower swing zones expand using ATR distance.
• Zones visualize potential reaction and rejection areas.
Volume Context per Swing —
• Buy and sell volume are accumulated during each swing leg.
• Delta and total volume are displayed in the dashboard.
Smart Dashboard —
• Displays each stored swing percentage.
• Shows calculated swing projection value.
Flexible Projection Method —
• Average: smooth and balanced.
• Median: filters out extreme outliers.
• Mode: focuses on the most common swing size.
Extendable Zones —
• Swing zones can optionally extend forward indefinitely.
🔵 HOW TO USE
Anticipate Swing Targets — Use the projected swing line as a probabilistic price objective.
Combine with Structure — Align projections with support, resistance, or liquidity zones.
Filter by Volume — Confirm swing quality using delta and total volume metrics.
Adjust Sensitivity — Tune swing length and historical sample size to match timeframe and volatility.
Context, Not Certainty — Use projections as guidance, not fixed take-profit levels.
🔵 CONCLUSION
Future Swing transforms past swing behavior into a forward-looking projection model.
By combining swing structure, statistical aggregation, ATR zones, and volume analysis, it offers traders a structured way to estimate where the next meaningful price move may reach — without relying on fixed targets or subjective assumptions.
Multi-Timeframe EMA Bundle (576/676/144/169/12)A comprehensive EMA (Exponential Moving Average) indicator combining five key moving averages used by professional traders for trend identification and dynamic support/resistance levels.
Included EMAs:
EMA 576 & EMA 676 (Blue) — Long-term trend filters commonly used on lower timeframes to represent higher timeframe structure. Acts as major support/resistance zones.
EMA 144 & EMA 169 (White) — Mid-term trend indicators derived from Fibonacci numbers. When price respects this zone, it often signals strong trend continuation.
EMA 12 (Yellow) — Short-term momentum tracker for entries and exits. Useful for identifying pullback opportunities within the trend.
All-in-One Multi-Indicator Straddle - Strangle StrategyAll-in-One Multi-Indicator Straddle – Strangle Strategy
Overview
All-in-One Multi-Indicator Straddle – Strangle Strategy is an analytical indicator designed for options premium analysis on Indian index derivatives. The script dynamically constructs option symbols based on user-selected index, expiry, and strikes, and visualizes the combined premium (Call + Put) or individual leg premium as candles.
On top of the premium structure, the indicator allows traders to optionally apply multiple technical indicators —EMA crossover, Supertrend, VWAP, RSI, and SMA—to generate structured buy and sell signals on the option premium itself.
This tool is intended strictly for educational and analytical purposes and does not execute trades.
Key Features
Dynamic Option Symbol Construction
Supports NIFTY, BANKNIFTY, FINNIFTY, MIDCPNIFTY, and BSX
User-defined expiry (day, month, year)
Custom Call and Put strike selection
Straddle / Strangle Premium Visualization
Combined Call + Put premium
Only Call premium
Only Put premium
Displayed as candle data for better price-action analysis
Multi-Indicator Confirmation Engine
EMA crossover (fast & slow)
Supertrend with adjustable ATR and factor
Session-reset VWAP on premium
RSI with customizable levels
SMA trend filter - Indicators can be enabled or disabled independently.
Signal Control Logic
One Buy and one Sell signal per trading day
Prevents repeated signals in the same direction
Signals are based on selected indicator confluence
Alerts
Built-in alert conditions for Buy and Sell signals
How It Works
The script builds option symbols using the selected index, expiry, and strike prices.
Option OHLCV data is fetched using request.security.
Depending on the selected mode: (1) Call and Put premiums are combined, or (2) A single leg is analyzed.
The resulting premium is plotted as candles.
Selected indicators are applied directly to the premium price.
Buy/Sell signals are generated only when all enabled conditions align.
Inputs Summary
Index & Expiry
Spot symbol
Expiry day, month, and year (string-based for accuracy)
Strike Selection
Call strike
Put strike
Combined / Only Call / Only Put mode
Indicators (Optional)
EMA (Fast & Slow lengths)
Supertrend (ATR length & factor)
VWAP (volume-weighted premium)
RSI (length, overbought & oversold levels)
SMA (length)
Important Notes & Limitations
This indicator does not place trades and is not a strategy.
Option symbols must exactly match broker-specific naming conventions supported by TradingView.
Data availability depends on TradingView’s option data coverage.
VWAP is session-based and resets on a new trading day.
Signals are analytical references only and should not be considered financial advice.
Intended Use
This indicator is best suited for:
Studying straddle and strangle premium behavior
Monitoring premium trends using technical indicators
Educational analysis of option premium dynamics
Users are encouraged to combine this tool with their own risk management and market understanding.
MTF Equals v1.0MTF Equals is a professional-grade tool designed to identify significant price levels across multiple timeframes. It scans the current chart and higher timeframes (HTF) for identical highs and lows ("Equals"), which often act as price magnets or liquidity pools.
Key Features:
Multi-Timeframe Analysis: Automatically detects identical highs and lows on the current chart, as well as M5, M15, M30, H1, H4, and Daily.
NQ Auto-Detection: Specialized logic for Nasdaq (NQ) that automatically determines the ideal starting point for analysis based on volume, efficiency, and price density.
Live Statistics: Displays the number of touches and the bar distance from the first touchpoint directly on the price level.
Smart Cleaning: Levels are automatically removed once they are significantly breached by price, keeping your chart clutter-free.
Advanced Visuals: Fully customizable colors, line styles, and label positioning (e.g., Align to Margin).
How to use:
Perfect for spotting "Equal Highs/Lows" (Liquidity) or confirming institutional support and resistance zones.
