Volume Sentiment Breakout Channels [AlgoAlpha]🟠 OVERVIEW
This tool visualizes breakout zones based on volume sentiment within dynamic price channels . It identifies high-impact consolidation areas, quantifies buy/sell dominance inside those zones, and then displays real-time shifts in sentiment strength. When the market breaks above or below these sentiment-weighted channels, traders can interpret the event as a change in conviction, not just a technical breakout.
🟠 CONCEPTS
The script builds on two layers of logic:
Channel Detection : A volatility-based algorithm locates price compression areas using normalized highs and lows over a defined lookback. These “boxes” mark accumulation or distribution ranges.
Volume Sentiment Profiling : Each channel is internally divided into small bins, where volume is aggregated and signed by candle direction. This produces a granular sentiment map showing which levels are dominated by buyers or sellers.
When a breakout occurs, the script clears the previous box and forms a new one, letting traders visually track transitions between phases of control. The colored gradients and text updates continuously reflect the internal bias—green for net-buying, red for net-selling—so you can see conviction strength at a glance.
🟠 FEATURES
Volume-weighted sentiment map inside each box, with gradient color intensity proportional to participation.
Dynamic text display of current and overall sentiment within each channel.
Real-time trail lines to show active bullish/bearish trend extensions after breakout.
🟠 USAGE
Setup : Add the script to your chart and enable Strong Closes Only if you prefer cleaner breakouts. Use shorter normalization length (e.g., 50–80) for fast markets; longer (100–200) for smoother transitions.
Read Signals : Transparent boxes mark active sentiment channels. Green gradients show buy-side dominance, red shows sell-side. The middle dashed line is the equilibrium of the channel. “▲” appears when price breaks upward, “▼” when it breaks downward.
Understanding Sentiment : The sentiment profile can be used to show the probability of the price moving up or down at respective price levels.
Volatility
SigmaRevert: Z-Score Adaptive Mean Reversion [KedArc Quant]🔍 Overview
SigmaRevert is a clean, research-driven mean-reversion framework built on Z-Score deviation — a statistical measure of how far the current price diverges from its dynamic mean.
When price stretches too far from equilibrium (the mean), SigmaRevert identifies the statistical “sigma distance” and seeks reversion trades back toward it. Designed primarily for 5-minute intraday use, SigmaRevert automatically adapts to volatility via ATR-based scaling, optional higher-timeframe trend filters, and cooldown logic for controlled frequency
🧠 What “Sigma” Means Here
In statistics, σ (sigma) represents standard deviation, the measure of dispersion or variability.
SigmaRevert uses this concept directly:
Each bar’s price deviation from the mean is expressed as a Z-Score — the number of sigmas away from the mean.
When Z > 1.5, the price is statistically “over-extended”; when it returns toward 0, it reverts to the mean.
In short:
Sigma = Standard deviation distance
SigmaRevert = Trading the reversion of extreme sigma deviations
💡 Why Traders Use SigmaRevert
Quant-based clarity: removes emotion by relying on statistical extremes.
Volatility-adaptive: automatically adjusts to changing market noise.
Low drawdown: filters avoid over-exposure during strong trends.
Multi-market ready: works across stocks, indices, and crypto with parameter tuning.
Modular design: every component can be toggled without breaking the core logic.
🧩 Why This Is NOT a Mash-Up
Unlike “mash-up” scripts that randomly combine indicators, this strategy is built around one cohesive hypothesis:
“Price deviations from a statistically stable mean (Z-Score) tend to revert.”
Every module — ATR scaling, cooldown, HTF trend gating, exits — reinforces that single hypothesis rather than mixing unrelated systems (like RSI + MACD + EMA).
The structure is minimal yet expandable, maintaining research integrity and transparency.
⚙️ Input Configuration (Simplified Table)
Core
`maLen` 120 Lookback for mean (SMA)
`zLen` 60 Window for Z-score deviation
`zEntry` 1.5 Entry when Z exceeds threshold
`zExit` 0.3 Exit when Z normalizes
Filters (optional)
`useReCross` false Requires re-entry confirmation
`useTrend` false / true Enables HTF SMA bias
`htfTF` “60” HTF timeframe (e.g. 60-min)
`useATRDist` false Demands min distance from mean
`atrK` 1.0 ATR distance multiplier
`useCooldown` false / true Forces rest after exit
Risk
`useATRSL` false / true Adaptive stop-loss via ATR
`atrLen` 14 ATR lookback
`atrX` 1.4 ATR multiplier for stop
Session
`useSession` false Restrict to market hours
`sess` “0915-1530” NSE timing
`skipOpenBars` 0–3 Avoid early volatility
UI
`showBands` true Displays ±1σ & ±2σ
`showMarks` true Shows triggers and exits
🎯 Entry & Exit Logic
Long Entry
Trigger: `Z < -zEntry`
Optional re-cross: prior Z < −zEntry, current Z −zEntry
Optional trend bias: current close above HTF SMA
Optional ATR filter: distance from mean ATR × K
Short Entry
Trigger: `Z +zEntry`
Optional re-cross: prior Z +zEntry, current Z < +zEntry
Optional trend bias: current close below HTF SMA
Optional ATR filter: distance from mean ATR × K
Exit Conditions
Primary exit: `Z < zExit` (price normalized)
Time stop: `bars since entry timeStop`
Optional ATR stop-loss: ±ATR × multiplier
Optional cooldown: no new trade for X bars after exit
🕒 When to Use
Intraday (5m)
`maLen=120`, `zEntry=1.5`, `zExit=0.3`, `useTrend=false`, `cooldownBars=6` Capture intraday oscillations Minutes → hours
Swing (30m–1H)
`maLen=200`, `zEntry=1.8`, `zExit=0.4`, `useTrend=true`, `htfTF="D"` Mean-reversion between daily pivots 1–2 days
Positional (4H–1D)
`maLen=300`, `zEntry=2.0`, `zExit=0.5`, `useTrend=true` Capture multi-day mean reversions Days → weeks
📘 Glossary
Z-Score
Statistical measure of how far current price deviates from its mean, normalized by standard deviation.
Mean Reversion
The tendency of price to return to its average after temporary divergence.
ATR
Average True Range — measures volatility and defines adaptive stop distances.
Re-Cross
Secondary signal confirming reversal after an extreme.
HTF
Higher Timeframe — provides macro trend bias (e.g. 1-hour or daily).
Cooldown
Minimum bars to wait before re-entering after a trade closes.
❓ FAQ
Q1: Why are there no trades sometimes?
➡ Check that all filters are off. If still no trades, Z-scores might not breach the thresholds. Lower `zEntry` (1.2–1.4) to increase frequency.
Q2: Why does it sometimes fade breakouts?
➡ Mean reversion assumes overextension — disable it during strong trending days or use the HTF filter.
Q3: Can I use this for Forex or Crypto?
➡ Yes — but adjust session filters (`useSession=false`) and increase `maLen` for smoother means.
Q4: Why is profit factor so high but small overall gain?
➡ Because this script focuses on capital efficiency — low drawdown and steady scaling. Increase position size once stable.
Q5: Can I automate this on broker integration?
➡ Yes — the strategy uses standard `strategy.entry` and `strategy.exit` calls, compatible with TradingView webhooks.
🧭 How It Helps Traders
This strategy gives:
Discipline: no impulsive trades — strict statistical rules.
Consistency: removes emotional bias; same logic applies every bar.
Scalability: works across instruments and timeframes.
Transparency: all signals are derived from visible Z-Score math.
It’s ideal for quant-inclined discretionary traders who want rule-based entries but maintain human judgment for context (earnings days, macro news, etc.).
🧱 Final Notes
Best used on liquid stocks with continuous price movement.
Avoid illiquid or gap-heavy tickers.
Validate parameters per instrument — Z behavior differs between equities and indices.
Remember: Mean reversion works best in range-bound volatility, not during explosive breakouts.
⚠️ Disclaimer
This script is provided for educational purposes only.
Past performance does not guarantee future results.
Trading involves risk, and users should exercise caution and use proper risk management when applying this strategy.
Multi-Mode Seasonality Map [BackQuant]Multi-Mode Seasonality Map
A fast, visual way to expose repeatable calendar patterns in returns, volatility, volume, and range across multiple granularities (Day of Week, Day of Month, Hour of Day, Week of Month). Built for idea generation, regime context, and execution timing.
What is “seasonality” in markets?
Seasonality refers to statistically repeatable patterns tied to the calendar or clock, rather than to price levels. Examples include specific weekdays tending to be stronger, certain hours showing higher realized volatility, or month-end flow boosting volumes. This tool measures those effects directly on your charted symbol.
Why seasonality matters
It’s orthogonal alpha: timing edges independent of price structure that can complement trend, mean reversion, or flow-based setups.
It frames expectations: when a session typically runs hot or cold, you size and pace risk accordingly.
It improves execution: entering during historically favorable windows, avoiding historically noisy windows.
It clarifies context: separating normal “calendar noise” from true anomaly helps avoid overreacting to routine moves.
How traders use seasonality in practice
Timing entries/exits : If Tuesday morning is historically weak for this asset, a mean-reversion buyer may wait for that drift to complete before entering.
Sizing & stops : If 13:00–15:00 shows elevated volatility, widen stops or reduce size to maintain constant risk.
Session playbooks : Build repeatable routines around the hours/days that consistently drive PnL.
Portfolio rotation : Compare seasonal edges across assets to schedule focus and deploy attention where the calendar favors you.
Why Day-of-Week (DOW) can be especially helpful
Flows cluster by weekday (ETF creations/redemptions, options hedging cadence, futures roll patterns, macro data releases), so DOW often encodes a stable micro-structure signal.
Desk behavior and liquidity provision differ by weekday, impacting realized range and slippage.
DOW is simple to operationalize: easy rules like “fade Monday afternoon chop” or “press Thursday trend extension” can be tested and enforced.
What this indicator does
Multi-mode heatmaps : Switch between Day of Week, Day of Month, Hour of Day, Week of Month .
Metric selection : Analyze Returns , Volatility ((high-low)/open), Volume (vs 20-bar average), or Range (vs 20-bar average).
Confidence intervals : Per cell, compute mean, standard deviation, and a z-based CI at your chosen confidence level.
Sample guards : Enforce a minimum sample size so thin data doesn’t mislead.
Readable map : Color palettes, value labels, sample size, and an optional legend for fast interpretation.
Scoreboard : Optional table highlights best/worst DOW and today’s seasonality with CI and a simple “edge” tag.
How it’s calculated (under the hood)
Per bar, compute the chosen metric (return, vol, volume %, or range %) over your lookback window.
Bucket that metric into the active calendar bin (e.g., Tuesday, the 15th, 10:00 hour, or Week-2 of month).
For each bin, accumulate sum , sum of squares , and count , then at render compute mean , std dev , and confidence interval .
Color scale normalizes to the observed min/max of eligible bins (those meeting the minimum sample size).
How to read the heatmap
Color : Greener/warmer typically implies higher mean value for the chosen metric; cooler implies lower.
Value label : The center number is the bin’s mean (e.g., average % return for Tuesdays).
Confidence bracket : Optional “ ” shows the CI for the mean, helping you gauge stability.
n = sample size : More samples = more reliability. Treat small-n bins with skepticism.
Suggested workflows
Pick the lens : Start with Analysis Type = Returns , Heatmap View = Day of Week , lookback ≈ 252 trading days . Note the best/worst weekdays and their CI width.
Sanity-check volatility : Switch to Volatility to see which bins carry the most realized range. Use that to plan stop width and trade pacing.
Check liquidity proxy : Flip to Volume , identify thin vs thick windows. Execute risk in thicker windows to reduce slippage.
Drill to intraday : Use Hour of Day to reveal opening bursts, lunchtime lulls, and closing ramps. Combine with your main strategy to schedule entries.
Calendar nuance : Inspect Week of Month and Day of Month for end-of-month, options-cycle, or data-release effects.
Codify rules : Translate stable edges into rules like “no fresh risk during bottom-quartile hours” or “scale entries during top-quartile hours.”
Parameter guidance
Analysis Period (Days) : 252 for a one-year view. Shorten (100–150) to emphasize the current regime; lengthen (500+) for long-memory effects.
Heatmap View : Start with DOW for robustness, then refine with Hour-of-Day for your execution window.
Confidence Level : 95% is standard; use 90% if you want wider coverage with fewer false “insufficient data” bins.
Min Sample Size : 10–20 helps filter noise. For Hour-of-Day on higher timeframes, consider lowering if your dataset is small.
Color Scheme : Choose a palette with good mid-tone contrast (e.g., Red-Green or Viridis) for quick thresholding.
Interpreting common patterns
Return-positive but low-vol bins : Favorable drift windows for passive adds or tight-stop trend continuation.
Return-flat but high-vol bins : Opportunity for mean reversion or breakout scalping, but manage risk accordingly.
High-volume bins : Better expected execution quality; schedule size here if slippage matters.
Wide CI : Edge is unstable or sample is thin; treat as exploratory until more data accumulates.
Best practices
Revalidate after regime shifts (new macro cycle, liquidity regime change, major exchange microstructure updates).
Use multiple lenses: DOW to find the day, then Hour-of-Day to refine the entry window.
Combine with your core setup signals; treat seasonality as a filter or weight, not a standalone trigger.
Test across assets/timeframes—edges are instrument-specific and may not transfer 1:1.
Limitations & notes
History-dependent: short histories or sparse intraday data reduce reliability.
Not causal: a hot Tuesday doesn’t guarantee future Tuesday strength; treat as probabilistic bias.
Aggregation bias: changing session hours or symbol migrations can distort older samples.
CI is z-approximate: good for fast triage, not a substitute for full hypothesis testing.
Quick setup
Use Returns + Day of Week + 252d to get a clean yearly map of weekday edge.
Flip to Hour of Day on intraday charts to schedule precise entries/exits.
Keep Show Values and Confidence Intervals on while you calibrate; hide later for a clean visual.
The Multi-Mode Seasonality Map helps you convert the calendar from an afterthought into a quantitative edge, surfacing when an asset tends to move, expand, or stay quiet—so you can plan, size, and execute with intent.
XAUUSD Multi-Timeframe Supertrend Alert v2**Indicator Overview: XAUUSD Multi-Timeframe Supertrend Alert v2**
**Core Components:**
1. **Multi-Timeframe Supertrend System**
- Two Supertrend indicators (ST1 & ST2) with customizable timeframes
- ST1 typically set to Daily, ST2 to Weekly as main trend
- Visualized with distinct colors and background fills
2. **Customizable SMA**
- Adjustable period and timeframe
- Plotted as blue line for additional trend reference
3. **Neutral Zone System**
- Creates a neutral line offset from ST1 by customizable tick distance
- Yellow dashed line that adjusts based on ST1 trend direction
- **Alert Conditions:**
- **Test Buy Zone**: Both ST1 & ST2 in uptrend AND price enters neutral zone above ST1
- **Test Sell Zone**: Both ST1 & ST2 in downtrend AND price enters neutral zone below ST1
4. **Distance Lines from ST2**
- Upper/lower lines at customizable tick distance from ST2
- Purple dashed lines with touch alerts
**Trading Signals:**
- **Bullish Signal**: Price above ST2 but below ST1 (potential buy)
- **Bearish Signal**: Price below ST2 but above ST1 (potential sell)
- **Neutral Zone Alerts**: Price enters defined zone when both trends align
- **Line Touch Alerts**: Price touches distance lines from ST2
**Alert System:**
- Limited to 3 consecutive alerts per signal type
- Visual markers (triangles, diamonds, circles)
- Background coloring for signal zones
- Separate alert conditions for each signal type
**Visual Features:**
- Candles colored green/red based on signals
- Clear trend visualization with colored backgrounds
- Real-time alert markers without information table clutter
This indicator provides multi-timeframe trend analysis with precise entry zone detection and comprehensive alert system for XAUUSD trading. SAM89 M15, ST1 (5:10) M5, ST2 ( 1,5:20) H1, Test Buy Sell 7000, Line 15000
ATR x Trend x Volume SignalsATR x Trend x Volume Signals is a multi-factor indicator that combines volatility, trend, and volume analysis into one adaptive framework. It is designed for traders who use technical confluence and prefer clear, rule-based setups.
🎯 Purpose
This tool identifies high-probability market moments when volatility structure (ATR), momentum direction (CCI-based trend logic), and volume expansion all align. It helps filter out noise and focus on clean, actionable trade conditions.
⚙️ Structure
The indicator consists of three main analytical layers:
1️⃣ ATR Trailing Stop – calculates two adaptive ATR lines (fast and slow) that define volatility context, trend bias, and potential reversal points.
2️⃣ Trend Indicator (CCI + ATR) – uses a CCI-based logic combined with ATR smoothing to determine the dominant trend direction and reduce false flips.
3️⃣ Volume Analysis – evaluates volume deviations from their historical average using standard deviation. Bars are highlighted as medium, high, or extra-high volume depending on intensity.
💡 Signal Logic
A Buy Signal (green) appears when all of the following are true:
• The ATR (slow) line is green.
• The Trend Indicator is blue.
• A bullish candle closes above both the ATR (slow) and the Trend Indicator.
• The candle shows medium, high, or extra-high volume.
A Sell Signal (red) appears when:
• The ATR (slow) line is red.
• The Trend Indicator is red.
• A bearish candle closes below both the ATR (slow) and the Trend Indicator.
• The candle shows medium, high, or extra-high volume.
Only one signal can appear per ATR trend phase. A new signal is generated only after the ATR direction changes.
❌ Exit Logic
Exit markers are shown when price crosses the slow ATR line. This behavior simulates a trailing stop exit. The exit is triggered one bar after entry to prevent same-bar exits.
⏰ Session Filter
Signals are generated only between the user-defined session start and end times (default: 14:00–18:00 chart time). This allows the trader to limit signal generation to active trading hours.
💬 Practical Use
It is recommended to trade with a fixed risk-reward ratio such as 1 : 1.5. Stop-loss placement should be beyond the slow ATR line and adjusted gradually as the trade develops.
For better confirmation, the Trend Indicator timeframe should be higher than the chart timeframe (for example: trading on 1 min → set Trend Indicator timeframe to 15 min; trading on 5 min → set to 1 hour).
🧠 Main Features
• Dual ATR volatility structure (fast and slow)
• CCI-based trend direction filtering
• Volume deviation heatmap logic
• Time-restricted signal generation
• Dynamic trailing-stop exit system
• Non-repainting logic
• Fully optimized for Pine Script v6
📊 Usage Tip
Best results are achieved when combining this indicator with additional technical context such as support-resistance, higher-timeframe confirmation, or market structure analysis.
📈 Credits
Inspired by:
• ATR Trailing Stop by Ceyhun
• Trend Magic by Kivanc Ozbilgic
• Heatmap Volume by xdecow
SuperTrend Cyan — Split ST & Triple Bands (A/B/C)SuperTrend Cyan — Split ST & Triple Bands (A/B/C)
✨ Concept:
The SuperTrend Cyan indicator expands the classical SuperTrend logic into a split-line + triple-band visualization for clearer structure and volatility mapping.
Instead of a single ATR-based line, this tool separates SuperTrend direction from volatility envelopes (A/B/C), providing a layered view of both regime and range compression.
✨ The design goal:
Preserve the simplicity of SuperTrend
Add volatility context via multi-band envelopes
Provide a compact MTF (Multi-Timeframe) summary for broader trend alignment
✨ How It Works
1. SuperTrend Core (Active & Opposite Lines)
Uses ATR-based bands (Factor × ATR-Length).
Active SuperTrend is plotted according to current regime.
Opposite SuperTrend (optional) shows potential reversal threshold.
2. Triple Band System (A/B/C)
Each band (A, B, C) scales from the median price (hl2) by different ATR multipliers.
A: Outer band (wider, long-range context)
B: Inner band (mid-range activity)
C: Core band (closest to price, short-term compression)
Smoothness can be controlled with EMA.
Uptrend fills are lime-toned, downtrend fills are red-toned, with adjustable opacity (gap intensity).
3. Automatic Directional Switch
When the regime flips from up → down (or vice versa), the overlay automatically switches between lower and upper bands for a clean transition.
4. Multi-Timeframe SuperTrend Table
Displays SuperTrend direction across 5m, 15m, 1h, 4h, and 1D frames.
Green ▲ = Uptrend, Red ▼ = Downtrend.
Useful for checking cross-timeframe trend alignment.
✨ How to Read It
Green SuperTrend + Lime Bands
- Uptrend regime; volatility expanding upward
Red SuperTrend + Red Bands
- Downtrend regime; volatility expanding downward
Narrow gaps (A–C)
- Low volatility / compression (potential squeeze)
Wide gaps
- High volatility / active trend phase
Opposite ST line close to price
- Early warning for regime transition
✨ Practical Use
Identify trend direction (SuperTrend color & line position).
Assess volatility conditions (band width and gap transparency).
Watch for MTF alignment: consistent up/down signals across 1h–4h–1D = strong structural trend.
Combine with momentum indicators (e.g., RSI, DFI, PCI) for confirmation of trend maturity or exhaustion.
✨ Customization Tips
ST Factor / ATR Length
- Adjust sensitivity of SuperTrend direction changes
Band ATR Length
- Controls overall smoothness of volatility envelopes
Band Multipliers (A/B/C)
- Define how wide each volatility band extends
Gap Opacity
- Affects visual contrast between layers
MTF Table
- Enable/disable multi-timeframe display
✨ Educational Value
This script visualizes the interaction between trend direction (SuperTrend) and volatility envelopes, helping traders understand how price reacts within layered ATR zones.
It also introduces a clean MTF (multi-timeframe) perspective — ideal for discretionary and system traders alike.
✨ Disclaimer
This indicator is provided for educational and research purposes only.
It does not constitute financial advice or a trading signal.
Use at your own discretion and always confirm with additional tools.
───────────────────────────────
📘 한국어 설명 (Korean translation below)
───────────────────────────────
✨개념
SuperTrend Cyan 지표는 기존의 SuperTrend를 확장하여,
추세선 분리(Split Line) + 3중 밴드 시스템(Triple Bands) 으로
시장의 구조적 흐름과 변동성 범위를 동시에 시각화합니다.
단순한 SuperTrend의 강점을 유지하면서도,
ATR 기반의 A/B/C 밴드를 통해 변동성 압축·확장 구간을 직관적으로 파악할 수 있습니다.
✨ 작동 방식
1. SuperTrend 코어 (활성/반대 라인)
ATR×Factor를 기반으로 추세선을 계산합니다.
현재 추세 방향에 따라 활성 라인이 표시되고, “Show Opposite” 옵션을 켜면 반대편 경계선도 함께 보입니다.
2. 트리플 밴드 시스템 (A/B/C)
hl2(중간값)를 기준으로 ATR 배수에 따라 세 개의 밴드를 계산합니다.
A: 외곽 밴드 (가장 넓고 장기 구조 반영)
B: 중간 밴드 (중기적 움직임)
C: 코어 밴드 (가격에 가장 근접, 단기 변동성 반영)
EMA 스무딩으로 부드럽게 조정 가능.
업트렌드 구간은 라임색, 다운트렌드는 빨간색 음영으로 표시됩니다.
3. 자동 전환 시스템
추세가 전환될 때(Up ↔ Down), 밴드 오버레이도 자동으로 교체되어 깔끔한 시각적 구조를 유지합니다.
4. MTF SuperTrend 테이블
5m / 15m / 1h / 4h / 1D 프레임별 SuperTrend 방향을 표시합니다.
초록 ▲ = 상승, 빨강 ▼ = 하락.
복수 타임프레임 정렬 확인용으로 유용합니다.
✨ 해석 방법
초록 SuperTrend + 라임 밴드
- 상승 추세 및 확장 구간
빨강 SuperTrend + 레드 밴드
- 하락 추세 및 확장 구간
밴드 폭이 좁음
- 변동성 축소 (스퀴즈)
밴드 폭이 넓음
- 변동성 확장, 추세 강화
반대선이 근접
- 추세 전환 가능성 높음
✨ 활용 방법
SuperTrend 색상으로 추세 방향을 확인
A/B/C 밴드 폭으로 변동성 수준을 판단
MTF 테이블을 통해 복수 타임프레임 정렬 여부 확인
RSI, DFI, PCI 등 다른 지표와 함께 활용 시, 추세 피로·모멘텀 변화를 조기에 파악 가능
✨ 교육적 가치
이 스크립트는 추세 구조(SuperTrend) 와 변동성 레이어(ATR Bands) 의 상호작용을
시각적으로 학습하기 위한 교육용 지표입니다.
또한, MTF 구조를 통해 시장의 “위계적 정렬(hierarchical alignment)”을 쉽게 인식할 수 있습니다.
✨ 면책
이 지표는 교육 및 연구 목적으로만 제공됩니다.
투자 판단의 책임은 사용자 본인에게 있으며, 본 지표는 매매 신호를 보장하지 않습니다.
Candlestick StrengthThis indicator quantifies the “energy” of each candlestick by combining its height (high–low span), trading volume, and internal structure (body vs. wick proportions). It provides a numeric measure of how strongly each candle contributes to market momentum, allowing traders to distinguish meaningful price action from indecision or noise.
Concept
Every candlestick represents a short-term contest between buyers and sellers. Large candles with significant volume indicate strong market participation, while small or low-volume candles suggest hesitation or absorption. Candlestick Strength captures this by calculating a normalized measure of each candle’s energy relative to recent activity, making it comparable across different market conditions and timeframes.
The indicator also analyzes the candle’s internal structure:
The body reflects net directional movement.
The wicks represent back-and-forth price traversal within the candle. Because wick movement does not fully contribute to directional momentum, it is weighted at half the body’s contribution. This ensures the indicator emphasizes sustained directional pressure while still acknowledging rejection or absorption.
Interpretation
High values indicate candles with energy above recent averages — suggesting expanding momentum and strong directional intent.
Average values reflect typical candle activity, representing neutral or steady market behavior.
Low values suggest weak candles — either the market is pausing, consolidating, or momentum is fading.
The outputs are displayed as a symmetric histogram: bullish candle energy is shown in green above zero, bearish energy in red below zero, with ±1 reference lines marking the normalized average energy level.
Usage
Combine with trend analysis, swing highs/lows, or volume-weighted averages to validate breakouts or trend continuation.
Monitor for divergence between price movement and candle energy to identify exhaustion, absorption, or potential reversals.
Filter out false momentum signals caused by narrow-range or low-volume candles.
Adaptable across timeframes: normalized energy allows comparison between small and large timeframe candles.
Vandan V2Vandan V2 is an automated trend-following strategy for NASDAQ E-mini Futures (NQ1!).
It uses multi-timeframe momentum and volatility filters to identify high-probability entries.
Includes dynamic risk management and trailing logic optimized for intraday trading.
Aggression IndexAggression index is a simple yet very helpful indicator.
It measures:
- the number of bull vs bear candles;
- bull vs bear volume;
- length bull vs bear candlesticks over a predetermined lookback period.
It will use that information to come up with a delta for each measurement and an Aggression Index in the end.
FXbyFaris – Liquidity & Trend Frameworkfxbyfaris is a ultimate pro strategy which gives you accurate entry and exits
pine script tradingbot - many ema oscillator## 🧭 **Many EMA Oscillator (TradingView Pine Script Indicator)**
*A multi-layer EMA differential oscillator for trend strength and momentum analysis*
---
### 🧩 **Overview**
The **Many EMA Oscillator** is a **TradingView Pine Script indicator** designed to help traders visualize **trend direction**, **momentum strength**, and **multi-timeframe EMA alignment** in one clean oscillator panel.
It’s a **custom EMA-based trend indicator** that shows how fast or slow different **Exponential Moving Averages (EMAs)** are expanding or contracting — helping you identify **bullish and bearish momentum shifts** early.
This **Pine Script EMA indicator** is especially useful for traders looking to combine multiple **EMA signals** into one **momentum oscillator** for better clarity and precision.
---
### ⚙️ **How It Works**
1. **Multiple EMA Layers:**
The indicator calculates seven **EMAs** (default: 20, 50, 100, 150, 200, 300) and applies a **smoothing filter** using another EMA (default smoothing = 20).
This removes short-term noise and gives a smoother, professional-grade momentum reading.
2. **EMA Gap Analysis:**
The oscillator measures the **difference between consecutive EMAs**, revealing how trend layers are separating or converging.
```
diff1 = EMA(20) - EMA(50)
diff2 = EMA(50) - EMA(100)
diff3 = EMA(100) - EMA(150)
diff4 = EMA(150) - EMA(200)
diff5 = EMA(200) - EMA(300)
```
These gaps (or “differentials”) show **trend acceleration or compression**, acting like a **multi-EMA MACD system**.
3. **Color-Coded Visualization:**
Each differential (`diff1`–`diff5`) is plotted as a **histogram**:
- 🟢 **Green bars** → EMAs expanding → bullish momentum growing
- 🔴 **Red bars** → EMAs contracting → bearish momentum or correction
This gives a clean, compact view of **trend strength** without cluttering your chart.
4. **Automatic Momentum Signals:**
- **🟡 Up Triangle** → All EMA gaps increasing → strong bullish trend alignment
- **⚪ Down Triangle** → All EMA gaps decreasing → trend weakening or bearish transition
---
### 📊 **Inputs**
| Input | Default | Description |
|-------|----------|-------------|
| `smmoth_emas` | 20 | Smoothing factor for all EMAs |
| `Length2`–`Length7` | 20–300 | Adjustable EMA periods |
| `Length21`, `Length31`, `Length41`, `Length51` | Optional | For secondary EMA analysis |
---
### 🧠 **Interpretation Guide**
| Observation | Meaning |
|--------------|----------|
| Increasing green bars | Trend acceleration and bullish continuation |
| Decreasing red bars | Trend exhaustion or sideways consolidation |
| Yellow triangles | All EMA layers aligned bullishly |
| White triangles | All EMA layers aligned bearishly |
This **EMA oscillator for TradingView** simplifies **multi-EMA trading strategies** by showing alignment strength in one place.
It works great for **swing traders**, **scalpers**, and **trend-following systems**.
---
### 🧪 **Best Practices for Use**
- Works on **all TradingView timeframes** (1m, 5m, 1h, 1D, etc.)
- Suitable for **stocks, forex, crypto, and indices**
- Combine with **RSI**, **MACD**, or **price action** confirmation
- Excellent for detecting **EMA compression zones**, **trend continuation**, or **momentum shifts**
- Can be used as part of a **multi-EMA trading strategy** or **trend strength indicator setup**
---
### 💡 **Why It Stands Out**
- 100% built in **Pine Script v6**
- Optimized for **smooth EMA transitions**
- Simple color-coded momentum visualization
- Professional-grade **multi-timeframe trend oscillator**
This is one of the most **lightweight and powerful EMA oscillators** available for TradingView users who prefer clarity over clutter.
---
### ⚠️ **Disclaimer**
This indicator is published for **educational and analytical purposes only**.
It does **not provide financial advice**, buy/sell signals, or investment recommendations.
Always backtest before live use and trade responsibly.
---
### 👨💻 **Author**
Developed by **@algo_coders**
Built in **Pine Script v6** on **TradingView**
Licensed under the (mozilla.org)
Quantum Rotational Field MappingQuantum Rotational Field Mapping (QRFM):
Phase Coherence Detection Through Complex-Plane Oscillator Analysis
Quantum Rotational Field Mapping applies complex-plane mathematics and phase-space analysis to oscillator ensembles, identifying high-probability trend ignition points by measuring when multiple independent oscillators achieve phase coherence. Unlike traditional multi-oscillator approaches that simply stack indicators or use boolean AND/OR logic, this system converts each oscillator into a rotating phasor (vector) in the complex plane and calculates the Coherence Index (CI) —a mathematical measure of how tightly aligned the ensemble has become—then generates signals only when alignment, phase direction, and pairwise entanglement all converge.
The indicator combines three mathematical frameworks: phasor representation using analytic signal theory to extract phase and amplitude from each oscillator, coherence measurement using vector summation in the complex plane to quantify group alignment, and entanglement analysis that calculates pairwise phase agreement across all oscillator combinations. This creates a multi-dimensional confirmation system that distinguishes between random oscillator noise and genuine regime transitions.
What Makes This Original
Complex-Plane Phasor Framework
This indicator implements classical signal processing mathematics adapted for market oscillators. Each oscillator—whether RSI, MACD, Stochastic, CCI, Williams %R, MFI, ROC, or TSI—is first normalized to a common scale, then converted into a complex-plane representation using an in-phase (I) and quadrature (Q) component. The in-phase component is the oscillator value itself, while the quadrature component is calculated as the first difference (derivative proxy), creating a velocity-aware representation.
From these components, the system extracts:
Phase (φ) : Calculated as φ = atan2(Q, I), representing the oscillator's position in its cycle (mapped to -180° to +180°)
Amplitude (A) : Calculated as A = √(I² + Q²), representing the oscillator's strength or conviction
This mathematical approach is fundamentally different from simply reading oscillator values. A phasor captures both where an oscillator is in its cycle (phase angle) and how strongly it's expressing that position (amplitude). Two oscillators can have the same value but be in opposite phases of their cycles—traditional analysis would see them as identical, while QRFM sees them as 180° out of phase (contradictory).
Coherence Index Calculation
The core innovation is the Coherence Index (CI) , borrowed from physics and signal processing. When you have N oscillators, each with phase φₙ, you can represent each as a unit vector in the complex plane: e^(iφₙ) = cos(φₙ) + i·sin(φₙ).
The CI measures what happens when you sum all these vectors:
Resultant Vector : R = Σ e^(iφₙ) = Σ cos(φₙ) + i·Σ sin(φₙ)
Coherence Index : CI = |R| / N
Where |R| is the magnitude of the resultant vector and N is the number of active oscillators.
The CI ranges from 0 to 1:
CI = 1.0 : Perfect coherence—all oscillators have identical phase angles, vectors point in the same direction, creating maximum constructive interference
CI = 0.0 : Complete decoherence—oscillators are randomly distributed around the circle, vectors cancel out through destructive interference
0 < CI < 1 : Partial alignment—some clustering with some scatter
This is not a simple average or correlation. The CI captures phase synchronization across the entire ensemble simultaneously. When oscillators phase-lock (align their cycles), the CI spikes regardless of their individual values. This makes it sensitive to regime transitions that traditional indicators miss.
Dominant Phase and Direction Detection
Beyond measuring alignment strength, the system calculates the dominant phase of the ensemble—the direction the resultant vector points:
Dominant Phase : φ_dom = atan2(Σ sin(φₙ), Σ cos(φₙ))
This gives the "average direction" of all oscillator phases, mapped to -180° to +180°:
+90° to -90° (right half-plane): Bullish phase dominance
+90° to +180° or -90° to -180° (left half-plane): Bearish phase dominance
The combination of CI magnitude (coherence strength) and dominant phase angle (directional bias) creates a two-dimensional signal space. High CI alone is insufficient—you need high CI plus dominant phase pointing in a tradeable direction. This dual requirement is what separates QRFM from simple oscillator averaging.
Entanglement Matrix and Pairwise Coherence
While the CI measures global alignment, the entanglement matrix measures local pairwise relationships. For every pair of oscillators (i, j), the system calculates:
E(i,j) = |cos(φᵢ - φⱼ)|
This represents the phase agreement between oscillators i and j:
E = 1.0 : Oscillators are in-phase (0° or 360° apart)
E = 0.0 : Oscillators are in quadrature (90° apart, orthogonal)
E between 0 and 1 : Varying degrees of alignment
The system counts how many oscillator pairs exceed a user-defined entanglement threshold (e.g., 0.7). This entangled pairs count serves as a confirmation filter: signals require not just high global CI, but also a minimum number of strong pairwise agreements. This prevents false ignitions where CI is high but driven by only two oscillators while the rest remain scattered.
The entanglement matrix creates an N×N symmetric matrix that can be visualized as a web—when many cells are bright (high E values), the ensemble is highly interconnected. When cells are dark, oscillators are moving independently.
Phase-Lock Tolerance Mechanism
A complementary confirmation layer is the phase-lock detector . This calculates the maximum phase spread across all oscillators:
For all pairs (i,j), compute angular distance: Δφ = |φᵢ - φⱼ|, wrapping at 180°
Max Spread = maximum Δφ across all pairs
If max spread < user threshold (e.g., 35°), the ensemble is considered phase-locked —all oscillators are within a narrow angular band.
This differs from entanglement: entanglement measures pairwise cosine similarity (magnitude of alignment), while phase-lock measures maximum angular deviation (tightness of clustering). Both must be satisfied for the highest-conviction signals.
Multi-Layer Visual Architecture
QRFM includes six visual components that represent the same underlying mathematics from different perspectives:
Circular Orbit Plot : A polar coordinate grid showing each oscillator as a vector from origin to perimeter. Angle = phase, radius = amplitude. This is a real-time snapshot of the complex plane. When vectors converge (point in similar directions), coherence is high. When scattered randomly, coherence is low. Users can see phase alignment forming before CI numerically confirms it.
Phase-Time Heat Map : A 2D matrix with rows = oscillators and columns = time bins. Each cell is colored by the oscillator's phase at that time (using a gradient where color hue maps to angle). Horizontal color bands indicate sustained phase alignment over time. Vertical color bands show moments when all oscillators shared the same phase (ignition points). This provides historical pattern recognition.
Entanglement Web Matrix : An N×N grid showing E(i,j) for all pairs. Cells are colored by entanglement strength—bright yellow/gold for high E, dark gray for low E. This reveals which oscillators are driving coherence and which are lagging. For example, if RSI and MACD show high E but Stochastic shows low E with everything, Stochastic is the outlier.
Quantum Field Cloud : A background color overlay on the price chart. Color (green = bullish, red = bearish) is determined by dominant phase. Opacity is determined by CI—high CI creates dense, opaque cloud; low CI creates faint, nearly invisible cloud. This gives an atmospheric "feel" for regime strength without looking at numbers.
Phase Spiral : A smoothed plot of dominant phase over recent history, displayed as a curve that wraps around price. When the spiral is tight and rotating steadily, the ensemble is in coherent rotation (trending). When the spiral is loose or erratic, coherence is breaking down.
Dashboard : A table showing real-time metrics: CI (as percentage), dominant phase (in degrees with directional arrow), field strength (CI × average amplitude), entangled pairs count, phase-lock status (locked/unlocked), quantum state classification ("Ignition", "Coherent", "Collapse", "Chaos"), and collapse risk (recent CI change normalized to 0-100%).
Each component is independently toggleable, allowing users to customize their workspace. The orbit plot is the most essential—it provides intuitive, visual feedback on phase alignment that no numerical dashboard can match.
Core Components and How They Work Together
1. Oscillator Normalization Engine
The foundation is creating a common measurement scale. QRFM supports eight oscillators:
RSI : Normalized from to using overbought/oversold levels (70, 30) as anchors
MACD Histogram : Normalized by dividing by rolling standard deviation, then clamped to
Stochastic %K : Normalized from using (80, 20) anchors
CCI : Divided by 200 (typical extreme level), clamped to
Williams %R : Normalized from using (-20, -80) anchors
MFI : Normalized from using (80, 20) anchors
ROC : Divided by 10, clamped to
TSI : Divided by 50, clamped to
Each oscillator can be individually enabled/disabled. Only active oscillators contribute to phase calculations. The normalization removes scale differences—a reading of +0.8 means "strongly bullish" regardless of whether it came from RSI or TSI.
2. Analytic Signal Construction
For each active oscillator at each bar, the system constructs the analytic signal:
In-Phase (I) : The normalized oscillator value itself
Quadrature (Q) : The bar-to-bar change in the normalized value (first derivative approximation)
This creates a 2D representation: (I, Q). The phase is extracted as:
φ = atan2(Q, I) × (180 / π)
This maps the oscillator to a point on the unit circle. An oscillator at the same value but rising (positive Q) will have a different phase than one that is falling (negative Q). This velocity-awareness is critical—it distinguishes between "at resistance and stalling" versus "at resistance and breaking through."
The amplitude is extracted as:
A = √(I² + Q²)
This represents the distance from origin in the (I, Q) plane. High amplitude means the oscillator is far from neutral (strong conviction). Low amplitude means it's near zero (weak/transitional state).
3. Coherence Calculation Pipeline
For each bar (or every Nth bar if phase sample rate > 1 for performance):
Step 1 : Extract phase φₙ for each of the N active oscillators
Step 2 : Compute complex exponentials: Zₙ = e^(i·φₙ·π/180) = cos(φₙ·π/180) + i·sin(φₙ·π/180)
Step 3 : Sum the complex exponentials: R = Σ Zₙ = (Σ cos φₙ) + i·(Σ sin φₙ)
Step 4 : Calculate magnitude: |R| = √
Step 5 : Normalize by count: CI_raw = |R| / N
Step 6 : Smooth the CI: CI = SMA(CI_raw, smoothing_window)
The smoothing step (default 2 bars) removes single-bar noise spikes while preserving structural coherence changes. Users can adjust this to control reactivity versus stability.
The dominant phase is calculated as:
φ_dom = atan2(Σ sin φₙ, Σ cos φₙ) × (180 / π)
This is the angle of the resultant vector R in the complex plane.
4. Entanglement Matrix Construction
For all unique pairs of oscillators (i, j) where i < j:
Step 1 : Get phases φᵢ and φⱼ
Step 2 : Compute phase difference: Δφ = φᵢ - φⱼ (in radians)
Step 3 : Calculate entanglement: E(i,j) = |cos(Δφ)|
Step 4 : Store in symmetric matrix: matrix = matrix = E(i,j)
The matrix is then scanned: count how many E(i,j) values exceed the user-defined threshold (default 0.7). This count is the entangled pairs metric.
For visualization, the matrix is rendered as an N×N table where cell brightness maps to E(i,j) intensity.
5. Phase-Lock Detection
Step 1 : For all unique pairs (i, j), compute angular distance: Δφ = |φᵢ - φⱼ|
Step 2 : Wrap angles: if Δφ > 180°, set Δφ = 360° - Δφ
Step 3 : Find maximum: max_spread = max(Δφ) across all pairs
Step 4 : Compare to tolerance: phase_locked = (max_spread < tolerance)
If phase_locked is true, all oscillators are within the specified angular cone (e.g., 35°). This is a boolean confirmation filter.
6. Signal Generation Logic
Signals are generated through multi-layer confirmation:
Long Ignition Signal :
CI crosses above ignition threshold (e.g., 0.80)
AND dominant phase is in bullish range (-90° < φ_dom < +90°)
AND phase_locked = true
AND entangled_pairs >= minimum threshold (e.g., 4)
Short Ignition Signal :
CI crosses above ignition threshold
AND dominant phase is in bearish range (φ_dom < -90° OR φ_dom > +90°)
AND phase_locked = true
AND entangled_pairs >= minimum threshold
Collapse Signal :
CI at bar minus CI at current bar > collapse threshold (e.g., 0.55)
AND CI at bar was above 0.6 (must collapse from coherent state, not from already-low state)
These are strict conditions. A high CI alone does not generate a signal—dominant phase must align with direction, oscillators must be phase-locked, and sufficient pairwise entanglement must exist. This multi-factor gating dramatically reduces false signals compared to single-condition triggers.
Calculation Methodology
Phase 1: Oscillator Computation and Normalization
On each bar, the system calculates the raw values for all enabled oscillators using standard Pine Script functions:
RSI: ta.rsi(close, length)
MACD: ta.macd() returning histogram component
Stochastic: ta.stoch() smoothed with ta.sma()
CCI: ta.cci(close, length)
Williams %R: ta.wpr(length)
MFI: ta.mfi(hlc3, length)
ROC: ta.roc(close, length)
TSI: ta.tsi(close, short, long)
Each raw value is then passed through a normalization function:
normalize(value, overbought_level, oversold_level) = 2 × (value - oversold) / (overbought - oversold) - 1
This maps the oscillator's typical range to , where -1 represents extreme bearish, 0 represents neutral, and +1 represents extreme bullish.
For oscillators without fixed ranges (MACD, ROC, TSI), statistical normalization is used: divide by a rolling standard deviation or fixed divisor, then clamp to .
Phase 2: Phasor Extraction
For each normalized oscillator value val:
I = val (in-phase component)
Q = val - val (quadrature component, first difference)
Phase calculation:
phi_rad = atan2(Q, I)
phi_deg = phi_rad × (180 / π)
Amplitude calculation:
A = √(I² + Q²)
These values are stored in arrays: osc_phases and osc_amps for each oscillator n.
Phase 3: Complex Summation and Coherence
Initialize accumulators:
sum_cos = 0
sum_sin = 0
For each oscillator n = 0 to N-1:
phi_rad = osc_phases × (π / 180)
sum_cos += cos(phi_rad)
sum_sin += sin(phi_rad)
Resultant magnitude:
resultant_mag = √(sum_cos² + sum_sin²)
Coherence Index (raw):
CI_raw = resultant_mag / N
Smoothed CI:
CI = SMA(CI_raw, smoothing_window)
Dominant phase:
phi_dom_rad = atan2(sum_sin, sum_cos)
phi_dom_deg = phi_dom_rad × (180 / π)
Phase 4: Entanglement Matrix Population
For i = 0 to N-2:
For j = i+1 to N-1:
phi_i = osc_phases × (π / 180)
phi_j = osc_phases × (π / 180)
delta_phi = phi_i - phi_j
E = |cos(delta_phi)|
matrix_index_ij = i × N + j
matrix_index_ji = j × N + i
entangle_matrix = E
entangle_matrix = E
if E >= threshold:
entangled_pairs += 1
The matrix uses flat array storage with index mapping: index(row, col) = row × N + col.
Phase 5: Phase-Lock Check
max_spread = 0
For i = 0 to N-2:
For j = i+1 to N-1:
delta = |osc_phases - osc_phases |
if delta > 180:
delta = 360 - delta
max_spread = max(max_spread, delta)
phase_locked = (max_spread < tolerance)
Phase 6: Signal Evaluation
Ignition Long :
ignition_long = (CI crosses above threshold) AND
(phi_dom > -90 AND phi_dom < 90) AND
phase_locked AND
(entangled_pairs >= minimum)
Ignition Short :
ignition_short = (CI crosses above threshold) AND
(phi_dom < -90 OR phi_dom > 90) AND
phase_locked AND
(entangled_pairs >= minimum)
Collapse :
CI_prev = CI
collapse = (CI_prev - CI > collapse_threshold) AND (CI_prev > 0.6)
All signals are evaluated on bar close. The crossover and crossunder functions ensure signals fire only once when conditions transition from false to true.
Phase 7: Field Strength and Visualization Metrics
Average Amplitude :
avg_amp = (Σ osc_amps ) / N
Field Strength :
field_strength = CI × avg_amp
Collapse Risk (for dashboard):
collapse_risk = (CI - CI) / max(CI , 0.1)
collapse_risk_pct = clamp(collapse_risk × 100, 0, 100)
Quantum State Classification :
if (CI > threshold AND phase_locked):
state = "Ignition"
else if (CI > 0.6):
state = "Coherent"
else if (collapse):
state = "Collapse"
else:
state = "Chaos"
Phase 8: Visual Rendering
Orbit Plot : For each oscillator, convert polar (phase, amplitude) to Cartesian (x, y) for grid placement:
radius = amplitude × grid_center × 0.8
x = radius × cos(phase × π/180)
y = radius × sin(phase × π/180)
col = center + x (mapped to grid coordinates)
row = center - y
Heat Map : For each oscillator row and time column, retrieve historical phase value at lookback = (columns - col) × sample_rate, then map phase to color using a hue gradient.
Entanglement Web : Render matrix as table cell with background color opacity = E(i,j).
Field Cloud : Background color = (phi_dom > -90 AND phi_dom < 90) ? green : red, with opacity = mix(min_opacity, max_opacity, CI).
All visual components render only on the last bar (barstate.islast) to minimize computational overhead.
How to Use This Indicator
Step 1 : Apply QRFM to your chart. It works on all timeframes and asset classes, though 15-minute to 4-hour timeframes provide the best balance of responsiveness and noise reduction.
Step 2 : Enable the dashboard (default: top right) and the circular orbit plot (default: middle left). These are your primary visual feedback tools.
Step 3 : Optionally enable the heat map, entanglement web, and field cloud based on your preference. New users may find all visuals overwhelming; start with dashboard + orbit plot.
Step 4 : Observe for 50-100 bars to let the indicator establish baseline coherence patterns. Markets have different "normal" CI ranges—some instruments naturally run higher or lower coherence.
Understanding the Circular Orbit Plot
The orbit plot is a polar grid showing oscillator vectors in real-time:
Center point : Neutral (zero phase and amplitude)
Each vector : A line from center to a point on the grid
Vector angle : The oscillator's phase (0° = right/east, 90° = up/north, 180° = left/west, -90° = down/south)
Vector length : The oscillator's amplitude (short = weak signal, long = strong signal)
Vector label : First letter of oscillator name (R = RSI, M = MACD, etc.)
What to watch :
Convergence : When all vectors cluster in one quadrant or sector, CI is rising and coherence is forming. This is your pre-signal warning.
Scatter : When vectors point in random directions (360° spread), CI is low and the market is in a non-trending or transitional regime.
Rotation : When the cluster rotates smoothly around the circle, the ensemble is in coherent oscillation—typically seen during steady trends.
Sudden flips : When the cluster rapidly jumps from one side to the opposite (e.g., +90° to -90°), a phase reversal has occurred—often coinciding with trend reversals.
Example: If you see RSI, MACD, and Stochastic all pointing toward 45° (northeast) with long vectors, while CCI, TSI, and ROC point toward 40-50° as well, coherence is high and dominant phase is bullish. Expect an ignition signal if CI crosses threshold.
Reading Dashboard Metrics
The dashboard provides numerical confirmation of what the orbit plot shows visually:
CI : Displays as 0-100%. Above 70% = high coherence (strong regime), 40-70% = moderate, below 40% = low (poor conditions for trend entries).
Dom Phase : Angle in degrees with directional arrow. ⬆ = bullish bias, ⬇ = bearish bias, ⬌ = neutral.
Field Strength : CI weighted by amplitude. High values (> 0.6) indicate not just alignment but strong alignment.
Entangled Pairs : Count of oscillator pairs with E > threshold. Higher = more confirmation. If minimum is set to 4, you need at least 4 pairs entangled for signals.
Phase Lock : 🔒 YES (all oscillators within tolerance) or 🔓 NO (spread too wide).
State : Real-time classification:
🚀 IGNITION: CI just crossed threshold with phase-lock
⚡ COHERENT: CI is high and stable
💥 COLLAPSE: CI has dropped sharply
🌀 CHAOS: Low CI, scattered phases
Collapse Risk : 0-100% scale based on recent CI change. Above 50% warns of imminent breakdown.
Interpreting Signals
Long Ignition (Blue Triangle Below Price) :
Occurs when CI crosses above threshold (e.g., 0.80)
Dominant phase is in bullish range (-90° to +90°)
All oscillators are phase-locked (within tolerance)
Minimum entangled pairs requirement met
Interpretation : The oscillator ensemble has transitioned from disorder to coherent bullish alignment. This is a high-probability long entry point. The multi-layer confirmation (CI + phase direction + lock + entanglement) ensures this is not a single-oscillator whipsaw.
Short Ignition (Red Triangle Above Price) :
Same conditions as long, but dominant phase is in bearish range (< -90° or > +90°)
Interpretation : Coherent bearish alignment has formed. High-probability short entry.
Collapse (Circles Above and Below Price) :
CI has dropped by more than the collapse threshold (e.g., 0.55) over a 5-bar window
CI was previously above 0.6 (collapsing from coherent state)
Interpretation : Phase coherence has broken down. If you are in a position, this is an exit warning. If looking to enter, stand aside—regime is transitioning.
Phase-Time Heat Map Patterns
Enable the heat map and position it at bottom right. The rows represent individual oscillators, columns represent time bins (most recent on left).
Pattern: Horizontal Color Bands
If a row (e.g., RSI) shows consistent color across columns (say, green for several bins), that oscillator has maintained stable phase over time. If all rows show horizontal bands of similar color, the entire ensemble has been phase-locked for an extended period—this is a strong trending regime.
Pattern: Vertical Color Bands
If a column (single time bin) shows all cells with the same or very similar color, that moment in time had high coherence. These vertical bands often align with ignition signals or major price pivots.
Pattern: Rainbow Chaos
If cells are random colors (red, green, yellow mixed with no pattern), coherence is low. The ensemble is scattered. Avoid trading during these periods unless you have external confirmation.
Pattern: Color Transition
If you see a row transition from red to green (or vice versa) sharply, that oscillator has phase-flipped. If multiple rows do this simultaneously, a regime change is underway.
Entanglement Web Analysis
Enable the web matrix (default: opposite corner from heat map). It shows an N×N grid where N = number of active oscillators.
Bright Yellow/Gold Cells : High pairwise entanglement. For example, if the RSI-MACD cell is bright gold, those two oscillators are moving in phase. If the RSI-Stochastic cell is bright, they are entangled as well.
Dark Gray Cells : Low entanglement. Oscillators are decorrelated or in quadrature.
Diagonal : Always marked with "—" because an oscillator is always perfectly entangled with itself.
How to use :
Scan for clustering: If most cells are bright, coherence is high across the board. If only a few cells are bright, coherence is driven by a subset (e.g., RSI and MACD are aligned, but nothing else is—weak signal).
Identify laggards: If one row/column is entirely dark, that oscillator is the outlier. You may choose to disable it or monitor for when it joins the group (late confirmation).
Watch for web formation: During low-coherence periods, the matrix is mostly dark. As coherence builds, cells begin lighting up. A sudden "web" of connections forming visually precedes ignition signals.
Trading Workflow
Step 1: Monitor Coherence Level
Check the dashboard CI metric or observe the orbit plot. If CI is below 40% and vectors are scattered, conditions are poor for trend entries. Wait.
Step 2: Detect Coherence Building
When CI begins rising (say, from 30% to 50-60%) and you notice vectors on the orbit plot starting to cluster, coherence is forming. This is your alert phase—do not enter yet, but prepare.
Step 3: Confirm Phase Direction
Check the dominant phase angle and the orbit plot quadrant where clustering is occurring:
Clustering in right half (0° to ±90°): Bullish bias forming
Clustering in left half (±90° to 180°): Bearish bias forming
Verify the dashboard shows the corresponding directional arrow (⬆ or ⬇).
Step 4: Wait for Signal Confirmation
Do not enter based on rising CI alone. Wait for the full ignition signal:
CI crosses above threshold
Phase-lock indicator shows 🔒 YES
Entangled pairs count >= minimum
Directional triangle appears on chart
This ensures all layers have aligned.
Step 5: Execute Entry
Long : Blue triangle below price appears → enter long
Short : Red triangle above price appears → enter short
Step 6: Position Management
Initial Stop : Place stop loss based on your risk management rules (e.g., recent swing low/high, ATR-based buffer).
Monitoring :
Watch the field cloud density. If it remains opaque and colored in your direction, the regime is intact.
Check dashboard collapse risk. If it rises above 50%, prepare for exit.
Monitor the orbit plot. If vectors begin scattering or the cluster flips to the opposite side, coherence is breaking.
Exit Triggers :
Collapse signal fires (circles appear)
Dominant phase flips to opposite half-plane
CI drops below 40% (coherence lost)
Price hits your profit target or trailing stop
Step 7: Post-Exit Analysis
After exiting, observe whether a new ignition forms in the opposite direction (reversal) or if CI remains low (transition to range). Use this to decide whether to re-enter, reverse, or stand aside.
Best Practices
Use Price Structure as Context
QRFM identifies when coherence forms but does not specify where price will go. Combine ignition signals with support/resistance levels, trendlines, or chart patterns. For example:
Long ignition near a major support level after a pullback: high-probability bounce
Long ignition in the middle of a range with no structure: lower probability
Multi-Timeframe Confirmation
Open QRFM on two timeframes simultaneously:
Higher timeframe (e.g., 4-hour): Use CI level to determine regime bias. If 4H CI is above 60% and dominant phase is bullish, the market is in a bullish regime.
Lower timeframe (e.g., 15-minute): Execute entries on ignition signals that align with the higher timeframe bias.
This prevents counter-trend trades and increases win rate.
Distinguish Between Regime Types
High CI, stable dominant phase (State: Coherent) : Trending market. Ignitions are continuation signals; collapses are profit-taking or reversal warnings.
Low CI, erratic dominant phase (State: Chaos) : Ranging or choppy market. Avoid ignition signals or reduce position size. Wait for coherence to establish.
Moderate CI with frequent collapses : Whipsaw environment. Use wider stops or stand aside.
Adjust Parameters to Instrument and Timeframe
Crypto/Forex (high volatility) : Lower ignition threshold (0.65-0.75), lower CI smoothing (2-3), shorter oscillator lengths (7-10).
Stocks/Indices (moderate volatility) : Standard settings (threshold 0.75-0.85, smoothing 5-7, oscillator lengths 14).
Lower timeframes (5-15 min) : Reduce phase sample rate to 1-2 for responsiveness.
Higher timeframes (daily+) : Increase CI smoothing and oscillator lengths for noise reduction.
Use Entanglement Count as Conviction Filter
The minimum entangled pairs setting controls signal strictness:
Low (1-2) : More signals, lower quality (acceptable if you have other confirmation)
Medium (3-5) : Balanced (recommended for most traders)
High (6+) : Very strict, fewer signals, highest quality
Adjust based on your trade frequency preference and risk tolerance.
Monitor Oscillator Contribution
Use the entanglement web to see which oscillators are driving coherence. If certain oscillators are consistently dark (low E with all others), they may be adding noise. Consider disabling them. For example:
On low-volume instruments, MFI may be unreliable → disable MFI
On strongly trending instruments, mean-reversion oscillators (Stochastic, RSI) may lag → reduce weight or disable
Respect the Collapse Signal
Collapse events are early warnings. Price may continue in the original direction for several bars after collapse fires, but the underlying regime has weakened. Best practice:
If in profit: Take partial or full profit on collapse
If at breakeven/small loss: Exit immediately
If collapse occurs shortly after entry: Likely a false ignition; exit to avoid drawdown
Collapses do not guarantee immediate reversals—they signal uncertainty .
Combine with Volume Analysis
If your instrument has reliable volume:
Ignitions with expanding volume: Higher conviction
Ignitions with declining volume: Weaker, possibly false
Collapses with volume spikes: Strong reversal signal
Collapses with low volume: May just be consolidation
Volume is not built into QRFM (except via MFI), so add it as external confirmation.
Observe the Phase Spiral
The spiral provides a quick visual cue for rotation consistency:
Tight, smooth spiral : Ensemble is rotating coherently (trending)
Loose, erratic spiral : Phase is jumping around (ranging or transitional)
If the spiral tightens, coherence is building. If it loosens, coherence is dissolving.
Do Not Overtrade Low-Coherence Periods
When CI is persistently below 40% and the state is "Chaos," the market is not in a regime where phase analysis is predictive. During these times:
Reduce position size
Widen stops
Wait for coherence to return
QRFM's strength is regime detection. If there is no regime, the tool correctly signals "stand aside."
Use Alerts Strategically
Set alerts for:
Long Ignition
Short Ignition
Collapse
Phase Lock (optional)
Configure alerts to "Once per bar close" to avoid intrabar repainting and noise. When an alert fires, manually verify:
Orbit plot shows clustering
Dashboard confirms all conditions
Price structure supports the trade
Do not blindly trade alerts—use them as prompts for analysis.
Ideal Market Conditions
Best Performance
Instruments :
Liquid, actively traded markets (major forex pairs, large-cap stocks, major indices, top-tier crypto)
Instruments with clear cyclical oscillator behavior (avoid extremely illiquid or manipulated markets)
Timeframes :
15-minute to 4-hour: Optimal balance of noise reduction and responsiveness
1-hour to daily: Slower, higher-conviction signals; good for swing trading
5-minute: Acceptable for scalping if parameters are tightened and you accept more noise
Market Regimes :
Trending markets with periodic retracements (where oscillators cycle through phases predictably)
Breakout environments (coherence forms before/during breakout; collapse occurs at exhaustion)
Rotational markets with clear swings (oscillators phase-lock at turning points)
Volatility :
Moderate to high volatility (oscillators have room to move through their ranges)
Stable volatility regimes (sudden VIX spikes or flash crashes may create false collapses)
Challenging Conditions
Instruments :
Very low liquidity markets (erratic price action creates unstable oscillator phases)
Heavily news-driven instruments (fundamentals may override technical coherence)
Highly correlated instruments (oscillators may all reflect the same underlying factor, reducing independence)
Market Regimes :
Deep, prolonged consolidation (oscillators remain near neutral, CI is chronically low, few signals fire)
Extreme chop with no directional bias (oscillators whipsaw, coherence never establishes)
Gap-driven markets (large overnight gaps create phase discontinuities)
Timeframes :
Sub-5-minute charts: Noise dominates; oscillators flip rapidly; coherence is fleeting and unreliable
Weekly/monthly: Oscillators move extremely slowly; signals are rare; better suited for long-term positioning than active trading
Special Cases :
During major economic releases or earnings: Oscillators may lag price or become decorrelated as fundamentals overwhelm technicals. Reduce position size or stand aside.
In extremely low-volatility environments (e.g., holiday periods): Oscillators compress to neutral, CI may be artificially high due to lack of movement, but signals lack follow-through.
Adaptive Behavior
QRFM is designed to self-adapt to poor conditions:
When coherence is genuinely absent, CI remains low and signals do not fire
When only a subset of oscillators aligns, entangled pairs count stays below threshold and signals are filtered out
When phase-lock cannot be achieved (oscillators too scattered), the lock filter prevents signals
This means the indicator will naturally produce fewer (or zero) signals during unfavorable conditions, rather than generating false signals. This is a feature —it keeps you out of low-probability trades.
Parameter Optimization by Trading Style
Scalping (5-15 Minute Charts)
Goal : Maximum responsiveness, accept higher noise
Oscillator Lengths :
RSI: 7-10
MACD: 8/17/6
Stochastic: 8-10, smooth 2-3
CCI: 14-16
Others: 8-12
Coherence Settings :
CI Smoothing Window: 2-3 bars (fast reaction)
Phase Sample Rate: 1 (every bar)
Ignition Threshold: 0.65-0.75 (lower for more signals)
Collapse Threshold: 0.40-0.50 (earlier exit warnings)
Confirmation :
Phase Lock Tolerance: 40-50° (looser, easier to achieve)
Min Entangled Pairs: 2-3 (fewer oscillators required)
Visuals :
Orbit Plot + Dashboard only (reduce screen clutter for fast decisions)
Disable heavy visuals (heat map, web) for performance
Alerts :
Enable all ignition and collapse alerts
Set to "Once per bar close"
Day Trading (15-Minute to 1-Hour Charts)
Goal : Balance between responsiveness and reliability
Oscillator Lengths :
RSI: 14 (standard)
MACD: 12/26/9 (standard)
Stochastic: 14, smooth 3
CCI: 20
Others: 10-14
Coherence Settings :
CI Smoothing Window: 3-5 bars (balanced)
Phase Sample Rate: 2-3
Ignition Threshold: 0.75-0.85 (moderate selectivity)
Collapse Threshold: 0.50-0.55 (balanced exit timing)
Confirmation :
Phase Lock Tolerance: 30-40° (moderate tightness)
Min Entangled Pairs: 4-5 (reasonable confirmation)
Visuals :
Orbit Plot + Dashboard + Heat Map or Web (choose one)
Field Cloud for regime backdrop
Alerts :
Ignition and collapse alerts
Optional phase-lock alert for advance warning
Swing Trading (4-Hour to Daily Charts)
Goal : High-conviction signals, minimal noise, fewer trades
Oscillator Lengths :
RSI: 14-21
MACD: 12/26/9 or 19/39/9 (longer variant)
Stochastic: 14-21, smooth 3-5
CCI: 20-30
Others: 14-20
Coherence Settings :
CI Smoothing Window: 5-10 bars (very smooth)
Phase Sample Rate: 3-5
Ignition Threshold: 0.80-0.90 (high bar for entry)
Collapse Threshold: 0.55-0.65 (only significant breakdowns)
Confirmation :
Phase Lock Tolerance: 20-30° (tight clustering required)
Min Entangled Pairs: 5-7 (strong confirmation)
Visuals :
All modules enabled (you have time to analyze)
Heat Map for multi-bar pattern recognition
Web for deep confirmation analysis
Alerts :
Ignition and collapse
Review manually before entering (no rush)
Position/Long-Term Trading (Daily to Weekly Charts)
Goal : Rare, very high-conviction regime shifts
Oscillator Lengths :
RSI: 21-30
MACD: 19/39/9 or 26/52/12
Stochastic: 21, smooth 5
CCI: 30-50
Others: 20-30
Coherence Settings :
CI Smoothing Window: 10-14 bars
Phase Sample Rate: 5 (every 5th bar to reduce computation)
Ignition Threshold: 0.85-0.95 (only extreme alignment)
Collapse Threshold: 0.60-0.70 (major regime breaks only)
Confirmation :
Phase Lock Tolerance: 15-25° (very tight)
Min Entangled Pairs: 6+ (broad consensus required)
Visuals :
Dashboard + Orbit Plot for quick checks
Heat Map to study historical coherence patterns
Web to verify deep entanglement
Alerts :
Ignition only (collapses are less critical on long timeframes)
Manual review with fundamental analysis overlay
Performance Optimization (Low-End Systems)
If you experience lag or slow rendering:
Reduce Visual Load :
Orbit Grid Size: 8-10 (instead of 12+)
Heat Map Time Bins: 5-8 (instead of 10+)
Disable Web Matrix entirely if not needed
Disable Field Cloud and Phase Spiral
Reduce Calculation Frequency :
Phase Sample Rate: 5-10 (calculate every 5-10 bars)
Max History Depth: 100-200 (instead of 500+)
Disable Unused Oscillators :
If you only want RSI, MACD, and Stochastic, disable the other five. Fewer oscillators = smaller matrices, faster loops.
Simplify Dashboard :
Choose "Small" dashboard size
Reduce number of metrics displayed
These settings will not significantly degrade signal quality (signals are based on bar-close calculations, which remain accurate), but will improve chart responsiveness.
Important Disclaimers
This indicator is a technical analysis tool designed to identify periods of phase coherence across an ensemble of oscillators. It is not a standalone trading system and does not guarantee profitable trades. The Coherence Index, dominant phase, and entanglement metrics are mathematical calculations applied to historical price data—they measure past oscillator behavior and do not predict future price movements with certainty.
No Predictive Guarantee : High coherence indicates that oscillators are currently aligned, which historically has coincided with trending or directional price movement. However, past alignment does not guarantee future trends. Markets can remain coherent while prices consolidate, or lose coherence suddenly due to news, liquidity changes, or other factors not captured by oscillator mathematics.
Signal Confirmation is Probabilistic : The multi-layer confirmation system (CI threshold + dominant phase + phase-lock + entanglement) is designed to filter out low-probability setups. This increases the proportion of valid signals relative to false signals, but does not eliminate false signals entirely. Users should combine QRFM with additional analysis—support and resistance levels, volume confirmation, multi-timeframe alignment, and fundamental context—before executing trades.
Collapse Signals are Warnings, Not Reversals : A coherence collapse indicates that the oscillator ensemble has lost alignment. This often precedes trend exhaustion or reversals, but can also occur during healthy pullbacks or consolidations. Price may continue in the original direction after a collapse. Use collapses as risk management cues (tighten stops, take partial profits) rather than automatic reversal entries.
Market Regime Dependency : QRFM performs best in markets where oscillators exhibit cyclical, mean-reverting behavior and where trends are punctuated by retracements. In markets dominated by fundamental shocks, gap openings, or extreme low-liquidity conditions, oscillator coherence may be less reliable. During such periods, reduce position size or stand aside.
Risk Management is Essential : All trading involves risk of loss. Use appropriate stop losses, position sizing, and risk-per-trade limits. The indicator does not specify stop loss or take profit levels—these must be determined by the user based on their risk tolerance and account size. Never risk more than you can afford to lose.
Parameter Sensitivity : The indicator's behavior changes with input parameters. Aggressive settings (low thresholds, loose tolerances) produce more signals with lower average quality. Conservative settings (high thresholds, tight tolerances) produce fewer signals with higher average quality. Users should backtest and forward-test parameter sets on their specific instruments and timeframes before committing real capital.
No Repainting by Design : All signal conditions are evaluated on bar close using bar-close values. However, the visual components (orbit plot, heat map, dashboard) update in real-time during bar formation for monitoring purposes. For trade execution, rely on the confirmed signals (triangles and circles) that appear only after the bar closes.
Computational Load : QRFM performs extensive calculations, including nested loops for entanglement matrices and real-time table rendering. On lower-powered devices or when running multiple indicators simultaneously, users may experience lag. Use the performance optimization settings (reduce visual complexity, increase phase sample rate, disable unused oscillators) to improve responsiveness.
This system is most effective when used as one component within a broader trading methodology that includes sound risk management, multi-timeframe analysis, market context awareness, and disciplined execution. It is a tool for regime detection and signal confirmation, not a substitute for comprehensive trade planning.
Technical Notes
Calculation Timing : All signal logic (ignition, collapse) is evaluated using bar-close values. The barstate.isconfirmed or implicit bar-close behavior ensures signals do not repaint. Visual components (tables, plots) render on every tick for real-time feedback but do not affect signal generation.
Phase Wrapping : Phase angles are calculated in the range -180° to +180° using atan2. Angular distance calculations account for wrapping (e.g., the distance between +170° and -170° is 20°, not 340°). This ensures phase-lock detection works correctly across the ±180° boundary.
Array Management : The indicator uses fixed-size arrays for oscillator phases, amplitudes, and the entanglement matrix. The maximum number of oscillators is 8. If fewer oscillators are enabled, array sizes shrink accordingly (only active oscillators are processed).
Matrix Indexing : The entanglement matrix is stored as a flat array with size N×N, where N is the number of active oscillators. Index mapping: index(row, col) = row × N + col. Symmetric pairs (i,j) and (j,i) are stored identically.
Normalization Stability : Oscillators are normalized to using fixed reference levels (e.g., RSI overbought/oversold at 70/30). For unbounded oscillators (MACD, ROC, TSI), statistical normalization (division by rolling standard deviation) is used, with clamping to prevent extreme outliers from distorting phase calculations.
Smoothing and Lag : The CI smoothing window (SMA) introduces lag proportional to the window size. This is intentional—it filters out single-bar noise spikes in coherence. Users requiring faster reaction can reduce the smoothing window to 1-2 bars, at the cost of increased sensitivity to noise.
Complex Number Representation : Pine Script does not have native complex number types. Complex arithmetic is implemented using separate real and imaginary accumulators (sum_cos, sum_sin) and manual calculation of magnitude (sqrt(real² + imag²)) and argument (atan2(imag, real)).
Lookback Limits : The indicator respects Pine Script's maximum lookback constraints. Historical phase and amplitude values are accessed using the operator, with lookback limited to the chart's available bar history (max_bars_back=5000 declared).
Visual Rendering Performance : Tables (orbit plot, heat map, web, dashboard) are conditionally deleted and recreated on each update using table.delete() and table.new(). This prevents memory leaks but incurs redraw overhead. Rendering is restricted to barstate.islast (last bar) to minimize computational load—historical bars do not render visuals.
Alert Condition Triggers : alertcondition() functions evaluate on bar close when their boolean conditions transition from false to true. Alerts do not fire repeatedly while a condition remains true (e.g., CI stays above threshold for 10 bars fires only once on the initial cross).
Color Gradient Functions : The phaseColor() function maps phase angles to RGB hues using sine waves offset by 120° (red, green, blue channels). This creates a continuous spectrum where -180° to +180° spans the full color wheel. The amplitudeColor() function maps amplitude to grayscale intensity. The coherenceColor() function uses cos(phase) to map contribution to CI (positive = green, negative = red).
No External Data Requests : QRFM operates entirely on the chart's symbol and timeframe. It does not use request.security() or access external data sources. All calculations are self-contained, avoiding lookahead bias from higher-timeframe requests.
Deterministic Behavior : Given identical input parameters and price data, QRFM produces identical outputs. There are no random elements, probabilistic sampling, or time-of-day dependencies.
— Dskyz, Engineering precision. Trading coherence.
Mean Reversion Trading V1Overview
This is a simple mean reversion strategy that combines RSI, Keltner Channels, and MACD Histograms to predict reversals. Current parameters were optimized for NASDAQ 15M and performance varies depending on asset. The strategy can be optimized for specific asset and timeframe.
How it works
Long Entry (All must be true):
1. RSI < Lower Threshold
2. Close < Lower KC Band
3. MACD Histogram > 0 and rising
4. No open trades
Short Entry (All must be true):
1. RSI > Upper Threshold
2. Close > Upper KC Band
3. MACD Histogram < 0 and falling
4. No open trades
Long Exit:
1. Stop Loss: Average position size x ( 1 - SL percent)
2. Take Profit: Average position size x ( 1 + TP percent)
3. MACD Histogram crosses below zero
Short Exit:
1. Stop Loss: Average position size x ( 1 + SL percent)
2. Take Profit: Average position size x ( 1 - TP percent)
3. MACD Histogram crosses above zero
Settings and parameters are explained in the tooltips.
Important
Initial capital is set as 100,000 by default and 100 percent equity is used for trades
NY Open 5 minute Range (5m Box Extended)Draws a box around the first 5 minute candle for the New York session.
EXTPO TRENDIndicator designed for traders who prefer quick scalping or day trading.
Applicable to timeframes below M15.
Currently, I’m using it on BTC M1.
Note:
When the status is Buy, only buy signals will appear.
When the status is Sell, only sell signals will appear.
When the status is Off, no signals will appear because one of the entry conditions is not met.
Luxy BIG beautiful Dynamic ORBThis is an advanced Opening Range Breakout (ORB) indicator that tracks price breakouts from the first 5, 15, 30, and 60 minutes of the trading session. It provides complete trade management including entry signals, stop-loss placement, take-profit targets, and position sizing calculations.
The ORB strategy is based on the concept that the opening range of a trading session often acts as support/resistance, and breakouts from this range tend to lead to significant moves.
What Makes This Different?
Most ORB indicators simply draw horizontal lines and leave you to figure out the rest. This indicator goes several steps further:
Multi-Stage Tracking
Instead of just one ORB timeframe, this tracks FOUR simultaneously (5min, 15min, 30min, 60min). Each stage builds on the previous one, giving you multiple trading opportunities throughout the session.
Active Trade Management
When a breakout occurs, the indicator automatically calculates and displays entry price, stop-loss, and multiple take-profit targets. These lines extend forward and update in real-time until the trade completes.
Cycle Detection
Unlike indicators that only show the first breakout, this tracks the complete cycle: Breakout → Retest → Re-breakout. You can see when price returns to test the ORB level after breaking out (potential re-entry).
Failed Breakout Warning
If price breaks out but quickly returns inside the range (within a few bars), the label changes to "FAILED BREAK" - warning you to exit or avoid the trade.
Position Sizing Calculator
Built-in risk management that tells you exactly how many shares to buy based on your account size and risk tolerance. No more guessing or manual calculations.
Advanced Filtering
Optional filters for volume confirmation, trend alignment, and Fair Value Gaps (FVG) to reduce false signals and improve win rate.
Core Features Explained
### 1. Multi-Stage ORB Levels
The indicator builds four separate Opening Range levels:
ORB 5 - First 5 minutes (fastest signals, most volatile)
ORB 15 - First 15 minutes (balanced, most popular)
ORB 30 - First 30 minutes (slower, more reliable)
ORB 60 - First 60 minutes (slowest, most confirmed)
Each level is drawn as a horizontal range on your chart. As time progresses, the ranges expand to include more price action. You can enable or disable any stage and assign custom colors to each.
How it works: During the opening minutes, the indicator tracks the highest high and lowest low. Once the time period completes, those levels become your ORB high and low for that stage.
### 2. Breakout Detection
When price closes outside the ORB range, a label appears:
BREAK UP (green label above price) - Price closed above ORB High
BREAK DOWN (red label below price) - Price closed below ORB Low
The label shows which ORB stage triggered (ORB5, ORB15, etc.) and the cycle number if tracking multiple breakouts.
Important: Signals appear on bar close only - no repainting. What you see is what you get.
### 3. Retest Detection
After price breaks out and moves away, if it returns to test the ORB level, a "RETEST" label appears (orange). This indicates:
The original breakout level is now acting as support/resistance
Potential re-entry opportunity if you missed the first breakout
Confirmation that the level is significant
The indicator requires price to move a minimum distance away before considering it a valid retest (configurable in settings).
### 4. Failed Breakout Detection
If price breaks out but returns inside the ORB range within a few bars (before the breakout is "committed"), the original label changes to "FAILED BREAK" in orange.
This warns you:
The breakout lacked conviction
Consider exiting if already in the trade
Wait for better setup
Committed Breakout: The indicator tracks how many bars price stays outside the range. Only after staying outside for the minimum number of bars does it become a committed breakout that can be retested.
### 5. TP/SL Lines (Trade Management)
When a breakout occurs, colored horizontal lines appear showing:
Entry Line (cyan for long, orange for short) - Your entry price (the ORB level)
Stop Loss Line (red) - Where to exit if trade goes against you
TP1, TP2, TP3 Lines (same color as entry) - Profit targets at 1R, 2R, 3R
These lines extend forward as new bars form, making it easy to track your trade. When a target is hit, the line turns green and the label shows a checkmark.
Lines freeze (stop updating) when:
Stop loss is hit
The final enabled take-profit is hit
End of trading session (optional setting)
### 6. Position Sizing Dashboard
The dashboard (bottom-left corner by default) shows real-time information:
Current ORB stage and range size
Breakout status (Inside Range / Break Up / Break Down)
Volume confirmation (if filter enabled)
Trend alignment (if filter enabled)
Entry and Stop Loss prices
All enabled Take Profit levels with percentages
Risk/Reward ratio
Position sizing: Max shares to buy and total risk amount
Position Sizing Example:
If your account is $25,000 and you risk 1% per trade ($250), and the distance from entry to stop loss is $0.50, the calculator shows you can buy 500 shares (250 / 0.50 = 500).
### 7. FVG Filter (Fair Value Gap)
Fair Value Gaps are price inefficiencies - gaps left by strong momentum where one candle's high doesn't overlap with a previous candle's low (or vice versa).
When enabled, this filter:
Detects bullish and bearish FVGs
Draws semi-transparent boxes around these gaps
Only allows breakout signals if there's an FVG near the breakout level
Why this helps: FVGs indicate institutional activity. Breakouts through FVGs tend to be stronger and more reliable.
Proximity setting: Controls how close the FVG must be to the ORB level. 2.0x means the breakout can be within 2 times the FVG size - a reasonable default.
### 8. Volume & Trend Filters
Volume Filter:
Requires current volume to be above average (customizable multiplier). High volume breakouts are more likely to sustain.
Set minimum multiplier (e.g., 1.5x = 50% above average)
Set "strong volume" multiplier (e.g., 2.5x) that bypasses other filters
Dashboard shows current volume ratio
Trend Filter:
Only shows breakouts aligned with a higher timeframe trend. Choose from:
VWAP - Price above/below volume-weighted average
EMA - Price above/below exponential moving average
SuperTrend - ATR-based trend indicator
Combined modes (VWAP+EMA, VWAP+SuperTrend) for stricter filtering
### 9. Pullback Filter (Advanced)
Purpose:
Waits for price to pull back slightly after initial breakout before confirming the signal.
This reduces false breakouts from immediate reversals.
How it works:
- After breakout is detected, indicator waits for a small pullback (default 2%)
- Once pullback occurs AND price breaks out again, signal is confirmed
- If no pullback within timeout period (5 bars), signal is issued anyway
Settings:
Enable Pullback Filter: Turn this filter on/off
Pullback %: How much price must pull back (2% is balanced)
Timeout (bars): Max bars to wait for pullback (5 is standard)
When to use:
- Choppy markets with many fake breakouts
- When you want higher quality signals
- Combine with Volume filter for maximum confirmation
Trade-off:
- Better signal quality
- May miss some valid fast moves
- Slight entry delay
How to Use This Indicator
### For Beginners - Simple Setup
Add the indicator to your chart (5-minute or 15-minute timeframe recommended)
Leave all default settings - they work well for most stocks
Watch for BREAK UP or BREAK DOWN labels to appear
Check the dashboard for entry, stop loss, and targets
Use the position sizing to determine how many shares to buy
Basic Trading Plan:
Wait for a clear breakout label
Enter at the ORB level (or next candle open if you're late)
Place stop loss where the red line indicates
Take profit at TP1 (50% of position) and TP2 (remaining 50%)
### For Advanced Traders - Customized Setup
Choose which ORB stages to track (you might only want ORB15 and ORB30)
Enable filters: Volume (stocks) or Trend (trending markets)
Enable FVG filter for institutional confirmation
Set "Track Cycles" mode to catch retests and re-breakouts
Customize stop loss method (ATR for volatile stocks, ORB% for stable ones)
Adjust risk per trade and account size for accurate position sizing
Advanced Strategy Example:
Enable ORB15 only (disable others for cleaner chart)
Turn on Volume filter at 1.5x with Strong at 2.5x
Enable Trend filter using VWAP
Set Signal Mode to "Track Cycles" with Max 3 cycles
Wait for aligned breakouts (Volume + Trend + Direction)
Enter on retest if you missed the initial break
### Timeframe Recommendations
5-minute chart: Scalping, very active trading, crypto
15-minute chart: Day trading, balanced approach (most popular)
30-minute chart: Swing entries, less screen time
60-minute chart: Position trading, longer holds
The indicator works on any intraday timeframe, but ORB is fundamentally a day trading strategy. Daily charts don't make sense for ORB.
DEFAULT CONFIGURATION
ON by Default:
• All 4 ORB stages (5/15/30/60)
• Breakout Detection
• Retest Labels
• All TP levels (1/1.5/2/3)
• TP/SL Lines (Detailed mode)
• Dashboard (Bottom Left, Dark theme)
• Position Size Calculator
OFF by Default (Optional Filters):
• FVG Filter
• Pullback Filter
• Volume Filter
• Trend Filter
• HTF Bias Check
• Alerts
Recommended for Beginners:
• Leave all defaults
• Session Mode: Auto-Detect
• Signal Mode: Track Cycles
• Stop Method: ATR
• Add Volume Filter if trading stocks
Recommended for Advanced:
• Enable ORB15 + ORB30 only (disable 5 & 60)
• Enable: Volume + Trend + FVG
• Signal Mode: Track Cycles, Max 3
• Stop Method: ATR or Safer
• Enable HTF Daily bias check
## Settings Guide
The settings are organized into logical groups. Here's what each section controls:
### ORB COLORS Section
Show Edge Labels: Display "ORB 5", "ORB 15" labels at the right edge of the levels
Background: Fill the area between ORB high/low with color
Transparency: How see-through the background is (95% is nearly invisible)
Enable ORB 5/15/30/60: Turn each stage on or off individually
Colors: Assign colors to each ORB stage for easy identification
### SESSION SETTINGS Section
Session Mode: Choose trading session (Auto-Detect works for most instruments)
Custom Session Hours: Define your own hours if needed (format: HHMM-HHMM)
Auto-Detect uses the instrument's natural hours (stocks use exchange hours, crypto uses 24/7).
### BREAKOUT DETECTION Section
Enable Breakout Detection: Master switch for signals
Show Retest Labels: Display retest signals
Label Size: Visual size for all labels (Small recommended)
Enable FVG Filter: Require Fair Value Gap confirmation
Show FVG Boxes: Display the gap boxes on chart
Signal Mode: "First Only" = one signal per direction per day, "Track Cycles" = multiple signals
Max Cycles: How many breakout-retest cycles to track (6 is balanced)
Breakout Buffer: Extra distance required beyond ORB level (0.1-0.2% recommended)
Min Distance for Retest: How far price must move away before retest is valid (2% recommended)
Min Bars Outside ORB: Bars price must stay outside for committed breakout (2 is balanced)
### TARGETS & RISK Section
Enable Targets & Stop-Loss: Calculate and show trade management
TP1/TP2/TP3 checkboxes: Select which profit targets to display
Stop Method: How to calculate stop loss placement
- ATR: Based on volatility (best for most cases)
- ORB %: Fixed % of ORB range
- Swing: Recent swing high/low
- Safer: Widest of all methods
ATR Length & Multiplier: Controls ATR stop distance (14 period, 1.5x is standard)
ORB Stop %: Percentage beyond ORB for stop (20% is balanced)
Swing Bars: Lookback period for swing high/low (3 is recent)
### TP/SL LINES Section
Show TP/SL Lines: Display horizontal lines on chart
Label Format: "Short" = minimal text, "Detailed" = shows prices
Freeze Lines at EOD: Stop extending lines at session close
### DASHBOARD Section
Show Info Panel: Display the metrics dashboard
Theme: Dark or Light colors
Position: Where to place dashboard on chart
Toggle rows: Show/hide specific information rows
Calculate Position Size: Enable the position sizing calculator
Risk Mode: Risk fixed $ amount or % of account
Account Size: Your total trading capital
Risk %: Percentage to risk per trade (0.5-1% recommended)
### VOLUME FILTER Section
Enable Volume Filter: Require volume confirmation
MA Length: Average period (20 is standard)
Min Volume: Required multiplier (1.5x = 50% above average)
Strong Volume: Multiplier that bypasses other filters (2.5x)
### TREND FILTER Section
Enable Trend Filter: Require trend alignment
Trend Mode: Method to determine trend (VWAP is simple and effective)
Custom EMA Length: If using EMA mode (50 for swing, 20 for day trading)
SuperTrend settings: Period and Multiplier if using SuperTrend mode
### HIGHER TIMEFRAME Section
Check Daily Trend: Display higher timeframe bias in dashboard
Timeframe: What TF to check (D = daily, recommended)
Method: Price vs MA (stable) or Candle Direction (reactive)
MA Period: EMA length for Price vs MA method (20 is balanced)
Min Strength %: Minimum strength threshold for HTF bias to be considered
- For "Price vs MA": Minimum distance (%) from moving average
- For "Candle Direction": Minimum candle body size (%)
- 0.5% is balanced - increase for stricter filtering
- Lower values = more signals, higher values = only strong trends
### ALERTS Section
Enable Alerts: Master switch (must be ON to use any alerts)
Breakout Alerts: Notify on ORB breakouts
Retest Alerts: Notify when price retests after breakout
Failed Break Alerts: Notify on failed breakouts
Stage Complete Alerts: Notify when each ORB stage finishes forming
After enabling desired alert types, click "Create Alert" button, select this indicator, choose "Any alert() function call".
## Tips & Best Practices
### General Trading Tips
ORB works best on liquid instruments (stocks with good volume, major crypto pairs)
First hour of the session is most important - that's when ORB is forming
Breakouts WITH the trend have higher success rates - use the trend filter
Failed breakouts are common - use the "Min Bars Outside" setting to filter weak moves
Not every day produces good ORB setups - be patient and selective
### Position Sizing Best Practices
Never risk more than 1-2% of your account on a single trade
Use the built-in calculator - don't guess your position size
Update your account size monthly as it grows
Smaller accounts: use $ Amount mode for simplicity
Larger accounts: use % of Account mode for scaling
### Take Profit Strategy
Most traders use: 50% at TP1, 50% at TP2
Aggressive: Hold through TP1 for TP2 or TP3
Conservative: Full exit at TP1 (1:1 risk/reward)
After TP1 hits, consider moving stop to breakeven
TP3 rarely hits - only on strong trending days
### Filter Combinations
Maximum Quality: Volume + Trend + FVG (fewest signals, highest quality)
Balanced: Volume + Trend (good quality, reasonable frequency)
Active Trading: No filters or Volume only (many signals, lower quality)
Trending Markets: Trend filter essential (indices, crypto)
Range-Bound: Volume + FVG (avoid trend filter)
### Common Mistakes to Avoid
Chasing breakouts - wait for the bar to close, don't FOMO into wicks
Ignoring the stop loss - always use it, move it manually if needed
Over-leveraging - the calculator shows MAX shares, you can buy less
Trading every signal - quality > quantity, use filters
Not tracking results - keep a journal to see what works for YOU
## Pros and Cons
### Advantages
Complete all-in-one solution - from signal to position sizing
Multiple timeframes tracked simultaneously
Visual clarity - easy to see what's happening
Cycle tracking catches opportunities others miss
Built-in risk management eliminates guesswork
Customizable filters for different trading styles
No repainting - what you see is locked in
Works across multiple markets (stocks, forex, crypto)
### Limitations
Intraday strategy only - doesn't work on daily charts
Requires active monitoring during first 1-2 hours of session
Not suitable for after-hours or extended sessions by default
Can produce many signals in choppy markets (use filters)
Dashboard can be overwhelming for complete beginners
Performance depends on market conditions (trends vs ranges)
Requires understanding of risk management concepts
### Best For
Day traders who can watch the first 1-2 hours of market open
Traders who want systematic entry/exit rules
Those learning proper position sizing and risk management
Active traders comfortable with multiple signals per day
Anyone trading liquid instruments with clear sessions
### Not Ideal For
Swing traders holding multi-day positions
Set-and-forget / passive investors
Traders who can't watch market open
Complete beginners unfamiliar with trading concepts
Low volume / illiquid instruments
## Frequently Asked Questions
Q: Why are no signals appearing?
A: Check that you're on an intraday timeframe (5min, 15min, etc.) and that the current time is within your session hours. Also verify that "Enable Breakout Detection" is ON and at least one ORB stage is enabled. If using filters, they might be blocking signals - try disabling them temporarily.
Q: What's the best ORB stage to use?
A: ORB15 (15 minutes) is most popular and balanced. ORB5 gives faster signals but more noise. ORB30 and ORB60 are slower but more reliable. Many traders use ORB15 + ORB30 together.
Q: Should I enable all the filters?
A: Start with no filters to see all signals. If too many false signals, add Volume filter first (stocks) or Trend filter (trending markets). FVG filter is most restrictive - use for maximum quality but fewer signals.
Q: How do I know which stop loss method to use?
A: ATR works for most cases - it adapts to volatility. Use ORB% if you want predictable stop placement. Swing is for respecting chart structure. Safer gives you the most room but largest risk.
Q: Can I use this for swing trading?
A: Not really - ORB is fundamentally an intraday strategy. The ranges reset each day. For swing trading, look at weekly support/resistance or moving averages instead.
Q: Why do TP/SL lines disappear sometimes?
A: Lines freeze (stop extending) when: stop loss is hit, the last enabled take-profit is hit, or end of session arrives (if "Freeze at EOD" is enabled). This is intentional - the trade is complete.
Q: What's the difference between "First Only" and "Track Cycles"?
A: "First Only" shows one breakout UP and one DOWN per day maximum - clean but might miss opportunities. "Track Cycles" shows breakout-retest-rebreak sequences - more signals but busier chart.
Q: Is position sizing accurate for options/forex?
A: The calculator is designed for shares (stocks). For options, ignore the share count and use the risk amount. For forex, you'll need to adapt the lot size calculation manually.
Q: How much capital do I need to use this?
A: The indicator works for any account size, but practical day trading typically requires $25,000 in the US due to Pattern Day Trader rules. Adjust the "Account Size" setting to match your capital.
Q: Can I backtest this strategy?
A: This is an indicator, not a strategy script, so it doesn't have built-in backtesting. You can visually review historical signals or code a strategy script using similar logic.
Q: Why does the dashboard show different entry price than the breakout label?
A: If you're looking at an old breakout, the ORB levels may have changed when the next stage completed. The dashboard always shows the CURRENT active range and trade setup.
Q: What's a good win rate to expect?
A: ORB strategies typically see 40-60% win rate depending on market conditions and filters used. The strategy relies on positive risk/reward ratios (2:1 or better) to be profitable even with moderate win rates.
Q: Does this work on crypto?
A: Yes, but crypto trades 24/7 so you need to define what "session start" means. Use Session Mode = Custom and set your preferred daily reset time (e.g., 0000-2359 UTC).
## Credits & Transparency
### Development
This indicator was developed with the assistance of AI technology to implement complex ORB trading logic.
The strategy concept, feature specifications, and trading logic were designed by the publisher. The implementation leverages modern development tools to ensure:
Clean, efficient, and maintainable code
Comprehensive error handling and input validation
Detailed documentation and user guidance
Performance optimization
### Trading Concepts
This indicator implements several public domain trading concepts:
Opening Range Breakout (ORB): Trading strategy popularized by Toby Crabel, Mark Fisher and many more talanted traders.
Fair Value Gap (FVG): Price imbalance concept from ICT methodology
SuperTrend: ATR-based trend indicator using public formula
Risk/Reward Ratio: Standard risk management principle
All mathematical formulas and technical concepts used are in the public domain.
### Pine Script
Uses standard TradingView built-in functions:
ta.ema(), ta.atr(), ta.vwap(), ta.highest(), ta.lowest(), request.security()
No external libraries or proprietary code from other authors.
## Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice.
Trading involves substantial risk of loss and is not suitable for every investor. Past performance shown in examples is not indicative of future results.
The indicator provides signals and calculations, but trading decisions are solely your responsibility. Always:
Test strategies on paper before using real money
Never risk more than you can afford to lose
Understand that all trading involves risk
Consider seeking advice from a licensed financial advisor
The publisher makes no guarantees regarding accuracy, profitability, or performance. Use at your own risk.
---
Version: 3.0
Pine Script Version: v6
Last Updated: October 2024
For support, questions, or suggestions, please comment below or send a private message.
---
Happy trading, and remember: consistent risk management beats perfect entry timing every time.
Risk Leverage ToolRisk Leverage Tool – Calculate Position Size and Required Leverage
This script automatically calculates the optimal position size and the leverage needed based on the amount of capital you are willing to risk on a trade. It is designed for traders who want precise control over their risk management.
The script determines the distance between the entry and stop-loss price, calculates the maximum position size that fits within the defined risk, and derives the notional value of the trade. Based on the available margin, it then calculates the required leverage. It also displays the percentage of margin at risk if the stop-loss is hit.
All results are displayed in a table in the top-right corner of the chart. Additionally, a label appears at the entry price level showing the same data.
To use the tool, simply input your planned entry price, stop-loss price, the maximum risk amount in dollars, and the available margin in the settings menu. The script will update all values automatically in real time.
This tool works with any market where capital risk is expressed in absolute terms (such as USD), including futures, CFDs, and leveraged spot positions. For inverse contracts or percentage-based stops, manual adjustment is required.
FX Realized Volatility *The downward signal for Euqities!?*The Russel 2000 put in a new ath today as capital is moving further out the risk curve. Risk-Assets continue to rally to the upside.
This will last until we see a lasting driver happening on a real time basis that drag pull equties down
When volatility rises, we need to see the DRIVER of the volatility have persistence behind it as opposed to one off shocks.
We are not there yet as volatility in FX and bonds continues to compress since the April lows in equities.
Equities will continue to rally until long end yields blow out or the carry trade unwinds. Long end yields blowing out is not occuring on an imminent basis but the FX side of things could be a significant risk soon.
Its all about: When will that liquidity beginn to create inflation or a problem in the currency
Monitoring the equity vol, Bond vol and FX volatiliy is crucial here
You can watch them via:
VIX,
Move,
+ i build an Trading view modell which conducts the vol of the major FX pairs.
(its 100% free)
If you just want it simple, just look at USD & EUR vol as they are the most trades foreign exchange currencies.
Watching these 2 Risks (Vol & long-end) will put you upfront most people in the market.
Once we see information in the underlying economy shifting i will adjust my views as they relate to every major asset class.
But for now we are likely moving higher in basically every risky asset.
**Feel free to ask me any questions**
Liquidity Levels - PMH/PWH/PDH/HODWhat is it?
An indicator that tracks the main liquidity levels on TradingView, displaying the highs and lows of reference for month, week, previous day and current day.
What's it for?
It identifies price zones where there are many pending orders (liquidity). Traders use it to:
Find support and resistance points
Identify areas where price could bounce or break through
Receive alerts when price touches or breaks these levels
Which levels does it show?
LevelDescriptionColorLinePMH/PMLPrevious month's high and lowPurpleSolidPWH/PWLPrevious week's high and lowBlueSolidPDH/PDLPrevious day's high and lowOrangeSolidHOD/LODCurrent day's high and lowGrayDotted
How to use it?
Apply the indicator to your chart
Customize colors and enable/disable the levels you prefer
Set alerts to receive notifications when price touches or breaks levels
Use the levels to make trading decisions (entry, exit, stop loss)
Perfect for: Scalping, Day Trading, Swing Trading on any asset (forex, crypto, stocks)
THAIT Moving Averages Tight within # ATR EMA SMA convergence
THAIT(tight) indicator is a powerful tool for identifying moving average convergence in price action. This indicator plots four user-defined moving averages (EMA or SMA). It highlights moments when the MAs converge within a user specified number of ATRs, adjusted by the 14-period ATR, signaling potential trend shifts or consolidation.
A convergence is flagged when MA1 is the maximum, the spread between MAs is tight, and the price is above MA1, excluding cases where the longest MA (MA4) is the highest. The indicator alerts and visually marks convergence zones with a shaded green background, making it ideal for traders seeking precise entry or exit points.
Flux AI PullBack System (Hybrid Pro)Flux AI PullBack System (Hybrid Pro)
//Session-Aware | Adaptive Confluence | Grace Confirm Logic//
Overview:
The Flux AI PullBack System (Hybrid Pro v5) is an adaptive, session-aware pullback indicator designed to identify high-probability continuation setups within trending markets. It automatically adjusts between “Classic” and “Enhanced” logic modes based on volatility, volume, and ATR slope, allowing it to perform seamlessly across different market sessions (Asian, London, and New York).
Core Features:
Hybrid Auto Mode — Dynamically switches between Classic (fast-moving) and Enhanced (strict) modes.
Session-Aware Context — Optimized for intraday trading in ES, NQ, and SPY.
Grace Confirmation Logic — Validates pullbacks with a follow-through condition to reduce noise.
Adaptive EMA Zone (38/62) — Highlights pullback areas with dynamic aqua fill and transparency linked to trend strength.
Noise Suppression Filter — Prevents false pullbacks during EMA crossovers or unstable transitions.
Weighted Confluence Model — Combines trend, ATR, volume, and swing structure for confirmation strength.
Pine v6 Compliant Alerts — Constant-string safe, ready for webhooks and automation.
Visual Elements:
Aqua EMA Zone: Displays the “breathing” pullback band (tightens during volatility spikes).
PB↑ / PB↓ Markers: Confirmed pullbacks with subtle transparency and fixed label size.
Bar Highlights: Yellow for pullbacks; ice-blue for confirmed continuation.
Use Cases
Perfect for:
Intraday trend traders
0DTE SPX / ES scalpers
Futures traders (NQ, MNQ, MES)
Algorithmic strategy builders using webhooks
Recommended Timeframes:
1–15 minute charts (scalping / intraday)
Higher timeframes for swing confirmations.
Attribution:
This open-source script was inspired by Chris Moody’s “CM Slingshot System” and JustUncleL’s Pullback Tools, but it was built from scratch using AI-assisted code refinement (ChatGPT).
All logic and enhancements are original, not derived from proprietary software.
License: MIT (Open Source)
© 2025 Ken Anderson — You may modify, use, or redistribute with credit.
Keywords:
Pullback, Reversal, AI Trading, EMA Zone, Session Aware, Futures Trading, SPX, ES, NQ, ATR Filter, Volume Confirmation, Flux System, Pine Script v6, Non-Repainting, Adaptive Trading Indicator.
Smart Money Concept: FVG Block Filter Smart Money Concept: FVG Block Filter (FVG Block Range vs N Range) with Candle Highlighter
Summary:
Smart Money Concept (SMC): An advanced indicator designed to visualize and filter Fair Value Gaps (FVG) blocks based on their size (Range) compared to the preceding N Range candle movement. It also includes a customizable Candle Highlighter function that marks the specific candle responsible for creating the FVG. The indicator allows full color customization for both blocks and the highlighter, and features clean, label-free charts by default.
Key Features:
FVG Block Detection: Automatically identifies and groups sequential FVG imbalances to form consolidated FVG blocks.
FVG Block Filtering (N Range): Filters blocks based on a user-defined rule, comparing the block's size (Range) to the range of the preceding N candles (e.g., requiring the FVG block to be larger than the range of the previous 6 candles).
Customizable Candle Highlighter: Marks the central candle (B) within the FVG structure (A-B-C) to highlight the source of the price imbalance. Highlighter colors are fully adjustable via inputs.
Visualization Control: Labels are turned OFF by default to keep the chart clean but can be easily enabled via the indicator settings.
Full Color Customization: Allows independent customization of Bullish and Bearish FVG Block colors, Block Transparency, and Bullish/Bearish Highlighter colors.
Keywords:
Smart Money Concept, SMC, Fair Value Gap, FVG, Imbalance, Block Filter, Candle Highlighter, Range.
