ADR Daily Range + Volatility + KZs — SMC/ICT (@PueblaATH)ADR Daily Range + Volatility + KZs — SMC/ICT (@PueblaATH) is a complete intraday context and volatility HUD that plots market opens, killzones, previous period highs/lows, and a dynamic ADR/volatility dashboard. It is built to give SMC/ICT traders an at-a-glance view of when and where price is moving: sessions, overlaps, ranges, and distance to key levels, all on a single clean overlay.
What the Indicator Does
Market Opens (Tokyo, London, New York)
Professional-grade session open lines with:
Individually configurable open times per session and timezone.
Infinite vertical lines or height-limited extensions (custom tick offsets).
Fully styled labels: size, alignment, auto-background, manual background, and vertical offset.
Killzones & Session Overlaps
Precision-timed shaded boxes for:
Tokyo Killzone
London Killzone
New York Killzone
London–New York Overlap
Previous Period Levels (PDH/PWH/PMH & PDL/PWL/PML)
Robust daily/weekly/monthly high/low engine:
Accurate Previous Day / Week / Month Highs & Lows (Europe/Madrid reference).
Line length modes: infinite, N bars, or end-of-day projection.
Per-level colors + labeled markers placed to the right of price with custom horizontal/vertical spacing.
Timeframe & Weekend Filters
Keep charts clean by hiding components based on:
Custom timeframe ranges (hide opens or killzones on HTFs).
Weekend filters for opens, killzones, and ADR/table.
Optional override to display the HUD table across all timeframes.
Session Comparison Table (Top-Right HUD)
A compact, institutional-style session dashboard comparing:
Tokyo, London, New York — current open vs previous session and previous day.
Bullish/Bearish state with color-coded logic (+ optional ▲/▼ arrows).
Optional Δ% change column relative to previous day’s open.
ADR / Volatility Panel (24h Rolling Window)
A powerful real-time volatility module providing:
True 24-hour rolling high–low range.
SMA-based ADR calculation with automatic bar-count safety limits.
ADR% expansion metric with two thresholds + blinking color logic for volatility extremes.
Directional bias vs price 24 hours ago (Bullish/Bearish).
Optional metrics: distance to PDH/PDL (in price units) and absolute H–L / ADR values.
How to Use It
Set each session’s open time and killzone window according to your broker or desired timezone alignment.
Enable or disable session opens and killzones to frame the trading windows you prioritize (e.g., LDN Killzone or NY session expansion).
Activate key previous period levels (PDH/PDL, PWH/PWL, PMH/PML) and tune the line-length mode and label spacing to match your workflow.
Use timeframe & weekend filters to keep higher-timeframe charts clean while maintaining precise intraday visibility on lower timeframes.
Monitor the session comparison table to understand directional behavior relative to previous sessions and previous day opens.
Watch the ADR panel to classify the day as compressed, normal, or expanded—and anticipate potential reversion or continuation.
Originality & Credits Disclaimer
This indicator is an original work by @PueblaATH , created specifically for the tool ADR Daily Range + Volatility + KZs — SMC/ICT (@PueblaATH) and distributed under the MPL 2.0 license.
While the concepts implemented—session opens, killzones, ADR, and previous highs/lows—are public and widely known in the trading community, this script introduces a uniquely integrated framework that combines:
Multi-timezone session scheduling with dynamic TF/weekend filtering.
A modular PDH/PWH/PMH + PDL/PWL/PML engine with versatile projection and labeling controls.
A precise 24-hour volatility model tied to an ADR panel with extension thresholds, blinking alerts, and distance-to-PD metrics.
A multi-session comparative table that unifies Tokyo, London, and New York open data in real time.
This work does not reuse or repackage code from other authors. Any future adaptations from public sources will always include full, transparent credit and documentation.
ボラティリティ
VWAP D/W/M + MA100 & EMA100 albanThis TradingView indicator displays three independent VWAPs (Volume Weighted Average Prices) along with MA100 (Simple Moving Average) and EMA100 (Exponential Moving Average) on the chart.
Key Features:
VWAP #1, VWAP #2, VWAP #3: Each VWAP can be configured independently with:
Source (hlc3, close, etc.)
Anchor period (Session, Week, Month, Quarter, Year, Decade, Century, Earnings, Dividends, Splits)
Offset
Option to hide on daily or higher timeframes
MA100: 100-period Simple Moving Average
EMA100: 100-period Exponential Moving Average
Purpose:
This script is ideal for traders who want to track multiple VWAP levels simultaneously while also monitoring the 100-period moving averages for trend analysis. It provides a clean setup without bands or fills, focusing solely on price averages.
Use Cases:
Identify intraday or multi-timeframe VWAP levels
Combine VWAP levels with MA100/EMA100 for support/resistance analysis
Analyze trend direction and momentum using moving averages
Adaptive Trend & Momentum [ATM] - All-in-One Confirmation Tired of Cluttered Charts and Conflicting Signals? This All-in-One Indicator is Your Solution.
The Adaptive Trend & Momentum (ATM) indicator is a powerful, next-generation trading tool designed to eliminate chart clutter and provide clear, high-conviction signals. Instead of using multiple conflicting indicators, the ATM system combines trend, momentum, and volatility into a single, cohesive, and adaptive framework. It automatically adjusts to changing market conditions, giving you a reliable edge in any environment.
This is not just another moving average crossover. It is a complete trading system that helps you identify the trend, confirm its strength, and time your entries with precision.
Key Features
•
Adaptive Moving Average (AMA): The core of the system. The AMA automatically adjusts its length based on market volatility (using the Average True Range). It becomes faster and more responsive in volatile markets to catch moves early, and smoother in calm markets to avoid noise and false signals.
•
Dynamic Volatility Bands: These bands expand and contract based on market volatility, providing a dynamic map of support and resistance. They are crucial for identifying pullback opportunities and setting effective stop-loss levels.
•
Integrated Momentum Oscillator: A smoothed RSI-based oscillator that runs in a separate pane. It is designed to confirm the signals from the main chart. The oscillator and its histogram are color-coded to show whether bullish or bearish momentum is in control, giving you an instant read on market strength.
•
Clear Consensus Signals: The ATM indicator provides four distinct, easy-to-read signals directly on your chart:
•
STRONG BUY: The highest-conviction signal, appearing when the trend is bullish, momentum is bullish, and the price has pulled back to a strategic entry zone near the AMA.
•
BUY: A standard confirmation signal when both trend and momentum are aligned to the upside.
•
STRONG SELL: The highest-conviction short signal, appearing when the trend is bearish, momentum is bearish, and the price has rallied to a strategic entry zone.
•
SELL: A standard confirmation signal when both trend and momentum are aligned to the downside.
•
Real-Time Dashboard: A convenient on-chart table that provides a complete overview of the market at a glance. It shows the current adaptive length, trend direction, momentum status, consensus signal, and volatility percentage, so you always know what the indicator is thinking.
How It Works: The Adaptive Engine
The magic of the ATM indicator lies in its adaptive engine. Traditional moving averages use a fixed length (e.g., 50-period MA), which can be too slow in a fast market or too sensitive in a choppy one. The ATM’s Adaptive Moving Average solves this by dynamically adjusting its calculation period in real-time:
When volatility increases, the AMA shortens its length to react more quickly to price changes. When volatility decreases, it lengthens its period to smooth out noise and prevent false signals.
This adaptive nature ensures that the indicator remains relevant and effective across different assets and timeframes, from scalping to swing trading.
How to Use This Indicator: A Simple Trading Strategy
The ATM indicator is designed for clarity and ease of use. Here is a basic framework for trading with it:
For Long (Buy) Positions:
1.
Identify the Trend: Wait for the Adaptive Moving Average (AMA) line to turn green, indicating a confirmed uptrend.
2.
Confirm with Momentum: Check that the momentum oscillator is above 50 and preferably rising, confirming bullish strength.
3.
Find Your Entry: The best entry is a "STRONG BUY" signal. This tells you that the price has pulled back to a value area within the uptrend, offering a high-probability entry. A standard "BUY" signal can also be used, but the conviction is higher on "STRONG" signals.
4.
Set Your Stop-Loss: A logical place for a stop-loss is just below the lower volatility band.
5.
Take Profit: Consider taking profits when an opposing "SELL" or "STRONG SELL" signal appears, or when the price reaches a key resistance level.
For Short (Sell) Positions:
1.
Identify the Trend: Wait for the Adaptive Moving Average (AMA) line to turn red, indicating a confirmed downtrend.
2.
Confirm with Momentum: Check that the momentum oscillator is below 50 and preferably falling, confirming bearish strength.
3.
Find Your Entry: The best entry is a "STRONG SELL" signal. This indicates the price has rallied to a resistance area within the downtrend, offering a prime shorting opportunity. A standard "SELL" signal can also be used.
4.
Set Your Stop-Loss: A logical place for a stop-loss is just above the upper volatility band.
5.
Take Profit: Consider taking profits when an opposing "BUY" or "STRONG BUY" signal appears, or when the price reaches a key support level.
Customization and Settings
The indicator is fully customizable to fit your trading style and the asset you are trading. You can adjust:
•
AMA Settings: Control the base length and the volatility multiplier to make the indicator more or less sensitive.
•
Momentum Settings: Adjust the RSI length and smoothing for the oscillator.
•
Volatility Bands: Change the multiplier to widen or narrow the bands.
•
Visuals: Toggle signals, labels, and the dashboard on or off, and customize all colors to your preference.
Summary
The Adaptive Trend & Momentum (ATM) indicator is more than just a tool; it is a complete system for making more confident trading decisions. By adapting to the market and combining trend, momentum, and volatility, it provides a clear, uncluttered, and powerful view of price action.
Add it to your chart today and experience the clarity of adaptive trading!
Disclaimer: This indicator is a tool for technical analysis and should not be considered financial advice. Trading involves risk, and you should always use proper risk management. Past performance is not indicative of future results. Practice on a demo account before trading with real capital.
Keywords: Adaptive, Moving Average, Trend, Momentum, Volatility, RSI, Bands, Signal, Confirmation, All-in-One, System, Strategy, ATR, Volatility, Dashboard, Alert
Long Term indicator for financial marketsIts the indicator that i have made for my friends following the learnings which i have learnt over the last few years for momentum traders
GEX / Gamma - SPX Indicator Description – GEX / Gamma (SPX)
This indicator allows you to manually plot your daily +GEX, TRANS-GEX, and –GEX levels on SPX and visualize how price reacts around key gamma zones.
You enter the three levels each morning, and the script automatically draws:
+GEX / TRANS / –GEX zones with an adjustable buffer
Clean labels (e.g., “+GEX: 6850”) pinned to the right side of the chart
Today-only candle coloring (green above TRANS-GEX, red below)
Zones extend from yesterday’s session through the current session, helping highlight areas where dealer hedging flows may influence volatility, compression, or acceleration.
How to Use
Add the indicator to any intraday SPX chart.
Open settings and enter your +GEX, TRANS-GEX, and –GEX levels for the day.
Adjust the buffer, colors, and label style as needed.
Watch how price behaves as it moves above or below TRANS-GEX and interacts with +/- GEX zones.
Best For
Intraday SPX / ES / SPY
Options traders
Volatility and gamma-aware strategies
Strategy Behind It (Tight Version)
GEX levels help identify where dealer hedging flows can influence SPX price behavior.
+GEX (Positive Gamma)
Market tends to stabilize here. Dealers hedge against price moves, creating mean-reversion and lower volatility.
TRANS-GEX (Transition Level)
Key pivot where gamma flips. Price crossing this level often signals a shift in volatility or intraday direction.
–GEX (Negative Gamma)
Market becomes more reactive. Dealers hedge with price, increasing volatility, momentum, and trend potential.
How traders use it:
Expect resistance or slowdown into +GEX
Watch for potential bottoming or increased volatility –GEX
Use TRANS-GEX as a bias line or trigger for intraday shifts
A move outside of either the +GEX or -GEX will likely result in some type of high volume move.
Accurate Sideways Market Detectorthis indicator is used to determine when the market is moving sideways
Swing Trade BUY/SELL + SCORING +COLOUR FIXBUY/SELL labels now appear with a score (1–3) next to them.
Color coding visually distinguishes signal strength:
BUY → 1 yellow, 2 light green, 3 dark green
SELL → 1 orange, 2 red, 3 burgundy
This allows you to instantly see the signal strength both numerically and visually.
VIX Calm vs Choppy (Bar Version, VIX High Threshold)This indicator tracks market stability by measuring how long the VIX stays below or above a chosen intraday threshold. Instead of looking at VIX closes, it uses VIX high, so even a brief intraday spike will flip the regime into “choppy.”
The tool builds a running clock of consecutive bars spent in each regime:
Calm regime: VIX high stays below the threshold
Choppy regime: VIX high hits or exceeds the threshold
Calm streaks plot as positive bars (light blue background).
Choppy streaks plot as negative bars (dark pink background).
This gives a clean picture of how long the market has been stable vs volatile — useful for trend traders, breakout traders, and anyone who watches risk-on/risk-off conditions. A table shows the current regime and streak length for quick reference.
RADAR Oscillator (Regime Adaptive Directional Analysis)RADAR (Regime Adaptive Directional Analysis)
This script is available by invitation only.
What is it?
The RADAR Oscillator is a multi-layered decision support oscillator designed to filter market noise and detect high-probability trend resumptions. It combines multiple analytical engines that analyze different aspects of the market (Structure, Momentum, Trend Strength, Rhythm) to eliminate the weaknesses of a single indicator. Final buy/sell signals are generated only when a consensus is reached between these engines.
This is not a "strategy," but a signal-generating oscillator. Therefore, it does not provide backtest results (profit/loss, drawdown, etc.) as seen in TradingView's strategy tester. Its purpose is to add clarity and accuracy to the investor's decision-making process.
What Does It Promise, and What Does It Not Promise?
• What Does It Promise:
o Clarity and Noise Filtering: Aims to significantly reduce misleading signals in sideways and unstable markets.
o High-Probability Setup Detection: Thanks to its multiple confirmation mechanism, it generates signals only during strong and distinct market conditions.
o Adaptation to Market Conditions: It offers the ability to automatically adjust the analysis method based on the market's current "regime" (trend or sideways).
• What It Doesn't Promise:
o Guaranteed Profit: No financial instrument can guarantee future profits. RADAR is a probability-enhancing tool, not a magic formula.
o Automatic Wealth: Successful use requires proper risk management, market experience, and user discipline.
o Backtest Results: Because it is an oscillator, it does not provide historical performance metrics. Its value should be measured by its effectiveness in real-time market analysis.
Which Well-Known Indicators Are Used For What Purpose?
While RADAR creates a unique decision-making mechanism, it utilizes the fundamental building blocks of technical analysis. However, these indicators are never used directly to generate signals; instead, they serve as data sources and filters for our unique algorithm.
• ADX and DMI: Used to measure the strength and directional dominance of a trend. RADAR uses this data as a filter to confirm only the existence of a sufficiently strong trend.
• Moving Averages (EMA and SMA): Used as primary inputs to smooth price data and determine overall direction. Their outputs are processed in the consensus engine along with other filters.
• ATR (Average True Range): Does not directly generate signals, but measures market volatility. This data forms the basis of the oscillator's dynamic volatility smoothing engine, helping to adjust risk to market conditions.
Original Methodology and Proprietary Logic
This algorithm is not based on any open-source strategy code. The author's unique methodology combines multi-filter consensus, adaptive thresholding, statistical noise filtering, and market structure-based execution logic. Specifically, the oscillator's ability to analyze market characteristics (trending or sideways) and automatically adjust filtering multipliers accordingly forms the basis of its trading value. This combination is the author's original work, and preserving the source code is preferred.
What Problems Does It Solve?
Problem 1: Misleading Signals and Market Noise
o RADAR Solution: Consensus-Based Decision Mechanism. RADAR never relies on a single signal. No signal is generated unless the different analytical engines agree on the same direction. This filters out market noise, ensuring only high-probability signals are processed.
Problem 2: Static Analysis and Changing Market Conditions
o RADAR Solution: Adaptive Regime Shifting. The Oscillator actively analyzes whether the market is in "Trend Mode" or "Sideways Mode" using its proprietary market character analysis engine. It adapts to conditions like a chameleon, automatically adjusting signal generation rules and filter sensitivity according to the current regime.
Problem 3: Fixed Parameters and Declining Performance
o RADAR Solution: Full Adaptation Principle. To reduce reliance on fixed settings, it dynamically adjusts analysis speed and filter sensitivity based on the market's natural rhythm and volatility.
Automation Ready: Customizable Webhook Alerts
RADAR is more than just a visual analysis tool; it's designed to work seamlessly with full automation systems.
The oscillator generates alert messages in fully configurable JSON format for buy (long) and sell (short) signals. This feature allows you to easily connect RADAR signals to popular automation platforms like 3Commas, PineConnector, Tickeron, or your own custom bots. This allows you to execute your strategy 24/7 without manual intervention.
Why Released "By Invitation Only"?
• Protecting Proprietary Intellectual Property: RADAR is the product of hundreds of hours of research and development. Its consensus logic, regime detection, and engine integration are unique. Opening the source code would instantly destroy this intellectual property and competitive advantage.
• Maintaining Performance Integrity: Uncontrolled distribution can lead to misuse or theft and resale of signals by malicious actors. The invitation model protects the integrity of the oscillator.
• Business Model and Support: RADAR is a premium analysis tool. Access by invitation reflects its value and compensates the developer for ongoing maintenance, support, and future improvements.
____________________________
This indicator is for educational purposes only. Past performance does not guarantee future results. Always practice appropriate risk management and protect your capital.
DAO - Demand Advanced Oscillator# DAO - Demand Advanced Oscillator
## 📊 Overview
DAO (Demand Advanced Oscillator) is a powerful momentum oscillator that measures buying and selling pressure by analyzing consecutive high-low relationships. It helps identify market extremes, divergences, and potential trend reversals.
**Values range from 0 to 1:**
- **Above 0.70** = Overbought (potential reversal down)
- **Below 0.30** = Oversold (potential reversal up)
- **0.30 - 0.70** = Neutral zone
---
## ✨ Key Features
✅ **Automatic Divergence Detection**
- Bullish divergences (price lower low + DAO higher low)
- Bearish divergences (price higher high + DAO lower high)
- Visual lines connecting divergence points
✅ **Multi-Timeframe Analysis**
- View higher timeframe DAO on current chart
- Perfect for trend alignment strategies
✅ **Signal Line (EMA)**
- Customizable EMA for trend confirmation
- Crossover signals for momentum shifts
✅ **Real-Time Statistics Dashboard**
- Current DAO value
- Market status (Overbought/Oversold/Neutral)
- Trend direction indicator
✅ **Complete Alert System**
- Overbought/Oversold signals
- Bullish/Bearish divergences
- Signal line crosses
- Level crosses
✅ **Fully Customizable**
- Adjustable periods and levels
- Customizable colors and zones
- Toggle features on/off
---
## 📈 Trading Signals
### 1. Divergences (Most Powerful)
**Bullish Divergence:**
- Price makes lower low
- DAO makes higher low
- Signal: Strong reversal up likely
**Bearish Divergence:**
- Price makes higher high
- DAO makes lower high
- Signal: Strong reversal down likely
### 2. Overbought/Oversold
**Overbought (>0.70):**
- Market may be overextended
- Consider taking profits or looking for shorts
- Can remain overbought in strong trends
**Oversold (<0.30):**
- Market may be oversold
- Consider buying opportunities
- Can remain oversold in strong downtrends
### 3. Signal Line Crossovers
**Bullish Cross:**
- DAO crosses above signal line
- Momentum turning positive
**Bearish Cross:**
- DAO crosses below signal line
- Momentum turning negative
### 4. Level Crosses
**Cross Above 0.30:** Exiting oversold zone (potential uptrend)
**Cross Below 0.70:** Exiting overbought zone (potential downtrend)
---
## ⚙️ Default Settings
📊 Oscillator Period: 14
Number of bars for calculation
📈 Signal Line Period: 9
EMA period for signal line
🔴 Overbought Level: 0.70
Upper threshold
🟢 Oversold Level: 0.30
Lower threshold
🎯 Divergence Detection: ON
Auto divergence identification
⏰ Multi-Timeframe: OFF
Higher TF overlay (optional)
All parameters are fully customizable!
---
## 🔔 Alerts
Six pre-configured alerts available:
1. DAO Overbought
2. DAO Oversold
3. DAO Bullish Divergence
4. DAO Bearish Divergence
5. DAO Signal Cross Up
6. DAO Signal Cross Down
**Setup:** Right-click indicator → Add Alert → Choose condition
---
## 💡 How to Use
### Best Practices:
✅ Focus on divergences (strongest signals)
✅ Combine with support/resistance levels
✅ Use multiple timeframes for confirmation
✅ Wait for price action confirmation
✅ Practice proper risk management
### Avoid:
❌ Trading on indicator alone
❌ Fighting strong trends
❌ Ignoring market context
❌ Overtrading
### Recommended Settings by Trading Style:
**Day Trading:** Period 7-10, All alerts ON
**Swing Trading:** Period 14-21, Divergence alerts
**Scalping:** Period 5-7, Signal crosses
**Position Trading:** Period 21-30, Weekly/Daily TF
---
## 🌍 Markets & Timeframes
**Works on all markets:**
- Forex (all pairs)
- Stocks (all exchanges)
- Cryptocurrencies
- Commodities
- Indices
- Futures
**Works on all timeframes:** 1m to Monthly
---
## 📊 How It Works
DAO calculates the ratio of buying pressure to total market pressure:
1. **Calculate Buying Pressure (DemandMax):**
- If current high > previous high: DemandMax = difference
- Otherwise: DemandMax = 0
2. **Calculate Selling Pressure (DemandMin):**
- If previous low > current low: DemandMin = difference
- Otherwise: DemandMin = 0
3. **Apply Smoothing:**
- Calculate SMA of DemandMax over N periods
- Calculate SMA of DemandMin over N periods
4. **Final Formula:**
```
DAO = SMA(DemandMax) / (SMA(DemandMax) + SMA(DemandMin))
```
This produces a normalized value (0-1) representing market demand strength.
---
## 🎯 Trading Strategies
### Strategy 1: Divergence Trading
- Wait for divergence label
- Confirm at support/resistance
- Enter on confirming candle
- Stop loss beyond recent swing
- Target: opposite level or 0.50
### Strategy 2: Overbought/Oversold
- Best for ranging markets
- Wait for extreme readings
- Enter on reversal from extremes
- Target: middle line (0.50)
### Strategy 3: Trend Following
- Identify trend direction first
- Use DAO to time entries in trend direction only
- Enter on pullbacks to oversold (uptrend) or overbought (downtrend)
- Trade with the trend
### Strategy 4: Multi-Timeframe
- Enable MTF feature
- Trade only when both timeframes align
- Higher TF = trend direction
- Lower TF = precise entry
---
## 📂 Category
**Primary:** Oscillators
**Secondary:** Statistics, Volatility, Momentum
---
## 🏷️ Tags
dao, oscillator, momentum, overbought-oversold, divergence, reversal, demand-indicator, price-exhaustion, statistics, volatility, forex, stocks, crypto, multi-timeframe, technical-analysis
---
## ⚠️ Disclaimer
**This indicator is for educational purposes only.** It does not constitute financial advice. Trading involves substantial risk of loss. Always conduct your own research, use proper risk management, and consult with financial professionals before making trading decisions. Past performance does not guarantee future results.
---
## 📄 License
Open source - Free to use for personal trading, modify as needed, and share with attribution.
---
**Version:** 1.0
**Status:** Production Ready ✅
**Pine Script:** v5
**Trademark-Free:** 100% Safe to Publish
---
*Made with 💙 for traders worldwide*
PDH/PDL Breakout Reversal [Invite-Only]Detects daily breakout reversals based on Previous Day High/Low structure.
Ideal for intraday reversals and continuation entries with built-in SL/TP visualization.
Average Daily Range DashboardThis script displays a non-intrusive ADR (Average Daily Range) dashboard designed to assist traders in monitoring real-time range expansion throughout the trading session. It compares the current day's high-low range to the average daily range calculated over a user-defined number of previous completed days (default: 5).
The tool provides a numerical ADR score (0–5) based on how much of the average daily range has been filled. It also includes optional visual cues and narrative descriptions to help contextualize current price behavior.
📘 Key Features:
Calculates ADR using fully completed daily bars (excluding the current session)
Tracks the current session’s intraday range live (high to low)
Outputs a score from 0 (low range expansion) to 5 (ADR fully filled or exceeded)
Optional alerts when ADR thresholds are crossed (e.g., 60%, 100%)
Displays optional debug values: ADR value, today’s range, session high/low
Customizable table position, size, colors, and visibility settings
🧮 Formula Transparency:
ADR = Simple Moving Average of (Daily High - Low) over the last N completed days
Intraday Range = Real-time (Session High - Session Low)
ADR Score is derived by comparing current range to ADR:
score = floor((sessionRange / adr) * 5), capped at 5
⚠️ Disclaimer:
This tool does not provide buy/sell signals, trading advice, or predictive forecasts. It is intended for educational and informational purposes only. Users should independently verify all data and apply their own analysis. Past performance of any range behavior is not indicative of future results.
Adaptive Momentum Pressure (AMP)🔹 Adaptive Momentum Pressure (AMP)
A hybrid momentum oscillator that adapts to volatility and trend dynamics.
AMP measures the rate of change of price pressure and automatically adjusts its sensitivity based on market volatility.
It reacts faster in trending markets and smooths out noise during consolidation — helping traders identify genuine momentum shifts early while avoiding whipsaws.
🧠 Core Concept
AMP fuses three elements into one adaptive momentum model:
Normalized Momentum (ROC) – captures directional acceleration of price.
Adaptive Smoothing – the smoothing length dynamically contracts when volatility rises and expands when it falls.
Directional Bias – derived from the short-term EMA slope to weight momentum toward the prevailing trend.
Combined, these form a pressure value oscillating between –100 and +100, revealing when momentum expands or fades.
⚙️ How It Works
Calculates a normalized rate of change (ROC) relative to recent volatility.
Adjusts its effective length using the ATR — more volatile periods shorten the lookback for quicker reaction.
Applies a custom EMA that adapts in real time.
Modulates momentum by a normalized EMA slope (“trend bias”).
Produces a smoothed AMP line with a Signal line and crossover markers.
🔍 How to Read It
Green AMP line rising above Signal → Building bullish momentum.
Red AMP line falling below Signal → Fading or bearish momentum.
White Signal line = smoothed confirmation of trend energy.
Green dots = early bullish crossovers.
Red dots = early bearish crossovers.
Typical interpretations:
AMP crossing above 0 from below → early bullish impulse.
AMP peaking near +50–100 and curling down → potential momentum exhaustion.
Crosses below 0 with red pressure → bearish confirmation.
⚡ Advantages
✅ Adaptive across all markets and timeframes
✅ Built-in trend bias filters false signals
✅ Reacts earlier than RSI/MACD while reducing noise
✅ No manual retuning required
🧩 Suggested Use
Combine with structure or volume tools to confirm breakouts.
Works well as a momentum confirmation filter for entries/exits.
Optimal display: separate oscillator pane (not overlay).
Use it responsibly — AMP is an analytical tool, not financial advice.
Adaptive SuperTrend - Multi-Method# 📊 Adaptive SuperTrend - Multi-Method with Advanced Analytics
## 🎯 Overview
The **Adaptive SuperTrend - Multi-Method** is a sophisticated trading indicator that enhances the traditional SuperTrend by dynamically adjusting its parameters based on market conditions. Unlike static SuperTrend indicators, this version adapts to volatility changes, providing more reliable signals across different market regimes.
## ✨ Key Features
### 🤖 7 Adaptive Methods
Choose from multiple adaptation strategies or use the powerful Hybrid mode that combines all methods:
1. **Percentile-Based Adaptation**
- Adjusts multiplier based on ATR percentile ranking
- Tightens during extreme volatility, widens during calm periods
- Lookback: 100 bars (customizable)
2. **Volatility Regime Classification**
- Categorizes market into Low/Normal/High volatility regimes
- Applies different multipliers for each regime
- Default: Low=4.0x, Normal=2.5x, High=1.5x
3. **Z-Score Normalization**
- Uses statistical Z-score to normalize ATR
- Adapts to volatility outliers intelligently
- Sensitivity: 0.3 (adjustable)
4. **Dynamic Period Adjustment**
- Blends short and long ATR periods based on volatility
- Responsive in volatile markets, stable in calm markets
- Period range: 7-20 bars
5. **Rate of Change Method**
- Adjusts based on ATR's rate of change
- Detects accelerating/decelerating volatility
- Lookback: 20 bars
6. **Multi-Timeframe Comparison**
- Compares current timeframe ATR with higher timeframe
- Provides macro-context awareness
- Default HTF: Daily
7. **Hybrid Approach** ⭐ RECOMMENDED
- Combines all 6 methods with equal weighting
- Smoothed with EMA for stability
- Best overall performance
### 📈 Professional Statistics Panel
A comprehensive performance tracking panel with ML Fusion-inspired color scheme:
**Features:**
- 💼 **Current Position**: Live LONG/SHORT status with entry price
- 📊 **Total Points**: Cumulative P&L for selected period (default: 60 days)
- 💰 **Current P&L**: Unrealized profit/loss with percentage
- 🟢 **Long Stats**: Separate tracking for long trades
- 🔴 **Short Stats**: Separate tracking for short trades
- 📈 **Averages**: Average points per trade (overall, long, short)
- 📅 **Date Range**: Start and end dates of tracking period
**Customizable Options:**
- Lookback period: 1-365 days (default: 60 days)
- Table position: Top Left/Right, Bottom Left/Right
- Toggle date range display on/off
### 🎨 Visual Features
- **Color-Coded Signals**: Clear buy (green) and sell (red) markers
- **Trend Background**: Subtle background coloring for trend direction
- **SuperTrend Line**: Dynamic color based on current trend
- **Price Fill**: Shaded area between price and SuperTrend
- **Vibrant Colors**: Professional Material Design color palette
### 📊 Information Panel
Real-time display of:
- Active adaptation method
- Current ATR value
- ATR percentile ranking
- Active multiplier vs base multiplier
- Volatility regime (Low/Normal/High)
- ATR Z-Score
- Current trend direction
## 🔧 How to Use
### Quick Start
1. Add indicator to your chart
2. Choose adaptation method (start with "Hybrid")
3. Monitor the statistics panel for performance
4. Use signals for entry/exit points
### Recommended Settings
**For Intraday Trading:**
- Method: Hybrid or Dynamic Period
- Base ATR Period: 10
- Base Multiplier: 2.5-3.0
- P&L Tracking: 30 days
**For Swing Trading:**
- Method: Hybrid or Multi-Timeframe
- Base ATR Period: 14
- Base Multiplier: 3.0-4.0
- P&L Tracking: 90 days
**For Scalping:**
- Method: Rate of Change or Z-Score
- Base ATR Period: 7
- Base Multiplier: 2.0-2.5
- P&L Tracking: 7-14 days
### Signal Interpretation
✅ **BUY Signal**: Triangle up below bar
- Enter long position
- Place stop loss below SuperTrend line
❌ **SELL Signal**: Triangle down above bar
- Exit long / Enter short position
- Place stop loss above SuperTrend line
## ⚙️ Input Parameters
### Basic Settings
- **Base ATR Period**: Default 10 (1-50)
- **Base Multiplier**: Default 3.0 (0.1-10.0)
### Method-Specific Settings
Each of the 7 methods has its own customizable parameters for fine-tuning.
### Display Settings
- **Show Volatility Regime**: Toggle regime display
- **Show ATR Info Panel**: Toggle information panel
- **Show Statistics Panel**: Toggle performance stats
- **Stats Table Position**: Choose corner placement
- **P&L Tracking Period**: 1-365 days (default: 60)
- **Show P&L Date Range**: Toggle date range display
- **Bullish Color**: Customize trend-up color
- **Bearish Color**: Customize trend-down color
## 📊 Statistics Tracking
The indicator automatically tracks:
- **Entry Points**: Recorded on every trend change
- **Exit Points**: Calculated on opposite signal
- **Points Gained/Lost**: Per trade and cumulative
- **Long vs Short Performance**: Separate analytics
- **Trade Count**: Total, long, and short trades
- **Average Performance**: Overall and per direction
- **Time-Based Filtering**: Only shows trades within lookback period
## 🎯 Advantages Over Standard SuperTrend
1. **Adaptive to Market Conditions**: No more whipsaws in ranging markets or missed trends in volatile markets
2. **Multiple Adaptation Strategies**: Choose the method that fits your market and timeframe
3. **Comprehensive Analytics**: Track your performance with detailed statistics
4. **Professional Presentation**: Clean, organized display with Material Design colors
5. **Flexible Configuration**: Highly customizable for any trading style
6. **Real-Time Monitoring**: Live P&L tracking and performance metrics
## 🔔 Alerts
Built-in alert conditions for:
- Buy Signal (trend change to bullish)
- Sell Signal (trend change to bearish)
- Trend Change (any direction change)
Set up TradingView alerts to get notified on your phone or email when signals occur.
## 💡 Pro Tips
1. **Combine with Volume**: Use with volume indicators for confirmation
2. **Multiple Timeframes**: Add on multiple timeframes for confluence
3. **Risk Management**: Always use stop losses at SuperTrend line
4. **Backtest First**: Test on historical data before live trading
5. **Monitor Statistics**: Track your win rate and average gains
6. **Adjust for Market**: Switch methods based on market conditions
7. **Use Hybrid Mode**: When unsure, Hybrid mode provides balanced adaptation
## 📝 Version Notes
**Version 1.0**
- 7 adaptive methods with Hybrid mode
- Professional statistics panel with P&L tracking
- Configurable lookback period (1-365 days)
- Date range display
- Material Design color scheme
- Real-time performance analytics
- Multiple table position options
## ⚠️ Disclaimer
This indicator is for educational and informational purposes only. It should not be considered as financial advice. Always do your own research and consider consulting with a financial advisor before making trading decisions. Past performance does not guarantee future results.
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**Happy Trading! 🚀📈**
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## 🏷️ Tags
#SuperTrend #Adaptive #Volatility #TrendFollowing #ATR #Statistics #Analytics #PnL #Trading #Technical #Indicators #MultiMethod #Swing #Intraday #Scalping #RiskManagement
Average True Range Stop Loss Finder [MasterYodi]This indicator utilizes the Average True Range (ATR) to help traders identify optimal stop-loss levels that reduce the risk of premature exits caused by market volatility or tight stop placements. The default multiplier is set to 1.5, providing a balanced stop-loss buffer. For more conservative setups, a multiplier of 2 is recommended; for tighter risk management, use 1.
ATR values and corresponding stop-loss levels are displayed in a table at the bottom of the chart.
Use the high-based (red) level for short positions
Use the low-based (teal) level for long positions
Market Echo Screener [BigBeluga]
The Market Echo Screener is a structured multi-asset dashboard capable of tracking up to 15 symbols simultaneously .
Designed to condense complex market data into an actionable format. Each column represents a specialized calculation, giving traders insight into signals, phases, retests, and volatility — all updated in real time.
For each symbol, it displays a full set of analytics: trend signals, take profit progression, wave structure, equilibrium pulls, volatility-adjusted flows, smart band retests, volatility regimes, and live price context — all condensed into one unified table.
Instead of flipping through multiple charts, traders get an instant overview of market dynamics across an entire watchlist, making it easier to spot alignment and high-probability opportunities.
⬤ Trend Signals
This column is powered by a low-pass digital trend filter that smooths short-term fluctuations and isolates directional momentum.
It produces Buy and Sell signals when price crosses adaptive thresholds relative to the smoothed baseline. Stronger “＋” signals appear when slope acceleration or momentum divergence confirms additional conviction.
• Uses recursive filtering to eliminate noise.
• Signal strength is determined by the magnitude of deviation from the baseline.
• Tracks how many bars back the signal occurred, using a bar-counting algorithm.
• Combines both normal and power signals to reflect phases of market conviction.
⬤ TPs (Take Profits)
The take profit ladder is generated through an adaptive volatility-projection model .
When a signal fires, projected levels are based on volatility-weighted extensions. Each level (TP1–TP6) represents an incrementally wider confidence band, dynamically recalculated with every new bar.
• Uses volatility-normalized ranges for TP distances.
• Level activation is sequential, progressing as price reaches thresholds.
• Reset occurs when opposite signals are detected.
• Higher TPs imply extended momentum runs, while early TP triggers highlight conservative exits.
⬤ ActionWave
The ActionWave column applies a dual-smoothing algorithm combining custom MA stacks and polynomial regression to capture the underlying wave structure.
It identifies macro phases (Bullish ∆ / Bearish ∇) and flags retests when price folds back into the average after expansion.
• Wave slope is calculated using gradient differentials.
• Retests are confirmed within a bar-window threshold (e.g., 20–25 bars).
• Distinguishes continuation from exhaustion by analyzing whether slope remains positive/negative.
• Provides a clean map of trend rhythm without intrabar noise.
⬤ Magnet
The Magnet measure calculates a dynamic equilibrium band around price.
By averaging the midpoints of recent high–low ranges and weighting them by volatility, it defines a “fair zone” where price tends to trend and mean-revert.
• Bullish/Bearish status is derived from price position relative to the equilibrium mean.
• Retests occur when price leaves the zone and then re-enters within a tolerance band.
• Incorporates a mean-reversion index to highlight strength of pull.
• Acts as a gravitational anchor, showing when price is likely to snap back.
⬤ FlowTrend
FlowTrend is calculated using volatility and noise adjusted envelope bands .
It determines the active market flow by testing whether price consistently holds above or below the smoothed envelope. Retests are logged when price touches the envelope and respects trend direction.
• Bands expand/contract based on ATR and rolling variance.
• Flow state = Bullish if closing above upper envelope, Bearish if below.
• Retests validated only if trend slope and band alignment remain intact.
• Helps identify continuation setups by filtering false flips.
⬤ Smart Bands
Smart Bands employ an adaptive trailing stop framework that shifts with volatility and momentum.
Price interaction with these bands is tracked for bullish (∆) or bearish (∇) retests, highlighting whether the current move has revalidated at its volatility boundary.
• Bands derived from trailing volatility-adjusted stops.
• Upward retest fires when price tests support bands during uptrend.
• Downward retest occurs when resistance bands are tapped in downtrend.
• Provides structured “confirmation points” that validate signals.
⬤ Volatility
Volatility is measured via a hybrid standard deviation logic .
First, the standard deviation of closing prices over 10 bars is scaled by a factor, then normalized against its own 20-bar rolling standard deviation. The result is converted into a 0–100 index, producing three regimes:
❄️ Calm (<50): low dispersion, mean-reversion conditions dominate.
⚠️ Elevated (50–70): directional expansion likely, watch for breakout tension.
💥 Explosive (>70): strong dispersion, trend-following setups favored.
• Uses layered smoothing to dampen noise.
• Normalization ensures comparability across different assets.
• Acts as a meta-filter for selecting strategy type (range vs. momentum).
⬤ Price
The price column displays the latest close rounded to the nearest tick size.
It is color-coded by candle bias: green for bullish closes, red for bearish closes.
• Tick normalization ensures clean display across assets with different decimal precision.
• Color-coding gives instant sentiment context.
• Serves as the anchor reference for all other metrics in the row.
The Market Echo Screener is not a simple signal table — it’s a layered analytics framework.
Each column is driven by technical calculations: smoothing filters, volatility projections, equilibrium models, and adaptive band logic. Together, they create a unified lens on multiple assets, allowing traders to rapidly identify alignment, filter out noise, and focus on the clearest opportunities.
ATR (No Gap) - Advanced Volatility IndicatorA customizable Average True Range indicator that eliminates gap distortion between trading sessions, providing cleaner volatility measurements for intraday and swing traders.
Key Features:
Gap Filtering: Optional toggle to ignore overnight/weekend gaps that distort volatility readings
EMA Smoothing: Defaults to EMA for more responsive volatility tracking (also supports RMA and SMA)
Half ATR Display: Shows 50% ATR value for quick stop-loss and take-profit calculations
Clean Value Table: Real-time values displayed on chart with configurable decimal precision
Flexible Settings: Customize length, smoothing method, and display options
Ideal for:
Setting dynamic stop losses and take profits
Position sizing based on current volatility
Comparing gap vs. no-gap volatility measurements
Trading instruments with large overnight gaps (indices, forex, crypto)
Use this indicator to get a more accurate picture of intraday volatility without the noise from session gaps!
Volatility-Targeted Momentum Portfolio [BackQuant]Volatility-Targeted Momentum Portfolio
A complete momentum portfolio engine that ranks assets, targets a user-defined volatility, builds long, short, or delta-neutral books, and reports performance with metrics, attribution, Monte Carlo scenarios, allocation pie, and efficiency scatter plots. This description explains the theory and the mechanics so you can configure, validate, and deploy it with intent.
Table of contents
What the script does at a glance
Momentum, what it is, how to know if it is present
Volatility targeting, why and how it is done here
Portfolio construction modes: Long Only, Short Only, Delta Neutral
Regime filter and when the strategy goes to cash
Transaction cost modelling in this script
Backtest metrics and definitions
Performance attribution chart
Monte Carlo simulation
Scatter plot analysis modes
Asset allocation pie chart
Inputs, presets, and deployment checklist
Suggested workflow
1) What the script does at a glance
Pulls a list of up to 15 tickers, computes a simple momentum score on each over a configurable lookback, then volatility-scales their bar-to-bar return stream to a target annualized volatility.
Ranks assets by raw momentum, selects the top 3 and bottom 3, builds positions according to the chosen mode, and gates exposure with a fast regime filter.
Accumulates a portfolio equity curve with risk and performance metrics, optional benchmark buy-and-hold for comparison, and a full alert suite.
Adds visual diagnostics: performance attribution bars, Monte Carlo forward paths, an allocation pie, and scatter plots for risk-return and factor views.
2) Momentum: definition, detection, and validation
Momentum is the tendency of assets that have performed well to continue to perform well, and of underperformers to continue underperforming, over a specific horizon. You operationalize it by selecting a horizon, defining a signal, ranking assets, and trading the leaders versus laggards subject to risk constraints.
Signal choices . Common signals include cumulative return over a lookback window, regression slope on log-price, or normalized rate-of-change. This script uses cumulative return over lookback bars for ranking (variable cr = price/price - 1). It keeps the ranking simple and lets volatility targeting handle risk normalization.
How to know momentum is present .
Leaders and laggards persist across adjacent windows rather than flipping every bar.
Spread between average momentum of leaders and laggards is materially positive in sample.
Cross-sectional dispersion is non-trivial. If everything is flat or highly correlated with no separation, momentum selection will be weak.
Your validation should include a diagnostic that measures whether returns are explained by a momentum regression on the timeseries.
Recommended diagnostic tool . Before running any momentum portfolio, verify that a timeseries exhibits stable directional drift. Use this indicator as a pre-check: It fits a regression to price, exposes slope and goodness-of-fit style context, and helps confirm if there is usable momentum before you force a ranking into a flat regime.
3) Volatility targeting: purpose and implementation here
Purpose . Volatility targeting seeks a more stable risk footprint. High-vol assets get sized down, low-vol assets get sized up, so each contributes more evenly to total risk.
Computation in this script (per asset, rolling):
Return series ret = log(price/price ).
Annualized volatility estimate vol = stdev(ret, lookback) * sqrt(tradingdays).
Leverage multiplier volMult = clamp(targetVol / vol, 0.1, 5.0).
This caps sizing so extremely low-vol assets don’t explode weight and extremely high-vol assets don’t go to zero.
Scaled return stream sr = ret * volMult. This is the per-bar, risk-adjusted building block used in the portfolio combinations.
Interpretation . You are not levering your account on the exchange, you are rescaling the contribution each asset’s daily move has on the modeled equity. In live trading you would reflect this with position sizing or notional exposure.
4) Portfolio construction modes
Cross-sectional ranking . Assets are sorted by cr over the chosen lookback. Top and bottom indices are extracted without ties.
Long Only . Averages the volatility-scaled returns of the top 3 assets: avgRet = mean(sr_top1, sr_top2, sr_top3). Position table shows per-asset leverages and weights proportional to their current volMult.
Short Only . Averages the negative of the volatility-scaled returns of the bottom 3: avgRet = mean(-sr_bot1, -sr_bot2, -sr_bot3). Position table shows short legs.
Delta Neutral . Long the top 3 and short the bottom 3 in equal book sizes. Each side is sized to 50 percent notional internally, with weights within each side proportional to volMult. The return stream mixes the two sides: avgRet = mean(sr_top1,sr_top2,sr_top3, -sr_bot1,-sr_bot2,-sr_bot3).
Notes .
The selection metric is raw momentum, the execution stream is volatility-scaled returns. This separation is deliberate. It avoids letting volatility dominate ranking while still enforcing risk parity at the return contribution stage.
If everything rallies together and dispersion collapses, Long Only may behave like a single beta. Delta Neutral is designed to extract cross-sectional momentum with low net beta.
5) Regime filter
A fast EMA(12) vs EMA(21) filter gates exposure.
Long Only active when EMA12 > EMA21. Otherwise the book is set to cash.
Short Only active when EMA12 < EMA21. Otherwise cash.
Delta Neutral is always active.
This prevents taking long momentum entries during obvious local downtrends and vice versa for shorts. When the filter is false, equity is held flat for that bar.
6) Transaction cost modelling
There are two cost touchpoints in the script.
Per-bar drag . When the regime filter is active, the per-bar return is reduced by fee_rate * avgRet inside netRet = avgRet - (fee_rate * avgRet). This models proportional friction relative to traded impact on that bar.
Turnover-linked fee . The script tracks changes in membership of the top and bottom baskets (top1..top3, bot1..bot3). The intent is to charge fees when composition changes. The template counts changes and scales a fee by change count divided by 6 for the six slots.
Use case: increase fee_rate to reflect taker fees and slippage if you rebalance every bar or trade illiquid assets. Reduce it if you rebalance less often or use maker orders.
Practical advice .
If you rebalance daily, start with 5–20 bps round-trip per switch on liquid futures and adjust per venue.
For crypto perp microcaps, stress higher cost assumptions and add slippage buffers.
If you only rotate on lookback boundaries or at signals, use alert-driven rebalances and lower per-bar drag.
7) Backtest metrics and definitions
The script computes a standard set of portfolio statistics once the start date is reached.
Net Profit percent over the full test.
Max Drawdown percent, tracked from running peaks.
Annualized Mean and Stdev using the chosen trading day count.
Variance is the square of annualized stdev.
Sharpe uses daily mean adjusted by risk-free rate and annualized.
Sortino uses downside stdev only.
Omega ratio of sum of gains to sum of losses.
Gain-to-Pain total gains divided by total losses absolute.
CAGR compounded annual growth from start date to now.
Alpha, Beta versus a user-selected benchmark. Beta from covariance of daily returns, Alpha from CAPM.
Skewness of daily returns.
VaR 95 linear-interpolated 5th percentile of daily returns.
CVaR average of the worst 5 percent of daily returns.
Benchmark Buy-and-Hold equity path for comparison.
8) Performance attribution
Cumulative contribution per asset, adjusted for whether it was held long or short and for its volatility multiplier, aggregated across the backtest. You can filter to winners only or show both sides. The panel is sorted by contribution and includes percent labels.
9) Monte Carlo simulation
The panel draws forward equity paths from either a Normal model parameterized by recent mean and stdev, or non-parametric bootstrap of recent daily returns. You control the sample length, number of simulations, forecast horizon, visibility of individual paths, confidence bands, and a reproducible seed.
Normal uses Box-Muller with your seed. Good for quick, smooth envelopes.
Bootstrap resamples realized returns, preserving fat tails and volatility clustering better than a Gaussian assumption.
Bands show 10th, 25th, 75th, 90th percentiles and the path mean.
10) Scatter plot analysis
Four point-cloud modes, each plotting all assets and a star for the current portfolio position, with quadrant guides and labels.
Risk-Return Efficiency . X is risk proxy from leverage, Y is expected return from annualized momentum. The star shows the current book’s composite.
Momentum vs Volatility . Visualizes whether leaders are also high vol, a cue for turnover and cost expectations.
Beta vs Alpha . X is a beta proxy, Y is risk-adjusted excess return proxy. Useful to see if leaders are just beta.
Leverage vs Momentum . X is volMult, Y is momentum. Shows how volatility targeting is redistributing risk.
11) Asset allocation pie chart
Builds a wheel of current allocations.
Long Only, weights are proportional to each long asset’s current volMult and sum to 100 percent.
Short Only, weights show the short book as positive slices that sum to 100 percent.
Delta Neutral, 50 percent long and 50 percent short books, each side leverage-proportional.
Labels can show asset, percent, and current leverage.
12) Inputs and quick presets
Core
Portfolio Strategy . Long Only, Short Only, Delta Neutral.
Initial Capital . For equity scaling in the panel.
Trading Days/Year . 252 for stocks, 365 for crypto.
Target Volatility . Annualized, drives volMult.
Transaction Fees . Per-bar drag and composition change penalty, see the modelling notes above.
Momentum Lookback . Ranking horizon. Shorter is more reactive, longer is steadier.
Start Date . Ensure every symbol has data back to this date to avoid bias.
Benchmark . Used for alpha, beta, and B&H line.
Diagnostics
Metrics, Equity, B&H, Curve labels, Daily return line, Rolling drawdown fill.
Attribution panel. Toggle winners only to focus on what matters.
Monte Carlo mode with Normal or Bootstrap and confidence bands.
Scatter plot type and styling, labels, and portfolio star.
Pie chart and labels for current allocation.
Presets
Crypto Daily, Long Only . Lookback 25, Target Vol 50 percent, Fees 10 bps, Regime filter on, Metrics and Drawdown on. Monte Carlo Bootstrap with Recent 200 bars for bands.
Crypto Daily, Delta Neutral . Lookback 25, Target Vol 50 percent, Fees 15–25 bps, Regime filter always active for this mode. Use Scatter Risk-Return to monitor efficiency and keep the star near upper left quadrants without drifting rightward.
Equities Daily, Long Only . Lookback 60–120, Target Vol 15–20 percent, Fees 5–10 bps, Regime filter on. Use Benchmark SPX and watch Alpha and Beta to keep the book from becoming index beta.
13) Suggested workflow
Universe sanity check . Pick liquid tickers with stable data. Thin assets distort vol estimates and fees.
Check momentum existence . Run on your timeframe. If slope and fit are weak, widen lookback or avoid that asset or timeframe.
Set risk budget . Choose a target volatility that matches your drawdown tolerance. Higher target increases turnover and cost sensitivity.
Pick mode . Long Only for bull regimes, Short Only for sustained downtrends, Delta Neutral for cross-sectional harvesting when index direction is unclear.
Tune lookback . If leaders rotate too often, lengthen it. If entries lag, shorten it.
Validate cost assumptions . Increase fee_rate and stress Monte Carlo. If the edge vanishes with modest friction, refine selection or lengthen rebalance cadence.
Run attribution . Confirm the strategy’s winners align with intuition and not one unstable outlier.
Use alerts . Enable position change, drawdown, volatility breach, regime, momentum shift, and crash alerts to supervise live runs.
Important implementation details mapped to code
Momentum measure . cr = price / price - 1 per symbol for ranking. Simplicity helps avoid overfitting.
Volatility targeting . vol = stdev(log returns, lookback) * sqrt(tradingdays), volMult = clamp(targetVol / vol, 0.1, 5), sr = ret * volMult.
Selection . Extract indices for top1..top3 and bot1..bot3. The arrays rets, scRets, lev_vals, and ticks_arr track momentum, scaled returns, leverage multipliers, and display tickers respectively.
Regime filter . EMA12 vs EMA21 switch determines if the strategy takes risk for Long or Short modes. Delta Neutral ignores the gate.
Equity update . Equity multiplies by 1 + netRet only when the regime was active in the prior bar. Buy-and-hold benchmark is computed separately for comparison.
Tables . Position tables show current top or bottom assets with leverage and weights. Metric table prints all risk and performance figures.
Visualization panels . Attribution, Monte Carlo, scatter, and pie use the last bars to draw overlays that update as the backtest proceeds.
Final notes
Momentum is a portfolio effect. The edge comes from cross-sectional dispersion, adequate risk normalization, and disciplined turnover control, not from a single best asset call.
Volatility targeting stabilizes path but does not fix selection. Use the momentum regression link above to confirm structure exists before you size into it.
Always test higher lag costs and slippage, then recheck metrics, attribution, and Monte Carlo envelopes. If the edge persists under stress, you have something robust.
VWAP CATS background flipped 4.0VWAP CATS Background Flipped 4.0 is a sophisticated Pine Script v5 indicator for TradingView that combines a configurable moving average (MA) with dynamic Gann Square of 9 levels to create a multi-layered background shading system for price action analysis. It visualizes support/resistance zones around a central MA (often VWAP or RVWAP) using incremental offsets (either % or absolute points), generating symmetrical bands that resemble a "CATS" (Concentric Adaptive Tiered System) — hence the name.The background is "flipped" in the sense that shading intensity and structure emphasize higher-tier zones, and labels are placed to the right of the chart for future projection.Key FeaturesFeature
Description
Multi-MA Engine
Supports 20+ MA types: EMA, DEMA, TEMA, SMA, VWAP, RVWAP, HMA, ALMA, custom volume blends (CVB1–4)
RVWAP Mode
Rolling VWAP with adaptive or fixed time window (days/hours/minutes)
Gann Square of 9 Logic
Generates 80+ symmetric levels (0.25x to 17x increment) above/below the MA
Dual Increment Mode
Choose Percent or Points for spacing
Background Fills
Tiered transparency fills between Gann levels (darker = stronger zones)
Visual MA Offset
Shift MA line left/right without breaking fill alignment
Smart Labels
Projected labels on last bar: "FV", "normal", "high", "3/4" at key levels
Performance Optimized
Hidden plots + label cleanup to prevent lag
Primary Use Cases
1. Institutional VWAP Anchoring
Use RVWAP (1-day fixed) as maRaw
Set Increment = 0.5 points or 0.05%
Watch price interaction with "normal" (2x), "high" (4x), "3/4" (6x) zones
Ideal for intraday scalping on indices (ES, NQ) or forex
2. Swing Trading with Gann Projections
Use 400-period SMA/EMA on daily chart
Increment in Percent mode (~1.22%)
Identify confluence when price rejects at 2x, 4x, or 6x bands
Labels project future targets to the right
3. Volume-Weighted Mean Reversion
Select CVB1–CVB4 for heavy volume smoothing
Use Points mode for stocks with stable tick sizes (e.g. $0.50 increments)
Trade mean reversion between ±1x and ±2x bands
4. Risk Management & Stop Placement
Place stops beyond 2x or 4x bands
Take profits at next major tier (e.g. 4x → 6x)
Pro Tips
Enable "Use Fixed Time Period" for RVWAP to avoid session reset issues
Increase i_label_offset on lower timeframes to avoid overlap
Combine with volume profile or order flow for confluence
The "FV" label marks the Fair Value MA — core anchor
Summary"VWAP CATS Background Flipped 4.0" turns any moving average into a dynamic Gann-based pricing grid with intelligent background shading and forward-projected labels — perfect for institutional-style mean reversion, swing targeting, and risk-defined trading."
Smarter Money Volume Rejection Blocks [PhenLabs]📊 Smarter Money Volume Rejection Blocks – Institutional Rejection Zone Detection
The Smarter Money Volume Rejection Blocks indicator combines high-volume analysis with statistical confidence intervals to identify where institutional traders are actively defending price levels through volume spikes and rejection patterns.
🔥 Core Methodology
Volume Spike Detection analyzes when current volume exceeds moving average by configurable multipliers (1.0-5.0x) to identify institutional activity
Rejection Candle Analysis uses dual-ratio system measuring wick percentage (30-90%) and maximum body ratio (10-60%) to confirm genuine rejections
Statistical Confidence Channels create three-level zones (upper, center, lower) based on ATR or Standard Deviation calculations
Smart Invalidation Logic automatically clears zones when price significantly breaches confidence levels to maintain relevance
Dynamic Channel Projection extends confidence intervals forward up to 200 bars with customizable length
Support Zone Identification detects bullish rejections where smart money absorbs selling pressure with high volume and strong lower wicks
Resistance Zone Mapping identifies bearish rejections where institutions defend price levels with volume spikes and pronounced upper wicks
Visual Information Dashboard displays real-time status table showing volume spike conditions and active support/resistance zones
⚙️ Technical Configuration
Dual Confidence Interval Methods: Choose between ATR-Based for trend-following environments or StdDev-Based for range-bound statistical precision
Volume Moving Average: Configurable period (default 20) for baseline volume comparison calculations
Volume Spike Multiplier: Adjustable threshold from 1.0 to 5.0 times average volume to filter institutional activity
Rejection Wick Percentage: Set minimum wick size from 30% to 90% of candle range for valid rejection detection
Maximum Body Ratio: Configure body-to-range ratio from 10% to 60% to ensure genuine rejection structures
Confidence Multiplier: Statistical multiplier (default 1.96) for 95% confidence interval calculations
Channel Projection Length: Extend confidence zones forward from 10 to 200 bars for anticipatory analysis
ATR Period: Customize Average True Range lookback from 5 to 50 bars for volatility-based calculations
StdDev Period: Adjust Standard Deviation period from 10 to 100 bars for statistical precision
🎯 Real-World Trading Applications
Identify high-probability support zones where institutional buyers have historically defended price with significant volume
Map resistance levels where smart money sellers consistently reject higher prices with volume confirmation
Combine with price action analysis to confirm breakout validity when price approaches confidence channel boundaries
Use invalidation signals to exit positions when smart money zones are definitively breached
Monitor the real-time dashboard to quickly assess current market structure and active rejection zones
Adapt strategy based on calculation method: ATR for trending markets, StdDev for ranging conditions
Set alerts on confidence level breaches to catch potential trend reversals or continuation patterns
📈 Visual Interpretation Guide
Green Zones indicate bullish rejection blocks where buyers defended with high volume and lower wicks
Red Zones indicate bearish rejection blocks where sellers defended with high volume and upper wicks
Solid Center Lines represent the core rejection price level where maximum volume activity occurred
Dashed Confidence Boundaries show upper and lower statistical limits based on volatility calculations
Zone Opacity decreases as channels extend forward to indicate decreasing confidence over time
Dashboard Color Coding provides instant visual feedback on active volume spike and zone conditions
⚠️ Important Considerations
Volume-based indicators identify historical rejection zones but cannot predict future price action with certainty
Market conditions change rapidly and institutional activity patterns evolve continuously
High volume does not guarantee level defense as market structure can shift without warning
Confidence intervals represent statistical probabilities, not guaranteed price boundaries
ORB | Feng FuturesThe ORB | Feng Futures indicator automatically detects the Opening Range Breakout (ORB) for each trading session, plotting the High, Low, and Midline in real time. This tool is built for futures traders who rely on ORB structure to confirm trends, identify breakout zones, and recognize reversal areas early in the session.
Features:
• Auto-calculated ORB High, Low, and Midline
• Multi-timezone session support (NY, Chicago, London, Tokyo, etc.)
• Customize ORB time range and time window for display
• Real-time updating lines that freeze at session close
• Optional labels with customizable size, color, and offset
• Save and view multiple previous ORB sessions
• Full color customization for all levels
• Automatically hides on higher timeframes (Daily+) to reduce clutter
• Works on ES, NQ, and all intraday futures charts
• Works on stocks, crypto, forex, and other tradeable assets where ORB is applicable
Disclaimer: This indicator is for educational purposes only and does not constitute financial advice. Trading futures involves significant risk and may not be suitable for all investors. Always do your own research and use proper risk management.
Buy/Sell Volume Tracker [wjdtks255]Indicator Description
Function: Separates buy and sell volume based on candle direction (close ≥ open) and displays the buy−sell difference (hist_val) as a histogram.
Visuals: Buy/sell bars are distinguished by user-selectable colors and opacity; two moving averages (MA1 and MA2) are shown to smooth the flow.
Meaning: A positive histogram indicates buy dominance; a negative histogram indicates sell dominance.
Limitation: The current separation is estimated from candle direction and may differ from execution-side (tick/trade-side) based data.
Trading Rules (Summary)
Conservative trend-following long
Entry: Enter long when hist_val turns above 0 and MA1 crosses MA2 from below.
Stop-loss: Exit if hist_val falls back below 0 or MA1 drops below MA2.
Take-profit: Use a risk:reward of 1:1.5 or set targets based on ATR.
Short-term rebound long
Entry: Enter a short-term long when a large negative histogram region begins to narrow and shows a recovery sign.
Stop-loss: Exit if hist_val drops below the previous low or bearish candles continue.
Take-profit: Prefer quick partial profit-taking.
Short (sell) strategy
Entry: Enter short when hist_val falls below 0 and MA1 crosses MA2 from above.
Stop-loss / Take-profit: Apply the inverse rules of the long strategy.
Filters and risk management
Volume filter: Only accept signals when volume exceeds a fraction of average volume to reduce noise.
Entry strength: Require |hist_val| to exceed a historical average threshold (e.g., avg(|hist_val|, N) × factor) to strengthen signals.
Position sizing: Size positions so that account risk per trade is within limits (e.g., 1–2% of account equity).
Timeframe: Use short timeframes for scalping and 1h+ for swing trading.
Customized Double Bollinger Bands [wjdtks255]This indicator combines two Bollinger Bands to visualize both short-term and extreme volatility zones on the same chart.
While a standard Bollinger Band shows how far price deviates from its mean,
this customized version displays two standard deviation ranges, allowing traders to distinguish between mild and extreme volatility conditions.
Band 1 (StdDev 0.5) captures short-term fluctuations near the price average,
while Band 2 (StdDev 3.0) highlights overbought or oversold conditions at market extremes.
When the distance between the two bands widens, volatility is increasing;
when it narrows, the market is stabilizing or preparing for a breakout.
ㆍPrice breaking above Band 2 → Potential overbought or strong bullish trend
ㆍPrice falling below Band 2 → Possible oversold or bearish continuation
ㆍBands tightening → Volatility compression, potential reversal zone
This indicator is designed primarily for volatility visualization rather than directional prediction.
For higher accuracy, use it alongside RSI, MACD, or trend-based indicators.
Developed by wjdtks255
