High Volume Vector CandlesHigh Volume Vector Candles highlights candles where trading activity significantly exceeds the average, helping you quickly identify powerful moves driven by strong volume.
How it works:
- The script calculates a moving average of volume over a user-defined period.
- When current volume exceeds the chosen threshold (e.g. 150% of the average), the candle is marked as a high-volume event.
- Bullish high-volume candles are highlighted in blue tones, while bearish ones are shown in yellow, both with adjustable opacity.
This visualization makes it easier to spot potential breakout points, absorption zones, or institutional activity directly on your chart.
Customizable Settings:
• Moving average length
• Threshold percentage above average
• Bullish/Bearish highlight colors
• Opacity level
Ideal for traders who combine price action with volume analysis to anticipate market momentum.
Hacim
Retail vs Banker Net Positions – Symmetry BreakRetail vs Banker Net Positions – Symmetry Break (Institution Focus)
Description:
This advanced indicator is a volume-proxy-based positioning tool that separates institutional vs. retail behavior using bar structure, trend-following logic, and statistical analysis. It identifies net position flows over time, detects institutional aggression spikes, and highlights symmetry breaks—those moments when institutional action diverges sharply from retail behavior. Designed for intraday to swing traders, this is a powerful tool for gauging smart money activity and retail exhaustion.
What It Does:
Separates Volume into Two Groups:
Institutional Proxy: Volume on large bars in trend direction
Retail Proxy: Volume on small or counter-trend bars
Calculates Net Positions (%):
Smooths cumulative buying vs. selling behavior for each group over time.
Highlights Symmetry Breaks:
Alerts when institutions make statistically abnormal moves while retail is quiet or doing the opposite.
Detects Extremes in Institutional Activity:
Flags major tops/bottoms in institutional positioning using swing pivots or rolling windows.
Retail Sentiment Flips:
Marks when the retail line crosses the zero line (e.g., flipping from net short to net long).
How to Use It:
Interpreting the Two Lines:
Aqua/Orange Line (Institutional Proxy):
Rising above zero = Net buying bias
Falling below zero = Net selling bias
Lime/Red Line (Retail Proxy):
Green = Retail buying; Red = Retail selling
Watch for crosses of zero for sentiment shifts
Spotting Symmetry Breaks:
Pink Circle or Background Highlight =
Institutions made a sharp, outsized move while retail was:
Quiet (low ROC), or
Moving in the opposite direction
These often precede explosive directional moves or stop hunts.
Institutional Extremes:
Marked with aqua (top) or orange (bottom) dots
Based on swing pivot logic or rolling highs/lows in institutional positioning
Optional filter: Only show extremes that coincide with a symmetry break
Settings You Can Tune:
Lookback lengths for trend, z-scores, smoothing
Z-Score thresholds to control sensitivity
Retail quiet filters to reduce false positives
Cool-down timer to avoid rapid repeat signals
Toggle visual aids like shading, markers, and threshold lines
Alerts Included:
-Retail flips (green/red)
- Institutional symmetry breaks
- Institutional extreme tops/bottoms
Strategy Tip:
Use this indicator to track institutional accumulation or distribution phases and catch asymmetric inflection points where the "smart money" acts decisively. Confluence with price structure or FVGs (Fair Value Gaps) can further enhance signal quality.
MTF K-Means Price Regimes [matteovesperi] ⚠️ The preview uses a custom example to identify support/resistance zones. due to the fact that this identifier clusterizes, this is possible. this example was set up "in a hurry", therefore it has a possible inaccuracy. When setting up the indicator, it is extremely important to select the correct parameters and double-check them on the selected history.
📊 OVERVIEW
Purpose
MTF K-Means Price Regimes is a TradingView indicator that automatically identifies and classifies the current market regime based on the K-Means machine learning algorithm. The indicator uses data from a higher timeframe (Multi-TimeFrame, MTF) to build stable classification and applies it to the working timeframe in real-time.
Key Features
✅ Automatic market regime detection — the algorithm finds clusters of similar market conditions
✅ Multi-timeframe (MTF) — clustering on higher TF, application on lower TF
✅ Adaptive — model recalculates when a new HTF bar appears with a rolling window
✅ Non-Repainting — classification is performed only on closed bars
✅ Visualization — bar coloring + information panel with cluster characteristics
✅ Flexible settings — from 2 to 10 clusters, customizable feature periods, HTF selection
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🔬 TECHNICAL DETAILS
K-Means Clustering Algorithm
What is K-Means?
K-Means is one of the most popular clustering algorithms (unsupervised machine learning). It divides a dataset into K groups (clusters) so that similar elements are within each cluster, and different elements are between clusters.
Algorithm objective:
Minimize within-cluster variance (sum of squared distances from points to their cluster center).
How Does K-Means Work in Our Indicator?
Step 1: Data Collection
The indicator accumulates history from the higher timeframe (HTF):
RSI (Relative Strength Index) — overbought/oversold indicator
ATR% (Average True Range as % of price) — volatility indicator
ΔP% (Price Change in %) — trend strength and direction indicator
By default, 200 HTF bars are accumulated (clusterLookback parameter).
Step 2: Creating Feature Vectors
Each HTF bar is described by a three-dimensional vector:
Vector =
Step 3: Normalization (Z-Score)
All features are normalized to bring them to a common scale:
Normalized_Value = (Value - Mean) / StdDev
This is critically important, as RSI is in the range 0-100, while ATR% and ΔP% have different scales. Without normalization, one feature would dominate over others.
Step 4: K-Means++ Centroid Initialization
Instead of random selection of K initial centers, an improved K-Means++ method is used:
First centroid is randomly selected from the data
Each subsequent centroid is selected with probability proportional to the square of the distance to the nearest already selected centroid
This ensures better initial centroid distribution and faster convergence
Step 5: Iterative Optimization (Lloyd's Algorithm)
Repeat until convergence (or maxIterations):
1. Assignment step:
For each point find the nearest centroid and assign it to this cluster
2. Update step:
Recalculate centroids as the average of all points in each cluster
3. Convergence check:
If centroids shifted less than 0.001 → STOP
Euclidean distance in 3D space is used:
Distance = sqrt((RSI1 - RSI2)² + (ATR1 - ATR2)² + (ΔP1 - ΔP2)²)
Step 6: Adaptive Update
With each new HTF bar:
The oldest bar is removed from history (rolling window method)
New bar is added to history
K-Means algorithm is executed again on updated data
Model remains relevant for current market conditions
Real-Time Classification
After building the model (clusters + centroids), the indicator works in classification mode:
On each closed bar of the current timeframe, RSI, ATR%, ΔP% are calculated
Feature vector is normalized using HTF statistics (Mean/StdDev)
Distance to all K centroids is calculated
Bar is assigned to the cluster with minimum distance
Bar is colored with the corresponding cluster color
Important: Classification occurs only on a closed bar (barstate.isconfirmed), which guarantees no repainting .
Data Architecture
Persistent variables (var):
├── featureVectors - Normalized HTF feature vectors
├── centroids - Cluster center coordinates (K * 3 values)
├── assignments - Assignment of each HTF bar to a cluster
├── htfRsiHistory - History of RSI values from HTF
├── htfAtrHistory - History of ATR values from HTF
├── htfPcHistory - History of price changes from HTF
├── htfCloseHistory - History of close prices from HTF
├── htfRsiMean, htfRsiStd - Statistics for RSI normalization
├── htfAtrMean, htfAtrStd - Statistics for ATR normalization
├── htfPcMean, htfPcStd - Statistics for Price Change normalization
├── isCalculated - Model readiness flag
└── currentCluster - Current active cluster
All arrays are synchronized and updated atomically when a new HTF bar appears.
Computational Complexity
Data collection: O(1) per bar
K-Means (one pass):
- Assignment: O(N * K) where N = number of points, K = number of clusters
- Update: O(N * K)
- Total: O(N * K * I) where I = number of iterations (usually 5-20)
Example: With N=200 HTF bars, K=5 clusters, I=20 iterations:
200 * 5 * 20 = 20,000 operations (executes quickly)
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📖 USER GUIDE
Quick Start
1. Adding the Indicator
TradingView → Indicators → Favorites → MTF K-Means Price Regimes
Or copy the code from mtf_kmeans_price_regimes.pine into Pine Editor.
2. First Launch
When adding the indicator to the chart, you'll see a table in the upper right corner:
┌─────────────────────────┐
│ Status │ Collecting HTF │
├─────────────────────────┤
│ Collected│ 15 / 50 │
└─────────────────────────┘
This means the indicator is accumulating history from the higher timeframe. Wait until the counter reaches the minimum (default 50 bars for K=5).
3. Active Operation
After data collection is complete, the main table with cluster information will appear:
┌────┬──────┬──────┬──────┬──────────────┬────────┐
│ ID │ RSI │ ATR% │ ΔP% │ Description │Current │
├────┼──────┼──────┼──────┼──────────────┼────────┤
│ 1 │ 68.5 │ 2.15 │ 1.2 │ High Vol,Bull│ │
│ 2 │ 52.3 │ 0.85 │ 0.1 │ Low Vol,Flat │ ► │
│ 3 │ 35.2 │ 1.95 │ -1.5 │ High Vol,Bear│ │
└────┴──────┴──────┴──────┴──────────────┴────────┘
The arrow ► indicates the current active regime. Chart bars are colored with the corresponding cluster color.
Customizing for Your Strategy
Choosing Higher Timeframe (HTF)
Rule: HTF should be at least 4 times higher than the working timeframe.
| Working TF | Recommended HTF |
|------------|-----------------|
| 1 min | 15 min - 1H |
| 5 min | 1H - 4H |
| 15 min | 4H - D |
| 1H | D - W |
| 4H | D - W |
| D | W - M |
HTF Selection Effect:
Lower HTF (closer to working TF): More sensitive, frequently changing classification
Higher HTF (much larger than working TF): More stable, long-term regime assessment
Number of Clusters (K)
K = 2-3: Rough division (e.g., "uptrend", "downtrend", "flat")
K = 4-5: Optimal for most cases (DEFAULT: 5)
K = 6-8: Detailed segmentation (requires more data)
K = 9-10: Very fine division (only for long-term analysis with large windows)
Important constraint:
clusterLookback ≥ numClusters * 10
I.e., for K=5 you need at least 50 HTF bars, for K=10 — at least 100 bars.
Clustering Depth (clusterLookback)
This is the rolling window size for building the model.
50-100 HTF bars: Fast adaptation to market changes
200 HTF bars: Optimal balance (DEFAULT)
500-1000 HTF bars: Long-term, stable model
If you get an "Insufficient data" error:
Decrease clusterLookback
Or select a lower HTF (e.g., "4H" instead of "D")
Or decrease numClusters
Color Scheme
Default 10 colors:
Red → Often: strong bearish, high volatility
Orange → Transition, medium volatility
Yellow → Neutral, decreasing activity
Green → Often: strong bullish, high volatility
Blue → Medium bullish, medium volatility
Purple → Oversold, possible reversal
Fuchsia → Overbought, possible reversal
Lime → Strong upward momentum
Aqua → Consolidation, low volatility
White → Undefined regime (rare)
Important: Cluster colors are assigned randomly at each model recalculation! Don't rely on "red = bearish". Instead, look at the description in the table (RSI, ATR%, ΔP%).
You can customize colors in the "Colors" settings section.
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⚙️ INDICATOR PARAMETERS
Main Parameters
Higher Timeframe (htf)
Type: Timeframe selection
Default: "D" (daily)
Description: Timeframe on which the clustering model is built
Recommendation: At least 4 times larger than your working TF
Clustering Depth (clusterLookback)
Type: Integer
Range: 50 - 2000
Default: 200
Description: Number of HTF bars for building the model (rolling window size)
Recommendation:
- Increase for more stable long-term model
- Decrease for fast adaptation or if there's insufficient historical data
Number of Clusters (K) (numClusters)
Type: Integer
Range: 2 - 10
Default: 5
Description: Number of market regimes the algorithm will identify
Recommendation:
- K=3-4 for simple strategies (trending/ranging)
- K=5-6 for universal strategies
- K=7-10 only when clusterLookback ≥ 100*K
Max K-Means Iterations (maxIterations)
Type: Integer
Range: 5 - 50
Default: 20
Description: Maximum number of algorithm iterations
Recommendation:
- 10-20 is sufficient for most cases
- Increase to 30-50 if using K > 7
Feature Parameters
RSI Period (rsiLength)
Type: Integer
Default: 14
Description: Period for RSI calculation (overbought/oversold feature)
Recommendation:
- 14 — standard
- 7-10 — more sensitive
- 20-25 — more smoothed
ATR Period (atrLength)
Type: Integer
Default: 14
Description: Period for ATR calculation (volatility feature)
Recommendation: Usually kept equal to rsiLength
Price Change Period (pcLength)
Type: Integer
Default: 5
Description: Period for percentage price change calculation (trend feature)
Recommendation:
- 3-5 — short-term trend
- 10-20 — medium-term trend
Visualization
Show Info Panel (showDashboard)
Type: Checkbox
Default: true
Description: Enables/disables the information table on the chart
Cluster Color 1-10
Type: Color selection
Description: Customize colors for visual cluster distinction
Recommendation: Use contrasting colors for better readability
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📊 INTERPRETING RESULTS
Reading the Information Table
┌────┬──────┬──────┬──────┬──────────────┬────────┐
│ ID │ RSI │ ATR% │ ΔP% │ Description │Current │
├────┼──────┼──────┼──────┼──────────────┼────────┤
│ 1 │ 68.5 │ 2.15 │ 1.2 │ High Vol,Bull│ │
│ 2 │ 52.3 │ 0.85 │ 0.1 │ Low Vol,Flat │ ► │
│ 3 │ 35.2 │ 1.95 │ -1.5 │ High Vol,Bear│ │
│ 4 │ 45.0 │ 1.20 │ -0.3 │ Low Vol,Bear │ │
│ 5 │ 72.1 │ 3.05 │ 2.8 │ High Vol,Bull│ │
└────┴──────┴──────┴──────┴──────────────┴────────┘
"ID" Column
Cluster number (1-K). Order doesn't matter.
"RSI" Column
Average RSI value in the cluster (0-100):
< 30: Oversold zone
30-45: Bearish sentiment
45-55: Neutral zone
55-70: Bullish sentiment
> 70: Overbought zone
"ATR%" Column
Average volatility in the cluster (as % of price):
< 1%: Low volatility (consolidation, narrow range)
1-2%: Normal volatility
2-3%: Elevated volatility
> 3%: High volatility (strong movements, impulses)
Compared to the average volatility across all clusters to determine "High Vol" or "Low Vol".
"ΔP%" Column
Average price change in the cluster (in % over pcLength period):
> +0.05%: Bullish regime
-0.05% ... +0.05%: Flat (sideways movement)
< -0.05%: Bearish regime
"Description" Column
Automatic interpretation:
"High Vol, Bull" → Strong upward momentum, high activity
"Low Vol, Flat" → Consolidation, narrow range, uncertainty
"High Vol, Bear" → Strong decline, panic, high activity
"Low Vol, Bull" → Slow growth, low activity
"Low Vol, Bear" → Slow decline, low activity
"Current" Column
Arrow ► shows which cluster the last closed bar of your working timeframe is in.
Typical Cluster Patterns
Example 1: Trend/Flat Division (K=3)
Cluster 1: RSI=65, ATR%=2.5, ΔP%=+1.5 → Bullish trend
Cluster 2: RSI=50, ATR%=0.8, ΔP%=0.0 → Flat/Consolidation
Cluster 3: RSI=35, ATR%=2.3, ΔP%=-1.4 → Bearish trend
Strategy: Open positions when regime changes Flat → Trend, avoid flat.
Example 2: Volatility Breakdown (K=5)
Cluster 1: RSI=72, ATR%=3.5, ΔP%=+2.5 → Strong bullish impulse (high risk)
Cluster 2: RSI=60, ATR%=1.5, ΔP%=+0.8 → Moderate bullish (optimal entry point)
Cluster 3: RSI=50, ATR%=0.7, ΔP%=0.0 → Flat
Cluster 4: RSI=40, ATR%=1.4, ΔP%=-0.7 → Moderate bearish
Cluster 5: RSI=28, ATR%=3.2, ΔP%=-2.3 → Strong bearish impulse (panic)
Strategy: Enter in Cluster 2 or 4, avoid extremes (1, 5).
Example 3: Mixed Regimes (K=7+)
With large K, clusters can represent condition combinations:
High RSI + Low volatility → "Quiet overbought"
Neutral RSI + High volatility → "Uncertainty with high activity"
Etc.
Requires individual analysis of each cluster.
Regime Changes
Important signal: Transition from one cluster to another!
Trading situation examples:
Flat → Bullish trend → Buy signal
Bullish trend → Flat → Take profit, close longs
Flat → Bearish trend → Sell signal
Bearish trend → Flat → Close shorts, wait
You can build a trading system based on the current active cluster and transitions between them.
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💡 USAGE EXAMPLES
Example 1: Scalping with HTF Filter
Task: Scalping on 5-minute charts, but only enter in the direction of the daily regime.
Settings:
Working TF: 5 min
HTF: D (daily)
K: 3 (simple division)
clusterLookback: 100
Logic:
IF current cluster = "Bullish" (ΔP% > 0.5)
→ Look for long entry points on 5M
IF current cluster = "Bearish" (ΔP% < -0.5)
→ Look for short entry points on 5M
IF current cluster = "Flat"
→ Don't trade / reduce risk
Example 2: Swing Trading with Volatility Filtering
Task: Swing trading on 4H, enter only in regimes with medium volatility.
Settings:
Working TF: 4H
HTF: D (daily)
K: 5
clusterLookback: 200
Logic:
Allowed clusters for entry:
- ATR% from 1.5% to 2.5% (not too quiet, not too chaotic)
- ΔP% with clear direction (|ΔP%| > 0.5)
Prohibited clusters:
- ATR% > 3% → Too risky (possible gaps, sharp reversals)
- ATR% < 1% → Too quiet (small movements, commissions eat profit)
Example 3: Portfolio Rotation
Task: Managing a portfolio of multiple assets, allocate capital depending on regimes.
Settings:
Working TF: D (daily)
HTF: W (weekly)
K: 4
clusterLookback: 100
Logic:
For each asset in portfolio:
IF regime = "Strong trend + Low volatility"
→ Increase asset weight in portfolio (40-50%)
IF regime = "Medium trend + Medium volatility"
→ Standard weight (20-30%)
IF regime = "Flat" or "High volatility without trend"
→ Minimum weight or exclude (0-10%)
Example 4: Combining with Other Indicators
MTF K-Means as a filter:
Main strategy: MA Crossover
Filter: MTF K-Means on higher TF
Rule:
IF MA_fast > MA_slow AND Cluster = "Bullish regime"
→ LONG
IF MA_fast < MA_slow AND Cluster = "Bearish regime"
→ SHORT
ELSE
→ Don't trade (regime doesn't confirm signal)
This dramatically reduces false signals in unsuitable market conditions.
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📈 OPTIMIZATION RECOMMENDATIONS
Optimal Settings for Different Styles
Day Trading
Working TF: 5M - 15M
HTF: 1H - 4H
numClusters: 4-5
clusterLookback: 100-150
Swing Trading
Working TF: 1H - 4H
HTF: D
numClusters: 5-6
clusterLookback: 150-250
Position Trading
Working TF: D
HTF: W - M
numClusters: 4-5
clusterLookback: 100-200
Scalping
Working TF: 1M - 5M
HTF: 15M - 1H
numClusters: 3-4
clusterLookback: 50-100
Backtesting
To evaluate effectiveness:
Load historical data (minimum 2x clusterLookback HTF bars)
Apply the indicator with your settings
Study cluster change history:
- Do changes coincide with actual trend transitions?
- How often do false signals occur?
Optimize parameters:
- If too much noise → increase HTF or clusterLookback
- If reaction too slow → decrease HTF or increase numClusters
Combining with Other Techniques
Regime-Based Approach:
MTF K-Means (regime identification)
↓
+---+---+---+
| | | |
v v v v
Trend Flat High_Vol Low_Vol
↓ ↓ ↓ ↓
Strategy_A Strategy_B Don't_trade
Examples:
Trend: Use trend-following strategies (MA crossover, Breakout)
Flat: Use mean-reversion strategies (RSI, Bollinger Bands)
High volatility: Reduce position sizes, widen stops
Low volatility: Expect breakout, don't open positions inside range
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📞 SUPPORT
Report an Issue
If you found a bug or have a suggestion for improvement:
Describe the problem in as much detail as possible
Specify your indicator settings
Attach a screenshot (if possible)
Specify the asset and timeframe where the problem is observed
#1 Vishal Toora Buy/Sell Table#1 Vishal Toora Buy/Sell Table
A multi-range volume analysis tool that tracks Short, Medium, and Long-term volume activity directly from recent candles.
It calculates Buy and Sell volumes for each range, shows their Delta (difference), and generates a combined Signal (Buy / Sell / Neutral) based on all active ranges.
Each column and the Signal row can be switched ON/OFF for custom clarity.
🧠 What the Numbers Represent (Candle Connection)
Each number represents total volume from a group of candles:
The script looks back a certain number of candles in each range (e.g., 2–3 candles for Short, 10–20 for Medium, 50–100 for Long).
It measures how much volume occurred on bullish candles (Buy) vs bearish candles (Sell).
Buy Volume (Green Numbers):
Volume from candles where price closed higher than it opened → bullish pressure.
Sell Volume (Red Numbers):
Volume from candles where price closed lower than it opened → bearish pressure.
Delta (White or Yellow Numbers):
The difference between Buy and Sell volumes within that range.
Positive → More bullish volume.
Negative → More bearish volume.
Larger absolute values = stronger imbalance between buyers and sellers.
Signal Row:
Summarizes all ranges’ deltas:
🟢 Buy → majority of ranges show positive delta.
🔴 Sell → majority show negative delta.
⚪ Neutral → roughly balanced or mixed candle behavior.
🎯 In Simple Terms
Each number in the table is a summary of what recent candles did —
it converts multiple candles’ volume data into clean, readable signals,
so you instantly see who’s in control (buyers or sellers) across short, medium, and long perspectives.
© 2025 Vishal Toora — counting volumes so you don’t have to.
Buy or Sell... or just stare at the screen.
Making deltas speak louder than your ex. 💀
Disclaimer:
This indicator is for educational and informational purposes only.
It does not guarantee accuracy or performance.
You are solely responsible for your trading decisions.
NDOG [派大星]🧠 Indicator Description — “NDOG ”
This indicator visualizes Night-Day Opening Gaps (NDOG) based on the custom trading session timing used in U.S. markets.
Instead of using the standard daily candle change, it detects gaps between the 16:59 close and the 18:00 open (New York time, UTC-4).
Whenever the market reopens after the evening pause (from 16:59 → 18:00),
the script measures the price difference between the previous session’s close and the new session’s open,
then draws a shaded box to highlight the opening gap region.
🟦 Bullish Gap (Upward) — when the new session opens above the previous close.
🟪 Bearish Gap (Downward) — when the new session opens below the previous close.
You can control the maximum number of displayed gaps with the “Amount” setting.
This custom session logic allows more accurate visualization of after-hours transitions for futures or extended-hours instruments (e.g., ES, NQ, SPY).
Nqaba Goldminer StrategyThis indicator plots the New York session key timing levels used in institutional intraday models.
It automatically marks the 03:00 AM, 10:00 AM, and 2:00 PM (14:00) New York times each day:
Vertical lines show exactly when those time windows open — allowing traders to identify major global liquidity shifts between London, New York, and U.S. session overlaps.
Horizontal lines mark the opening price of the 5-minute candle that begins at each of those key times, providing precision reference levels for potential reversals, continuation setups, and intraday bias shifts.
Users can customize each line’s color, style (solid/dashed/dotted), width, and horizontal-line length.
A history toggle lets you display all past occurrences or just today’s key levels for a cleaner chart.
These reference levels form the foundation for strategies such as:
London Breakout to New York Reversal models
Opening Range / Session Open bias confirmation
Institutional volume transfer windows (London → NY → Asia)
The tool provides a simple visual structure for traders to frame intraday decision-making around recurring institutional time events.
Percentile Rank Oscillator (Price + VWMA)A statistical oscillator designed to identify potential market turning points using percentile-based price analytics and volume-weighted confirmation.
What is PRO?
Percentile Rank Oscillator measures how extreme current price behavior is relative to its own recent history. It calculates a rolling percentile rank of price midpoints and VWMA deviation (volume-weighted price drift). When price reaches historically rare levels – high or low percentiles – it may signal exhaustion and potential reversal conditions.
How it works
Takes midpoint of each candle ((H+L)/2)
Ranks the current value vs previous N bars using rolling percentile rank
Maps percentile to a normalized oscillator scale (-1..+1 or 0–100)
Optionally evaluates VWMA deviation percentile for volume-confirmed signals
Highlights extreme conditions and confluence zones
Why percentile rank?
Median-based percentiles ignore outliers and read the market statistically – not by fixed thresholds. Instead of guessing “overbought/oversold” values, the indicator adapts to current volatility and structure.
Key features
Rolling percentile rank of price action
Optional VWMA-based percentile confirmation
Adaptive, noise-robust structure
User-selectable thresholds (default 95/5)
Confluence highlighting for price + VWMA extremes
Optional smoothing (RMA)
Visual extreme zone fills for rapid signal recognition
How to use
High percentile values –> statistically extreme upward deviation (potential top)
Low percentile values –> statistically extreme downward deviation (potential bottom)
Price + VWMA confluence strengthens reversal context
Best used as part of a broader trading framework (market structure, order flow, etc.)
Tip: Look for percentile spikes at key HTF levels, after extended moves, or where liquidity sweeps occur. Strong moves into rare percentile territory may precede mean reversion.
Suggested settings
Default length: 100 bars
Thresholds: 95 / 5
Smoothing: 1–3 (optional)
Important note
This tool does not predict direction or guarantee outcomes. It provides statistical context for price extremes to help traders frame probability and timing. Always combine with sound risk management and other tools.
量价策略信号+K线pinbar+波动率出场+市场结构【梦喂马】v3Part 1: Indicator Module Explained (Code Analysis and Function Description)
Module 1: Master Switches
This is your "dashboard master control." Due to the numerous indicator functions, charts can appear cluttered. Here, you can easily turn each major function module on or off, allowing you to focus on the information you need most.
- Suggested Usage: When using it for the first time, you can start by only turning on the Vegas Channel and Core Entry Signals to familiarize yourself with the system's main trend judgment and entry logic. Then gradually turn on other modules to experience how they work together.
Module 2: Core Entry Signals (Long/Short Signals)
This is the "engine" of the entire system, responsible for generating the highest quality trend-following trading signals. The appearance of a "long" or "short" signal represents the resonance of multiple indicators, satisfying extremely stringent filtering conditions:
- 1. Vegas Channel Filtering:
- When going long, the price must be above the slow channel (576/676 EMA) and the fast channel (21/55 EMA).
- When shorting, the price must break below both the slow and fast channels.
- Interpretation: This ensures your trading direction is perfectly aligned with the medium- to long-term macro trend.
- 2. Alligator Line Confirmation:
- When going long, the price must be above the alligator lines (lips, teeth, jaws), and the alligator lines must be in a bullish alignment (opening upwards).
- When shorting, the opposite applies.
- Interpretation: This confirms that short-term momentum aligns with the long-term trend, avoiding hasty entry at the start or end of a trend.
- 3. OBV (On-Balance Volume) Filter:
- When going long, the OBV value must be above its own moving average (default 34 periods).
- When shorting, the OBV value must be below its moving average.
- Interpretation: OBV is a key indicator measuring fund inflows and outflows. This condition ensures that trading volume (funds) is supporting your trading direction.
- 4. ADX Trend Strength Filter:
- Whether going long or short, the ADX value must be greater than the set threshold (default 20).
- Interpretation: This is a crucial "insurance" layer. It helps filter out volatile market conditions with no clear direction, prone to repeated "misjudgments." We only act in markets with clear and strong trends.
Core Usage: Once a "long"/"short" signal appears, it represents a high-certainty trend-following trading opportunity. Due to the very strict nature of the signals, they appear infrequently, but each one deserves your close attention.
Module Three: Vegas Channel & Alligator Line (Trend Judgment Tool)
- Vegas Channel: Composed of two sets of EMAs.
- Slow Channel (576/676): Your "bull/bear dividing line." Above this line, only consider going long; below this line, only consider going short. It is your strategic compass.
- Fast Channel (21/55): Your "short-term momentum line." In an uptrend, price pullbacks to the vicinity of the fast channel are potential areas for adding to positions or entering.
- Alligator Line:
- Widening divergence: Indicates that a trend is underway.
- Convergence/Entanglement: Indicates the market is dormant or consolidating.
- Interpretation: Alligator lines allow you to visually see whether the market is in a "trending" or "consolidating" state. We primarily trade when the alligator lines widen.
Module Four: R/C Volume-Price Signals (Refined Entry/Warning Signals)
This is the system's "special forces," specifically designed to identify abnormal volume and price movements on key candlesticks. It is divided into the R series (Reversal) and the C series (Continuation).
- Prerequisites: All signals are based on trading volume. A signal's appearance must be accompanied by a significantly higher-than-average trading volume (increased volume). This indicates large capital participation at that price level, making the signal more reliable.
- R Series - Trend Reversal Signals (Warning/Opportunity):
- R1 (Core Reversal): In a downtrend, a sudden increase in volume on a bullish candlestick; or in an uptrend, an increase in volume on a bearish candlestick.
- Interpretation: This is the most basic reversal warning signal. It tells you that counter-trend forces are emerging, but it doesn't mean the trend will immediately reverse. Confirmation needs to be combined with other signals.
- R2 (Pattern Confirmation): In addition to R1, this candlestick must also be a well-defined Pin Bar (a bullish Pin Bar with a long lower shadow, or a bearish Pin Bar with a long upper shadow).
- Interpretation: This is a more reliable reversal signal. The Pin Bar pattern represents a strong rejection of the price after an attempt to break through; combined with increased volume, this indicates strong reversal momentum.
- R3 (Top Momentum): In addition to R2, the trading volume reaches a "massive" level (default is more than 4 times the average volume).
- Interpretation: This is the highest level reversal signal. It usually appears at the end of a trend, representing the extreme struggle and conversion of bullish and bearish forces, and is a potential sign of a "V-shaped reversal" or a deep V-bottom/top.
- C Series - Trend Continuation/Termination Signals:
- C0 (Trend Continuation): In a clear uptrend, a bearish Pin Bar (long upper shadow) with increased volume appears during a price pullback; or in a downtrend, a bullish Pin Bar (long lower shadow) with increased volume appears during a rebound.
- Interpretation: This is a classic "buy on pullback/sell on rebound" signal. It indicates that the pullback/rebound attempt to counterattack is quickly suppressed by the strong main trend, making it an excellent entry point for adding to positions or following the trend.
- CX (Exhaustion Signal): A C-series signal that appears when the price has moved far away from the slow Vegas Channel (default more than 5 times the ATR distance).
- Interpretation: This is an advanced use of the C-series. After a trend has run for a long time, market sentiment may be overly enthusiastic. The high-volume PinBar appearing at this time, while trend-following in form, is more likely to represent the exhaustion or "final frenzy" of the trend. This is an alert that the trend may be running out of momentum, and you should consider taking profits in batches rather than adding to your position.
Signal Priority: This indicator has been internally optimized: CX/R3 > R2 > C0 > R1. Higher-level signals will override lower-level signals, ensuring you see the most important information at the moment.
Module 5: Chandelier Exit - Dynamic Risk Management
This is a dynamic stop-loss system based on ATR (Average True Range).
- How it works:
- In an uptrend, it subtracts N times the ATR from the recent high, forming a stepped upward stop-loss line.
- In a downtrend, it adds N times the ATR from the recent low, forming a stepped downward stop-loss line.
- Core advantages: It automatically adjusts the stop-loss distance based on market volatility. During periods of high market volatility, the stop-loss widens, giving you more room; during periods of market stability, the stop-loss tightens, locking in profits more quickly.
- Usage:
- As an initial stop-loss: After entering a position, the stop-loss can be set outside the Chandelier line.
- As a trailing stop: The position is held as long as the price does not fall below (uptrend) or rise above (downtrend) the Chandelier line. This is a powerful tool for "letting profits run."
- As an auxiliary trend indicator: The direction of the chandelier line (upward/downward) also provides a concise short-term trend perspective.
Module Six: Candlestick Coloring
This feature is very intuitive; it colors candlesticks based on volume:
- High Volume (Orange): Volume exceeds twice the average volume.
- Huge Volume (Red): Volume exceeds four times the average volume.
- Usage: Helps you identify key candlesticks indicating significant market events at a glance, typically the start, acceleration, reversal, or exhaustion points of a trend.
Module Seven: ICT Market Structure
This is an advanced price behavior analysis tool based on ICT (Inner Circle Trader) theory, helping you understand the market's "skeleton."
- Core Concepts:
- Swing High/Low: Local tops and bottoms in market prices.
- BOS (Break of Structure): In an uptrend, the price creates a higher high than the previous swing high; in a downtrend, it creates a lower low.
- Interpretation: BOS (Bullish Oscillator) is a confirmation signal of trend continuation. Consecutive upward BOS indicate a healthy bullish trend, and vice versa.
- MSS (Market Structure Shift, also often called CHOCH): In an uptrend, the price fails to make a new high and instead falls below the previous valid swing low.
- Interpretation: MSS is the first and most important signal of a potential trend reversal. It indicates that market forces are shifting from bullish to bearish (or vice versa).
- Period Settings (Short/Intermediate/Long Term):
- Short Term: Based on the most minute 3-bar swing points, very sensitive, suitable for short-term traders to observe subtle changes.
- Intermediate Term (Recommended): Based on higher-level swing points formed from short-term swing points, filtering out some noise, suitable for day and swing traders.
- Long Term: Based on swing points formed from intermediate-term swing points, reflecting a longer-term structure, suitable for swing and long-term traders.
- Usage: Combine market structure with your trading signals. For example, in an uptrend (price above the Vegas Channel), each upward BOS confirms the health of the trend. If a C0 pullback signal appears at this point, it would be an excellent entry point. Conversely, if an MSS appears, even with a strong buy signal, caution is advised, as the trend may be reversing.
Module Eight: Information Panel
This is your "cockpit dashboard," consolidating all key information in one place, giving you a clear overview of the current market state:
- Main Trend Direction: The final trend judgment given by multiple indicators.
- Alligator Line Pattern: Shows whether the current trend is trending or consolidating.
- OBV Status: Whether funds are flowing in or out.
- ADX Status: Whether the trend is strong or weak.
- Chandelier Stop-Loss Direction: Short-term trend direction.
Dynamic Intraday Volume RatioCompares intraday candle volume to average intraday candle volume over a predefined period
Volume Spike | viResearchVolume Spike | viResearch
Conceptual Foundation and Innovation
The Volume Spike indicator by viResearch is designed to identify the underlying strength and health of market participation by analyzing volume behavior. Rather than simply detecting high or low volume, this indicator distinguishes between healthy, gradual accumulation and unsustainable volume surges, giving traders a nuanced understanding of market sentiment.
The indicator focuses on the relationship between current trading volume and its moving average, classifying market activity into several key regimes — gradual, consistent, spiking, or weakening. This allows traders to quickly assess whether a price move is supported by solid participation or driven by temporary excitement that may not last.
Core Concept and Analysis Approach
At its core, Volume Spike measures the quality and consistency of trading activity over time. When volume rises steadily and remains within a stable range, it reflects healthy participation and sustainable trends. In contrast, when volume suddenly surges several times above average, it may indicate a climax move, often preceding a short-term top or bottom.
The indicator also incorporates consistency and trend assessments to evaluate whether current volume conditions align with accumulation, distribution, or exhaustion phases — helping traders interpret why a move is happening, not just that it is.
Features and User Inputs
The Volume Spike script includes several key parameters that allow traders to tailor its behavior to different assets and timeframes:
Volume Average Length: Defines the lookback period for calculating the average volume baseline.
Spike Multiplier: Sets the threshold (in multiples of the average) to define a true “spike” in volume.
Gradual Max Multiplier: Determines the upper limit of what is considered healthy, gradual volume growth.
Consistency Check Period: Evaluates how stable or erratic recent volume behavior has been.
Volume MA & EMA Display: Optional overlays for visual comparison against current activity.
These settings allow traders to distinguish between normal volume growth during trend formation and excessive spikes that often signal exhaustion or reversal risk.
Market Interpretation and Use Cases
The Volume Spike indicator provides valuable insights into market conditions, particularly during strong price movements or breakout phases. It can be used to:
Identify Healthy Trend Participation: Gradually rising volume within consistent ranges confirms genuine trend momentum.
Detect Volume Climax Events: Sudden spikes far above the average often mark exhaustion points, signaling caution.
Spot Divergences: When price rises but volume weakens, it can indicate a fading rally or distribution phase.
Evaluate Accumulation vs. Distribution: Volume patterns during down moves reveal whether smart money is buying weakness or selling strength.
Visual Cues and Color Logic
The indicator uses intuitive color coding to make volume interpretation straightforward:
Aqua (Healthy Gradual Volume): Stable, sustainable participation supporting trend continuation.
Pink (Volume Spike): Sharp, excessive surge — a warning of possible exhaustion or reversal.
Yellow (Elevated Volume): Moderate increase, often during breakout confirmation.
Gray (Low Volume): Reduced participation, signaling potential indecision.
Background highlights and on-chart alerts visually reinforce these signals:
Green background: Healthy, consistent volume environment.
Pink background: Warning of sudden volume spikes.
Orange background: Price-volume divergence, signaling weakening conviction.
Strategic Insights and Warnings
A gradual rise in volume typically validates trend strength, while sharp spikes can serve as early warnings of potential exhaustion. Repeated volume spikes near resistance levels may indicate distribution, whereas spikes near lows often suggest capitulation. Monitoring how volume evolves — not just its magnitude — helps traders stay aligned with smart money flow.
Information Table and Alerts
A real-time dashboard displays key statistics such as current volume, relative multiple of average, consistency level, and pattern type. Built-in alerts notify traders of critical situations, including:
Volume Spike on Up Candle — potential short-term top or euphoria.
Volume Spike on Down Candle — possible bottom or panic-driven selling.
Summary and Practical Use
The Volume Spike | viResearch indicator provides traders with a deeper understanding of volume dynamics, highlighting when market activity supports a move and when it signals exhaustion. By combining volume consistency, relative strength, and pattern recognition, it transforms raw volume data into actionable insights.
Use it to confirm breakout quality, detect unsustainable rallies, or identify accumulation zones before reversals occur. Sustainable trends are built on consistent participation — Volume Spike helps you see when that conviction begins to fade or surge beyond control.
Trading example: Spike volume + Oversold Commodity Index For Loop | viResearch
Note: Historical readings are for analytical purposes only and do not guarantee future performance.
RKT_(CVD + Δ Vol) DESCRIPTION
The Volume & Volume Delta (CVD) indicator tracks buy–sell imbalance to gauge money flow strength. Delta is calculated from aggressive (market) volume and accumulated into CVD to identify directional flow. Suitable for crypto/futures/forex, intraday and swing trading.
HOW TO USE
When Delta > 0 and CVD makes higher highs → favor the uptrend; when Delta < 0 and CVD makes lower lows → favor the downtrend.
Divergence between price and CVD suggests potential reversals or pullbacks.
Recommend confirming with price structure/MA/volume before acting.
#1 Vishal Toora Buy Sell Tablecopyright Vishal Toora
**“© 2025 Vishal Toora — counting volumes so you don’t have to. Buy, sell, or just stare at the screen.”**
Or a few more playful options:
1. **“© Vishal Toora — making deltas speak louder than your ex.”**
2. **“© Vishal Toora — one signal to rule them all (Buy/Sell/Neutral).”**
3. **“© Vishal Toora — because guessing markets is so 2024.”**
Disclaimer: This indicator is for educational and informational purposes only. I do not claim 100% accuracy, and you are responsible for your own trading decisions.
FVG MagicFVG Magic — Fair Value Gaps with Smart Mitigation, Inversion & Auto-Clean-up
FVG Magic finds every tradable Fair Value Gap (FVG), shows who powered it, and then manages each gap intelligently as price interacts with it—so your chart stays actionable and clean.
Attribution
This tool is inspired by the idea popularized in “Volumatic Fair Value Gaps ” by BigBeluga (licensed CC BY-NC-SA 4.0). Credit to BigBeluga for advancing FVG visualization in the community.
Important: This is a from-scratch implementation—no code was copied from the original. I expanded the concept substantially with a different detection stack, a gap state machine (ACTIVE → 50% SQ → MITIGATED → INVERSED), auto-clean up rules, lookback/nearest-per-side pruning, zoom-proof volume meters, and timeframe auto-tuning for 15m/H1/H4.
What makes this version more accurate
Full-coverage detection (no “missed” gaps)
Default ICT-minimal rule (Bullish: low > high , Bearish: high < low ) catches all valid 3-candle FVGs.
Optional Strict filter (stricter structure checks) for traders who prefer only “clean” gaps.
Optional size percentile filter—off by default so nothing is hidden unless you choose to filter.
Correct handling of confirmations (wick vs close)
Mitigation Source is user-selectable: high/low (wick-based) or close (strict).
This avoids false “misses” when you expect wick confirmations (50% or full fill) but your logic required closes.
State-aware labelling to prevent misleading data
The Bull%/Bear% meter is shown only while a gap is ACTIVE.
As soon as a gap is 50% SQ, MITIGATED, or INVERSED, the meter is hidden and replaced with a clear tag—so you never read stale participation stats.
Robust zoom behaviour
The meter uses a fixed bar-width (not pixels), so it stays proportional and readable at any zoom level.
Deterministic lifecycle (no stale boxes)
Remove on 50% SQ (instant or delayed).
Inversion window after first entry: if price enters but doesn’t invert within N bars, the box auto-removes once fully filled.
Inversion clean up: after a confirmed flip, keep for N bars (context) then delete (or 0 = immediate).
Result: charts auto-maintain themselves and never “lie” about relevance.
Clarity near current price
Nearest-per-side (keep N closest bullish & bearish gaps by distance to the midpoint) focuses attention where it matters without altering detection accuracy.
Lookback (bars) ensures reproducible behaviour across accounts with different data history.
Timeframe-aware defaults
Sensible auto-tuning for 15m / H1 / H4 (right-extension length, meter width, inversion windows, clean up bars) to reduce setup friction and improve consistency.
What it does (under the hood)
Detects FVGs using ICT-minimal (default) or a stricter rule.
Samples volume from a 10× lower timeframe to split participation into Bull % / Bear % (sum = 100%).
Manages each gap through a state machine:
ACTIVE → 50% SQ (midline) → MITIGATED (full) → INVERSED (SR flip after fill).
Auto-clean up keeps only relevant levels, per your rules.
Dashboard (top-right) displays counts by side and the active state tags.
How to use it
First run (show everything)
Use Strict FVG Filter: OFF
Enable Size Filter (percentile): OFF
Mitigation Source: high/low (wick-based) or close (stricter), as you prefer.
Remove on 50% SQ: ON, Delay: 0
Read the context
While ACTIVE, use the Bull%/Bear% meter to gauge demand/supply behind the impulse that created the gap.
Confluence with your HTF structure, sessions, VWAP, OB/FVG, RSI/MACD, etc.
Trade interactions
50% SQ: often the highest-quality interaction; if removal is ON, the box clears = “job done.”
Full mitigation then rejection through the other side → tag changes to INVERSED (acts like SR). Keep for N bars, then auto-remove.
Keep the chart tidy (optional)
If too busy, enable Size Filter or set Nearest per side to 2–4.
Use Lookback (bars) to make behaviour consistent across symbols and histories.
Inputs (key ones)
Use Strict FVG Filter: OFF(default)/ON
Enable Size Filter (percentile): OFF(default)/ON + threshold
Mitigation Source: high/low or close
Remove on 50% SQ + Delay
Inversion window after entry (bars)
Remove inversed after (bars)
Lookback (bars), Nearest per side (N)
Right Extension Bars, Max FVGs, Meter width (bars)
Colours: Bullish, Bearish, Inversed fill
Suggested defaults (per TF)
15m: Extension 50, Max 12, Inversion window 8, Clean up 8, Meter width 20
H1: Extension 25, Max 10, Inversion window 6, Clean up 6, Meter width 15
H4: Extension 15, Max 8, Inversion window 5, Clean up 5, Meter width 10
Notes & edge cases
If a wick hits 50% or the far edge but state doesn’t change, you’re likely on close mode—switch to high/low for wick-based behaviour.
If a gap disappears, it likely met a clean up condition (50% removal, inversion window, inversion clean up, nearest-per-side, lookback, or max-cap).
Meters are hidden after ACTIVE to avoid stale percentages.
Cumulative Delta Volume MTFCumulative Delta Volume MTF (CDV_MTF)
Within volume analytics, “delta (buy − sell)” often acts as a leading indicator for price.
This indicator is a cumulative delta tailored for day trading.
It differs from conventional cumulative delta in two key ways:
Daily Reset
If heavy buying hits into the prior day’s close, a standard cumulative delta “carries” that momentum into the next day’s open. You can then misread direction—selling may actually be dominant, but yesterday’s residue still pushes the delta positive. With Daily Reset, accumulation uses only the current day’s delta, giving you a more reliable, open-to-close read for intraday decision-making.
Timeframe Selection (MTF)
You might chart 30s/15s candles to capture micro structure, while wanting the cumulative delta on 5-minute to judge the broader flow. With Timeframe (MTF), you can view a lower-timeframe chart and a higher-timeframe delta in one pane.
Overview
MTF aggregation: choose the delta’s computation timeframe via Timeframe (empty = chart) (empty = chart timeframe).
Daily Reset: toggle on/off to accumulate strictly within the current session/day.
Display: Candle or Line (Candle supports Heikin Ashi), with Bull/Bear background shading.
Overlays: up to two SMA and two EMA lines.
Panel: plotted in a sub-window (overlay=false).
Example Use Cases
At the open: turn Daily Reset = ON to see the pure, same-day buy/sell build-up.
Entry on lower TF, bias from higher TF: chart at 30s, set Timeframe = 5 to reduce noise and false signals.
Quick read of momentum: Candle + HA + background shading for intuitive direction; confirm with SMA/EMA slope or crosses.
Key Parameters
Timeframe (empty = chart): timeframe used to compute cumulative delta.
Enable Daily Reset: resets accumulation when the trading day changes.
Style: Candle / Line; Heikin Ashi toggle for Candle mode.
SMA/EMA 1 & 2: individual length and color settings.
Background: customize Bull and Bear background colors.
How to Read
Distance from zero: positive build = buy-side dominance; negative = sell-side dominance.
Slope × MAs: use CDV slope and MA direction/crossovers for momentum and potential turns.
Reset vs. non-reset:
ON → isolates intraday net flow.
OFF → tracks multi-day accumulation/dispersion.
Notes & Caveats
The delta here is a heuristic derived from candle body/wick proportions—it is not true bid/ask tape.
MTF updates are based on the selected timeframe’s bar closes; values can fluctuate intrabar.
Date logic follows the symbol’s exchange timezone.
Renders in a separate pane.
Suggested Defaults
Timeframe = 5 (or 15) / Daily Reset = ON
Style = Candle + Heikin Ashi = ON
EMA(50/200) to frame trend context
For the first decisions after the open—and for scalps/day trades throughout the session—MTF × Daily Reset helps you lock onto the flow that actually matters, right now.
==========================
Cumulative Delta Volume MTF（CDV_MTF）
出来高の中でも“デルタ（買い−売り）”は株価の先行指標になりやすい。
本インジケーターはデイトレードに特化した累積デルタです。
通常の累積デルタと異なるポイントは2つ。
デイリーリセット機能
前日の大引けで大きな買いが入ると、通常の累積デルタはその勢いを翌日の寄りにも“持ち越し”ます。実際は売り圧が強いのに、前日の残渣に引っ張られて方向を誤ることがある。デイリーリセットを使えば当日分だけで累積するため、寄り直後からの判断基準として信頼度が上がります。
タイムフレーム指定（MTF）機能
たとえばチャートは30秒足/15秒足で細部の動きを追い、累積デルタは5分足で“大きな流れ”を確認したい──そんなニーズに対応。**一画面で“下位足の値動き × 上位足のフロー”**を同時に把握できます。
概要
MTF対応：Timeframe で集計足を指定（空欄＝チャート足）
デイリーリセット：当日分のみで累積（オン/オフ切替）
表示：Candle/Line（CandleはHA切替可）、背景をBull/Bearで自動塗り分け
補助線：SMA/EMA（各2本）を重ね描き
表示先：サブウィンドウ（overlay=false）
使い方の例
寄りのフロー判定：デイリーリセット＝オンで、寄り直後の純粋な買い/売りの積み上がりを確認
下位足のエントリー × 上位足のバイアス：チャート＝30秒、Timeframe=5分で騙しを減らす
勢いの視認：Candle＋HA＋背景色で直感的に上げ下げを把握、SMA/EMAの傾きで補強
主なパラメータ
Timeframe (empty = chart)：累積に使う時間足
デイリーリセットを有効にする：日付切替で累積をリセット
Style：Candle / Line、Heikin Ashi切替
SMA/EMA 1・2：期間・色を個別設定
背景色：Bull背景 / Bear背景 を任意のトーンに
読み取りのコツ
ゼロからの乖離：＋側へ積み上がるほど買い優位、−側は売り優位
傾き×MA：CDVの傾きと移動平均の方向/クロスで転換やモメンタムを推測
日内/日跨ぎの切替：デイリーリセット＝オンで日内の純流入出、オフで期間全体の偏り
仕様・注意
本デルタはローソクのボディ/ヒゲ比率から近似したヒューリスティックで、実際のBid/Ask集計とは異なります。
MTFは指定足の確定ベースで更新されます。
日付判定はシンボルの取引所タイムゾーン準拠。
推奨初期セット
Timeframe=5（または15）／デイリーリセット=有効
Style=Candle＋HA=有効
EMA(50/200)で流れの比較
寄りの一手、そしてスキャル/デイの判断材料に。MTF×デイリーリセットで、“効いているフロー”を最短距離で捉えます。
RightFlow Universal Volume Profile - Any Market Any TimeframeSummary in one paragraph
RightFlow is a right anchored microstructure volume profile for stocks, futures, FX, and liquid crypto on intraday and daily timeframes. It acts only when several conditions align inside a session window and presents the result as a compact right side profile with value area, POC, a bull bear mix by price bin, and a HUD of profile VWAP and pressure shares. It is original because it distributes each bar’s weight into multiple mid price slices, blends bull bear pressure per bin with a CLV based split, and grows the profile to the right so price action stays readable. Add to a clean chart, read the table, and use the visuals. For conservative workflows read on bar close.
Scope and intent
• Markets. Major FX pairs, index futures, large cap equities and ETFs, liquid crypto.
• Timeframes. One minute to daily.
• Default demo used in the publication. SPY on 15 minute.
• Purpose. See where participation concentrates, which side dominated by price level, and how far price sits from VA and POC.
Originality and usefulness
• Unique fusion. Right anchored growth plus per bar slicing and CLV split, with weight modes Raw, Notional, and DeltaProxy.
• Failure mode addressed. False reads from single bar direction and coarse binning.
• Testability. All parts sit in Inputs and the HUD.
• Portable yardstick. Value Area percent and POC are universal across symbols.
• Protected scripts. Not applicable. Method and use are fully disclosed.
Method overview in plain language
Pick a scope Rolling or Today or This Week. Define a window and number of price bins. For each bar, split its range into small slices, assign each slice a weight from the selected mode, and split that weight by CLV or by bar direction. Accumulate totals per bin. Find the bin with the highest total as POC. Expand left and right until the chosen share of total volume is covered to form the value area. Compute profile VWAP for all, buyers, and sellers and show them with pressure shares.
Base measures
Range basis. High minus low and mid price samples across the bar window.
Return basis. Not used. VWAP trio is price weighted by weights.
Components
• RightFlow Bins. Price histogram that grows to the right.
• Bull Bear Split. CLV based 0 to 1 share or pure bar direction.
• Weight Mode. Raw volume, notional volume times close, or DeltaProxy focus.
• Value Area Engine. POC then outward expansion to target share.
• HUD. Profile VWAP, Buy and Sell percent, winner delta, split and weight mode.
• Session windows optional. Scope resets on day or week.
Fusion rule
Color of each bin is the convex blend of bull and bear shares. Value area shading is lighter inside and darker outside.
Signal rule
This is context, not a trade signal. A strong separation between buy and sell percent with price holding inside VA often confirms balance. Price outside VA with skewed pressure often marks initiative moves.
What you will see on the chart
• Right side bins with blended colors.
• A POC line across the profile width.
• Labels for POC, VAH, and VAL.
• A compact HUD table in the top right.
Table fields and quick reading guide
• VWAP. Profile VWAP.
• Buy and Sell. Pressure shares in percent.
• Delta Winner. Winner side and margin in percent.
• Split and Weight. The active modes.
Reading tip. When Session scope is Today or This Week and Buy minus Sell is clearly positive or negative, that side often controls the day’s narrative.
Inputs with guidance
Setup
• Profile scope. Rolling or session reset. Rolling uses window bars.
• Rolling window bars. Typical 100 to 300. Larger is smoother.
Binning
• Price bins. Typical 32 to 128. More bins increase detail.
• Slices per bar. Typical 3 to 7. Raising it smooths distribution.
Weighting
• Weight mode. Raw, Notional, DeltaProxy. Notional emphasizes expensive prints.
• Bull Bear split. CLV or BarDir. CLV is more nuanced.
• Value Area percent. Typical 68 to 75.
View
• Profile width in bars, color split toggle, value area shading, opacities, POC line, VA labels.
Usage recipes
Intraday trend focus
• Scope Today, bins 64, slices 5, Value Area 70.
• Split CLV, Weight Notional.
Intraday mean reversion
• Scope Today, bins 96, Value Area 75.
• Watch fades back to POC after initiative pushes.
Swing continuation
• Scope Rolling 200 bars, bins 48.
• Use Buy Sell skew with price relative to VA.
Realism and responsible publication
No performance claims. Shapes can move while a bar forms and settle on close. Education only.
Honest limitations and failure modes
Thin liquidity and data gaps can distort bin weights. Very quiet regimes reduce contrast. Session time is the chart venue time.
Open source reuse and credits
None.
Legal
Education and research only. Not investment advice. Test on history and simulation before live use.
Buying/Selling PressureBuying/Selling Pressure - Volume-Based Market Sentiment
Buying/Selling Pressure identifies market dominance by separating volume into buying and selling components. The indicator uses Volume ATR normalization to create a universal pressure oscillator that works consistently across all markets and timeframes.
What is Buying/Selling Pressure?
This indicator answers a fundamental question: Are buyers or sellers in control? By analyzing how volume distributes within each bar, it calculates cumulative buying and selling pressure, then normalizes the result using Volume ATR for cross-market comparability.
Formula: × 100
Where Delta = Buying Volume - Selling Volume
Calculation Methods
Money Flow (Recommended):
Volume weighted by close position in bar range. Close near high = buying pressure, close near low = selling pressure.
Formula: / (high - low)
Simple Delta:
Basic approach where bullish bars = 100% buying, bearish bars = 100% selling.
Weighted Delta:
Volume weighted by body size relative to total range, focusing on candle strength.
Key Features
Volume ATR Normalization: Adapts to volume volatility for consistent readings across assets
Cumulative Delta: Tracks net buying/selling pressure over time (similar to OBV)
Signal Line: EMA smoothing for trend identification and crossover signals
Zero Line: Clear visual separation between buyer and seller dominance
Color-Coded Display: Green area = buyers control, red area = sellers control
Interpretation
Above Zero: Buyers dominating - cumulative buying pressure exceeds selling
Below Zero: Sellers dominating - cumulative selling pressure exceeds buying
Cross Signal Line: Momentum shift - pressure trend changing direction
Increasing Magnitude: Strengthening pressure in current direction
Decreasing Magnitude: Weakening pressure, potential reversal
Volume vs Pressure
High volume with low pressure indicates balanced battle between buyers and sellers. High pressure with high volume confirms strong directional conviction. This separation provides insights beyond traditional volume analysis.
Best Practices
Use with price action for confirmation
Divergences signal potential reversals (price makes new high/low but pressure doesn't)
Large volume with near-zero pressure = indecision, breakout preparation
Signal line crossovers provide momentum change signals
Extreme readings suggest potential exhaustion
Settings
Calculation Method: Choose Money Flow, Simple Delta, or Weighted Delta
EMA Length: Period for cumulative delta smoothing (default: 21)
Signal Line: Optional EMA of oscillator for crossover signals (default: 9)
Buying/Selling Pressure transforms volume analysis into actionable market sentiment, revealing whether buyers or sellers control price action beneath surface volatility.
This indicator is designed for educational and analytical purposes. Past performance does not guarantee future results. Always conduct thorough research and consider consulting with financial professionals before making investment decisions.
CHN-M-HA secure buy/sell indicator for futures and spot trading. A green cloud indicates a trend. A magic line is available as support or a stop level. Buy and sell signals. Voluminous candlesticks are indicated.
SerenitySerenity: Find Serenity in Market Chaos
Every trader starts somewhere, often diving headfirst into the markets with charts cluttered by layers of lines, oscillators, and signals. It's easy to get caught up testing one approach after another—adding more tools, tweaking strategies, chasing the latest idea that promises clarity. The cycle repeats: overload the setup, second-guess every move, switch things up when results don't click right away. Over time, it becomes clear that jumping between setups rarely builds the consistency needed to navigate the ups and downs.
That's where the idea for Serenity came from—a way to step back from the noise and focus on a structured approach that encourages sticking to a plan and building consistency.
Built on the philosophy that no single perspective captures the full picture, Serenity offers two complementary views—Skye and Shade—to provide a more rounded interpretation of the market. Serenity’s logic builds on core market concepts—trend, momentum, and volume—combining them through carefully structured conditions that work across multiple timeframes. By focusing on where these elements align, it highlights key moments in the market while filtering out noise, providing clear and meaningful visual cues for analysis.
How Serenity Works
Serenity is designed to cut through market noise and simplify complex price action. By combining public, simple, everyday indicators and concepts into a progressive decision hierarchy of multi-layered signals, it removes ambiguity and leaves no room for guesswork—providing traders with straightforward, easy-to-read visual cues for decision-making.
Serenity's foundation starts with a core trend bias, built around two key concepts that set the stage for all signals:
Volatility-adjusted trend boundary (ATR-based) defines real-time directional bias using a dynamic channel that expands in choppy markets and tightens in calm ones — it only shifts when price proves real strength or weakness. This provides the overall market context, ensuring signals are in harmony with the prevailing direction.
Four nested volume-weighted price zones create progressive support levels—each acting as a filter for signal quality. These zones build on the trend boundary, requiring price to prove itself at increasing levels of conviction before triggering visuals.
Skye: Agile Momentum
Skye focuses on the faster side of market behavior. It reacts quickly to changes in trend and momentum, making it well-suited for traders who prefer agility and earlier entries. Skye thrives in environments where price moves sharply and timing matters.
Skye activates only when five independent filters align:
Momentum reversal — fast oscillator crosses above slow.
Volume surge — confirms participation strength, signaling that fresh momentum is backed by meaningful activity rather than isolated price movement.
Zone break — price closes above the earliest volume-weighted level.
Trend support — price remains above the dynamic channel.
Directional strength — positive momentum index rises above a required minimum.
This multi-condition gate eliminates single-trigger noise.
Shade: Structural Conviction Filter
Shade takes a more conservative stance, emphasizing broader confirmations and requires sustained dominance across four core pillars:
Long-term structure — price holds above deep volume-weighted trend.
Directional control — one side clearly dominates.
Zone hold — price sustains in mid or deep confluence level.
Volume trend — reveals sustained directional flow, confirming underlying market commitment behind the trend.
Each pillar must confirm — no partial signals.
Twilight & Eclipse: Reversal Cues
Twilight Reversal
Twilight draws attention to areas where upward momentum might begin to build. It serves as a visual cue for zones where buying interest could be forming, helping you focus on potential opportunities for a positive shift in market behavior.
Eclipse Reversal
Eclipse highlights areas where downward pressure may be emerging. It marks zones where sellers could be gaining influence, guiding your attention to potential points where market strength may start to wane.
These markers appear using:
Smoothed divergence — oscillator deviates from price at extremes.
Trend peak — strength index rolls over from overbought/oversold.
Volume opposition — surge against price direction.
What Makes Serenity Unique
What sets Serenity apart is not which concepts or indicators are used—but how they are applied together. Serenity employs a progressive decision hierarchy of multi-layered signals to identify meaningful confluences across trend, momentum, volume, and structure.
Instead of using standard setups that rely on default indicator inputs, Serenity uses carefully chosen, non-standard tailored inputs, ensuring that familiar indicators work together in a unique, confluence-driven way—offering structured context and visually intuitive cues to support clearer decision-making.
OBV with Divergence (SMA Smoother)Title: OBV Divergence with SMA Smoothing
Description:
This indicator is a powerful tool designed to identify regular (reversal) and hidden (continuation) On-Balance Volume (OBV) divergences against price action. It uses a modified OBV calculation (an OBV Oscillator) and integrates pivot analysis to automatically highlight potential turning points or trend continuations directly on your chart.
Key Features
Advanced Divergence Detection: Automatically detects and labels four types of divergences:
Regular Bullish/Bearish: Signals potential trend reversals.
Regular Bullish: Price makes a Lower Low (LL) but the OBV Oscillator makes a Higher Low (HL).
Regular Bearish: Price makes a Higher High (HH) but the OBV Oscillator makes a Lower High (LH).
Hidden Bullish/Bearish: Signals potential trend continuations.
Hidden Bullish: Price makes a Higher Low (HL) but the OBV Oscillator makes a Lower Low (LL).
Hidden Bearish: Price makes a Lower High (LH) but the OBV Oscillator makes a Higher High (HH).
OBV Oscillator: Instead of plotting the raw OBV, this script uses the difference between the OBV and its Exponential Moving Average (EMA). This technique centers the indicator around zero, making it easier to visualize volume momentum shifts and clearly identify peaks and troughs for divergence analysis.
Optional SMA Smoothing Line (New Feature): An added Simple Moving Average (SMA) line can be toggled on to further smooth the OBV Oscillator. Traders can use this line for crossover signals or to confirm the underlying trend of the volume momentum, reducing whipsaws.
Customizable Lookback: The indicator allows you to define the lookback periods (Pivot Lookback Left/Right) for price and oscillator pivots, giving you precise control over sensitivity. The Max/Min of Lookback Range helps filter out divergences that are too close or too far apart.
🔥 QUANT MOMENTUM SKORQUANT MOMENTUM SCORE – Description (EN)
Summary: This indicator fuses Price ROC, RSI, MACD, Trend Strength (ADX+EMA) and Volume into a single 0-100 “Momentum Score.” Guide bands (50/60/70/80) and ready-to-use alert conditions are included.
How it works
Price Momentum (ROC): Rate of change normalized to 0-100.
RSI Momentum: RSI treated as a momentum proxy and mapped to 0-100.
MACD Momentum: MACD histogram normalized to capture acceleration.
Trend Strength: ADX is direction-aware (DI+ vs DI–) and blended with EMA state (above/below) to form a combined trend score.
Volume Momentum: Volume relative to its moving average (ratio-based).
Weighting: All five components are weighted, auto-normalized, and summed into the final 0-100 score.
Visuals & Alerts: Score line with 50/60/70/80 guides; threshold-cross alerts for High/Strong/Ultra-Strong regimes.
Inputs, weights and thresholds are configurable; total weights are normalized automatically.
How to use
Timeframes: Works on any timeframe—lower TFs react faster; higher TFs reduce noise.
Reading the score:
<50: Weak momentum
50-60: Transition
60-70: Moderate-Strong (potential acceleration)
≥70: Strong, ≥80: Ultra Strong
Practical tip: Use it as a filter, not a stand-alone signal. Combine score breakouts with market structure/trend context (e.g., pullback-then-re-acceleration) to improve selectivity.
Disclaimer: This is not financial advice; past performance does not guarantee future results.
5x Relative Volume vs 30-Day AverageRelative Volume.
If today's volume is more than average of last 30 days volume by 5x.
Demand/Supply Oscillator_immyDemand/Supply Oscillator, probably the only D/S oscillator on TV which doesn't draw the lines on the chart but to show you the actual reasons behind the price moves.
Concept Overview
A demand/supply oscillator would aim to look for the hidden spots/order which institutes place in small quantities to not to upset the trend and suddenly place one big order to liquidate the retailers and make a final big move.
The lite color candles in histogram shows the hidden demand/supply which is the reason behind the sudden price pullback, even for short period of time.
Measure demand and supply based on volume, price movement, or candle structure
Identify price waves or impulses (e.g., using fractals, zigzag, or swing high/low logic)
Detect hidden demand/supply (e.g., low volume pullbacks or absorption zones)
Plotted on histogram boxes to visualize strength and direction of each wave
What “Hidden Demand” Means?
Hidden demand refers to buying pressure that isn’t immediately obvious from price action — in other words, buyers are active “behind the scenes” even though the price doesn’t yet show strong upward movement.
What Hidden supply Means?
refers to selling pressure that isn’t obvious yet on the price chart. It means smart money (big players) are quietly selling or distributing positions, even though the price might not be dropping sharply yet.
It usually appears when:
The price is pulling back slightly (down candle),
But volume or an oscillator (like RSI, MACD, or OBV) shows bullish strength (e.g., higher low or positive divergence).
That suggests smart money is accumulating (buying quietly) while the public may think it’s just a normal dip.
💹 Price Reaction — Up or Down?
If there is hidden demand, it’s generally a bullish signal → meaning price is likely to go up afterward.
However, on that exact candle, the price may still be down or neutral, because:
Hidden demand is “hidden” — buyers are absorbing supply quietly.
The move up usually comes after the hidden demand signal, not necessarily on the same candle.
📊 Example
Suppose:
Price makes a slightly lower low,
But RSI makes a higher low → this is bullish (hidden) divergence, or “hidden demand.”
➡️ Interpretation:
Smart buyers are stepping in → next few candles likely move up.
The current candle might still be red or show a small body — that’s okay. The key is the shift in underlying strength.
🧭 Quick Summary
Term Meaning Candle Effect Expected Move After
Hidden Demand Buyers active below surface Candle may still go down or stay flat
Hidden Supply Sellers active behind the scenes Price likely to rise soon
🛠️ Key Components
Best results with Price/Action e.g. Use swing high/low or zigzag to segment price into waves.
Optionally apply fractal logic for more refined wave detection
Combine with other indicators (e.g., RSI, OBV) for confirmation
Include zone strength metrics (e.g., “Power Number” as seen in some indicators)
Demand/Supply Calculation
Demand: Strong bullish candles, increasing volume, breakout zones
Supply: Strong bearish candles, volume spikes on down moves
Hidden Demand/Supply: Pullbacks with low volume or absorption candles
Histogram Visualization
Use plot() or plotshape() to draw histogram bars
Color-code bars: e.g., green for demand, red for supply, lite colors for hidden zones
Add alerts for wave transitions or hidden zone detection
How It Works
Demand/Supply: Detected when price moves strongly with volume spikes.
Hidden Zones: Detected when price moves but volume is low (potential absorption).
Histogram Values:
+2: Strong Demand
+1: Hidden Demand
-1: Hidden Supply
-2: Strong Supply
0: Neutral
Feature Demand (Visible) Hidden Demand
Visibility Clearly seen on price charts Subtle, often masked in consolidation
Participants Retail + Institutional Primarily Institutional
Price Behavior Sharp rallies from zone Sideways movement, low volatility
Tools to Identify Candlestick patterns, support zones Volume profile, order flow, price clusters
Risk/Reward Moderate (widely known) High (less crowded, early entry potential)
