ADR(20)% - Qullamagi (corner value) v6This indicator displays the 20-bar Average Daily Range (ADR) either as a percentage of price or in raw dollar terms, shown in a clean corner box on the chart.
Switch between % ADR and $ ADR with a single checkbox.
Place the output box in any chart corner.
Useful for volatility assessment, stop-loss sizing, and stock selection.
Inspired by the trading approach of Kristjan Qullamägi (Qullamaggie), who uses ADR(20) both to filter high-momentum stocks and to size risk (stops should generally be ≤ 1×ADR).
אינדיקטורים ואסטרטגיות
Squeeze Momentum CV [Divergencias]RAFAEL CEPEDA Strategy es parte del mejor, una estrategia super facil
Recovery StrategyDescription:
The Recovery Strategy is a long-only trading system designed to capitalize on significant price drops from recent highs. It enters a position when the price falls 10% or more from the highest high over a 6-month lookback period and adds positions on further 2% drops, up to a maximum of 5 positions. Each trade is held for 6 months before exiting, regardless of profit or loss. The strategy uses margin to amplify position sizes, with a default leverage of 5:1 (20% margin requirement). All key parameters are customizable via inputs, allowing flexibility for different assets and timeframes. Visual markers indicate recent highs for reference.
How It Works:
Entry: Buys when the closing price drops 10% or more from the recent high (highest high in the lookback period, default 126 bars ~6 months). If already in a position, additional buys occur on further 2% drops (e.g., 12%, 14%, 16%, 18%), up to 5 positions (pyramiding).
Exit: Each trade exits after its own holding period (default 126 bars ~6 months), regardless of profit or loss. No stop loss or take-profit is used.
Margin: Uses leverage to control larger positions (default 20% margin, 5:1 leverage). The order size is a percentage of equity (default 100%), adjustable via inputs.
Visualization: Displays blue markers (without text) at new recent highs to highlight reference levels.
Inputs:
Lookback Period for High Peak (bars): Number of bars to look back for the recent high (default: 126, ~6 months on daily charts).
Initial Drop Percentage to Buy (%): Percentage drop from recent high to trigger the first buy (default: 10.0%).
Additional Drop Percentage to Buy (%): Further drop percentage to add positions (default: 2.0%).
Holding Period (bars): Number of bars to hold each position before selling (default: 126, ~6 months).
Order Size (% of Equity): Percentage of equity used per trade (default: 100%).
Margin for Long Positions (%): Percentage of position value covered by equity (default: 20%, equivalent to 5:1 leverage).
Usage:
Timeframe: Designed for daily charts (126 bars ~6 months). Adjust Lookback Period and Holding Period for other timeframes (e.g., 1008 hours for hourly charts, assuming 8 trading hours/day).
Assets: Suitable for stocks, ETFs, or other assets with significant price volatility. Test thoroughly on your chosen asset.
Settings: Customize inputs in the strategy settings to match your risk tolerance and market conditions. For example, lower Margin for Long Positions (e.g., to 10% for 10:1 leverage) to increase position sizes, but beware of higher risk.
Backtesting: Use TradingView’s Strategy Tester to evaluate performance. Check the “List of Trades” for skipped trades due to insufficient equity or margin requirements.
Risks and Considerations:
No Stop Loss: The strategy holds trades for the full 6 months without a stop loss, exposing it to significant drawdowns in prolonged downtrends.
Margin Risk: Leverage (default 5:1) amplifies both profits and losses. Ensure sufficient equity to cover margin requirements to avoid skipped trades or simulated margin calls.
Pyramiding: Up to 5 positions can be open simultaneously, increasing exposure. Adjust pyramiding in the code if fewer positions are desired (e.g., change to pyramiding=3).
Market Conditions: Performance depends on price drops and recoveries. Test on historical data to assess effectiveness in your market.
Broker Emulator: TradingView’s paper trading simulates margin but does not execute real margin trading. Results may differ in live trading due to broker-specific margin rules.
How to Use:
Add the strategy to your chart in TradingView.
Adjust input parameters in the settings panel to suit your asset, timeframe, and risk preferences.
Run a backtest in the Strategy Tester to evaluate performance.
Monitor open positions and margin levels in the Trading Panel to manage risk.
For live trading, consult your broker’s margin requirements and leverage policies, as TradingView’s simulation may not match real-world conditions.
Disclaimer:
This strategy is for educational purposes only and does not constitute financial advice. Trading involves significant risk, especially with leverage and no stop loss. Always backtest thoroughly and consult a financial advisor before using any strategy in live trading.
ADR(20)% - Qullamagi (corner value) v6Description:
This indicator calculates the 20-day Average Daily Range (ADR) as a percentage (or in raw $) and displays it in a clean corner table on the chart.
Formula: average of (High ÷ Low – 1) over the last 20 bars.
Use % or $ mode via settings.
Position the box in any chart corner.
Inspired by Kristjan Qullamägi (Qullamaggie), who uses ADR to filter strong movers and size stop-losses (stops should generally be ≤ 1×ADR).
Kalman Sigmoid Z-score | SurgeQuantTitle: Kalman Sigmoid Z-score Indicator
The Kalman Sigmoid Z-score indicator is a sophisticated tool designed to identify market momentum and potential trend changes using a combination of Kalman filtering, sigmoid-weighted averaging, and Z-score calculations. By processing price data through a Kalman filter and applying adaptive sigmoid weighting, this indicator provides clear visual signals for bullish and bearish market conditions. The Z-score output and price bars are dynamically colored to highlight momentum shifts, aiding traders in identifying potential trading opportunities.
How It Works
Kalman Filter Calculation
Computes a smoothed price series using a Kalman filter based on a user-selected price source (Close, High, Low, or Open) with configurable parameters for process noise, measurement noise, and filter order (default: 3).
The Kalman filter reduces noise in the price data, providing a stable foundation for further analysis.
Sigmoid-Weighted Averaging
Applies a sigmoid function to calculate adaptive weights based on price comparisons over a user-defined lookback period (default: 10).
Weights are adjusted dynamically using a volatility ratio (standard deviation over ATR) to account for market conditions, enhancing signal reliability.
Z-score Calculation
Calculates the Z-score of the Kalman-filtered price relative to a sigmoid-weighted moving average over a user-defined period (default: 20).
Bullish Signal: Triggered when the Z-score crosses above 0, indicating potential upward momentum.
Bearish Signal: Triggered when the Z-score crosses below 0, indicating potential downward momentum.
Visual Representation
The indicator provides a clear and customizable visual interface:
Z-score Histogram: Displayed as colored columns, with distinct colors for bullish (Z-score > 0) and bearish (Z-score < 0) conditions.
Bright green (#4DFFBE) for rising Z-score above 0.
Light green (#56DFCF) for falling Z-score above 0.
Dark purple (#AE75DA) for falling Z-score below 0.
Light purple (#4D2D8C) for rising Z-score below 0.
Price Bar Coloring: Synchronizes with the Z-score colors to reflect momentum on the main chart.
Reference Line: A zero line is plotted on the Z-score panel for easy reference.
Customization & Parameters
The Kalman Sigmoid Z-score indicator offers flexible parameters to suit various trading styles:
Source: Select the input price (default: Close; options: Close, High, Low, Open).
Lookback Period: Set the period for sigmoid weight calculations (default: 10).
Volatility Period: Adjust the period for volatility ratio calculation (default: 30).
Base Steepness: Control the sigmoid function’s sensitivity (default: 5).
Base Midpoint: Set the sigmoid function’s midpoint (default: 0.01).
Z-score Period: Define the period for Z-score calculation (default: 20).
Kalman Parameters:
Process Noise (default: 0.01).
Measurement Noise (default: 3).
Filter Order (default: 3).
Color Settings: Predefined colors with distinct shades for bullish and bearish states, ensuring clear visual differentiation.
Trading Applications
This indicator is versatile and can be applied across various markets and strategies:
Momentum Trading: Highlights strong bullish or bearish momentum for potential entry or exit points based on Z-score crossings.
Trend Confirmation: Use bar coloring to confirm Z-score signals with price action on the main chart.
Reversal Detection: Identify potential reversals when the Z-score crosses the zero line.
Scalping and Swing Trading: Adjust parameters (e.g., lookback, Z-score period) to suit short-term or longer-term strategies.
Final Note
The Kalman Sigmoid Z-score indicator is a powerful tool for traders seeking to leverage advanced filtering and statistical analysis for momentum and trend-based opportunities. Its combination of Kalman-filtered price smoothing, sigmoid-weighted averaging, dynamic Z-score signals, and synchronized bar coloring offers a robust framework for informed trading decisions. As with all indicators, backtest thoroughly and integrate into a comprehensive trading strategy for optimal results. This indicator is provided for educational and informational purposes and should not be considered financial advice.
ADR(20) % ValueDisplays the 20-day Average Daily Range (ADR) as a % of price, following the method popularized by Kristjan Qullamägi (Qullamaggie). The ADR value updates dynamically and is printed directly on the chart for quick reference.
Machine Learning Gaussian Mixture Model | AlphaNattMachine Learning Gaussian Mixture Model | AlphaNatt
A revolutionary oscillator that uses Gaussian Mixture Models (GMM) with unsupervised machine learning to identify market regimes and automatically adapt momentum calculations - bringing statistical pattern recognition techniques to trading.
"Markets don't follow a single distribution - they're a mixture of different regimes. This oscillator identifies which regime we're in and adapts accordingly."
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🤖 THE MACHINE LEARNING
Gaussian Mixture Models (GMM):
Unlike K-means clustering which assigns hard boundaries, GMM uses probabilistic clustering :
Models data as coming from multiple Gaussian distributions
Each market regime is a different Gaussian component
Provides probability of belonging to each regime
More sophisticated than simple clustering
Expectation-Maximization Algorithm:
The indicator continuously learns and adapts using the E-M algorithm:
E-step: Calculate probability of current market belonging to each regime
M-step: Update regime parameters based on new data
Continuous learning without repainting
Adapts to changing market conditions
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🎯 THREE MARKET REGIMES
The GMM identifies three distinct market states:
Regime 1 - Low Volatility:
Quiet, ranging markets
Uses RSI-based momentum calculation
Reduces false signals in choppy conditions
Background: Pink tint
Regime 2 - Normal Market:
Standard trending conditions
Uses Rate of Change momentum
Balanced sensitivity
Background: Gray tint
Regime 3 - High Volatility:
Strong trends or volatility events
Uses Z-score based momentum
Captures extreme moves
Background: Cyan tint
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💡 KEY INNOVATIONS
1. Probabilistic Regime Detection:
Instead of binary regime assignment, provides probabilities:
30% Regime 1, 60% Regime 2, 10% Regime 3
Smooth transitions between regimes
No sudden indicator jumps
2. Weighted Momentum Calculation:
Combines three different momentum formulas
Weights based on regime probabilities
Automatically adapts to market conditions
3. Confidence Indicator:
Shows how certain the model is (white line)
High confidence = strong regime identification
Low confidence = transitional market state
Line transparency changes with confidence
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⚙️ PARAMETER OPTIMIZATION
Training Period (50-500):
50-100: Quick adaptation to recent conditions
100: Balanced (default)
200-500: Stable regime identification
Number of Components (2-5):
2: Simple bull/bear regimes
3: Low/Normal/High volatility (default)
4-5: More granular regime detection
Learning Rate (0.1-1.0):
0.1-0.3: Slow, stable learning
0.3: Balanced (default)
0.5-1.0: Fast adaptation
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📊 TRADING STRATEGIES
Visual Signals:
Cyan gradient: Bullish momentum
Magenta gradient: Bearish momentum
Background color: Current regime
Confidence line: Model certainty
1. Regime-Based Trading:
Regime 1 (pink): Expect mean reversion
Regime 2 (gray): Standard trend following
Regime 3 (cyan): Strong momentum trades
2. Confidence-Filtered Signals:
Only trade when confidence > 70%
High confidence = clearer market state
Avoid transitions (low confidence)
3. Adaptive Position Sizing:
Regime 1: Smaller positions (choppy)
Regime 2: Normal positions
Regime 3: Larger positions (trending)
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🚀 ADVANTAGES OVER OTHER ML INDICATORS
vs K-Means Clustering:
Soft clustering (probabilities) vs hard boundaries
Captures uncertainty and transitions
More mathematically robust
vs KNN (K-Nearest Neighbors):
Unsupervised learning (no historical labels needed)
Continuous adaptation
Lower computational complexity
vs Neural Networks:
Interpretable (know what each regime means)
No overfitting issues
Works with limited data
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📈 PERFORMANCE CHARACTERISTICS
Best Market Conditions:
Markets with clear regime shifts
Volatile to trending transitions
Multi-timeframe analysis
Cryptocurrency markets (high regime variation)
Key Strengths:
Automatically adapts to market changes
No manual parameter adjustment needed
Smooth transitions between regimes
Probabilistic confidence measure
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🔬 TECHNICAL BACKGROUND
Gaussian Mixture Models are used extensively in:
Speech recognition (Google Assistant)
Computer vision (facial recognition)
Astronomy (galaxy classification)
Genomics (gene expression analysis)
Finance (risk modeling at investment banks)
The E-M algorithm was developed at Stanford in 1977 and is one of the most important algorithms in unsupervised machine learning.
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💡 PRO TIPS
Watch regime transitions: Best opportunities often occur when regimes change
Combine with volume: High volume + regime change = strong signal
Use confidence filter: Avoid low confidence periods
Multi-timeframe: Compare regimes across timeframes
Adjust position size: Scale based on identified regime
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⚠️ IMPORTANT NOTES
Machine learning adapts but doesn't predict the future
Best used with other confirmation indicators
Allow time for model to learn (100+ bars)
Not financial advice - educational purposes
Backtest thoroughly on your instruments
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🏆 CONCLUSION
The GMM Momentum Oscillator brings institutional-grade machine learning to retail trading. By identifying market regimes probabilistically and adapting momentum calculations accordingly, it provides:
Automatic adaptation to market conditions
Clear regime identification with confidence levels
Smooth, professional signal generation
True unsupervised machine learning
This isn't just another indicator with "ML" in the name - it's a genuine implementation of Gaussian Mixture Models with the Expectation-Maximization algorithm, the same technology used in:
Google's speech recognition
Tesla's computer vision
NASA's data analysis
Wall Street risk models
"Let the machine learn the market regimes. Trade with statistical confidence."
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Developed by AlphaNatt | Machine Learning Trading Systems
Version: 1.0
Algorithm: Gaussian Mixture Model with E-M
Classification: Unsupervised Learning Oscillator
Not financial advice. Always DYOR.
5 EMA Close/Open Cross StrategyLong Entry - 5 EMA Close crossing above 5 EMA open
exit - 5 EMA Close crossing below 5 EMA open
Short entry - 5 EMA Close crossing below 5 EMA open
exit - 5 EMA Close crossing above 5 EMA open
FVMA + SuperTrend + top and bottom Strategy Full CustomizationFVMA + SuperTrend + top and bottom Strategy Full Customization
Stockbee Reversal Bullish v2Custom indicator for identifying stocks that meet the Stockbee's Reversal Bullish New criteria. This can be used as a standalone indicator or use it to screen for stocks in Pine Screener.
Stockbee Reversal BullishCustom indicator for identifying stocks that meet the Stockbee's Reversal Bullish criteria. This can be used as a standalone indicator or use it to screen for stocks in Pine Screener.
NQ Open Playbook (with Toggles)marks out asain,london.ny high and lows on 4h,1h,15m simple little stradGY FOER BEGINERS TO GET A FEEL FOR THE MARKET.
Pro Trend: Double BB + Chandelier + ZigZag by KidevThis indicator combines multiple powerful tools into a single overlay:
Bollinger Bands (0.5σ & 2σ): Tracks short-term and wider volatility ranges.
SMA 75: Smooth trend filter to identify medium-term direction.
Centered Chandelier Exit: Dynamic stop/trend tool based on ATR; midline highlights trend bias.
Double ZigZag with HH/LL Labels: Two independent ZigZags (configurable periods) mark pivots and identify Higher Highs / Higher Lows / Lower Highs / Lower Lows.
Quickly visualize volatility channels and trend direction.
Identify breakout vs. mean-reversion conditions.
Spot pivot structure (HH/HL vs. LH/LL) for market structure analysis.
Combine ATR-based stop levels with SMA filter for trade entries/exit
SPX Gamma Pin DetectorUnlock the power of gamma pinning in the S&P 500 (SPX) with this essential overlay indicator, designed for day traders and options enthusiasts. The SPX Gamma Pin Detector highlights key gamma strike levels where market makers and large positions create "sticky" price action, often leading to mean reversion and intraday pins. Based on advanced options flow insights (like those from SpotGamma transcripts), it plots critical support/resistance zones to help you anticipate reversals around high-gamma strikes—such as the 99th percentile levels that stabilize or propel SPX moves.
Key Features:
Visual Gamma Levels: Automatically plots the primary pin strike (e.g., 6475), upper gamma target (e.g., 6550), and lower risk-off support (e.g., 6400). These are customizable via inputs for real-time adaptation to market conditions.
Pin Alert Zone: A dynamic background highlight (yellow) activates when SPX is within 0.1% of the pin strike, signaling potential mean reversion opportunities—perfect for entering 0DTE call flies or put hedges pre-NFP or OPEX.
Buy Dip Alert: Generates TradingView alerts on crossovers above the lower tolerance (e.g., 0.5% below pin), with a message like "SPX near gamma pin - Enter fly!" to catch dip-buying flows from zero-DTE algos.
Vol Crush Filter (Beta): Includes a basic VIX threshold input (default <15) to boost signal strength during low-IV environments, where realized vol contracts and upside is cheap.
How It Works:
This Pine Script v5 indicator overlays horizontal lines and conditional backgrounds on your SPX (or ES1! futures) chart. It uses simple math tolerances to detect proximity to gamma hotspots, mimicking the "sticky gamma" dynamics from options positioning data. For example:
If SPX drifts toward the pin level post-data release (e.g., ADP/NFP), the alert fires to prompt bullish structures like the 6525/6550/6575 call fly (net debit ~$2.25 for $25 max profit).
Negative gamma voids below support warn of slippage risks, aligning with charm effects that support closes near 6465-6475.
Backtest it against historical pins (e.g., Tuesday's 6400 reversal with 5B delta buy) to see 70-80% hit rates in stable regimes. Ideal for our GrokPHDTrading day trading show—pair with transcript parses for edge in low-vol setups (VIX ~15, ATM IV 10-11%).
Usage Tips for Traders:
Setup: Add to a 1-min or 5-min SPX chart. Adjust strikes based on daily gamma maps (e.g., from SpotGamma or our tools).
Entry Signals: Alert triggers? Scale into mean-reversion plays—buy the dip if holds support, target pin for 3-5x ROI.
Risk Management: Stop below risk-off level; hedge with OTM put flies (~$0.30 debit) for tail risks like VIX spikes to 19+.
Customization: Tweak tolerances for ES or SPY equivalents (e.g., SPY 645 for SPX 6465). Add VIX plot for vol confirmation.
Training Integration: Use in our Phase 2: Setup Execution modules—simulates gamma edges for 80% win-rate drills.
Disclaimer: This indicator is for educational and informational purposes only. It draws from public options analysis but does not provide financial advice. Always backtest, use proper risk management, and consult a professional. Past performance isn't indicative of future results. Not affiliated with SpotGamma—purely inspired by their methodologies for our AI-driven trading tools at GrokPHDTrading.com.
Invite to Community: Love gamma trading? Subscribe to our show for live NFP breakdowns and affiliate links to premium flow tools. Questions? Drop in the comments or join our Discord for Pine tweaks!
LP Sweep / Reclaim & Breakout Grading: Long-onlySignals
1) LP Sweep & Reclaim (mean-reversion entry)
Compute LP bounds from prior-bar window extremes:
lpLL_prev = lowest low of the last N bars (offset 1).
lpHH_prev = highest high of the last N bars (offset 1).
Sweep long trigger: current low dips below lpLL_prev and closes back above it.
Real-time quality grading (A/B/C) for sweep:
Trend filter & slope via EMA(88).
BOS bonus: close > last confirmed swing high.
Body size vs ATR, location above a long EMA, headroom to swing high (penalty if too close), and multi-sweep count bonus.
Sum → score → grade A/B/C; A or B required for sweep entry.
2) Trend Breakout (momentum entry)
Core trigger: close > previous Donchian high (length boLen) + ATR buffer.
Optional filter: close must be above the default EMA.
Breakout grading (A/B/C) in real time combining:
Trend up (price > EMA and EMA rising),
Body/ATR, Gap above breakout level (in ATR),
Volume vs MA,
Upper-wick penalty,
Position-in-Score: headroom to last swing high (penalty if too near) + EMA slope bonus.
Sum → score → A or B required if grading enabled.
by A.Alasfoor RSI + Stochastic Alert with Doji Confirmationa buy and sell signals upon :
1- Sell : red hammer break (lower body) of 5min , ensure the wick is equal to or longer than the red body range.
2- Buy: Green hammer (upper body) break of 5min , ensure the wick is equal to or longer than the red body range.
Trigger buy/sell upon the break clean at 1min of the body closing level, risking (SL) the earlier 1 min tops/lows.
Credits to Ahmed Alasfoor & Zakariya Hamad AlJulandani by Sumou Oman
DMI + ADX + Key Level — Carlos VizcarraMi indicador personal de adx para la estrategia de Rafael Cepeda Trader
RSI + Stochastic Alert with Advanced Doji ConfirmationCredits to Ahmed Alasfoor and Somou by Zakariya Hamad AlJulandani
Custom Time Range HighlightThis indicator highlights specific time ranges on your TradingView chart with customizable background colors and labels, making it easier to identify key trading sessions and ICT (Inner Circle Trader) Killzones. It is designed for traders who want to mark important market hours, such as major sessions (Asia, New York, London) or high-volatility Killzones, with full control over activation, timing, colors, and transparency.
Features
Customizable Time Ranges: Define up to 9 different time ranges, including one custom range, three major market sessions (Asia, New York, London), and five ICT Killzones (Asia, NY Open, NY Close, London Open, London Close).
Individual Activation: Enable or disable each time range independently via checkboxes in the settings. By default, only the ICT Killzones are active.
Custom Colors and Transparency: Set unique background and label colors for each range, with adjustable transparency for both.
Labeled Time Ranges: Each active range is marked with a customizable label at the start of the period, displayed above the chart for easy identification.
Priority Handling: If multiple ranges overlap, the range with the higher number (e.g., Asia Killzone over Custom Range) determines the background color.
CET Time Zone: Time ranges are based on Central European Time (CET, Europe/Vienna). Adjust the hours and minutes to match your trading needs.
Settings
The indicator settings are organized into three groups for clarity:
Custom Range: A flexible range (default: 15:30–18:00 CET) for user-defined periods.
Session - Asia, NY, London: Major market sessions (Asia: 01:00–10:00, New York: 14:00–23:00, London: 09:00–18:00 CET).
ICT Killzones - Asia, NY, London: High-volatility periods (NY Open: 13:00–16:00, NY Close: 20:00–23:00, London Open: 08:00–11:00, London Close: 16:00–18:00, Asia: 02:00–05:00 CET).
For each range, you can:
Toggle activation (default: only ICT Killzones enabled).
Adjust start and end times (hours and minutes).
Customize the label text.
Choose background and label colors with transparency levels (0–100).
How to Use
Add the indicator to your chart.
Open the settings to enable/disable specific ranges, adjust their times, or customize colors and labels.
The chart will highlight active time ranges with the selected background colors and display labels at the start of each range.
Use it to focus on key trading periods, such as ICT Killzones for high-probability setups or major sessions for market analysis.
Notes
Ensure your time ranges align with your trading instrument’s session times.
Overlapping ranges prioritize higher-numbered ranges (e.g., Asia Killzone overrides London Session).
Ideal for day traders, scalpers, or ICT strategy followers who need clear visual cues for specific market hours.
Feedback
If you have suggestions for improvements or need help with customization, feel free to leave a comment or contact the author!
NDOG & NWOG - Liquidity + Sunday Box rroielDescription:
This script combines NDOG & NWOG liquidity levels with a Sunday Box framework to provide traders with structured levels for weekly bias, liquidity mapping, and potential entry/exit zones.
Features:
• Automatic plotting of NDOG & NWOG liquidity zones.
• Sunday Box (weekly open range) drawn to define structure and bias.
• Highlights liquidity sweeps and retests for trade confirmation.
• Configurable settings for box time, liquidity range, and display options.
• Built to support ROI/EL strategies by aligning liquidity with weekly key levels.
Use Case:
Helps traders identify where price is likely to react by combining liquidity-based zones with the Sunday box framework. Designed for clarity, confluence, and efficiency in execution.
Volume mura visionOverview
A simple, readable volume tool that highlights volume spikes relative to a moving-average baseline. Bars are color-coded:
Spike UP (price closed up)
Spike DOWN (price closed down)
Below-average volume
Near/above MA but not a spike (neutral)
Optional: plot the selected Volume MA as a line.
How it works
1. Compute a Volume MA (SMA/EMA/RMA/WMA) over Volume MA Length.
2. A spike occurs when Volume ≥ MA × (1 + Spike threshold%).
3. Bar color:
Spike + up candle → Spike UP color
Spike + down candle → Spike DOWN color
Volume < MA → Below-MA grey
Otherwise → Base grey
4. The MA line can be shown/hidden.
Inputs
Volume MA Length (len) — lookback for the volume moving average.
Spike threshold (%) over MA (thr_pct) — how far above the MA a bar must be to count as a spike.
MA Type (ma_type) — SMA / EMA / RMA / WMA for the volume baseline.
Show MA line (showMA) — toggle the MA overlay on the volume pane.
Colors
Base grey — volume near/above MA but below spike threshold.
Below-MA grey — volume below the MA.
Spike UP — spike on an up candle (close ≥ open).
Spike DOWN — spike on a down candle.
Alert
Volume spike — fires when Volume ≥ MA × (1 + threshold).
Usage tips
Lower the threshold to catch more activity; raise it to see only major bursts.
Shorter MA length reacts faster (more spikes); longer length smooths noise.
Combine with price action (breakouts, reversals) to confirm whether spikes signal participation or exhaustion.
Disclaimer
Educational tool, not financial advice. Trading involves risk.
