Day-Type Detector — Rejection / FNL / Outside / StopRun (Clean)Day-Type Detector — Rejection / FNL / Outside / Stop-Run (Clean Version)
This indicator identifies four high-impact candlestick day-types commonly used in professional price-action and auction-market trading: Rejection Days, Failed New Low (FNL) Days, Outside Days, and Stop-Run Days. These patterns often precede major directional moves, reversals, and absorption events, making them particularly valuable for swing traders, positional traders, and short-term discretionary traders.
The script is designed to work across all timeframes and is built around volatility-adjusted measurements using Average Daily Range (ADR) for accuracy and consistency.
What This Indicator Detects
1. Rejection Day (Bullish & Bearish)
A Rejection Day is a wide-range bar that rejects a previous extreme.
The indicator identifies rejection based on:
Range > ADR × threshold
Long lower wick (for bullish) or long upper wick (for bearish)
Close located in the strong zone of the day’s range
These conditions highlight areas where aggressive counter-orderflow entered the market.
2. Failed New Low (FNL) / Failed New High
An FNL day traps traders who attempted breakout selling or buying.
The indicator checks for:
A break beyond the previous session’s low or high
Immediate rejection back inside
Midpoint recapture conditions
ADR-normalized range requirements
These days often trigger powerful directional reversals.
3. Outside Day (Bullish & Bearish)
An Outside Day is a statistically significant expansion day that breaks both the previous high and low.
The script validates:
High > previous high and low < previous low
Range > ADR threshold
Close beyond prior session extreme to complete the rejection sequence
Outside Days often represent stop runs, shakeouts, or trend accelerations.
4. Stop-Run Day (Bullish & Bearish)
Stop-Run Days are aggressive volatility expansions and tend to be the largest ranges within short windows.
This detector identifies them using:
Range > ADR × multiplier
Close located near the extreme of the day (top for bullish, bottom for bearish)
Strong body relative to total range
Break above/below previous session extreme
These patterns indicate capitulation or forced liquidation and are often followed by continuation or sharp counter-rotation.
Key Features
✔ Historical Pattern Marking
All qualifying bars are marked on the chart using plotshape() in global scope, ensuring full historical visibility.
✔ Event Logging & Table Display
A table (top-right of the chart) displays the most recent pattern detections, including:
Timestamp
Pattern type
Bar index
This allows users to monitor and study past pattern occurrences without scanning the chart manually.
✔ ADR-Adjusted Detection
Volatility uncertainty is removed by anchoring all thresholds to ADR.
This ensures consistency across:
Different symbols
Different timeframes
Different market regimes
✔ Alerts Included
Alerts are preconfigured for:
Rejection Day Bull / Bear
FNL Bull / Bear
Outside Day Bull / Bear
Stop-Run Bull / Bear
This allows the user to receive real-time notifications when major day-type structures develop.
How to Use
Add the indicator to any timeframe chart.
Enable or disable:
Historical markers
History table
ADR diagnostics
Watch for shape markers or use alerts for real-time signals.
Use the history table to review recent occurrences.
Combine these day-types with:
Market structure levels
High/low volume nodes (LVNs)
Support/resistance zones
Trend context
These day-types are most effective when they occur near meaningful structural levels because they show where strong order-flow entered the market.
Best Practices
Use higher timeframes (1H–1D) for swing entries.
Confirm signals with market structure or volume profile.
Treat these day-types as context, not standalone signals.
Observe follow-through behavior in the next 1–3 bars after detection.
Credits
This script is based on concepts commonly seen in auction-market theory and professional price-action frameworks, such as Rejection Days, Failed New Lows, Outside Days, and Stop-Run behaviors.
All calculations and logic have been rebuilt from scratch to ensure clean, reliable, and optimized Pine Script v6 execution.
Zmienność
OTT Volatility [RunRox]📊 OTT Volatility is an indicator developed by the RunRox team to pinpoint the most optimal time to trade across different markets.
OTT stands for Optimal Trade Time Volatility and is designed primarily for markets without a fixed trading session, such as cryptocurrencies that trade 24/7. At the same time, it works equally well on any other market.
🔶 The concept is straightforward. The indicator takes a specified number of historical periods (Samples) and statistically evaluates which hours of the day or which days show the highest volatility for the selected asset.
As a result, it highlights time windows with elevated volatility where traders can focus on searching for trade setups and building positions.
🔶 As the core volatility metric, the indicator uses ATR (Average True Range) to measure intraday volatility. Then it calculates the average ATR value over the last N Samples, creating a statistically stable estimate of typical volatility for the selected asset.
🔶 Statistically, during these highlighted periods the market shows higher-than-average volatility.
This means that in these time windows price is more likely to be subject to stronger moves and potential manipulation, making them attractive for active trade execution and position management.
⚠️ However, historical behavior does not guarantee future results.
These periods should be treated only as zones where volatility has a higher probability of being above normal, not as a promise of movement.
As shown in the screenshot above, the indicator also projects potential future volatility based on historical data. This helps you better plan your trading hours and align your activity with periods where volatility is statistically expected to be higher or lower.
🔶 Current Volatility – as shown in the screenshot above, you can also monitor the real-time volatility of the market without any statistical averaging.
On top of that, you can overlay the current volatility on top of the statistical volatility levels, which makes it easy to see whether the market is now trading in a high- or low-volatility regime relative to its usual behavior.
4 display modes – you can choose any visualization style that fits your trading workflow:
Absolute – displays the raw volatility values.
Relative – shows volatility relative to its typical levels.
Average Centered – centers volatility around its average value.
Trim Low Value – filters out low-volatility noise and highlights only more significant moves.
This indicator helps you define the most effective trading hours on any market by relying on historical volatility statistics.
Use it to quickly see when your market tends to be more active and to structure your trading sessions around those periods.
✅ We hope this tool becomes a useful part of your trading toolkit and helps you improve the quality of your decisions and timing.
Strat Reversal MTF TableStrat Reversal MTF Table — Your Complete Multi-Timeframe Strat Command Center
Take your Strat trading to the next level with an indicator that shows every reversal, on every timeframe, in one powerful visual dashboard.
Designed for traders who demand speed, clarity, and full Strat alignment, the Strat Reversal MTF Table instantly identifies all major bullish and bearish reversal patterns:
Bullish Patterns
2-1-2
3-1-2
1-3-2
3-2-2
Bearish Patterns
2-1-2
3-1-2
1-3-2
3-2-2
Each signal is displayed with:
Clear pattern name (e.g., “2-1-2 Bull”)
Automatic trigger price
Timeframe label
Color-coded background (Bullish / Bearish / Neutral)
Whether you trade options, equities, futures, or crypto, this indicator makes it effortless to see what’s flipping — and where the strongest setups are emerging.
🔥 Key Features
📊 Multi-Timeframe Scanning (1 min → Daily)
Monitor 7 customizable timeframes at once.
From scalping to swing trading, you always know which timeframe is turning.
⚡ Real-Time OR Close-Confirmed Logic
Choose your style:
Realtime (Wick Mode) → Fast entries
Close-Confirmed → Stronger validation
Ideal for traders who want precision on any timeframe.
🎨 Clean & Customizable Dashboard
Move the table anywhere on the chart
Adjust text size
Choose your own colors
Lightweight and non-intrusive
A perfect blend of simplicity and power.
📩 Instant Alerts, Built In
Get notified instantly when:
Any timeframe reverses
A specific timeframe flips
Multiple reversals fire across the stack
The indicator works great with TradingView’s push notifications, email, and webhooks.
🎯 What This Helps You Do
✔ Catch Strat reversals as they happen
✔ Quickly spot full-timeframe alignment
✔ Improve your entries for options plays
✔ Avoid chop by reading higher-timeframe intent
✔ Trade more confidently with automated trigger levels
This indicator is built for Strat traders who want to trade smarter, faster, and cleaner.
✨ Perfect For
Strat Traders
Options Traders
Futures Scalpers
Intraday & Swing Traders
Quant/Algo-inspired traders
Anyone following Rob Smith’s methodology
Today Range Calculator1. Indicator Name
Today (Today’s Volatility)
2. One-line Introduction
Displays real-time 30-day historical volatility (HV30) as a compact table on the chart, helping traders instantly assess market risk levels.
3. General Overview
Today ↑↓ is a lightweight informational widget that calculates and displays the 30-day Historical Volatility (HV30) of the asset in real time.
Using logarithmic returns over the past 30 periods, the script computes variance and then annualizes it to express volatility as a percentage (%) per year.
The result is shown in a clean 1x1 table cell, which can be positioned anywhere on the chart—top/bottom, left/right—depending on your preference.
This makes it easy to quickly evaluate whether the current market is high-risk (volatile) or stable, without cluttering the chart.
It’s especially useful for position sizing, risk management, volatility-based entry/exit decisions, and as a filter for breakout strategies.
Built with performance in mind, the script uses minimal system resources and can be used alongside any indicator or strategy without interference.
4. Key Advantages
📈 Real-time HV30 Display
Calculates and displays 30-day historical volatility using annualized log return variance.
📍 Custom Table Positioning
Place the volatility display in any corner of the chart for optimal visibility.
🧮 Accurate Log Return Calculation
Uses logarithmic returns to ensure precise volatility representation over time.
🎯 Quick Market Sentiment Read
Helps you determine at a glance whether the asset is in a calm or volatile environment.
🧼 Minimalist Design
Clean 1-cell table format keeps your chart readable and organized.
🚀 Ultra-Lightweight Script
Runs efficiently with negligible impact on chart performance.
📘 Indicator User Guide
📌 Basic Concept
Today ↑↓ calculates 30-day Historical Volatility (HV30) by analyzing the asset’s log returns over the past 30 bars.
The result is annualized and shown as a percentage to reflect volatility in standardized terms.
Useful for gauging risk levels and strategy suitability in current market conditions.
⚙️ Settings Explained
Table Position: Choose where the volatility table appears:
Top Left / Top Right / Bottom Left / Bottom Right
📈 High Volatility Example
HV30 > 50% indicates a volatile environment
Suggests wider stop-losses, cautious position sizing, or favoring breakout strategies
📉 Low Volatility Example
HV30 < 15% suggests a calm market or range-bound behavior
Useful as a signal for upcoming volatility expansions or breakout preparations
🧪 Recommended Use Cases
Position Sizing: Scale position size based on HV30 readings
Strategy Filter: Activate certain systems only when volatility meets predefined conditions
Breakout Timing: Identify low-volatility zones as potential breakout opportunities
🔒 Precautions
This indicator does not generate buy/sell signals; it is a volatility reference tool
HV thresholds vary across asset classes—adjust interpretation accordingly
Since HV30 is historical, it may lag during rapid market changes
Price Action - LegsRooted in Al Brooks' leg counting philosophy from "Trading Price Action Trends," this draws zigzag lines connecting swing points: green for up legs (until low < previous low), red for down legs (until high > previous high). Updates dynamically to new extremes, with optional count labels (0 resets on stronger pivots). Visualizes twists in channels or ranges—markets always test with two legs; use for pullback entries or reversals.
Trend Continuation [OmegaTools]Trend Continuation is a trend-following and trend-continuation tool designed to highlight high-probability pullbacks within an existing directional bias. It helps discretionary and systematic traders visually isolate “continuation zones” where a retracement is more likely to resolve in favor of the prevailing trend rather than trigger a full reversal.
1. Concept and Objective
The indicator combines two key components:
1. A trend bias engine (based either on a Rolling VWAP regime or on swing market structure).
2. A pullback pressure model, which quantifies how deep and “aggressive” the recent retracement has been relative to the trend.
The goal is to identify moments where the market pulls back against the trend, builds enough “reversal pressure,” and then shows signs that the trend is likely to **continue** rather than flip. When specific conditions are met, the indicator highlights bars and plots reference levels that can be used as potential continuation zones, filters, or confluence areas in a broader trading plan.
2. Trend Bias Modes
The primary trend direction is defined through the `Trend Mode` input:
* **RVWAP Mode (default)**
The script computes two rolling volume-weighted average prices over different lengths:
* A **shorter-term rolling VWAP**
* A **longer-term rolling VWAP**
When the shorter RVWAP is above the longer one, the bias is set to **bullish (+1)**. When it is below, the bias is **bearish (-1)**.
This creates a smooth, volume-weighted trend definition that tends to adapt to shifting regimes and filters out minor noise.
* **Market Structure Mode**
In this mode, trend bias is derived from **pivot highs and lows**:
* When price breaks above a recent pivot high, the bias flips to **bullish (+1)**.
* When price breaks below a recent pivot low, the bias flips to **bearish (-1)**.
This approach is more structurally oriented and reacts to significant swing breaks rather than just moving-average style relationships.
If no clear condition is met, the internal bias can temporarily be neutral, though the main design assumes working with clearly bullish or bearish environments.
3. Pullback and Reversal Pressure Logic
Once the trend bias is defined, the indicator measures **pullback intensity** against that trend:
* A **lookback window (“Pullback Length”)** scans recent highs and lows:
* In an uptrend, it tracks the **highest high** over the window and measures how far the current low pulls back from that high.
* In a downtrend, it tracks the **lowest low** and measures how far the current high bounces up from that low.
* This distance is converted into a **“reversal pressure” value**:
* In a bullish bias, deeper pullbacks (lower lows relative to the recent high) indicate stronger counter-trend pressure.
* In a bearish bias, stronger rallies (higher highs relative to the recent low) indicate stronger counter-trend pressure.
The raw reversal pressure is then smoothed with a long-term moving average to separate normal retracements from **statistically significant extremes**.
4. Thresholds and Histogram Coloring
To avoid reacting to every minor pullback, the indicator builds a **dynamic threshold** using a combination of:
* Long-term averages of reversal pressure.
* Standard deviation of reversal pressure.
* High-percentile values of reversal behavior over different sample sizes.
From this, a **threshold line** is derived, and the script then compares the current reversal pressure to this adaptive level:
* The **Reversal Histogram** (column plot) represents the excess reversal pressure above its own long-term average.
* When:
* There is a valid bullish or bearish bias, and
* The histogram is above the dynamic threshold,
the bars of the histogram are **colored**:
* Blue (or a similar “positive” color) in bullish bias.
* Red/pink (or a similar “negative” color) in bearish bias.
* When reversal pressure is below threshold or bias is not relevant, the histogram remains **neutral gray**.
These colored histogram segments represent **“high-tension” pullback states**, where counter-trend pressure has reached an extreme that, historically, often resolves with the original trend continuing rather than fully reversing.
5. Continuation Level and Bar Coloring on Price Chart
To connect the oscillator logic back to the chart:
* A **continuation reference level** is computed on the price series:
* In an uptrend, this is derived by subtracting the threshold from recent highs.
* In a downtrend, it is derived by adding the threshold to recent lows.
* This level is plotted as a **line on the price chart** (only when the trend bias is stable), acting as a visual guide for:
* Potential continuation zones,
* Possible stop-placement or invalidation areas,
* Or filters for entries/exits.
The bars are then **colored** when price crosses or interacts with these levels in the direction of the trend:
* In a bullish bias, bars closing below the continuation level can be highlighted as potential **deep pullback/continuation opportunities** or as warning signals, depending on the user’s playbook.
* In a bearish bias, bars closing above the continuation level are similarly highlighted.
This makes it easy to see where the oscillator’s “extreme pullback” conditions align with structural movements on the actual price bars.
6. Embedded Win-Rate Estimation (WR Table)
The script also includes an internal **win-rate style metric (WR%)** displayed in a small table on the chart:
* It tracks occurrences where:
* A valid bullish or bearish bias is present, and
* The Reversal Histogram is **above the threshold** (i.e., histogram is colored).
* It then approximates the **probability that the trend bias does not change** following such high-pressure pullback events.
* The WR value is shown as a percentage and represents, in essence, the **historical trend-continuation rate** under these specific conditions over the most recent sample of events.
This is not a formal statistical test and does not guarantee future performance, but it provides a quick visual indication of how often these continuation setups have led to **trend persistence** in the recent past.
7. How to Use in Practice
Typical applications include:
Trend-following entries on pullbacks
Identify the main trend using either RVWAP or Market Structure mode.
Wait for a colored histogram bar (reversal pressure above threshold).
Use the continuation reference line and bar coloring on the price chart to refine entry zones or invalidation levels.
Filtering signals from other systems
Run the indicator in the background to confirm trend continuation conditions before taking signals from another strategy (e.g., breakouts or momentum entries).
Only act on long signals when the bias is bullish and a high-pressure pullback has recently occurred; similarly for short signals in bearish conditions.
Risk management and trend monitoring
Monitor when reversal pressure is building against your current position.
Use shifts in bias combined with high reversal pressure to re-evaluate or scale out of trend-following trades.
Recommended steps:
1. Choose your Trend Mode:
- RVWAP for smoother, regime-style trend detection.
- Market Structure for swing-based structural changes.
2. Adjust Trend Length and Pullback Length to match your timeframe (shorter for intraday, longer for swing/position trading).
3. Observe where histogram colors appear and how price reacts around the continuation line and highlighted bars.
4. Integrate these signals into a pre-defined trading plan with clear entry, exit, and risk rules.
8. Limitations and Disclaimer
* This tool is a **technical analysis aid**, not a complete trading system.
* Past behavior of trend continuation or reversal pressure does **not** guarantee future results.
* The embedded WR metric is a **descriptive statistic** based on recent historical conditions only; it is not a promise of performance or a robust statistical forecast.
* All parameters (lengths, thresholds, modes) are user-configurable and should be **tested and validated** on your own data, instruments, and timeframes before any live use.
Disclaimer
This indicator is provided for informational and educational purposes only and does not constitute financial, investment, or trading advice. Trading and investing in financial markets involve substantial risk, including the possible loss of all capital. You are solely responsible for your own trading decisions and for evaluating all information provided by this tool. OmegaTools and the author of this script expressly disclaim any liability for any direct or indirect loss resulting from the use of this indicator. Always consult with a qualified financial professional before making any investment decisions.
Dynamic Fair-Value Ribbon Pro @darshakssc1. What This Indicator Is (In Simple Terms)
The Dynamic Fair-Value Ribbon Pro is a visual tool that helps you see how price behaves around a statistically derived “fair-value zone”:
A colored ribbon/cloud marks a central “fair” area.
Areas above the ribbon are labeled as “Unfair High Zone”.
Areas below the ribbon are labeled as “Unfair Low Zone”.
A small state panel tells you where price currently sits relative to this ribbon.
All calculations are based only on historical price, volume, and volatility.
It does not predict future price, does not give buy/sell signals, and is not financial advice.
2. Adding the Indicator
Open a chart on TradingView.
Click on Indicators .
Search for “Dynamic Fair-Value Ribbon Pro” .
Click to add it to your chart.
You will see:
A cloud/ribbon around price.
Colored bars when price is outside the ribbon.
A panel in the top right describing the current state.
3. Core Concept: Fair vs Unfair Zones (Analytical Only)
The indicator tries to answer a descriptive question:
“Where is price trading relative to a historically derived central area?”
It does this by:
Calculating a central value (“fair mid”).
Building a band around that mid.
Coloring the chart depending on whether price is inside or outside that band.
It is not claiming that:
Price “must” return to the band.
Price is “overvalued” or “undervalued”.
Any state is good or bad.
It is simply a visual classification tool .
4. Engine Modes — How the Ribbon Is Calculated
Under “Fair-Value Engine” you can choose:
4.1 Mode 1: Range
Looks back over a chosen number of bars (default: 100).
Finds the highest high and lowest low in that window.
Defines a central “slice” of that range as the fair-value ribbon :
Range Mode: Lower Percent → bottom boundary of the slice (e.g., 30%).
Range Mode: Upper Percent → top boundary of the slice (e.g., 70%).
Effect:
The ribbon represents a middle portion of the historical range .
Above the ribbon = “Unfair High Zone” (analytical label only).
Below the ribbon = “Unfair Low Zone”.
This is purely statistical — it does not mean price is wrong or will revert.
4.2 Mode 2: VWAP + Stdev
In this mode, the central value is based on VWAP :
VWAP (Volume-Weighted Average Price) is used as the midline.
A standard deviation envelope is built around VWAP:
VWAP Mode: Stdev Multiplier controls how wide that envelope is.
Effect:
The ribbon shows where price is trading relative to a volume-weighted average .
Again, areas above and below are just described as “unfair” zones in a visual, analytical sense , not a predictive one.
5. ATR Adaptive Width — Making the Ribbon React to Volatility
Under “ATR Adaptive Width” :
Use ATR Adaptive Width:
On: the band width scales with volatility.
Off: band width stays fixed based on Range or VWAP settings.
ATR Length: how many bars to use for ATR.
Reference ATR (% of price): a reference level for normal volatility.
Min Width Scale / Max Width Scale: clamps the scaling so that the band doesn’t get too narrow or too wide.
What this does (analytically):
When volatility (ATR) is higher than the reference, the band can become wider .
When volatility is lower , the band can become narrower .
This is a mathematical rescaling only and does not imply any optimal levels or performance.
6. Visual Elements — What You See on the Chart
6.1 Fair-Value Ribbon (Cloud)
The cloud between Fair Ribbon Low and Fair Ribbon High is the fair zone .
Color can be changed via “Fair Ribbon Color” .
6.2 Midline
If “Show Center Line” is enabled:
A line runs through the middle of the ribbon.
In Range mode, this is the average of the upper and lower band.
In VWAP mode, it’s essentially the VWAP-based mid.
This line is for visual reference only and makes no claims about support, resistance, or reversion.
6.3 Bar Colors
Unfair High Zone: bars are colored with Unfair High Bar Color.
Unfair Low Zone: bars are colored with Unfair Low Bar Color.
Inside the ribbon:
If “Fade Bars Inside Fair Zone” is ON, bars may be more faded/neutral.
These colors are simply classification highlights ; they do not tell you what to do.
6.4 State Panel (Top Right)
If “Show State Panel” is enabled, you’ll see a small box that displays:
Current engine:
Range or VWAP+Stdev.
Current price state:
Inside Ribbon (Fair Zone)
Above Ribbon (Unfair High Zone)
Below Ribbon (Unfair Low Zone)
This is a quick summary of where price sits relative to the computed ribbon.
7. Typical Ways to Use It (Informational Only)
The indicator can help you visually:
See when price is spending time inside a historically defined central zone.
Notice when price is frequently trading outside that zone.
Compare different timeframes (e.g., 5m vs 1h vs 4h) to see how the fair zone shifts.
Experiment with:
Range length (shorter vs longer lookback).
VWAP vs Range mode.
ATR adaptation on/off.
Important:
Any interpretation of these visuals is entirely up to the user.
The script does not tell you to buy, sell, hold, or do anything specific.
8. Limitations and Important Notes
All calculations use past data only (price, volume, volatility).
The ribbon does not guarantee:
that price will revert,
that zones will hold,
or that any outcome will occur.
There are no built-in signals such as “long/short” or automatic entries/exits.
The script is best used as a supporting, visual layer alongside other tools or methods you choose.
9. Disclaimer
This indicator is:
Strictly informational and educational.
Not a trading system or strategy.
Not financial advice or a recommendation.
Not guaranteed to be accurate, complete, or suitable for any specific purpose.
Users should always perform their own research and due diligence.
Past behavior of any visual pattern or zone does not guarantee future behavior.
I4I Inside Vortex Strike RateThis indicator identifies what I call an "Inside Vortex": It's similar to a Doji but more strict in having to be inside a keltner and also have a lower ATR than a blended average.
The bar itself is not that special. But it indicates that a potential big move might come in the next 2 periods.
After the patter: It then looks at what I call the Market Maker High and Low: A % of a blended ATR. It then looks back 100-200 or more bars and calculates the overall strike % in history for the High and low after the pattern happens.
This allows us to know how often these levels are hit within the next 2 periods to find if we have any edge on spread, call or put prices or use them as targets.
So its:
Pattern:
Levels
Strike Rate.
Very unique and EXTREME useful. Especially for options traders.
NeuroPolynomial Channel🧠 NeuroPolynomial Channel – AI-Inspired Market Structure Engine
In modern market microstructure analysis, price is no longer treated as a simple line — it is viewed as a continuously evolving signal governed by nonlinear dynamics, volatility deformation, and behavioral state shifts.
The NeuroPolynomial Channel (NPC) is a mathematically structured, AI-inspired indicator designed to approximate this dynamic behavior using a hybrid of:
• Polynomial regression smoothing
• Neural blending functions
• Volatility-adaptive envelopes
• Distribution-based bias levels
While full deep-learning models cannot be directly implemented in Pine Script due to computational and architectural limitations, the NeuroPolynomial Channel brings core AI concepts into TradingView through mathematically constrained approximations, creating an efficient, real-time neural structure model suitable for intraday and swing analysis.
📐 Mathematical Foundation
NPC is not a standard moving average or simple channel system.
It applies a multi-layer non-linear approximation built on four core mathematical components.
1️⃣ NeuroPolynomial Core Line
At the heart of the system lies a recursive polynomial smoothing kernel inspired by neural weighted blending:
K = α · K
+ (1 - α) · P
+ Δx · ( K - K ) / F
Where:
• K = Neuro core estimate
• P = Current price input
• α = Neural morph factor
• F = Flattening constant
• Δx = Position delta (horizontal deformation component)
The recursive references introduce memory similar to RNN-style feedback behavior.
This produces a structurally smooth, non-linear trajectory that adapts to both local and historical price deformation.
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2️⃣ Neural Volatility Envelope
Instead of classical standard deviation, NPC uses a cumulative error field:
E = ( Σ | P - K | ) / N
Using this error field, the dynamic envelope bands are constructed as:
Inner Band = K ± E · m1
Mid Band = K ± E · m2
Outer Band = K ± E · m3
Where:
• m1, m2, m3 are probabilistic band multipliers
• E represents actual observed deviation, not synthetic volatility
This creates a probabilistic price container that deforms with real market behavior rather than static statistical assumptions.
The channel automatically adapts its curvature based on current price regime:
trending, compressing, or expanding.
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3️⃣ Neural Regression Spine
Alongside the polynomial core, NPC calculates a ridge-regularized regression spine:
y = β · x + α (with L2 regularization)
This acts as a structural bias vector or "neural backbone".
It prevents overfitting and provides directional stabilization during extended trend phases.
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4️⃣ Neuro Bias Zones (Daily Reset)
NPC also introduces daily volatility-anchored regime thresholds:
Z_levels = Open ± ATR_daily × {0.1, 0.382, 0.618}
These act as:
• Neuro Mid Zones – equilibrium bands
• Neuro Strong Zones – trend activation boundaries
Unlike classical pivot systems, these levels reset daily and expand dynamically based on real volatility.
They approximate probability field boundaries similar to those used in institutional volatility modeling.
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🤖 AI Philosophy
While Pine Script cannot host full neural networks, GPU models or multi-layer AI pipelines, NeuroPolynomial Channel introduces AI concepts through mathematical abstraction, including:
• Neural blending mechanics
• Memory-based recursion
• Volatility adaptation
• Bias field modeling
• Structured envelope projection
This creates an AI-style behavior using real-time deterministic mathematics — allowing performance on TradingView while preserving interpretability and stability.
🛠 How To Use
NPC is designed for structure-based interpretation, not random signal chasing.
① Trend Structure
Use the Neural Core Line and channel slope to establish trend direction and regime.
② Compression & Expansion
Observe band width.
Contracting channels signal volatility compression.
Expanding channels signal range expansion.
③ Bias Zones
Neuro Mid and Strong levels act as macro intraday bias framework — especially powerful for session trading and index futures.
⚙️ Settings Overview
• Morph Factor – Controls neural blending strength (higher = smoother, lower = reactive)
• Flatten – Reduces polynomial curvature noise
• Band Multipliers – Adjust envelope thickness
• Neural Bias Levels – ATR-anchored regime zones resetting daily
• Theme & Visual Controls – Dark/Light with pro-grade visibility
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Companion AI:
I also built a free Trading AI on ChatGPT that reads chart screenshots and enforces a rule-based intraday checklist.
Use with this indicator: chatgpt.com
For educational & decision-support only. Not financial advice.
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⚠️ Disclaimer
The information contained in my Scripts / Indicators / Ideas / Systems does not constitute financial advice or a solicitation to buy or sell any securities.
All markets carry risk. This tool is for educational and analytical purposes only.
I do not accept liability for any financial loss or damage resulting from direct or indirect use of this script.
Trading decisions must be made independently based on your own risk profile and financial assessment.
Volatility Signal-to-Noise Ratio🙏🏻 this is VSNR: the most effective and simple volatility regime detector & automatic volatility threshold scaler that somehow no1 ever talks about.
This is simply an inverse of the coefficient of variation of absolute returns, but properly constructed taking into account temporal information, and made online via recursive math with algocomplexity O(1) both in expanding and moving windows modes.
How do the available alternatives differ (while some’re just worse)?
Mainstream quant stat tests like Durbin-Watson, Dickey-Fuller etc: default implementations are ALL not time aware. They measure different kinds of regime, which is less (if at all) relevant for actual trading context. Mix of different math, high algocomplexity.
The closest one is MMI by financialhacker, but his approach is also not time aware, and has a higher algocomplexity anyways. Best alternative to mine, but pls modify it to use a time-weighted median.
Fractal dimension & its derivatives by John Ehlers: again not time aware, very low info gain, relies on bar sizes (high and lows), which don’t always exist unlike changes between datapoints. But it’s a geometric tool in essence, so this is fundamental. Let it watch your back if you already use it.
Hurst exponent: much higher algocomplexity, mix of parametric and non-parametric math inside. An invention, not a math entity. Again, not time aware. Also measures different kinds of regime.
How to set it up:
Given my other tools, I choose length so that it will match the amount of data that your trading method or study uses multiplied by ~ 4-5. E.g if you use some kind of bands to trade volatility and you calculate them over moving window 64, put VSNR on 256.
However it depends mathematically on many things, so for your methods you may instead need multipliers of 1 or ~ 16.
Additionally if you wanna use all data to estimate SNR, put 0 into length input.
How to use for regime detection:
First we define:
MR bias: mean reversion bias meaning volatility shorts would work better, fading levels would work better
Momo bias: momentum bias meaning volatility longs would work better, trading breakouts of levels would work better.
The study plots 3 horizontal thresholds for VSNR, just check its location:
Above upper level: significant Momo bias
Above 1 : Momo bias
Below 1 : MR bias
Below lower level: significant MR bias
Take a look at the screenshots, 2 completely different volatility regimes are spotted by VSNR, while an ADF does not show different regime:
^^ CBOT:ZN1!
^^ INDEX:BTCUSD
How to use as automatic volatility threshold scaler
Copy the code from the script, and use VSNR as a multiplier for your volatility threshold.
E.g you use a regression channel and fade/push upper and lower thresholds which are RMSEs multiples. Inside the code, multiply RMSE by VSNR, now you’re adaptive.
^^ The same logic as when MM bots widen spreads with vola goes wild.
How it works:
Returns follow Laplace distro -> logically abs returns follow exponential distro , cuz laplace = double exponential.
Exponential distro has a natural coefficient of variation = 1 -> signal to noise ratio defined as mean/stdev = 1 as well. The same can be said for Student t distro with parameter v = 4. So 1 is our main threshold.
We can add additional thresholds by discovering SNRs of Student t with v = 3 and v = 5 (+- 1 from baseline v = 4). These have lighter & heavier tails each favoring mean reversion or momentum more. I computed the SNR values you see in the code with mpmath python module, with precision 256 decimals, so you can trust it I put it on my momma.
Then I use exponential smoothing with properly defined alphas (one matches cumulative WMA and another minimizes error with WMA in moving window mode) to estimate SNR of abs returns.
…
Lightweight huh?
∞
Ultra Hassas SuperTrend v6 – HEIKEN + 2x + ALARMUltra hassas trend takibi ile dip ve tepelerden gelen sinyallerle hitli bir sekilde kar edilebilir.
Z-Score Regime DetectorThe Z-Score Regime Detector is a statistical market regime indicator that helps identify bullish and bearish market conditions based on normalized momentum of three core metrics:
- Price (Close)
- Volume
- Market Capitalization (via CRYPTOCAP:TOTAL)
Each metric is standardized using the Z-score over a user-defined period, allowing comparison of relative extremes across time. This removes raw value biases and reveals underlying momentum structure.
📊 How it Works
- Z-Score: Measures how far a current value deviates from its average in terms of standard deviations.
- A Bullish Regime is identified when both price and market cap Z-scores are above the volume Z-score.
- A Bearish Regime occurs when price and market cap Z-scores fall below volume Z-score.
Bias Signal:
- Bullish Bias = Price Z-score > Market Cap Z-score
- Bearish Bias = Market Cap Z-score > Price Z-score
This provides a statistically consistent framework to assess whether the market is flowing with strength or stress.
✅ Why This Might Be Effective
- Normalizing the data via Z-scores allows comparison of diverse metrics on a common scale.
- Using market cap offers broader insight than price alone, especially for crypto.
- Volume as a reference threshold helps identify accumulation/distribution regimes.
- Simple regime logic makes it suitable for trend confirmation, filtering, or position biasing in systems.
⚠️ Disclaimer
This script is for educational purposes only and should not be considered financial advice. Always perform your own research and risk management. Past performance is not indicative of future results. Use at your own discretion.
Average True Range % infoATR% is a modified version of the classic Average True Range indicator that displays price volatility as a percentage of the instrument's value, rather than in absolute values. This allows you to easily compare the volatility of different assets (e.g., Bitcoin vs Tesla stock) regardless of their price.
Main Features
1. ATR% Chart
The red line shows the average volatility from the last N candles (default 14), expressed as a percentage. For example:
ATR% = 2.5% means that the average daily move is approximately 2.5% of the asset's value
Higher values = greater volatility (higher profit potential, but also greater risk)
Lower values = lower volatility (calmer market)
2. Volatility Trend Analysis
The indicator automatically detects whether volatility is rising, falling, or stable:
Up arrow (↑) - volatility is rising (price becomes more "nervous")
Down arrow (↓) - volatility is falling (market is calming down)
Horizontal arrow (⮆) - volatility is stable (within ±3% of the moving average)
3. Information Table
In the upper right corner of the chart you will see Current ATR% value and Trend arrow with color coding:
- Green = rising volatility
- Red = falling volatility
- Gray = stable volatility
Parameters to Configure
Indicator Length (default: 14) - How many candles back to include in calculations:
Lower values (5-10): more sensitive to sudden changes, reacts faster
Higher values (20-30): more smoothed, shows long-term volatility picture
Trend Length (default: 10) - Period to analyze whether volatility is rising/falling:
Lower values: faster trend change signals
Higher values: more reliable, but slower signals
Sample Interpretations
ATR% Volatility Asset Type/Situation
< 1% Very low Stable blue-chip stocks, calm market
1-3% Low-medium Typical stocks, normal conditions
3-5% Medium-high Volatile stocks, cryptocurrencies at rest
5-10% High Cryptocurrencies, penny stocks
> 10% Extremely high Market panic, crash, pump & dump
ATH/ATL/DaysThis indicator displays the All-Time High (ATH) and All-Time Low (ATL) — or more precisely, the highest and lowest price within the last N days. It works on any timeframe and uses only local chart data (no security() calls), ensuring stable and accurate results.
It plots horizontal lines for both the ATH and ATL and includes a clean, compact table showing:
Date of the extreme
Days since it occurred
Price
% distance from current price
$ distance from current price
A reliable tool for identifying local extremes, spotting market structure shifts, and tracking short-term price ranges.
SCOB Pattern with ERC & AlertsSingle Candle Block (SC0B) consists of a single candle appearing at a significant price level, indicating a confirmed reversal in price direction from that particular area of interest.
SCOB is primarily used to confirm and execute trades.
Using a single candle block to enter a trade minimizes risk and maximizes reward.
Single bullish candle block?
1st candle closes at bullish point of interest with a short or long wick.
2nd candle sweeps the low of previous(1st) candle and closes above the low of previous candle.
3rd candle closes above the high of 2nd candle.
How to trade with Scob bullish.
To Trade using Bullish SCOB you have to wait for price to come down and test the single candle order block.
When price tests the SCOB you can directly execute a buy trade or for a precise entry you can wait for a market structure shift in lower time frame.
Scob discount is the opposite of price increase.
This strategy should only be used when price "sweeps through key lever, liquidity, imbalance, poi htf areas.
This indicator will add a filter to help you reduce signal noise.
Use the "Use engulfing candle to test" function to filter the 3rd candle.
Only search for Scob if the 3rd candle is an Engulfing candle.
The logic for finding Engulfing candles can be changed based on the "% maximum wick length" option. The default is that the candle wick is 25% of the total candle wick length.
You can also use the alert function when Scob appears
With Smart money concept, no strategy is perfect in trading, so you should not risk too much of your capital on this strategy.
To be safer, always remember to use stop loss for every trade.
Đại Ka 3 ATR BandsĐại Ka 3 ATR Bands – The ultimate single-slot indicator that replaces three separate ATR plots.
Designed specifically for ICT/SMC traders in 2025:
• Light red band (±0.5 ATR) → fake moves, Judas Swing, Turtle Soup zone
• Gray band (±1.0 ATR) → normal price action
• Light green band (±2.0 ATR) → real displacement zone → Silver Bullet, SFT, high-probability entries
How to use:
– Price stuck inside red band → expect reversal/fakeout
– Price breaks and closes outside green band + volume spike → enter aggressively in that direction (85%+ win-rate inside Killzones)
Default ATR(14), subtle fills for instant visual filtering of real vs fake moves.
Perfect companion for Order Blocks, FVG, Breaker Blocks and NY/London Killzones.
Free forever – coded with love by Đại Ka & Vietnamese ICT crew.
ATR multiple from High & LowA simple numerical indicator measuring ATR multiple from recent 252 days high and low.
ATR multiples from high (and low) are used as a base in many systematic trading and trend following systems. As an example many systems buy after a 2.5–4 ATR multiple pullback in a strong stock if the regime allows it. This would then be paired with an entry tactic, for example buy as it recaptures the a pivot within the upper range, a MA or breaks out again after this mid term pullback/shakeout.
This indicator uses a function which captures the recent high and low no matter if we have 252 bars or not, which is not how standard high/low works in Tradingview. This means it also works with recent IPO:s.
I prefer to overlay the indicator in one of the lower panes, for example the volume pane and then right click on the indicator and select Pin to scale > No scale (fullscreen).
Prev Day/Week Breakout Signals (15m, 1st 15 min BO)- Dr VinayPrev Day/Week Breakout Signals (15m, First Candle Only)- For taking break out entries
Smart Money Concepts [Dau_tu_hieu_goc]Credits to LuxAlgo for the SMC Parts.
Edited by Dau_Tu_Hieu_Goc
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.
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.
ICT Macro Slot Algo Event📊 Overview
A powerful multi-timeframe trading indicator that combines Institutional Macro Session Tracking 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
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
