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Breakout Targets [AlgoAlpha]๐ OVERVIEW
This script identifies consolidation zones and provides automated breakout targets with risk management levels. It focuses on finding periods where price action compresses and then tracks the subsequent breakout from these ranges. When a price breakout is confirmed, the script automatically projects three take-profit (TP) levels and a stop-loss (SL) based on current market volatility. This helps traders move from identifying a range to executing a trade with predefined exit points without manual calculation.
๐ CONCEPTS
The script uses a relationship between Weighted Moving Averages (WMA) and Exponential Moving Averages (EMA) of price ranges to detect consolidation. When these moving averages cross, it triggers the detection of recent pivot highs and lows to draw a visual "box" or channel. This channel represents the current trading range. Once price closes outside this box, the script uses the Average True Range (ATR) to determine the volatility-adjusted distance for the stop loss. The take-profit levels are then calculated as multiples of this risk distance, ensuring a consistent reward-to-risk approach.
๐ FEATURES
Dynamic box drawing that highlights potential supply and demand zones within the range.
Real-time breakout signals with bullish (green) and bearish (red) markers.
Automated trade projection including Entry, SL, and three TP levels.
Integrated alert system for breakouts and hits on any profit or loss target.
๐ USAGE
Setup : Add the script to your chart and adjust the "Range Detection Period." A higher period will find larger, more significant ranges, while a lower period will find smaller, short-term consolidation zones.
Read the chart : Look for the grey boxes on your chart; these represent areas where the market is "coiling." A green arrow label indicates a bullish breakout from the top of the box, while a red arrow indicates a bearish breakout from the bottom. Once a breakout occurs, follow the projected horizontal levels for your trade management.
Settings that matter : The Stop Loss ATR Multiplier is the most critical setting for risk; increasing it will give the trade more room to breathe but will also push your TP levels further away. The Prevent Overlap toggle is useful for keeping the chart clean by ensuring the script doesn't draw new boxes until the current range has been resolved.
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MAD Supertrend [Alpha Extract]A sophisticated SuperTrend implementation that replaces traditional ATR calculations with Mean Absolute Deviation methodology for adaptive volatility measurement and band construction. Utilizing SMA baseline with MAD-based deviation bands and optional adaptive factor adjustments, this indicator delivers institutional-grade trend detection with strength-based filtering and dynamic visual feedback. The system's MAD approach provides superior noise reduction compared to ATR while maintaining responsiveness to genuine volatility changes, combined with momentum-based strength calculations for high-conviction signal generation.
๐ถ Advanced MAD-Based Band Construction
Implements Mean Absolute Deviation calculation as volatility proxy, measuring absolute price deviations from mean and smoothing for stable band generation without ATR dependency. The system calculates SMA baseline, computes MAD from configurable lookback period, applies factor multipliers to create upper and lower bands, then implements classic SuperTrend ratcheting logic where bands only adjust when price violates previous levels or calculations warrant updates.
// Core MAD SuperTrend Framework
SMA_Value = ta.sma(src, SMA_Length)
Mean = ta.sma(src, MAD_Length)
Abs_Deviation = abs(src - Mean)
MAD_Value = ta.sma(Abs_Deviation, MAD_Length)
// Band Construction with Ratcheting
Upper_Band = SMA_Value + MAD_Factor * MAD_Value
Lower_Band = SMA_Value - MAD_Factor * MAD_Value
// Ratcheting logic prevents premature band adjustments
๐ถ Adaptive Factor Adjustment Engine
Features optional adaptive multiplier system that modulates MAD factor based on normalized MAD magnitude relative to recent extremes, creating bands that automatically expand during high-volatility regimes and contract during consolidation. The system applies min-max normalization to MAD values over configurable lookback, multiplies by adaptation parameter, and adds to base factor for dynamic volatility sensitivity without manual recalibration.
๐ถ Momentum-Based Strength Filter
Implements sophisticated strength calculation measuring price momentum relative to baseline divided by volatility-adjusted MAD bands, producing normalized 0-1 strength scores with exponential smoothing. The system calculates distance from SMA baseline, normalizes by MAD-derived band width, and applies configurable minimum threshold requiring sufficient momentum before trend signals activate, filtering weak or choppy market conditions.
๐ถ SuperTrend Direction Logic
Utilizes classic SuperTrend methodology adapted for MAD bands where trend direction flips on opposite band violations with state persistence until confirmation. The system tracks whether price closes above upper band (bearish flip to bullish) or below lower band (bullish flip to bearish), maintains directional state until opposing violation occurs, and generates binary +1/-1 trend signals suitable for systematic position management.
๐ถ Intelligent Candle Sticking System
Provides advanced line positioning option that anchors SuperTrend line to candle wicks or bodies rather than pure calculation values for enhanced visual clarity. The system supports two modes: Wick (positions at high/low extremes based on trend direction) and Body (constrains line between calculation and candle extremes), creating cleaner chart presentation while maintaining mathematical integrity of underlying signals.
๐ถ Dynamic Gradient Visualization Framework
Implements color intensity modulation based on smoothed strength calculations, transitioning from muted to vivid hues as momentum conviction increases. The system applies gradient interpolation using strength ratio, creating visual feedback where strong trending moves display intense colors while weak or consolidating conditions show faded tones across trend line, channel bands, and candle coloring for immediate regime assessment.
๐ถ MAD Channel Architecture
Features volatility-adjusted channel bands centered on baseline or candle-stuck line with configurable multiplier for support/resistance visualization. The system calculates upper and lower bounds using MAD values scaled by adaptive factors and channel multipliers, applies dynamic transparency based on trend strength, and creates filled regions that intensify during strong trends and fade during weak conditions.
๐ถ Multi-Layer Glow Effect System
Provides sophisticated line rendering with triple-layer plot system creating glow effect through progressively wider and more transparent outer layers. The system plots core trend line at specified width with full color intensity, adds inner glow layer at +2 width with moderate transparency, and outer glow at +4 width with higher transparency, creating visual depth and emphasis without cluttering chart space.
๐ถ Strength-Based State Management
Implements intelligent trend state logic requiring both directional signal and minimum strength threshold breach before confirming trend transitions. The system calculates raw SuperTrend direction, evaluates smoothed strength against configurable minimum, generates filtered trend state that can be bullish (+1), bearish (-1), or neutral (0), and maintains state persistence using hold logic that prevents oscillation during ambiguous conditions.
๐ถ Comprehensive Alert Integration
Generates trend flip alerts when filtered state transitions from bearish to bullish or bullish to bearish with full confirmation requirements satisfied. The system detects state changes through comparison with previous bar, triggers single alert per transition rather than continuous notifications, and provides customizable message templates for automated trading system integration or manual notification preferences.
๐ถ Performance Optimization Architecture
Utilizes efficient calculation methods with null value handling, nz() functions preventing errors during initialization bars, and optimized gradient calculations. The system includes intelligent state persistence minimizing recalculation overhead, streamlined MAD computation avoiding redundant mean calculations, and smooth visual updates maintaining consistent performance across extended historical periods.
This indicator delivers sophisticated SuperTrend analysis through Mean Absolute Deviation methodology providing superior statistical properties compared to traditional ATR-based approaches. MAD calculations offer more robust volatility measurement resistant to extreme outliers while maintaining sensitivity to genuine market regime changes. The system's adaptive factor adjustment, momentum-based strength filtering, and dynamic visual feedback make it essential for traders seeking reliable trend-following signals with reduced false breakouts during choppy conditions. The combination of MAD bands, candle-sticking options, gradient strength visualization, and comprehensive filtering creates institutional-grade trend detection suitable for systematic approaches across cryptocurrency, forex, and equity markets with clear entry/exit signals and comprehensive alert capabilities. Indikator

Support & Resistance Automated๐ Support and Resistance Automated (Pivot-Based)
Support and Resistance Automated is a lightweight and fully automated indicator that plots key support and resistance levels using pivot highs and pivot lows. It helps traders quickly identify important price reaction zones without manual drawing.
This indicator is especially useful for price-action traders, swing traders, and intraday traders who rely on clean charts and objective levels.
๐ How It Works
Pivot Highs โ Resistance Levels
Pivot Lows โ Support Levels
Each detected pivot creates a horizontal dotted line that extends forward, allowing you to observe how price reacts over time.
Once a level is formed, it is kept permanently on the chart โ no repainting, no disappearing levels.
โ๏ธ Customizable Settings
You can easily adjust:
Left & Right Pivot Bars โ control how strong a pivot must be
Line Extension Length
Line Width
Support & Resistance Colors
Show / Hide Pivot Highs and Pivot Lows independently
This flexibility allows the indicator to adapt to intraday, swing, or higher-timeframe analysis.
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Key Features
โ Fully automatic support & resistance detection
โ Based on proven pivot-point logic
โ No repainting
โ Clean, minimal chart appearance
โ Unlimited support & resistance levels
โ Works on all timeframes & instruments
๐ Best Use Cases
Identifying key demand and supply zones
Planning entries, targets, and stop-losses
Confluence with price action, RSI, moving averages
Breakout and rejection-based strategies Indikator

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Volume-Adjusted CCI Trend [Alpha Extract]A sophisticated trend identification system that combines dual EMA direction analysis with volume-weighted normalization and CCI momentum filtering for comprehensive trend validation. Utilizing Volume RSI integration and standard deviation-based bands that expand and contract with volume characteristics, this indicator delivers institutional-grade trend detection with multi-layered confirmation requirements. The system's volume adjustment mechanism modulates signal sensitivity based on participation strength while CCI thresholds prevent false signals during weak momentum conditions, creating a robust trend-following framework with reduced whipsaw susceptibility.
๐ถ Advanced Dual EMA Direction Engine
Implements fast and slow exponential moving average comparison to establish primary trend direction bias with configurable period parameters for timeframe optimization. The system calculates trend direction as binary +1 (bullish when fast EMA exceeds slow EMA) or -1 (bearish when slow exceeds fast), providing foundational directional input that requires additional confirmation before generating actionable trend states.
๐ถ Volume-Adjusted Normalization Framework
Features sophisticated normalization calculation that measures price deviation from basis EMA, scales by standard deviation, then applies volume-weighted adjustment factor for participation-sensitive signal generation. The system calculates Volume RSI to quantify relative volume strength, converts to ratio format, and multiplies normalized deviation by volume factor scaled by impact parameter, creating signals that strengthen during high-volume confirmations and weaken during low-volume moves.
// Volume-Adjusted Normalization
Vol_Ratio = Volume_RSI / 50
Vol_Factor = 1 + (Vol_Ratio - 1) * Vol_Impact
Dev = src - Basis_EMA
Raw_Normalized = Dev / (StdDev * Multiplier)
Vol_Adjusted_Norm = Raw_Normalized * Vol_Factor
๐ถ CCI Momentum Filter Integration
Implements Commodity Channel Index threshold system with configurable upper and lower bounds to validate trend strength and filter sideways market conditions. The system calculates standard CCI with adjustable length, compares against asymmetric thresholds (default +100 bullish, -50 bearish), and requires CCI confirmation in addition to EMA direction and normalized deviation before transitioning trend states, ensuring only high-conviction signals generate entries.
๐ถ Multi-Layer Trend State Logic
Provides intelligent trend state machine requiring simultaneous confirmation from EMA direction, volume-adjusted normalization threshold breach, and optional CCI momentum validation. The system maintains persistent trend state that only transitions when all three conditions align, preventing premature reversals during temporary retracements or low-volume fluctuations while capturing genuine trend changes with institutional-grade confirmation requirements.
๐ถ Dynamic Volume Band Architecture
Creates volatility-adjusted bands around basis EMA using standard deviation multiplied by volume factor, producing channels that widen during high-volume periods and contract during low-volume consolidations. The system applies identical volume adjustment to band calculations as normalization metric, ensuring visual envelope consistency with underlying signal logic and providing intuitive reference boundaries for trend-following price action.
๐ถ Gradient Strength Visualization System
Implements color intensity modulation based on normalized signal strength relative to threshold requirements, creating visual feedback that communicates trend conviction. The system calculates strength ratio by dividing absolute normalized value by threshold, caps at 1.0, and applies gradient interpolation from muted to vivid colors, instantly conveying whether current trend exhibits marginal or strong characteristics through line and candle coloring.
๐ถ Volume RSI Calculation Engine
Utilizes RSI methodology applied to volume series rather than price to quantify relative participation strength with normalization to 0.5-1.5 range for factor multiplication. The system processes volume through standard RSI calculation, divides by 50 to center around 1.0, and produces ratio values where readings above 1.0 indicate above-average volume and below 1.0 suggest below-average participation for signal adjustment purposes.
๐ถ Asymmetric Threshold Configuration
Features separate positive and negative normalization thresholds with independent CCI upper and lower bounds enabling optimization for bullish versus bearish signal generation characteristics. The system defaults to symmetric normalized thresholds (ยฑ0.2) but asymmetric CCI levels (+100/-50), recognizing that bullish momentum often requires stronger confirmation than bearish reversals in typical market structures.
๐ถ Comprehensive Visual Integration
Provides multi-dimensional trend visualization through color-coded basis line, volume-adjusted bands with gradient fills, trend-synchronized candle coloring, and transition signal labels. The system enables selective display toggling for each visual component while maintaining consistent color scheme and strength-based intensity across all elements for cohesive chart presentation without overwhelming information density.
๐ถ Alert and Signal Framework
Generates trend change alerts when state transitions occur with all confirmation requirements satisfied, providing notifications for bullish (transition to +1) and bearish (transition to -1) signals. The system implements state change detection through comparison with previous bar trend state, ensuring single alert per transition rather than continuous notifications during sustained trends.
๐ถ Performance Optimization Architecture
Employs efficient calculation methods with null value handling for Volume RSI initialization and nz() functions preventing calculation errors during early bars. The system includes intelligent state persistence maintaining previous trend during ambiguous conditions and optimized gradient calculations balancing visual quality with computational efficiency across extended historical periods.
๐ถ Why Choose Volume-Adjusted CCI Trend ?
This indicator delivers sophisticated trend identification through multi-layered confirmation combining directional EMA analysis, volume-weighted normalization, and momentum validation via CCI filtering. Unlike traditional trend indicators relying solely on price-based calculations, the volume adjustment mechanism ensures signals strengthen during high-participation moves and weaken during low-volume drifts, reducing false breakouts and choppy market whipsaws. The system's requirement for simultaneous EMA direction, normalized threshold breach, and CCI momentum confirmation creates institutional-grade signal quality suitable for systematic trend-following approaches across cryptocurrency, forex, and equity markets. The volume-adjusted bands provide dynamic support/resistance references while the gradient strength visualization enables instant assessment of trend conviction for position sizing and risk management decisions. Indikator

Swing Failure Signals [AlgoAlpha]๐ OVERVIEW
This script detects swing failure patterns by tracking how price interacts with recent swing highs and lows, then confirming those sweeps with a change in candle behavior. The goal is to highlight areas where price briefly breaks a key level, fails to continue, and then shifts direction. These events often occur around liquidity runs, where stops are triggered before price reverses. The script draws levels, colors bars, and prints clear markers to help visualize where these failures occur and when they are confirmed.
๐ CONCEPTS
The logic starts with pivot-based swing detection. Recent swing highs and lows are stored and monitored. When price trades beyond one of these levels within a defined historical window, it is treated as a sweep. A sweep alone is not enough. The script then waits for a Change in State of Delivery (CISD), which is defined by a shift in candle structure that shows follow-through in the opposite direction. A tolerance filter measures how far price traveled beyond the level relative to the reaction that followed. If the reaction is strong enough and happens within a limited number of bars, the sweep is validated as a swing failure. In short: the swing defines the reference, the sweep shows intent, and the CISD confirms acceptance or rejection.
๐ FEATURES
Sweep detection with a maximum lookback to avoid outdated levels
CISD confirmation using candle structure and price expansion
Alert conditions for bullish and bearish swing failures
๐ USAGE
Setup : Add the script to your chart. It works on any market and timeframe. Lower timeframes highlight intraday liquidity runs, while higher timeframes show structural failures. Start with the default inputs before adjusting.
Read the chart : A bullish swing failure occurs when price sweeps a prior low, then reverses and confirms with a bullish CISD. A bearish swing failure is the opposite, sweeping a prior high and confirming with a bearish CISD. Dashed lines mark the swept swing. Solid lines mark the CISD level. Bars are colored while the SFP state is active.
Settings that matter : Increasing Pivot Detection Length finds more significant swings but fewer signals. Reducing Max Pivot Point Edge limits how far back sweeps are allowed, keeping signals more current. The Patience setting controls how many bars are allowed for confirmation after a sweep. The Trend Noise Filter raises or lowers how strong the reaction must be to qualify as a valid failure.
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Market Entropy [Alpha Extract]A sophisticated information theory-based market analysis system that measures price randomness and structural order using Shannon entropy calculations across price, returns, and volume distributions. Utilizing adaptive percentile-based thresholds and multi-timeframe confirmation, this indicator delivers institutional-grade regime classification distinguishing between structured trending conditions and chaotic ranging environments. The system's composite entropy framework combined with dynamic gradient visualization and MTF alignment validation provides comprehensive market state assessment for optimal strategy selection and risk management.
๐ถ Advanced Shannon Entropy Engine
Implements pure information theory methodology using histogram distribution analysis with configurable bin counts to calculate normalized entropy values for price, returns, and volume metrics. The system constructs probability distributions from rolling windows, applies logarithmic entropy calculations, and normalizes against theoretical maximum entropy to produce 0-1 bounded measurements of market randomness and predictability.
float entropy = 0.0
float total = float(len)
for i = 0 to bins - 1
float count = array.get(bin_counts, i)
if count > 0
float prob = count / total
entropy -= prob * math.log(prob) / math.log(2)
float max_entropy = math.log(bins) / math.log(2)
result := entropy / max_entropy
๐ถ Adaptive Percentile Threshold System
Features intelligent threshold determination using rolling percentile calculations over configurable calibration periods to establish structure and chaos zones that adapt to changing market characteristics. The system calculates lower percentile for structure threshold (ordered markets) and upper percentile for chaos threshold (random markets), enabling regime classification that adjusts automatically to market evolution.
๐ถ Multi-Timeframe Alignment Framework
Implements comprehensive MTF entropy analysis retrieving composite entropy from three configurable higher timeframes with alignment validation logic. The system calculates divergence between current timeframe entropy and higher timeframe values, generating confirmation signals only when all timeframes exhibit entropy agreement within tolerance bands for enhanced signal reliability.
๐ถ Three-Regime Classification Engine
Provides sophisticated market state determination classifying conditions as structure (entropy below lower threshold), chaos (entropy above upper threshold), or neutral (entropy between thresholds) with regime strength measurement. The system tracks regime transitions and calculates conviction scores based on distance from thresholds, enabling nuanced assessment of market order versus randomness.
๐ถ Composite Entropy Architecture
Combines three distinct entropy measurements weighted by relevance to create unified market randomness metric with exponential smoothing for stability. The system applies 40% weight to price entropy (distribution shape), 35% to return entropy (movement patterns), and 25% to volume entropy (participation randomness), capturing comprehensive market microstructure information.
๐ถ Dynamic Gradient Visualization System
Features advanced color blending engine that transitions between primary and secondary colors based on entropy momentum intensity with glow effects for conviction emphasis. The system calculates entropy rate of change, normalizes against recent extremes, and applies smooth color interpolation from secondary to primary hues as momentum intensifies, creating intuitive visual representation of regime strength.
๐ถ Intelligent Zone Fill Architecture
Implements multi-layer gradient fills within structure and chaos zones that intensify as entropy moves deeper into extremes, providing immediate visual feedback on regime conviction. The system creates three-tier gradient levels at 33%, 66%, and 100% penetration into zones with progressively lower transparency, emphasizing extreme entropy conditions requiring attention.
๐ถ Momentum-Based Divergence Detection
Generates entry signals when entropy crosses below bull divergence level or above bear divergence level, identifying potential regime transitions before price confirmation. The system monitors entropy momentum direction during threshold crossings and validates with MTF alignment, producing high-probability reversal signals at entropy extremes.
๐ถ Normalized Display Framework
Provides 0-100 scaled visualization using adaptive min-max normalization calculated from percentile analysis, ensuring consistent visual interpretation across different market conditions and instruments. The system transforms raw composite entropy into normalized space with dynamic thresholds, enabling cross-market and cross-timeframe entropy comparison.
๐ถ Regime Strength Measurement
Calculates conviction scores measuring depth of entropy penetration into structure or chaos zones relative to historical ranges, quantifying how definitively current conditions favor trending versus ranging strategies. The system produces 0-1 strength values that modulate visual intensity and can inform position sizing or strategy allocation decisions.
๐ถ Performance Optimization Framework
Utilizes efficient array operations with optimized histogram calculations and configurable lookback limits to balance accuracy with computational efficiency. The system includes intelligent caching of percentile calculations and streamlined probability summations for smooth real-time entropy updates across extended historical periods.
๐ถ Why Choose Market Entropy ?
This indicator delivers sophisticated market regime analysis through pure information theory methodology measuring actual randomness versus structure in price behavior. Unlike traditional volatility or trend indicators that measure price movement characteristics, Market Entropy quantifies the fundamental predictability of market conditions using Shannon entropy calculations. The system's composite approach combining price, return, and volume distributions with adaptive thresholds, MTF confirmation, and gradient visualization makes it essential for traders seeking objective regime classification to optimize strategy selection. Low entropy (structure zone) indicates ordered, trending conditions favorable for directional strategies, while high entropy (chaos zone) signals random, ranging markets better suited for mean reversion or reduced exposure. The indicator excels at identifying regime transitions before they become obvious in price action across cryptocurrency, forex, and equity markets. Indikator

SMA MAD Trend [Alpha Extract]A sophisticated trend identification system that combines Simple Moving Average with Mean Absolute Deviation methodology to create adaptive Super Trend-style bands with advanced strength filtering and gradient visualization. Utilizing ADX-based trend strength validation and slope analysis for signal quality enhancement, this indicator delivers institutional-grade trend detection with dynamic ATR-based ribbon visualization and comprehensive strength measurement. The system's dual-filter architecture eliminates false signals during weak or choppy market conditions while maintaining sensitivity to genuine trend establishment and reversal events.
๐ถ Advanced SMA-MAD Band Construction
Implements innovative Mean Absolute Deviation calculation around Simple Moving Average baseline to create volatility-adaptive bands with ratcheting logic for trend persistence. The system calculates MAD by measuring absolute price deviations from the mean, then applies configurable multipliers to generate upper and lower bands that adjust to changing market conditions while preventing premature band violations.
// Core SMA-MAD Framework
SMA_Value = ta.sma(close, SMA_Length)
Mean = ta.sma(close, MAD_Length)
Abs_Deviation = abs(close - Mean)
MAD_Value = ta.sma(Abs_Deviation, MAD_Length)
// Adaptive Bands
Upper_Band = SMA_Value + MAD_Factor * MAD_Value
Lower_Band = SMA_Value - MAD_Factor * MAD_Value
๐ถ Intelligent Dual-Filter System
Features comprehensive trend validation using ADX strength measurement and slope analysis to eliminate low-conviction signals during ranging or consolidating markets. The system calculates normalized slope strength using ATR scaling and combines with ADX threshold analysis, generating filtered trend states that distinguish genuine trends from temporary price fluctuations.
๐ถ Dynamic Trend Strength Engine
Implements sophisticated strength calculation combining slope intensity and ADX readings to produce normalized 0-100% strength scores with gradient colour intensity modulation. The system normalizes slope by minimum threshold and ADX by configurable level, multiplying factors to create composite strength measurement that drives visual feedback intensity across all indicator elements.
๐ถ Super Trend-Style Direction Logic
Utilizes classic Super Trend methodology adapted for SMA-MAD bands, where trend direction flips occur on opposite band violations with persistent state maintenance. The system tracks previous band levels with ratcheting behaviour that adjusts bands only when price movement or new calculations warrant changes, preventing oscillation during normal volatility.
๐ถ ATR-Based Ribbon Visualization
Provides dynamic ribbon overlay using ATR-scaled width around the trend line with opacity modulation based on trend strength for intuitive conviction assessment. The system creates upper and lower ribbon bounds at configurable ATR multiples, filling the channel with gradient-adjusted transparency that increases during strong trends and fades during weak conditions.
๐ถ Multi-Dimensional Visual Architecture
Provides complete chart integration through trend line overlay, ATR ribbon fills, candle colouring, background glow, and transition signal labels with configurable visibility toggles. The system enables traders to customize display density from minimal (trend line only) to comprehensive (all visual elements) while maintaining consistent colour scheme and strength-based intensity across components.
๐ถ Slope Strength Validation
Calculates ATR-normalized slope over configurable lookback periods to measure trend line momentum and filter sideways price action. The system compares absolute slope against minimum threshold requirements, preventing trend signals when price movement relative to the trend line lacks sufficient directional conviction regardless of band position.
๐ถ Signal Generation Framework
Generates trend change signals when filtered direction state transitions from bearish to bullish or vice versa, with label placement and alert integration. The system implements state persistence that maintains previous trend until both ADX and slope filters confirm directional change, reducing whipsaw signals while capturing genuine reversals with minimal lag.
๐ถ Performance Optimization Framework
Utilizes efficient calculation methods with optimized variable management and configurable parameters for balance between responsiveness and stability. The system includes intelligent state tracking with NA handling for initial bars and smooth gradient calculations that maintain performance across extended historical periods and real-time updates.
This indicator delivers sophisticated trend identification through Mean Absolute Deviation methodology combined with dual-strength filtering for superior signal quality. Unlike traditional Super Trend indicators that rely solely on ATR bands, the SMA-MAD approach uses statistical deviation measurement while incorporating ADX strength and slope validation to eliminate false signals during choppy conditions. The system's gradient-based visual feedback, ATR ribbon visualization, comprehensive dashboard, and multi-dimensional filtering make it essential for traders seeking reliable trend-following approaches with clear conviction measurement across cryptocurrency, forex, and equity markets. The combination of adaptive bands, strength-based transparency, and intelligent filtering creates an institutional-grade trend system suitable for systematic trading strategies. Indikator

Orderblock Footprints [AlgoAlpha]๐ OVERVIEW
This script highlights orderblocks and then drills into what actually trades inside them. Zones are created only after an abnormal directional impulse, measured with a z-score on consecutive candle bodies, so the orderblocks are tied to real expansion rather than simple pivots. Once a zone exists, the script overlays lower-timeframe volume footprints inside the candle when price trades back into that zone. The goal is to show not just where an orderblock sits, but whether price is being accepted or absorbed when it is revisited.
๐ CONCEPTS
Orderblocks are detected after extreme bullish or bearish impulses. The script tracks consecutive body movement up or down, normalizes that distance with a rolling z-score, and only triggers when the move is statistically large. The last opposite candle before that impulse defines the orderblock range. These zones then extend forward until they are either mitigated by price closing through them or they expire by age.
Inside an active zone, the script switches to a lower timeframe and builds a footprint-style profile for each bar. Each candle is split into price rows, counting time-at-price and volume delta. Positive and negative delta are colored separately. Absorption is flagged when opposing delta prints appear in the wick that rejects the zone. In practice: the impulse defines context ; the footprint shows interaction .
๐ FEATURES
Separate bullish and bearish zones with automatic extension
Volume split inside each zone candle (up vs down volume)
Lower-timeframe footprint with TPO-style rows and delta gradient
Absorption detection using opposing delta in rejection wicks
Alerts for zone creation and absorption events
๐ USAGE
Setup : Add the script to your chart. It works on any market and timeframe. The lower timeframe for footprints is fixed at 5 minutes, so higher chart timeframes show clearer structure. Use the Z-Score Window to control how strict impulse detection is and Max Box Age to limit how long old zones stay on the chart.
Read the chart : Bullish orderblocks are created after strong upward impulses and are invalidated when price closes below them. Bearish orderblocks are created after strong downward impulses and are invalidated when price closes above them. When price trades inside a zone, footprint rows appear. Green-tinted rows show positive delta; red-tinted rows show negative delta. Absorption labels appear when opposing delta prints into a rejecting wick.
Settings that matter : Increasing the Z-Score Window makes orderblocks rarer but more significant. Disabling Prevent Overlap allows stacked zones if you want to study clustering. Adjusting Rows per bar changes footprint resolutionโlower values are cleaner, higher values show more detail but use more objects.
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Liquidation Heatmap [Alpha Extract]A sophisticated liquidity zone visualization system that identifies and maps potential liquidation levels based on swing point analysis with volume-weighted intensity measurement and gradient heatmap coloring. Utilizing pivot-based pocket detection and ATR-scaled zone heights, this indicator delivers institutional-grade liquidity mapping with dynamic color intensity reflecting relative liquidity concentration. The system's dual-swing detection architecture combined with configurable weight metrics creates comprehensive liquidation level identification suitable for strategic position planning and market structure analysis.
๐ถ Advanced Pivot-Based Pocket Detection
Implements dual swing width analysis to identify potential liquidation zones at pivot highs and lows with configurable lookback periods for comprehensive level coverage. The system detects primary swing points using main pivot width and optional secondary swing detection for increased pocket density, creating layered liquidity maps that capture both major and minor liquidation levels across extended price history.
๐ถ Multi-Metric Weight Calculation Engine
Features flexible weight source selection including Volume, Range (high-low spread), and Volume ร Range composite metrics for liquidity intensity measurement. The system calculates pocket weights based on market activity at pivot formation, enabling traders to identify which liquidation levels represent higher concentration of potential stops and liquidations with configurable minimum weight thresholds for noise filtering.
๐ถ ATR-Based Zone Height Framework
Utilizes Average True Range calculations with percentage-based multipliers to determine pocket vertical dimensions that adapt to market volatility conditions. The system creates ATR-scaled bands above swing highs for short liquidation zones and below swing lows for long liquidation zones, ensuring zone heights remain proportional to current market volatility for accurate level representation.
๐ถ Dynamic Gradient Heatmap Visualization
Implements sophisticated color gradient system that maps pocket weights to intensity scales, creating intuitive visual representation of relative liquidity concentration. The system applies power-law transformation with configurable contrast adjustment to enhance differentiation between weak and strong liquidity pockets, using cyan-to-blue gradients for long liquidations and yellow-to-orange for short liquidations.
๐ถ Intelligent Pocket State Management
Features advanced pocket tracking system that monitors price interaction with liquidation zones and updates pocket states dynamically. The system detects when price trades through pocket midpoints, marking them as "hit" with optional preservation or removal, and manages pocket extension for untouched levels with configurable forward projection to maintain visibility of approaching liquidity zones.
๐ถ Real-Time Liquidity Scale Display
Provides gradient legend showing min-max range of pocket weights with 24-segment color bar for instant liquidity intensity reference. The system positions the scale at chart edge with volume-formatted labels, enabling traders to quickly assess relative strength of visible liquidation pockets without numerical clutter on the main chart area.
๐ถ Touched Pocket Border System
Implements visual confirmation of executed liquidations through border highlighting when price trades through pocket zones. The system applies configurable transparency to touched pocket borders with inverted slider logic (lower values fade borders, higher values emphasize them), providing clear historical record of liquidated levels while maintaining focus on active untouched pockets.
๐ถ Dual-Swing Density Enhancement
Features optional secondary swing width parameter that creates additional pocket layer with tighter pivot detection for increased liquidation level density. The system runs parallel pivot detection at both primary and secondary swing widths, populating chart with comprehensive liquidity mapping that captures both major swing liquidations and intermediate level clusters.
๐ถ Adaptive Pocket Extension Framework
Utilizes intelligent time-based extension that projects untouched pockets forward by configurable bar count, maintaining visibility as price approaches potential liquidation zones. The system freezes touched pocket right edges at hit timestamps while extending active pockets dynamically, creating clear distinction between historical liquidations and forward-projected active levels.
๐ถ Weight-Based Label Integration
Provides floating labels on untouched pockets displaying volume-formatted weight values with dynamic positioning that follows pocket extension. The system automatically manages label lifecycle, creating labels for new pockets, updating positions as pockets extend, and removing labels when pockets are touched, ensuring clean chart presentation with relevant liquidity information.
๐ถ Performance Optimization Framework
Implements efficient array management with automatic clean-up of old pockets beyond lookback period and optimized box/label deletion to maintain smooth performance. The system includes configurable maximum object counts (500 boxes, 50 labels, 100 lines) with intelligent removal of oldest elements when limits are approached, ensuring consistent operation across extended timeframes.
This indicator delivers sophisticated liquidity zone analysis through pivot-based detection and volume-weighted intensity measurement with intuitive heatmap visualization. Unlike simple support/resistance indicators, the Liquidation Heatmap combines swing point identification with market activity metrics to identify where concentrated liquidations are likely to occur, while the gradient color system instantly communicates relative liquidity strength. The system's dual-swing architecture, configurable weight metrics, ATR-adaptive zone heights, and intelligent state management make it essential for traders seeking strategic position planning around institutional liquidity levels across cryptocurrency, forex, and futures markets. The visual heatmap approach enables instant identification of high-probability reversal zones where cascading liquidations may trigger significant price reactions. Indikator

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Simple Line๐ Understanding the Basic Concept
The trend reverses only when the price moves up or down by a fixed filter size.
It ignores normal volatility and noise, recognizing a trend change only when price moves beyond a specified threshold.
Trend direction is visually intuitive through line colors (green: uptrend, red: downtrend).
โ๏ธ Explanation of Settings
Auto Brick Size: Automatically determines the brick/filter size.
Fixed Brick Size: Manually set the size (e.g., 15, 30, 50, 100, etc.).
Volatility Length: The lookback period used for calculations (default: 14).
๐ Example of Identifying Buy Timing
When the line changes from gray or red to green, it signals the start of an uptrend.
This indicates that the price has moved upward by more than the required threshold.
๐ Example of Identifying Sell Timing
When the line changes from green to red, it suggests a possible downtrend reversal.
At this point, consider closing long positions or evaluating short entries.
๐งช Recommended Use Cases
Use as a trend filter to enhance the accuracy of existing strategies.
Can be used alone as a clean directional indicator without complex oscillators.
Works synergistically with trend-following strategies, breakout strategies, and more.
๐ Notes & Cautions
More suitable for medium- to long-term trend trading than for fast scalping.
If the brick size is too small, the indicator may react to noise.
Sensitivity varies greatly depending on the selected brick size, so backtesting is essential to determine optimal values.
โ The Trend Simple Line focuses solely on directionโremove the noise and focus purely on the trend.
์ด๋ ์ ์ฉ ์คํฌ๋ฆฝํธ
์ด ์คํฌ๋ฆฝํธ์ ๋ํ ์ ๊ทผ์ด ์ ํ๋์ด ์์ต๋๋ค. ์ฌ์ฉ์๋ ์ฆ๊ฒจ์ฐพ๊ธฐ์ ์ถ๊ฐํ ์ ์์ง๋ง ์ฌ์ฉํ๋ ค๋ฉด ์ฌ์ฉ์์ ๊ถํ์ด ํ์ํฉ๋๋ค. ์ฐ๋ฝ์ฒ ์ ๋ณด๋ฅผ ํฌํจํ์ฌ ์ก์ธ์ค ์์ฒญ์ ๋ํ ๋ช
ํํ ์ง์นจ์ ์ ๊ณตํด ์ฃผ์ธ์.
์ด ๋น๊ณต๊ฐ ์ด๋ ์ ์ฉ ์คํฌ๋ฆฝํธ๋ ์คํฌ๋ฆฝํธ ๋ชจ๋๋ ์ดํฐ์ ๊ฒํ ๋ฅผ ๊ฑฐ์น์ง ์์์ผ๋ฉฐ, ํ์ฐ์ค ๋ฃฐ ์ค์ ์ฌ๋ถ๋ ํ์ธ๋์ง ์์์ต๋๋ค. ํธ๋ ์ด๋ฉ๋ทฐ๋ ์คํฌ๋ฆฝํธ์ ์๋ ๋ฐฉ์์ ์ถฉ๋ถํ ์ดํดํ๊ณ ์์ฑ์๋ฅผ ์์ ํ ์ ๋ขฐํ์ง ์๋ ์ด์, ํด๋น ์คํฌ๋ฆฝํธ์ ๋น์ฉ์ ์ง๋ถํ๊ฑฐ๋ ์ฌ์ฉํ๋ ๊ฒ์ ๊ถ์ฅํ์ง ์์ต๋๋ค. ์ปค๋ฎค๋ํฐ ์คํฌ๋ฆฝํธ์์ ๋ฌด๋ฃ ์คํ์์ค ๋์์ ์ฐพ์๋ณด์ค ์๋ ์์ต๋๋ค.
์์ฑ์ ์ง์ ์ฌํญ
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c9indicator
๋ฉด์ฑ
์ฌํญ
ํด๋น ์ ๋ณด์ ๊ฒ์๋ฌผ์ ๊ธ์ต, ํฌ์, ํธ๋ ์ด๋ฉ ๋๋ ๊ธฐํ ์ ํ์ ์กฐ์ธ์ด๋ ๊ถ์ฅ ์ฌํญ์ผ๋ก ๊ฐ์ฃผ๋์ง ์์ผ๋ฉฐ, ํธ๋ ์ด๋ฉ๋ทฐ์์ ์ ๊ณตํ๊ฑฐ๋ ๋ณด์ฆํ๋ ๊ฒ์ด ์๋๋ Indikator

Momentum Tide [Alpha Extract]A sophisticated momentum-based trend identification system that measures normalized price deviation from an EMA baseline using ATR scaling and hyperbolic tangent smoothing for precise trend state classification. Utilizing advanced signal processing with configurable neutral bands and slope sensitivity adjustments, this indicator delivers institutional-grade momentum analysis with continuous strength measurement and visual trend confirmation. The system's three-state classification (bullish, bearish, neutral) combined with dynamic color intensity scaling provides comprehensive market momentum assessment across varying volatility conditions.
๐ถ Advanced Baseline Deviation Framework
Implements EMA-based baseline calculation with ATR-normalized deviation measurement to create volatility-adjusted momentum signals. The system calculates raw price deviation from the baseline, scales by ATR and slope sensitivity factor, then applies exponential smoothing for stable signal generation with reduced noise and false transitions.
// Core Momentum Calculation
Baseline = ta.ema(close, Baseline_Length)
ATR_Value = ta.atr(ATR_Length)
Raw_Deviation = (close - Baseline) / (ATR_Value * Slope_Scaler)
Signal = ta.ema(Raw_Deviation, Signal_Smoothing)
๐ถ Hyperbolic Tangent Normalization Engine
Features sophisticated tanh transformation that clamps raw deviation signals into normalized -1 to +1 range for consistent interpretation across all market conditions. The system applies safe exponential calculations with value capping to prevent overflow while maintaining signal sensitivity, creating bounded momentum readings suitable for systematic threshold analysis.
// Tanh Normalization
Clamped_Signal = tanh(Signal) // Bounded to
Strength = abs(Clamped_Signal) // Momentum intensity
๐ถ Three-State Classification System
Implements intelligent trend state determination using configurable neutral band thresholds to reduce whipsaw signals during ranging conditions. The system classifies market as bullish (+1) when momentum exceeds upper neutral band, bearish (-1) below lower neutral band, and neutral (0) within the band, providing clear directional bias with built-in consolidation recognition.
๐ถ Dynamic Color Intensity Architecture
Provides advanced visual feedback through momentum strength-based color intensity modulation, where stronger trends display more opaque colors and weaker trends show increased transparency. The system dynamically adjusts color alpha values based on absolute momentum strength, creating intuitive visual representation of trend conviction across baseline, candles, and bars.
๐ถ Trend Strength Meter Visualization
Features innovative horizontal gradient meter displaying real-time momentum position across bear-to-bull spectrum with 24-segment resolution. The system creates smooth color transitions from bearish red through neutral gray to bullish green, with arrow indicator showing precise momentum location for instant trend strength assessment without cluttering the price chart.
๐ถ Intelligent Flip Detection System
Generates transition markers when trend state changes from neutral/bearish to bullish or neutral/bullish to bearish, with duplicate signal suppression to prevent marker clustering. The system tracks previous signal states and only plots new markers on genuine trend reversals, providing clean entry signal visualization for systematic trading approaches.
snapshot
๐ถ Configurable Neutral Band Framework
Implements adjustable neutral zone width using ATR percentage parameters to optimize signal frequency for different trading styles and market conditions. Wider bands reduce flip frequency for position trading while tighter bands increase sensitivity for active trading strategies, enabling customization without code modification.
๐ถ Slope Sensitivity Adjustment
Features slope scaler parameter that modulates ATR normalization factor, controlling signal smoothness versus responsiveness trade-off. Higher values create smoother momentum readings with fewer transitions while lower values increase snappiness for faster reaction to price changes, allowing optimization across different volatility regimes and timeframes.
๐ถ Comprehensive Visual Integration
Provides multi-dimensional trend visualization through color-coded baseline overlay, momentum-synchronized candle coloring, and bar color modification with configurable display toggles. The system includes optional flip markers and strength meter with position control for complete chart integration without visual overload.
๐ถ Performance Optimization Framework
Utilizes efficient calculation methods with optimized table management for strength meter updates and minimal computational overhead for real-time momentum processing. The system includes intelligent state tracking and safe mathematical operations to prevent errors during extreme market conditions while maintaining consistent performance.
๐ถ Why Choose Momentum Tide ?
This indicator delivers sophisticated momentum-based trend analysis through normalized deviation measurement and intelligent three-state classification. Unlike traditional momentum oscillators that operate in separate windows, Momentum Tide integrates directly with price action through baseline overlay and candle coloring while providing the analytical depth of bounded momentum measurement. The system's combination of tanh normalization, configurable neutral bands, dynamic color intensity, and innovative strength meter makes it essential for traders seeking adaptive trend-following approaches with clear visual feedback across cryptocurrency, forex, and equity markets. The three-state system naturally filters ranging periods while the momentum strength measurement enables position sizing and confidence assessment for systematic trading strategies. Indikator
