MA Distance Percentile - HighQ ToolsHighQTools — MA Distance Percentile (MADP)
As always, if anyone has any tips or additional features they'd like to see, feel free to reach out!
MA Distance Percentile (MADP) measures how far price is from its moving average relative to its own recent history.
Instead of showing raw distance (which varies by symbol, volatility, and timeframe), MADP normalizes price-to-MA distance into a 0–100 percentile rank over a rolling lookback window. This allows traders to quickly identify when price is relatively extended or compressed compared to recent conditions.
🔍 How It Works
A moving average is calculated (EMA by default, configurable).
The ratio of price / MA is computed.
That ratio is percentile-ranked over a user-defined lookback window.
The result is optionally smoothed for clarity.
High values (e.g., 80–100): Price is more extended above its MA than it has been recently.
Low values (e.g., 0–20): Price is relatively compressed or discounted vs its MA.
🧭 How to Use It
MADP is best used as a context tool, not a standalone signal:
Identify mean-reversion potential at relative extremes
Distinguish trend continuation vs exhaustion
Filter entries taken near highs/lows vs those taken in compression
Combine with structure, volume, delta, or VWAP-based tools
Optional visual levels (20 / 50 / 80) are provided for quick reference. Simple signals are included but disabled by default to encourage discretionary use.
⚙️ Defaults & Notes
Default MA: 20-period EMA
Default lookback: 200 bars
Designed for intraday and swing analysis
Does not repaint
Percentile-based normalization makes it robust across symbols and timeframes
This indicator is part of the HighQTools framework: clean, transparent tools designed to provide context first, not overfitted signals.
Hareketli Ortalamalar
Smart Money Fluid [JOAT]
Smart Money Fluid — Accumulation and Distribution Flow Analysis
Smart Money Fluid tracks institutional-style accumulation and distribution patterns using a sophisticated combination of Money Flow Index, Chaikin Money Flow, and VWAP-relative price analysis. It aims to reveal whether larger participants may be accumulating (buying) or distributing (selling)—information that can precede significant price moves.
What Makes This Indicator Unique
Unlike single money flow indicators, Smart Money Fluid:
Combines three different money flow methodologies into one composite signal
Detects divergences between price and money flow automatically
Identifies high-volume conditions that add conviction to signals
Provides both the composite signal and individual component values
Features a momentum histogram showing flow acceleration
What This Indicator Does
Combines multiple money flow indicators into a composite signal (0-100 scale)
Identifies accumulation zones (potential institutional buying) and distribution zones (potential selling)
Detects divergences between price and money flow
Highlights high-volume conditions for stronger signals
Tracks momentum direction within the flow
Provides comprehensive dashboard with all component values
Composite Calculation Explained
The Smart Money Flow composite combines three proven money flow methodologies:
// Component 1: Money Flow Index (MFI) - 40% weight
// Measures buying/selling pressure using price and volume
float mfi = 100 - (100 / (1 + mfRatio))
// Component 2: Chaikin Money Flow (CMF) - 30% weight
// Measures accumulation/distribution based on close position within range
float cmf = sum(mfVolume, length) / sum(volume, length) * 100
// Component 3: VWAP Price Strength - 30% weight
// Measures price position relative to volume-weighted average price
float priceVsVWAP = (close - vwap) / vwap * 100
// Final Composite (scaled to 0-100)
float rawSMF = (mfi * 0.4 + (cmf + 50) * 0.3 + (50 + priceVsVWAP * 5) * 0.3)
float smf = ta.ema(rawSMF, smoothLength)
State Classification
Accumulating (Green Zone) — SMF above accumulation threshold (default: 60). Suggests institutional buying may be occurring.
Distributing (Red Zone) — SMF below distribution threshold (default: 40). Suggests institutional selling may be occurring.
Neutral (Gray Zone) — SMF between thresholds. No clear accumulation or distribution detected.
Divergence Detection
The indicator automatically detects divergences using pivot analysis:
Bullish Divergence — Price makes a lower low while SMF makes a higher low. This suggests selling pressure is weakening despite lower prices—potential reversal signal.
Bearish Divergence — Price makes a higher high while SMF makes a lower high. This suggests buying pressure is weakening despite higher prices—potential reversal signal.
Divergences are marked with "DIV" labels on the chart.
Visual Features
SMF Line with Glow — Main composite line with gradient coloring and glow effect
Signal Line — Slower EMA of SMF for crossover signals
Flow Momentum Histogram — Shows the difference between SMF and signal line with four-color coding:
- Bright green: Positive and accelerating
- Faded green: Positive but decelerating
- Bright red: Negative and accelerating
- Faded red: Negative but decelerating
Zone Backgrounds — Green tint in accumulation zone, red tint in distribution zone
Reference Lines — Dashed lines at accumulation/distribution thresholds, dotted line at 50
Strong Signal Markers — Triangles appear when accumulation/distribution occurs with high volume
Divergence Labels — "DIV" markers when divergences are detected
Color Scheme
Accumulation Color — Default: #00E676 (bright green)
Distribution Color — Default: #FF5252 (red)
Neutral Color — Default: #9E9E9E (gray)
Gradient Coloring — SMF line transitions smoothly between colors based on value
Dashboard Information
The on-chart table (top-right corner) displays:
Current SMF value with state coloring
State classification (ACCUMULATING, DISTRIBUTING, or NEUTRAL)
Flow momentum direction (Up/Down with magnitude)
MFI component value
CMF component value with directional coloring
Volume status (High or Normal)
Active divergence detection (Bullish, Bearish, or None)
Inputs Overview
Calculation Settings:
Money Flow Length — Period for flow calculations (default: 14, range: 5-50)
Smoothing Length — EMA smoothing period (default: 5, range: 1-20)
Divergence Lookback — Bars for pivot detection in divergence analysis (default: 5, range: 2-20)
Sensitivity:
Accumulation Threshold — Level above which accumulation is detected (default: 60, range: 50-90)
Distribution Threshold — Level below which distribution is detected (default: 40, range: 10-50)
High Volume Multiplier — Multiple of average volume for "high volume" classification (default: 1.5x, range: 1.0-3.0)
Visual Settings:
Accumulation/Distribution/Neutral Colors — Customizable color scheme
Show Flow Histogram — Toggle momentum histogram
Show Divergences — Toggle divergence detection and labels
Show Dashboard — Toggle the information table
Show Zone Background — Toggle colored backgrounds in accumulation/distribution zones
Alerts:
Await Bar Confirmation — Wait for bar close before triggering (recommended)
How to Use It
For Trend Confirmation:
Accumulation during uptrends confirms buying pressure
Distribution during downtrends confirms selling pressure
Divergence between price trend and SMF warns of potential reversal
For Reversal Detection:
Bullish divergence at price lows suggests potential bottom
Bearish divergence at price highs suggests potential top
Strong signals (triangles) with high volume add conviction
For Entry Timing:
Enter longs when SMF crosses into accumulation zone
Enter shorts when SMF crosses into distribution zone
Wait for high volume confirmation for stronger signals
Use divergences as early warning for position management
Alerts Available
SMF Accumulation Started — SMF entered accumulation zone
SMF Distribution Started — SMF entered distribution zone
SMF Strong Accumulation — Accumulation with high volume
SMF Strong Distribution — Distribution with high volume
SMF Bullish Divergence — Bullish divergence detected
SMF Bearish Divergence — Bearish divergence detected
Best Practices
High volume during accumulation/distribution adds significant conviction
Divergences are early warnings—don't trade them alone
Use in conjunction with price action and support/resistance
Works best on liquid markets with reliable volume data
This indicator is provided for educational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always conduct your own analysis and use proper risk management before making trading decisions.
— Made with passion by officialjackofalltrades
Adaptive 2 EMA Cloud (Trend-Aware)Adaptive 2 EMA Cloud (Trend-Aware)
This indicator combines a classic 2-EMA cloud and crossover with an adaptive Trend vs Chop filter designed to reduce whipsaws during sideways markets.
Instead of treating every EMA crossover equally, this script evaluates EMA separation and directional commitment (normalized by ATR) to determine whether price is trending or chopping. Signals can optionally be filtered so they only appear during qualified trend conditions.
What This Indicator Does
Plots two configurable EMAs with a filled EMA cloud
Marks bullish and bearish EMA crossovers
Classifies market state as BULLISH / BEARISH / CHOP
Optionally filters signals during chop
Highlights chop zones with a subtle background
Displays a movable Trend status label (Top / Bottom × Left / Middle / Right) with offset controls to avoid UI overlap
This makes the indicator useful both as:
A visual trend context tool
A signal filter to pair with discretionary or systematic entries
Quick Presets (Main Framework)
Scalp / Fast (1–2 min)
Built for speed and momentum bursts. Uses tighter EMAs and stricter filters to avoid chop on very fast charts.
EMA pairs (choose one):
5 / 9
8 / 13
slopeLen: 4–6
minDistATR: 0.25–0.40
minSlopeATR: 0.06–0.12
Balanced Intraday (3–5 min)
General-purpose intraday setup. Balances early trend participation with chop filtering. Recommended starting point if unsure.
EMA pairs (choose one):
8 / 13
9 / 21
slopeLen: 5–8
minDistATR: 0.18–0.30
minSlopeATR: 0.04–0.08
Slower / Swing (15–60 min)
Designed for higher timeframes and smoother trends. Allows longer trends to develop without requiring sharp acceleration.
EMA pairs (choose one):
13 / 21
21 / 34
slopeLen: 8–14
minDistATR: 0.10–0.22
minSlopeATR: 0.02–0.06
Input Guide (Streamlined)
minDistATR — EMA Separation
Sets the minimum EMA spacing (ATR-normalized) required for a trend.
Higher = stricter, fewer signals
Filters EMA compression / ranges
Too much chop → increase
Too few signals → decrease
Too low = congestion signals · Too high = late entries
minSlopeATR — EMA Slope / Commitment
Sets the minimum directional strength (ATR-normalized) of the EMAs.
Higher = stricter, fewer signals
Filters weak drift and slow grind
Signals stall → increase
Miss smooth trends → decrease
Too low = flat EMAs allowed · Too high = requires acceleration
slopeLen — Slope Lookback
Controls how quickly the filter reacts.
Lower = faster, noisier
Higher = smoother, fewer signals
3–5 responsive · 8–14 stable
atrLen — Normalization
Stabilizes distance and slope across symbols and timeframes.
Leave at 14 normally
Use 20–30 during extreme volatility shifts
Notes
This is an indicator, not a strategy. It does not backtest or predict outcomes.
No filter eliminates chop entirely—this tool is designed to reduce low-quality conditions, not remove them.
Best results come from matching presets to timeframe first, then making small adjustments only when behavior is clearly off.
UM Premarket Volume DashboardSUMMARY
Do you track the largest percent movers in the premarket?
Instantly compare current premarket volume to its recent average with built-in trend confirmation.
⸻
DESCRIPTION
This indicator is a compact premarket intelligence dashboard that combines live volume analysis with adaptive trend detection. It highlights unusually strong premarket activity while confirming directional bias using either a Nadaraya–Watson Estimator (NWE) or traditional moving averages.
The goal is to quickly identify symbols that are both active and aligned with trend before the regular trading session begins.
⸻
HOW IT WORKS
• Calculates average daily volume using a 50-day rolling average
• Tracks live premarket volume between 04:00–09:30 (exchange time)
• Computes a rolling average of prior premarket sessions and blends in the current day’s partial premarket volume in real time
• Highlights premarket volume in dark green when it exceeds both a user-defined threshold and the rolling premarket average
• Determines bullish or bearish trend status using a selectable method:
• Nadaraya–Watson Estimator (NWE)
• EMA, WMA, or SMA
• Trend status is based on directional slope (current value vs prior bar)
• Displays percent gain from the previous regular-session close (4:00pm ET)
• Shows total shares outstanding for quick liquidity context (when available)
⸻
DEFAULT SETTINGS
• Trend Method: Nadaraya–Watson Estimator (NWE)
• NWE Lookback Window (h): 8
• NWE Relative Weighting (r): 8
• Regression Length: 120 bars
• Premarket Average Days: 10
• Premarket Green Volume Threshold: 50,000 shares
• Average Daily Volume: 50-day SMA
• Trend Source: Close
⸻
SUGGESTED SETTINGS AND USES
• Use the default NWE settings for smoother, adaptive trend confirmation, especially on lower timeframes (1–5 minute charts) during premarket
• Switch to EMA or WMA if you prefer faster trend flips or want behavior consistent with MA-based systems
• Increase the Premarket Volume Threshold for large-cap stocks or ETFs to reduce noise
• Decrease the threshold for small-cap stocks to surface early momentum names
Ideal for:
• Premarket gap scanners
• Momentum continuation setups
• Liquidity confirmation before market open
• Building dynamic watchlists for the opening bell
This indicator is best used as a filtering and confirmation tool, not as a standalone entry signal.
Trend Regime Bands (EMA 50 / 150 / 200)📘 Trend Regime Bands – EMA 50·150·200
Overview
Trend Regime Bands is a visual trend-context indicator designed to help users quickly understand whether the market is in a bullish or bearish regime. The indicator uses the alignment of EMA 50, EMA 150, and EMA 200 to determine overall trend direction, while additional EMAs are used only to create color-based bands for visual context. No buy or sell signals are generated.
How Trend Direction Is Determined
Trend direction is derived exclusively from the relative positioning of: EMA 50 (short-term trend) , EMA 150 (medium-term trend) , EMA 200 (long-term trend) . Bullish regime: EMA 50 ≥ EMA 150 ≥ EMA 200 . Bearish regime: EMA 50 < EMA 150 < EMA 200. These three EMAs act as the decision framework for the indicator.
What the Color Bands Represent : The indicator displays two visual bands on the chart:
Fast Band (Momentum Context) - Built using faster EMAs, Represents short-term momentum and pullback behavior. Brighter color intensity reflects stronger momentum
Slow Band (Regime Context) - Built using slower EMAs. Represents broader trend structure and regime stability.Deeper color intensity reflects stronger trend alignment
The color of both bands follows the trend direction determined by EMA 50/150/200:
Green shades indicate a bullish regime. Red shades indicate a bearish regime. Color intensity increases or decreases smoothly based on trend strength.
How to Use This Indicator
Use the bands to understand market context, not as entry or exit signals. Strong, bright bands suggest a well-established trend. Lighter bands indicate weaker or transitioning trends. The indicator works across intraday, swing, and higher timeframes. This tool is best used alongside price action, support/resistance, or other confirmation methods.
Important Notes
This indicator does not provide buy or sell signals. It does not predict future price movement. It is intended solely as a visual trend-regime and context tool
Summary
Trend Regime Bands offers a clean, distraction-free way to visualize bullish and bearish market regimes using EMA structure and color intensity, helping traders maintain directional awareness and discipline.
ATR-Normalized VWMA DeviationThis indicator measures how far price deviates from the Volume-Weighted Moving Average ( VWMA ), normalized by market volatility ( ATR ). It identifies significant price reversal points by combining price structure and volatility-adjusted deviation behavior.
The core idea is to use VWMA as a dynamic trend anchor, then measure how far price travels away from it relative to recent volatility . This helps highlight when price has stretched too far and may be due for a reversal or pullback.
How it works:
VWMA deviation is calculated as the difference between price and the VWMA.
That deviation is divided by ATR (Average True Range) to normalize for current volatility.
The script tracks the highest and lowest normalized deviations over the chosen lookback period.
It also tracks price structure (highest/lowest highs/lows) over the same period.
A reversal signal is generated when a historical extreme in deviation aligns with a price structure extreme, and a confirmed reversal candle forms.
You get visual signals and color highlights where these conditions occur.
Settings explained:
Lookback period defines how many bars the script uses to find recent extremes.
ATR length controls how volatility is measured.
VWMA length controls how the volume-weighted moving average is calculated.
Signal filters help refine entries based on price vs deviation behavior.
Display options let you customize how signals and levels appear on the chart.
This indicator is especially useful for spotting potential turning points where price has moved far from VWMA relative to volatility, suggesting possible exhaustion or overextension.
Tips for use:
Combine with broader trend context (higher timeframe support/resistance).
Use with risk management rules (position sizing, stops) — signals are guides, not guaranteed entries.
Adjust lookback and ATR settings based on your trading timeframe and asset volatility.
Adaptive ML Trailing Stop [BOSWaves]Adaptive ML Trailing Stop – Regime-Aware Risk Control with KAMA Adaptation and Pattern-Based Intelligence
Overview
Adaptive ML Trailing Stop is a regime-sensitive trailing stop and risk control system that adjusts stop placement dynamically as market behavior shifts, using efficiency-based smoothing and pattern-informed biasing.
Instead of operating with fixed ATR offsets or rigid trailing rules, stop distance, responsiveness, and directional treatment are continuously recalculated using market efficiency, volatility conditions, and historical pattern resemblance.
This creates a live trailing structure that responds immediately to regime change - contracting during orderly directional movement, relaxing during rotational conditions, and applying probabilistic refinement when pattern confidence is present.
Price is therefore assessed relative to adaptive, condition-aware trailing boundaries rather than static stop levels.
Conceptual Framework
Adaptive ML Trailing Stop is founded on the idea that effective risk control depends on regime context rather than price location alone.
Conventional trailing mechanisms apply constant volatility multipliers, which often results in trend suppression or delayed exits. This framework replaces static logic with adaptive behavior shaped by efficiency state and observed historical outcomes.
Three core principles guide the design:
Stop distance should adjust in proportion to market efficiency.
Smoothing behavior must respond to regime changes.
Trailing logic benefits from probabilistic context instead of fixed rules.
This shifts trailing stops from rigid exit tools into adaptive, regime-responsive risk boundaries.
Theoretical Foundation
The indicator combines adaptive averaging techniques, volatility-based distance modeling, and similarity-weighted pattern analysis.
Kaufman’s Adaptive Moving Average (KAMA) is used to quantify directional efficiency, allowing smoothing intensity and stop behavior to scale with trend quality. Average True Range (ATR) defines the volatility reference, while a K-Nearest Neighbors (KNN) process evaluates historical price patterns to introduce directional weighting when appropriate.
Three internal systems operate in tandem:
KAMA Efficiency Engine : Evaluates directional efficiency to distinguish structured trends from range conditions and modulate smoothing and stop behavior.
Adaptive ATR Stop Engine : Expands or contracts ATR-derived stop distance based on efficiency, tightening during strong trends and widening in low-efficiency environments.
KNN Pattern Influence Layer : Applies distance-weighted historical pattern outcomes to subtly influence stop placement on both sides.
This design allows stop behavior to evolve with market context rather than reacting mechanically to price changes.
How It Works
Adaptive ML Trailing Stop evaluates price through a sequence of adaptive processes:
Efficiency-Based Regime Identification : KAMA efficiency determines whether conditions favor trend continuation or rotational movement, influencing stop sensitivity.
Volatility-Responsive Scaling : ATR-based stop distance adjusts automatically as efficiency rises or falls.
Pattern-Weighted Adjustment : KNN compares recent price sequences to historical analogs, applying confidence-based bias to stop positioning.
Adaptive Stop Smoothing : Long and short stop levels are smoothed using KAMA logic to maintain structural stability while remaining responsive.
Directional Trailing Enforcement : Stops advance only in the direction of the prevailing regime, preserving invalidation structure.
Gradient Distance Visualization : Gradient fills reflect the relative distance between price and the active stop.
Controlled Interaction Markers : Diamond markers highlight meaningful stop interactions, filtered through cooldown logic to reduce clustering.
Together, these elements form a continuously adapting trailing stop system rather than a fixed exit mechanism.
Interpretation
Adaptive ML Trailing Stop should be interpreted as a dynamic risk envelope:
Long Stop (Green) : Acts as the downside invalidation level during bullish regimes, tightening as efficiency improves.
Short Stop (Red) : Serves as the upside invalidation level during bearish regimes, adjusting width based on efficiency and volatility.
Trend State Changes : Regime flips occur only after confirmed stop breaches, filtering temporary price spikes.
Gradient Depth : Deeper gradient penetration indicates increased extension from the stop rather than imminent reversal.
Pattern Influence : KNN weighting affects stop behavior only when historical agreement is strong and remains neutral otherwise.
Distance, efficiency, and context outweigh isolated price interactions.
Signal Logic & Visual Cues
Adaptive ML Trailing Stop presents two primary visual signals:
Trend Transition Circles : Display when price crosses the opposing trailing stop, confirming a regime change rather than anticipating one.
Stop Interaction Diamonds : Indicate controlled contact with the active stop, subject to cooldown filtering to avoid excessive signals.
Alert generation is limited to confirmed trend transitions to maintain clarity.
Strategy Integration
Adaptive ML Trailing Stop fits within trend-following and risk-managed trading approaches:
Dynamic Risk Framing : Use adaptive stops as evolving invalidation levels instead of fixed exits.
Directional Alignment : Base execution on confirmed regime state rather than speculative reversals.
Efficiency-Based Tolerance : Allow greater price fluctuation during inefficient movement while enforcing tighter control during clean trends.
Pattern-Guided Refinement : Let KNN influence adjust sensitivity without overriding core structure.
Multi-Timeframe Context : Apply higher-timeframe efficiency states to inform lower-timeframe stop responsiveness.
Technical Implementation Details
Core Engine : KAMA-based efficiency measurement with adaptive smoothing
Volatility Model : ATR-derived stop distance scaled by regime
Machine Learning Layer : Distance-weighted KNN with confidence modulation
Visualization : Directional trailing stops with layered gradient fills
Signal Logic : Regime-based transitions and controlled interaction markers
Performance Profile : Optimized for real-time chart execution
Optimal Application Parameters
Timeframe Guidance:
1 - 5 min : Tight adaptive trailing for short-term momentum control
15 - 60 min : Structured intraday trend supervision
4H - Daily : Higher-timeframe regime monitoring
Suggested Baseline Configuration:
KAMA Length : 20
Fast/Slow Periods : 15 / 50
ATR Period : 21
Base ATR Multiplier : 2.5
Adaptive Strength : 1.0
KNN Neighbors : 7
KNN Influence : 0.2
These suggested parameters should be used as a baseline; their effectiveness depends on the asset volatility, liquidity, and preferred entry frequency, so fine-tuning is expected for optimal performance.
Parameter Calibration Notes
Use the following adjustments to refine behavior without altering the core logic:
Excessive chop or overreaction : Increase KAMA Length, Slow Period, and ATR Period to reinforce regime filtering.
Stops feel overly permissive : Reduce the Base ATR Multiplier to tighten invalidation boundaries.
Frequent false regime shifts : Increase KNN Neighbors to demand stronger historical agreement.
Delayed adaptation : Decrease KAMA Length and Fast Period to improve responsiveness during regime change.
Adjustments should be incremental and evaluated over multiple market cycles rather than isolated sessions.
Performance Characteristics
High Effectiveness:
Markets exhibiting sustained directional efficiency
Instruments with recurring structural behavior
Trend-oriented, risk-managed strategies
Reduced Effectiveness:
Highly erratic or event-driven price action
Illiquid markets with unreliable volatility readings
Integration Guidelines
Confluence : Combine with BOSWaves structure or trend indicators
Discipline : Follow adaptive stop behavior rather than forcing exits
Risk Framing : Treat stops as adaptive boundaries, not forecasts
Regime Awareness : Always interpret stop behavior within efficiency context
Disclaimer
Adaptive ML Trailing Stop is a professional-grade adaptive risk and regime management tool. It does not forecast price movement and does not guarantee profitability. Results depend on market conditions, parameter selection, and disciplined execution. BOSWaves recommends deploying this indicator within a broader analytical framework that incorporates structure, volatility, and contextual risk management.
TwinSmooth ATR Bands | QuantEdgeBTwinSmooth ATR Bands | QuantEdgeB
🔍 Overview
TwinSmooth ATR Bands | QuantEdgeB is a dual-smoothing, ATR-adaptive trend filter that blends two complementary smoothing engines into a single baseline, then builds dynamic ATR bands around it to detect decisive breakouts. When price closes above the upper band it triggers a Long regime; when it closes below the lower band it flips to Short—otherwise it stays neutral. The script enhances clarity with regime-colored candles, an active-band fill, and an optional on-chart backtest table.
✨ Key Features
1. 🧠 Twin-Smooth Baseline (Dual Engine Blend)
- Computes two separate smoothed baselines (a slower “smooth” leg + a faster “responsive” leg).
- Blends them into a single midpoint baseline for balanced stability + speed.
- Applies an extra EMA smoothing pass to produce a clean trend_base.
2. 📏 ATR Volatility Bands
- Builds upper/lower bands using ATR × multiplier around the trend_base.
- Bands expand in volatile conditions and contract when markets quiet down—auto-adapting without manual tweaks.
3. ⚡ Clear Breakout Regime Logic
- Long when close > upperBand.
- Short when close < lowerBand.
- Neutral otherwise (no forced signals inside the band zone).
4. 🎨 Visual Clarity
- Plots only the active band (lower band in long regime, upper band in short regime).
- Fills between active band and price for instant regime context.
- Colors candles to match the current state (bullish / bearish / neutral).
- Multiple color palettes + transparency control.
💼 Use Cases
• Trend Confirmation Filter: Use the regime as a higher-confidence trend gate for entries from other indicators.
• Breakout/Breakdown Trigger: Trade closes outside ATR bands to catch momentum expansions.
• Volatility-Aware Stops/Targets: Bands naturally reflect volatility, making them useful as adaptive reference levels.
• Multi-Timeframe Alignment: Confirm higher-timeframe regime before executing on lower timeframes.
🎯 For Who
• Trend Traders who want clean regime shifts without constant whipsaw.
• Breakout Traders who prefer confirmation via ATR expansion rather than raw MA crossovers.
• System Builders needing a simple, robust “state engine” (Long / Short / Neutral) to plug into larger strategies.
• Analysts who want quick on-chart validation with a backtest table.
⚙️ Default Settings
• SMMA Length (Base Smooth Leg): 24
• TEMA Length (Base Responsive Leg): 8
• EMA Extra Smoothing: 14
• ATR Length: 14
• ATR Multiplier: 1.1
• Color Mode: Alpha
• Color Transparency: 30
• Backtest Table: On (toggleable)
• Backtest Start Date: 09 Oct 2017
• Labels: Off by default
📌 Conclusion
TwinSmooth ATR Bands | QuantEdgeB merges a dual-speed smoothing core into a single trend baseline, then wraps it with ATR-based bands to deliver clean, volatility-adjusted breakout signals. With regime coloring, active-band plotting, and optional backtest stats, it’s a compact, readable tool for spotting momentum shifts and trend continuation across any market and timeframe.
🔹 Disclaimer: Past performance is not indicative of future results. Always backtest and align settings with your risk tolerance and objectives before live trading.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Simple VWMA Smooth | QuantEdgeBSimple VWMA Smooth (SVS) | QuantEdgeB
🔍 What Is Simple VWMA Smooth?
SVS is a smoothed, volume-aware trend filter that blends a Gaussian-pre-filtered, low-lag moving average with dynamic standard-deviation bands. It identifies trends by measuring when price moves decisively above or below a VWMA (Volume-Weighted Moving Average) baseline—filtering out noise while letting high-volume moves carry more influence than low-volume noise.
⚙️ Core Components
1) DEMA Pre-Filter
A double-EMA smoothing step to reduce initial noise before further processing.
2) Gaussian Smoothing
Applies a small-kernel Gaussian filter to produce a cleaner input series that suppresses rapid spikes.
3) VWMA Baseline (Volume-Weighted Average)
Computes a moving average where each bar is weighted by volume, so the baseline tracks “meaningful” price moves more than low-liquidity fluctuations.
• In high volume → the baseline reacts more to those candles
• In low volume → price changes have less impact
4) Volatility Bands
Surrounds the VWMA line with ± N × SD bands (separate multipliers for upper and lower) to capture current market volatility, creating dynamic thresholds for trend detection.
5) Trend Signal
• Long when price closes above the upper band
• Short when price closes below the lower band
• Otherwise neutral
💡 Why It’s Special
• Volume-Validated Responsiveness: VWMA prioritizes moves backed by volume, helping reduce signals caused by thin-market noise.
• Multi-Stage Filtering: The DEMA → Gaussian → VWMA sequence suppresses noise while keeping trend structure clear.
• Asymmetric Bands: Separate multipliers for upper/lower bands let you tune bullish vs bearish sensitivity independently.
• Visual Clarity: Color-coded candles and filled bands highlight trending phases at a glance, while backtest tables quantify performance.
📊 Backtest Mode
SVS includes an optional backtest table, enabling traders to assess historical effectiveness before using it live.
Backtest Metrics Displayed:
• Equity Max Drawdown
• Profit Factor
• Sharpe Ratio
• Sortino Ratio
• Omega Ratio
• Half Kelly
• Total Trades & Win Rate
💼 Ideal Use Cases
• Trend Identification: Spot cleaner trend starts/exits across stocks, FX, or crypto with reduced lag and fewer false breakouts.
• Volume Regimes: Helps distinguish “real” moves (high participation) from weak moves (low participation).
• Multitimeframe Alignment: Confirm direction across timeframes before entries.
• System Building Block: Use as a volume-aware filter inside broader strategies.
🎨 Default Configuration
• DEMA Length: 7
• Gaussian Kernel: length = 4, sigma = 2.0
• VWMA Length: 14
• Volatility Bands: SD length = 40
📌 In Summary
Simple VWMA Smooth | QuantEdgeB is a volume-weighted, noise-suppressed trend filter that combines DEMA smoothing, Gaussian filtering, a VWMA baseline, and dynamic SD bands to separate genuine directional moves from market noise—across any asset or timeframe.
🔹 Disclaimer : Past performance is not indicative of future results. Always backtest and align settings with your risk tolerance and objectives before live trading.
🔹 Strategic Advice : Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Rapid Signal GeometryMechanism Explained (Simple & Practical)
1. Fair Value Baseline
A smoothed moving average (RMA) is used to represent price equilibrium. This baseline filters noise and avoids reacting to minor fluctuations.
2. Volatility Envelope
ATR or Standard Deviation (user selectable) defines how far price must move away from equilibrium to be considered meaningful. This adaptive range expands and contracts with market conditions.
3. Regime Shift Detection
A bullish regime is confirmed when price decisively breaks above the upper volatility boundary.
A bearish regime is confirmed when price decisively breaks below the lower volatility boundary.
The logic resets on every candle — there is no trailing or repainting behaviour.
4. Signal Candle Geometry
On the first candle of a new regime, RSG draws two short horizontal guides:
• 50% Body Level
The midpoint of the signal candle’s body, representing balance within the impulse.
• Projected Wick Level
A mirrored wick projection calculated from the candle’s close:
– Bullish signal: upper wick distance projected downward
– Bearish signal: lower wick distance projected upward
These levels provide a geometric framework for execution planning.
Signals & Alerts
• Buy signal prints only on the first confirmed bullish regime
• Sell signal prints only on the first confirmed bearish regime
• No repeated signals during the same trend
Alert options include:
• Buy only
• Sell only
• Combined Buy/Sell
All alerts are bar-close confirmed.
How to Use Rapid Signal Geometry
RSG is best used as an execution aid, not a standalone strategy.
Common use cases:
• Refining entries after a confirmed directional bias
• Identifying pullback or reaction zones on signal candles
• Aligning discretionary entries with volatility-aware structure
• Complementing higher-timeframe analysis or session-based strategies
The geometric levels are reference points — traders should always apply their own risk management.
Recommended Timeframes
RSG performs best on:
• 15-minute
• 1-hour
These timeframes provide a strong balance between signal clarity and noise reduction.
Lower timeframes may produce more frequent regime changes, while higher timeframes offer fewer but broader signals.
Important Notes
• This indicator does not predict future price movement
• Signals are not trade recommendations
• Designed for educational and analytical purposes
• Always combine with your own market context and risk rules
Summary
Rapid Signal Geometry focuses on one thing only:
revealing the internal geometry of decisive market moments .
By combining volatility-aware regime detection with precise candle-level reference marks, RSG offers a clean and disciplined approach to execution-focused chart analysis.
Instant Start EMA RibbonHave you noticed that EMAs on Tradingview start to appear on chart after the number of candles required by the EMA has fulfilled?
Example, 200 EMA shows up only when 200 candles have been printed on the canvas irrespective of the timeframe.
You might also have noticed that in some other charting software, the EMAs start from the very first candle of the instrument/asset class, a good example is a newly listed stock. And then the EMA automatically aligns itself once the amount of candles required by the EMA is fulfilled.
So if you want similar behavior of EMAs on Tradingview, you can use this "Instant Start EMA Ribbon" specifically coded in Pinescript to exactly and accurately mimic the behavior of EMAs like the other software. You can check that EMAs with this custom indicator start from the very first candles after listing of the instrument/asset class. This indicator will optimize the EMAs and work as a normal EMA once the amount of candles required are fulfilled, until then, it will use custom parameters to calculate the EMAs (that is the available current candle data).
Tip: You can change the values and colors of EMAs from the indicator settings.
Disclaimer/Warning: This indicator does not provide Buy/Sell signals or nor is an investment advice. This indicator solely for the purpose of study of price and Exponential Moving Averages. Users are responsible for their own actions, profit/loss of the users is not the liability of author.
S&D Trend Pullback StrategyThis is simple indicator for myself to alert me when in trend pullback and entry.
Use in M5 chart.
SL put 30-50pips
TP can set 30-90pips
Signals, Emas Bahena Indicator: Emas Bahena Signals
This indicator uses three Exponential Moving Averages (EMAs) to identify buy and sell entries based on crossovers and trend.
🔹 EMAs used
EMA 9 → fast (signals)
EMA 21 → intermediate (confirmation)
EMA 85 → slow (main trend)
🟢 BUY Signal
Generated when:
The EMA 9 crosses above the EMA 21
The EMA 9 is above the EMA 85 ➡️ Indicates the start of an uptrend
🔴 SELL Signal
Generated when:
The EMA 9 crosses below the EMA 21
The EMA 9 is below the EMA 85 ➡️ Indicates the start of a downtrend
📌 Visualization
EMAs drawn on the chart
BUY arrow below the price
SELL arrow above the price
Compatible with TradingView alerts
⚠️ Recommendation
Works best in trending markets and on medium and high timeframes (15m, 1H, 4H)
UVOL Thrust TrackerUVOL Thrust Tracker identifies institutional breadth thrusts using NYSE up-volume as a percentage of total volume (USI:UVOL / USI:TVOL), plotted directly on price.
The indicator highlights:
TRUE 90% UVOL thrusts (rare, high-conviction breadth events)
Surrogate thrust clusters (multi-day 80–89% participation)
Cluster failures (momentum that fails to expand)
Structural thrust failures (2022-style false starts)
A regime filter based on the chart symbol’s moving averages separates bull vs bear environments, dynamically adjusting thresholds and failure logic.
This tool is designed for regime confirmation and risk management, not short-term entries. TRUE thrusts typically confirm trend continuation, while failures warn when breadth support breaks down.
Note: This indicator is intended for regime and risk assessment, not precise entries or exits.
Ultimate Pattern Engine - Elite Suite v54Here's the description I wrote for your Pine Script publication:
Ultimate Pattern Engine - Elite Suite v54
A comprehensive technical analysis tool combining multiple pattern recognition algorithms and indicators in one powerful suite.
Pattern Recognition:
Head & Shoulders patterns with automatic neckline detection
Bull and Bear flag formations
9-count sequential patterns
Breakout pattern detection with alerts
Support/Resistance zones with dynamic S/R levels
Reversal cloud visualization
Moving Averages:
Multiple Simple Moving Averages (SMA) - 9, 50, 200 periods
Exponential Moving Averages (EMA) with customizable lengths
Color-coded for easy trend identification
Visual Features:
Pattern fill areas for clear visualization
Breakout labels showing price action
Customizable color schemes (bullish green, bearish red, neutral gray)
H&S neckline highlighting
Volume multiplier analysis
Configuration:
Adjustable sensitivity and flatness thresholds
Toggle individual patterns on/off
Customizable moving average periods and colors
Full control over visual elements
Ideal for traders looking to identify key chart patterns, trend reversals, and breakout opportunities across all timeframes.
Neural Trend Engine [JOAT]Neural Trend Engine - Multi-Layer Adaptive Trend Detection
Neural Trend Engine uses a multi-layer filtering approach inspired by neural network concepts. It combines multiple adaptive moving averages with proprietary momentum and volatility weighting to generate trend signals with reduced lag and improved confidence scoring.
Why This Script is Protected
This script is published as closed-source to protect the proprietary signal composition algorithm and the specific weighting methodology from unauthorized republishing. The unique combination of adaptive layer calculations, momentum normalization, and volatility integration represents original work that goes beyond standard indicator implementations.
What Makes This Indicator Unique
Unlike simple moving average crossover systems, Neural Trend Engine:
Uses three Kaufman Adaptive Moving Averages (KAMA) that automatically adjust their smoothing based on market efficiency
Combines layer alignment, momentum, and volatility into a single "neural signal"
Provides signal strength percentages so you know the conviction level of each signal
Creates a visual trend cloud that makes direction immediately obvious
What This Indicator Does
Plots three adaptive moving average "layers" that respond dynamically to market efficiency
Creates a trend cloud between fast and slow layers for visual trend identification
Generates weighted composite signals from layer alignment, momentum, and volatility
Displays buy/sell labels with signal strength percentages
Provides a comprehensive dashboard with multi-component breakdown
Colors the neural line and cloud based on current trend direction
Core Methodology
The indicator employs a three-layer adaptive system where each layer responds to market conditions at different speeds:
Fast Layer (default: 8) — Quick response for short-term direction changes
Medium Layer (default: 21) — Intermediate trend reference
Slow Layer (default: 55) — Long-term trend anchor
Each layer uses efficiency-based adaptation, meaning they become more responsive during trending conditions and smoother during choppy markets.
The neural signal is a proprietary composite that weighs three distinct market components:
Momentum Component (default: 40%) — Measures directional price velocity, normalized to its recent range
Trend Component (default: 35%) — Evaluates alignment between the three adaptive layers
Volatility Component (default: 25%) — Incorporates market volatility state into signal generation
These components are combined using a weighted formula that has been calibrated to balance responsiveness with noise reduction.
Signal Generation
Direction changes occur when the smoothed neural signal crosses a configurable strength threshold:
Bullish — Signal exceeds positive threshold with layer alignment confirmation
Bearish — Signal drops below negative threshold with layer alignment confirmation
Neutral — Signal remains within threshold range, indicating consolidation
Signal strength percentages indicate the conviction level of each signal, helping traders assess trade quality. Higher percentages suggest stronger trend conviction.
Visual Features
Trend Cloud — Filled area between fast and slow layers, colored by trend direction
Neural Line with Glow — Weighted average of all three layers with glow effect
Medium Layer — Subtle white line showing intermediate trend
Signal Labels — BUY/SELL labels with strength percentages at signal points
Small Markers — Alternative triangle markers when labels are disabled
Color Scheme
Bullish Color — Default: #26A69A (teal green) — Used for bullish trends and signals
Bearish Color — Default: #EF5350 (red) — Used for bearish trends and signals
Cloud Fill — 85% transparent version of trend color
Neural Line Glow — 60% transparent version for glow effect
Dashboard Information
The on-chart table (top-right corner) displays:
Current direction (BULLISH, BEARISH, or NEUTRAL)
Neural signal percentage
Layer alignment status (ALIGNED UP, ALIGNED DOWN, or MIXED)
Momentum direction and percentage
Trend strength percentage
Inputs Overview
Neural Layers:
Fast Layer — Period for fast adaptive MA (default: 8, range: 2-50)
Medium Layer — Period for medium adaptive MA (default: 21, range: 5-100)
Slow Layer — Period for slow adaptive MA (default: 55, range: 10-200)
Source — Price source for calculations (default: close)
Sensitivity:
Momentum Weight — Weight for momentum component (default: 0.4)
Trend Weight — Weight for trend/layer alignment (default: 0.35)
Volatility Weight — Weight for volatility component (default: 0.25)
ATR Period — Period for volatility calculations (default: 14)
Visual Settings:
Bullish/Bearish Colors — Customizable color scheme
Show Trend Cloud — Toggle the filled cloud area
Show Signal Labels — Toggle BUY/SELL labels with percentages
Show Neural Line — Toggle the main trend line
Show Dashboard — Toggle the information table
Alerts:
Await Bar Confirmation — Wait for bar close before triggering (recommended)
Min Signal Strength — Threshold for direction changes (default: 0.3 = 30%)
How to Use It
For Trend Following:
Follow the trend cloud color for overall market direction
Enter long when cloud turns bullish (teal) and signal strength is high
Enter short when cloud turns bearish (red) and signal strength is high
Use the neural line as a trailing stop reference
For Signal Trading:
Wait for BUY/SELL labels to appear
Check the signal strength percentage—higher is better
Confirm with dashboard showing aligned layers
Avoid signals during MIXED layer alignment
For Confirmation:
Use Neural Trend Engine to confirm signals from other systems
Strong confirmation when all three layers are aligned
Dashboard shows momentum and trend strength for additional context
Alerts Available
NTE Buy Signal — Bullish direction change detected
NTE Sell Signal — Bearish direction change detected
NTE Direction Change — Any trend direction change
Best Practices
Higher signal strength percentages indicate more reliable signals
Wait for layer alignment (shown in dashboard) before entering trades
Use on higher timeframes for more reliable trend identification
Combine with support/resistance levels for entry timing
This indicator is provided for educational purposes. It does not constitute financial advice. Past performance does not guarantee future results. Always conduct your own analysis and use proper risk management before making trading decisions.
— Made with passion by officialjackofalltrades
A-Share Broad-Based ETF Dual-Core Timing System1. Strategy Overview
The "A-Share Broad-Based ETF Dual-Core Timing System" is a quantitative trading strategy tailored for the Chinese A-share market (specifically for broad-based ETFs like CSI 300, CSI 500, STAR 50). Recognizing the market's characteristic of "short bulls, long bears, and sharp bottoms," this strategy employs a "Left-Side Latency + Right-Side Full Position" dual-core driver. It aims to safely bottom-fish during the late stages of a bear market and maximize profits during the main ascending waves of a bull market.
2. Core Logic
A. Left-Side Latency (Rebound/Bottom Fishing)
Capital Allocation: Defaults to 50% position.
Philosophy: "Buy when others fear." Seeks opportunities in extreme panic or momentum divergence.
Entry Signals (Triggered by any of the following):
Extreme Panic: RSI Oversold (<30) + Price below Bollinger Lower Band + Bullish Candle Close (Avoid catching falling knives).
Oversold Bias: Price deviates more than 15% from the 60-day MA (Life Line), betting on mean reversion.
MACD Bullish Divergence: Price makes a new low while MACD histogram does not, accompanied by strengthening momentum.
B. Right-Side Full Position (Trend Following)
Capital Allocation: Aggressively scales up to Full Position (~99%) upon signal trigger.
Philosophy: "Follow the trend." Strike heavily once the trend is confirmed.
Entry Signals (All must be met):
Upward Trend: MACD Golden Cross + Price above 20-day MA.
Breakout Confirmation: CCI indicator breaks above 100, confirming a main ascending wave.
Volume Support: Volume MACD Golden Cross, ensuring price increase is backed by volume.
C. Smart Risk Control
Bear Market Exhaustion Exit: In a bearish trend (MA20 < MA60), the strategy does not "hold and hope." It immediately liquidates left-side positions upon signs of rebound exhaustion (breaking below MA20, touching MA60 resistance, or RSI failure).
ATR Trailing Stop: Uses Average True Range (ATR) to calculate a dynamic stop-profit line that rises with the price to lock in profits.
Hard Stop Loss: Forces a stop-loss if the left-side bottom fishing fails and losses exceed a set ATR multiple, preventing deep drawdowns.
3. Recommendations
Target Assets: High liquidity broad-based ETFs such as CSI 300 ETF (510300), CSI 500 ETF (510500), ChiNext ETF (159915), STAR 50 ETF (588000).
Timeframe: Daily Chart.
Scaled SMAs + Bollinger BandsScales another symbol's SMAs to the price of the symbol on the chart you are trading.
IDAHL | QuantEdgeBIDAHL | QuantEdgeB
🔍 Overview
The IDAHL indicator builds adaptive, volatility-aware threshold bands from two separate ALMA lines—one smoothed from recent highs, the other from recent lows—then uses percentiles of those lines to define a dynamic “high/low” channel. Price crossing above or below that channel triggers clear long/short signals, with on-chart candle coloring, fills, optional labels and even a built-in backtest table.
✨ Key Features
• 📈 Dual ALMA Bands (with DEMA pre-smoothing)
o High ALMA: ALMA applied to DEMA-smoothed highs (high → DEMA(30) → ALMA).
o Low ALMA: ALMA applied to DEMA-smoothed lows (low → DEMA(30) → ALMA).
• 📊 Percentile Thresholds
o Computes a high threshold at the Xth percentile of the High ALMA over a lookback window.
o Computes a low threshold at the Yth percentile of the Low ALMA.
o Shifts each threshold forward by a small period to reduce repainting.
• ⚡ Dynamic Channel Logic
o When price closes above the high percentile line, the “final” threshold flips down to the low percentile line (and vice versa), creating an adaptive channel that only moves when the outer bound is violated.
o Inside the channel, the threshold holds its last value to avoid whipsaw.
• 🎨 Visual & Alerts
o Plots the two percentile lines and fills between them with a color that reflects the current regime (green for long, yellow for neutral, orange for short).
o Colors your candles to match the active signal.
o Optional “Long”/“Short” labels on confirmed flips.
o Alert conditions fire on each long/short crossover.
• 📊 On-Chart Backtest Metrics
o Toggle on a small performance table—complete with win-rate, net P/L, drawdown—from your chosen start date, without any extra code.
⚙️ How It Works
1. Adaptive Smoothing (ALMA)
o Uses ALMA (Arnaud Legoux Moving Average) for smooth, low-lag filtering. In this script, the inputs are additionally pre-smoothed with DEMA(30) to reduce noise before ALMA is applied—improving stability on highs/lows.
2. Percentile Lines
o The High ALMA series feeds a linear-interpolation percentile function to generate the upper bound; the Low ALMA produces the lower bound.
o These lines are offset by a small look-ahead (X bars) to reduce repaint behavior.
3. Channel Logic
o Breakout Flip: When the selected source (default: Close) closes above the upper bound, the active threshold “jumps” to the lower bound—locking in a new channel until price next crosses.
o Breakdown Flip: Conversely, a close below the lower bound flips the threshold to the upper bound.
4. Signal Generation
o Long while the source is above the current “final” threshold.
o Short while below.
o Neutral inside the channel before any flip.
5. Visualization & Alerts
o Dynamic fills between the two percentile lines change hue as the regime flips.
o Candles adopt the regime color.
o Optional pinned “Long”/“Short” labels at flip bars.
o Alerts on every signal crossover of the zero-based regime line.
6. Backtest Table
o From your chosen start date, a mini-table displays cumulative P/L, win rate and drawdown for this strategy—handy for quick in-chart validation.
🎯 Who Should Use It
• Breakout Traders hunting for adaptive channels that auto-recenter on new highs/lows.
• Volatility Traders who want thresholds that expand and contract with market turbulence.
• Trend-Chasers seeking a fresh take on high/low channels with built-in smoothing.
• Systematic Analysts who appreciate on-chart backtesting without leaving TradingView.
⚙️ Default Settings
• ALMA Length: 14
• Percentile Length: 35 bars
• Percentile Lookback Period (offset): 4 bars
• Upper Percentile: 92%
• Lower Percentile: 50%
• Threshold Source: Close
• Visuals: Candle coloring on, labels off by default, “Strategy” palette
• Backtest Table: on by default (toggleable)
• Start Date (Backtest): 09 Oct 2017
📌 Conclusion
IDAHL blends two smooth, low-lag ALMA filters (fed by DEMA-smoothed highs/lows) with percentile-based channel construction for a self-rewiring high/low envelope. It gives you robust breakout/breakdown signals, immediate visual context via colored fills and candles, optional labels, alerts, and even performance stats—everything you need to spot and confirm regime shifts in one compact script.
🔹 Disclaimer : Past performance is not indicative of future results. Always backtest and align settings with your risk tolerance and objectives before live trading.
🔹 Strategic Advice : Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
FL Core Signals Only 4AM 4PMFL Core – Signals Only is a confirmation-based trading indicator designed to highlight structured entry and exit points during active market hours.
This script is not predictive and does not generate trade recommendations. It provides visual confirmation only after conditions are met and candles are closed.
Core characteristics:
• Signals are limited to 4:00 AM – 4:00 PM (exchange time)
• Designed for lower timeframes (1–5 minute charts)
• No indicator clutter — entries, exits, and profit target references only
• Logic is based on trend alignment and momentum confirmation
• Customizable profit target distances for different instruments
This indicator is intended for experienced traders who already understand risk management and execution. Users are responsible for their own trade decisions.
This is not an indicator you trade into.
It is a confirmation system you wait for.
Past performance does not guarantee future results.
SMC Confluence Suite [Pure Score Alerts]🚀 The Missing Link in SMC Trading: Timing & Confluence
Knowing "Where" to trade (Order Blocks/FVG) is only half the battle. Knowing "When" to pull the trigger is what separates amateurs from professionals.
The SMC Confluence Suite is a sophisticated Market Scoring Engine designed to validate your trade setups. It acts as a "Market Weather Station," analyzing Structure, Momentum, Extension, and Volatility in real-time to generate a single Confidence Score (0-100).
🧠 How It Works (The Logic)
This indicator processes 5 key dimensions to calculate a Long and Short Score:
Structure: Is the trend Bullish, Bearish, or in a Pullback?
Momentum: Analyzes RSI and divergence (Bull/Bear Div).
Extension (The Dux Logic): Detects if price is "Parabolic" (Overheated) or at a "Discount". It prevents FOMO buying at the top.
Rotation: Analyzes Volume Churn. Is the volume supporting the move, or is it stalling (distribution)?
Mood: A synthesis of market sentiment (Greed vs. Fear).
📊 The Dashboard
Long/Short Score:
> 80 (Aggressive 🚀): Market is priming for a strong move (Setup B / Unicorn).
60 - 80 (Standard ✅): Healthy trend, safe for Pullbacks (Setup C / Golden Swing).
< 40 (No Entry ⛔): Weak market or dangerous conditions.
Warning Flags:
PARABOLIC 🔥: Price moved too fast. Score resets to 0 to prevent chasing.
HIGH CHURN 🌪️: High volume but no price movement. Potential reversal.
✨ Key Features in V8.1
Score Trace (History): See historical scores printed directly on the chart (above/below candles). This allows you to backtest: "Did my winning trade have a high score?"
Asset Modes: optimized settings for Crypto, Stocks, and Metals (Gold/Silver).
Pure Alerts: Simplified alert system. Get notified only when Score > 80 (The "Sniper" moment).
💡 How to Trade (The Strategy)
Use this script alongside an SMC Structure indicator (like the SMC Strategy Companion).
Setup B (Breakout): Requires Score > 80 + High Volatility.
Setup C (Pullback): Requires Score > 60 + No "Parabolic" warning.
Kill Switch: If the Dashboard shows "PARABOLIC" or "CHURN", cancel all entries immediately.
Su Shen Comprehensive Trading System V2.0Su Shen Comprehensive Trading System V2.0
Su Shen Comprehensive Trading System is an intelligent trading assistant indicator that integrates multiple technical analysis tools. This system provides a comprehensive market perspective by combining multi-timeframe trend analysis, key level identification, and intelligent trading signals.
Core Features
Multi-dimensional Trend Analysis: Analyzes market trends across multiple timeframes simultaneously
Intelligent Trading Signals: Automatically identifies potential entry, take-profit, and exit opportunities
Key Level Identification: Marks important support and resistance zones
Risk Alerts: Indicates current risk level based on market conditions
Applicable Scenarios
Day trading
Swing trading
Trend following
How to Use
After adding the indicator to your chart, the system will automatically display analysis results and trading signals. Users can refer to these signals in conjunction with their own trading strategies.
