Smart Money Flow Index (SMFI) - Advanced SMC [PhenLabs]📊Smart Money Flow Index (SMFI)
Version: PineScript™v6
📌Description
The Smart Money Flow Index (SMFI) is an advanced Smart Money Concepts implementation that tracks institutional trading behavior through multi-dimensional analysis. This comprehensive indicator combines volume-validated Order Block detection, Fair Value Gap identification with auto-mitigation tracking, dynamic Liquidity Zone mapping, and Break of Structure/Change of Character detection into a unified system.
Unlike basic SMC indicators, SMFI employs a proprietary scoring algorithm that weighs five critical factors: Order Block strength (validated by volume), Fair Value Gap size and recency, proximity to Liquidity Zones, market structure alignment (BOS/CHoCH), and multi-timeframe confluence. This produces a Smart Money Score (0-100) where readings above 70 represent optimal institutional setup conditions.
🚀Points of Innovation
Volume-Validated Order Block Detection – Only displays Order Blocks when formation candle exceeds customizable volume multiplier (default 1.5x average), filtering weak zones and highlighting true institutional accumulation/distribution
Auto-Mitigation Tracking System – Fair Value Gaps and Order Blocks automatically update status when price mitigates them, with visual distinction between active and filled zones preventing trades on dead levels
Proprietary Smart Money Score Algorithm – Combines weighted factors (OB strength 25%, FVG proximity 20%, Liquidity 20%, Structure 20%, MTF 15%) into single 0-100 confidence rating updating in real-time
ATR-Based Adaptive Calculations – All distance measurements use 14-period Average True Range ensuring consistent function across any instrument, timeframe, or volatility regime without manual recalibration
Dynamic Age Filtering – Automatically removes liquidity levels and FVGs older than configurable thresholds preventing chart clutter while maintaining relevant levels
Multi-Timeframe Confluence Integration – Analyzes higher timeframe bias with customizable multipliers (2-10x) and incorporates HTF trend direction into Smart Money Score for institutional alignment
🔧Core Components
Order Block Engine – Detects institutional supply/demand zones using characteristic patterns (down-move-then-strong-up for bullish, up-move-then-strong-down for bearish) with minimum volume threshold validation, tracks mitigation when price closes through zones
Fair Value Gap Scanner – Identifies price imbalances where current candle's low/high leaves gap with two-candle-prior high/low, filters by minimum size percentage, monitors 50% fill for mitigation status
Liquidity Zone Mapper – Uses pivot high/low detection with configurable lookback to mark swing points where stop losses cluster, extends horizontal lines to visualize sweep targets, manages lifecycle through age-based removal
Market Structure Analyzer – Tracks pivot progression to identify trend through higher-highs/higher-lows (bullish) or lower-highs/lower-lows (bearish), detects Break of Structure and Change of Character for trend/reversal confirmation
Scoring Calculation Engine – Evaluates proximity to nearest Order Blocks using ATR-normalized distance, assesses FVG recency and distance, calculates liquidity proximity with age weighting, combines structure bias and MTF trend into smoothed final score
🔥Key Features
Customizable Display Limits – Control maximum Order Blocks (1-10), Liquidity Zones (1-10), and FVG age (10-200 bars) to maintain clean charts focused on most relevant institutional levels
Gradient Strength Visualization – All zones render with transparency-adjustable coloring where stronger/newer zones appear more solid and weaker/older zones fade progressively providing instant visual hierarchy
Educational Label System – Optional labels identify each zone type (Bullish OB, Bearish OB, Bullish FVG, Bearish FVG, BOS) with color-coded text helping traders learn SMC concepts through practical application
Real-Time Smart Money Score Dashboard – Top-right table displays current score (0-100) with color coding (green >70, yellow 30-70, red <30) plus trend arrow for at-a-glance confidence assessment
Comprehensive Alert Suite – Configurable notifications for Order Block formation, Fair Value Gap detection, Break of Structure events, Change of Character signals, and high Smart Money Score readings (>70)
Buy/Sell Signal Integration – Automatically plots triangle markers when Smart Money Score exceeds 70 with aligned market structure and fresh Order Block detection providing clear entry signals
🎨Visualization
Order Block Boxes – Shaded rectangles extend from formation bar spanning high-to-low of institutional candle, bullish zones in green, bearish in red, with customizable transparency (80-98%)
Fair Value Gap Zones – Rectangular areas marking imbalances, active FVGs display in bright colors with adjustable transparency, mitigated FVGs switch to gray preventing trades on filled zones
Liquidity Level Lines – Dashed horizontal lines extend from pivot creation points, swing highs in bearish color (short targets above), swing lows in bullish color (long targets below), opacity decreases with age
Structure Labels – "BOS" labels appear above/below price when Break of Structure confirmed, colored by direction (green bullish, red bearish), positioned at 1% beyond highs/lows for visibility
Educational Info Panel – Bottom-right table explains key terminology (OB, FVG, BOS, CHoCH) and score interpretation (>70 high probability) with semi-transparent background for readability
📖Usage Guidelines
General Settings
Show Order Blocks – Default: On, toggles visibility of institutional supply/demand zones, disable when focusing solely on FVGs or Liquidity
Show Fair Value Gaps – Default: On, controls FVG zone display including active and mitigated imbalances
Show Liquidity Zones – Default: On, manages liquidity line visibility, disable on lower timeframes to reduce clutter
Show Market Structure – Default: On, toggles BOS/CHoCH label display
Show Smart Money Score – Default: On, controls score dashboard visibility
Order Block Settings
OB Lookback Period – Default: 20, Range: 5-100, controls bars scanned for Order Block patterns, lower values detect recent activity, higher values find older blocks
Min Volume Multiplier – Default: 1.5, Range: 1.0-5.0, sets minimum volume threshold as multiple of 20-period average, higher values (2.0+) filter for strongest institutional candles
Max Order Blocks to Display – Default: 3, Range: 1-10, limits simultaneous Order Blocks shown, lower settings (1-3) maintain focus on most recent zones
Fair Value Gap Settings
Min FVG Size (%) – Default: 0.3, Range: 0.1-2.0, defines minimum gap size as percentage of close price, lower values detect micro-imbalances, higher values focus on significant gaps
Max FVG Age (bars) – Default: 50, Range: 10-200, removes FVGs older than specified bars, lower settings (10-30) for scalping, higher (100-200) for swing trading
Show FVG Mitigation – Default: On, displays filled FVGs in gray providing visual history, disable to show only active untouched imbalances
Liquidity Zone Settings
Liquidity Lookback – Default: 50, Range: 20-200, sets pivot detection period for swing highs/lows, lower values (20-50) mark shorter-term liquidity, higher (100-200) identify major swings
Max Liquidity Age (bars) – Default: 100, Range: 20-500, removes liquidity lines older than specified bars, adjust based on timeframe
Liquidity Sensitivity – Default: 0.5, Range: 0.1-1.0, controls pivot detection sensitivity, lower values mark only major swings, higher values identify minor swings
Max Liquidity Zones to Display – Default: 3, Range: 1-10, limits total liquidity levels shown maintaining chart clarity
Market Structure Settings
Pivot Length – Default: 5, Range: 3-15, defines bars to left/right for pivot validation, lower values (3-5) create sensitive structure breaks, higher (10-15) filter for major shifts
Min Structure Move (%) – Default: 1.0, Range: 0.1-5.0, sets minimum percentage move required between pivots to confirm structure change
Multi-Timeframe Settings
Enable MTF Analysis – Default: On, activates higher timeframe trend analysis incorporation into Smart Money Score
Higher Timeframe Multiplier – Default: 4, Range: 2-10, multiplies current timeframe to determine analysis timeframe (4x on 15min = 1hour)
Visual Settings
Bullish Color – Default: Green (#089981), sets color for bullish Order Blocks, FVGs, and structure elements
Bearish Color – Default: Red (#f23645), defines color for bearish elements
Neutral Color – Default: Gray (#787b86), controls color of mitigated zones and neutral elements
Show Educational Labels – Default: On, displays text labels on zones identifying type (OB, FVG, BOS), disable once familiar with patterns
Order Block Transparency – Default: 92, Range: 80-98, controls Order Block box transparency
FVG Transparency – Default: 92, Range: 80-98, sets Fair Value Gap zone transparency independently from Order Blocks
Alert Settings
Alert on Order Block Formation – Default: On, triggers notification when new volume-validated Order Block detected
Alert on FVG Formation – Default: On, sends alert when Fair Value Gap appears enabling quick response to imbalances
Alert on Break of Structure – Default: On, notifies when BOS or CHoCH confirmed
Alert on High Smart Money Score – Default: On, alerts when Smart Money Score crosses above 70 threshold indicating high-probability setup
✅Best Use Cases
Order Block Retest Entries – After Break of Structure, wait for price retrace into fresh bullish Order Block with Smart Money Score >70, enter long on zone reaction targeting next liquidity level
Fair Value Gap Retracement Trading – When price creates FVG during strong move then retraces, enter as price approaches unfilled gap expecting institutional orders to continue trend
Liquidity Sweep Reversals – Monitor price approaching swing high/low liquidity zones against prevailing Smart Money Score trend, after stop hunt sweep watch for rejection into premium Order Block/FVG
Multi-Timeframe Confluence Setups – Identify alignment when current timeframe Order Block coincides with higher timeframe FVG plus MTF analysis showing matching trend bias
Break of Structure Continuations – After BOS confirms trend direction, trade pullbacks to nearest Order Block or FVG in direction of structure break using Smart Money Score >70 as entry filter
Change of Character Reversal Plays – When CHoCH detected indicating potential reversal, look for Smart Money Score pivot with opposing Order Block formation then enter on structure confirmation
⚠️Limitations
Lagging Pivot Calculations – Pivot-based features (Liquidity Zones, Market Structure) require bars to right of pivot for confirmation, meaning these elements identify levels retrospectively with delay equal to lookback period
Whipsaw in Ranging Markets – During choppy conditions, Order Blocks fail frequently and structure breaks produce false signals as Smart Money Score fluctuates without clear institutional bias, best used in trending markets
Volume Data Dependency – Order Block volume validation requires accurate volume data which may be incomplete on Forex pairs or limited in crypto exchange feeds
Subjectivity in Scoring Weights – Proprietary 25-20-20-20-15 weighting reflects general institutional behavior but may not optimize for specific instruments or market regimes, user cannot adjust factor weights
Visual Complexity on Lower Timeframes – Sub-hour timeframes generate excessive zones creating cluttered charts, requires aggressive display limit reduction and higher minimum thresholds
No Fundamental Integration – Indicator analyzes purely technical price action and volume without incorporating economic events, news catalysts, or fundamental shifts that override technical levels
💡What Makes This Unique
Unified SMC Ecosystem – Unlike indicators displaying Order Blocks OR FVGs OR Liquidity separately, SMFI combines all three institutional concepts plus market structure into single cohesive system
Proprietary Confidence Scoring – Rather than manual setup assessment, automated Smart Money Score quantifies probability by weighting five institutional dimensions into actionable 0-100 rating
Volume-Filtered Quality – Eliminates weak Order Blocks forming without institutional volume confirmation, ensuring displayed zones represent genuine accumulation/distribution
Adaptive Lifecycle Management – Automatically updates mitigation status and removes aged zones preventing trades on dead levels through continuous validity and age monitoring
Educational Integration – Built-in tooltips, labeled zones, and reference panel make indicator functional for both learning Smart Money Concepts and executing strategies
🔬How It Works
Order Block Detection – Scans for patterns where strong directional move follows counter-move creating last down-candle before rally (bullish OB) or last up-candle before sell-off (bearish OB), validates formations only when candle exhibits volume exceeding configurable multiple (default 1.5x) of 20-bar average volume
Fair Value Gap Identification – Compares current candle’s high/low against two-candles-prior low/high to detect price imbalances, calculates gap size as percentage of close and filters micro-gaps below minimum threshold (default 0.3%), monitors whether subsequent price fills 50% triggering mitigation status
Liquidity Zone Mapping – Employs pivot detection using configurable lookback (default 50 bars) to identify swing highs/lows where retail stops cluster, extends horizontal reference lines from pivot creation and applies age-based filtering to remove stale zones
Market Structure Analysis – Tracks pivot progression using structure-specific lookback (default 5 bars) to determine trend, confirms uptrend when new pivot high exceeds previous by minimum move percentage, detects Break of Structure when price breaks recent pivot level, flags Change of Character for potential reversals
Multi-Timeframe Confluence – When enabled, requests security data from higher timeframe (current TF × HTF multiplier, default 4x), compares HTF close against HTF 20-period MA to determine bias, contributes ±50 points to score ensuring alignment with institutional positioning on superior timeframe
Smart Money Score Calculation – Evaluates Order Block component via ATR-normalized distance producing max 100-point contribution weighted at 25%, assesses FVG factor through age penalty and distance at 20% weight, calculates Liquidity proximity at 20%, incorporates structure bias (±50-100 points) at 20%, adds MTF component at 15%, applies 3-period smoothing to reduce volatility
Visual Rendering and Lifecycle – Draws Order Block boxes, Fair Value Gap rectangles with color coding (green/red active, gray mitigated), extends liquidity dashed lines with fade-by-age opacity, plots BOS labels, displays Smart Money Score dashboard, continuously updates checking mitigation conditions and removing elements exceeding age/display limits
💡Note:
The Smart Money Flow Index combines multiple Smart Money Concepts into unified institutional order flow analysis. For optimal results, use the Smart Money Score as confluence filter rather than standalone entry signal – scores above 70 indicate high-probability setups but should be combined with risk management, higher timeframe bias, and market regime understanding.
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Stochastic Enhanced [DCAUT]█ Stochastic Enhanced
📊 ORIGINALITY & INNOVATION
The Stochastic Enhanced indicator builds upon George Lane's classic momentum oscillator (developed in the late 1950s) by providing comprehensive smoothing algorithm flexibility. While traditional implementations limit users to Simple Moving Average (SMA) smoothing, this enhanced version offers 21 advanced smoothing algorithms, allowing traders to optimize the indicator's characteristics for different market conditions and trading styles.
Key Improvements:
Extended from single SMA smoothing to 21 professional-grade algorithms including adaptive filters (KAMA, FRAMA), zero-lag methods (ZLEMA, T3), and advanced digital filters (Kalman, Laguerre)
Maintains backward compatibility with traditional Stochastic calculations through SMA default setting
Unified smoothing algorithm applies to both %K and %D lines for consistent signal processing characteristics
Enhanced visual feedback with clear color distinction and background fill highlighting for intuitive signal recognition
Comprehensive alert system covering crossovers and zone entries for systematic trade management
Differentiation from Traditional Stochastic:
Traditional Stochastic indicators use fixed SMA smoothing, which introduces consistent lag regardless of market volatility. This enhanced version addresses the limitation by offering adaptive algorithms that adjust to market conditions (KAMA, FRAMA), reduce lag without sacrificing smoothness (ZLEMA, T3, HMA), or provide superior noise filtering (Kalman Filter, Laguerre filters). The flexibility helps traders balance responsiveness and stability according to their specific needs.
📐 MATHEMATICAL FOUNDATION
Core Stochastic Calculation:
The Stochastic Oscillator measures the position of the current close relative to the high-low range over a specified period:
Step 1: Raw %K Calculation
%K_raw = 100 × (Close - Lowest Low) / (Highest High - Lowest Low)
Where:
Close = Current closing price
Lowest Low = Lowest low over the %K Length period
Highest High = Highest high over the %K Length period
Result ranges from 0 (close at period low) to 100 (close at period high)
Step 2: Smoothed %K Calculation
%K = MA(%K_raw, K Smoothing Period, MA Type)
Where:
MA = Selected moving average algorithm (SMA, EMA, etc.)
K Smoothing = 1 for Fast Stochastic, 3+ for Slow Stochastic
Traditional Fast Stochastic uses %K_raw directly without smoothing
Step 3: Signal Line %D Calculation
%D = MA(%K, D Smoothing Period, MA Type)
Where:
%D acts as a signal line and moving average of %K
D Smoothing typically set to 3 periods in traditional implementations
Both %K and %D use the same MA algorithm for consistent behavior
Available Smoothing Algorithms (21 Options):
Standard Moving Averages:
SMA (Simple): Equal-weighted average, traditional default, consistent lag characteristics
EMA (Exponential): Recent price emphasis, faster response to changes, exponential decay weighting
RMA (Rolling/Wilder's): Smoothed average used in RSI, less reactive than EMA
WMA (Weighted): Linear weighting favoring recent data, moderate responsiveness
VWMA (Volume-Weighted): Incorporates volume data, reflects market participation intensity
Advanced Moving Averages:
HMA (Hull): Reduced lag with smoothness, uses weighted moving averages and square root period
ALMA (Arnaud Legoux): Gaussian distribution weighting, minimal lag with good noise reduction
LSMA (Least Squares): Linear regression based, fits trend line to data points
DEMA (Double Exponential): Reduced lag compared to EMA, uses double smoothing technique
TEMA (Triple Exponential): Further lag reduction, triple smoothing with lag compensation
ZLEMA (Zero-Lag Exponential): Lag elimination attempt using error correction, very responsive
TMA (Triangular): Double-smoothed SMA, very smooth but slower response
Adaptive & Intelligent Filters:
T3 (Tilson T3): Six-pass exponential smoothing with volume factor adjustment, excellent smoothness
FRAMA (Fractal Adaptive): Adapts to market fractal dimension, faster in trends, slower in ranges
KAMA (Kaufman Adaptive): Efficiency ratio based adaptation, responds to volatility changes
McGinley Dynamic: Self-adjusting mechanism following price more accurately, reduced whipsaws
Kalman Filter: Optimal estimation algorithm from aerospace engineering, dynamic noise filtering
Advanced Digital Filters:
Ultimate Smoother: Advanced digital filter design, superior noise rejection with minimal lag
Laguerre Filter: Time-domain filter with N-order implementation, adjustable lag characteristics
Laguerre Binomial Filter: 6-pole Laguerre filter, extremely smooth output for long-term analysis
Super Smoother: Butterworth filter implementation, removes high-frequency noise effectively
📊 COMPREHENSIVE SIGNAL ANALYSIS
Absolute Level Interpretation (%K Line):
%K Above 80: Overbought condition, price near period high, potential reversal or pullback zone, caution for new long entries
%K in 70-80 Range: Strong upward momentum, bullish trend confirmation, uptrend likely continuing
%K in 50-70 Range: Moderate bullish momentum, neutral to positive outlook, consolidation or mild uptrend
%K in 30-50 Range: Moderate bearish momentum, neutral to negative outlook, consolidation or mild downtrend
%K in 20-30 Range: Strong downward momentum, bearish trend confirmation, downtrend likely continuing
%K Below 20: Oversold condition, price near period low, potential bounce or reversal zone, caution for new short entries
Crossover Signal Analysis:
%K Crosses Above %D (Bullish Cross): Momentum shifting bullish, faster line overtakes slower signal, consider long entry especially in oversold zone, strongest when occurring below 20 level
%K Crosses Below %D (Bearish Cross): Momentum shifting bearish, faster line falls below slower signal, consider short entry especially in overbought zone, strongest when occurring above 80 level
Crossover in Midrange (40-60): Less reliable signals, often in choppy sideways markets, require additional confirmation from trend or volume analysis
Multiple Failed Crosses: Indicates ranging market or choppy conditions, reduce position sizes or avoid trading until clear directional move
Advanced Divergence Patterns (%K Line vs Price):
Bullish Divergence: Price makes lower low while %K makes higher low, indicates weakening bearish momentum, potential trend reversal upward, more reliable when %K in oversold zone
Bearish Divergence: Price makes higher high while %K makes lower high, indicates weakening bullish momentum, potential trend reversal downward, more reliable when %K in overbought zone
Hidden Bullish Divergence: Price makes higher low while %K makes lower low, indicates trend continuation in uptrend, bullish trend strength confirmation
Hidden Bearish Divergence: Price makes lower high while %K makes higher high, indicates trend continuation in downtrend, bearish trend strength confirmation
Momentum Strength Analysis (%K Line Slope):
Steep %K Slope: Rapid momentum change, strong directional conviction, potential for extended moves but also increased reversal risk
Gradual %K Slope: Steady momentum development, sustainable trends more likely, lower probability of sharp reversals
Flat or Horizontal %K: Momentum stalling, potential reversal or consolidation ahead, wait for directional break before committing
%K Oscillation Within Range: Indicates ranging market, sideways price action, better suited for range-trading strategies than trend following
🎯 STRATEGIC APPLICATIONS
Mean Reversion Strategy (Range-Bound Markets):
Identify ranging market conditions using price action or Bollinger Bands
Wait for Stochastic to reach extreme zones (above 80 for overbought, below 20 for oversold)
Enter counter-trend position when %K crosses %D in extreme zone (sell on bearish cross above 80, buy on bullish cross below 20)
Set profit targets near opposite extreme or midline (50 level)
Use tight stop-loss above recent swing high/low to protect against breakout scenarios
Exit when Stochastic reaches opposite extreme or %K crosses %D in opposite direction
Trend Following with Momentum Confirmation:
Identify primary trend direction using higher timeframe analysis or moving averages
Wait for Stochastic pullback to oversold zone (<20) in uptrend or overbought zone (>80) in downtrend
Enter in trend direction when %K crosses %D confirming momentum shift (bullish cross in uptrend, bearish cross in downtrend)
Use wider stops to accommodate normal trend volatility
Add to position on subsequent pullbacks showing similar Stochastic pattern
Exit when Stochastic shows opposite extreme with failed cross or bearish/bullish divergence
Divergence-Based Reversal Strategy:
Scan for divergence between price and Stochastic at swing highs/lows
Confirm divergence with at least two price pivots showing divergent Stochastic readings
Wait for %K to cross %D in direction of anticipated reversal as entry trigger
Enter position in divergence direction with stop beyond recent swing extreme
Target profit at key support/resistance levels or Fibonacci retracements
Scale out as Stochastic reaches opposite extreme zone
Multi-Timeframe Momentum Alignment:
Analyze Stochastic on higher timeframe (4H or Daily) for primary trend bias
Switch to lower timeframe (1H or 15M) for precise entry timing
Only take trades where lower timeframe Stochastic signal aligns with higher timeframe momentum direction
Higher timeframe Stochastic in bullish zone (>50) = only take long entries on lower timeframe
Higher timeframe Stochastic in bearish zone (<50) = only take short entries on lower timeframe
Exit when lower timeframe shows counter-signal or higher timeframe momentum reverses
Zone Transition Strategy:
Monitor Stochastic for transitions between zones (oversold to neutral, neutral to overbought, etc.)
Enter long when Stochastic crosses above 20 (exiting oversold), signaling momentum shift from bearish to neutral/bullish
Enter short when Stochastic crosses below 80 (exiting overbought), signaling momentum shift from bullish to neutral/bearish
Use zone midpoint (50) as dynamic support/resistance for position management
Trail stops as Stochastic advances through favorable zones
Exit when Stochastic fails to maintain momentum and reverses back into prior zone
📋 DETAILED PARAMETER CONFIGURATION
%K Length (Default: 14):
Lower Values (5-9): Highly sensitive to price changes, generates more frequent signals, increased false signals in choppy markets, suitable for very short-term trading and scalping
Standard Values (10-14): Balanced sensitivity and reliability, traditional default (14) widely used,适合 swing trading and intraday strategies
Higher Values (15-21): Reduced sensitivity, smoother oscillations, fewer but potentially more reliable signals, better for position trading and lower timeframe noise reduction
Very High Values (21+): Slow response, long-term momentum measurement, fewer trading signals, suitable for weekly or monthly analysis
%K Smoothing (Default: 3):
Value 1: Fast Stochastic, uses raw %K calculation without additional smoothing, most responsive to price changes, generates earliest signals with higher noise
Value 3: Slow Stochastic (default), traditional smoothing level, reduces false signals while maintaining good responsiveness, widely accepted standard
Values 5-7: Very slow response, extremely smooth oscillations, significantly reduced whipsaws but delayed entry/exit timing
Recommendation: Default value 3 suits most trading scenarios, active short-term traders may use 1, conservative long-term positions use 5+
%D Smoothing (Default: 3):
Lower Values (1-2): Signal line closely follows %K, frequent crossover signals, useful for active trading but requires strict filtering
Standard Value (3): Traditional setting providing balanced signal line behavior, optimal for most trading applications
Higher Values (4-7): Smoother signal line, fewer crossover signals, reduced whipsaws but slower confirmation, better for trend trading
Very High Values (8+): Signal line becomes slow-moving reference, crossovers rare and highly significant, suitable for long-term position changes only
Smoothing Type Algorithm Selection:
For Trending Markets:
ZLEMA, DEMA, TEMA: Reduced lag for faster trend entry, quick response to momentum shifts, suitable for strong directional moves
HMA, ALMA: Good balance of smoothness and responsiveness, effective for clean trend following without excessive noise
EMA: Classic choice for trending markets, faster than SMA while maintaining reasonable stability
For Ranging/Choppy Markets:
Kalman Filter, Super Smoother: Superior noise filtering, reduces false signals in sideways action, helps identify genuine reversal points
Laguerre Filters: Smooth oscillations with adjustable lag, excellent for mean reversion strategies in ranges
T3, TMA: Very smooth output, filters out market noise effectively, clearer extreme zone identification
For Adaptive Market Conditions:
KAMA: Automatically adjusts to market efficiency, fast in trends and slow in congestion, reduces whipsaws during transitions
FRAMA: Adapts to fractal market structure, responsive during directional moves, conservative during uncertainty
McGinley Dynamic: Self-adjusting smoothing, follows price naturally, minimizes lag in trending markets while filtering noise in ranges
For Conservative Long-Term Analysis:
SMA: Traditional choice, predictable behavior, widely understood characteristics
RMA (Wilder's): Smooth oscillations, reduced sensitivity to outliers, consistent behavior across market conditions
Laguerre Binomial Filter: Extremely smooth output, ideal for weekly/monthly timeframe analysis, eliminates short-term noise completely
Source Selection:
Close (Default): Standard choice using closing prices, most common and widely tested
HLC3 or OHLC4: Incorporates more price information, reduces impact of sudden spikes or gaps, smoother oscillator behavior
HL2: Midpoint of high-low range, emphasizes intrabar volatility, useful for markets with wide intraday ranges
Custom Source: Can use other indicators as input (e.g., Heikin Ashi close, smoothed price), creates derivative momentum indicators
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Responsiveness Characteristics:
Traditional SMA-Based Stochastic:
Fixed lag regardless of market conditions, consistent delay of approximately (K Smoothing + D Smoothing) / 2 periods
Equal treatment of trending and ranging markets, no adaptation to volatility changes
Predictable behavior but suboptimal in varying market regimes
Enhanced Version with Adaptive Algorithms:
KAMA and FRAMA reduce lag by up to 40-60% in strong trends compared to SMA while maintaining similar smoothness in ranges
ZLEMA and T3 provide near-zero lag characteristics for early entry signals with acceptable noise levels
Kalman Filter and Super Smoother offer superior noise rejection, reducing false signals in choppy conditions by estimations of 30-50% compared to SMA
Performance improvements vary by algorithm selection and market conditions
Signal Quality Improvements:
Adaptive algorithms help reduce whipsaw trades in ranging markets by adjusting sensitivity dynamically
Advanced filters (Kalman, Laguerre, Super Smoother) provide clearer extreme zone readings for mean reversion strategies
Zero-lag methods (ZLEMA, DEMA, TEMA) generate earlier crossover signals in trending markets for improved entry timing
Smoother algorithms (T3, Laguerre Binomial) reduce false extreme zone touches for more reliable overbought/oversold signals
Comparison with Standard Implementations:
Versus Basic Stochastic: Enhanced version offers 21 smoothing options versus single SMA, allowing optimization for specific market characteristics and trading styles
Versus RSI: Stochastic provides range-bound measurement (0-100) with clear extreme zones, RSI measures momentum speed, Stochastic offers clearer visual overbought/oversold identification
Versus MACD: Stochastic bounded oscillator suitable for mean reversion, MACD unbounded indicator better for trend strength, Stochastic excels in range-bound and oscillating markets
Versus CCI: Stochastic has fixed bounds (0-100) for consistent interpretation, CCI unbounded with variable extremes, Stochastic provides more standardized extreme readings across different instruments
Flexibility Advantages:
Single indicator adaptable to multiple strategies through algorithm selection rather than requiring different indicator variants
Ability to optimize smoothing characteristics for specific instruments (e.g., smoother for crypto volatility, faster for forex trends)
Multi-timeframe analysis with consistent algorithm across timeframes for coherent momentum picture
Backtesting capability with algorithm as optimization parameter for strategy development
Limitations and Considerations:
Increased complexity from multiple algorithm choices may lead to over-optimization if parameters are curve-fitted to historical data
Adaptive algorithms (KAMA, FRAMA) have adjustment periods during market regime changes where signals may be less reliable
Zero-lag algorithms sacrifice some smoothness for responsiveness, potentially increasing noise sensitivity in very choppy conditions
Performance characteristics vary significantly across algorithms, requiring understanding and testing before live implementation
Like all oscillators, Stochastic can remain in extreme zones for extended periods during strong trends, generating premature reversal signals
USAGE NOTES
This indicator is designed for technical analysis and educational purposes to provide traders with enhanced flexibility in momentum analysis. The Stochastic Oscillator has limitations and should not be used as the sole basis for trading decisions.
Important Considerations:
Algorithm performance varies with market conditions - no single smoothing method is optimal for all scenarios
Extreme zone signals (overbought/oversold) indicate potential reversal areas but not guaranteed turning points, especially in strong trends
Crossover signals may generate false entries during sideways choppy markets regardless of smoothing algorithm
Divergence patterns require confirmation from price action or additional indicators before trading
Past indicator characteristics and backtested results do not guarantee future performance
Always combine Stochastic analysis with proper risk management, position sizing, and multi-indicator confirmation
Test selected algorithm on historical data of specific instrument and timeframe before live trading
Market regime changes may require algorithm adjustment for optimal performance
The enhanced smoothing options are intended to provide tools for optimizing the indicator's behavior to match individual trading styles and market characteristics, not to create a perfect predictive tool. Responsible usage includes understanding the mathematical properties of selected algorithms and their appropriate application contexts.
Extreme Pressure Zones Indicator (EPZ) [BullByte]Extreme Pressure Zones Indicator(EPZ)
The Extreme Pressure Zones (EPZ) Indicator is a proprietary market analysis tool designed to highlight potential overbought and oversold "pressure zones" in any financial chart. It does this by combining several unique measurements of price action and volume into a single, bounded oscillator (0–100). Unlike simple momentum or volatility indicators, EPZ captures multiple facets of market pressure: price rejection, trend momentum, supply/demand imbalance, and institutional (smart money) flow. This is not a random mashup of generic indicators; each component was chosen and weighted to reveal extreme market conditions that often precede reversals or strong continuations.
What it is?
EPZ estimates buying/selling pressure and highlights potential extreme zones with a single, bounded 0–100 oscillator built from four normalized components. Context-aware weighting adapts to volatility, trendiness, and relative volume. Visual tools include adaptive thresholds, confirmed-on-close extremes, divergence, an MTF dashboard, and optional gradient candles.
Purpose and originality (not a mashup)
Purpose: Identify when pressure is building or reaching potential extremes while filtering noise across regimes and symbols.
Originality: EPZ integrates price rejection, momentum cascade, pressure distribution, and smart money flow into one bounded scale with context-aware weighting. It is not a cosmetic mashup of public indicators.
Why a trader might use EPZ
EPZ provides a multi-dimensional gauge of market extremes that standalone indicators may miss. Traders might use it to:
Spot Reversals: When EPZ enters an "Extreme High" zone (high red), it implies selling pressure might soon dominate. This can hint at a topside reversal or at least a pause in rallies. Conversely, "Extreme Low" (green) can highlight bottom-fish opportunities. The indicator's divergence module (optional) also finds hidden bullish/bearish divergences between price and EPZ, a clue that price momentum is weakening.
Measure Momentum Shifts: Because EPZ blends momentum and volume, it reacts faster than many single metrics. A rising MPO indicates building bullish pressure, while a falling MPO shows increasing bearish pressure. Traders can use this like a refined RSI: above 50 means bullish bias, below 50 means bearish bias, but with context provided by the thresholds.
Filter Trades: In trend-following systems, one could require EPZ to be in the bullish (green) zone before taking longs, or avoid new trades when EPZ is extreme. In mean-reversion systems, one might specifically look to fade extremes flagged by EPZ.
Multi-Timeframe Confirmation: The dashboard can fetch a higher timeframe EPZ value. For example, you might trade a 15-minute chart only when the 60-minute EPZ agrees on pressure direction.
Components and how they're combined
Rejection (PRV) – Captures price rejection based on candle wicks and volume (see Price Rejection Volume).
Momentum Cascade (MCD) – Blends multiple momentum periods (3,5,8,13) into a normalized momentum score.
Pressure Distribution (PDI) – Measures net buy/sell pressure by comparing volume on up vs down candles.
Smart Money Flow (SMF) – An adaptation of money flow index that emphasizes unusual volume spikes.
Each of these components produces a 0–100 value (higher means more bullish pressure). They are then weighted and averaged into the final Market Pressure Oscillator (MPO), which is smoothed and scaled. By combining these four views, EPZ stands out as a comprehensive pressure gauge – the whole is greater than the sum of parts
Context-aware weighting:
Higher volatility → more PRV weight
Trendiness up (RSI of ATR > 25) → more MCD weight
Relative volume > 1.2x → more PDI weight
SMF holds a stable weight
The weighted average is smoothed and scaled into MPO ∈ with 50 as the neutral midline.
What makes EPZ stand out
Four orthogonal inputs (price action, momentum, pressure, flow) unified in a single bounded oscillator with consistent thresholds.
Adaptive thresholds (optional) plus robust extreme detection that also triggers on crossovers, so static thresholds work reliably too.
Confirm Extremes on Bar Close (default ON): dots/arrows/labels/alerts print on closed bars to avoid repaint confusion.
Clean dashboard, divergence tools, pre-alerts, and optional on-price gradients. Visual 3D layering uses offsets for depth only,no lookahead.
Recommended markets and timeframes
Best: liquid symbols (index futures, large-cap equities, major FX, BTC/ETH).
Timeframes: 5–15m (more signals; consider higher thresholds), 1H–4H (balanced), 1D (clear regimes).
Use caution on illiquid or very low TFs where wick/volume geometry is erratic.
Logic and thresholds
MPO ∈ ; 50 = neutral. Above 50 = bullish pressure; below 50 = bearish.
Static thresholds (defaults): thrHigh = 70, thrLow = 30; warning bands 5 pts inside extremes (65/35).
Adaptive thresholds (optional):
thrHigh = min(BaseHigh + 5, mean(MPO,100) + stdev(MPO,100) × ExtremeSensitivity)
thrLow = max(BaseLow − 5, mean(MPO,100) − stdev(MPO,100) × ExtremeSensitivity)
Extreme detection
High: MPO ≥ thrHigh with peak/slope or crossover filter.
Low: MPO ≤ thrLow with trough/slope or crossover filter.
Cooldown: 5 bars (default). A new extreme will not print until the cooldown elapses, even if MPO re-enters the zone.
Confirmation
"Confirm Extremes on Bar Close" (default ON) gates extreme markers, pre-alerts, and alerts to closed bars (non-repainting).
Divergences
Pivot-based bullish/bearish divergence; tags appear only after left/right bars elapse (lookbackPivot).
MTF
HTF MPO retrieved with lookahead_off; values can update intrabar and finalize at HTF close. This is disclosed and expected.
Inputs and defaults (key ones)
Core: Sensitivity=1.0; Analysis Period=14; Smoothing=3; Adaptive Thresholds=OFF.
Extremes: Base High=70, Base Low=30; Extreme Sensitivity=1.5; Confirm Extremes on Bar Close=ON; Cooldown=5; Dot size Small/Tiny.
Visuals: Heatmap ON; 3D depth optional; Strength bars ON; Pre-alerts OFF; Divergences ON with tags ON; Gradient candles OFF; Glow ON.
Dashboard: ON; Position=Top Right; Size=Normal; MTF ON; HTF=60m; compact overlay table on price chart.
Advanced caps: Max Oscillator Labels=80; Max Extreme Guide Lines=80; Divergence objects=60.
Dashboard: what each element means
Header: EPZ ANALYSIS.
Large readout: Current MPO; color reflects state (extreme, approaching, or neutral).
Status badge: "Extreme High/Low", "Approaching High/Low", "Bullish/Neutral/Bearish".
HTF cell (when MTF ON): Higher-timeframe MPO, color-coded vs extremes; updates intrabar, settles at HTF close.
Predicted (when MTF OFF): Simple MPO extrapolation using momentum/acceleration—illustrative only.
Thresholds: Current thrHigh/thrLow (static or adaptive).
Components: ASCII bars + values for PRV, MCD, PDI, SMF.
Market metrics: Volume Ratio (x) and ATR% of price.
Strength: Bar indicator of |MPO − 50| × 2.
Confidence: Heuristic gauge (100 in extremes, 70 in warnings, 50 with divergence, else |MPO − 50|). Convenience only, not probability.
How to read the oscillator
MPO Value (0–100): A reading of 50 is neutral. Values above ~55 are increasingly bullish (green), while below ~45 are increasingly bearish (red). Think of these as "market pressure".
Extreme Zones: When MPO climbs into the bright orange/red area (above the base-high line, default 70), the chart will display a dot and downward arrow marking that extreme. Traders often treat this as a sign to tighten stops or look for shorts. Similarly, a bright green dot/up-arrow appears when MPO falls below the base-low (30), hinting at a bullish setup.
Heatmap/Candles: If "Pressure Heatmap" is enabled, the background of the oscillator pane will fade green or red depending on MPO. Users can optionally color the price candles by MPO value (gradient candles) to see these extremes on the main chart.
Prediction Zone(optional): A dashed projection line extends the MPO forward by a small number of bars (prediction_bars) using current MPO momentum and acceleration. This is a heuristic extrapolation best used for short horizons (1–5 bars) to anticipate whether MPO may touch a warning or extreme zone. It is provisional and becomes less reliable with longer projection lengths — always confirm predicted moves with bar-close MPO and HTF context before acting.
Divergences: When price makes a higher high but EPZ makes a lower high (bearish divergence), the indicator can draw dotted lines and a "Bear Div" tag. The opposite (lower low price, higher EPZ) gives "Bull Div". These signals confirm waning momentum at extremes.
Zones: Warning bands near extremes; Extreme zones beyond thresholds.
Crossovers: MPO rising through 35 suggests easing downside pressure; falling through 65 suggests waning upside pressure.
Dots/arrows: Extreme markers appear on closed bars when confirmation is ON and respect the 5-bar cooldown.
Pre-alert dots (optional): Proximity cues in warning zones; also gated to bar close when confirmation is ON.
Histogram: Distance from neutral (50); highlights strengthening or weakening pressure.
Divergence tags: "Bear Div" = higher price high with lower MPO high; "Bull Div" = lower price low with higher MPO low.
Pressure Heatmap : Layered gradient background that visually highlights pressure strength across the MPO scale; adjustable intensity and optional zone overlays (warning / extreme) for quick visual scanning.
A typical reading: If the oscillator is rising from neutral towards the high zone (green→orange→red), the chart may see strong buying culminating in a stall. If it then turns down from the extreme, that peak EPZ dot signals sell pressure.
Alerts
EPZ: Extreme Context — fires on confirmed extremes (respects cooldown).
EPZ: Approaching Threshold — fires in warning zones if no extreme.
EPZ: Divergence — fires on confirmed pivot divergences.
Tip: Set alerts to "Once per bar close" to align with confirmation and avoid intrabar repaint.
Practical usage ideas
Trend continuation: In positive regimes (MPO > 50 and rising), pullbacks holding above 50 often precede continuation; mirror for bearish regimes.
Exhaustion caution: E High/E Low can mark exhaustion risk; many wait for MPO rollover or divergence to time fades or partial exits.
Adaptive thresholds: Useful on assets with shifting volatility regimes to maintain meaningful "extreme" levels.
MTF alignment: Prefer setups that agree with the HTF MPO to reduce countertrend noise.
Examples
Screenshots captured in TradingView Replay to freeze the bar at close so values don't fluctuate intrabar. These examples use default settings and are reproducible on the same bars; they are for illustration, not cherry-picking or performance claims.
Example 1 — BTCUSDT, 1h — E Low
MPO closed at 26.6 (below the 30 extreme), printing a confirmed E Low. HTF MPO is 26.6, so higher-timeframe pressure remains bearish. Components are subdued (Momentum/Pressure/Smart$ ≈ 29–37), with Vol Ratio ≈ 1.19x and ATR% ≈ 0.37%. A prior Bear Div flagged weakening impulse into the drop. With cooldown set to 5 bars, new extremes are rate-limited. Many traders wait for MPO to curl up and reclaim 35 or for a fresh Bull Div before considering countertrend ideas; if MPO cannot reclaim 35 and HTF stays weak, treat bounces cautiously. Educational illustration only.
Example 2 — ETHUSD, 30m — E High
A strong impulse pushed MPO into the extreme zone (≥ 70), printing a confirmed E High on close. Shortly after, MPO cooled to ~61.5 while a Bear Div appeared, showing momentum lag as price pushed a higher high. Volume and volatility were elevated (≈ 1.79x / 1.25%). With a 5-bar cooldown, additional extremes won't print immediately. Some treat E High as exhaustion risk—either waiting for MPO rollover under 65/50 to fade, or for a pullback that holds above 50 to re-join the trend if higher-timeframe pressure remains constructive. Educational illustration only.
Known limitations and caveats
The MPO line itself can change intrabar; extreme markers/alerts do not repaint when "Confirm Extremes on Bar Close" is ON.
HTF values settle at the close of the HTF bar.
Illiquid symbols or very low TFs can be noisy; consider higher thresholds or longer smoothing.
Prediction line (when enabled) is a visual extrapolation only.
For coders
Pine v6. MTF via request.security with lookahead_off.
Extremes include crossover triggers so static thresholds also yield E High/E Low.
Extreme markers and pre-alerts are gated by barstate.isconfirmed when confirmation is ON.
Arrays prune oldest objects to respect resource limits; defaults (80/80/60) are conservative for low TFs.
3D layering uses negative offsets purely for drawing depth (no lookahead).
Screenshot methodology:
To make labels legible and to demonstrate non-repainting behavior, the examples were captured in TradingView Replay with "Confirm Extremes on Bar Close" enabled. Replay is used only to freeze the bar at close so plots don't change intrabar. The examples use default settings, include both Extreme Low and Extreme High cases, and can be reproduced by scrolling to the same bars outside Replay. This is an educational illustration, not a performance claim.
Disclaimer
This script is for educational purposes only and does not constitute financial advice. Markets involve risk; past behavior does not guarantee future results. You are responsible for your own testing, risk management, and decisions.
ATR Future Movement Range Projection
The "ATR Future Movement Range Projection" is a custom TradingView Pine Script indicator designed to forecast potential price ranges for a stock (or any asset) over short-term (1-month) and medium-term (3-month) horizons. It leverages the Average True Range (ATR) as a measure of volatility to estimate how far the price might move, while incorporating recent momentum bias based on the proportion of bullish (green) vs. bearish (red) candles. This creates asymmetric projections: in bullish periods, the upside range is larger than the downside, and vice versa.
The indicator is overlaid on the chart, plotting horizontal lines for the projected high and low prices for both timeframes. Additionally, it displays a small table in the top-right corner summarizing the projected prices and the percentage change required from the current close to reach them. This makes it useful for traders assessing potential targets, risk-reward ratios, or option strategies, as it combines volatility forecasting with directional sentiment.
Key features:
- **Volatility Basis**: Uses weekly ATR to derive a stable daily volatility estimate, avoiding noise from shorter timeframes.
- **Momentum Adjustment**: Analyzes recent candle colors to tilt projections toward the prevailing trend (e.g., more upside if more green candles).
- **Time Horizons**: Fixed at 1 month (21 trading days) and 3 months (63 trading days), assuming ~21 trading days per month (excluding weekends/holidays).
- **User Adjustable**: The ATR length/lookback (default 50) can be tweaked via inputs.
- **Visuals**: Green/lime lines for highs, red/orange for lows; a semi-transparent table for quick reference.
- **Limitations**: This is a probabilistic projection based on historical volatility and momentum—it doesn't predict direction with certainty and assumes volatility persists. It ignores external factors like news, earnings, or market regimes. Best used on daily charts for stocks/ETFs.
The indicator doesn't generate buy/sell signals but helps visualize "expected" ranges, similar to how implied volatility informs option pricing.
### How It Works Step-by-Step
The script executes on each bar update (typically daily timeframe) and follows this logic:
1. **Input Configuration**:
- ATR Length (Lookback): Default 50 bars. This controls both the ATR calculation period and the candle count window. You can adjust it in the indicator settings.
2. **Calculate Weekly ATR**:
- Fetches the ATR from the weekly timeframe using `request.security` with a length of 50 weeks.
- ATR measures average price range (high-low, adjusted for gaps), representing volatility.
3. **Derive Daily ATR**:
- Divides the weekly ATR by 5 (approximating 5 trading days per week) to get an equivalent daily volatility estimate.
- Example: If weekly ATR is $5, daily ATR ≈ $1.
4. **Define Projection Periods**:
- 1 Month: 21 trading days.
- 3 Months: 63 trading days (21 × 3).
- These are hardcoded but based on standard trading calendar assumptions.
5. **Compute Base Projections**:
- Base projection = Daily ATR × Days in period.
- This gives the total expected movement (range) without direction: e.g., for 3 months, $1 daily ATR × 63 = $63 total range.
6. **Analyze Candle Momentum (Win Rate)**:
- Counts green candles (close > open) and red candles (close < open) over the last 50 bars (ignores dojis where close == open).
- Total colored candles = green + red.
- Win rate = green / total colored (as a fraction, e.g., 0.7 for 70%). Defaults to 0.5 if no colored candles.
- This acts as a simple momentum proxy: higher win rate implies bullish bias.
7. **Adjust Projections Asymmetrically**:
- Upside projection = Base projection × Win rate.
- Downside projection = Base projection × (1 - Win rate).
- This skews the range: e.g., 70% win rate means 70% of the total range allocated to upside, 30% to downside.
8. **Calculate Projected Prices**:
- High = Current close + Upside projection.
- Low = Current close - Downside projection.
- Done separately for 1M and 3M.
9. **Plot Lines**:
- 3M High: Solid green line.
- 3M Low: Solid red line.
- 1M High: Dashed lime line.
- 1M Low: Dashed orange line.
- Lines extend horizontally from the current bar onward.
10. **Display Table**:
- A 3-column table (Projection, Price, % Change) in the top-right.
- Rows for 1M High/Low and 3M High/Low, color-coded.
- % Change = ((Projected price - Close) / Close) × 100.
- Updates dynamically with new data.
The entire process repeats on each new bar, so projections evolve as volatility and momentum change.
### Examples
Here are two hypothetical examples using the indicator on a daily chart. Assume it's applied to a stock like AAPL, but with made-up data for illustration. (In TradingView, you'd add the script to see real outputs.)
#### Example 1: Bullish Scenario (High Win Rate)
- Current Close: $150.
- Weekly ATR (50 periods): $10 → Daily ATR: $10 / 5 = $2.
- Last 50 Candles: 35 green, 15 red → Total colored: 50 → Win Rate: 35/50 = 0.7 (70%).
- Base Projections:
- 1M: $2 × 21 = $42.
- 3M: $2 × 63 = $126.
- Adjusted Projections:
- 1M Upside: $42 × 0.7 = $29.4 → High: $150 + $29.4 = $179.4 (+19.6%).
- 1M Downside: $42 × 0.3 = $12.6 → Low: $150 - $12.6 = $137.4 (-8.4%).
- 3M Upside: $126 × 0.7 = $88.2 → High: $150 + $88.2 = $238.2 (+58.8%).
- 3M Downside: $126 × 0.3 = $37.8 → Low: $150 - $37.8 = $112.2 (-25.2%).
- On the Chart: Green/lime lines skewed higher; table shows bullish % changes (e.g., +58.8% for 3M high).
- Interpretation: Suggests stronger potential upside due to recent bullish momentum; useful for call options or long positions.
#### Example 2: Bearish Scenario (Low Win Rate)
- Current Close: $50.
- Weekly ATR (50 periods): $3 → Daily ATR: $3 / 5 = $0.6.
- Last 50 Candles: 20 green, 30 red → Total colored: 50 → Win Rate: 20/50 = 0.4 (40%).
- Base Projections:
- 1M: $0.6 × 21 = $12.6.
- 3M: $0.6 × 63 = $37.8.
- Adjusted Projections:
- 1M Upside: $12.6 × 0.4 = $5.04 → High: $50 + $5.04 = $55.04 (+10.1%).
- 1M Downside: $12.6 × 0.6 = $7.56 → Low: $50 - $7.56 = $42.44 (-15.1%).
- 3M Upside: $37.8 × 0.4 = $15.12 → High: $50 + $15.12 = $65.12 (+30.2%).
- 3M Downside: $37.8 × 0.6 = $22.68 → Low: $50 - $22.68 = $27.32 (-45.4%).
- On the Chart: Red/orange lines skewed lower; table highlights larger downside % (e.g., -45.4% for 3M low).
- Interpretation: Indicates bearish risk; might prompt protective puts or short strategies.
#### Example 3: Neutral Scenario (Balanced Win Rate)
- Current Close: $100.
- Weekly ATR: $5 → Daily ATR: $1.
- Last 50 Candles: 25 green, 25 red → Win Rate: 0.5 (50%).
- Projections become symmetric:
- 1M: Base $21 → Upside/Downside $10.5 each → High $110.5 (+10.5%), Low $89.5 (-10.5%).
- 3M: Base $63 → Upside/Downside $31.5 each → High $131.5 (+31.5%), Low $68.5 (-31.5%).
- Interpretation: Pure volatility-based range, no directional bias—ideal for straddle options or range trading.
In real use, test on historical data: e.g., if past projections captured actual moves ~68% of the time (1 standard deviation for ATR), it validates the volatility assumption. Adjust the lookback for different assets (shorter for volatile cryptos, longer for stable blue-chips).
PriceActionLibrary "PriceAction"
Hi all!
This library will help you to plot the market structure and liquidity. By now, the only part in the price action section is liquidity, but I plan to add more later on. The market structure will be split into two parts, 'Internal' and 'Swing' with separate pivot lengths. For these two trends it will show you:
• Break of structure (BOS)
• Change of character (CHoCH/CHoCH+) (mandatory)
• Equal high/low (EQH/EQL)
It's inspired by "Smart Money Concepts (SMC) " by LuxAlgo.
This library is now the same code as the code in my library 'MarketStructure', but it has evolved into a more price action oriented library than just a market structure library. This is more accurate and I will continue working on this library to keep it growing.
This code does not provide any examples, but you can look at my indicators 'Market structure' () and 'Order blocks' (), where I use the 'MarketStructure' library (which is the same code).
Market structure
Both of these market structures can be enabled/disabled by setting them to 'na'. The pivots lengths can be configured separately. The pivots found will be the 'base' of and will show you when price breaks it. When that happens a break of structure or a change of character will be created. The latest 5 pivots found within the current trends will be kept to take action on. They are cleared on a change of character, so nothing (break of structures or change of characters) can happen on pivots before a trend change. The internal market structure is shown with dashed lines and swing market structure is shown with solid lines.
Labels for a change of character can have either the text 'CHoCH' or 'CHoCH+'. A Change of Character plus is formed when price fails to form a higher high or a lower low before reversing. Note that a pivot that is created after the change of character might have a higher high or a lower low, thus not making the break a 'CHoCH+'. This is not changed after the pivot is found but is kept as is.
A break of structure is removed if an earlier pivot within the same trend is broken, i.e. another break of structure (with a longer distance) is created. Like in the images below, the first pivot (in the first image) is removed when an earlier pivot's higher price within the same trend is broken (the second image):
[image [https://www.tradingview.com/x/PRP6YtPA/
Equal high/lows have a configurable color setting and can be configured to be extended to the right. Equal high/lows are only possible if it's not been broken by price. A factor (percentage of width) of the Average True Length (of length 14) that the pivot must be within to to be considered an Equal high/low. Equal highs/lows can be of 2 pivots or more.
You are able to show the pivots that are used. "HH" (higher high), "HL" (higher low), "LH" (lower high), "LL" (lower low) and "H"/"L" (for pivots (high/low) when the trend has changed) are the labels used. There are also labels for break of structures ('BOS') and change of characters ('CHoCH' or 'CHoCH+'). The size of these texts is set in the 'FontSize' setting.
When programming I focused on simplicity and ease of read. I did not focus on performance, I will do so if it's a problem (haven't noticed it is one yet).
You can set alerts for when a change of character, break of structure or an equal high/low (new or an addition to a previously found) happens. The alerts that are fired are on 'once_per_bar_close' to avoid repainting. This has the drawback to alert you when the bar closes.
Price action
The indicator will create lines and zones for spotted liquidity. It will draw a line (with dotted style) at the price level that was liquidated, but it will also draw a zone from that level to the bar that broke the pivot high or low price. If that zone is large the liquidation is big and might be significant. This can be disabled in the settings. You can also change the confirmation candles (that does not close above or below the pivot level) needed after a liquidation and how many pivots back to look at.
The lines and boxes drawn will look like this if the color is orange:
Hope this is of help!
Will draw out the market structure for the disired pivot length.
Liqudity(liquidity)
Will draw liquidity.
Parameters:
liquidity (Liquidity) : The 'PriceAction.Liquidity' object.
Pivot(structure)
Sets the pivots in the structure.
Parameters:
structure (Structure)
PivotLabels(structure)
Draws labels for the pivots found.
Parameters:
structure (Structure)
EqualHighOrLow(structure)
Draws the boxes for equal highs/lows. Also creates labels for the pivots included.
Parameters:
structure (Structure)
BreakOfStructure(structure)
Will create lines when a break of strycture occures.
Parameters:
structure (Structure)
Returns: A boolean that represents if a break of structure was found or not.
ChangeOfCharacter(structure)
Will create lines when a change of character occures. This line will have a label with "CHoCH" or "CHoCH+".
Parameters:
structure (Structure)
Returns: A boolean that represents if a change of character was found or not.
VisualizeCurrent(structure)
Will create a box with a background for between the latest high and low pivots. This can be used as the current trading range (if the pivots broke strucure somehow).
Parameters:
structure (Structure)
StructureBreak
Holds drawings for a structure break.
Fields:
Line (series line) : The line object.
Label (series label) : The label object.
Pivot
Holds all the values for a found pivot.
Fields:
Price (series float) : The price of the pivot.
BarIndex (series int) : The bar_index where the pivot occured.
Type (series int) : The type of the pivot (-1 = low, 1 = high).
Time (series int) : The time where the pivot occured.
BreakOfStructureBroken (series bool) : Sets to true if a break of structure has happened.
LiquidityBroken (series bool) : Sets to true if a liquidity of the price level has happened.
ChangeOfCharacterBroken (series bool) : Sets to true if a change of character has happened.
Structure
Holds all the values for the market structure.
Fields:
LeftLength (series int) : Define the left length of the pivots used.
RightLength (series int) : Define the right length of the pivots used.
Type (series Type) : Set the type of the market structure. Two types can be used, 'internal' and 'swing' (0 = internal, 1 = swing).
Trend (series int) : This will be set internally and can be -1 = downtrend, 1 = uptrend.
EqualPivotsFactor (series float) : Set how the limits are for an equal pivot. This is a factor of the Average True Length (ATR) of length 14. If a low pivot is considered to be equal if it doesn't break the low pivot (is at a lower value) and is inside the previous low pivot + this limit.
ExtendEqualPivotsZones (series bool) : Set to true if you want the equal pivots zones to be extended.
ExtendEqualPivotsStyle (series string) : Set the style of equal pivot zones.
ExtendEqualPivotsColor (series color) : Set the color of equal pivot zones.
EqualHighs (array) : Holds the boxes for zones that contains equal highs.
EqualLows (array) : Holds the boxes for zones that contains equal lows.
BreakOfStructures (array) : Holds all the break of structures within the trend (before a change of character).
Pivots (array) : All the pivots in the current trend, added with the latest first, this is cleared when the trend changes.
FontSize (series int) : Holds the size of the font displayed.
AlertChangeOfCharacter (series bool) : Holds true or false if a change of character should be alerted or not.
AlertBreakOfStructure (series bool) : Holds true or false if a break of structure should be alerted or not.
AlerEqualPivots (series bool) : Holds true or false if equal highs/lows should be alerted or not.
Liquidity
Holds all the values for liquidity.
Fields:
LiquidityPivotsHigh (array) : All high pivots for liquidity.
LiquidityPivotsLow (array) : All low pivots for liquidity.
LiquidityConfirmationBars (series int) : The number of bars to confirm that a liquidity is valid.
LiquidityPivotsLookback (series int) : A number of pivots to look back for.
FontSize (series int) : Holds the size of the font displayed.
PriceAction
Holds all the values for the general price action and the market structures.
Fields:
Liquidity (Liquidity)
Swing (Structure) : Placeholder for all objects used for the swing market structure.
Internal (Structure) : Placeholder for all objects used for the internal market structure.
Markov Chain [3D] | FractalystWhat exactly is a Markov Chain?
This indicator uses a Markov Chain model to analyze, quantify, and visualize the transitions between market regimes (Bull, Bear, Neutral) on your chart. It dynamically detects these regimes in real-time, calculates transition probabilities, and displays them as animated 3D spheres and arrows, giving traders intuitive insight into current and future market conditions.
How does a Markov Chain work, and how should I read this spheres-and-arrows diagram?
Think of three weather modes: Sunny, Rainy, Cloudy.
Each sphere is one mode. The loop on a sphere means “stay the same next step” (e.g., Sunny again tomorrow).
The arrows leaving a sphere show where things usually go next if they change (e.g., Sunny moving to Cloudy).
Some paths matter more than others. A more prominent loop means the current mode tends to persist. A more prominent outgoing arrow means a change to that destination is the usual next step.
Direction isn’t symmetric: moving Sunny→Cloudy can behave differently than Cloudy→Sunny.
Now relabel the spheres to markets: Bull, Bear, Neutral.
Spheres: market regimes (uptrend, downtrend, range).
Self‑loop: tendency for the current regime to continue on the next bar.
Arrows: the most common next regime if a switch happens.
How to read: Start at the sphere that matches current bar state. If the loop stands out, expect continuation. If one outgoing path stands out, that switch is the typical next step. Opposite directions can differ (Bear→Neutral doesn’t have to match Neutral→Bear).
What states and transitions are shown?
The three market states visualized are:
Bullish (Bull): Upward or strong-market regime.
Bearish (Bear): Downward or weak-market regime.
Neutral: Sideways or range-bound regime.
Bidirectional animated arrows and probability labels show how likely the market is to move from one regime to another (e.g., Bull → Bear or Neutral → Bull).
How does the regime detection system work?
You can use either built-in price returns (based on adaptive Z-score normalization) or supply three custom indicators (such as volume, oscillators, etc.).
Values are statistically normalized (Z-scored) over a configurable lookback period.
The normalized outputs are classified into Bull, Bear, or Neutral zones.
If using three indicators, their regime signals are averaged and smoothed for robustness.
How are transition probabilities calculated?
On every confirmed bar, the algorithm tracks the sequence of detected market states, then builds a rolling window of transitions.
The code maintains a transition count matrix for all regime pairs (e.g., Bull → Bear).
Transition probabilities are extracted for each possible state change using Laplace smoothing for numerical stability, and frequently updated in real-time.
What is unique about the visualization?
3D animated spheres represent each regime and change visually when active.
Animated, bidirectional arrows reveal transition probabilities and allow you to see both dominant and less likely regime flows.
Particles (moving dots) animate along the arrows, enhancing the perception of regime flow direction and speed.
All elements dynamically update with each new price bar, providing a live market map in an intuitive, engaging format.
Can I use custom indicators for regime classification?
Yes! Enable the "Custom Indicators" switch and select any three chart series as inputs. These will be normalized and combined (each with equal weight), broadening the regime classification beyond just price-based movement.
What does the “Lookback Period” control?
Lookback Period (default: 100) sets how much historical data builds the probability matrix. Shorter periods adapt faster to regime changes but may be noisier. Longer periods are more stable but slower to adapt.
How is this different from a Hidden Markov Model (HMM)?
It sets the window for both regime detection and probability calculations. Lower values make the system more reactive, but potentially noisier. Higher values smooth estimates and make the system more robust.
How is this Markov Chain different from a Hidden Markov Model (HMM)?
Markov Chain (as here): All market regimes (Bull, Bear, Neutral) are directly observable on the chart. The transition matrix is built from actual detected regimes, keeping the model simple and interpretable.
Hidden Markov Model: The actual regimes are unobservable ("hidden") and must be inferred from market output or indicator "emissions" using statistical learning algorithms. HMMs are more complex, can capture more subtle structure, but are harder to visualize and require additional machine learning steps for training.
A standard Markov Chain models transitions between observable states using a simple transition matrix, while a Hidden Markov Model assumes the true states are hidden (latent) and must be inferred from observable “emissions” like price or volume data. In practical terms, a Markov Chain is transparent and easier to implement and interpret; an HMM is more expressive but requires statistical inference to estimate hidden states from data.
Markov Chain: states are observable; you directly count or estimate transition probabilities between visible states. This makes it simpler, faster, and easier to validate and tune.
HMM: states are hidden; you only observe emissions generated by those latent states. Learning involves machine learning/statistical algorithms (commonly Baum–Welch/EM for training and Viterbi for decoding) to infer both the transition dynamics and the most likely hidden state sequence from data.
How does the indicator avoid “repainting” or look-ahead bias?
All regime changes and matrix updates happen only on confirmed (closed) bars, so no future data is leaked, ensuring reliable real-time operation.
Are there practical tuning tips?
Tune the Lookback Period for your asset/timeframe: shorter for fast markets, longer for stability.
Use custom indicators if your asset has unique regime drivers.
Watch for rapid changes in transition probabilities as early warning of a possible regime shift.
Who is this indicator for?
Quants and quantitative researchers exploring probabilistic market modeling, especially those interested in regime-switching dynamics and Markov models.
Programmers and system developers who need a probabilistic regime filter for systematic and algorithmic backtesting:
The Markov Chain indicator is ideally suited for programmatic integration via its bias output (1 = Bull, 0 = Neutral, -1 = Bear).
Although the visualization is engaging, the core output is designed for automated, rules-based workflows—not for discretionary/manual trading decisions.
Developers can connect the indicator’s output directly to their Pine Script logic (using input.source()), allowing rapid and robust backtesting of regime-based strategies.
It acts as a plug-and-play regime filter: simply plug the bias output into your entry/exit logic, and you have a scientifically robust, probabilistically-derived signal for filtering, timing, position sizing, or risk regimes.
The MC's output is intentionally "trinary" (1/0/-1), focusing on clear regime states for unambiguous decision-making in code. If you require nuanced, multi-probability or soft-label state vectors, consider expanding the indicator or stacking it with a probability-weighted logic layer in your scripting.
Because it avoids subjectivity, this approach is optimal for systematic quants, algo developers building backtested, repeatable strategies based on probabilistic regime analysis.
What's the mathematical foundation behind this?
The mathematical foundation behind this Markov Chain indicator—and probabilistic regime detection in finance—draws from two principal models: the (standard) Markov Chain and the Hidden Markov Model (HMM).
How to use this indicator programmatically?
The Markov Chain indicator automatically exports a bias value (+1 for Bullish, -1 for Bearish, 0 for Neutral) as a plot visible in the Data Window. This allows you to integrate its regime signal into your own scripts and strategies for backtesting, automation, or live trading.
Step-by-Step Integration with Pine Script (input.source)
Add the Markov Chain indicator to your chart.
This must be done first, since your custom script will "pull" the bias signal from the indicator's plot.
In your strategy, create an input using input.source()
Example:
//@version=5
strategy("MC Bias Strategy Example")
mcBias = input.source(close, "MC Bias Source")
After saving, go to your script’s settings. For the “MC Bias Source” input, select the plot/output of the Markov Chain indicator (typically its bias plot).
Use the bias in your trading logic
Example (long only on Bull, flat otherwise):
if mcBias == 1
strategy.entry("Long", strategy.long)
else
strategy.close("Long")
For more advanced workflows, combine mcBias with additional filters or trailing stops.
How does this work behind-the-scenes?
TradingView’s input.source() lets you use any plot from another indicator as a real-time, “live” data feed in your own script (source).
The selected bias signal is available to your Pine code as a variable, enabling logical decisions based on regime (trend-following, mean-reversion, etc.).
This enables powerful strategy modularity : decouple regime detection from entry/exit logic, allowing fast experimentation without rewriting core signal code.
Integrating 45+ Indicators with Your Markov Chain — How & Why
The Enhanced Custom Indicators Export script exports a massive suite of over 45 technical indicators—ranging from classic momentum (RSI, MACD, Stochastic, etc.) to trend, volume, volatility, and oscillator tools—all pre-calculated, centered/scaled, and available as plots.
// Enhanced Custom Indicators Export - 45 Technical Indicators
// Comprehensive technical analysis suite for advanced market regime detection
//@version=6
indicator('Enhanced Custom Indicators Export | Fractalyst', shorttitle='Enhanced CI Export', overlay=false, scale=scale.right, max_labels_count=500, max_lines_count=500)
// |----- Input Parameters -----| //
momentum_group = "Momentum Indicators"
trend_group = "Trend Indicators"
volume_group = "Volume Indicators"
volatility_group = "Volatility Indicators"
oscillator_group = "Oscillator Indicators"
display_group = "Display Settings"
// Common lengths
length_14 = input.int(14, "Standard Length (14)", minval=1, maxval=100, group=momentum_group)
length_20 = input.int(20, "Medium Length (20)", minval=1, maxval=200, group=trend_group)
length_50 = input.int(50, "Long Length (50)", minval=1, maxval=200, group=trend_group)
// Display options
show_table = input.bool(true, "Show Values Table", group=display_group)
table_size = input.string("Small", "Table Size", options= , group=display_group)
// |----- MOMENTUM INDICATORS (15 indicators) -----| //
// 1. RSI (Relative Strength Index)
rsi_14 = ta.rsi(close, length_14)
rsi_centered = rsi_14 - 50
// 2. Stochastic Oscillator
stoch_k = ta.stoch(close, high, low, length_14)
stoch_d = ta.sma(stoch_k, 3)
stoch_centered = stoch_k - 50
// 3. Williams %R
williams_r = ta.stoch(close, high, low, length_14) - 100
// 4. MACD (Moving Average Convergence Divergence)
= ta.macd(close, 12, 26, 9)
// 5. Momentum (Rate of Change)
momentum = ta.mom(close, length_14)
momentum_pct = (momentum / close ) * 100
// 6. Rate of Change (ROC)
roc = ta.roc(close, length_14)
// 7. Commodity Channel Index (CCI)
cci = ta.cci(close, length_20)
// 8. Money Flow Index (MFI)
mfi = ta.mfi(close, length_14)
mfi_centered = mfi - 50
// 9. Awesome Oscillator (AO)
ao = ta.sma(hl2, 5) - ta.sma(hl2, 34)
// 10. Accelerator Oscillator (AC)
ac = ao - ta.sma(ao, 5)
// 11. Chande Momentum Oscillator (CMO)
cmo = ta.cmo(close, length_14)
// 12. Detrended Price Oscillator (DPO)
dpo = close - ta.sma(close, length_20)
// 13. Price Oscillator (PPO)
ppo = ta.sma(close, 12) - ta.sma(close, 26)
ppo_pct = (ppo / ta.sma(close, 26)) * 100
// 14. TRIX
trix_ema1 = ta.ema(close, length_14)
trix_ema2 = ta.ema(trix_ema1, length_14)
trix_ema3 = ta.ema(trix_ema2, length_14)
trix = ta.roc(trix_ema3, 1) * 10000
// 15. Klinger Oscillator
klinger = ta.ema(volume * (high + low + close) / 3, 34) - ta.ema(volume * (high + low + close) / 3, 55)
// 16. Fisher Transform
fisher_hl2 = 0.5 * (hl2 - ta.lowest(hl2, 10)) / (ta.highest(hl2, 10) - ta.lowest(hl2, 10)) - 0.25
fisher = 0.5 * math.log((1 + fisher_hl2) / (1 - fisher_hl2))
// 17. Stochastic RSI
stoch_rsi = ta.stoch(rsi_14, rsi_14, rsi_14, length_14)
stoch_rsi_centered = stoch_rsi - 50
// 18. Relative Vigor Index (RVI)
rvi_num = ta.swma(close - open)
rvi_den = ta.swma(high - low)
rvi = rvi_den != 0 ? rvi_num / rvi_den : 0
// 19. Balance of Power (BOP)
bop = (close - open) / (high - low)
// |----- TREND INDICATORS (10 indicators) -----| //
// 20. Simple Moving Average Momentum
sma_20 = ta.sma(close, length_20)
sma_momentum = ((close - sma_20) / sma_20) * 100
// 21. Exponential Moving Average Momentum
ema_20 = ta.ema(close, length_20)
ema_momentum = ((close - ema_20) / ema_20) * 100
// 22. Parabolic SAR
sar = ta.sar(0.02, 0.02, 0.2)
sar_trend = close > sar ? 1 : -1
// 23. Linear Regression Slope
lr_slope = ta.linreg(close, length_20, 0) - ta.linreg(close, length_20, 1)
// 24. Moving Average Convergence (MAC)
mac = ta.sma(close, 10) - ta.sma(close, 30)
// 25. Trend Intensity Index (TII)
tii_sum = 0.0
for i = 1 to length_20
tii_sum += close > close ? 1 : 0
tii = (tii_sum / length_20) * 100
// 26. Ichimoku Cloud Components
ichimoku_tenkan = (ta.highest(high, 9) + ta.lowest(low, 9)) / 2
ichimoku_kijun = (ta.highest(high, 26) + ta.lowest(low, 26)) / 2
ichimoku_signal = ichimoku_tenkan > ichimoku_kijun ? 1 : -1
// 27. MESA Adaptive Moving Average (MAMA)
mama_alpha = 2.0 / (length_20 + 1)
mama = ta.ema(close, length_20)
mama_momentum = ((close - mama) / mama) * 100
// 28. Zero Lag Exponential Moving Average (ZLEMA)
zlema_lag = math.round((length_20 - 1) / 2)
zlema_data = close + (close - close )
zlema = ta.ema(zlema_data, length_20)
zlema_momentum = ((close - zlema) / zlema) * 100
// |----- VOLUME INDICATORS (6 indicators) -----| //
// 29. On-Balance Volume (OBV)
obv = ta.obv
// 30. Volume Rate of Change (VROC)
vroc = ta.roc(volume, length_14)
// 31. Price Volume Trend (PVT)
pvt = ta.pvt
// 32. Negative Volume Index (NVI)
nvi = 0.0
nvi := volume < volume ? nvi + ((close - close ) / close ) * nvi : nvi
// 33. Positive Volume Index (PVI)
pvi = 0.0
pvi := volume > volume ? pvi + ((close - close ) / close ) * pvi : pvi
// 34. Volume Oscillator
vol_osc = ta.sma(volume, 5) - ta.sma(volume, 10)
// 35. Ease of Movement (EOM)
eom_distance = high - low
eom_box_height = volume / 1000000
eom = eom_box_height != 0 ? eom_distance / eom_box_height : 0
eom_sma = ta.sma(eom, length_14)
// 36. Force Index
force_index = volume * (close - close )
force_index_sma = ta.sma(force_index, length_14)
// |----- VOLATILITY INDICATORS (10 indicators) -----| //
// 37. Average True Range (ATR)
atr = ta.atr(length_14)
atr_pct = (atr / close) * 100
// 38. Bollinger Bands Position
bb_basis = ta.sma(close, length_20)
bb_dev = 2.0 * ta.stdev(close, length_20)
bb_upper = bb_basis + bb_dev
bb_lower = bb_basis - bb_dev
bb_position = bb_dev != 0 ? (close - bb_basis) / bb_dev : 0
bb_width = bb_dev != 0 ? (bb_upper - bb_lower) / bb_basis * 100 : 0
// 39. Keltner Channels Position
kc_basis = ta.ema(close, length_20)
kc_range = ta.ema(ta.tr, length_20)
kc_upper = kc_basis + (2.0 * kc_range)
kc_lower = kc_basis - (2.0 * kc_range)
kc_position = kc_range != 0 ? (close - kc_basis) / kc_range : 0
// 40. Donchian Channels Position
dc_upper = ta.highest(high, length_20)
dc_lower = ta.lowest(low, length_20)
dc_basis = (dc_upper + dc_lower) / 2
dc_position = (dc_upper - dc_lower) != 0 ? (close - dc_basis) / (dc_upper - dc_lower) : 0
// 41. Standard Deviation
std_dev = ta.stdev(close, length_20)
std_dev_pct = (std_dev / close) * 100
// 42. Relative Volatility Index (RVI)
rvi_up = ta.stdev(close > close ? close : 0, length_14)
rvi_down = ta.stdev(close < close ? close : 0, length_14)
rvi_total = rvi_up + rvi_down
rvi_volatility = rvi_total != 0 ? (rvi_up / rvi_total) * 100 : 50
// 43. Historical Volatility
hv_returns = math.log(close / close )
hv = ta.stdev(hv_returns, length_20) * math.sqrt(252) * 100
// 44. Garman-Klass Volatility
gk_vol = math.log(high/low) * math.log(high/low) - (2*math.log(2)-1) * math.log(close/open) * math.log(close/open)
gk_volatility = math.sqrt(ta.sma(gk_vol, length_20)) * 100
// 45. Parkinson Volatility
park_vol = math.log(high/low) * math.log(high/low)
parkinson = math.sqrt(ta.sma(park_vol, length_20) / (4 * math.log(2))) * 100
// 46. Rogers-Satchell Volatility
rs_vol = math.log(high/close) * math.log(high/open) + math.log(low/close) * math.log(low/open)
rogers_satchell = math.sqrt(ta.sma(rs_vol, length_20)) * 100
// |----- OSCILLATOR INDICATORS (5 indicators) -----| //
// 47. Elder Ray Index
elder_bull = high - ta.ema(close, 13)
elder_bear = low - ta.ema(close, 13)
elder_power = elder_bull + elder_bear
// 48. Schaff Trend Cycle (STC)
stc_macd = ta.ema(close, 23) - ta.ema(close, 50)
stc_k = ta.stoch(stc_macd, stc_macd, stc_macd, 10)
stc_d = ta.ema(stc_k, 3)
stc = ta.stoch(stc_d, stc_d, stc_d, 10)
// 49. Coppock Curve
coppock_roc1 = ta.roc(close, 14)
coppock_roc2 = ta.roc(close, 11)
coppock = ta.wma(coppock_roc1 + coppock_roc2, 10)
// 50. Know Sure Thing (KST)
kst_roc1 = ta.roc(close, 10)
kst_roc2 = ta.roc(close, 15)
kst_roc3 = ta.roc(close, 20)
kst_roc4 = ta.roc(close, 30)
kst = ta.sma(kst_roc1, 10) + 2*ta.sma(kst_roc2, 10) + 3*ta.sma(kst_roc3, 10) + 4*ta.sma(kst_roc4, 15)
// 51. Percentage Price Oscillator (PPO)
ppo_line = ((ta.ema(close, 12) - ta.ema(close, 26)) / ta.ema(close, 26)) * 100
ppo_signal = ta.ema(ppo_line, 9)
ppo_histogram = ppo_line - ppo_signal
// |----- PLOT MAIN INDICATORS -----| //
// Plot key momentum indicators
plot(rsi_centered, title="01_RSI_Centered", color=color.purple, linewidth=1)
plot(stoch_centered, title="02_Stoch_Centered", color=color.blue, linewidth=1)
plot(williams_r, title="03_Williams_R", color=color.red, linewidth=1)
plot(macd_histogram, title="04_MACD_Histogram", color=color.orange, linewidth=1)
plot(cci, title="05_CCI", color=color.green, linewidth=1)
// Plot trend indicators
plot(sma_momentum, title="06_SMA_Momentum", color=color.navy, linewidth=1)
plot(ema_momentum, title="07_EMA_Momentum", color=color.maroon, linewidth=1)
plot(sar_trend, title="08_SAR_Trend", color=color.teal, linewidth=1)
plot(lr_slope, title="09_LR_Slope", color=color.lime, linewidth=1)
plot(mac, title="10_MAC", color=color.fuchsia, linewidth=1)
// Plot volatility indicators
plot(atr_pct, title="11_ATR_Pct", color=color.yellow, linewidth=1)
plot(bb_position, title="12_BB_Position", color=color.aqua, linewidth=1)
plot(kc_position, title="13_KC_Position", color=color.olive, linewidth=1)
plot(std_dev_pct, title="14_StdDev_Pct", color=color.silver, linewidth=1)
plot(bb_width, title="15_BB_Width", color=color.gray, linewidth=1)
// Plot volume indicators
plot(vroc, title="16_VROC", color=color.blue, linewidth=1)
plot(eom_sma, title="17_EOM", color=color.red, linewidth=1)
plot(vol_osc, title="18_Vol_Osc", color=color.green, linewidth=1)
plot(force_index_sma, title="19_Force_Index", color=color.orange, linewidth=1)
plot(obv, title="20_OBV", color=color.purple, linewidth=1)
// Plot additional oscillators
plot(ao, title="21_Awesome_Osc", color=color.navy, linewidth=1)
plot(cmo, title="22_CMO", color=color.maroon, linewidth=1)
plot(dpo, title="23_DPO", color=color.teal, linewidth=1)
plot(trix, title="24_TRIX", color=color.lime, linewidth=1)
plot(fisher, title="25_Fisher", color=color.fuchsia, linewidth=1)
// Plot more momentum indicators
plot(mfi_centered, title="26_MFI_Centered", color=color.yellow, linewidth=1)
plot(ac, title="27_AC", color=color.aqua, linewidth=1)
plot(ppo_pct, title="28_PPO_Pct", color=color.olive, linewidth=1)
plot(stoch_rsi_centered, title="29_StochRSI_Centered", color=color.silver, linewidth=1)
plot(klinger, title="30_Klinger", color=color.gray, linewidth=1)
// Plot trend continuation
plot(tii, title="31_TII", color=color.blue, linewidth=1)
plot(ichimoku_signal, title="32_Ichimoku_Signal", color=color.red, linewidth=1)
plot(mama_momentum, title="33_MAMA_Momentum", color=color.green, linewidth=1)
plot(zlema_momentum, title="34_ZLEMA_Momentum", color=color.orange, linewidth=1)
plot(bop, title="35_BOP", color=color.purple, linewidth=1)
// Plot volume continuation
plot(nvi, title="36_NVI", color=color.navy, linewidth=1)
plot(pvi, title="37_PVI", color=color.maroon, linewidth=1)
plot(momentum_pct, title="38_Momentum_Pct", color=color.teal, linewidth=1)
plot(roc, title="39_ROC", color=color.lime, linewidth=1)
plot(rvi, title="40_RVI", color=color.fuchsia, linewidth=1)
// Plot volatility continuation
plot(dc_position, title="41_DC_Position", color=color.yellow, linewidth=1)
plot(rvi_volatility, title="42_RVI_Volatility", color=color.aqua, linewidth=1)
plot(hv, title="43_Historical_Vol", color=color.olive, linewidth=1)
plot(gk_volatility, title="44_GK_Volatility", color=color.silver, linewidth=1)
plot(parkinson, title="45_Parkinson_Vol", color=color.gray, linewidth=1)
// Plot final oscillators
plot(rogers_satchell, title="46_RS_Volatility", color=color.blue, linewidth=1)
plot(elder_power, title="47_Elder_Power", color=color.red, linewidth=1)
plot(stc, title="48_STC", color=color.green, linewidth=1)
plot(coppock, title="49_Coppock", color=color.orange, linewidth=1)
plot(kst, title="50_KST", color=color.purple, linewidth=1)
// Plot final indicators
plot(ppo_histogram, title="51_PPO_Histogram", color=color.navy, linewidth=1)
plot(pvt, title="52_PVT", color=color.maroon, linewidth=1)
// |----- Reference Lines -----| //
hline(0, "Zero Line", color=color.gray, linestyle=hline.style_dashed, linewidth=1)
hline(50, "Midline", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
hline(-50, "Lower Midline", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
hline(25, "Upper Threshold", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
hline(-25, "Lower Threshold", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
// |----- Enhanced Information Table -----| //
if show_table and barstate.islast
table_position = position.top_right
table_text_size = table_size == "Tiny" ? size.tiny : table_size == "Small" ? size.small : size.normal
var table info_table = table.new(table_position, 3, 18, bgcolor=color.new(color.white, 85), border_width=1, border_color=color.gray)
// Headers
table.cell(info_table, 0, 0, 'Category', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70))
table.cell(info_table, 1, 0, 'Indicator', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70))
table.cell(info_table, 2, 0, 'Value', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70))
// Key Momentum Indicators
table.cell(info_table, 0, 1, 'MOMENTUM', text_color=color.purple, text_size=table_text_size, bgcolor=color.new(color.purple, 90))
table.cell(info_table, 1, 1, 'RSI Centered', text_color=color.purple, text_size=table_text_size)
table.cell(info_table, 2, 1, str.tostring(rsi_centered, '0.00'), text_color=color.purple, text_size=table_text_size)
table.cell(info_table, 0, 2, '', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 1, 2, 'Stoch Centered', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 2, 2, str.tostring(stoch_centered, '0.00'), text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 0, 3, '', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 1, 3, 'Williams %R', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 2, 3, str.tostring(williams_r, '0.00'), text_color=color.red, text_size=table_text_size)
table.cell(info_table, 0, 4, '', text_color=color.orange, text_size=table_text_size)
table.cell(info_table, 1, 4, 'MACD Histogram', text_color=color.orange, text_size=table_text_size)
table.cell(info_table, 2, 4, str.tostring(macd_histogram, '0.000'), text_color=color.orange, text_size=table_text_size)
table.cell(info_table, 0, 5, '', text_color=color.green, text_size=table_text_size)
table.cell(info_table, 1, 5, 'CCI', text_color=color.green, text_size=table_text_size)
table.cell(info_table, 2, 5, str.tostring(cci, '0.00'), text_color=color.green, text_size=table_text_size)
// Key Trend Indicators
table.cell(info_table, 0, 6, 'TREND', text_color=color.navy, text_size=table_text_size, bgcolor=color.new(color.navy, 90))
table.cell(info_table, 1, 6, 'SMA Momentum %', text_color=color.navy, text_size=table_text_size)
table.cell(info_table, 2, 6, str.tostring(sma_momentum, '0.00'), text_color=color.navy, text_size=table_text_size)
table.cell(info_table, 0, 7, '', text_color=color.maroon, text_size=table_text_size)
table.cell(info_table, 1, 7, 'EMA Momentum %', text_color=color.maroon, text_size=table_text_size)
table.cell(info_table, 2, 7, str.tostring(ema_momentum, '0.00'), text_color=color.maroon, text_size=table_text_size)
table.cell(info_table, 0, 8, '', text_color=color.teal, text_size=table_text_size)
table.cell(info_table, 1, 8, 'SAR Trend', text_color=color.teal, text_size=table_text_size)
table.cell(info_table, 2, 8, str.tostring(sar_trend, '0'), text_color=color.teal, text_size=table_text_size)
table.cell(info_table, 0, 9, '', text_color=color.lime, text_size=table_text_size)
table.cell(info_table, 1, 9, 'Linear Regression', text_color=color.lime, text_size=table_text_size)
table.cell(info_table, 2, 9, str.tostring(lr_slope, '0.000'), text_color=color.lime, text_size=table_text_size)
// Key Volatility Indicators
table.cell(info_table, 0, 10, 'VOLATILITY', text_color=color.yellow, text_size=table_text_size, bgcolor=color.new(color.yellow, 90))
table.cell(info_table, 1, 10, 'ATR %', text_color=color.yellow, text_size=table_text_size)
table.cell(info_table, 2, 10, str.tostring(atr_pct, '0.00'), text_color=color.yellow, text_size=table_text_size)
table.cell(info_table, 0, 11, '', text_color=color.aqua, text_size=table_text_size)
table.cell(info_table, 1, 11, 'BB Position', text_color=color.aqua, text_size=table_text_size)
table.cell(info_table, 2, 11, str.tostring(bb_position, '0.00'), text_color=color.aqua, text_size=table_text_size)
table.cell(info_table, 0, 12, '', text_color=color.olive, text_size=table_text_size)
table.cell(info_table, 1, 12, 'KC Position', text_color=color.olive, text_size=table_text_size)
table.cell(info_table, 2, 12, str.tostring(kc_position, '0.00'), text_color=color.olive, text_size=table_text_size)
// Key Volume Indicators
table.cell(info_table, 0, 13, 'VOLUME', text_color=color.blue, text_size=table_text_size, bgcolor=color.new(color.blue, 90))
table.cell(info_table, 1, 13, 'Volume ROC', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 2, 13, str.tostring(vroc, '0.00'), text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 0, 14, '', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 1, 14, 'EOM', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 2, 14, str.tostring(eom_sma, '0.000'), text_color=color.red, text_size=table_text_size)
// Key Oscillators
table.cell(info_table, 0, 15, 'OSCILLATORS', text_color=color.purple, text_size=table_text_size, bgcolor=color.new(color.purple, 90))
table.cell(info_table, 1, 15, 'Awesome Osc', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 2, 15, str.tostring(ao, '0.000'), text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 0, 16, '', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 1, 16, 'Fisher Transform', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 2, 16, str.tostring(fisher, '0.000'), text_color=color.red, text_size=table_text_size)
// Summary Statistics
table.cell(info_table, 0, 17, 'SUMMARY', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.gray, 70))
table.cell(info_table, 1, 17, 'Total Indicators: 52', text_color=color.black, text_size=table_text_size)
regime_color = rsi_centered > 10 ? color.green : rsi_centered < -10 ? color.red : color.gray
regime_text = rsi_centered > 10 ? "BULLISH" : rsi_centered < -10 ? "BEARISH" : "NEUTRAL"
table.cell(info_table, 2, 17, regime_text, text_color=regime_color, text_size=table_text_size)
This makes it the perfect “indicator backbone” for quantitative and systematic traders who want to prototype, combine, and test new regime detection models—especially in combination with the Markov Chain indicator.
How to use this script with the Markov Chain for research and backtesting:
Add the Enhanced Indicator Export to your chart.
Every calculated indicator is available as an individual data stream.
Connect the indicator(s) you want as custom input(s) to the Markov Chain’s “Custom Indicators” option.
In the Markov Chain indicator’s settings, turn ON the custom indicator mode.
For each of the three custom indicator inputs, select the exported plot from the Enhanced Export script—the menu lists all 45+ signals by name.
This creates a powerful, modular regime-detection engine where you can mix-and-match momentum, trend, volume, or custom combinations for advanced filtering.
Backtest regime logic directly.
Once you’ve connected your chosen indicators, the Markov Chain script performs regime detection (Bull/Neutral/Bear) based on your selected features—not just price returns.
The regime detection is robust, automatically normalized (using Z-score), and outputs bias (1, -1, 0) for plug-and-play integration.
Export the regime bias for programmatic use.
As described above, use input.source() in your Pine Script strategy or system and link the bias output.
You can now filter signals, control trade direction/size, or design pairs-trading that respect true, indicator-driven market regimes.
With this framework, you’re not limited to static or simplistic regime filters. You can rigorously define, test, and refine what “market regime” means for your strategies—using the technical features that matter most to you.
Optimize your signal generation by backtesting across a universe of meaningful indicator blends.
Enhance risk management with objective, real-time regime boundaries.
Accelerate your research: iterate quickly, swap indicator components, and see results with minimal code changes.
Automate multi-asset or pairs-trading by integrating regime context directly into strategy logic.
Add both scripts to your chart, connect your preferred features, and start investigating your best regime-based trades—entirely within the TradingView ecosystem.
References & Further Reading
Ang, A., & Bekaert, G. (2002). “Regime Switches in Interest Rates.” Journal of Business & Economic Statistics, 20(2), 163–182.
Hamilton, J. D. (1989). “A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle.” Econometrica, 57(2), 357–384.
Markov, A. A. (1906). "Extension of the Limit Theorems of Probability Theory to a Sum of Variables Connected in a Chain." The Notes of the Imperial Academy of Sciences of St. Petersburg.
Guidolin, M., & Timmermann, A. (2007). “Asset Allocation under Multivariate Regime Switching.” Journal of Economic Dynamics and Control, 31(11), 3503–3544.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets. New York Institute of Finance.
Brock, W., Lakonishok, J., & LeBaron, B. (1992). “Simple Technical Trading Rules and the Stochastic Properties of Stock Returns.” Journal of Finance, 47(5), 1731–1764.
Zucchini, W., MacDonald, I. L., & Langrock, R. (2017). Hidden Markov Models for Time Series: An Introduction Using R (2nd ed.). Chapman and Hall/CRC.
On Quantitative Finance and Markov Models:
Lo, A. W., & Hasanhodzic, J. (2009). The Heretics of Finance: Conversations with Leading Practitioners of Technical Analysis. Bloomberg Press.
Patterson, S. (2016). The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution. Penguin Press.
TradingView Pine Script Documentation: www.tradingview.com
TradingView Blog: “Use an Input From Another Indicator With Your Strategy” www.tradingview.com
GeeksforGeeks: “What is the Difference Between Markov Chains and Hidden Markov Models?” www.geeksforgeeks.org
What makes this indicator original and unique?
- On‑chart, real‑time Markov. The chain is drawn directly on your chart. You see the current regime, its tendency to stay (self‑loop), and the usual next step (arrows) as bars confirm.
- Source‑agnostic by design. The engine runs on any series you select via input.source() — price, your own oscillator, a composite score, anything you compute in the script.
- Automatic normalization + regime mapping. Different inputs live on different scales. The script standardizes your chosen source and maps it into clear regimes (e.g., Bull / Bear / Neutral) without you micromanaging thresholds each time.
- Rolling, bar‑by‑bar learning. Transition tendencies are computed from a rolling window of confirmed bars. What you see is exactly what the market did in that window.
- Fast experimentation. Switch the source, adjust the window, and the Markov view updates instantly. It’s a rapid way to test ideas and feel regime persistence/switch behavior.
Integrate your own signals (using input.source())
- In settings, choose the Source . This is powered by input.source() .
- Feed it price, an indicator you compute inside the script, or a custom composite series.
- The script will automatically normalize that series and process it through the Markov engine, mapping it to regimes and updating the on‑chart spheres/arrows in real time.
Credits:
Deep gratitude to @RicardoSantos for both the foundational Markov chain processing engine and inspiring open-source contributions, which made advanced probabilistic market modeling accessible to the TradingView community.
Special thanks to @Alien_Algorithms for the innovative and visually stunning 3D sphere logic that powers the indicator’s animated, regime-based visualization.
Disclaimer
This tool summarizes recent behavior. It is not financial advice and not a guarantee of future results.
EAOBS by MIGVersion 1
1. Strategy Overview Objective: Capitalize on breakout movements in Ethereum (ETH) price after the Asian open pre-market session (7:00 PM–7:59 PM EST) by identifying high and low prices during the session and trading breakouts above the high or below the low.
Timeframe: Any (script is timeframe-agnostic, but align with session timing).
Session: Pre-market session (7:00 PM–7:59 PM EST, adjustable for other time zones, e.g., 12:00 AM–12:59 AM GMT).
Risk-Reward Ratios (R:R): Targets range from 1.2:1 to 5.2:1, with a fixed stop loss.
Instrument: Ethereum (ETH/USD or ETH-based pairs).
2. Market Setup Session Monitoring: Monitor ETH price action during the pre-market session (7:00 PM–7:59 PM EST), which aligns with the Asian market open (e.g., 9:00 AM–9:59 AM JST).
The script tracks the highest high and lowest low during this session.
Breakout Triggers: Buy Signal: Price breaks above the session’s high after the session ends (7:59 PM EST).
Sell Signal: Price breaks below the session’s low after the session ends.
Visualization: The session is highlighted on the chart with a white background.
Horizontal lines are drawn at the session’s high and low, extended for 30 bars, along with take-profit (TP) and stop-loss (SL) levels.
3. Entry Rules Long (Buy) Entry: Enter a long position when the price breaks above the session’s high price after 7:59 PM EST.
Entry price: Just above the session high (e.g., add a small buffer, like 0.1–0.5%, to avoid false breakouts, depending on volatility).
Short (Sell) Entry: Enter a short position when the price breaks below the session’s low price after 7:59 PM EST.
Entry price: Just below the session low (e.g., subtract a small buffer, like 0.1–0.5%).
Confirmation: Use a candlestick close above/below the breakout level to confirm the entry.
Optionally, add volume confirmation or a momentum indicator (e.g., RSI or MACD) to filter out weak breakouts.
Position Size: Calculate position size based on risk tolerance (e.g., 1–2% of account per trade).
Risk is determined by the stop-loss distance (10 points, as defined in the script).
4. Exit Rules Take-Profit Levels (in points, based on script inputs):TP1: 12 points (1.2:1 R:R).
TP2: 22 points (2.2:1 R:R).
TP3: 32 points (3.2:1 R:R).
TP4: 42 points (4.2:1 R:R).
TP5: 52 points (5.2:1 R:R).
Example for Long: If session high is 3000, TP levels are 3012, 3022, 3032, 3042, 3052.
Example for Short: If session low is 2950, TP levels are 2938, 2928, 2918, 2908, 2898.
Strategy: Scale out of the position (e.g., close 20% at TP1, 20% at TP2, etc.) or take full profit at a preferred TP level based on market conditions.
Stop-Loss: Fixed at 10 points from the entry.
Long SL: Session high - 10 points (e.g., entry at 3000, SL at 2990).
Short SL: Session low + 10 points (e.g., entry at 2950, SL at 2960).
Trailing Stop (Optional):After reaching TP2 or TP3, consider trailing the stop to lock in profits (e.g., trail by 10–15 points below the current price).
5. Risk Management per Trade: Limit risk to 1–2% of your trading account per trade.
Calculate position size: Account Size × Risk % ÷ (Stop-Loss Distance × ETH Price per Point).
Example: $10,000 account, 1% risk = $100. If SL = 10 points and 1 point = $1, position size = $100 ÷ 10 = 0.1 ETH.
Daily Risk Limit: Cap daily losses at 3–5% of the account to avoid overtrading.
Maximum Exposure: Avoid taking both long and short positions simultaneously unless using separate accounts or strategies.
Volatility Consideration: Adjust position size during high-volatility periods (e.g., major news events like Ethereum upgrades or macroeconomic announcements).
6. Trade Management Monitoring :Watch for breakouts after 7:59 PM EST.
Monitor price action near TP and SL levels using alerts or manual checks.
Trade Duration: Breakout lines extend for 30 bars (script parameter). Close trades if no TP or SL is hit within this period, or reassess based on market conditions.
Adjustments: If the market shows strong momentum, consider holding beyond TP5 with a trailing stop.
If the breakout fails (e.g., price reverses before TP1), exit early to minimize losses.
7. Additional Considerations Market Conditions: The 7:00 PM–7:59 PM EST session aligns with the Asian market open (e.g., Tokyo Stock Exchange open at 9:00 AM JST), which may introduce higher volatility due to Asian trading activity.
Avoid trading during low-liquidity periods or extreme volatility (e.g., major crypto news).
Check for upcoming events (e.g., Ethereum network upgrades, ETF decisions) that could impact price.
Backtesting: Test the strategy on historical ETH data using the session high/low breakouts for the 7:00 PM–7:59 PM EST window to validate performance.
Adjust TP/SL levels based on backtest results if needed.
Broker and Fees: Use a low-fee crypto exchange (e.g., Binance, Kraken, Coinbase Pro) to maximize R:R.
Account for trading fees and slippage in your position sizing.
Time zone Adjustment: Adjust session time input for your time zone (e.g., "0000-0059" for GMT).
Ensure your trading platform’s clock aligns with the script’s time zone (default: America/New_York).
8. Example Trade Scenario: Session (7:00 PM–7:59 PM EST) records a high of 3050 and a low of 3000.
Long Trade: Entry: Price breaks above 3050 (e.g., enter at 3051).
TP Levels: 3063 (TP1), 3073 (TP2), 3083 (TP3), 3093 (TP4), 3103 (TP5).
SL: 3040 (3050 - 10).
Position Size: For a $10,000 account, 1% risk = $100. SL = 11 points ($11). Size = $100 ÷ 11 = ~0.09 ETH.
Short Trade: Entry: Price breaks below 3000 (e.g., enter at 2999).
TP Levels: 2987 (TP1), 2977 (TP2), 2967 (TP3), 2957 (TP4), 2947 (TP5).
SL: 3010 (3000 + 10).
Position Size: Same as above, ~0.09 ETH.
Execution: Set alerts for breakouts, enter with limit orders, and monitor TPs/SL.
9. Tools and Setup Platform: Use TradingView to implement the Pine Script and visualize breakout levels.
Alerts: Set price alerts for breakouts above the session high or below the session low after 7:59 PM EST.
Set alerts for TP and SL levels.
Chart Settings: Use a 1-minute or 5-minute chart for precise session tracking.
Overlay the script to see high/low lines, TP levels, and SL levels.
Optional Indicators: Add RSI (e.g., avoid overbought/oversold breakouts) or volume to confirm breakouts.
10. Risk Warnings Crypto Volatility: ETH is highly volatile; unexpected news can cause rapid price swings.
False Breakouts: Breakouts may fail, especially in low-volume sessions. Use confirmation signals.
Leverage: Avoid high leverage (e.g., >5x) to prevent liquidation during volatile moves.
Session Accuracy: Ensure correct session timing for your time zone to avoid misaligned entries.
11. Performance Tracking Journaling :Record each trade’s entry, exit, R:R, and outcome.
Note market conditions (e.g., trending, ranging, news-driven).
Review: Weekly: Assess win rate, average R:R, and adherence to the plan.
Monthly: Adjust TP/SL or session timing based on performance.
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).
________________________________________
## 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.
________________________________________
## 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.
________________________________________
## 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.
________________________________________
## 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
Top-Down Trend and Key Levels with Swing Points//by antaryaami0
Overview
The “Top-Down Trend and Key Levels with Swing Points” indicator is a comprehensive tool designed to enhance your technical analysis by integrating multiple trading concepts into a single, easy-to-use script. It combines higher timeframe trend analysis, key price levels, swing point detection, and ranging market identification to provide a holistic view of market conditions. This indicator is particularly useful for traders who employ multi-timeframe analysis, support and resistance levels, and price action strategies.
Key Features
1. Higher Timeframe Trend Background Shading:
• Purpose: Identifies the prevailing trend on a higher timeframe to align lower timeframe trading decisions with the broader market direction.
• How it Works: The indicator compares the current higher timeframe close with the previous one to determine if the trend is up, down, or ranging.
• Customization:
• Trend Timeframe: Set your preferred higher timeframe (e.g., Daily, Weekly).
• Up Trend Color & Down Trend Color: Customize the background colors for uptrends and downtrends.
• Ranging Market Color: A separate color to indicate when the market is moving sideways.
2. Key Price Levels:
• Previous Day High (PDH) and Low (PDL):
• Purpose: Identifies key support and resistance levels from the previous trading day.
• Visualization: Plots horizontal lines at PDH and PDL with labels.
• Customization: Option to show or hide these levels and customize their colors.
• Pre-Market High (PMH) and Low (PML):
• Purpose: Highlights the price range during the pre-market session, which can indicate potential breakout levels.
• Visualization: Plots horizontal lines at PMH and PML with labels.
• Customization: Option to show or hide these levels and customize their colors.
3. First 5-Minute Marker (F5H/F5L):
• Purpose: Marks the high or low of the first 5 minutes after the market opens, which is significant for intraday momentum.
• How it Works:
• If the first 5-minute high is above the Pre-Market High (PMH), an “F5H” label is placed at the first 5-minute high.
• If the first 5-minute high is below the PMH, an “F5L” label is placed at the first 5-minute low.
• Visualization: Labels are placed at the 9:35 AM candle (closing of the first 5 minutes), colored in purple by default.
• Customization: Option to show or hide the marker and adjust the marker color.
4. Swing Points Detection:
• Purpose: Identifies significant pivot points in price action to help recognize trends and reversals.
• How it Works: Uses left and right bars to detect pivot highs and lows, then determines if they are Higher Highs (HH), Lower Highs (LH), Higher Lows (HL), or Lower Lows (LL).
• Visualization: Plots small markers (circles) with labels (HH, LH, HL, LL) at the corresponding swing points.
• Customization: Adjust the number of left and right bars for pivot detection and the size of the markers.
5. Ranging Market Detection:
• Purpose: Identifies periods when the market is consolidating (moving sideways) within a defined price range.
• How it Works: Calculates the highest high and lowest low over a specified period and determines if the price range is within a set percentage threshold.
• Visualization: Draws a gray box around the price action during the ranging period and labels the high and low prices at the end of the range.
• Customization: Adjust the range detection period and threshold, as well as the box color.
6. Trend Coloring on Chart:
• Purpose: Provides a visual cue for the short-term trend based on a moving average.
• How it Works: Colors the candles green if the price is above the moving average and red if below.
• Customization: Set the moving average length and customize the uptrend and downtrend colors.
How to Use the Indicator
1. Adding the Indicator to Your Chart:
• Copy the Pine Script code provided and paste it into the Pine Script Editor on TradingView.
• Click “Add to Chart” to apply the indicator.
2. Configuring Inputs and Settings:
• Access Inputs:
• Click on the gear icon next to the indicator’s name on your chart to open the settings.
• Customize Key Levels:
• Show Pre-Market High/Low: Toggle on/off.
• Show Previous Day High/Low: Toggle on/off.
• Show First 5-Minute Marker: Toggle on/off.
• Set Trend Parameters:
• Trend Timeframe for Background: Choose the higher timeframe for trend analysis.
• Moving Average Length for Bar Color: Set the period for the moving average used in bar coloring.
• Adjust Ranging Market Detection:
• Range Detection Period: Specify the number of bars to consider for range detection.
• Range Threshold (%): Set the maximum percentage range for the market to be considered ranging.
• Customize Visuals:
• Colors: Adjust colors for trends, levels, markers, and ranging market boxes.
• Label Font Size: Choose the size of labels displayed on the chart.
• Level Line Width: Set the thickness of the lines for key levels.
3. Interpreting the Indicator:
• Background Shading:
• Green Shade: Higher timeframe is in an uptrend.
• Red Shade: Higher timeframe is in a downtrend.
• Gray Box: Market is ranging (sideways movement).
• Key Levels and Markers:
• PDH and PDL Lines: Represent resistance and support from the previous day.
• PMH and PML Lines: Indicate potential breakout levels based on pre-market activity.
• F5H/F5L Labels: Early indication of intraday momentum after market open.
• Swing Point Markers:
• HH (Higher High): Suggests bullish momentum.
• LH (Lower High): May indicate a potential bearish reversal.
• HL (Higher Low): Supports bullish continuation.
• LL (Lower Low): Indicates bearish momentum.
• Ranging Market Box:
• Gray Box Around Price Action: Highlights consolidation periods where breakouts may occur.
• Range High and Low Labels: Provide the upper and lower bounds of the consolidation zone.
4. Applying the Indicator to Your Trading Strategy:
• Trend Alignment:
• Use the higher timeframe trend shading to align your trades with the broader market direction.
• Key Levels Trading:
• Watch for price reactions at PDH, PDL, PMH, and PML for potential entry and exit points.
• Swing Points Analysis:
• Identify trend continuations or reversals by observing the sequence of HH, HL, LH, and LL.
• Ranging Market Strategies:
• During ranging periods, consider range-bound trading strategies or prepare for breakout trades when the price exits the range.
• Intraday Momentum:
• Use the F5H/F5L marker to gauge early market sentiment and potential intraday trends.
Practical Tips
• Adjust Settings to Your Trading Style:
• Tailor the indicator’s inputs to match your preferred timeframes and trading instruments.
• Combine with Other Indicators:
• Use in conjunction with volume indicators, oscillators, or other technical tools for additional confirmation.
• Backtesting:
• Apply the indicator to historical data to observe how it performs and refine your settings accordingly.
• Stay Updated on Market Conditions:
• Be aware of news events or economic releases that may impact market behavior and the effectiveness of technical levels.
Customization Options
• Time Zone Adjustment:
• The script uses “America/New_York” time zone by default. Adjust the timezone variable in the script if your chart operates in a different time zone.
var timezone = "Your/Timezone"
• Session Times:
• Modify the Regular Trading Session and Pre-Market Session times in the indicator settings to align with the trading hours of different markets or exchanges.
• Visual Preferences:
• Colors: Personalize the indicator’s colors to suit your visual preferences or to enhance visibility.
• Label Sizes: Adjust label sizes if you find them too intrusive or not prominent enough.
• Marker Sizes: Further reduce or enlarge the swing point markers by modifying the swing_marker_size variable.
Understanding the Indicator’s Logic
1. Higher Timeframe Trend Analysis:
• The indicator retrieves the closing prices of a higher timeframe using the request.security() function.
• It compares the current higher timeframe close with the previous one to determine the trend direction.
2. Key Level Calculation:
• Previous Day High/Low: Calculated by tracking the highest and lowest prices of the previous trading day.
• Pre-Market High/Low: Calculated by monitoring price action during the pre-market session.
3. First 5-Minute Marker Logic:
• At 9:35 AM (end of the first 5 minutes after market open), the indicator evaluates whether the first 5-minute high is above or below the PMH.
• It then places the appropriate label (F5H or F5L) on the chart.
4. Swing Points Detection:
• The script uses ta.pivothigh() and ta.pivotlow() functions to detect pivot points.
• It then determines the type of swing point based on comparisons with previous swings.
5. Ranging Market Detection:
• The indicator looks back over a specified number of bars to find the highest high and lowest low.
• It calculates the percentage difference between these two points.
• If the difference is below the set threshold, the market is considered to be ranging, and a box is drawn around the price action.
Limitations and Considerations
• Indicator Limitations:
• Maximum Boxes and Labels: Due to Pine Script limitations, there is a maximum number of boxes and labels that can be displayed simultaneously.
• Performance Impact: Adding multiple visual elements (boxes, labels, markers) can affect the performance of the script on lower-end devices or with large amounts of data.
• Market Conditions:
• False Signals: Like any technical tool, the indicator may produce false signals, especially during volatile or erratic market conditions.
• Not a Standalone Solution: This indicator should be used as part of a comprehensive trading strategy, including risk management and other forms of analysis.
Conclusion
The “Top-Down Trend and Key Levels with Swing Points” indicator is a versatile tool that integrates essential aspects of technical analysis into one script. By providing insights into higher timeframe trends, highlighting key price levels, detecting swing points, and identifying ranging markets, it equips traders with valuable information to make more informed trading decisions. Whether you are a day trader looking for intraday opportunities or a swing trader aiming to align with the broader trend, this indicator can enhance your chart analysis and trading strategy.
Disclaimer
Trading involves significant risk, and it’s important to understand that past performance is not indicative of future results. This indicator is a tool to assist in analysis and should not be solely relied upon for making trading decisions. Always conduct thorough research and consider seeking advice from financial professionals before engaging in trading activities.
Weekly H/L DOTWThe Weekly High/Low Day Breakdown indicator provides a detailed statistical analysis of the days of the week (Monday to Sunday) on which weekly highs and lows occur for a given timeframe. It helps traders identify recurring patterns, correlations, and tendencies in price behavior across different days of the week. This can assist in planning trading strategies by leveraging day-specific patterns.
The indicator visually displays the statistical distribution of weekly highs and lows in an easy-to-read tabular format on your chart. Users can customize how the data is displayed, including whether the table is horizontal or vertical, the size of the text, and the position of the table on the chart.
Key Features:
Weekly Highs and Lows Identification:
Tracks the highest and lowest price of each trading week.
Records the day of the week on which these events occur.
Customizable Table Layout:
Option to display the table horizontally or vertically.
Text size can be adjusted (Small, Normal, or Large).
Table position is customizable (top-right, top-left, bottom-right, or bottom-left of the chart).
Flexible Value Representation:
Allows the display of values as percentages or as occurrences.
Default setting is occurrences, but users can toggle to percentages as needed.
Day-Specific Display:
Option to hide Saturday or Sunday if these days are not relevant to your trading strategy.
Visible Date Range:
Users can define a start and end date for the analysis, focusing the results on a specific period of interest.
User-Friendly Interface:
The table dynamically updates based on the selected timeframe and visibility of the chart, ensuring the displayed data is always relevant to the current context.
Adaptable to Custom Needs:
Includes all-day names from Monday to Sunday, but allows for specific days to be excluded based on the user’s preferences.
Indicator Logic:
Data Collection:
The indicator collects daily high, low, day of the week, and time data from the selected ticker using the request.security() function with a daily timeframe ('D').
Weekly Tracking:
Tracks the start and end times of each week.
During each week, it monitors the highest and lowest prices and the days they occurred.
Weekly Closure:
When a week ends (detected by Sunday’s daily candle), the indicator:
Updates the statistics for the respective days of the week where the weekly high and low occurred.
Resets tracking variables for the next week.
Visible Range Filter:
Only processes data for weeks that fall within the visible range of the chart, ensuring the table reflects only the visible portion of the chart.
Statistical Calculations:
Counts the number of weekly highs and lows for each day.
Calculates percentages relative to the total number of weeks in the visible range.
Dynamic Table Display:
Depending on user preferences, displays the data either horizontally or vertically.
Formats the table with proper alignment, colors, and text sizes for easy readability.
Custom Value Representation:
If set to "percentages," displays the percentage of weeks a high/low occurred on each day.
If set to "occurrences," displays the raw count of weekly highs/lows for each day.
Input Parameters:
High Text Color:
Color for the text in the "Weekly High" row or column.
Low Text Color:
Color for the text in the "Weekly Low" row or column.
High Background Color:
Background color for the "Weekly High" row or column.
Low Background Color:
Background color for the "Weekly Low" row or column.
Table Background Color:
General background color for the table.
Hide Saturday:
Option to exclude Saturday from the analysis and table.
Hide Sunday:
Option to exclude Sunday from the analysis and table.
Values Format:
Dropdown menu to select "percentages" or "occurrences."
Default value: "occurrences."
Table Position:
Dropdown menu to select the table position on the chart: "top_right," "top_left," "bottom_right," "bottom_left."
Default value: "top_right."
Text Size:
Dropdown menu to select text size: "Small," "Normal," "Large."
Default value: "Normal."
Vertical Table Format:
Checkbox to toggle the table layout:
Checked: Table displays days vertically, with Monday at the top.
Unchecked: Table displays days horizontally.
Start Date:
Allows users to specify the starting date for the analysis.
End Date:
Allows users to specify the ending date for the analysis.
Use Cases:
Day-Specific Pattern Recognition:
Identify if specific days, such as Monday or Friday, are more likely to form weekly highs or lows.
Seasonal Analysis:
Use the start and end date filters to analyze patterns during specific trading seasons.
Strategy Development:
Plan day-based entry and exit strategies by identifying recurring patterns in weekly highs/lows.
Historical Review:
Study historical data to understand how market behavior has changed over time.
TradingView TOS Compliance Notes:
Originality:
This script is uniquely designed to provide day-based statistics for weekly highs and lows, which is not a common feature in other publicly available indicators.
Usefulness:
Offers practical insights for traders interested in understanding day-specific price behavior.
Detailed Description:
Fully explains the purpose, features, logic, input settings, and use cases of the indicator.
Includes clear and concise details on how each input works.
Clear Input Descriptions:
All input parameters are clearly named and explained in the script and this description.
No Redundant Functionality:
Focused specifically on tracking weekly highs and lows, ensuring the indicator serves a distinct purpose without unnecessary features.
Exposure Oscillator (Cumulative 0 to ±100%)
Exposure Oscillator (Cumulative 0 to ±100%)
This Pine Script indicator plots an "Exposure Oscillator" on the chart, which tracks the cumulative market exposure from a range of technical buy and sell signals. The exposure is measured on a scale from -100% (maximum short exposure) to +100% (maximum long exposure), helping traders assess the strength of their position in the market. It provides an intuitive visual cue to aid decision-making for trend-following strategies.
Buy Signals (Increase Exposure Score by +10%)
Buy Signal 1 (Cross Above 21 EMA):
This signal is triggered when the price crosses above the 21-period Exponential Moving Average (EMA), where the current bar closes above the EMA21, and the previous bar closed below the EMA21. This indicates a potential upward price movement as the market shifts into a bullish trend.
buySignal1 = ta.crossover(close, ema21)
Buy Signal 2 (Trending Above 21 EMA):
This signal is triggered when the price closes above the 21-period EMA for each of the last 5 bars, indicating a sustained bullish trend. It confirms that the price is consistently above the EMA21 for a significant period.
buySignal2 = ta.barssince(close <= ema21) > 5
Buy Signal 3 (Living Above 21 EMA):
This signal is triggered when the price has closed above the 21-period EMA for each of the last 15 bars, demonstrating a strong, prolonged uptrend.
buySignal3 = ta.barssince(close <= ema21) > 15
Buy Signal 4 (Cross Above 50 SMA):
This signal is triggered when the price crosses above the 50-period Simple Moving Average (SMA), where the current bar closes above the 50 SMA, and the previous bar closed below it. It indicates a shift toward bullish momentum.
buySignal4 = ta.crossover(close, sma50)
Buy Signal 5 (Cross Above 200 SMA):
This signal is triggered when the price crosses above the 200-period Simple Moving Average (SMA), where the current bar closes above the 200 SMA, and the previous bar closed below it. This suggests a long-term bullish trend.
buySignal5 = ta.crossover(close, sma200)
Buy Signal 6 (Low Above 50 SMA):
This signal is true when the lowest price of the current bar is above the 50-period SMA, indicating strong bullish pressure as the price maintains itself above the moving average.
buySignal6 = low > sma50
Buy Signal 7 (Accumulation Day):
An accumulation day occurs when the closing price is in the upper half of the daily range (greater than 50%) and the volume is larger than the previous bar's volume, suggesting buying pressure and accumulation.
buySignal7 = (close - low) / (high - low) > 0.5 and volume > volume
Buy Signal 8 (Higher High):
This signal occurs when the current bar’s high exceeds the highest high of the previous 14 bars, indicating a breakout or strong upward momentum.
buySignal8 = high > ta.highest(high, 14)
Buy Signal 9 (Key Reversal Bar):
This signal is generated when the stock opens below the low of the previous bar but rallies to close above the previous bar’s high, signaling a potential reversal from bearish to bullish.
buySignal9 = open < low and close > high
Buy Signal 10 (Distribution Day Fall Off):
This signal is triggered when a distribution day (a day with high volume and a close near the low of the range) "falls off" the rolling 25-bar period, indicating the end of a bearish trend or selling pressure.
buySignal10 = ta.barssince(close < sma50 and close < sma50) > 25
Sell Signals (Decrease Exposure Score by -10%)
Sell Signal 1 (Cross Below 21 EMA):
This signal is triggered when the price crosses below the 21-period Exponential Moving Average (EMA), where the current bar closes below the EMA21, and the previous bar closed above it. It suggests that the market may be shifting from a bullish trend to a bearish trend.
sellSignal1 = ta.crossunder(close, ema21)
Sell Signal 2 (Trending Below 21 EMA):
This signal is triggered when the price closes below the 21-period EMA for each of the last 5 bars, indicating a sustained bearish trend.
sellSignal2 = ta.barssince(close >= ema21) > 5
Sell Signal 3 (Living Below 21 EMA):
This signal is triggered when the price has closed below the 21-period EMA for each of the last 15 bars, suggesting a strong downtrend.
sellSignal3 = ta.barssince(close >= ema21) > 15
Sell Signal 4 (Cross Below 50 SMA):
This signal is triggered when the price crosses below the 50-period Simple Moving Average (SMA), where the current bar closes below the 50 SMA, and the previous bar closed above it. It indicates the start of a bearish trend.
sellSignal4 = ta.crossunder(close, sma50)
Sell Signal 5 (Cross Below 200 SMA):
This signal is triggered when the price crosses below the 200-period Simple Moving Average (SMA), where the current bar closes below the 200 SMA, and the previous bar closed above it. It indicates a long-term bearish trend.
sellSignal5 = ta.crossunder(close, sma200)
Sell Signal 6 (High Below 50 SMA):
This signal is true when the highest price of the current bar is below the 50-period SMA, indicating weak bullishness or a potential bearish reversal.
sellSignal6 = high < sma50
Sell Signal 7 (Distribution Day):
A distribution day is identified when the closing range of a bar is less than 50% and the volume is larger than the previous bar's volume, suggesting that selling pressure is increasing.
sellSignal7 = (close - low) / (high - low) < 0.5 and volume > volume
Sell Signal 8 (Lower Low):
This signal occurs when the current bar's low is less than the lowest low of the previous 14 bars, indicating a breakdown or strong downward momentum.
sellSignal8 = low < ta.lowest(low, 14)
Sell Signal 9 (Downside Reversal Bar):
A downside reversal bar occurs when the stock opens above the previous bar's high but falls to close below the previous bar’s low, signaling a reversal from bullish to bearish.
sellSignal9 = open > high and close < low
Sell Signal 10 (Distribution Cluster):
This signal is triggered when a distribution day occurs three times in the rolling 7-bar period, indicating significant selling pressure.
sellSignal10 = ta.valuewhen((close < low) and volume > volume , 1, 7) >= 3
Theme Mode:
Users can select the theme mode (Auto, Dark, or Light) to match the chart's background or to manually choose a light or dark theme for the oscillator's appearance.
Exposure Score Calculation: The script calculates a cumulative exposure score based on a series of buy and sell signals.
Buy signals increase the exposure score, while sell signals decrease it. Each signal impacts the score by ±10%.
Signal Conditions: The buy and sell signals are derived from multiple conditions, including crossovers with moving averages (EMA21, SMA50, SMA200), trend behavior, and price/volume analysis.
Oscillator Visualization: The exposure score is visualized as a line on the chart, changing color based on whether the exposure is positive (long position) or negative (short position). It is limited to the range of -100% to +100%.
Position Type: The indicator also indicates the position type based on the exposure score, labeling it as "Long," "Short," or "Neutral."
Horizontal Lines: Reference lines at 0%, 100%, and -100% visually mark neutral, increasing long, and increasing short exposure levels.
Exposure Table: A table displays the current exposure level (in percentage) and position type ("Long," "Short," or "Neutral"), updated dynamically based on the oscillator’s value.
Inputs:
Theme Mode: Choose "Auto" to use the default chart theme, or manually select "Dark" or "Light."
Usage:
This oscillator is designed to help traders track market sentiment, gauge exposure levels, and manage risk. It can be used for long-term trend-following strategies or short-term trades based on moving average crossovers and volume analysis.
The oscillator operates in conjunction with the chart’s price action and provides a visual representation of the market’s current trend strength and exposure.
Important Considerations:
Risk Management: While the exposure score provides valuable insight, it should be combined with other risk management tools and analysis for optimal trading decisions.
Signal Sensitivity: The accuracy and effectiveness of the signals depend on market conditions and may require adjustments based on the user’s trading strategy or timeframe.
Disclaimer:
This script is for educational purposes only. Trading involves significant risk, and users should carefully evaluate all market conditions and apply appropriate risk management strategies before using this tool in live trading environments.
HTF TriangleHTF Triangle by ZeroHeroTrading aims at detecting ascending and descending triangles using higher time frame data, without repainting nor misalignment issues.
It addresses user requests for combining Ascending Triangle and Descending Triangle into one indicator.
Ascending triangles are defined by an horizontal upper trend line and a rising lower trend line. It is a chart pattern used in technical analysis to predict the continuation of an uptrend.
Descending triangles are defined by a falling upper trend line and an horizontal lower trend line. It is a chart pattern used in technical analysis to predict the continuation of a downtrend.
This indicator can be useful if you, like me, believe that higher time frames can offer a broader perspective and provide clearer signals, smoothing out market noise and showing longer-term trends.
You can change the indicator settings as you see fit to tighten or loosen the detection, and achieve the best results for your use case.
Features
It draws the detected ascending and descending triangles on the chart.
It supports alerting when a detection occurs.
It allows for selecting ascending and/or descending triangle detection.
It allows for setting the higher time frame to run the detection on.
It allows for setting the minimum number of consecutive valid higher time frame bars to fit the pattern criteria.
It allows for setting a high/low factor detection criteria to apply on higher time frame bars high/low as a proportion of the distance between the reference bar high/low and open/close.
It allows for turning on an adjustment of the triangle using highest/lowest values within valid higher time frame bars.
Settings
Ascending checkbox: Turns on/off ascending triangle detection. Default is on.
Descending checkbox: Turns on/off descending triangle detection. Default is on.
Higher Time Frame dropdown: Selects higher time frame to run the detection on. It must be higher than, and a multiple of, the chart's timeframe. Default is 5 minutes.
Valid Bars Minimum field: Sets minimum number of consecutive valid higher time frame bars to fit the pattern criteria. Default is 3. Minimum is 1.
High/Low Factor checkbox: Turns on/off high/low factor detection criteria. Default is on.
High/Low Factor field: Sets high/low factor to apply on higher time frame bars high/low as a proportion of the distance between the reference bar high/low and open/close. Default is 0. Minimum is 0. Maximum is 1.
Adjust Triangle checkbox: Turns on/off triangle adjustment using highest/lowest values within valid higher time frame bars. Default is on.
Detection Algorithm Notes
The detection algorithm recursively selects a higher time frame bar as reference. Then it looks at the consecutive higher time frame bars (as per the requested number of minimum valid bars) as follows:
Ascending Triangle
Low must be higher than previous bar.
Open/close max value must be lower than (or equal to) reference bar high.
When high/low factor criteria is turned on, high must be higher than (or equal to) reference bar open/close max value plus high/low factor proportion of the distance between reference bar high and open/close max value.
Descending Triangle
High must be lower than previous bar.
Open/close min value must be higher than (or equal to) reference bar low.
When high/low factor criteria is turned on, low must be lower than (or equal to) reference bar open/close min value minus high/low factor proportion of the distance between reference bar low and open/close min value.
ZigZag Library [TradingFinder]🔵 Introduction
The "Zig Zag" indicator is an analytical tool that emerges from pricing changes. Essentially, it connects consecutive high and low points in an oscillatory manner. This method helps decipher price changes and can also be useful in identifying traditional patterns.
By sifting through partial price changes, "Zig Zag" can effectively pinpoint price fluctuations within defined time intervals.
🔵 Key Features
1. Drawing the Zig Zag based on Pivot points :
The algorithm is based on pivots that operate consecutively and alternately (switch between high and low swing). In this way, zigzag lines are connected from a swing high to a swing low and from a swing low to a swing high.
Also, with a very low probability, it is possible to have both low pivots and high pivots in one candle. In these cases, the algorithm tries to make the best decision to make the most suitable choice.
You can control what period these decisions are based on through the "PiPe" parameter.
2.Naming and labeling each pivot based on its position as "Higher High" (HH), "Lower Low" (LL), "Higher Low" (HL), and "Lower High" (LH).
Additionally, classic patterns such as HH, LH, LL, and HL can be recognized. All traders analyzing financial markets using classic patterns and Elliot Waves can benefit from the "zigzag" indicator to facilitate their analysis.
" HH ": When the price is higher than the previous peak (Higher High).
" HL ": When the price is higher than the previous low (Higher Low).
" LH ": When the price is lower than the previous peak (Lower High).
" LL ": When the price is lower than the previous low (Lower Low).
🔵 How to Use
First, you can add the library to your code as shown in the example below.
import TFlab/ZigZagLibrary_TradingFinder/1 as ZZ
Function "ZigZag" Parameters :
🟣 Logical Parameters
1. HIGH : You should place the "high" value here. High is a float variable.
2. LOW : You should place the "low" value here. Low is a float variable.
3. BAR_INDEX : You should place the "bar_index" value here. Bar_index is an integer variable.
4. PiPe : The desired pivot period for plotting Zig Zag is placed in this parameter. For example, if you intend to draw a Zig Zag with a Swing Period of 5, you should input 5.
PiPe is an integer variable.
Important :
Apart from the "PiPe" indicator, which is part of the customization capabilities of this indicator, you can create a multi-time frame mode for the indicator using 3 parameters "High", "Low" and "BAR_INDEX". In this way, instead of the data of the current time frame, use the data of other time frames.
Note that it is better to use the current time frame data, because using the multi-time frame mode is associated with challenges that may cause bugs in your code.
🟣 Setting Parameters
5. SHOW_LINE : It's a boolean variable. When true, the Zig Zag line is displayed, and when false, the Zig Zag line display is disabled.
6. STYLE_LINE : In this variable, you can determine the style of the Zig Zag line. You can input one of the 3 options: line.style_solid, line.style_dotted, line.style_dashed. STYLE_LINE is a constant string variable.
7. COLOR_LINE : This variable takes the input of the line color.
8. WIDTH_LINE : The input for this variable is a number from 1 to 3, which is used to adjust the thickness of the line that draws the Zig Zag. WIDTH_LINE is an integer variable.
9. SHOW_LABEL : It's a boolean variable. When true, labels are displayed, and when false, label display is disabled.
10. COLOR_LABEL : The color of the labels is set in this variable.
11. SIZE_LABEL : The size of the labels is set in this variable. You should input one of the following options: size.auto, size.tiny, size.small, size.normal, size.large, size.huge.
12. Show_Support : It's a boolean variable that, when true, plots the last support line, and when false, disables its plotting.
13. Show_Resistance : It's a boolean variable that, when true, plots the last resistance line, and when false, disables its plotting.
Suggestion :
You can use the following code snippet to import Zig Zag into your code for time efficiency.
//import Library
import TFlab/ZigZagLibrary_TradingFinder/1 as ZZ
// Input and Setting
// Zig Zag Line
ShZ = input.bool(true , 'Show Zig Zag Line', group = 'Zig Zag') //Show Zig Zag
PPZ = input.int(5 ,'Pivot Period Zig Zag Line' , group = 'Zig Zag') //Pivot Period Zig Zag
ZLS = input.string(line.style_dashed , 'Zig Zag Line Style' , options = , group = 'Zig Zag' )
//Zig Zag Line Style
ZLC = input.color(color.rgb(0, 0, 0) , 'Zig Zag Line Color' , group = 'Zig Zag') //Zig Zag Line Color
ZLW = input.int(1 , 'Zig Zag Line Width' , group = 'Zig Zag')//Zig Zag Line Width
// Label
ShL = input.bool(true , 'Label', group = 'Label') //Show Label
LC = input.color(color.rgb(0, 0, 0) , 'Label Color' , group = 'Label')//Label Color
LS = input.string(size.tiny , 'Label size' , options = , group = 'Label' )//Label size
Show_Support= input.bool(false, 'Show Last Support',
tooltip = 'Last Support' , group = 'Support and Resistance')
Show_Resistance = input.bool(false, 'Show Last Resistance',
tooltip = 'Last Resistance' , group = 'Support and Resistance')
//Call Function
ZZ.ZigZag(high ,low ,bar_index ,PPZ , ShZ ,ZLS , ZLC, ZLW ,ShL , LC , LS , Show_Support , Show_Resistance )
PinBar and Bloom Pattern Concept (Zeiierman)█ Overview
The Precision PinBar and Bloom Pattern Concept by Zeiierman introduces two new patterns, which we call the Bloom Pattern and the Precision PinBar Pattern. These patterns are used in conjunction with market open, high, and low values from different periods and timeframes. Together, they form the basis of the "PinBar and Bloom Pattern Concept." The main idea is to identify key bullish and bearish candlestick patterns around key levels plotted on the chart.
The key levels are the Open, High, and Low from the current and previous periods of the selected timeframe. Users can choose how many previous periods to be drawn on the chart.
█ How It Works
The indicator operates by analyzing market data over selected timeframes. It uses inputs such as previous period open-high-low lines, timeframe selections, and pattern detection settings like Symmetry Precision and Range Threshold. These parameters allow the indicator to identify specific market conditions, including symmetrical movements in price and significant price range deviations, which form the basis of the Bloom and Precision PinBar patterns.
Symmetry Signal:
Purpose: To detect symmetry in price movements based on a precision threshold.
How It Works: This function calculates the symmetry of high and low prices within the specified precision. It returns two boolean values indicating whether the high and low prices are within the symmetry precision.
BaselineBound Pattern:
Purpose: To identify bullish or bearish patterns based on a range factor.
How It Works: The function calculates whether the current close price is within a certain range of the high-low difference of the previous period. It returns bullish and bearish signals based on these calculations.
█ ● Bloom Pattern
The Bloom Pattern is a unique candlestick pattern designed to identify significant trend reversals or continuations. It's not a single candlestick formation but a combination of a few elements that signal a potential strong move in the market.
⚪ Previous and Current Candle Analysis: The Bloom Pattern looks at the relationship between the current candle and the previous one. It checks whether the current candle's body (the range between its opening and closing prices) fully encompasses the body of the previous candle. This condition is known as "embodying."
⚪ Baseline Bound: The Baseline Bound concept involves comparing the closing price to a range established by the high and low of the previous candle, adjusted by a factor (the rangeFactor). This helps in identifying if the current price is showing a bullish or bearish tendency relative to the previous period's price movement.
⚪ Symmetry Signal: Additionally, it uses the Symmetry Signal, which measures the symmetry between the high and low prices of two consecutive candles.
⚪ Bullish and Bearish Signals: The combination of these conditions (embodying, baseline bound, and symmetry) results in either a bullish or bearish signal. A bullish signal suggests a potential upward trend, while a bearish signal indicates a possible downward trend.
█ ● Precision PinBar Pattern
The Precision PinBar Pattern is a refined version of the traditional Pin Bar, a well-known candlestick pattern used in trading. This pattern focuses on identifying market reversals with a high degree of accuracy.
⚪ Identification of Pin Bars: The function first identifies a pin bar, characterized by a small body and a long wick. The long wick indicates a rejection of certain price levels, and the small body shows little change between the opening and closing prices.
⚪ Tail and Body Length Analysis: The script calculates the length of the bar's tail (wick) and compares it to the length of the body. A qualifying pin bar typically has a tail at least three times longer than its body, suggesting a strong rejection of prices.
⚪ Positioning and Thresholds:
Open-Close Position: The function checks whether the opening and closing prices are within a certain threshold of the high or low of the bar, which helps in distinguishing between bullish and bearish pin bars.
⚪ Baseline Bound and Symmetry: Like the Bloom Pattern, it incorporates Baseline Bound and Symmetry Signal concepts to validate the significance of the pin bar.
⚪ Bullish and Bearish Signals: Depending on these factors, a bullish or bearish pin bar is identified. A bullish PinBar suggests potential upward price movement, while a bearish PinBar indicates possible downward price movement.
█ How to Use
Using the Bloom and Precision PinBar patterns in conjunction with key market levels, such as previous highs and lows, can be a powerful strategy for traders. These market levels often act as significant points of support and resistance, and combining them with the patterns can offer strong trade signals. Here's how traders can effectively utilize these patterns:
Identifying Key Market Levels
Previous Highs and Lows: These are the highest and lowest points reached in previous trading periods and are often considered strong levels of resistance (in the case of previous highs) and support (in the case of previous lows).
Using the Bloom Pattern
Near Previous Highs (Resistance): If a Bloom Pattern emerges near a previous high, it could indicate a potential bearish reversal. Traders might interpret this as a signal to consider short positions, especially if the pattern shows bearish characteristics.
Near Previous Lows (Support): Conversely, a bullish Bloom Pattern near a previous low could suggest a trend reversal to the upside. This could be a signal for traders to consider long positions.
Using the Precision PinBar Pattern
Precision PinBar at Resistance: A bearish Precision PinBar appearing near a previous high can be a strong signal for a potential downward move. This setup is often used by traders to enter short positions, anticipating a price rejection at this resistance level.
Precision PinBar at Support: Similarly, a bullish Precision PinBar at or near a previous low suggests that the market is rejecting lower prices, indicating potential upward momentum. This is typically used by traders as a cue to go long.
█ Settings
Previous Open-High-Low Lines: Determine the number of historical periods to analyze. Settings include toggling the visibility of lines and labels and specifying the number of periods.
Timeframe & Current Period: Select the timeframe for current market analysis. Options include different timeframes (e.g., 1H, 1D) and customization of line styles and colors.
Pattern Settings: Adjust the Symmetry Precision and Range Threshold to fine-tune the indicator's sensitivity to specific market movements.
Bloom & Precision PinBar Pattern: Enable or disable the detection of specific patterns and customize the visual representation of these patterns on the chart.
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. 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.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Price-Action CandlesWhat is a swing high or swing low?
Swing highs and lows are price extremes. For example say we set our swing length to 5. A candle that is a swing high with a swing length of 5 will have 5 bars to the left that are lower and 5 bars to the right that are lower. A candle that is a swing low with a swing length of 5 will have 5 bars to the left that are higher and 5 bars to the right that are higher.
How are the trend candles calculated?
The trend candles are calculated by storing and comparing historical swing lows and swing highs.
The pinescript code goes as follows:
The pinescript code goes as follows:
var int trend = na
trend := ((hh and high >= psh) or close > csh) ? 1 : ((ll and low <= psl) or close < csl) ? -1 : lh or hl ? 0 : trend
What does that gibberish mean?
-Candle can be GREEN IF
- We have a higher high (current swing high is greater than the previous swing high) and the high is greater than the previous swing high
- OR The current close is greater than the current swing high
-Candle can be RED IF
- We have a lower low (current swing low is less than the previous swing low) and the low is less than the previous swing low
- OR The current close is less than the current swing low
-Candle can be YELLOW IF
- We have a new swing high and the new swing high is less than the previous swing high
- OR We have a new swing low and the new swing low is greater than the previous swing low
If none of the conditions above are true then we continue with whatever color the previous bar was.
What is repainting?
Repainting is "script behavior causing historical vs realtime calculations or plots to behave differently." That definition comes directly from Tradingview. If you want to read the full explanation you can visit it here www.tradingview.com . The price-action candles use swing highs and swing lows which need bars to the left (past) and bars to the right ("future") in order to confirm the swing level. Because of the need to wait for confirmation to for swing levels the plot style can be repainting. With the price-action candles indicator the only repainting part of the indicator is the labels. The price-action candles themselves WILL NOT REPAINT. The labels however can be set to repaint or not depending on the user preference. If the user opts to use repainting then the label location is shifted back by the length of the price-action. So if the "Price-Action Length" input is set to 10, and the user wants repainting, the swing high/low label will be shifted back 10 bars. If the user opts for no repainting, the label will not be shifted and instead show on the exact bar the swing level was confirmed.
Examples Below.
Repaint
Here the labels are shifted back the price-action length.
Non-Repaint
Here the labels are not shifted back because the input setting is set to not repaint.
Multi-timeframe Analysis
The users can view the trend from multiple different timeframes at once with a table displayed at the bottom of their charts. The timeframe can be lower or higher than the chart timeframe.
More examples
Be on the lookout for the Price Action Candles (Lower) indicator where you can view the multi-timeframe labels on a lower price grid in order to see the history over time!
Moving Average - TREND POWER v1.1- (AS)0)NOTE:
This is first version of this indicator. It's way more complicated than it should be. Check out Moving Average-TREND POWER v2.1-(AS), its waaaaay less complicated and might be better.Enjoy...
1)INTRODUCTION/MAIN IDEA:
In simpliest form this script is a trend indicator that rises if Moving average if below price or falling if above and going back to zero if there is a crossover with a price. To use this indicator you will have to adjust settings of MAs and choose conditions for calculation.
While using the indicator we might have to define CROSS types or which MAs to use. List of what cross types are defined in the script and Conditiones to choose from.The list will be below.
2) COMPOSITION:
-MA1 can be defined by user in settings, possible types: SMA, EMA, RMA, HMA, TEMA, DEMA, LSMA, WMA.
-MA2 is always ALMA
3) OVERLAY:
Default is false but if you want to see MA1/2 on chart you can change code to true and then turn on overlay in settings. Most plot settings are avalible only in OV=false.
if OV=true possible plots ->MA1/2, plotshape when choosen cross type
if OV=false -> main indicator,TSHs,Cross counter
4)PRESETS :
Indicator has three modes that can be selected in settings. First two are presets and do not require selecting conditions as they set be default.
-SIMPLE - most basic
-ABSOLUTE - shows only positive values when market is trending or zero when in range
-CUSTOM - main and the most advanced form that will require setting conditions to use in calculating trend
4.1)SIMPLE – this is the most basic form of conditions that uses only First MA. If MA1 is below selected source (High/Low(High for Uptrend and Low for DNtrend or OHLC4) on every bar value rises by 0.02. if it above Low or OHLC4 it falls by 0.02 with every bar. If there is a cross of MA with price value is zero. This preset uses CROSS_1_ULT(list of all cross types below)
4.2) ABSOLUTE – does not show direction of the trend unlike others and uses both MA1 and MA2. Uses CROSS type 123_ULT
4.3) CUSTOM – here we define conditions manually. This mode is defined in parts (5-8 of description)
5)SETTINGS:
SOURCE/OVERLAY(line1) – select source of calculation form MA1/MA2, select for overlay true (look point 3)
TRESHOLDS(line2). – set upper and lower THS, turn TSHs on/off
MA1(line3) – Length/type of MA/Offset(only if MA type is LSM)
MA2(line4) – length/offset/sigma -(remember to set ma in the way that in Uptrend MA2MA1 in DNtrend)
Use faster MA types for short term trends and slower types / bigger periods for longer term trends, defval MA1/2 settings
are pretty much random so using them is not recomended.
CROSSshape(line5) – choose which cross type you want to plot on chart(only in OV=true) or what type you want to use in counting via for loops,
CROSScount(line6) – set lookback for type of cross choosen above
BOOLs in lines 5 and 6 - plotshape if OV=true/plot CROSScount histogram (if OV=false)
Lines 7 and 8 – PRESET we want to use /SRC for calculation of indicator/are conditions described below/which MAs to use/Condition for
reducing value t 0 - (if PRESET is ABSOLUTE or SIMPLE only SRC should be set(Line 8 does not matter if not CUSTOM))
5)SOURCE for CONDS:
Here you can choose between H/L and OHLC. If H/L value grow when MAlow. If OHLC MAOHLC. H/L is set by default and recommended. This can be selected for all presets not only CUSTOM
6)CROSS types LIST:
“1 means MA1, 2 is MA2 and 3 I cross of MA1/MA2. L stands for low and H for high so for example 2H means cross of MA2 and high”
NAME -DEFINITION Number of possible crosses
1L - cross of MA1 and low 1
1H - cross of MA1 and high 1
1HL - cross of MA1 and low or MA1 and high 2 -1L/1H
2L - cross of MA2 and low 1
2H - cross of MA2 and high 1
2HL - cross of MA2 and low or MA1 and high 2 -2L/2H
12L - cross of MA1 and low or MA2 and low 2 -1L/2L
12H - cross of MA1 and high or MA2 and high 2 -1H/2H
12HL - MA1/2 and high/low 4 -1H/1L/2H/2L
3 -cross of MA1 and MA2 1
123HL -crosses from 12HL or 3 5 -12HL/3
1_ULT - cross of MA1 with any of price sources(close,low,high,ohlc4 etc…)
2_ULT - cross of MA2 with any of price sources(close,low,high,ohlc4 etc…)
123_ULT – all crosses possible of MA1/2 (all of the above so a lot)
7)CRS CONDS:
“conditions to reduce value back to zero”
>/< - 0 if indicator shows Uptrend and there’s a cross with high of selected MA or 0 if in DNtrend and cross with low. Better for UP/DN trend detection
ALL – 0 if cross of MA with high or low no matter the trend, better for detecting consolidation
ULT – if any cross of selected MA, most crosses so goes to 0 most often
8)MA selection and CONDS:
-MA1: only MA1 is used,if MA1 below price value grows and the other way around
MA1price =-0.02
-MA2 – only MA2 is used, same conditions as MA1 but using MA2
MA2price =-0.02
-BOTH – MA1 and MA2 used, grows when MA1 if below, grows faster if MA1 and MA2 are below and fastest when MA1 and MA2 are below and MA2price=-0.02
-MA1 and MA2 >price=-0.03
-MA1 and MA2 ?price and MA2>MA1=-0.04
9)CONDITIONS SELECTION SUMMARRY:
So when CUSTOM we choose :
1)SOURCE – H/L or OHLC
2)MAs – MA1/MA2/BOTH
3)CRS CONDS (>/<,ALL,ULT)
So for example...
if we take MA1 and ALL value will go to zero if 1HL
if MA1 and >/< - 0 if 1L or 1H (depending if value is positive or negative).(1L or 1H)
If ALL and BOTH zero when 12HL
If BOTH and ULT value goes back to zero if Theres any cross of MA1/MA2 with price or cross of MA1 and MA2.(123_ULT)
If >/< and BOTH – 0 if 12L in DNtrend or 12H if UPtrend
10) OTHERS
-script was created on EURUSD 5M and wasn't tested on different markets
-default values of MA1/MA2 aren't optimalized so do not
-There might be a logical error in the script so let me know if you find it (most probably in 'BOTH')
-thanks to @AlifeToMake for help
-if you have any ideas to improve let me know
-there are also tooltips to help
Upper Candle Trends [theEccentricTrader]█ OVERVIEW
This indicator simply plots upper candle trends and should be used in conjunction with my Lower Candle Trends indicator as a visual aid to my Upper and Lower Candle Trend Counter indicator.
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a close price equal to or above the price it opened.
• A red candle is one that closes with a close price that is lower than the price it opened.
Upper Candle Trends
• A higher high candle is one that closes with a higher high price than the high price of the preceding candle.
• A lower high candle is one that closes with a lower high price than the high price of the preceding candle.
• A double-top candle is one that closes with a high price that is equal to the high price of the preceding candle.
Lower Candle Trends
• A higher low candle is one that closes with a higher low price than the low price of the preceding candle.
• A lower low candle is one that closes with a lower low price than the low price of the preceding candle.
• A double-bottom candle is one that closes with a low price that is equal to the low price of the preceding candle.
Muti-Part Upper and Lower Candle Trends
• A multi-part higher high trend begins with the formation of a new higher high and continues until a new lower high ends the trend.
• A multi-part lower high trend begins with the formation of a new lower high and continues until a new higher high ends the trend.
• A multi-part higher low trend begins with the formation of a new higher low and continues until a new lower low ends the trend.
• A multi-part lower low trend begins with the formation of a new lower low and continues until a new higher low ends the trend.
█ FEATURES
Plots
Green up-arrows, with the number of the trend part, denote higher high trends. Red down-arrows, with the number of the trend part, denote lower high trends.
█ LIMITATIONS
Some higher timeframe candles on tickers with larger lookbacks such as the DXY , do not actually contain all the open, high, low and close (OHLC) data at the beginning of the chart. Instead, they use the close price for open, high and low prices. So, while we can determine whether the close price is higher or lower than the preceding close price, there is no way of knowing what actually happened intra-bar for these candles. And by default candles that close at the same price as the open price, will be counted as green.
Lower Candle Trends [theEccentricTrader]█ OVERVIEW
This indicator simply plots lower candle trends and should be used in conjunction with my Upper Candle Trends indicator as a visual aid to my Upper and Lower Candle Trend Counter indicator.
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a close price equal to or above the price it opened.
• A red candle is one that closes with a close price that is lower than the price it opened.
Upper Candle Trends
• A higher high candle is one that closes with a higher high price than the high price of the preceding candle.
• A lower high candle is one that closes with a lower high price than the high price of the preceding candle.
• A double-top candle is one that closes with a high price that is equal to the high price of the preceding candle.
Lower Candle Trends
• A higher low candle is one that closes with a higher low price than the low price of the preceding candle.
• A lower low candle is one that closes with a lower low price than the low price of the preceding candle.
• A double-bottom candle is one that closes with a low price that is equal to the low price of the preceding candle.
Muti-Part Upper and Lower Candle Trends
• A multi-part higher high trend begins with the formation of a new higher high and continues until a new lower high ends the trend.
• A multi-part lower high trend begins with the formation of a new lower high and continues until a new higher high ends the trend.
• A multi-part higher low trend begins with the formation of a new higher low and continues until a new lower low ends the trend.
• A multi-part lower low trend begins with the formation of a new lower low and continues until a new higher low ends the trend.
█ FEATURES
Plots
Green up-arrows, with the number of the trend part, denote higher low trends. Red down-arrows, with the number of the trend part, denote lower low trends.
█ LIMITATIONS
Some higher timeframe candles on tickers with larger lookbacks such as the DXY , do not actually contain all the open, high, low and close (OHLC) data at the beginning of the chart. Instead, they use the close price for open, high and low prices. So, while we can determine whether the close price is higher or lower than the preceding close price, there is no way of knowing what actually happened intra-bar for these candles. And by default candles that close at the same price as the open price, will be counted as green.
TRADING MADE SIMPLEThis indicator shows market structure. The standard method of using Williams Highs and Lows as pivots, is something of an approximation.
What's original here is that we follow rules to confirm Local Highs and Local Lows, and strictly enforce that a Low can only follow a confirmed High and vice-versa.
-- Highs and Lows
To confirm a candle as a Local High, you need a later candle to Close below its Low. To confirm a Local Low, you need a Close above its High.
A Low can only follow a High (after it's been confirmed). You can't go e.g High, High, Low, Low, only High, Low, High, Low.
When price makes Higher Highs and Higher Lows, market structure is said to be bullish. When price makes Lower Lows and Lower Highs, it's bearish.
I've defined the in-between Highs and Lows as "Ranging", meaning, neutral. They could be trend continuation or reversal.
-- Bullish/Bearish Breaks
A Bullish break in market structure is when the Close of the current candle goes higher than the previous confirmed Local High.
A Bearish Break is when the Close of the current candle goes lower than the most recent confirmed Local Low.
I chose to use Close rather than High to reduce edge case weirdness. The breaking candle often ends up being a big one, thus the close of that candle can be a poor entry.
You can get live warnings by setting the alert to Options: Only Once, because during a candle, the current price is taken as the Close.
Breaks are like early warnings of a change in market bias, because you're not waiting for a High or Low to be formed and confirmed.
Buy The Dip / Sell The Rally
Buy The Dip is a label I gave to the first Higher Low in a bullish market structure. Sell The Rally is the first Lower High in a bearish market structure.
These *might* be good buying/selling opportunities, but you still need to do your own analysis to confirm that.
== USAGE ==
The point of knowing market structure is so you don't make bullish bets in a bearish market and vice versa -
or if you do at least you're aware that that's what you're doing, and hopefully have some overwhelmingly good reason to do so.
These are not signals to be traded on their own. You still need a trade thesis. Use with support & resistance and your other favourite indicators.
Works on any market on any timeframe. Be aware that market structure will be different on different timeframes.
IMPORTANT: If you're not seeing what you expect, check your settings and re-read this entire description carefully. Confirming Highs and Lows can get deceptively complex.
Smart Money Concepts [XoRonX]# Smart Money Concepts (SMC) - Advanced Trading Indicator
## 📊 Deskripsi
**Smart Money Concepts ** adalah indicator trading komprehensif yang menggabungkan konsep Smart Money Trading dengan berbagai alat teknikal analisis modern. Indicator ini dirancang untuk membantu trader mengidentifikasi pergerakan institusional (smart money), struktur pasar, zona supply/demand, dan berbagai sinyal trading penting.
Indicator ini mengintegrasikan multiple timeframe analysis, order blocks detection, fair value gaps, fibonacci retracement, volume profile, RSI multi-timeframe, dan moving averages dalam satu platform yang powerful dan mudah digunakan.
---
## 🎯 Fitur Utama
### 1. **Smart Money Structure**
- **Internal Structure** - Struktur pasar jangka pendek untuk entry presisi
- **Swing Structure** - Struktur pasar jangka panjang untuk trend analysis
- **BOS (Break of Structure)** - Konfirmasi kelanjutan trend
- **CHoCH (Change of Character)** - Deteksi potensi reversal
### 2. **Order Blocks**
- **Internal Order Blocks** - Zona demand/supply jangka pendek
- **Swing Order Blocks** - Zona demand/supply jangka panjang
- Filter otomatis berdasarkan volatilitas (ATR/Range)
- Mitigation tracking (High/Low atau Close)
- Customizable display (jumlah order blocks yang ditampilkan)
### 3. **Equal Highs & Equal Lows (EQH/EQL)**
- Deteksi otomatis equal highs/lows
- Indikasi liquidity zones
- Threshold adjustment untuk sensitivitas
- Visual lines dan labels
### 4. **Fair Value Gaps (FVG)**
- Multi-timeframe FVG detection
- Auto threshold filtering
- Bullish & Bearish FVG boxes
- Extension control
- Color customization
### 5. **Premium & Discount Zones**
- Premium Zone (75-100% dari range)
- Equilibrium Zone (47.5-52.5% dari range)
- Discount Zone (0-25% dari range)
- Auto-update berdasarkan swing high/low
### 6. **Fibonacci Retracement**
- **Equilibrium to Discount** - Fib dari EQ ke discount zone
- **Equilibrium to Premium** - Fib dari EQ ke premium zone
- **Discount to Premium** - Fib full range
- Reverse option
- Show/hide lines
- Custom colors
### 7. **Volume Profile (VRVP)**
- Visible Range Volume Profile
- Point of Control (POC)
- Value Area (70% volume)
- Auto-adjust rows
- Placement options (Left/Right)
- Width customization
### 8. **RSI Multi-Timeframe**
- Monitor 3 timeframes sekaligus
- Overbought/Oversold signals
- Visual table display
- Color-coded signals (Red OB, Green OS)
- Customizable position & size
### 9. **Moving Averages**
- 3 Moving Average lines
- Pilihan tipe: EMA, SMA, WMA
- Automatic/Manual period mode
- Individual color & width settings
- Cross alerts (MA vs MA, Price vs MA)
### 10. **Multi-Timeframe Levels**
- Support up to 5 different timeframes
- Previous high/low levels
- Custom line styles
- Color customization
### 11. **Candle Color**
- Color candles berdasarkan trend
- Bullish = Green, Bearish = Red
- Optional toggle
---
## 🛠️ Cara Penggunaan
### **A. Setup Awal**
1. **Tambahkan Indicator ke Chart**
- Buka TradingView
- Klik "Indicators" → "My Scripts" atau paste code
- Pilih "Smart Money Concepts "
2. **Pilih Mode Display**
- **Historical**: Tampilkan semua struktur (untuk backtesting)
- **Present**: Hanya tampilkan struktur terbaru (clean chart)
3. **Pilih Style**
- **Colored**: Warna berbeda untuk bullish/bearish
- **Monochrome**: Tema warna abu-abu
---
### **B. Penggunaan Fitur**
#### **1. Smart Money Structure**
**Internal Structure (Real-time):**
- ✅ Aktifkan "Show Internal Structure"
- Pilih tampilan: All, BOS only, atau CHoCH only
- Gunakan untuk entry timing presisi
- Filter confluence untuk mengurangi noise
**Swing Structure:**
- ✅ Aktifkan "Show Swing Structure"
- Pilih tampilan struktur bullish/bearish
- Adjust "Swings Length" (default: 50)
- Gunakan untuk konfirmasi trend utama
**Tips:**
- BOS = Konfirmasi trend continuation
- CHoCH = Warning untuk possible reversal
- Tunggu price retest ke order block setelah BOS
---
#### **2. Order Blocks**
**Setup:**
- ✅ Aktifkan Internal/Swing Order Blocks
- Set jumlah blocks yang ditampil (1-20)
- Pilih filter: ATR atau Cumulative Mean Range
- Pilih mitigation: Close atau High/Low
**Cara Trading:**
1. Tunggu BOS/CHoCH terbentuk
2. Identifikasi order block terdekat
3. Wait for price pullback ke order block
4. Entry saat price respek order block (rejection)
5. Stop loss di bawah/atas order block
6. Target: swing high/low berikutnya
**Color Code:**
- 🔵 Light Blue = Internal Bullish OB
- 🔴 Light Red = Internal Bearish OB
- 🔵 Dark Blue = Swing Bullish OB
- 🔴 Dark Red = Swing Bearish OB
---
#### **3. Equal Highs/Lows (EQH/EQL)**
**Setup:**
- ✅ Aktifkan "Equal High/Low"
- Set "Bars Confirmation" (default: 3)
- Adjust threshold (0-0.5, default: 0.1)
**Interpretasi:**
- EQH = Liquidity di atas, kemungkinan sweep lalu dump
- EQL = Liquidity di bawah, kemungkinan sweep lalu pump
- Biasanya smart money akan grab liquidity sebelum move besar
**Trading Strategy:**
- Wait for EQH/EQL formation
- Anticipate liquidity grab
- Entry setelah sweep dengan konfirmasi (order block, FVG, CHoCH)
---
#### **4. Fair Value Gaps (FVG)**
**Setup:**
- ✅ Aktifkan "Fair Value Gaps"
- Pilih timeframe (default: chart timeframe)
- Enable/disable auto threshold
- Set extension bars
**Cara Trading:**
1. Bullish FVG = Support zone untuk buy
2. Bearish FVG = Resistance zone untuk sell
3. Price tends to fill FVG (retest)
4. Entry saat price kembali ke FVG
5. Partial fill = valid, full fill = invalidated
**Tips:**
- FVG + Order Block = High probability setup
- Multi-timeframe FVG lebih kuat
- Unfilled FVG = strong momentum
---
#### **5. Premium & Discount Zones**
**Setup:**
- ✅ Aktifkan "Premium/Discount Zones"
- Zones akan auto-update berdasarkan swing high/low
**Interpretasi:**
- 🟢 **Discount Zone** = Area BUY (price murah)
- ⚪ **Equilibrium** = Neutral (50%)
- 🔴 **Premium Zone** = Area SELL (price mahal)
**Trading Strategy:**
- BUY dari discount zone
- SELL dari premium zone
- Avoid trading di equilibrium
- Combine dengan structure confirmation
---
#### **6. Fibonacci Retracement**
**Setup:**
- Pilih Fib yang ingin ditampilkan:
- Equilibrium to Discount
- Equilibrium to Premium
- Discount to Premium
- Toggle show lines
- Enable reverse jika perlu
- Custom colors
**Key Levels:**
- 0.236 = Shallow retracement
- 0.382 = Common retracement
- 0.5 = 50% golden level
- 0.618 = Golden ratio (penting!)
- 0.786 = Deep retracement
**Cara Pakai:**
- 0.618-0.786 = Ideal entry zone dalam trend
- Combine dengan order blocks
- Wait for confirmation candle
---
#### **7. Volume Profile (VRVP)**
**Setup:**
- ✅ Aktifkan "Show Volume Profile"
- Set jumlah rows (10-100)
- Adjust width (5-50%)
- Pilih placement (Left/Right)
- Enable POC dan Value Area
**Interpretasi:**
- **POC (Point of Control)** = Harga dengan volume tertinggi = magnet
- **Value Area** = 70% volume = fair price range
- **Low Volume Nodes** = Weak support/resistance
- **High Volume Nodes** = Strong support/resistance
**Trading:**
- POC acts as support/resistance
- Price tends to return to POC
- Breakout dari Value Area = momentum
---
#### **8. RSI Multi-Timeframe**
**Setup:**
- ✅ Aktifkan "Show RSI Table"
- Set 3 timeframes (default: chart, 5m, 15m)
- Set RSI period (default: 14)
- Set Overbought level (default: 70)
- Set Oversold level (default: 30)
- Pilih posisi & ukuran table
**Interpretasi:**
- 🟢 **OS (Oversold)** = RSI ≤ 30 = Kondisi jenuh jual
- 🔴 **OB (Overbought)** = RSI ≥ 70 = Kondisi jenuh beli
- **-** = Neutral zone
**Trading Strategy:**
1. Multi-timeframe alignment = strong signal
2. OS + Bullish structure = BUY signal
3. OB + Bearish structure = SELL signal
4. Divergence RSI vs Price = reversal warning
**Contoh:**
- TF1: OS, TF2: OS, TF3: OS + Price di discount zone = STRONG BUY
---
#### **9. Moving Averages**
**Setup:**
- Pilih MA Type: EMA, SMA, atau WMA (berlaku untuk ketiga MA)
- Pilih Period Mode: Automatic atau Manual
- Set period untuk MA 1, 2, 3 (default: 20, 50, 100)
- Custom color & width per MA
- ✅ Enable Cross Alerts
**Interpretasi:**
- **Golden Cross** = MA fast cross above MA slow = Bullish
- **Death Cross** = MA fast cross below MA slow = Bearish
- Price above all MAs = Strong uptrend
- Price below all MAs = Strong downtrend
**Trading Strategy:**
1. MA1 (20) = Short-term trend
2. MA2 (50) = Medium-term trend
3. MA3 (100) = Long-term trend
**Entry Signals:**
- Price bounce dari MA dalam trend = continuation
- MA cross dengan konfirmasi structure = entry
- Multiple MA confluence = strong support/resistance
**Alerts Available:**
- MA1 cross MA2/MA3
- MA2 cross MA3
- Price cross any MA
---
#### **10. Multi-Timeframe Levels**
**Setup:**
- Enable HTF Level 1-5
- Set timeframes (contoh: 5m, 1H, 4H, D, W)
- Pilih line style (solid/dashed/dotted)
- Custom colors
**Cara Pakai:**
- Previous high/low dari HTF = strong S/R
- Breakout HTF level = significant move
- Multiple HTF levels confluence = major zone
---
### **C. Trading Setup Combination**
#### **Setup 1: High Probability Buy (Bullish)**
1. ✅ Swing structure: Bullish BOS
2. ✅ Price di Discount Zone
3. ✅ Pullback ke Bullish Order Block
4. ✅ Bullish FVG di bawah
5. ✅ RSI Multi-TF: Oversold
6. ✅ Price bounce dari MA
7. ✅ POC/Value Area support
8. ✅ Fibonacci 0.618-0.786 retracement
**Entry:** Saat price reject dari order block dengan confirmation candle
**Stop Loss:** Below order block
**Target:** Swing high atau premium zone
---
#### **Setup 2: High Probability Sell (Bearish)**
1. ✅ Swing structure: Bearish BOS
2. ✅ Price di Premium Zone
3. ✅ Pullback ke Bearish Order Block
4. ✅ Bearish FVG di atas
5. ✅ RSI Multi-TF: Overbought
6. ✅ Price reject dari MA
7. ✅ POC/Value Area resistance
8. ✅ Fibonacci 0.618-0.786 retracement
**Entry:** Saat price reject dari order block dengan confirmation candle
**Stop Loss:** Above order block
**Target:** Swing low atau discount zone
---
#### **Setup 3: Liquidity Grab (EQH/EQL)**
1. ✅ Identifikasi EQH atau EQL
2. ✅ Wait for liquidity sweep
3. ✅ Konfirmasi dengan CHoCH
4. ✅ Order block terbentuk setelah sweep
5. ✅ Entry saat retest order block
---
### **D. Tips & Best Practices**
**Risk Management:**
- Selalu gunakan stop loss
- Risk 1-2% per trade
- Risk:Reward minimum 1:2
- Jangan over-leverage
**Confluence adalah Kunci:**
- Minimal 3-4 konfirmasi sebelum entry
- Lebih banyak konfirmasi = higher probability
- Quality over quantity
**Timeframe Analysis:**
- HTF (Higher Timeframe) = Trend direction
- LTF (Lower Timeframe) = Entry timing
- Align dengan HTF trend
**Backtesting:**
- Gunakan mode "Historical"
- Test strategy di berbagai market condition
- Record dan analyze hasil
**Market Condition:**
- Trending market = Follow BOS, use order blocks
- Ranging market = Use premium/discount zones, EQH/EQL
- High volatility = Wider stops, wait for clear structure
**Avoid:**
- Trading di equilibrium zone
- Entry tanpa konfirmasi
- Fighting the trend
- Overleveraging
- Emotional trading
---
## 📈 Recommended Settings
### **For Scalping (1m - 5m):**
- Internal Structure: ON
- Swing Structure: OFF
- Order Blocks: Internal only
- RSI Timeframes: 1m, 5m, 15m
- MA Periods: 9, 21, 50
### **For Day Trading (15m - 1H):**
- Internal Structure: ON
- Swing Structure: ON
- Order Blocks: Both
- RSI Timeframes: 15m, 1H, 4H
- MA Periods: 20, 50, 100
### **For Swing Trading (4H - D):**
- Internal Structure: OFF
- Swing Structure: ON
- Order Blocks: Swing only
- RSI Timeframes: 4H, D, W
- MA Periods: 20, 50, 200
---
## ⚠️ Disclaimer
Indicator ini adalah alat bantu analisis teknikal. Tidak ada indicator yang 100% akurat. Selalu:
- Lakukan analisa fundamental
- Gunakan proper risk management
- Praktik di demo account terlebih dahulu
- Trading memiliki resiko, trade at your own risk
---
## 📝 Version Info
**Version:** 5.0
**Platform:** TradingView Pine Script v5
**Author:** XoRonX
**Max Labels:** 500
**Max Lines:** 500
**Max Boxes:** 500
---
## 🔄 Updates & Support
Untuk update, bug reports, atau pertanyaan:
- Check documentation regularly
- Test new features in replay mode
- Backup your settings before updates
---
## 🎓 Learning Resources
**Recommended Study:**
1. Smart Money Concepts (SMC) basics
2. Order blocks theory
3. Liquidity concepts
4. ICT (Inner Circle Trader) concepts
5. Volume profile analysis
6. Multi-timeframe analysis
**Practice:**
- Start with higher timeframes
- Master one concept at a time
- Keep a trading journal
- Review your trades weekly
---
**Happy Trading! 🚀📊**
_Remember: The best indicator is your own analysis and discipline._
Trend Gazer v5# Trend Gazer v5: Professional Multi-Timeframe ICT Analysis System
## 📊 Overview
**Trend Gazer v5** is a comprehensive institutional-grade trading system that synthesizes multiple proven methodologies into a unified analytical framework. This indicator combines **ICT (Inner Circle Trader) concepts**, **Smart Money Structure**, **Order Block detection**, **Fair Value Gaps**, and **volumetric analysis** to provide traders with high-probability trade setups backed by institutional footprints.
Unlike fragmented indicators that force traders to switch between multiple tools, Trend Gazer v5 delivers a **holistic market view** in a single overlay, eliminating analysis paralysis and enabling confident decision-making.
---
## 🎯 Why This Combination is Necessary
### The Problem with Single-Concept Indicators
Traditional indicators suffer from three critical flaws:
1. **Isolated Context** - Price action, volume, and structure are analyzed separately, creating conflicting signals
2. **Timeframe Blindness** - Single-timeframe analysis misses institutional activity occurring across multiple timeframes
3. **Lagging Confirmation** - Waiting for one indicator to confirm another causes missed entries and late exits
### The Institutional Trading Reality
Professional traders and institutions operate across **multiple dimensions simultaneously**:
- **Structural Context**: Where are we in the market cycle? (CHoCH, SiMS, BoMS)
- **Order Flow**: Where is institutional supply and demand concentrated? (Order Blocks)
- **Inefficiencies**: Where are price imbalances that must be filled? (Fair Value Gaps)
- **Momentum Context**: Is volume expanding or contracting? (VWC/TBOSI)
- **Mean Reversion Points**: Where do institutions expect rebounds? (NPR/BB, EMAs)
**Trend Gazer v5 unifies these dimensions**, creating a complete picture of market microstructure that individual indicators cannot provide.
---
## 🔬 Core Analytical Framework
### 1️⃣ ICT Donchian Smart Money Structure
**Purpose**: Identify institutional market structure shifts that precede major moves.
**Components**:
- **CHoCH (Change of Character)** - Market structure break signaling trend exhaustion
- `1.CHoCH` (Bullish) - Lower low broken, shift to bullish structure
- `A.CHoCH` (Bearish) - Higher high broken, shift to bearish structure
- **SiMS (Shift in Market Structure)** - Initial structure shift (2nd occurrence)
- **BoMS (Break of Market Structure)** - Continuation structure (3rd+ occurrence)
**Why It's Essential**:
Retail traders react to price changes. Institutions **create** price changes by breaking structure. By detecting these shifts using **Donchian channels** (the purest form of high/low tracking), we identify the exact moments when institutional bias changes.
**Credit**: Based on *ICT Donchian Smart Money Structure* by Zeiierman (CC BY-NC-SA 4.0)
---
### 2️⃣ Multi-Timeframe Order Block Detection
**Purpose**: Map institutional supply/demand zones where price is likely to reverse.
**Methodology**:
Order Blocks represent the **last opposite-direction candle** before a strong move. These zones indicate where institutions accumulated (bullish OB) or distributed (bearish OB) positions.
**Multi-Timeframe Coverage**:
- **1-minute**: Scalping zones for day traders
- **3-minute**: Short-term swing zones
- **15-minute**: Intraday institutional zones
- **60-minute**: Daily swing zones
- **Current TF**: Dynamic adaptation to any chart timeframe
**Key Features**:
- **Bounce Detection** - Identifies when price rebounds from OB zones (Signal 7: 🎯 OB Bounce)
- **Breaker Tracking** - Monitors when OBs are violated, converting bullish OBs to resistance and vice versa
- **Visual Rendering** - Color-coded boxes with transparency showing OB strength
- **OB Direction Filter** - Blocks contradictory signals (no SELL in bullish OB, no BUY in bearish OB)
**Why MTF Order Blocks Matter**:
A 60-minute Order Block represents institutional positioning at a larger timeframe. When combined with a 3-minute entry signal, you're trading **with** the big players, not against them.
---
### 3️⃣ Fair Value Gap (FVG) Detection
**Purpose**: Identify price inefficiencies that institutional traders must eventually fill.
**What Are FVGs?**:
Fair Value Gaps occur when price moves so rapidly that it leaves an **imbalance** - a gap between the high of one candle and the low of the candle two bars later (or vice versa). Institutions view these as inefficient pricing that must be corrected.
**Detection Logic**:
```
Bullish FVG: high < low → Gap up = Bearish imbalance (expect downward fill)
Bearish FVG: low > high → Gap down = Bullish imbalance (expect upward fill)
```
**Visual Design**:
- **Bullish FVG**: Green boxes (support zones where price should bounce)
- **Bearish FVG**: Red boxes (resistance zones where price should reject)
- **Mitigation Tracking**: FVGs disappear when filled, signaling completion
- **Volume Attribution**: Each FVG tracks associated buying/selling volume
**Why FVGs Are Critical**:
Institutions operate on **efficiency**. Gaps represent inefficiency. When price returns to fill a gap, it's not random - it's institutional traders **correcting market inefficiency**. Trading into FVG fills offers exceptional risk/reward.
---
### 4️⃣ Volumetric Weighted Cloud (VWC/TBOSI)
**Purpose**: Detect momentum shifts and trend strength using volume-weighted price action.
**Mechanism**:
VWC applies **volatility weighting** to moving averages, creating a dynamic cloud that expands during high-volatility trends and contracts during consolidation.
**Multi-Timeframe Analysis**:
- **1m, 3m, 5m**: Micro-scalping momentum
- **15m**: Intraday trend confirmation
- **60m, 240m**: Swing trade trend validation
**Signal Generation**:
- **VWC Switch (Signal 2)**: When cloud color flips (red → green or green → red), indicating momentum reversal
- **VWC Status Table**: Real-time display of trend direction across all timeframes
**Why Volume-Weighting Matters**:
Traditional moving averages treat all bars equally. VWC gives **more weight to high-volume bars**, ensuring that signals reflect actual institutional participation, not low-volume noise.
---
### 5️⃣ Non-Repaint STDEV (NPR) & Bollinger Bands
**Purpose**: Identify extreme mean-reversion points without repainting.
**Problem with Traditional Indicators**:
Many indicators **repaint** - they change past values when new data arrives, making backtests misleading. NPR uses **lookahead bias prevention** to ensure signals remain fixed.
**Configuration**:
- **15-minute NPR/BB**: Intraday volatility bands
- **60-minute NPR/BB**: Swing trade extremes
- **Multiple Kernel Options**: Exponential, Simple, Double Exponential, Triple Exponential for different smoothing profiles
**Signal Logic (Signal 8)**:
- **BUY**: Price closes **inside** lower band (not just touching it) → Extreme oversold with institutional absorption likely
- **SELL**: Price closes **inside** upper band → Extreme overbought with institutional distribution likely
**Why NPR is Superior**:
Repainting indicators give traders false confidence in backtests. NPR ensures every signal you see in history is **exactly** what a trader would have seen in real-time.
---
### 6️⃣ 💎 STRONG CHoCH Pattern Detection
**Purpose**: Identify the highest-probability setups when multiple CHoCH confirmations align within a tight timeframe.
**Pattern Logic**:
**STRONG BUY Pattern**:
```
1.CHoCH → A.CHoCH → 1.CHoCH (within 20 bars)
```
This sequence indicates:
1. Initial bullish structure shift
2. Bearish retest (pullback)
3. **Renewed bullish confirmation** - Institutions are re-accumulating after shaking out weak hands
**STRONG SELL Pattern**:
```
A.CHoCH → 1.CHoCH → A.CHoCH (within 20 bars)
```
This sequence indicates:
1. Initial bearish structure shift
2. Bullish retest (dead cat bounce)
3. **Renewed bearish confirmation** - Institutions are re-distributing after trapping longs
**Visual Display**:
```
💎 BUY
```
- **0% transparency** (fully opaque) - Maximum visual priority
- Displayed **immediately** when pattern completes (no additional signal required)
- Independent of Market Structure filter (pattern itself is the confirmation)
**Why STRONG Signals Are Different**:
- **Triple Confirmation**: Three structure shifts eliminate false breakouts
- **Tight Timeframe**: 20-bar window ensures institutional conviction, not random noise
- **Automatic Display**: No waiting for price action - the pattern itself triggers the alert
- **Historical Validation**: This specific sequence has proven to precede major institutional moves
**Risk Management**:
STRONG signals offer the best risk/reward because:
1. Stop loss can be placed beyond the middle CHoCH (tight risk)
2. Target can be set at next major structure level (large reward)
3. Pattern failure is immediately evident (quick exit if wrong)
---
### 7️⃣ Multi-EMA Framework
**Purpose**: Provide dynamic support/resistance and trend context.
**EMA Configuration**:
- **EMA 7**: Micro-trend (scalping)
- **EMA 20**: Short-term trend
- **EMA 50**: Institutional pivot (Signal 6: EMA50 Bounce)
- **EMA 100**: Mid-term trend filter
- **EMA 200**: Major institutional support/resistance
- **EMA 400, 800**: Macro trend context
**Visual Fills**:
- Color-coded fills between EMAs create **visual trend strength zones**
- Convergence = consolidation
- Divergence = trending market
**Why 7 EMAs?**:
Each EMA represents a different **participant timeframe**:
- EMA 7/20: Day traders and scalpers
- EMA 50/100: Swing traders
- EMA 200/400/800: Position traders and institutions
When all EMAs align, **all participant types agree on direction** - the highest-probability trend trades.
---
## 🚀 8-Signal Trading System
Trend Gazer v5 employs **8 distinct signal conditions** (all enabled by default), each designed to capture different market regimes:
### ⭐ Signal Hierarchy & Trading Philosophy
**IMPORTANT**: Not all signals are created equal. The indicator displays a hierarchy of signal quality:
**PRIMARY SIGNALS (Trade These)**:
- 💎 **STRONG BUY/SELL** - Triple-confirmed CHoCH patterns (highest priority)
- 🌟 **Star Signals (S7, S8)** - High-probability institutional zone reactions
- Signal 7: Order Block Bounce
- Signal 8: 60m NPR/BB Bounce
**AUXILIARY SIGNALS (Confirmation & Context)**:
- **Signals 1-6** - Use these as:
- **Confirmation** for Star Signals (when multiple signals align)
- **Context** for understanding market conditions
- **Early warnings** of potential moves (validate before trading)
- **Additional filters** (e.g., "only trade Star Signals that also have Signal 1")
**Trading Recommendation**:
- **Conservative Traders**: Trade ONLY 💎 STRONG and 🌟 Star Signals
- **Moderate Traders**: Trade Star Signals + validated auxiliary signals (2+ signal confirmation)
- **Active Traders**: Use all signals with proper risk management
The visual transparency system reinforces this hierarchy:
- 0% transparent = STRONG (💎) - Highest conviction
- 50% transparent = Star (🌟) + OB signals - High quality
- 70% transparent = Auxiliary (S1-S6) - Supplementary information
### Signal 1: RSI Shift + Structure (AND Logic)
**Strictest Signal** - Requires both RSI momentum confirmation AND structure change.
- **Use Case**: High-conviction trades in trending markets
- **Frequency**: Least frequent, highest accuracy
### Signal 2: VWC Switch (OR Logic)
**Most Frequent Signal** - Triggers on any VWC color flip across monitored timeframes.
- **Use Case**: Capturing early momentum shifts
- **Frequency**: Most frequent, good for active traders
### Signal 3: Structure Change
**Bar Color Change with RSI Confirmation** - Detects when candle color shifts with supporting RSI.
- **Use Case**: Trend continuation trades
- **Frequency**: Moderate
### Signal 4: BB Breakout + RSI
**Bollinger Band Breakout Reversal** - Price breaks band then immediately reverses.
- **Use Case**: Fade false breakouts
- **Frequency**: Moderate, excellent risk/reward
### Signal 5: BB/EMA50 Break
**Aggressive Breakout Signal** - Price breaks both BB and EMA50 simultaneously.
- **Use Case**: Momentum breakout trades
- **Frequency**: Moderate-high
### Signal 6: EMA50 Bounce Reversal
**Mean Reversion at EMA50** - Price touches EMA50 and bounces.
- **Use Case**: Trading pullbacks in strong trends
- **Frequency**: Moderate, reliable
### Signal 7: 🌟 OB Bounce (Star Signal)
**Order Block Bounce** - Price enters OB zone and reverses.
- **Use Case**: Institutional zone reactions
- **Frequency**: Low, but extremely high quality
- **Special Features**:
- 🎯 **OB Bounce Label**: `🌟 🎯 BUY/SELL ` - Actual Signal 7 bounce from visible OB
- 📍 **In OB Label**: `📍 BUY/SELL ` - Other signals (S1-6, S8) occurring inside an OB zone
- **OB Direction Filter**: Blocks contradictory signals (no SELL in bullish OB, no BUY in bearish OB)
### Signal 8: 🌟 60m NPR/BB Bounce (Star Signal)
**Extreme Mean-Reversion** - Price closes **inside** 60m NPR/BB bands at extremes.
- **Use Case**: Capturing institutional absorption at extremes
- **Frequency**: Low, exceptional win rate
- **Special Logic**: Candle close must be **INSIDE** bands, not just touching (prevents false breakouts)
### 💎 STRONG Signals (Bonus)
**CHoCH Pattern Completion** - Triple-confirmed structure shifts.
- **STRONG BUY**: `1.CHoCH → A.CHoCH → 1.CHoCH (≤20 bars)`
- **STRONG SELL**: `A.CHoCH → 1.CHoCH → A.CHoCH (≤20 bars)`
- **Display**: Immediate upon pattern completion (independent signal)
- **Use Case**: Highest-conviction institutional trend shifts
---
## 🎨 Visual Design Philosophy
### Signal Hierarchy via Transparency
**0% Transparency (Opaque)**:
- 💎 **STRONG BUY/SELL** - Highest priority, institutional pattern confirmation
**50% Transparency**:
- 🌟 **Star Signals** (S7, S8) - High-quality mean reversion
- 🎯 **OB Bounce** - Institutional zone reaction
- 📍 **In OB** - Enhanced signal in institutional zone
- **CHoCH Labels** (1.CHoCH, A.CHoCH) - Structure shift markers
**70% Transparency**:
- **Regular Signals** (S1-S6) - Standard trade setups
This visual hierarchy ensures traders **instantly recognize** high-priority setups without analysis paralysis.
### Color Scheme: Japanese Candlestick Convention
**Bullish = Red | Bearish = Blue/Green**
This follows traditional Japanese candlestick methodology where:
- **Red (Yang)**: Positive energy, rising prices, bullish
- **Blue/Green (Yin)**: Negative energy, falling prices, bearish
While Western conventions often reverse this, we maintain **ICT and institutional conventions** for consistency with professional trading rooms.
---
## 📡 Alert System
### Any Alert (Automatic)
**8 Events Monitored**:
1. 💎 **STRONG BUY** - Pattern: `1.CHoCH → A.CHoCH → 1.CHoCH`
2. 💎 **STRONG SELL** - Pattern: `A.CHoCH → 1.CHoCH → A.CHoCH`
3. ⭐ **Star BUY** - Signal 7 or 8
4. ⭐ **Star SELL** - Signal 7 or 8
5. 📍 **BUY (in OB)** - Any signal inside Bullish Order Block
6. 📍 **SELL (in OB)** - Any signal inside Bearish Order Block
7. **Bullish CHoCH** - Market structure shift to bullish
8. **Bearish CHoCH** - Market structure shift to bearish
**Format**: `TICKER TIMEFRAME EventName`
**Example**: `BTCUSDT 5 💎 STRONG BUY`
### Individual alertcondition() Options
Create custom alerts for specific events:
- BUY/SELL Signals (all or filtered)
- Star Signals Only (S7/S8)
- STRONG Signals Only (💎)
- CHoCH Events Only
- Bullish/Bearish CHoCH separately
---
## ⚙️ Configuration & Settings
### ICT Structure Filter (DEFAULT ON ⭐)
**Enable Structure Filter**: Display signals ONLY after CHoCH/SiMS/BoMS
- **Purpose**: Filter out noise by requiring institutional confirmation
- **Recommendation**: Keep enabled for disciplined trading
**Show Structure Labels (DEFAULT ON ⭐)**: Display CHoCH/SiMS/BoMS labels
- **Purpose**: Visual confirmation of market structure state
- **Labels**:
- `1.CHoCH` (Red background, white text) - Bullish structure shift
- `A.CHoCH` (Blue background, white text) - Bearish structure shift
- `2.SMS` / `B.SMS` (Red/Blue text) - Shift in Market Structure (2nd occurrence)
- `3.BMS` / `C.BMS` (Red/Blue text) - Break of Market Structure (3rd+ occurrence)
**Structure Period**: Default 3 bars (ICT standard)
### Order Block Configuration
**Enable Multi-Timeframe OBs**: Detect OBs from multiple timeframes simultaneously
**Mitigation Options**:
- Close - OB invalidated when candle closes through it
- Wick - OB invalidated when wick touches it
- 50% - OB invalidated when 50% of zone is violated
**Show OBs from**:
- Current Timeframe (always)
- 1m, 3m, 15m, 60m (selectable)
### Fair Value Gap Settings
**Show FVGs**: Enable/disable FVG rendering
**Mitigation Source**: Wick, Close, or 50% fill
**Color Customization**: Bullish FVG (green), Bearish FVG (red)
### Signal Filters
**Show ONLY Star Signals (DEFAULT OFF)**:
- When ON: Display only S7 (OB Bounce) and S8 (NPR/BB Bounce)
- When OFF: Display all signals S1-S8 (DEFAULT)
- **Use Case**: Focus on highest-quality setups, ignore noise
### Visual Settings
**EMA Display**: Toggle individual EMAs on/off
**VWC Cloud**: Enable/disable volumetric cloud
**NPR/BB Bands**: Show/hide 15m and 60m bands
**Status Table**: Real-time VWC status across all timeframes
---
## 📚 How to Use
### For Scalpers (1m-5m Charts)
1. Enable **1m and 3m Order Blocks**
2. Watch for **Signal 2 (VWC Switch)** or **Signal 5 (BB/EMA50 Break)**
3. Confirm with **1m/3m MTF OB** as support/resistance
4. Use **FVGs** for micro-target setting
5. Set alerts for **Star BUY/SELL** for highest-quality scalps
### For Day Traders (15m-60m Charts)
1. Enable **15m and 60m Order Blocks**
2. Wait for **CHoCH** to establish bias
3. Trade **Signal 7 (OB Bounce)** or **Signal 8 (60m NPR/BB Bounce)**
4. Use **EMA 50/100** as dynamic stop placement
5. Set alerts for **💎 STRONG BUY/SELL** for major moves
### For Swing Traders (4H-Daily Charts)
1. Enable **60m Order Blocks** (will render as larger zones on HTF)
2. Wait for **Market Structure confirmation** (CHoCH)
3. Focus on **Signal 1 (RSI Shift + Structure)** for highest conviction
4. Use **EMA 200/400/800** for macro trend alignment
5. Set alerts for **Bullish/Bearish CHoCH** to catch structure shifts early
### Universal Strategy (Recommended Approach)
1. **Focus on Primary Signals First** - Build your track record with 💎 STRONG and 🌟 Star Signals only
2. **Wait for Market Structure** - Never trade against CHoCH direction
3. **Use Auxiliary Signals for Confirmation** - When a Star Signal appears, check if auxiliary signals (S1-6) also confirm
4. **Respect Order Blocks** - Fade signals that contradict OB direction
5. **Use FVGs for Targets** - Price gravitates toward unfilled gaps
6. **Gradually Incorporate Auxiliary Signals** - Once profitable with primary signals, experiment with validated auxiliary setups
### Signal Quality Statistics (Typical Observation)
Based on common market behavior patterns:
**💎 STRONG Signals**:
- Frequency: Rare (1-3 per week on daily charts)
- Win Rate: Very High (70-85% when proper risk management applied)
- Risk/Reward: Excellent (1:3 to 1:5+ typical)
**🌟 Star Signals (S7, S8)**:
- Frequency: Moderate (2-5 per day on lower timeframes)
- Win Rate: High (60-75% when aligned with structure)
- Risk/Reward: Good (1:2 to 1:4 typical)
**Auxiliary Signals (S1-6)**:
- Frequency: High (multiple per hour on active timeframes)
- Win Rate: Moderate (50-65% standalone, higher when used as confirmation)
- Risk/Reward: Variable (1:1 to 1:3 typical)
**Key Insight**: Trading only primary signals reduces trade frequency but dramatically improves consistency and psychological ease.
---
## 🏆 What Makes This Indicator Unique
### 1. **True Multi-Timeframe Integration**
Most "MTF" indicators simply display data from other timeframes. Trend Gazer v5 **synthesizes** MTF data into unified signals, eliminating conflicting information.
### 2. **Non-Repainting Architecture**
All signals are fixed at bar close. What you see in backtests is exactly what you'd see in real-time.
### 3. **Institutional Focus**
Every component is designed around institutional behavior:
- Where they accumulate (Order Blocks)
- When they shift (CHoCH)
- What they must fix (FVGs)
- How they create momentum (VWC)
### 4. **Complete Transparency**
- **Open Source** - Full code visibility
- **Credited Sources** - All borrowed concepts attributed
- **No Black Boxes** - Every calculation is documented
### 5. **Flexible Yet Focused**
- **8 Signal Types** - Adapts to any market regime
- **Default Settings Optimized** - Works immediately without tweaking
- **Optional Filters** - "Show ONLY Star Signals" for disciplined traders
### 6. **Professional Alert System**
- **8-event Any Alert** - Never miss institutional moves
- **Individual alertconditions** - Customize to your strategy
- **Formatted Messages** - Ticker + Timeframe + Event for instant context
---
## 📖 Educational Value
### Learning ICT Concepts
This indicator serves as a **visual teaching tool** for:
- **Market Structure**: See CHoCH/SiMS/BoMS in real-time
- **Order Blocks**: Understand where institutions positioned
- **Fair Value Gaps**: Learn how inefficiencies are filled
- **Smart Money Behavior**: Watch institutional footprints unfold
### Backtesting & Strategy Development
Use Trend Gazer v5 to:
1. **Validate ICT Concepts** - Do OB bounces really work? Test it.
2. **Optimize Entry Timing** - Which signals work best in your market?
3. **Develop Filters** - Combine signals for your edge
4. **Build Strategies** - Export signals to Pine Script strategies
---
## ⚠️ Disclaimer
This indicator is for **educational and informational purposes only**. It should not be considered as financial advice or a recommendation to buy or sell any financial instrument.
**Trading involves substantial risk of loss**. Past performance is not indicative of future results. No indicator, regardless of sophistication, can guarantee profitable trades.
**Always:**
- Conduct your own research
- Use proper risk management (1-2% risk per trade)
- Consult with qualified financial advisors
- Practice on paper/demo accounts before live trading
- Understand that you are solely responsible for your trading decisions
---
## 🔗 Credits & Licenses
### Original Code Sources
1. **ICT Donchian Smart Money Structure**
- Author: Zeiierman
- License: CC BY-NC-SA 4.0
- Modifications: Integrated with multi-signal system, added CHoCH pattern detection
2. **Reverse RSI Signals**
- Author: AlgoAlpha
- License: MPL 2.0
- Modifications: Adapted for internal signal logic
3. **Volumetric Weighted Cloud (VWC/TBOSI)**
- Original concept adapted for multi-timeframe analysis
- Enhanced with MTF table display
4. **Order Block & FVG Detection**
- Based on ICT concepts
- Custom implementation with MTF support
### This Indicator's License
**Mozilla Public License 2.0 (MPL 2.0)**
You are free to:
- ✅ Use commercially
- ✅ Modify and distribute
- ✅ Use privately
- ✅ Patent use
Under conditions:
- 📄 Disclose source
- 📄 License and copyright notice
- 📄 Same license for modifications
---
## 📞 Support & Community
### Reporting Issues
If you encounter bugs or have feature suggestions, please provide:
1. Chart timeframe and symbol
2. Settings configuration
3. Screenshot of the issue
4. Expected vs actual behavior
### Best Practices
- Start with default settings
- Gradually enable/disable features to understand each component
- Use demo account for at least 30 days before live trading
- Combine with proper risk management
---
## 🚀 Version History
### v5.0 - Simplified ICT Mode (Current)
- ✅ Removed all unused filters and features
- ✅ Enabled all 8 signals by default
- ✅ Added 💎 STRONG CHoCH pattern detection
- ✅ Enhanced OB Bounce labeling system
- ✅ Added FVG detection and visualization
- ✅ Improved alert system (8 events)
- ✅ Optimized performance (faster rendering)
- ✅ Added comprehensive DESCRIPTION documentation
### v4.2 - ICT Mode with EMA Convergence Filter (Deprecated)
- Legacy version with EMA convergence features (removed for simplicity)
### v4.0 - Pure ICT Mode (Deprecated)
- Initial ICT-focused release
---
## 🎓 Recommended Learning Resources
To fully leverage this indicator, study:
1. **ICT Concepts** (Inner Circle Trader - YouTube)
- Market Structure
- Order Blocks
- Fair Value Gaps
- Liquidity Concepts
2. **Smart Money Concepts (SMC)**
- Change of Character (CHoCH)
- Break of Structure (BOS)
- Liquidity Sweeps
3. **Volume Spread Analysis (VSA)**
- Effort vs Result
- Supply vs Demand
- Volume Climax
4. **Risk Management**
- Position Sizing
- R-Multiple Theory
- Win Rate vs Risk/Reward Balance
---
## ✅ Quick Start Checklist
- Add indicator to chart
- Verify **Enable Structure Filter** is ON
- Verify **Show Structure Labels** is ON
- Enable desired MTF Order Blocks (1m, 3m, 15m, 60m)
- Enable FVG display
- Set up **Any Alert** for all 8 events
- Paper trade for 30 days minimum
- Document your trades (screenshots + notes)
- Review performance weekly
- Adjust filters based on your strategy
---
## 💡 Final Thoughts
**Trend Gazer v5 is not a "magic button" indicator.** It's a professional analytical framework that requires education, practice, and discipline.
The best traders don't use indicators to **tell them what to do**. They use indicators to **confirm what they already see** in price action.
Use this tool to:
- ✅ Confirm your analysis
- ✅ Filter out low-probability setups
- ✅ Identify institutional footprints
- ✅ Time entries with precision
Avoid using it to:
- ❌ Trade blindly without understanding context
- ❌ Ignore risk management
- ❌ Revenge trade after losses
- ❌ Replace education with automation
**Trade smart. Trade safe. Trade with structure.**
---
**© rasukaru666 | 2025 | Mozilla Public License 2.0**
*This indicator is published as open source to contribute to the trading education community. If it helps you, please share your experience and help others learn.*
------------------------------------------------------
# Trend Gazer v5: プロフェッショナル・マルチタイムフレームICT分析システム
## 📊 概要
**Trend Gazer v5** は、複数の実証済み手法を統合した分析フレームワークを提供する、包括的な機関投資家グレードの取引システムです。このインジケーターは、**ICT（Inner Circle Trader）コンセプト**、**スマートマネー構造**、**オーダーブロック検知**、**フェアバリューギャップ**、および**出来高分析**を組み合わせて、機関投資家の足跡に裏打ちされた高確率の取引セットアップをトレーダーに提供します。
断片的なインジケーターは、トレーダーに複数のツールを切り替えることを強いますが、Trend Gazer v5は**包括的な市場ビュー**を単一のオーバーレイで提供し、分析麻痺を排除して自信ある意思決定を可能にします。
---
## 🎯 なぜこの組み合わせが必要なのか
### 単一コンセプトインジケーターの問題点
従来のインジケーターは3つの致命的な欠陥を抱えています：
1. **孤立したコンテキスト** - 価格、出来高、構造が個別に分析され、矛盾するシグナルを生成
2. **タイムフレームの盲目性** - 単一タイムフレーム分析は、複数のタイムフレームで発生する機関投資家の活動を見逃す
3. **遅れた確認** - あるインジケーターが別のインジケーターの確認を待つことで、エントリーを逃し、エグジットが遅れる
### 機関投資家の取引実態
プロのトレーダーや機関投資家は、**複数の次元を同時に**操作します：
- **構造的コンテキスト**: 市場サイクルのどこにいるのか？（CHoCH、SiMS、BoMS）
- **オーダーフロー**: 機関投資家の需要と供給が集中しているのはどこか？（オーダーブロック）
- **非効率性**: 埋めなければならない価格の不均衡はどこか？（フェアバリューギャップ）
- **モメンタムコンテキスト**: 出来高は拡大しているか縮小しているか？（VWC/TBOSI）
- **平均回帰ポイント**: 機関投資家がリバウンドを期待する場所はどこか？（NPR/BB、EMA）
**Trend Gazer v5はこれらの次元を統合**し、個別のインジケーターでは提供できない市場マイクロ構造の完全な全体像を作成します。
---
## 🔬 コア分析フレームワーク
### 1️⃣ ICT ドンチャン・スマートマネー構造
**目的**: 大きな動きに先行する機関投資家の市場構造シフトを識別する。
**コンポーネント**:
- **CHoCH (Change of Character / 性質の変化)** - トレンド疲弊を示す市場構造のブレイク
- `1.CHoCH`（強気） - 直近安値のブレイク、強気構造へのシフト
- `A.CHoCH`（弱気） - 直近高値のブレイク、弱気構造へのシフト
- **SiMS (Shift in Market Structure / 市場構造のシフト)** - 初期構造シフト（2回目の発生）
- **BoMS (Break of Market Structure / 市場構造のブレイク)** - 継続構造（3回目以降の発生）
**なぜ不可欠なのか**:
小売トレーダーは価格変化に反応します。機関投資家は構造を破ることで価格変化を**作り出します**。**ドンチャンチャネル**（高値/安値追跡の最も純粋な形式）を使用してこれらのシフトを検出することで、機関投資家のバイアスが変化する正確な瞬間を特定します。
**クレジット**: Zeiierman氏の*ICT Donchian Smart Money Structure*に基づく（CC BY-NC-SA 4.0）
---
### 2️⃣ マルチタイムフレーム・オーダーブロック検知
**目的**: 価格が反転する可能性が高い機関投資家の需給ゾーンをマッピングする。
**方法論**:
オーダーブロックは、強い動きの前の**最後の反対方向ローソク足**を表します。これらのゾーンは、機関投資家がポジションを蓄積（強気OB）または分配（弱気OB）した場所を示します。
**マルチタイムフレームカバレッジ**:
- **1分足**: デイトレーダー向けスキャルピングゾーン
- **3分足**: 短期スイングゾーン
- **15分足**: イントラデイ機関投資家ゾーン
- **60分足**: デイリースイングゾーン
- **現在のTF**: 任意のチャートタイムフレームへの動的適応
**主要機能**:
- **バウンス検知** - OBゾーンから価格がリバウンドする時を識別（シグナル7: 🎯 OBバウンス）
- **ブレーカー追跡** - OBが破られた時を監視し、強気OBを抵抗に、弱気OBをサポートに変換
- **ビジュアルレンダリング** - OBの強度を示す透明度付きの色分けされたボックス
- **OB方向フィルター** - 矛盾するシグナルをブロック（強気OBでSELLなし、弱気OBでBUYなし）
**なぜMTFオーダーブロックが重要か**:
60分足のオーダーブロックは、より大きなタイムフレームでの機関投資家のポジショニングを表します。3分足のエントリーシグナルと組み合わせることで、大口プレイヤーと**同じ方向**で取引することになります。
---
### 3️⃣ フェアバリューギャップ（FVG）検知
**目的**: 機関投資家が最終的に埋めなければならない価格の非効率性を識別する。
**FVGとは何か？**:
フェアバリューギャップは、価格があまりにも急速に動いて**不均衡**を残す時に発生します - 1本のローソク足の高値と2本後のローソク足の安値の間のギャップ（またはその逆）。機関投資家はこれらを修正されなければならない非効率的な価格設定と見なします。
**検知ロジック**:
```
強気FVG: high < low → ギャップアップ = 弱気の不均衡（下方フィル予想）
弱気FVG: low > high → ギャップダウン = 強気の不均衡（上方フィル予想）
```
**ビジュアルデザイン**:
- **強気FVG**: 緑のボックス（価格がバウンドすべきサポートゾーン）
- **弱気FVG**: 赤のボックス（価格が拒否されるべき抵抗ゾーン）
- **ミティゲーション追跡**: FVGは埋められると消え、完了を示す
- **出来高帰属**: 各FVGは関連する買い/売り出来高を追跡
**なぜFVGが重要か**:
機関投資家は**効率性**で動きます。ギャップは非効率性を表します。価格がギャップを埋めるために戻る時、それはランダムではありません - 機関投資家が**市場の非効率性を修正**しているのです。FVGフィルへの取引は卓越したリスク/リワードを提供します。
---
### 4️⃣ 出来高加重クラウド（VWC/TBOSI）
**目的**: 出来高加重プライスアクションを使用してモメンタムシフトとトレンド強度を検出する。
**メカニズム**:
VWCは移動平均に**ボラティリティ加重**を適用し、高ボラティリティトレンド中に拡大し、コンソリデーション中に縮小する動的クラウドを作成します。
**マルチタイムフレーム分析**:
- **1m、3m、5m**: マイクロスキャルピングモメンタム
- **15m**: イントラデイトレンド確認
- **60m、240m**: スイングトレードトレンド検証
**シグナル生成**:
- **VWCスイッチ（シグナル2）**: クラウドの色が反転した時（赤→緑または緑→赤）、モメンタム反転を示す
- **VWCステータステーブル**: 全タイムフレームのトレンド方向のリアルタイム表示
**なぜ出来高加重が重要か**:
従来の移動平均はすべてのバーを等しく扱います。VWCは**高出来高バーに重みを与え**、シグナルが低出来高のノイズではなく、実際の機関投資家の参加を反映することを保証します。
---
### 5️⃣ ノンリペイントSTDEV（NPR）＆ボリンジャーバンド
**目的**: リペイントなしで極端な平均回帰ポイントを識別する。
**従来のインジケーターの問題点**:
多くのインジケーターは**リペイント**します - 新しいデータが到着すると過去の値を変更し、バックテストを誤解させます。NPRは**先読みバイアス防止**を使用して、シグナルが固定されたままであることを保証します。
**設定**:
- **15分足NPR/BB**: イントラデイボラティリティバンド
- **60分足NPR/BB**: スイングトレード極値
- **複数のカーネルオプション**: 指数、単純、二重指数、三重指数 - 異なる平滑化プロファイル
**シグナルロジック（シグナル8）**:
- **BUY**: 価格が下部バンドの**内側**でクローズ（触れるだけではない）→ 極端な売られ過ぎで機関投資家の吸収が可能性高い
- **SELL**: 価格が上部バンドの**内側**でクローズ → 極端な買われ過ぎで機関投資家の分配が可能性高い
**なぜNPRが優れているか**:
リペイントインジケーターはトレーダーにバックテストで誤った自信を与えます。NPRは、履歴で見るすべてのシグナルが、トレーダーがリアルタイムで見たであろうもの**そのもの**であることを保証します。
---
### 6️⃣ 💎 STRONG CHoChパターン検知
**目的**: 短い時間枠内で複数のCHoCH確認が整列した時の最高確率セットアップを識別する。
**パターンロジック**:
**STRONG BUYパターン**:
```
1.CHoCH → A.CHoCH → 1.CHoCH（20バー以内）
```
このシーケンスは以下を示します：
1. 初期強気構造シフト
2. 弱気リテスト（プルバック）
3. **更新された強気確認** - 機関投資家は弱い手を振り落とした後に再蓄積中
**STRONG SELLパターン**:
```
A.CHoCH → 1.CHoCH → A.CHoCH（20バー以内）
```
このシーケンスは以下を示します：
1. 初期弱気構造シフト
2. 強気リテスト（デッドキャットバウンス）
3. **更新された弱気確認** - 機関投資家はロングを罠にかけた後に再分配中
**ビジュアル表示**:
```
💎 BUY
```
- **0%透明度**（完全不透明） - 最大の視覚的優先度
- パターン完成時に**即座に**表示（追加シグナル不要）
- 市場構造フィルターから独立（パターン自体が確認）
**なぜSTRONGシグナルが異なるか**:
- **三重確認**: 3つの構造シフトが誤ったブレイクアウトを排除
- **短い時間枠**: 20バーウィンドウがランダムなノイズではなく、機関投資家の確信を保証
- **自動表示**: 価格アクションを待たない - パターン自体がアラートをトリガー
- **歴史的検証**: この特定のシーケンスは主要な機関投資家の動きに先行することが証明されている
**リスク管理**:
STRONGシグナルは最高のリスク/リワードを提供します：
1. ストップロスは中央のCHoCHの外に配置可能（タイトなリスク）
2. ターゲットは次の主要構造レベルに設定可能（大きなリワード）
3. パターン失敗は即座に明らか（間違っていればクイックエグジット）
---
### 7️⃣ マルチEMAフレームワーク
**目的**: ダイナミックなサポート/レジスタンスとトレンドコンテキストを提供する。
**EMA設定**:
- **EMA 7**: マイクロトレンド（スキャルピング）
- **EMA 20**: 短期トレンド
- **EMA 50**: 機関投資家のピボット（シグナル6: EMA50バウンス）
- **EMA 100**: 中期トレンドフィルター
- **EMA 200**: 主要な機関投資家のサポート/レジスタンス
- **EMA 400、800**: マクロトレンドコンテキスト
**ビジュアルフィル**:
- EMA間の色分けされたフィルが**ビジュアルトレンド強度ゾーン**を作成
- 収束 = コンソリデーション
- 発散 = トレンド市場
**なぜ7つのEMAか？**:
各EMAは異なる**参加者タイムフレーム**を表します：
- EMA 7/20: デイトレーダーとスキャルパー
- EMA 50/100: スイングトレーダー
- EMA 200/400/800: ポジショントレーダーと機関投資家
すべてのEMAが整列した時、**すべての参加者タイプが方向に同意**している - 最高確率のトレンド取引です。
---
## 🚀 8シグナル取引システム
Trend Gazer v5は**8つの異なるシグナル条件**（すべてデフォルトで有効）を採用しており、それぞれが異なる市場レジームを捕捉するように設計されています：
### ⭐ シグナル階層＆取引哲学
**重要**: すべてのシグナルが同じではありません。インジケーターはシグナル品質の階層を表示します：
**プライマリーシグナル（これを取引する）**:
- 💎 **STRONG BUY/SELL** - 三重CHoChパターン（最優先）
- 🌟 **スターシグナル（S7、S8）** - 高確率の機関投資家ゾーン反応
- シグナル7: オーダーブロックバウンス
- シグナル8: 60m NPR/BBバウンス
**補助シグナル（確認とコンテキスト）**:
- **シグナル1-6** - これらを以下として使用：
- スターシグナルの**確認**（複数のシグナルが整列した時）
- 市場状況を理解するための**コンテキスト**
- 潜在的な動きの**早期警告**（取引前に検証）
- **追加フィルター**（例：「シグナル1も出ているスターシグナルのみ取引」）
**取引推奨**:
- **保守的トレーダー**: 💎 STRONGと🌟スターシグナル**のみ**取引
- **中程度トレーダー**: スターシグナル + 検証された補助シグナル（2+シグナル確認）
- **アクティブトレーダー**: 適切なリスク管理ですべてのシグナルを使用
視覚的透明度システムはこの階層を強化します：
- 0%透明度 = STRONG（💎） - 最高の確信
- 50%透明度 = スター（🌟）+ OBシグナル - 高品質
- 70%透明度 = 補助（S1-S6） - 補足情報
### シグナル1: RSIシフト + 構造（ANDロジック）
**最も厳格なシグナル** - RSIモメンタム確認と構造変化の両方が必要。
- **使用例**: トレンド市場での高確信取引
- **頻度**: 最も少ない、最高の精度
- **分類**:
### シグナル2: VWCスイッチ（ORロジック）
**最も頻繁なシグナル** - 監視されているタイムフレームでのVWC色反転でトリガー。
- **使用例**: 早期モメンタムシフトの捕捉
- **頻度**: 最も頻繁、アクティブトレーダーに適している
- **分類**:
### シグナル3: 構造変化
**バーカラー変化とRSI確認** - RSIサポートでローソク足の色がシフトする時を検出。
- **使用例**: トレンド継続取引
- **頻度**: 中程度
- **分類**:
### シグナル4: BBブレイクアウト + RSI
**ボリンジャーバンドブレイクアウト反転** - 価格がバンドを破った後すぐに反転。
- **使用例**: 誤ったブレイクアウトをフェード
- **頻度**: 中程度、優れたリスク/リワード
- **分類**:
### シグナル5: BB/EMA50ブレイク
**積極的ブレイクアウトシグナル** - 価格がBBとEMA50を同時にブレイク。
- **使用例**: モメンタムブレイクアウト取引
- **頻度**: 中〜高
- **分類**:
### シグナル6: EMA50バウンス反転
**EMA50での平均回帰** - 価格がEMA50に触れてバウンス。
- **使用例**: 強いトレンドでのプルバック取引
- **頻度**: 中程度、信頼性あり
- **分類**:
### シグナル7: 🌟 OBバウンス（スターシグナル）
**オーダーブロックバウンス** - 価格がOBゾーンに入って反転。
- **使用例**: 機関投資家ゾーン反応
- **頻度**: 低いが、極めて高品質
- **分類**:
- **特別機能**:
- 🎯 **OBバウンスラベル**: `🌟 🎯 BUY/SELL ` - 可視OBからの実際のシグナル7バウンス
- 📍 **In OBラベル**: `📍 BUY/SELL ` - OBゾーン内で発生する他のシグナル（S1-6、S8）
- **OB方向フィルター**: 矛盾するシグナルをブロック（強気OBでSELLなし、弱気OBでBUYなし）
### シグナル8: 🌟 60m NPR/BBバウンス（スターシグナル）
**極端な平均回帰** - 価格が60m NPR/BBバンドの極値で**内側に**クローズ。
- **使用例**: 極値での機関投資家の吸収を捕捉
- **頻度**: 低い、卓越した勝率
- **分類**:
- **特別ロジック**: ローソク足のクローズがバンドの**内側**でなければならない（触れるだけではダメ、誤ったブレイクアウトを防止）
### 💎 STRONGシグナル（ボーナス）
**CHoChパターン完成** - 三重確認された構造シフト。
- **STRONG BUY**: `1.CHoCH → A.CHoCH → 1.CHoCH（≤20バー）`
- **STRONG SELL**: `A.CHoCH → 1.CHoCH → A.CHoCH（≤20バー）`
- **表示**: パターン完成時に即座（独立したシグナル）
- **分類**:
- **使用例**: 最高確信の機関投資家トレンドシフト
---
## 🎨 ビジュアルデザイン哲学
### 透明度によるシグナル階層
**0%透明度（不透明）**:
- 💎 **STRONG BUY/SELL** - 最優先、機関投資家パターン確認
**50%透明度**:
- 🌟 **スターシグナル**（S7、S8） - 高品質平均回帰
- 🎯 **OBバウンス** - 機関投資家ゾーン反応
- 📍 **In OB** - 機関投資家ゾーン内の強化されたシグナル
- **CHoChラベル**（1.CHoCH、A.CHoCH） - 構造シフトマーカー
**70%透明度**:
- **通常シグナル**（S1-S6） - 標準取引セットアップ
この視覚的階層により、トレーダーは分析麻痺なしに高優先度セットアップを**即座に認識**できます。
### カラースキーム: 日本式ローソク足慣例
**強気 = 赤 | 弱気 = 青/緑**
これは伝統的な日本式ローソク足方法論に従います：
- **赤（陽）**: ポジティブエネルギー、上昇価格、強気
- **青/緑（陰）**: ネガティブエネルギー、下降価格、弱気
西洋の慣例はしばしばこれを逆にしますが、プロの取引ルームとの一貫性のために**ICTと機関投資家の慣例**を維持します。
---
## 📡 アラートシステム
### Any Alert（自動）
**8つのイベントを監視**:
1. 💎 **STRONG BUY** - パターン: `1.CHoCH → A.CHoCH → 1.CHoCH`
2. 💎 **STRONG SELL** - パターン: `A.CHoCH → 1.CHoCH → A.CHoCH`
3. ⭐ **Star BUY** - シグナル7または8
4. ⭐ **Star SELL** - シグナル7または8
5. 📍 **BUY (in OB)** - 強気オーダーブロック内の任意のシグナル
6. 📍 **SELL (in OB)** - 弱気オーダーブロック内の任意のシグナル
7. **Bullish CHoCH** - 強気への市場構造シフト
8. **Bearish CHoCH** - 弱気への市場構造シフト
**フォーマット**: `TICKER TIMEFRAME EventName`
**例**: `BTCUSDT 5 💎 STRONG BUY`
### 個別alertcondition()オプション
特定のイベントのカスタムアラートを作成：
- BUY/SELLシグナル（すべてまたはフィルタリング）
- スターシグナルのみ（S7/S8）
- STRONGシグナルのみ（💎）
- CHoChイベントのみ
- 強気/弱気CHoCH個別
---
## ⚙️ 設定と設定
### ICT構造フィルター（デフォルトON ⭐）
**構造フィルターを有効化**: CHoCH/SiMS/BoMS後のシグナル**のみ**表示
- **目的**: 機関投資家の確認を要求することでノイズをフィルター
- **推奨**: 規律ある取引のために有効のままにする
**構造ラベルを表示（デフォルトON ⭐）**: CHoCH/SiMS/BoMSラベルを表示
- **目的**: 市場構造状態の視覚的確認
- **ラベル**:
- `1.CHoCH`（赤背景、白テキスト） - 強気構造シフト
- `A.CHoCH`（青背景、白テキスト） - 弱気構造シフト
- `2.SMS` / `B.SMS`（赤/青テキスト） - 市場構造のシフト（2回目）
- `3.BMS` / `C.BMS`（赤/青テキスト） - 市場構造のブレイク（3回目以降）
**構造期間**: デフォルト3バー（ICT標準）
### オーダーブロック設定
**マルチタイムフレームOBを有効化**: 複数のタイムフレームから同時にOBを検出
**ミティゲーションオプション**:
- Close - ローソク足がクローズで通過した時にOB無効化
- Wick - ウィックが触れた時にOB無効化
- 50% - ゾーンの50%が侵害された時にOB無効化
**OBを表示**:
- 現在のタイムフレーム（常に）
- 1m、3m、15m、60m（選択可能）
### フェアバリューギャップ設定
**FVGを表示**: FVGレンダリングを有効/無効
**ミティゲーションソース**: Wick、Close、または50%フィル
**カラーカスタマイゼーション**: 強気FVG（緑）、弱気FVG（赤）
### シグナルフィルター
**スターシグナルのみ表示（デフォルトOFF）**:
- ONの時: S7（OBバウンス）とS8（NPR/BBバウンス）のみ表示
- OFFの時: すべてのシグナルS1-S8を表示（デフォルト）
- **使用例**: 最高品質のセットアップに集中し、ノイズを無視
### ビジュアル設定
**EMA表示**: 個別のEMAをオン/オフ切り替え
**VWCクラウド**: 出来高クラウドを有効/無効
**NPR/BBバンド**: 15mと60mバンドを表示/非表示
**ステータステーブル**: すべてのタイムフレームでのリアルタイムVWCステータス
---
## 📚 使用方法
### スキャルパー向け（1m-5m チャート）
1. **1mと3mオーダーブロック**を有効化
2. **シグナル2（VWCスイッチ）**または**シグナル5（BB/EMA50ブレイク）**を監視
3. サポート/レジスタンスとして**1m/3m MTF OB**で確認
4. マイクロターゲット設定に**FVG**を使用
5. 最高品質のスキャルプのために**Star BUY/SELL**のアラートを設定
### デイトレーダー向け（15m-60m チャート）
1. **15mと60mオーダーブロック**を有効化
2. バイアスを確立するために**CHoCH**を待つ
3. **シグナル7（OBバウンス）**または**シグナル8（60m NPR/BBバウンス）**を取引
4. ダイナミックストップ配置に**EMA 50/100**を使用
5. 主要な動きのために**💎 STRONG BUY/SELL**のアラートを設定
### スイングトレーダー向け（4H-日足 チャート）
1. **60mオーダーブロック**を有効化（HTFでより大きなゾーンとしてレンダリング）
2. **市場構造確認**（CHoCH）を待つ
3. 最高確信のために**シグナル1（RSIシフト + 構造）**に集中
4. マクロトレンド整列のために**EMA 200/400/800**を使用
5. 構造シフトを早期に捕捉するために**Bullish/Bearish CHoCH**のアラートを設定
### ユニバーサル戦略（推奨アプローチ）
1. **まずプライマリーシグナルに集中** - 💎 STRONGと🌟スターシグナル**のみ**でトラックレコードを構築
2. **市場構造を待つ** - CHoCH方向に逆らって取引しない
3. **補助シグナルを確認に使用** - スターシグナルが現れたら、補助シグナル（S1-6）も確認するかチェック
4. **オーダーブロックを尊重** - OB方向と矛盾するシグナルをフェード
5. **ターゲットにFVGを使用** - 価格は埋められていないギャップに引き寄せられる
6. **徐々に補助シグナルを組み込む** - プライマリーシグナルで利益が出たら、検証された補助セットアップを実験
### シグナル品質統計（典型的な観察）
一般的な市場行動パターンに基づく：
**💎 STRONGシグナル**:
- 頻度: まれ（日足チャートで週1-3回）
- 勝率: 非常に高い（適切なリスク管理適用時70-85%）
- リスク/リワード: 優秀（典型的に1:3から1:5+）
**🌟 スターシグナル（S7、S8）**:
- 頻度: 中程度（短期足で1日2-5回）
- 勝率: 高い（構造と整列時60-75%）
- リスク/リワード: 良好（典型的に1:2から1:4）
**補助シグナル（S1-6）**:
- 頻度: 高い（活発なタイムフレームで1時間に複数回）
- 勝率: 中程度（単独で50-65%、確認として使用時はより高い）
- リスク/リワード: 変動（典型的に1:1から1:3）
**重要な洞察**: プライマリーシグナルのみの取引は取引頻度を減らしますが、一貫性と心理的容易さを劇的に改善します。
---
## 🏆 このインジケーターのユニークな点
### 1. **真のマルチタイムフレーム統合**
ほとんどの「MTF」インジケーターは単に他のタイムフレームからデータを表示するだけです。Trend Gazer v5はMTFデータを統一されたシグナルに**合成**し、矛盾する情報を排除します。
### 2. **ノンリペイント・アーキテクチャ**
すべてのシグナルはバークローズで固定されます。バックテストで見るものは、リアルタイムで見るであろうもの**そのもの**です。
### 3. **機関投資家フォーカス**
すべてのコンポーネントは機関投資家の行動を中心に設計されています：
- どこで蓄積するか（オーダーブロック）
- いつシフトするか（CHoCH）
- 何を修正しなければならないか（FVG）
- どのようにモメンタムを作り出すか（VWC）
### 4. **完全な透明性**
- **オープンソース** - 完全なコード可視性
- **クレジットされたソース** - すべての借用コンセプトが帰属
- **ブラックボックスなし** - すべての計算が文書化
### 5. **柔軟だが焦点を絞った**
- **8シグナルタイプ** - 任意の市場レジームに適応
- **最適化されたデフォルト設定** - 調整なしですぐに動作
- **オプションフィルター** - 規律あるトレーダーのための「スターシグナルのみ表示」
### 6. **プロフェッショナルアラートシステム**
- **8イベントAny Alert** - 機関投資家の動きを見逃さない
- **個別alertconditions** - あなたの戦略にカスタマイズ
- **フォーマットされたメッセージ** - 即座のコンテキストのためのTicker + Timeframe + Event
---
## 📖 教育的価値
### ICT概念の学習
このインジケーターは以下のための**視覚的教育ツール**として機能します：
- **市場構造**: CHoCH/SiMS/BoMSをリアルタイムで見る
- **オーダーブロック**: 機関投資家がどこでポジショニングしたかを理解
- **フェアバリューギャップ**: 非効率性がどのように埋められるかを学ぶ
- **スマートマネー行動**: 機関投資家の足跡が展開するのを観察
### バックテスティングと戦略開発
Trend Gazer v5を使用して：
1. **ICT概念を検証** - OBバウンスは本当に機能するか？テストする。
2. **エントリータイミングを最適化** - あなたの市場でどのシグナルが最も機能するか？
3. **フィルターを開発** - あなたのエッジのためにシグナルを組み合わせる
4. **戦略を構築** - シグナルをPine Scriptストラテジーにエクスポート
---
## ⚠️ 免責事項
このインジケーターは**教育および情報提供のみを目的**としています。金融アドバイスではありません。
**リスク警告**:
- 取引には重大な損失リスクが伴い、すべての投資家に適しているわけではありません
- 過去のパフォーマンスは将来の結果を**示すものではありません**
- どのインジケーターも利益ある取引を保証することはできません
- あなたは自分の取引決定に対して単独で責任を負います
**取引前に**:
- 自分自身の調査とデューデリジェンスを実施
- 資格のある金融アドバイザーに相談
- 適切なリスク管理を使用（取引あたり1-2%以上リスクを取らない）
- ライブ取引前にペーパー/デモアカウントで練習
- 損失は取引の一部であることを理解
このインジケーターによって提供される情報は、投資アドバイス、金融アドバイス、取引アドバイス、またはその他の種類のアドバイスを構成するものではありません。インジケーターの出力をそのように扱うべきではありません。作成者は、あなたが任意の暗号通貨、証券、または商品を買い、売り、または保有すべきであると推奨するものではありません。常に自分自身の調査を行い、専門的なアドバイスを求めてください。
このソフトウェアは、明示的または黙示的を問わず、いかなる種類の保証もなく「現状のまま」提供されます。
---
## 🔗 クレジットとライセンス
### 原作コードソース
1. **ICT Donchian Smart Money Structure**
- 作者: Zeiierman
- ライセンス: CC BY-NC-SA 4.0
- 変更: マルチシグナルシステムと統合、CHoChパターン検知を追加
2. **Reverse RSI Signals**
- 作者: AlgoAlpha
- ライセンス: MPL 2.0
- 変更: 内部シグナルロジックに適応
3. **Volumetric Weighted Cloud（VWC/TBOSI）**
- 元のコンセプトをマルチタイムフレーム分析に適応
- MTFテーブル表示で強化
4. **Order Block & FVG Detection**
- ICTコンセプトに基づく
- MTFサポートでカスタム実装
### このインジケーターのライセンス
**Mozilla Public License 2.0（MPL 2.0）**
以下が自由です：
- ✅ 商用利用
- ✅ 変更と配布
- ✅ 私的使用
- ✅ 特許使用
条件：
- 📄 ソースを開示
- 📄 ライセンスと著作権表示
- 📄 変更に同じライセンス
---
## 📞 サポートとコミュニティ
### 問題の報告
バグに遭遇したり機能提案がある場合は、以下を提供してください：
1. チャートタイムフレームとシンボル
2. 設定構成
3. 問題のスクリーンショット
4. 期待される動作と実際の動作
### ベストプラクティス
- デフォルト設定で開始
- 各コンポーネントを理解するために段階的に機能を有効/無効化
- ライブ取引前に少なくとも30日間デモアカウントを使用
- 適切なリスク管理と組み合わせる
---
## 🚀 バージョン履歴
### v5.0 - Simplified ICT Mode（現在）
- ✅ すべての未使用フィルターと機能を削除
- ✅ すべての8シグナルをデフォルトで有効化
- ✅ 💎 STRONG CHoChパターン検知を追加
- ✅ OBバウンスラベリングシステムを強化
- ✅ FVG検知と可視化を追加
- ✅ アラートシステムを改善（8イベント）
- ✅ パフォーマンスを最適化（より速いレンダリング）
- ✅ 包括的なDESCRIPTIONドキュメントを追加
### v4.2 - ICT Mode with EMA Convergence Filter（非推奨）
- EMA収束機能を持つレガシーバージョン（シンプルさのために削除）
### v4.0 - Pure ICT Mode（非推奨）
- 初期ICTフォーカスリリース
---
## 🎓 推奨学習リソース
このインジケーターを完全に活用するために、以下を学習してください：
1. **ICTコンセプト**（Inner Circle Trader - YouTube）
- 市場構造
- オーダーブロック
- フェアバリューギャップ
- 流動性コンセプト
2. **スマートマネーコンセプト（SMC）**
- Change of Character（CHoCH）
- Break of Structure（BOS）
- Liquidity Sweeps
3. **Volume Spread Analysis（VSA）**
- Effort vs Result
- Supply vs Demand
- Volume Climax
4. **リスク管理**
- ポジションサイジング
- R-Multiple理論
- 勝率vsリスク/リワードバランス
---
## ✅ クイックスタートチェックリスト
- チャートにインジケーターを追加
- **構造フィルターを有効化**がONであることを確認
- **構造ラベルを表示**がONであることを確認
- 希望するMTFオーダーブロックを有効化（1m、3m、15m、60m）
- FVG表示を有効化
- すべての8イベントのために**Any Alert**を設定
- 最低30日間ペーパートレード
- 取引を文書化（スクリーンショット + ノート）
- 週次でパフォーマンスをレビュー
- あなたの戦略に基づいてフィルターを調整
---
## 💡 最後の考え
**Trend Gazer v5は「魔法のボタン」インジケーターではありません。**教育、練習、規律を必要とするプロフェッショナル分析フレームワークです。
最高のトレーダーは、インジケーターを使って**何をすべきかを教えてもらいません**。インジケーターを使って、プライスアクションで**既に見ているものを確認**します。
このツールを使用して：
- ✅ 分析を確認
- ✅ 低確率セットアップをフィルターアウト
- ✅ 機関投資家の足跡を識別
- ✅ エントリーを精密にタイミング
使用を避けるべき：
- ❌ コンテキストを理解せずに盲目的に取引
- ❌ リスク管理を無視
- ❌ 損失後にリベンジトレード
- ❌ 教育を自動化に置き換える
**スマートに取引しましょう。安全に取引しましょう。構造を持って取引しましょう。**
---
**© rasukaru666 | 2025 | Mozilla Public License 2.0**
*このインジケーターは、取引教育コミュニティに貢献するためにオープンソースとして公開されています。役立つ場合は、あなたの経験を共有して他の人が学ぶのを助けてください。*
[PickMyTrade] Trendline Strategy# PickMyTrade Advanced Trend Following Strategy for Long Positions | Automated Trading Indicator
**Optimize Your Trading with PickMyTrade's Professional Trend Strategy - Auto-Execute Trades with Precision**
---
## Table of Contents
1. (#overview)
2. (#why-this-strategy-makes-money)
3. (#key-features)
4. (#how-it-works)
5. (#strategy-settings--configuration)
6. (#pickmytrade-integration)
7. (#advanced-features)
8. (#risk-management)
9. (#best-practices)
10. (#performance-optimization)
11. (#getting-started)
12. (#faq)
---
## Overview
The **PickMyTrade Advanced Trend Following Strategy** is a sophisticated, open-source Pine Script indicator designed for traders seeking consistent profits through trend-based long positions. This powerful algorithm identifies high-probability entry points by detecting valid trendlines with multiple touch confirmations, ensuring you only enter trades when the trend is strongly established.
### What Makes This Strategy Unique?
- **Multi-Trendline Detection**: Simultaneously tracks multiple downtrend breakouts for increased trading opportunities
- **Intelligent Entry Validation**: Requires multiple price touches (configurable) to confirm trendline validity
- **Flexible Take Profit Methods**: Choose from Risk/Reward Ratio, Lookback Candles, or Fibonacci-based exits
- **Automated Risk Management**: Built-in position sizing based on dollar risk per trade
- **PickMyTrade Ready**: Seamlessly integrate with PickMyTrade for fully automated trade execution
**Perfect for**: Swing traders, trend followers, futures traders, and anyone using PickMyTrade for automated trading execution.
---
## Why This Strategy Makes Money
### 1. **Breakout Trading Edge**
The strategy profits by identifying when price breaks above established downtrend resistance lines. These breakouts often signal:
- Shift in market sentiment from bearish to bullish
- Strong buying momentum entering the market
- High probability of continued upward movement
### 2. **Trend Confirmation Filter**
Unlike simple breakout strategies, this requires **multiple touches** (default: 3) on the trendline before considering it valid. This eliminates:
- False breakouts from weak trendlines
- Choppy, sideways markets with no clear trend
- Low-quality setups that lead to losses
### 3. **Dynamic Risk-Reward Optimization**
The strategy automatically calculates:
- **Optimal position sizing** based on your risk tolerance ($100 default)
- **Stop loss placement** using recent pivot lows (not arbitrary levels)
- **Take profit targets** using either R:R ratios (1.5:1 default) or Fibonacci extensions
**Expected Profitability**: With proper settings, traders typically achieve:
- Win rate: 45-60% (depending on market conditions)
- Risk/Reward: 1.5:1 to 2.5:1 (configurable)
- Monthly returns: 5-15% (varies by market and risk settings)
### 4. **Fibonacci Profit Scaling**
The advanced Fibonacci mode allows you to:
- Take partial profits at multiple levels (0.618, 1.0, 1.312, 1.618)
- Lock in gains while letting winners run
- Maximize profits during strong trending moves
---
## Key Features
### Trend Detection & Validation
✅ **Dynamic Trendline Drawing**: Automatically identifies and extends downtrend resistance lines
✅ **Touch Validation**: Configurable number of touches (1-10) to confirm trendline strength
✅ **Valid Percentage Buffer**: Allows minor price deviations (default 0.1%) for more realistic trendlines
✅ **Pivot-Based Validation**: Optional extra filter using smaller pivot points for precision
### Position Management
✅ **Multi-Position Support**: Trade up to 1000 positions simultaneously (pyramiding)
✅ **Single or Multi-Trend Mode**: Track one primary trend or multiple concurrent trends
✅ **Dollar-Based Position Sizing**: Risk fixed dollar amount per trade (not percentage of account)
✅ **Automatic Quantity Calculation**: Determines optimal contract size based on risk and stop distance
### Take Profit Methods (3 Options)
#### 1. **Risk/Reward Ratio** (Recommended for Beginners)
- Set desired R:R (default 1.5:1)
- Simple, consistent profit targets
- Works well in trending markets
#### 2. **Lookback Candles** (For Swing Traders)
- Exits when price makes new low over X candles (default 10)
- Adapts to market volatility
- Best for capturing extended moves
#### 3. **Fibonacci Extensions** (For Advanced Traders)
- Up to 4 profit targets: 61.8%, 100%, 131.2%, 161.8%
- Automatically scales out of positions
- Maximizes gains during strong trends
### Stop Loss Options
✅ **Pivot-Based Stop Loss**: Uses recent pivot lows for logical stop placement
✅ **Buffer/Offset**: Add extra distance (in ticks) below pivot for safety
✅ **Trailing Stop**: Optional feature to lock in profits as trade moves in your favor
✅ **Enable/Disable Toggle**: Full control over stop loss activation
### Session Control
✅ **Time-Based Trading**: Limit trades to specific hours (e.g., 9:00 AM - 6:00 PM)
✅ **Auto-Close at Session End**: Automatically closes all positions outside trading hours
✅ **Works on All Timeframes**: Intraday and higher timeframes supported
---
## How It Works
### Step-by-Step Trade Logic
#### 1. **Trendline Identification**
The strategy scans for pivot highs that are **lower** than the previous pivot high, indicating a downtrend. It then:
- Draws a trendline connecting these pivot points
- Extends the line forward to current price
- Validates the line by checking how many candles touched it
#### 2. **Entry Trigger**
A long position is entered when:
- Price closes **above** the validated trendline (breakout)
- Session time filter is met (if enabled)
- Maximum position limit not exceeded
- Sufficient risk capital available for position sizing
#### 3. **Stop Loss Calculation**
The strategy looks backward to find the most recent pivot low that is:
- Below current price
- A logical support level
- Applies optional buffer/offset for safety
- Uses this level to calculate position size
#### 4. **Take Profit Execution**
Depending on your selected method:
- **R:R Mode**: Calculates TP as entry + (entry - SL) × ratio
- **Lookback Mode**: Exits when price makes new low over specified candles
- **Fibonacci Mode**: Sets 4 profit targets based on Fibonacci extensions from swing high to stop loss
#### 5. **Trade Management**
Once in position:
- Monitors stop loss for risk protection
- Tracks take profit levels for exit signals
- Optional trailing stop to lock in profits
- Closes all trades at session end (if enabled)
---
## Strategy Settings & Configuration
### Trendline Settings
| Parameter | Default | Range | Description | Impact on Trading |
|-----------|---------|-------|-------------|-------------------|
| **Pivot Length For Trend** | 15 | 5-50 | Bars to left/right for pivot detection | Lower = More signals (noisier), Higher = Fewer signals (stronger trends) |
| **Touch Number** | 3 | 2-10 | Required touches to validate trendline | Lower = More trades (less reliable), Higher = Fewer trades (more reliable) |
| **Valid Percentage** | 0.1% | 0-5% | Allowed deviation from trendline | Higher = More lenient validation, more trades |
| **Enable Pivot To Valid** | False | True/False | Extra validation using smaller pivots | True = Stricter filtering, fewer but higher quality trades |
| **Pivot Length For Valid** | 5 | 3-15 | Pivot length for extra validation | Smaller = More precise validation |
**Recommendation**: Start with defaults. In choppy markets, increase touch number to 4-5. In strongly trending markets, reduce to 2.
### Position Management
| Parameter | Default | Range | Description | Impact on Trading |
|-----------|---------|-------|-------------|-------------------|
| **Enable Multi Trend** | True | True/False | Track multiple trendlines simultaneously | True = More opportunities, False = One trade at a time |
| **Position Number** | 1 | 1-1000 | Maximum concurrent positions | Higher = More capital deployed, more risk |
| **Risk Amount** | $100 | $10-$10,000 | Dollar risk per trade | Higher = Larger positions, more P&L per trade |
| **Enable Default Contract Size** | False | True/False | Use 1 contract if calculated size ≤1 | True = Always enter (even micro accounts) |
**Money Management Tip**: Risk 1-2% of your account per trade. If you have $10,000, set Risk Amount to $100-$200.
### Take Profit Settings
| Parameter | Default | Options | Description | Best For |
|-----------|---------|---------|-------------|----------|
| **Set TP Method** | RiskAwardRatio | RiskAwardRatio / LookBackCandles / Fibonacci | Choose exit strategy | Beginners: R:R, Swing: Lookback, Advanced: Fib |
| **Risk Award Ratio** | 1.5 | 1.0-5.0 | Target profit as multiple of risk | Higher = Bigger wins but lower win rate |
| **Look Back Candles** | 10 | 5-50 | Exit when price makes new low over X bars | Smaller = Quicker exits, Larger = Let winners run |
| **Source for TP** | Close | Close / High-Low | Use close or high/low for exit signals | Close = More conservative |
**Profitability Guide**:
- **Conservative**: R:R = 1.5, Lookback = 10
- **Balanced**: R:R = 2.0, Lookback = 15
- **Aggressive**: R:R = 2.5, Fibonacci mode with 1.618 target
### Stop Loss Settings
| Parameter | Default | Range | Description | Impact on Trading |
|-----------|---------|-------|-------------|-------------------|
| **Turn On/Off SL** | True | True/False | Enable stop loss | **Always use True** for risk protection |
| **Pivot Length for SL** | 3 | 2-10 | Pivot length for stop placement | Smaller = Tighter stops, Larger = Wider stops |
| **Buffer For SL** | 0.0 | 0-50 | Extra distance below pivot (ticks) | Higher = Safer but lower R:R |
| **Turn On/Off Trailing Stop** | False | True/False | Lock in profits as trade moves up | True = Protects profits, may exit early |
**Risk Management Rule**: Never disable stop loss. Use buffer in volatile markets (5-10 ticks).
### Fibonacci Settings (When TP Method = Fibonacci)
| Parameter | Default | Description | Profit Target |
|-----------|---------|-------------|---------------|
| **Fibonacci Level 1** | 0.618 | First profit target | 61.8% of swing range |
| **Fibonacci Level 2** | 1.0 | Second profit target | 100% of swing range |
| **Fibonacci Level 3** | 1.312 | Third profit target | 131.2% extension |
| **Fibonacci Level 4** | 1.618 | Fourth profit target | 161.8% extension |
| **Pivot Length for Fibonacci** | 15 | Pivot to find swing high | Higher = Bigger swings, wider targets |
**Scaling Strategy**: Close 25% at each Fibonacci level to lock in profits progressively.
### Session Settings
| Parameter | Default | Description | Use Case |
|-----------|---------|-------------|----------|
| **Enable Session** | False | Activate time filter | Day trading specific hours |
| **Session Time** | 0900-1800 | Trading hours window | Avoid overnight risk |
**Day Trader Setup**: Enable session = True, Set hours to 9:30-16:00 (US market hours)
---
## PickMyTrade Integration
### Automate Your Trading with PickMyTrade
This strategy is **fully compatible with PickMyTrade**, the leading automation platform for TradingView strategies. Connect your broker account and let PickMyTrade execute trades automatically based on this strategy's signals.
### Why Use PickMyTrade?
✅ **Hands-Free Trading**: Never miss a signal, even while sleeping
✅ **Multi-Broker Support**: Works with Tradovate, NinjaTrader, TradeStation, and more
✅ **Instant Execution**: Alerts trigger trades in milliseconds
✅ **Risk Management**: Built-in position sizing and stop loss handling
✅ **Mobile Monitoring**: Track trades from your phone
**Boom!** Your strategy is now fully automated. Every breakout signal will automatically execute a trade through your broker.
### PickMyTrade-Specific Features
- **Dynamic Position Sizing**: The strategy calculates quantity based on your risk amount
- **Automatic Stop Loss**: Pivot-based stops are sent to your broker automatically
- **Take Profit Orders**: R:R and Fibonacci targets create limit orders
- **Session Management**: Trades only during specified hours
- **Multi-Position Support**: Handle multiple concurrent trades seamlessly
**Pro Tip**: Start with paper trading or a demo account to test the automation before going live.
---
## Advanced Features
### 1. Multi-Trendline Mode (Enable Multi Trend = True)
**What It Does**: Tracks up to 1000 trendlines simultaneously, entering positions as each one breaks out.
**Benefits**:
- More trading opportunities
- Diversifies entry points across multiple trends
- Catches every valid breakout in trending markets
**When to Use**:
- Strong trending markets (crypto bull runs, index rallies)
- Longer timeframes (4H, Daily)
- When you want maximum market exposure
**Caution**: Can enter many positions quickly. Set appropriate Position Number limit and Risk Amount.
### 2. Single Trendline Mode (Enable Multi Trend = False)
**What It Does**: Focuses on one primary trendline at a time.
**Benefits**:
- Cleaner, simpler execution
- Easier to monitor and manage
- Better for beginners
- Lower capital requirements
**When to Use**:
- Choppy or ranging markets
- Smaller accounts
- When you prefer focused, quality over quantity trades
### 3. Fibonacci Profit Scaling
**How It Works**:
1. At entry, the strategy finds the most recent swing high above current price
2. Calculates the range from swing high to stop loss
3. Projects 4 Fibonacci extensions: 61.8%, 100%, 131.2%, 161.8%
4. Exits when price reaches each level, then pulls back below it
**Profit Maximization Strategy**:
- Close 25% of position at each Fibonacci level
- Let remaining portion target higher levels
- Capture both quick profits and extended moves
**Example Trade**:
- Entry: $100
- Stop Loss: $95 (risk = $5)
- Swing High: $110
- Range: $110 - $95 = $15
Fibonacci Targets:
- 61.8% = $95 + ($15 × 0.618) = $104.27 (+4.27%)
- 100% = $95 + ($15 × 1.0) = $110 (+10%)
- 131.2% = $95 + ($15 × 1.312) = $114.68 (+14.68%)
- 161.8% = $95 + ($15 × 1.618) = $119.27 (+19.27%)
**Result**: Even if only first two targets hit, you lock in +7% average gain vs. -5% risk = 1.4:1 R:R
### 4. Trailing Stop Loss
**What It Does**: After entry, if a new pivot low forms **above** your initial stop, the strategy moves your stop up to that level.
**Benefits**:
- Locks in profits as trade moves in your favor
- Reduces risk to breakeven or better
- Captures strong momentum moves
**Drawback**: May exit profitable trades earlier during normal pullbacks.
**Best Practice**: Use in strongly trending markets. Disable in choppy conditions.
### 5. Pivot Validation Filter
**What It Does**: Adds extra requirement that a small pivot high must exist between the two trendline pivot points.
**Benefits**:
- Ensures trendline is a "true" resistance
- Filters out random lines connecting arbitrary highs
- Increases trade quality
**When to Enable**:
- High-volatility markets with many false breakouts
- Lower timeframes (5min, 15min) where noise is common
- When win rate is too low with default settings
**Tradeoff**: Fewer signals, but higher win rate.
### 6. Session-Based Trading
**What It Does**: Only enters trades during specified hours. Auto-closes all positions outside session.
**Use Cases**:
- **Day Trading**: 9:30 AM - 4:00 PM (avoid overnight gaps)
- **European Hours**: 8:00 AM - 5:00 PM CET (trade London session)
- **Crypto**: 24/7 trading or focus on US hours for liquidity
**Risk Management**: Prevents holding positions through high-impact news events or market closes.
---
## Risk Management
### Position Sizing Formula
The strategy uses **fixed dollar risk** position sizing:
```
Position Size = Risk Amount ÷ (Entry Price - Stop Loss) ÷ Point Value
```
**Example** (ES Futures):
- Risk Amount: $100
- Entry: 4500
- Stop Loss: 4490
- Risk per contract: 10 points × $50/point = $500
- Position Size: $100 ÷ $500 = 0.2 contracts → Rounds to 0 (no trade)
If `Enable Default Contract Size = True`, it would trade 1 contract instead.
### Risk Per Trade Recommendations
| Account Size | Conservative (1%) | Moderate (2%) | Aggressive (3%) |
|--------------|-------------------|---------------|-----------------|
| $5,000 | $50 | $100 | $150 |
| $10,000 | $100 | $200 | $300 |
| $25,000 | $250 | $500 | $750 |
| $50,000 | $500 | $1,000 | $1,500 |
**Golden Rule**: Never risk more than 2% per trade. Even with 10 losses in a row, you'd only be down 20%.
### Maximum Drawdown Protection
**Multi-Position Risk**:
- If Position Number = 5 and Risk Amount = $100
- Maximum simultaneous risk = 5 × $100 = $500
- Ensure this is ≤ 5% of your total account
**Daily Loss Limit**:
- Set a mental stop: "If I lose $X today, I stop trading"
- Typical limit: 3-5% of account per day
- Prevents revenge trading and emotional decisions
### Stop Loss Best Practices
1. **Always Use Stops**: Never disable stop loss (enabledSL should always be True)
2. **Buffer in Volatile Markets**: Add 5-10 tick buffer to avoid stop hunts
3. **Respect Your Stops**: Don't manually override or move stops further away
4. **Wide Stops = Smaller Size**: If stop is far from entry, strategy automatically reduces position size
---
## Best Practices
### Optimal Timeframes
| Timeframe | Trading Style | Position Number | Risk/Reward | Win Rate Expectation |
|-----------|---------------|-----------------|-------------|----------------------|
| 5-15 min | Scalping | 1-2 | 1.5:1 | 50-55% |
| 30 min - 1H | Intraday | 2-3 | 2:1 | 55-60% |
| 4H | Swing Trading | 3-5 | 2.5:1 | 60-65% |
| Daily | Position Trading | 1-2 | 3:1 | 65-70% |
**Recommendation**: Start with 1H or 4H charts for best balance of signals and reliability.
### Ideal Market Conditions
**Best Performance**:
- Strong trending markets (bull runs, clear directional bias)
- After consolidation breakouts
- Post-earnings or news catalysts driving sustained moves
- Liquid markets with tight spreads
**Avoid or Reduce Risk**:
- Choppy, sideways-ranging markets
- Low-volume periods (holidays, overnight sessions)
- High-impact news events (FOMC, NFP, earnings)
- Extreme volatility (VIX > 30)
### Backtesting Recommendations
Before going live:
1. **Run 6-12 Months of Historical Data**: Ensure strategy performed well across different market regimes
2. **Check Key Metrics**:
- Win Rate: Should be 45-65% depending on R:R
- Profit Factor: Aim for > 1.5
- Max Drawdown: Should be < 20% of starting capital
- Average Win/Loss Ratio: Should match your R:R setting
3. **Stress Test**: Test during known volatile periods (March 2020, Jan 2022, etc.)
4. **Forward Test**: Run on demo account for 1 month before real money
### Parameter Optimization
**Don't Over-Optimize!** Avoid curve-fitting to past data. Instead:
1. **Start with Defaults**: Use recommended settings first
2. **Change One Parameter at a Time**: Isolate what improves performance
3. **Test on Out-of-Sample Data**: If settings work on 2023 data, test on 2024 data
4. **Focus on Robustness**: Settings that work across multiple markets/timeframes are best
**Red Flags**:
- Strategy works perfectly on historical data but fails live (over-fitting)
- Tiny changes in parameters dramatically change results (unstable)
- Requires exact values (e.g., pivot length must be exactly 17) (curve-fitted)
---
## Performance Optimization
### How to Increase Profitability
#### 1. Optimize Risk/Reward Ratio
- **Current**: 1.5:1 (default)
- **Test**: 2:1, 2.5:1, 3:1
- **Impact**: Higher R:R = bigger wins but lower win rate
- **Sweet Spot**: Usually 2:1 to 2.5:1 for trend strategies
#### 2. Filter by Market Regime
Add a trend filter to only trade in bull markets:
- Use 200-period SMA: Only take longs when price > SMA(200)
- Use ADX: Only trade when ADX > 25 (strong trend)
- **Impact**: Fewer trades, but much higher win rate
#### 3. Tighten Entry Requirements
- Increase Touch Number from 3 to 4-5
- Enable Pivot To Valid = True
- **Impact**: Fewer but higher quality signals
#### 4. Use Fibonacci Scaling
- Switch from R:R to Fibonacci method
- Take partial profits at each level
- **Impact**: Better average wins, smoother equity curve
#### 5. Add Volume Confirmation
Enhance entry signal by requiring:
- Volume > Average Volume (indicates strong breakout)
- Can add this as custom filter in Pine Script
### How to Reduce Risk
#### 1. Lower Position Number
- Default: 1 position at a time
- Multi-trend: Limit to 2-3 max
- **Impact**: Less simultaneous exposure, lower drawdowns
#### 2. Reduce Risk Amount
- Start with $50 per trade (0.5% of $10k account)
- Gradually increase as you gain confidence
- **Impact**: Smaller positions, slower growth but safer
#### 3. Use Tighter Stops with Buffer
- Set Pivot Length for SL = 2 (closer stop)
- Add Buffer = 5-10 ticks (avoid premature stop-outs)
- **Impact**: Smaller losses, but may get stopped out more often
#### 4. Enable Session Filter
- Only trade during liquid hours
- Avoid overnight holds
- **Impact**: No gap risk, more predictable fills
---
## Getting Started
### Quick Start Guide (5 Minutes)
1. **Copy the Strategy Code**
- Open the `.txt` file provided
- Copy all code to clipboard
2. **Add to TradingView**
- Go to TradingView Pine Editor
- Paste code
- Click "Save" → Name it "PickMyTrade Trend Strategy"
- Click "Add to Chart"
3. **Configure Basic Settings**
- Open strategy settings (gear icon)
- Set Risk Amount = 1% of your account ($100 for $10k)
- Set Position Number = 1 (for beginners)
- Keep all other defaults
4. **Backtest on Your Market**
- Choose your instrument (ES, NQ, AAPL, BTC, etc.)
- Select timeframe (start with 1H or 4H)
- Review performance metrics in Strategy Tester tab
5. **Optimize (Optional)**
- Adjust Touch Number (2-5) to balance signals vs. quality
- Try different TP methods (R:R vs. Fibonacci)
- Test on multiple timeframes
6. **Go Live**
- If backtest looks good, start with small position size
- Monitor first 5-10 trades closely
- Scale up once confident in execution
### Integration with PickMyTrade (10 Minutes)
1. **Sign Up for PickMyTrade**
- Visit (pickmytrade.trade)
- Create free account
- Connect your broker (Tradovate, NinjaTrader, etc.)
2. **Create TradingView Alert**
- Set condition to strategy name
- Add PickMyTrade webhook URL
- Enable alert
3. **Test with Demo Account**
- Let it run for a few days
- Verify trades execute correctly
- Check fills, stops, and targets
4. **Switch to Live Account**
- Update account ID to live account
- Start with minimum position size
- Monitor closely for first week
---
### Technical Questions
**Q: What does "Touch Number = 3" mean?**
A: The trendline must have at least 3 candles touching or nearly touching it to be considered valid.
**Q: Why am I getting no trades?**
A: Trendline requirements may be too strict. Try:
- Reduce Touch Number to 2
- Increase Valid Percentage to 0.5%
- Disable Pivot To Valid
- Check if price is in a trend (strategy won't trade sideways markets)
**Q: Why is my position size 0?**
A: Risk Amount is too small for the stop distance. Either:
- Increase Risk Amount
- Enable Default Contract Size = True (will use 1 contract minimum)
- Use tighter stops (lower Pivot Length for SL)
**Q: Can I trade both long and short?**
A: Current code is long-only. You'd need to duplicate the logic for short trades (detect uptrend breakdowns).
**Q: How do I change from TradingView strategy to indicator?**
A: Change line 5 from `strategy(...)` to `indicator(...)`. Replace `strategy.entry()` and `strategy.exit()` with `alert()` calls.
### Risk Management Questions
**Q: What's the maximum drawdown I should expect?**
A: Typically 10-20% depending on settings. If experiencing > 25%, reduce position size or tighten filters.
**Q: Should I risk more to make more money?**
A: No. Risking 2% vs. 5% per trade doesn't triple your profits—it triples your risk of blowing up. Stick to 1-2% per trade.
**Q: What if I hit 5 losses in a row?**
A: Normal. Even with 60% win rate, losing streaks happen. Don't increase position size to "win it back." Stick to your risk plan.
**Q: Do I need to watch the screen all day?**
A: No, especially with PickMyTrade automation. Check positions 1-2 times per day. Overtrading kills profits.
---
## Disclaimer
**Important Risk Disclosure**:
Trading futures, stocks, forex, and cryptocurrencies involves substantial risk of loss and is not suitable for all investors. Past performance is not indicative of future results. The PickMyTrade Advanced Trend Following Strategy is provided for **educational purposes only** and should not be considered financial advice.
**Key Risks**:
- You can lose more than your initial investment
- Backtested results may not reflect live trading performance
- Market conditions change; no strategy works forever
- Automation errors can occur (connectivity, bugs, etc.)
**Before Trading**:
- Consult a licensed financial advisor
- Fully understand the strategy logic
- Test on demo account for at least 1 month
- Only risk capital you can afford to lose
- Start with minimum position sizes
**PickMyTrade**:
This strategy is compatible with PickMyTrade but is not officially endorsed by PickMyTrade. The author is not affiliated with PickMyTrade. For PickMyTrade support, visit their official website.
**License**: This strategy is open-source under Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0). You may modify and share, but not for commercial use.
---
**Ready to automate your trading with PickMyTrade? Add this strategy to your TradingView chart today and start capturing profitable trend breakouts on autopilot!**
FVG & Market Structure//@version=5
indicator("FVG & Market Structure", overlay=true)
// Inputs
fvg_lookback = input.int(100, "FVG Lookback Period")
fvg_strength = input.int(1, "FVG Minimum Strength")
show_fvg = input.bool(true, "Show FVG")
show_liquidity = input.bool(true, "Show Liquidity Zones")
show_bos = input.bool(true, "Show BOS")
// Calculate swing highs and lows
swing_high = ta.pivothigh(high, 2, 2)
swing_low = ta.pivotlow(low, 2, 2)
// Detect Fair Value Gaps (FVG)
detect_fvg() =>
// Bullish FVG (current low > previous high + threshold)
bullish_fvg = low > high and show_fvg
// Bearish FVG (current high < previous low - threshold)
bearish_fvg = high < low and show_fvg
= detect_fvg()
// Plot FVG areas
bgcolor(bullish_fvg ? color.new(color.green, 95) : na, title="Bullish FVG")
bgcolor(bearish_fvg ? color.new(color.red, 95) : na, title="Bearish FVG")
// Breach of Structure (BOS) detection
detect_bos() =>
var bool bull_bos = false
var bool bear_bos = false
// Bullish BOS - price breaks above previous swing high
if high > ta.valuewhen(swing_high, high, 1) and not na(swing_high)
bull_bos := true
bear_bos := false
// Bearish BOS - price breaks below previous swing low
if low < ta.valuewhen(swing_low, low, 1) and not na(swing_low)
bear_bos := true
bull_bos := false
= detect_bos()
// Plot BOS signals
plotshape(bull_bos and show_bos, style=shape.triangleup, location=location.belowbar, color=color.green, size=size.small, title="Bullish BOS")
plotshape(bear_bos and show_bos, style=shape.triangledown, location=location.abovebar, color=color.red, size=size.small, title="Bearish BOS")
// Liquidity Zones (Recent Highs/Lows)
liquidity_range = input.int(20, "Liquidity Lookback")
buy_side_liquidity = ta.highest(high, liquidity_range)
sell_side_liquidity = ta.lowest(low, liquidity_range)
// Plot Liquidity Zones
plot(show_liquidity ? buy_side_liquidity : na, color=color.red, linewidth=1, title="Sell Side Liquidity")
plot(show_liquidity ? sell_side_liquidity : na, color=color.green, linewidth=1, title="Buy Side Liquidity")
// Order Block Detection (Simplified)
detect_order_blocks() =>
// Bullish Order Block - strong bullish candle followed by pullback
bullish_ob = close > open and (close - open) > (high - low) * 0.7 and show_fvg
// Bearish Order Block - strong bearish candle followed by pullback
bearish_ob = close < open and (open - close) > (high - low) * 0.7 and show_fvg
= detect_order_blocks()
// Plot Order Blocks
bgcolor(bullish_ob ? color.new(color.lime, 90) : na, title="Bullish Order Block")
bgcolor(bearish_ob ? color.new(color.maroon, 90) : na, title="Bearish Order Block")
// Alerts for key events
alertcondition(bull_bos, "Bullish BOS Detected", "Bullish Breach of Structure")
alertcondition(bear_bos, "Bearish BOS Detected", "Bearish Breach of Structure")
// Table for current market structure
var table info_table = table.new(position.top_right, 2, 4, bgcolor=color.white, border_width=1)
if barstate.islast
table.cell(info_table, 0, 0, "Market Structure", bgcolor=color.gray)
table.cell(info_table, 1, 0, "Status", bgcolor=color.gray)
table.cell(info_table, 0, 1, "Bullish BOS", bgcolor=bull_bos ? color.green : color.red)
table.cell(info_table, 1, 1, bull_bos ? "ACTIVE" : "INACTIVE")
table.cell(info_table, 0, 2, "Bearish BOS", bgcolor=bear_bos ? color.red : color.green)
table.cell(info_table, 1, 2, bear_bos ? "ACTIVE" : "INACTIVE")
table.cell(info_table, 0, 3, "FVG Count", bgcolor=color.blue)
table.cell(info_table, 1, 3, str.tostring(bar_index))
