This study calculates CCI strategy The Commodity Channel Index (CCI) is best used with markets that display cyclical or
seasonal characteristics, and is formulated to detect the beginning and ending of these
cycles by incorporating a moving average together with a divisor that reflects both possible
and actual trading ranges. The final index measures the deviation from normal, which indicates
major changes in market trend.
To put it simply, the Commodity Channel Index (CCI) value shows how the instrument is trading
relative to its mean (average) price. When the CCI value is high, it means that the prices are
high compared to the average price; when the CCI value is down, it means that the prices are low
compared to the average price. The CCI value usually does not fall outside the -300 to 300 range
and, in fact, is usually in the -100 to 100 range.
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Continuous Partial Buying Signals v7.1🇬🇧 English Description: Continuous Partial Buying Signals v7.1
This indicator is built on a long-term accumulation philosophy , not a traditional buy-sell strategy. Its main purpose is to systematically increase your position in an asset you believe in by identifying significant price drops as buying opportunities. It is a tool designed for long-term investors who want to automate the "buy the dip" or "Dollar Cost Averaging (DCA)" mindset.
How It Works
The logic follows a simple but powerful cycle: Find a Peak -> Wait for a Drop -> Signal a Buy -> Wait for a New Peak.
1. Identifies a Significant Peak: Instead of reacting to minor price spikes, the indicator looks back over a user-defined period (e.g., the last 200 candles) to find the highest price. This stable peak (marked with an orange circle) becomes the reference point for the current cycle.
2. Waits for a Pullback: The indicator then calculates the percentage drop from this locked-in peak.
3. Generates Buy Signals: When the price drops by the percentages you define (e.g., -5% and -10%), it plots a "BUY" signal on the chart. It will only signal once per level within the same cycle.
4. Resets the Cycle: This is the key. If the price recovers and establishes a new significant peak higher than the previous one, the entire cycle resets. The new peak becomes the new reference, and the buy signals are re-armed, allowing the indicator to perpetually find new buying opportunities in a rising market.
How to Get the Most Out of This Indicator
* Timeframe: It is highly recommended to use this on higher timeframes (4H, Daily, Weekly) to align with its long-term accumulation philosophy.
* Peak Lookback Period:
* Higher values (200, 300): Create more stable and less frequent signals. Ideal for long-term, patient investors.
* Lower values (50, 100): More sensitive to recent price action, resulting in more frequent cycles.
* Drop Percentages: Adjust these based on the asset's volatility.
* Volatile assets (Crypto): Consider larger percentages like 10%, 20%.
* Less volatile assets (Stocks, Indices): Smaller percentages like 3%, 5%, 8% might be more appropriate.
This indicator is a tool for disciplined, emotion-free accumulation. It does not provide sell signals.
Open Interest OverlayOpen Interest Overlay
Overview
This indicator displays Open Interest (OI) data directly on your price chart as an overlay, eliminating the need for separate panes while preserving authentic OI movement patterns. Perfect for traders who want to analyze OI correlations without sacrificing chart real estate.
Key Features
📊 Smart Price Scaling
• Automatically maps Open Interest values to fit within your chart's price range
• Preserves all directional movements, timing, and relative magnitude relationships
• Uses official TradingView Open Interest feed for accuracy
🎨 Full Customization
• Custom Colors: Choose your own colors for rising/falling OI (defaults: teal/red)
• Line Style: Toggle between step-line (traditional) or smooth line display
• Optional Fill: Shade area between OI line and mid-price for better visual reference
• Smoothing Options: Apply moving average smoothing to reduce noise
⚙️ Intelligent Settings
• Normalization Window: 300-bar lookback (customizable) for scaling calculations
• Auto Timeframe: Uses daily data for intraday charts on traditional assets, chart timeframe for crypto
• Real Value Display: Shows actual (unscaled) OI value on the last bar
How It Works
The indicator performs proportional mapping of Open Interest data:
1. Calculates OI range (high/low) over the lookback period
2. Maps this range to your chart's price range during the same period
3. Displays OI movements that maintain authentic patterns and timing
Perfect For
✅ Correlation Analysis - See how OI moves with price in real-time
✅ Divergence Spotting - Identify when OI and price trends diverge
✅ Clean Charts - No need for separate panes or window splitting
✅ Pattern Recognition - Spot OI building/declining during key price levels
✅ Cross-Market Analysis - View any symbol's OI overlay on your current chart (e.g., Bitcoin OI while viewing Ethereum prices)
What You Get vs Traditional OI Indicators
Advantages:
• Authentic OI movement patterns preserved
• Direct visual correlation with price action
• No chart real estate sacrifice
• Immediate trend and divergence recognition
Trade-offs:
• Shows relative OI changes rather than absolute values
• Scaling is relative to the selected lookback period
Ideal For
• Day traders monitoring intraday OI flow
• Swing traders analyzing OI trends with price movements
• Futures traders tracking institutional interest
• Anyone wanting clean, correlation-focused OI analysis
Compatible With
• Futures contracts with Open Interest data
• Any timeframe (auto-adjusts for optimal data)
• All TradingView-supported OI symbols
TRAPPER TRENDLINES — PRICEDraws dynamic trendlines on price by connecting the two most recent confirmed swing points (highs to highs for resistance, lows to lows for support). Swings are defined with a symmetric left/right pivot window. Old anchors are ignored so lines stay attached to current structure. Optional break alerts are included.
How it works (plain language)
Pivots: A bar is a swing high (or low) only if it’s the most extreme point compared with a set number of bars on the left and the right.
Lines:
Support connects the last two confirmed swing lows.
Resistance connects the last two confirmed swing highs.
Lines can be extended right only or both left & right (toggle).
Recency filter: Only swings within the last N bars are kept. This avoids anchoring to very old pivots far from current price.
Alerts: Optional alerts fire when price closes above resistance or below support.
Inputs
Auto Settings
Auto pivot size by chart timeframe: When ON, the script picks a pivot size suitable for the current timeframe (you can scale it with Auto pivot multiplier). When OFF, the manual left/right inputs are used.
Auto pivot multiplier: Scales the auto pivot size (e.g., 1.5 makes pivots stricter).
Manual Pivots
Pivot Left / Pivot Right: Bars to the left/right required to confirm a swing. Example: Left=50 & Right=50 keeps only major swings.
Recency Filter
Use last N bars for pivots: Swings older than this window are discarded so trendlines stay relevant to current price.
Style
Support/Resistance color: Line colors.
Extend Left & Right: When ON, both endpoints extend; when OFF, lines extend to the right only.
Alerts
Enable Break Alerts: When ON, alert conditions are exposed:
Price: Break Up — close above resistance.
Price: Break Down — close below support.
Suggested settings
Higher timeframes (4H / 1D / 1W):
Manual: Pivot Left = 50, Pivot Right = 50, Use last N bars = 400–800.
Or enable Auto with Auto pivot multiplier = 1.0–1.5.
Intraday (15m / 30m / 1H):
Manual: Pivot Left = 30, Pivot Right = 30, Use last N bars = 300–500.
Or enable Auto with multiplier ≈ 1.0–1.2.
Pairing with RSI for confluence/divergence
This tool is designed to pair with a companion TRAPPER TRENDLINES — RSI (or any RSI trendline script):
To mirror swings, set RSI Pivot Lookback equal to the price Pivot Left/Right you use here.
Example: Price = 50/50 → RSI Pivot Lookback = 50.
Keep RSI at Length 14 with 70/30 channel for clarity.
Confluence: Price holds/rejects at a trendline while RSI trendline agrees.
Divergence: Price prints a higher high (resistance line rising) while RSI prints a lower high (RSI resistance line falling), or vice-versa for lows. Matching pivot windows makes these relationships clear and reduces false signals.
Reading the signals
Trendline touch/hold: Potential reaction area; wait for follow-through.
Break Up / Break Down (alerts): Close beyond the line. Consider retest behavior, higher-timeframe context, and volume/RSI confirmation.
Notes & limitations
Pivots require future bars to confirm (by design). Lines update as pivots confirm.
“Use last N bars” purposely ignores very old swings. Increase this value if you need legacy structure.
Lines are based on two most recent confirmed pivots per side; rapidly changing markets can replace anchors as new swings confirm.
This is a visual/analytical tool. No strategy entries/exits or performance claims are provided.
Compliance
This script is for educational purposes only and does not constitute financial advice. Trading involves risk. Past results do not guarantee future outcomes. No promises of profit, accuracy, or performance are made.
Alerts (titles/messages)
Price: Break Up — “Price broke above resistance trendline.”
Price: Break Down — “Price broke below support trendline.”
Quick start
Add the indicator to your chart.
Choose Auto or set Pivot Left/Right manually.
Set Use last N bars for how far back to consider swings.
Toggle Extend Left & Right to your preference.
(Optional) Add your RSI trendline indicator and match Pivot Lookback with your price pivot size for clean confluence/divergence.
Enable alerts if you want notifications on breaks.
MACD StrategyOverview
The "MACD Strategy" is a straightforward trading strategy tested for BTCUSDT Futures on the 1-minute timeframe, leveraging the Moving Average Convergence Divergence (MACD) indicator to identify momentum-based buy and sell opportunities. Developed with input from expert trading analyst insights, this strategy combines technical precision with risk management, making it suitable for traders of all levels on platforms like TradingView. It focuses on capturing trend reversals and momentum shifts, with clear visual cues and automated alerts for seamless integration with trading bots (e.g., Bitget webhooks).
#### How It Works
This strategy uses the MACD indicator to generate trading signals based on momentum and trend direction:
- **Buy Signal**: Triggered when the MACD line crosses above the signal line, and the MACD histogram turns positive (above zero). This suggests increasing bullish momentum.
- **Sell Signal**: Triggered when the MACD line crosses below the signal line, and the MACD histogram turns negative (below zero), indicating growing bearish momentum.
Once a signal is detected, the strategy opens a position (long for buy, short for sell) with a position size calculated based on your risk tolerance. It includes a stop-loss to limit losses and a take-profit to lock in gains, both dynamically adjusted using the Average True Range (ATR) for adaptability to market volatility.
#### Key Features
- **MACD-Based Signals**: Relies solely on MACD for entry points, plotted in a separate pane for clear momentum analysis.
- **Risk Management**: Automatically calculates position size based on a percentage of your account balance and sets stop-loss and take-profit levels using ATR multipliers and a risk:reward ratio.
- **Visual Feedback**: Plots entry, stop-loss, and take-profit lines on the chart with labeled markers for easy tracking.
- **Alerts**: Includes Bitget webhook-compatible alerts for automated trading, notifying you of buy and sell signals in real-time.
#### Input Parameters
- **Account Balance**: Default 10000 – Set your initial trading capital to determine position sizing.
- **MACD Fast Length**: Default 12 – The short-term EMA period for MACD sensitivity.
- **MACD Slow Length**: Default 26 – The long-term EMA period for MACD calculation.
- **MACD Signal Length**: Default 9 – The smoothing period for the signal line.
- **Risk Per Trade (%)**: Default 3.0 – The percentage of your account balance risked per trade (e.g., 3% of 10000 = 300).
- **Risk:Reward Ratio**: Default 3.0 – The ratio of potential profit to risk (e.g., 3:1 means risking 1 to gain 3).
- **SL Multiplier**: Default 1.0 – Multiplies ATR to set the stop-loss distance (e.g., 1.0 x ATR).
- **TP Multiplier**: Default 3.0 – Multiplies ATR to set the take-profit distance, adjusted by the risk:reward ratio.
- **Line Length (bars)**: Default 25 – Duration in bars for displaying trade lines on the chart.
- **Label Position**: Default 'left' – Position of text labels (left or right) relative to trade lines.
- **ATR Period**: Default 14 – The number of periods for calculating ATR to measure volatility.
#### How to Use
1. **Add to Chart**: Load the "MACD Strategy" as a strategy and the "MACD Indicator" as a separate indicator on your TradingView chart (recommended for BTCUSDT Futures on the 1-minute timeframe).
2. **Customize Settings**: Adjust the input parameters based on your risk tolerance and market conditions. For BTCUSDT Futures, consider reducing `Risk Per Trade (%)` during high volatility (e.g., 1%) or increasing `SL Multiplier` for wider stops.
3. **Visual Analysis**: Watch the main chart for trade entry lines (green for buy, red for sell), stop-loss (red), and take-profit (green) lines with labels. Use the MACD pane below to confirm momentum shifts.
4. **Set Alerts**: Create alerts in TradingView for "Buy Signal" and "Sell Signal" to automate trades via Bitget webhooks.
5. **Backtest and Optimize**: Test the strategy on historical BTCUSDT Futures 1-minute data to fine-tune parameters. The short timeframe requires quick execution, so monitor closely for slippage or latency.
#### Tips for Success
- **Market Conditions**: This strategy performs best in trending markets on the 1-minute timeframe. Avoid choppy conditions where MACD crossovers may produce false signals.
- **Risk Management**: Start with the default 3% risk per trade and adjust downward (e.g., 1%) during volatile periods like BTCUSDT news events. The 3:1 risk:reward ratio targets consistent profitability.
- **Timeframe**: Optimized for 1-minute charts; switch to 5-minute or 15-minute for less noise if needed.
- **Confirmation**: Cross-check MACD signals with price action or support/resistance levels for higher accuracy on BTCUSDT Futures.
#### Limitations
- This strategy relies solely on MACD, so it may lag in fast-moving or sideways markets. Consider adding a secondary filter (e.g., RSI) if needed.
- Stop-loss and take-profit are ATR-based and may need adjustment for BTCUSDT Futures’ high volatility, especially during leverage trading.
#### Conclusion
The "MACD Strategy" offers a simple yet effective way to trade momentum shifts using the MACD indicator, tested for BTCUSDT Futures on the 1-minute timeframe, with robust risk management and visual tools. Whether you’re scalping crypto futures or exploring short-term trends, this strategy provides a solid foundation for automated or manual trading. Share your feedback or customizations in the comments, and happy trading!
Donchian Squeeze Oscillator# Donchian Squeeze Oscillator (DSO) - User Guide
## Overview
The Donchian Squeeze Oscillator is a technical indicator designed to identify periods of low volatility (squeeze) and high volatility (expansion) in financial markets by measuring the distance between Donchian Channel bands. The indicator normalizes this measurement to a 0-100 scale, making it easy to interpret across different timeframes and instruments.
## How It Works
The DSO calculates the width of Donchian Channels as a percentage of the middle line, smooths this data, and then normalizes it using historical highs and lows over a specified lookback period. The result is inverted so that:
- **High values (80+)** = Narrow channels = Low volatility = Squeeze
- **Low values (20-)** = Wide channels = High volatility = Expansion
## Key Parameters
### Core Settings
- **Donchian Channel Period (20)**: The number of bars used to calculate the highest high and lowest low for the Donchian Channels
- **Smoothing Period (5)**: Applies moving average smoothing to reduce noise in the oscillator
- **Normalization Lookback (200)**: Historical period used to normalize the oscillator between 0-100
### Threshold Levels
- **Over Squeeze (80)**: Values above this level indicate strong squeeze conditions
- **Over Expansion (20)**: Values below this level indicate strong expansion conditions
## Reading the Indicator
### Color Coding
- **Red Line**: Squeeze condition (above 80 threshold) - Markets are consolidating
- **Orange Line**: Neutral/trending condition with upward momentum
- **Green Line**: Expansion condition or downward momentum
### Visual Elements
- **Red Dashed Line (80)**: Squeeze threshold - potential breakout zone
- **Gray Dotted Line (50)**: Middle line - neutral zone
- **Green Dashed Line (20)**: Expansion threshold - high volatility zone
- **Red Background**: Highlights active squeeze periods
## Trading Applications
### 1. Breakout Trading
- **Setup**: Wait for DSO to reach 80+ (squeeze zone)
- **Entry**: Look for breakouts when DSO starts declining from squeeze levels
- **Logic**: Prolonged low volatility often precedes significant price movements
### 2. Volatility Cycle Trading
- **Squeeze Phase**: DSO > 80 - Prepare for potential breakout
- **Breakout Phase**: DSO declining from 80 - Trade the direction of breakout
- **Expansion Phase**: DSO < 20 - Expect trend continuation or reversal
### 3. Trend Confirmation
- **Orange Color**: Suggests bullish momentum during expansion
- **Green Color**: Suggests bearish momentum or consolidation
- Use in conjunction with price action for trend confirmation
## Best Practices
### Timeframe Selection
- **Higher Timeframes (Daily, 4H)**: More reliable signals, fewer false breakouts
- **Lower Timeframes (1H, 15M)**: More frequent signals but higher noise
- **Multi-timeframe Analysis**: Confirm squeeze on higher TF, enter on lower TF
### Parameter Optimization
- **Volatile Markets**: Increase Donchian period (25-30) and smoothing (7-10)
- **Range-bound Markets**: Decrease Donchian period (15-20) for more sensitivity
- **Trending Markets**: Use longer normalization lookback (300-400)
### Signal Confirmation
Always combine DSO signals with:
- **Price Action**: Support/resistance levels, chart patterns
- **Volume**: Confirm breakouts with increasing volume
- **Other Indicators**: RSI, MACD, or momentum oscillators
## Alert System
The indicator includes built-in alerts for:
- **Squeeze Started**: When DSO crosses above the squeeze threshold
- **Expansion Started**: When DSO crosses below the expansion threshold
## Common Pitfalls to Avoid
1. **False Breakouts**: Don't trade every squeeze - wait for confirmation
2. **Parameter Over-optimization**: Stick to default settings initially
3. **Ignoring Market Context**: Consider overall market conditions and news
4. **Single Indicator Reliance**: Always use additional confirmation tools
## Advanced Tips
- Monitor squeeze duration - longer squeezes often lead to bigger moves
- Look for squeeze patterns at key support/resistance levels
- Use DSO divergences with price for potential reversal signals
- Combine with Bollinger Band squeezes for enhanced accuracy
## Conclusion
The Donchian Squeeze Oscillator is a powerful tool for identifying volatility cycles and potential breakout opportunities. Like all technical indicators, it should be used as part of a comprehensive trading strategy rather than as a standalone signal generator. Practice with the indicator on historical data before implementing it in live trading to understand its behavior in different market conditions.
Imbalance RSI Divergence Strategy# Imbalance RSI Divergence Strategy - User Guide
## What is This Strategy?
This strategy identifies **imbalance** zones in the market and combines them with **RSI divergence** to generate trading signals. It aims to capitalize on price gaps left by institutional investors and large volume movements.
### Main Settings
- **RSI Period (14)**: Period used for RSI calculation. Lower values = more sensitive, higher values = more stable signals.
- **ATR Period (10)**: Period for volatility measurement using Average True Range.
- **ATR Stop Loss Multiplier (2.0)**: How many ATR units to use for stop loss calculation.
- **Risk:Reward Ratio (4.0)**: Risk-reward ratio. 2.0 = 2 units of reward for 1 unit of risk.
- **Use RSI Divergence Filter (true)**: Enables/disables the RSI divergence filter.
### Imbalance Filters
- **Minimum Imbalance Size (ATR) (0.3)**: Minimum imbalance size in ATR units to filter out small imbalances.
- **Enable Lookback Limit (false)**: Activates historical lookback limitations.
- **Maximum Lookback Bars (300)**: Maximum number of bars to look back.
### Visual Settings
- **Show Imbalance Size**: Displays imbalance size in ATR units.
- **Show RSI Divergence Lines**: Shows/hides divergence lines.
- **Divergence Line Colors**: Colors for bullish/bearish divergence lines.
### Volatility-Based Adjustments
- **Low volatility markets**:
- Minimum Imbalance Size: 0.2-0.4 ATR
- ATR Stop Loss Multiplier: 1.5-2.0
- **High volatility markets**:
- Minimum Imbalance Size: 0.5-1.0 ATR
- ATR Stop Loss Multiplier: 2.5-3.5
### Risk Tolerance
- **Conservative approach**:
- Risk:Reward Ratio: 2.0-3.0
- RSI Divergence Filter: Enabled
- Minimum Imbalance Size: Higher (0.5+ ATR)
- **Aggressive approach**:
- Risk:Reward Ratio: 4.0-6.0
- Minimum Imbalance Size: Lower (0.2-0.3 ATR)
###Market Conditions
- **Trending markets**: Higher RSI Period (21-28)
- **Sideways markets**: Lower RSI Period (10-14)
- **Volatile markets**: Higher ATR Multiplier
## Recommended Testing Procedure
1. **Start with default settings** and backtest on 3-6 months of historical data
2. **Adjust RSI Period** to see which value produces better results
3. **Optimize ATR Multiplier** for stop loss levels
4. **Test different Risk:Reward ratios** comparatively
5. **Fine-tune Minimum Imbalance Size** to improve signal quality
## Important Considerations
- **False positive signals**: Imbalances may be less reliable during low volatility periods
- **Market openings**: First hours often produce more imbalances but can be riskier
- **News events**: Consider disabling strategy during major news releases
- **Backtesting**: Test across different market conditions (trending, sideways, volatile)
## Recommended Settings for Beginners
**Safe settings for new users:**
- RSI Period: 14
- ATR Period: 14
- ATR Stop Loss Multiplier: 2.5
- Risk:Reward Ratio: 3.0
- Minimum Imbalance Size: 0.5 ATR
- RSI Divergence Filter: Enabled
## Advanced Tips
### Signal Quality Improvement
- **Combine with market structure**: Look for imbalances near key support/resistance levels
- **Volume confirmation**: Higher volume during imbalance formation increases reliability
- **Multiple timeframe analysis**: Confirm signals on higher timeframes
### Risk Management
- **Position sizing**: Never risk more than 1-2% of account per trade
- **Maximum drawdown**: Set overall stop loss for the strategy
- **Market hours**: Consider avoiding low liquidity periods
### Performance Monitoring
- **Win rate**: Track percentage of profitable trades
- **Average R:R**: Monitor actual risk-reward achieved vs. target
- **Maximum consecutive losses**: Set alerts for strategy review
This strategy works best when combined with proper risk management and market analysis. Always backtest thoroughly before using real money and adjust parameters based on your specific market and trading style.
ADR/ATR Session No Probability Table by LKHere you go—clear, English docs you can drop into your script’s description or share with teammates.
ADR/ATR Session by LK — Overview
This indicator summarizes Average Daily Range (ADR) and Average True Range (ATR) for two horizons:
• Session H4 (e.g., 06:00–13:00 on a 4‑hour chart)
• Daily (D)
It shows:
• Current ADR/ATR values (using your chosen smoothing method)
• How much of ADR/ATR today/this bar has already been consumed (% of ADR/ATR)
• ADR/ATR as a percent of price
• Optional probability blocks: likelihood that %ADR will exceed user‑defined thresholds over a lookback window
• Optional on‑chart lines for the current H4 and Daily candles: Open, ADR High, ADR Low
⸻
What the metrics mean
• ADR (H4 / D): Moving average of the bar range (high - low).
• ATR (H4 / D): Moving average of True Range (max(hi-lo, |hi-close |, |lo-close |)).
• % of ADR (curr H4): (H4 range of the current H4 bar) / ADR(H4) × 100. Updates live even if the current time is outside the session.
• % of ADR (Daily): (today’s intra‑day range) / ADR(D) × 100.
• % of ATR (curr H4 / Daily): TR / ATR × 100 for that horizon.
• ADR % of Price / ATR % of Price: ADR or ATR divided by current price × 100 (a quick “volatility vs. price” gauge).
Session logic (H4): ADR/ATR(H4) only update on bars that fall inside the configured session window; outside the window the values hold steady (no recalculation “bleed”).
Daily range tracking: The indicator tracks today’s high/low in real‑time and resets at the day change.
⸻
Inputs (quick reference)
Core
• Length (ADR/ATR): smoothing length for ADR/ATR (default 21).
• Wait for Higher TF Bar Close: if true, updates ADR/ATR only after the higher‑TF bar closes when using request.security.
Timeframes
• Session Timeframe (H4): default 240.
• Daily Timeframe: default D.
Session time
• Session Timezone: “Chart” (default) or a fixed timezone.
• Session Start Hour, End Hour (minutes are fixed to 0 in this version).
Smoothing methods
• H4 ADR Method / H4 ATR Method: SMA/EMA/RMA/WMA.
• Daily ADR Method / Daily ATR Method: SMA/EMA/RMA/WMA.
Table appearance
• Table BG, Table Text, Table Font Size.
Lines (optional)
• Show current H4 segments, Show current Daily segments
• Line colors for Open / ADR High / ADR Low
• Line width
Probability
• H4 Probability Lookback (bars): number of H4 bars to examine (e.g., 300).
• Daily Probability Lookback (days): number of D bars (e.g., 180).
• ADR thresholds (%): CSV list of thresholds (e.g., 25,50,55,60,65,70,75,80,85,90,95,100,125,150).
The table will show the % of lookback bars where %ADR ≥ threshold.
Tip: If you want probabilities only for session H4 bars (not every H4 bar), ask and I can add a toggle to filter by inSess.
⸻
How to read the table
H4 block
• ADR (method) / ATR (method): the session‑aware averages.
• % of ADR (curr H4): live progress of this H4 bar toward the session ADR.
• ADR % of Price: ADR(H4) relative to price.
• % of ATR (curr H4) and ATR % of Price: same idea for ATR.
H4 Probability (lookback N bars)
• Rows like “≥ 80% ADR” show the fraction (in %) of the last N H4 bars that reached at least 80% of ADR(H4).
Daily block
• Mirrors the H4 block, but for Daily.
Daily Probability (lookback M days)
• Rows like “≥ 100% ADR” show the fraction of the last M daily bars whose daily range reached at least 100% of ADR(D).
⸻
Practical usage
• Use % of ADR (curr H4 / Daily) to judge exhaustion or room left in the day/session.
E.g., if Daily %ADR is already 95%, be cautious with momentum continuation trades.
• The probability tables give a quick historical context:
If “≥ 125% ADR” is ~18%, the market rarely stretches that far; your trade sizing/targets can reflect that.
• ADR/ATR % of Price helps normalize volatility between instruments.
⸻
Troubleshooting
• If probability rows are blank: ensure lookback windows are large enough (and that the chart has enough history).
• If ADR/ATR show … (NA): usually you don’t have enough bars for the chosen length/TF yet.
• If line segments are missing: verify you’re on a chart with visible current H4/D bars and the toggles are enabled.
⸻
Notes & customization ideas
• Add a toggle to count only session bars in H4 probability.
• Add separate thresholds for H4 vs Daily.
• Let users pick minutes for session start/end if needed.
• Add alerts when %ADR crosses specified thresholds.
If you want me to bundle any of the “ideas” above into the code, say the word and I’ll ship a clean patch.
Map Multiple QQQ Levels to NQ (Custom Labels)maps user-defined price levels from the QQQ (Invesco QQQ Trust, tracking the NASDAQ-100) to equivalent levels on the NQ (NASDAQ-100 futures) chart, displaying them as colored lines with optional labels. It’s designed to overlay on the NQ chart, helping traders visualize QQQ price levels in terms of NQ values based on the ratio between their prices.
Key Features:
Inputs for QQQ Levels: Users can specify up to four QQQ price levels (default: 300, 310, 320, 330) with a step of 0.1 for precision.
Customizable Appearance: Each level has its own color (default: teal, orange, purple, green) and a shared line width (default: 2).
Time Filters:
Option to display levels only for the current day (show_today_only).
Option to show levels only after 9:30 AM Eastern Time (show_after_open), aligning with market open.
Custom Labels: Each level can have a toggleable label with a customizable template (e.g., "QQQ {qqq} → NQ {mapped}"), showing the QQQ level and its mapped NQ value, formatted to two decimal places.
Dynamic Mapping: Calculates the ratio between NQ and QQQ closing prices to map QQQ levels to NQ equivalents in real-time.
Conditional Display: Levels are plotted only when user-defined conditions (day and time filters) are met, otherwise hidden (na).
Label Placement: Labels are displayed on the last confirmed historical bar, unaffected by time filters, ensuring visibility without cluttering real-time bars.
SuperTrend Strategy with Trend-Based Exits🟩 SuperTrend Strategy with Trend-Based Exits
This is a fully automated trend-following strategy based on the popular SuperTrend indicator, enhanced with a position sizing algorithm tied to stop-loss distance and dynamic entry/exit rules. The strategy is designed for futures trading with an emphasis on sustainable risk, realistic backtesting, and transparent logic.
🧠 Concept and Methodology
The strategy uses the SuperTrend indicator, which is derived from ATR (Average True Range) and is widely used to capture medium- to long-term market trends.
Key features:
✅ Entries are triggered only when the SuperTrend direction changes (trend reversal).
✅ Exits are performed using a dynamic stop-loss placed at the SuperTrend line.
✅ Position size is automatically calculated based on the trader’s fixed dollar risk per trade and the current distance to the stop-loss.
✅ Rounding logic is included to ensure quantity is valid for the exchange’s lot size.
This strategy does not use any take-profit or classic trailing stop — the position is only closed when the trend reverses or the stop is hit by touching the SuperTrend line.
⚙️ Default Parameters
ATR Length: 300
Factor: 7.5
Risk per trade: $90 (3% of the default $3,000 capital)
Lot step: 10
Commission: 0.05%
These default parameters are not universal. They were optimized specifically for STXUSDT swap at 15M timeframe at Bybit and may not produce viable results on other pairs and timeframes.
Users are encouraged to customize the settings according to specific asset’s volatility, timeframe and other characteristics.
❗ These default settings yield meaningful backtesting results on STXUSDT with a reasonable number of trades (105+) over 7-month period. If applied to other assets, results may vary significantly.
📈 Position Sizing Logic
The strategy uses a dynamic position sizing formula:
Pine Script®
position_size = floor((risk_per_trade / stop_loss_distance) / lot_step) * lot_step
This ensures the trader always risks a fixed dollar amount per trade and never exceeds a sustainable equity exposure (recommended 2% or less).
✅ Realism in Backtesting
To ensure realistic and non-misleading backtest results, this strategy includes:
— Slippage and commission settings matching average exchange conditions (commission = 0.05%, slippage 5 ticks).
— Position sizing based on stop-loss distance (not fixed contract quantity).*
— A fixed risk-per-trade model that adheres to responsible capital management principles.
— This is in compliance with TradingView's Script publishing rules and House Rules.
📌 How to Use
Apply the strategy to a clean chart (preferably 15M for STXUSDT by default).
If using another asset, adjust:
- ATR Length
- Factor
- Risk per trade
- Qty step (lot precision for the symbol)
Avoid using with other indicators unless you understand their purpose.
Use the Strategy Tester to evaluate performance and optimize parameters.
⚠️ Disclaimer
This is not financial advice. Always perform forward testing and assess risk before deploying any strategy on live capital. The strategy is designed for educational and experimental use.
Pre-Market & Previous Day Levels 300here is the indicator pre market high low and prev day hihg low levels
NativeLenSA CISD w/1st 5m FVG5m CISD + FVG Indicator which works best on 5m TimeFrame, with the concept of 5m Liquidity sweeps of the previous highs/lows and the next candle closing below/above the opening price of candle that swept the highs/lows.
A line marking +CISD or -CISD will show as soon as the CISD is created, and a first 5m Fair Value Gap will also be displayed. This is advantageous for an extra confluence and re-entry.
The indicator also provides the trader with:
i. The flexibility of allowing to only show Bearish, Bullish or both Bearish and Bullish CISD + FVG,
ii. Showing only London Session, New York Session, or both London and New York Sessions' CISD & FVG,
iii. Option of hiding/showing 5m CISD+FVG on time frames greater than 5m,
iv. Adjustable:
(a) Look back bars (max=300),
(b) CISD line length,
(c) FVG line length,
v. Customizable Bearish and Bullish CISD line colors.
I hope you find value in this indicator, and convenient for time when trading, no CISD markups needed
Info TableOverview
The Info Table V1 is a versatile TradingView indicator tailored for intraday futures traders, particularly those focusing on MESM2 (Micro E-mini S&P 500 futures) on 1-minute charts. It presents essential market insights through two customizable tables: the Main Table for predictive and macro metrics, and the New Metrics Table for momentum and volatility indicators. Designed for high-activity sessions like 9:30 AM–11:00 AM CDT, this tool helps traders assess price alignment, sentiment, and risk in real-time. Metrics update dynamically (except weekly COT data), with optional alerts for key conditions like volatility spikes or momentum shifts.
This indicator builds on foundational concepts like linear regression for predictions and adapts open-source elements for enhanced functionality. Gradient code is adapted from TradingView's Color Library. QQE logic is adapted from LuxAlgo's QQE Weighted Oscillator, licensed under CC BY-NC-SA 4.0. The script is released under the Mozilla Public License 2.0.
Key Features
Two Customizable Tables: Positioned independently (e.g., top-right for Main, bottom-right for New Metrics) with toggle options to show/hide for a clutter-free chart.
Gradient Coloring: User-defined high/low colors (default green/red) for quick visual interpretation of extremes, such as overbought/oversold or high volatility.
Arrows for Directional Bias: In the New Metrics Table, up (↑) or down (↓) arrows appear in value cells based on metric thresholds (top/bottom 25% of range), indicating bullish/high or bearish/low conditions.
Consensus Highlighting: The New Metrics Table's title cells ("Metric" and "Value") turn green if all arrows are ↑ (strong bullish consensus), red if all are ↓ (strong bearish consensus), or gray otherwise.
Predicted Price Plot: Optional line (default blue) overlaying the ML-predicted price for visual comparison with actual price action.
Alerts: Notifications for high/low Frahm Volatility (≥8 or ≤3) and QQE Bias crosses (bullish/bearish momentum shifts).
Main Table Metrics
This table focuses on predictive, positional, and macro insights:
ML-Predicted Price: A linear regression forecast using normalized price, volume, and RSI over a customizable lookback (default 500 bars). Gradient scales from low (red) to high (green) relative to the current price ± threshold (default 100 points).
Deviation %: Percentage difference between current price and predicted price. Gradient highlights extremes (±0.5% default threshold), signaling potential overextensions.
VWAP Deviation %: Percentage difference from Volume Weighted Average Price (VWAP). Gradient indicates if price is above (green) or below (red) fair value (±0.5% default).
FRED UNRATE % Change: Percentage change in U.S. unemployment rate (via FRED data). Cell turns red for increases (economic weakness), green for decreases (strength), gray if zero or disabled.
Open Interest: Total open MESM2 futures contracts. Gradient scales from low (red) to high (green) up to a hardcoded 300,000 threshold, reflecting market participation.
COT Commercial Long/Short: Weekly Commitment of Traders data for commercial positions. Long cell green if longs > shorts (bullish institutional sentiment); Short cell red if shorts > longs (bearish); gray otherwise.
New Metrics Table Metrics
This table emphasizes technical momentum and volatility, with arrows for quick bias assessment:
QQE Bias: Smoothed RSI vs. trailing stop (default length 14, factor 4.236, smooth 5). Green for bullish (RSI > stop, ↑ arrow), red for bearish (RSI < stop, ↓ arrow), gray for neutral.
RSI: Relative Strength Index (default period 14). Gradient from oversold (red, <30 + threshold offset, ↓ arrow if ≤40) to overbought (green, >70 - offset, ↑ arrow if ≥60).
ATR Volatility: Score (1–20) based on Average True Range (default period 14, lookback 50). High scores (green, ↑ if ≥15) signal swings; low (red, ↓ if ≤5) indicate calm.
ADX Trend: Average Directional Index (default period 14). Gradient from weak (red, ↓ if ≤0.25×25 threshold) to strong trends (green, ↑ if ≥0.75×25).
Volume Momentum: Score (1–20) comparing current to historical volume (lookback 50). High (green, ↑ if ≥15) suggests pressure; low (red, ↓ if ≤5) implies weakness.
Frahm Volatility: Score (1–20) from true range over a window (default 24 hours, multiplier 9). Dynamic gradient (green/red/yellow); ↑ if ≥7.5, ↓ if ≤2.5.
Frahm Avg Candle (Ticks): Average candle size in ticks over the window. Blue gradient (or dynamic green/red/yellow); ↑ if ≥0.75 percentile, ↓ if ≤0.25.
Arrows trigger on metric-specific logic (e.g., RSI ≥60 for ↑), providing directional cues without strict color ties.
Customization Options
Adapt the indicator to your strategy:
ML Inputs: Lookback (10–5000 bars) and RSI period (2+) for prediction sensitivity—shorter for volatility, longer for trends.
Timeframes: Individual per metric (e.g., 1H for QQE Bias to match higher frames; blank for chart timeframe).
Thresholds: Adjust gradients and arrows (e.g., Deviation 0.1–5%, ADX 0–100, RSI overbought/oversold).
QQE Settings: Length, factor, and smooth for fine-tuned momentum.
Data Toggles: Enable/disable FRED, Open Interest, COT for focus (e.g., disable macro for pure intraday).
Frahm Options: Window hours (1+), scale multiplier (1–10), dynamic colors for avg candle.
Plot/Table: Line color, positions, gradients, and visibility.
Ideal Use Case
Perfect for MESM2 scalpers and trend traders. Use the Main Table for entry confirmation via predicted deviations and institutional positioning. Leverage the New Metrics Table arrows for short-term signals—enter bullish on green consensus (all ↑), avoid chop on low volatility. Set alerts to catch shifts without constant monitoring.
Why It's Valuable
Info Table V1 consolidates diverse metrics into actionable visuals, answering critical questions: Is price mispriced? Is momentum aligning? Is volatility manageable? With real-time updates, consensus highlights, and extensive customization, it enhances precision in fast markets, reducing guesswork for confident trades.
Note: Optimized for futures; some metrics (OI, COT) unavailable on non-futures symbols. Test on demo accounts. No financial advice—use at your own risk.
The provided script reuses open-source elements from TradingView's Color Library and LuxAlgo's QQE Weighted Oscillator, as noted in the script comments and description. Credits are appropriately given in both the description and code comments, satisfying the requirement for attribution.
Regarding significant improvements and proportion:
The QQE logic comprises approximately 15 lines of code in a script exceeding 400 lines, representing a small proportion (<5%).
Adaptations include integration with multi-timeframe support via request.security, user-customizable inputs for length, factor, and smooth, and application within a broader table-based indicator for momentum bias display (with color gradients, arrows, and alerts). This extends the original QQE beyond standalone oscillator use, incorporating it as one of seven metrics in the New Metrics Table for confluence analysis (e.g., consensus highlighting when all metrics align). These are functional enhancements, not mere stylistic or variable changes.
The Color Library usage is via official import (import TradingView/Color/1 as Color), leveraging built-in gradient functions without copying code, and applied to enhance visual interpretation across multiple metrics.
The script complies with the rules: reused code is minimal, significantly improved through integration and expansion, and properly credited. It qualifies for open-source publication under the Mozilla Public License 2.0, as stated.
TZanalyserTZanalyser (Trend Zone Monitor With Trend Strength, Volume Focus And -Events Markers)
Before I used TrendZones to manage my portfolio I used Fibonacci Zone Oscillator as my favorite in the sub panel, accompanied with another subpanel indicator which I never published called IncliValue and also REVE Cohorts.
TZanalyser inherits Ideas and code from all three of them: The visual and the idea of using a channel as the basis for an oscillator depicted as a histogram, is taken from the FibZone Oscillator. The idea of providing a number to evaluate the trend is taken from IncliValue. The idea to create a horizontal line which indicates high and low volume focus completed with markers for volume events, is taken from REVE-cohorts.
These ideas are combined in one sleek visual called TZanalyser. TZ stand for TrendZones, because the histogram is based on it.
The histogram.
Depicted is the distance of the price from COG as percent. The distance between Upper Curve and Lower Curve is used as 100%. The values may reach between 300 and -300. The colors indicate in which zone the candle lives, blue in the blue zone, green in the green zone etc. Despite the absence of a gray zone, there are gray bars. These depict candles that wrap around COG. Because hl2 is used as price, some gray bars point up and others down. The orange and red bars point down because the orange and red downtrend zones are below COG.
Use of the histogram.
Sometimes I need to create a list of stocks which are in uptrend in monthly, weekly and daily charts from the stocks I follow in my universe. This job is done fast and easy by looking at the last bar of the histogram. The histogram also gives a quick evaluation of how the stock fared in the past.
The number.
Suppose I need to allocate some money to another stock, selected a few, looked into news and gurus and they look equally good. Then it is nice to be able to find out which has the best charts. Which one has the strongest uptrend. For this purpose this number can be consulted, because it indicates somehow the strength of the trend. It is an integer between 20 and -20, the closer to 20 the stronger the uptrend, closer to -20 indicates a stronger downtrend. The color of the background is the same as the last column of the histogram.
Volume focus and events
The horizontal lines depict volume focus, the line below the focus that comes with the uptrend columns pointing up, the one above the focus for the downtrend columns pointing down. Thes line have tree colors: maroon for high volume focus, green for normal volume and gray for low volume situations. Between the lines and the histogram triangles appear at volume events, a green triangle when the candle comes with high volume, i.e. 120-200 percent of normal, maroon when extreme volume, i.e. more than 200 percent of normal.
The direction of these triangles is that of the histogram, i.e. when the price is higher, direction is up and vice versa.
Take care and have fun.
Round Number Levels ProRound Number Levels Pro is a powerful support and resistance indicator that automatically plots psychological price levels on your chart.
What it does:
- Displays major round number levels (100, 200, 300, etc.) with prominent lines
- Shows mid-level lines (50, 150, 250, etc.) for additional reference points
- All lines extend across the entire chart for maximum visibility
- Automatically adjusts levels based on current price action
Key Features:
- Customizable Font Sizes - Large text for main levels, normal for mid-levels
- Clean Black Styling - Professional appearance that works on any chart background
- Flexible Line Styles - Choose solid, dashed, or dotted lines for main and mid levels
- Adjustable Parameters - Control number of levels, rounding increments, and label positioning
- Full Chart Extension - Lines extend both directions for complete price reference
Perfect for:
- Day traders looking for key psychological support/resistance levels
- Swing traders identifying major price zones
- Any trader who uses round numbers as decision points
How to use:
Simply add to your chart and the indicator will automatically plot relevant round number levels. Customize the settings to match your trading style and timeframe.
These psychological levels are where many traders make decisions, often creating natural support and resistance zones in the market.
UT Bot + LinReg Candles (Dual Sensitivity)
Script Description:
This indicator combines the popular UT Bot Alerts system with Linear Regression Candles (open source) for enhanced trend detection and trading signals in one singel script. The UT Bot features independent, then 2 x ATR sensitivity and periods controls for buy and sell signals, allowing you to fine-tune entries and exits to match your strategy. The script also overlays colored Linear Regression Candles with an optional signal line, helping you visually identify trend strength and direction. All calculations are performed on standard chart prices (no Heikin Ashi). Suitable for all asset classes and timeframes.
Eample setting for usdjpy 5 min chart for repeated buy and sell singnals based on trend:
BUY ATR period 300 multiplier 1
SELL ATR period 1 multiplier 2
Disclaimer:
This script is for informational and educational purposes only. It is not financial advice. Use at your own risk; the author assumes no responsibility for any trading results or losses.
Credits goes to to Ugurvu for linreg candles and quantnomad for UT Bot alerts that make this script possible.
Author: Patrick
Aetherium Institutional Market Resonance EngineAetherium Institutional Market Resonance Engine (AIMRE)
A Three-Pillar Framework for Decoding Institutional Activity
🎓 THEORETICAL FOUNDATION
The Aetherium Institutional Market Resonance Engine (AIMRE) is a multi-faceted analysis system designed to move beyond conventional indicators and decode the market's underlying structure as dictated by institutional capital flow. Its philosophy is built on a singular premise: significant market moves are preceded by a convergence of context , location , and timing . Aetherium quantifies these three dimensions through a revolutionary three-pillar architecture.
This system is not a simple combination of indicators; it is an integrated engine where each pillar's analysis feeds into a central logic core. A signal is only generated when all three pillars achieve a state of resonance, indicating a high-probability alignment between market organization, key liquidity levels, and cyclical momentum.
⚡ THE THREE-PILLAR ARCHITECTURE
1. 🌌 PILLAR I: THE COHERENCE ENGINE (THE 'CONTEXT')
Purpose: To measure the degree of organization within the market. This pillar answers the question: " Is the market acting with a unified purpose, or is it chaotic and random? "
Conceptual Framework: Institutional campaigns (accumulation or distribution) create a non-random, organized market environment. Retail-driven or directionless markets are characterized by "noise" and chaos. The Coherence Engine acts as a filter to ensure we only engage when institutional players are actively steering the market.
Formulaic Concept:
Coherence = f(Dominance, Synchronization)
Dominance Factor: Calculates the absolute difference between smoothed buying pressure (volume-weighted bullish candles) and smoothed selling pressure (volume-weighted bearish candles), normalized by total pressure. A high value signifies a clear winner between buyers and sellers.
Synchronization Factor: Measures the correlation between the streams of buying and selling pressure over the analysis window. A high positive correlation indicates synchronized, directional activity, while a negative correlation suggests choppy, conflicting action.
The final Coherence score (0-100) represents the percentage of market organization. A high score is a prerequisite for any signal, filtering out unpredictable market conditions.
2. 💎 PILLAR II: HARMONIC LIQUIDITY MATRIX (THE 'LOCATION')
Purpose: To identify and map high-impact institutional footprints. This pillar answers the question: " Where have institutions previously committed significant capital? "
Conceptual Framework: Large institutional orders leave indelible marks on the market in the form of anomalous volume spikes at specific price levels. These are not random occurrences but are areas of intense historical interest. The Harmonic Liquidity Matrix finds these footprints and consolidates them into actionable support and resistance zones called "Harmonic Nodes."
Algorithmic Process:
Footprint Identification: The engine scans the historical lookback period for candles where volume > average_volume * Institutional_Volume_Filter. This identifies statistically significant volume events.
Node Creation: A raw node is created at the mean price of the identified candle.
Dynamic Clustering: The engine uses an ATR-based proximity algorithm. If a new footprint is identified within Node_Clustering_Distance (ATR) of an existing Harmonic Node, it is merged. The node's price is volume-weighted, and its magnitude is increased. This prevents chart clutter and consolidates nearby institutional orders into a single, more significant level.
Node Decay: Nodes that are older than the Institutional_Liquidity_Scanback period are automatically removed from the chart, ensuring the analysis remains relevant to recent market dynamics.
3. 🌊 PILLAR III: CYCLICAL RESONANCE MATRIX (THE 'TIMING')
Purpose: To identify the market's dominant rhythm and its current phase. This pillar answers the question: " Is the market's immediate energy flowing up or down? "
Conceptual Framework: Markets move in waves and cycles of varying lengths. Trading in harmony with the current cyclical phase dramatically increases the probability of success. Aetherium employs a simplified wavelet analysis concept to decompose price action into short, medium, and long-term cycles.
Algorithmic Process:
Cycle Decomposition: The engine calculates three oscillators based on the difference between pairs of Exponential Moving Averages (e.g., EMA8-EMA13 for short cycle, EMA21-EMA34 for medium cycle).
Energy Measurement: The 'energy' of each cycle is determined by its recent volatility (standard deviation). The cycle with the highest energy is designated as the "Dominant Cycle."
Phase Analysis: The engine determines if the dominant cycles are in a bullish phase (rising from a trough) or a bearish phase (falling from a peak).
Cycle Sync: The highest conviction timing signals occur when multiple cycles (e.g., short and medium) are synchronized in the same direction, indicating broad-based momentum.
🔧 COMPREHENSIVE INPUT SYSTEM
Pillar I: Market Coherence Engine
Coherence Analysis Window (10-50, Default: 21): The lookback period for the Coherence Engine.
Lower Values (10-15): Highly responsive to rapid shifts in market control. Ideal for scalping but can be sensitive to noise.
Balanced (20-30): Excellent for day trading, capturing the ebb and flow of institutional sessions.
Higher Values (35-50): Smoother, more stable reading. Best for swing trading and identifying long-term institutional campaigns.
Coherence Activation Level (50-90%, Default: 70%): The minimum market organization required to enable signal generation.
Strict (80-90%): Only allows signals in extremely clear, powerful trends. Fewer, but potentially higher quality signals.
Standard (65-75%): A robust filter that effectively removes choppy conditions while capturing most valid institutional moves.
Lenient (50-60%): Allows signals in less-organized markets. Can be useful in ranging markets but may increase false signals.
Pillar II: Harmonic Liquidity Matrix
Institutional Liquidity Scanback (100-400, Default: 200): How far back the engine looks for institutional footprints.
Short (100-150): Focuses on recent institutional activity, providing highly relevant, immediate levels.
Long (300-400): Identifies major, long-term structural levels. These nodes are often extremely powerful but may be less frequent.
Institutional Volume Filter (1.3-3.0, Default: 1.8): The multiplier for detecting a volume spike.
High (2.5-3.0): Only registers climactic, undeniable institutional volume. Fewer, but more significant nodes.
Low (1.3-1.7): More sensitive, identifying smaller but still relevant institutional interest.
Node Clustering Distance (0.2-0.8 ATR, Default: 0.4): The ATR-based distance for merging nearby nodes.
High (0.6-0.8): Creates wider, more consolidated zones of liquidity.
Low (0.2-0.3): Creates more numerous, precise, and distinct levels.
Pillar III: Cyclical Resonance Matrix
Cycle Resonance Analysis (30-100, Default: 50): The lookback for determining cycle energy and dominance.
Short (30-40): Tunes the engine to faster, shorter-term market rhythms. Best for scalping.
Long (70-100): Aligns the timing component with the larger primary trend. Best for swing trading.
Institutional Signal Architecture
Signal Quality Mode (Professional, Elite, Supreme): Controls the strictness of the three-pillar confluence.
Professional: Loosest setting. May generate signals if two of the three pillars are in strong alignment. Increases signal frequency.
Elite: Balanced setting. Requires a clear, unambiguous resonance of all three pillars. The recommended default.
Supreme: Most stringent. Requires perfect alignment of all three pillars, with each pillar exhibiting exceptionally strong readings (e.g., coherence > 85%). The highest conviction signals.
Signal Spacing Control (5-25, Default: 10): The minimum bars between signals to prevent clutter and redundant alerts.
🎨 ADVANCED VISUAL SYSTEM
The visual architecture of Aetherium is designed not merely for aesthetics, but to provide an intuitive, at-a-glance understanding of the complex data being processed.
Harmonic Liquidity Nodes: The core visual element. Displayed as multi-layered, semi-transparent horizontal boxes.
Magnitude Visualization: The height and opacity of a node's "glow" are proportional to its volume magnitude. More significant nodes appear brighter and larger, instantly drawing the eye to key levels.
Color Coding: Standard nodes are blue/purple, while exceptionally high-magnitude nodes are highlighted in an accent color to denote critical importance.
🌌 Quantum Resonance Field: A dynamic background gradient that visualizes the overall market environment.
Color: Shifts from cool blues/purples (low coherence) to energetic greens/cyans (high coherence and organization), providing instant context.
Intensity: The brightness and opacity of the field are influenced by total market energy (a composite of coherence, momentum, and volume), making powerful market states visually apparent.
💎 Crystalline Lattice Matrix: A geometric web of lines projected from a central moving average.
Mathematical Basis: Levels are projected using multiples of the Golden Ratio (Phi ≈ 1.618) and the ATR. This visualizes the natural harmonic and fractal structure of the market. It is not arbitrary but is based on mathematical principles of market geometry.
🧠 Synaptic Flow Network: A dynamic particle system visualizing the engine's "thought process."
Node Density & Activation: The number of particles and their brightness/color are tied directly to the Market Coherence score. In high-coherence states, the network becomes a dense, bright, and organized web. In chaotic states, it becomes sparse and dim.
⚡ Institutional Energy Waves: Flowing sine waves that visualize market volatility and rhythm.
Amplitude & Speed: The height and speed of the waves are directly influenced by the ATR and volume, providing a feel for market energy.
📊 INSTITUTIONAL CONTROL MATRIX (DASHBOARD)
The dashboard is the central command console, providing a real-time, quantitative summary of each pillar's status.
Header: Displays the script title and version.
Coherence Engine Section:
State: Displays a qualitative assessment of market organization: ◉ PHASE LOCK (High Coherence), ◎ ORGANIZING (Moderate Coherence), or ○ CHAOTIC (Low Coherence). Color-coded for immediate recognition.
Power: Shows the precise Coherence percentage and a directional arrow (↗ or ↘) indicating if organization is increasing or decreasing.
Liquidity Matrix Section:
Nodes: Displays the total number of active Harmonic Liquidity Nodes currently being tracked.
Target: Shows the price level of the nearest significant Harmonic Node to the current price, representing the most immediate institutional level of interest.
Cycle Matrix Section:
Cycle: Identifies the currently dominant market cycle (e.g., "MID ") based on cycle energy.
Sync: Indicates the alignment of the cyclical forces: ▲ BULLISH , ▼ BEARISH , or ◆ DIVERGENT . This is the core timing confirmation.
Signal Status Section:
A unified status bar that provides the final verdict of the engine. It will display "QUANTUM SCAN" during neutral periods, or announce the tier and direction of an active signal (e.g., "◉ TIER 1 BUY ◉" ), highlighted with the appropriate color.
🎯 SIGNAL GENERATION LOGIC
Aetherium's signal logic is built on the principle of strict, non-negotiable confluence.
Condition 1: Context (Coherence Filter): The Market Coherence must be above the Coherence Activation Level. No signals can be generated in a chaotic market.
Condition 2: Location (Liquidity Node Interaction): Price must be actively interacting with a significant Harmonic Liquidity Node.
For a Buy Signal: Price must be rejecting the Node from below (testing it as support).
For a Sell Signal: Price must be rejecting the Node from above (testing it as resistance).
Condition 3: Timing (Cycle Alignment): The Cyclical Resonance Matrix must confirm that the dominant cycles are synchronized with the intended trade direction.
Signal Tiering: The Signal Quality Mode input determines how strictly these three conditions must be met. 'Supreme' mode, for example, might require not only that the conditions are met, but that the Market Coherence is exceptionally high and the interaction with the Node is accompanied by a significant volume spike.
Signal Spacing: A final filter ensures that signals are spaced by a minimum number of bars, preventing over-alerting in a single move.
🚀 ADVANCED TRADING STRATEGIES
The Primary Confluence Strategy: The intended use of the system. Wait for a Tier 1 (Elite/Supreme) or Tier 2 (Professional/Elite) signal to appear on the chart. This represents the alignment of all three pillars. Enter after the signal bar closes, with a stop-loss placed logically on the other side of the Harmonic Node that triggered the signal.
The Coherence Context Strategy: Use the Coherence Engine as a standalone market filter. When Coherence is high (>70%), favor trend-following strategies. When Coherence is low (<50%), avoid new directional trades or favor range-bound strategies. A sharp drop in Coherence during a trend can be an early warning of a trend's exhaustion.
Node-to-Node Trading: In a high-coherence environment, use the Harmonic Liquidity Nodes as both entry points and profit targets. For example, after a BUY signal is generated at one Node, the next Node above it becomes a logical first profit target.
⚖️ RESPONSIBLE USAGE AND LIMITATIONS
Decision Support, Not a Crystal Ball: Aetherium is an advanced decision-support tool. It is designed to identify high-probability conditions based on a model of institutional behavior. It does not predict the future.
Risk Management is Paramount: No indicator can replace a sound risk management plan. Always use appropriate position sizing and stop-losses. The signals provided are probabilistic, not certainties.
Past Performance Disclaimer: The market models used in this script are based on historical data. While robust, there is no guarantee that these patterns will persist in the future. Market conditions can and do change.
Not a "Set and Forget" System: The indicator performs best when its user understands the concepts behind the three pillars. Use the dashboard and visual cues to build a comprehensive view of the market before acting on a signal.
Backtesting is Essential: Before applying this tool to live trading, it is crucial to backtest and forward-test it on your preferred instruments and timeframes to understand its unique behavior and characteristics.
🔮 CONCLUSION
The Aetherium Institutional Market Resonance Engine represents a paradigm shift from single-variable analysis to a holistic, multi-pillar framework. By quantifying the abstract concepts of market context, location, and timing into a unified, logical system, it provides traders with an unprecedented lens into the mechanics of institutional market operations.
It is not merely an indicator, but a complete analytical engine designed to foster a deeper understanding of market dynamics. By focusing on the core principles of institutional order flow, Aetherium empowers traders to filter out market noise, identify key structural levels, and time their entries in harmony with the market's underlying rhythm.
"In all chaos there is a cosmos, in all disorder a secret order." - Carl Jung
— Dskyz, Trade with insight. Trade with confluence. Trade with Aetherium.
Ultimate Regression Channel v5.0 [WhiteStone_Ibrahim]Ultimate Regression Channel v5.0: Comprehensive User Guide
This indicator is designed to visualize the current trend, potential support/resistance levels, and market volatility through a statistical analysis of price action. At its core, it plots a regression line (a trend line) based on prices over a specific period and adds channels based on standard deviation around this line.
1. Core Features and Settings
Length Mode:
Numerical (Manual): You define the number of bars to be used for the regression channel calculation. You can use lower values (e.g., 50-100) for short-term analysis and higher values (e.g., 200-300) to identify long-term trends.
Automatic (Based on Market Structure): This mode automatically draws the channel starting from the highest high or lowest low that has formed within the Auto Scan Period. This allows the indicator to adapt itself to significant market turning points (swing points), which is highly useful.
Regression Model:
Linear: Calculates the trend as a straight line. It generally works well in stable, short-to-medium-term trends.
Logarithmic: Calculates the trend as a curved line. It more accurately reflects price action, especially on long-term charts or for assets that experience exponential growth/decline (like cryptocurrencies or growth stocks).
Channel Widths:
These settings determine how far from the central trend line (in terms of standard deviations) the channels will be drawn.
The 0 (Inner), 1 (Middle), and 2 (Outer) channels represent the "normal" range of price movement and the "extreme" zones. Statistically, about 95% of all price action occurs within the outer channels (2nd standard deviation).
2. Visual Extras and Their Interpretation
Breakout Style:
This feature alerts you when the price closes above the uppermost channel (Channel 2) with a green arrow/background or below the lowermost channel with a red arrow/background.
This is a very important signal. A breakout can signify that the current trend is strengthening and likely to continue (a breakout/trend-following strategy) or that the market has become overextended and may be due for a reversal (an exhaustion/top-bottom signal). It is critical to confirm this signal with other indicators (e.g., RSI, Volume).
Info Label:
This provides an at-a-glance summary of the channel on the right side of the chart:
Trend Status: Identifies the trend as "Uptrend," "Downtrend," or "Sideways" based on the slope of the centerline. The Horizontal Threshold setting allows you to filter out noise by treating very small slopes as "Sideways."
Regression Model and Length: Shows your current settings.
Trend Slope: A numerical value representing how steep or weak the trend is.
Channel Width: Shows the price difference between the outermost channels. This is a measure of current volatility. A widening channel indicates increasing volatility, while a narrowing one indicates decreasing volatility.
3. What Users Should Pay Attention To & Best Practices
Define Your Strategy: Mean Reversion or Breakout?
Mean Reversion: If the market is in a ranging or gently trending phase, the price will tend to revert to the centerline after hitting the outer channels (overbought/oversold zones). In this case, the outer channels can be considered opportunities to sell (upper channel) or buy (lower channel).
Breakout: If a strong trend is in place, a price close beyond an outer channel can be a sign that the trend is accelerating. In this scenario, one might consider taking a position in the direction of the breakout. Correctly analyzing the current market state (ranging vs. trending) is key to deciding which strategy to employ.
Don't Use It in Isolation: No indicator is a holy grail. Use the Regression Channel in conjunction with other tools. Confirm signals with RSI divergences for overbought/oversold conditions, Moving Averages for the overall trend direction, or Volume indicators to confirm the strength of a breakout.
Choose the Right Model: On shorter-term charts (e.g., 1-hour, 4-hour), the Linear model is often sufficient. However, on long-term charts like the daily, weekly, or monthly, the Logarithmic model will provide much more accurate results, especially for assets with parabolic movements.
The Power of Automatic Mode: The Automatic length mode is often the most practical choice because it finds the most logical starting point for you. It saves you the trouble of adjusting settings, especially when analyzing different assets or timeframes.
Use the Alerts: If you don't want to miss the moment the price touches a key channel line, set up an alert from the Alert Settings section for your desired line (e.g., only the "Outer Channels"). This helps you catch opportunities even when you are not in front of the screen.
TrueTrend MaxRThe TrueTrend MaxR indicator is designed to identify the most consistent exponential price trend over extended periods. It uses statistical analysis on log-transformed prices to find the trendline that best fits historical price action, and highlights the most frequently tested or traded level within that trend channel.
For optimal results, especially on high timeframes such as weekly or monthly, it is recommended to use this indicator on charts set to logarithmic scale. This ensures proper visual alignment with the exponential nature of long-term price movements.
How it works
The indicator tests 50 different lookback periods, ranging from 300 to 1280 bars. For each period, it:
- Applies a linear regression on the natural logarithm of the price
- Computes the slope and intercept of the trendline
- Calculates the unbiased standard deviation from the regression line
- Measures the correlation strength using Pearson's R coefficient
The period with the highest Pearson R value is selected, meaning the trendline drawn corresponds to the log-scale trend with the best statistical fit.
Trendline and deviation bands
Once the optimal period is identified, the indicator plots:
- A main log-scale trendline
- Upper and lower bands, based on a user-defined multiple of the standard deviation
These bands help visualize how far price deviates from its core trend, and define the range of typical fluctuations.
Point of Control (POC)
Inside the trend channel, the space between upper and lower bands is divided into 15 logarithmic levels. The script evaluates how often price has interacted with each level, using one of two selectable methods:
- Touches: Counts the number of candles crossing each level
- Volume: Weighs each touch by the traded volume at that candle
The level with the highest cumulative interaction is considered the dynamic Point of Control (POC), and is plotted as a line.
Annualized performance and confidence display
When used on daily or weekly timeframes, the script also calculates the annualized return (CAGR) based on the detected trend, and displays:
- A performance estimate in percentage terms
- A textual label describing the confidence level based on the Pearson R value
Why this indicator is useful
- Automatically detects the most statistically consistent exponential trendline
- Designed for log-scale analysis, suited to long-term investment charts
- Highlights key price levels frequently visited or traded within the trend
- Provides objective, data-based trend and volatility insights
- Displays annualized growth rate and correlation strength for quick evaluation
Notes
- All calculations are performed only on the last bar
- No future data is used, and the script does not repaint
- Works on any instrument or timeframe, with optimal use on higher timeframes and logarithmic scaling
MNQ EMA StrategyThis strategy is not perfected yet. ONE MINUTE TIMEFRAME
The goal is to take Longs above the 5 ema when price is above all the 200, 30, and 5 ema.
Short side is when candle closes below the 5 ema and price is below the 300, 30, and 5 ema.
I use candle range blocks for different time zones to avoid excess orders from being triggered. As well as blocks when stoploss is hit or after a profitable trade of certain ticks.
There is an RSI to avoid trades when there isn't too much movement.
My goal is to get an entry when price trades above the 5 ema and then next candle passes it by .25 instead of entering immediately. The stoploss as the low of candle before entry and TP as 3 times the stoploss. I've tried a million times to make it like this but I don't know how to use pine script or Code.
The sell side is basically the same, enter at candle close below 5 ema wait for low to get swept to enter and stoploss above previous high, with TP 3 times the stoploss.
Publishing in hopes anyone knows how to adjust this
CAUTION THIS STRATEGY WORKS WITH CURRENT PRICE ACTION DUE TO ME USING RECENT TICK COUNT RATHER THAN BASED ON CANDLES OR PERCENTAGES. THIS WILL ONLY WORK AS LONG AS MARKET MOVES AS IT HAS BEEN SINCE 2024. CME_MINI:MNQ1!
Hurst Exponent Oscillator [PhenLabs]📊 Hurst Exponent Oscillator -
Version: PineScript™ v5
📌 Description
The Hurst Exponent Oscillator (HEO) by PhenLabs is a powerful tool developed for traders who want to distinguish between trending, mean-reverting, and random market behaviors with clarity and precision. By estimating the Hurst Exponent—a statistical measure of long-term memory in financial time series—this indicator helps users make sense of underlying market dynamics that are often not visible through traditional moving averages or oscillators.
Traders can quickly know if the market is likely to continue its current direction (trending), revert to the mean, or behave randomly, allowing for more strategic timing of entries and exits. With customizable smoothing and clear visual cues, the HEO enhances decision-making in a wide range of trading environments.
🚀 Points of Innovation
Integrates advanced Hurst Exponent calculation via Rescaled Range (R/S) analysis, providing unique market character insights.
Offers real-time visual cues for trending, mean-reverting, or random price action zones.
User-controllable EMA smoothing reduces noise for clearer interpretation.
Dynamic coloring and fill for immediate visual categorization of market regime.
Configurable visual thresholds for critical Hurst levels (e.g., 0.4, 0.5, 0.6).
Fully customizable appearance settings to fit different charting preferences.
🔧 Core Components
Log Returns Calculation: Computes log returns of the selected price source to feed into the Hurst calculation, ensuring robust and scale-independent analysis.
Rescaled Range (R/S) Analysis: Assesses the dispersion and cumulative deviation over a rolling window, forming the core statistical basis for the Hurst exponent estimate.
Smoothing Engine: Applies Exponential Moving Average (EMA) smoothing to the raw Hurst value for enhanced clarity.
Dynamic Rolling Windows: Utilizes arrays to maintain efficient, real-time calculations over user-defined lengths.
Adaptive Color Logic: Assigns different highlight and fill colors based on the current Hurst value zone.
🔥 Key Features
Visually differentiates between trending, mean-reverting, and random market modes.
User-adjustable lookback and smoothing periods for tailored sensitivity.
Distinct fill and line styles for each regime to avoid ambiguity.
On-chart reference lines for strong trending and mean-reverting thresholds.
Works with any price series (close, open, HL2, etc.) for versatile application.
🎨 Visualization
Hurst Exponent Curve: Primary plotted line (smoothed if EMA is used) reflects the ongoing estimate of the Hurst exponent.
Colored Zone Filling: The area between the Hurst line and the 0.5 reference line is filled, with color and opacity dynamically indicating the current market regime.
Reference Lines: Dash/dot lines mark standard Hurst thresholds (0.4, 0.5, 0.6) to contextualize the current regime.
All visual elements can be customized for thickness, color intensity, and opacity for user preference.
📖 Usage Guidelines
Data Settings
Hurst Calculation Length
Default: 100
Range: 10-300
Description: Number of bars used in Hurst calculation; higher values mean longer-term analysis, lower values for quicker reaction.
Data Source
Default: close
Description: Select which data series to analyze (e.g., Close, Open, HL2).
Smoothing Length (EMA)
Default: 5
Range: 1-50
Description: Length for smoothing the Hurst value; higher settings yield smoother but less responsive results.
Style Settings
Trending Color (Hurst > 0.5)
Default: Blue tone
Description: Color used when trending regime is detected.
Mean-Reverting Color (Hurst < 0.5)
Default: Orange tone
Description: Color used when mean-reverting regime is detected.
Neutral/Random Color
Default: Soft blue
Description: Color when market behavior is indeterminate or shifting.
Fill Opacity
Default: 70-80
Range: 0-100
Description: Transparency of area fills—higher opacity for stronger visual effect.
Line Width
Default: 2
Range: 1-5
Description: Thickness of the main indicator curve.
✅ Best Use Cases
Identifying if a market is regime-shifting from trending to mean-reverting (or vice versa).
Filtering signals in automated or systematic trading strategies.
Spotting periods of randomness where trading signals should be deprioritized.
Enhancing mean-reversion or trend-following models with regime-awareness.
⚠️ Limitations
Not predictive: Reflects current and recent market state, not future direction.
Sensitive to input parameters—overfitting may occur if settings are changed too frequently.
Smoothing can introduce lag in regime recognition.
May not work optimally in markets with structural breaks or extreme volatility.
💡 What Makes This Unique
Employs advanced statistical market analysis (Hurst exponent) rarely found in standard toolkits.
Offers immediate regime visualization through smart dynamic coloring and zone fills.
🔬 How It Works
Rolling Log Return Calculation:
Each new price creates a log return, forming the basis for robust, non-linear analysis. This ensures all price differences are treated proportionally.
Rescaled Range Analysis:
A rolling window maintains cumulative deviations and computes the statistical “range” (max-min of deviations). This is compared against the standard deviation to estimate “memory”.
Exponent Calculation & Smoothing:
The raw Hurst value is translated from the log of the rescaled range ratio, and then optionally smoothed via EMA to dampen noise and false signals.
Regime Detection Logic:
The smoothed value is checked against 0.5. Values above = trending; below = mean-reverting; near 0.5 = random. These control plot/fill color and zone display.
💡 Note:
Use longer calculation lengths for major market character study, and shorter ones for tactical, short-term adaptation. Smoothing balances noise vs. lag—find a best fit for your trading style. Always combine regime awareness with broader technical/fundamental context for best results.
CAN INDICATORCAN Moving Averages Indicator - Feature Guide
1. Multiple Moving Averages (20 MAs)
- Supports up to 20 individual moving averages
- Each MA can be independently configured:
- Enable/Disable toggle
- Length (period) setting
- Type selection (SMA, EMA, DEMA, VWMA, RMA, WMA)
- Color customization
- Individual timeframe settings when global timeframe is disabled
Pre-configured MA Settings:
1. MA1-8: SMA type
- Lengths: 20, 50, 100, 200, 365, 489, 600, 1460
2. MA9-20: EMA type
- Lengths: 30, 60, 120, 240, 300, 400, 500, 700, 800, 900, 1000, 2000
2. Global Timeframe Settings
Location: Global Settings group
Features:
- Use Global Timeframe: Toggle to use one timeframe for all MAs
- Global Timeframe: Select the timeframe to apply globally
3. Label Display Options
Location: Main Inputs section
Controls:
- Show MA Type: Display MA type (SMA, EMA, etc.)
- Show MA Length: Display period length
- Show Resolution: Display timeframe
- Label Offset: Adjust label position
4. Cross Alerts System
Location: Cross Alerts group
Features:
1. Price Crosses:
- Alerts when price crosses any selected MA
- Select MA to monitor (1-20)
- Triggers on crossover/crossunder
2. MA Crosses:
- Alerts when one MA crosses another
- Select fast MA (1-20)
- Select slow MA (1-20)
- Triggers on crossover/crossunder
5. Relative Strength (RS) Analysis
Location: Relative Strength group
Features:
- Select any MA to monitor (1-20)
- Compares MA to its own average
- Adjustable RS Length (default 14)
- Visual feedback via background color:
- Green: MA above its average (uptrend)
- Red: MA below its average (downtrend)
- Customizable colors and transparency
6. Moving Average Types Available
1. **SMA** (Simple Moving Average)
- Equal weight to all prices
2. **EMA** (Exponential Moving Average)
- More weight to recent prices
3. **DEMA** (Double Exponential Moving Average)
- Reduced lag compared to EMA
4. **VWMA** (Volume Weighted Moving Average)
- Incorporates volume data
5. **RMA** (Running Moving Average)
- Smoother than EMA
6. **WMA** (Weighted Moving Average)
- Linear weight distribution
Usage Tips
1. **For Trend Following:**
- Enable longer-period MAs (MA4-MA8)
- Use cross alerts between long-term MAs
- Monitor RS for trend strength
2. **For Short-term Trading:**
- Focus on shorter-period MAs (MA1-MA3, MA9-MA11)
- Enable price cross alerts
- Use multiple timeframe analysis
3. **For Multiple Timeframe Analysis:**
- Disable global timeframe
- Set different timeframes for each MA
- Compare MA relationships across timeframes
4. **For Performance:**
- Disable unused MAs
- Limit active alerts to necessary pairs
- Use RS selectively on key MAs
Multi-SMA Dashboard (10 SMAs)Description:
This script, "Multi-SMA Dashboard (10 SMAs)," creates a dashboard on a TradingView chart to analyze ten Simple Moving Averages (SMAs) of varying lengths. It overlays the chart and displays a table with each SMA’s direction, price position relative to the SMA, and angle of movement, providing a comprehensive trend overview.
How It Works:
1. **Inputs**: Users define lengths for 10 SMAs (default: 5, 10, 20, 50, 100, 150, 200, 250, 300, 350), select a price source (default: close), and customize table appearance and options like angle units (degrees/radians) and debug plots.
2. **SMA Calculation**: Computes 10 SMAs using the `ta.sma()` function with user-specified lengths and price source.
3. **Direction Determination**: The `sma_direction()` function checks each SMA’s trend:
- "Up" if current SMA > previous SMA.
- "Down" if current SMA < previous SMA.
- "Flat" if equal (no strength distinction).
4. **Price Position**: Compares the price source to each SMA, labeling it "Above" or "Below."
5. **Angle Calculation**: Tracks the most recent direction change point for each SMA and calculates its angle (atan of price change over time) in degrees or radians, based on the `showInRadians` toggle.
6. **Table Display**: A 12-column table shows:
- Columns 1-10: SMA name, direction (Up/Down/Flat), Above/Below status, and angle.
- Column 11: Summary of Up, Down, and Flat counts.
- Colors reflect direction (lime for Up/Above, red for Down/Below, white for Flat).
7. **Debug Option**: Optionally plots all SMAs and price for visual verification when `debug_plots_toggle` is enabled.
Indicators Used:
- Simple Moving Averages (SMAs): 10 user-configurable SMAs ranging from short-term (e.g., 5) to long-term (e.g., 350) periods.
The script runs continuously, updating the table on each bar, and overlays the chart to assist traders in assessing multi-timeframe trend direction and momentum without cluttering the view unless debug mode is active.
