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
Historical Volatility
HV Spike Strategy (HVP + OR Breakout + Reversal + TP/SL Modes)Here is a script that I tried to make it simple, although it has several parameters, I will try to explain, here we go:
Logic: Open Range Breakout: otherwise knows as First Candle Rule, usually used for the first candle in the opening of a market session, in my strategy there is an option to use it even for Crypto that operate 24/7, how to do that? Simply by detecting Volatility from the HVP (Historical Volatility Percentile). Then the ORB logic kicks in and the first candle with high volatility gives the ranges for the trades. The proper HVP Activation Threshold has to be selected for each currency pair/index/crypto in order to have maximum profit.
Enter a trade: when the price goes 100% above/below the First Candle Rule Range. That way it is filtering fake breakouts. Also if the price reverses back into the range the strategy takes the opposite trade.
Exit a trade: SL/TP By percentage or ATR, selection in the input menu.
My intention is to avoid using lagging indicators or guessing of Price Action, purely Bull/Bear indication by the first candle.
I hope you find this helpful! Wishing all successful Trades!
Sigma Volatility BandsThis indicator models and displays bands of potential future price based on historic realized volatility.
This can be used for finding price target where there is no past price action.
The price bands are derived from Standard Deviations based on input bars back of historic volatility.
More Inputs:
Lookback = Number of bars considered
Forward Bars = Number of bars to project bands forward
There are two display modes:
Forward shifted envelopes = (see below) Draws bands of price from the Standard Deviation
Forward for Anchor Lines = Draws a wedge out number of bars forward
(Vibe coded. Message me for suggested updates and improvements)
DTR & ATR with live zonesThis indicator is designed to help traders gauge the day's volatility in real-time. It compares the current Daily True Range (DTR)—the distance between the session's high and low—to the historical Average True Range (ATR).
The main purpose is to project potential price levels where the market might reach based on its average volatility. These levels (100% ATR, 150%, 200%, etc.) can be used as price targets. For instance, if you're in a long trade, you might consider taking partial or full profits as the price approaches these upper ATR extension levels. The indicator is highly customisable, allowing you to control the appearance of the ATR lines, zones, and labels to fit your charting preferences.
Core Concepts: ATR and DTR
To use this indicator effectively, it's important to understand its two main components:
Average True Range (ATR): This is a classic technical analysis indicator that measures market volatility. It calculates the average range of price movement over a specific period (e.g., 14 days). A higher ATR means the price is, on average, moving more, while a low ATR indicates less volatility. This script uses a higher timeframe ATR (e.g., Daily) to establish a stable volatility baseline for the current trading day.
Daily True Range (DTR): This is simply the difference between the current trading session's highest high and lowest low (session high - session low). It tells you how much the price has actually moved so far today.
The indicator's logic revolves around comparing the live, unfolding DTR to the historical, baseline ATR. An on-screen table conveniently shows this comparison as a percentage, to show how volatile the day has been.
How It Works: The Dynamic & Locked Mechanism
The most clever part of this indicator is how it draws the ATR levels. It operates in two distinct phases during the trading session:
Phase 1: Dynamic Expansion (Before DTR meets ATR)
At the start of the session, the DTR is small. The indicator calculates the remaining range needed to "complete" the 100% ATR level (difference = avg_atr - dtr). It then adds this remaining amount to the session high and subtracts it from the session low. This creates a "floating" 100% ATR range that expands dynamically as the session high or low is extended.
Phase 2: The Lock-in (After DTR meets or exceeds ATR)
Once the day's range (DTR) becomes equal to or greater than the avg_atr, the day has met its "expected" volatility. At this point, the levels lock in place. The indicator intelligently determines the anchor point for the locked range.
Once this primary 100% ATR range is established (either dynamically or locked), the script projects the other levels (150%, 200%, 250%, and 300%) by adding or subtracting multiples of the avg_atr from this base.
How to Use It for Trading
The primary use of this indicator is to set logical, volatility-based price targets.
Setting Profit Targets: If you enter a long position, the upper ATR levels (100%, 150%, 200%) serve as excellent areas to consider taking profits. A move to the 200% or 250% level often signifies an overextended or "exhaustion" move, making it a high-probability exit zone. For short positions, the lower ATR levels serve the same purpose.
Assessing Intraday Momentum: The on-screen table tells you how much of the expected daily range has been used. If it's early in the session and the DTR is only at 30% of the ATR, you can anticipate more significant price movement is likely to come. Conversely, if the DTR is already at 150% of ATR, the bulk of the day's move may already be complete.
Mean Reversion Signals: If the price pushes to an extreme level (e.g., 250% ATR) and shows signs of stalling (e.g., bearish divergence on an oscillator), it could signal a potential reversal or pullback, offering an opportunity for a counter-trend trade.
Key Settings
ATR Length & Smoothing Type: These settings control how the baseline ATR is calculated. The default 14 period and RMA smoothing are standard, but you can adjust them to your preference.
Session Settings: This is crucial. You must set the Market Session and Time Zone to match the primary trading hours of the asset you are analysing (e.g., "0930-1600" for the NYSE session).
Show Lines / Show Labels / Show Zones: The script gives you full control over the visual display. You can toggle each ATR level's lines, labels, and background zones individually to avoid a cluttered chart and focus only on the levels that matter to your strategy.
HV-SMA DeltaHistorical Volatility with SMA Multiplier
Concept
This indicator acts as a "volatility explosion meter" for the market. Its core principle is to compare the current volatility with its historical average to detect moments when the market begins to "swing" with significantly more force.
The main components are as follows:
① Historical Volatility (HV) This line is an indicator of the current price volatility.
If this line moves higher, it means the price is swinging wildly (high volatility).
If this line is low, it means the price is calm or moving within a narrow range (low volatility).
② SMA x Multiplier This line functions as a "threshold" or "volatility resistance" level. It is calculated from the moving average of past volatility and then multiplied by an adjustable number (smaMultiplier) to create an upper band. In simple terms, this line tells us: "Normally, volatility should not exceed this level."
③ Difference (Histogram) This is the result of subtracting the Threshold Line (②) from the HV value (①).
Appear when the HV breaks above the threshold line. This signals that "volatility has now spiked significantly above its historical average."
Appear when the HV is still below the threshold line. This indicates that volatility remains at a normal or below-average level.
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How to Use
This indicator does not tell you the direction of the price. Instead, it indicates the "power" or "momentum" of the movement. Therefore, it should always be used in conjunction with other tools to confirm the direction.
① Look for "Volatility Breakout" signals.
② Use it to confirm the strength of a trend.
③ Use it for risk management.
You can try adjusting the smaLength and smaMultiplier values in the indicator's settings to fit the specific asset and timeframe you are trading. More volatile assets may require a higher Multiplier.
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หลักการทำงาน (Concept)
Indicator ตัวนี้เป็น "เครื่องวัดการระเบิดของความผันผวน" ในตลาด
โดยแกนหลักเป็นการเปรียบเทียบความผันผวนในปัจจุบันกับความผันผวนโดยเฉลี่ยในอดีต
เพื่อหาจังหวะที่ตลาดเริ่ม "เหวี่ยง" แรงขึ้นอย่างมีนัยสำคัญ
ส่วนประกอบหลักๆ มีดังนี้:
① Historical Volatility (HV)
เส้นนี้คือตัวชี้วัดความผันผวนของราคา ณ ปัจจุบัน
ถ้าเส้นนี้วิ่งขึ้นสูง แปลว่าราคากำลังแกว่งตัวรุนแรง (ผันผวนสูง)
ถ้าเส้นนี้อยู่ต่ำ แปลว่าราคานิ่งๆ หรือเคลื่อนไหวในกรอบแคบๆ (ผันผวนต่ำ)
② SMA x Multiplier
เส้นนี้ทำหน้าที่เป็น "เส้นเกณฑ์" หรือ "แนวต้านของความผันผวน"
ถูกคำนวณมาจากเส้นค่าเฉลี่ยของความผันผวนในอดีต
แล้วคูณด้วยตัวเลข Adjustable (sma-Multiplier) เพื่อสร้างเป็นกรอบบน
พูดง่ายๆ คือ เส้นนี้บอกเราว่า "โดยปกติแล้ว ความผันผวนไม่ควรจะเกินระดับนี้"
③ Difference (Histogram)
เป็นผลลัพธ์จากการนำค่า HV ข้อ ① มาลบกับ เส้นเกณฑ์ ข้อ ②
เกิดขึ้นเมื่อ HV ทะลุเส้นเกณฑ์ขึ้นไป
เป็นสัญญาณว่า ณ ตอนนี้ "ความผันผวนได้พุ่งสูงกว่าค่าเฉลี่ยในอดีตอย่างมีนัยสำคัญ"
เกิดขึ้นเมื่อ HV ยังอยู่ต่ำกว่าเส้นเกณฑ์
บอกว่าความผันผวนยังอยู่ในระดับปกติหรือต่ำกว่าค่าเฉลี่ย
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วิธีการนำไปใช้ (How to Use)
Indicator ตัวนี้ ไม่ได้บอกทิศทางของราคา
แต่จะบอก "พลัง" หรือ "โมเมนตัม" ของการเคลื่อนไหว
เราจึงควรใช้มันร่วมกับเครื่องมืออื่นเพื่อยืนยันทิศทางเสมอ
① มองหาสัญญาณ "การระเบิดของราคา" (Volatility Breakout)
② ใช้ยืนยันความแข็งแกร่งของเทรนด์
③ ใช้ในการบริหารความเสี่ยง
สามารถลองปรับค่า smaLength และ smaMultiplier ในการตั้งค่า Indicator
เพื่อให้เข้ากับสินทรัพย์และ Timeframe ที่เทรดได้นะ
สินทรัพย์ที่เหวี่ยงแรงๆ อาจต้องใช้ Multiplier ที่สูงขึ้น เป็นต้น
ADR - Average Daily Range [KasTrades]This is an Average Daily Range (ADR) indicator.
There are two settings for ADR:
Two Look back period ADR range (e.g. 7 and 14 days)
One Look back period ADR (e.g. 5 days only)
Two day ADR ranges are typically used in equities and index futures whereas one day ADR is typically used in forex.
The opening time by default is 17:00 New York (Eastern) time. The ranges are always calculated from the opening price of the first bar on the respected timeframe.
ADR [KasTrades]This ADR indicator has 2 options: a Range of ADR, such as 7 and 14 which is typically used for indexes, index futures and equities, or a single ADR such as a 5 day which is typically used for forex.
The session start time is 17:00 ET (NY Time) by default, this is adjustable.
You can adjust the ADR days to different ranges such as 5 and 10, or a single ADR day such as 7.
Colors of the ADR high and low are also adjustable.
Volatility Adjusted Relative Strength (VARS) - Histogram OptionI’ve developed a new version of VARS that includes an option to toggle it into a histogram view. I recommend using a single neutral color rather than the conventional “red below 0, green above 0” scheme — because true RS analysis shouldn’t rely on color cues. The focus should be on the immediacy and persistence of RS itself to capture that initial breakout move as the most optimal RRR entry. This also provides clearer insight and visualization into how RS functions (both traditional and VARS) since RS is a static EOD metric derived from a defined timeframe.
I want to emphasize again that VARS is useful to identify low-risk entries, with relative strength calibrated to the volatility of the reference index (in this case, AMEX:SPY ). It is not used to determine my exits — those should be governed by a strict, non-discretionary framework for partial profit-taking and final exit of a position.
First Passage Time - Distribution AnalysisThe First Passage Time (FPT) Distribution Analysis indicator is a sophisticated probabilistic tool that answers one of the most critical questions in trading: "How long will it take for price to reach my target, and what are the odds of getting there first?"
Unlike traditional technical indicators that focus on what might happen, this indicator tells you when it's likely to happen.
Mathematical Foundation: First Passage Time Theory
What is First Passage Time?
First Passage Time (FPT) is a concept in stochastic processes that measures the time it takes for a random process to reach a specific threshold for the first time. Originally developed in physics and mathematics, FPT has applications in:
Quantitative Finance: Option pricing, risk management, and algorithmic trading
Neuroscience: Modeling neural firing patterns
Biology: Population dynamics and disease spread
Engineering: Reliability analysis and failure prediction
The Mathematics Behind It
This indicator uses Geometric Brownian Motion (GBM), the same stochastic model used in the Black-Scholes option pricing formula:
dS = μS dt + σS dW
Where:
S = Asset price
μ = Drift (trend component)
σ = Volatility (uncertainty component)
dW = Wiener process (random walk)
Through Monte Carlo simulation, the indicator runs 1,000+ price path simulations to statistically determine:
When each threshold (+X% or -X%) is likely to be hit
Which threshold is hit first (directional bias)
How often each scenario occurs (probability distribution)
🎯 How This Indicator Works
Core Algorithm Workflow:
Calculate Historical Statistics
Measures recent price volatility (standard deviation of log returns)
Calculates drift (average directional movement)
Annualizes these metrics for meaningful comparison
Run Monte Carlo Simulations
Generates 1,000+ random price paths based on historical behavior
Tracks when each path hits the upside (+X%) or downside (-X%) threshold
Records which threshold was hit first in each simulation
Aggregate Statistical Results
Calculates percentile distributions (10th, 25th, 50th, 75th, 90th)
Computes "first hit" probabilities (upside vs downside)
Determines average and median time-to-target
Visual Representation
Displays thresholds as horizontal lines
Shows gradient risk zones (purple-to-blue)
Provides comprehensive statistics table
📈 Use Cases
1. Options Trading
Selling Options: Determine if your strike price is likely to be hit before expiration
Buying Options: Estimate probability of reaching profit targets within your time window
Time Decay Management: Compare expected time-to-target vs theta decay
Example: You're considering selling a 30-day call option 5% out of the money. The indicator shows there's a 72% chance price hits +5% within 12 days. This tells you the trade has high assignment risk.
2. Swing Trading
Entry Timing: Wait for higher probability setups when directional bias is strong
Target Setting: Use median time-to-target to set realistic profit expectations
Stop Loss Placement: Understand probability of hitting your stop before target
Example: The indicator shows 85% upside probability with median time of 3.2 days. You can confidently enter long positions with appropriate position sizing.
3. Risk Management
Position Sizing: Larger positions when probability heavily favors one direction
Portfolio Allocation: Reduce exposure when probabilities are near 50/50 (high uncertainty)
Hedge Timing: Know when to add protective positions based on downside probability
Example: Indicator shows 55% upside vs 45% downside—nearly neutral. This signals high uncertainty, suggesting reduced position size or wait for better setup.
4. Market Regime Detection
Trending Markets: High directional bias (70%+ one direction)
Range-bound Markets: Balanced probabilities (45-55% both directions)
Volatility Regimes: Compare actual vs theoretical minimum time
Example: Consistent 90%+ bullish bias across multiple timeframes confirms strong uptrend—stay long and avoid counter-trend trades.
First Hit Rate (Most Important!)
Shows which threshold is likely to be hit FIRST:
Upside %: Probability of hitting upside target before downside
Downside %: Probability of hitting downside target before upside
These always sum to 100%
⚠️ Warning: If you see "Low Hit Rate" warning, increase this parameter!
Advanced Parameters
Drift Mode
Allows you to explore different scenarios:
Historical: Uses actual recent trend (default—most realistic)
Zero (Neutral): Assumes no trend, only volatility (symmetric probabilities)
50% Reduced: Dampens trend effect (conservative scenario)
Use Case: Switch to "Zero (Neutral)" to see what happens in a pure volatility environment, useful for range-bound markets.
Distribution Type
Percentile: Shows 10%, 25%, 50%, 75%, 90% levels (recommended for most users)
Sigma: Shows standard deviation levels (1σ, 2σ)—useful for statistical analysis
⚠️ Important Limitations & Best Practices
Limitations
Assumes GBM: Real markets have fat tails, jumps, and regime changes not captured by GBM
Historical Parameters: Uses recent volatility/drift—may not predict regime shifts
No Fundamental Events: Cannot predict earnings, news, or macro shocks
Computational: Runs only on last bar—doesn't give historical signals
Remember: Probabilities are not certainties. Use this indicator as part of a comprehensive trading plan with proper risk management.
Created by: Henrique Centieiro. feedback is more than welcome!
Lakshmi - Vajra Energy Signal (VES)Vajra Energy Signal (VES) is an advanced volume analysis indicator that detects energy accumulated inside the market.
When assessing the strength of trading activity, conventional practice looks at the magnitude of volume; VES is designed with the understanding that the same volume can have different meanings depending on the price range.
VES analyzes the complex relationship between price movement and volume with a proprietary algorithm and can detect internal market activities that are invisible from surface‑level price action, visualizing the characteristic whereby the value rises before a breakout.
In other words, VES views the market as an “energy system.” In the energy accumulation phase, relatively high volume occurs relative to the price range, and in the energy release phase, the stored energy is emitted as high volatility in price, that is, a breakout—this is the core concept on which VES is established.
⚡️ Basic Demonstration
i.imgur.com
As you can see in the image above, VES simply displays the highs and lows of energy stored in the market as a thin line in a separate panel.
It is easy for traders to understand its intuitive patterns: it rises when hidden buying accumulation or selling activity continue and sink when a price breakout occurs. It can be applied across symbols and markets (stocks, commodities, cryptocurrencies, spot, and futures). While reducing clutter in price scale labels, it also supports dynamic autoscaling.
⚡️ Practical Usage
VES is expected to be used for the following purposes.
- Entry signal
When the VES value continues to rise—i.e., during energy accumulation—it can be considered on standby for a breakout. After a breakout, a trader can confirm the trend direction and enter.
- Exit signal
If the VES value rises during a trend, consider the possibility of a reversal and consider taking profits.
- Risk management
If the VES value remains elevated for a long period, regard it as increased market uncertainty and an approaching breakout; adopt a cautious trading strategy to prepare for higher volatility and adjust position size.
For example, in the BINANCE:SOLUSDT daily chart below, VES clearly shows how it functions in short‑term trading.
i.imgur.com
In September 2023, when the price was moving around 20 USDT, VES formed frequent small spikes. These early spikes suggest that market participants were still in a wait‑and‑see mode and that small‑scale accumulation was being conducted intermittently.
A decisive change came in early October 2023. While the price still stagnated in the 20–25 USDT range, VES suddenly formed a huge spike. The scale of this spike was far larger than those in September 2023, clearly suggesting that hidden substantial trading activities by large investors had begun.
In mid‑October 2023, the price began to rise. It climbed stepwise from 25 USDT to 40 USDT, then to 60 USDT and 75 USDT, and then surged to above 120 USDT within just a few weeks. This suggests that the energy built in the buy accumulation phase in early October 2023 was converted into price appreciation.
Therefore, after such a large VES signal is observed and the price breaks upward, entering a long position could have been profitable.
A large VES reaction is not only a quiet “buy signal” as in the example above; it can also be a “sell signal.” Such a case is explained below using an example on the BTC chart.
i.imgur.com
This BITSTAMP:BTCUSD 4‑hour chart is a valuable example showing how VES detects top formation on a short timeframe. In the first half of February 2024, the price moved in a relatively narrow 96,000–99,000 USD range. During this period, VES remained stable at low levels, and the market continued a calm uptrend.
The first sign appeared on February 16, 2024. While the price still held around 97,000 USD, VES formed a clearly identifiable small spike. This implied that some large investors had begun to take profits, or that new sellers had started to build short positions. However, at that point, the impact on price was limited, and many traders may have overlooked the signal.
The decisive turning point came on February 23, 2024. With the price moving around 98,000 USD, VES suddenly formed a huge spike. The scale of this spike was far larger than previous moves, clearly indicating that significant energy was accumulating.
Importantly, even at this moment the price still remained at the highs. On the surface, price barely moved and the bull trend appeared intact, but VES detected a major internal change underway.
On February 24, 2024, the price collapsed and began to fall. It dropped about 15% from 97,000 USD to 82,000 USD in a few days. The speed and magnitude of this decline corroborated the quiet “sell signal” indicated by the VES spikes.
The key lesson from this chart is that a VES spike does not necessarily mean buy accumulation. A large VES spike formed at high prices may instead indicate a distribution phase—that is, large investors exiting or building short positions. When the price is at elevated levels, a VES spike should be considered not only as a precursor to further upside but also as a warning of potential downside.
From a trading‑strategy perspective, the huge VES spike on February 23, 2024 was a clear signal to exit or to consider entering short positions. At that point, traders should have either closed long positions or to consider building a short position. The moment when price started to decline from its peak was exactly the entry timing for a short.
On the 4‑hour timeframe, changes in VES appear faster and more dramatically. While this allows more agile responses, the risk of false signals is also higher; therefore, confirmation on other timeframes and comprehensive judgment with price action are essential.
VES is a powerful tool for reading internal market activities, and this chart clearly shows that its interpretation requires flexibility that takes into account market conditions and price location.
⚡️ Parameter Settings
Strength 1: The lower the number, the more it emphasizes responses closer to the present timeframe; the higher the number, the more it emphasizes responses farther from the present timeframe. 5 is recommended.
Strength 2: The lower the number, the greater the volatility of the value; the higher the number, the smaller the volatility. 5 is recommended.
Scale: Adjusts the display scale. −30 is recommended.
⚡️ Conclusion
Vajra Energy Signal (VES) visualizes the cycle of energy accumulation in the market from the relative relationship between price range and volume, detecting hidden activities by market participants that conventional volume analysis cannot capture. VES serves as a powerful auxiliary tool for early detection of turning points, enabling deeper market understanding and more accurate timing decisions. As the examples show, there is a possibility of sensing major price movements in advance. When using VES, flexible interpretation according to market environment and price location is required, and it demonstrates its true value when combined with price action and other analysis methods such as support/resistance.
⚡️ Important Notes
- VES is a tool that infers internal market energy; it does not guarantee trades or suggest future results.
- We strongly recommend using it together with price action analysis and support/resistance.
- Confirmation across different timeframes improves reliability.
- Effectiveness may vary depending on market conditions and liquidity.
- Very illiquid instruments or newly listed assets may produce more noise.
⚡️ How to Get Access
This indicator is Public Invite‑Only. If you would like access, please apply by following the Author’s Instructions.
SMR - Simple Market Recap📊 Simple Market Recap (SMR)
🎯 A comprehensive market overview tool displaying price changes, percentage movements, and status indicators for multiple financial instruments across customizable timeframes with intelligent data synchronization.
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📋 OVERVIEW
The Simple Market Recap indicator provides a professional market analysis dashboard that displays key performance metrics for major financial instruments. This educational tool features intelligent asset selection, automatic dark mode detection, comprehensive period analysis with bilingual support, and advanced data synchronization ensuring accurate price data regardless of the current chart symbol.
Perfect for:
Market overview analysis and educational study
Multi-asset performance comparison and research
Weekly, daily, and monthly market recap visualization
Educational purposes and market trend analysis
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🚀 KEY FEATURES & ENHANCEMENTS
🌙 Intelligent Dark Mode Detection
Automatic chart background color analysis and adaptation
Dynamic color scheme adjustment for optimal visibility
Enhanced contrast ratios for both light and dark themes
Professional appearance across all chart backgrounds
📊 Comprehensive Asset Coverage
Major Forex Pairs: EURUSD, GBPUSD, AUDUSD, NZDUSD, USDCHF, USDJPY, USDCAD
Indices & Dollar: DXY (US Dollar Index), SPX (S&P 500)
Commodities: XAUUSD (Gold), USOIL (Crude Oil)
Bonds: US10Y (10-Year Treasury)
Cryptocurrencies: BTCUSDT, ETHUSDT
Selective asset display with individual on/off controls
Fixed asset order: DXY, EURUSD, GBPUSD, AUDUSD, NZDUSD, USDCHF, USDCAD, USDJPY, XAUUSD, USOIL, SPX, US10Y, ETHUSDT, BTCUSDT
⏰ Flexible Timeframe Analysis
Multiple Periods: Daily (1D), Weekly (1W), Monthly (1M)
Time Selection: Current Period or Previous Period analysis
Dynamic Titles: Automatic report naming with dates and periods
Historical Comparison: Compare current vs previous period performance
📈 Enhanced Data Visualization
Professional table with adaptive row count based on selected assets
Color-coded price movements: Enhanced green for positive, bright red for negative
Status emojis: ↗️ Up, ↘️ Down, ↔️ Sideways, ❓ No data
Smart price formatting based on asset type and price level
Improved contrast colors for better visibility in all lighting conditions
🔄 Advanced Data Synchronization
Symbol-Independent Accuracy: Correct data display regardless of current chart symbol
Real-Time Security Requests: Direct data fetching from specific instrument sources
Cross-Asset Reliability: Accurate price data for all monitored assets simultaneously
Data Integrity: No cross-contamination between different financial instruments
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🎨 PROFESSIONAL TABLE LAYOUT
Adaptive Design Features:
Automatic dark mode detection and color adaptation
Enhanced contrast ratios for better readability
Professional color scheme with clear data separation
Responsive design for all screen sizes and themes
Comprehensive Data Display:
Dynamic Title Row: Period-specific report titles with dates
Asset Column: Selected financial instruments
Open/Close Prices: Period opening and closing values
Change Percentage: Color-coded performance indicators
Pips Movement: Precise pip calculations for each asset
Status Indicators: Visual emoji representations of trend direction
Visual Design Features:
Merged title cells for clean header presentation
Asset-specific price formatting for optimal readability
Color-coded positive/negative movements
Professional table borders and spacing
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⚙️ ADVANCED CUSTOMIZATION
Timeframe Controls:
Report Period selection: Daily, Weekly, or Monthly analysis
Time Selection toggle: Current vs Previous period comparison
Dynamic row count based on active asset selection
Automatic title generation with period-specific formatting
Asset Selection:
Individual toggle controls for each supported asset
Major forex pairs with complete coverage
Cryptocurrency and precious metals options
Index and commodity instrument support
Display Options:
9 table positioning options across the entire chart
5 text size levels from Tiny to Huge for optimal visibility
Language selection between English and Vietnamese
Automatic theme adaptation for all chart backgrounds
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⚠️ EDUCATIONAL & ANALYTICAL PURPOSE
This indicator is designed exclusively for educational market analysis and research purposes .
📚 Educational Applications:
Understanding multi-asset market performance correlation
Studying period-based price movements and trends
Analyzing market volatility across different timeframes
Learning to read and interpret market recap data
📊 Analysis Capabilities:
Market overview visualization for educational study
Multi-timeframe performance comparison research
Historical period analysis and trend identification
Cross-asset correlation studies and market research
🚨 Important Disclaimer: This tool provides educational market data visualization only and does NOT generate trading signals or investment advice. All data is for learning and analysis purposes. Users must conduct independent research and consult financial professionals before making any investment decisions.
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🛠️ SETUP & CONFIGURATION
Quick Start Guide:
Add the indicator to your chart from the indicators library
Select your preferred language (English or Vietnamese)
Choose your desired reporting timeframe (Daily, Weekly, or Monthly)
Select Current Period or Previous Period for analysis
Toggle on/off specific assets you want to monitor
Adjust table position and text size for optimal viewing
Advanced Configuration:
Customize asset selection based on your analysis needs
Configure timeframe settings for different market studies
Set up language preferences for your region
Fine-tune display options for your screen setup
Optimize table positioning for your chart layout
Theme Optimization:
Indicator automatically detects your chart theme
Colors adapt automatically for optimal contrast and readability
No manual adjustments required for theme changes
Professional appearance maintained across all backgrounds
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🔧 TECHNICAL SPECIFICATIONS
Performance & Reliability:
Pine Script v6 with optimized data retrieval
Real-time updates with minimal CPU and memory usage
No repainting or lookahead bias in calculations
Stable performance across all timeframes and instruments
Universal Compatibility:
Works with all TradingView chart types and instruments
Compatible with mobile and desktop platforms
Supports all timeframes with period-specific analysis
Cross-platform functionality with consistent behavior
Data Precision:
High-precision floating-point calculations
Asset-specific formatting and pip calculations
Real-time price data from multiple exchanges
Accurate percentage and movement calculations
Advanced Features:
Automatic chart background detection and color adaptation
Dynamic table sizing based on active asset selection
Intelligent price formatting for different asset classes
Professional status indicators with emoji visualization
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📋 VERSION HISTORY
v1.7 - Enhanced Data Synchronization & Color Improvements
Fixed critical data synchronization issue - accurate data regardless of current chart symbol
Enhanced data retrieval system with symbol-specific security requests
Improved color scheme: brighter red for negative values, enhanced contrast
Fixed asset order: DXY, EURUSD, GBPUSD, AUDUSD, NZDUSD, USDCHF, USDCAD, USDJPY, XAUUSD, USOIL, SPX, US10Y, ETHUSDT, BTCUSDT
Optimized price formatting with proper decimal display and leading zeros
Enhanced calendar-based time calculations for accurate period reporting
Improved pip calculations for different asset classes
Professional color coding with adaptive contrast for all themes
Previous Versions:
v1.6 - Data accuracy improvements and bug fixes
v1.5 - Enhanced market analysis with flexible timeframes
v1.4 - Professional table layout and bilingual support
Earlier versions - Core market data display functionality development
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Author: tohaitrieu
Version: 1.7
Category: Market Analysis / Educational Overview
Language Support: English, Vietnamese
License: Educational Use Only
This indicator is provided exclusively for educational and analytical purposes to help users understand market overview concepts and multi-asset analysis. It features automatic theme adaptation, flexible timeframe analysis, enhanced data synchronization, and comprehensive market data visualization for the most accurate and informative educational experience. It does not provide trading signals or investment advice. Always conduct thorough research and consider professional guidance before making financial decisions.
Omega ATR Indicator📖 Introduction
The Ω ATR Indicator was created to provide a more complete and professional framework for volatility analysis than the classic Average True Range (ATR).
While the traditional ATR is a useful tool, it has limitations: it delivers a simple rolling average of volatility, but it does not adapt to market regimes, it does not highlight extreme events, and it often leaves the trader with incomplete information about risk.
The Ω ATR takes the same foundation and elevates it into a multi-dimensional volatility dashboard, adding statistical layers, adaptive calculations, and clear visual references that allow traders to interpret volatility in a way that is immediately actionable.
🔎 What makes it different from a standard ATR?
This indicator introduces several features beyond the classic formula:
True Range Core – plots the raw True Range (TR) for each bar, providing a direct, bar-by-bar view of volatility impulses.
Standard & Adjusted ATR – includes both the conventional ATR (smoothed average) and an Adjusted ATR that automatically corrects for extreme conditions by incorporating percentile rescaling.
Percentile Volatility Levels – dynamically calculated extreme thresholds (99.8%, 75%, 50%, 25%), plotted as dotted levels across the chart. These act as reference lines for “normal” vs. “abnormal” volatility, useful for spotting unusual price expansions or contractions.
Linear Regression Volatility Trend – overlays a regression line of volatility, showing whether the market is moving toward expansion (rising vol), contraction (falling vol), or stability.
Monetary Value Translation – the indicator converts volatility into points, ticks, and dollar values (based on the instrument’s point value). This allows futures traders and high-value instruments users to immediately see how much volatility is “worth” in cash terms.
Interactive Table Display – a real-time statistics table is displayed directly on the chart, showing:
SMA of ATR in $ and points
Percentile-based volatility range (VAR) in $ and points
Tick equivalences, for quick position sizing
⚡ How traders can use it
The Ω ATR Indicator is designed to be versatile, fitting both discretionary traders and systematic strategy developers.
Risk Management: ATR-based stop losses and position sizing are significantly improved by using the adjusted ATR and percentile thresholds. Traders can size their positions according to volatility regimes, not just raw averages.
Breakout & Exhaustion Detection: When TR or ATR values spike above the 99.8% or 95% percentile levels, this often corresponds to breakout conditions or volatility exhaustion — useful for breakout strategies, mean-reversion setups, and volatility fades.
Market Regime Identification: The regression line helps distinguish if volatility is rising (trending environment, larger swings expected) or compressing (range-bound environment, lower risk opportunities).
Multi-Asset Flexibility: Works equally well on equities, futures, crypto, and FX. Its point/tick/dollar conversion makes it especially powerful for futures traders who need to quantify risk precisely.
Scalping to Swing Trading: On lower timeframes, it acts as a micro-volatility detector; on higher timeframes, it functions as a strategic risk gauge for position management.
⚙️ Settings and Customization
Length: The ATR lookback period (default = 34).
Shorter lengths (14–21) for intraday traders who want fast response.
Longer lengths (34–55) for swing/position traders who want smoother readings.
AVG / ADJ AVG: Toggle to display the standard ATR or the adjusted ATR.
Volatility Levels: Enable/disable up to 4 percentile-based levels (1st = 25%, 2nd = 50%, 3rd = 75%, 4th = 99.8%). Recommended: keep 3 levels active for clarity.
Color Controls: All plots and levels are fully customizable to match your chart style.
Table Display: Positioned on the chart (default: middle-right) with key values updated in real time.
🧭 Best Practices for Use
Combine with Trend Tools: Volatility readings are most powerful when combined with trend filters or volume analysis. For example, a breakout with both high volatility and trend confirmation is stronger than either alone.
ATR Stops: Use the Adjusted ATR rather than the standard one when trailing stops in highly volatile instruments like crypto or Nasdaq futures, as it adapts to outlier spikes.
Dollar Risk Translation: Use the dollar-value outputs to predefine maximum acceptable risk per trade (e.g., “I only risk $250 per position”). This bridges volatility to portfolio risk management.
Event Monitoring: Around economic events or earnings, expect volatility spikes above higher percentile levels. The indicator makes these moves instantly visible.
📌 Summary
The Ω ATR Indicator is not just “another ATR.” It is a comprehensive volatility framework that transforms volatility from a simple statistic into an actionable trading signal.
By combining:
the classic ATR,
an adjusted ATR,
percentile extremes,
regression-based volatility trends,
and real-time dollar conversions,
…this tool allows traders to precisely understand, visualize, and act on volatility in ways that a standard ATR simply cannot provide.
Whether you are scalping intraday moves, swing trading equities, or managing futures positions, the Ω ATR equips you with a professional-grade volatility dashboard that clarifies risk, highlights opportunity, and adapts across all markets and timeframes.
👉 Designed and developed by OmegaTools for traders who demand precision, clarity, and adaptability in their volatility analysis.
MIT MACD • Filled/Hollow Momentum HistogramThe MIT MACD • Filled/Hollow Momentum Histogram is an enhanced version of the classic MACD.
- Dual-style histogram (filled for acceleration, hollow for deceleration).
- Customizable colors for bars, MACD/Signal lines, and background.
- Background highlight when the slow line crosses the zero-line.
- Fully adjustable parameters, keeping TradingView defaults.
此脚本是经典 MACD 的进阶版，支持实心/空心动能柱体，零轴背景高亮，参数与配色可自由调整，更直观捕捉趋势与动能变化。
Realized Volatility (StdDev of Returns, %)Realized Volatility (StdDev of Returns, %)
This indicator measures realized (historical) volatility by calculating the standard deviation of log returns over a user-defined lookback period. It helps traders and analysts observe how much the price has varied in the past, expressed as a percentage.
How it works:
Computes close-to-close logarithmic returns.
Calculates the standard deviation of these returns over the selected lookback window.
Provides three volatility measures:
Daily Volatility (%): Standard deviation over the chosen period.
Annualized Volatility (%): Scaled using the square root of the number of trading days per year (default = 250).
Horizon Volatility (%): Scaled to a custom horizon (default = 5 days, useful for short-term views).
Inputs:
Lookback Period: Number of bars used for volatility calculation.
Trading Days per Year: Used for annualizing volatility.
Horizon (days): Adjusts volatility to a shorter or longer time frame.
Notes:
This is a statistical measure of past volatility, not a forecasting tool.
If you change the scale to logarithmic, the indicator readibility improves.
It should be used for analysis in combination with other tools and not as a standalone signal.
Realized Volatility (StdDev of Returns, %)📌 Realized Volatility (StdDev of Returns, %)
This indicator measures realized volatility directly from price returns, instead of the common but misleading approach of calculating standard deviation around a moving average.
🔹 How it works:
Computes close-to-close log returns (the most common way volatility is measured in finance).
Calculates the standard deviation of these returns over a chosen lookback period (default = 200 bars).
Converts results into percentages for easier interpretation.
Provides three key volatility measures:
Daily Realized Vol (%) – raw standard deviation of returns.
Annualized Vol (%) – scaled by √250 trading days (market convention).
Horizon Vol (%) – volatility over a custom horizon (default = 5 days, i.e. weekly).
🔹 Why use this indicator?
Shows true realized volatility from historical returns.
More accurate than measuring deviation around a moving average.
Useful for traders analyzing risk, position sizing, and comparing realized vs implied volatility.
⚠️ Note:
It is best used on the Daily Chart!
By default, this uses log returns (which are additive and standard in quant finance).
If you prefer, you can easily switch to simple % returns in the code.
Volatility estimates depend on your chosen lookback length and may vary across timeframes.
Auto Fib V2Auto Fib V2 — Advanced Fibonacci Mapping Tool
Introduction
Auto Fib V2 is an advanced Fibonacci retracement indicator that automatically adapts to recent market ranges. Rather than manually drawing Fibonacci lines, this script dynamically maps them based on the most recent highs and lows, allowing traders to see the chart as if it were a "navigation map." Its primary purpose is to help identify potential buy and sell zones with greater clarity.
Key Concept
The script is built on a simple but powerful interpretation of Fibonacci retracement:
When the price moves below the 0.236 level, it suggests an oversold zone, where buyers may step in and market reversal potential increases.
When the price rises above the 0.764 level, it highlights an overbought zone, where sellers may become more active and risk of reversal grows.
Between these extremes, the Golden Pocket (0.382–0.618 zone) is highlighted as the area where institutional traders and algorithms often react. Historically, this is one of the most respected Fibonacci areas in technical analysis.
Features & Customization
Automatic Range Detection: The indicator automatically finds the recent high/low (based on user-defined lookback bars) and applies Fibonacci levels.
Flexible Direction Setting: Traders can use Auto Mode to let the script decide direction from price movement, or manually choose upward/downward mapping.
Multiple Levels Display: Beyond the standard levels, extra fractional retracements (0.146, 0.309, 0.441, etc.) are included for more precise mapping.
Golden Pocket Highlighting: Visually emphasizes the 0.382–0.618 retracement zone for quick recognition.
Custom Styles: Switch between line-based and dot-based plotting, with adjustable colors and transparency for improved readability.
Practical Use
Auto Fib V2 is not intended as a direct buy/sell signal generator, but as a contextual guide. Traders can use it to:
Confirm whether the current price area is closer to an overbought or oversold condition.
Combine it with oscillators (RSI, MACD) or trend indicators (EMA, ADX) to strengthen trading decisions.
Identify confluence zones where Fibonacci levels overlap with key supports/resistances.
Quickly adapt to market shifts without the need to redraw Fibonacci retracement lines repeatedly.
Why Use Auto Fib V2?
Manual Fibonacci drawing can be subjective, often depending on the swing points a trader chooses. Auto Fib V2 reduces that subjectivity by using consistent logic, creating a more systematic approach. For intraday traders, it provides rapid context to assess whether the market is stretched or balanced. For swing traders, it offers a map of reaction zones across higher timeframes.
Intelligent Trading SuiteIntelligent Trading Suite
“One script to rule them all.”
Overview
The Intelligent Trading Suite is a professional-grade decision system built in Pine Script. It is a unified engine—not a bundle of indicators—that combines adaptive pattern recognition, historical memory, and multi-context intelligence into one framework. Using a deep historical pattern database and integrating session dynamics, market calendars, holiday effects, and economic events, it filters noise and adapts to conditions. Core emphasis: precise pattern detection with target-price projection that remains stable as new candles print (mitigates target drift) and early detection of forming geometric patterns and divergences/hidden divergences.
Core Features
All-Timeframe Operation: Works across every TradingView timeframe—from 1m to 1W—without performance drift.
Pattern Recognition with Targets: Detects triangles, wedges, cup & handle, flags, and H&S; projects targets and stabilizes them against common drift as price evolves.
Early Signal Engine: Flags forming patterns and divergences before completion and notifies when prerequisites align.
Historical Pattern Intelligence: Stores and compares thousands of prior states (Hull, VWAP, RSI, MACD, SMA, CVD) to weight current conditions and calibrate confidence.
Context & Regime Awareness: Adjusts for volatility regimes, liquidity sessions, day-of-week bias, holidays, and macro events.
Unified Signal & Confidence: Fuses all streams into a single Overall signal with calibrated confidence levels (Weak / Neutral / Strong).
Visualization & Alerts
Compact Ultimate Intelligence Table showing each analytical pillar, plus the Overall signal, and an option to show them on the chart as well.
Alerts on table for: new pattern detection, divergence events, volatility shifts, and trend reversals.
Important Notes
-Free plan runtime: TradingView Free accounts may hit platform limits.
Fix: Open settings → switch Mode from Paid to Free → runs within Free limits.
-Heavy computation: The script is calculation- and data-intensive; initial runs can take time.
If a rare runtime error occurs, simply reload the page and continue.
Attributions
Hull Moving Average (Alan Hull)
VWAP (Volume Weighted Average Price)
RSI (Relative Strength Index, J. Welles Wilder Jr.)
MACD (Moving Average Convergence Divergence, Gerald Appel)
Black Flag ATR bands (Jose Azcarate)
Proprietary enhancements, target-stabilization logic, and the nuclear intelligence architecture are original research for this suite.
Compliance
Educational and analytical use only
No financial advice
Ad-free; aligned with TradingView House Rules
Proper attribution included
Access
To get access, please read the Author’s instructions on the script’s page.
Monthly Expected Move (IV + Realized)What it does
Overlays 1-month expected move bands on price using both forward-looking options data and backward-looking realized movement:
IV30 band — from your pasted 30-day implied vol (%)
Straddle band — from your pasted ATM ~30-DTE call+put total
HV band — from Historical Volatility computed on-chart
ATR band — from ATR% extrapolated to ~1 trading month
Use it to quickly answer: “How much could this stock move in ~1 month?” and “Is the market now pricing more/less movement than we’ve actually been getting?”
Inputs (quick)
Implied (forward-looking)
Use IV30 (%) — paste annualized IV30 from your options platform.
Use ATM 30-DTE Straddle — paste Call+Put total (per share) at the ATM strike, ~30 DTE.
Realized (backward-looking)
HV lookback (days) — default 21 (≈1 trading month).
ATR length — default 14.
Note: TradingView can’t fetch option data automatically. Paste the IV30 % or the straddle total you read from your broker (use Mark/mid prices).
How it’s calculated
IV band (±%) = IV30 × √(21/252) (annualized → ~1-month).
Straddle band (±%) = (ATM Call + Put) / Spot to that expiry (≈30 DTE).
HV band (±%) = stdev(log returns, N) × √252 × √(21/252).
ATR band (±%) = (ATR(len)/Close) × √21.
All bands are plotted as upper/lower envelopes around price, plus an on-chart readout of each ±% for quick scanning.
How to use it (at a glance)
IV/Straddle bands wider than HV/ATR → market expects bigger movement than recent actuals (possible catalyst/expansion).
All bands narrow → likely a low-mover; look elsewhere if you want action.
HV > IV → realized swings exceed current pricing (mean-reversion or vol bleed often follows).
Pro tips
For ATM straddle: pick the expiry closest to ~30 DTE, use the ATM strike (closest to spot), and add Call Mark + Put Mark (per share). If the exact ATM strike isn’t quoted, average the two neighboring strikes.
The simple straddle/spot heuristic can read slightly below the IV-derived 1σ; that’s normal.
Keep the chart on daily timeframe—the math assumes trading-day conventions (~252/yr, ~21/mo).
ATR Dynamische Candles 1.2 (by Droes)This script visualizes ATR values as candles to the right of the last candle at today's high and today's low.
ATR Daily Viz V30.0This script visualizes ATR values as candles to the right of the last candle at today's high and low.
This is the first version.
ATR Daily Viz V30.0This script visualizes ATR values as candles to the right of the last candle at today's high and low.
This is the first version.
Institutional HeatmapHeatmap Range - Volume Profile Visualization Indicator
What This Indicator Does
The Heatmap Range indicator provides a sophisticated volume profile visualization that displays price levels with the highest trading activity using color-coded heatmaps directly on your chart. Unlike traditional volume indicators, this tool shows WHERE the most significant trading occurred within specific price ranges over a customizable lookback period.
Advanced Volume Analysis
Volume-Weighted Price Levels: Calculates and displays up to 20 price levels based on actual trading volume
Customizable Time Period: Analyze volume distribution over 10-500 bars (default: 180 bars)
Smart Bin Sizing: Adjustable pip range (0.1-50 pips) for precise level identification
Peak Detection: Automatically identifies and centers display around highest volume areas
Visual Customization
3 Color Patterns:
Inverted Heat (Orange to Dark Red)
Inverted Cool (Orange to Dark Blue)
Inverted Purple (Light Pink to Dark Purple)
Transparency Control: 0-95% transparency for optimal chart readability
Adaptive Display: Shows most relevant levels centered around peak volume
Multi-Asset Support
Forex Pairs (EUR/USD, GBP/USD, etc.)
Precious Metals (Gold/XAUUSD, Silver/XAGUSD)
Futures (NQ, ES, YM, etc.)
Cryptocurrencies
Stock Indices
Customizable Parameters
Histogram Period (10-500, Default: 180) Bars to analyze for volume distribution
Bin Range (0.1-50 pips, Default: 5.0) Price range for each volume level
Color Pattern (1-3, Default: 1) Visual color scheme selection
Average Volume Period (10-200, Default: 100) Period for volume normalization
Max Display Levels (5-20, Default: 20) Maximum price levels to show
Transparency (0-95%, Default: 50%) Opacity of heatmap display
How to Use
For Day Traders
Identify key support/resistance levels based on actual volume
Spot high-probability reversal zones
Plan entries/exits around significant volume levels
For Swing Traders
Analyze longer-term volume distribution patterns
Identify major accumulation/distribution zones
Confirm breakout levels with volume validation
For Scalpers
Quick identification of intraday volume hotspots
Real-time volume level updates
Precise entry/exit timing around volume clusters
Visual Interpretation
Darker Colors: Higher volume concentration (stronger levels)
Lighter Colors: Lower volume concentration
Color Intensity: Directly correlates to volume strength at that price level
Level Positioning: Automatically centers around peak volume areas
Technical Specifications
Pine Script Version: v5
Chart Overlay: Yes
Max Bars Back: 1000
Performance Optimized: Limited to 200 bins for smooth operation
Real-time Updates: Dynamic calculation on each bar close
Getting Started
Add to Chart: Apply indicator to any supported timeframe
Adjust Period: Set histogram period based on your trading style
Choose Colors: Select color pattern that suits your chart theme
Fine-tune Levels: Adjust bin range and max levels for optimal display
Set Transparency: Balance visibility with chart clarity
Important Notes
Minimum Data Requirement: Needs at least 10 bars of history to function
Performance: Higher periods and smaller bin ranges require more processing
Volume Dependency: Most effective on instruments with consistent volume data
Timeframe Agnostic: Works on all timeframes from 1-minute to monthly
Status Information
The indicator includes a real-time information table showing:
Current settings (Period, Bin Range, Color Pattern, Transparency)
Indicator status (Active/Loading)
Disclaimer: This indicator is for educational and informational purposes only. Past performance does not guarantee future results. Always conduct your own analysis and risk management before making trading decisions.
Compatible with TradingView's Pine Script v5 | Optimized for all market conditions | Professional-grade volume analysis
