Pivot S/RThis support/resistance indicator draws a horizontal line at historical Daily swing points.
I've found this to be a very accurate indicator for determining current levels of support and resistance. Double lines and clusters of lines provide particularly strong levels.
Most of the settings are changeable.
חפש סקריפטים עבור "horizontal line"
Directional Movement Index 4 colors (DMI 4c)It is a normal Directional Movement Index, but instead of using lines for +DI and -DI it uses histogram and 4 colors. It also contains an horizontal line (default value @20) to indicate when a trend is confirmed or not.
Relative Price Difference [LAVA]EDIT: Look below for updates to the script.
EDIT: After several updates to this script, I think it's safe to say it will work with all timelines. Using hand drawn trendlines, it can predict tops and bottoms with pretty good accuracy.
Shows a change in the relative price difference via percentage on a 0 horizontal. Added a bollinger band to help identify weak areas (orange). If orange starts showing, the current price direction is strong but can reverse harshly. If you are in a weak position, exit here. Otherwise, don't enter a trade after/during orange sessions until a full cycle (up/dn > 1% without orange) has completed. The main line indicator fluctuates according to the price difference. 1% horizontal lines are added to help identify profit taking spots or OTE zones. Ensure the 1% line is crossed completely before you decide to enter/exit. Cross points are identified with crosses if you missed your window, this is the last spot to exit, enter. This indicator doesn't work that well with small time intervals. As always, use more than one indicator to ensure your decision is right. (The colors are ugly so change them if you wish! :)
First Candle High-Low (ORB Style)This indicator will
✅ Detect the first candle of each day (on any intraday timeframe),
✅ Draw two horizontal lines — one at the high and one at the low of that first candle, and
✅ Extend those lines across all candles of that same day.
Point of Control (POC)**Point of Control (POC) Indicator**
This indicator identifies the price level where the most trading volume occurred over a specified lookback period (default: 365 days). The POC represents a significant support/resistance level where the market found the most acceptance.
**Key Features:**
- **POC Line**: Bright green horizontal line showing the highest volume price level
- **Volume Profile Analysis**: Divides price range into rows and calculates volume distribution
- **Value Area (Optional)**: Shows VAH and VAL levels containing 70% of total volume
- **Customizable**: Adjust lookback period, price resolution, colors, and line width
**How to Use:**
- POC acts as a magnet - price often returns to test these high-volume levels
- Strong support/resistance zone where significant trading activity occurred
- Useful for identifying key price levels for entries, exits, and stops
- Higher lookback periods (365 days) show longer-term significant levels
**Settings:**
- Lookback Period: Number of bars to analyze (default: 365)
- Price Rows: Calculation resolution - higher = more precise (default: 24)
- Toggle Value Area High/Low for additional context
---
London Ghost CandleCandle representation of the London session. 2am-5am NYT
By default the wicks is turned off because I only care about whether the session was green or red. You can add the wick, remove the open/close horizontal lines or even darken the colors in the settings. You can also remove the pane label box.
Hope it helps.
Swing LevelsThe Swing Levels indicator automatically detects and plots recent swing highs and lows on the chart, turning them into dynamic support and resistance levels.
Each new swing point creates a horizontal line that extends forward in time until price “fills” (touches or breaks) that level. Once a level is filled, it can either disappear or remain visible — depending on your settings.
You can enable alerts to be notified whenever price fills a swing high (breaks resistance) or a swing low (breaks support).
A lookback filter allows limiting how far back in history swing levels are drawn, helping keep the chart clean and efficient.
Main benefits:
• Automatically tracks key market structure turning points
• Helps visualize support and resistance zones in real time
• Optional alerts for breakout confirmations
• Fully customizable colors, line styles, and management behavior
• Works on any timeframe or market
In short:
Swing Levels gives you a clear and automated view of where price has recently reversed — powerful zones where liquidity and reactions often occur again.
Сreated with vibecoding using ChatGPT and Claude.
Standardization (Z-score)Standardization, often referred to as Z-score normalization, is a data preprocessing technique that rescales data to have a mean of 0 and a standard deviation of 1. The resulting values, known as Z-scores, indicate how many standard deviations an individual data point is from the mean of the dataset (or a rolling sample of it).
This indicator calculates and plots the Z-score for a given input series over a specified lookback period. It is a fundamental tool for statistical analysis, outlier detection, and preparing data for certain machine learning algorithms.
## Core Concepts
* **Standardization:** The process of transforming data to fit a standard normal distribution (or more generally, to have a mean of 0 and standard deviation of 1).
* **Z-score (Standard Score):** A dimensionless quantity that represents the number of standard deviations by which a data point deviates from the mean of its sample.
The formula for a Z-score is:
`Z = (x - μ) / σ`
Where:
* `x` is the individual data point (e.g., current value of the source series).
* `μ` (mu) is the mean of the sample (calculated over the lookback period).
* `σ` (sigma) is the standard deviation of the sample (calculated over the lookback period).
* **Mean (μ):** The average value of the data points in the sample.
* **Standard Deviation (σ):** A measure of the amount of variation or dispersion of a set of values. A low standard deviation indicates that the values tend to be close to the mean, while a high standard deviation indicates that the values are spread out over a wider range.
## Common Settings and Parameters
| Parameter | Type | Default | Function | When to Adjust |
| :-------------- | :----------- | :------ | :------------------------------------------------------------------------------------------------------ | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Source | series float | close | The input data series (e.g., price, volume, indicator values). | Choose the series you want to standardize. |
| Lookback Period | int | 20 | The number of bars (sample size) used for calculating the mean (μ) and standard deviation (σ). Min 2. | A larger period provides more stable estimates of μ and σ but will be less responsive to recent changes. A shorter period is more reactive. `minval` is 2 because `ta.stdev` requires it. |
**Pro Tip:** Z-scores are excellent for identifying anomalies or extreme values. For instance, applying Standardization to trading volume can help quickly spot days with unusually high or low activity relative to the recent norm (e.g., Z-score > 2 or < -2).
## Calculation and Mathematical Foundation
The Z-score is calculated for each bar as follows, using a rolling window defined by the `Lookback Period`:
1. **Calculate Mean (μ):** The simple moving average (`ta.sma`) of the `Source` data over the specified `Lookback Period` is calculated. This serves as the sample mean `μ`.
`μ = ta.sma(Source, Lookback Period)`
2. **Calculate Standard Deviation (σ):** The standard deviation (`ta.stdev`) of the `Source` data over the same `Lookback Period` is calculated. This serves as the sample standard deviation `σ`.
`σ = ta.stdev(Source, Lookback Period)`
3. **Calculate Z-score:**
* If `σ > 0`: The Z-score is calculated using the formula:
`Z = (Current Source Value - μ) / σ`
* If `σ = 0`: This implies all values in the lookback window are identical (and equal to the mean). In this case, the Z-score is defined as 0, as the current source value is also equal to the mean.
* If `σ` is `na` (e.g., insufficient data in the lookback period), the Z-score is `na`.
> 🔍 **Technical Note:**
> * The `Lookback Period` must be at least 2 for `ta.stdev` to compute a valid standard deviation.
> * The Z-score calculation uses the sample mean and sample standard deviation from the rolling lookback window.
## Interpreting the Z-score
* **Magnitude and Sign:**
* A Z-score of **0** means the data point is identical to the sample mean.
* A **positive Z-score** indicates the data point is above the sample mean. For example, Z = 1 means the point is 1 standard deviation above the mean.
* A **negative Z-score** indicates the data point is below the sample mean. For example, Z = -1 means the point is 1 standard deviation below the mean.
* **Typical Range:** For data that is approximately normally distributed (bell-shaped curve):
* About 68% of Z-scores fall between -1 and +1.
* About 95% of Z-scores fall between -2 and +2.
* About 99.7% of Z-scores fall between -3 and +3.
* **Outlier Detection:** Z-scores significantly outside the -2 to +2 range, and especially outside -3 to +3, are often considered outliers or extreme values relative to the recent historical data in the lookback window.
* **Volatility Indication:** When applied to price, large absolute Z-scores can indicate moments of high volatility or significant deviation from the recent price trend.
The indicator plots horizontal lines at ±1, ±2, and ±3 standard deviations to help visualize these common thresholds.
## Common Applications
1. **Outlier Detection:** Identifying data points that are unusual or extreme compared to the rest of the sample. This is a primary use in financial markets for spotting abnormal price moves, volume spikes, etc.
2. **Comparative Analysis:** Allows for comparison of scores from different distributions that might have different means and standard deviations. For example, comparing the Z-score of returns for two different assets.
3. **Feature Scaling in Machine Learning:** Standardizing features to have a mean of 0 and standard deviation of 1 is a common preprocessing step for many machine learning algorithms (e.g., SVMs, logistic regression, neural networks) to improve performance and convergence.
4. **Creating Normalized Oscillators:** The Z-score itself can be used as a bounded (though not strictly between -1 and +1) oscillator, indicating how far the current price has deviated from its moving average in terms of standard deviations.
5. **Statistical Process Control:** Used in quality control charts to monitor if a process is within expected statistical limits.
## Limitations and Considerations
* **Assumption of Normality for Probabilistic Interpretation:** While Z-scores can always be calculated, the probabilistic interpretations (e.g., "68% of data within ±1σ") strictly apply to normally distributed data. Financial data is often not perfectly normal (e.g., it can have fat tails).
* **Sensitivity of Mean and Standard Deviation to Outliers:** The sample mean (μ) and standard deviation (σ) used in the Z-score calculation can themselves be influenced by extreme outliers within the lookback period. This can sometimes mask or exaggerate the Z-score of other points.
* **Choice of Lookback Period:** The Z-score is highly dependent on the `Lookback Period`. A short period makes it very sensitive to recent fluctuations, while a long period makes it smoother and less responsive. The appropriate period depends on the analytical goal.
* **Stationarity:** For time series data, Z-scores are calculated based on a rolling window. This implicitly assumes some level of local stationarity (i.e., the mean and standard deviation are relatively stable within the window).
FU Candle Detector (Smart Money Concept) En Anglais🧠 Overall concept: “FU Candle” in Smart Money logic
In the context of Smart Money Concepts (SMC) or ICT (Inner Circle Trader), an FU Candle (also known as a “Fakeout Candle” or “Manipulation Candle”) is a candle that:
Creates an imbalance or a break (often above a swing high or below a swing low),
Attracts liquidity by trapping retail traders (liquidity grab),
Then abruptly reverses direction, revealing the hand of “Smart Money” (large institutions).
It therefore often marks:
The point of manipulation before an impulsive movement (reversal),
An area of interest for entering in the institutional direction (after the liquidity grab).
---
⚙️ How the “FU Candle Detector” script works
The script identifies these candlesticks by observing several typical criteria:
1. Detection of the manipulative candle (FU Candle)
Search for a candlestick that breaks a previous swing (significant high or low),
But closes in the opposite direction, often below/above the broken zone,
Thus indicating a fakeout.
Examples:
Bullish FU Candle: breaks a previous low, but closes bullish.
Bearish FU Candle: breaks a previous high, but closes bearish.
---
2. Visualization on the chart
The script generally displays:
🔴 Red markers for bearish FUs (Fake Breakout upwards),
🟢 Green markers for bullish FUs (Fake Breakout downwards),
🟦 Rectangles of areas of interest (often around the FU Candle Open),
📏 Horizontal lines on areas of imbalance (OB/FVG if integrated).
---
3. Possible additions depending on the version
Depending on the version you have received, the script can also:
Detect Fair Value Gaps (FVG) around FU Candles,
Mark Order Blocks (OB) associated with manipulation,
Add alerts when new FU Candles are detected,
Calculate the distance between the manipulation point and the price return,
Filter according to candle size, volume, or market structure (MSB/CHoCH).
---
🎯 Practical use
FU Candles are often used:
As confirmation of an imminent reversal,
To identify institutional entry zones (hidden Order Block),
To anticipate the direction of the next impulse after the liquidity hunt.
Typical entry example:
> Wait for the formation of an FU Candle + price return within the candle body = entry in the opposite direction to the false breakout.
📈 Recommended combinations
This detector is often combined with:
Structure Break Indicator (CHoCH / BOS)
Liquidity Pool Zones
Fair Value Gap Finder
Order Block Detector
This gives you a complete Smart Money Concept system, capable of mapping:
1. Where liquidity has been taken,
2. Where the price is rebalancing,
3. Where Smart Money is repositioning its orders.
First X Days Of A YearFirst X-Day Indicator
Overview
The "First X-Day Indicator" is a powerful tool to visualize and analyze market sentiment during the crucial first trading days of each new year. It provides immediate visual feedback on whether the year is starting with positive or negative momentum compared to the previous year's close, a concept often related to market theories like the "January Effect" or the "First Five Days Rule."
The indicator is designed to be clean, intuitive, and fully customizable to fit your charting style.
Key Features
Yearly Baseline: Automatically draws a horizontal line at the previous year's closing price. This line serves as a clear 0% reference for the current year's performance.
Dynamic Background Coloring: For a user-defined number of days at the start of the year, the chart background is colored daily. Green indicates the close is above the previous year's close, while red indicates it's below.
Final Performance Symbol: At the end of the analysis period (e.g., on the 5th day), a single summary symbol (like 👍 or 👎) appears. This symbol represents the final performance outcome of the initial trading period.
Settings & Customization
You have full control over all visual elements:
Analysis Period: Define exactly how many days at the start of the year you want to analyze (e.g., 3, 5, or 10 days).
Line Customization: Fully control the yearly baseline's appearance. You can change its color, width, and style (Solid, Dashed, or Dotted) or hide it completely.
Symbol Customization: Choose any character or emoji for the positive and negative performance symbols. You can also adjust their size (Small, Normal, Large) or hide them.
Background Control: Enable or disable the daily background coloring and select your preferred custom colors for positive and negative days.
Custom Drawdown LevelsInput fields for three custom percentages.
Calculation of drawdown levels from the all-time high.
Plotting horizontal lines at those levels.
Puell Multiple Variants [OperationHeadLessChicken]Overview
This script contains three different, but related indicators to visualise Bitcoin miner revenue.
The classical Puell Multiple : historically, it has been good at signaling Bitcoin cycle tops and bottoms, but due to the diminishing rewards miners get after each halving, it is not clear how you determine overvalued and undervalued territories on it. Here is how the other two modified versions come into play:
Halving-Corrected Puell Multiple : The idea is to multiply the miner revenue after each halving with a correction factor, so overvalued levels are made comparable by a horizontal line across cycles. After experimentation, this correction factor turned out to be around 1.63. This brings cycle tops close to each other, but we lose the ability to see undervalued territories as a horizontal region. The third variant aims to fix this:
Miner Revenue Relative Strength Index (Miner Revenue RSI) : It uses RSI to map miner revenue into the 0-100 range, making it easy to visualise over/undervalued territories. With correct parameter settings, it eliminates the diminishing nature of the original Puell Multiple, and shows both over- and undervalued revenues correctly.
Example usage
The goal is to determine cycle tops and bottoms. I recommend using it on high timeframes, like monthly or weekly . Lower than that, you will see a lot of noise, but it could still be used. Here I use monthly as the example.
The classical Puell Multiple is included for reference. It is calculated as Miner Revenue divided by the 365-day Moving Average of the Miner Revenue . As you can see in the picture below, it has been good at signaling tops at 1,3,5,7.
The problems:
- I have to switch the Puell Multiple to a logarithmic scale
- Still, I cannot use a horizontal oversold territory
- 5 didn't touch the trendline, despite being a cycle top
- 9 touched the trendline despite not being a cycle top
Halving-Corrected Puell Multiple (yellow): Multiplies the Puell Multiple by 1.63 (a number determined via experimentation) after each halving. In the picture below, you can see how the Classical (white) and Corrected (yellow) Puell Multiples compare:
Advantages:
- Now you can set a constant overvalued level (12.49 in my case)
- 1,3,7 are signaled correctly as cycle tops
- 9 is correctly not signaled as a cycle top
Caveats:
- Now you don't have bottom signals anymore
- 5 is still not signaled as cycle top
Let's see if we can further improve this:
Miner Revenue RSI (blue):
On the monthly, you can see that an RSI period of 6, an overvalued threshold of 90, and an undervalued threshold of 35 have given historically pretty good signals.
Advantages:
- Uses two simple and clear horizontal levels for undervalued and overvalued levels
- Signaling 1,3,5,7 correctly as cycle tops
- Correctly does not signal 9 as a cycle top
- Signaling 4,6,8 correctly as cycle bottoms
Caveats:
- Misses two as a cycle bottom, although it was a long time ago when the Bitcoin market was much less mature
- In the past, gave some early overvalued signals
Usage
Using the example above, you can apply these indicators to any timeframe you like and tweak their parameters to obtain signals for overvalued/undervalued BTC prices
You can show or hide any of the three indicators individually
Set overvalued/undervalued thresholds for each => the background will highlight in green (undervalued) or red (overvalued)
Set special parameters for the given indicators: correction factor for the Corrected Puell and RSI period for Revenue RSI
Show or hide halving events on the indicator panel
All parameters and colours are adjustable
Trading Sessions with 15 minute ORBA working copy of the original Tradingview trading sessions indicator with the addition of horizontal lines marking the 15 minute opening range for your ORB strategy. The lines reset with each session start.
Master Trend Strategy - by jake_thebossMaster Trend Strategy
This strategy combines multiple technical indicators to identify high-probability trend entries across all asset classes.
Core Signal Logic:
Entry triggered when EMA 4 crosses above/below EMA 5
Confirmation required from RSI (>50 for long, <50 for short)
Price must be above/below key moving averages: EMA 21, SMA 50, EMA 55, EMA 89, and EMA 750
Additional confirmation from Stochastic (>52 bullish, <48 bearish) or EMA 89 breakout or VWAP cross
Key Features:
VWAP filter: Only takes bullish signals above VWAP and bearish signals below VWAP
Optional pyramiding: Allows multiple entries in the same direction (up to 200 orders)
Individual stop loss and take profit management for each pyramid level
Time filter: Customizable trading hours with timezone offset
Risk management: Adjustable stop loss (default 0.3%) and take profit (default 0.6%)
Visualization:
Entry, stop loss, and take profit levels drawn as horizontal lines
Customizable signal markers (triangles) for bull/bear entries
Optional EMA overlay display
The strategy is designed for trend-following on lower timeframes, with strict multi-indicator confirmation to filter out false signals.
HTF Control Shift + Prev Candle Break Sequence 🧭 HTF Control Shift + Previous Candle Break Sequence
Overview
The HTF Control Shift + Previous Candle Break Sequence indicator identifies high-probability shift candles that suggest a potential change in market control — from sellers to buyers or vice versa — and then tracks whether price confirms that shift by breaking the previous candle’s high or low.
This tool is designed to help traders detect institutional control shifts and confirm them with price structure breaks, providing a framework for spotting early trend reversals or strong continuation moves.
How It Works
Control Shift Candle Detection
A Bullish Control Shift occurs when a candle shows:
A long lower wick (≥ Wick % Threshold of total range).
A close near the high (within Body % Threshold of the top).
A Bearish Control Shift occurs when a candle shows:
A long upper wick (≥ Wick % Threshold of total range).
A close near the low (within Body % Threshold of the bottom).
These candles are highlighted in green (bullish) or red (bearish), and optionally labeled on the chart.
Previous Candle High/Low Tracking
The script automatically plots horizontal lines at the previous candle’s high (green) and low (red).
These act as key reference levels for breakout confirmation.
Breakout Confirmation Sequence
A Bullish Sequence triggers when a Bullish Control Shift candle is followed by a break above the previous candle’s high.
A Bearish Sequence triggers when a Bearish Control Shift candle is followed by a break below the previous candle’s low.
When either sequence completes, the indicator can send a TradingView alert confirming the directional breakout.
How to Use
Timeframe:
Optimized for higher timeframes (1H, 4H, Daily) to filter out intraday noise and identify structural market shifts.
Trend Reversal Identification:
Watch for Control Shift candles at major highs/lows, order blocks, or liquidity zones — a confirmed breakout often signals a trend reversal or new directional push.
Continuation Confirmation:
In trending markets, a Control Shift candle that breaks in the direction of trend can validate a strong continuation setup.
Alert Usage:
Set alerts for:
Bullish Control Shift Confirmed Breakout
Bearish Control Shift Confirmed Breakdown
Optional: raw Control Shift or Break alerts.
Customization
Wick % Threshold: Adjusts the required wick size to define a control shift.
Body % Threshold: Controls how close the close must be to the high/low for confirmation.
Label Toggle: Optionally display labels only on control shift candles.
Best Practices
Combine with higher-timeframe trend filters.
Avoid using it alone in tight consolidation zones.
Strongest signals occur when:
Control Shift appears at key structure levels.
The breakout bar closes firmly beyond the previous high/low.
Volume supports the breakout.
Summary
✅ Detects when market control flips (buyers ↔ sellers).
✅ Confirms shift with breakout above/below previous candle.
✅ Ideal for 1H–4H swing or position trading.
✅ Provides visual, structural, and alert-based confirmation.
Multi Timeframe Market Structure ContinuationOverview
This indicator identifies Break of Structure (BOS) and Change of Character (ChoCh) patterns using multi-timeframe (MTF) analysis to filter high-probability trade setups. By aligning lower timeframe signals with higher timeframe bias, it helps traders enter positions in the direction of the dominant trend while avoiding counter-trend traps.
Multi-Timeframe Analysis
The indicator analyzes market structure on two timeframes simultaneously:
Current Timeframe (CTF): Detects immediate BOS and ChoCh signals for entry timing
Higher Timeframe (HTF): Establishes the overall trend direction (default: 1H, customizable)
Signals only appear when the current timeframe structure aligns with the higher timeframe bias, ensuring you're trading with the momentum, not against it.
Break of Structure (BOS)
BOS signals indicate trend continuation - when price breaks a previous high in an uptrend or a previous low in a downtrend. These are reliable entries that confirm the trend is still active and strong.
Change of Character (ChoCh)
ChoCh signals mark early trend reversals - when market structure shifts from bearish to bullish (or vice versa). When captured in alignment with the higher timeframe trend, ChoCh entries can achieve exceptional risk-to-reward ratios as they allow entry near the beginning of a new impulse move.
Exit Signals
Exit signals are plotted when a ChoCh occurs in the opposite direction of the HTF trend. For example, if the HTF is bullish and a bearish ChoCh forms on the current timeframe, an orange "EXIT" signal appears - warning long traders that the lower timeframe structure is shifting against them. This provides an early warning system to protect profits or minimize losses before the HTF trend itself reverses.
Trading Strategy Recommendations
Trending Markets (Recommended)
In strong trending conditions, both BOS and ChoCh signals can be taken when aligned with the HTF bias. ChoCh entries are particularly powerful as they catch early reversals within the larger trend, offering entries with tight stop losses and extended profit targets.
Ranging Markets
During consolidation or choppy conditions, it's best to be selective and take only BOS entries. BOS signals confirm that the trend is continuing beyond the range, reducing false breakouts and whipsaw trades that are common with counter-trend ChoCh signals in sideways markets.
Customization
Pivot Length: Adjust the sensitivity of structure detection (default: 5). Lower values detect structure more frequently with earlier but potentially noisier signals. Higher values provide cleaner, more significant structural breaks but with some delay.
Higher Timeframe: Customize the HTF to suit your trading style. Day traders might use 1H HTF on 5m charts, while swing traders could use 4H or Daily HTF.
Alert System
Six alert conditions available:
Long BOS Entry / Long ChoCh Entry
Short BOS Entry / Short ChoCh Entry
Long Exit / Short Exit
All alerts fire only on confirmed candle closes to eliminate repainting and false signals.
Visual Features
Color-coded background showing HTF bias
Clear BOS/ChoCh labels with horizontal lines at structure levels
Orange "EXIT" signals when structure breaks against your position
Gray lines tracking current swing highs/lows
HTF trend indicator in the top-right corner
Previous Day High-LowIt will show Previous Day High-Low. This will create two horizontal lines automatically updated each day, marking yesterday’s high and low levels clearly on any intraday chart.
HELAL TRICKS FOREX NY TimeThe indicator marks the New York session opening candle at 9:30 AM (New York time), drawing horizontal lines at its high and low. These levels remain visible until 7:00 PM, helping traders identify key breakout and reversal zones during the most volatile session of the day. Developed by Helal – Tricks Forex, this tool simplifies New York session analysis for smarter intraday trading decisions.
FVG Volume Profile [ChartPrime]⯁ OVERVIEW
FVG Volume Profile is a smart volume analysis tool that identifies Fair Value Gaps (FVGs) and overlays a volume profile inside each gap using data from lower timeframes. The indicator automatically selects the best time resolution or allows for manual control, giving traders deeper insight into the volume structure within each imbalance. POC levels and total volumes gives a full microstructure view inside every FVG.
⯁ KEY FEATURES
Fair Value Gap Detection (Bullish & Bearish)
Detects price gaps where inefficiency exists using a 3-bar structure.
-Bullish Gaps: Low > High with confirming middle bar.
-Bearish Gaps: High < Low with confirming middle bar.
Only significant gaps (filtered by standard deviation) are plotted to avoid noise.
Multi-Timeframe Volume Profiling
Pulls granular candle and volume data from a lower timeframe —
In Auto Mode, uses a resolution ~10x lower than the current chart.
In Manual Mode, lets the user select a custom timeframe.
This ensures accurate intra-gap volume distribution.
Dynamic Volume Binning
Each FVG is divided into vertical volume bins based on the Resolution input.
Each bin displays relative volume intensity as a horizontal box, scaled by percentage of the max bin volume.
Point of Control (PoC) Line & Label
The bin with the maximum volume inside each FVG is marked with:
A horizontal line (PoC) extending from the left to right side.
A label showing the absolute volume of that bin.
Color-coded to match bullish or bearish FVGs.
Total Volume Label Inside FVG
Each FVG displays the total volume sum from its profile:
For bullish FVGs , shown in the bottom-right corner.
For bearish FVGs , shown in the top-right corner.
Auto-Removal of Invalid Gaps
If price fully closes the gap (crosses its bounds), the FVG, profile, and PoC are deleted automatically.
This keeps the chart clean and focused only on active zones.
Toggleable Volume Profile Display
User can show or hide the volume profiles within FVGs using the "Display" toggle under the "FVG Volume Profile" group.
Only the PoC and FVG boxes remain visible if toggled off.
Volume Resolution Customization
Control the number of bins used for each FVG profile.
Higher resolution = more bins and finer volume analysis. (default 15)
Auto Timeframe Validation Warning
If the selected lower timeframe isn’t actually lower than the chart's, the script shows a visible warning label prompting adjustment.
Helps prevent calculation errors.
⯁ USAGE
Use this tool to identify active imbalance zones (FVGs) with embedded volume context.
Look for PoC positioning inside gaps — near top may indicate absorption or reversal zones.
Combine with price action at the PoC level for precision entries.
Hide volume profile for a cleaner view while retaining key POC and FVG boxes.
Use resolution controls to zoom into fine-grained profiles inside large gaps.
Consider Auto mode for seamless multi-timeframe analysis, or switch to Manual for full control.
⯁ CONCLUSION
FVG Volume Profile transforms raw imbalance detection into actionable insight by embedding lower-timeframe volume structure inside each Fair Value Gap. With PoC highlights, total volume labels, and customizable bin resolution, this indicator is essential for traders who want to understand not just where the gap is — but what volume did inside it .
Wyckoff Effort vs. Result📌 Wyckoff Effort vs. Result (E/R) – Visualizing Supply & Demand Imbalance with Volume Confirmation
📖 Overview
The Wyckoff Effort vs. Result (E/R) indicator is designed to help traders interpret market behavior through the lens of volume vs. price movement — a foundational concept in Richard Wyckoff’s methodology.
This tool aims to highlight moments where the “effort” (volume) is not in proportion to the “result” (price movement) — giving insight into potential accumulation or distribution events.
By detecting high-volume candles and classifying them based on their price direction, the indicator visualizes zones where smart money might be active .
⚙️ How It Works
1. Effort Accumulation (High Volume Down Bar):
• When a candle closes lower than it opens (down bar) and has above-average volume , it’s marked as potential absorption of selling pressure (effort to push down met by buying).
• These candles are colored red and the open level is plotted, acting as a potential support or re-test zone.
2. Effort Distribution (High Volume Up Bar):
• When a candle closes higher than it opens (up bar) and has above-average volume , it’s marked as potential distribution (effort to push up absorbed by sellers).
• These candles are colored green and the open level is plotted , acting as a potential resistance or rejection zone.
3. Average Volume Calculation:
• The script calculates a simple moving average (SMA) of volume over a user-defined lookback period.
• If current volume exceeds the average multiplied by a set threshold, it’s treated as a high-effort bar .
🧪 Inputs
Input Description
Average Volume Lookback - Number of bars used to calculate the volume average
High Volume Multiplier. - Multiplier to define what qualifies as “high volume”
🖥️ Visual Output
• 🔴 Red candles = High volume on a down bar → possible accumulation
• 🟢 Green candles = High volume on an up bar → possible distribution
• 📉 Horizontal lines at bar open price mark the potential zones where effort occurred
These zones can serve as:
• Areas of support/resistance
• Trap zones where smart money absorbs liquidity
• Entry/exit filters when combined with price action
🧠 How to Use
• Use in combination with price structure, support/resistance, and volume profile tools
• Watch how price reacts when it revisits the plotted lines
• Look for effort bars that fail to lead to continuation, signaling potential reversal
• Can be used in scalping, swing trading, or Wyckoff-style phase analysis
🔒 Technical Notes
• ✅ Does not repaint
• ✅ Built with Pine Script v6
• ✅ Lightweight and customizable
• ❌ Does not generate buy/sell signals — it provides context, not predictions
