Hidden Markov Model [Extension] | FractalystWhat's the indicator's purpose and functionality?
The Hidden Markov Model is specifically designed to integrate with the Quantify Trading Model framework, serving as a probabilistic market regime identification system for institutional trading analysis.
Hidden Markov Models are particularly well-suited for market regime detection because they can model the unobservable (hidden) state of the market, capture probabilistic transitions between different states, and account for observable market data that each state generates.
The indicator uses Hidden Markov Model mathematics to automatically detect distinct market regimes such as low-volatility bull markets, high-volatility bear markets, or range-bound consolidation periods.
This approach provides real-time regime probabilities without requiring optimization periods that can lead to overfitting, enabling systematic trading based on genuine probabilistic market structure.
How does this extension work with the Quantify Trading Model?
The Hidden Markov Model | Fractalyst serves as a probabilistic state estimation engine for systematic market analysis.
Instead of relying on traditional technical indicators, this system automatically identifies market regimes using forward algorithm implementation with three-state probability calculation (bullish/neutral/bearish), Viterbi decoding process for determining most likely regime sequence without repainting, online parameter learning with adaptive emission probabilities based on market observations, and multi-feature analysis combining normalized returns, volatility comprehensive regime assessment.
The indicator outputs regime probabilities and confidence levels that can be used for systematic trading decisions, portfolio allocation, or risk management protocols.
Why doesn't this use optimization periods like other indicators?
The Hidden Markov Model | Fractalyst deliberately avoids optimization periods to prevent overfitting bias that destroys out-of-sample performance.
The system uses a fixed mathematical framework based on Hidden Markov Model theory rather than optimized parameters, probabilistic state estimation using forward algorithm calculations that work across all market conditions, online learning methodology with adaptive parameter updates based on real-time market observations, and regime persistence modeling using fixed transition probabilities with 70% diagonal bias for realistic regime behavior.
This approach ensures the regime detection signals remain robust across different market cycles without the performance degradation typical of over-optimized traditional indicators.
Can this extension be used independently for discretionary trading?
No, the Hidden Markov Model | Fractalyst is specifically engineered for systematic implementation within institutional trading frameworks.
The indicator is designed to provide regime filtering for systematic trading algorithms and risk management systems, enable automated backtesting through mathematical regime identification without subjective interpretation, and support institutional-level analysis when combined with systematic entry/exit models.
Using this indicator independently would miss the primary value proposition of systematic regime-based strategy optimization that institutional frameworks provide.
How do I integrate this with the Quantify Trading Model?
Integration enables institutional-grade systematic trading through advanced machine learning and statistical validation:
- Add both HMM Extension and Quantify Trading Model to your chart
- Select HMM Extension as the bias source using input.source()
- Quantify automatically uses the extension's bias signals for entry/exit analysis
- The built-in machine learning algorithms score optimal entry and exit levels based on trend intensity, and market structure patterns identified by the extension
The extension handles all bias detection complexity while Quantify focuses on optimal trade timing, position sizing, and risk management along with PineConnector automation
What markets and assets does the indicator Extension work best on?
The Hidden Markov Model | Fractalyst performs optimally on markets with sufficient price movement since the system relies on statistical analysis of returns, volatility, and momentum patterns for regime identification.
Recommended asset classes include major forex pairs (EURUSD, GBPUSD, USDJPY) with high liquidity and clear regime transitions, stock index futures (ES, NQ, YM) providing consistent regime behavior patterns, individual equities (large-cap stocks with sufficient volatility for regime detection), cryptocurrency markets (BTC, ETH with pronounced regime characteristics), and commodity futures (GC, CL showing distinct market cycles and regime transitions).
These markets provide sufficient statistical variation in returns and volatility patterns, ensuring the HMM system's mathematical framework can effectively distinguish between bullish, neutral, and bearish regime states.
Any timeframe from 15-minute to daily charts provides sufficient data points for regime calculation, with higher timeframes (4H, Daily) typically showing more stable regime identification with fewer false transitions, while lower timeframes (30m, 1H) provide more responsive regime detection but may show increased noise.
Acceptable Timeframes and Portfolio Integration:
- Any timeframe that can be evaluated within Quantify Trading Model's backtesting engine is acceptable for live trading implementation.
Legal Disclaimers and Risk Acknowledgments
Trading Risk Disclosure
The HMM Extension is provided for informational, educational, and systematic bias detection purposes only and should not be construed as financial, investment, or trading advice. The extension provides institutional analysis but does not guarantee profitable outcomes, accurate bias predictions, or positive investment returns.
Trading systems utilizing bias detection algorithms carry substantial risks including but not limited to total capital loss, incorrect bias identification, market regime changes, and adverse conditions that may invalidate analysis. The extension's performance depends on accurate data, TradingView infrastructure stability, and proper integration with Quantify Trading Model, any of which may experience data errors, technical failures, or service interruptions that could affect bias detection accuracy.
System Dependency Acknowledgment
The extension requires continuous operation of multiple interconnected systems: TradingView charts and real-time data feeds, accurate reporting from exchanges, Quantify Trading Model integration, and stable platform connectivity. Any interruption or malfunction in these systems may result in incorrect bias signals, missed transitions, or unexpected analytical behavior.
Users acknowledge that neither Fractalyst nor the creator has control over third-party data providers, exchange reporting accuracy, or TradingView platform stability, and cannot guarantee data accuracy, service availability, or analytical performance. Market microstructure changes, reporting delays, exchange outages, and technical factors may significantly affect bias detection accuracy compared to theoretical or backtested performance.
Intellectual Property Protection
The HMM Extension, including all proprietary algorithms, classification methodologies, three-state bias detection systems, and integration protocols, constitutes the exclusive intellectual property of Fractalyst. Unauthorized reproduction, reverse engineering, modification, or commercial exploitation of these proprietary technologies is strictly prohibited and may result in legal action.
Liability Limitation
By utilizing this extension, users acknowledge and agree that they assume full responsibility and liability for all trading decisions, financial outcomes, and potential losses resulting from reliance on the extension's bias detection signals. Fractalyst shall not be liable for any unfavorable outcomes, financial losses, missed opportunities, or damages resulting from the development, use, malfunction, or performance of this extension.
Past performance of bias detection accuracy, classification effectiveness, or integration with Quantify Trading Model does not guarantee future results. Trading outcomes depend on numerous factors including market regime changes, pattern evolution, institutional behavior shifts, and proper system configuration, all of which are beyond the control of Fractalyst.
User Responsibility Statement
Users are solely responsible for understanding the risks associated with algorithmic bias detection, properly configuring system parameters, maintaining appropriate risk management protocols, and regularly monitoring extension performance. Users should thoroughly validate the extension's bias signals through comprehensive backtesting before live implementation and should never base trading decisions solely on automated bias detection.
This extension is designed to provide systematic institutional flow analysis but does not replace the need for proper market understanding, risk management discipline, and comprehensive trading methodology. Users should maintain active oversight of bias detection accuracy and be prepared to implement manual overrides when market conditions invalidate analysis assumptions.
Terms of Service Acceptance
Continued use of the HMM Extension constitutes acceptance of these terms, acknowledgment of associated risks, and agreement to respect all intellectual property protections. Users assume full responsibility for compliance with applicable laws and regulations governing automated trading system usage in their jurisdiction.
การวิเคราะห์แนวโน้ม
Bitcoin Power Law Clock [LuxAlgo]The Bitcoin Power Law Clock is a unique representation of Bitcoin prices proposed by famous Bitcoin analyst and modeler Giovanni Santostasi.
It displays a clock-like figure with the Bitcoin price and average lines as spirals, as well as the 12, 3, 6, and 9 hour marks as key points in the cycle.
🔶 USAGE
Giovanni Santostasi, Ph.D., is the creator and discoverer of the Bitcoin Power Law Theory. He is passionate about Bitcoin and has 12 years of experience analyzing it and creating price models.
As we can see in the above chart, the tool is super intuitive. It displays a clock-like figure with the current Bitcoin price at 10:20 on a 12-hour scale.
This tool only works on the 1D INDEX:BTCUSD chart. The ticker and timeframe must be exact to ensure proper functionality.
According to the Bitcoin Power Law Theory, the key cycle points are marked at the extremes of the clock: 12, 3, 6, and 9 hours. According to the theory, the current Bitcoin prices are in a frenzied bull market on their way to the top of the cycle.
🔹 Enable/Disable Elements
All of the elements on the clock can be disabled. If you disable them all, only an empty space will remain.
The different charts above show various combinations. Traders can customize the tool to their needs.
🔹 Auto scale
The clock has an auto-scale feature that is enabled by default. Traders can adjust the size of the clock by disabling this feature and setting the size in the settings panel.
The image above shows different configurations of this feature.
🔶 SETTINGS
🔹 Price
Price: Enable/disable price spiral, select color, and enable/disable curved mode
Average: Enable/disable average spiral, select color, and enable/disable curved mode
🔹 Style
Auto scale: Enable/disable automatic scaling or set manual fixed scaling for the spirals
Lines width: Width of each spiral line
Text Size: Select text size for date tags and price scales
Prices: Enable/disable price scales on the x-axis
Handle: Enable/disable clock handle
Halvings: Enable/disable Halvings
Hours: Enable/disable hours and key cycle points
🔹 Time & Price Dashboard
Show Time & Price: Enable/disable time & price dashboard
Location: Dashboard location
Size: Dashboard size
HMA Swing Levels [BigBeluga]An advanced swing structure and trend-following tool built on Hull Moving Average logic, designed to detect major reversals and track dynamic support/resistance zones.
This indicator analyzes price swings using pivot highs/lows and a smoothed HMA trend baseline. It highlights key reversal levels and keeps them active until breached, giving traders a clear visual framework for price structure and trend alignment. The pivots are calculated in real-time using non-lagging logic, making them highly responsive to market conditions.
🔵 CONCEPTS
Combines a fast-reacting Hull Moving Average (HMA) with pivot logic to capture precise directional changes.
Detects non-lagging reversal highs and lows when pivot points form and the HMA direction flips.
Projects these reversal levels forward as horizontal support/resistance lines until broken by price.
Active trend is shown with a step-style trail line that reflects HMA bias over time.
🔵 FEATURES
Swing Level Detection:
Identifies high/low reversals when trend direction changes and plots horizontal zones.
Non-lagging logic of swing points detection:
if h == high and high < h and change > 0
// Detected Swing High
if l == low and low > l and change < 0
// Detected Swing Low
Persistent Support & Resistance Lines:
Each detected swing high or low is extended forward until price invalidates the level. Dotted style is applied once breached.
Color-Coded Trend Trail:
Displays a stepped trend trail using HMA slope: lime = uptrend, blue = downtrend.
Automatic Labeling:
Each reversal level is labeled with its price for clear reference.
Age-Based Line Thickness:
Every level increases in thickness every 250 bars. The longer the level lasts, the stronger it is.
🔵 HOW TO USE
Use green (support) and blue (resistance) levels to frame key reaction zones.
Trade with the trend defined by the trail color: lime for bullish bias, blue for bearish.
Explore where buy or sell orders are stacked
Look for breaks of swing lines to anticipate trend shifts or breakout setups.
Adjust the "Trend Change" input to tune the sensitivity of swing detection.
Adjust the "SwingLevels" input to define how far back to search for valid pivots.
🔵 CONCLUSION
HMA Swing Levels offers a hybrid approach to structural and trend-based trading. With automated non-lagging swing detection, persistent support/resistance tracking, and intuitive HMA-based trend coloring, it provides a powerful visual system for discretionary and systematic traders alike.
Volume Weighted Regression ChannelThis indicator constructs a volume-weighted linear regression channel over a custom time range.
It’s conceptually similar to a Volume Profile, but instead of projecting horizontal value zones, it builds a tilted trend channel that reflects both price direction and volume concentration.
🧠 Core Features:
Volume-weighted points: Each candle contributes to the regression line proportionally to its volume — heavier candles shift the channel toward high-activity price zones.
Linear regression line: Shows the trend direction within the selected time interval.
±σ boundaries: Outer bands represent the standard deviation of price (also volume-weighted), highlighting statistical dispersion.
Fully customizable: Adjustable line styles, widths, and channel width (sigma multiplier).
Time window control: Select any start and end time to define the regression interval.
📊 Why use this instead of Volume Profile?
While Volume Profile shows horizontal distributions of traded volume, this indicator is ideal when:
You want to understand how volume clusters affect trend direction, not just price levels.
You're analyzing time-dependent flow rather than static price zones.
You're looking for a dynamic volume-adjusted channel that moves with the market's structure.
It’s especially useful in identifying volume-supported trends, hidden pullback zones, and statistical extremes.
⚙️ Notes:
Works on any timeframe and instrument.
Does not repaint.
Does not require volume profile data feeds — uses standard volume and hl2.
True Market Structure [Advanced Liquidity Hunter] v1True Market Structure v1
📌 Table of Contents
1. Introduction
2. Core Concepts
3. Indicator Components
4. Configuration
5. Signal Interpretation
6. Trading Strategies
7. Risk Management
8. FAQ
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🎯 Introduction
What is True Market Structure?
True Market Structure is an advanced technical analysis indicator that reveals hidden market mechanisms. Based on Smart Money Concepts (SMC) and ICT (Inner Circle Trader) methodology, it identifies where large financial institutions hunt retail traders' stop losses.
Who is this indicator for?
• ✅ Beginners - Intuitive visualizations and clear signals
• ✅ Intermediate - Deeper market structure analysis
• ✅ Advanced - Full parameter control and advanced strategies
Key Benefits
• 🔍 Sees the invisible - Hidden liquidity levels
• 🎯 Precise signals - Based on real data
• ⚡ Real-time - Instant analysis
• 🛡️ Capital protection - Warns against traps
💡 Pro Tip: Start with 15M timeframe! That's where most action happens - stop hunts every few candles, retail traps, liquidity battles. It's the best "microscope" to understand how the market really works.
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📚 Core Concepts
Smart Money vs Retail Money
Smart Money:
• Banks, hedge funds, large institutions
• Create market moves, don't follow them
• Exploit retail predictability
Retail Money:
• Individual traders
• Often act emotionally
• Place stop losses at predictable levels
Liquidity
Liquidity refers to areas where many orders are waiting:
• Stop losses above highs (shorts)
• Stop losses below lows (longs)
• Orders at round numbers
Key principle: Smart Money needs liquidity to enter/exit large positions. That's why they "hunt" stop losses first, then make the real move.
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🔧 Indicator Components
1. 💧 Liquidity Pools
What is it?
• Price levels tested multiple times
• Stop loss accumulation areas
• Displayed as blue horizontal lines
How to read?
• LIQ HIGH x15 = Level tested 15 times from above
• LIQ LOW x8 = Level tested 8 times from below
• Higher number = stronger zone
Significance:
• Price magnet
• High probability of reaction
• Smart Money target
2. 🎣 Stop Hunts
What is it?
• Candles with long wicks
• Brief penetrations of important levels
• Marked with purple labels
Types:
• STOP HUNT ⬆ - Upward hunt (shorts' stop losses)
• STOP HUNT ⬇ - Downward hunt (longs' stop losses)
Characteristics:
• Long wick (minimum 2x larger than body)
• Wick must also be larger than 0.5 ATR (default)
• Breaks recent high/low from lookback period
• Quick price return
3. 🪤 Trapped Traders
What is it?
• Areas where retail got trapped
• Failed breakouts that didn't hold
• Colored rectangles on chart
Trap types:
• 🔴 TRAPPED LONGS - Buyers caught at top
• 🟢 TRAPPED SHORTS - Sellers caught at bottom
Mechanism:
1. Important level break
2. Retail enters breakout direction
3. Price returns leaving them at loss
4. Stop losses get activated
4. 🎪 Inducement Levels
What is it?
• "Too obvious" support/resistance
• Levels respected minimum 3 times
• Orange dashed lines
Why is it a trap?
• Look like perfect trading spots
• Attract retail traders' attention
• Smart Money uses them to collect liquidity
Example:
• 100,000 level on BTC - round number
• 3 bounces = "strong support"
• Retail buys, Smart Money sells to them
5. ⏰ Kill Zones
What is it?
• Highest Smart Money activity periods
• Red background on chart
• Maximum manipulation time
Default Kill Zones:
• 🌆 London Open (08:00-09:00 UTC)
• 🏙️ NY Open (13:00-14:00 UTC)
• 🌃 Midnight (00:00-01:00 UTC)
Trading Sessions (chart background):
• 🌏 Asian (00:00-08:00 UTC) - Gray background
• 🇬🇧 London (08:00-16:00 UTC) - Blue background
• 🇺🇸 New York (13:00-21:00 UTC) - Orange background
Note: London and New York sessions overlap (13:00-16:00 UTC) - this is the highest liquidity period!
6. 🎯 Smart Money Signals
What is it?
• Potential institutional entry points
• Large labels with 🎯 emoji
• Appear after stop hunts
Conditions:
1. Stop hunt in one direction
2. High volume (2x average)
3. In Kill Zone
4. Direction reversal
7. 📊 Market Analysis Table
The table displays 9 rows with key information:
1. Session - Current trading session (ASIA/LONDON/NEW YORK/CLOSED)
2. Kill Zone - Zone status (🔴 ACTIVE / ✅ SAFE)
3. Liquidity Pools - Number of liquidity zones found
4. Inducement Levels - Number of bait levels
5. Traps (50 bars) - Number of traps in last 50 bars
6. Market Bias - Market direction:
o BULLISH 📈 (close > SMA50 and EMA21)
o BEARISH 📉 (close < SMA50 and EMA21)
o NEUTRAL ➡️ (other cases)
7. Volume - Volume status:
o 🔥 EXTREME (>2x average)
o ⬆️ HIGH (>1.5x average)
o NORMAL (>average)
o ⬇️ LOW (3 traps)
o ⚠️ CHOPPY (>5 traps)
o 👀 WATCH LIQUIDITY (>3 liquidity zones)
o ✓ NORMAL (other)
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⚙️ Configuration
Step 1: Basic Configuration
Where to find settings:
• Method 1: Click the ⚙️ (gear) icon next to indicator name on chart
• Method 2: Double-click any indicator line/label
• Method 3: Right-click → "Settings" on indicator name
🌍 Timezone Setting
UTC Offset: Your timezone
Examples:
- London: 0 (winter) or +1 (summer)
- New York: -5 (winter) or -4 (summer)
- Tokyo: +9
🎚️ Sensitivity Adjustment
For beginners - Default settings:
• Lookback Period: 30
• Detection Sensitivity: 0.3
• Min. Touches: 2
For different timeframes:
• 15M: Sensitivity 0.2-0.3, Lookback 20-30
• 1H: Sensitivity 0.3-0.4, Lookback 30-40
• 4H: Sensitivity 0.4-0.5, Lookback 40-50
For different instruments:
• Forex Majors (EUR/USD): Sensitivity 0.1-0.2
• Indices (S&P500;): Sensitivity 0.2-0.4
• Crypto (BTC): Sensitivity 0.4-0.8
• Stocks: Sensitivity 0.3-0.5
Step 2: Advanced Configuration
🔧 Liquidity Zones Parameters
• Min. Touches (1-5): Less = more signals
• Lookback (20-200): More = further levels
• Max Zones (1-10): Display quantity control
🎣 Stop Hunt Parameters
• Wick/Body Ratio (1-5): Lower = more signals
• Min. Wick Size (0.1-2 ATR): Filters small wicks
🎯 Smart Money Analysis
• Require Kill Zone: Enable for fewer signals
• Volume Multiplier: Higher = only big moves
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📖 Signal Interpretation
Note: Most examples are shown on 15M timeframe, because that's where you can best see all market manipulations in action!
Signal Importance Hierarchy
1. 🎯 Smart Money Signal - Strongest signal
2. 🪤 Trapped Traders - High reliability
3. 🎣 Stop Hunt - Medium reliability
4. 💧 Liquidity Touch - Needs confirmation
Interpretation Examples
Scenario 1: "Liquidity Grab"
You see: LIQ HIGH x20 at 100,000
+ Stop Hunt ⬆
+ Volume spike
= Likely decline
Scenario 2: "Trap and Reverse"
You see: TRAPPED LONGS
+ Kill Zone Active
+ SM SHORT 🎯
= Strong short signal
Scenario 3: "Inducement Break"
You see: Inducement Level break
+ No volume
+ Status: NORMAL
= Likely trap, wait
Colors and Their Meaning
• 🔵 Blue - Liquidity (neutral)
• 🟠 Orange - Caution, possible trap
• 🔴 Red - Negative signal / long trap
• 🟢 Green - Positive signal / short trap
• 🟣 Purple - Stop hunt (neutral, wait for reaction)
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💡 Trading Strategies
Strategy 1: "Liquidity Sweep" (For Beginners)
Assumptions:
• Trade only with trend
• Wait for liquidity collection
• Enter on return
Best timeframe for learning: 15M - you'll see all manipulation stages in real-time!
Steps:
1. Identify trend (Market Bias in table)
2. Find nearest liquidity zone aligned with trend
3. Wait for price to touch and bounce
4. Enter after confirming candle
5. Stop loss beyond liquidity zone
6. Take profit at next zone
Example:
• Trend: BULLISH
• Liquidity at 100,000 (support)
• Price drops to 99,950 (stop hunt)
• Returns above 100,000
• LONG with SL 99,900, TP 101,000
Strategy 2: "Kill Zone Hunter" (Intermediate)
Assumptions:
• Trade only in Kill Zones
• Exploit stop hunts
• Aggressive entries
Ideal timeframe: 15M - in Kill Zones on 15M you'll see exactly every Smart Money move!
Steps:
1. Wait for Kill Zone (red background)
2. Watch first 15-30 minutes
3. Look for stop hunt
4. Enter immediately after stop hunt
5. Tight stop loss (0.5 ATR)
6. Scale position with profit
Tips:
• London Open - often stop hunt down, then rise
• NY Open - often tests Asian High/Low
• Midnight - position resets, false moves
Strategy 3: "Smart Money Follow" (Advanced)
Assumptions:
• Ignore minor signals
• Wait only for SM signals
• Larger positions, fewer trades
Steps:
1. Status must show HIGH RISK or WATCH LIQUIDITY
2. Wait for stop hunt series (minimum 2)
3. Watch Trapped Traders
4. Enter only on SM signal 🎯
5. Stop loss beyond last extreme
6. Hold position until opposite SM signal
Position Management:
• 1/3 position at signal
• 1/3 after direction confirmation
• 1/3 after breaking last high/low
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🛡️ Risk Management
Basic Rules
1. Never place stop loss at obvious level
o Add 5-10 pips buffer
o Avoid round numbers
o Check where Liquidity Pools are
2. Reduce position in Kill Zones
o 50% of normal size
o Or wait until they end
3. Avoid trading at HIGH RISK status
o Unless experienced
o Then reverse logic - look for traps
Stop Loss - Where to Place?
❌ Bad places:
• Exactly below/above candle
• At Inducement Levels
• At round numbers
• Where Liquidity Pools visible
✅ Good places:
• Beyond last stop hunt
• Behind Trapped Traders zone
• Minimum 1.5 ATR from entry
• Where SM would lose significantly
Position Sizing
Safe position formula:
Risk per trade = 1-2% of capital
Position size = Risk / (Stop Loss in pips × Pip value)
Modifiers:
• Kill Zone active: × 0.5
• After SM signal: × 1.5
• HIGH RISK status: × 0.3
• With trend: × 1.2
________________________________________
❓ FAQ
General Questions
Q: Indicator shows nothing, what to do? A: Check in settings:
1. Reduce "Min. Touches" to 1
2. Increase "Detection Sensitivity"
3. Enable "Debug Mode" to see statistics
4. Ensure proper timeframe (15M+)
5. On 15M sometimes wait a few candles for first signal
Tip for 15M: If you don't see signals on 15M, enable Debug Mode. If it shows Liq=0, reduce "Min. Touches" to 1 and increase "Liquidity Lookback" to 100.
Q: Too many signals, I'm lost A:
1. Increase requirements (min. touches, respects)
2. Disable some components
3. Trade only strongest signals (SM 🎯)
Q: Which timeframe is best? A:
• 15M - PERFECT FOR LEARNING! Many signals, shows all manipulations, great for beginners
• 30M - Good balance, less noise than 15M
• 1H - Medium-term trading, clear setups
• 4H - Fewer signals but bigger moves, for patient traders
• 1D - Only major levels, position trading
💡 For beginners: Start with 15M! That's where you'll see how the market really works - stop hunts, traps, false breakouts. Only after understanding the mechanics, move to higher timeframes.
Technical Questions
Q: What does "x15" mean at LIQ? A: Number of level touches. Higher = stronger level.
Q: Why are Kill Zones red? A: High risk periods - most manipulation.
Q: What does Debug Mode show? A: When "Show Debug Info" is enabled, a label appears above the last candle with:
• Liq=X - number of Liquidity Pools found
• Ind=X - number of Inducement Levels found
• HighLvl=X - number of highs stored in memory
• LowLvl=X - number of lows stored in memory
This helps understand why sometimes no signals appear (e.g., when Liq=0).
Trading Questions
Q: Can I use only this indicator? A: Yes, but better combined with:
• Trend analysis
• Support/resistance
• Volume
Q: Does it work on all markets? A: Best on liquid ones:
• ✅ Major Forex pairs
• ✅ Main indices
• ✅ BTC, ETH
• ⚠️ Less liquid altcoins
• ❌ Exotic pairs, small caps
Q: How to remove indicator from chart? A:
• Method 1: Click X next to indicator name
• Method 2: Right-click on name → "Remove"
• Method 3: In indicators panel (left side) find and click trash icon
Q: Can I use multiple copies of the indicator? A: Yes! You can add the indicator multiple times with different settings (e.g., one for liquidity, another for stop hunts only).
Q: How much can I earn? A: Indicator doesn't guarantee profit. It's an analysis tool, not a trading system. Your results depend on:
• Discipline
• Risk management
• Experience
• Market conditions
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🎯 Quick Start - Checklist
Pro Tip: After adding the indicator, click the star ⭐ to add to favorites - you'll have quick access in the future!
For Beginners:
• After adding indicator, set your UTC offset in settings
• Start on 15M timeframe (where you'll see the most action!)
• Observe for a week without trading
• Learn to recognize each signal type
• Practice on 15M, then try 1H
• Start with "Liquidity Sweep" strategy
• Max 1% risk per trade
• Keep trading journal
First Steps:
1. Days 1-3: Observe and learn signals
2. Days 4-7: Mark potential entries (no trading)
3. Week 2: Demo trading with small positions
4. Week 3+: Real trading with strict risk management
________________________________________
💬 Support
• Questions & Suggestions: Comments section under the indicator
• Bug Reports: Describe issue in comments with timeframe and instrument
• Updates: Click "Follow" to receive notifications
• Examples: Regular trading idea publications with usage examples
💡 Community: Share your setups in comments - let's help each other!
________________________________________
⚖️ Disclaimer
This indicator is an educational and analytical tool. It does not constitute investment advice. Trading involves risk of capital loss. Always conduct your own analysis and apply appropriate risk management. Historical results do not guarantee future profits.
CoffeeShopCrypto Supertrend Liquidity EngineMost SuperTrend indicators use fixed ATR multipliers that ignore context—forcing traders to constantly tweak settings that rarely adapt well across timeframes or assets.
This Supertrend is a nodd to and a more completion of the work
done by Olivier Seban ( @olivierseban )
This version replaces guesswork with an adaptive factor based on prior session volatility, dynamically adjusting stops to match current conditions. It also introduces liquidity-aware zones, real-time strength histograms, and a visual control panel—making your stoploss smarter, more responsive, and aligned with how the market actually moves.
📏 The Multiplier Problem & Adaptive Factor Solution
Traditional SuperTrend indicators rely on fixed ATR multipliers—often arbitrary numbers like 1.5, 2, or 3. The issue? No logical basis ties these values to actual market conditions. What works on a 5-minute Nasdaq chart fails on a daily EUR/USD chart. Traders spend hours tweaking multipliers per asset, timeframe, or volatility phase—and still end up with stoplosses that are either too tight or too loose. Worse, the market doesn’t care about your setting—it behaves according to underlying volatility, not your parameter.
This version fixes that by automating the multiplier selection entirely. It uses a 4-zone model based on the current ATR relative to the previous session’s ATR, dynamically adjusting the SuperTrend factor to match current volatility. It eliminates guesswork, adapts to the asset and timeframe, and ensures you’re always using a context-aware stoploss—one that evolves with the market instead of fighting it.
ATR EXAMPLE
Let’s say prior session ATR = 2.00
Now suppose current ATR = 0.32
This places us in Zone 1 (Very Low Volatility)
It doesn’t imply "overbought" or "oversold" — it tells you the market is moving very little, which often means:
Lower risk | Smaller stops | Smaller opportunities (and losses)
🔁 Liquidity Zones vs. Arbitrary Pullbacks
The standard SuperTrend stop loss line often looks like price “barely misses it” before continuing its trend. Traders call this "stop hunting," but what’s really happening is liquidity collection—price pulls back into a zone rich in orders before continuing. The problem? The old SuperTrend doesn’t show this zone. It only draws the outer limit, leaving no visual cue for where entries or continuation moves might realistically originate.
This script introduces 2 levels in the Liquidity Zone. One for Support and one for Stophunts, which draw dynamically between the current price and the SuperTrend line. These levels reflect where the market is most likely to revisit before resuming the trend. By visualizing the area just above the Supertrend stop loss, you can anticipate pullbacks, spot ideal re-entries, and avoid premature exits. This bridges the gap between mechanical stoploss logic and real-world liquidity behavior.
⏳ Prior Session ATR vs. Live ATR
Using real-time ATR to determine movement potential is like driving by looking in your rearview mirror. It’s reactive, not predictive. Traders often base decisions on live ATR, unaware that today’s range is still unfolding —creating volatility mismatches between what’s calculated and what actually matters. Since ATR reflects range, calculating it mid-session gives an incomplete and misleading picture of true volatility.
Instead, this system uses the ATR from the previous session , anchoring your volatility assumptions in a fully-formed price structure . It tells you how far price moved in the last full market phase—be it London, New York, or Tokyo—giving you a more reliable gauge of expected range today. This is a smarter way to estimate how far price could move rather than how far it has moved.
The Smoothing function will take the ATR, Support, Resistance, Stophunt Levels, and the Moving Avearage and smooth them by the calculation you choose.
It will also plot a moving average on your chart against closing prices by the smoothing function you choose.
🧭 Scalping vs. Trending Modes
The market moves in at least 4 phases. Trending, Ranging, Consolidation, Distribution.
Every trader has a different style —some scalp low-volatility moves during off-hours, while others ride macro trends across days. The problem with classic SuperTrend? It treats every market condition the same. A fixed system can’t possibly provide proper stoploss spacing for both a fast scalp and a long-term swing. Traders are forced to rebuild their system every time the market changes character or the session shifts.
This version solves that with a simple toggle:
Scalping or Trend Mode . With one switch, it inverts the logic of the adaptive factor to either tighten or loosen your trailing stops. During low-liquidity hours or consolidation phases, Scalping Mode offers snug stoplosses. During expansion or clear directional bias.
Trend Mode lets the trade breathe. This is flexibility built directly into the logic—not something you have to recalibrate manually.
📉 Histogram Oscillator for Move Strength
In legacy indicators, there’s no built-in way to gauge when the move is losing power . Traders rely on price action or momentum indicators to guess if a trend is fading. But this adds clutter, lag, and often contradiction. The classic SuperTrend doesn’t offer insight into how strong or weak the current trend leg is—only whether price has crossed a line.
This version includes a Trending Liquidity Histogram —a histogram that shows whether the liquidity in the SuperTrend zone is expanding or compressing. When the bars weaken or cross toward zero, it signals liquidity exhaustion . This early warning gives you time to prep for reversals or anticipate pullbacks. It even adapts visually depending on your trading mode, showing color-coded signals for scalping vs. trending behavior. It's both a strength gauge and a trade timing tool—built into your stoploss logic.
Histogram in Scalping Mode
Histogram in Trending Mode
📊 Visual Table for Real-Time Clarity
A major issue with custom indicators is opacity —you don’t always know what settings or values are currently being used. Even worse, if your dynamic logic changes mid-trade, you may not notice unless you go digging into the code or logs. This can create confusion, especially for discretionary traders.
This SuperTrend solves it with a clean visual summary table right on your chart. It shows your current ATR value, adaptive multiplier, trailing stop level, and whether a new zone size is active. That means no surprises and no second-guessing—everything important is visible and updated in real-time.
Previous Daily OHLCPrevious Daily OHLC Indicator
Overview:
This professional TradingView indicator displays the previous day's key price levels (Open, High, Low, Close, and 50% midpoint) as horizontal lines on your chart. These levels are essential for traders who use previous day data as support and resistance zones in their technical analysis.
What It Does
Displays Previous Day Levels: Automatically shows horizontal lines for yesterday's OHLC data
Real-Time Updates: Lines update dynamically each new trading day
Fully Customizable: Complete control over which levels to display and how they appear
Smart Line Management: Choose between showing lines for recent bars or across the entire chart
Professional Labels: Clear labels with optional price values for each level
Color Coded System: Distinct colors for each level type for instant recognition
Key Features
Five Important Price Levels
Previous Day Open: Yesterday's opening price - often acts as psychological level
Previous Day High: Yesterday's highest price - key resistance level for breakout trading
Previous Day Low: Yesterday's lowest price - important support level for breakdowns
Previous Day Close: Yesterday's closing price - significant reference point
50% Midpoint: Calculated midpoint between previous day's high and low - bias indicator
Inside Bar Detector - 15min
🔍 What is an Inside Bar?
An **Inside Bar** is a candle that forms **entirely within the high and low of the previous candle**. It represents **consolidation**, **indecision**, or **potential reversal**, and is a key signal in The Strat trading method.
🔧 What the Script Does:
1. **Timeframe Restriction**:
* The script activates **only on the 15-minute timeframe**, avoiding clutter on other timeframes.
2. **Inside Bar Logic**:
* It checks whether the **current bar’s high is lower than the previous bar’s high**, **AND** the **current bar’s low is higher than the previous bar’s low**.
* If both conditions are true, it confirms an Inside Bar.
3. **Visual Display**:
* When an Inside Bar is detected, the script **plots a yellow label ("1") above the bar**.
* The label represents the Strat 1-bar and helps you easily spot potential setups.
🎯 Use Case:
* Ideal for **Strat traders**, **price action analysts**, or **any trader** looking for breakout or reversal opportunities.
* Common setups include **1-2**, **1-3**, or **double inside bar** breakouts.
Modified Fractal Open/CloseModified Fractal (Open/Close Based) - Indicator
The Modified Fractal (Open/Close Based) indicator offers a new way to detect fractal patterns on your chart by analyzing the open and close prices instead of the traditional high and low values.
🧮 How it works:
The indicator evaluates a group of 5 consecutive candles.
The central candle (2 bars ago) is analyzed.
For a Bullish Fractal:
The open or close of the central candle must be lower than the open and close of the other 4 surrounding candles.
For a Bearish Fractal:
The open or close of the central candle must be higher than the open and close of the other 4 surrounding candles.
Once a valid pattern is detected, a visual symbol (triangle) is plotted directly on the chart and an alert can be triggered.
✅ Key Features:
Non-repainting signals (evaluated after candle close)
Fully mechanical detection logic
Easy-to-use visual signals
Alert conditions ready to be integrated into TradingView’s alert system
Suitable for multiple timeframes (can be used from M1 to Daily and beyond)
🎯 Use case:
This modified fractal approach can help traders:
Spot potential swing points
Identify possible reversals
Confirm price exhaustion zones
Support breakout or mean reversion strategies
⚠ Note:
This indicator does not provide trade signals by itself. It is recommended to be combined with additional tools, price action analysis, or risk management rules.
Quantum Market Intelligence (QMI)Quantum Market Intelligence (QMI) Indicator
The Quantum Market Intelligence (QMI) is a sophisticated multi-factor technical indicator that combines four key market analysis components into a single composite score. This indicator provides traders with a comprehensive market assessment tool that adapts to changing market conditions. The QMI score oscillates between -100 and +100, offering clear visual signals through color-coded plotting and an informative dashboard display.
The indicator analyzes markets through four distinct lenses: Trend Analysis (using EMAs and volatility-adjusted momentum), Momentum Analysis (combining RSI, Stochastic, and Williams %R), Volume Analysis (incorporating volume ratios and Accumulation/Distribution), and Volatility Analysis (utilizing ATR and Bollinger Bands). These components are intelligently weighted based on detected market regimes - whether trending, volatile, or range-bound. The adaptive mode feature continuously evaluates the indicator's recent performance and adjusts sensitivity accordingly, making it responsive to evolving market dynamics.
Traders can utilize the QMI's signal system which generates four types of alerts: Strong Buy (above 70 and rising), Buy (crossing above 30), Strong Sell (below -70 and falling), and Sell (crossing below -30). The visual presentation includes triangular markers for strong signals, circular markers for regular signals, and background shading that indicates the current market regime. The information table displays real-time metrics including the QMI score, individual component scores, detected market regime, and performance ratio, providing traders with a complete analytical dashboard for informed decision-making.
Important Notice:
The use of this technical indicator does not guarantee profitable results. This indicator should not be used as a standalone analysis tool. It is essential to combine it with other forms of analysis, such as fundamental analysis, risk management strategies, and awareness of current market conditions. Always conduct thorough research.
Note: The effectiveness of any technical indicator can vary based on market conditions and individual trading styles. It's crucial to test indicators thoroughly using historical data before applying them in live trading scenarios.
Disclaimer:
Trading financial instruments involves substantial risk and may not be suitable for all investors. Past performance is not indicative of future results. This indicator is provided for informational and educational purposes only and should not be considered investment advice. Always conduct your own research before making any trading decisions.
Mark specific candle (e.g. bar 20)This Pine Script indicator, "Mark specific candle (e.g. bar 20)" (short title "Mark candle"), is a simple yet powerful tool to visually highlight a particular candle on your chart.
What it does:
It marks a specific candle (e.g., the 20th, 10th, or any number you choose) counting backwards from the most recent candle on your chart. The marked candle will be colored in a subtle light grey and also feature a tiny, matching grey arrow pointing down from above it.
Why it's useful:
This indicator helps you quickly identify and track a consistent reference point in recent price action. It's great for strategies that depend on fixed look-back periods or for simply keeping an eye on a specific historical candle's position as new data comes in.
Key Features:
Adjustable Candle Number: Easily change which candle is marked (e.g., 20th, 10th, 5th) directly from the indicator settings using the "Candle Number to Mark (from end)" input.
Clear Visuals: Both the candle color and a small arrow provide a subtle, yet effective, visual cue.
How to use:
Simply add this script to your TradingView chart. Then, open the indicator's settings to set your desired candle number.
Heatmap Trailing Stop with Breakouts (Zeiierman)█ Overview
Heatmap Trailing Stop with Breakouts (Zeiierman) is a trend and breakout detection tool that combines dynamic trailing stop logic, Fibonacci-based levels, and a real-time market heatmap into a single, intuitive system.
This indicator is designed to help traders visualize pressure zones, manage stop placement, and identify breakout opportunities supported by contextual price–derived heat. Whether you're trailing trends, detecting reversals, or entering on explosive breakouts — this tool keeps you anchored in structure and sentiment.
It projects adaptive trailing stop levels and calculates Fibonacci extensions from swing-based extremes. These levels are then colored by a market heatmap engine that tracks price interaction intensity — showing where the market is "hot" and likely to respond.
On top of that, it includes breakout signals powered by HTF momentum conditions, trend direction, and heatmap validation — giving you signals only when the context is strong.
█ How It Works
⚪ Trailing Stop Engine
At its core, the script uses an ATR-based trailing stop with trend detection:
ATR Length – Defines volatility smoothing using EMA MA of true range.
Multiplier – Expands/retracts the trailing offset depending on market aggression.
Real-Time Extremum Tracking – Uses local highs/lows to define Fibonacci anchors.
⚪ Fibonacci Projection + Heatmap
With each trend shift, Fibonacci levels are projected from the new swing to the current trailing stop. These include:
Fib 61.8, 78.6, 88.6, and 100% (trailing stop) lines
Heatmap Coloring – Each level'slevel's color is determined by how frequently price has interacted with that level in the recent range (defined by ATR).
Strength Score (1–10) – The number of touches per level is normalized and averaged to create a heatmap ""score"" displayed as a colored bar on the chart.
⚪ Breakout Signal System
This engine detects high-confidence breakout signals using a higher timeframe candle structure:
Bullish Breakout – Strong bullish candle + momentum + trend confirmation + heatmap score threshold.
Bearish Breakout – Strong bearish candle + momentum + trend confirmation + heatmap score threshold.
Cooldown Logic – Prevents signals from clustering too frequently during volatile periods.
█ How to Use
⚪ Trend Following & Trail Stops
Use the Trailing Stop line to manage positions or time entries in line with trend direction. Trailing stop flips are highlighted with dot markers.
⚪ Fibonacci Heat Zones
The projected Fibonacci levels serve as price magnets or support/resistance zones. Watch how price reacts at Fib 61.8/78.6/88.6 levels — especially when they're glowing with high heatmap scores (more glow = more historical touches = stronger significance).
⚪ Breakout Signals
Enable breakout signals when you want to trade breakouts only under strong context. Use the "Heatmap Strength Threshold" to require a minimum score (1–10).
█ Settings
Stop Distance ATR Length – ATR period for volatility smoothing
Stop Distance Multiplier – Adjusts the trailing stop'sstop's distance from price
Heatmap Range ATR Length – Defines how far back the heatmap scans for touches
Number of Heat Levels – Total levels used in the heatmap (more = finer resolution)
Minimum Touches per Level – Defines what counts as a ""hot"" level
Heatmap Strength Threshold – Minimum average heat score (1–10) required for breakouts
Timeframe – HTF source used to evaluate breakout momentum structure
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Bias Bar Coloring + Multi-Timeframe Bias Table + AlertsMulti-Timeframe Bias Bar Coloring with Alerts & Table
This indicator provides a powerful, visual way to assess price action bias across multiple timeframes—Monthly, Weekly, and Daily—while also coloring each bar based on the current chart’s bias.
Features:
Persistent Bar Coloring: Bars are colored green for bullish bias (close above previous high), red for bearish bias (close below previous low), and persist the last color if neither condition is met. This makes trend shifts and momentum easy to spot at a glance.
Bias Change Alerts: Get notified instantly when the bias flips from bullish to bearish or vice versa, helping you stay on top of potential trade setups or risk management decisions.
Multi-Timeframe Bias Table: A table anchored in the top right corner displays the current bias for the Monthly, Weekly, and Daily charts, color-coded for quick reference. This gives you a clear view of higher timeframe context while trading any chart.
Consistent Logic: The same objective bias logic is used for all timeframes, ensuring clarity and reliability in your analysis.
How to Use:
Use the bar colors for instant visual feedback on trend and momentum shifts.
Watch the top-right table to align your trades with higher timeframe bias, improving your edge and filtering out lower-probability setups.
Set alerts to be notified of bias changes, so you never miss a potential opportunity.
This tool is ideal for traders who value multi-timeframe analysis, want clear visual cues for trend direction, and appreciate having actionable alerts and context at their fingertips.
Gap Open DetectorIndicator Note: Gap Open Detector
What This Indicator Does
This indicator helps you spot significant price gaps at the start of new candles compared to the previous candle’s close. A gap means the current candle’s opening price is noticeably higher or lower than the previous candle’s closing price.
Gap Up: The new candle opens above the previous candle’s close.
Gap Down: The new candle opens below the previous candle’s close.
The indicator highlights these gaps with colored candles:
Green Candle: Gap Up detected.
Red Candle: Gap Down detected.
How to Use the Indicator:
This indicator gives Best Results on Hourly Candles:
This indicator works best on hourly charts (1-hour time frame). It is especially useful for spotting gaps at the start of the next day or after a significant break in trading.
Wait for Confirmation:
After a gap is detected at the open, wait for the candle to form. Ideally, wait for one hour (until the hourly candle is complete) to confirm the candle’s direction and strength before taking any action.
Customize Gap Size:
You can set the minimum gap size using either points or percentage:
Points: Enter the minimum number of points for a gap to be considered significant.
Percentage: Enter the minimum percentage change for a gap to be considered significant.
This flexibility allows you to adjust the indicator to suit different markets and volatility levels.
Trading Logic
If there is a Gap Up and the one hour candle is green:
Buy Option: Consider initiating a buy (long) position.
If there is a Gap Up but the one hour candle is red:
Sell Option: Consider initiating a sell (short) position.
If there is a Gap Down and the one hour closing candle is red:
Sell Option: Consider initiating a sell (short) position.
If there is a Gap Down but the one hour candle is green:
Buy Option: Consider initiating a buy (long) position.
Important Tips
1. Patience Pays: Always wait for the hourly candle to close before making any trading decisions based on the gap.
2. Next Day Open: This strategy is especially effective for catching gaps at the start of a new trading day or after a market break.
3. Visual Cues: The indicator gives you a simple visual cue to spot potential trading opportunities.
4. Flexible Settings: Set your preferred gap size in points or percentage to match your trading style.
Volume Weighted Average Price Dynamic Slope [sgbpulse]VWAP Dynamic Slope: A Comprehensive Indicator for Trend Identification and Smart Trading
Introducing VWAP Dynamic Slope, an innovative TradingView indicator that harnesses the power of Volume Weighted Average Price (VWAP) and enhances it with immediate visual feedback. The indicator colors the VWAP line based on its slope, allowing you to quickly and easily identify the direction and strength of the current trend for the asset, providing advanced tools for in-depth analysis.
What is VWAP and Why is it so Important?
VWAP (Volume Weighted Average Price) is an indicator that represents the average price at which an asset has traded, weighted by the volume traded at each price level. Unlike a simple moving average, VWAP gives greater weight to trades executed with high volume, making it a reliable measure of the asset's "true" or "fair" price within a given period. Many institutional traders use VWAP as a central reference point for evaluating the effectiveness of entries and exits. An asset trading above its VWAP is considered to have bullish momentum, and below it – bearish momentum.
How it Works: Dynamic VWAP Slope Analysis
VWAP Dynamic Slope analyzes the inclination of the VWAP line and displays it using an intuitive color scheme:
Positive Slope (Uptrend): When the VWAP points upwards, signaling positive momentum, the default color will be green.
Negative Slope (Downtrend): When the VWAP points downwards, signaling negative momentum, the default color will be orange.
Trend Change (CHG): When a change in the VWAP's trend direction occurs, a "CHG" label will be displayed. The label's color will be green if the change is to an uptrend, and orange if the change is to a downtrend.
Identifying Steep Slopes for Increased Momentum:
The indicator's uniqueness lies in its ability to identify "steep" slopes – rapid and particularly strong changes in the VWAP's direction. This indicates exceptionally strong momentum:
Steep Positive Slope: The VWAP color will change to dark green, indicating significant buying pressure.
Steep Negative Slope: The VWAP color will change to dark red, indicating significant selling pressure.
Dynamic Momentum Strength Label: In situations of steep slope (positive or negative), a dynamic label will be displayed with the change value of the VWAP at that point. This label allows you to monitor momentum strength, intensification, or weakening in real-time.
Advanced Analytical Tools for Complete Control
VWAP Dynamic Slope provides you with unprecedented flexibility through a variety of customizable tools:
Multiple VWAP Anchors and Visual Marking:
Common Time Anchors: Choose whether the VWAP resets at the beginning of each Session (daily), Week, Month, Quarter, Year, Decade, or Century.
Advanced Intraday Anchors: Within the Session, you can choose to calculate VWAP specifically for Pre-Market, Regular Hours, and Post-Market hours. This option is particularly crucial for intraday traders.
Important Event Anchors: The indicator allows for VWAP resets at significant milestones such as Earnings, Dividends, and Splits, for analyzing the market's immediate reaction.
Visual Anchor Marking: To enhance clarity and orientation, a Label ⚓ can be displayed at each selected anchor point, helping to immediately identify the start point of the VWAP calculation in the chosen context.
Customizable Bands (Up to Three on Each Side):
Add up to three Bands above and below the VWAP to identify areas of deviation and excursion from the average price. You have two calculation options:
Standard Deviation: Based on volatility and statistical distance from the VWAP.
Percentage: Defines fixed percentage-based bands from the VWAP.
Key Pre-Market Levels (Pre-Market High/Low):
Display the Pre-Market High and Low levels as separate lines on the chart. These lines often serve as important psychological support and resistance zones, allowing you to see how the VWAP behaves near them.
Full Customization and Precise Control:
VWAP Source Selection: Determine which price data type will be used for the VWAP calculation. The default is HLC3 (average of High, Low, and Close), but any other relevant data source available in TradingView can be selected.
Offset: Set an offset for the VWAP line, allowing you to shift it left or right on the time axis by a chosen number of bars.
Customizable Colors: Choose your preferred colors for each slope state, Pre-Market High/Low lines, and Bands.
Setting the "Steepness" Threshold (Per-mille Price Change Per Minute ‱/min with Auto-Adjustment): Determine the sensitivity for identifying a steep slope by setting the required change threshold in VWAP in terms of per-mille price change per minute (‱/min). The indicator performs smart adjustment for any timeframe you select on the chart (e.g., 30 seconds, 1 minute, 5 minutes, 10 minutes, etc.), ensuring that the "steepness" setting maintains consistency and relevance.
Examples for Setting the Steepness Threshold:
Suppose you set the steepness threshold to 0.3‱/min (per-mille price change per minute).
On a 30-second chart: The indicator will check if the VWAP changed by 0.15 ‱/min (half of the per-minute threshold) within a single bar. If so, the slope will be considered steep. Explanation: Since 30 seconds is half a minute, the indicator looks for a change that is half of the threshold set for a full minute.
On a 1-minute chart: The indicator will check if the VWAP changed by 0.3 ‱/min (the full per-minute threshold) within a single bar. If so, the slope will be considered steep. Explanation: Here, the bar represents a full minute, so we check the full threshold.
On a 5-minute chart: The indicator will check if the VWAP changed by 1.5 ‱/min (5 times the per-minute threshold) within a single bar. If so, the slope will be considered steep. Explanation: A 5-minute bar contains 5 minutes, so the cumulative change in VWAP needs to be 5 times greater to be considered "steep" on the same scale.
In summary, this setting allows you to precisely and uniformly control the sensitivity of steep slope detection across all timeframes, providing immense flexibility in analyzing the asset's momentum.
Advantages of Using Per-mille Price Change Per Minute (‱/min)
Using per-mille price change per minute (‱/min) offers several key advantages for your indicator:
Normalized and Objective Measurement: It provides a uniform scale for the VWAP's rate of change, regardless of the asset's price or nominal value. A 0.1 per-mille change per minute always carries the same relative significance.
Comparison Across Different Asset Prices: Using per-mille allows for direct comparison of VWAP movement strength between assets trading at very different prices (e.g., a $100 asset versus a $1 asset), enabling an understanding of true momentum without bias from the nominal price.
Smart Timeframe Agnostic Adjustment: This is a critical capability. The indicator automatically adjusts the per-mille per minute threshold you set to any chart timeframe (30 seconds, 1 minute, 5 minutes, etc.), maintaining consistency in "steepness" detection without manual recalibration.
Precise Momentum Identification: This measurement precisely identifies when the VWAP's rate of change becomes significant, and when momentum strengthens or weakens, contributing to more informed trading decisions.
In short, per-mille change per minute (‱/min) provides accuracy, consistency, and flexibility in identifying VWAP momentum changes, with smart adaptation across all timeframes.
Who is this Indicator For?
VWAP Dynamic Slope is a powerful tool for:
Intraday Traders: For quick identification of intraday trend directions and momentum across any timeframe, with specific consideration for Pre-Market, Regular Hours, or Post-Market VWAP, and incorporating key pre-market levels.
Swing Traders and Long-Term Investors: For analyzing longer-term trends based on periodic and event-driven VWAP anchors.
Beginner Traders: As an excellent visual aid for understanding the relationship between price, volume, and trend direction, and how different anchor points, pre-market levels, and data sources influence price behavior.
Experienced Traders: For integration with existing strategies, gaining additional confirmation for trend strength identification, and highly precise and flexible parameter calibration.
VWAP Dynamic Slope provides a rich, multi-dimensional layer of information about the VWAP, helping you make more informed trading decisions in real-time, within the context of your chosen asset.
Bear Market Defender [QuantraSystems]Bear Market Defender
A system to short Altcoins when BTC is ranging or falling - benefit from Altcoin bleed or collapse .
QuantraSystems guarantees that the information created and published within this document and on the TradingView platform is fully compliant with applicable regulations, does not constitute investment advice, and is not exclusively intended for qualified investors.
Important Note!
The system equity curve presented here has been generated as part of the process of testing and verifying the methodology behind this script.
Crucially, it was developed after the system was conceptualized, designed, and created, which helps to mitigate the risk of overfitting to historical data. In other words, the system was built for robustness, not for simply optimizing past performance.
This ensures that the system is less likely to degrade in performance over time, compared to hyper-optimized systems that are tailored to past data. No tweaks or optimizations were made to this system post-backtest.
Even More Important Note!!
The nature of markets is that they change quickly and unpredictably. Past performance does not guarantee future results - this is a fundamental rule in trading and investing.
While this system is designed with broad, flexible conditions to adapt quickly to a range of market environments, it is essential to understand that no assumptions should be made about future returns based on historical data. Markets are inherently uncertain, and this system - like all trading systems - cannot predict future outcomes.
INTRODUCTION TO THE STAR FRAMEWORK
The STAR Framework – an abbreviation for Strategic Trading with Adaptive Risk - is a bespoke portfolio-level infrastructure for dynamic, multi-asset crypto trading systems. It combines systematic position management, adaptive sizing, and “intra-system” diversification, all built on a rigorous foundation of Risk-based position sizing .
At its core, STAR is designed to facilitate:
Adaptive position sizing based on user-defined maximum portfolio risk
Capital allocation across multiple assets with dynamic weight adjustment
Execution-aware trading with robust fee and slippage adjustment
Realistic equity curve logic based on a compounding realized PnL and additive unrealized PnL
The STAR Framework is intended for use as both a standalone portfolio system or preferred as a modular component within a broader trading “global portfolio” - delivering a balance of robustness and scalability across strategy types, timeframes, and market regimes.
RISK ALLOCATION VIA "R" CALCULATIONS
The foundational concept behind STAR is the use of the R unit - a dynamic representation of risk per trade. R is defined by the distance between a trade's entry and its stoploss, making it an intuitive and universally adaptive sizing unit across any token, timeframe, or market.
Example: Suppose the entry price is $100, and the stoploss is $95. A $5 move against the position represents a 1R loss. A 15% price increase to $115 would equal a +3R gain.
This makes R-based systems highly flexible: the user defines the percentage of capital that is put at risk per R and all positions are scaled accordingly - whether the token is volatile, illiquid, or slow-moving.
R is an advantageous method for determine position sizing - instead of being tied to complex value at risk mechanisms with having layered exit criteria, or continuous volatility-based sizing criteria that need to be adjusted while in an open trade, R allows for very straightforward sizing, invalidation and especially risk control – which is the most fundamental.
REALIZED BALANCE, FEES & SLIPPAGE ACCOUNTING
All position sizing, risk metrics, and the base equity curve within STAR are calculated based on realized balance only .
This means:
No sizing adjustments are made based on unrealized profit and loss ✅
No active positions are included in the system's realized equity until fully closed ✅
Every trade is sized precisely according to current locked-in realized portfolio balance ✅
This creates the safest risk profile - especially when multiple trades are open. Unrealized gains are not used to inflate sizing, ensuring margin safety across all assets.
All calculations also incorporate slippage and fees, based on user-defined estimates – which can and should be based upon user-collected data - and updated frequently forwards in time. These are not cosmetic, or simply applied to the final equity curve - they are fully integrated into the dynamic position sizing and equity performance , ensuring:
Stoploss hits result in exactly a −1R loss, even after slippage and fees ✅
Winners are discounted based on realistic execution costs ✅
No trade is oversized due to unaccounted execution costs ✅
Example - Slippage in R Units:
Let R be defined as the distance from entry to stoploss.
Suppose that distance is $1, and the trade is closed at a win of +$2.
If execution slippage leads to a 50 cent worse entry and a 50 cent worse exit, you’ve lost $1 extra - which is an additional 1R in execution slippage. This makes the effective return 1.0R instead of the intended 2.0R.
This is equivalent to a slippage value of 50%.
Thus, slippage in STAR is tracked and modelled on an R-adjusted basis , enabling more accurate long-term performance modelling.
MULTI-ASSET, LONG/SHORT SUPPORT
STAR supports concurrent long and short positions across multiple tokens. This can sometimes result in partially hedged exposure - for example, being long one asset and short another.
This structure has key benefits:
Diversifies idiosyncratic risk by distributing exposure across multiple tokens
Allows simultaneous exploitation of relative strength and weakness
Reduces portfolio volatility via natural hedging during reduced trending periods
Even in a highly correlated market like crypto, short-term momentum behaviour often varies between tokens - making diversified, multi-directional exposure a strategic advantage .
EQUITY CURVE
The STAR framework only updates the underlying realized equity when a position is closed, and the trade outcome is known. This approach ensures:
True representation of actual capital available for trading
No exposure distortion due to unrealized gains
Risk remains tightly linked to realized results
This trade-to-trade basis for realized equity modelling eliminates the common pitfall of overallocation based on unrealized profits.
The visual equity curve represents an accurate visualization of the Total Equity however, which is equivalent to what would be the realized equity if all trades were closed on the prior bar close.
TIMEFRAME CONSIDERATIONS
Lower timeframes typically yield better performance for STAR due to:
Greater data density per day - more observations = better statistical inference
Faster compounding - more trades per week = faster capital rotation
However, lower timeframes also suffer from increased slippage and fees. STAR's execution-aware structure helps mitigate this, but users must still choose timeframes appropriate to their liquidity, costs, and operational availability.
INPUT OPTIONS
Fees (direct trading costs - the percentage of capital removed from the initial position size)
Slippage (execution delay, as a percentage. In practice, the fill price is often worse than the signal price. This directly affects R and hence position sizing)
Risk % ( Please note : this is the risk level if every position is opened at once. 5% risk for 5 assets is 1% risk per position)
System Start date
Float Precision value of displayed numbers
Table visualization - positioning and table sizes
Adjustable color options
VISUAL SIMPLICITY
To avoid usual unnecessary complexity and empower fast at-a-glance action taking, as well as enable mobile compatibility, only the most relevant information is presented.
This includes all information required to open positions in one table.
As well as a quick and straightforward overview for the system stats
Lastly, there is an optional table that can be enabled
displaying more detailed information if desired:
USAGE GUIDELINES
To use STAR effectively:
Input your average slippage and fees %
Input your maximum portfolio risk % (this controls overall leverage and is equivalent to the maximum loss that the allocation to STAR would bring if ALL positions are allocated AND hit their stop loss at the same time)
Wait for signal alerts with entry, stop, and size details
STAR will dynamically calculate sizing, risk exposure, and portfolio allocation on your behalf. Position multipliers, stop placement, and asset-specific risk are all embedded in the system logic.
Note: Leverage must be manually set to ISOLATED on your exchange platform to prevent unwanted position linking.
ABOUT THE BEAR MARKET DEFENDER STRATEGY
The first strategy to launch on the STAR Framework is the BEAR MARKET DEFENDER (BMD) - a fast-acting, trend following system based upon the Trend Titan NEUTRONSTAR. For the details of the logic behind NEUTRONSTAR, please refer to the methodology and trend aggregation section of the following indicator:
The BMD ’s short side exit calculation methodology is slightly improved compared to NEUTRONSTAR, to capture downtrends more consistently and also cut positions faster – which is crucial when considering general jump risk in the Crypto space.
Accordingly, the only focus of the BMD is to capture trends to the short side, providing the benefit of being in a spectrum from no correlation to being negatively correlated in risk and return behavior to classical Crypto long exposure.
More precisely, Crypto behavior showcases that when Bitcoin is in a ranging/mean reverting environment, most tokens that don’t fall into the “Blue-Chip” category tend to find themselves in a trend towards 0.
Typically during this period most Crypto portfolios suffer heavily due to a “Crypto-long” biased exposure.
The Bear Market Defender thrives in these chaotic, high volatility markets where most coins trend towards zero while the traditional Crypto long exposure is either flat or in a drawdown, therefore the BMD adds a source of uncorrelated risk and returns to hedge typical long exposure and bolster portfolio volatility.
Because of the BMD's short-only exposure, it will often suffer small losses during strong uptrends. During these periods, long exposure performs the best and the goal is to outperform the temporary underperformance in the BMD .
To take advantage of the abovementioned behavior of most tokens trending to zero, assets traded in the BMD are systematically updated on a quarterly basis with available liquidity being an important consideration for the tokens to be eligible for selection.
FINAL SUMMARY
The STAR Framework represents a new generation of portfolio grade trading infrastructure, built around disciplined execution, realized equity, and adaptive position sizing. It is designed to support any number of future methodologies - beginning with BMD .
The Bear Market Defender is here to hedge out commonly long biased portfolio allocations in the Crypto market, specializing in bringing uncorrelated returns during periods of sideways price action on Bitcoin, or whole-market downturns.
Together, STAR + BMD deliver a scalable, volatility tuned system that prioritizes capital preservation, signal accuracy, and adaptive risk allocation. Whether deployed standalone or within a broader portfolio, this framework is engineered for high performance, longevity, and adaptability in the ever-evolving crypto landscape.
Timeframe LoopThe Timeframe Loop publication aims to visualize intrabar price progression in a new, different way.
🔶 CONCEPTS and USAGE
I got inspiration from the Pressure/Volume loop, which is used in Mechanical Ventilation with Critical Care patients to visualize pressure/volume evolution during inhalation/exhalation.
The main idea is that intrabar prices are visualized by a loop, going to the right during the first half and returning to the left towards its closing point. Here, the main chart timeframe (CTF) is 4 hours, and we see the movements of eight 30-minute lower timeframe (LTF) periods, highlighted by four yellow dots/lines (first 2 hours -> "Right") and four blue dots/lines (last 2 hours <- "Left"):
🔹 BTF
If "Show Lowest TF" is enabled, the LTF is split into another lower TF (BTF - "Base TF"); in this case, the 30-minute LTF is split into 10 parts of 3 minutes (BTF):
Enabling "Loop Lowest TF" will enable the BTF to react similarly to the largest loop; from halfway, it will return to its startpoint:
Here is a more detailed example:
🔹 Mini-Candles
The included option "Mini-Candles" will bring even more detail, showing the LTF as Japanese candlesticks with user-defined colors and adjustable body width; in this example, the mini-candles associated with the first half (yellow lines/dots) are green/red, while blue/fuchsia in the second half (blue lines/dots):
CTF 10 minutes, LTF 1 minute, BTF 5 seconds
One can see the detailed intrabar price progression in one glance.
CTF 5 minutes, LTF 1 minute, BTF 5 seconds
If the LTF/BTF ratio, divided by two, results in a non-integer number, the right side will be a vertical line instead of just a turning point. In that case, the smaller, most right blue loop will be situated at the right of that line.
10 minutes / 1 minute = 10 -> 10 / 2 = 5 parts
5 minutes / 1 minute = 5 -> 5 / 2 = 2.5 parts
🔶 SETTINGS
🔹 Timeframes
Lower Timeframe 1
Lower Timeframe 2
No need to worry about the order of both timeframes; BTF will be the lowest TF of the 2, LTF the highest; both have to be lower than the main chart TF (CTF); otherwise, it will result in the error: "`Lower Timeframes` should be lower than current chart timeframe".
The ratio LTF / BTF should be equal or higher than 2; otherwise, this error will show: "`Lower Timeframe` should minimally be twice the `Base (smallest) Timeframe`"
Lastly, the ratio CTF / BTF should be lower than 500; otherwise, this error will pop up: "`Current Chart timeframe` / `Lower Timeframe` should be less than 500."
I have tried to capture runtime errors as best I could. If one should be triggered (red exclamation mark next to the title), it is best to increase the lowest TF.
🔹 Options
Show Lowest TF: Show BTF progression.
Loop Lowest TF: Enabling will let the BTF line return halfway.
Show Mini-Candles
Show Steps
"Show Steps" can be useful to see how the script works, where the location of the current price is compared against the position of the left (L) and right (R) labels:
🔹 Style
Support & Resistance External/Internal & BoS [sgbpulse]Market Structure Support & Resistance External/Internal & BoS
Overview: Smart & Fast Market Structure Analysis
The Market Structure "Support & Resistance External/Internal & BoS " indicator is designed to empower your technical analysis by automatically and precisely identifying significant support and resistance levels. It achieves this by pinpointing high and low Pivot Points, plus key Pre-Market High/Low levels.
Its unique strength lies in its dynamic adaptability to any timeframe and any asset you choose. This tool analyzes the relevant market structure for the current timeframe and asset, providing you with accurate and relevant levels in real-time. The indicator maintains a clean chart and swiftly displays all support, resistance, and Pre-Market levels for any asset, saving valuable analysis time and enabling you to get a clear and quick snapshot of the market.
How the Indicator Works
The indicator identifies and displays three critical types of key levels:
External Pivots: These are more significant pivot points, indicating important reversal points across a broader range of price movement, considering the current timeframe. The indicator draws dark green support lines (for low pivots) and dark red resistance lines (for high pivots) from these points.
Internal Pivots: These are shorter-term pivot points, signifying smaller corrections or reversals within the overall structure of the current timeframe. These lines provide additional areas of interest within the ranges of the External Pivots.
Pre-Market High/Low Levels: The indicator displays the High and Low reached during pre-market hours as distinct lines on the chart. Please note: These levels will only appear when the selected timeframe is lower than one day (e.g., 1-hour, 15-minute) and provided that the "Session extended trading hours" option is enabled in your TradingView chart settings. These levels are crucial for identifying potential opening ranges and critical support/resistance areas upon regular market open, especially for intraday trading.
Break of Structure (BoS) Identification
A key feature of this indicator is its ability to identify Break of Structure (BoS). When a support or resistance line is breached, the indicator changes the line's color to gray and displays a "Break of Structure" label, indicating a potential trend change or continuation:
External BoS: When an external support/resistance line is broken, a "BoS" label in red will appear. This is a strong signal for a potential shift in the primary market structure or a strong trend continuation.
Internal BoS: When an internal support/resistance line is broken, an "iBoS" label in green will appear. This indicates a break within the existing market structure, which can be used to confirm direction or identify shorter-term entry/exit opportunities.
Full Indicator Customization
The indicator provides maximum flexibility to suit any trading style and timeframe:
Number of Lines Displayed: You can choose how many support and resistance lines you want to see on your chart. The default is 15 lines, but you can increase or decrease this number according to your needs and desired level of detail.
External Pivot Settings: Define the number of bars before and after a pivot point required for External Pivot identification.
Internal Pivot Settings: Define the number of bars before and after a pivot point required for Internal Pivot identification.
Color Customization: Full control over colors! You can change the colors of the support and resistance lines, the colors of the Pre-Market levels, and also the colors of the BoS and iBoS labels to create a visual appearance that perfectly matches your personal preferences.
This flexibility allows you to adapt the indicator to your trading style and any timeframe you operate in, without needing to manually change settings each time.
Recommended Uses
Clean Chart & Quick Analysis: The indicator displays important levels clearly, enabling quick identification of areas of interest without visual clutter on the chart. This significantly saves analysis time and allows you to make faster decisions.
Critical Levels for Any Timeframe & Asset: Get precise and adaptive support and resistance, plus essential Pre-Market levels (in relevant timeframes), for any timeframe and on any asset you choose.
Trend Direction Identification: Clear support and resistance lines help understand market structure.
Breakout Confirmation: The BoS label provides visual confirmation of key level breaches, helping to confirm potential trend changes.
Locating Entry & Exit Points: Use these levels as potential areas of interest for trades, after confirming a breakout or reversal.
Finding Stop-Loss & Take-Profit Points: Strategically place protective stops and profit targets around these support and resistance levels.
Important Note
Like any technical indicator, Market Structure "Support & Resistance External/Internal & BoS " is a supplementary tool. It's highly recommended to use it in conjunction with additional analysis methods (such as price action analysis, other indicators, and fundamental analysis) for informed trading decisions. Financial markets are dynamic, and trading always carries inherent risk.
Percent Change of Range Candles - FullPercent Change of Range Candles – Full (PCR Full)
Description:
PCR Full is a custom momentum indicator that measures the percentage price change relative to a defined range, offering traders a unique way to evaluate strength, direction, and potential reversals in price movement.
How it works:
The main value (PCR) is calculated by comparing the price change over a selected number of candles (length) to the range between the highest high and lowest low in the same period.
This percentage change is normalized and visualized with dynamic candles on the subgraph.
Reference levels at +100, +50, 0, -50, and -100 serve as key zones to indicate potential overbought/oversold conditions, continuation, or neutrality.
How to read the indicator:
1. Trend continuation:
When PCR breaks above +50 and holds, it often confirms a strong bullish move.
Similarly, values below -50 and staying low signal a bearish continuation.
2. Wick behavior (volatility insight):
Long wicks on PCR candles suggest uncertainty or failed breakout attempts.
Short or no wicks with strong body color show stable momentum and conviction.
On the chart, multiple long wicks near -50 suggest bulls are attempting to push price upward, but lack the strength — until a confirmed breakout.
3. Polarity transition (Bearish to Bullish or vice versa):
A transition from negative PCR values to above zero shows that the market is possibly turning.
Especially if PCR climbs gradually and stabilizes above zero, it indicates a developing bullish phase.
Components:
Main PCR line: Color-coded (green for rising, red for falling).
Open Average (gray line): Smooths recent PCR values, indicating balance.
High/Low adaptive bands: Adjust dynamically to PCR polarity.
PCR Candles: Visualize OHLC of PCR data for enhanced interpretation.
Suggested use cases:
Enter trend trades when PCR crosses +50 or -50 with volume or price confirmation.
Watch for reversal signs near ±100 if PCR fails to break further.
Use 0 line as a neutral zone — markets hovering near 0 are often in consolidation.
Combine with price action or oscillators like RSI/MACD for additional signals.
Customization:
The length input allows users to define the range for PCR calculations, making it adjustable to various timeframes and strategies (scalping, intraday, swing).
Bitcoin Power Law [LuxAlgo]The Bitcoin Power Law tool is a representation of Bitcoin prices first proposed by Giovanni Santostasi, Ph.D. It plots BTCUSD daily closes on a log10-log10 scale, and fits a linear regression channel to the data.
This channel helps traders visualise when the price is historically in a zone prone to tops or located within a discounted zone subject to future growth.
🔶 USAGE
Giovanni Santostasi, Ph.D. originated the Bitcoin Power-Law Theory; this implementation places it directly on a TradingView chart. The white line shows the daily closing price, while the cyan line is the best-fit regression.
A channel is constructed from the linear fit root mean squared error (RMSE), we can observe how price has repeatedly oscillated between each channel areas through every bull-bear cycle.
Excursions into the upper channel area can be followed by price surges and finishing on a top, whereas price touching the lower channel area coincides with a cycle low.
Users can change the channel areas multipliers, helping capture moves more precisely depending on the intended usage.
This tool only works on the daily BTCUSD chart. Ticker and timeframe must match exactly for the calculations to remain valid.
🔹 Linear Scale
Users can toggle on a linear scale for the time axis, in order to obtain a higher resolution of the price, (this will affect the linear regression channel fit, making it look poorer).
🔶 DETAILS
One of the advantages of the Power Law Theory proposed by Giovanni Santostasi is its ability to explain multiple behaviors of Bitcoin. We describe some key points below.
🔹 Power-Law Overview
A power law has the form y = A·xⁿ , and Bitcoin’s key variables follow this pattern across many orders of magnitude. Empirically, price rises roughly with t⁶, hash-rate with t¹² and the number of active addresses with t³.
When we plot these on log-log axes they appear as straight lines, revealing a scale-invariant system whose behaviour repeats proportionally as it grows.
🔹 Feedback-Loop Dynamics
Growth begins with new users, whose presence pushes the price higher via a Metcalfe-style square-law. A richer price pool funds more mining hardware; the Difficulty Adjustment immediately raises the hash-rate requirement, keeping profit margins razor-thin.
A higher hash rate secures the network, which in turn attracts the next wave of users. Because risk and Difficulty act as braking forces, user adoption advances as a power of three in time rather than an unchecked S-curve. This circular causality repeats without end, producing the familiar boom-and-bust cadence around the long-term power-law channel.
🔹 Scale Invariance & Predictions
Scale invariance means that enlarging the timeline in log-log space leaves the trajectory unchanged.
The same geometric proportions that described the first dollar of value can therefore extend to a projected million-dollar bitcoin, provided no catastrophic break occurs. Institutional ETF inflows supply fresh capital but do not bend the underlying slope; only a persistent deviation from the line would falsify the current model.
🔹 Implications
The theory assigns scarcity no direct role; iterative feedback and the Difficulty Adjustment are sufficient to govern Bitcoin’s expansion. Long-term valuation should focus on position within the power-law channel, while bubbles—sharp departures above trend that later revert—are expected punctuations of an otherwise steady climb.
Beyond about 2040, disruptive technological shifts could alter the parameters, but for the next order of magnitude the present slope remains the simplest, most robust guide.
Bitcoin behaves less like a traditional asset and more like a self-organising digital organism whose value, security, and adoption co-evolve according to immutable power-law rules.
🔶 SETTINGS
🔹 General
Start Calculation: Determine the start date used by the calculation, with any prior prices being ignored. (default - 15 Jul 2010)
Use Linear Scale for X-Axis: Convert the horizontal axis from log(time) to linear calendar time
🔹 Linear Regression
Show Regression Line: Enable/disable the central power-law trend line
Regression Line Color: Choose the colour of the regression line
Mult 1: Toggle line & fill, set multiplier (default +1), pick line colour and area fill colour
Mult 2: Toggle line & fill, set multiplier (default +0.5), pick line colour and area fill colour
Mult 3: Toggle line & fill, set multiplier (default -0.5), pick line colour and area fill colour
Mult 4: Toggle line & fill, set multiplier (default -1), pick line colour and area fill colour
🔹 Style
Price Line Color: Select the colour of the BTC price plot
Auto Color: Automatically choose the best contrast colour for the price line
Price Line Width: Set the thickness of the price line (1 – 5 px)
Show Halvings: Enable/disable dotted vertical lines at each Bitcoin halving
Halvings Color: Choose the colour of the halving lines
Trend Gauge [BullByte]Trend Gauge
Summary
A multi-factor trend detection indicator that aggregates EMA alignment, VWMA momentum scaling, volume spikes, ATR breakout strength, higher-timeframe confirmation, ADX-based regime filtering, and RSI pivot-divergence penalty into one normalized trend score. It also provides a confidence meter, a Δ Score momentum histogram, divergence highlights, and a compact, scalable dashboard for at-a-glance status.
________________________________________
## 1. Purpose of the Indicator
Why this was built
Traders often monitor several indicators in parallel - EMAs, volume signals, volatility breakouts, higher-timeframe trends, ADX readings, divergence alerts, etc., which can be cumbersome and sometimes contradictory. The “Trend Gauge” indicator was created to consolidate these complementary checks into a single, normalized score that reflects the prevailing market bias (bullish, bearish, or neutral) and its strength. By combining multiple inputs with an adaptive regime filter, scaling contributions by magnitude, and penalizing weakening signals (divergence), this tool aims to reduce noise, highlight genuine trend opportunities, and warn when momentum fades.
Key Design Goals
Signal Aggregation
Merged trend-following signals (EMA crossover, ATR breakout, higher-timeframe confirmation) and momentum signals (VWMA thrust, volume spikes) into a unified score that reflects directional bias more holistically.
Market Regime Awareness
Implemented an ADX-style filter to distinguish between trending and ranging markets, reducing the influence of trend signals during sideways phases to avoid false breakouts.
Magnitude-Based Scaling
Replaced binary contributions with scaled inputs: VWMA thrust and ATR breakout are weighted relative to recent averages, allowing for more nuanced score adjustments based on signal strength.
Momentum Divergence Penalty
Integrated pivot-based RSI divergence detection to slightly reduce the overall score when early signs of momentum weakening are detected, improving risk-awareness in entries.
Confidence Transparency
Added a live confidence metric that shows what percentage of enabled sub-indicators currently agree with the overall bias, making the scoring system more interpretable.
Momentum Acceleration Visualization
Plotted the change in score (Δ Score) as a histogram bar-to-bar, highlighting whether momentum is increasing, flattening, or reversing, aiding in more timely decision-making.
Compact Informational Dashboard
Presented a clean, scalable dashboard that displays each component’s status, the final score, confidence %, detected regime (Trending/Ranging), and a labeled strength gauge for quick visual assessment.
________________________________________
## 2. Why a Trader Should Use It
Main benefits and use cases
1. Unified View: Rather than juggling multiple windows or panels, this indicator delivers a single score synthesizing diverse signals.
2. Regime Filtering: In ranging markets, trend signals often generate false entries. The ADX-based regime filter automatically down-weights trend-following components, helping you avoid chasing false breakouts.
3. Nuanced Momentum & Volatility: VWMA and ATR breakout contributions are normalized by recent averages, so strong moves register strongly while smaller fluctuations are de-emphasized.
4. Early Warning of Weakening: Pivot-based RSI divergence is detected and used to slightly reduce the score when price/momentum diverges, giving a cautionary signal before a full reversal.
5. Confidence Meter: See at a glance how many sub-indicators align with the aggregated bias (e.g., “80% confidence” means 4 out of 5 components agree ). This transparency avoids black-box decisions.
6. Trend Acceleration/Deceleration View: The Δ Score histogram visualizes whether the aggregated score is rising (accelerating trend) or falling (momentum fading), supplementing the main oscillator.
7. Compact Dashboard: A corner table lists each check’s status (“Bull”, “Bear”, “Flat” or “Disabled”), plus overall Score, Confidence %, Regime, Trend Strength label, and a gauge bar. Users can scale text size (Normal, Small, Tiny) without removing elements, so the full picture remains visible even in compact layouts.
8. Customizable & Transparent: All components can be enabled/disabled and parameterized (lengths, thresholds, weights). The full Pine code is open and well-commented, letting users inspect or adapt the logic.
9. Alert-ready: Built-in alert conditions fire when the score crosses weak thresholds to bullish/bearish or returns to neutral, enabling timely notifications.
________________________________________
## 3. Component Rationale (“Why These Specific Indicators?”)
Each sub-component was chosen because it adds complementary information about trend or momentum:
1. EMA Cross
o Basic trend measure: compares a faster EMA vs. a slower EMA. Quickly reflects trend shifts but by itself can whipsaw in sideways markets.
2. VWMA Momentum
o Volume-weighted moving average change indicates momentum with volume context. By normalizing (dividing by a recent average absolute change), we capture the strength of momentum relative to recent history. This scaling prevents tiny moves from dominating and highlights genuinely strong momentum.
3. Volume Spikes
o Sudden jumps in volume combined with price movement often accompany stronger moves or reversals. A binary detection (+1 for bullish spike, -1 for bearish spike) flags high-conviction bars.
4. ATR Breakout
o Detects price breaking beyond recent highs/lows by a multiple of ATR. Measures breakout strength by how far beyond the threshold price moves relative to ATR, capped to avoid extreme outliers. This gives a volatility-contextual trend signal.
5. Higher-Timeframe EMA Alignment
o Confirms whether the shorter-term trend aligns with a higher timeframe trend. Uses request.security with lookahead_off to avoid future data. When multiple timeframes agree, confidence in direction increases.
6. ADX Regime Filter (Manual Calculation)
o Computes directional movement (+DM/–DM), smoothes via RMA, computes DI+ and DI–, then a DX and ADX-like value. If ADX ≥ threshold, market is “Trending” and trend components carry full weight; if ADX < threshold, “Ranging” mode applies a configurable weight multiplier (e.g., 0.5) to trend-based contributions, reducing false signals in sideways conditions. Volume spikes remain binary (optional behavior; can be adjusted if desired).
7. RSI Pivot-Divergence Penalty
o Uses ta.pivothigh / ta.pivotlow with a lookback to detect pivot highs/lows on price and corresponding RSI values. When price makes a higher high but RSI makes a lower high (bearish divergence), or price makes a lower low but RSI makes a higher low (bullish divergence), a divergence signal is set. Rather than flipping the trend outright, the indicator subtracts (or adds) a small penalty (configurable) from the aggregated score if it would weaken the current bias. This subtle adjustment warns of weakening momentum without overreacting to noise.
8. Confidence Meter
o Counts how many enabled components currently agree in direction with the aggregated score (i.e., component sign × score sign > 0). Displays this as a percentage. A high percentage indicates strong corroboration; a low percentage warns of mixed signals.
9. Δ Score Momentum View
o Plots the bar-to-bar change in the aggregated score (delta_score = score - score ) as a histogram. When positive, bars are drawn in green above zero; when negative, bars are drawn in red below zero. This reveals acceleration (rising Δ) or deceleration (falling Δ), supplementing the main oscillator.
10. Dashboard
• A table in the indicator pane’s top-right with 11 rows:
1. EMA Cross status
2. VWMA Momentum status
3. Volume Spike status
4. ATR Breakout status
5. Higher-Timeframe Trend status
6. Score (numeric)
7. Confidence %
8. Regime (“Trending” or “Ranging”)
9. Trend Strength label (e.g., “Weak Bullish Trend”, “Strong Bearish Trend”)
10. Gauge bar visually representing score magnitude
• All rows always present; size_opt (Normal, Small, Tiny) only changes text size via text_size, not which elements appear. This ensures full transparency.
________________________________________
## 4. What Makes This Indicator Stand Out
• Regime-Weighted Multi-Factor Score: Trend and momentum signals are adaptively weighted by market regime (trending vs. ranging) , reducing false signals.
• Magnitude Scaling: VWMA and ATR breakout contributions are normalized by recent average momentum or ATR, giving finer gradation compared to simple ±1.
• Integrated Divergence Penalty: Divergence directly adjusts the aggregated score rather than appearing as a separate subplot; this influences alerts and trend labeling in real time.
• Confidence Meter: Shows the percentage of sub-signals in agreement, providing transparency and preventing blind trust in a single metric.
• Δ Score Histogram Momentum View: A histogram highlights acceleration or deceleration of the aggregated trend score, helping detect shifts early.
• Flexible Dashboard: Always-visible component statuses and summary metrics in one place; text size scaling keeps the full picture available in cramped layouts.
• Lookahead-Safe HTF Confirmation: Uses lookahead_off so no future data is accessed from higher timeframes, avoiding repaint bias.
• Repaint Transparency: Divergence detection uses pivot functions that inherently confirm only after lookback bars; description documents this lag so users understand how and when divergence labels appear.
• Open-Source & Educational: Full, well-commented Pine v6 code is provided; users can learn from its structure: manual ADX computation, conditional plotting with series = show ? value : na, efficient use of table.new in barstate.islast, and grouped inputs with tooltips.
• Compliance-Conscious: All plots have descriptive titles; inputs use clear names; no unnamed generic “Plot” entries; manual ADX uses RMA; all request.security calls use lookahead_off. Code comments mention repaint behavior and limitations.
________________________________________
## 5. Recommended Timeframes & Tuning
• Any Timeframe: The indicator works on small (e.g., 1m) to large (daily, weekly) timeframes. However:
o On very low timeframes (<1m or tick charts), noise may produce frequent whipsaws. Consider increasing smoothing lengths, disabling certain components (e.g., volume spike if volume data noisy), or using a larger pivot lookback for divergence.
o On higher timeframes (daily, weekly), consider longer lookbacks for ATR breakout or divergence, and set Higher-Timeframe trend appropriately (e.g., 4H HTF when on 5 Min chart).
• Defaults & Experimentation: Default input values are chosen to be balanced for many liquid markets. Users should test with replay or historical analysis on their symbol/timeframe and adjust:
o ADX threshold (e.g., 20–30) based on instrument volatility.
o VWMA and ATR scaling lengths to match average volatility cycles.
o Pivot lookback for divergence: shorter for faster markets, longer for slower ones.
• Combining with Other Analysis: Use in conjunction with price action, support/resistance, candlestick patterns, order flow, or other tools as desired. The aggregated score and alerts can guide attention but should not be the sole decision-factor.
________________________________________
## 6. How Scoring and Logic Works (Step-by-Step)
1. Compute Sub-Scores
o EMA Cross: Evaluate fast EMA > slow EMA ? +1 : fast EMA < slow EMA ? -1 : 0.
o VWMA Momentum: Calculate vwma = ta.vwma(close, length), then vwma_mom = vwma - vwma . Normalize: divide by recent average absolute momentum (e.g., ta.sma(abs(vwma_mom), lookback)), clip to .
o Volume Spike: Compute vol_SMA = ta.sma(volume, len). If volume > vol_SMA * multiplier AND price moved up ≥ threshold%, assign +1; if moved down ≥ threshold%, assign -1; else 0.
o ATR Breakout: Determine recent high/low over lookback. If close > high + ATR*mult, compute distance = close - (high + ATR*mult), normalize by ATR, cap at a configured maximum. Assign positive contribution. Similarly for bearish breakout below low.
o Higher-Timeframe Trend: Use request.security(..., lookahead=barmerge.lookahead_off) to fetch HTF EMAs; assign +1 or -1 based on alignment.
2. ADX Regime Weighting
o Compute manual ADX: directional movements (+DM, –DM), smoothed via RMA, DI+ and DI–, then DX and ADX via RMA. If ADX ≥ threshold, market is considered “Trending”; otherwise “Ranging.”
o If trending, trend-based contributions (EMA, VWMA, ATR, HTF) use full weight = 1.0. If ranging, use weight = ranging_weight (e.g., 0.5) to down-weight them. Volume spike stays binary ±1 (optional to change if desired).
3. Aggregate Raw Score
o Sum weighted contributions of all enabled components. Count the number of enabled components; if zero, default count = 1 to avoid division by zero.
4. Divergence Penalty
o Detect pivot highs/lows on price and corresponding RSI values, using a lookback. When price and RSI diverge (bearish or bullish divergence), check if current raw score is in the opposing direction:
If bearish divergence (price higher high, RSI lower high) and raw score currently positive, subtract a penalty (e.g., 0.5).
If bullish divergence (price lower low, RSI higher low) and raw score currently negative, add a penalty.
o This reduces score magnitude to reflect weakening momentum, without flipping the trend outright.
5. Normalize and Smooth
o Normalized score = (raw_score / number_of_enabled_components) * 100. This yields a roughly range.
o Optional EMA smoothing of this normalized score to reduce noise.
6. Interpretation
o Sign: >0 = net bullish bias; <0 = net bearish bias; near zero = neutral.
o Magnitude Zones: Compare |score| to thresholds (Weak, Medium, Strong) to label trend strength (e.g., “Weak Bullish Trend”, “Medium Bearish Trend”, “Strong Bullish Trend”).
o Δ Score Histogram: The histogram bars from zero show change from previous bar’s score; positive bars indicate acceleration, negative bars indicate deceleration.
o Confidence: Percentage of sub-indicators aligned with the score’s sign.
o Regime: Indicates whether trend-based signals are fully weighted or down-weighted.
________________________________________
## 7. Oscillator Plot & Visualization: How to Read It
Main Score Line & Area
The oscillator plots the aggregated score as a line, with colored fill: green above zero for bullish area, red below zero for bearish area. Horizontal reference lines at ±Weak, ±Medium, and ±Strong thresholds mark zones: crossing above +Weak suggests beginning of bullish bias, above +Medium for moderate strength, above +Strong for strong trend; similarly for bearish below negative thresholds.
Δ Score Histogram
If enabled, a histogram shows score - score . When positive, bars appear in green above zero, indicating accelerating bullish momentum; when negative, bars appear in red below zero, indicating decelerating or reversing momentum. The height of each bar reflects the magnitude of change in the aggregated score from the prior bar.
Divergence Highlight Fill
If enabled, when a pivot-based divergence is confirmed:
• Bullish Divergence : fill the area below zero down to –Weak threshold in green, signaling potential reversal from bearish to bullish.
• Bearish Divergence : fill the area above zero up to +Weak threshold in red, signaling potential reversal from bullish to bearish.
These fills appear with a lag equal to pivot lookback (the number of bars needed to confirm the pivot). They do not repaint after confirmation, but users must understand this lag.
Trend Direction Label
When score crosses above or below the Weak threshold, a small label appears near the score line reading “Bullish” or “Bearish.” If the score returns within ±Weak, the label “Neutral” appears. This helps quickly identify shifts at the moment they occur.
Dashboard Panel
In the indicator pane’s top-right, a table shows:
1. EMA Cross status: “Bull”, “Bear”, “Flat”, or “Disabled”
2. VWMA Momentum status: similarly
3. Volume Spike status: “Bull”, “Bear”, “No”, or “Disabled”
4. ATR Breakout status: “Bull”, “Bear”, “No”, or “Disabled”
5. Higher-Timeframe Trend status: “Bull”, “Bear”, “Flat”, or “Disabled”
6. Score: numeric value (rounded)
7. Confidence: e.g., “80%” (colored: green for high, amber for medium, red for low)
8. Regime: “Trending” or “Ranging” (colored accordingly)
9. Trend Strength: textual label based on magnitude (e.g., “Medium Bullish Trend”)
10. Gauge: a bar of blocks representing |score|/100
All rows remain visible at all times; changing Dashboard Size only scales text size (Normal, Small, Tiny).
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## 8. Example Usage (Illustrative Scenario)
Example: BTCUSD 5 Min
1. Setup: Add “Trend Gauge ” to your BTCUSD 5 Min chart. Defaults: EMAs (8/21), VWMA 14 with lookback 3, volume spike settings, ATR breakout 14/5, HTF = 5m (or adjust to 4H if preferred), ADX threshold 25, ranging weight 0.5, divergence RSI length 14 pivot lookback 5, penalty 0.5, smoothing length 3, thresholds Weak=20, Medium=50, Strong=80. Dashboard Size = Small.
2. Trend Onset: At some point, price breaks above recent high by ATR multiple, volume spikes upward, faster EMA crosses above slower EMA, HTF EMA also bullish, and ADX (manual) ≥ threshold → aggregated score rises above +20 (Weak threshold) into +Medium zone. Dashboard shows “Bull” for EMA, VWMA, Vol Spike, ATR, HTF; Score ~+60–+70; Confidence ~100%; Regime “Trending”; Trend Strength “Medium Bullish Trend”; Gauge ~6–7 blocks. Δ Score histogram bars are green and rising, indicating accelerating bullish momentum. Trader notes the alignment.
3. Divergence Warning: Later, price makes a slightly higher high but RSI fails to confirm (lower RSI high). Pivot lookback completes; the indicator highlights a bearish divergence fill above zero and subtracts a small penalty from the score, causing score to stall or retrace slightly. Dashboard still bullish but score dips toward +Weak. This warns the trader to tighten stops or take partial profits.
4. Trend Weakens: Score eventually crosses below +Weak back into neutral; a “Neutral” label appears, and a “Neutral Trend” alert fires if enabled. Trader exits or avoids new long entries. If score subsequently crosses below –Weak, a “Bearish” label and alert occur.
5. Customization: If the trader finds VWMA noise too frequent on this instrument, they may disable VWMA or increase lookback. If ATR breakouts are too rare, adjust ATR length or multiplier. If ADX threshold seems off, tune threshold. All these adjustments are explained in Inputs section.
6. Visualization: The screenshot shows the main score oscillator with colored areas, reference lines at ±20/50/80, Δ Score histogram bars below/above zero, divergence fill highlighting potential reversal, and the dashboard table in the top-right.
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## 9. Inputs Explanation
A concise yet clear summary of inputs helps users understand and adjust:
1. General Settings
• Theme (Dark/Light): Choose background-appropriate colors for the indicator pane.
• Dashboard Size (Normal/Small/Tiny): Scales text size only; all dashboard elements remain visible.
2. Indicator Settings
• Enable EMA Cross: Toggle on/off basic EMA alignment check.
o Fast EMA Length and Slow EMA Length: Periods for EMAs.
• Enable VWMA Momentum: Toggle VWMA momentum check.
o VWMA Length: Period for VWMA.
o VWMA Momentum Lookback: Bars to compare VWMA to measure momentum.
• Enable Volume Spike: Toggle volume spike detection.
o Volume SMA Length: Period to compute average volume.
o Volume Spike Multiplier: How many times above average volume qualifies as spike.
o Min Price Move (%): Minimum percent change in price during spike to qualify as bullish or bearish.
• Enable ATR Breakout: Toggle ATR breakout detection.
o ATR Length: Period for ATR.
o Breakout Lookback: Bars to look back for recent highs/lows.
o ATR Multiplier: Multiplier for breakout threshold.
• Enable Higher Timeframe Trend: Toggle HTF EMA alignment.
o Higher Timeframe: E.g., “5” for 5-minute when on 1-minute chart, or “60” for 5 Min when on 15m, etc. Uses lookahead_off.
• Enable ADX Regime Filter: Toggles regime-based weighting.
o ADX Length: Period for manual ADX calculation.
o ADX Threshold: Value above which market considered trending.
o Ranging Weight Multiplier: Weight applied to trend components when ADX < threshold (e.g., 0.5).
• Scale VWMA Momentum: Toggle normalization of VWMA momentum magnitude.
o VWMA Mom Scale Lookback: Period for average absolute VWMA momentum.
• Scale ATR Breakout Strength: Toggle normalization of breakout distance by ATR.
o ATR Scale Cap: Maximum multiple of ATR used for breakout strength.
• Enable Price-RSI Divergence: Toggle divergence detection.
o RSI Length for Divergence: Period for RSI.
o Pivot Lookback for Divergence: Bars on each side to identify pivot high/low.
o Divergence Penalty: Amount to subtract/add to score when divergence detected (e.g., 0.5).
3. Score Settings
• Smooth Score: Toggle EMA smoothing of normalized score.
• Score Smoothing Length: Period for smoothing EMA.
• Weak Threshold: Absolute score value under which trend is considered weak or neutral.
• Medium Threshold: Score above Weak but below Medium is moderate.
• Strong Threshold: Score above this indicates strong trend.
4. Visualization Settings
• Show Δ Score Histogram: Toggle display of the bar-to-bar change in score as a histogram. Default true.
• Show Divergence Fill: Toggle background fill highlighting confirmed divergences. Default true.
Each input has a tooltip in the code.
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## 10. Limitations, Repaint Notes, and Disclaimers
10.1. Repaint & Lag Considerations
• Pivot-Based Divergence Lag: The divergence detection uses ta.pivothigh / ta.pivotlow with a specified lookback. By design, a pivot is only confirmed after the lookback number of bars. As a result:
o Divergence labels or fills appear with a delay equal to the pivot lookback.
o Once the pivot is confirmed and the divergence is detected, the fill/label does not repaint thereafter, but you must understand and accept this lag.
o Users should not treat divergence highlights as predictive signals without additional confirmation, because they appear after the pivot has fully formed.
• Higher-Timeframe EMA Alignment: Uses request.security(..., lookahead=barmerge.lookahead_off), so no future data from the higher timeframe is used. This avoids lookahead bias and ensures signals are based only on completed higher-timeframe bars.
• No Future Data: All calculations are designed to avoid using future information. For example, manual ADX uses RMA on past data; security calls use lookahead_off.
10.2. Market & Noise Considerations
• In very choppy or low-liquidity markets, some components (e.g., volume spikes or VWMA momentum) may be noisy. Users can disable or adjust those components’ parameters.
• On extremely low timeframes, noise may dominate; consider smoothing lengths or disabling certain features.
• On very high timeframes, pivots and breakouts occur less frequently; adjust lookbacks accordingly to avoid sparse signals.
10.3. Not a Standalone Trading System
• This is an indicator, not a complete trading strategy. It provides signals and context but does not manage entries, exits, position sizing, or risk management.
• Users must combine it with their own analysis, money management, and confirmations (e.g., price patterns, support/resistance, fundamental context).
• No guarantees: past behavior does not guarantee future performance.
10.4. Disclaimers
• Educational Purposes Only: The script is provided as-is for educational and informational purposes. It does not constitute financial, investment, or trading advice.
• Use at Your Own Risk: Trading involves risk of loss. Users should thoroughly test and use proper risk management.
• No Guarantees: The author is not responsible for trading outcomes based on this indicator.
• License: Published under Mozilla Public License 2.0; code is open for viewing and modification under MPL terms.
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## 11. Alerts
• The indicator defines three alert conditions:
1. Bullish Trend: when the aggregated score crosses above the Weak threshold.
2. Bearish Trend: when the score crosses below the negative Weak threshold.
3. Neutral Trend: when the score returns within ±Weak after being outside.
Good luck
– BullByte
Supply/Demand Zones (Synthetic SMA Candles)Supply/Demand Zones (Synthetic SMA Candles)
Created by The_Forex_Steward
This indicator highlights institutional-style supply and demand zones using synthetic SMA-based candles rather than raw price data. It provides a smoother, more refined view of price action to help identify key imbalance areas where price is likely to react.
Features:
- Uses SMA-smoothed synthetic candles to detect bullish and bearish engulfing structures
- Draws demand zones after bullish breakouts and supply zones after bearish breakouts
- Zones are persistent for a customizable number of bars
- Mitigated zones can optionally be removed from the chart
- Includes alerts for breakout and mitigation events
- Optional plotting of synthetic candles over price for visual clarity
How It Works:
When a synthetic candle closes above the high of a previous bearish candle, a bullish engulfing is detected, and a demand zone is created from that bearish candle’s high and low. Conversely, when price closes below the low of a previous bullish candle, a supply zone is formed. These zones stay on the chart for the user-defined duration or until they are mitigated by price, at which point they can be removed automatically.
How to Use:
- Adjust the SMA Length to control how smooth the synthetic candles appear
- Enable or disable Show Supply Zones and Show Demand Zones as needed
- Set the Zone Duration to control how long each zone persists
- Use Delete Mitigated Zones to automatically remove zones when price returns to them
- Optionally enable Show Synthetic SMA Candles to see the candle logic used in detection
- Use the built-in alerts to stay notified of new zone creation or mitigation
Note: This tool is most effective when combined with structure or trend-based strategies for confirmation.
ADX Trend Visualizer with Dual ThresholdsADX Trend Visualizer with Dual Thresholds
A minimal, color coded ADX indicator designed to filter market conditions into weak, moderate, or strong trend phases.
Uses a dual threshold system for separating weak, moderate, and strong trend conditions.
Color coded ADX line:
Green– Strong trend (above upper threshold)
Yellow – Moderate trend (between thresholds)
Red – Weak or no trend (below lower threshold)
Two horizontal reference lines plotted at threshold levels
Optional +DI and -DI lines (Style tab)
Recommended Use:
Use on higher time frames (1h and above) as a trend filter
Combine with entry/exit signals from other indicators or strategies
Avoid possible false entries when ADX is below the weak threshold
This trend validator helps highlight strong directional moves and avoid weak market conditions
5DMA Optional HMA Entry📈 5DMA Optional HMA Entry Signal – Precision-Based Momentum Trigger
Category: Trend-Following / Reversal Timing / Entry Optimization
🔍 Overview:
The 5DMA Optional HMA Entry indicator is a refined price-action entry tool built for traders who rely on clean trend alignment and precise timing. This script identifies breakout-style entry points when price gains upward momentum relative to short-term moving averages — specifically the 5-day Simple Moving Average (5DMA) and an optional Hull Moving Average (HMA).
Whether you're swing trading stocks, scalping ETFs like UVXY or VXX, or looking for pullback recovery entries, this tool helps time your long entries with clarity and flexibility.
⚙️ Core Logic:
Primary Condition (Always On):
🔹 Close must be above the 5DMA – ensuring upward short-term momentum is confirmed.
Optional Condition (Toggled by User):
🔹 Close above the HMA – adds slope-responsive trend filtering for smoother setups. Enable or disable via checkbox.
Bonus Entry Filter (Optional):
🔹 Green Candle Wick Breakout – optional pattern logic that detects bullish momentum when the high pierces above both MAs, with a green body.
Reset Mechanism:
🔁 Signal resets only after price closes back below all active MAs (5DMA and HMA if enabled), reducing noise and avoiding repeated signals during chop.
🧠 Why This Works:
This indicator captures the kind of setups that professional traders look for:
Momentum crossovers without chasing late.
Mean reversion snapbacks that align with fresh bullish moves.
Avoids premature entries by requiring clear structure above moving averages.
Optional HMA filter allows adaptability: turn it off during choppy markets or range conditions, and on during trending environments.
🔔 Features:
✅ Adjustable HMA Length
✅ Enable/Disable HMA Filter
✅ Optional Green Wick Breakout Detection
✅ Visual “Buy” label plotted below qualifying bars
✅ Real-time Alert Conditions for automated trading or manual alerts
🎯 Use Cases:
VIX-based ETFs (e.g., UVXY, VXX): Catch early breakouts aligned with volatility spikes.
Growth Stocks: Time pullback entries during bullish runs.
Futures/Indices: Combine with macro levels for intraday scalps or swing setups.
Overlay on Trend Filters: Combine with RSI, MACD, or VWAP for confirmation.
🛠️ Recommended Settings:
For smooth setups in volatile names, use:
HMA Length: 20
Keep green wick filter ON
For fast momentum trades, disable the HMA filter to act on 5DMA alone.
⭐ Final Thoughts:
This script is built to serve both systematic traders and discretionary scalpers who want actionable signals without noise or lag. The toggleable HMA feature lets you adjust sensitivity depending on market conditions — a key edge in adapting to volatility cycles.
Perfect for those who value clean, non-repainting entries rooted in logical structure.