ICT-Elliott Hybrid Oscillator네이버 프리미엄 콘텐츠 > 재테크 사관학교 검색
This indicator uses Elliott Wave Theory and ICT (Inner Circle Trader) concepts to help easily and accurately predict when asset prices like cryptocurrencies or stocks will rise or fall.
📌 Easy Explanation of Terms
✅ What is Elliott Wave?
A theory stating that price movements follow a specific pattern (5 upward waves + 3 downward waves) repeatedly. Simply put, it's about repetitive cycles of rises and falls creating overall trends.
✅ What is ICT Theory?
A strategy that identifies optimal trading times by observing critical price areas traded by institutional investors (Order Blocks), imbalances in price (Fair Value Gaps - FVG), and major turning points (Break of Structure - BOS).
📈 Signals Provided by the Indicator
🔹 ① Pivot Highs & Lows
Red ▼: Short-term high (increased likelihood of price falling)
Green ▲: Short-term low (increased likelihood of price rising)
🔹 ② Fair Value Gap (FVG)
Green highlighted area: Zone where price is likely to rise again
Red highlighted area: Zone where price is likely to fall again
🔹 ③ Break of Structure (BOS)
Blue "BOS Up": Indicates a shift to an upward trend
Orange "BOS Down": Indicates a shift to a downward trend
⏳ Recommended Timeframe Combinations
| Major Trend (Basic Analysis) | Entry Point (Detailed Analysis) | Short-term Timing (Precision Analysis) |
| ---------------------------- | ------------------------------- | -------------------------------------- |
| 4-hour | 1-hour | 15-minute |
Use the 4-hour timeframe to gauge overall trends,
the 1-hour timeframe to pinpoint exact entry and exit points,
and the 15-minute timeframe for precise timing.
Include Source
🕯 Recommended Candle Patterns
* Pin Bar (Long wick candle) → Trend reversal signal
* Engulfing Candle (fully covering previous candle) → Strong trend reversal signal
* Hammer & Shooting Star (small body with a long wick) → Bullish or bearish reversal signal
* Doji (balance between buyers and sellers) → High potential for trend reversal
Dönemler
Multi-Index Gap Confluence Indicator by ATALLAOverview of the Multi-Index Gap Confluence Indicator
This indicator is designed to identify and highlight price gaps across multiple market indices and their related ETFs/futures. It specifically looks for:
True gaps (where there's no overlap between the current and previous bar's range)
Negative gaps (where only the candle bodies have no overlap, but wicks might)
The indicator has the capability to:
Visualize gaps on charts using colored rectangles
Compare gaps across up to 6 different symbols (3 ETFs and 3 futures)
Generate confluence signals when multiple symbols show gaps simultaneously
Customize appearance and detection parameters
Key Components
Gap Detection
The script distinguishes between:
True gaps: No overlap at all between current and previous bars
Negative gaps: Only the candle bodies have no overlap
Multi-Asset Comparison
The indicator can monitor gaps across six major market indices:
ETFs: QQQ (Nasdaq-100), SPY (S&P 500), and DIA (Dow Jones)
Futures: NQ1! (Nasdaq-100), ES1! (S&P 500), and YM1! (Dow Jones)
Confluence Detection
The script identifies when multiple assets display gaps simultaneously, with:
Configurable minimum threshold (default is 5 out of 6 assets)
Option to require both ETF and futures representation
A strong confluence signal when 5-6 assets show gaps
Customization Options
The indicator offers many parameters for customization:
Gap colors and opacity
Symbol selection and enablement
Confluence thresholds
Display options
Visual Elements
The indicator displays:
Colored rectangles highlighting gap areas
Optional up/down triangles for gap direction
A flag symbol for strong confluence signals (when 5-6 assets show gaps)
Labels listing which specific assets have gaps
Practical Use
This indicator appears designed for traders looking to identify potentially significant market moves by spotting when multiple major indices show price gaps simultaneously. The emphasis on "strong confluence" (5-6 assets showing gaps) suggests these are considered particularly noteworthy signals.
smc bullrider 1.0The smc bullrider 1.0 indicator is specifically crafted for mapping market structures. It excels in clearly recognizing type of Points Of Interest (SCOB) offering traders a straightforward and effective method to analyze market movements. It helps identify strategic entry points with precision.
🟠 Exploring Structure Mapping.
🔹This indicator presents a distinctive method for examining the market structure, emphasizing liquidity through the concept of 'Inducement'. Inducement plays a pivotal role in pinpointing essential structural indicators in the market, including Higher Highs (HH), Higher Lows (HL), Lower Lows (LL), and Lower Highs (LH).
🔹Consider Inducement as a strategically placed trap near supply or demand zones. It lures in eager buyers or sellers before the actual zone is reached, effectively creating liquidity. To validate an inducement, it must signify a legitimate pullback.
🔹A valid scenario arises when the price either sweeps or closes beyond the high or low of the preceding candle. In this context, the candle's color, whether bullish or bearish, holds no significance, and both situations are deemed valid. Inside bars are disregarded unless they meet this specific criterion. The indicator facilitates this process by automatically highlighting valid pullbacks with a distinctive gray round label.
🔹This feature serves not only as a visual guide but also as a vital tool for effortlessly comprehending market movements, offering a clear and visual representation of ongoing market trends
🟣 Understanding POI Functionality
🔹Single Candle Order Block (SCOB): Leveraging single-candle mitigation proves to be a powerful method for incorporating multiple entries into your successful trades.
🔵 How to Utilize the smc bullrider 1.0 Indicator:
🔹The smc bullrider 1.0 Indicator is crafted to elevate your trading strategy by pinpointing crucial order blocks and market signals. Below is a guide on how to make the most of the different components of the smc bullrider 1.0 Indicator:
🔹SCOB (Single Candle Order Block):
Application: SCOB is well-suited for scaling into a position. It is best utilized to increase positions when the market responds to OB or OB-EXT, signaling a potential reversal.
🟢Here's how to use it.
🔹Market Structure Drawing
This diagram depicts significant market indicators, such as instances of ascending prices (Higher Highs - HH) or descending prices (Lower Lows - LL). It serves as a valuable visual tool for comprehending the dynamics of market behavior
PICTURE (DIAGRAM)
Live Chart Example: Our indicator efficiently dissects market structure, showcasing the 'Inducement' concept with precision in real-time trends—highlighting HH, HL, LL, and LH
PICTURE (REAL CHART)
Valid Pullback ( IDM ):
Valid Pullback Example: This image illustrates a common situation where the price extends beyond the high or low of the preceding candle, signifying a valid pullback. Pay attention to the identifiable gray dotted line label marking the inducement point.
PICTURE (DRAW/REAL)
Single Candle Order Block (SCOB)
The provided chart showcases the SCOB in a real trading setting, highlighting its effectiveness in optimizing trades.
🟡 Summary
🔹smc bullrider 1.0 Indicator distinguishes itself in the realm of market analysis, with a distinct focus on structure mapping and high-probability Point of Interest (POI).
Furthermore, it provides a visual representation of three key areas for each market move: discount, premium, and the equilibrium area at 50%. Its innovative approach involves scrutinizing market structure using the 'Inducement' concept, a pivotal strategy for identifying vital structural markers and steering
ict cbdr# ICT CBDR - Central Bank Dealers Range
This indicator identifies and displays the Central Bank Dealers Range (CBDR), a concept from Inner Circle Trader (ICT) methodology. The CBDR represents the consolidation period between 2:00 PM and 8:00 PM New York time, during which major financial institutions establish their positions.
## Features
- **Customizable Time Range:** Default setting is the standard 2:00 PM - 8:00 PM NY time, but can be adjusted to any session
- **Timezone Selection:** Choose your preferred timezone while maintaining accurate CBDR tracking
- **Visual Range Box:** Clearly displays the high and low range established during the selected session
- **Equator (EQ) Line:** Shows the 50% mid-point of the range for potential support/resistance
- **Projection Lines:** Automatically projects extensions of the range for potential targets
- **Adjustable Multiplier:** Option for 0.5× or 1× range projections
- **Range Type Selection:** Use price wicks or bodies to establish the range
## How to Use This Indicator
The CBDR forms a consolidation zone that often precedes significant price movements. After this range is established, markets tend to move away from this area with directional bias. Trading strategies commonly involve:
1. **Breakout Trading:** Enter when price breaks above/below the CBDR
2. **Range Trading:** Fade moves from the edges of the range back to the EQ line
3. **EQ Line Support/Resistance:** Use the mid-range as a pivot point
4. **Extension Targets:** Utilize the projection lines as potential take-profit levels
## Settings
- **Show CBDR:** Toggle the visibility of the range box
- **Range Type:** Select whether to use candle wicks or bodies for range calculation
- **Timezone:** Choose your preferred timezone (default is America/New York)
- **Session Time:** Adjust the session time in 24-hour format (default is 1400-2000)
- **EQ Line:** Toggle and customize the equator line
- **Projections:** Toggle and adjust the number and appearance of projection lines
- **Use 0.5 Deviation:** When enabled, uses half-sized projections
- **Hide Above __ Minutes:** Controls on which timeframes the indicator is displayed
## Notes
- The traditional CBDR is specifically the 2:00 PM - 8:00 PM NY time range
- This indicator is most effective on lower timeframes (1-15 minute charts)
- Remember to combine this tool with proper risk management and additional confirmation
- Works best on forex and highly liquid markets
## Disclaimer
This indicator is for informational and educational purposes only. Past performance is not indicative of future results. Always conduct your own analysis and use proper risk management.
Yearly History Calendar-Aligned Price up to 10 Years)Overview
This indicator helps traders compare historical price patterns from the past 10 calendar years with the current price action. It overlays translucent lines (polylines) for each year’s price data on the same calendar dates, providing a visual reference for recurring trends. A dynamic table at the top of the chart summarizes the active years, their price sources, and history retention settings.
Key Features
Historical Projections
Displays price data from the last 10 years (e.g., January 5, 2023 vs. January 5, 2024).
Price Source Selection
Choose from Open, Low, High, Close, or HL2 ((High + Low)/2) for historical alignment.
The selected source is shown in the legend table.
Bulk Control Toggles
Show All Years : Display all 10 years simultaneously.
Keep History for All : Preserve historical lines on year transitions.
Hide History for All : Automatically delete old lines to update with current data.
Individual Year Settings
Toggle visibility for each year (-1 to -10) independently.
Customize color and line width for each year.
Control whether to keep or delete historical lines for specific years.
Visual Alignment Aids
Vertical lines mark yearly transitions for reference.
Polylines are semi-transparent for clarity.
Dynamic Legend Table
Shows active years, their price sources, and history status (On/Off).
Updates automatically when settings change.
How to Use
Configure Settings
Projection Years : Select how many years to display (1–10).
Price Source : Choose Open, Low, High, Close, or HL2 for historical alignment.
History Precision : Set granularity (Daily, 60m, or 15m).
Daily (D) is recommended for long-term analysis (covers 10 years).
60m/15m provides finer precision but may only cover 1–3 years due to data limits.
Adjust Visibility & History
Show Year -X : Enable/disable specific years for comparison.
Keep History for Year -X : Choose whether to retain historical lines or delete them on new year transitions.
Bulk Controls
Show All Years : Display all 10 years at once (overrides individual toggles).
Keep History for All / Hide History for All : Globally enable/disable history retention for all years.
Customize Appearance
Line Width : Adjust polyline thickness for better visibility.
Colors : Assign unique colors to each year for easy identification.
Interpret the Legend Table
The table shows:
Year : Label (e.g., "Year -1").
Source : The selected price type (e.g., "Close", "HL2").
Keep History : Indicates whether lines are preserved (On) or deleted (Off).
Tips for Optimal Use
Use Daily Timeframes for Long-Term Analysis :
Daily (1D) allows 10+ years of data. Smaller timeframes (60m/15m) may have limited historical coverage.
Compare Recurring Patterns :
Look for overlaps between historical polylines and current price to identify potential support/resistance levels.
Customize Colors & Widths :
Use contrasting colors for years you want to highlight. Adjust line widths to avoid clutter.
Leverage Global Toggles :
Enable Show All Years for a quick overview. Use Keep History for All to maintain continuity across transitions.
Example Workflow
Set Up :
Select Projection Years = 5.
Choose Price Source = Close.
Set History Precision = 1D for long-term data.
Customize :
Enable Show Year -1 to Show Year -5.
Assign distinct colors to each year.
Disable Keep History for All to ensure lines update on year transitions.
Analyze :
Observe how the 2023 close prices align with 2024’s price action.
Use vertical lines to identify yearly boundaries.
Common Questions
Why are some years missing?
Ensure the chart has sufficient historical data (e.g., daily charts cover 10 years, 60m/15m may only cover 1–3 years).
How do I update the data?
Adjust the Price Source or toggle years/history settings. The legend table updates automatically.
AMA Alpha TrendKey Features
4 EMAs (20, 50, 100, 200) plotted in distinct colors
ATR-based Trend Line
Uses mid-price (HL/2) ± ATR × Multiplier
Automatically “steps” higher in up-trends and lower in down-trends
Colored green when bullish, red when bearish
Breakout Triangles
▲ Green triangle when price closes above the trend line → potential long entry
▼ Red triangle when price closes below the trend line → potential short entry
Continuation Dots
● Green dot under every bar that remains above the trend line (bullish continuation)
● Red dot above every bar that remains below the trend line (bearish continuation)
Inputs & Customization
ATR Length: look-back period for True Range (default 14)
ATR Multiplier: channel width factor (default 2.0)
EMA Periods: hard-coded to 20, 50, 100, 200 but can be modified in code
How to Use
Trend Identification
When the trend line turns green, the market is bullish.
When it turns red, the market is bearish.
Entries
Long: look for a ▲ green triangle (price crossing above the green trend line).
Short: look for a ▼ red triangle (price crossing below the red trend line).
Trend Following
Hold as long as continuation dots (●) keep appearing in the trend direction.
Exits & Stops
Consider exiting when the opposite breakout triangle appears.
Place stops just beyond the trend line or a multiple of ATR.
Why This Works
Combining multiple EMAs with a dynamically-sized ATR channel captures both the direction and strength of a move. Breakout triangles mark fresh trend initiations, while the tiny dots confirm that momentum is still intact.
Tip: Experiment with the ATR multiplier on different timeframes—lower values for tighter, more sensitive signals; higher for filtering out noise.
Bollinger Volatility AnalyzerThe Bollinger Volatility Analyzer (BVA) is a powerful enhancement of the traditional Bollinger Bands indicator, tailored to help traders identify volatility cycles and catch potential breakouts with better precision and timing. It builds upon the foundational concept of Bollinger Bands—using a moving average and standard deviation bands—but adds crucial insights into market contraction and expansion, which can be instrumental in timing entries and exits.
Here's how it works and why it's useful
At its core, the indicator calculates a moving average (called the "basis") and plots two bands—one above and one below—based on a multiple of standard deviation. These bands expand during volatile periods and contract during quiet ones. The width between these bands, normalized as a percentage of the basis, gives us a sense of how compressed or expanded the market currently is. When the band width drops below a user-defined threshold (like 2%), the script highlights this with an orange triangle below the bar. This is the "squeeze" condition, signaling a potential buildup of market energy—a kind of calm before the storm.
What makes this version of Bollinger Bands particularly powerful is that it not only detects squeezes, but also tells you when price breaks out of that squeeze range. If price closes above the upper band after a squeeze, a green "Breakout ↑" label is shown; if it closes below the lower band, a red "Breakout ↓" appears. These breakout labels act as entry signals, suggesting that volatility is returning and a directional move has begun.
This indicator is especially useful in markets that tend to alternate between consolidation and breakout phases, such as forex, crypto, and even individual stocks. Traders who look for early signs of momentum—whether for swing trading, scalping, or position building—can benefit from this tool. During a quiet market phase, the indicator warns you that a move might be coming; when the move starts, it tells you the direction.
In fast-moving markets, BVA helps filter out noise by focusing only on high-probability conditions: quiet consolidation followed by a strong breakout. It’s not a complete system by itself—it works best when paired with volume confirmation or oscillators like RSI—but as a volatility trigger and directional guide, it’s a reliable component of a trading workflow.
MA Dispersion+MA Dispersion+ — read the “breathing space” between your moving-averages
Get instant feedback on trend strength, volatility expansion and mean-reversion — across any timeframe.
MA Dispersion+ turns the humble moving-average stack into a single, easy-to-read oscillator that tells you at a glance whether price is coiling or fanning out.
🧩 What it does
Plugs into your favourite MA setup
• Pick the classic 5 / 20 / 50 / 200 lengths or disable any combination with one click.
• Choose the MA engine you trust — SMA, EMA, RMA, VWMA or WMA.
• Works on any timeframe thanks to TradingView’s security() engine.
Measures “spread”
For every bar it calculates the absolute distance of each selected MA from their average.
The tighter the stack, the lower the value; the wider the fan, the higher the value.
Adds professional-grade controls
• Weighting — let short-term MAs dominate (Inverse Length), keep everything equal, or dial in your own custom weights.
• Normalisation — convert the raw distance into a percentage of price, ATR multiples, or scale by the MAs’ own mean so you can compare symbols of any price or volatility.
🔍 How traders use it
Trend confirmation – rising dispersion while price breaks out = momentum is genuine.
Volatility squeeze – dispersion parking near zero warns that a big move is loading.
Multi-TF outlook – drop one pane per timeframe (e.g. 5 m, 1 h, 1 D) and see which layer of the market is driving.
Mean-reversion plays – spikes that fade quickly often coincide with exhaustion and snap-backs.
⚙️ Quick-start
Add MA Dispersion+ to your chart.
Set the pane’s timeframe in the first input.
Tick the MA lengths you actually use.
(Optional) Pick a weighting scheme and a normaliser.
Repeat the indicator for as many timeframes as you like — each instance keeps its own settings.
✨ Why you’ll love it
Zero clutter – one orange line tells you what four separate MAs whisper.
Configurable yet bullet-proof – all lengths are hard-coded constants, so Pine never complains.
Context aware – normalisation lets you compare BTC’s $60 000 chaos with EURUSD’s four--decimals calm.
Lightweight – no labels, no drawings, no background processing — perfect for mobile and multi-pane layouts.
Give MA Dispersion+ a try and let your charts breathe — you’ll never look at moving-average ribbons the same way again.
Happy trading!
LANZ Strategy 2.0🔷 LANZ Strategy 2.0 — London Breakout Confirmation with Structural Swing Protection
LANZ Strategy 2.0 is a structured trading system that leverages the last confirmed market direction before the London session to define directional bias and manage trades based on key structural swing levels. It is tailored for intraday traders looking to capitalize on early London volatility with built-in risk management and visual clarity.
🧠 Core Components:
Directional Confirmation (Pre-London Bias): Validates the last breakout or structural move from the 15-minute timeframe before 02:15 a.m. New York time (start of the London session), establishing the expected market direction.
Time-Based Execution: Executes potential entries strictly at 02:15 a.m. NY time, using market structure to support Long or Short bias.
Dynamic Swing-Based SL System: Allows user to select between three SL protection models: First Swing (most recent structural point) Second Swing (prior level) Total Coverage (includes both swings + extra buffer) This supports flexibility based on trader profile or market conditions.
Visual Risk Mapping: All SL and TP levels are clearly plotted.
End-of-Session Management: Positions are automatically evaluated for closure at 11:45 a.m. NY time. SL, TP, or manual close outcomes are labeled accordingly.
📊 Visual Features:
Labels for 1st and 2nd swing levels upon entry.
Dynamic lines projecting SL/TP levels toward the end of the session.
Session background coloring for Pre-London, Execution, and NY sessions.
Real-time percentage outcome labels (+2.00%, -1.00%, or net % at session end).
Automatic deletion of previous visuals on new entries for clean charting.
⚙️ How It Works:
Detects last structural breakout on the 15m timeframe before 02:15 a.m. NY.
On the 02:15 a.m. candle, executes a Long or Short logic entry.
Plots corresponding SL and TP based on selected swing model.
Monitors price action: If TP or SL is hit, labels it accordingly. If no exit is hit, trade closes manually at 11:45 a.m. NY with net result shown.
Optional logic to reverse entries if market structure breaks before execution.
🔔 Alerts:
Daily execution alert at 02:15 a.m. NY (prompting manual review or action).
Optional alert logic can be extended for SL/TP hits or structure breaks.
📝 Notes:
Designed for semi-automated or discretionary intraday trading.
Best used on Forex pairs or indices with strong London session behavior.
Adjustable parameters include session hours, swing SL type, and buffer settings.
Credits:
Developed by LANZ, this script combines time-based execution with dynamic structure protection, offering a disciplined framework for participating in the London session breakout with clear visuals and risk logic.
Divergence Macro Sentiment Indicator (DMSI)The Divergence Macro Sentiment Indicator (DMSI)
Think of DMSI as your daily “mood ring” for the markets. It boils down the tug-of-war between growth assets (S&P 500, copper, oil) and safe havens (gold, VIX) into one clear histogram—so you instantly know if the bulls have broad backing or are charging ahead with one foot tied behind.
🔍 What You’re Seeing
Green bars (above zero): Risk-on conviction.
Equities and commodities are rallying while gold and volatility retreat.
Red bars (below zero): Risk-off caution.
Gold or VIX are climbing even as stocks rise—or stocks aren’t fully joined by oil/copper.
Zero line: The line in the sand between “full-steam ahead” and “proceed with care.”
📈 How to Read It
Cross-Zero Signals
Bullish trigger: DMSI flips up through zero after a red stretch → fresh long entries.
Bearish trigger: DMSI tumbles below zero from green territory → tighten stops or go defensive.
Divergence Warnings
If SPX makes new highs but DMSI is rolling over (lower green bars or red), that’s your early red flag—rallies may fizzle.
Strength Confirmation
On pullbacks, only buy dips when DMSI ≥ 0. When DMSI is deeply positive, you can be more aggressive on position size or add leverage.
💡 Trade Guidance & Use Cases
Trend Filter: Only take your S&P or sector-ETF long setups when DMSI is non-negative—avoids hollow rallies.
Macro Pair Trades:
Deep red DMSI: go long gold or gold miners (GLD, GDX).
Strong green DMSI: lean into cyclicals, industrials, even energy names.
Risk Management:
Scale out as DMSI fades into negative territory mid-trade.
Scale in or add to winners when it stays bullish.
Swing Confirmation: Overlay on any oscillator or price-pattern system—accept signals only when the macro tide is flowing in your favour.
🚀 Why It Works
Markets don’t move in a vacuum. When stocks rally but the “real-economy” metals and volatility aren’t cooperating, something’s off under the hood. DMSI catches those cross-asset cracks before price alone can—and gives you an early warning system for smarter entries, tighter risk, and bigger gains when the macro trend really kicks in.
Vietnamese Market Structure With CountersThis indicator is designed to track Market Structure with Swing-Low Breakdowns and Swing-High Breakups specifically tailored for the Vietnamese stock market, though it can be applied elsewhere too. By default, it uses a 10-period EMA to dynamically detect key turning points in price action and count significant breakdowns or breakups from previous swing levels.
As an open source, you can modify the source code to match your needs.
What it does:
Detects when price breaks below previous swing lows or above previous swing highs.
Plots swing levels for both highs and lows.
Displays labeled counters on the chart to show how many consecutive breakdowns or breakups have occurred.
Helps traders identify trend shifts and possible exhaustion in moves.
Why it's useful:
This tool is great for visually tracking market momentum and structure changes — especially in trending or volatile environments. It emphasizes structure over indicators, helping you understand price behavior in a simplified, intuitive way.
License:
This script is published under the Mozilla Public License 2.0. Feel free to use, modify, and contribute!
Created with care by @doqkhanh.
If you find it useful, consider leaving a comment or sharing it with others!
Ultimate NATR█ | Overview
This N-ATR (Normalized Average True Range) volatility indicator illustrates the trend of percentage-based candle volatility over a self-defined number of bars (period). The primary objective of the indicator is to highlight periods of high or low volatility, which can be exploited within the cyclical logic of volatility contraction and expansion. If market behavior is inherently cyclical, it naturally follows that candle volatility itself also exhibits cyclical characteristics.
It can therefore be defined as a recurring pattern:
Low Volatility --> High Volatility --> Low Volatility -->
Here is a concrete example of the cyclical phases of volatility, which compresses during Accumulation or Distribution phases, and then explodes with a mark-up or mark-down in price.
█ | Features
🔵 Plots on Overlay false
Smoothed NATR Line
NATR's Fixed Levels
NATR's Standard Deviation Levels (Dynamic)
🔵 Elements, overlapped to the chart
Analytical and Statistical Tables
NATR Information Label
🔵 Customization
Button to calculate fixed or dynamic (auto-calculated) levels
Dark / light mode based on the layout background
Setting of the initial date for the calculation of N-ATR dependent functions
ATR period
Moving Average of the N-ATR
Data sample (number) on which to calculate the standard deviation of the N-ATR
Adjustment of the multiplicative coefficients of the standard deviation σ
Setting of static values L1, L2, L3, and L4 of the N-ATR
Adjustment of the table zoom factor
█ | N-ATR Calculation
The N-ATR function is built upon the ATR (Average True Range), the quintessential volatility indicator.
Once the ATR_period is defined, the N-ATR is calculated using the following formula:
N-ATR = 100 * ATR / close
A moving average of the N-ATR completes the main indicator curve (yellow), making the function smoother and less sensitive to the instantaneous fluctuations of individual candles.
SMA_natr = sum(natr_i) / ATR_period
natr = 100 * ta.atr(periodo_ATR) / close
media_natr = ta.sma(natr, media_len)
█ | Settings
Show selected calc period : allows you to display or hide a background color that extends from the initial calculation date to the current bar, or from the first available bar if the selected date is earlier.
Set data range for ST.DEV : this setting defines the number of bars over which the standard deviation is calculated—an essential foundational element for plotting the upper and lower curves relative to the N-ATR, as well as for defining the statistical ranges in the tables overlaid on the price chart.
Static Levels : these are user-defined input values representing N-ATR value thresholds, used to classify table values within the ranges L1–L2 / L2–L3 / L3–L4 / >L4. To be meaningful, the user is expected to conduct separate statistical analysis using a spreadsheet or external data analysis tools or languages.
Coefficients x, w, y : these are input values used in the code to calculate statistical ranges and the bands above and below the N-ATR. For example, when expressing the statistical range as μ ± nσ, n can take the value of x, w, or y. By default, the values are x=1, w=2, y=3. However, as explained, they can be customized to represent wider or narrower statistical clusters, depending on the user's analytical preference.
█ | Tables
Static Levels : when the boolean button "Fixed Levels" is active, the table counts and distributes the data across five ranges, defined by the custom input values L1, L2, L3, and L4. Studying the table immediately answers the question: "Have I set appropriate values for the L_x levels?"
If the majority of data points fall within the lowest range, it indicates that the levels are spaced too far apart; conversely, if most values are in the "> L4" range, the levels are likely too narrow.
From left to right, the table also displays the probability that the current candle might move from its current range to the next one (Update Prob.); the absolute frequency of each range and the relative frequency are shown in the rightmost column.
Dynamic Levels : alternatively, you can deselect "Fixed Levels" to obtain an auto-calculated / self-adjusting representation of the N-ATR and its bands, based on the standard deviation input settings. In this case, the table takes on a more statistical form, useful for analyzing the frequency of outliers beyond a certain standard deviation, as defined by the largest multiplicative coefficient "y".
This visualization may also be preferred when aiming to study the standard deviation of the N-ATR in greater depth for a given asset, timeframe, and configuration more broadly.
█ | Next-to-Price Label
Information in the label next to the live price: if the first settings button in the indicator, "Fixed levels", is enabled (true), a label appears next to the price showing information about the relative position of the N-ATR associated with the current candle.
Specifically, if:
natr ≤ L1, ⇨ "Minimum-"
natr > L1 and natr ≤ L2, ⇨ "Minimum+"
natr > L2 and natr ≤ L3, ⇨ "Neutral L3"
natr > L3 and natr ≤ L4, ⇨ "Topping L4"
natr > L4, ⇨ "Excess L4: natr > V4"
Additionally, the corresponding N-ATR range is displayed to the right of the evaluated category for the individual candle.
1-Please note: this allows you to avoid constantly checking the N-ATR curve, especially when working in full-screen mode and focusing solely on the price chart for a cleaner view.
2-Please note : unfortunately, the informational label is not available in Dynamic display mode.
█ | Conclusion
• This indicator captures a snapshot of market turbulence. Whether currently unfolding or approaching, the combination of volatility breakout forecasting with price structure analysis—further evaluated based on periods of compression or high turbulence—offers traders a powerful tool for identifying trend-aligned trade opportunities.
• The accompanying analytical tables enhance the indicator by enabling a statistical interpretation of the likelihood that certain excess thresholds will be reached. Based on this data, traders can gain deeper insight into the nature of the asset, identify outlier volatility levels, and strengthen the hedging of their trades. Used as a filter, this indicator significantly improves win rate potential.
Please note : the indicator is shown here on a black background. I suggest you trying it on a white layout as well, so you can decide which visualization best suits your preferences.
Bitcoin Impact AnalyzerSummary of the "Bitcoin Impact Analyzer" script, the adjustments users can make, and an explanation of what the chart and table represent:
Script Summary:
The "Bitcoin Impact Analyzer" script is designed to help traders and analysts understand the relationship between a chosen altcoin and Bitcoin (BTC). It does this by:
Fetching price data for the specified altcoin and Bitcoin.
Calculating several key comparative metrics:
Normalized Prices: Shows the percentage performance of both assets from a common starting point.
Price Correlation: Measures how similarly the two assets' prices move over a defined period.
Beta: Indicates the altcoin's volatility relative to Bitcoin.
Altcoin/BTC Ratio: Shows the altcoin's value expressed in Bitcoin.
Fetching and displaying Bitcoin Dominance (BTC.D) data.
Visualizing these metrics on the chart as distinct plots.
Displaying the current values of these key metrics in a data table on the chart for quick reference.
The script aims to provide insights into whether an altcoin is outperforming or underperforming Bitcoin, how closely its price movements are tied to Bitcoin's, and its relative volatility.
User Adjustments:
Users can customize the script's behavior through several input settings:
Symbol Inputs:
Altcoin Symbol: Users can enter the ticker symbol for any altcoin they wish to analyze (e.g., BINANCE:ETHUSDT, KUCOIN:SOLUSDT).
Bitcoin Reference Symbol: Users can specify the Bitcoin pair to use as a reference, though BINANCE:BTCUSDT is a common default.
Lookback for Correlation/Beta:
Lookback Period: This integer value (default 50 periods) determines how many past candles are used to calculate the price correlation and beta.
A shorter lookback makes the metrics more sensitive to recent price action.
A longer lookback provides a smoother, more stable indication of the longer-term relationship.
Plot Visibility Options:
Users can toggle on or off the display of each individual plot on the chart:
Normalized BTC & Altcoin Prices
Altcoin/BTC Ratio
Correlation Plot
Bitcoin Dominance (BTC.D)
Beta Plot
This allows users to focus on specific metrics and reduce chart clutter.
What the Chart Represents:
The chart visually displays the historical trends and relationships of the selected metrics:
Normalized Prices Plot: Two lines (typically orange for BTC, blue for the altcoin) show the percentage growth of each asset from the start of the loaded chart data (or the first available data point for each symbol). This makes it easy to see which asset has performed better over time on a relative basis.
Correlation Plot: A single line (purple) oscillates between -1 and +1.
Values near +1 indicate a strong positive correlation (altcoin and BTC prices tend to move in the same direction).
Values near -1 indicate a strong negative correlation (they tend to move in opposite directions).
Values near 0 indicate little to no linear relationship.
Lines at +0.7 and -0.7 are often plotted as thresholds for "strong" correlation.
Beta Plot (if enabled): A single line (teal) shows the altcoin's volatility relative to BTC.
A Beta of 1 (often marked by a dashed line) means the altcoin has, on average, the same volatility as BTC.
Beta > 1 suggests the altcoin is more volatile than BTC (moves by a larger percentage for a given BTC move).
Beta < 1 suggests the altcoin is less volatile than BTC.
Bitcoin Dominance Plot: An area plot (gray) shows the percentage of the total cryptocurrency market capitalization that Bitcoin holds. This helps understand broader market sentiment and capital flows.
Altcoin/BTC Ratio Plot: A line (fuchsia) shows the price of the altcoin denominated in BTC.
An upward trend means the altcoin is gaining value against Bitcoin (outperforming).
A downward trend means the altcoin is losing value against Bitcoin (underperforming).
What the Table Represents:
The data table, typically located in the bottom-right corner of the chart, provides a snapshot of the current values for the most important calculated metrics. It includes:
Altcoin: The ticker symbol of the analyzed altcoin.
Bitcoin Ref: The ticker symbol of the Bitcoin reference.
Correlation (lookback): The current correlation coefficient between the altcoin and BTC, based on the specified lookback period. The value is color-coded (e.g., green for strong positive, red for strong negative).
Beta (lookback): The current beta value of the altcoin relative to BTC, based on the specified lookback period. The value may be color-coded to highlight significantly high or low volatility.
BTC.D Current: The current Bitcoin Dominance percentage.
ALT/BTC Ratio: The current price of the altcoin expressed in Bitcoin.
The table offers a quick, at-a-glance summary of the present market dynamics between the two assets without needing to interpret the lines on the chart for their exact current values.
Quarterly Theory ICT 05 [TradingFinder] Doubling Theory Signals🔵 Introduction
Doubling Theory is an advanced approach to price action and market structure analysis that uniquely combines time-based analysis with key Smart Money concepts such as SMT (Smart Money Technique), SSMT (Sequential SMT), Liquidity Sweep, and the Quarterly Theory ICT.
By leveraging fractal time structures and precisely identifying liquidity zones, this method aims to reveal institutional activity specifically smart money entry and exit points hidden within price movements.
At its core, the market is divided into two structural phases: Doubling 1 and Doubling 2. Each phase contains four quarters (Q1 through Q4), which follow the logic of the Quarterly Theory: Accumulation, Manipulation (Judas Swing), Distribution, and Continuation/Reversal.
These segments are anchored by the True Open, allowing for precise alignment with cyclical market behavior and providing a deeper structural interpretation of price action.
During Doubling 1, a Sequential SMT (SSMT) Divergence typically forms between two correlated assets. This time-structured divergence occurs between two swing points positioned in separate quarters (e.g., Q1 and Q2), where one asset breaks a significant low or high, while the second asset fails to confirm it. This lack of confirmation—especially when aligned with the Manipulation and Accumulation phases—often signals early smart money involvement.
Following this, the highest and lowest price points from Doubling 1 are designated as liquidity zones. As the market transitions into Doubling 2, it commonly returns to these zones in a calculated move known as a Liquidity Sweep—a sharp, engineered spike intended to trigger stop orders and pending positions. This sweep, often orchestrated by institutional players, facilitates entry into large positions with minimal slippage.
Bullish :
Bearish :
🔵 How to Use
Applying Doubling Theory requires a simultaneous understanding of temporal structure and inter-asset behavioral divergence. The method unfolds over two main phases—Doubling 1 and Doubling 2—each divided into four quarters (Q1 to Q4).
The first phase focuses on identifying a Sequential SMT (SSMT) divergence, which forms when two correlated assets (e.g., EURUSD and GBPUSD, or NQ and ES) react differently to key price levels across distinct quarters. For example, one asset may break a previous low while the other maintains structure. This misalignment—especially in Q2, the Manipulation phase—often indicates early smart money accumulation or distribution.
Once this divergence is observed, the extreme highs and lows of Doubling 1 are marked as liquidity zones. In Doubling 2, the market gravitates back toward these zones, executing a Liquidity Sweep.
This move is deliberate—designed to activate clustered stop-loss and pending orders and to exploit pockets of resting liquidity. These sweeps are typically driven by institutional forces looking to absorb liquidity and position themselves ahead of the next major price move.
The key to execution lies in the fact that, during the sweep in Doubling 2, a classic SMT divergence should also appear between the two assets. This indicates a weakening of the previous trend and adds an extra layer of confirmation.
🟣 Bullish Doubling Theory
In the bullish scenario, Doubling 1 begins with a bullish SSMT divergence, where one asset forms a lower low while the other maintains its structure. This divergence signals weakening bearish momentum and possible smart money accumulation. In Doubling 2, the market returns to the previous low and sweeps the liquidity zone—breaking below it on one asset, while the second fails to confirm, forming a bullish SMT divergence.
f this move is followed by a bullish PSP and a clear market structure break (MSB), a long entry is triggered. The stop-loss is placed just below the swept liquidity zone, while the target is set in the premium zone, anticipating a move driven by institutional buyers.
🟣 Bearish Doubling Theory
The bearish scenario follows the same structure in reverse. In Doubling 1, a bearish SSMT divergence occurs when one asset prints a higher high while the other fails to do so. This suggests distribution and weakening buying pressure. Then, in Doubling 2, the market returns to the previous high and executes a liquidity sweep, targeting trapped buyers.
A bearish SMT divergence appears, confirming the move, followed by a bearish PSP on the lower timeframe. A short position is initiated after a confirmed MSB, with the stop-loss placed
🔵 Settings
⚙️ Logical Settings
Quarterly Cycles Type : Select the time segmentation method for SMT analysis.
Available modes include : Yearly, Monthly, Weekly, Daily, 90 Minute, and Micro.
These define how the indicator divides market time into Q1–Q4 cycles.
Symbol : Choose the secondary asset to compare with the main chart asset (e.g., XAUUSD, US100, GBPUSD).
Pivot Period : Sets the sensitivity of the pivot detection algorithm. A smaller value increases responsiveness to price swings.
Pivot Sync Threshold : The maximum allowed difference (in bars) between pivots of the two assets for them to be compared.
Validity Pivot Length : Defines the time window (in bars) during which a divergence remains valid before it's considered outdated.
🎨 Display Settings
Show Cycle :Toggles the visual display of the current Quarter (Q1 to Q4) based on the selected time segmentation
Show Cycle Label : Shows the name (e.g., "Q2") of each detected Quarter on the chart.
Show Labels : Displays dynamic labels (e.g., “Q2”, “Bullish SMT”, “Sweep”) at relevant points.
Show Lines : Draws connection lines between key pivot or divergence points.
Color Settings : Allows customization of colors for bullish and bearish elements (lines, labels, and shapes)
🔔 Alert Settings
Alert Name : Custom name for the alert messages (used in TradingView’s alert system).
Message Frequenc y:
All : Every signal triggers an alert.
Once Per Bar : Alerts once per bar regardless of how many signals occur.
Per Bar Close : Only triggers when the bar closes and the signal still exists.
Time Zone Display : Choose the time zone in which alert timestamps are displayed (e.g., UTC).
Bullish SMT Divergence Alert : Enable/disable alerts specifically for bullish signals.
Bearish SMT Divergence Alert : Enable/disable alerts specifically for bearish signals
🔵 Conclusion
Doubling Theory is a powerful and structured framework within the realm of Smart Money Concepts and ICT methodology, enabling traders to detect high-probability reversal points with precision. By integrating SSMT, SMT, Liquidity Sweeps, and the Quarterly Theory into a unified system, this approach shifts the focus from reactive trading to anticipatory analysis—anchored in time, structure, and liquidity.
What makes Doubling Theory stand out is its logical synergy of time cycles, behavioral divergence, liquidity targeting, and institutional confirmation. In both bullish and bearish scenarios, it provides clearly defined entry and exit strategies, allowing traders to engage the market with confidence, controlled risk, and deeper insight into the mechanics of price manipulation and smart money footprints.
Candle Rating (1–5)This “Candle Rating (1–5)” indicator measures where each bar’s close sits within its own high-low range and assigns a simple strength score:
Range Calculation
It computes the candle’s total range (high − low) and finds the close’s position as a percentage of that range (0 = close at low, 1 = close at high).
Five-Point Rating
1 (Strong Buy): Close in the top 20% of the range
2 (Moderate Buy): 60–80%
3 (Neutral): 40–60%
4 (Moderate Sell): 20–40%
5 (Strong Sell): Bottom 20%
Visual Feedback
It plots the numeric rating above each bar (colored green → red), giving you an at-a-glance read of candle momentum and potential reversal strength across any timeframe.
Parsifal.Swing.TrendScoreThe Parsifal.Swing.TrendScore indicator is a module within the Parsifal Swing Suite, which includes a set of swing indicators such as:
• Parsifal Swing TrendScore
• Parsifal Swing Composite
• Parsifal Swing RSI
• Parsifal Swing Flow
Each module serves as an indicator facilitating judgment of the current swing state in the underlying market.
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Background
Market movements typically follow a time-varying trend channel within which prices oscillate. These oscillations—or swings—within the trend are inherently tradable.
They can be approached:
• One-sidedly, aligning with the trend (generally safer), or
• Two-sidedly, aiming to profit from mean reversions as well.
Note: Mean reversions in strong trends often manifest as sideways consolidations, making one-sided trades more stable.
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The Parsifal Swing Suite
The modules aim to provide additional insights into the swing state within a trend and offer various trigger points to assist with entry decisions.
All modules in the suite act as weak oscillators, meaning they fluctuate within a range but are not bounded like true oscillators (e.g., RSI, which is constrained between 0% and 100%).
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The Parsifal.Swing.TrendScore – Specifics
The Parsifal.Swing.TrendScore module combines short-term trend data with information about the current swing state, derived from raw price data and classical technical indicators. It provides an indication of how well the short-term trend aligns with the prevailing swing, based on recent market behavior.
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How Swing.TrendScore Works
The Swing.TrendScore calculates a swing score by collecting data within a bin (i.e., a single candle or time bucket) that signals an upside or downside swing. These signals are then aggregated together with insights from classical swing indicators.
Additionally, it calculates a short-term trend score using core technical signals, including:
• The Z-score of the price's distance from various EMAs
• The slope of EMAs
• Other trend-strength signals from additional technical indicators
These two components—the swing score and the trend score—are then combined to form the Swing.TrendScore indicator, which evaluates the short-term trend in context with swing behavior.
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How to Interpret Swing.TrendScore
The trend component enhances Swing.TrendScore’s ability to provide stronger signals when the short-term trend and swing state align.
It can also override the swing score; for example, even if a mean reversion appears to be forming, a dominant short-term trend may still control the market behavior.
This makes Swing.TrendScore particularly valuable for:
• Short-term trend-following strategies
• Medium-term swing trading
Unlike typical swing indicators, Swing.TrendScore is designed to respond more to medium-term swings rather than short-lived fluctuations.
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Behavior and Chart Representation
The Swing.TrendScore indicator fluctuates within a range, as most of its components are range-bound (though Z-score components may technically extend beyond).
• Historically high or low values may suggest overbought or oversold conditions
• The chart displays:
o A fast curve (orange)
o A slow curve (white)
o A shaded background representing the market state
• Extreme values followed by curve reversals may signal a developing mean reversion
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TrendScore Background Value
The Background Value reflects the combined state of the short-term trend and swing:
• > 0 (shaded green) → Bullish mode: swing and short-term trend both upward
• < 0 (shaded red) → Bearish mode: swing and short-term trend both downward
• The absolute value represents the confidence level in the market mode
Notably, the Background Value can remain positive during short downswings if the short-term trend remains bullish—and vice versa.
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How to Use the Parsifal.Swing.TrendScore
Several change points can act as entry triggers or aids:
• Fast Trigger: change in slope of the fast signal curve
• Trigger: fast line crosses slow line or the slope of the slow signal changes
• Slow Trigger: change in sign of the Background Value
Examples of these trigger points are illustrated in the accompanying chart.
Additionally, market highs and lows aligning with the swing indicator values may serve as pivot points in the evolving price process.
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As always, this indicator should be used in conjunction with other tools and market context in live trading.
While it provides valuable insight and potential entry points, it does not predict future price action.
Instead, it reflects recent tendencies and should be used judiciously.
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Extensions
The aggregation of information—whether derived from bins or technical indicators—is currently performed via simple averaging. However, this can be modified using alternative weighting schemes, based on:
• Historical performance
• Relevance of the data
• Specific market conditions
Smoothing periods used in calculations are also modifiable. In general, the EMAs applied for smoothing can be extended to reflect expectations based on relevance-weighted probability measures.
Since EMAs inherently give more weight to recent data, this allows for adaptive smoothing.
Additionally, EMAs may be further extended to incorporate negative weights, akin to wavelet transform techniques.
Trading Sessions
Trading Sessions
Highlights the Asia, London, and New York trading sessions with dynamic High-Low boxes.
General
Timezone : select your reference zone (e.g. Exchange, UTC, Europe/Rome, America/New_York).
Extend Session High/Low : extend the High/Low lines to the last candle.
Extend Lines (bars) : number of bars to extend lines beyond the last candle (0–100, default 15).
Show High/Low Labels : display labels for the High/Low levels.
Show Mitigated Levels : also show mitigated (broken) levels.
Show Only Recent Levels : filter levels from the last N days.
Number of Recent Days : sets how many days are considered “recent” (1–30).
Show Debug Info : enable a panel with current time, session status, and active filters.
Sessions
Asia , London , New York : enable or disable each session.
Session Time : set the start/end times with the time picker.
Box Color : choose a semi-transparent highlight color for each session.
Line Style & Width : customize style (Solid, Dotted, Dashed) and width of current and past High/Low lines.
Text Size : select the label text size (Tiny, Small, Normal, Large).
Show Only Recent Levels – filters High/Low lines to show only those from the last Number of Recent Days .
Number of Recent Days – sets how many days are considered “recent” for the filter.
Show Mitigated Levels – enables display of broken levels; otherwise only active levels remain visible.
Show High/Low Labels – toggles text labels at the ends of lines on or off.
Show Debug Info – displays a floating panel showing:
Current time in the selected timezone
On/Off status of Asia, London, NY sessions
Active filters (recent days, mitigated levels)
Line style settings for each session
Key Benefits
Visualize session-specific volatility and potential breakouts.
No historical limit: scroll back through any past sessions.
Filter and extend High/Low levels for precise price context.
Fully customize to fit any chart layout.
Ideal For
Intraday traders who need clear session boundaries and price level context.
10 AM NY Box - By KaVeH📦 10 AM New York Box till 4 PM — \
--By KaVeH--
This indicator automatically draws a price range box that captures the high and low between 10:00 AM and 11:00 AM New York Time (Eastern Time) on "5-minute charts".
### 🔍 What It Does
The "10 AM NY Box" is a simple but powerful visualization tool for day traders and ICT-based strategies. It highlights a key hourly session right after the "New York open" — often a time of increased volatility, liquidity grabs, and the formation of critical intraday highs or lows.
### 📊 Features
Time Window: Customizable start and end hours (defaults: 10 AM to 11 AM NY time).
Box Color: Customizable with transparency.
Chart Restriction: The indicator "only works on 5-minute charts" to ensure accuracy and prevent misalignment.
### ⚙️ Inputs
- 'Start Hour (NY Time)' – Default: 10
- 'End Hour (NY Time)' – Default: 11
- 'Box Color' – Default: Red with transparency
### 📈 How It Works
- During the specified time window, the script tracks the "highest high and lowest low".
- Once the time window ends, it draws a "box" from the starting to the ending time, extending a little beyond to keep it visible.
- Each day's box is created independently, and only once per day.
### 🧠 Use Cases
- Spotting potential liquidity zones
- Identifying breakout or fakeout traps
- Aligning with ICT concepts like "FVG", "BAG", or "Judas Swing"
### ⚠️ Notes & Limitations
- "Only functions on 5-minute timeframes" — this is intentional to maintain session accuracy.
- Does not repaint.
- Time is aligned to **New York (Eastern Time)** regardless of your chart’s timezone.
- One box per day.
Modern Economic Eras DashboardOverview
This script provides a historical macroeconomic visualization of U.S. markets, highlighting long-term structural "eras" such as the Bretton Woods period, the inflationary 1970s, and the post-2020 "Age of Disorder." It overlays key economic indicators sourced from FRED (Federal Reserve Economic Data) and displays notable market crashes, all in a clean and rescaled format for easy comparison.
Data Sources & Indicators
All data is loaded monthly from official FRED series and rescaled to improve readability:
🔵 Real GDP (FRED:GDP): Total output of the U.S. economy.
🔴 Inflation Index (FRED:CPIAUCSL): Consumer price index as a proxy for inflation.
⚪ Debt to GDP (FRED:GFDGDPA188S): Federal debt as % of GDP.
🟣 Labor Force Participation (FRED:CIVPART): % of population in the labor force.
🟠 Oil Prices (FRED:DCOILWTICO): Monthly WTI crude oil prices.
🟡 10Y Real Yield (FRED:DFII10): Inflation-adjusted yield on 10-year Treasuries.
🔵 Symbol Price: Optionally overlays the charted asset’s price, rescaled.
Historical Crashes
The dashboard highlights 10 major U.S. market crashes, including 1929, 2000, and 2008, with labeled time spans for quick context.
Era Classification
Six macroeconomic eras based on Deutsche Bank’s Long-Term Asset Return Study (2020) are shaded with background color. Each era reflects dominant economic regimes—globalization, wars, monetary systems, inflationary cycles, and current geopolitical disorder.
Best Use Cases
✅ Long-term macro investors studying structural market behavior
✅ Educators and analysts explaining economic transitions
✅ Portfolio managers aligning strategy with macroeconomic phases
✅ Traders using history for cycle timing and risk assessment
Technical Notes
Designed for monthly timeframe, though it works on weekly.
Uses close price and standard request.security calls for consistency.
Max labels/lines configured for broader history (from 1860s to present).
All plotted series are rescaled manually for better visibility.
Originality
This indicator is original and not derived from built-in or boilerplate code. It combines multiple economic dimensions and market history into one interactive chart, helping users frame today's markets in a broader structural context.
MissedPrice Volume Method[KiomarsRakei]█ Core Concept:
This script detects price zones that are highly likely to be revisited — areas where price moved too quickly to fully fill market activity. Using sharp volume shifts and volatility filters, the script identifies these “missed” levels and generates signals pointing toward them.
Signals are generated before price reaches the zone, allowing you to analyze price behavior both before and after the zone is touched. These zones often act like magnets for price, making them ideal for short-term.
Examples of signals and high hit rate of Missed zones
█ How It Works:
The script monitors 3-candle volume and price behavior to detect moments where volume accelerates abnormally compared to recent averages. When a potential missed zone is found and price hasn’t revisited it yet, a signal is created in advance, pointing to that zone as a likely future target.
█ Features:
Zone Visualization: Dynamic boxes show price targets based on missed volume areas.
Pre-Zone Signals: Alerts fire before price returns, offering early trade setups.
Stat Tracking System: Automatically logs signals, win rate, and average profit.
Live Performance Table: On-chart stats including hit/miss breakdown and late-return analysis.
Works on All Markets: Compatible with any chart that provides volume — crypto, forex, indices, or stocks.
A signal is considered successful when price touches the zone. However, not all zones are guaranteed to be revisited.
█ Key Inputs & Stats Table:
Volume Filters: Control signal sensitivity using min/max relative volume shift.
Zone & Line Settings: Adjust how long the zone stays visible and whether entry lines are drawn.
Custom Colors: Choose colors for buy/sell zones, lines, and visuals.
📊 Table Metrics:
Total Signals: Count of all generated signals.
Win Rate: % of signals where price returned to the zone (hit = touched the zone, regardless of timing).
Bad Signals: Signals that took too long to hit or were never hit.
Bad but Hit: Signals marked bad but eventually touched the zone.
Bad signals are marked in red. These indicate zones that price failed to reach within the expected time window, showing where the script identified a target that remained unfulfilled.
LANZ Strategy 3.0🔷 LANZ Strategy 3.0 — Asian Range Fibonacci Strategy with Execution Window Logic
LANZ Strategy 3.0 is a rule-based trading system that utilizes the Asian session range to project Fibonacci levels and manage entries during a defined execution window. Designed for Forex and index traders, this strategy focuses on structured price behavior around key levels before the New York session.
🧠 Core Components:
Asian Session Range Mapping: Automatically detects the high, low, and midpoint during the Asian session.
Fibonacci Level Projection: Projects configurable Fibonacci retracement and extension levels based on the Asian range.
Execution Window Logic: Uses the 01:15 NY candle as a reference to validate potential reversals or continuation setups.
Conditional Entry System: Includes logic for limit order entries (buy or sell) at specific Fib levels, with reversal logic if price breaks structure before execution.
Risk Management: Entry orders are paired with dynamic SL and TP based on Fibonacci-based distances, maintaining a risk-reward ratio consistent with intraday strategies.
📊 Visual Features:
Asian session high/low/mid lines.
Fibonacci levels: Original (based on raw range) and Optimized (user-adjustable).
Session background coloring for Asia, Execution Window, and NY session.
Labels and lines for entry, SL, and TP targets.
Dynamic deletion of untriggered orders after execution window expires.
⚙️ How It Works:
The script calculates the Asian session range.
Projects Fibonacci levels from the range.
Waits for the 01:15 NY candle to close to validate a signal.
If valid, a limit entry order (BUY or SELL) is plotted at the selected level.
If price structure changes (e.g., breaks the high/low), reversal logic may activate.
If no trade is triggered, orders are cleared before the NY session.
🔔 Alerts:
Alerts trigger when a valid setup appears after 01:15 NY candle.
Optional alerts for order activation, SL/TP hit, or trade cancellation.
📝 Notes:
Intended for semi-automated or discretionary trading.
Best used on highly liquid markets like Forex majors or indices.
Script parameters include session times, Fib ratios, SL/TP settings, and reversal logic toggle.
Credits:
Developed by LANZ, this script merges traditional session-based analysis with Fibonacci tools and structured execution timing, offering a unique framework for morning volatility plays.
ZenAlgo - AvengerThe ZenAlgo - Avenger indicator provides a multi-layered view of market behavior by combining volume delta analytics, trend-following EMAs, average price comparison, and price-volume profiling into a unified overlay. It is designed to visually assist traders in identifying areas of interest, momentum shifts, and potential reversals using cumulative data from both spot and perpetual markets.
Volume Delta Calculation
This indicator computes delta as the difference between estimated buy and sell volumes using volume data from multiple centralized exchanges. It distinguishes between spot and perpetual volumes, combining them into total volume.
To estimate buying and selling volume from raw volume data, candle structure is broken down into body and wicks. The body is interpreted as the core directional movement (buy/sell), while the wicks are treated as uncertain or counteraction. This segmentation helps infer the likely share of buying and selling within each bar.
The delta is calculated per bar and then aggregated over a lookback period (default 14 bars) to generate a cumulative delta. This approach provides a smoothed value of volume pressure trends over time.
A moving average is applied to the delta values (using selectable MA types like EMA or SMA) to define signal crossovers and suppress noise.
Delta Visualization
To contextualize delta within price action, the delta is scaled dynamically (by ATR or user-defined value) and plotted as a band around the closing price. Positive delta expands upward from price, negative delta downward. This provides a visual overlay that reflects net market pressure in context with price movement.
In cases of extreme delta (threshold set at 80% of recent maximum), the indicator marks spike bars using symbols to indicate significant directional pressure.
Identification of Noteworthy Conditions
The indicator highlights points on the chart where specific conditions are met based on the interaction between volume delta and its moving average. These conditions may align with moments of market pressure imbalance and directional movement, but they are not to be interpreted as trade signals in isolation.
Instead, these chart markers serve as visual flags for potential interest. They are intended to draw the user’s attention to scenarios where:
The delta crosses above or below its moving average, suggesting a potential shift in volume pressure.
The cumulative delta supports the direction of this crossover.
Optional filters can further restrict these markings to periods where:
The short-term trend (as inferred from EMA slope) supports the direction.
Volume is elevated relative to a recent average.
A user-defined cooldown period prevents multiple markings within short succession to avoid clutter.
It is essential to underscore that these markers do not constitute buy or sell advice . Their role is diagnostic , helping the trader to identify potential moments of interest which should be analyzed in conjunction with broader context, such as trend structure, price action, support/resistance levels, or external market data.
EMA Structure
Six EMAs with fixed lengths (13 to 56) are plotted and colored dynamically based on the most recent crossover between the fastest and slowest (EMA1 and EMA6). These EMAs help visualize short- to mid-term trends. The crossover itself is marked with symbols, with vertical offset based on ATR to maintain chart readability.
Average Line (AVG)
The indicator also calculates an average price based on a fixed window (100 bars). This is not a standard moving average but rather a raw average of recent prices stored in a circular buffer. The average is plotted, and its relative distance to the current price is labeled as a percentage. This feature serves as a simplified representation of fair value or mean reversion anchor.
EMA6 vs AVG Cross
Another layer of point of interest detection involves EMA6 crossing the AVG line. This crossover is only considered valid if EMA6 shows slope consistency in the crossing direction. These events are marked using symbols and offset vertically to avoid overlapping price action.
Divergence Detection
The script detects both regular and hidden divergences between price and delta:
Regular divergences are defined when price makes a higher high or lower low, while delta fails to confirm (makes a lower high or higher low).
Hidden divergences occur when price retraces (lower high or higher low), but delta moves against this retracement, indicating underlying strength or weakness.
Divergence points are labeled with "R" (regular) or "H" (hidden) and appear at local pivot highs or lows. The number of visible divergence labels can be limited for chart clarity.
POC and nPOC Calculations
The script includes a simplified volume profile implementation, calculating:
POC (Point of Control): the price level with the highest volume for the given period.
nPOC (non-tested POC): historical POCs that have not yet been revisited by price.
Price levels are bucketed into rows (user-defined), and volume per bucket is tracked to identify the POC. Upon a new period (e.g., day, week), a horizontal POC line is drawn. Once tested by price, the line’s appearance changes (color fades, label shrinks), helping users distinguish between untouched and touched levels.
Limits are enforced on the number of retained POCs and their maximum distance from current bars to optimize performance and chart readability.
Exchange Aggregation
Volume data is aggregated across major exchanges. This ensures that the delta calculation captures a broader market picture beyond a single venue, reducing exchange-specific noise.
How to Interpret Values
Delta Band: Wide bands indicate strong directional imbalance. Narrow bands suggest indecision or low volume.
EMA Crossover Symbols: Appear on directional shifts in moving averages. Multiple EMAs reinforcing the same slope typically indicate stronger trend.
AVG Line: Represents average price over recent history. Large deviations can indicate overextension or potential mean reversion.
Divergences: Regular ones may point to weakening momentum; hidden ones can suggest continuation despite corrective price action.
POC / nPOC: Key volume-based support/resistance levels. Untested nPOCs can act as magnets for price retests.
How to Best Use This Indicator
Use in conjunction with trend context (e.g., higher timeframe EMAs) to avoid counter-trend indications.
Treat delta spikes as caution zones—especially if they occur at known support/resistance.
Watch for divergences as early warning signs before price reverses.
Use POC/nPOC as target levels, especially if aligned with delta signals.
Apply volume and trend filters to reduce noise on shorter timeframes.
Added Value
Multi-exchange volume aggregation makes the delta calculation more robust.
Real-time cumulative delta overlaid directly on the price chart provides immediate context.
Points of interest on chart are conservative and filterable, intended to reduce false positives.
The combination of delta, trend-following EMAs, fair value line, and volume profile data is rarely found in one overlay script.
POC/nPOC visualization based on real traded volume helps identify high-interest zones for future price interaction.
Why Is It Worth Paying For
While free alternatives may provide partial insights (e.g., basic delta or single EMA crossovers), this indicator integrates multiple domains—delta, divergence, average price, trend overlays, and profile levels—into a coherent, optimized chart tool. The value lies not just in having these tools, but in how they are synchronized and visualized.
Furthermore, sourcing and synchronizing volume data from multiple exchanges for delta estimation is not straightforward in Pine Script and adds to the indicator's complexity and utility.
Disclaimers and Limitations
Delta estimation is based on candle structure and assumes wick/body distribution reflects buyer/seller activity, which may not always be precise.
Multi-exchange volume data relies on availability via TradingView’s request.security() function; if exchange data is missing or delayed, results may be incomplete.
Divergences do not guarantee reversals—should be used as part of a broader analysis framework.
On illiquid instruments or exotic pairs, the value of delta and volume-based analytics may be reduced due to unreliable volume.
6 Moving Averages Difference TableIndicator Summary: 6 Moving Averages Difference Table (6MADIFF)
This TradingView indicator calculates and plots up to six distinct moving averages (MAs) directly on the price chart. Users have extensive control over each MA, allowing selection of:
Type: SMA, EMA, WMA, VWMA, HMA, RMA
Length: Any positive integer
Color: User-defined
Visibility: Can be toggled on/off
A core feature is the on-chart data table, designed to provide a quick overview of the relationships between the MAs and the price. This table displays:
$-MA Column: The absolute difference between the user-selected Input Source (e.g., Close, Open, HLC3) and the current value of each MA.
MA$ Column: The actual calculated price value of each MA for the current bar.
MA vs. MA Matrix: A grid showing the absolute difference between every possible pair of the calculated MAs (e.g., MA1 vs. MA2, MA1 vs. MA3, MA2 vs. MA5, etc.).
Customization Options:
Input Source: Select the price source (Open, High, Low, Close, HL2, HLC3, OHLC4) used for all MA calculations and the price difference column.
Table Settings: Control the table's visibility, position on the chart, text size, decimal precision for displayed values, and the text used for the column headers ("$-MA" and "MA$").
Purpose:
This indicator is useful for traders who utilize multiple moving averages in their analysis. The table provides an immediate, quantitative snapshot of:
How far the current price is from each MA.
The exact value of each MA.
The spread or convergence between different MAs.
This helps in quickly assessing trend strength, potential support/resistance levels based on MA clusters, and the relative positioning of short-term versus long-term averages.
