Change in State of Delivery CISD [AlgoAlpha]🟠 OVERVIEW
This script tracks how price “changes delivery” after failed attempts to push in one direction. It builds swing levels from pivots, watches for those levels to be wicked, and then checks if price delivers cleanly in the opposite direction. When the pattern meets the script’s tolerance rules, it marks a Change in State of Delivery (CISD). These CISD levels are drawn as origin lines and are used to spot shifts in intent, failed pushes, and continuation attempts. A CISD becomes stronger when it forms after opposing liquidity is swept within a defined lookback.
🟠 CONCEPTS
The script first defines structure using swing highs/lows. These levels act as potential liquidity points. When price wicks through a swing, the script registers a mitigation event. After this, it looks for a reversal-style candle sequence: a failed push, followed by a counter-move strong enough to pass a tolerance ratio. This ratio compares how far price expanded away from the failed attempt versus the counter-move that followed. If the ratio is high enough, this becomes a CISD. The idea is simple: liquidity interaction sets context , and the tolerance logic identifies actual intent . CISD levels and sweep markers combine these two ideas into a clean map of where delivery flipped.
🟠 FEATURES
Liquidity tracking: marks swing highs/lows and updates them until expiry
Liquidity sweep confirmation when CISD aligns with recent mitigations
Alert conditions for all key events: mitigations, CISDs, and strong CISDs
🟠 USAGE
Setup : Add the script to your chart. Use it on any timeframe where swing behavior matters. Set the Swing Period for how wide a pivot must be. Set Noise Filter to control how strict the CISD detection is. Liquidity Lookback defines how recent a wick must be to confirm a sweep.
Read the chart : Origin lines mark where the CISD began. A green line signals bullish intent; a red line signals bearish intent. ▲ and ▼ shapes show CISDs that form after liquidity is swept, these mark strong signals for potential entry. Swing dots show recent swing highs/lows. Candle colors follow the latest CISD trend.
Settings that matter : Increasing Swing Period produces fewer but stronger swings. Raising Noise Filter requires cleaner counter-moves and reduces false CISDs. Liquidity Lookback controls how strict the sweep confirmation is. Expiry Bars decides how long swing levels remain active.
المؤشرات والاستراتيجيات
Uptrick: Dynamic Z-Score DivergenceIntroduction
Uptrick: Dynamic Z-Score Divergence is an oscillator that combines multiple momentum sources within a Z-Score framework, allowing for the detection of statistically significant mean-reversion setups, directional shifts, and divergence signals. It integrates a multi-source normalized oscillator, a slope-based signal engine, structured divergence logic, a slope-adaptive EMA with dynamic bands, and a modular bar coloring system. This script is designed to help traders identify statistically stretched conditions, evolving trend dynamics, and classical divergence behavior using a unified statistical approach.
Overview
At its core, this script calculates the Z-Score of three momentum sources—RSI, Stochastic RSI, and MACD—using a user-defined lookback period. These are averaged and smoothed to form the main oscillator line. This normalized oscillator reflects how far short-term momentum deviates from its mean, highlighting statistically extreme areas.
Signals are triggered when the oscillator reverses slope within defined inner zones, indicating a shift in direction while the signal remains in a statistically stretched state. These mean-reversion flips (referred to as TP signals) help identify turning points when price momentum begins to revert from extended zones.
In addition, the script includes a divergence detection engine that compares oscillator pivot points with price pivot points. It confirms regular bullish and bearish divergence by validating spacing between pivots and visualizes both the oscillator-side and chart-side divergences clearly.
A dynamic trend overlay system is included using a Slope Adaptive EMA (SA-EMA). This trend line becomes more responsive when Z-Score deviation increases, allowing the trend line to adapt to market conditions. It is paired with ATR-based bands that are slope-sensitive and selectively visible—offering context for dynamic support and resistance.
The script includes configurable bar coloring logic, allowing users to color candles based on oscillator slope, last confirmed divergence, or the most recent signal of any type. A full alert system is also built-in for key signals.
Originality
The script is based on the well-known concept of Z-Score valuation, which is a standard statistical method for identifying how far a signal deviates from its mean. This foundation—normalizing momentum values such as RSI or MACD to measure relative strength or weakness—is not unique to this script and is widely used in quantitative analysis.
What makes this implementation original is how it expands the Z-Score foundation into a fully featured, signal-producing system. First, it introduces a multi-source composite oscillator by combining three momentum inputs—RSI, Stochastic RSI, and MACD—into a unified Z-Score stream. Second, it builds on that stream with a directional slope logic that identifies turning points inside statistical zones.
The most distinctive additions are the layered features placed on top of this normalized oscillator:
A structured divergence detection engine that compares oscillator pivots with price pivots to validate regular bullish and bearish divergence using precise spacing and timing filters.
A fully integrated slope-adaptive EMA overlay, where the smoothing dynamically adjusts based on real-time Z-Score movement of RSI, allowing the trend line to become more reactive during high-momentum environments and slower during consolidation.
ATR-based dynamic bands that adapt to slope direction and offer real-time visual zones for support and resistance within trend structures.
These features are not typically found in standard Z-Score indicators and collectively provide a unique approach that bridges statistical normalization, structure detection, and adaptive trend modeling within one script.
Features
Z-Score-based oscillator combining RSI, StochRSI, and MACD
Configurable smoothing for stable composite signal output
Buy/Sell TP signals based on slope flips in defined zones
Background highlighting for extreme outer bands
Inner and outer zones with fill logic for statistical context
Pivot-based divergence detection (regular bullish/bearish)
Divergence markers on oscillator and price chart
Slope-Adaptive EMA (SA-EMA) with real-time adaptivity based on RSI Z-Score
ATR-based upper and lower bands around the SA-EMA, visibility tied to slope direction
Configurable bar coloring (oscillator slope, divergence, or most recent signal)
Alerts for TP signals and confirmed divergences
Optional fixed Y-axis scaling for consistent oscillator view
The full setup mode can be seen below:
Input Parameters
General Settings
Full Setup: Enables rendering of the full visual system (lines, bands, signals)
Z-Score Lookback: Lookback period for normalization (mean and standard deviation)
Main Line Smoothing: EMA length applied to the averaged Z-Score
Slope Detection Index: Used to calculate directional flips for signal logic
Enable Background Highlighting: Enables visual region coloring in
overbought/oversold areas
Force Visible Y-Axis Scale: Forces max/min bounds for a consistent oscillator range
Divergence Settings
Enable Divergence Detection: Toggles divergence logic
Pivot Lookback Left / Right: Defines the structure of oscillator pivot points
Minimum / Maximum Bars Between Pivots: Controls the allowed spacing range for divergence validation
Bar Coloring Settings
Bar Coloring Mode:
➜ Line Color: Colors bars based on oscillator slope
➜ Latest Confirmed Signal: Colors bars based on the most recent confirmed divergence
➜ Any Latest Signal: Colors based on the most recent signal (TP or divergence)
SA-EMA Settings
RSI Length: RSI period used to determine adaptivity
Z-Score Length: Lookback for normalizing RSI in adaptive logic
Base EMA Length: Base length for smoothing before adaptivity
Adaptivity Intensity: Scales the smoothing responsiveness based on RSI deviation
Slope Index: Determines slope direction for coloring and band logic
Band ATR Length / Band Multiplier: Controls the width and responsiveness of the trend-following bands
Alerts
The script includes the following alert conditions:
Buy Signal (TP reversal detected in oversold zone)
Sell Signal (TP reversal detected in overbought zone)
Confirmed Bullish Divergence (oscillator HL, price LL)
Confirmed Bearish Divergence (oscillator LH, price HH)
These alerts allow integration into automation systems or signal monitoring setups.
Summary
Uptrick: Dynamic Z-Score Divergence is a statistically grounded trading indicator that merges normalized multi-momentum analysis with real-time slope logic, divergence detection, and adaptive trend overlays. It helps traders identify mean-reversion conditions, divergence structures, and evolving trend zones using a modular system of statistical and structural tools. Its alert system, layered visuals, and flexible input design make it suitable for discretionary traders seeking to combine quantitative momentum logic with structural pattern recognition.
Disclaimer
This script is for educational and informational purposes only. No indicator can guarantee future performance, and trading involves risk. Always use risk management and test strategies in a simulated environment before deploying with live capital.
15m ORB BREAK AND RETEST - MIDPOINT═══════════════════════════════════
15m ORB BREAK AND RETEST - MIDPOINT
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Free professional 15-minute Opening Range Breakout indicator from QuantCrawler - your AI-powered futures trading analysis platform.
Built as a free resource for the trading community. Support us at quantcrawler.com and on YouTube @AutomateWithAaron.
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📊 HOW IT WORKS
1. Captures the 15-minute Opening Range (default: 9:30-9:45 AM ET)
2. Draws OR High, OR Low, and Midpoint levels on your chart
3. Detects breakouts when price closes beyond the OR zone + your specified distance
4. Fires LONG/SHORT entry signals when price retests the OR midpoint after breakout
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✓ FEATURES
- Runs on 1m or 5m charts - captures 15m opening range automatically
- Universal - works on futures, forex, stocks, and crypto
- Customizable sessions - NY, London, Asia, or any custom timeframe
- Adjustable breakout distance to match your instrument
- Clean visual signals - only shows actionable entries
- Session end time stops monitoring after market close
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⚙️ SETTINGS
- Breakout Distance (Points): Distance outside OR zone to confirm breakout
- Timezone: Select your trading session
- Opening Range Time: First 15 minutes to capture (default 9:30-9:45)
- Session End Time: When to stop monitoring (default 16:00)
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🎯 IDEAL FOR
Day traders and swing traders who prefer wider opening ranges for reduced noise. The 15-minute OR provides more stable support/resistance levels compared to 5m setups.
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🚀 WANT MORE?
This indicator pairs perfectly with QuantCrawler's AI-powered chart analysis:
- Multi-timeframe futures analysis (15m/5m/1m scalping, 4H/1H/30m intraday, 1D/4H/1H swing)
- Precision entry points, stop losses, and profit targets
- Confidence scoring for every setup
- Covers futures, forex, and crypto markets
Visit quantcrawler.com to see how AI can level up your trading.
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⚠️ DISCLAIMER
This indicator is for educational purposes only. Past performance does not guarantee future results. Always use proper risk management and never risk more than you can afford to lose.
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Built with ❤️ by Aaron and QuantCrawler
quantcrawler.com | AI-Powered Futures Trading Analysis
Pre-Market ORB Break and Retest - Institutional═══════════════════════════════════
PRE-MARKET ORB BREAK AND RETEST - INSTITUTIONAL
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Free professional Pre-Market Opening Range Breakout indicator from QuantCrawler - your AI-powered futures trading analysis platform.
Built as a free resource for the trading community. Support us at quantcrawler.com and on YouTube @AutomateWithAaron.
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📊 HOW IT WORKS
1. Captures the 8:00-8:15 AM ET pre-market range where institutional investors position
2. Draws OR High, OR Low, and Midpoint levels on your chart
3. Waits for market open at 9:30 AM EST before detecting breakouts
4. Fires LONG/SHORT entry signals when price retests the OR midpoint after breakout
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✓ FEATURES
- Runs on 1m or 5m charts - captures 15m pre-market range automatically
- Zone marked at 8:15 AM, trades trigger after 9:30 AM market open
- Universal - works on futures, forex, stocks, and crypto
- Customizable sessions - NY, London, Asia, or any custom timeframe
- Adjustable breakout distance to match your instrument
- Clean visual signals - only shows actionable entries
- Session end time stops monitoring after market close
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⚙️ SETTINGS
- Breakout Distance (Points): Distance outside OR zone to confirm breakout
- Timezone: Select your trading session
- Opening Range Time: Pre-market positioning window (default 8:00-8:15)
- Session End Time: When to stop monitoring (default 16:00)
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🎯 IDEAL FOR
Day traders who defend institutional positioning levels. The 8:00-8:15 AM range captures where smart money positions before retail market open, giving you an edge on key support/resistance zones.
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🚀 WANT MORE?
This indicator pairs perfectly with QuantCrawler's AI-powered chart analysis:
- Multi-timeframe futures analysis (15m/5m/1m scalping, 4H/1H/30m intraday, 1D/4H/1H swing)
- Precision entry points, stop losses, and profit targets
- Confidence scoring for every setup
- Covers futures, forex, and crypto markets
Visit quantcrawler.com to see how AI can level up your trading.
═══════════════════════════════════
⚠️ DISCLAIMER
This indicator is for educational purposes only. Past performance does not guarantee future results. Always use proper risk management and never risk more than you can afford to lose.
═══════════════════════════════════
Built with ❤️ by Aaron at QuantCrawler
quantcrawler.com | AI-Powered Futures Trading Analysis
Dresteghamat:Adaptive Multi-TF Decision Engine**Dresteghamat: Adaptive Multi-Timeframe Decision Engine**
This open-source indicator is an algorithmic decision-support system designed to filter market noise by quantifying three core market dimensions: **Regime**, **Direction**, and **Exhaustion**.
**⚠️ Technical Note on Originality:**
This script solves the "Timeframe Irrelevance" problem found in standard dashboards. Instead of using static HTF references, it implements a custom **"Adaptive Context Engine"** (see lines 245-270 in source code). It calculates the user's current `timeframe.multiplier` and dynamically maps the mathematically relevant Higher Timeframes.
* *Innovation:* A 5m chart automatically weights 15m/1H structure, whereas a 1H chart weights 4H/Daily structure. This dynamic logic is proprietary and ensures contextual accuracy.
---
### 🛠️ Logic & Calculation Methodology
The script does not simply overlay indicators. It processes raw market data through a **Weighted Scoring Engine** (lines 275-285) to output a unified market state.
**1. Regime Identification (Volatility Normalized)**
We calculate a custom "Volatility Ratio" to distinguish Trend vs. Range regimes.
* **Logic:** `Range / Smoothed_ATR`.
* **Function:** If Ratio > 2.0, the market is in Expansion (Trend). If < 1.2, it is in Compression (Range). This normalizes volatility across assets (Crypto/Forex/Stocks).
**2. Directional Bias (Composite Metric)**
Direction is calculated via a voting system of three sub-components (lines 80-130):
* **Structural Pivots:** Detects Swing Highs/Lows using a 25-bar lookback to define market structure.
* **Cumulative Body Delta:** Tracks the net buying/selling pressure within candle bodies.
* **Micro-Flow:** A short-term (5-bar) momentum filter to detect immediate order flow shifts.
**3. Exhaustion Model (Risk Management)**
The script prevents late entries by calculating an "Exhaustion Score" (lines 150-200). It aggregates:
* **VRSD (Volatility Regime Shift):** Detects when volatility expands > 2 standard deviations (Mean Reversion risk).
* **Volume Decay (VEFF):** Identifies Divergence where price makes new highs on declining Volume MA.
* **RSI/Impulse Divergence:** Standard momentum divergence logic.
**4. The Decision Output (MODE)**
The dashboard renders a final signal based on a hierarchical algorithm:
* **BUY/SELL ONLY:** Triggered when Current Momentum aligns with the Dynamically Selected HTF Structure AND the Exhaustion Score is low.
* **PULLBACK:** Triggered when HTF Structure is bullish, but Current Momentum is bearish (indicating a corrective phase).
* **HTF EXHAUST:** Overrides signals when the Higher Timeframe metrics hit extreme levels.
* **WAIT:** Default state during Range Regimes or conflicting signals.
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### 📊 Usage Guide
1. Apply to chart (Auto-adapts to any timeframe).
2. **Status Column:** Shows the raw health of the trend (Strong/Weakening/Exhausted).
3. **MODE Column:** Displays the final actionable bias based on the scoring algorithm.
**Disclaimer:** This tool provides statistical analysis based on historical data. It does not guarantee future results.
Labden Swing 1.0Labden Swing Indicator, non real-time. good with semafor, ema 12 & 26 stochastic rsi and macd
GOLD 5MIN — 9×21 EMA Strategy (Aggressive)GOLD 5-MIN 9×21 EMA (Aggressive Version)
EMA Trend + VWAP Direction + Statistical RSI/MACD Filter
📌 Overview
This strategy is a short-term trend-following system built for GOLD MGC1! on the 5-minute chart.
It uses a combination of:
9/21 EMA momentum cross
50 & 200 EMA trend filters
VWAP directional alignment
Data-driven RSI + MACD histogram filter (for shorts)
Strict time-of-day filters
Statistically optimized SL & TP levels based on average run-up and drawdown
This version represents the highest-performing configuration after analyzing hundreds of trades across a multi-month dataset.
It is designed specifically for manual traders (including prop traders) who must trade themselves and cannot use bots.
📌 Why This Strategy Works
Backtesting revealed several repeatable tendencies in the GOLD 5-minute market:
EMA Trend + VWAP Alignment Increases Win Probability
Trades taken with both EMA structure And VWAP direction had much better follow-through.
Longs → work best when above VWAP and VWAP risingShorts → work best when below VWAP and VWAP falling
This filter alone removed many losing signals.
Shorts Were Bad When RSI > 55 AND MACD Histogram Rising
This scenario repeatedly produced:
reduced R-multiple output
shallow follow-through
high likelihood of being squeezed
Filtering out these shorts increased profitability significantly.
3. Certain Hours of the Day Lose Money
The two statistically weakest windows were:
❌ 08:00 EST
❌ 10:00 EST
Removing these increased expectancy without sacrificing win rate.
4. A Fixed 2R Target on Longs + Fixed $161 TP on Shorts
Using the statistical distribution of run-up:
Longs favored ~2R
Shorts favored a fixed TP of $161 per contract (equivalent avg move)
This combination produced the most stable equity curve.
📌 Backtest Summary (Aggressive Version)
(Numbers reflect your exact dataset: Sept 25 – Nov 22)
+8.4% account growth trading a single micro contract
Profit Factor ~ 2.2
~58% win rate
Shallow max drawdown (~1.3%)
Very consistent equity curve
Highest P&L of all strategy variants tested
This version provided the best risk-adjusted performance and the smoothest equity curve, outperforming conservative and hybrid exit versions.
📌 When This Strategy Works Best
Based on verified trade statistics, the strategy performs strongest during:
Best Sessions
⭐ London Session (3–5 AM EST)
⭐ NY Pre-Market (7–8:30 AM EST)
⭐ NY Session Trend Legs (9:30–12:00 PM EST)
Avoid
❌ 8:00 AM EST spike
❌ 10:00 AM EST chop
❌ 16:30–18:00 PM EST session reset
❌ Wild FOMC / CPI / NFP moments unless you turn the strategy off
📌 How Entries Work
You get an entry signal only if:
9 EMA crosses 21 EMA
50 & 200 EMA confirm trend direction
VWAP confirms direction
Not during weak hours
Not during the 16:30–18:00 reset
Shorts pass RSI+MACD filter
Confidence weighting determines position size:
Conf 3 (high confidence) → 2 contracts
Low confidence → 1 contract
📌 Stop Loss & Take Profit Logic
LONGS
Stop = swing low − 3 ticks
Target = 2R
SHORTS
Stop = swing high + 3 ticks
Target = fixed $161 per contract
This TP was statistically verified from average short-run behavior.
📌 Setting Up Alerts (Manual Trader Instructions)
STEP 1 — Use “Order fills & alert() function calls”
In the Create Alert panel:
Condition: GOLD 5MIN — 9×21 EMA Strategy (Aggressive…)
Type: ✔ Order fills & alert() function calls
Interval: Same as chart (5 min)
Expiration: choose a long window (e.g., 6–12 months)
This ensures you receive:
✓ Entry alerts (Long / Short)
✗ No exit alerts unless explicitly coded
📌 What to Put in the Message Box
Use this simple, readable format:
text{{strategy.order.action}}
{{strategy.order.contracts}} contract(s)
@ {{strategy.order.price}}
Position size: {{strategy.position_size}}
You can also include SL / TP if needed:
textEntry: {{strategy.order.price}}
SL: {{plot("stop_level")}}
TP: {{plot("tp_level")}}
(I can wire these into Pine if you'd like.)
📌 How to Use Alerts in a Prop Firm (No Bots Allowed)
When an alert fires:
Open your DOM / order panel
Match the direction (Buy or Sell)
Enter:
* Entry price (market or limit)
* Stop loss at the strategy’s stop level
* Take profit at the displayed TP level
Size
* 1 contract = Low confidence
* 2 contracts = Conf 3
Let the trade run—do not manually override unless platform constraints require it.
This creates a mechanical, rules-based approach without automation, fully compliant with prop firm rules.
📌 Intended Audience
This strategy is ideal for:
✔ Prop traders (TP Trader, Apex, Topstep)
Manual execution only—no bots required.
✔ Intraday gold traders
Those who want a rules-based, statistically proven, trend-following micro futures system.
✔ New systematic traders
Clear logic, easy visuals, simple alerts.
📌 Final Notes
This script is the product of:
data-driven optimization
hundreds of trades
removal of low-probability behavior
strict adherence to verifiable edges
It is not curve-fit—all rules are independently validated via:
distribution analysis
time-of-day heatmaps
indicator correlation
run-up/drawdown buckets
This makes it robust enough for prop evaluation trading and real capital deployment.
— ASALEH2297
Trend ProTrend Pro is a volatility-adaptive trend and momentum system designed for scalping, day trading, and short-term swing trading.
It uses an ATR-based dynamic trend line (Alpha-Trend style) to identify momentum shifts and confirm directional strength.
Unlike traditional moving averages, Trend Pro adapts to volatility and reacts faster during expansions while filtering noise during chop.
🔍 How Trend Pro Works
Trend Pro builds a dynamic volatility channel using ATR and tracks whether price stays above or below this adaptive line.
When price crosses and closes on the opposite side, it suggests a shift in market control.
When price closes above the line → the trend turns BULLISH (green)
When price closes below the line → the trend turns BEARISH (red)
This gives a clear, visual trend state without repainting.
Tips for Best Performance:
✔ Avoid signals directly inside major ranges or sideways chop
✔ Strongest entries come after small pullbacks into the line
✔ Combine signals with:
Market structure
Key swing highs/lows
Liquidity sweeps
Session timing (NYSE open, power hour)
✔ Trend Pro works best when used with the trend, not counter-trend
Enjoy!
Multi Timeframe Bollinger Bands Spectrum [Ata]Multi-Timeframe Bollinger Bands Spectrum
Technical Overview
This script integrates multi-timeframe volatility analysis with volume-derived order flow estimation. By combining Bollinger Bands (statistical deviation) with internal candle volume logic, the indicator qualifies price movements to differentiate between sustained trends, reversals, and exhaustion events.
The system is designed to provide a structural context for price action, visualizing market regimes through a dual-zone spectrum and filtering signals based on the interaction between price location and specific volume thresholds.
Core Logic & Calculation
1. Volume Decomposition Algorithm
Instead of using total volume, the script estimates Buying Pressure vs. Selling Pressure based on the close position relative to the candle's High/Low range:
- Buying Volume (vb): Increases as the close approaches the High.
- Selling Volume (vs): Increases as the close approaches the Low.
This logic allows the detection of directional flow even within standard volume bars.
2. Statistical Spectrum
The indicator renders deviations from the Basis (SMA) as two distinct zones:
- Bullish Zone (Blue): Price positioning between the Basis and Upper Band.
- Bearish Zone (Red): Price positioning between the Basis and Lower Band.
This structure is applied across multiple timeframes (overlay) to visualize the macro trend context without noise.
3. Non-Repainting Execution
To ensure historical accuracy and reliability for backtesting, all higher-timeframe data is requested using "lookahead_off". Signals are confirmed only upon the closure of the respective timeframe's candle.
Signal Definitions
Signals are generated only when specific Volatility and Volume conditions intersect:
Reversal Setups (Reaction to Liquidity)
- WALL: Triggered when price rejects the Upper Band accompanied by Extreme Selling Volume (vs > Limit). This suggests active limit sell orders absorbing the rally.
- FLOOR: Triggered when price rejects the Lower Band accompanied by Extreme Buying Volume (vb > Limit). This suggests active limit buy orders absorbing the drop.
- ABSORP: Identifies absorption near the lower bands where selling pressure is met with passive buying (indicated by lower wicks and relative buy volume).
Momentum Setups (Trend Continuation)
- POWER: Validates a breakout above the Upper Band only if supported by Dominant Buying Volume and a strong candle body.
- PANIC: Validates a breakdown below the Lower Band only if supported by Dominant Selling Volume.
- TRAP: Marks failed breakouts where price exits the bands but volume analysis contradicts the move (e.g., low directional volume).
Exhaustion Setups (Statistical Extremes)
- CLIMAX/CRASH: Identifies anomalies where price deviates significantly from the mean (Extreme Deviation) or when volume reaches unsustainable levels relative to the average, often preceding a mean reversion.
Input Parameters
- Bollinger Logic: Configuration for Length and Standard Deviation Multiplier.
- Volume Thresholds: Adjustable factors for Minimum Volume (Trend) and Extreme Volume (Reversal/Climax).
- Timeframe Layers: Toggle visibility for up to 5 higher timeframes.
- Theme: Adjusts label contrast for Dark/Light backgrounds.
Disclaimer
This indicator is strictly for analytical purposes. It provides a visualization of past market data based on statistical and volumetric formulas. Users should apply their own risk management protocols.
Supply and Demand Zones [Clean v6]Supply and Demand Zones
Overview
The Supply and Demand Zones indicator is an automated market structure tool designed to identify high-probability Points of Interest (POI) on any asset or timeframe. Built using Pine Script v6, this script focuses on clarity and performance, providing traders with a clutter-free view of where institutional buying and selling pressure has previously occurred.
Unlike crowded indicators that overwhelm the chart, this script dynamically manages zones—drawing new ones as structure forms and automatically removing invalid zones as price breaks through them.
Key Features
Automated Zone Detection: Automatically identifies Supply (Resistance) and Demand (Support) zones based on Swing Highs and Swing Lows.
Dynamic Zone Management: Active zones extend to the right until price interacts with them.
Break of Structure (BOS) Logic: When price violates a zone (closes beyond the invalidation level), the zone is automatically removed and marked as "Broken" to keep the chart clean.
Zig Zag Structure: Includes an optional Zig Zag overlay to visualize market flow, Higher Highs, and Lower Lows.
ATR-Based Sizing: Zone width is calculated using the Average True Range (ATR), ensuring zones adapt to the asset's current volatility.
Pine Script v6: Optimized using the latest array and method functions for speed and stability.
How It Works
Zone Creation: The script looks for Pivot Highs and Lows based on your defined Swing Length.
Supply Zones (Red): Created at Swing Highs.
Demand Zones (Blue): Created at Swing Lows.
Zone Width: The height of the box is determined by the ATR multiplied by your Zone Width setting. This ensures the zone covers the "wick" area or the volatility range of the pivot.
Invalidation: If the price closes past the outer edge of a zone (the top of a Supply zone or bottom of a Demand zone), the script detects a break, removes the filled box, and leaves a subtle trace of the broken structure.
How to Use
Trend Following: Use the Zig Zag lines to identify the trend direction. Look for Long entries in Demand zones during an uptrend, and Short entries in Supply zones during a downtrend.
Reversals: Watch for price to react at older, unfilled zones (POIs) that align with major support/resistance levels.
Stop Loss Placement: The outer edge of the zone acts as a natural invalidation point. If price closes beyond it, the setup is typically invalidated.
Settings Guide
Swing Length: Determines the sensitivity of the pivot detection. Lower numbers find more local zones (scalping); higher numbers find major structural zones (swing trading).
Max Zones to Keep: Limits the number of historic zones displayed to prevent chart clutter.
Zone Width (ATR): Adjusts how thick the zones are. Increase this value if you want to capture wider wicks.
Visual Settings: Fully customizable colors for Supply, Demand, Borders, and Zig Zag lines.
Disclaimer
This tool is for informational and educational purposes only. It visualizes past price action and does not guarantee future performance. Always manage your risk appropriately.
Fib and Slope Trend Detector [EWT] + MTF Dashboard🚀 Overview
The Momentum Structure Trend Detector is a sophisticated trend-following tool that combines Price Velocity (Slope) with Market Structure (Fibonacci) to identify high-probability trend reversals and continuations.
Unlike traditional indicators that rely heavily on lagging moving averages, this script analyzes the speed of price action in real-time. It operates on the core principle of market structure: Impulse moves are fast and steep, while corrections are slow and shallow.
🧠 The Logic: Physics Meets Market Structure
This indicator determines the trend direction by calculating the Slope (Velocity) of price swings.
ZigZag Calculation: It first identifies market swings (Highs and Lows) using a standard pivot detection algorithm.
Slope Calculation: It calculates the velocity of every completed leg using the formula: $Slope = \frac{|Price Change|}{|Time Duration|}$.
Trend Definition:
Uptrend : If the previous Up-move was fast (Impulse) and the subsequent Down-move is slower (Correction), the market is primed for an uptrend.
Downtrend : If the previous Down-move was fast (Impulse) and the subsequent Up-move is slower (Correction), the market is primed for a downtrend.
🔥 Key Features
1. Aggressive Real-Time Detection (No Lag)
Most structure indicators wait for a "Higher High" to confirm a trend, which often leads to late entries. This script uses an Aggressive Live Slope calculation:
It compares the current developing slope of the live price action against the slope of the previous completed leg.
Result: As soon as the current move becomes "steeper" (faster) than the previous correction, the trend flips immediately. This allows you to catch the "meat" of the move before a new pivot is even confirmed.
2. Fibonacci Validity Filter
Momentum alone isn't enough; we need structural integrity.
The script calculates the 78.6% Retracement level of the impulse leg.
If a correction moves deeper than this Fibonacci limit (on a closing basis), the trend structure is considered "broken" or "invalid," and the indicator switches to a Neutral state. This filters out choppy/ranging markets.
3. Multi-Timeframe (MTF) Dashboard
A customizable dashboard on the chart allows for fractal analysis. You can view the trend state (UP/DOWN/NEUTRAL) across 9 different timeframes (1m to 1M) simultaneously.
Green Row : Uptrend
Red Row : Downtrend
Gray : Neutral/Indeterminate
4. Smart Visuals
Background Colo r: Changes dynamically (Teal for Bullish, Red for Bearish, Gray for Neutral) to give you an instant read of the market state.
Slope Labels : Displays the calculated numeric slope on the chart, helping you visualize the momentum difference between impulse and corrective waves.
Invalidation Levels : Automatically plots the invalidation line (Stop Loss level) based on the market structure.
🛠️ Settings & Inputs
Strategy Settings
Pivot Deviation Length : Sensitivity of the ZigZag calculation (Default: 5). Lower numbers = more sensitive to small swings.
Max Retracement % : The Fibonacci limit for a valid correction (Default: 78.6%).
Min Bars for Live Calc : To prevent noise, the script waits for this many bars after a pivot before calculating the "Live Slope" (Default: 3).
Dashboard Settings
Show Dashboard : Toggle the table on/off.
Timeframe Toggles : Enable/Disable specific timeframes (1m, 5m, 15m, 30m, 1H, 4H, 1D, 1W, 1M) to suit your trading style.
🎯 How to Use
Wait for Background Change : When the background turns Teal, it indicates that a corrective pullback has ended and a new impulse with high velocity has begun.
Check Invalidation : Look at the plotted Stop Loss Level. If price closes below this line, the trade idea is invalid.
Confirm with Dashboard : Use the table to ensure the higher timeframes (e.g., 1H, 4H) align with your current chart's direction for higher probability setups.
Disclaimer : This tool is designed for trend analysis and educational purposes. Past performance (momentum) is not indicative of future results. Always manage your risk.
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.
🔶 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)
🔶 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
🔶 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.
🔶 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.
🔶 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.
🔶 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
🔶 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.
🔶 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.
🔶 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.
🔶 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.
🔶 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.
Static K-means Clustering | InvestorUnknownStatic K-Means Clustering is a machine-learning-driven market regime classifier designed for traders who want a data-driven structure instead of subjective indicators or manually drawn zones.
This script performs offline (static) K-means training on your chosen historical window. Using four engineered features:
RSI (Momentum)
CCI (Price deviation / Mean reversion)
CMF (Money flow / Strength)
MACD Histogram (Trend acceleration)
It groups past market conditions into K distinct clusters (regimes). After training, every new bar is assigned to the nearest cluster via Euclidean distance in 4-dimensional standardized feature space.
This allows you to create models like:
Regime-based long/short filters
Volatility phase detectors
Trend vs. chop separation
Mean-reversion vs. breakout classification
Volume-enhanced money-flow regime shifts
Full machine-learning trading systems based solely on regimes
Note:
This script is not a universal ML strategy out of the box.
The user must engineer the feature set to match their trading style and target market.
K-means is a tool, not a ready made system, this script provides the framework.
Core Idea
K-means clustering takes raw, unlabeled market observations and attempts to discover structure by grouping similar bars together.
// STEP 1 — DATA POINTS ON A COORDINATE PLANE
// We start with raw, unlabeled data scattered in 2D space (x/y).
// At this point, nothing is grouped—these are just observations.
// K-means will try to discover structure by grouping nearby points.
//
// y ↑
// |
// 12 | •
// | •
// 10 | •
// | •
// 8 | • •
// |
// 6 | •
// |
// 4 | •
// |
// 2 |______________________________________________→ x
// 2 4 6 8 10 12 14
//
//
//
// STEP 2 — RANDOMLY PLACE INITIAL CENTROIDS
// The algorithm begins by placing K centroids at random positions.
// These centroids act as the temporary “representatives” of clusters.
// Their starting positions heavily influence the first assignment step.
//
// y ↑
// |
// 12 | •
// | •
// 10 | • C2 ×
// | •
// 8 | • •
// |
// 6 | C1 × •
// |
// 4 | •
// |
// 2 |______________________________________________→ x
// 2 4 6 8 10 12 14
//
//
//
// STEP 3 — ASSIGN POINTS TO NEAREST CENTROID
// Each point is compared to all centroids.
// Using simple Euclidean distance, each point joins the cluster
// of the centroid it is closest to.
// This creates a temporary grouping of the data.
//
// (Coloring concept shown using labels)
//
// - Points closer to C1 → Cluster 1
// - Points closer to C2 → Cluster 2
//
// y ↑
// |
// 12 | 2
// | 1
// 10 | 1 C2 ×
// | 2
// 8 | 1 2
// |
// 6 | C1 × 2
// |
// 4 | 1
// |
// 2 |______________________________________________→ x
// 2 4 6 8 10 12 14
//
// (1 = assigned to Cluster 1, 2 = assigned to Cluster 2)
// At this stage, clusters are formed purely by distance.
Your chosen historical window becomes the static training dataset , and after fitting, the centroids never change again.
This makes the model:
Predictable
Repeatable
Consistent across backtests
Fast for live use (no recalculation of centroids every bar)
Static Training Window
You select a period with:
Training Start
Training End
Only bars inside this range are used to fit the K-means model. This window defines:
the market regime examples
the statistical distributions (means/std) for each feature
how the centroids will be positioned post-trainin
Bars before training = fully transparent
Training bars = gray
Post-training bars = full colored regimes
Feature Engineering (4D Input Vector)
Every bar during training becomes a 4-dimensional point:
This combination balances: momentum, volatility, mean-reversion, trend acceleration giving the algorithm a richer "market fingerprint" per bar.
Standardization
To prevent any feature from dominating due to scale differences (e.g., CMF near zero vs CCI ±200), all features are standardized:
standardize(value, mean, std) =>
(value - mean) / std
Centroid Initialization
Centroids start at diverse coordinates using various curves:
linear
sinusoidal
sign-preserving quadratic
tanh compression
init_centroids() =>
// Spread centroids across using different shapes per feature
for c = 0 to k_clusters - 1
frac = k_clusters == 1 ? 0.0 : c / (k_clusters - 1.0) // 0 → 1
v = frac * 2 - 1 // -1 → +1
array.set(cent_rsi, c, v) // linear
array.set(cent_cci, c, math.sin(v)) // sinusoidal
array.set(cent_cmf, c, v * v * (v < 0 ? -1 : 1)) // quadratic sign-preserving
array.set(cent_mac, c, tanh(v)) // compressed
This makes initial cluster spread “random” even though true randomness is hardly achieved in pinescript.
K-Means Iterative Refinement
The algorithm repeats these steps:
(A) Assignment Step, Each bar is assigned to the nearest centroid via Euclidean distance in 4D:
distance = sqrt(dx² + dy² + dz² + dw²)
(B) Update Step, Centroids update to the mean of points assigned to them. This repeats iterations times (configurable).
LIVE REGIME CLASSIFICATION
After training, each new bar is:
Standardized using the training mean/std
Compared to all centroids
Assigned to the nearest cluster
Bar color updates based on cluster
No re-training occurs. This ensures:
No lookahead bias
Clean historical testing
Stable regimes over time
CLUSTER BEHAVIOR & TRADING LOGIC
Clusters (0, 1, 2, 3…) hold no inherent meaning. The user defines what each cluster does.
Example of custom actions:
Cluster 0 → Cash
Cluster 1 → Long
Cluster 2 → Short
Cluster 3+ → Cash (noise regime)
This flexibility means:
One trader might have cluster 0 as consolidation.
Another might repurpose it as a breakout-loading zone.
A third might ignore 3 clusters entirely.
Example on ETHUSD
Important Note:
Any change of parameters or chart timeframe or ticker can cause the “order” of clusters to change
The script does NOT assume any cluster equals any actionable bias, user decides.
PERFORMANCE METRICS & ROC TABLE
The indicator computes average 1-bar ROC for each cluster in:
Training set
Test (live) set
This helps measure:
Cluster profitability consistency
Regime forward predictability
Whether a regime is noise, trend, or reversion-biased
EQUITY SIMULATION & FEES
Designed for close-to-close realistic backtesting.
Position = cluster of previous bar
Fees applied only on regime switches. Meaning:
Staying long → no fee
Switching long→short → fee applied
Switching any→cash → fee applied
Fee input is percentage, but script already converts internally.
Disclaimers
⚠️ This indicator uses machine-learning but does not predict the future. It classifies similarity to past regimes, nothing more.
⚠️ Backtest results are not indicative of future performance.
⚠️ Clusters have no inherent “bullish” or “bearish” meaning. You must interpret them based on your testing and your own feature engineering.
🔥 SMC Reversal Engine v3.5 – Clean FVG + DashboardSMC Reversal Engine v3.5 – Clean FVG + Dashboard
The SMC Reversal Engine is a precision-built Smart Money Concepts tool designed to help traders understand market structure the single most important foundation in reading price action. It reveals how institutions move liquidity, where structure shifts occur, and how Fair Value Gaps (FVGs) align with these changes to signal potential reversals or continuations.
Understanding How It Works
At its core, the script detects CHoCH (Change of Character) and BOS (Break of Structure)—the two key turning points in institutional order flow. A CHoCH shows that the market has reversed intent (for example, from bearish to bullish), while a BOS confirms a continuation of the current trend. Together, they form the backbone of structure-based trading.
To refine this logic, the engine uses fractal pivots clusters of candles that confirm swing highs and lows. Fractals filter out noise, identifying points where price truly changes direction. The script lets you set this sensitivity manually or automatically adapts it depending on the timeframe. Lower fractal sensitivity captures smaller intraday swings for scalpers, while higher sensitivity locks onto major swing structures for swing and position traders.
The dashboard gives you a real-time reading of the trend, the last high and low, and what the market is likely to do next—for example, “Expect HL” or “Wait for LH.” It even tracks the accuracy of these structure predictions over time, giving an educational feedback loop to help you learn price behavior.
Fair Value Gaps and Tap Entries
Fair Value Gaps (FVGs) mark moments when price moves too quickly, leaving inefficiencies that institutions often revisit. When price taps into an FVG, it often acts as a high-probability entry zone for reversals or continuations. The script automatically detects, extends, and deletes old FVGs, keeping only relevant zones visible for a clean chart.
Traders can enable markTapEntry to visually confirm when an FVG gets filled. This is a simple but powerful trigger that often aligns with CHoCH or BOS moments.
Recommended Settings for Different Traders
For Scalpers, use a lower HTF structure such as 1 minute or 5 minutes. Keep Auto Fractals on for faster reaction, and limit FVG zones to 2–3. This gives you a clean, real-time reflection of order flow.
For Intraday Traders, 15-minute to 1-hour structure gives the perfect balance between reactivity and stability. Fractal sensitivity around 3–5 captures the most actionable levels without excessive noise.
For Swing Traders, use 4-hour, 1-day, or even 3-day structure. The chart becomes smoother, showing higher-order CHoCH and BOS that define true institutional transitions. Combine this with EMA confirmation for higher conviction.
For Position or Macro Traders, select Weekly or Monthly structure. The dynamic label system expands automatically to keep more historical BOS/CHoCH points visible, allowing you to see long-term shifts clearly.
Educational Value
This indicator is built to teach traders how to see structure the way professionals and smart money do. You’ll learn to recognize how markets transition from one phase to another from accumulation to manipulation to expansion. Each CHoCH or BOS helps you decode where liquidity is being taken and where new intent begins.
The included SMC Quick Guide explains each structural cue right on your chart. Within days of using it, you’ll start noticing patterns that reveal how price really moves, instead of guessing based on indicators.
Settings and How to Use Them
Everything in the SMC Reversal Engine is designed to adapt to your trading style and help you read structure like a professional.
When you open the Inputs Panel, you’ll see sections like Fractal Settings, FVG Settings, Buy/Sell Confirmation, and Educational Tools.
Under Fractal Settings, you can choose the higher timeframe (HTF) that defines structure—from minutes to weeks. The Auto Fractal Sensitivity option automatically adjusts how tight or wide swing points are detected. Lower sensitivity captures short-term fluctuations (great for scalpers), while higher values filter noise and isolate major swing highs and lows (perfect for swing traders).
The Fair Value Gap (FVG) options manage imbalance zones—the footprints of institutional orders. You can show or hide these zones, extend them into the future, and control how long they remain before auto-deletion. The Mark Entry When FVG is Tapped option places a small label when price revisits the gap—a potential entry signal that aligns with smart money logic.
EMA Confirmation adds a layer of confluence. The script can automatically scale EMA lengths based on timeframe, or you can input your preferred values (for example, 9/21 for intraday, 50/200 for swing). Require EMA Crossover Confirmation helps filter false moves, keeping you trading only with aligned momentum.
The Educational section gives traders visual reinforcement. When enabled, you’ll see tags like HH (Higher High), HL (Higher Low), LH (Lower High), and LL (Lower Low). These show structure shifts in real time, helping you learn visually what market structure really means. The Cheat Sheet panel summarizes each term, always visible in the corner for quick reference.
Early Top Warnings use wick size and RSI divergence to signal when price may be overextended—a useful heads-up before potential CHoCH formations.
Finally, the Narrative and Accuracy System translates structure into simple English—messages like Trend Bullish → Wait for HL or BOS Bearish → Expect LL. Over time, you can monitor how accurate these expectations have been, training your pattern recognition and confidence.
Pro Tips for Getting the Most Out of the SMC Reversal Engine
1. Start on Higher Timeframes First: Begin on the 4H or Daily chart where structure is cleaner and signals have more weight. Then scale down for entries once you grasp directional intent.
2. Use FVGs for Context, Not Just Entries: Observe how price behaves around unfilled FVGs—they often act as magnets or barriers, offering insight into where liquidity lies.
3. Combine With HTF Bias: Always trade in the direction of your higher timeframe trend. A bullish weekly BOS means lower timeframes should ideally align bullishly for optimal setups.
4. Clean Charts = Clear Mind: Use Minimal Mode when focusing on price action, then toggle the educational tools back on to review structure for learning.
5. Don’t Chase Every CHoCH or BOS: Focus on significant breaks that align with broader context and liquidity sweeps, not minor fluctuations.
6. Accuracy Rate Is a Feedback Tool: Use the accuracy stat as a reflection of consistency—not a trade trigger.
7. Build Narrative Awareness: Read the on-chart narrative messages to reinforce structured thinking and stay disciplined.
8. Practice Replay Mode: Step through past structures to visually connect CHoCH, BOS, and FVG behavior. It’s one of the best ways to train pattern recognition.
Summary
* Detects CHoCH and BOS automatically with fractal precision
* Identifies and manages Fair Value Gaps (FVGs) in real time
* Displays a smart dashboard with accuracy tracking
* Adapts label visibility dynamically by timeframe
* Perfect for both learning and trading with institutional clarity
This tool isn’t about predicting the market—it’s about understanding it. Once you can read structure, everything else in trading becomes secondary.
Flux-Tensor Singularity [FTS]Flux-Tensor Singularity - Multi-Factor Market Pressure Indicator
The Flux-Tensor Singularity (FTS) is an advanced multi-factor oscillator that combines volume analysis, momentum tracking, and volatility-weighted normalization to identify critical market inflection points. Unlike traditional single-factor indicators, FTS synthesizes price velocity, volume mass, and volatility context into a unified framework that adapts to changing market regimes.
This indicator identifies extreme market conditions (termed "singularities") where multiple confirming factors converge, then uses a sophisticated scoring system to determine directional bias. It is designed for traders seeking high-probability setups with built-in confluence requirements.
THEORETICAL FOUNDATION
The indicator is built on the premise that market time is not constant - different market conditions contain varying levels of information density. A 1-minute bar during a major news event contains far more actionable information than a 1-minute bar during overnight low-volume trading. Traditional indicators treat all bars equally; FTS does not.
The theoretical framework draws conceptual parallels to physics (purely as a mental model, not literal physics):
Volume as Mass: Large volume represents significant market participation and "weight" behind price moves. Just as massive objects have stronger gravitational effects, high-volume moves carry more significance.
Price Change as Velocity: The rate of price movement through price space represents momentum and directional force.
Volatility as Time Dilation: When volatility is high relative to its historical norm, the "information density" of each bar increases. The indicator weights these periods more heavily, similar to how time dilates near massive objects in physics.
This is a pedagogical metaphor to create a coherent mental model - the underlying mathematics are standard financial calculations combined in a novel way.
MATHEMATICAL FRAMEWORK
The indicator calculates a composite singularity value through four distinct steps:
Step 1: Raw Singularity Calculation
S_raw = (ΔP × V) × γ²
Where:
ΔP = Price Velocity = close - close
V = Volume Mass = log(volume + 1)
γ² = Time Dilation Factor = (ATR_local / ATR_global)²
Volume Transformation: Volume is log-transformed because raw volume can have extreme outliers (10x-100x normal). The logarithm compresses these spikes while preserving their significance. This is standard practice in volume analysis.
Volatility Weighting: The ratio of short-term ATR (5 periods) to long-term ATR (user-defined lookback) is squared to create a volatility amplification factor. When local volatility exceeds global volatility, this ratio increases, amplifying the raw singularity value. This makes the indicator regime-aware.
Step 2: Normalization
The raw singularity values are normalized to a 0-100 scale using a stochastic-style calculation:
S_normalized = ((S_raw - S_min) / (S_max - S_min)) × 100
Where S_min and S_max are the lowest and highest raw singularity values over the lookback period.
Step 3: Epsilon Compression
S_compressed = 50 + ((S_normalized - 50) / ε)
This is the critical innovation that makes the sensitivity control functional. By applying compression AFTER normalization, the epsilon parameter actually affects the final output:
ε < 1.0: Expands range (more signals)
ε = 1.0: No change (default)
ε > 1.0: Compresses toward 50 (fewer, higher-quality signals)
For example, with ε = 2.0, a normalized value of 90 becomes 70, making threshold breaches rarer and more significant.
Step 4: Smoothing
S_final = EMA(S_compressed, smoothing_period)
An exponential moving average removes high-frequency noise while preserving trend.
SIGNAL GENERATION LOGIC
When the tensor crosses above the upper threshold (default 90) or below the lower threshold (default 10), an extreme event is detected. However, the indicator does NOT immediately generate a buy or sell signal. Instead, it analyzes market context through a multi-factor scoring system:
Scoring Components:
Price Structure (+1 point): Current bar bullish/bearish
Momentum (+1 point): Price higher/lower than N bars ago
Trend Context (+2 points): Fast EMA above/below slow EMA (weighted heavier)
Acceleration (+1 point): Rate of change increasing/decreasing
Volume Multiplier (×1.5): If volume > average, multiply score
The highest score (bullish vs bearish) determines signal direction. This prevents the common indicator failure mode of "overbought can stay overbought" by requiring directional confirmation.
Signal Conditions:
A BUY signal requires:
Extreme event detection (tensor crosses threshold)
Bullish score > Bearish score
Price confirmation: Bullish candle (optional, user-controlled)
Volume confirmation: Volume > average (optional, user-controlled)
Momentum confirmation: Positive momentum (optional, user-controlled)
A SELL signal requires the inverse conditions.
INPUTS EXPLAINED - Core Parameters:
Global Horizon (Context): Default 20. Lookback period for normalization and volatility comparison. Higher values = smoother but less responsive. Lower values = more signals but potentially more noise.
Tensor Smoothing: Default 3. EMA period applied to final output. Removes "quantum foam" (high-frequency noise). Range 1-20.
Singularity Threshold: Default 90. Values above this (or below 100-threshold) trigger extreme event detection. Higher = rarer, stronger signals.
Signal Sensitivity (Epsilon): Default 1.0. Post-normalization compression factor. This is the key innovation - it actually works because it's applied AFTER normalization. Range 0.1-5.0.
Signal Interpreter Toggles:
Require Price Confirmation: Default ON. Only generates buy signals on bullish candles, sell signals on bearish candles. Reduces false signals but may delay entry.
Require Volume Confirmation: Default ON. Only signals when volume > average. Critical for stocks/crypto, less important for forex (unreliable volume data).
Use Momentum Filter: Default ON. Requires momentum agreement with signal direction. Prevents counter-trend signals.
Momentum Lookback: Default 5. Number of bars for momentum calculation. Shorter = more responsive, longer = trend-following bias.
Visual Controls:
Colors: Customizable colors for bullish flux, bearish flux, background, and event horizon.
Visual Transparency: Default 85. Master control for all visual elements (accretion disk, field lines, particles, etc.). Range 50-99. Signals and dashboard have separate controls.
Visibility Toggles: Individual on/off switches for:
Gravitational field lines (trend EMAs)
Field reversals (trend crossovers)
Accretion disk (background gradient)
Singularity diamonds (neutral extreme events)
Energy particles (volume bursts)
Event horizon flash (extreme event background)
Signal background flash
Signal Size: Tiny/Small/Normal triangle size
Signal Offsets: Separate controls for buy and sell signal vertical positioning (percentage of price)
Dashboard Settings:
Show Dashboard: Toggle on/off
Position: 9 placement options (all corners, centers, middles)
Text Size: Tiny/Small/Normal/Large
Background Transparency: 0-50, separate from visual transparency
VISUAL ELEMENTS EXPLAINED
1. Accretion Disk (Background Gradient):
A three-layer gradient background that intensifies as the tensor approaches extremes. The outer disk appears at any non-neutral reading, the inner disk activates above 70 or below 30, and the core layer appears above 85 or below 15. Color indicates direction (cyan = bullish, red = bearish). This provides instant visual feedback on market pressure intensity.
2. Gravitational Field Lines (EMAs):
Two trend-following EMAs (10 and 30 period) visualized as colored lines. These represent the "curvature" of market trend - when they diverge, trend is strong; when they converge, trend is weakening. Crossovers mark potential trend reversals.
3. Field Reversals (Circles):
Small circles appear when the fast EMA crosses the slow EMA, indicating a potential trend change. These are distinct from extreme events and appear at normal market structure shifts.
4. Singularity Diamonds:
Small diamond shapes appear when the tensor reaches extreme levels (>90 or <10) but doesn't meet the full signal criteria. These are "watch" events - extreme pressure exists but directional confirmation is lacking.
5. Energy Particles (Dots):
Tiny dots appear when volume exceeds 2× average, indicating significant participation. Color matches bar direction. These highlight genuine high-conviction moves versus low-volume drifts.
6. Event Horizon Flash:
A golden background flash appears the instant any extreme threshold is breached, before directional analysis. This alerts you to pay attention.
7. Signal Background Flash:
When a full buy/sell signal is confirmed, the background flashes cyan (buy) or red (sell). This is your primary alert that all conditions are met.
8. Signal Triangles:
The actual buy (▲) and sell (▼) markers. These only appear when ALL selected confirmation criteria are satisfied. Position is offset from bars to avoid overlap with other indicators.
DASHBOARD METRICS EXPLAINED
The dashboard displays real-time calculated values:
Event Density: Current tensor value (0-100). Above 90 or below 10 = critical. Icon changes: 🔥 (extreme high), ❄️ (extreme low), ○ (neutral).
Time Dilation (γ): Current volatility ratio squared. Values >2.0 indicate extreme volatility environments. >1.5 = elevated, >1.0 = above average. Icon: ⚡ (extreme), ⚠ (elevated), ○ (normal).
Mass (Vol): Log-transformed volume value. Compared to volume ratio (current/average). Icon: ● (>2× avg), ◐ (>1× avg), ○ (below avg).
Velocity (ΔP): Raw price change. Direction arrow indicates momentum direction. Shows the actual price delta value.
Bullish Flux: Current bullish context score. Displayed as both a bar chart (visual) and numeric value. Brighter when bullish score dominates.
Bearish Flux: Current bearish context score. Same visualization as bullish flux. These scores compete - the winner determines signal direction.
Field: Trend direction based on EMA relationship. "Repulsive" (uptrend), "Attractive" (downtrend), "Neutral" (ranging). Icon: ⬆⬇↔
State: Current market condition:
🚀 EJECTION: Buy signal active
💥 COLLAPSE: Sell signal active
⚠ CRITICAL: Extreme event, no directional confirmation
● STABLE: Normal market conditions
HOW TO USE THE INDICATOR
1. Wait for Extreme Events:
The indicator is designed to be selective. Don't trade every fluctuation - wait for tensor to reach >90 or <10. This alone is not a signal.
2. Check Context Scores:
Look at the Bullish Flux vs Bearish Flux in the dashboard. If scores are close (within 1-2 points), the market is indecisive - skip the trade.
3. Confirm with Signals:
Only act when a full triangle signal appears (▲ or ▼). This means ALL your selected confirmation criteria have been met.
4. Use with Price Structure:
Combine with support/resistance levels. A buy signal AT support is higher probability than a buy signal in the middle of nowhere.
5. Respect the Dashboard State:
When State shows "CRITICAL" (⚠), it means extreme pressure exists but direction is unclear. These are the most dangerous moments - wait for resolution.
6. Volume Matters:
Energy particles (dots) and the Mass metric tell you if institutions are participating. Signals without volume confirmation are lower probability.
MARKET AND TIMEFRAME RECOMMENDATIONS
Scalping (1m-5m):
Lookback: 10-14
Smoothing: 5-7
Threshold: 85
Epsilon: 0.5-0.7
Note: Expect more noise. Confirm with Level 2 data. Best on highly liquid instruments.
Intraday (15m-1h):
Lookback: 20-30 (default settings work well)
Smoothing: 3-5
Threshold: 90
Epsilon: 1.0
Note: Sweet spot for the indicator. High win rate on liquid stocks, forex majors, and crypto.
Swing Trading (4h-1D):
Lookback: 30-50
Smoothing: 3
Threshold: 90-95
Epsilon: 1.5-2.0
Note: Signals are rare but high conviction. Combine with higher timeframe trend analysis.
Position Trading (1D-1W):
Lookback: 50-100
Smoothing: 5-7
Threshold: 95
Epsilon: 2.0-3.0
Note: Extremely rare signals. Only trade the most extreme events. Expect massive moves.
Market-Specific Settings:
Forex (EUR/USD, GBP/USD, etc.):
Volume data is unreliable (spot forex has no centralized volume)
Disable "Require Volume Confirmation"
Focus on momentum and trend filters
News events create extreme singularities
Best on 15m-1h timeframes
Stocks (High-Volume Equities):
Volume confirmation is CRITICAL - keep it ON
Works excellently on AAPL, TSLA, SPY, etc.
Morning session (9:30-11:00 ET) shows highest event density
Earnings announcements create guaranteed extreme events
Best on 5m-1h for day trading, 1D for swing trading
Crypto (BTC, ETH, major alts):
Reduce threshold to 85 (crypto has constant high volatility)
Volume spikes are THE primary signal - keep volume confirmation ON
Works exceptionally well due to 24/7 trading and high volatility
Epsilon can be reduced to 0.7-0.8 for more signals
Best on 15m-4h timeframes
Commodities (Gold, Oil, etc.):
Gold responds to macro events (Fed announcements, geopolitical events)
Oil responds to supply shocks
Use daily timeframe minimum
Increase lookback to 50+
These are slow-moving markets - be patient
Indices (SPX, NDX, etc.):
Institutional volume matters - keep volume confirmation ON
Opening hour (9:30-10:30 ET) = highest singularity probability
Strong correlation with VIX - high VIX = more extreme events
Best on 15m-1h for day trading
WHAT MAKES THIS INDICATOR UNIQUE
1. Post-Normalization Sensitivity Control:
Unlike most oscillators where sensitivity controls don't actually work (they're applied before normalization, which then rescales everything), FTS applies epsilon compression AFTER normalization. This means the sensitivity parameter genuinely affects signal frequency. This is a novel implementation not found in standard oscillators.
2. Multi-Factor Confluence Requirement:
The indicator doesn't just detect "overbought" or "oversold" - it detects extreme conditions AND THEN analyzes context through five separate factors (price structure, momentum, trend, acceleration, volume). Most indicators are single-factor; FTS requires confluence.
3. Volatility-Weighted Normalization:
By squaring the ATR ratio (local/global), the indicator adapts to changing market regimes. A 1% move in a low-volatility environment is treated differently than a 1% move in a high-volatility environment. Traditional indicators treat all moves equally regardless of context.
4. Volume Integration at the Core:
Volume isn't an afterthought or optional filter - it's baked into the fundamental equation as "mass." The log transformation handles outliers elegantly while preserving significance. Most price-based indicators completely ignore volume.
5. Adaptive Scoring System:
Rather than fixed buy/sell rules ("RSI >70 = sell"), FTS uses competitive scoring where bullish and bearish evidence compete. The winner determines direction. This solves the classic problem of "overbought markets can stay overbought during strong uptrends."
6. Comprehensive Visual Feedback:
The multi-layer visualization system (accretion disk, field lines, particles, flashes) provides instant intuitive feedback on market state without requiring dashboard reading. You can see pressure building before extreme thresholds are hit.
7. Separate Extreme Detection and Signal Generation:
"Singularity diamonds" show extreme events that don't meet full criteria, while "signal triangles" only appear when ALL conditions are met. This distinction helps traders understand when pressure exists versus when it's actionable.
COMPARISON TO EXISTING INDICATORS
vs. RSI/Stochastic:
These normalize price relative to recent range. FTS normalizes (price change × log volume × volatility ratio) - a composite metric, not just price position.
vs. Chaikin Money Flow:
CMF combines price and volume but lacks volatility context and doesn't use adaptive normalization or post-normalization compression.
vs. Bollinger Bands + Volume:
Bollinger Bands show volatility but don't integrate volume or create a unified oscillator. They're separate components, not synthesized.
vs. MACD:
MACD is pure momentum. FTS combines momentum with volume weighting and volatility context, plus provides a normalized 0-100 scale.
The specific combination of log-volume weighting, squared volatility amplification, post-normalization epsilon compression, and multi-factor directional scoring is unique to this indicator.
LIMITATIONS AND PROPER DISCLOSURE
Not a Holy Grail:
No indicator is perfect. This tool identifies high-probability setups but cannot predict the future. Losses will occur. Use proper risk management.
Requires Confirmation:
Best used in conjunction with price action analysis, support/resistance levels, and higher timeframe trend. Don't trade signals blindly.
Volume Data Dependency:
On forex (spot) and some low-volume instruments, volume data is unreliable or tick-volume only. Disable volume confirmation in these cases.
Lagging Components:
The EMA smoothing and trend filters are inherently lagging. In extremely fast moves, signals may appear after the initial thrust.
Extreme Event Rarity:
With conservative settings (high threshold, high epsilon), signals can be rare. This is by design - quality over quantity. If you need more frequent signals, reduce threshold to 85 and epsilon to 0.7.
Not Financial Advice:
This indicator is an analytical tool. All trading decisions and their consequences are solely your responsibility. Past performance does not guarantee future results.
BEST PRACTICES
Don't trade every singularity - wait for context confirmation
Higher timeframes = higher reliability
Combine with support/resistance for entry refinement
Volume confirmation is CRITICAL for stocks/crypto (toggle off only for forex)
During major news events, singularities are inevitable but direction may be uncertain - use wider stops
When bullish and bearish flux scores are close, skip the trade
Test settings on your specific instrument/timeframe before live trading
Use the dashboard actively - it contains critical diagnostic information
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Z-Fusion Oscillator | Lyro RSThe Z-Fusion Oscillator converts five momentum indicators into Z-scores and blends them into one normalized signal that adapts across markets.
By combining normalization, smoothing, and divergence detection, users can easily identify when momentum is accelerating, weakening, reversing, or entering extreme zones
🔶 USAGE
The Z-Fusion Oscillator is designed to give traders a unified reading of market momentum—removing the noise of comparing tools that normally run on different scales.
By transforming RSI, MACD histogram, Stochastic, Momentum, and Rate of Change into Z-scores, this tool standardizes all inputs, making trend strength and shifts easier to interpret.
A dual-line system (fast Z-fusion line + slower baseline) highlights turning points, while overbought/oversold bands and “X-marks” help traders spot exhaustion and potential reversals.
🔹 Unified Momentum Structure
The indicator’s core strength comes from combining five Z-scored signals into one average.
Which makes momentum behavior more consistent across assets, reduces false extremes, and highlights true shifts in trend conviction.
🔹 Divergence Detection
The tool includes fully integrated divergence detection:
Regular Bullish Divergence: Price makes a lower low while Z-Fusion forms a higher low.
Regular Bearish Divergence: Price makes a higher high while Z-Fusion forms a lower high
Bullish and bearish divergences are marked directly on the oscillator with labels and colored pivot connections, making hidden momentum shifts obvious.
🔹 Visual Extremes
Two sets of upper and lower Z-score thresholds help identify:
Extreme overbought surges
Extreme oversold drops
Reversal zones
Potential exhaustion conditions
Background coloring reinforces when the oscillator moves beyond major levels, helping traders quickly assess momentum pressure.
🔹 Detecting Momentum Anomalies
Z-scores allow the oscillator to highlight when market momentum behaves abnormally relative to its own recent history.
For example:
The oscillator reaching +1 or –1 after an extended trend may indicate a climax.
A sharp Z-score reversal within an extreme zone can signal a trend exhaustion or a corrective move.
Divergences often appear earlier due to normalization smoothing out indicator noise.
This makes the Z-Fusion Oscillator particularly useful for spotting subtle shifts in trend direction that traditional indicators may miss.
🔶 DETAILS
🔹 Composite Z-Score Framework
Each momentum tool is smoothed, normalized, and transformed:
RSI → EMA-smoothed, Z-scored
MACD histogram → Z-scored
Stochastic → EMA + SMA smoothing, then Z-scored
Momentum → EMA-smoothed, Z-scored
Rate of Change → EMA-smoothed, Z-scored
These are averaged into one composite Z-score to provide a consistent reading across assets and market conditions.
🔹 Fusion Trend Lines
Two lines serve as the core signal:
Fast Line (savg) – reacts quicker to trend changes
Slow Line (savg2) – acts as a baseline filter
Crossovers between these lines highlight momentum shifts, while their color reflects trend bias.
🔹 Overbought/Oversold Zones
Two upper and two lower Z-score thresholds define “zones”:
Upper zones highlight overheated momentum or potential bearish reversals
Lower zones highlight depressed momentum or potential bullish reversals
Filled regions and background colors help visually confirm extreme conditions.
🔹 Pivot-Based Divergence Engine
The script includes filtered pivot detection with customizable look-backs and range limits to ensure divergences are meaningful, not noise-driven.
🔶 SETTINGS
🔹 Indicator Settings
Source — Price series used for all calculations.
Z-Score Length — Lookback period for Z-score normalization.
Z-Score MA Length — Smoothing length for the fusion signal lines.
Overbought/Oversold Levels — Four customizable threshold lines.
Color Palette — Choose from preset themes or define custom colors.
🔹 RSI
Length — RSI calculation period.
EMA Smoothing Length — Smooths RSI before Z-score conversion.
🔹 MACD
Fast Length — Fast EMA length.
Slow Length — Slow EMA length.
Signal Line Length — MACD signal smoothing.
🔹 Stochastic
%K Length — Main stochastic length.
EMA Smoothing — Smooths %K for stability.
%D Length — Smoothing for the signal line.
🔹 Momentum
Length — Momentum lookback.
EMA Smoothing — Smooths momentum before Z-scoring.
🔹 Rate of Change
Length — ROC lookback.
EMA Smoothing — Smooths ROC values.
🔹 Divergence
Enable/Disable Divergence Detection — Toggle divergence engine.
Pivot Left/Right Lookback — Defines pivot detection sensitivity.
Detection Range Limits — Controls allowable range for divergence.
Bull/Bear Colors & Styling — Customize divergence visualization.
🔶 SUMMARY
The Z-Fusion Oscillator combines multiple momentum signatures into a single normalized signal, enabling traders to:
Identify reversals early
Detect momentum exhaustion
Spot bullish and bearish divergences
Track overbought/oversold conditions
Visualize trend strength with clarity
Whether you're a swing trader, intraday analyst, or trend-reversal hunter, the Z-Fusion Oscillator provides a powerful and adaptive way to read momentum.
Divergence Channels Indicator — JudasBulletUnique Buy/Sell Indicator. Place stoploss above/below 18 EMA. Low risk/high reward. My No.1 indicator on every chart.
ParabolicSAR+EMA[TS_Indie]🚀 EMA + Parabolic SAR Reversal Trading Strategy
This trading system effectively combines the use of Exponential Moving Averages (EMA) with the Parabolic SAR to identify both price trends and key reversal points. The EMA Fast is used to signal the primary short-term trend, while the EMA Slow acts as a filter for the long-term trend direction. The Parabolic SAR then helps to confirm the reversal signals.
🛠️ Tools Used
1. EMA Fast – Primary Short-Term Trend
2. EMA Slow – Long-Term Trend Filter
3. Parabolic SAR – Reversal Confirmation
🎯 Entry Rules
📈 Buy Setup
1. Trend Filter: EMA Fast > EMA Slow → Uptrend
2. Pullback: Price pulls back and closes below the EMA Fast line.
3. Reversal: Price reverses/pulls back up and closes above the EMA Fast line.
4. SAR Confirmation: The previous Parabolic SAR dot is above the high, and the dot in the current candle is below the low → Reversal signal confirmed.
5. Entry: Enter Buy immediately.
📉 Sell Setup
1. Trend Filter: EMA Fast < EMA Slow → Downtrend
2. Pullback: Price pulls back and closes above the EMA Fast line.
3. Reversal: Price reverses/pulls back down and closes below the EMA Fast line.
4. SAR Confirmation: The previous Parabolic SAR dot is below the low, and the dot in the current candle is above the high → Reversal signal confirmed.
5. Entry: Enter Sell immediately.
💰 Exit Management (Entry, Stop Loss, Take Profit)
1. Entry: Enter the order at the closing price of the signal candle.
2. Stop Loss (SL): Set the Stop Loss at the Parabolic SAR dot.
3. Take Profit (TP): Calculated from the Entry and Stop Loss points, multiplied by the Risk Reward Ratio.
⚙️ Optional Parameters
➭ Custom Risk/Reward Ratio for Take Profit.
➭ Option to add an ATR buffer to the Stop Loss.
➭ Adjustable EMA Fast period.
➭ Adjustable EMA Slow period.
➭ Adjustable Parabolic SAR parameters.
➭ Option to enable Long-only / Short-only positions.
➭ Customizable Backtest start and end date.
➭ Customizable trading session time.
🔔 Alert Function
Alerts display:
➭ Entry Price
➭ Stop Loss Price
➭ Take Profit Price
💡 This strategy allows for many parameter adjustments, such as the MA type, adding/subtracting from the Stop Loss using ATR, and selecting specific sessions for backtesting. If you find interesting or profitable results after adjusting the parameters, please share your comments with other traders!
⚠️ Disclaimer
This indicator is designed for educational and research purposes only. It does not guarantee profits and should not be considered financial advice. Trading in financial markets involves significant risk , including the potential loss of capital.
ICT Macro Slot Algo Event📊 Overview
A powerful multi-timeframe trading indicator that combines Institutional Macro Session Tracking to identify optimal trading windows throughout the day. This tool helps traders align with institutional flow patterns and algorithmic activity across major sessions.
🎯 Key Features
1. Macro Algo Event Sessions
Tracks 6 key institutional time windows during NY Session:
NY Sweep (08:50-09:10) - Opening balance flows
Silver Bullet #1 (09:50-10:10) - First major macro move
Silver Bullet #2 (10:50-11:10) - Second chance/retest opportunity
Lunch Macro (11:50-12:10) - Mid-day repositioning
Post-Lunch Rebalance (13:10-13:40) - Post-lunch adjustments
NY Closing Macros (15:15-15:45) - End-of-day flows
Super momentum DBSISuper momentum DBSI: The Ultimate Guide
1. What is this Indicator?
The Super momentum DBSI is a "Consensus Engine." Instead of relying on a single line (like an RSI) to tell you where the market is going, this tool calculates 33 distinct technical indicators simultaneously for every single candle.
It treats the market like a democracy. It asks 33 mathematical "voters" (Momentum, Trend, Volume, Volatility) if they are Bullish or Bearish.
If 30 out of 33 say "Buy," the score is high (Yellow), and the trend is extremely strong.
If only 15 say "Buy," the score is low (Teal), and the trend is weak or choppy.
2. Visual Guide: How to Read the Numbers
The Scores
Top Number (Bears): Represents Selling Pressure.
Bottom Number (Bulls): Represents Buying Pressure.
The Colors (The Traffic Lights)
The colors are your primary signal. They tell you who is currently winning the war.
🟡 YELLOW (Dominance):
This indicates the Winning Side.
If the Bottom Number is Yellow, Bulls are in control.
If the Top Number is Yellow, Bears are in control.
🔴 RED (Weakness):
This appears on the Top. It means Bears are present but losing.
🔵 TEAL (Weakness):
This appears on the Bottom. It means Bulls are present but losing.
3. Trading Strategy
Scenario A: The "Strong Buy" (Long Entry)
The Setup: You are looking for a shift in momentum where Buyers overwhelm Sellers.
Watch the Bottom Number: Wait for it to turn Yellow.
Confirm Strength: Ensure the score is above 15 and rising (e.g., 12 → 18 → 22).
Check the Top: The Top Number should be Red and low (below 10).
Trigger: Enter on the candle close.
Scenario B: The "Strong Sell" (Short Entry)
The Setup: You are looking for Sellers to crush the Buyers.
Watch the Top Number: Wait for it to turn Yellow.
Confirm Strength: Ensure the score is above 15 and rising.
Check the Bottom: The Bottom Number should be Teal and low.
Trigger: Enter on the candle close.
Scenario C: The "No Trade Zone" (Choppy Market)
The Setup: The market is confused.
Visual: Top is Red, Bottom is Teal.
Meaning: NOBODY IS WINNING. There is no Yellow number.
Action: Do not trade. This usually happens during lunch hours, weekends, or right before big news. This filter alone will save you from many false breakouts.
4. What is Inside? (The 33 Indicators)
To give you confidence in the signals, here is exactly what the script is checking:
Group 1: Momentum (Oscillators)
Detects if price is moving fast.
RSI (Relative Strength Index)
CCI (Commodity Channel Index)
Stochastic
Williams %R
Momentum
Rate of Change (ROC)
Ultimate Oscillator
Awesome Oscillator
True Strength Index (TSI)
Stoch RSI
TRIX
Chande Momentum Oscillator
Group 2: Trend Direction
Detects the general path of the market.
13. MACD
14. Parabolic SAR
15. SuperTrend
16. ALMA (Moving Average)
17. Aroon
18. ADX (Directional Movement)
19. Coppock Curve
20. Ichimoku Conversion Line
21. Hull Moving Average
Group 3: Price Action
Detects where price is relative to averages.
22. Price vs EMA 20
23. Price vs EMA 50
24. Price vs EMA 200
Group 4: Volume & Force
Detects if there is money behind the move.
25. Money Flow Index (MFI)
26. On Balance Volume (OBV)
27. Chaikin Money Flow (CMF)
28. VWAP (Intraday)
29. Elder Force Index
30. Ease of Movement
Group 5: Volatility
Detects if price is pushing the outer limits.
31. Bollinger Bands
32. Keltner Channels
33. Donchian Channels
5. Pro Tips for Success
Don't Catch Knives: If the Bear score (Top) is Yellow and 25+, do not try to buy the dip. Wait for the Yellow score to break.
Exit Early: If you are Long and the Yellow Bull score drops from 28 to 15 in one candle, TAKE PROFIT. The momentum has died.
Use Higher Timeframes: This indicator works best on 15m, 1H, and 4H charts. On the 1m chart, it may be too volatile.
Time-Decay Liquidity Zones [BackQuant]Time-Decay Liquidity Zones
A dynamic liquidity map that turns single-bar exhaustion events into fading, color-graded zones, so you can see where trapped traders and unfinished business still matter, and when those areas have finally stopped pulling price.
What this is
This indicator detects unusually strong impulsive moves into wicks, converts them into supply or demand “zones,” then lets those zones decay over time. Each zone carries a strength score that fades bar by bar. Zones that stop attracting or rejecting price are gradually de-emphasized and eventually removed, while the most relevant areas stay bright and obvious.
Instead of static rectangles that live forever, you get a living liquidity map where:
Zones are born from objective criteria: volatility, wick size, and optional volume spikes.
Zones “age” using a configurable decay factor and maximum lifetime.
Zone color and opacity reflect current relative strength on a unified clear → green → red gradient.
Zones freeze when broken, so you can distinguish “active reaction areas” from “historical levels that have already given way”.
Conceptual idea
Large wicks with strong volatility often mark areas where aggressive orders met hidden liquidity and got absorbed. Price may revisit these areas to test leftover interest or to relieve trapped positions. However, not every wick matters for long. As time passes and more bars print, the market “forgets” some areas.
Time-Decay Liquidity Zones turns that idea into a rule-based system:
Find bars that likely reflect strong aggressive flows into liquidity.
Mark a zone around the wick using ATR-based thickness.
Assign a strength score of 1.0 at birth.
Each bar, reduce that score by a decay factor and remove zones that fall below a threshold or live too long.
Color all surviving zones from weak to strong using a single gradient scale and a visual legend.
How events are detected
Detection lives in the Event Detection group. The script combines range, wick size, and optional volume filters into simple rules.
Volatility filter
ATR Length — computes a rolling ATR over your chosen window. This is the volatility baseline.
Min range in ATRs — bar range (High–Low) must exceed this multiple of ATR for an event to be considered. This avoids tiny bars triggering zones.
Wick filters
For each bar, the script splits the candle into body and wicks:
Upper wick = High minus the max(Open, Close).
Lower wick = min(Open, Close) minus Low.
Then it tests:
Upper wick condition — upper wick must be larger than Min wick size in ATRs × ATR.
Lower wick condition — lower wick must be larger than Min wick size in ATRs × ATR.
Only bars with a sufficiently long wick relative to volatility qualify as candidate “liquidity events”.
Volume filter
Optionally, the script requires a volume spike:
Use volume filter — if enabled, volume must exceed a rolling volume SMA by a configurable multiplier.
Volume SMA length — period for the volume average.
Volume spike multiplier — how many times above the SMA current volume needs to be.
This lets you focus only on “heavy” tests of liquidity and ignore quiet bars.
Event types
Putting it together:
Upper event (potential supply / long liquidation, etc.)
Occurs when:
Upper wick is large in ATR terms.
Full bar range is large in ATR terms.
Volume is above the spike threshold (if enabled).
Lower event (potential demand / short liquidation, etc.)
Symmetric conditions using the lower wick.
How zones are constructed
Zone geometry lives in Zone Geometry .
When an event is detected, the script builds a rectangular box that anchors to the wick and extends in the appropriate direction by an ATR-based thickness.
For upper (supply-type) zones
Bottom of the zone = event bar high.
Top of the zone = event bar high + Zone thickness in ATRs × ATR.
The zone initially spans only the event bar on the x-axis, but is extended to the right as new bars appear while the zone is active.
For lower (demand-type) zones
Top of the zone = event bar low.
Bottom of the zone = event bar low − Zone thickness in ATRs × ATR.
Same extension logic: box starts on the event bar and grows rightward while alive.
The result is a band around the wick that scales with volatility. On high-ATR charts, zones are thicker. On calm charts, they are narrower and more precise.
Zone lifecycle, decay, and removal
All lifecycle logic is controlled by the Decay & Lifetime group.
Each zone carries:
Score — a floating-point “importance” measure, starting at 1.0 when created.
Direction — +1 for upper zones, −1 for lower zones.
Birth index — bar index at creation time.
Active flag — whether the zone is still considered unbroken and extendable.
1) Active vs broken
Each confirmed bar, the script checks:
For an upper zone , the zone is counted as “broken” when the close moves above the top of the zone.
For a lower zone , the zone is counted as “broken” when the close moves below the bottom of the zone.
When a zone breaks:
Its right edge is frozen at the previous bar (no further extension).
The zone remains on the chart, but is no longer updated by price interaction. It still decays in score until removal.
This lets you see where a major level was overrun, while naturally fading its influence over time.
2) Time decay
At each confirmed bar:
Score := Score × Score decay per bar .
A decay value close to 1.0 means very slow decay and long-lived zones.
Lower values (closer to 0.9) mean faster forgetting and more current-focused zones.
You are controlling how quickly the market “forgets” past events.
3) Age and score-based removal
Zones are removed when either:
Age in bars exceeds Max bars a zone can live .
This is a hard lifetime cap.
Score falls below Minimum score before removal .
This trims zones that have decayed into irrelevance even if their age is still within bounds.
When a zone is removed, its box is deleted and all associated state is freed to keep performance and visuals clean.
Unified gradient and color logic
Color control lives in Gradient & Color . The indicator uses a single continuous gradient for all zones, above and below price, so you can read strength at a glance without guessing what palette means what.
Base colors
You set:
Mid strength color (green) — used for mid-level strength zones and as the “anchor” in the gradient.
High strength color (red) — used for the strongest zones.
Max opacity — the maximum visual opacity for the solid part of the gradient. Lower values here mean more solid; higher values mean more transparent.
The script then defines three internal points:
Clear end — same as mid color, but with a high alpha (close to transparent).
Mid end — mid color at the strongest allowed opacity.
High end — high color at the strongest allowed opacity.
Strength normalization
Within each update:
The script finds the maximum score among all existing zones.
Each zone’s strength is computed as its score divided by this maximum.
Strength is clamped into .
This means a zone with strength 1.0 is currently the strongest zone on the chart. Other zones are colored relative to that.
Piecewise gradient
Color is assigned in two stages:
For strength between 0.0 and 0.5: interpolate from “clear” green to solid green.
Weak zones are barely visible, mid-strength zones appear as solid green.
For strength between 0.5 and 1.0: interpolate from solid green to solid red.
The strongest zones shift toward the red anchor, clearly separating them from everything else.
Strength scale legend
To make the gradient readable, the indicator draws a vertical legend on the right side of the chart:
About 15 cells from top (Strong) to bottom (Weak).
Each cell uses the same gradient function as the zones themselves.
Top cell is labeled “Strong”; bottom cell is labeled “Weak”.
This legend acts as a fixed reference so you can instantly map a zone’s color to its approximate strength rank.
What it plots
At a glance, the indicator produces:
Upper liquidity zones above price, built from large upper wick events.
Lower liquidity zones below price, built from large lower wick events.
All zones colored by relative strength using the same gradient.
Zones that freeze when price breaks them, then fade out via decay and removal.
A strength scale legend on the right to interpret the gradient.
There are no extra lines, labels, or clutter. The focus is the evolving structure of liquidity zones and their visual strength.
How to read the zones
Bright red / bright green zones
These are your current “major” liquidity areas. They have high scores relative to other zones and have not yet decayed. Expect meaningful reactions, absorption attempts, or spillover moves when price interacts with them.
Faded zones
Pale, nearly transparent zones are either old, decayed, or minor. They can still matter, but priority is lower. If these are in the middle of a long consolidation, they often become background noise.
Broken but still visible zones
Zones whose extension has stopped have been overrun by closing price. They show where a key level gave way. You can use them as context for regime shifts or failed attempts.
Absence of zones
A chart with few or no zones means that, under your current thresholds, there have not been strong enough liquidity events recently. Either tighten the filters or accept that recent price action has been relatively balanced.
Use cases
1) Intraday liquidity hunting
Run the indicator on lower timeframes (e.g., 1–15 minute) with moderately fast decay.
Use the upper zones as potential sell reaction areas, the lower zones as potential buy reaction areas.
Combine with order flow, CVD, or footprint tools to see whether price is absorbing or rejecting at each zone.
2) Swing trading context
Increase ATR length and range/wick multipliers to focus only on major spikes.
Set slower decay and higher max lifetime so zones persist across multiple sessions.
Use these zones as swing inflection areas for larger setups, for example anticipating re-tests after breakouts.
3) Stop placement and invalidation
For longs, place invalidation beyond a decaying lower zone rather than in the middle of noise.
For shorts, place invalidation beyond strong upper zones.
If price closes through a strong zone and it freezes, treat that as additional evidence your prior bias may be wrong.
4) Identifying trapped flows
Upper zones formed after violent spikes up that quickly fail can mark trapped longs.
Lower zones formed after violent spikes down that quickly reverse can mark trapped shorts.
Watching how price behaves on the next touch of those zones can hint at whether those participants are being rescued or squeezed.
Settings overview
Event Detection
Use volume filter — enable or disable the volume spike requirement.
Volume SMA length — rolling window for average volume.
Volume spike multiplier — how aggressive the volume spike filter is.
ATR length — period for ATR, used in all size comparisons.
Min wick size in ATRs — minimum wick size threshold.
Min range in ATRs — minimum bar range threshold.
Zone Geometry
Zone thickness in ATRs — vertical size of each liquidity zone, scaled by ATR.
Decay & Lifetime
Score decay per bar — multiplicative decay factor for each zone score per bar.
Max bars a zone can live — hard cap on lifetime.
Minimum score before removal — score cut-off at which zones are deleted.
Gradient & Color
Mid strength color (green) — base color for mid-level zones and the lower half of the gradient.
High strength color (red) — target color for the strongest zones.
Max opacity — controls the most solid end of the gradient (0 = fully solid, 100 = fully invisible).
Tuning guidance
Fast, session-only liquidity
Shorter ATR length (e.g., 20–50).
Higher wick and range multipliers to focus only on extreme events.
Decay per bar closer to 0.95–0.98 and moderate max lifetime.
Volume filter enabled with a decent multiplier (e.g., 1.5–2.0).
Slow, structural zones
Longer ATR length (e.g., 100+).
Moderate wick and range thresholds.
Decay per bar very close to 1.0 for slow fading.
Higher max lifetime and slightly higher min score threshold so only very weak zones disappear.
Noisy, high-volatility instruments
Increase wick and range ATR multipliers to avoid over-triggering.
Consider enabling the volume filter with stronger settings.
Keep decay moderate to avoid the chart getting overloaded with old zones.
Notes
This is a structural and contextual tool, not a complete trading system. It does not account for transaction costs, execution slippage, or your specific strategy rules. Use it to:
Highlight where liquidity has recently been tested hard.
Rank these areas by decaying strength.
Guide your attention when layering in separate entry signals, risk management, and higher-timeframe context.
Time-Decay Liquidity Zones is designed to keep your chart focused on where the market has most recently “cared” about price, and to gradually forget what no longer matters. Adjust the detection, geometry, decay, and gradient to fit your product and timeframe, and let the zones show you which parts of the tape still have unfinished business.
Swing Trading Quantum Trend SniperChange Hull - 55 for 1H or 1D time frame
Change Hull - 24 for 1 M or 5M time frame
