Multitimeframe Order Block Finder (Zeiierman)█ Overview
The Multitimeframe Order Block Finder (Zeiierman) is a powerful tool designed to identify potential institutional zones of interest — Order Blocks — across any timeframe, regardless of what chart you're viewing.
Order Blocks are critical supply and demand zones formed by the last opposing candle before an impulsive move. These areas often act as magnets for price and serve as smart-money footprints — ideal for anticipating reversals, retests, or breakouts.
This indicator not only detects such zones in real-time, but also visualizes their mitigation, bull/bear volume pressure, and a smoothed directional trendline based on Order Block behavior.
█ How It Works
The script fetches OHLCV data from your chosen timeframe using request.security() and processes it using strict pattern logic and volume-derived strength conditions. It detects Order Blocks only when the structure aligns with dominant pressure and visually extends valid zones forward for as long as they remain unmitigated.
⚪ Bull/Bear Volume Power Visualization
Each OB includes proportional bars representing estimated buy/sell effort:
Buy Power: % of volume attributed to buyers
Sell Power: % of volume attributed to sellers
This adds a visual, intuitive layer of intent — showing who controlled the price before the OB formed.
⚪ Order Block Trendline (Butterworth Filtered)
A smoothed trendline is derived from the average OB value over time using a two-pole Butterworth low-pass filter. This helps you understand the broader directional pressure:
Trendline up → favor bullish OBs
Trendline down → favor bearish OBs
█ How to Use
⚪ Trade From Order Blocks Like Institutions
Use this tool to find institutional footprints and reaction zones:
Enter at unmitigated OBs
⚪ Volume Power
Volume Pressure Bars inside each OB help you:
Confirm strong buyer/seller dominance
Detect possible traps or exhaustion
Understand how each zone formed
⚪ Find Trend & Pullbacks
The trendline not only helps traders detect the current trend direction, but the built-in trend coloring also highlights potential pullback areas within these trends.
█ Settings
Timeframe – Selects which timeframe to scan for Order Blocks.
Lookback Period – Defines how many bars back are used to detect bullish or bearish momentum shifts.
Sensitivity – When enabled, the indicator uses smoothed price (RMA) with rising/falling logic instead of raw candle closes. This allows more flexible detection of trend shifts and results in more Order Blocks being identified.
Minimum Percent Move – Filters out weak moves. Higher = only strong price shifts.
Mitigated on Mid – OB is removed when price touches its midpoint.
Show OB Table – Displays a panel listing all active (unmitigated) Order Blocks.
Extend Boxes – Controls how far OB boxes stretch into the future.
Show OB Trend – Toggles the trendline derived from Order Block strength.
Passband Ripple (dB) – Controls trendline reactivity. Higher = more sensitive.
Cutoff Frequency – Controls smoothness of trendline (0–0.5). Lower = smoother.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Indicatori e strategie
Equal High/Low (EQH/EQL) [AlgoAlpha]OVERVIEW
This script detects and visualizes Equal High (EQH) and Equal Low (EQL) zones—key liquidity areas where price has previously stalled or reversed. These levels often attract institutional interest due to the liquidity buildup around them. The indicator is built to highlight such zones using dynamic thresholding, overbought/oversold RSI filtering, and adaptive mitigation logic to manage zone relevance over time.
CONCEPTS
Equal Highs/Lows are price points where the market has repeatedly failed to break past a certain high or low, hinting at areas where stop orders and pending interest may be concentrated. These areas are often prime targets for liquidity grabs or reversals. By combining this with RSI filtering, the script avoids false signals during neutral conditions and instead focuses on zones where market pressure is more directional.
FEATURES
Detection Logic: The script identifies EQH and EQL zones by comparing the similarity between recent highs or lows with a dynamic volatility threshold. The `tolerance` input allows users to control how strict this comparison is.
RSI Filtering: If enabled, it only creates zones when RSI is significantly overbought or oversold (based on the `state_thresh` input). This helps ensure zones form only in meaningful market conditions.
Zone Display: Bullish (EQL) zones are shown in grey, while bearish (EQH) zones are in blue. Two horizontal lines mark the zone using wick and body extremes, and a filled area visualizes the zone between them.
Zone Management: Zones automatically extend with price until they’re invalidated. You can choose whether a zone is removed based on wick or body sweeps and whether it requires one or two candle confirmations. Zones also expire after a customizable number of bars.
Alerts: Four alert conditions are built in—when a new EQH/EQL is formed and when one is mitigated—making it easy to integrate into alert-based workflows.
USAGE
Equal highs/lows can be used as liquidity markers, either as entry points or as take-profit targets.
This tool is ideal for liquidity-based strategies and helps traders map out possible reversal or sweep zones that often precede aggressive moves.
OA - Volume FlowVolume Flow
Volume Flow is a powerful technical analysis tool that identifies and visualizes weekly and monthly Point of Control (POC) levels based on volume distribution. This indicator helps traders spot potential support and resistance areas by tracking where the highest trading volume occurs.
Key Features:
Weekly and Monthly POC Tracking: Visualizes Points of Control for both weekly and monthly timeframes, with customizable display options for each.
Dynamic POC Extensions: POC zones extend horizontally until price interacts with them, providing clear visual signals of potential support and resistance levels.
Price Interaction Markers: Diamond-shaped markers appear at the exact point where price touches a POC zone, highlighting these critical moments.
Color-Coded Visualization: Distinct colors for weekly (default: red) and monthly (default: blue) POC zones make identification easy and intuitive.
Alert Conditions: Built-in alerts for when price touches either weekly or monthly POC levels, allowing for automated trade notifications.
How It Works:
Volume Flow divides each week or month's price range into bins and calculates the volume distribution across these levels. The price level with the highest volume becomes the POC. This level is then extended as a horizontal zone that remains active until price either touches it (creating a diamond marker) or until a predetermined number of newer POCs have formed.
Trading Applications:
Identify potential support and resistance levels based on historical volume
Anticipate price reactions at key volume levels
Confirm breakouts and reversals with volume context
Plan entries and exits around high-volume price zones
The Volume Flow indicator provides valuable insight into market structure by highlighting where the most significant volume has occurred, helping you make more informed trading decisions based on actual market participation rather than price action alone.
Trend Classifier [ChartPrime]Trend Classifier
This is a multi-level trend classification tool that detects bullish, bearish, and ranging conditions using an adaptive smoothing method. It highlights trend strength through color-coded candles and layered bands, making it easy to interpret market momentum visually.
⯁ KEY FEATURES
Classifies trend strength using 3 bullish and 3 bearish levels relative to an adaptive trend line.
Neutral (range) zones are marked when price stays between key bands, often signaling low volatility or consolidation.
Automatically filters band visibility based on current trend direction:
In uptrends, only levels below the price are displayed.
In downtrends, only levels above the price are shown.
Color-coded candles:
Aqua candles for bullish conditions.
Red candles for bearish conditions.
Orange candles during neutral or ranging conditions.
Includes a trend direction change marker (diamond), plotted when a shift in trend is detected.
Plots a central smoothed trend line to anchor the trend bands dynamically.
Displays a trend strength dashboard in the top-right corner with real-time bull and bear scores (0 to 3).
Labels with arrows (▲/▼) show current trend direction and strength on the chart.
⯁ HOW TO USE
Use bull and bear levels (1–3) to assess the momentum of the current trend.
When bull = 0 and bear = 0 , market is considered ranging or consolidating – consider fading or waiting for breakout confirmation.
Trend bands can be used as dynamic support/resistance during trending phases.
Monitor the trend change diamonds to spot potential early reversals.
Combine with volume or oscillator tools for confirmation of strength shifts.
⯁ CONCLUSION
Trend Classifier helps traders stay aligned with the dominant trend while visually breaking down market momentum into levels. Its clean color-coded design and strength dashboard make it ideal for both trend following and range trading strategies.
[blackcat] L3 Smart Money FlowCOMPREHENSIVE ANALYSIS OF THE L3 SMART MONEY FLOW INDICATOR
🌐 OVERVIEW:
The L3 Smart Money Flow indicator represents a sophisticated multi-dimensional analytics tool combining traditional momentum measurements with advanced institutional investor tracking capabilities. It's particularly effective at identifying large-scale capital movement dynamics that often precede significant price shifts.
Core Objectives:
• Detect subtle but meaningful price action anomalies indicating major player involvement
• Provide clear entry/exit markers based on multiple validated criteria
• Offer risk-managed positioning strategies suitable for various account sizes
• Maintain operational efficiency even during high volatility regimes
THEORETICAL BACKDROP AND METHODOLOGY
🎓 Conceptual Foundation Principles:
Utilizes Time-Varying Moving Averages (TVMA) responding adaptively to changing market states
Implements Extended Smoothing Algorithm (XSA) providing enhanced filtration characteristics
Employs asymmetric weight distribution favoring recent price observations over historical ones
→ Analyzes price-weighted closing prices incorporating volume influence indirectly
← Applies Asymmetric Local Maximum (ALMA) filters generating institution-specific trends
⟸ Combines multiple temporal perspectives producing robust directional assessments
✓ Calculates normalized momentum ratios comparing current state against extended range extremes
✗ Filters out insignificant fluctuations via double-stage verification process
⤾ Generates actionable alerts upon exceeding predefined significance boundaries
CONFIGURABLE PARAMETERS IN DEPTH
⚙️ Input Customization Options Detailed Explanation:
Temporal Resolution Control:
→ TVMA Length Setting:
Minimum value constraint ensuring mathematical validity
Higher numbers increase smoothing effect reducing reaction velocity
Lower intervals enhance responsiveness potentially increasing noise exposure
Validation Threshold Definition:
↓ Bull-Bear Boundary Level:
Establishes fundamental acceptance/rejection zones
Typically set near extreme values reflecting rare occurrence probability
Can be adjusted per instrument liquidity profiles if necessary
ADVANCED ALGORITHMIC PROCEDURES BREAKDOWN
💻 Internal Operation Architecture:
Base Calculations Infrastructure:
☑ Raw Data Preparation and Normalization
☐ High/Low/Closing Aggregation Processes
☒ Range Estimation Algorithms
Intermediate Transform Engine:
📈 Momentum Ratio Computation Workflow
↔ First Pass XSA Application Details
➖ Second Stage Refinement Mechanics
Final Output Synthesis Framework:
➢ Composite Reading Compilation Logic
➣ Validation Status Determination Process
➤ Alert Trigger Decision Making Structure
INTERACTIVE VISUAL INTERFACE COMPONENTS
🎨 User Experience Interface Elements:
🔵 Plotting Series Hierarchy:
→ Primary FundFlow Signal: White trace marking core oscillator progression
↑ Secondary Confirmation Overlay: Orange/Yellow highlighting validation status
🟥 Risk/Reward Boundaries: Aqua line delineating strategic areas requiring attention
🏷️ Interactive Marker System:
✔ "BUY": Green upward-pointing labels denoting confirmed long entries
❌ "SELL": Red downward-facing badges signaling short setups
PRACTICAL APPLICATION STRATEGY GUIDE
📋 Operational Deployment Instructions:
Strategic Planning Initiatives:
• Define precise profit targets considering realistic reward/risk scenarios
→ Set maximum acceptable loss thresholds protecting available resources adequately
↓ Develop contingency plans addressing unexpected adverse developments promptly
Live Trading Engagement Protocols:
→ Maintaining vigilant monitoring of label placement activities continuously
↓ Tracking order fill success rates across implemented grids regularly
↑ Evaluating system effectiveness compared alternative methodologies periodically
Performance Optimization Techniques:
✔ Implement incremental improvements iteratively throughout lifecycle
❌ Eliminate ineffective component variations systematically
⟹ Ensure proportional growth capability matching user needs appropriately
EFFICIENCY ENHANCEMENT APPROACHES
🚀 Ongoing Development Strategy:
Resource Management Focus Areas:
→ Minimizing redundant computation cycles through intelligent caching mechanisms
↓ Leveraging parallel processing capabilities where feasible efficiently
↑ Optimizing storage access patterns improving response times substantially
Scalability Consideration Factors:
✔ Adapting to varying account sizes/market capitalizations seamlessly
❌ Preventing bottlenecks limiting concurrent operation capacity
⟹ Ensuring balanced growth capability matching evolving requirements accurately
Maintenance Routine Establishment:
✓ Regular codebase updates incorporation keeping functionality current
↓ Periodic performance audits conducting verifying continued effectiveness
↑ Documentation refinement updating explaining any material modifications made
SYSTEMATIC RISK CONTROL MECHANISMS
🛡️ Comprehensive Protection Systems:
Position Sizing Governance:
∅ Never exceed predetermined exposure limitations strictly observed
± Scale entries proportionally according to available resources carefully
× Include slippage allowances within planning stages realistically
Emergency Response Procedures:
↩ Well-defined exit strategies including trailing stops activation logic
🌀 Contingency plan formulation covering worst-case scenario contingencies
⇄ Recovery procedure documentation outlining restoration steps methodically
[blackcat] L2 Trend Guard OscillatorOVERVIEW
📊 The L2 Trend Guard Oscillator is a comprehensive technical analysis framework designed specifically to identify market trend reversals using adaptive filtering algorithms that combine price action dynamics with statistical measures of volatility and momentum.
Key Purpose:
Generate reliable early warning signals before major trend changes occur
Provide clear directional bias indicators aligned with institutional investor behavior patterns
Offer risk-managed entry/exit opportunities suitable for various timeframes
TECHNICAL FOUNDATION EXPLAINED
🎓 Core Mechanism Breakdown:
→ Advanced smoothing technique emphasizing recent data points more heavily than older ones
↓ Reduces lag while maintaining signal integrity compared to traditional MA approaches
• Short-term Momentum Assessment:
🔶 Relative strength between closing prices vs lower bounds
• Long-term Directional Bias Analysis:
📈 Extended timeframe comparison generating structural context
• Defense Level Generation:
➜ Protective boundary calculation incorporating EMAs for stability enhancement
PARAMETER CONFIGURATION GUIDE
🔧 Adjustable Settings Explained In Detail:
Timeframe Selection:**
↔ Controls lookback period sensitivity affecting responsiveness
↕ Adjusts reaction speed vs accuracy trade-off dynamically
Weight Factor Specification:**
⚡ Influences emphasis on newer versus historical observations
🎯 Defines key decision-making thresholds clearly
ALGORITHM EXECUTION FLOW
💻 Processing Sequence Overview:
:
→ Gather raw pricing inputs across required periods
↓ Normalize values preparing them for subsequent processing stages
:
✔ Calculate relative strength positions against established ranges
❌ Filter outliers maintaining signal integrity consistently
⟶ Apply dual-pass filtering reducing false signals effectively
➡ Generate actionable trading opportunities systematically
VISUALIZATION ARCHITECTURE
🎨 Display Elements Designated Purpose:
🔵 Primary Indicator Traces:
→ Aqua Trace: Buy/Sell Signal Progression
↑ Red Line: Opposing Force Boundary
🟥 Gray Dashed: Zero Reference Point
🏷️ Label System For Critical Events:
✅ BUY: Bullish Opportunity Markers
❌ SELL: Bearish Setup Validations
STRATEGIC IMPLEMENTATION FRAMEWORK
📋 Practical Deployment Steps:
Initial Integration Protocol:
• Select appropriate timeframe matching strategy objectives
• Configure input parameters aligning with target asset behavior traits
• Conduct thorough backtesting under simulated environments initially
Active Monitoring Procedures:
→ Regular observation of labeled event placements versus actual movements
↓ Track confirmation patterns leading up to signaled opportunities carefully
↑ Evaluate overall framework reliability across different regime types regularly
Execution Guidelines Formulation:
✔ Enter positions only after achieving minimum number of confirming inputs
❌ Avoid isolated occurrences lacking adequate supporting evidence always
➞ Look for convergent factors strengthening conviction before acting decisively
PERFORMANCE OPTIMIZATION TECHNIQUES
🚀 Continuous Improvement Strategies:
Parameter Calibration Approach:
✓ Start testing default suggested configurations thoroughly
↕ Gradually adjust individual components observing outcome changes methodically
✨ Document findings building personalized version profile incrementally
Context Adaptability Methods:
🔄 Add supplementary indicators enhancing overall reliability when needed
🔧 Remove unnecessary complexity layers avoiding confusion/distracted decisions
💫 Incorporate custom rules adapting specific security behaviors effectively
Efficiency Improvement Tactics:
⚙️ Streamline redundant computational routines wherever possible efficiently
♻️ Leverage shared data streams minimizing resource utilization significantly
⏳ Optimize refresh frequencies balancing update speed vs overhead properly
₿ober XM v1.3# ₿ober XM v1.3 Trading Bot Documentation
## Overview
The ₿ober XM v1.3 is an advanced dual-channel trading bot. It integrates multiple technical indicators, customizable risk management, and advanced order execution via webhook for automated trading. The bot's distinctive feature is its separate channel systems for long and short positions, allowing for asymmetric trade strategies that adapt to different market conditions.
### Key Features
- **Dual-Channel System**: Independent indicator settings for long and short positions
- **Multiple Entry Strategies**: Breakout, Pullback, and Mean Reversion options
- **Machine Learning Integration**: Predictive MLMA (Machine Learning Moving Average) for enhanced trend detection
- **Comprehensive Filtering**: Combines momentum, volatility, volume, and trend filters
- **Advanced Risk Management**: Dynamic position sizing, multiple stop-loss types, and trailing stops
- **Webhook Integration**: Direct connectivity to exchanges or third-party platforms
- **Configurable OBV MA Types**: Choose from multiple moving average types for OBV calculations
### General Settings
| Setting | Description | Default Value |
|---------|-------------|---------------|
| **Long Positions** | Enable or disable long trades | Enabled |
| **Short Positions** | Enable or disable short trades | Enabled |
| **Risk/Reward Area** | Visual display of stop-loss and take-profit zones | Enabled |
| **Long Entry Source** | Price data used for long entry signals | hl2 (High+Low/2) |
| **Short Entry Source** | Price data used for short entry signals | hl2 (High+Low/2) |
The bot allows you to trade long positions, short positions, or both simultaneously. Each direction has its own set of parameters, allowing for fine-tuned strategies that recognize the asymmetric nature of market movements.
### Webhook Configuration
| Setting | Description | Default Value |
|---------|-------------|---------------|
| **Long Entry Comment** | Webhook message for long entries | "ENTER-LONG" |
| **Short Entry Comment** | Webhook message for short entries | "ENTER-SHORT" |
| **Exit Comment** | Webhook message for position exits | "EXIT-ALL" |
| **Leverage** | Position size multiplier | 1.0 |
| **Reduce Only** | Restrict orders to reducing positions | Enabled |
| **Exchange Conditional Orders** | Place SL/TP directly on exchange | Disabled |
The webhook system allows for seamless integration with exchanges or third-party platforms:
- **Benefits**:
- Automated trade execution without manual intervention
- Immediate response to market conditions
- Consistent execution of your strategy
- **Implementation Notes**:
- Requires proper webhook configuration on your exchange or platform
- Test thoroughly with small position sizes before full deployment
- Consider latency between signal generation and execution
### Backtesting Period
Define a specific historical period to evaluate the bot's performance:
| Setting | Description | Default Value |
|---------|-------------|---------------|
| **Start Date** | Beginning of backtest period | January 1, 2025 |
| **End Date** | End of backtest period | December 31, 2026 |
- **Best Practice**: Test across different market conditions (bull markets, bear markets, sideways markets)
- **Limitation**: Past performance doesn't guarantee future results
## Entry and Exit Strategies
### Dual-Channel System
A key innovation of the Bober XM is its dual-channel approach:
- **Independent Parameters**: Each trade direction has its own channel settings
- **Asymmetric Trading**: Recognizes that markets often behave differently in uptrends versus downtrends
- **Optimized Performance**: Fine-tune settings for both bullish and bearish conditions
This approach allows the bot to adapt to the natural asymmetry of markets, where uptrends often develop gradually while downtrends can be sharp and sudden.
### Channel Types
#### 1. Keltner Channels
Traditional volatility-based channels using EMA and ATR:
| Setting | Long Default | Short Default |
|---------|--------------|---------------|
| **EMA Length** | 37 | 20 |
| **ATR Length** | 13 | 17 |
| **Multiplier** | 1.4 | 1.9 |
| **Source** | low | high |
- **Strengths**:
- Reliable in trending markets
- Less prone to whipsaws than Bollinger Bands
- Clear visual representation of volatility
- **Weaknesses**:
- Can lag during rapid market changes
- Less effective in choppy, non-trending markets
#### 2. Machine Learning Moving Average (MLMA)
Advanced predictive model using kernel regression (RBF kernel):
| Setting | Long Default | Short Default |
|---------|--------------|---------------|
| **Window Size** | 16 | 16 |
| **Forecast Length** | 3 | 3 |
| **Noise Parameter** | 0.43 | 0.44 |
| **Band Multiplier** | 0.6 | 0.5 |
| **Source** | low | high |
- **Strengths**:
- Predictive rather than reactive
- Adapts quickly to changing market conditions
- Better at identifying trend reversals early
- **Weaknesses**:
- More computationally intensive
- Requires careful parameter tuning
- Can be sensitive to input data quality
### Entry Strategies
| Strategy | Description | Ideal Market Conditions |
|----------|-------------|-------------------------|
| **Breakout** | Enters when price breaks through channel bands, indicating strong momentum | High volatility, emerging trends |
| **Pullback** | Enters when price retraces to the middle band after testing extremes | Established trends with regular pullbacks |
| **Mean Reversion** | Enters at channel extremes, betting on a return to the mean | Range-bound or oscillating markets |
#### Breakout Strategy (Default)
- **Implementation**: Enters long when price crosses above the upper band, short when price crosses below the lower band
- **Strengths**: Captures strong momentum moves, performs well in trending markets
- **Weaknesses**: Can lead to late entries, higher risk of false breakouts
- **Optimization Tips**:
- Increase channel multiplier for fewer but more reliable signals
- Combine with volume confirmation for better accuracy
#### Pullback Strategy
- **Implementation**: Enters long when price pulls back to middle band during uptrend, short during downtrend pullbacks
- **Strengths**: Better entry prices, lower risk, higher probability setups
- **Weaknesses**: Misses some strong moves, requires clear trend identification
- **Optimization Tips**:
- Use with trend filters to confirm overall direction
- Adjust middle band calculation for market volatility
#### Mean Reversion Strategy
- **Implementation**: Enters long at lower band, short at upper band, expecting price to revert to the mean
- **Strengths**: Excellent entry prices, works well in ranging markets
- **Weaknesses**: Dangerous in strong trends, can lead to fighting the trend
- **Optimization Tips**:
- Implement strong trend filters to avoid counter-trend trades
- Use smaller position sizes due to higher risk nature
### Confirmation Indicators
#### Pivot Point SuperTrend
Combines pivot points with ATR-based SuperTrend for trend confirmation:
| Setting | Default Value |
|---------|---------------|
| **Pivot Period** | 25 |
| **ATR Factor** | 2.2 |
| **ATR Period** | 41 |
- **Function**: Identifies significant market turning points and confirms trend direction
- **Implementation**: Requires price to respect the SuperTrend line for trade confirmation
#### Weighted Moving Average (WMA)
Provides additional confirmation layer for entries:
| Setting | Default Value |
|---------|---------------|
| **Period** | 15 |
| **Source** | ohlc4 (average of Open, High, Low, Close) |
- **Function**: Confirms trend direction and filters out low-quality signals
- **Implementation**: Price must be above WMA for longs, below for shorts
### Exit Strategies
#### On-Balance Volume (OBV) Based Exits
Uses volume flow to identify potential reversals:
| Setting | Default Value |
|---------|---------------|
| **Source** | ohlc4 |
| **MA Type** | HMA (Options: SMA, EMA, WMA, RMA, VWMA, HMA) |
| **Period** | 22 |
- **Function**: Identifies divergences between price and volume to exit before reversals
- **Implementation**: Exits when OBV crosses its moving average in the opposite direction
- **Customizable MA Type**: Different MA types provide varying sensitivity to OBV changes:
- **SMA**: Traditional simple average, equal weight to all periods
- **EMA**: More weight to recent data, responds faster to price changes
- **WMA**: Weighted by recency, smoother than EMA
- **RMA**: Similar to EMA but smoother, reduces noise
- **VWMA**: Factors in volume, helpful for OBV confirmation
- **HMA**: Reduces lag while maintaining smoothness (default)
#### ADX Exit Confirmation
Uses Average Directional Index to confirm trend exhaustion:
| Setting | Default Value |
|---------|---------------|
| **ADX Threshold** | 35 |
| **ADX Smoothing** | 60 |
| **DI Length** | 60 |
- **Function**: Confirms trend weakness before exiting positions
- **Implementation**: Requires ADX to drop below threshold or DI lines to cross
## Risk Management System
### Position Sizing
Automatically calculates position size based on account equity and risk parameters:
| Setting | Default Value |
|---------|---------------|
| **Risk % of Equity** | 50% |
- **Implementation**:
- Position size = (Account equity × Risk %) ÷ (Entry price × Stop loss distance)
- Adjusts automatically based on volatility and stop placement
- **Best Practices**:
- Start with lower risk percentages (1-2%) until strategy is proven
- Consider reducing risk during high volatility periods
### Stop-Loss Methods
Multiple stop-loss calculation methods with separate configurations for long and short positions:
| Method | Description | Configuration |
|--------|-------------|---------------|
| **ATR-Based** | Dynamic stops based on volatility | ATR Period: 14, Multiplier: 2.0 |
| **Percentage** | Fixed percentage from entry | Long: 1.5%, Short: 1.5% |
| **PIP-Based** | Fixed currency unit distance | 10.0 pips |
- **Implementation Notes**:
- ATR-based stops adapt to changing market volatility
- Percentage stops maintain consistent risk exposure
- PIP-based stops provide precise control in stable markets
### Trailing Stops
Locks in profits by adjusting stop-loss levels as price moves favorably:
| Setting | Default Value |
|---------|---------------|
| **Stop-Loss %** | 1.5% |
| **Activation Threshold** | 2.1% |
| **Trailing Distance** | 1.4% |
- **Implementation**:
- Initial stop remains fixed until profit reaches activation threshold
- Once activated, stop follows price at specified distance
- Locks in profit while allowing room for normal price fluctuations
### Risk-Reward Parameters
Defines the relationship between risk and potential reward:
| Setting | Default Value |
|---------|---------------|
| **Risk-Reward Ratio** | 1.4 |
| **Take Profit %** | 2.4% |
| **Stop-Loss %** | 1.5% |
- **Implementation**:
- Take profit distance = Stop loss distance × Risk-reward ratio
- Higher ratios require fewer winning trades for profitability
- Lower ratios increase win rate but reduce average profit
## Advanced Filtering System
### Momentum & Trend Filters
#### ADX Based Momentum Filter
| Setting | Default Value |
|---------|---------------|
| **Use Filter** | Enabled |
| **Apply D+/D- Check** | Enabled |
| **ADX Smoothing** | 34 |
| **DI Length** | 28 |
| **ADX Threshold** | 19 |
- **Function**: Ensures trades are taken only in strong trending conditions
- **Implementation**: Requires ADX above threshold for trade entry
#### RSI Filter
Uses Relative Strength Index to avoid overbought/oversold conditions:
| Setting | Default Value | Status |
|---------|---------------|--------|
| **RSI Period** | 14 | Disabled |
| **Overbought Level** | 70 | |
| **Oversold Level** | 30 | |
- **Function**: Prevents entries in potentially exhausted market conditions
- **Implementation**: Blocks long entries when RSI > 70, short entries when RSI < 30
### Volatility Filter
Controls trading during excessive market volatility:
| Setting | Default Value |
|---------|---------------|
| **Measure** | ATR |
| **Period** | 8 |
| **Threshold** | 1.3 |
| **Source** | ohlc4 |
- **Function**: Prevents trading during unpredictable market conditions
- **Implementation**: Blocks trades when current volatility exceeds threshold × average volatility
### Volume Filter
Ensures adequate market liquidity for trades:
| Setting | Default Value |
|---------|---------------|
| **Threshold** | 1.1× average |
| **Average Period** | 4 |
| **Smoothing Period** | 18 |
- **Function**: Prevents trading during low liquidity conditions
- **Implementation**: Requires current volume to exceed threshold × average volume
### Filter Combinations
The bot allows for simultaneous application of multiple filters:
- **Recommended Combinations**:
- Trending markets: ADX + Volume filters
- Ranging markets: Volatility + RSI filters
- All markets: Volume filter as minimum requirement
- **Performance Impact**:
- Each additional filter reduces the number of trades
- Quality of remaining trades typically improves
- Optimal combination depends on market conditions and timeframe
## Visual Indicators and Chart Analysis
The bot provides comprehensive visual feedback on the chart:
- **Channel Bands**: Keltner or MLMA bands showing potential support/resistance
- **Pivot SuperTrend**: Colored line showing trend direction and potential reversal points
- **Entry/Exit Markers**: Annotations showing actual trade entries and exits
- **Risk/Reward Zones**: Visual representation of stop-loss and take-profit levels
These visual elements allow for:
- Real-time strategy assessment
- Post-trade analysis and optimization
- Educational understanding of the strategy logic
## Implementation Guide
### TradingView Setup
1. Load the script in TradingView Pine Editor
2. Apply to your preferred chart and timeframe
3. Adjust parameters based on your trading preferences
4. Enable alerts for webhook integration
### Webhook Integration
1. Configure webhook URL in TradingView alerts
2. Set up receiving endpoint on your trading platform
3. Define message format matching the bot's output
4. Test with small position sizes before full deployment
### Optimization Process
1. Backtest across different market conditions
2. Identify parameter sensitivity through multiple tests
3. Focus on risk management parameters first
4. Fine-tune entry/exit conditions based on performance metrics
5. Validate with out-of-sample testing
## Performance Considerations
### Strengths
- Adaptability to different market conditions through dual channels
- Multiple layers of confirmation reducing false signals
- Comprehensive risk management protecting capital
- Machine learning integration for predictive edge
### Limitations
- Complex parameter set requiring careful optimization
- Potential over-optimization risk with so many variables
- Computational intensity of MLMA calculations
- Dependency on proper webhook configuration for execution
### Best Practices
- Start with conservative risk settings (1-2% of equity)
- Test thoroughly in demo environment before live trading
- Monitor performance regularly and adjust parameters
- Consider market regime changes when evaluating results
## Conclusion
The ₿ober XM v1.3 represents a sophisticated trading system combining traditional technical analysis with machine learning elements. Its dual-channel approach and comprehensive filtering system make it adaptable to various market conditions, while its risk management features help protect capital during adverse movements.
The addition of selectable OBV MA types in v1.3 provides further customization, allowing traders to fine-tune the exit strategy sensitivity according to market conditions and personal preferences. This enhancement offers more control over exit signals, potentially improving trade outcome profitability.
The bot is designed for traders who understand that no system is perfect, but that edge can be found through careful optimization and disciplined execution. With proper setup and realistic expectations, it provides a framework for systematic cryptocurrency trading across various market conditions.
2025 - Licensed under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International
Candilang RalpinoyWala lang..
Hirap kasi identify ng mga candlesticks
eto ay para sa mas madaling pag identify testing lang credits kay algomax original script writter
but simply effective
ICT Killzones & Pivots [TFO]adjusted the script to fit my needs. I mainly use it to identify the FVG and OB, as well as D/W/M HH/LL
Fire Sling Shot Stochastic// ============================================================================
// Stochastic Indicator (5,3,3) Explanation
// ============================================================================
//
// The Fire Sling Shot strategy uses a Stochastic oscillator (5,3,3) as a
// confirming indicator to enhance the reliability of EMA crossover signals.
//
// WHAT IS STOCHASTIC?
// The Stochastic oscillator is a momentum indicator that compares a security's
// closing price to its price range over a specific period. The indicator
// oscillates between 0 and 100, with readings above 80 considered overbought
// and readings below 20 considered oversold.
//
// SETTINGS USED:
// - %K Period: 5 (faster sensitivity to price movements)
// - %D Period: 3 (smoothing of %K)
// - Smoothing: 3 (additional smoothing applied to the %K line)
// - Overbought Level: 80
// - Oversold Level: 20
//
// HOW IT'S USED IN THIS STRATEGY:
//
// 1. Bull Signal Enhancement:
// When the 15 EMA crosses above the 50 EMA (primary signal), we check
// if the Stochastic is below 20 or has just crossed above 20. This suggests
// momentum is starting to turn upward from an oversold condition, improving
// the quality of the long entry.
//
// 2. Bear Signal Enhancement:
// When the 15 EMA crosses below the 50 EMA (primary signal), we check
// if the Stochastic is above 80 or has just crossed below 80. This suggests
// momentum is starting to turn downward from an overbought condition,
// improving the quality of the short entry.
//
// 3. Early Warning:
// Stochastic movements below 20 or above 80 can provide early warning of
// potential EMA crossovers, allowing traders to prepare for possible entry
// signals.
//
// The Stochastic filter is optional and can be enabled/disabled through the
// strategy inputs. When disabled, the strategy relies solely on EMA crossovers
// for entry signals.
//
// NOTE: While Stochastic can improve signal quality, no indicator is perfect.
// False signals can occur, especially in ranging or choppy markets. Always
// combine with proper risk management and consider the overall market context.
//
// ============================================================================
Ehlers Regime Dynamic CandlesCore Calculation Mechanism
The indicator uses advanced Ehlers signal processing techniques to identify market regimes and create dynamically colored candles that reflect market conditions.
Super Smoother Filter: Price data (open, high, low, close) is processed through an Ehlers Super Smoother Filter to reduce market noise while preserving important price movements. This creates a clearer signal for regime detection.
Autocorrelation Analysis: The core of regime detection uses autocorrelation functions at different lag periods:
Primary autocorrelation measures correlation between the current price and its previous value
Trending autocorrelation measures longer-term persistence in the data series
These values combined determine if the market is in a trending or choppy regime
(Image showing Ehlers custom candles vs default candlesticks)
Regime Strength Calculation:
-Raw signal from autocorrelation with user-defined threshold adjustment
-Adaptive scaling based on sensitivity parameter
-Optional volume validation that confirms signal strength using volume data
-Normalization to 0-1 range and smoothing for visual consistency
-Percentile ranking to provide contextually meaningful strength values
Fisher Transform: Applied to the smoothed price to identify statistical extremes, which helps adjust transparency levels during significant price movements.
Key Features & Components
Regime Detection: Identifies trending vs. choppy market conditions using Ehlers' autocorrelation techniques.
Dynamic Candle Coloring: Candles transition smoothly between three color states:
Bullish trending (typically green/teal)
Bearish trending (typically red/purple)
Choppy/neutral (typically blue/silver)
Volume Validation: Optional incorporation of volume data to confirm trend strength (stronger volume during trending periods increases confidence).
Adaptive Transparency: Candles become more opaque during statistically significant price movements based on Fisher Transform values.
Gradient Smoothing: Controls the visual transition between regime states for a more aesthetically pleasing appearance.
Customizable Colors and Style: Full control over all visual aspects including candle body/wick colors and transparency.
Configuration Options
Users can adjust the following parameters in the indicator settings:
Main Settings:
Cycle Length: Controls the lookback period for cycle detection. Lower values increase responsiveness but may introduce noise.
Gradient Smoothness: Determines how quickly colors transition when regime changes.
Trend Detection Threshold: Sets the autocorrelation strength required to classify a trend.
Trend Sensitivity: Scales regime strength calculation to produce a better distribution of values.
Use Volume: Toggles whether volume data is used to validate trend strength.
Color Settings:
Trending Regime Colors: Separate color options for bullish and bearish candle bodies and wicks.
Choppy Regime Colors: Color options for candle bodies and wicks during sideways/neutral markets.
Style Settings:
Candle Border Options: Toggle borders and adjust their color and transparency.
Adaptive Transparency: Enable/disable dynamic transparency based on statistical significance.
Base Transparency: Set the baseline transparency level for all candles.
Interpretation Notes
Color Transitions: As the market shifts between regimes, candle colors gradually transition, providing visual cues about market structure changes.
Regime Strength: The intensity of colors indicates the strength of the detected regime:
Strong trending regimes show vibrant trending colors
Weak or mixed regimes display colors closer to the choppy/neutral color
Transitions between regimes show gradient colors
Transparency Changes: More opaque candles indicate statistically significant price movements, while more transparent candles suggest routine or less significant price action.
Volume Interaction: When volume validation is enabled, trending colors become more pronounced during high volume trends and subdued during low volume periods.
Disclaimer: These are custom candles that are significantly different from normal candlesticks.
Unlike traditional candlesticks that display raw price data, these candles:
• Use Ehlers signal processing to filter and smooth price data
• Dynamically change color based on detected market regimes
• Show statistical significance through transparency
• May appear delayed compared to standard candles due to the filtering process
Traditional trading strategies dependent on candlestick patterns will not work with these.
Risk Disclaimer
Trading involves significant risk. This indicator is provided for analytical purposes only and does not constitute financial advice. Past performance is not indicative of future results. Use sound risk management practices and never trade with capital you cannot afford to lose. The Ehlers Regime Dynamic Candles indicator should be used as part of a comprehensive trading approach, not as a standalone trading system.
The Echo System🔊 The Echo System – Trend + Momentum Trading Strategy
Overview:
The Echo System is a trend-following and momentum-based trading tool designed to identify high-probability buy and sell signals through a combination of market trend analysis, price movement strength, and candlestick validation.
Key Features:
📈 Trend Detection:
Uses a 30 EMA vs. 200 EMA crossover to confirm bullish or bearish trends.
Visual trend strength meter powered by percentile ranking of EMA distance.
🔄 Momentum Check:
Detects significant price moves over the past 6 bars, enhanced by ATR-based scaling to filter weak signals.
🕯️ Candle Confirmation:
Validates recent price action using the previous and current candle body direction.
✅ Smart Conditions Table:
A live dashboard showing all trade condition checks (Trend, Recent Price Move, Candlestick confirmations) in real-time with visual feedback.
📊 Backtesting & Stats:
Auto-calculates average win, average loss, risk-reward ratio (RRR), and win rate across historical signals.
Clean performance dashboard with color-coded metrics for easy reading.
🔔 Alerts:
Set alerts for trade signals or significant price movements to stay updated without monitoring the chart 24/7.
Visuals:
Trend markers and price movement flags plotted directly on the chart.
Dual tables:
📈 Conditions table (top-right): breaks down trade criteria status.
📊 Performance table (bottom-right): shows real-time stats on win/loss and RRR.🔊 The Echo System – Trend + Momentum Trading Strategy
Overview:
The Echo System is a trend-following and momentum-based trading tool designed to identify high-probability buy and sell signals through a combination of market trend analysis, price movement strength, and candlestick validation.
Key Features:
📈 Trend Detection:
Uses a 30 EMA vs. 200 EMA crossover to confirm bullish or bearish trends.
Visual trend strength meter powered by percentile ranking of EMA distance.
🔄 Momentum Check:
Detects significant price moves over the past 6 bars, enhanced by ATR-based scaling to filter weak signals.
🕯️ Candle Confirmation:
Validates recent price action using the previous and current candle body direction.
✅ Smart Conditions Table:
A live dashboard showing all trade condition checks (Trend, Recent Price Move, Candlestick confirmations) in real-time with visual feedback.
📊 Backtesting & Stats:
Auto-calculates average win, average loss, risk-reward ratio (RRR), and win rate across historical signals.
Clean performance dashboard with color-coded metrics for easy reading.
🔔 Alerts:
Set alerts for trade signals or significant price movements to stay updated without monitoring the chart 24/7.
Visuals:
Trend markers and price movement flags plotted directly on the chart.
Dual tables:
📈 Conditions table (top-right): breaks down trade criteria status.
📊 Performance table (bottom-right): shows real-time stats on win/loss and RRR.
Dynamic Liquidity Depth [BigBeluga]
Dynamic Liquidity Depth
A liquidity mapping engine that reveals hidden zones of market vulnerability. This tool simulates where potential large concentrations of stop-losses may exist — above recent highs (sell-side) and below recent lows (buy-side) — by analyzing real price behavior and directional volume. The result is a dynamic two-sided volume profile that highlights where price is most likely to gravitate during liquidation events, reversals, or engineered stop hunts.
🔵 KEY FEATURES
Two-Sided Liquidity Profiles:
Plots two separate profiles on the chart — one above price for potential sell-side liquidity , and one below price for potential buy-side liquidity . Each profile reflects the volume distribution across binned zones derived from historical highs and lows.
Real Stop Zone Simulation:
Each profile is offset from the current high or low using an ATR-based buffer. This simulates where traders might cluster their stop-losses above swing highs (short stops) or below swing lows (long stops).
Directional Volume Analysis:
Buy-side volume is accumulated only from bullish candles (close > open), while sell-side volume is accumulated only from bearish candles (close < open). This directional filtering enhances accuracy by capturing genuine pressure zones.
Dynamic Volume Heatmap:
Each liquidity bin is rendered as a horizontal box with a color gradient based on volume intensity:
- Low activity bins are shaded lightly.
- High-volume zones appear more vividly in red (sell) or lime (buy).
- The maximum volume bin in each profile is emphasized with a brighter fill and a volume label.
Extended POC Zones:
The Point of Control (PoC) — the bin with the most volume — is extended backwards across the entire lookback period to mark critical resistance (sell-side) or support (buy-side) levels.
Total Volume Summary Labels:
At the center of each profile, a summary label displays Total Buy Liquidity and Total Sell Liquidity volume.
This metric helps assess directional imbalance — when buy liquidity is dominant, the market may favor upward continuation, and vice versa.
Customizable Profile Granularity:
You can fine-tune both Resolution (Bins) and Offset Distance to adjust how far profiles are displaced from price and how many levels are calculated within the ATR range.
🔵 HOW IT WORKS
The indicator calculates an ATR-based buffer above highs and below lows to define the top and bottom of the liquidity zones.
Using a user-defined lookback period, it scans historical candles and divides the buffered zones into bins.
Each bin checks if bullish (or bearish) candles pass through it based on price wicks and body.
Volume from valid candles is summed into the corresponding bin.
When volume exists in a bin, a horizontal box is drawn with a width scaled by relative volume strength.
The bin with the highest volume is highlighted and optionally extended backward as a zone of importance.
Total buy/sell liquidity is displayed with a summary label at the side of the profile.
🔵 USAGE/b]
Identify Stop Hunt Zones: High-volume clusters near swing highs/lows are likely liquidation zones targeted during fakeouts.
Fade or Follow Reactions: Price hitting a high-volume bin may reverse (fade opportunity) or break with strength (confirmation breakout).
Layer with Other Tools: Combine with market structure, order blocks, or trend filters to validate entries near liquidity.
Adjust Offset for Sensitivity: Use higher offset to simulate wider stop placement; use lower for tighter scalping zones.
🔵 CONCLUSION
Dynamic Liquidity Depth transforms raw price and volume into a spatial map of liquidity. By revealing areas where stop orders are likely hidden, it gives traders insight into price manipulation zones, potential reversal levels, and breakout traps. Whether you're hunting for traps or trading with the flow, this tool equips you to navigate liquidity with precision.
Really Key Levels█ OVERVIEW
This indicator shows the most useful and universally used key trading levels (and only those) in a visually appealing way. Its originality lies in the fact that it was developed due to being unable to find an indicator that wasn't cluttered with other features or far less relevant levels, or one that would indicate the bar causing the level (i.e., not just using a horizontal line over the whole chart), or one that was well-programmed and didn’t frequently refresh for many seconds for no obvious reason, taking far too long to do so for such a seemingly simple indicator.
█ FEATURES
Shows the most frequently used key levels in a visually appealing way
Indicates the bar that causes the level, with the line starting at that bar
Works correctly and consistently on both RTH and ETH charts
Lines can be optionally extended both left and right, if the user prefers
Works with US/European stocks and US futures (at least)
Configurable futures regular session (default time is for CME futures, e.g., ES/NQ, etc.)
Users can configure line colour, style, and thickness
Adjustable label locations to prevent overlap with other indicator labels
Nice defaults that look good, and a well-contrasting label text colour
Well-documented, high-quality, open-source code for those who are interested
█ CONCEPTS
The indicator shows the following levels by a line starting at the bar that causes them:
Current Day RTH High/Low (visible and updated only during RTH; visible with no further updates in the post-market)
Current Day RTH Open (only after the RTH open)
Pre-Market High/Low (as it develops in the pre-market and fixed after RTH open)
Previous Day RTH Close
Previous Day RTH High/Low
Previous Day Pre-Market High-Low
Two Days Ago RTH Close
Other levels may be added in future versions, if requested and if they are Really Key Levels.
Regarding futures: despite being a 23-hour market (for CME futures, 5 p.m. the previous day to 4 p.m. the current day), most trading activity takes place together with the RTH on stock exchanges in New York, 08:30 to 3 p.m. Central (Chicago) time. Therefore, a user-configurable regular market is defined at those times, with times before this (from 5 p.m. the previous day) being considered pre-market, and times after this (until 4 p.m.) being considered post-market.
Care was taken so that the code uses no hard-coded time zones, exchanges, or session times. For this reason, it can in principle work globally. However, it very much depends on the information provided by the exchange, which is reflected in built-in Pine Script variables (see Limitations below).
█ LIMITATIONS
Pre-market levels are not shown when viewing an RTH chart.
The indicator was developed and tested on US/European stocks and US futures. It may or may not work for stocks and futures in other countries (depending on their pre- and post-market definitions and what information the exchange provides to TradingView via the relevant built-in Pine Script variable). It does not work on other security types, especially those with a 24-hour market that don't have a uniquely defined daily close, implicit H/L time window, or a pre-market.
Machine Learning: ARIMA + SARIMADescription
The ARIMA (Autoregressive Integrated Moving Average) and SARIMA (Seasonal ARIMA) are advanced statistical models that use machine learning to forecast future price movements. It uses autoregression to find the relationship between observed data and its lagged observations. The data is differenced to make it more predictable. The MA component creates a dependency between observations and residual errors. The parameters are automatically adjusted to market conditions.
Differences
ARIMA - This excels at identifying trends in the form of directions
SARIMA - Incorporates seasonality. It's better at capturing patterns previously seen
How To Use
1. Model: Determine if you want to use ARIMA (better for direction) or SARIMA (better for overall prediction). You can click on the 'Show Historic Prediction' to see the direction of the previous candles. Green = forecast ending up, red = forecast ending down
2. Metrics: The RMSE% and MAPE are 10 day moving averages of the first 10 predictions made at candle close. They're error metrics that compare the observed data with the predicted data. It is better to use them when they're below 8%. Higher timeframes will be higher, as these models are partly mean-reverting and higher TFs tend to trend more. Better to compare RMSE% and MAPE with similar timeframes. They naturally lag as data is being collected
3. Parameter selection: The simpler, the better. Both are used for ARIMA(1,1,1) and SARIMA(1,1,1)(1,1,1)5. Increasing may cause overfitting
4. Training period: Keep at 50. Because of limitations in pine, higher values do not make for more powerful forecasts. They will only criminally lag. So best to keep between 20 and 80
Expected Move Manual EditVisualize key weekly support and resistance levels based on manually entered Previous Week
Close (PWC) and Expected Move (EM) values.
This script plots:
Your entered PWC (Black, Solid Line).
Expected Move Top (+1 SD based on your EM input) (Green, Solid Line).
Expected Move Bottom (-1 SD based on your EM input) (Red, Solid Line).
Intermediate quadrant levels (+/- 0.25, 0.50, 0.75 SD) (Green/Red, Dotted Lines).
Features:
Manual PWC & Expected Move inputs.
Clear visual styling for levels.
Toggleable labels on the price axis.
Toggleable labels directly on the chart (right-aligned).
How to Use:
Add to chart.
Go to Settings -> Inputs.
Enter your calculated/sourced PWC value.
Enter your calculated/sourced Expected Move value (treated as 1 Standard Deviation).
Adjust label visibility if desired.
Note: This indicator requires manual input for PWC and EM; it does not calculate them automatically. The Ticker Symbol input is for reference only.
Forex Fire Sling Shot// Forex Fire Sling Shot Strategy
// ============================================================================
//
// This strategy implements a simple yet effective trading system based on EMA
// crossovers with stochastic confirmation. The system identifies high-probability
// entry points for both long and short positions in forex markets.
//
// Features:
// - Uses 15 EMA crossing 50 EMA as primary signal generator
// - Stochastic (5,3,3) provides early confirmation signals
// - Take profit targets set at customizable pip levels (default 35 pips)
// - Visual labels for "Sling Shot" (long) and "Bear Sling" (short) signals
// - Real-time status indicator showing current market bias
// - Alert conditions for easy notification setup
//
// How it works:
// 1. LONG ENTRY ("Sling Shot"): When 15 EMA crosses above 50 EMA
// Stochastic below 20 and moving upward can provide early confirmation
// Target: 25-55 pips (default 35)
//
// 2. SHORT ENTRY ("Bear Sling"): When 15 EMA crosses below 50 EMA
// Stochastic above 80 and moving downward can provide early confirmation
// Target: 25-55 pips (default 35)
//
// DISCLAIMER:
// This script is for educational purposes only. Past performance is not
// indicative of future results. Always test strategies thoroughly before
// trading real capital.
//
// Author: Forex_Fire
// Version: 1.0 (2025-05-06)
You Need To Add My Fire Sling Shot Stochastic to this
Entropy Chart Analysis [PhenLabs]📊 Entropy Chart analysis -
Version: PineScript™ v6
📌 Description
The Entropy Chart indicator analysis applies Approximate Entropy (ApEn) to identify zones of potential support and resistance on your price chart. It is designed to locate changes in the market’s predictability, with a focus on zones near significant psychological price levels (e.g., multiples of 50). By quantifying entropy, the indicator aims to identify zones where price action might stabilize (potential support) or become randomized (potential resistance).
This tool automates the visualization of these key areas for traders, which may have the effect of revealing reversal levels or consolidation zones that would be hard to discern through traditional means. It also filters the signals by proximity to key levels in an attempt to reduce noise and highlight higher-probability setups. These dynamic zones adapt to changing market conditions by stretching, merging, and expiring based on user-inputted rules.
🚀 Points of Innovation
Combines Approximate Entropy (ApEn) calculation with price action near significant levels.
Filters zone signals based on proximity (in ticks) to predefined significant price levels (multiples of 50).
Dynamically merges overlapping or nearby zones to consolidate signals and reduce chart clutter.
Uses ApEn crossovers relative to its moving average as the core trigger mechanism.
Provides distinct visual coloring for bullish, bearish, and merged (mixed-signal) zones.
Offers comprehensive customization for entropy calculation, zone sensitivity, level filtering, and visual appearance.
🔧 Core Components
Approximate Entropy (ApEn) Calculation : Measures the regularity or randomness of price fluctuations over a specified window. Low ApEn suggests predictability, while high ApEn suggests randomness.
Zone Trigger Logic : Creates potential support zones when ApEn crosses below its average (indicating increasing predictability) and potential resistance zones when it crosses above (indicating increasing randomness).
Significant Level Filter : Validates zone triggers only if they occur within a user-defined tick distance from significant price levels (multiples of 50).
Dynamic Zone Management : Automatically creates, extends, merges nearby zones based on tick distance, and removes the oldest zones to maintain a maximum limit.
Zone Visualization : Draws and updates colored boxes on the chart to represent active support, resistance, or mixed zones.
🔥 Key Features
Entropy-Based S/R Detection : Uses ApEn to identify potential support (low entropy) and resistance (high entropy) areas.
Significant Level Filtering : Enhances signal quality by focusing on entropy changes near key psychological price points.
Automatic Zone Drawing & Merging : Visualizes zones dynamically, merging close signals for clearer interpretation.
Highly Customizable : Allows traders to adjust parameters for ApEn calculation, zone detection thresholds, level filter sensitivity, merging distance, and visual styles.
Integrated Alerts : Provides built-in alert conditions for the formation of new bullish or bearish zones near significant levels.
Clear Visual Output : Uses distinct, customizable colors for buy (support), sell (resistance), and mixed (merged) zones.
🎨 Visualization
Buy Zones : Represented by greenish boxes (default: #26a69a), indicating potential support areas formed during low entropy periods near significant levels.
Sell Zones : Represented by reddish boxes (default: #ef5350), indicating potential resistance areas formed during high entropy periods near significant levels.
Mixed Zones : Represented by bluish/purple boxes (default: #8894ff), formed when a buy zone and a sell zone merge, indicating areas of potential consolidation or conflict.
Dynamic Extension : Active zones are automatically extended to the right with each new bar.
📖 Usage Guidelines
Calculation Parameters
Window Length
Default: 15
Range: 10-100
Description: Lookback period for ApEn calculation. Shorter lengths are more responsive; longer lengths are smoother.
Embedding Dimension (m)
Default: 2
Range: 1-6
Description: Length of patterns compared in ApEn calculation. Higher values detect more complex patterns but require more data.
Tolerance (r)
Default: 0.5
Range: 0.1-1.0 (step 0.1)
Description: Sensitivity factor for pattern matching (as a multiple of standard deviation). Lower values require closer matches (more sensitive).
Zone Settings
Zone Lookback
Default: 5
Range: 5-50
Description: Lookback period for the moving average of ApEn used in threshold calculations.
Zone Threshold
Default: 0.5
Range: 0.5-3.0
Description: Multiplier for the ApEn average to set crossover trigger levels. Higher values require larger ApEn deviations to create zones.
Maximum Zones
Default: 5
Range: 1-10
Description: Maximum number of active zones displayed. The oldest zones are removed first when the limit is reached.
Zone Merge Distance (Ticks)
Default: 5
Range: 1-50
Description: Maximum distance in ticks for two separate zones to be merged into one.
Level Filter Settings
Tick Size
Default: 0.25
Description: The minimum price increment for the asset. Must be set correctly for the specific instrument to ensure accurate level filtering.
Max Ticks Distance from Levels
Default: 40
Description: Maximum allowed distance (in ticks) from a significant level (multiple of 50) for a zone trigger to be valid.
Visual Settings
Buy Zone Color : Default: color.new(#26a69a, 83). Sets the fill color for support zones.
Sell Zone Color : Default: color.new(#ef5350, 83). Sets the fill color for resistance zones.
Mixed Zone Color : Default: color.new(#8894ff, 83). Sets the fill color for merged zones.
Buy Border Color : Default: #26a69a. Sets the border color for support zones.
Sell Border Color : Default: #ef5350. Sets the border color for resistance zones.
Mixed Border Color : Default: color.new(#a288ff, 50). Sets the border color for mixed zones.
Border Width : Default: 1, Range: 1-3. Sets the thickness of zone borders.
✅ Best Use Cases
Identifying potential support/resistance near significant psychological price levels (e.g., $50, $100 increments).
Detecting potential market turning points or consolidation zones based on shifts in price predictability.
Filtering entries or exits by confirming signals occurring near significant levels identified by the indicator.
Adding context to other technical analysis approaches by highlighting entropy-derived zones.
⚠️ Limitations
Parameter Dependency : Indicator performance is sensitive to parameter settings ( Window Length , Tolerance , Zone Threshold , Max Ticks Distance ), which may need optimization for different assets and timeframes.
Volatility Sensitivity : High market volatility or erratic price action can affect ApEn calculations and potentially lead to less reliable zone signals.
Fixed Level Filter : The significant level filter is based on multiples of 50. While common, this may not capture all relevant levels for every asset or market condition. Accurate Tick Size input is essential.
Not Standalone : Should be used in conjunction with other analysis methods (price action, volume, other indicators) for confirmation, not as a sole basis for trading decisions.
💡 What Makes This Unique
Entropy + Level Context : Uniquely combines ApEn analysis with a specific filter for proximity to significant price levels (multiples of 50), adding locational context to entropy signals.
Intelligent Zone Merging : Automatically consolidates nearby buy/sell zones based on tick distance, simplifying visual analysis and highlighting stronger confluence areas.
Targeted Signal Generation : Focuses alerts and zone creation on specific market conditions (entropy shifts near key levels).
🔬 How It Works
Calculate Entropy : The script computes the Approximate Entropy (ApEn) of the closing prices over the defined Window Length to quantify price predictability.
Check Triggers : It monitors ApEn relative to its moving average. A crossunder below a calculated threshold (avg_apen / zone_threshold) indicates potential support; a crossover above (avg_apen * zone_threshold) indicates potential resistance.
Filter by Level : A potential zone trigger is confirmed only if the low (for support) or high (for resistance) of the trigger bar is within the Max Ticks Distance of a significant price level (multiple of 50).
Manage & Draw Zones : If a trigger is confirmed, a new zone box is created. The script checks for overlaps with existing zones within the Zone Merge Distance and merges them if necessary. Zones are extended forward, and the oldest are removed to respect the Maximum Zones limit. Active zones are drawn and updated on the chart.
💡 Note:
Crucially, set the Tick Size parameter correctly for your specific trading instrument in the “Level Filter Settings”. Incorrect Tick Size will make the significant level filter inaccurate.
Experiment with parameters, especially Window Length , Tolerance (r) , Zone Threshold , and Max Ticks Distance , to tailor the indicator’s sensitivity to your preferred asset and timeframe.
Always use this indicator as part of a comprehensive trading plan, incorporating risk management and seeking confirmation from other analysis techniques.
Adaptive RSI | Lyro RSThe Adaptive RSI | 𝓛𝔂𝓻𝓸 𝓡𝓢 indicator enhances the traditional Relative Strength Index (RSI) by integrating adaptive smoothing techniques and dynamic bands. This design aims to provide traders with a nuanced view of market momentum, highlighting potential trend shifts and overbought or oversold conditions.
Key Features
Adaptive RSI Calculation: Combines fast and slow Exponential Moving Averages (EMAs) of the RSI to capture momentum shifts effectively.
Dynamic Bands: Utilizes a smoothed standard deviation approach to create upper and lower bands around the adaptive RSI, aiding in identifying extreme market conditions.
Signal Line: An additional EMA of the adaptive RSI serves as a signal line, assisting in confirming trend directions.
Customizable Color Schemes: Offers multiple predefined color palettes, including "Classic," "Mystic," "Accented," and "Royal," with an option for users to define custom colors for bullish and bearish signals.
How It Works
Adaptive RSI Computation: Calculates the difference between fast and slow EMAs of the RSI, producing a responsive oscillator that adapts to market momentum.
Band Formation: Applies a smoothing factor to the standard deviation of the adaptive RSI, generating dynamic upper and lower bands that adjust to market volatility.
Signal Line Generation: Computes an EMA of the adaptive RSI to act as a signal line, providing additional confirmation for potential entries or exits.
Visualization: Plots the adaptive RSI as color-coded columns, with colors indicating bullish or bearish momentum. The dynamic bands are filled to visually represent overbought and oversold zones.
How to Use
Identify Momentum Shifts: Observe crossovers between the adaptive RSI and the signal line to detect potential changes in trend direction.
Spot Overbought/Oversold Conditions: Monitor when the adaptive RSI approaches or breaches the dynamic bands, signaling possible market extremes.
Customize Visuals: Select from predefined color palettes or define custom colors to align the indicator's appearance with personal preferences or chart themes.
Customization Options
RSI and EMA Lengths: Adjust the lengths of the RSI, fast EMA, slow EMA, and signal EMA to fine-tune the indicator's sensitivity.
Band Settings: Modify the band length, multiplier, and smoothing factor to control the responsiveness and width of the dynamic bands.
Color Schemes: Choose from predefined color modes or enable custom color settings to personalize the indicator's appearance.
⚠️ DISCLAIMER ⚠️: This indicator alone is not reliable and should be combined with other indicator(s) for a stronger signal.
EarlyBird MA Signals (MultiTimeFrame)Since there is the option in TradingView to set alerts on whole watchlists I wanted to have an indicator which alerts when a special "moving average crossing" on higher timeframe is happening.
I chose to be alerted when there is a "Golden/Death Cross" (SMA) on daily timeframe or when EMA20 crosses EMA50 on weekly timeframe. The plotshapes of the "higher timeframes" are visible on the "middle/lower timeframes". The lines are not visible when you add the indicator to your chart, you've to activate the checkbox.
Please check also my indicator "EMA (5,8,13,200) Strategy with Signals", maybe you want to combine both.
LANZ Strategy 3.0🔷 LANZ Strategy 3.0 — Asian Range Fibonacci Strategy with Execution Window Logic
LANZ Strategy 3.0 is a rule-based trading system that utilizes the Asian session range to project Fibonacci levels and manage entries during a defined execution window. Designed for Forex and index traders, this strategy focuses on structured price behavior around key levels before the New York session.
🧠 Core Components:
Asian Session Range Mapping: Automatically detects the high, low, and midpoint during the Asian session.
Fibonacci Level Projection: Projects configurable Fibonacci retracement and extension levels based on the Asian range.
Execution Window Logic: Uses the 01:15 NY candle as a reference to validate potential reversals or continuation setups.
Conditional Entry System: Includes logic for limit order entries (buy or sell) at specific Fib levels, with reversal logic if price breaks structure before execution.
Risk Management: Entry orders are paired with dynamic SL and TP based on Fibonacci-based distances, maintaining a risk-reward ratio consistent with intraday strategies.
📊 Visual Features:
Asian session high/low/mid lines.
Fibonacci levels: Original (based on raw range) and Optimized (user-adjustable).
Session background coloring for Asia, Execution Window, and NY session.
Labels and lines for entry, SL, and TP targets.
Dynamic deletion of untriggered orders after execution window expires.
⚙️ How It Works:
The script calculates the Asian session range.
Projects Fibonacci levels from the range.
Waits for the 01:15 NY candle to close to validate a signal.
If valid, a limit entry order (BUY or SELL) is plotted at the selected level.
If price structure changes (e.g., breaks the high/low), reversal logic may activate.
If no trade is triggered, orders are cleared before the NY session.
🔔 Alerts:
Alerts trigger when a valid setup appears after 01:15 NY candle.
Optional alerts for order activation, SL/TP hit, or trade cancellation.
📝 Notes:
Intended for semi-automated or discretionary trading.
Best used on highly liquid markets like Forex majors or indices.
Script parameters include session times, Fib ratios, SL/TP settings, and reversal logic toggle.
Credits:
Developed by LANZ, this script merges traditional session-based analysis with Fibonacci tools and structured execution timing, offering a unique framework for morning volatility plays.
Adaptive ATR Limits█ OVERVIEW
This indicator plots adaptive ATR limits for intraday trading. A key feature of this indicator, which makes it different from other ATR limit indicators, is that the top and bottom ATR limit lines are always exactly one ATR apart from each other (in "auto" mode; there is also a "basic" mode, which plots the limits in the more traditional way—i.e., one ATR above the low and one ATR below the high at all times—and this can be used for comparison).
█ FEATURES
Provides an algorithm to plot the most reasonable intraday ATR top/bottom limits based on currently available information
Dynamically adapts limits as the price evolves during the day
Works correctly and consistently on both RTH and ETH charts
Has a user-selected ADR mode to base the limits on ADR instead of ATR
Option to include the current pre-market and previous day's post-market range in the calculation
Configurable ATR/ADR averaging length
Provides a visual smoothing option
Provides an information box showing the current numerical ATR/ADR values
Reasonable defaults that work well if the user changes nothing
Well-documented, high-quality, open-source code for those interested
█ HOW TO USE
At a minimum, there is nothing that needs to be set. The defaults work well. The ATR top line (red, configurable) gives you the most reasonable move given the currently available information. The line will move away from the price as the price approaches it; that is normal—it is reacting to new information. This happens until the ATR bottom limit hits the lower of the daily low and the previous day's close (in ATR mode). The ATR bottom line (green, configurable) works the same way, with reversed logic.
There is an option to use ADR instead of ATR. The ATR includes the previous day's RTH close in the range, whereas ADR does not. Another option allows the user to add the current day's pre-market range or the previous day's post-market into the current day's range, which has an effect if either of those went outside of today's RTH range, plus yesterday's RTH close (in the default ATR mode). Pre-market and post-market range is not typically included in the daily true range, so only change it if you really know you want it.
█ CONCEPTS
Most traditional ATR limit indicators plot the top ATR limit one ATR above the current daily low, and the bottom ATR limit one ATR below the current daily high. This indicator can also do that (in "basic" mode), but its value lies in its default "auto" mode, which uses an algorithm to dynamically adapt the ATR limits throughout the day, keeping them one ATR apart at all times. It tries to plot the most sensible ATR limits based on the current daily ATR, in order to provide a reasonable visual intraday target, given the available information at that point in time.
"Auto" mode is actually a weighted average of two methods: midpoint and relative (both of which can also be explicitly selected). The midpoint method places the midpoint of the ATR limit equal to the midpoint of the currently established daily range. The relative method measures the currently established daily range and calculates the position of the current price within it (as a ratio between 0 and 1). It then uses that value as a weight in a weighted average of extreme locations for the ATR limits, which are: the ATR top anchored to one ATR above the daily low, and the ATR bottom anchored to one ATR below the daily high.
The relative method is more advanced and better for most of the day; however, it can cause wild swings in the early market or pre-market before a reasonable range (as a percentage of ATR) has been established. "Auto" mode therefore takes another weighted average between the two methods, with the weight determined by the percentage of the ATR currently established within the day, more strongly weighting the calmer midpoint method before a good range is established. Once the full ATR has been achieved, the algorithm in "auto" mode will have fully switched to the relative method and will remain with that method for the rest of the day.
To explain the effect further, as an example, imagine that the price is approaching the full ATR range on the high side. At this point, the indicator will have almost fully transitioned to the second (relative) method. The lower ATR limit will now be anchored to the daily low as the price hits the upper ATR limit. If the price goes beyond the upper ATR, the lower ATR limit will stay anchored to the daily low, and the upper limit will stay anchored to one ATR above the lower limit. This allows you to see how far the price is going beyond the upper ATR limit. If the price then returns and backs off the upper ATR limit, the lower ATR limit will un-anchor from the daily low (it will actually rise, since the daily ATR range has been exceeded, so the lower ATR limit needs to come up because the actual daily range can’t fit into the ATR range anymore). The overall effect is to give you the best visual indication of where the price is in relation to a possible upper ATR-based target. Reverse this example for when the price low approaches the ATR range on the low side.
Care was taken so that the code uses no hard-coded time zones, exchanges, or session times. For this reason, it can in principle work globally. However, it very much depends on the information provided by the exchange, which is reflected in built-in Pine Script variables (see Limitations below).
█ LIMITATIONS
The indicator was developed for US/European equities and is tested on them only. It is also known to work on US futures; in this case, the whole 23-hour session is used, and the "Sessions to include in range" setting has no effect. It may or may not work as intended on security types and equities/futures for other countries.
