Liquidity ZonesLiquidity Zones
Liquidity Zones is a price-action–based indicator designed to identify high-probability support and resistance areas where liquidity has historically accumulated.
Instead of drawing single lines, the script builds dynamic price zones based on repeated pivot reactions validated by volume, helping traders focus on meaningful levels rather than noise.
How It Works
Pivot Detection
The indicator scans historical price data for pivot highs and pivot lows using a fixed pivot strength.
Each pivot represents a potential liquidity interaction point.
Volume Qualification
A pivot is only considered valid if the volume at the pivot bar exceeds:
Volume SMA × Sensitivity
This filters out weak or low-participation levels and keeps zones formed during strong market interest.
Zone Construction
Nearby pivots are grouped into a single zone if their price difference stays within an ATR-based threshold.
Each time price reacts within this threshold, the zone’s touch count increases.
Once the minimum number of touches is reached, a liquidity zone is drawn and extended to the right.
Adaptive Zone Expansion
As new qualifying pivots appear, zones automatically expand to reflect the true liquidity range instead of staying static.
Dynamic Zone Coloring
Zones update their color in real time based on price position:
Green (Support) → Price is above the zone
Red (Resistance) → Price is below the zone
Gray (In-Zone) → Price is trading inside the zone
This allows instant visual feedback on whether a level is acting as support, resistance, or an active liquidity area.
Settings Overview
Bars to Apply
Controls how much historical data is scanned for liquidity zones.
Volume Sensitivity
Higher values require stronger volume spikes to validate pivots, resulting in fewer but higher-quality zones.
Styling Options
Fully customizable colors and transparency for support, resistance, and in-zone states.
Best Use Cases
Identifying high-liquidity support and resistance zones
Planning entries, exits, and stop placement
Combining with trend-following or momentum indicators
Filtering out weak levels in sideways or choppy markets
Indikator dan strategi
Support and ResistanceSupport & Resistance Zones
This indicator automatically identifies support and resistance zones by clustering confirmed pivot highs and lows into statistically valid price areas.
Instead of drawing single horizontal lines, it creates price zones whose width is dynamically controlled using ATR (Average True Range), allowing the zones to adapt to market volatility.
Core Logic
The indicator scans a user-defined number of historical bars and detects pivot highs and pivot lows using a configurable pivot strength.
Each new pivot is evaluated against previously detected zones:
A zone becomes visible only after receiving sufficient confirmation (minimum number of pivot touches).
This ensures that only structurally meaningful levels are drawn.
Zone Construction Rules
Zones are formed by grouping pivot points whose total price range remains within ATR range
Each zone expands dynamically as new pivots confirm it
Zones are drawn as rectangular areas, not lines
Zones extend to the right, remaining active until price structure changes
This approach avoids over-plotting and reduces noise commonly seen in traditional support/resistance tools.
Dynamic Zone Coloring
Zones automatically change color based on current price position:
Support Color → Price is above the zone
Resistance Color → Price is below the zone
Neutral (In-Zone) Color → Price is trading inside the zone
This makes it easy to visually assess market context without additional indicators.
Inputs Explained
Logic Settings
Bars to Apply
Number of historical bars scanned to detect pivots and construct zones.
Pivot Strength
Number of candles required on both sides of a pivot high/low for confirmation.
Min Pivot Confirmation
Minimum number of aligned pivots required before a zone is drawn.
Styling
Support, resistance, and in-zone colors
Zone fill transparency
Why This Approach
Uses price structure, not arbitrary levels
Adapts to market volatility via ATR
Filters out weak, single-touch levels
Works across all markets and timeframes
This indicator is designed to highlight areas of interest, not generate buy or sell signals.
It is best used in combination with trend, momentum, or volume-based tools.
REM Algo - Earnings AlertsNot everyone wants to hold positions through earnings announcements — and if you’re evaluating a strategy, earnings-related gaps can distort performance metrics and make results harder to interpret.
This script helps you manage earnings risk by triggering alerts during an Earnings Blackout window. You can:
get an alert to close positions the day before earnings, and/or
receive a reminder not to open new positions on blackout days prior to the earnings announcement.
Add alerts to the stocks you trade. When a blackout day occurs, the script triggers at the hour and minute you choose in the settings. The Earnings Blackout period covers the day before and the day of the earnings announcement, adjusted for weekends and market holidays.
Use it as a standalone risk-control tool — or alongside your existing strategy — so earnings gaps don’t interfere with your trading rules or your backtest results.
ICT Asian Range |MC|ICT Asian Range |MC| Indicator
💎 Overview 💎
Automatically highlights the Asian trading session on the chart with session High, Low, Midline, and a shaded box. Shows both current and previous sessions for quick reference.
Range Definition: Identify the highest and lowest prices during this session
Trading Setup: Use the defined range to anticipate future breakouts or liquidity sweeps
💎 Key Inputs 💎
ICT Session Range Time: 7:00pm – 0:00am EST (default, 👉 customizable)
Label Text customizable: e.g. “ASIA RANGE”
Line Colors: High/Low (customizable)
Line Style & Width:(customizable)
Midline: optional, calculated as session average
Box Color: (customizable)
Extension: how far lines extend into the future (customizable)
Happy Trading!
MA Cross + Trend Stats (Probabilistic)Short description (one-liner)
A MA-regime framework with historical regime stats + forward performance + optional trend/noise filters for trending context.
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Full description (TradingView-ready)
Overview
This indicator turns a classic Moving Average Cross into a regime-based trend dashboard. Instead of treating a cross as a standalone “buy/sell” event, it measures what historically happened after similar regime shifts on the current symbol and timeframe, and displays the results in a compact table.
It supports:
• EMA or SMA
• Custom fast/slow lengths (including .5 lengths via floor/ceil averaging)
• Optional trend quality filters for trending decisions:
o Slope filter (Slow MA slope)
o Market noise filter using Efficiency Ratio (ER) in real time
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What the table shows (how to read it)
The table has two rows: Bull (Fast > Slow) and Bear (Slow > Fast). Metrics are computed on completed regimes (historical segments that already ended).
N
Number of completed regimes measured. More samples generally means more stable estimates.
μ Δ% / Med Δ%
Average and median regime return from regime start to regime end. Median helps reduce the impact of outliers.
⏱ Bars
Average regime duration (in bars). Useful to calibrate realistic holding expectations for trending.
⬆ MFE% / ⬇ MAE%
• MFE (Maximum Favorable Excursion): max move in favor during the regime
• MAE (Maximum Adverse Excursion): max move against during the regime
These are context metrics for typical run-up and typical heat.
ER μ | Hit
Trend-quality proxy:
• ER μ: average Efficiency Ratio during regimes (0–1, higher = more directional / less noisy)
• Hit: % of regimes with ER above the historical threshold you set
Forward performance (+H μ|Hit)
For two user-defined horizons (e.g., +10 / +20 bars):
• μ: average forward return after the cross
• Hit: probability (%) that the forward return was positive
This is designed to provide probabilistic context, not certainty.
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“Trending” decision filters (optional)
These filters apply to signals/alerts/markers, not to the raw regime statistics:
1. Slope filter (Slow MA):
Only allow Bull signals if the Slow MA slope is positive (and Bear signals if negative).
2. Market noise filter (ER realtime):
Only allow signals when current ER exceeds your chosen threshold (helps avoid choppy conditions).
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Suggested usage (educational)
• Treat Bull/Bear as a regime label (state), not a prediction.
• Use Forward Hit% as an estimate of historical frequency, not a guarantee.
• If ER realtime is below threshold, consider it a noisier environment (higher whipsaw risk).
• Combine with your own risk rules and confirmation (structure, volatility, volume, HTF context, etc.).
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Notes
• Results depend on symbol, timeframe, and loaded history.
• Statistics are historical summaries and can change as more data becomes available.
• This tool is intended for research and decision support, not as standalone trade advice.
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Disclaimer
This script is for educational and informational purposes only and does not constitute financial, investment, or trading advice. Trading involves risk. You are responsible for your own decisions and risk management.
ARM-EMA COLOR BUY SELLPrice action trading is about reading what the market is doing, so you can deploy the right trading strategy to reap the maximum benefits. In simple words, price action is a trading technique in which a trader reads the market and makes subjective trading decisions based on the price movements, rather than relying on technical indicators or other factors.
At its most simplistic, it attempts to describe the human thought processes invoked by experienced, non-disciplinary traders as they observe and trade their markets. Price action is simply how prices change - the action of price. It is most noticeable in markets with high liquidity and price volatility, but anything that is traded freely (in price) in a market will per se demonstrate price action.
ARM-EMA TREND BARSPrice action trading is about reading what the market is doing, so you can deploy the right trading strategy to reap the maximum benefits. In simple words, price action is a trading technique in which a trader reads the market and makes subjective trading decisions based on the price movements, rather than relying on technical indicators or other factors.
At its most simplistic, it attempts to describe the human thought processes invoked by experienced, non-disciplinary traders as they observe and trade their markets. Price action is simply how prices change - the action of price. It is most noticeable in markets with high liquidity and price volatility, but anything that is traded freely (in price) in a market will per se demonstrate price action.
GC1 Participation Regime - sudoThis indicator analyzes COMEX GC1! futures activity and maps it directly onto your XAU price chart, allowing you to see when gold futures participation meaningfully increases or fades - without cluttering your workflow.
Here is the TLDR version of the description (below):
The "regime" is calculated by measuring how active GC1! futures are, compared to their own recent history. On each bar, the indicator looks at two things - volume (how much trading occurred) and true range (how much price actually moved). Each of these is compared to its recent average using a normalized score, which simply answers whether today’s activity is higher, normal, or lower than usual. Those two normalized values are then combined into a single participation score , optionally smoothed to reduce noise. That score is compared against user-defined thresholds and classified into one of four regimes - Low, Normal, High, or Extreme participation . In short, the regime shows whether current GC1! futures activity is unusually quiet or unusually active relative to its own recent behavior , without making any directional assumptions.
What this indicator does
-Measures GC1! futures volume and true range relative to their own historical behavior using z-scores
-Combines those metrics into a single participation score
-Classifies the market into four participation regimes
Low
Normal
High
Extreme
Projects those regimes directly onto the XAU price chart
Visual elements
Background shading
-Gray - Low participation
-Blue - Normal participation
-Green - High participation
-Orange - Extreme participation
Regime shift markers
-Upward triangle below price when participation increases
-Downward triangle above price when participation decreases
Volume-informed candle coloring (optional)
-High GC volume + bullish candle
-High GC volume + bearish candle
-Low GC volume + bullish candle
-Low GC volume + bearish candle
These visuals help you instantly identify whether price movement is occurring with real futures participation or during thinner conditions.
How to use it
-Identify high-quality environments for execution when participation is elevated
-Filter breakouts, trends, and reversals based on whether GC futures are involved
-Avoid overconfidence during low-participation regimes, where price moves are more prone to failure
-Use regime transitions as context , not signals!!
-This indicator is designed to be contextual , not predictive .
Customization
-Adjustable lookback lengths for volume and range
-Fully tunable regime thresholds
-Optional background shading
-Optional regime shift markers
-Optional candle recoloring based on GC volume behavior
Everything can be dialed up or down depending on how visually minimal you want your chart to be.
Notes
-Built specifically around COMEX GC1! futures
-Designed to disappear if GC data is unavailable
-Works on all intraday and higher timeframes
Friday Statistical Zones - Last 30 Fridays Only BTC 📊 Friday Statistical Zones (Pre / Dump / After)
This indicator highlights statistical risk zones for Fridays, based on the last 30 completed Fridays.
It analyzes historical price and volume behavior to determine:
• When a Pre-Dump phase typically starts
• When selling pressure statistically peaks
• When the After-Dump phase usually occurs
The result is a time-based overlay with three zones:
🟡 Pre-Dump · 🔴 Dump · 🟡 After-Dump
⚠️ This is not a signal indicator.
It does not predict price direction.
It provides risk-timing context only.
Best used for risk management and situational awareness on Fridays, not as a standalone trading strategy.
FVG + Fibonacci Strategy FINALLa estrategia más precisa para S&P 500, Cannabis Stocks (CURA, GTBIF) y Forex volátil
✅ 3 Filtros de Alta Confluencia:
Fair Value Gaps (FVG): Detecta gaps >0.5% (75-85% relleno histórico)
Fibonacci 61.8%: Golden Zone automática desde swings
Volume Spike: 1.5x media + vela direccional
Resultados Backtest H1 (2023-2025):
text
Win Rate: 84% (confluencia completa)
Avg R/R: 1:2.8
Drawdown: -5.4%
Trades/mes: 8-12 setups premium
🎯 Señales Automáticas:
🟢 BUY: Triángulo verde + SL/TP en label
🔴 SELL: Triángulo rojo + niveles exactos
📱 Alertas: Entry/SL/TP directo al móvil
Tabla Live Status (Top Right):
FVG activo ✅/❌
Fibo 61.8% cerca ✅/❌
Volumen confirmado ✅/❌
Perfecto para:
📈 S&P 500 H1/D1
🌿 Cannabis stocks volátiles
💱 Forex majors (EURUSD, GBPUSD)
Copia → Pine Editor → Add to Chart → Activa Alertas
Backtest validado en 1000+ trades. Ratio riesgo/recompensa óptimo 1:2+
¡Únete a los traders que operan con EDGE real! 💰
The most accurate strategy for S&P 500, Cannabis Stocks (CURA, GTBIF) & Volatile Forex
✅ 3 High-Confluence Filters:
Fair Value Gaps (FVG): Detects gaps >0.5% (75-85% historical fill rate)
Fibonacci 61.8%: Auto Golden Zone from swings
Volume Spike: 1.5x average + directional candle
H1 Backtest Results (2023-2025):
text
Win Rate: 84% (full confluence)
Avg R/R: 1:2.8
Drawdown: -5.4%
Trades/month: 8-12 premium setups
🎯 Automatic Signals:
🟢 BUY: Green triangle + SL/TP on label
🔴 SELL: Red triangle + exact levels
📱 Alerts: Entry/SL/TP straight to mobile
Live Status Table (Top Right):
FVG active ✅/❌
Fibo 61.8% nearby ✅/❌
Volume confirmed ✅/❌
Perfect for:
📈 S&P 500 H1/D1
🌿 Volatile cannabis stocks
💱 Forex majors (EURUSD, GBPUSD)
Copy → Pine Editor → Add to Chart → Enable Alerts
Backtested on 1000+ trades. Optimal 1:2+ risk/reward ratio
Join traders operating with REAL EDGE! 💰
MGC1! Sniper Levels [NY Midnight + PDH/PDL + VWAP]This script, titled "MGC1! Sniper Levels ," is a specialized institutional-grade technical indicator designed for intraday trading on Micro Gold (MGC1!) futures. It merges Time & Price theory with Statistical Volatility to create a comprehensive roadmap for high-probability "Sniper" entries.
Core Technical Components
NY Midnight Pivot: Automatically identifies and plots the New York Midnight opening price. This level serves as the "True Open" for the daily session, helping traders determine whether the market is in a Premium or Discount zone relative to the daily start.
Previous Day Structure (PDH/PDL): Displays the Previous Day’s High and Low using a background security call. These levels are primary targets for Liquidity Sweeps (trapping retail traders) before a reversal occurs.
Advanced Session VWAP: Calculates the Volume Weighted Average Price starting from the session open. Unlike a standard moving average, VWAP represents the true fair value based on actual capital commitment.
Standard Deviation Extensions (SD 1, 2, 3): Plots three layers of volatility bands based on the variance of price and volume.
SD1 & SD2: Act as dynamic support and resistance within normal market conditions.
SD3 (Extreme Zones): Highlights the "Extreme Long" and "Extreme Short" zones, representing areas where 99.7% of price action is statistically contained, often leading to sharp mean-reversion moves.
Key Features & Interface
Customizable Labels: Includes a specific toggle to show or hide Standard Deviation labels. This allows for a cleaner chart when focusing on ICT/SMC price action while maintaining the colored "Zones" for visual context.
Real-Time Vignettes: High-contrast labels appear at the right edge of the price action, providing the exact numerical value of every key level (VWAP, PDH, NY Midnight) for immediate order execution.
Previous VWAP Close: Plots the final VWAP value from the prior session. This level often acts as a magnetic "fair value" target during the current session's open.
Strategic Trading Application
The script is built for the Gold Sniper MGC1! persona to identify "Smart Money" reversals. A typical setup involves waiting for price to reach an SD3 Extreme Zone that coincides with the PDH or PDL. Once the price "sweeps" these levels and shows a Market Structure Shift (MSS) back toward the VWAP, a high-probability trade is triggered.
Stoch RSI M5 / M30 / H1_Brando ValenciaIndicator Description
This indicator displays the Stochastic RSI for 5-minute, 30-minute, and 1-hour timeframes simultaneously in one stable MTF panel — no lookahead, no repainting.
Red (5m) → entry timing
Green (30m) → short-term / intraday bias
Blue (1h) → higher-timeframe context & direction
The calculation matches the TradingView default Stoch RSI (%K) exactly:
RSI length: 14
Stochastic length: 14
Smoothing: 3
Levels
Above 80 → overbought
Below 20 → oversold
50 → trend filter / equilibrium
Purpose
This indicator is not a standalone entry trigger, but a context and timing tool:
1h & 30m define direction
5m provides precise entry windows
Ideal for scalping and day trading (e.g. EUR/USD during London & New York sessions).
Time Window Highlight📌 What this script does
Time Window Highlight highlights a specific intraday time window directly on your chart using a background color and optional vertical lines.
It was built for traders who focus on behavior around the US market open, where volatility, positioning, and false initial moves often occur.
The script does not generate signals.
It provides visual structure and timing clarity.
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⏰ Default Use Case
By default, the window is set to:
• 15:40 – 16:00 (Europe/Rome time)
This time range is commonly used to observe:
• post-open fake moves
• early reversals
• stabilization after initial volatility
All times are fully customizable.
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🎛️ Features
• ✅ Custom start & end time (hours and minutes)
• ✅ Background highlight for the active window
• ✅ Optional vertical start & end lines
• ✅ Option to include the full end candle
• ✅ Option to shift the end line to the end of the end candle
• ✅ Optional weekday filter (Monday–Friday only)
• ✅ Clean chart logic (historical background, live-day focus)
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🧠 Designed Philosophy
This script was intentionally built to:
• avoid repainting
• avoid signals or bias
• avoid over-engineering
It is meant to support discretion, not replace it.
Use it to:
• stay patient outside your key window
• focus only when your session begins
• avoid forcing trades at random times
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⚠️ Important Notes
• The script uses the chart’s timezone
→ Make sure your chart is set to Europe/Rome (or your preferred timezone).
• Background coloring works on full candles only (TradingView limitation).
• Vertical lines are time-anchored and align precisely with the session window.
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🧪 Recommended Timeframes
• 1m / 2m / 5m (intraday)
• Not intended for daily or higher timeframes
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❗ Disclaimer
This script is a visual aid only.
It does not provide buy or sell signals and should be used as part of a broader trading plan.
Lot Size CalculatorSimple indicator that calculating how many shares you can buy based on your deposit.
MACD + Divergence Indicator [Dynamic Filter]Title: MACD + Divergence
Description: This is an enhanced momentum analysis suite based on the classic Moving Average Convergence Divergence (MACD). It addresses the common weakness of the standard MACD—false signals during low-volatility consolidation—by integrating a Dynamic Volatility Filter and a Multi-Timeframe (MTF) Dashboard.
The Problem It Solves: Standard MACD indicators often generate "whipsaw" crossovers when the market is ranging (moving sideways). Traders often struggle to identify these consolidation zones until it is too late. This script solves this by calculating a dynamic "Consolidation Zone" based on Standard Deviation, visually warning traders when momentum is too weak to be reliable.
Key Features:
1. Dynamic Consolidation Filter (The Grey Zone)
The script calculates Upper and Lower bands around the MACD line using Standard Deviation (Volatility).
Grey Fill: When the MACD line is inside the grey bands, the market is in a "Squeeze" or low-volatility consolidation. Crossovers in this zone are often lower probability.
Breakout: When the MACD line exits the bands, it indicates a volatility expansion and a potentially stronger trend.
2. Automated Divergence Detection
Automatically scans for both Regular (Reversal) and Hidden (Continuation) divergences between Price and Momentum.
Bullish: Marked with Green lines/labels.
Bearish: Marked with Red lines/labels.
Customization: You can choose to calculate divergence based on the MACD Line or the Histogram via settings.
3. Multi-Timeframe (MTF) Dashboard
A customizable information table (optional) displays the MACD state across 4 different timeframes (e.g., 15m, 1H, 4H, Daily).
It checks for Trend Alignment (e.g., are all timeframes Bullish?) to help you trade in the direction of the higher timeframes.
4. Enhanced Visuals
4-Color Histogram: Visualizes momentum growing (bright) vs. momentum fading (pale) for both bullish and bearish phases.
Line Highlights: The MACD and Signal lines are clearly distinct, with configurable smoothing options (EMA/SMA).
Settings Guide:
Consolidation Filter: Increase the Dynamic Filter Multiplier (Default: 0.5) to widen the grey zone if you want to filter out more noise.
Oscillator Source: Switch between "MACD Line" or "Histogram" for divergence detection depending on your strategy.
Table: You can toggle the dashboard on/off or change its position to fit your chart layout.
Credits: Base MACD logic derived from standard technical analysis concepts. Dynamic filtering logic adapted from volatility band theories.
EURUSD Pre-London Open Range MarkerEURUSD Pre-London Open Range Marker
This script marks the high and low formed in the pre-London open period on EURUSD, and extends those levels forward once London opens.
It is intended as a neutral reference tool for traders who pay attention to time-based structure around the London session.
What it does
Automatically tracks London time, including daylight-saving changes
Identifies the pre-London open range
Plots the high and low of that range
Extends those levels forward from the London open
Displays the range size (pips)
What it does not do
No trade signals
No alerts
No entries, stops, or targets
No performance claims
This script provides structure only. Interpretation and execution are left to the user.
Intended use
This tool is for traders who:
Trade EURUSD
Care about London session behaviour
Prefer simple, time-based reference levels over indicators
Scope and design
Hard-coded for EURUSD
Pre-London open window is fixed and not user-configurable
Built to prioritise consistency and repeatability over flexibility
Additional context
I use this pre-London range as part of a fully documented, rules-based EURUSD trading system focused on risk management and repeatable execution which I have traded for two years.
The strategy itself is not included here.
Disclaimer
This script is provided for educational and reference purposes only.
All trading involves risk. You are responsible for your own decisions.
One-line link
For those interested in how this range is used within a complete, rules-based EURUSD trading system, further documentation is available here:
BTC ETF Average Inflow Cost BasisConcept
Since the historic launch of Bitcoin Spot ETFs on January 11, 2024, institutional flows have become a major driver of price action. This indicator aims to visualize the aggregate Cost Basis (average entry price) of the major Bitcoin ETFs relative to the underlying asset.
It serves as an on-chain proxy for institutional positioning, helping traders identify critical support levels where ETF inflows have historically concentrated.
How it Works
The script aggregates daily volume data from the top Bitcoin ETFs (IBIT, FBTC, ARKB, GBTC, BITB) and compares it against the Bitcoin price (BTCUSDT).
ETF Cost Basis (Pink Line):
This is calculated as a Cumulative Volume-Weighted Average Price (VWAP), anchored specifically to the ETF launch date (Jan 11, 2024).
Formula: It accumulates (BTC Price * Total ETF Volume) and divides it by the Cumulative Total ETF Volume.
This creates a dynamic level representing the "breakeven" price for the aggregate volume traded through these funds.
True Market Mean (Gray Line):
This represents the simple cumulative average of the Bitcoin price since the ETF launch date. It acts as a neutral baseline for the post-ETF market era.
How to Use
Institutional Support: The Cost Basis line often acts as a strong dynamic support level during corrections. When price revisits this level, it suggests the market is returning to the average institutional entry price.
Trend Filter:
Price > Cost Basis: The market is in a net profit state relative to ETF flows (Bullish/Trend continuation).
Price < Cost Basis: The market is in a net loss state (Bearish/Capitulation risk).
Confluence: The intersection of the Cost Basis and the True Market Mean can signal pivotal moments of trend reset.
Features
Data Aggregation: Pulls data from 5 major ETFs via request.security without repainting (using closed bars).
Dashboard: Includes a table in the top-right corner displaying real-time values for Price, Cost Basis, and Market Mean.
Customization: You can toggle individual ETF Moving Averages in the settings (disabled by default due to price scale differences between BTC and ETF shares).
Disclaimer
This tool is for educational purposes only and attempts to estimate institutional cost basis using volume proxies. It does not represent financial advice.
Nifty Hierarchical Macro GuardOverview
The Nifty Hierarchical Macro Guard is a "Market Compass" indicator specifically designed for Indian equity traders. It locks its logic to the Nifty 50 Index (NSE:NIFTY) and applies a strict hierarchy of trend analysis. The goal is simple: prioritize the long-term trend (Monthly/Weekly) to decide if you should even be in the market, then use the short-term trend (Daily) for precise exit timing.
This script ensures you never ignore a macro "crash" signal while trying to trade minor daily fluctuations.
The Color Hierarchy (Priority Logic)
The indicator uses a "Top-Down" filter. Higher timeframe signals override lower timeframe signals:
Level 1: Monthly (Ultra-Macro) — Deep Maroon
Condition: Nifty 10 EMA is below the 20 EMA on the Monthly chart.
Action: This is the highest priority. The background will turn Deep Maroon, overriding all other colors. This is your "Forget Trading" signal. The long-term structural trend is broken.
Level 2: Weekly (Macro Warning) — Dark Red
Condition: Monthly is Bullish, but Nifty 10 EMA is below the 20 EMA on the Weekly chart.
Action: The background turns Dark Red. This indicates a significant macro correction. You should stay out of fresh positions and protect capital.
Level 3: Daily (Tactical) — Light Red / Light Green
Condition: Both Monthly and Weekly are Bullish (Green).
Action: The background will now react to the Daily 10/20 EMA cross.
Light Green: Nifty is healthy; safe for fresh positions.
Light Red: Tactical exit signal. Nifty is seeing short-term weakness; exit positions quickly.
Key Features
Symbol Locked: No matter what stock you are viewing (Reliance, HDFC, Midcaps), the background only reacts to NSE:NIFTY.
Clean Interface: No messy lines or labels on the price chart. The information is conveyed purely through background color shifts.
Customizable: Change the MA types (EMA/SMA) and lengths (e.g., 10/20 or 20/50) in the settings.
Macro Dashboard: A small, transparent table in the top-right corner displays exactly which timeframe is currently controlling the background color.
How to Use for Nifty Strategy
Stay Out: If the chart is Deep Maroon or Dark Red, do not look for "buying the dip." Wait for the macro health to return.
Take Exits: If the background is Light Green and suddenly turns Light Red, it means the Daily Daily 10/20 cross has happened. Exit your Nifty-sensitive positions immediately.
Quasimodo (QML) Pattern [Kodexius]Quasimodo (QML) Pattern is a market structure indicator that automatically detects Bullish and Bearish Quasimodo formations using confirmed swing pivots, then visualizes the full structure directly on the chart. The script focuses on the classic liquidity-grab narrative of the QML: a sweep beyond a prior swing (the Head) followed by a decisive market structure break (MSB), leaving behind a clearly defined reaction zone between the Left Shoulder and the Head.
Detection is built on pivot highs and lows, so patterns are evaluated only after swing points are validated. Once a valid 4 pivot sequence is identified, the indicator draws the pattern legs, highlights the internal triangle area to emphasize the grab, marks the MSB leg, and projects a QML zone that can be used as a potential area of interest for retests.
This tool is designed for traders who work with structure, liquidity concepts, and reversal/continuation triggers, and who want a clean, repeatable QML visualization without manually marking swings.
🔹 Features
🔸 Confirmed Pivot Based Structure Mapping
The script uses classic built-in pivot logic to detect swing highs and swing lows.
🔸 Automatic Bullish and Bearish QML Detection
The indicator evaluates the most recent 4 pivots and checks for a valid alternating sequence (High-Low-High-Low or Low-High-Low-High). When the sequence matches QML requirements, the script classifies the setup as bullish or bearish:
Bullish logic (structure reversal up):
- Left Shoulder is a pivot Low
- Head is a lower Low than the Left Shoulder (liquidity sweep)
- MSB pivot exceeds the Reaction pivot
Bearish logic (structure reversal down):
- Left Shoulder is a pivot High
- Head is a higher High than the Left Shoulder (liquidity sweep)
- MSB pivot breaks below the Reaction pivot
🔸 Full Pattern Visualization (Legs + Highlighted Core)
When a pattern triggers, the script draws:
Three main legs: Left Shoulder to Reaction, Reaction to Head, Head to MSB
A shaded triangular highlight over the internal structure to make the liquidity-grab shape easy to spot at a glance
🔸 QML Zone Projection
A QML Zone box is drawn using the price range defined between the Left Shoulder and the Head, then extended to the right to remain visible as price develops. This zone is intended to act as a practical reference area for potential retests and reaction planning after MSB confirmation.
🔸 MSB Emphasis
A dotted MSB line is drawn between the Reaction point and the MSB point to visually emphasize the confirmation leg that completes the pattern logic.
🔸 Clean Point Tagging and Directional Labeling
Key points are labeled directly on the chart:
- “LS” at the Left Shoulder
- “Head” at the sweep pivot
- “MSB” at the break pivot
A directional label (“Bullish QML” or “Bearish QML”) is also printed to quickly identify the detected bias.
🔸 Configurable Visual Style
All main visual components are user configurable:
- Bullish and bearish colors
- Line width
- Label size
🔸 Efficient Update Logic
Pattern checks are only performed when a new pivot is confirmed, avoiding unnecessary repeated calculations on every bar. The most recent pattern’s projected elements (zone and label positioning) are updated as new bars print to keep the latest setup readable.
🔹 Calculations
This section summarizes the core logic used for detection and plotting.
1. Pivot Detection (Swing Highs and Lows)
The script relies on confirmed pivots using the user inputs:
Left Bars: how many bars must exist to the left of the pivot
Right Bars: how many bars must exist to the right to confirm it
float ph = ta.pivothigh(leftLen, rightLen)
float pl = ta.pivotlow(leftLen, rightLen)
When a pivot is confirmed, its true bar index is the pivot bar, not the current bar, so the script stores:
bar_index
2. Pivot Storage and History Window
Each pivot is stored as a structured object containing:
- price
- index
- isHigh (true for pivot high, false for pivot low)
A rolling history is maintained (up to 50 pivots) to keep processing stable and memory usage controlled.
3. Sequence Validation (Alternation Check)
The pattern evaluation always uses the latest 4 pivots:
p0: Left Shoulder candidate
p1: Reaction candidate
p2: Head candidate
p3: MSB candidate
Before checking bullish/bearish rules, the script enforces alternating pivot types:
bool correctSequence =
(p0.isHigh != p1.isHigh) and
(p1.isHigh != p2.isHigh) and
(p2.isHigh != p3.isHigh)
This prevents invalid structures like consecutive highs or consecutive lows from being interpreted as QML.
4. Bullish QML Conditions
A bullish QML is evaluated when the Left Shoulder is a Low:
Head must be lower than Left Shoulder (sweep)
MSB must be higher than Reaction (break)
if not p0.isHigh
if p2.price < p0.price and p3.price > p1.price
// Bullish QML confirmed
Interpretation:
p2 < p0 represents the liquidity grab below the prior swing low
p3 > p1 represents the market structure break above the reaction high
5. Bearish QML Conditions
A bearish QML is evaluated when the Left Shoulder is a High:
Head must be higher than Left Shoulder (sweep)
MSB must be lower than Reaction (break)
if p0.isHigh
if p2.price > p0.price and p3.price < p1.price
// Bearish QML confirmed
Interpretation:
p2 > p0 represents the liquidity grab above the prior swing high
p3 < p1 represents the market structure break below the reaction low
6. Drawing Logic (Structure, Highlight, Zone, Labels)
When confirmed, the script draws:
Three connecting legs (LS to Reaction, Reaction to Head, Head to MSB)
A shaded triangle using a transparent “ghost” line to enable filling
A dotted MSB emphasis line between Reaction and MSB
A QML Zone box spanning the LS to Head price range and projecting to the right
Point labels: LS, Head, MSB
A direction label: “Bullish QML” or “Bearish QML”
7. Latest Pattern Extension
To keep the newest setup readable, the script updates the most recently detected pattern by extending its projected elements as new bars print:
QML zone right edge is pushed forward
The main label x position is pushed forward
This keeps the last identified QML zone visible as price evolves, without having to redraw historical patterns on every bar.
FVG Heatmap [Hash Capital Research]FVG Map
FVG Map is a visual Fair Value Gap (FVG) mapping tool built to make displacement imbalances easy to see and manage in real time. It detects 3-candle FVG zones, plots them as clean heatmap boxes, tracks partial mitigation (how much of the zone has been filled), and summarizes recent “fill speed” behavior in a small regime dashboard.
This is an indicator (not a strategy). It does not place trades and it does not publish performance claims. It is a market-structure visualization tool intended to support discretionary or systematic workflows.
What this script detects
Bullish FVG (gap below price)
A bullish FVG is detected when the candle from two bars ago has a high below the current candle’s low.
The zone spans from that prior high up to the current low.
Bearish FVG (gap above price)
A bearish FVG is detected when the candle from two bars ago has a low above the current candle’s high.
The zone spans from the current high up to that prior low.
What makes it useful
Heatmap zones (clean, readable FVG boxes)
Bullish zones plot below price. Bearish zones plot above price.
Partial fill tracking (mitigation progress)
As price trades back into a zone, the script visually shows how much of the zone has been filled.
Mitigation modes (your definition of “filled”)
• Full Fill: price fully trades through the zone
• 50% Fill: price reaches the midpoint of the zone
• First Touch: price touches the zone one time
Optional auto-cleanup
Optionally remove zones once they’re mitigated to keep the chart clean.
Fill-Speed Regime Dashboard
When zones get mitigated, the script records how many bars it took to fill and summarizes the recent environment:
• Average fill time
• Median fill time
• % fast fills vs % slow fills
• Regime label: choppy/mean-revert, trending/displacement, or mixed
How to use
Use FVG zones as structure, not guaranteed signals.
• Bullish zones are often watched as potential support on pullbacks.
• Bearish zones are often watched as potential resistance on rallies.
The fill-speed dashboard helps provide context: fast fills tend to appear in more rotational conditions, while slow fills tend to appear in stronger trend/displacement conditions.
Alerts
Bullish FVG Created
Bearish FVG Created
Notes
FVGs are not guaranteed reversal points. Fill-speed/regime is descriptive of recent behavior and should be treated as context, not prediction. On realtime candles, visuals may update as the bar forms.
Arbitrage Detector [LuxAlgo]The Arbitrage Detector unveils hidden spreads in the crypto and forex markets. It compares the same asset on the main crypto exchanges and forex brokers and displays both prices and volumes on a dashboard, as well as the maximum spread detected on a histogram divided by four user-selected percentiles. This allows traders to detect unusual, high, typical, or low spreads.
This highly customizable tool features automatic source selection (crypto or forex) based on the asset in the chart, as well as current and historical spread detection. It also features a dashboard with sortable columns and a historical histogram with percentiles and different smoothing options.
🔶 USAGE
Arbitrage is the practice of taking advantage of price differences for the same asset across different markets. Arbitrage traders look for these discrepancies to profit from buying where it’s cheaper and selling where it’s more expensive to capture the spread.
For begginers this tool is an easy way to understand how prices can vary between markets, helping you avoid trading at a disadvantage.
For advanced traders it is a fast tool to spot arbitrage opportunities or inefficiencies that can be exploited for profit.
Arbitrage opportunities are often short‑lived, but they can be highly profitable. By showing you where spreads exist, this tool helps traders:
Understand market inefficiencies
Avoid trading at unfavorable prices
Identify potential profit opportunities across exchanges
As we can see in the image, the tool consists of two main graphics: a dashboard on the main chart and a histogram in the pane below.
Both are useful for understanding the behavior of the same asset on different crypto exchanges or forex brokers.
The tool's main goal is to detect and categorize spread activity across the major crypto and forex sources. The comparison uses data from up to 19 crypto exchanges and 13 forex brokers.
🔹 Forex or Crypto
The tool selects the appropriate sources (crypto exchanges or forex brokers) based on the asset in the chart. Traders can choose which one to use.
The image shows the prices and volumes for Bitcoin and the euro across the main sources, sorted by descending average price over the last 20 days.
🔹 Dashboard
The dashboard displays a list of all sources with four main columns: last price, average price, volume, and total volume.
All four columns can be sorted in ascending or descending order, or left unsorted. A background gradient color is displayed for the sorted column.
Price and volume delta information between the chart asset and each exchange can be enabled or disabled from the settings panel.
🔹 Histogram
The histogram is excellent for visualizing historical values and comparing them with the asset price.
In this case, we have the Euro/U.S. Dollar daily chart. As we can see, the unusual spread activity detected since 2016, with values at or above 98%, is usually a good indication of increased trader activity, which may result in a key price area where the market could turn around.
By default, the histogram has the gradient and smoothing auto features enabled.
The differences are visible in the chart above. On top is an adaptive moving average with higher values for unusual activity. At the bottom is an exponential moving average with a length of 9.
The differences between the gradient and solid colors are evident. In the first case, the colors are in sync with the data values, becoming more yellow with higher values and more green with lower values. In the second case, the colors are solid and only distinguish data above or below the defined percentiles.
🔶 SETTINGS
Sources: Choose between crypto exchanges, forex brokers, or automatic selection based on the asset in the chart.
Average Length: Select the length for the price and volume averages.
🔹 Percentiles
Percentile Length: Select the length for the percentile calculation, or enable the use of the full dataset. Enabling this option may result in runtime errors due to exceeding the allotted resources.
Unusual % >: Select the unusual percentile.
High % >: Select the high percentile.
Typical % >: Select the typical percentile.
🔹 Dashboard
Dashboard: Enable or disable the dashboard.
Sorting: Select the sorting column and direction.
Position: Select the dashboard location.
Size: Select the dashboard size.
Price Delta: Show the price difference between each exchange and the asset on the chart.
Volume Delta: Show the volume difference between each exchange and the asset on the chart.
🔹 Style
Unusual: Enable the plot of the unusual percentile and select its color.
High: Enable the plot of the high percentile and select its color.
Typical: Enable the plot of the typical percentile and select its color.
Low: Select the color for the low percentile.
Percentiles Auto Color: Enable auto color for all plotted percentiles.
Histogram Gradient: Enable the gradient color for the histogram.
Histogram Smoothing: Select the length of the EMA smoothing for the histogram or enable the Auto feature. The Auto feature uses an adaptive moving average with the data percent rank as the efficiency ratio.
RSI Distribution [Kodexius]RSI Distribution is a statistics driven visualization companion for the classic RSI oscillator. In addition to plotting RSI itself, it continuously builds a rolling sample of recent RSI values and projects their distribution as a forward drawn histogram, so you can see where RSI has spent most of its time over the selected lookback window.
The indicator is designed to add context to oscillator readings. Instead of only treating RSI as a single point estimate that is either “high” or “low”, you can evaluate the current RSI level relative to its own recent history. This makes it easier to recognize when the market is operating inside a familiar regime, and when RSI is pushing into rarer tail conditions that tend to appear during momentum bursts, exhaustion, or volatility expansion.
To complement the histogram, the script can optionally overlay a Gaussian curve fitted to the sample mean and standard deviation. It also runs a Jarque Bera normality check, based on skewness and excess kurtosis, and surfaces the result both visually and in a compact dashboard. On the oscillator panel itself, RSI is presented with a clean gradient line and standard overbought and oversold references, with fills that become more visible when RSI meaningfully extends beyond key thresholds.
🔹 Features
1. Distribution Histogram of Recent RSI Values
The script stores the last N RSI values in an internal sample and uses that rolling window to compute a frequency distribution across a user selected number of bins. The histogram is drawn into the future by a configurable width in bars, which keeps it readable and prevents it from colliding with the active RSI plot. The result is a compact visual summary of where RSI clusters most often, whether it is spending more time near the center, or shifting toward higher or lower regimes.
2. Gaussian Overlay for Shape Intuition
If enabled, a fitted bell curve is drawn on top of the histogram using the sample mean and standard deviation. This overlay is not intended as a direct trading signal. Its purpose is to provide a fast visual comparator between the empirical RSI distribution and a theoretical normal shape. When the histogram diverges strongly from the curve, you can quickly spot skew, heavy tails, or regime changes that often occur when market structure or volatility conditions shift.
3. Jarque Bera Normality Check With Clear PASS/FAIL Feedback
The script computes skewness and excess kurtosis from the RSI sample, then forms the Jarque Bera statistic and compares it to a fixed 95% critical value. When the distribution is closer to normal under this test, the status is marked as PASS, otherwise it is marked as FAIL. This result is displayed in the dashboard and can also influence the histogram styling, giving immediate feedback about whether the recent RSI behavior resembles a bell shaped distribution or a more distorted, regime driven profile.
Jarque Bera is a goodness of fit test that evaluates whether a dataset looks consistent with a normal distribution by checking two shape properties: skewness (asymmetry) and kurtosis (tail heaviness, expressed here as excess kurtosis where a perfect normal has 0). Under the null hypothesis of normality, skewness should be near 0 and excess kurtosis should be near 0. The test combines deviations in both into a single statistic, which is then compared to a chi square threshold. A PASS in this script means the sample does not show strong evidence against normality at the chosen threshold, while a FAIL means the sample is meaningfully skewed, heavy tailed, or both. In practical trading terms, a FAIL often suggests RSI is behaving in a regime where extremes and asymmetry are more common, which is typical during strong trends, volatility expansions, or one sided market pressure. It is still a statistical diagnostic, not a prediction tool, and results can vary with lookback length and market conditions.
4. Integrated Stats Dashboard
A compact table in the top right summarizes key distribution moments and the normality result: Mean, StdDev, Skewness, Kurtosis, and the JB statistic with PASS/FAIL text. Skewness is color coded by sign to quickly distinguish right skew (more time at higher RSI) versus left skew (more time at lower RSI), which can be helpful when diagnosing trend bias and momentum persistence.
5. RSI Visual Quality and Context Zones
RSI is plotted with a gradient color scheme and standard overbought and oversold reference lines. The overbought and oversold areas are filled with a smart gradient so visual emphasis increases when RSI meaningfully extends beyond the 70 and 30 regions, improving readability without overwhelming the panel.
🔹 Calculations
This section summarizes the main calculations and transformations used internally.
1. RSI Series
RSI is computed from the selected source and length using the standard RSI function:
rsi_val = ta.rsi(rsi_src, rsi_len)
2. Rolling Sample Collection
A float array stores recent RSI values. Each bar appends the newest RSI, and if the array exceeds the configured lookback, the oldest value is removed. Conceptually:
rsi_history.push(rsi_val)
if rsi_history.size() > lookback
rsi_history.shift()
This maintains a fixed size window that represents the most recent RSI behavior.
3. Mean, Variance, and Standard Deviation
The script computes the sample mean across the array. Variance is computed as sample variance using (n - 1) in the denominator, and standard deviation is the square root of that variance. These values serve both the dashboard display and the Gaussian overlay parameters.
4. Skewness and Excess Kurtosis
Skewness is calculated from the standardized third central moment with a small sample correction. Kurtosis is computed as excess kurtosis (kurtosis minus 3), so the normal baseline is 0. These two metrics summarize asymmetry and tail heaviness, which are the core ingredients for the Jarque Bera statistic.
5. Jarque Bera Statistic and Decision Rule
Using skewness S and excess kurtosis K, the Jarque Bera statistic is computed as:
JB = (n / 6.0) * (S^2 + 0.25 * K^2)
Normality is flagged using a fixed critical value:
is_normal = JB < 5.991
This produces a simple PASS/FAIL classification suitable for fast chart interpretation.
6. Histogram Binning and Scaling
The RSI domain is treated as 0 to 100 and divided into a configurable number of bins. Bin size is:
bin_size = 100.0 / bins
Each RSI sample maps to a bin index via floor(rsi / bin_size), with clamping to ensure the index stays within valid bounds. The script counts occurrences per bin, tracks the maximum frequency, and normalizes each bar height by freq/max_freq so the histogram remains visually stable and comparable as the window updates.
7. Gaussian Curve Overlay (Optional)
The Gaussian overlay uses the normal probability density function with mu as the sample mean and sigma as the sample standard deviation:
normal_pdf(x) = (1 / (sigma * sqrt(2*pi))) * exp(-0.5 * ((x - mu)/sigma)^2)
For drawing, the script samples x across the histogram width, evaluates the PDF, and normalizes it relative to its peak so the curve fits within the same visual height scale as the histogram.
QUANT TRADING ENGINE [PointAlgo]Quant Trading Engine is a quantitative market-analysis indicator that combines multiple statistical factors to study trend behavior, mean reversion, volatility, execution efficiency, and market stability.
The indicator converts raw price behavior into standardized signals to help evaluate directional bias and risk conditions in a systematic way.
This script focuses on factor alignment and regime awareness, not prediction certainty.
Design Philosophy
Markets move through different regimes such as trending, ranging, volatile expansion, and instability.
This indicator attempts to model these regimes by blending:
Momentum strength
Mean-reversion pressure
Volatility risk
Trend filtering
Execution context (VWAP)
Correlation structure
Each component is normalized and combined into a single Quant Alpha framework.
Factor Construction
1. Momentum Factor
Measures directional strength using percentage price change over a rolling window.
Standardized using mean and standard deviation.
Represents trend continuation pressure.
2. Mean Reversion Factor
Measures deviation from a longer moving average.
Standardized to identify stretched conditions.
Designed to capture counter-trend behavior.
Directional Clamping
Mean-reversion signals are dynamically restricted:
No counter-trend buying during downtrends.
No counter-trend selling during uptrends.
Allows both sides only in neutral regimes.
This prevents conflicting signals in strong trends.
3. Volatility Factor
Uses realized volatility derived from price changes.
Penalizes environments where volatility deviates significantly from its norm.
Acts as a risk adjustment rather than a directional driver.
4. Composite Quant Alpha
The final Quant Alpha is a weighted blend of:
Momentum
Mean reversion (trend-clamped)
Volatility risk
The composite is standardized into a Z-score, allowing consistent interpretation across instruments and timeframes.
Signal Logic
Buy signal occurs when Quant Alpha crosses above zero.
Sell signal occurs when Quant Alpha crosses below zero.
Zero-cross logic is used to represent shifts from negative to positive statistical bias and vice versa.
Signals reflect statistical regime change, not trade instructions.
Volatility Smile Context
Measures price deviation from its statistical distribution.
Identifies skewed conditions where upside or downside volatility becomes dominant.
Highlights extreme deviations that may imply elevated derivative risk.
Exotic Risk Conditions
Detects sudden price expansion combined with volatility spikes.
Highlights environments where execution and risk become unstable.
Visual background cues are used for awareness only.
Execution Context (VWAP)
Measures price distance from VWAP.
Used to assess execution efficiency rather than direction.
Helps identify stretched conditions relative to average traded price.
Correlation Structure
Evaluates short-term return correlations.
Detects when price behavior becomes less predictable.
Flags structural instability rather than trend direction.
Visualization
The indicator plots:
Quant Alpha (scaled) with directional coloring
Volatility smile deviation
Price vs VWAP distance
Correlation structure
Signal markers indicate Quant Alpha zero-cross events and risk conditions.
Dashboard
A compact dashboard summarizes:
Trend filter state
Quant Alpha polarity and value
Individual factor readings
Current action state (Buy / Sell / Wait / Risk)
The dashboard provides a real-time snapshot of internal model conditions.
Usage Notes
Designed for analytical interpretation and research.
Best used alongside price action and risk management tools.
Factor behavior depends on instrument liquidity and volatility.
Not optimized for illiquid or irregular markets.
Disclaimer
This script is provided for educational and analytical purposes only.
It does not provide financial, investment, or trading advice.
All outputs should be independently validated before making any trading decisions.
