Webhook Candle Sender (OHLCV)This indicator sends OHLCV (Open, High, Low, Close, Volume) candle data via webhook on every confirmed bar close.
It is designed to integrate TradingView with an external trading or analytics system (e.g. a local Flask server, paper trading engine, or algorithmic agent).
Features:
• Sends data only on bar close (no repainting)
• Works on any symbol (stocks, crypto, forex)
• Works on any timeframe
• Outputs structured JSON suitable for APIs and bots
• Uses TradingView alert() function for webhook delivery
Typical use cases:
• Algorithmic trading research
• Paper trading systems
• Backtesting external strategies
• Educational and learning purposes
This script does NOT place trades, manage risk, or provide trading signals.
It only transmits candle data.
No financial advice is provided.
In den Scripts nach "backtesting" suchen
Commodity Channel Index CCI + EMA strategy
================================================================================
COMMODITY CHANNEL INDEX CCI + EMA STRATEGY - STRATEGY GUIDE 📊
================================================================================
💡 COLLABORATION & SUPPORT
---------------------------
If you want to collaborate, have an idea for a strategy, or need help writing
or customizing code, send an email to burdytrader@gmail.com or send me a
message. Suggestions, ideas, and comments are always welcome! 🤝
I also develop automated trading codes for other trading platforms including:
- CTrader (C#)
- MetaTrader 4 (MQL4)
- MetaTrader 5 (MQL5)
If you need a strategy converted or developed for any of these platforms, feel
free to contact me!
================================================================================
⚠️ IMPORTANT: INSTRUMENT SELECTION 📈
-------------------------------------
This strategy performs BEST with currency pairs (forex). The CCI indicator
works particularly well in the forex market due to the nature of currency
movements and the effectiveness of the CCI in identifying overbought and
oversold conditions in trending markets.
Why Currency Pairs? 🎯
- CCI is highly effective in identifying reversals in forex markets
- Currency pairs show clear overbought/oversold patterns
- EMA filter (50/200) aligns well with major forex trends
- High liquidity ensures reliable signal execution
Performance Highlights:
In specific currency pairs, when properly configured, this strategy can achieve:
- Profit Factor: Over 2.0
- Win Rate: Up to 70%
- Particularly effective pairs: USDCAD, EURUSD, GBPJPY
While the strategy can work with other instruments (stocks, indices, commodities),
currency pairs provide the most consistent and reliable results. For optimal
performance, focus on major forex pairs with good liquidity and clear trending
characteristics.
================================================================================
WHAT DOES THIS STRATEGY DO? 🎯
---------------------------
This strategy combines the Commodity Channel Index (CCI) with Exponential
Moving Averages (EMA) to identify high-probability trading opportunities.
The strategy uses CCI crossovers with a smoothing moving average and filters
signals using EMA trend confirmation. The strategy automatically enters trades
when CCI crosses the smoothing MA in specific zones, indicating potential trend
reversals or continuations.
HOW IT WORKS? ⚙️
---------------
1. CCI CALCULATION 📈
The strategy calculates the Commodity Channel Index using:
- CCI = (Price - SMA(Price, length)) / (0.015 × Deviation(Price, length))
- Default length: 20 periods
- Source: HLC3 (typical price)
The CCI shows:
- Values above +100 = Overbought conditions
- Values below -100 = Oversold conditions
- Values around 0 = Neutral conditions
2. SMOOTHING MOVING AVERAGE 📊
A moving average is applied to the CCI to smooth out fluctuations:
- Types available: SMA, EMA, SMMA (RMA), WMA, VWMA
- Default: SMA with length 14
- Can be disabled (set to "None")
This smoothed line acts as a reference for crossover signals.
3. EMA TREND FILTER 🎯
Two EMAs are calculated on the CCI:
- EMA 50 (fast EMA)
- EMA 200 (slow EMA)
When the EMA filter is enabled:
- LONG signals only occur when EMA50 > EMA200 (uptrend confirmation)
- SHORT signals only occur when EMA50 < EMA200 (downtrend confirmation)
This filter can be enabled/disabled via the "Use EMA Filter" option.
4. ENTRY CONDITIONS 🎲
LONG ENTRY (Buy Signal):
- CCI crosses ABOVE the Smoothing MA (crossover)
- CCI is between Lower Level (-100) and Middle Level (0)
- EMA Filter: EMA50 > EMA200 (if filter enabled)
- No existing positions (or close opposite positions first)
SHORT ENTRY (Sell Signal):
- CCI crosses BELOW the Smoothing MA (crossunder)
- CCI is between Middle Level (0) and Upper Level (+100)
- EMA Filter: EMA50 < EMA200 (if filter enabled)
- No existing positions (or close opposite positions first)
5. POSITION MANAGEMENT 💰
The strategy uses a simple position management approach:
- Only ONE position at a time (no pyramiding)
- If a signal occurs in the opposite direction, closes existing position first
- Then opens new position in the new direction
- This prevents overexposure and simplifies risk management
6. TAKE PROFIT & STOP LOSS SETTINGS 🎯
The strategy uses percentage-based TP/SL:
- Take Profit: 1.0% (default, configurable)
- Stop Loss: 0.5% (default, configurable)
- Risk/Reward Ratio: 2:1 (TP is double the SL)
TP/SL are calculated once when the position opens and remain fixed.
AVAILABLE PARAMETERS ⚙️
-----------------------
CCI SETTINGS:
1. CCI Length (Default: 20)
- Period for CCI calculation
- Lower values = More sensitive to recent price action
- Higher values = More smoothed, less sensitive
2. CCI Source (Default: HLC3)
- Price source for CCI calculation
- Options: close, open, high, low, hlc3, hlcc4, ohlc4
3. CCI Lower Level (Default: -100)
- Lower boundary for LONG entry zone
- Typically -100 for oversold conditions
4. CCI Middle Level (Default: 0)
- Neutral level separating LONG and SHORT zones
5. CCI Upper Level (Default: +100)
- Upper boundary for SHORT entry zone
- Typically +100 for overbought conditions
SMOOTHING MA:
6. Type (Default: SMA)
- Moving average type: None, SMA, EMA, SMMA (RMA), WMA, VWMA
- Set to "None" to disable smoothing
7. Length (Default: 14)
- Period for smoothing MA
- Range: 7-28, step 7
EMA FILTER:
8. EMA 1 Length (Default: 50)
- Fast EMA period applied to CCI
9. EMA 2 Length (Default: 200)
- Slow EMA period applied to CCI
10. Use EMA Filter (Default: true)
- Enable/disable EMA trend filter
- When enabled: LONG only if EMA50 > EMA200, SHORT only if EMA50 < EMA200
RISK MANAGEMENT:
11. Take Profit (%) (Default: 1.0%)
- Profit target as percentage of entry price
- For LONG: Entry × (1 + TP%)
- For SHORT: Entry × (1 - TP%)
12. Stop Loss (%) (Default: 0.5%)
- Stop loss as percentage of entry price
- For LONG: Entry × (1 - SL%)
- For SHORT: Entry × (1 + SL%)
VISUALIZATION 📊
---------------
The strategy displays in a separate panel below the price chart:
1. CCI LINE
- Blue line showing the CCI value
- Oscillates around zero
2. SMOOTHING MA LINE
- Yellow line showing the smoothed CCI
- Reference line for crossover signals
3. CCI LEVEL LINES
- Red dashed line: Upper Level (+100)
- Green dashed line: Lower Level (-100)
- Yellow dashed line: Middle Level (0)
4. ENTRY SIGNALS
- Green cross: LONG entry signal (when CCI crosses above MA)
- Red cross: SHORT entry signal (when CCI crosses below MA)
RECOMMENDED SETTINGS 🎯
-----------------------
To get started, you can use these settings:
CCI SETTINGS:
- CCI Length: 20 (default)
- CCI Source: HLC3 (default)
- CCI Lower Level: -100 (default)
- CCI Middle Level: 0 (default)
- CCI Upper Level: +100 (default)
SMOOTHING MA:
- Type: SMA (default) or EMA for faster response
- Length: 14 (default)
EMA FILTER:
- EMA 1 Length: 50 (default)
- EMA 2 Length: 200 (default)
- Use EMA Filter: true (recommended for better signal quality)
RISK MANAGEMENT:
- Take Profit (%): 1.0% (adjust based on your risk/reward preference)
- Stop Loss (%): 0.5% (adjust based on your risk tolerance)
For more aggressive trading:
- Reduce CCI Length to 14-16
- Reduce Smoothing MA Length to 7
- Disable EMA Filter
For more conservative trading:
- Increase CCI Length to 24-30
- Increase Smoothing MA Length to 21-28
- Keep EMA Filter enabled
RECOMMENDED CURRENCY PAIRS 💱
------------------------------
This strategy is optimized for currency pairs and performs exceptionally well
on the following pairs when properly configured:
TOP PERFORMING PAIRS:
- USDCAD: Can achieve Profit Factor > 2.0 and Win Rate up to 70%
- EURUSD: Excellent performance with consistent signals
- GBPJPY: Strong results with proper EMA filter configuration
These pairs have shown the best historical performance due to:
- Clear trending characteristics
- Good response to CCI overbought/oversold levels
- Strong alignment with EMA 50/200 trend filter
- High liquidity ensuring reliable execution
When trading these pairs, use the default settings or slightly adjusted
parameters based on the pair's volatility. Always backtest on historical
data before using real money to find the optimal configuration for each
specific pair.
PRACTICAL EXAMPLE 📝
--------------------
Scenario: LONG Entry on EUR/USD
1. Market conditions:
- Price: 1.1000
- CCI: -80 (in oversold zone)
- Smoothing MA: -90
- CCI crosses above Smoothing MA (crossover occurs)
- EMA50: -50, EMA200: -70 (EMA50 > EMA200, uptrend confirmed)
2. Strategy checks conditions:
✓ Smoothing MA enabled: Yes
✓ Crossover: Yes (CCI crosses above MA)
✓ CCI in range: Yes (-100 <= -80 <= 0)
✓ EMA Filter: Yes (EMA50 > EMA200)
✓ No existing position: Yes
3. Strategy opens position:
- Direction: LONG (Buy)
- Entry: 1.1000 (current close)
- Take Profit: 1.1110 (1.0% above entry)
- Stop Loss: 1.0945 (0.5% below entry)
- Risk/Reward: 2:1
4. Outcome scenarios:
- If price rises to 1.1110 → Take Profit hit (profit)
- If price falls to 1.0945 → Stop Loss hit (loss limited)
IMPORTANT NOTE ⚠️
-----------------
This strategy is a technical analysis tool based on CCI and EMA indicators.
Like all trading strategies, it does NOT guarantee profits. Trading involves
significant risks and you can lose money, including your entire investment.
Past performance does not guarantee future results.
Always:
- Use appropriate risk management
- Never risk more than you can afford to lose
- Test the strategy on historical data (backtesting) before using real money
- Start with small position sizes or paper trading
- Understand that no strategy works 100% of the time
- Consider market conditions, news events, and other factors
- Keep a trading journal to learn and improve
The author and contributors are NOT responsible for any losses incurred from
using this strategy. Trading decisions are your own responsibility. Profits
are NOT guaranteed, and losses are possible.
LICENSE 📄
----------
This code is open source and available for modification. You are free to use,
modify, and distribute this strategy. If you republish or share a modified
version, please kindly mention the original author.
================================================================================
Delta Volume EMA Strategy
================================================================================
DELTA VOLUME EMA STRATEGY - STRATEGY GUIDE 📊
================================================================================
💡 COLLABORATION & SUPPORT
---------------------------
If you want to collaborate, have an idea for a strategy, or need help writing
or customizing code, send an email to burdytrader@gmail.com or send me a
message. Suggestions, ideas, and comments are always welcome! 🤝
================================================================================
⚠️ IMPORTANT: INSTRUMENT SELECTION 📈
-------------------------------------
This strategy performs BEST with instruments that have a centralized data flow,
such as Futures contracts. Centralized markets provide more accurate and
reliable volume data, which is essential for Volume Delta analysis to work
effectively.
Why Futures? 🎯
- Centralized exchange = Accurate volume data
- All trades flow through a single exchange
- Volume reflects true buying/selling pressure
- Better correlation between volume and price movements
While the strategy can work with other instruments (stocks, forex, etc.),
volume data quality may vary, which can affect the reliability of Volume Delta
signals. For optimal performance, use Futures contracts or other instruments
with centralized, high-quality volume data.
================================================================================
WHAT DOES THIS STRATEGY DO? 🎯
---------------------------
This strategy uses Volume Delta analysis combined with Exponential Moving
Averages (EMA) to identify high-probability trading opportunities. The Volume
Delta measures the difference between buying and selling pressure, helping to
identify when strong institutional or smart money movements occur. The strategy
automatically enters trades when volume delta reaches extreme levels, indicating
potential trend continuation or reversal points.
HOW IT WORKS? ⚙️
---------------
1. VOLUME DELTA CALCULATION 📈
The strategy calculates the Volume Delta using the following formula:
- Volume Ratio (v) = Current Volume / Previous Volume
- EMA of Close (mac) = EMA(Close, MA Length) × Volume Ratio
- EMA of Open (mao) = EMA(Open, MA Length) × Volume Ratio
- Volume Delta (vd) = mac - mao
The Volume Delta shows:
- Positive values (green) = Buying pressure (buyers are more active)
- Negative values (red) = Selling pressure (sellers are more active)
2. VOLUME DELTA MOVING AVERAGE 📊
The strategy calculates an EMA of the Volume Delta (vdma) to smooth out
fluctuations and identify the overall trend of buying/selling pressure:
- vdma = EMA(Volume Delta, EMA Length)
- When vdma is above zero = Overall buying pressure
- When vdma is below zero = Overall selling pressure
3. PERCENTILE-BASED ENTRY CONDITIONS 🎲
Instead of using fixed thresholds, the strategy uses percentile analysis to
identify extreme volume delta movements:
For LONG entries:
- Analyzes seller volumes (negative volume delta) over the lookback period
- Calculates the percentile threshold (default: 80th percentile)
- Enters LONG when volume delta becomes positive AND exceeds the threshold
- This indicates a strong shift from selling to buying pressure
For SHORT entries:
- Analyzes buyer volumes (positive volume delta) over the lookback period
- Calculates the percentile threshold (default: 80th percentile)
- Enters SHORT when volume delta becomes negative AND exceeds the threshold
- This indicates a strong shift from buying to selling pressure
4. POSITION SIZING 💰
The strategy offers two position sizing methods:
a) RISK VALUE (Fixed Risk in Dollars):
- Calculates position size based on a fixed dollar risk amount
- Formula: Position Size = Risk Amount / (Entry Price × Stop Loss %)
- Ensures consistent risk per trade regardless of price level
b) LOTS SIZE:
- Uses a fixed lot size for all trades
- Simple and straightforward approach
- Useful when you want consistent position sizes
5. TAKE PROFIT & STOP LOSS SETTINGS 🎯
The strategy offers flexible TP/SL configuration in three modes:
a) PERCENTAGE (%):
- TP/SL calculated as a percentage of entry price
- Example: 2% TP means entry price × 1.02 (for LONG) or × 0.98 (for SHORT)
- Adapts automatically to different price levels
b) CURRENCY:
- TP/SL set as a fixed currency amount
- Example: $100 TP means entry price + $100 (for LONG) or - $100 (for SHORT)
- Useful for instruments with consistent price movements
c) PIPS:
- TP/SL set as a fixed number of pips
- Automatically converts pips to price using the instrument's minimum tick
- Ideal for forex and other pip-based instruments
6. AUTOMATIC TRADE EXECUTION ⚡
When entry conditions are met:
- Opens a position (LONG or SHORT) at market price
- Automatically sets Take Profit and Stop Loss based on selected mode
- Sends an alert with all trade information
- Only one position at a time (waits for current position to close)
AVAILABLE PARAMETERS ⚙️
----------------------
1. MA LENGTH (Default: 10)
- Length of the Exponential Moving Average used for close and open prices
- Lower values = More sensitive to recent price action
- Higher values = More smoothed, less sensitive
2. EMA LENGTH (Default: 20)
- Length of the EMA applied to Volume Delta
- Controls the smoothing of the volume delta signal
- Lower values = Faster signals, more trades
- Higher values = Slower signals, fewer but potentially more reliable trades
3. POSITION SIZE MODE
- "Risk Value": Calculate position size based on fixed dollar risk
- "Lots Size": Use fixed lot size for all trades
4. FIXED RISK IN $ (Default: 50)
- Only used when Position Size Mode = "Risk Value"
- The dollar amount you're willing to risk per trade
- Strategy calculates position size automatically
5. LOT SIZE (Default: 0.01)
- Only used when Position Size Mode = "Lots Size"
- Fixed lot size for all trades
6. TAKE PROFIT MODE
- "%": Percentage of entry price
- "Currency": Fixed currency amount
- "Pips": Fixed number of pips
7. STOP LOSS MODE
- "%": Percentage of entry price
- "Currency": Fixed currency amount
- "Pips": Fixed number of pips
8. TAKE PROFIT / STOP LOSS VALUES
- Different input fields appear based on selected mode
- Configure TP and SL independently
9. VOLUME LOOKBACK PERIOD (Default: 20)
- Number of bars used to calculate percentile thresholds
- Lower values = More sensitive, adapts faster to recent conditions
- Higher values = More stable, uses longer-term statistics
10. PERCENTILE THRESHOLD (Default: 80%)
- The percentile level used to identify extreme volume delta movements
- 80% means: only enter when volume delta exceeds 80% of recent values
- Higher values = Fewer but potentially stronger signals
- Lower values = More frequent signals
VISUALIZATION 📊
---------------
The strategy displays on the chart:
1. VOLUME DELTA COLUMNS
- Green columns = Positive volume delta (buying pressure)
- Red columns = Negative volume delta (selling pressure)
- Height represents the magnitude of buying/selling pressure
2. VOLUME DELTA MA AREA
- Two overlapping area plots showing the smoothed volume delta
- Black area (base layer) for overall visualization
- Green area (when positive) = Overall buying pressure trend
- Red area (when negative) = Overall selling pressure trend
- Helps identify the dominant market sentiment
3. ZERO LINE
- Horizontal line at zero
- Helps visualize when buying/selling pressure crosses the neutral point
ALERTS 🔔
--------
When enabled, the strategy sends alerts when a trade is opened. The alert
message includes:
- Direction: "Buy" for LONG positions or "Sell" for SHORT positions
- Entry Price: The price at which the position was opened
- TP (Take Profit): The target profit price
- SL (Stop Loss): The stop loss price
Example alert message:
"Buy | Entry: 1.2050 | TP: 1.2250 | SL: 1.1950"
Alerts can be configured in TradingView to send notifications via email,
SMS, webhooks, or other platforms.
RECOMMENDED SETTINGS 🎯
-----------------------
To get started, you can use these settings:
STRATEGY PARAMETERS:
- MA Length: 10 (default)
- EMA Length: 20 (default)
- Volume Lookback Period: 20 (default)
- Percentile Threshold: 80% (default)
POSITION SIZING:
- Position Size Mode: "Risk Value" (for risk management)
- Fixed Risk in $: Adjust based on your account size (e.g., 1-2% of account)
- OR use "Lots Size" with 0.01 lots for small accounts
TAKE PROFIT & STOP LOSS:
- TP Mode: "%" (recommended for most instruments)
- SL Mode: "%" (recommended for most instruments)
- Take Profit (%): 2.0% (adjust based on your risk/reward preference)
- Stop Loss (%): 1.0% (adjust based on your risk tolerance)
For Forex:
- Consider using "Pips" mode for TP/SL
- Typical values: 20-50 pips TP, 10-30 pips SL
For Stocks/Indices:
- Use "%" mode for TP/SL
- Typical values: 2-5% TP, 1-2% SL
PRACTICAL EXAMPLE 📝
-------------------
Scenario: LONG Entry on EUR/USD
1. Market conditions:
- Price: 1.1000
- Volume Delta becomes strongly positive
- Volume Delta exceeds 80th percentile of recent seller volumes
2. Strategy calculates:
- Entry Price: 1.1000 (current close)
- Position Size Mode: "Risk Value"
- Fixed Risk: $50
- Stop Loss Mode: "%"
- Stop Loss: 1.0%
- Position Size = $50 / (1.1000 × 0.01) = 4.55 lots
3. Strategy opens position:
- Direction: LONG (Buy)
- Entry: 1.1000
- Take Profit: 1.1220 (2% above entry)
- Stop Loss: 1.0890 (1% below entry)
- Alert sent: "Buy | Entry: 1.1000 | TP: 1.1220 | SL: 1.0890"
4. Outcome scenarios:
- If price rises to 1.1220 → Take Profit hit (profit)
- If price falls to 1.0890 → Stop Loss hit (loss limited to $50)
IMPORTANT NOTE ⚠️
-----------------
This strategy is a technical analysis tool based on volume delta analysis.
Like all trading strategies, it does NOT guarantee profits. Trading involves
significant risks and you can lose money, including your entire investment.
Past performance does not guarantee future results.
Always:
- Use appropriate risk management
- Never risk more than you can afford to lose
- Test the strategy on historical data (backtesting) before using real money
- Start with small position sizes or paper trading
- Understand that no strategy works 100% of the time
- Consider market conditions, news events, and other factors
- Keep a trading journal to learn and improve
The author and contributors are NOT responsible for any losses incurred from
using this strategy. Trading decisions are your own responsibility. Profits
are NOT guaranteed, and losses are possible.
LICENSE 📄
---------
This code is open source and available for modification. You are free to use,
modify, and distribute this strategy. If you republish or share a modified
version, please kindly mention the original author.
================================================================================
Algomist.app v1.0🚀 WMA Crossover Momentum Scalper: Algomist.app AUTO-EXECUTION
This strategy is a momentum-based trend-following system optimized for fully automated, high-frequency trade execution via algomist.app webhooks. It systematically enters trades based on a powerful moving average crossover, confirmed by both volume and volatility filters.
⚙️ Core Strategy Logic
This script is designed to capture short- to medium-term moves in trending markets by combining three key indicators:
Trend Confirmation (WMA Crossover): The primary signal is generated when a Fast WMA (50-period) crosses the Slow WMA (100-period). This crossover confirms the shift in the prevailing trend direction.
Volume Filter (VWAP): The trade is only taken if the price is trading above the VWAP for Long entries, or below the VWAP for Short entries. This ensures the trade is aligned with the asset's average price relative to trading volume.
Volatility Filter (ATR): A minimum Average True Range (ATR) filter is applied. This is critical for avoiding entries during periods of extreme low volatility ("chop"), ensuring the market has enough movement to justify the trade.
🔗 Algomist.app Automation Ready
This is the most important feature. The script contains custom-coded alert() functions that output a perfect JSON payload, making it 100% compatible with the algomist.app webhook infrastructure.
Seamless Execution: The strategy instantly transmits all required parameters—symbol, side, entry_price, dynamic stop_loss, and dynamic take_profit—directly to your MT5 terminal through the algomist.app connector.
Simple Setup: To enable live automation, you only need to configure a TradingView alert using the provided webhook URL and the {{strategy.order.alert_message}} placeholder on the bar's close.
Default Asset: The webhook is pre-configured to trade the ETHUSDC symbol. This can be easily adapted to other crypto or Forex pairs within the algomist.app settings.
🛡️ Dynamic Risk Management (ATR-Based)
Risk management is dynamic, ensuring the Stop Loss and Take Profit levels automatically adapt to current market volatility:
Stop Loss (SL): Placed at a customizable (x) * ATR distance from the entry price. The default setting is 3.0x ATR.
Take Profit (TP): Placed at a customizable (x) * ATR distance from the entry price. The default setting is 9.0x ATR, offering a fixed Reward-to-Risk ratio of 3:1 (9.0 / 3.0).
Position Sizing: The script uses strategy.percent_of_equity = 10% for backtesting, but the algomist.app execution is based on an internal calculation using a small percentage (e.g., 5%) of a leveraged notional value for illustrative purposes. Users must set their risk size within the algomist.app platform.
Disclaimer: This script is provided as an example for Algomist.app users and is NOT financial advice. Backtest thoroughly across various assets and timeframes. Past performance is not indicative of future results. The user assumes all responsibility for live trading risk.
Estrategia Timing SMA 10 de Faber Introduction This strategy is based on the classic trend-following logic popularized by Meb Faber in his white papers (such as "A Quantitative Approach to Tactical Asset Allocation") and frequently discussed by financial analyst José Luis Cárpatos. The core philosophy is simple but effective: stay in the market during uptrends to capture growth, and move to cash during downtrends to protect capital from major drawdowns.
This is a long-term "Timing" strategy designed for investors who want to filter out market noise and focus on the primary macro trend.
How it Works The strategy utilizes a specific Moving Average on a Monthly timeframe to determine the trend direction.
The Indicator: A 10-period Simple Moving Average (SMA) calculated on the Monthly timeframe (1M).
Long Condition: When the Monthly Close price is above the 10-Month SMA, the strategy enters a Long position (Risk On).
Exit Condition (Cash): When the Monthly Close price falls below the 10-Month SMA, the strategy closes the position and stays in Cash (Risk Off). It does not open short positions; it simply exits the market to preserve capital.
Key Features (Multi-Timeframe) This script has been coded using request.security to force the calculation on Monthly data (1M), regardless of the chart timeframe you are currently viewing.
This allows you to view the strategy on a Daily or Weekly chart while ensuring the mathematical logic remains strictly bound to the Monthly moving average.
The SMA line will appear "stepped" on lower timeframes (e.g., Daily), representing the constant value of the SMA for that specific month.
Settings
Length: Default is 10 (representing 10 Months), but this can be adjusted if you wish to test other periods (e.g., 12 months).
Source: Defaults to close.
Visuals
Blue Line: Represents the 10-Month SMA.
Background Color:
Green: Indicates the strategy is currently Long (Price > SMA).
Red/Grey: Indicates the strategy is in Cash (Price < SMA).
Important Note on Backtesting & Repainting Because this strategy requests Monthly data on lower timeframes (like Daily), please be aware that the current month's data is dynamic. The signal is technically confirmed only at the close of the monthly bar. When viewing on a Daily chart, the script evaluates the relationship between the current price and the current monthly SMA.
Disclaimer This script is for educational and research purposes only. Past performance is not indicative of future results. Always manage your risk appropriately.
NY Session Bar Counter & Bar painterThe NY Session Bar Counter is a high-visibility technical utility that provides an automated, sequential count of every candle during the New York session (09:30 to 16:00 EST). Unlike standard session highlighters, this tool numbers each bar starting from the market open, allowing traders to identify specific "time-of-day" windows with surgical precision.
This script is specifically engineered for traders who follow setups based on specific bar numbers (e.g., the Bar 17 reversal, the Bar 36 lunch-power-hour, or the final EOD flush).
🚀 Key Features
Precision Timing: Automatically resets every day at 09:30 AM New York time, regardless of your local timezone settings.
Multi-Timeframe Logic: Optimized to work seamlessly on 1m, 5m, 15m, and 30m charts without breaking the daily count.
Historical & Replay Compatibility: Unlike many session tools, this script is fully compatible with Bar Replay and displays historical data across several days (up to 500 labels).
Special Bar Highlighting: Includes a "Paint Bar" feature that allows you to choose a specific bar number (e.g., Bar 17) and automatically color the candle body for instant visual recognition.
Customizable Display: Filter for Odd/Even numbers to reduce chart clutter and adjust font size, color, and position (Above/Below bar).
💡 Why It Is Useful
In the modern trading environment, the market moves in cycles of liquidity and volatility that are often tied to specific times. This script is useful because:
Standardization: It provides a common language for traders. Instead of saying "the 10:50 AM candle," traders can refer to "Bar 17" (on a 5m chart), which is faster and more consistent.
Backtesting Accuracy: When reviewing past days or using Bar Replay, you can easily identify if your strategy triggers at the same relative time every day.
Visual Discipline: By highlighting a "Target Bar," you can train your eyes to wait for specific time windows before looking for a setup, helping to prevent overtrading during low-probability hours.
Operational Efficiency: It removes the manual work of counting bars from the open, allowing you to focus entirely on price action and order flow.
How to Use
Install the script on any intraday timeframe (best on 5m or 15m).
Adjust Lookback: Use the settings to determine how many historical days you want to view.
Identify Patterns: Use the "Special Bar Highlight" to mark the bar where your strategy most frequently triggers.
CryptoFlux Dynamo [JOAT]CryptoFlux Dynamo: Velocity Scalping Strategy
WHAT THIS STRATEGY IS
CryptoFlux Dynamo is an open-source Pine Script v6 strategy designed for momentum-based scalping on cryptocurrency perpetual futures. It combines multiple technical analysis methods into a unified system that adapts its behavior based on current market volatility conditions.
This script is published open-source so you can read, understand, and modify the complete logic. The description below explains everything the strategy does so that traders who cannot read Pine Script can fully understand how it works before using it.
HOW THIS STRATEGY IS ORIGINAL AND WHY THE INDICATORS ARE COMBINED
This strategy uses well-known indicators (MACD, EMA, RSI, MFI, Bollinger Bands, Keltner Channels, ATR). The originality is not in the individual indicators themselves, but in the specific way they are integrated into a regime-adaptive system. Here is the detailed justification for why these components are combined and how they work together:
The Problem Being Solved:
Standard indicator-based strategies use fixed thresholds. For example, a typical MACD strategy might enter when the histogram crosses above zero. However, in cryptocurrency markets, volatility changes dramatically throughout the day and week. A MACD crossover during a low-volatility consolidation period has very different implications than the same crossover during a high-volatility trending period. Using the same entry thresholds and stop distances in both conditions leads to either:
Too many false signals during consolidation (if thresholds are loose)
Missing valid opportunities during expansion (if thresholds are tight)
Stops that are too tight during volatility spikes (causing premature exits)
Stops that are too wide during compression (giving back profits)
The Solution Approach:
This strategy first classifies the current volatility regime using normalized ATR (ATR as a percentage of price), then dynamically adjusts ALL other parameters based on that classification. This creates a context-aware system rather than a static threshold comparison.
How Each Component Contributes to the System:
ATR-Based Regime Classification (The Foundation)
The strategy calculates ATR over 21 periods, smooths it with a 13-period EMA to reduce noise from wicks, then divides by price to get a normalized percentage. This ATR% is classified into three regimes:
- Compression (ATR% < 0.8%): Market is consolidating, breakouts are more likely but false signals are common
- Expansion (ATR% 0.8% - 1.6%): Normal trending conditions
- Velocity (ATR% > 1.6%): High volatility, larger moves but also larger adverse excursions
This regime classification then controls stop distances, profit targets, trailing stop offsets, and signal strength requirements. The regime acts as a "meta-parameter" that tunes the entire system.
EMA Ribbon (8/21/34) - Trend Structure Detection
The three EMAs establish trend direction and structure. When EMA 8 > EMA 21 > EMA 34, the trend structure is bullish. The slope of the middle EMA (21) is calculated over 8 bars and converted to degrees using arctangent. This slope measurement quantifies trend strength, not just direction.
Why these specific periods? The 8/21/34 sequence follows Fibonacci-like spacing and provides good separation on 5-minute cryptocurrency charts. The fast EMA (8) responds to immediate price action, the mid EMA (21) represents the short-term trend, and the slow EMA (34) acts as a trend filter.
The EMA ribbon works with the regime classification: during compression regimes, the strategy requires stronger ribbon alignment before entry because false breakouts are more common.
MACD (8/21/5) - Momentum Measurement
The MACD uses faster parameters (8/21/5) than the standard (12/26/9) because cryptocurrency markets move faster than traditional markets. The histogram is smoothed with a 5-period EMA to reduce noise.
The key innovation is the adaptive histogram baseline. Instead of using a fixed threshold, the strategy calculates a rolling baseline from the smoothed absolute histogram value, then multiplies by a sensitivity factor (1.15). This means the threshold for "significant momentum" automatically adjusts based on recent momentum levels.
The MACD works with the regime classification: during velocity regimes, the histogram baseline is effectively higher because recent momentum has been stronger, preventing entries on relatively weak momentum.
RSI (21 period) and MFI (21 period) - Independent Momentum Confirmation
RSI measures momentum using price changes only. MFI (Money Flow Index) measures momentum using price AND volume. By requiring both to confirm, the strategy filters out price moves that lack volume support.
The 21-period length is longer than typical (14) to reduce noise on 5-minute charts. The trigger threshold (55 for longs, 45 for shorts) is slightly offset from 50 to require momentum in the trade direction, not just neutral readings.
These indicators work together: a signal requires RSI > 55 AND MFI > 55 for longs. This dual confirmation reduces false signals from price manipulation or low-volume moves.
Bollinger Bands (1.5 mult) and Keltner Channels (1.8 mult) - Squeeze Detection
When Bollinger Bands contract inside Keltner Channels, volatility is compressing and a breakout is likely. This is the "squeeze" condition. When the bands expand back outside the channels, the squeeze "releases."
The strategy uses a 1.5 multiplier for Bollinger Bands (tighter than standard 2.0) and 1.8 for Keltner Channels. These values were chosen to identify meaningful squeezes on 5-minute cryptocurrency charts without triggering too frequently.
The squeeze detection works with the regime classification: squeeze releases during compression regimes receive additional signal strength points because breakouts from consolidation are more significant.
Volume Impulse Detection - Institutional Participation Filter
The strategy calculates a volume baseline (34-period SMA) and standard deviation. A "volume impulse" is detected when current volume exceeds the baseline by 1.15x OR when the volume z-score exceeds 0.5.
This filter ensures entries occur when there is meaningful market participation, not during low-volume periods where price moves are less reliable.
Volume impulse is required for all entries and adds points to the composite signal strength score.
Cycle Oscillator - Trend Alignment Filter
The strategy calculates a 55-period EMA as a cycle basis, then measures price deviation from this basis as a percentage. When price is more than 0.15% above the cycle basis, the cycle is bullish. When more than 0.15% below, the cycle is bearish.
This filter prevents counter-trend entries. Long signals require bullish cycle alignment; short signals require bearish cycle alignment.
BTC Dominance Filter (Optional) - Market Regime Filter
The strategy can optionally use BTC.D (Bitcoin Dominance) as a market regime filter. When BTC dominance is rising (slope > 0.12), the market is in "risk-off" mode and long entries on altcoins are filtered. When dominance is falling (slope < -0.12), short entries are filtered.
This filter is optional because the BTC.D data feed may lag during low-liquidity periods.
How The Components Work Together (The Mashup Justification):
The strategy uses a composite scoring system where each signal pathway contributes points:
Trend Break pathway (30 points): Requires EMA ribbon alignment + positive slope + price breaks above recent structure high
Momentum Surge pathway (30 points): Requires MACD histogram > adaptive baseline + MACD line > signal + RSI > 55 + MFI > 55 + volume impulse
Squeeze Release pathway (25 points): Requires BB inside KC (squeeze) then release + momentum bias + histogram confirmation
Micro Pullback pathway (15 points): Requires shallow retracement to fast EMA within established trend + histogram confirmation + volume impulse
Additional modifiers:
+5 points if volume impulse is present, -5 if absent
+5 points in velocity regime, -2 in compression regime
+5 points if cycle is aligned, -5 if counter-trend
A trade only executes when the composite score reaches the minimum threshold (default 55) AND all filters agree (session, cycle bias, BTC dominance if enabled).
This scoring system is the core innovation: instead of requiring ALL conditions to be true (which would generate very few signals) or ANY condition to be true (which would generate too many false signals), the strategy requires ENOUGH conditions to be true, with different conditions contributing different weights based on their reliability.
HOW THE STRATEGY CALCULATES ENTRIES AND EXITS
Entry Logic:
1. Calculate current volatility regime from ATR%
2. Calculate all indicator values (MACD, EMA, RSI, MFI, squeeze, volume)
3. Evaluate each signal pathway and sum points
4. Check all filters (session, cycle, dominance, kill switch)
5. If composite score >= 55 AND all filters pass, generate entry signal
6. Calculate position size based on risk per trade and regime-adjusted stop distance
7. Execute entry with regime name as comment
Position Sizing Formula:
RiskCapital = Equity * (0.65 / 100)
StopDistance = ATR * StopMultiplier(regime)
RawQuantity = RiskCapital / StopDistance
MaxQuantity = Equity * (12 / 100) / Price
Quantity = min(RawQuantity, MaxQuantity)
Quantity = round(Quantity / 0.001) * 0.001
This ensures each trade risks approximately 0.65% of equity regardless of volatility, while capping total exposure at 12% of equity.
Stop Loss Calculation:
Stop distance is ATR multiplied by a regime-specific multiplier:
Compression regime: 1.05x ATR (tighter stops because moves are smaller)
Expansion regime: 1.55x ATR (standard stops)
Velocity regime: 2.1x ATR (wider stops to avoid premature exits during volatility)
Take Profit Calculation:
Target distance is ATR multiplied by regime-specific multiplier and base risk/reward:
Compression regime: 1.6x ATR * 1.8 base R:R * 0.9 regime bonus = approximately 2.6x ATR
Expansion regime: 2.05x ATR * 1.8 base R:R * 1.0 regime bonus = approximately 3.7x ATR
Velocity regime: 2.8x ATR * 1.8 base R:R * 1.15 regime bonus = approximately 5.8x ATR
Trailing Stop Logic:
When adaptive trailing is enabled, the strategy calculates a trailing offset based on ATR and regime:
Compression regime: 1.1x base offset (looser trailing to avoid noise)
Expansion regime: 1.0x base offset (standard)
Velocity regime: 0.8x base offset (tighter trailing to lock in profits during fast moves)
The trailing stop only activates when it would be tighter than the initial stop.
Momentum Fail-Safe Exits:
The strategy closes positions early if momentum reverses:
Long positions close if MACD histogram turns negative OR EMA ribbon structure breaks (fast EMA crosses below mid EMA)
Short positions close if MACD histogram turns positive OR EMA ribbon structure breaks
This prevents holding through momentum reversals even if stop loss hasn't been hit.
Kill Switch:
If maximum drawdown exceeds 6.5%, the strategy disables new entries until manually reset. This prevents continued trading during adverse conditions.
HOW TO USE THIS STRATEGY
Step 1: Apply to Chart
Use a 5-minute chart of a high-liquidity cryptocurrency perpetual (BTC/USDT, ETH/USDT recommended)
Ensure at least 200 bars of history are loaded for indicator stabilization
Use standard candlestick charts only (not Heikin Ashi, Renko, or other non-standard types)
Step 2: Understand the Visual Elements
EMA Ribbon: Three lines (8/21/34 periods) showing trend structure. Bullish when stacked upward, bearish when stacked downward.
Background Color: Shows current volatility regime
- Indigo/dark blue = Compression (low volatility)
- Purple = Expansion (normal volatility)
- Magenta/pink = Velocity (high volatility)
Bar Colors: Reflect signal strength divergence. Brighter colors indicate stronger directional bias.
Triangle Markers: Entry signals. Up triangles below bars = long entry. Down triangles above bars = short entry.
Dashboard (top-right): Real-time display of regime, ATR%, signal strengths, position status, stops, targets, and risk metrics.
Step 3: Interpret the Dashboard
Regime: Current volatility classification (Compression/Expansion/Velocity)
ATR%: Normalized volatility as percentage of price
Long/Short Strength: Current composite signal scores (0-100)
Cycle Osc: Price deviation from 55-period EMA as percentage
Dominance: BTC.D slope and filter status
Position: Current position direction or "Flat"
Stop/Target: Current stop loss and take profit levels
Kill Switch: Status of drawdown protection
Volume Z: Current volume z-score
Impulse: Whether volume impulse condition is met
Step 4: Adjust Parameters for Your Needs
For more conservative trading: Increase "Minimum Composite Signal Strength" to 65 or higher
For more aggressive trading: Decrease to 50 (but expect more false signals)
For higher timeframes (15m+): Increase "Structure Break Window" to 12-15, increase "RSI Momentum Trigger" to 58
For lower liquidity pairs: Increase "Volume Impulse Multiplier" to 1.3, increase slippage in strategy properties
To disable short selling: Uncheck "Enable Short Structure"
To disable BTC dominance filter: Uncheck "BTC Dominance Confirmation"
STRATEGY PROPERTIES (BACKTEST SETTINGS)
These are the exact settings used in the strategy's Properties dialog box. You must use these same settings when evaluating the backtest results shown in the publication:
Initial Capital: $100,000
Justification: This amount is higher than typical retail accounts. I chose this value to demonstrate percentage-based returns that scale proportionally. The strategy uses percentage-based position sizing (0.65% risk per trade), so a $10,000 account would see the same percentage returns with 10x smaller position sizes. The absolute dollar amounts in the backtest should be interpreted as percentages of capital.
Commission: 0.04% (commission_value = 0.04)
Justification: This reflects typical perpetual futures exchange fees. Major exchanges charge between 0.02% (maker) and 0.075% (taker). The 0.04% value is a reasonable middle estimate. If your exchange charges different fees, adjust this value accordingly. Higher fees will reduce net profitability.
Slippage: 1 tick
Justification: This is conservative for liquid pairs like BTC/USDT on major exchanges during normal conditions. For less liquid altcoins or during high volatility, actual slippage may be higher. If you trade less liquid pairs, increase this value to 2-3 ticks for more realistic results.
Pyramiding: 1
Justification: No position stacking. The strategy holds only one position at a time. This simplifies risk management and prevents overexposure.
calc_on_every_tick: true
Justification: The strategy evaluates on every price update, not just bar close. This is necessary for scalping timeframes where waiting for bar close would miss opportunities. Note that this setting means backtest results may differ slightly from bar-close-only evaluation.
calc_on_order_fills: true
Justification: The strategy recalculates immediately after order fills for faster response to position changes.
RISK PER TRADE JUSTIFICATION
The default risk per trade is 0.65% of equity. This is well within the TradingView guideline that "risking more than 5-10% on a trade is not typically considered viable."
With the 12% maximum exposure cap, even if the strategy takes multiple consecutive losses, the total risk remains manageable. The kill switch at 6.5% drawdown provides additional protection by halting new entries during adverse conditions.
The position sizing formula ensures that stop distance (which varies by regime) is accounted for, so actual risk per trade remains approximately 0.65% regardless of volatility conditions.
SAMPLE SIZE CONSIDERATIONS
For statistically meaningful backtest results, you should select a dataset that generates at least 100 trades. On 5-minute BTC/USDT charts, this typically requires:
2-3 months of data during normal market conditions
1-2 months during high-volatility periods
3-4 months during low-volatility consolidation periods
The strategy's selectivity (requiring 55+ composite score plus all filters) means it generates fewer signals than less filtered approaches. If your backtest shows fewer than 100 trades, extend the date range or reduce the minimum signal strength threshold.
Fewer than 100 trades produces statistically unreliable results. Win rate, profit factor, and other metrics can vary significantly with small sample sizes.
STRATEGY DESIGN COMPROMISES AND LIMITATIONS
Every strategy involves trade-offs. Here are the compromises made in this design and the limitations you should understand:
Selectivity vs. Opportunity Trade-off
The 55-point minimum threshold filters many potential trades. This reduces false signals but also misses valid setups that don't meet all criteria. Lowering the threshold increases trade frequency but decreases win rate. There is no "correct" threshold; it depends on your preference for fewer higher-quality signals vs. more signals with lower individual quality.
Regime Classification Lag
The ATR-based regime detection uses historical data (21 periods + 13-period smoothing). It cannot predict sudden volatility spikes. During flash crashes or black swan events, the strategy may be classified in the wrong regime for several bars before the classification updates. This is an inherent limitation of any lagging indicator.
Indicator Parameter Sensitivity
The default parameters (MACD 8/21/5, EMA 8/21/34, RSI 21, etc.) are tuned for BTC/ETH perpetuals on 5-minute charts during 2024 market conditions. Different assets, timeframes, or market regimes may require different parameters. There is no guarantee that parameters optimized on historical data will perform similarly in the future.
BTC Dominance Filter Limitations
The CRYPTOCAP:BTC.D data feed may lag during low-liquidity periods or weekends. The dominance slope calculation uses a 5-bar SMA, adding additional delay. If you notice the filter behaving unexpectedly, consider disabling it.
Backtest vs. Live Execution Differences
TradingView backtesting does not replicate actual broker execution. Key differences:
Backtests assume perfect fills at calculated prices; real execution involves order book depth, latency, and partial fills
The calc_on_every_tick setting improves backtest realism but still cannot capture sub-bar price action or order book dynamics
Commission and slippage settings are estimates; actual costs vary by exchange, time of day, and market conditions
Funding rates on perpetual futures are not modeled in backtests and can significantly impact profitability over time
Exchange-specific limitations (position limits, liquidation mechanics, order types) are not modeled
Market Condition Dependencies
This strategy is designed for trending and breakout conditions. During extended sideways consolidation with no clear direction, the strategy may generate few signals or experience whipsaws. No strategy performs well in all market conditions.
Cryptocurrency-Specific Risks
Cryptocurrency markets operate 24/7 without session boundaries. This means:
No natural "overnight" risk reduction
Volatility can spike at any time
Liquidity varies significantly by time of day
Exchange outages or issues can occur at any time
WHAT THIS STRATEGY DOES NOT DO
To be straightforward about limitations:
This strategy does not guarantee profits. Past backtest performance does not indicate future results.
This strategy does not predict the future. It reacts to current conditions based on historical patterns.
This strategy does not account for funding rates, which can significantly impact perpetual futures profitability.
This strategy does not model exchange-specific execution issues (partial fills, requotes, outages).
This strategy does not adapt to fundamental news events or black swan scenarios.
This strategy is not optimized for all market conditions. It may underperform during extended consolidation.
IMPORTANT RISK WARNINGS
Past performance does not guarantee future results. The backtest results shown reflect specific historical market conditions and parameter settings. Markets change constantly, and strategies that performed well historically may underperform or lose money in the future. A single backtest run does not constitute proof of future profitability.
Trading involves substantial risk of loss. Cryptocurrency derivatives are highly volatile instruments. You can lose your entire investment. Only trade with capital you can afford to lose completely.
This is not financial advice. This strategy is provided for educational and informational purposes only. It does not constitute investment advice, trading recommendations, or any form of financial guidance. The author is not a licensed financial advisor.
You are responsible for your own decisions. Before using this strategy with real capital:
Thoroughly understand the code and logic by reading the open-source implementation
Forward test with paper trading or very small positions for an extended period
Verify that commission, slippage, and execution assumptions match your actual trading environment
Understand that live results will differ from backtest results
Consider consulting with a qualified financial advisor
No guarantees or warranties. This strategy is provided "as is" without any guarantees of profitability, accuracy, or suitability for any purpose. The author is not responsible for any losses incurred from using this strategy.
OPEN-SOURCE CODE STRUCTURE
The strategy code is organized into these sections for readability:
Configuration Architecture: Input parameters organized into logical groups (Core Controls, Optimization Constants, Regime Intelligence, Signal Pathways, Risk Architecture, Visualization)
Helper Functions: calcQty() for position sizing, clamp01() and normalize() for value normalization, calcMFI() for Money Flow Index calculation
Core Indicator Engine: EMA ribbon, ATR and regime classification, MACD with adaptive baseline, RSI, MFI, volume analytics, cycle oscillator, BTC dominance filter, squeeze detection
Signal Pathway Logic: Trend break, momentum surge, squeeze release, micro pullback pathways with composite scoring
Entry/Exit Orchestration: Signal filtering, position sizing, entry execution, stop/target calculation, trailing stop logic, momentum fail-safe exits
Visualization Layer: EMA plots, regime background, bar coloring, signal labels, dashboard table
You can read and modify any part of the code. Understanding the logic before deployment is strongly recommended.
- Made with passion by officialjackofalltrades
Elite MTF EMA Reclaim StrategyThis script is a 6-minute execution MTF EMA “retest → reclaim” strategy. It looks for trend-aligned pullbacks into fast EMAs, then enters when price reclaims and (optionally) retests the reclaim level—while filtering out chop (low trend strength/volatility or recent EMA20/50 crosses) and enforcing higher-timeframe alignment (Daily + 1H, or whichever you select).
How to use
Run it on a 6-minute chart (that’s what the presets are tuned for).
Pick your Market (Forex / XAUUSD / Crypto / Indices) and a Preset:
Elite = strictest, cleanest (fewer signals)
Balanced = middle ground
Aggressive = most signals, loosest filters
Set HTF Alignment Mode:
D + H1 (recommended) for highest quality
Off if you want more trades / LTF-only testing
Leave Kill Chop = ON (recommended). If you’re not getting trades, this is usually the blocker.
Choose entry behavior:
If Require Retest = true, entries happen on the retest after reclaim (cleaner, later).
If Require Retest = false, entries trigger on reclaim using Reclaim Timing Default:
“Preset” uses the strategy’s recommended default per market/preset
or force Reclaim close / Next bar confirmation
For backtesting, keep Mode = Strategy (Backtest). For alerts/visual-only, set Mode = Indicator (Signals Only).
Use Show Signals (All Modes) to toggle triangles on/off without affecting trades.
Tip: If TradingView says “not enough data,” switch symbol history to “All,” reduce HTF alignment (try H1 only), or backtest a more recent date range.
Volatility Shield ProConcept: Volatility Shield Pro is a multi-dimensional execution engine designed to filter high-probability entries by triangulating Trend, Institutional Volume, and Statistical Exhaustion.
Why this is original: Unlike standard indicators that look at price in a vacuum, this uses a Volume-Weighted ATR (VWATR) to distinguish between retail noise and institutional "Strikes." It integrates an ADR (Average Daily Range) Fuel gauge to prevent entries into exhausted moves, solving the common problem of buying the "top" of a trend.
Components & Logic:
Institutional Strike Engine: Uses VWATR normalized against a 50-period SMA to find momentum backed by volume.
ADR Fuel Gauge: Calculated by comparing current price travel to the 10-day ADR. A "State" of EXHAUSTED is triggered at 120% to warn of mean reversion.
HTF Anchor: A built-in Higher Time Frame EMA filter (default 4H) to ensure local trades align with the macro tide.
Live EDGE Tracker: A real-time backtesting module that calculates the win rate of the "Strike" signals on the current chart history using a 1.5:1 Reward-to-Risk ratio.
This combined tool addresses the three main reasons most trading systems fail by integrating higher-timeframe bias, daily range exhaustion, and volume confirmation into one framework:
Fighting the Tide (HTF Ribbon): Keeps traders aligned with the dominant higher-timeframe trend to avoid counter-trend entries.
Running Out of Gas (ADR Fuel): Measures a symbol’s average daily range to prevent chasing moves that have already reached their statistical limit.
Ghost Volume (RVOL/VWATR): Filters out low-quality, retail-driven activity by requiring institutional-level volume spikes before taking trades.
In essence, it combines trend alignment, range exhaustion detection, and real-volume filtering to eliminate the most common account-killing mistakes.
The "Triple-Threat" Trade Setup
This is the highest-probability setup the tool can produce. When these three things align, the "Edge" is at its peak:
The Anchor: HTF Ribbon is Bright Green.
The Local: Atlas Trend Bias is BULLISH and State is STRIKE.
The Value: ADR Fuel is Low (40-60%), meaning the stock has massive room to move before hitting daily resistance.
TradingView Alert Adapter for AlgoWayTRALADAL is a universal TradingView alert adapter designed for traders who work with indicators and want to test and automate indicator-based signals in a structured way.
It allows users to convert indicator outputs into a TradingView strategy and forward the same logic through alerts for multi-platform execution via AlgoWay.
This script can be used as TradingView indicator automation, enabling traders to build a TradingView strategy from indicators and route TradingView alerts through an AlgoWay connector TradingView workflow for multi-platform execution.
Why this adapter is needed
Most TradingView indicators are not available as strategies.
Traders often receive visual signals or alerts but have no access to objective statistics such as win rate, drawdown, or profit factor.
This adapter solves that problem by providing a generic framework that transforms indicator signals into a backtestable strategy — without modifying indicator code and without requiring Pine Script knowledge.
Input source–based design (including closed indicators)
All conditions in TRALADAL are built using input sources, which means you can connect:
Event-based signals (1 / non-zero values, arrows, shapes)
Indicator lines and values (EMA, VWAP, RSI, MACD, etc.)
Outputs from invite-only or closed-source indicators
If an indicator produces a visible signal or alert-compatible output, it can be evaluated and tested using this adapter, even when the source code is locked.
Three-level signal logic
The strategy uses a three-layer condition model commonly applied in discretionary and systematic trading:
Signal — primary entry trigger
Confirmation — directional validation
Filter — additional noise reduction
Each level can be enabled independently and combined using AND / OR logic, allowing traders to test multi-indicator systems without writing complex scripts.
Risk management and alert execution
The adapter supports practical risk parameters:
Stop Loss (pips)
Take Profit (pips)
Trailing Stop (pips)
Two execution modes are available:
Strategy Mode — risk rules are applied inside the TradingView Strategy Tester
Alert Mode — risk parameters are embedded into structured TradingView alerts and handled by AlgoWay during execution
Position sizing follows TradingView conventions (percent of equity, cash, or contracts) to keep strategy results and alerts aligned.
Typical use cases
This TradingView alert adapter is intended for:
Indicator-based trading systems
Backtesting signals from closed or invite-only scripts
Comparing multiple indicators within a single strategy
Sending TradingView alerts to external trading platforms via AlgoWay
The adapter does not generate signals or trading recommendations.
Its purpose is to provide a transparent and testable workflow from indicator signals to TradingView alerts and automated execution.
Kalman Hull Kijun [BackQuant]Kalman Hull Kijun
A trend baseline that merges three ideas into one clean overlay, Kalman filtering for noise control, Hull-style responsiveness, and a Kijun-like Donchian midline for structure and bias.
Context and lineage
This indicator sits in the same family as two related scripts:
Kalman Price Filter
This is the foundational building block. It introduces the Kalman filter concept, a state-estimation algorithm designed to infer an underlying “true” signal from noisy measurements, originally used in aerospace guidance and later adopted across robotics, economics, and markets.
Kalman Hull Supertrend
This is the original script made, which people loved. So it inspired me to create this one.
Kalman Hull Kijun uses the same core philosophy as the Supertrend variant, but instead of building a Supertrend band system, it produces a single structural baseline that behaves like a Kijun-style reference line.
What this indicator is trying to solve
Most trend baselines sit on a bad trade-off curve:
If you smooth hard, the line reacts late and misses turns.
If you react fast, the line whipsaws and tracks noise.
Kalman Hull Kijun is designed to land closer to the middle:
Cleaner than typical fast moving averages in chop.
More responsive than slow averages in directional phases.
More “structure aware” than pure averages because the baseline is range-derived (Kijun-like) after filtering.
Core idea in plain language
The plotted line is a Kijun-like baseline, but it is not built from raw candles directly.
High level flow:
Start with a chosen price stream (source input).
Reduce measurement noise using Kalman-style state estimation.
Add Hull-style responsiveness so the filtered stream stays usable for trend work.
Build a Kijun-like baseline by taking a Donchian midpoint of that filtered stream over the base period.
So the output is a single baseline that is intended to be:
Less jittery than a simple fast MA.
Less laggy than a slow MA.
More “range anchored” than standard smoothing lines.
How to read it
1) Trend and bias (the primary use)
Price above the baseline, bullish bias.
Price below the baseline, bearish bias.
Clean flips across the baseline are regime changes, especially when followed by a hold or retest.
2) Retests and dynamic structure
Treat the baseline like dynamic S/R rather than a signal generator:
In uptrends, pullbacks that respect the baseline can act as continuation context.
In downtrends, reclaim failures around the baseline can act as continuation context.
Repeated back-and-forth around the line usually means compression or chop, not clean trend.
3) Extension vs compression (using the fill)
The fill is meant to communicate “distance” and “pressure” visually:
Large separation between price and baseline suggests expansion.
Price compressing into the baseline suggests rebalancing and decision points.
Inputs and what they change
Kijun Base Period
Controls the structural memory of the baseline.
Higher values track broader swings and reduce flips.
Lower values track tighter swings and react faster.
Kalman Price Source
Defines what data the filter is estimating.
Close is usually the cleanest default.
HL2 often “feels” smoother as an average price.
High/Low sources can become more reactive and less stable depending on the market.
Measurement Noise
Think of this as the main smoothness knob:
Higher values generally produce a calmer filtered stream.
Lower values generally produce a faster, more reactive stream.
Process Noise
Think of this as adaptability:
Higher values adapt faster to changing conditions but can get twitchy.
Lower values adapt slower but stay stable.
Plotting and UI (what you see on chart)
1) Adaptive line coloring
Baseline turns bullish color when price is above it.
Baseline turns bearish color when price is below it.
This makes the state readable without extra panels.
2) Gradient “energy” fill
Bull fill appears between price and baseline when above.
Bear fill appears between price and baseline when below.
The goal is clarity on separation and control, not decoration.
3) Rim effect
A subtle band around price that only appears on the active side.
Helps highlight directional control without hiding candles.
4) Candle painting (optional)
Candles can be colored to match the current bias.
Useful for scanning many charts quickly.
Disable if you prefer raw candles.
Alerts
Long state alert when price is above the baseline.
Short state alert when price is below the baseline.
Best used as a bias or regime notification, not a standalone entry trigger.
Where it fits in a workflow
This is a context layer, it pairs well with:
Market structure tools, BOS/MSB, OBs, FVGs.
Momentum triggers that need a regime filter.
Mean reversion tools that need “do not fade trends” context.
Limitations
No baseline eliminates chop whipsaws, tuning only manages the trade-off.
Settings should not be copy pasted across assets without checking behavior.
This does not forecast, it estimates and smooths state, then expresses it as a structural baseline.
Disclaimer
Educational and informational only, not financial advice.
Not a complete trading system.
If you use it in any trading workflow, do proper backtesting, forward testing, and risk management before any live execution.
SMC Post-Analysis Lab [PhenLabs]📊 SMC Post-Analysis Lab
Version: PineScript™ v6
📌 Description
The SMC Post-Analysis Lab is a dedicated hindsight analysis tool built for traders who want to understand what really happened during any historical trading period. Unlike forward-looking indicators, this tool lets you scroll back through time and instantly receive algorithmic classification of market states using Smart Money Concepts methodology.
Whether you’re reviewing a losing trade, studying a successful session, or building your pattern recognition skills, this indicator provides immediate context. The expansion-aware algorithm processes price action within your selected window and outputs clear, actionable classifications ranging from Parabolic Expansion to Consolidation Inducements.
Stop relying on subjective post-trade analysis. Let the algorithm objectively tell you whether institutional players were accumulating, distributing, or running inducements during your trades.
🚀 Points of Innovation
First indicator specifically designed for SMC-based post-trade review rather than live signal generation
Dual-mode analysis system allowing both dynamic scrollback and precise date selection
Expansion-aware classification algorithm that weighs range position against net displacement
Real-time efficiency metrics calculating directional quality of price movement
Integrated visual FVG detection within the analysis window only
Interactive table with clickable date range adjustment via chart interface
🔧 Core Components
Pivot Detection Engine: Uses configurable pivot length to identify significant swing highs and lows for structure break detection
Window Calculator: Determines active analysis zone based on either bar offset or timestamp boundaries
Data Aggregator: Tracks window open, high, low, close and counts bullish/bearish structure break events
State Classification Algorithm: Applies hierarchical logic to determine market state from six possible classifications
Visual Renderer: Draws structure breaks, FVG boxes, and window highlighting within the active zone
🔥 Key Features
Sliding Window Mode: Use the Scroll Back slider to dynamically move your analysis zone backwards through history bar-by-bar
Date Range Mode: Select specific start and end timestamps for precise session or trade review
Six Market State Classifications: Parabolic Expansion (Bull/Bear), Bullish/Bearish Order Flow, Accumulation/Distribution Reversal, and Consolidation/Inducement
Range Position Percentile: See exactly where price closed relative to the window’s high-low range as a percentage
Bull/Bear Event Counter: Quantified count of structure breaks in each direction during the analysis period
Efficiency Calculation: Net move divided by total range reveals trending quality versus chop
🎨 Visualization
Blue Window Highlight: Active analysis zone is clearly marked with blue background shading on the chart
Structure Break Lines: Dashed lines appear at each bullish or bearish structure break within the window
FVG Boxes: Fair Value Gaps automatically render as semi-transparent boxes in bullish or bearish colors
Dashboard Table: Top-right positioned table displays State, Analysis description, and Metrics in real-time
Color-Coded States: Each classification uses distinct coloring for immediate visual recognition
Interactive Tip Row: Optional help text guides users on clicking the table to adjust date range
📖 Usage Guidelines
General Configuration
Analysis Mode: Default is Sliding Window. Choose Date Range for specific timestamp analysis.
Sliding Window Settings
Scroll Back (Bars): Default 0. Increase to move window backwards into history.
Window Width (Bars): Default 100. Range 20-50 for scalping, 100+ for swing analysis.
Date Range Settings
Start Date: Select the beginning timestamp for your analysis period.
End Date: Select the ending timestamp for your analysis period.
Visual Settings
Show Help Tip: Default true. Toggle to hide instructional row in dashboard.
Bullish Color: Default teal. Customize for bullish elements.
Bearish Color: Default red. Customize for bearish elements.
SMC Parameters
Pivot Length: Default 5. Lower values (3-5) catch minor breaks. Higher values (10+) focus on major swings.
✅ Best Use Cases
Post-trade review to understand why entries succeeded or failed
Session analysis to identify institutional activity patterns
Trade journaling with objective algorithmic classifications
Pattern recognition training through historical scrollback
Identifying whether stop hunts were inducements or legitimate breaks
Comparing your real-time read versus what the algorithm detected
⚠️ Limitations
Designed for historical analysis only, not live trade signals
Classification accuracy depends on appropriate pivot length for the timeframe
FVG detection uses simple gap logic without mitigation tracking
State classification is based on window data only, not broader context
Requires manual scrolling or date input to review different periods
💡 What Makes This Unique
Purpose-Built for Review: Unlike most indicators focused on live signals, this is designed specifically for post-trade analysis
Expansion-Aware Logic: Algorithm weighs both position in range AND directional efficiency for accurate state detection
Interactive Date Control: Click the dashboard table to reveal draggable anchors for window adjustment directly on chart
🔬 How It Works
1. Window Definition:
User selects either Sliding Window or Date Range mode
System calculates which bars fall within the active analysis zone
Active zone receives blue background highlighting
2. Data Collection:
Algorithm captures window open, running high, running low, and current close
Structure breaks are detected when price crosses above last pivot high or below last pivot low
Bullish and bearish events are counted separately
3. State Classification:
Range Position calculates where close sits as percentage of high-low range
Efficiency calculates net move divided by total range
Hierarchical logic applies priority rules from Parabolic states down to Consolidation
4. Output Rendering:
Dashboard table updates with State title, Analysis description, and Metrics
Visual elements render within window only to keep chart clean
Colors reflect bullish, bearish, or neutral classification
💡 Note:
This indicator is intended for educational and review purposes. Use it to develop your understanding of Smart Money Concepts by analyzing what institutional order flow looked like during historical periods. Combine insights with your own analysis methodology for best results.
IDAHL | QuantEdgeBIDAHL | QuantEdgeB
🔍 Overview
The IDAHL indicator builds adaptive, volatility-aware threshold bands from two separate ALMA lines—one smoothed from recent highs, the other from recent lows—then uses percentiles of those lines to define a dynamic “high/low” channel. Price crossing above or below that channel triggers clear long/short signals, with on-chart candle coloring, fills, optional labels and even a built-in backtest table.
✨ Key Features
• 📈 Dual ALMA Bands (with DEMA pre-smoothing)
o High ALMA: ALMA applied to DEMA-smoothed highs (high → DEMA(30) → ALMA).
o Low ALMA: ALMA applied to DEMA-smoothed lows (low → DEMA(30) → ALMA).
• 📊 Percentile Thresholds
o Computes a high threshold at the Xth percentile of the High ALMA over a lookback window.
o Computes a low threshold at the Yth percentile of the Low ALMA.
o Shifts each threshold forward by a small period to reduce repainting.
• ⚡ Dynamic Channel Logic
o When price closes above the high percentile line, the “final” threshold flips down to the low percentile line (and vice versa), creating an adaptive channel that only moves when the outer bound is violated.
o Inside the channel, the threshold holds its last value to avoid whipsaw.
• 🎨 Visual & Alerts
o Plots the two percentile lines and fills between them with a color that reflects the current regime (green for long, yellow for neutral, orange for short).
o Colors your candles to match the active signal.
o Optional “Long”/“Short” labels on confirmed flips.
o Alert conditions fire on each long/short crossover.
• 📊 On-Chart Backtest Metrics
o Toggle on a small performance table—complete with win-rate, net P/L, drawdown—from your chosen start date, without any extra code.
⚙️ How It Works
1. Adaptive Smoothing (ALMA)
o Uses ALMA (Arnaud Legoux Moving Average) for smooth, low-lag filtering. In this script, the inputs are additionally pre-smoothed with DEMA(30) to reduce noise before ALMA is applied—improving stability on highs/lows.
2. Percentile Lines
o The High ALMA series feeds a linear-interpolation percentile function to generate the upper bound; the Low ALMA produces the lower bound.
o These lines are offset by a small look-ahead (X bars) to reduce repaint behavior.
3. Channel Logic
o Breakout Flip: When the selected source (default: Close) closes above the upper bound, the active threshold “jumps” to the lower bound—locking in a new channel until price next crosses.
o Breakdown Flip: Conversely, a close below the lower bound flips the threshold to the upper bound.
4. Signal Generation
o Long while the source is above the current “final” threshold.
o Short while below.
o Neutral inside the channel before any flip.
5. Visualization & Alerts
o Dynamic fills between the two percentile lines change hue as the regime flips.
o Candles adopt the regime color.
o Optional pinned “Long”/“Short” labels at flip bars.
o Alerts on every signal crossover of the zero-based regime line.
6. Backtest Table
o From your chosen start date, a mini-table displays cumulative P/L, win rate and drawdown for this strategy—handy for quick in-chart validation.
🎯 Who Should Use It
• Breakout Traders hunting for adaptive channels that auto-recenter on new highs/lows.
• Volatility Traders who want thresholds that expand and contract with market turbulence.
• Trend-Chasers seeking a fresh take on high/low channels with built-in smoothing.
• Systematic Analysts who appreciate on-chart backtesting without leaving TradingView.
⚙️ Default Settings
• ALMA Length: 14
• Percentile Length: 35 bars
• Percentile Lookback Period (offset): 4 bars
• Upper Percentile: 92%
• Lower Percentile: 50%
• Threshold Source: Close
• Visuals: Candle coloring on, labels off by default, “Strategy” palette
• Backtest Table: on by default (toggleable)
• Start Date (Backtest): 09 Oct 2017
📌 Conclusion
IDAHL blends two smooth, low-lag ALMA filters (fed by DEMA-smoothed highs/lows) with percentile-based channel construction for a self-rewiring high/low envelope. It gives you robust breakout/breakdown signals, immediate visual context via colored fills and candles, optional labels, alerts, and even performance stats—everything you need to spot and confirm regime shifts in one compact script.
🔹 Disclaimer : Past performance is not indicative of future results. Always backtest and align settings with your risk tolerance and objectives before live trading.
🔹 Strategic Advice : Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Gold Smart Scalper V3 - Clean ChartOverview
The Gold Smart Scalper V3 is a trend-following momentum strategy specifically optimized for XAU/USD (Gold). It focuses on catching "value pullbacks" within a strong trend, avoiding the noise of sideways markets. Unlike many scalpers that use lagging indicators for exits, this version uses fixed ATR-based targets to lock in profits during high-volatility moves common in Gold.
Core Methodology
The strategy operates on three layers of confirmation:
Macro Trend (HTF Filter): Uses a 50-period EMA to ensure trades are only taken in the direction of the higher-timeframe momentum.
The Value Zone: Instead of "chasing" green or red candles, the script waits for a pullback to the space between the 9 EMA and 21 EMA. This ensures a better risk-to-reward entry point.
The Trigger: A trade is only executed when price confirms the resumption of the trend by crossing back over the signal EMA after the pullback.
Key Features
Fixed Profit Targets: Replaced dynamic trailing stops with fixed Take Profit (TP) and Stop Loss (SL) levels based on ATR, ensuring exits aren't "hunted" by Gold's signature volatility spikes.
C lean Chart Interface : All moving average plots are hidden. The only visuals provided are the active TP/SL levels when a trade is live, keeping your workspace clutter-free.
Single-Trade Logic: The script includes a "One Trade Per Cross" gate, preventing the strategy from over-trading or "stacking" positions during choppy price action.
Settings & OptimizationATR Multipliers :
Stop Loss (SL): Default $2.0 \times ATR$. Protects against standard market noise.Take Profit (TP): Default $3.0 \times ATR$. Designed for a high Risk/Reward profile.Timeframe Recommendation: Optimized for 15m and 1H for swing scalping, or 5m for aggressive scalping.Instrument: Specifically tuned for Gold (XAU/USD), but applicable to other high-volatility pairs like GBP/JPY or NASDAQ.
Disclaimer
This script is for educational and backtesting purposes only. Past performance does not guarantee future results. Always practice proper risk management.
Body Close Continuity & failure Backtesting @MaxMaseratiThis indicator, is a highly advanced institutional-grade tool designed to track the "lifespan" of a trend based on Body Close (BC) sequences.
Unlike basic indicators that just show direction, this script analyzes the structural integrity of a trend by monitoring how many candles continue the move before a "Touch" (retest) or a "Break" (failure) occurs.
The Continuity & Failure Stats indicator tracks sequences of Bullish Body Closes (BuBC) and Bearish Body Closes (BeBC). It measures three critical phases: Building (pure momentum), Touching (price retesting the low/high of the sequence), and Resumption (price continuing the trend after a retest). It provides a statistical distribution of how long these "buildings" typically last before failing, allowing traders to know exactly when a trend is overextended.
This comprehensive analysis blends the statistical breakdown of the Continuity & Failure Stats indicator to provide a deep understanding of the structural momentum for the S&P 500 E-mini (ES1!) on a 4-hour timeframe.
1. Extensive Table Breakdown
A. Building Distribution (Left Table): The Fatigue Gauge
This table acts as a histogram of momentum, tracking the "Building Count"—the number of consecutive candles closing in a trend without price returning to its origin.
Count Column: Represents the streak length (e.g., 1, 2, or 3 candles).
Touch Column: Shows how many times a streak was interrupted by a retest ("touch") but remained structurally intact.
Break Column: Counts total structural failures where price closed beyond the sequence's anchor.
Data Insight: For BuBC, 92 sequences reached Count 1, but only 28 remained by Count 4. This reveals a steep momentum decay after the 3rd candle, establishing a "Statistical Wall" where only 2 sequences in history reached a count of 9.
B. MMM Summary Stats (Top Right): The Mathematical DNA
This table provides the "Expected Value" and behavior of a trend over the lookback period.
Avg Building (2.39 for BuBC): On average, a bullish move lasts ~2.4 candles of pure momentum before a retest or reversal occurs.
Avg Touches (0.8): This low number indicates "clean" trends that rarely wobble back to retest levels multiple times before reaching a conclusion.
Avg R Cycles (0.55): This suggests that once a bullish trend is interrupted, it only successfully resumes its momentum about half the time.
Max R Count (1): Typically, once a trend is "touched," it only manages one more push before failing.
C. Multi-Timeframe (MTF) Quick Stats (Bottom Right): Trend Weight
This compares the 4H chart against other layers of the market to identify "global" alignment.
Sample Comparison: There are 3,594 tracked BuBC sequences on the 4H compared to only 142 on the Weekly chart.
Fractal Law: The Avg Building (2.4) is consistent across several timeframes, implying that the "Rule of Three" (momentum fading after 3 candles) is a fractal characteristic of this asset.
2. Table Comparison: Synthesizing the Data
To trade effectively, you must compare Distribution (timing) against Summary Stats (averages):
Continuity vs. Failure: The Summary Stats show an average building of 2.39. When checking the Distribution table at Count 2, the "Break" count (58) is already high relative to the "Total". This confirms that the risk of failure increases exponentially the moment you exceed the average.
Momentum vs. Mean Reversion: Distribution tells you when a trend is "tired". If the 4H is at a "Building Count 4" (statistically overextended) while the Weekly chart is at "Building Count 1" (fresh momentum), you may choose to prioritize the higher timeframe's strength despite the local overextension.
3. Strategic Summary & Application
This indicator proves that market momentum follows a predictable "Building" cycle rather than an infinite streak.
The "Rule of Three" for ES1! 4H:
The Entry Zone (Momentum Start): The most profitable entries occur at Building Count 1. Statistically, you have a high probability of reaching a count of 2 or 3.
The Exit Zone (Momentum Limit): Take profits or tighten stops at Count 3. The data shows the sample size drops by nearly 50% between Count 3 and Count 4.
The "Touch" Rule (Retest Reliability): If price returns to the sequence low (a "Touch"), do not expect a massive continuation. The Max R Count of 1 tells us that resumptions are usually short-lived.
Danger Zone: Entering at Building Count 4 or higher is statistically dangerous, as the "Break" probability significantly outweighs the "Touch" or continuation probability.
Hardwaybets Strat Market Checklist Trading## **Hardwaybets TheStrat Market Checklist Engine**
**A Checklist-Driven TheStrat Trading**
---
### **Overview**
This script is an **informational market context and permission framework** designed to help users **organize structural and liquidity information** in a clear, checklist-based format.
It evaluates **price context only** and displays the results in a table.
It does **not** generate trade signals or trading instructions.
---
### **What This Script Does**
The indicator evaluates and displays:
* Nearest prior **Area of Interest (AOI)**
(Previous Day High/Low or Previous Week High/Low)
* Higher-timeframe structural bias (Daily & Weekly)
* Proximity to liquidity
* Liquidity behavior (acceptance vs rejection)
* **Strat pattern classification only** (12 canonical patterns)
* A final **permission state** based on the above conditions
All information is presented as **contextual reference data**, not execution guidance.
---
### **What This Script Does NOT Do**
* ❌ No buy or sell signals
* ❌ No arrows, markers, or execution prompts
* ❌ No entries, exits, stops, or targets
* ❌ No performance metrics or profitability claims
* ❌ No strategy or backtesting logic
The word **“TRADE”** in the dashboard refers to **permission status only**, not a recommendation to trade.
---
### **Dashboard Modes**
* **Full Mode**: displays AOI price and distance (points & ticks)
* **Compact Mode**: minimal checklist view for reduced screen usage
Both modes are **informational only**.
---
### **Pattern Classification**
The script identifies and labels Strat candle pattern **types only**, including:
* Reversal patterns
* Continuation patterns
* Compression patterns
* Expansion patterns
Pattern labels are **descriptive classifications**, not signals or instructions.
---
### **Intended Use**
This script is intended to be used as a **contextual reference tool** alongside a user’s own analysis, rules, or education.
It may be useful for:
* Market structure study
* Liquidity behavior observation
* Pattern classification review
* Educational purposes
---
### **Technical Notes**
* Pine Script® v6
* Uses completed candles only
* No repainting logic
* No future data access
* Table-based UI only
---
### **Disclaimer**
This indicator is provided **for educational and informational purposes only**.
The author does not provide financial advice, trading recommendations, or execution guidance.
All trading decisions remain the sole responsibility of the user.
---
### **Conceptual Attribution**
This script is inspired by publicly available market structure concepts commonly referred to as “The Strat” methodology.
No proprietary or paid content is included.
---
### **Feedback**
Constructive feedback and suggestions are welcome.
Please note that this script is intentionally **non-signaling by design**.
Kijun Sen Standard Deviation | QuantLapse SystemsOverview
The Kijun Sen Standard Deviation indicator by QuantLapse Systems is a volatility-aware trend-following framework that combines the structural equilibrium of the Kijun Sen (基準線) with statistically adaptive standard deviation bands.
By anchoring trend detection to market structure and confirming direction through volatility expansion, the indicator delivers a cleaner, more reliable regime classification across varying market conditions.
Rather than reacting to short-term noise, the system focuses on identifying statistically justified trend phases , making it well-suited for disciplined, rule-based trading.
Technical Composition, Calculation, Key Components & Features
📌 Kijun Sen (基準線) – Structural Trend Baseline
Calculated as the midpoint between the highest high and lowest low over a user-defined period.
Represents market equilibrium and structural balance rather than short-term momentum.
Naturally adapts to expanding and contracting price ranges.
Provides a stable baseline for regime detection and volatility validation.
Acts as the anchor for deviation bands and persistent trend-state logic.
Unlike fast or reactive moving averages, the Kijun Sen emphasizes price structure and equilibrium , making it especially effective for higher-quality trend confirmation.
📌 Volatility Adjustment – Standard Deviation Bands
Standard deviation is calculated over a configurable lookback to measure current price dispersion.
Upper and lower envelopes are formed by applying a deviation multiplier to the Kijun Sen.
Band width expands during volatility surges and contracts during consolidation.
Creates proportional, volatility-aware thresholds instead of static offsets.
Visually represents market energy through expanding and compressing channels.
These adaptive bands ensure that trend signals only occur when volatility supports directional movement.
📌 Trend Signal & Regime Calculation
Bullish Trend is confirmed when price closes above the upper deviation band.
Bearish Trend is confirmed when price closes below the lower deviation band.
Once established, the trend state persists until an opposing volatility break occurs.
This persistence reduces whipsaws and improves regime stability.
Trend state is reinforced with color-coded lines, envelopes, and background shading.
This volatility-confirmed persistence model is visible in the chart, where trends remain intact through minor pullbacks and only flip on decisive expansion.
How It Works in Trading
✅ Volatility-Confirmed Trend Detection – Requires expansion beyond deviation bands.
✅ Noise Suppression – Filters low-energy price movement within volatility envelopes.
✅ Regime Persistence – Maintains trend state until statistical invalidation.
✅ Immediate Visual Context – Direction, strength, and transitions are clear at a glance.
Visual Representation
Trend signals are displayed directly on price using both line and background context:
🟢 Green / Teal Kijun & Envelope → Confirmed bullish regime.
🔴 Red / Pink Kijun & Envelope → Confirmed bearish regime.
Semi-transparent band fill visualizes volatility expansion and compression.
Buy and Sell labels appear only on confirmed regime transitions.
The lower panel includes:
Strategy equity curve based on trend exposure.
Buy & Hold equity for performance comparison.
Background regime shading synchronized with trend state.
Features and User Inputs
The Kijun Sen Standard Deviation framework offers a focused yet powerful set of configurable inputs:
Kijun Sen Length – Controls structural trend sensitivity.
Standard Deviation Controls – Adjust lookback length and multiplier for regime strictness.
Backtesting & Date Filters – Define evaluation periods and starting conditions.
Display Options – Toggle labels, equity curves, and background shading.
Color Customization – Fully configurable buy/sell colors for trends and equity curves.
These controls allow users to balance responsiveness, stability, and clarity without overfitting.
Practical Applications
The Kijun Sen Standard Deviation indicator is designed for traders who prioritize structure, volatility confirmation, and regime awareness.
Primary Trend Filtering – Identify and stay aligned with dominant market direction.
Volatility-Aware Trend Following – Participate only when price expansion confirms intent.
Risk-Managed Exposure – Avoid chop during compression and transitional phases.
Systematic Strategy Development – Use as a regime engine or higher-timeframe filter.
Performance Evaluation – Compare trend-following equity against buy-and-hold benchmarks.
This framework bridges classical Ichimoku structure with modern statistical validation.
Conclusion
The Kijun Sen Standard Deviation indicator by QuantLapse Systems represents a refined evolution of Ichimoku-based trend analysis.
By integrating the structural equilibrium of the Kijun Sen with adaptive standard deviation confirmation, the system delivers clearer regime classification, reduced noise, and more reliable trend participation.
Rather than attempting to predict price, it focuses on confirming when trends are statistically justified .
Who should use Kijun Sen Standard Deviation:
📊 Trend-Following Traders – Stay aligned with dominant market structure.
⚡ Momentum & Swing Traders – Enter only on volatility-backed expansions.
🤖 Systematic & Algorithmic Traders – Ideal as a regime filter or trend-state engine.
Past performance is not indicative of future results.
Disclaimer: All trading involves risk, and no indicator can guarantee profitability.
Strategic Advice: Always backtest thoroughly, optimize parameters responsibly, and align settings with your timeframe, asset class, and risk tolerance before live deployment.
Monday Range - User Defined LookbackEnglish Description
Monday Range Expansion & Multi-Week Projections
This indicator identifies the Monday Range (the price action from Monday's open at 00:00) and projects symmetric expansion levels across the entire trading week. It is designed for traders who use the weekly open and Monday's volatility as a benchmark for the week's price action.
Key Features:
Exact Monday 00:00 Start: Using advanced logic, the indicator pins the starting point precisely to the weekly open (Monday 00:00), ensuring no lag or offset regardless of your timeframe.
Symmetric Expansion Levels: It calculates the Monday High-Low range and projects a +100%, +50%, -50%, and -100% expansion, providing clear support and resistance targets.
User-Defined Lookback: You can choose exactly how many past weeks to display on your chart, keeping your workspace clean and focused.
Force Overlay Technology: All lines and labels use force_overlay, ensuring they always stay on the top layer, above candles and other indicators.
Weekly Freeze: Historical weeks stay "frozen" at their Friday closing points, allowing for clear backtesting of previous weekly levels.
Open Interest Bubbles [BackQuant]Open Interest Bubbles
A visual OI positioning overlay that aggregates futures open interest across major venues, normalizes it into a consistent “signal strength” scale, then plots extreme events as bubbles, labels, and optional horizontal levels directly on price.
What this is for
Open interest is one of the cleanest ways to track when positioning is building, unwinding, or aggressively shifting. The problem is raw OI is noisy, exchange-specific, and hard to compare across time. This script solves that by:
- Aggregating OI across multiple exchanges.
- Letting you choose what “OI signal” you care about (raw, delta, percent versions).
- Normalizing the signal so “big events” are easy to spot.
- Plotting those events as bubbles and levels at the exact price they occurred.
You end up with a clean, fast visual map of where large positioning changes occurred, and where those events may later matter as reaction points.
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Plotting types (what you can display)
Bubbles
This mode plots OI events as size-bucketed circles on the chart. Bigger bubbles represent stronger normalized events. You can tune:
- Bubble sizing by bucket (Tiny → Huge).
- Heatmap vs solid color styling.
- Signed vs unsigned coloring (positive/negative separation or magnitude-only).
Best use:
- Spotting “where something changed” at a glance.
- Identifying clusters of positioning events around key price zones.
- Seeing whether the market is repeatedly building/closing positions at similar levels.
Levels
Levels mode draws a horizontal line at the anchor price when an extreme OI event triggers. These act like “positioning memory” levels:
- They do not claim to be support/resistance by themselves.
- They highlight prices where the derivatives market clearly did something meaningful.
Best use:
- Marking potential reaction zones.
- Combining with your price action tools (structure, OBs, FVGs) to confirm whether an OI level aligns with a technical level.
- Building a “map” of where leverage likely entered or exited.
Modes available in the script:
- Off
- Bubbles
- Bubbles + Labels
- Labels Only
- Levels + Labels
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Aggregated Open Interest source (multi-exchange)
This indicator builds a single aggregated OI series by requesting OI data from multiple exchanges and summing it. You can toggle exchanges on/off:
- Binance, Bybit, OKX, Bitget, Kraken, HTX, Deribit
You can also choose OI units:
- COIN , OI in base units (native sizing)
- USD , converted for a dollar-value representation
Important note:
Not every symbol has OI data on every venue. If the script cannot build an aggregated series for the symbol, it will throw an error rather than quietly plotting garbage.
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OI Source, what the bubbles are measuring
You control what “signal” is normalized and plotted:
- Delta , change in aggregated OI from the prior bar.
Use when you want to highlight bursts of new positioning or sudden unwind events.
- Raw OI , the aggregated open interest level itself.
Use when you want to highlight absolute positioning build-up periods.
- Delta % , percent change in OI.
Use when you want moves normalized to the current OI regime, useful across different market eras.
- Raw OI % , percent change form of the raw series.
Use when you want relative changes rather than absolute size.
Practical guidance:
- Delta modes are best for “event detection”.
- Raw modes are better for “regime context” and whether positioning is structurally rising or fading.
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Normalization (the key to making it readable)
Because OI varies massively across assets and time, the script includes multiple normalization modes to convert your chosen OI source into a comparable “strength” value.
Options:
- ZScore , deviation from a rolling mean in standard deviation units.
- StdNorm , scaled by rolling standard deviation.
- AbsZScore , absolute value version for magnitude-only mapping.
- AbsStdNorm , absolute value version for magnitude-only mapping.
- None , plots raw values (advanced users only, often too noisy visually).
Why this matters:
Normalization makes a “1.5” or “3.0” threshold mean something across different assets and timeframes, instead of being stuck to raw OI units.
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Threshold system (when bubbles/levels trigger)
The plot is driven by two user thresholds:
- Base Threshold
Controls where “meaningful” events start. Raising this reduces noise and focuses on larger deviations.
- Extreme Threshold
Controls what qualifies as a top-tier event. Extreme events are what you typically want to convert into labels and levels.
You also control side filtering:
- Both , show positive and negative events.
- Positive Only , show only increases (or positive signal side depending on source).
- Negative Only , show only decreases (or negative signal side).
In practice:
- Use Base Threshold to tune chart cleanliness.
- Use Extreme Threshold to mark only the “big stuff” that tends to matter later.
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Anchor Source (where the bubble/level is placed)
The indicator places bubbles, labels, and levels at a price anchor you choose:
- HL2, Close, Open, High, Low, VWAP
This is important because “where you pin the event” changes how it reads:
- Close is clean and consistent for backtesting and candle-close logic.
- High/Low can better represent where the fight occurred intrabar.
- VWAP can be useful for “fair price” anchoring in active markets.
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Style system (theme, palette, signed logic)
This script is built to look good and stay readable on busy charts.
Themes
- BackQuant, Classic, Ice, Fire, Mono, Custom
Palette Mode
- Solid , one consistent color
- Heatmap , intensity increases with magnitude
- Single Color Adaptive , adapts to chart background for clarity
Side Coloring
- Signed , positive and negative events can use different ramps
- Unsigned , magnitude-only coloring
Negative theme handling:
- Auto (mirrors your chosen theme),
- Invert (flips the ramp),
- Custom (fully user-defined negative palette).
What this gives you:
- You can run a clean “mono” look for professional charts.
- Or a high-contrast heatmap for fast scanning.
- Or fully custom branding colors for BackQuant-style presentation.
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Labels (what’s inside the label)
When labels are enabled, the script can display:
- OI , the aggregated OI value
- OI + Norm , OI plus normalized strength
- Norm Only , just the normalized strength
- Src + Norm , the selected source value (Delta, Raw, %) plus normalized strength
You can also control:
- Left/Center/Right label alignment
- Number formatting style (Raw, Compact, Volume format)
Best practice:
- Use “Src + Norm” when you want both the raw event size and its rarity.
- Use “Norm Only” when you want a clean, minimal chart.
────────────────────────────────────────────────────────────
Levels and object limits (performance and cleanliness)
Because this script draws objects, it includes a hard cleanup system:
- You set Max Levels / Labels to control chart clutter.
- The script deletes older lines/labels when the limit is exceeded.
This is critical if you trade lower timeframes, where OI events can trigger frequently.
────────────────────────────────────────────────────────────
How to interpret the signals
What a large bubble usually means:
- A statistically large positioning change relative to recent history.
- This can represent fresh leverage entering, forced liquidations, or aggressive de-risking, depending on direction and context.
How to use levels:
- Treat them as “attention levels”, not automatic entries.
- Combine them with structure and liquidity tools:
- If price revisits an OI level and shows rejection, it often confirms that level mattered.
- If price slices through with no reaction, it often indicates the OI event was transitional, not defended.
Common setups:
- Clustered extreme bubbles near a breakout zone, then retest later.
- Extreme negative event at capitulation low, followed by structure flip.
- Extreme positive build into resistance, then unwind and mean reversion.
Also, please check out @NoveltyTrade for the OI Aggregation logic & pulling the data source!
Here is the original script:
Advanced custom multi MA signals (EMA/SMA/VWMA/VWAP) Features of Multi Moving Averages
The biggest enemy in trading is "Noise." If you get swayed by minute fluctuations on the chart, you end up missing the forest for the trees.
This indicator (Advanced Custom Multi MA Signals) is not just a simple line. By combining the three core elements of Price, Time, and Volume, it acts as a navigation system that visualizes the market's "true trend." In particular, the ability to analyze 5 moving averages simultaneously across various timeframes is akin to viewing a 3D map of the battlefield.
Understanding Core Concepts
This indicator supports 4 types of moving averages. It is crucial to clearly understand the nature of each tool.
SMA (Simple Moving Average): The most basic average value. Since it produces fewer whipsaws (false signals), it is used as a baseline to judge the "long-term trend."
EMA (Exponential Moving Average): Places more weight on recent prices. It reacts sensitively to market changes, making it advantageous for identifying "entry points."
VWMA (Volume Weighted Moving Average): Incorporates "volume" into the price calculation. It acts as a "false signal filter," weeding out price moves that aren't backed by trading volume.
VWAP (Volume Weighted Average Price): The benchmark price used by institutional investors for daily trading. It is calculated based on the session, regardless of the period settings. It is considered the "lifeline" of day trading.
Indicator Settings Guide
Open the settings window and tune it to fit your trading style.
MA 01 ~ 05 (Moving Average Settings)
MA Type: Select according to your purpose. (Generally, EMA is recommended for short-term analysis, SMA/VWMA for long-term).
Length: Enter the period you wish to analyze (e.g., 20, 60, 120, 200).
Timeframe: This is the core feature. It allows you to overlay moving averages from a higher timeframe (e.g., 4-hour, Daily) onto the chart you are currently viewing (e.g., 15-minute).
Signal Option (Trading Signals)
Golden Cross (GC) / Death Cross (DC): Captures the moment the short-term line breaks through the long-term line. You can run up to 3 strategies simultaneously.
Ribbon Gradient (Trend Visualization)
Represents the gap between two moving averages with color. As the color deepens and the width expands, it indicates a powerful trend; if the width narrows, it suggests a high probability of a trend reversal.
5 Usage Strategies
The highlight of this indicator is the cross strategy utilizing the "Multi-Timeframe (MTF)" feature. Familiarize yourself with the 5 example strategies below and set up your own strategy based on your expertise.
💡 Tip 1. Do not go against the "Major Trend" (The Authority of the Weekly Candle)
Settings: Set MA5 to .
Interpretation: The Weekly 50 line is the "major trend line" managed by institutions and market makers. If the current price is above this line, maintain only a "Buy (Long)" bias; if below, maintain only a "Sell (Short)" bias. Adhering to this rule alone can help you avoid massive losses.
💡 Tip 2. Highly Reliable "Swing Signal" (Daily Golden Cross)
Settings: In Signal 1, configure the Short MA to and the Long MA to .
Interpretation: A Golden Cross where the 4-Hour 50 EMA breaks above the Daily 50 EMA often signifies a major "trend reversal" rather than a temporary rebound. This provides an ideal entry signal for office workers or swing traders who need high reliability.
💡 Tip 3. 4-Hour Candle as the Standard for "Precision Entry"
Situation: When the Daily trend is rising (Bullish alignment).
Strategy: While watching the 15-minute or 1-hour chart, set the indicator's Signal 2 to the cross of and .
Interpretation: When the Daily chart is in an uptrend, a Golden Cross occurring on the 4-Hour chart marks "the point where a correction (pullback) ends and the rise resumes." This is the entry point with the best risk-to-reward ratio.
💡 Tip 4. Filtering Out "Fake Signals" (The Secret of Volume)
Strategy: When creating a cross signal, try using VWMA (Volume Weighted) for the Long MA, even if you use EMA for the Short MA.
Reason: A Golden Cross caused simply by a rise in price can be a trap. However, if it breaks through the heavy VWMA line accompanied by volume, it is strong evidence that "genuine liquidity" has entered.
💡 Tip 5. Remember the "Hierarchy" (Higher Timeframe Priority Rule)
Principle: If a Golden Cross (Buy Signal) appears on the 4-Hour chart, but the Daily chart is in a Death Cross (Sell Signal) state, do not enter.
Interpretation: A signal from a lower timeframe cannot overcome the power of a higher timeframe. The professional approach is to trade with significant volume only when signals align (Sync) in the order of Weekly > Daily > 4-Hour. Keep this indicator's dashboard feature on and always check the status of higher timeframes.
Signal Generation Principle (Operating Mechanism)
Signals are generated when the set short-term moving average and long-term moving average cross each other.
📈 1. Golden Cross (BUY = Buy Signal)
Situation: The moment the short-term MA crosses upward from below the long-term MA.
Principle: It implies that recent buying pressure has broken through the resistance level accumulated over a long period.
📉 2. Death Cross (SELL = Sell Signal)
Situation: The moment the short-term MA crosses downward from above the long-term MA.
Principle: It implies that recent selling pressure has collapsed the long-term support line.
※ If the candles are not displaying correctly or are flickering, please set the indicator's 'Visual order' to 'Bring to front' as shown in the image below.
Investment Caution and Disclaimer
Before using this indicator for actual trading, please strictly read the contents below.
① Auxiliary indicators are a "Compass," not a "Book of Prophecy."
This indicator is merely a tool that mathematically calculates and visualizes past price data. A "magic indicator" that predicts future price fluctuations 100% accurately or guarantees profit does not exist. The signals provided are for reference only and must never be the sole basis for entry/exit decisions.
② The responsibility for all investments lies with "Yourself."
Financial investment (Cryptocurrencies, Stocks, Futures, etc.) involves high volatility and is a risky activity that can result in the loss of some or all of the principal. The final responsibility for all trading results (profits and losses) incurred by utilizing this indicator lies entirely with the investor. The distributor and developer accept no legal responsibility for investment results under any circumstances.
③ Past data does not guarantee the future.
Even a Golden Cross that fit perfectly in backtesting or past charts may operate differently in tomorrow's market situation (News, Macroeconomics, Unexpected Variables, etc.). Do not rely solely on technical analysis; you must conduct fundamental analysis and risk management in parallel.
④ Risk management is the top priority.
No matter how promising a signal appears, "all-in trading" (investing all assets in a single trade) is a shortcut to bankruptcy. More important than the indicator itself is adhering to the principles of strict scaling in (split buying) and Stop-Loss.
ORB Fusion🎯 CORE INNOVATION: INSTITUTIONAL ORB FRAMEWORK WITH FAILED BREAKOUT INTELLIGENCE
ORB Fusion represents a complete institutional-grade Opening Range Breakout system combining classic Market Profile concepts (Initial Balance, day type classification) with modern algorithmic breakout detection, failed breakout reversal logic, and comprehensive statistical tracking. Rather than simply drawing lines at opening range extremes, this system implements the full trading methodology used by professional floor traders and market makers—including the critical concept that failed breakouts are often higher-probability setups than successful breakouts .
The Opening Range Hypothesis:
The first 30-60 minutes of trading establishes the day's value area —the price range where the majority of participants agree on fair value. This range is formed during peak information flow (overnight news digestion, gap reactions, early institutional positioning). Breakouts from this range signal directional conviction; failures to hold breakouts signal trapped participants and create exploitable reversals.
Why Opening Range Matters:
1. Information Aggregation : Opening range reflects overnight news, pre-market sentiment, and early institutional orders. It's the market's initial "consensus" on value.
2. Liquidity Concentration : Stop losses cluster just outside opening range. Breakouts trigger these stops, creating momentum. Failed breakouts trap traders, forcing reversals.
3. Statistical Persistence : Markets exhibit range expansion tendency —when price accepts above/below opening range with volume, it often extends 1.0-2.0x the opening range size before mean reversion.
4. Institutional Behavior : Large players (market makers, institutions) use opening range as reference for the day's trading plan. They fade extremes in rotation days and follow breakouts in trend days.
Historical Context:
Opening Range Breakout methodology originated in commodity futures pits (1970s-80s) where floor traders noticed consistent patterns: the first 30-60 minutes established a "fair value zone," and directional moves occurred when this zone was violated with conviction. J. Peter Steidlmayer formalized this observation in Market Profile theory, introducing the "Initial Balance" concept—the first hour (two 30-minute periods) defining market structure.
📊 OPENING RANGE CONSTRUCTION
Four ORB Timeframe Options:
1. 5-Minute ORB (0930-0935 ET):
Captures immediate market direction during "opening drive"—the explosive first few minutes when overnight orders hit the tape.
Use Case:
• Scalping strategies
• High-frequency breakout trading
• Extremely liquid instruments (ES, NQ, SPY)
Characteristics:
• Very tight range (often 0.2-0.5% of price)
• Early breakouts common (7 of 10 days break within first hour)
• Higher false breakout rate (50-60%)
• Requires sub-minute chart monitoring
Psychology: Captures panic buyers/sellers reacting to overnight news. Range is small because sample size is minimal—only 5 minutes of price discovery. Early breakouts often fail because they're driven by retail FOMO rather than institutional conviction.
2. 15-Minute ORB (0930-0945 ET):
Balances responsiveness with statistical validity. Captures opening drive plus initial reaction to that drive.
Use Case:
• Day trading strategies
• Balanced scalping/swing hybrid
• Most liquid instruments
Characteristics:
• Moderate range (0.4-0.8% of price typically)
• Breakout rate ~60% of days
• False breakout rate ~40-45%
• Good balance of opportunity and reliability
Psychology: Includes opening panic AND the first retest/consolidation. Sophisticated traders (institutions, algos) start expressing directional bias. This is the "Goldilocks" timeframe—not too reactive, not too slow.
3. 30-Minute ORB (0930-1000 ET):
Classic ORB timeframe. Default for most professional implementations.
Use Case:
• Standard intraday trading
• Position sizing for full-day trades
• All liquid instruments (equities, indices, futures)
Characteristics:
• Substantial range (0.6-1.2% of price)
• Breakout rate ~55% of days
• False breakout rate ~35-40%
• Statistical sweet spot for extensions
Psychology: Full opening auction + first institutional repositioning complete. By 10:00 AM ET, headlines are digested, early stops are hit, and "real" directional players reveal themselves. This is when institutional programs typically finish their opening positioning.
Statistical Advantage: 30-minute ORB shows highest correlation with daily range. When price breaks and holds outside 30m ORB, probability of reaching 1.0x extension (doubling the opening range) exceeds 60% historically.
4. 60-Minute ORB (0930-1030 ET) - Initial Balance:
Steidlmayer's "Initial Balance"—the foundation of Market Profile theory.
Use Case:
• Swing trading entries
• Day type classification
• Low-frequency institutional setups
Characteristics:
• Wide range (0.8-1.5% of price)
• Breakout rate ~45% of days
• False breakout rate ~25-30% (lowest)
• Best for trend day identification
Psychology: Full first hour captures A-period (0930-1000) and B-period (1000-1030). By 10:30 AM ET, all early positioning is complete. Market has "voted" on value. Subsequent price action confirms (trend day) or rejects (rotation day) this value assessment.
Initial Balance Theory:
IB represents the market's accepted value area . When price extends significantly beyond IB (>1.5x IB range), it signals a Trend Day —strong directional conviction. When price remains within 1.0x IB, it signals a Rotation Day —mean reversion environment. This classification completely changes trading strategy.
🔬 LTF PRECISION TECHNOLOGY
The Chart Timeframe Problem:
Traditional ORB indicators calculate range using the chart's current timeframe. This creates critical inaccuracies:
Example:
• You're on a 5-minute chart
• ORB period is 30 minutes (0930-1000 ET)
• Indicator sees only 6 bars (30min ÷ 5min/bar = 6 bars)
• If any 5-minute bar has extreme wick, entire ORB is distorted
The Problem Amplifies:
• On 15-minute chart with 30-minute ORB: Only 2 bars sampled
• On 30-minute chart with 30-minute ORB: Only 1 bar sampled
• Opening spike or single large wick defines entire range (invalid)
Solution: Lower Timeframe (LTF) Precision:
ORB Fusion uses `request.security_lower_tf()` to sample 1-minute bars regardless of chart timeframe:
```
For 30-minute ORB on 15-minute chart:
- Traditional method: Uses 2 bars (15min × 2 = 30min)
- LTF Precision: Requests thirty 1-minute bars, calculates true high/low
```
Why This Matters:
Scenario: ES futures, 15-minute chart, 30-minute ORB
• Traditional ORB: High = 5850.00, Low = 5842.00 (range = 8 points)
• LTF Precision ORB: High = 5848.50, Low = 5843.25 (range = 5.25 points)
Difference: 2.75 points distortion from single 15-minute wick hitting 5850.00 at 9:31 AM then immediately reversing. LTF precision filters this out by seeing it was a fleeting wick, not a sustained high.
Impact on Extensions:
With inflated range (8 points vs 5.25 points):
• 1.5x extension projects +12 points instead of +7.875 points
• Difference: 4.125 points (nearly $200 per ES contract)
• Breakout signals trigger late; extension targets unreachable
Implementation:
```pinescript
getLtfHighLow() =>
float ha = request.security_lower_tf(syminfo.tickerid, "1", high)
float la = request.security_lower_tf(syminfo.tickerid, "1", low)
```
Function returns arrays of 1-minute high/low values, then finds true maximum and minimum across all samples.
When LTF Precision Activates:
Only when chart timeframe exceeds ORB session window:
• 5-minute chart + 30-minute ORB: LTF used (chart TF > session bars needed)
• 1-minute chart + 30-minute ORB: LTF not needed (direct sampling sufficient)
Recommendation: Always enable LTF Precision unless you're on 1-minute charts. The computational overhead is negligible, and accuracy improvement is substantial.
⚖️ INITIAL BALANCE (IB) FRAMEWORK
Steidlmayer's Market Profile Innovation:
J. Peter Steidlmayer developed Market Profile in the 1980s for the Chicago Board of Trade. His key insight: market structure is best understood through time-at-price (value area) rather than just price-over-time (traditional charts).
Initial Balance Definition:
IB is the price range established during the first hour of trading, subdivided into:
• A-Period : First 30 minutes (0930-1000 ET for US equities)
• B-Period : Second 30 minutes (1000-1030 ET)
A-Period vs B-Period Comparison:
The relationship between A and B periods forecasts the day:
B-Period Expansion (Bullish):
• B-period high > A-period high
• B-period low ≥ A-period low
• Interpretation: Buyers stepping in after opening assessed
• Implication: Bullish continuation likely
• Strategy: Buy pullbacks to A-period high (now support)
B-Period Expansion (Bearish):
• B-period low < A-period low
• B-period high ≤ A-period high
• Interpretation: Sellers stepping in after opening assessed
• Implication: Bearish continuation likely
• Strategy: Sell rallies to A-period low (now resistance)
B-Period Contraction:
• B-period stays within A-period range
• Interpretation: Market indecisive, digesting A-period information
• Implication: Rotation day likely, stay range-bound
• Strategy: Fade extremes, sell high/buy low within IB
IB Extensions:
Professional traders use IB as a ruler to project price targets:
Extension Levels:
• 0.5x IB : Initial probe outside value (minor target)
• 1.0x IB : Full extension (major target for normal days)
• 1.5x IB : Trend day threshold (classifies as trending)
• 2.0x IB : Strong trend day (rare, ~10-15% of days)
Calculation:
```
IB Range = IB High - IB Low
Bull Extension 1.0x = IB High + (IB Range × 1.0)
Bear Extension 1.0x = IB Low - (IB Range × 1.0)
```
Example:
ES futures:
• IB High: 5850.00
• IB Low: 5842.00
• IB Range: 8.00 points
Extensions:
• 1.0x Bull Target: 5850 + 8 = 5858.00
• 1.5x Bull Target: 5850 + 12 = 5862.00
• 2.0x Bull Target: 5850 + 16 = 5866.00
If price reaches 5862.00 (1.5x), day is classified as Trend Day —strategy shifts from mean reversion to trend following.
📈 DAY TYPE CLASSIFICATION SYSTEM
Four Day Types (Market Profile Framework):
1. TREND DAY:
Definition: Price extends ≥1.5x IB range in one direction and stays there.
Characteristics:
• Opens and never returns to IB
• Persistent directional movement
• Volume increases as day progresses (conviction building)
• News-driven or strong institutional flow
Frequency: ~20-25% of trading days
Trading Strategy:
• DO: Follow the trend, trail stops, let winners run
• DON'T: Fade extremes, take early profits
• Key: Add to position on pullbacks to previous extension level
• Risk: Getting chopped in false trend (see Failed Breakout section)
Example: FOMC decision, payroll report, earnings surprise—anything creating one-sided conviction.
2. NORMAL DAY:
Definition: Price extends 0.5-1.5x IB, tests both sides, returns to IB.
Characteristics:
• Two-sided trading
• Extensions occur but don't persist
• Volume balanced throughout day
• Most common day type
Frequency: ~45-50% of trading days
Trading Strategy:
• DO: Take profits at extension levels, expect reversals
• DON'T: Hold for massive moves
• Key: Treat each extension as a profit-taking opportunity
• Risk: Holding too long when momentum shifts
Example: Typical day with no major catalysts—market balancing supply and demand.
3. ROTATION DAY:
Definition: Price stays within IB all day, rotating between high and low.
Characteristics:
• Never accepts outside IB
• Multiple tests of IB high/low
• Decreasing volume (no conviction)
• Classic range-bound action
Frequency: ~25-30% of trading days
Trading Strategy:
• DO: Fade extremes (sell IB high, buy IB low)
• DON'T: Chase breakouts
• Key: Enter at extremes with tight stops just outside IB
• Risk: Breakout finally occurs after multiple failures
Example: [/b> Pre-holiday trading, summer doldrums, consolidation after big move.
4. DEVELOPING:
Definition: Day type not yet determined (early in session).
Usage: Classification before 12:00 PM ET when IB extension pattern unclear.
ORB Fusion's Classification Algorithm:
```pinescript
if close > ibHigh:
ibExtension = (close - ibHigh) / ibRange
direction = "BULLISH"
else if close < ibLow:
ibExtension = (ibLow - close) / ibRange
direction = "BEARISH"
if ibExtension >= 1.5:
dayType = "TREND DAY"
else if ibExtension >= 0.5:
dayType = "NORMAL DAY"
else if close within IB:
dayType = "ROTATION DAY"
```
Why Classification Matters:
Same setup (bullish ORB breakout) has opposite implications:
• Trend Day : Hold for 2.0x extension, trail stops aggressively
• Normal Day : Take profits at 1.0x extension, watch for reversal
• Rotation Day : Fade the breakout immediately (likely false)
Knowing day type prevents catastrophic errors like fading a trend day or holding through rotation.
🚀 BREAKOUT DETECTION & CONFIRMATION
Three Confirmation Methods:
1. Close Beyond Level (Recommended):
Logic: Candle must close above ORB high (bull) or below ORB low (bear).
Why:
• Filters out wicks (temporary liquidity grabs)
• Ensures sustained acceptance above/below range
• Reduces false breakout rate by ~20-30%
Example:
• ORB High: 5850.00
• Bar high touches 5850.50 (wick above)
• Bar closes at 5848.00 (inside range)
• Result: NO breakout signal
vs.
• Bar high touches 5850.50
• Bar closes at 5851.00 (outside range)
• Result: BREAKOUT signal confirmed
Trade-off: Slightly delayed entry (wait for close) but much higher reliability.
2. Wick Beyond Level:
Logic: [/b> Any touch of ORB high/low triggers breakout.
Why:
• Earliest possible entry
• Captures aggressive momentum moves
Risk:
• High false breakout rate (60-70%)
• Stop runs trigger signals
• Requires very tight stops (difficult to manage)
Use Case: Scalping with 1-2 point profit targets where any penetration = trade.
3. Body Beyond Level:
Logic: [/b> Candle body (close vs open) must be entirely outside range.
Why:
• Strictest confirmation
• Ensures directional conviction (not just momentum)
• Lowest false breakout rate
Example: Trade-off: [/b> Very conservative—misses some valid breakouts but rarely triggers on false ones.
Volume Confirmation Layer:
All confirmation methods can require volume validation:
Volume Multiplier Logic: Rationale: [/b> True breakouts are driven by institutional activity (large size). Volume spike confirms real conviction vs. stop-run manipulation.
Statistical Impact: [/b>
• Breakouts with volume confirmation: ~65% success rate
• Breakouts without volume: ~45% success rate
• Difference: 20 percentage points edge
Implementation Note: [/b>
Volume confirmation adds complexity—you'll miss breakouts that work but lack volume. However, when targeting 1.5x+ extensions (ambitious goals), volume confirmation becomes critical because those moves require sustained institutional participation.
Recommended Settings by Strategy: [/b>
Scalping (1-2 point targets): [/b>
• Method: Close
• Volume: OFF
• Rationale: Quick in/out doesn't need perfection
Intraday Swing (5-10 point targets): [/b>
• Method: Close
• Volume: ON (1.5x multiplier)
• Rationale: Balance reliability and opportunity
Position Trading (full-day holds): [/b>
• Method: Body
• Volume: ON (2.0x multiplier)
• Rationale: Must be certain—large stops require high win rate
🔥 FAILED BREAKOUT SYSTEM
The Core Insight: [/b>
Failed breakouts are often more profitable [/b> than successful breakouts because they create trapped traders with predictable behavior.
Failed Breakout Definition: [/b>
A breakout that:
1. Initially penetrates ORB level with confirmation
2. Attracts participants (volume spike, momentum)
3. Fails to extend (stalls or immediately reverses)
4. Returns inside ORB range within N bars
Psychology of Failure: [/b>
When breakout fails:
• Breakout buyers are trapped [/b>: Bought at ORB high, now underwater
• Early longs reduce: Take profit, fearful of reversal
• Shorts smell blood: See failed breakout as reversal signal
• Result: Cascade of selling as trapped bulls exit + new shorts enter
Mirror image for failed bearish breakouts (trapped shorts cover + new longs enter).
Failure Detection Parameters: [/b>
1. Failure Confirmation Bars (default: 3): [/b>
How many bars after breakout to confirm failure?
Logic: Settings: [/b>
• 2 bars: Aggressive failure detection (more signals, more false failures)
• 3 bars Balanced (default)
• 5-10 bars: Conservative (wait for clear reversal)
Why This Matters:
Too few bars: You call "failed breakout" when price is just consolidating before next leg.
Too many bars: You miss the reversal entry (price already back in range).
2. Failure Buffer (default: 0.1 ATR): [/b>
How far inside ORB must price return to confirm failure?
Formula: Why Buffer Matters: clear rejection [/b> (not just hovering at level).
Settings: [/b>
• 0.0 ATR: No buffer, immediate failure signal
• 0.1 ATR: Small buffer (default) - filters noise
• [b>0.2-0.3 ATR: Large buffer - only dramatic failures count
Example: Reversal Entry System: [/b>
When failure confirmed, system generates complete reversal trade:
For Failed Bull Breakout (Short Reversal): [/b>
Entry: [/b> Current close when failure confirmed
Stop Loss: [/b> Extreme high since breakout + 0.10 ATR padding
Target 1: [/b> ORB High - (ORB Range × 0.5)
Target 2: Target 3: [/b> ORB High - (ORB Range × 1.5)
Example:
• ORB High: 5850, ORB Low: 5842, Range: 8 points
• Breakout to 5853, fails, reverses to 5848 (entry)
• Stop: 5853 + 1 = 5854 (6 point risk)
• T1: 5850 - 4 = 5846 (-2 points, 1:3 R:R)
• T2: 5850 - 8 = 5842 (-6 points, 1:1 R:R)
• T3: 5850 - 12 = 5838 (-10 points, 1.67:1 R:R)
[b>Why These Targets? [/b>
• T1 (0.5x ORB below high): Trapped bulls start panic
• T2 (1.0x ORB = ORB Mid): Major retracement, momentum fully reversed
• T3 (1.5x ORB): Reversal extended, now targeting opposite side
Historical Performance: [/b>
Failed breakout reversals in ORB Fusion's tracking system show:
• Win Rate: 65-75% (significantly higher than initial breakouts)
• Average Winner: 1.2x ORB range
• Average Loser: 0.5x ORB range (protected by stop at extreme)
• Expectancy: Strongly positive even with <70% win rate
Why Failed Breakouts Outperform: [/b>
1. Information Advantage: You now know what price did (failed to extend). Initial breakout trades are speculative; reversal trades are reactive to confirmed failure.
2. Trapped Participant Pressure: Every trapped bull becomes a seller. This creates sustained pressure.
3. Stop Loss Clarity: Extreme high is obvious stop (just beyond recent high). Breakout trades have ambiguous stops (ORB mid? Recent low? Too wide or too tight).
4. Mean Reversion Edge: Failed breakouts return to value (ORB mid). Initial breakouts try to escape value (harder to sustain).
Critical Insight: [/b>
"The best trade is often the one that trapped everyone else."
Failed breakouts create asymmetric opportunity because you're trading against [/b> trapped participants rather than with [/b> them. When you see a failed breakout signal, you're seeing real-time evidence that the market rejected directional conviction—that's exploitable.
📐 FIBONACCI EXTENSION SYSTEM
Six Extension Levels: [/b>
Extensions project how far price will travel after ORB breakout. Based on Fibonacci ratios + empirical market behavior.
1. 1.272x (27.2% Extension): [/b>
Formula: [/b> ORB High/Low + (ORB Range × 0.272)
Psychology: [/b> Initial probe beyond ORB. Early momentum + trapped shorts (on bull side) covering.
Probability of Reach: [/b> ~75-80% after confirmed breakout
Trading: [/b>
• First resistance/support after breakout
• Partial profit target (take 30-50% off)
• Watch for rejection here (could signal failure in progress)
Why 1.272? [/b> Related to harmonic patterns (1.272 is √1.618). Empirically, markets often stall at 25-30% extension before deciding whether to continue or fail.
2. 1.5x (50% Extension):
Formula: [/b> ORB High/Low + (ORB Range × 0.5)
Psychology: [/b> Breakout gaining conviction. Requires sustained buying/selling (not just momentum spike).
Probability of Reach: [/b> ~60-65% after confirmed breakout
Trading: [/b>
• Major partial profit (take 50-70% off)
• Move stops to breakeven
• Trail remaining position
Why 1.5x? [/b> Classic halfway point to 2.0x. Markets often consolidate here before final push. If day type is "Normal," this is likely the high/low for the day.
3. 1.618x (Golden Ratio Extension): [/b>
Formula: [/b> ORB High/Low + (ORB Range × 0.618)
Psychology: [/b> Strong directional day. Institutional conviction + retail FOMO.
Probability of Reach: [/b> ~45-50% after confirmed breakout
Trading: [/b>
• Final partial profit (close 80-90%)
• Trail remainder with wide stop (allow breathing room)
Why 1.618? [/b> Fibonacci golden ratio. Appears consistently in market geometry. When price reaches 1.618x extension, move is "mature" and reversal risk increases.
4. 2.0x (100% Extension): [/b>
Formula: ORB High/Low + (ORB Range × 1.0)
Psychology: [/b> Trend day confirmed. Opening range completely duplicated.
Probability of Reach: [/b> ~30-35% after confirmed breakout
Trading: Why 2.0x? [/b> Psychological level—range doubled. Also corresponds to typical daily ATR in many instruments (opening range ~ 0.5 ATR, daily range ~ 1.0 ATR).
5. 2.618x (Super Extension):
Formula: [/b> ORB High/Low + (ORB Range × 1.618)
Psychology: [/b> Parabolic move. News-driven or squeeze.
Probability of Reach: [/b> ~10-15% after confirmed breakout
[b>Trading: Why 2.618? [/b> Fibonacci ratio (1.618²). Rare to reach—when it does, move is extreme. Often precedes multi-day consolidation or reversal.
6. 3.0x (Extreme Extension): [/b>
Formula: [/b> ORB High/Low + (ORB Range × 2.0)
Psychology: [/b> Market melt-up/crash. Only in extreme events.
[b>Probability of Reach: [/b> <5% after confirmed breakout
Trading: [/b>
• Close immediately if reached
• These are outlier events (black swans, flash crashes, squeeze-outs)
• Holding for more is greed—take windfall profit
Why 3.0x? [/b> Triple opening range. So rare it's statistical noise. When it happens, it's headline news.
Visual Example:
ES futures, ORB 5842-5850 (8 point range), Bullish breakout:
• ORB High : 5850.00 (entry zone)
• 1.272x : 5850 + 2.18 = 5852.18 (first resistance)
• 1.5x : 5850 + 4.00 = 5854.00 (major target)
• 1.618x : 5850 + 4.94 = 5854.94 (strong target)
• 2.0x : 5850 + 8.00 = 5858.00 (trend day)
• 2.618x : 5850 + 12.94 = 5862.94 (extreme)
• 3.0x : 5850 + 16.00 = 5866.00 (parabolic)
Profit-Taking Strategy:
Optimal scaling out at extensions:
• Breakout entry at 5850.50
• 30% off at 1.272x (5852.18) → +1.68 points
• 40% off at 1.5x (5854.00) → +3.50 points
• 20% off at 1.618x (5854.94) → +4.44 points
• 10% off at 2.0x (5858.00) → +7.50 points
[b>Average Exit: Conclusion: [/b> Scaling out at extensions produces 40% higher expectancy than holding for home runs.
📊 GAP ANALYSIS & FILL PSYCHOLOGY
[b>Gap Definition: [/b>
Price discontinuity between previous close and current open:
• Gap Up : Open > Previous Close + noise threshold (0.1 ATR)
• Gap Down : Open < Previous Close - noise threshold
Why Gaps Matter: [/b>
Gaps represent unfilled orders [/b>. When market gaps up, all limit buy orders between yesterday's close and today's open are never filled. Those buyers are "left behind." Psychology: they wait for price to return ("fill the gap") so they can enter. This creates magnetic pull [/b> toward gap level.
Gap Fill Statistics (Empirical): [/b>
• Gaps <0.5% [/b>: 85-90% fill within same day
• Gaps 0.5-1.0% [/b>: 70-75% fill within same day, 90%+ within week
• Gaps >1.0% [/b>: 50-60% fill within same day (major news often prevents fill)
Gap Fill Strategy: [/b>
Setup 1: Gap-and-Go
Gap opens, extends away from gap (doesn't fill).
• ORB confirms direction away from gap
• Trade WITH ORB breakout direction
• Expectation: Gap won't fill today (momentum too strong)
Setup 2: Gap-Fill Fade
Gap opens, but fails to extend. Price drifts back toward gap.
• ORB breakout TOWARD gap (not away)
• Trade toward gap fill level
• Target: Previous close (gap fill complete)
Setup 3: Gap-Fill Rejection
Gap fills (touches previous close) then rejects.
• ORB breakout AWAY from gap after fill
• Trade away from gap direction
• Thesis: Gap filled (orders executed), now resume original direction
[b>Example: Scenario A (Gap-and-Go):
• ORB breaks upward to $454 (away from gap)
• Trade: LONG breakout, expect continued rally
• Gap becomes support ($452)
Scenario B (Gap-Fill):
• ORB breaks downward through $452.50 (toward gap)
• Trade: SHORT toward gap fill at $450.00
• Target: $450.00 (gap filled), close position
Scenario C (Gap-Fill Rejection):
• Price drifts to $450.00 (gap filled) early in session
• ORB establishes $450-$451 after gap fill
• ORB breaks upward to $451.50
• Trade: LONG breakout (gap is filled, now resume rally)
ORB Fusion Integration: [/b>
Dashboard shows:
• Gap type (Up/Down/None)
• Gap size (percentage)
• Gap fill status (Filled ✓ / Open)
This informs setup confidence:
• ORB breakout AWAY from unfilled gap: +10% confidence (gap becomes support/resistance)
• ORB breakout TOWARD unfilled gap: -10% confidence (gap fill may override ORB)
[b>📈 VWAP & INSTITUTIONAL BIAS [/b>
[b>Volume-Weighted Average Price (VWAP): [/b>
Average price weighted by volume at each price level. Represents true "average" cost for the day.
[b>Calculation: Institutional Benchmark [/b>: Institutions (mutual funds, pension funds) use VWAP as performance benchmark. If they buy above VWAP, they underperformed; below VWAP, they outperformed.
2. [b>Algorithmic Target [/b>: Many algos are programmed to buy below VWAP and sell above VWAP to achieve "fair" execution.
3. [b>Support/Resistance [/b>: VWAP acts as dynamic support (price above) or resistance (price below).
[b>VWAP Bands (Standard Deviations): [/b>
• [b>1σ Band [/b>: VWAP ± 1 standard deviation
- Contains ~68% of volume
- Normal trading range
- Bounces common
• [b>2σ Band [/b>: VWAP ± 2 standard deviations
- Contains ~95% of volume
- Extreme extension
- Mean reversion likely
ORB + VWAP Confluence: [/b>
Highest-probability setups occur when ORB and VWAP align:
Bullish Confluence: [/b>
• ORB breakout upward (bullish signal)
• Price above VWAP (institutional buying)
• Confidence boost: +15%
Bearish Confluence: [/b>
• ORB breakout downward (bearish signal)
• Price below VWAP (institutional selling)
• Confidence boost: +15%
[b>Divergence Warning:
• ORB breakout upward BUT price below VWAP
• Conflict: Breakout says "buy," VWAP says "sell"
• Confidence penalty: -10%
• Interpretation: Retail buying but institutions not participating (lower quality breakout)
📊 MOMENTUM CONTEXT SYSTEM
[b>Innovation: Candle Coloring by Position
Rather than fixed support/resistance lines, ORB Fusion colors candles based on their [b>relationship to ORB :
[b>Three Zones: [/b>
1. Inside ORB (Blue Boxes): [/b>
[b>Calculation:
• Darker blue: Near extremes of ORB (potential breakout imminent)
• Lighter blue: Near ORB mid (consolidation)
[b>Trading: [/b> Coiled spring—await breakout.
[b>2. Above ORB (Green Boxes):
[b>Calculation: 3. Below ORB (Red Boxes):
Mirror of above ORB logic.
[b>Special Contexts: [/b>
[b>Breakout Bar (Darkest Green/Red): [/b>
The specific bar where breakout occurs gets maximum color intensity regardless of distance. This highlights the pivotal moment.
[b>Failed Breakout Bar (Orange/Warning): [/b>
When failed breakout is confirmed, that bar gets orange/warning color. Visual alert: "reversal opportunity here."
[b>Near Extension (Cyan/Magenta Tint): [/b>
When price is within 0.5 ATR of an extension level, candle gets tinted cyan (bull) or magenta (bear). Indicates "target approaching—prepare to take profit."
[b>Why Visual Context? [/b>
Traditional indicators show lines. ORB Fusion shows [b>context-aware momentum [/b>. Glance at chart:
• Lots of blue? Consolidation day (fade extremes).
• Progressive green? Trend day (follow).
• Green then orange? Failed breakout (reversal setup).
This visual language communicates market state instantly—no interpretation needed.
🎯 TRADE SETUP GENERATION & GRADING [/b>
[b>Algorithmic Setup Detection: [/b>
ORB Fusion continuously evaluates market state and generates current best trade setup with:
• Action (LONG / SHORT / FADE HIGH / FADE LOW / WAIT)
• Entry price
• Stop loss
• Three targets
• Risk:Reward ratio
• Confidence score (0-100)
• Grade (A+ to D)
[b>Setup Types: [/b>
[b>1. ORB LONG (Bullish Breakout): [/b>
[b>Trigger: [/b>
• Bullish ORB breakout confirmed
• Not failed
[b>Parameters:
• Entry: Current close
• Stop: ORB mid (protects against failure)
• T1: ORB High + 0.5x range (1.5x extension)
• T2: ORB High + 1.0x range (2.0x extension)
• T3: ORB High + 1.618x range (2.618x extension)
[b>Confidence Scoring:
[b>Trigger: [/b>
• Bearish breakout occurred
• Failed (returned inside ORB)
[b>Parameters: [/b>
• Entry: Close when failure confirmed
• Stop: Extreme low since breakout + 0.10 ATR
• T1: ORB Low + 0.5x range
• T2: ORB Low + 1.0x range (ORB mid)
• T3: ORB Low + 1.5x range
[b>Confidence Scoring:
[b>Trigger:
• Inside ORB
• Close > ORB mid (near high)
[b>Parameters: [/b>
• Entry: ORB High (limit order)
• Stop: ORB High + 0.2x range
• T1: ORB Mid
• T2: ORB Low
[b>Confidence Scoring: [/b>
Base: 40 points (lower base—range fading is lower probability than breakout/reversal)
[b>Use Case: [/b> Rotation days. Not recommended on normal/trend days.
[b>6. FADE LOW (Range Trade):
Mirror of FADE HIGH.
[b>7. WAIT:
[b>Trigger: [/b>
• ORB not complete yet OR
• No clear setup (price in no-man's-land)
[b>Action: [/b> Observe, don't trade.
[b>Confidence: [/b> 0 points
[b>Grading System:
```
Confidence → Grade
85-100 → A+
75-84 → A
65-74 → B+
55-64 → B
45-54 → C
0-44 → D
```
[b>Grade Interpretation: [/b>
• [b>A+ / A: High probability setup. Take these trades.
• [b>B+ / B [/b>: Decent setup. Trade if fits system rules.
• [b>C [/b>: Marginal setup. Only if very experienced.
• [b>D [/b>: Poor setup or no setup. Don't trade.
[b>Example Scenario: [/b>
ES futures:
• ORB: 5842-5850 (8 point range)
• Bullish breakout to 5851 confirmed
• Volume: 2.0x average (confirmed)
• VWAP: 5845 (price above VWAP ✓)
• Day type: Developing (too early, no bonus)
• Gap: None
[b>Setup: [/b>
• Action: LONG
• Entry: 5851
• Stop: 5846 (ORB mid, -5 point risk)
• T1: 5854 (+3 points, 1:0.6 R:R)
• T2: 5858 (+7 points, 1:1.4 R:R)
• T3: 5862.94 (+11.94 points, 1:2.4 R:R)
[b>Confidence: LONG with 55% confidence.
Interpretation: Solid setup, not perfect. Trade it if your system allows B-grade signals.
[b>📊 STATISTICS TRACKING & PERFORMANCE ANALYSIS [/b>
[b>Real-Time Performance Metrics: [/b>
ORB Fusion tracks comprehensive statistics over user-defined lookback (default 50 days):
[b>Breakout Performance: [/b>
• [b>Bull Breakouts: [/b> Total count, wins, losses, win rate
• [b>Bear Breakouts: [/b> Total count, wins, losses, win rate
[b>Win Definition: [/b> Breakout reaches ≥1.0x extension (doubles the opening range) before end of day.
[b>Example: [/b>
• ORB: 5842-5850 (8 points)
• Bull breakout at 5851
• Reaches 5858 (1.0x extension) by close
• Result: WIN
[b>Failed Breakout Performance: [/b>
• [b>Total Failed Breakouts [/b>: Count of breakouts that failed
• [b>Reversal Wins [/b>: Count where reversal trade reached target
• [b>Failed Reversal Win Rate [/b>: Wins / Total Failed
[b>Win Definition for Reversals: [/b>
• Failed bull → reversal short reaches ORB mid
• Failed bear → reversal long reaches ORB mid
[b>Extension Tracking: [/b>
• [b>Average Extension Reached [/b>: Mean of maximum extension achieved across all breakout days
• [b>Max Extension Overall [/b>: Largest extension ever achieved in lookback period
[b>Example: 🎨 THREE DISPLAY MODES
[b>Design Philosophy: [/b>
Not all traders need all features. Beginners want simplicity. Professionals want everything. ORB Fusion adapts.
[b>SIMPLE MODE: [/b>
[b>Shows: [/b>
• Primary ORB levels (High, Mid, Low)
• ORB box
• Breakout signals (triangles)
• Failed breakout signals (crosses)
• Basic dashboard (ORB status, breakout status, setup)
• VWAP
[b>Hides: [/b>
• Session ORBs (Asian, London, NY)
• IB levels and extensions
• ORB extensions beyond basic levels
• Gap analysis visuals
• Statistics dashboard
• Momentum candle coloring
• Narrative dashboard
[b>Use Case: [/b>
• Traders who want clean chart
• Focus on core ORB concept only
• Mobile trading (less screen space)
[b>STANDARD MODE:
[b>Shows Everything in Simple Plus: [/b>
• Session ORBs (Asian, London, NY)
• IB levels (high, low, mid)
• IB extensions
• ORB extensions (1.272x, 1.5x, 1.618x, 2.0x)
• Gap analysis and fill targets
• VWAP bands (1σ and 2σ)
• Momentum candle coloring
• Context section in dashboard
• Narrative dashboard
[b>Hides: [/b>
• Advanced extensions (2.618x, 3.0x)
• Detailed statistics dashboard
[b>Use Case: [/b>
• Most traders
• Balance between information and clarity
• Covers 90% of use cases
[b>ADVANCED MODE:
[b>Shows Everything:
• All session ORBs
• All IB levels and extensions
• All ORB extensions (including 2.618x and 3.0x)
• Full gap analysis
• VWAP with both 1σ and 2σ bands
• Momentum candle coloring
• Complete statistics dashboard
• Narrative dashboard
• All context metrics
[b>Use Case: [/b>
• Professional traders
• System developers
• Those who want maximum information density
[b>Switching Modes: [/b>
Single dropdown input: "Display Mode" → Simple / Standard / Advanced
Entire indicator adapts instantly. No need to toggle 20 individual settings.
📖 NARRATIVE DASHBOARD
[b>Innovation: Plain-English Market State [/b>
Most indicators show data. ORB Fusion explains what the data [b>means [/b>.
[b>Narrative Components: [/b>
[b>1. Phase: [/b>
• "📍 Building ORB..." (during ORB session)
• "📊 Trading Phase" (after ORB complete)
• "⏳ Pre-Market" (before ORB session)
[b>2. Status (Current Observation): [/b>
• "⚠️ Failed breakout - reversal likely"
• "🚀 Bullish momentum in play"
• "📉 Bearish momentum in play"
• "⚖️ Consolidating in range"
• "👀 Monitoring for setup"
[b>3. Next Level:
Tells you what to watch for:
• "🎯 1.5x @ 5854.00" (next extension target)
• "Watch ORB levels" (inside range, await breakout)
[b>4. Setup: [/b>
Current trade setup + grade:
• "LONG " (bullish breakout, A-grade)
• "🔥 SHORT REVERSAL " (failed bull breakout, A+-grade)
• "WAIT " (no setup)
[b>5. Reason: [/b>
Why this setup exists:
• "ORB Bullish Breakout"
• "Failed Bear Breakout - High Probability Reversal"
• "Range Fade - Near High"
[b>6. Tip (Market Insight):
Contextual advice:
• "🔥 TREND DAY - Trail stops" (day type is trending)
• "🔄 ROTATION - Fade extremes" (day type is rotating)
• "📊 Gap unfilled - magnet level" (gap creates target)
• "📈 Normal conditions" (no special context)
[b>Example Narrative:
```
📖 ORB Narrative
━━━━━━━━━━━━━━━━
Phase | 📊 Trading Phase
Status | 🚀 Bullish momentum in play
Next | 🎯 1.5x @ 5854.00
📈 Setup | LONG
Reason | ORB Bullish Breakout
💡 Tip | 🔥 TREND DAY - Trail stops
```
[b>Glance Interpretation: [/b>
"We're in trading phase. Bullish breakout happened (momentum in play). Next target is 1.5x extension at 5854. Current setup is LONG with A-grade. It's a trend day, so trail stops (don't take early profits)."
Complete market state communicated in 6 lines. No interpretation needed.
[b>Why This Matters:
Beginner traders struggle with "So what?" question. Indicators show lines and signals, but what does it mean [/b>? Narrative dashboard bridges this gap.
Professional traders benefit too—rapid context assessment during fast-moving markets. No time to analyze; glance at narrative, get action plan.
🔔 INTELLIGENT ALERT SYSTEM
[b>Four Alert Types: [/b>
[b>1. Breakout Alert: [/b>
[b>Trigger: [/b> ORB breakout confirmed (bull or bear)
[b>Message: [/b>
```
🚀 ORB BULLISH BREAKOUT
Price: 5851.00
Volume Confirmed
Grade: A
```
[b>Frequency: [/b> Once per bar (prevents spam)
[b>2. Failed Breakout Alert: [/b>
[b>Trigger: [/b> Breakout fails, reversal setup generated
[b>Message: [/b>
```
🔥 FAILED BULLISH BREAKOUT!
HIGH PROBABILITY SHORT REVERSAL
Entry: 5848.00
Stop: 5854.00
T1: 5846.00
T2: 5842.00
Historical Win Rate: 73%
```
[b>Why Comprehensive? [/b> Failed breakout alerts include complete trade plan. You can execute immediately from alert—no need to check chart.
[b>3. Extension Alert:
[b>Trigger: [/b> Price reaches extension level for first time
[b>Message: [/b>
```
🎯 Bull Extension 1.5x reached @ 5854.00
```
[b>Use: [/b> Profit-taking reminder. When extension hit, consider scaling out.
[b>4. IB Break Alert: [/b>
[b>Trigger: [/b> Price breaks above IB high or below IB low
[b>Message: [/b>
```
📊 IB HIGH BROKEN - Potential Trend Day
```
[b>Use: [/b> Day type classification. IB break suggests trend day developing—adjust strategy to trend-following mode.
[b>Alert Management: [/b>
Each alert type can be enabled/disabled independently. Prevents notification overload.
[b>Cooldown Logic: [/b>
Alerts won't fire if same alert type triggered within last bar. Prevents:
• "Breakout" alert every tick during choppy breakout
• Multiple "extension" alerts if price oscillates at level
Ensures: One clean alert per event.
⚙️ KEY PARAMETERS EXPLAINED
[b>Opening Range Settings: [/b>
• [b>ORB Timeframe [/b> (5/15/30/60 min): Duration of opening range window
- 30 min recommended for most traders
• [b>Use RTH Only [/b> (ON/OFF): Only trade during regular trading hours
- ON recommended (avoids thin overnight markets)
• [b>Use LTF Precision [/b> (ON/OFF): Sample 1-minute bars for accuracy
- ON recommended (critical for charts >1 minute)
• [b>Precision TF [/b> (1/5 min): Timeframe for LTF sampling
- 1 min recommended (most accurate)
[b>Session ORBs: [/b>
• [b>Show Asian/London/NY ORB [/b> (ON/OFF): Display multi-session ranges
- OFF in Simple mode
- ON in Standard/Advanced if trading 24hr markets
• [b>Session Windows [/b>: Time ranges for each session ORB
- Defaults align with major session opens
[b>Initial Balance: [/b>
• [b>Show IB [/b> (ON/OFF): Display Initial Balance levels
- ON recommended for day type classification
• [b>IB Session Window [/b> (0930-1030): First hour of trading
- Default is standard for US equities
• [b>Show IB Extensions [/b> (ON/OFF): Project IB extension targets
- ON recommended (identifies trend days)
• [b>IB Extensions 1-4 [/b> (0.5x, 1.0x, 1.5x, 2.0x): Extension multipliers
- Defaults are Market Profile standard
[b>ORB Extensions: [/b>
• [b>Show Extensions [/b> (ON/OFF): Project ORB extension targets
- ON recommended (defines profit targets)
• [b>Enable Individual Extensions [/b> (1.272x, 1.5x, 1.618x, 2.0x, 2.618x, 3.0x)
- Enable 1.272x, 1.5x, 1.618x, 2.0x minimum
- Disable 2.618x and 3.0x unless trading very volatile instruments
[b>Breakout Detection:
• [b>Confirmation Method [/b> (Close/Wick/Body):
- Close recommended (best balance)
- Wick for scalping
- Body for conservative
• [b>Require Volume Confirmation [/b> (ON/OFF):
- ON recommended (increases reliability)
• [b>Volume Multiplier [/b> (1.0-3.0):
- 1.5x recommended
- Lower for thin instruments
- Higher for heavy volume instruments
[b>Failed Breakout System: [/b>
• [b>Enable Failed Breakouts [/b> (ON/OFF):
- ON strongly recommended (highest edge)
• [b>Bars to Confirm Failure [/b> (2-10):
- 3 bars recommended
- 2 for aggressive (more signals, more false failures)
- 5+ for conservative (fewer signals, higher quality)
• [b>Failure Buffer [/b> (0.0-0.5 ATR):
- 0.1 ATR recommended
- Filters noise during consolidation near ORB level
• [b>Show Reversal Targets [/b> (ON/OFF):
- ON recommended (visualizes trade plan)
• [b>Reversal Target Mults [/b> (0.5x, 1.0x, 1.5x):
- Defaults are tested values
- Adjust based on average daily range
[b>Gap Analysis:
• [b>Show Gap Analysis [/b> (ON/OFF):
- ON if trading instruments that gap frequently
- OFF for 24hr markets (forex, crypto—no gaps)
• [b>Gap Fill Target [/b> (ON/OFF):
- ON to visualize previous close (gap fill level)
[b>VWAP:
• [b>Show VWAP [/b> (ON/OFF):
- ON recommended (key institutional level)
• [b>Show VWAP Bands [/b> (ON/OFF):
- ON in Standard/Advanced
- OFF in Simple
• [b>Band Multipliers (1.0σ, 2.0σ):
- Defaults are standard
- 1σ = normal range, 2σ = extreme
[b>Day Type: [/b>
• [b>Show Day Type Analysis [/b> (ON/OFF):
- ON recommended (critical for strategy adaptation)
• [b>Trend Day Threshold [/b> (1.0-2.5 IB mult):
- 1.5x recommended
- When price extends >1.5x IB, classifies as Trend Day
[b>Enhanced Visuals:
• [b>Show Momentum Candles [/b> (ON/OFF):
- ON for visual context
- OFF if chart gets too colorful
• [b>Show Gradient Zone Fills [/b> (ON/OFF):
- ON for professional look
- OFF for minimalist chart
• [b>Label Display Mode [/b> (All/Adaptive/Minimal):
- Adaptive recommended (shows nearby labels only)
- All for information density
- Minimal for clean chart
• [b>Label Proximity [/b> (1.0-5.0 ATR):
- 3.0 ATR recommended
- Labels beyond this distance are hidden (Adaptive mode)
[b>🎓 PROFESSIONAL USAGE PROTOCOL [/b>
[b>Phase 1: Learning the System (Week 1) [/b>
[b>Goal: [/b> Understand ORB concepts and dashboard interpretation
[b>Setup: [/b>
• Display Mode: STANDARD
• ORB Timeframe: 30 minutes
• Enable ALL features (IB, extensions, failed breakouts, VWAP, gap analysis)
• Enable statistics tracking
[b>Actions: [/b>
• Paper trade ONLY—no real money
• Observe ORB formation every day (9:30-10:00 AM ET for US markets)
• Note when ORB breakouts occur and if they extend
• Note when breakouts fail and reversals happen
• Watch day type classification evolve during session
• Track statistics—which setups are working?
[b>Key Learning: [/b>
• How often do breakouts reach 1.5x extension? (typically 50-60% of confirmed breakouts)
• How often do breakouts fail? (typically 30-40%)
• Which setup grade (A/B/C) actually performs best? (should see A-grade outperforming)
• What day type produces best results? (trend days favor breakouts, rotation days favor fades)
[b>Phase 2: Parameter Optimization (Week 2) [/b>
[b>Goal: [/b> Tune system to your instrument and timeframe
[b>ORB Timeframe Selection:
• Run 5 days with 15-minute ORB
• Run 5 days with 30-minute ORB
• Compare: Which captures better breakouts on your instrument?
• Typically: 30-minute optimal for most, 15-minute for very liquid (ES, SPY)
[b>Volume Confirmation Testing:
• Run 5 days WITH volume confirmation
• Run 5 days WITHOUT volume confirmation
• Compare: Does volume confirmation increase win rate?
• If win rate improves by >5%: Keep volume confirmation ON
• If no improvement: Turn OFF (avoid missing valid breakouts)
[b>Failed Breakout Bars:
[b>Goal: [/b> Develop personal trading rules based on system signals
[b>Setup Selection Rules: [/b>
Define which setups you'll trade:
• [b>Conservative: [/b> Only A+ and A grades
• [b>Balanced: [/b> A+, A, B+ grades
• [b>Aggressive: [/b> All grades B and above
Test each approach for 5-10 trades, compare results.
[b>Position Sizing by Grade: [/b>
Consider risk-weighting by setup quality:
• A+ grade: 100% position size
• A grade: 75% position size
• B+ grade: 50% position size
• B grade: 25% position size
Example: If max risk is $1000/trade:
• A+ setup: Risk $1000
• A setup: Risk $750
• B+ setup: Risk $500
This matches bet sizing to edge.
[b>Day Type Adaptation: [/b>
Create rules for different day types:
Trend Days:
• Take ALL breakout signals (A/B/C grades)
• Hold for 2.0x extension minimum
• Trail stops aggressively (1.0 ATR trail)
• DON'T fade—reversals unlikely
Rotation Days:
• ONLY take failed breakout reversals
• Ignore initial breakout signals (likely to fail)
• Take profits quickly (0.5x extension)
• Focus on fade setups (Fade High/Fade Low)
Normal Days:
• Take A/A+ breakout signals only
• Take ALL failed breakout reversals (high probability)
• Target 1.0-1.5x extensions
• Partial profit-taking at extensions
Time-of-Day Rules: [/b>
Breakouts at different times have different probabilities:
10:00-10:30 AM (Early Breakout):
• ORB just completed
• Fresh breakout
• Probability: Moderate (50-55% reach 1.0x)
• Strategy: Conservative position sizing
10:30-12:00 PM (Mid-Morning):
• Momentum established
• Volume still healthy
• Probability: High (60-65% reach 1.0x)
• Strategy: Standard position sizing
12:00-2:00 PM (Lunch Doldrums):
• Volume dries up
• Whipsaw risk increases
• Probability: Low (40-45% reach 1.0x)
• Strategy: Avoid new entries OR reduce size 50%
2:00-4:00 PM (Afternoon Session):
• Late-day positioning
• EOD squeezes possible
• Probability: Moderate-High (55-60%)
• Strategy: Watch for IB break—if trending all day, follow
[b>Phase 4: Live Micro-Sizing (Month 2) [/b>
[b>Goal: [/b> Validate paper trading results with minimal risk
[b>Setup: [/b>
• 10-20% of intended full position size
• Take ONLY A+ and A grade setups
• Follow stop loss and targets religiously
[b>Execution: [/b>
• Execute from alerts OR from dashboard setup box
• Entry: Close of signal bar OR next bar market order
• Stop: Use exact stop from setup (don't widen)
• Targets: Scale out at T1/T2/T3 as indicated
[b>Tracking: [/b>
• Log every trade: Entry, Exit, Grade, Outcome, Day Type
• Calculate: Win rate, Average R-multiple, Max consecutive losses
• Compare to paper trading results (should be within 15%)
[b>Red Flags: [/b>
• Win rate <45%: System not suitable for this instrument/timeframe
• Major divergence from paper trading: Execution issues (slippage, late entries, emotional exits)
• Max consecutive losses >8: Hitting rough patch OR market regime changed
[b>Phase 5: Scaling Up (Months 3-6)
[b>Goal: [/b> Gradually increase to full position size
[b>Progression: [/b>
• Month 3: 25-40% size (if micro-sizing profitable)
• Month 4: 40-60% size
• Month 5: 60-80% size
• Month 6: 80-100% size
[b>Milestones Required to Scale Up: [/b>
• Minimum 30 trades at current size
• Win rate ≥48%
• Profit factor ≥1.2
• Max drawdown <20%
• Emotional control (no revenge trading, no FOMO)
[b>Advanced Techniques:
[b>Multi-Timeframe ORB: Assumes first 30-60 minutes establish value. Violation: Market opens after major news, price discovery continues for hours (opening range meaningless).
2. [b>Volume Indicates Conviction: ES, NQ, RTY, SPY, QQQ—high liquidity, clean ORB formation, reliable extensions
• [b>Large-Cap Stocks: AAPL, MSFT, TSLA, NVDA (>$5B market cap, >5M daily volume)
• [b>Liquid Futures: CL (crude oil), GC (gold), 6E (EUR/USD), ZB (bonds)—24hr markets benefit from session ORBs
• [b>Major Forex Pairs: [/b> EUR/USD, GBP/USD, USD/JPY—London/NY session ORBs work well
[b>Performs Poorly On: [/b>
• [b>Illiquid Stocks: <$1M daily volume, wide spreads, gappy price action
• [b>Penny Stocks: [/b> Manipulated, pump-and-dump, no real price discovery
• [b>Low-Volume ETFs: Exotic sector ETFs, leveraged products with thin volume
• [b>Crypto on Sketchy Exchanges: Wash trading, spoofing invalidates volume analysis
• [b>Earnings Days: [/b> ORB completes before earnings release, then completely resets (useless)
• Binary Event Days: FDA approvals, court rulings—discontinuous price action
[b>Known Weaknesses: [/b>
• [b>Slow Starts: ORB doesn't complete until 10:00 AM (30-min ORB). Early morning traders have no signals for 30 minutes. Consider using 15-minute ORB if this is problematic.
• [b>Failure Detection Lag: [/b> Failed breakout requires 3+ bars to confirm. By the time system signals reversal, price may have already moved significantly back inside range. Manual traders watching in real-time can enter earlier.
• [b>Extension Overshoot: [/b> System projects extensions mathematically (1.5x, 2.0x, etc.). Actual moves may stop short (1.3x) or overshoot (2.2x). Extensions are targets, not magnets.
• [b>Day Type Misclassification: [/b> Early in session, day type is "Developing." By the time it's classified definitively (often 11:00 AM+), half the day is over. Strategy adjustments happen late.
• [b>Gap Assumptions: [/b> System assumes gaps want to fill. Strong trend days never fill gaps (gap becomes support/resistance forever). Blindly trading toward gaps can backfire on trend days.
• [b>Volume Data Quality: Forex doesn't have centralized volume (uses tick volume as proxy—less reliable). Crypto volume is often fake (wash trading). Volume confirmation less effective on these instruments.
• [b>Multi-Session Complexity: [/b> When using Asian/London/NY ORBs simultaneously, chart becomes cluttered. Requires discipline to focus on relevant session for current time.
[b>Risk Factors: [/b>
• [b>Opening Gaps: Large gaps (>2%) can create distorted ORBs. Opening range might be unusually wide or narrow, making extensions unreliable.
• [b>Low Volatility Environments:[/b> When VIX <12, opening ranges can be tiny (0.2-0.3%). Extensions are equally tiny. Profit targets don't justify commission/slippage.
• [b>High Volatility Environments:[/b> When VIX >30, opening ranges are huge (2-3%+). Extensions project unrealistic targets. Failed breakouts happen faster (volatility whipsaw).
• [b>Algorithm Dominance:[/b> In heavily algorithmic markets (ES during overnight session), ORB levels can be manipulated—algos pin price to ORB high/low intentionally. Breakouts become stop-runs rather than genuine directional moves.
[b>⚠️ RISK DISCLOSURE[/b>
Trading futures, stocks, options, forex, and cryptocurrencies involves substantial risk of loss and is not suitable for all investors. Opening Range Breakout strategies, while based on sound market structure principles, do not guarantee profits and can result in significant losses.
The ORB Fusion indicator implements professional trading concepts including Opening Range theory, Market Profile Initial Balance analysis, Fibonacci extensions, and failed breakout reversal logic. These methodologies have theoretical foundations but past performance—whether backtested or live—is not indicative of future results.
Opening Range theory assumes the first 30-60 minutes of trading establish a meaningful value area and that breakouts from this range signal directional conviction. This assumption may not hold during:
• Major news events (FOMC, NFP, earnings surprises)
• Market structure changes (circuit breakers, trading halts)
• Low liquidity periods (holidays, early closures)
• Algorithmic manipulation or spoofing
Failed breakout detection relies on patterns of trapped participant behavior. While historically these patterns have shown statistical edges, market conditions change. Institutional algorithms, changing market structure, or regime shifts can reduce or eliminate edges that existed historically.
Initial Balance classification (trend day vs rotation day vs normal day) is a heuristic framework, not a deterministic prediction. Day type can change mid-session. Early classification may prove incorrect as the day develops.
Extension projections (1.272x, 1.5x, 1.618x, 2.0x, etc.) are probabilistic targets derived from Fibonacci ratios and empirical market behavior. They are not "support and resistance levels" that price must reach or respect. Markets can stop short of extensions, overshoot them, or ignore them entirely.
Volume confirmation assumes high volume indicates institutional participation and conviction. In algorithmic markets, volume can be artificially high (HFT activity) or artificially low (dark pools, internalization). Volume is a proxy, not a guarantee of conviction.
LTF precision sampling improves ORB accuracy by using 1-minute bars but introduces additional data dependencies. If 1-minute data is unavailable, inaccurate, or delayed, ORB calculations will be incorrect.
The grading system (A+/A/B+/B/C/D) and confidence scores aggregate multiple factors (volume, VWAP, day type, IB expansion, gap context) into a single assessment. This is a mechanical calculation, not artificial intelligence. The system cannot adapt to unprecedented market conditions or events outside its programmed logic.
Real trading involves slippage, commissions, latency, partial fills, and rejected orders not present in indicator calculations. ORB Fusion generates signals at bar close; actual fills occur with delay. Opening range forms during highest volatility (first 30 minutes)—spreads widen, slippage increases. Execution quality significantly impacts realized results.
Statistics tracking (win rates, extension levels reached, day type distribution) is based on historical bars in your lookback window. If lookback is small (<50 bars) or market regime changed, statistics may not represent future probabilities.
Users must independently validate system performance on their specific instruments, timeframes, and broker execution environment. Paper trade extensively (100+ trades minimum) before risking capital. Start with micro position sizing (5-10% of intended size) for 50+ trades to validate execution quality matches expectations.
Never risk more than you can afford to lose completely. Use proper position sizing (0.5-2% risk per trade maximum). Implement stop losses on every single trade without exception. Understand that most retail traders lose money—sophisticated indicators do not change this fundamental reality. They systematize analysis but cannot eliminate risk.
The developer makes no warranties regarding profitability, suitability, accuracy, reliability, or fitness for any purpose. Users assume full responsibility for all trading decisions, parameter selections, risk management, and outcomes.
By using this indicator, you acknowledge that you have read, understood, and accepted these risk disclosures and limitations, and you accept full responsibility for all trading activity and potential losses.
[b>═══════════════════════════════════════════════════════════════════════════════[/b>
[b>CLOSING STATEMENT[/b>
[b>═══════════════════════════════════════════════════════════════════════════════[/b>
Opening Range Breakout is not a trick. It's a framework. The first 30-60 minutes reveal where participants believe value lies. Breakouts signal directional conviction. Failures signal trapped participants. Extensions define profit targets. Day types dictate strategy. Failed breakouts create the highest-probability reversals.
ORB Fusion doesn't predict the future—it identifies [b>structure[/b>, detects [b>breakouts[/b>, recognizes [b>failures[/b>, and generates [b>probabilistic trade plans[/b> with defined risk and reward.
The edge is not in the opening range itself. The edge is in recognizing when the market respects structure (follow breakouts) versus when it violates structure (fade breakouts). The edge is in detecting failures faster than discretionary traders. The edge is in systematic classification that prevents catastrophic errors—like fading a trend day or holding through rotation.
Most indicators draw lines. ORB Fusion implements a complete institutional trading methodology: Opening Range theory, Market Profile classification, failed breakout intelligence, Fibonacci projections, volume confirmation, gap psychology, and real-time performance tracking.
Whether you're a beginner learning market structure or a professional seeking systematic ORB implementation, this system provides the framework.
"The market's first word is its opening range. Everything after is commentary." — ORB Fusion
Selected Days Indicator V3-TrDoes the stock drop every Wednesday? Do March months always move similarly? Does the 1st week of the month behave differently?
Do you ever say "it always makes this move in these months"? Don't you want to see more clearly whether it actually makes this move or not? Don't you want to see and test periodically repeating price patterns?
Hisse her Çarşamba düşüyor mu? Mart ayları hep benzer mi hareket ediyor? Ayın 1. haftası farklı mı davranıyor?
Bazen "bu aylarda hep bu hareketi yapıyor" dediğiniz oluyor mu? Gerçekten de bu hareketi yapıp yapmadığını daha net görmek istemez misiniz? Periyodik tekrarlayan fiyat kalıplarını görmek ve test etmek istemiyor musunuz?
1. Problem
Some stocks or crypto assets exhibit systematic behaviors on certain days, weeks, or months. But it's hard to see - everything is mixed together on the chart. This indicator isolates the days/weeks/months you want and shows only them. Hides everything else.
2. How It Works
Three-layer filter: Day (Monday, Tuesday...), Week (1st, 2nd, 3rd week of the month), Month (January, February...). Select what you want, let the rest disappear. Example: Show only Thursdays of March-June-September. Or compare every 1st week of the month. View as candlestick, line, or column chart.
3. What's It Good For?
Test "end-of-month effect". Find "day-of-the-week anomaly". Analyze crypto volatility by days. See seasonality in commodities. Discover patterns specific to your own strategy. Past data doesn't guarantee the future but provides statistical advantage.
[AlscapeLabs] HTF Candle Stack (Multi-Timeframe)
Overview
The HTF Candle Stack (Multi-TF) indicator is a powerful visualization tool designed to overlay high-timeframe (HTF) price action directly onto your current chart, independent of the chart's price scale. This gives traders a clear, aligned, and non-overlapping view of simultaneous price movements across customizable timeframes.
By stacking the candles horizontally next to the chart's price action, the indicator allows for quick identification of multi-timeframe correlation, trend confluence, and key levels without switching chart timeframes.
Key Features
6 Independent Stacks: Configure up to 6 separate timeframes (e.g., 5m, 15m, 1H, 4H, Daily, Weekly) to view the complete market fractals from micro to macro.
Price-Aligned Visualization : All HTF candle stacks are perfectly aligned with the main chart's vertical price axis
Replay Mode Safe : Includes dedicated logic to prevent "duplicate candles" during Bar Replay, ensuring accurate backtesting and historical analysis.
Toggleable Stacks : Each stack can be individually enabled or disabled via input settings
Dynamic Spacing : The distance between active stacks is automatically calculated and adjusted based on the visibility of the preceding stack.
Settings Guide
Stack Configuration (1 - 6)
Each of the six stacks has identical controls:
Show/Hide : Enable or disable this specific stack.
Timeframe : The specific HTF to display (e.g., "60" for 1 Hour, "D" for Daily).
[*} Count : How many candles to show in this stack (Current Active Candle + Past Closed Candles). Tip: Use higher counts (10-12) for lower TFs (Stack 1-2) and lower counts (2-4) for higher TFs (Stack 5-6)
Candle Color
Controls global coloring
Bullish / Bearish : Customize the body colors.
Wick : Separate control for wick color and transparency
Layout
Distance from Chart : How far (in bars) to the right the first stack begins
Space between Stacks : The gap (in bars) between each active stack.
Candle Width : The thickness of the HTF candles.
Labels
Displays a time-frame next to the active (live) candle in each stack
Show TF Labels : Enable or disable labels through all stacks
Text Color : Label text color
Background : Label background color
Style : Label position (Left, Down)
Size : Label text size (Tiny, Small, Normal, Large, Huge)
Developed by AlscapeLabs
