Enhanced Cycle IndicatorEnhanced Cycle Indicator Guide
DISCLAIMER
"This PineScript indicator evolved from a foundational algorithm designed to visualize cycle-based center average differentials. The original concept has been significantly enhanced and optimized through collaborative refinement with AI, resulting in improved functionality, performance, and visualization capabilities while maintaining the core mathematical principles of the original design"
Overview
The Enhanced Cycle Indicator is designed to identify market cycles with minimal lag while ensuring the cycle lows and highs correspond closely with actual price bottoms and tops. This indicator transforms price data into observable cycles that help you identify when a market is likely to change direction.
Core Principles
Cycle Detection: Identifies natural market rhythms using multiple timeframes
Dynamic Adaptation: Adjusts to changing market conditions for consistent performance
Precise Signals: Provides clear entry and exit points aligned with actual market turns
Reduced Lag: Uses advanced calculations to minimize delay in cycle identification
How To Use
1. Main Cycle Interpretation
Green Histogram Bars: Bullish cycle phase (upward momentum)
Red Histogram Bars: Bearish cycle phase (downward momentum)
Cycle Extremes: When the histogram reaches extreme values (+80/-80), the market is likely approaching a turning point
Zero Line: Crossovers often indicate a shift in the underlying market direction
2. Trading Signals
Green Triangle Up (bottom of chart): Strong bullish signal - ideal for entries or covering shorts
Red Triangle Down (top of chart): Strong bearish signal - ideal for exits or short entries
Diamond Shapes: Indicate divergence between price and cycle - early warning of potential reversals
Small Circles: Minor cycle turning points - useful for fine-tuning entries/exits
3. Optimal Signal Conditions
Bullish Signals Work Best When:
The cycle is deeply oversold (below -60)
RSI is below 40 or turning up
Price is near a significant low
Multiple confirmation bars have occurred
Bearish Signals Work Best When:
The cycle is heavily overbought (above +60)
RSI is above 60 or turning down
Price is near a significant high
Multiple confirmation bars have occurred
4. Parameter Adjustments
For Shorter Timeframes: Reduce cycle periods and smoothing factor for faster response
For Daily/Weekly Charts: Increase cycle periods and smoothing for smoother signals
For Volatile Markets: Reduce cycle responsiveness to filter noise
For Trending Markets: Increase signal confirmation requirement to avoid false signals
Recommended Settings
Default (All-Purpose)
Main Cycle: 50
Half Cycle: 25
Quarter Cycle: 12
Smoothing Factor: 0.5
RSI Filter: Enabled
Signal Confirmation: 2 bars
Faster Response (Day Trading)
Main Cycle: 30
Half Cycle: 15
Quarter Cycle: 8
Smoothing Factor: 0.3
Cycle Responsiveness: 1.2
Signal Confirmation: 1 bar
Smoother Signals (Swing Trading)
Main Cycle: 80
Half Cycle: 40
Quarter Cycle: 20
Smoothing Factor: 0.7
Cycle Responsiveness: 0.8
Signal Confirmation: 3 bars
Advanced Features
Adaptive Period
When enabled, the indicator automatically adjusts cycle periods based on recent price volatility. This is particularly useful in markets that alternate between trending and ranging behaviors.
Momentum Filter
Enhances cycle signals by incorporating price momentum, making signals more responsive during strong trends and less prone to whipsaws during consolidations.
RSI Filter
Adds an additional confirmation layer using RSI, helping to filter out lower-quality signals and improve overall accuracy.
Divergence Detection
Identifies situations where price makes a new high/low but the cycle doesn't confirm, often preceding significant market reversals.
Best Practices
Use the indicator in conjunction with support/resistance levels
Look for signal clusters across multiple timeframes
Reduce position size when signals appear far from cycle extremes
Pay special attention to signals that coincide with divergences
Customize cycle periods to match the natural rhythm of your traded instrument
Troubleshooting
Too Many Signals: Increase signal confirmation bars or reduce cycle responsiveness
Missing Major Turns: Decrease smoothing factor or increase cycle responsiveness
Signals Too Late: Decrease cycle periods and smoothing factor
False Signals: Enable RSI filter and increase signal confirmation requirement
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Bullish/Bearish Body StrengthThis indicator analyzes candlestick body sizes to measure bullish versus bearish strength over a specified period. Here's what it does:
Features:
- Measures and totals the body sizes of bullish and bearish candles over your chosen lookback period
- Shows the total bullish and bearish body measurements as separate plots
- Calculates and displays a bull/bear ratio (bullish total divided by bearish total)
- Shows the difference between bullish and bearish totals
- Colors the background based on bullish (green) or bearish (red) dominance
- Includes an information table with current values and signals
Customization Options:
- Lookback Period: Set how many bars to analyze (default: 14)
- Normalize by ATR: Option to normalize body sizes by the Average True Range for more consistent measurement across different volatility periods
- Smoothing Period: Apply smoothing to the ratio and difference values
- Display Options: Toggle for showing the bull/bear ratio and bull-bear difference
How to Use:
1. Add the indicator to your chart in TradingView
2. Adjust the lookback period to fit your trading timeframe
3. Watch for:
- When bullish bodies significantly outweigh bearish ones (green dominance)
- When bearish bodies significantly outweigh bullish ones (red dominance)
- Ratio values above 2 (strong bullish signal) or below 0.5 (strong bearish signal)
The indicator provides both visual cues and numerical data to help identify periods of bullish or bearish momentum based on actual price movement rather than just candle count.
FibSync - DynamicFibSupportWhat is this indicator?
FibSync – DynamicFibSupport overlays your chart with both static and dynamic Fibonacci retracement levels, making it easy to spot potential areas of support and resistance.
Static Fibs: Calculated from the highest and lowest price over a user-defined lookback period.
Dynamic Fibs: Calculated from the most recent swing high and swing low, automatically adapting as new swings form.
How to use
Add the indicator to your chart.
Configure the settings:
Static Fib Period: Sets the lookback window for static fib levels.
Show Dynamic Fibonacci Levels: Toggle dynamic fibs on/off.
Dynamic Fib Swing Search Window: How far back to search for valid swing highs/lows.
Swing Strength (bars left/right): How many bars define a swing high/low (higher = stronger swing).
Interpret the levels:
Solid lines are static fibs.
Transparent lines are dynamic fibs (if enabled).
Colors match standard fib conventions (yellow = 0.236, red = 0.382, blue = 0.618, green = 0.786, gray = 0.5).
Tips
Static and dynamic fibs can overlap-this often highlights especially important support/resistance zones.
Adjust the swing strength for your trading style: lower values for short-term, higher for long-term swings.
Hide/show individual lines using the indicator’s style settings in TradingView.
Trading Ideas (for higher timeframes and static fibs)
Close above the blue line (0.618 static fib):
This can be interpreted as a potential long (buy) signal, suggesting the market is breaking above a key resistance level.
Close below the red line (0.382 static fib):
This can be interpreted as a potential short (sell) signal, indicating the market is breaking below a key support level.
Note: These signals are most meaningful on higher timeframes and when using the static fib lines. Always confirm with your own strategy and risk management.
Elliott Wave Noise FilterElliott Wave Noise Filter
Overview
The Elliott Wave Noise Filter is a specialized indicator for TradingView, designed to solve one of the biggest challenges in Elliott Wave analysis on lower timeframes: the identification of market noise. By combining multiple advanced filtering techniques, this indicator helps distinguish meaningful price action from random fluctuations.
The Problem
On lower timeframes—especially below 15 minutes—Elliott Wave analysis is significantly impacted by excessive market noise. This noise can lead to misinterpretation of wave structures, making it difficult to execute reliable trading decisions.
The Solution
The Elliott Wave Noise Filter utilizes four powerful methods to detect and filter noise:
ATR-Based Volatility Analysis: Identifies price movements too small to be structurally meaningful
Volume Confirmation: Filters out price moves that occur with insufficient volume
Trend Strength Measurement (ADX): Detects periods of weak trend activity, where noise tends to dominate
Fractal Pattern Recognition: Marks significant turning points that could be relevant for Elliott Wave analysis
Features
Visual Indicators
Background Coloring: Red indicates noise; green signifies a clear signal
Hull Moving Average: Smooths price action and highlights the prevailing trend
Fractal Markers: Triangles mark significant highs and lows
Status Panel: Displays current noise status and ADX value
Customization Options
ATR Period: Adjust the lookback period for ATR calculations
Noise Threshold: Defines the percentage of ATR below which a movement is considered noise
Volume Filter: Can be enabled or disabled
Volume Threshold: Sets the ratio to average volume for a move to be deemed significant
Hull MA Display and Length: Configure the moving average settings
ADX Parameters: Adjust trend strength sensitivity
Use Cases
For Elliott Wave Analysis
Eliminate noise to identify cleaner wave structures
Use fractal markers as potential wave endpoints
Reference the Hull MA for determining the broader trend
For General Trading
Identify high-noise periods to avoid low-quality setups
Spot clearer market phases for better entries
Assess price action quality through visual cues
Multi-Timeframe Approach
Apply the indicator across different timeframes for a comprehensive view
Prefer trading when both higher and lower timeframes align with consistent signals
Optimal Settings
For Very Short Timeframes (1–5 minutes)
Higher Noise Threshold (0.4–0.5)
Longer ATR Period (20–30)
Higher Volume Threshold (1.0–1.2)
For Medium Timeframes (15–60 minutes)
Medium Noise Threshold (0.2–0.3)
Standard ATR Period (14)
Standard Volume Threshold (0.8)
For Higher Timeframes (4h and above)
Lower Noise Threshold (0.1–0.2)
Shorter ATR Period (10)
Lower Volume Threshold (0.6–0.7)
Conclusion
The Elliott Wave Noise Filter is an essential tool for any Elliott Wave analyst or trader working on lower timeframes. By reducing noise and emphasizing significant market movements, it enables more precise analysis and potentially more profitable trading decisions.
Note: As with any technical indicator, the Elliott Wave Noise Filter should be used as part of a broader trading strategy and not as a standalone signal for trade execution.
(DAFE) DEVMA - Crossover (Deviation Moving Average) (DAFE) DEVMA - Crossover (Deviation Moving Average)
Let’s keep pushing the edge. After the breakthrough of Deviation over Deviation (DoD)—which gave traders a true lens into volatility’s hidden regime shifts—many asked: “What’s next?” The answer is DEVMA: a crossover engine built not on price, but on the heartbeat of the market itself.
Why is this different?
DEVMA isn’t just a moving average crossover. It’s a regime detector that tracks the expansion and contraction of deviation—giving you a real-time readout of when the market’s energy is about to shift. This is the next step for anyone who wants to anticipate volatility, not just react to it.
What sets DEVMA apart:
Volatility-First Logic:Both fast and slow lines are moving averages of deviation, not price. You’re tracking the market’s “energy,” not just its direction. This is the quant edge that most scripts miss.
Regime-Colored Lines:
The fast and slow DEVMA lines change color in real time—green/aqua for expansion, maroon/orange for contraction—so you can see regime shifts at a glance.
Quant-Pro Visuals:
Subtle glow, clean cross markers, and a minimalist dashboard keep your focus on what matters: the regime, not the noise.
Static Regime Thresholds:
Reference lines at 1.5 and 0.5 (custom colors) give you instant context for “normal” vs. “extreme” volatility states.
No Price Chasing:
This isn’t about following price. It’s about anticipating the next volatility regime—before the crowd even knows what’s coming.
How this builds on DoD:
DoD showed you when volatility itself was about to change. DEVMA takes that insight and turns it into a crossover engine—so you can see, filter, and act on regime shifts in real time. If DoD was the radar, DEVMA is the navigation system.
Inputs/Signals—explained for clarity:
Deviation Lookback:
Controls the sensitivity of the regime detector. Shorter = more signals, longer = only the rarest events.
Fast/Slow DEVMA Lengths:
Fine-tune how quickly the regime lines react. Fast for scalping, slow for swing trading.
Source Selection:
Choose from price, volume, volatility, or VoVix. Each source gives you a different lens on market stress. VoVix is for those who want to see the “regime quake” before the aftershocks.
VoVix Parameters:
Fine-tune the volatility-of-volatility engine for your market. Lower ATR Fast = more responsive; higher ATR Slow = more selective.
Bottom line:
DEVMA is for those who want to see the market’s heartbeat, not just its shadow. Use it to filter your trades, time your entries, or simply understand the market’s true rhythm. Every input is there for a reason. Every plot is a direct readout of the quant logic. Use with discipline, and make it your own.
Disclaimer:
Trading is risky. This script is for research and informational purposes only, not financial advice. Backtest, paper trade, and know your risk before going live. Past performance is not a guarantee of future results.
*Updated the Dashboard/Metrics Display for better visibility
Use with discipline. Trade your edge.
— Dskyz, for DAFE Trading Systems
Bober XM v2.0# ₿ober XM v2.0 Trading Bot Documentation
**Developer's Note**: While our previous Bot 1.3.1 was removed due to guideline violations, this setback only fueled our determination to create something even better. Rising from this challenge, Bober XM 2.0 emerges not just as an update, but as a complete reimagining with multi-timeframe analysis, enhanced filters, and superior adaptability. This adversity pushed us to innovate further and deliver a strategy that's smarter, more agile, and more powerful than ever before. Challenges create opportunity - welcome to Cryptobeat's finest work yet.
## !!!!You need to tune it for your own pair and timeframe and retune it periodicaly!!!!!
## Overview
The ₿ober XM v2.0 is an advanced dual-channel trading bot with multi-timeframe analysis capabilities. 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 across multiple timeframes.
### Key Features
- **Multi-Timeframe Analysis**: Analyze price data across multiple timeframes simultaneously
- **Dual Channel System**: Separate parameter sets for long and short positions
- **Advanced Entry Filters**: RSI, Volatility, Volume, Bollinger Bands, and KEMAD filters
- **Machine Learning Moving Average**: Adaptive prediction-based channels
- **Multiple Entry Strategies**: Breakout, Pullback, and Mean Reversion modes
- **Risk Management**: Customizable stop-loss, take-profit, and trailing stop settings
- **Webhook Integration**: Compatible with external trading bots and platforms
### Strategy Components
| Component | Description |
|---------|-------------|
| **Dual Channel Trading** | Uses either Keltner Channels or Machine Learning Moving Average (MLMA) with separate settings for long and short positions |
| **MLMA Implementation** | Machine learning algorithm that predicts future price movements and creates adaptive bands |
| **Pivot Point SuperTrend** | Trend identification and confirmation system based on pivot points |
| **Three Entry Strategies** | Choose between Breakout, Pullback, or Mean Reversion approaches |
| **Advanced Filter System** | Multiple customizable filters with multi-timeframe support to avoid false signals |
| **Custom Exit Logic** | Exits based on OBV crossover of its moving average combined with pivot trend changes |
### Note for Novice Users
This is a fully featured real trading bot and can be tweaked for any ticker — SOL is just an example. It follows this structure:
1. **Indicator** – gives the initial signal
2. **Entry strategy** – decides when to open a trade
3. **Exit strategy** – defines when to close it
4. **Trend confirmation** – ensures the trade follows the market direction
5. **Filters** – cuts out noise and avoids weak setups
6. **Risk management** – controls losses and protects your capital
To tune it for a different pair, you'll need to start from scratch:
1. Select the timeframe (candle size)
2. Turn off all filters and trend entry/exit confirmations
3. Choose a channel type, channel source and entry strategy
4. Adjust risk parameters
5. Tune long and short settings for the channel
6. Fine-tune the Pivot Point Supertrend and Main Exit condition OBV
This will generate a lot of signals and activity on the chart. Your next task is to find the right combination of filters and settings to reduce noise and tune it for profitability.
### Default Strategy values
Default values are tuned for: Symbol BITGET:SOLUSDT.P 5min candle
Filters are off by default: Try to play with it to understand how it works
## Configuration Guide
### 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.
### Multi-Timeframe Settings
1. **Enable Multi-Timeframe Analysis**: Toggle 'Enable Multi-Timeframe Analysis' in the Multi-Timeframe Settings section
2. **Configure Timeframes**: Set appropriate higher timeframes based on your trading style:
- Timeframe 1: Default is now 15 minutes (intraday confirmation)
- Timeframe 2: Default is 4 hours (trend direction)
3. **Select Sources per Indicator**: For each indicator (RSI, KEMAD, Volume, etc.), choose:
- The desired timeframe (current, mtf1, or mtf2)
- The appropriate price type (open, high, low, close, hl2, hlc3, ohlc4)
### Entry Strategies
- **Breakout**: Enter when price breaks above/below the channel
- **Pullback**: Enter when price pulls back to the channel
- **Mean Reversion**: Enter when price is extended from the channel
You can enable different strategies for long and short positions.
### Core Components
### Risk Management
- **Position Size**: Control risk with percentage-based position sizing
- **Stop Loss Options**:
- Fixed: Set a specific price or percentage from entry
- ATR-based: Dynamic stop-loss based on market volatility
- Swing: Uses recent swing high/low points
- **Take Profit**: Multiple targets with percentage allocation
- **Trailing Stop**: Dynamic stop that follows price movement
## Advanced Usage Strategies
### Moving Average Type Selection Guide
- **SMA**: More stable in choppy markets, good for higher timeframes
- **EMA/WMA**: More responsive to recent price changes, better for entry signals
- **VWMA**: Adds volume weighting for stronger trends, use with Volume filter
- **HMA**: Balance between responsiveness and noise reduction, good for volatile markets
### Multi-Timeframe Strategy Approaches
- **Trend Confirmation**: Use higher timeframe RSI (mtf2) for overall trend, current timeframe for entries
- **Entry Precision**: Use KEMAD on current timeframe with volume filter on mtf1
- **False Signal Reduction**: Apply RSI filter on mtf1 with strict KEMAD settings
### Market Condition Optimization
| Market Condition | Recommended Settings |
|------------------|----------------------|
| **Trending** | Use Breakout strategy with KEMAD filter on higher timeframe |
| **Ranging** | Use Mean Reversion with strict RSI filter (mtf1) |
| **Volatile** | Increase ATR multipliers, use HMA for moving averages |
| **Low Volatility** | Decrease noise parameters, use pullback strategy |
## Webhook Integration
The strategy features a professional webhook system that allows direct connectivity to your exchange or trading platform of choice through third-party services like 3commas, Alertatron, or Autoview.
The webhook payload includes all necessary parameters for automated execution:
- Entry price and direction
- Stop loss and take profit levels
- Position size
- Custom identifier for webhook routing
## Performance Optimization Tips
1. **Start with Defaults**: Begin with the default settings for your timeframe before customizing
2. **Adjust One Component at a Time**: Make incremental changes and test the impact
3. **Match MA Types to Market Conditions**: Use appropriate moving average types based on the Market Condition Optimization table
4. **Timeframe Synergy**: Create logical relationships between timeframes (e.g., 5min chart with 15min and 4h higher timeframes)
5. **Periodic Retuning**: Markets evolve - regularly review and adjust parameters
## Common Setups
### Crypto Trend-Following
- MLMA with EMA or HMA
- Higher RSI thresholds (75/25)
- KEMAD filter on mtf1
- Breakout entry strategy
### Stock Swing Trading
- MLMA with SMA for stability
- Volume filter with higher threshold
- KEMAD with increased filter order
- Pullback entry strategy
### Forex Scalping
- MLMA with WMA and lower noise parameter
- RSI filter on current timeframe
- Use highest timeframe for trend direction only
- Mean Reversion strategy
## Webhook Configuration
- **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 | Description | Options |
|---------|-------------|--------|
| **Source MA** | Price data used for MA calculations | Any price source (low/high/close/etc.) |
| **Moving Average Type** | Type of MA algorithm for calculations | SMA, EMA, WMA, VWMA, RMA, HMA |
| **Trend Source** | Price data used for trend determination | Any price source (close default) |
| **Window Size** | Historical window for MLMA calculations | 5+ (default: 16) |
| **Forecast Length** | Number of bars to forecast ahead | 1+ (default: 3) |
| **Noise Parameter** | Controls smoothness of prediction | 0.01+ (default: ~0.43) |
| **Band Multiplier** | Multiplier for channel width | 0.1+ (default: 0.5-0.6) |
- **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
## Filter System
### RSI Filter
- **Function**: Controls entries based on momentum conditions
- **Parameters**:
- Period: 15 (default)
- Overbought level: 71
- Oversold level: 23
- Multi-timeframe support: Current, MTF1 (15min), or MTF2 (4h)
- Customizable price source (open, high, low, close, hl2, hlc3, ohlc4)
- **Implementation**: Blocks long entries when RSI > overbought, short entries when RSI < oversold
### Volatility Filter
- **Function**: Prevents trading during excessive market volatility
- **Parameters**:
- Measure: ATR (Average True Range)
- Period: Customizable (default varies by timeframe)
- Threshold: Adjustable multiplier
- Multi-timeframe support
- Customizable price source
- **Implementation**: Blocks trades when current volatility exceeds threshold × average volatility
### Volume Filter
- **Function**: Ensures adequate market liquidity for trades
- **Parameters**:
- Threshold: 0.4× average (default)
- Measurement period: 5 (default)
- Moving average type: Customizable (HMA default)
- Multi-timeframe support
- Customizable price source
- **Implementation**: Requires current volume to exceed threshold × average volume
### Bollinger Bands Filter
- **Function**: Controls entries based on price relative to statistical boundaries
- **Parameters**:
- Period: Customizable
- Standard deviation multiplier: Adjustable
- Moving average type: Customizable
- Multi-timeframe support
- Customizable price source
- **Implementation**: Can require price to be within bands or breaking out of bands depending on strategy
### KEMAD Filter (Kalman EMA Distance)
- **Function**: Advanced trend confirmation using Kalman filter algorithm
- **Parameters**:
- Process Noise: 0.35 (controls smoothness)
- Measurement Noise: 24 (controls reactivity)
- Filter Order: 6 (higher = more smoothing)
- ATR Length: 8 (for bandwidth calculation)
- Upper Multiplier: 2.0 (for long signals)
- Lower Multiplier: 2.7 (for short signals)
- Multi-timeframe support
- Customizable visual indicators
- **Implementation**: Generates signals based on price position relative to Kalman-filtered EMA bands
## 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
### Filter Combinations
The strategy allows for simultaneous application of multiple filters:
- **Recommended Combinations**:
- Trending markets: RSI + KEMAD filters
- Ranging markets: Bollinger Bands + Volatility 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
### Multi-Timeframe Filter Applications
| Filter Type | Current Timeframe | MTF1 (15min) | MTF2 (4h) |
|-------------|-------------------|-------------|------------|
| RSI | Quick entries/exits | Intraday trend | Overall trend |
| Volume | Immediate liquidity | Sustained support | Market participation |
| Volatility | Entry timing | Short-term risk | Regime changes |
| KEMAD | Precise signals | Trend confirmation | Major reversals |
## 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 v2.0 represents a significant evolution in trading strategy design, combining traditional technical analysis with machine learning elements and multi-timeframe analysis. The core strength of this system lies in its adaptability and recognition of market asymmetry.
### Market Asymmetry and Adaptive Approach
The strategy acknowledges a fundamental truth about markets: bullish and bearish phases behave differently and should be treated as distinct environments. The dual-channel system with separate parameters for long and short positions directly addresses this asymmetry, allowing for optimized performance regardless of market direction.
### Targeted Backtesting Philosophy
It's counterproductive to run backtests over excessively long periods. Markets evolve continuously, and strategies that worked in previous market regimes may be ineffective in current conditions. Instead:
- Test specific market phases separately (bull markets, bear markets, range-bound periods)
- Regularly re-optimize parameters as market conditions change
- Focus on recent performance with higher weight than historical results
- Test across multiple timeframes to ensure robustness
### Multi-Timeframe Analysis as a Game-Changer
The integration of multi-timeframe analysis fundamentally transforms the strategy's effectiveness:
- **Increased Safety**: Higher timeframe confirmations reduce false signals and improve trade quality
- **Context Awareness**: Decisions made with awareness of larger trends reduce adverse entries
- **Adaptable Precision**: Apply strict filters on lower timeframes while maintaining awareness of broader conditions
- **Reduced Noise**: Higher timeframe data naturally filters market noise that can trigger poor entries
The ₿ober XM v2.0 provides traders with a framework that acknowledges market complexity while offering practical tools to navigate it. With proper setup, realistic expectations, and attention to changing market conditions, it delivers a sophisticated approach to systematic trading that can be continuously refined and optimized.
Intraday Fibs RetracementFibonacci (Fibs) levels are often used by traders as a way to find support and resistance, based on the Fibonacci sequence. These levels are widely used in technical analysis to identify potential reversal points in the price of an asset.
Fibs retracement draws lines at these Fibs level between a significant high and low point on a price chart.
What it shows:
This indicator will automatically draw Fibs Retracement Levels on your chart without any manual work.
It is designed to be used for day trading, especially in scenarios where a ticker gaps up/down large compared to the prior day close. (i.e. scenario where the difference of day's open and prior day close is large)
The drawing will happen on each trading day the moment trading hours open, and will NOT draw during pre-market and post-market.
User can see the line of each Fibs level, labelled with the Fib percentage and price value for the corresponding levels.
User will specify a start and end point of Fibs and based on the choice the indicator will automatically compute the other user defined Fibs levels and display on the chart.
How to use it:
The Fib levels drawn can be a potential support and resistance zone. Therefore in scenario where you already have a position and are approaching one of these levels it could be a point to close out some or all the position as you are approaching a resistance. On the other hand when price do approach these levels you could enter a position for a reversal trade. These are few ways to use the indicator but there are other ways that can be used, which can be found out by researching "Fibonacci (Fibs) Retracement".
In the example on the chart you can see a price bounce from the 0.7886 Fibs level on this particular day, where the price gapped up and was coming down after market hours opened.
Key settings:
1. Fibs Retracement Start and end Point: User selects where the Fibs levels should be drawn.
Available Options are:
Start Points:
Market Open
Market Open High (Dependent on the time frame you are on)
Pre-market High
Day's High
End Points:
Previous Day Close
Previous Day Low
Previous Day High
Pre-market Low (Current Day)
Day's Low
2. Custom Fib Levels: User can manually enter the Fib levels they want to see. (Max 9)
Default values are: 0,0.236,0.382,0.5,0.618,0.786,1,1.618,2.618.
3. Display settings: User can specify the line colour, thickness and style.
4. Label Setting: User can choose to turn on/off the labels for the each Fibs Level. Label will show the fib percentage and the corresponding price. User can also choose the location of the labels, defined by an offset from the current candle.
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If anything is not clear please let me know!
Hybrid Swing/Day Alert System - PLATINUM EditionThis indicator is a complete trading assistant designed for crypto swing and day traders, built to identify high-probability long and short setups based on a multi-confirmation system.
Strategy Logic
The system scans and confirms entries only when 6 major confluences align:
1. EMA Trend: Price is above or below the EMA 9, 21, and 200 (bullish or bearish trend).
2. RSI Zone: RSI(14) is between 40-60 (ideal reversal zone).
3. Volume Confirmation: Volume is declining on pullback and then spikes.
4. Accumulation/Distribution: A/D line rising (for longs) or falling (for shorts).
5. Fibonacci Pullback Zone: Automatic detection of swing high/low and checks if price is inside the golden zone (0.5-0.618).
Built-In Alerts
- Long Setup Confirmed - Short Setup Confirmed - Setup Forming: Monitor
Conclusion
This script is ideal for disciplined traders who value confluence-based entries, risk/reward logic, and trend-aligned trades. Perfect for semi-automated trading via alerts or manual execution.6. Candle Pattern: Bullish (hammer, doji, engulfing) or Bearish (rejection wick, engulfing, doji).
Visual Features
- Long Entry: Green square
- Short Entry: Red triangle
- Pre-Signal Alert: Blue circle (confluence forming)
- Dynamic Table: Displays all 6 confirmations in real time
- Fibonacci Zones: Auto-plotted long/short retracement zones
- Customizable: Turn on/off alerts, overlays, and direction filters
Best Use Cases
- 4H/Daily: Trend confirmation
- 1H: Entry execution
- 15min: Scalping (use cautiously)
- Works great with BTC, ETH, SOL, XAU, and meme coins
Price Lag Factor (PLF)📊 Price Lag Factor (PLF) for Crypto Traders: A Comprehensive Breakdown
The Price Lag Factor (PLF) is a momentum indicator designed to identify overextended price movements and gauge market momentum. It is particularly optimized for the crypto market, which is known for its high volatility and rapid trend shifts.
🔎 What is the Price Lag Factor (PLF)?
The PLF measures the difference between long-term and short-term price momentum and scales it dynamically based on recent volatility. This helps traders identify when the market might be overbought or oversold while filtering out noise.
The formula used in the PLF calculation is:
PLF = (Z-Long - Z-Short) / Stdev(PLF)
Where:
Z-long: Z-score of the long-term moving average (50-period by default).
Z-short: Z-score of the short-term moving average (14-period by default).
Stdev(PLF): Standard deviation of the PLF over a longer period (50-period by default).
🧠 How to Interpret the PLF:
1. Trend Direction:
Positive PLF (Green Bars): Indicates bullish momentum. The long-term trend is up, and short-term movements are confirming it.
Negative PLF (Red Bars): Indicates bearish momentum. The long-term trend is down, and short-term movements are consistent with it.
2. Momentum Strength:
PLF near Zero (±0.5): Low momentum; trend direction is not strong.
PLF between ±1 and ±2: Moderate momentum, indicating that the market is moving with strength but not in an overextended state.
PLF beyond ±2: High momentum (overbought/oversold), indicating potential trend exhaustion and a possible reversal.
📈 Trading Strategies:
1. Trend Following:
Bullish Signal:
Enter long when PLF crosses above 0 and remains green.
Confirm with other indicators like RSI or MACD to reduce false signals.
Bearish Signal:
Enter short when PLF crosses below 0 and remains red.
Use trend confirmation (e.g., moving average crossover) for better accuracy.
2. Reversal Trading:
Overbought Signal:
If PLF rises above +2, look for signs of bearish divergence or a reversal pattern to consider a short entry.
Oversold Signal:
If PLF falls below -2, watch for bullish divergence or a support bounce to consider a long entry.
3. Momentum Divergence:
Bullish Divergence:
Price makes a lower low while PLF makes a higher low.
Indicates weakening bearish momentum and a potential bullish reversal.
Bearish Divergence:
Price makes a higher high while PLF makes a lower high.
Signals weakening bullish momentum and a potential bearish reversal.
💡 Best Practices:
Combine with Volume:
Volume spikes during high PLF readings can confirm trend continuation.
Low volume during PLF extremes may hint at false breakouts.
Watch for Extreme Levels:
PLF beyond ±2 suggests overextended price action. Use caution when entering new positions.
Confirm with Other Indicators:
Use with Relative Strength Index (RSI) or Bollinger Bands to get a better sense of overbought/oversold conditions.
Overlay with a moving average to gauge trend consistency.
🚀 Why the PLF Works for Crypto:
Crypto markets are highly volatile and prone to rapid trend changes. The PLF's adaptive scaling ensures it remains relevant regardless of market conditions.
It highlights momentum shifts more accurately than static indicators because it accounts for changing volatility in its calculation.
🚨 Disclaimer for Traders Using the Price Lag Factor (PLF) Indicator:
The Price Lag Factor (PLF) indicator is designed as a technical analysis tool to gauge momentum and identify potential overbought or oversold conditions. However, it should not be relied upon as a sole decision-making factor for trading or investing.
Important Points to Consider:
Market Risk: Trading cryptocurrencies and other financial assets involves significant risk. The PLF may not accurately predict future price movements, especially during unexpected market events.
Indicator Limitations: No technical indicator, including the PLF, is infallible. False signals can occur, particularly in low-volume or highly volatile conditions.
Supplementary Analysis: Always combine PLF insights with other technical indicators, fundamental analysis, and risk management strategies to make informed decisions.
Personal Judgment: Traders should use their own discretion when interpreting PLF signals and never trade based solely on this indicator.
No Guarantees: The PLF is designed for educational and informational purposes only. Past performance is not indicative of future results.
Always perform thorough research and consider consulting with a professional financial advisor before making any trading decisions.
Extended Altman Z-Score ModelThe Extended Altman Z-Score Model represents a significant advancement in financial analysis and risk assessment, building upon the foundational work of Altman (1968) while incorporating contemporary data analytics approaches as proposed by Fung (2023). This sophisticated model enhances the traditional bankruptcy prediction framework by integrating additional financial metrics and modern analytical techniques, offering a more comprehensive approach to identifying financially distressed companies.
The model's architecture is built upon two distinct yet complementary scoring systems. The traditional Altman Z-Score components form the foundation, including Working Capital to Total Assets (X1), which measures a company's short-term liquidity and operational efficiency. Retained Earnings to Total Assets (X2) provides insight into the company's historical profitability and reinvestment capacity. EBIT to Total Assets (X3) evaluates operational efficiency and earning power, while Market Value of Equity to Total Liabilities (X4) assesses market perception and leverage. Sales to Total Assets (X5) measures asset utilization efficiency.
These traditional components are enhanced by extended metrics introduced by Fung (2023), which provide additional layers of financial analysis. The Cash Ratio (X6) offers insights into immediate liquidity and financial flexibility. Asset Composition (X7) evaluates the quality and efficiency of asset utilization, particularly in working capital management. The Debt Ratio (X8) provides a comprehensive view of financial leverage and long-term solvency, while the Net Profit Margin (X9) measures overall profitability and operational efficiency.
The scoring system employs a sophisticated formula that combines the traditional Z-Score with weighted additional metrics. The traditional Z-Score is calculated as 1.2X1 + 1.4X2 + 3.3X3 + 0.6X4 + 1.0X5, while the extended components are weighted as follows: 0.5 * X6 + 0.3 * X7 - 0.4 * X8 + 0.6 * X9. This enhanced scoring mechanism provides a more nuanced assessment of a company's financial health, incorporating both traditional bankruptcy prediction metrics and modern financial analysis approaches.
The model categorizes companies into three distinct risk zones, each with specific implications for financial stability and required actions. The Safe Zone (Score > 3.0) indicates strong financial health, with low probability of financial distress and suitability for conservative investment strategies. The Grey Zone (Score between 1.8 and 3.0) suggests moderate risk, requiring careful monitoring and additional fundamental analysis. The Danger Zone (Score < 1.8) signals high risk of financial distress, necessitating immediate attention and potential risk mitigation strategies.
In practical application, the model requires systematic and regular monitoring. Users should track the Extended Score on a quarterly basis, monitoring changes in individual components and comparing results with industry benchmarks. Component analysis should be conducted separately, identifying specific areas of concern and tracking trends in individual metrics. The model's effectiveness is significantly enhanced when used in conjunction with other financial metrics and when considering industry-specific factors and macroeconomic conditions.
The technical implementation in Pine Script v6 provides real-time calculations of both traditional and extended scores, offering visual representation of risk zones, detailed component breakdowns, and warning signals for critical values. The indicator automatically updates with new financial data and provides clear visual cues for different risk levels, making it accessible to both technical and fundamental analysts.
However, as noted by Fung (2023), the model has certain limitations that users should consider. It may not fully account for industry-specific factors, requires regular updates of financial data, and should be used in conjunction with other analysis tools. The model's effectiveness can be enhanced by incorporating industry-specific benchmarks and considering macroeconomic factors that may affect financial performance.
References:
Altman, E.I. (1968) 'Financial ratios, discriminant analysis and the prediction of corporate bankruptcy', The Journal of Finance, 23(4), pp. 589-609.
Li, L., Wang, B., Wu, Y. and Yang, Q., 2020. Identifying poorly performing listed firms using data analytics. Journal of Business Research, 109, pp.1–12. doi.org
Gamma + Fibonacci EMA Bands# Gamma + Fibonacci EMA Bands
## Overview
The Gamma + Fibonacci EMA Bands indicator combines two powerful analytical approaches: Gamma-weighted Exponential Moving Averages and Fibonacci sequence-based standard EMAs. This dual system creates a comprehensive "band" structure that helps identify trend direction, strength, and potential reversal zones with greater precision than single moving average systems.
## Features
- **Gamma-weighted EMAs**: Three customizable Gamma EMAs (fast-responding) with adjustable gamma parameters
- **Fibonacci Sequence EMAs**: Six standard EMAs based on the Fibonacci sequence (34, 55, 89, 144, 233, 377)
- **Visual Band Structure**: Color-coded for instant visual analysis
- **Trend Confirmation**: Multiple timeframe validation through varied moving average periods
- **Support/Resistance Identification**: Natural price reaction zones highlighted by EMA confluences
## How It Works
The indicator uses two complementary EMA systems:
1. **Gamma EMAs** (γ-EMAs) - These responsive moving averages use a direct gamma weighting factor (between 0-1) rather than a period length. Lower gamma values create smoother lines, while higher values create more responsive ones. These react quickly to price changes and serve as short-term trend indicators.
2. **Fibonacci EMAs** - These traditional EMAs use period lengths based on the Fibonacci sequence (34, 55, 89, 144, 233, 377). They provide longer-term trend context and naturally identify key support/resistance levels that align with market psychology.
## Interpretation
### Trend Direction
- When price is above all bands: Strong bullish trend
- When price is below all bands: Strong bearish trend
- When price is between bands: Consolidation or trend transition
### Support/Resistance
- Gamma EMAs (purple shades): Short-term dynamic support/resistance
- Fibonacci EMAs (orange/red shades): Stronger, longer-term support/resistance
### Trend Strength
- Wider band separation: Stronger trend momentum
- Compressed bands: Consolidation or trend weakness
### Reversal Signals
- Price breaking through multiple bands: Potential trend reversal
- Gamma EMAs crossing Fibonacci EMAs: Changing momentum
## Settings
- **Source**: Price data source (default: close)
- **Gamma 1**: Fast γ-EMA value (default: 0.2)
- **Gamma 2**: Medium γ-EMA value (default: 0.5)
- **Gamma 3**: Slow γ-EMA value (default: 0.8)
## Notes
This indicator works best on higher timeframes (1H+) and liquid markets. The Gamma-weighted EMAs provide faster signals while the Fibonacci sequence EMAs provide reliable support/resistance levels that often align with key market turning points.
For optimal use, watch for price interaction with these bands and how the bands interact with each other to confirm trend changes before they become obvious to the majority of market participants.
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.
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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.
Time-Based Fair Value Gaps (FVG) with Inversions (iFVG)Overview
The Time-Based Fair Value Gaps (FVG) with Inversions (iFVG) (ICT/SMT) indicator is a specialized tool designed for traders using Inner Circle Trader (ICT) methodologies. Inspired by LuxAlgo's Fair Value Gap indicator, this script introduces significant enhancements by integrating ICT principles, focusing on precise time-based FVG detection, inversion tracking, and retest signals tailored for institutional trading strategies. Unlike LuxAlgo’s general FVG approach, this indicator filters FVGs within customizable 10-minute windows aligned with ICT’s macro timeframes and incorporates ICT-specific concepts like mitigation, liquidity grabs, and session-based gap prioritization.
This tool is optimized for 1–5 minute charts, though probably best for 1 minute charts, identifying bullish and bearish FVGs, tracking their mitigation into inverted FVGs (iFVGs) as key support/resistance zones, and generating retest signals with customizable “Close” or “Wick” confirmation. Features like ATR-based filtering, optional FVG labels, mitigation removal, and session-specific FVG detection (e.g., first FVG in AM/PM sessions) make it a powerful tool for ICT traders.
Originality and Improvements
While inspired by LuxAlgo’s FVG indicator (credit to LuxAlgo for their foundational work), this script significantly extends the original concept by:
1. Time-Based FVG Detection: Unlike LuxAlgo’s continuous FVG identification, this script filters FVGs within user-defined 10-minute windows each hour (:00–:10, :10–:20, etc.), aligning with ICT’s emphasis on specific periods of institutional activity, such as hourly opens/closes or kill zones (e.g., New York 7:00–11:00 AM EST). This ensures FVGs are relevant to high-probability ICT setups.
2. Session-Specific First FVG Option: A unique feature allows traders to display only the first FVG in ICT-defined AM (9:30–10:00 AM EST) or PM (1:30–2:00 PM EST) sessions, reflecting ICT’s focus on initial market imbalances during key liquidity events.
3. ICT-Driven Mitigation and Inversion Logic: The script tracks FVG mitigation (when price closes through a gap) and converts mitigated FVGs into iFVGs, which serve as ICT-style support/resistance zones. This aligns with ICT’s view that mitigated gaps become critical reversal points, unlike LuxAlgo’s simpler gap display.
4. Customizable Retest Signals: Retest signals for iFVGs are configurable for “Close” (conservative, requiring candle body confirmation) or “Wick” (faster, using highs/lows), catering to ICT traders’ need for precise entry timing during liquidity grabs or Judas swings.
5. ATR Filtering and Mitigation Removal: An optional ATR filter ensures only significant FVGs are displayed, reducing noise, while mitigation removal declutters the chart by removing filled gaps, aligning with ICT’s principle that mitigated gaps lose relevance unless inverted.
6. Timezone and Timeframe Safeguards: A timezone offset setting aligns FVG detection with EST for ICT’s New York-centric strategies, and a timeframe warning alerts users to avoid ≥1-hour charts, ensuring accuracy in time-based filtering.
These enhancements make the script a distinct tool that builds on LuxAlgo’s foundation while offering ICT traders a tailored, high-precision solution.
How It Works
FVG Detection
FVGs are identified when a candle’s low is higher than the high of two candles prior (bullish FVG) or a candle’s high is lower than the low of two candles prior (bearish FVG). Detection is restricted to:
• User-selected 10-minute windows (e.g., :00–:10, :50–:60) to capture ICT-relevant periods like hourly transitions.
• AM/PM session first FVGs (if enabled), focusing on 9:30–10:00 AM or 1:30–2:00 PM EST for key market opens.
An optional ATR filter (default: 0.25× ATR) ensures only gaps larger than the threshold are displayed, prioritizing significant imbalances.
Mitigation and Inversion
When price closes through an FVG (e.g., below a bullish FVG’s bottom), the FVG is mitigated and becomes an iFVG, plotted as a support/resistance zone. iFVGs are critical in ICT for identifying reversal points where institutional orders accumulate.
Retest Signals
The script generates signals when price retests an iFVG:
• Close: Triggers when the candle body confirms the retest (conservative, lower noise).
• Wick: Triggers when the candle’s high/low touches the iFVG (faster, higher sensitivity). Signals are visualized with triangular markers (▲ for bullish, ▼ for bearish) and can trigger alerts.
Visualization
• FVGs: Displayed as colored boxes (green for bullish, red for bearish) with optional “Bull FVG”/“Bear FVG” labels.
• iFVGs: Shown as extended boxes with dashed midlines, limited to the user-defined number of recent zones (default: 5).
• Mitigation Removal: Mitigated FVGs/iFVGs are removed (if enabled) to keep the chart clean.
How to Use
Recommended Settings
• Timeframe: Use 1–5 minute charts for precision, avoiding ≥1-hour timeframes (a warning label appears if misconfigured).
• Time Windows: Enable :00–:10 and :50–:60 for hourly open/close FVGs, or use the “Show only 1st presented FVG” option for AM/PM session focus.
• ATR Filter: Keep enabled (multiplier 0.25–0.5) for significant gaps; disable on 1-minute charts for more FVGs during volatility.
• Signal Preference: Use “Close” for conservative entries, “Wick” for aggressive setups.
• Timezone Offset: Set to -5 for EST (or -4 for EDT) to align with ICT’s New York session.
Trading Strategy
1. Macro Timeframes: Focus on New York (7:00–11:00 AM EST) or London (2:00–5:00 AM EST) kill zones for high institutional activity.
2. FVG Entries: Trade bullish FVGs as support in uptrends or bearish FVGs as resistance in downtrends, especially in :00–:10 or :50–:60 windows.
3. iFVG Retests: Enter on retest signals (▲/▼) during liquidity grabs or Judas swings, using “Close” for confirmation or “Wick” for speed.
4. Session FVGs: Use the “Show only 1st presented FVG” option to target the first gap in AM/PM sessions, often tied to ICT’s market maker algorithms.
5. Risk Management: Combine with ICT concepts like order blocks or breaker blocks for confluence, and set stops beyond FVG/iFVG boundaries.
Alerts
Set alerts for:
• “Bullish FVG Detected”/“Bearish FVG Detected”: New FVGs in selected windows.
• “Bullish Signal”/“Bearish Signal”: iFVG retest confirmations.
Settings Description
• Show Last (1–100, default: 5): Number of recent iFVGs to display. Lower values reduce clutter.
• Show only 1st presented FVG : Limits FVGs to the first in 9:30–10:00 AM or 1:30–2:00 PM EST sessions (overrides time window checkboxes).
• Time Window Checkboxes: Enable/disable FVG detection in 10-minute windows (:00–:10, :10–:20, etc.). All enabled by default.
• Signal Preference: “Close” (default) or “Wick” for iFVG retest signals.
• Use ATR Filter: Enables ATR-based size filtering (default: true).
• ATR Multiplier (0–∞, default: 0.25): Sets FVG size threshold (higher values = larger gaps).
• Remove Mitigated FVGs: Removes filled FVGs/iFVGs (default: true).
• Show FVG Labels: Displays “Bull FVG”/“Bear FVG” labels (default: true).
• Timezone Offset (-12 to 12, default: -5): Aligns time windows with EST.
• Colors: Customize bullish (green), bearish (red), and midline (gray) colors.
Why Use This Indicator?
This indicator empowers ICT traders with a tool that goes beyond generic FVG detection, offering precise, time-filtered gaps and inversion tracking aligned with institutional trading principles. By focusing on ICT’s macro timeframes, session-specific imbalances, and customizable signal logic, it provides a clear edge for scalping, swing trading, or reversal setups in high-liquidity markets.
Strong Trend Bars (ATR-based)This is a ChatGPT pinescript meant as an indicator for detecting strength in the market. The primary function I use it for is to decide which bars to trail a stop loss beneath.
💥 Explanation of adjustable inputs:
Bull Close Threshold (default 0.6):
If set to 0.6, bull bars must close above 60% of bar height → low + 0.6 * barHeight
Bear Close Threshold (default 0.6):
If set to 0.6, bear bars must close below 40% of bar height → high - 0.6 * barHeight
This lets you experiment with tighter or looser filters. For example:
0.7 → only bars closing near the extremes will light up
0.5 → about midpoint
0.8 → very demanding, “almost full body” bars
Reverse Keltner Channel StrategyReverse Keltner Channel Strategy
Overview
The Reverse Keltner Channel Strategy is a mean-reversion trading system that capitalizes on price movements between Keltner Channels. Unlike traditional Keltner Channel strategies that trade breakouts, this system takes the contrarian approach by entering positions when price returns to the channel after overextending.
Strategy Logic
Long Entry Conditions:
Price crosses above the lower Keltner Channel from below
This signals a potential reversal after an oversold condition
Position is entered at market price upon signal confirmation
Long Exit Conditions:
Take Profit: Price reaches the upper Keltner Channel
Stop Loss: Placed at half the channel width below entry price
Short Entry Conditions:
Price crosses below the upper Keltner Channel from above
This signals a potential reversal after an overbought condition
Position is entered at market price upon signal confirmation
Short Exit Conditions:
Take Profit: Price reaches the lower Keltner Channel
Stop Loss: Placed at half the channel width above entry price
Key Features
Mean Reversion Approach: Takes advantage of price tendency to return to mean after extreme moves
Adaptive Stop Loss: Stop loss dynamically adjusts based on market volatility via ATR
Visual Signals: Entry points clearly marked with directional triangles
Fully Customizable: All parameters can be adjusted to fit various market conditions
Customizable Parameters
Keltner EMA Length: Controls the responsiveness of the channel (default: 20)
ATR Multiplier: Determines channel width/sensitivity (default: 2.0)
ATR Length: Affects volatility calculation period (default: 10)
Stop Loss Factor: Adjusts risk management aggressiveness (default: 0.5)
Best Used On
This strategy performs well on:
Currency pairs with defined ranging behavior
Commodities that show cyclical price movements
Higher timeframes (4H, Daily) for more reliable signals
Markets with moderate volatility
Risk Management
The built-in stop loss mechanism automatically adjusts to market conditions by calculating position risk relative to the current channel width. This approach ensures that risk remains proportional to potential reward across varying market conditions.
Notes for Optimization
Consider adjusting the EMA length and ATR multiplier based on the specific asset and timeframe:
Lower values increase sensitivity and generate more signals
Higher values produce fewer but potentially more reliable signals
As with any trading strategy, thorough backtesting is recommended before live implementation.
Past performance is not indicative of future results. Always practice sound risk management.
External Signals Strategy Tester v5External Signals Strategy Tester v5 – User Guide (English)
1. Purpose
This Pine Script strategy is a universal back‑tester that lets you plug in any external buy/sell series (for example, another indicator, webhook feed, or higher‑time‑frame condition) and evaluate a rich set of money‑management rules around it – with a single click on/off workflow for every module.
2. Core Workflow
Feed signals
Buy Signal / Sell Signal inputs accept any series (price, boolean, output of request.security(), etc.).
A crossover above 0 is treated as “signal fired”.
Date filter
Start Date / End Date restricts the test window so you can exclude unwanted history.
Trade engine
Optional Long / Short enable toggles.
Choose whether opposite signals simply close the trade or reverse it (flip direction in one transaction).
Risk modules – all opt‑in via check‑boxes
Classic % block – fixed % Take‑Profit / Stop‑Loss / Break‑Even.
Fibonacci Bollinger Bands (FBB) module
Draws dynamic VWMA/HMA/SMA/EMA/DEMA/TEMA mid‑line with ATR‑scaled Fibonacci envelopes.
Every line can be used for stops, trailing, or multi‑target exits.
Separate LONG and SHORT sub‑modules
Each has its own SL plus three Take‑Profits (TP1‑TP3).
Per TP you set line, position‑percentage to close, and an optional trailing flag.
Executed TP/SLs deactivate themselves so they cannot refire.
Trailing behaviour
If Trail is checked, the selected line is re‑evaluated once per bar; the order is amended via strategy.exit().
3. Inputs Overview
Group Parameter Notes
Trade Settings Enable Long / Enable Short Master switches
Close on Opposite / Reverse Position How to react to a counter‑signal
Risk % Use TP / SL / BE + their % Traditional fixed‑distance management
Fibo Bands FIBO LEVELS ENABLE + visual style/length Turn indicator overlay on/off
FBB LONG SL / TP1‑TP3 Enable, Line, %, Trail Rules applied only while a long is open
FBB SHORT SL / TP1‑TP3 Enable, Line, %, Trail Rules applied only while a short is open
Line choices: Basis, 0.236, 0.382, 0.5, 0.618, 0.764, 1.0 – long rules use lower bands, short rules use upper bands automatically.
4. Algorithm Details
Position open
On the very first bar after entry, the script checks the direction and activates the corresponding LONG or SHORT module, deactivating the other.
Order management loop (every bar)
FBB Stop‑Loss: placed/updated at chosen band; if trailing, follows the new value.
TP1‑TP3: each active target updates its limit price to the selected band (or holds static if trailing is off).
The classic % block runs in parallel; its exits have priority because they call strategy.close_all().
Exit handling
When any strategy.exit() fires, the script reads exit_id and flips the *_Active flag so that order will not be recreated.
A Stop‑Loss (SL) also disables all remaining TPs for that leg.
5. Typical Use Cases
Scenario Suggested Setup
Scalping longs into VWAP‐reversion Enable LONG TP1 @ 0.382 (30 %), TP2 @ 0.618 (40 %), SL @ 0.236 + trailing
Fade shorts during news spikes Enable SHORT SL @ 1.0 (no trail) and SHORT TP1,2,3 on consecutive lowers with small size‑outs
Classic trend‑follow Use only classic % TP/SL block and disable FBB modules
6. Hints & Tips
Signal quality matters – this script manages exits, it does not generate entries.
Keep TV time zone in mind when picking start/end dates.
For portfolio‑style testing allocate smaller default_qty_value than 100 % or use strategy.percent_of_equity sizing.
You can combine FBB exits with fixed‑% ones for layered management.
7. Limitations / Safety
No pyramiding; the script holds max one position at a time.
All calculations are bar‑close; intra‑bar touches may differ from real‑time execution.
The indicator overlay is optional, so you can run visual‑clean tests by unchecking FIBO LEVELS ENABLE.
OTE & A-B-C Zone Indicator SwiftEdgeOTE & A-B-C Zone Indicator SwiftEdge
Overview
The OTE & A-B-C Zone Indicator SwiftEdge is a versatile tool designed to help traders identify high-probability trading setups using a combination of Optimal Trade Entry (OTE) zones, Fibonacci levels, and A-B-C price patterns. This indicator is particularly useful for traders who rely on price action and Fibonacci-based strategies to find entry points, set stop-losses, and target potential take-profit levels. By integrating swing point detection, trend analysis, and Fibonacci projections, SwiftEdge provides a clear visual framework for making informed trading decisions across various timeframes.
What It Does
SwiftEdge identifies key price levels and zones to guide your trading:
OTE Zone: Highlights the Optimal Trade Entry zone between swing points A (swing high) and B (swing low) using Fibonacci retracement levels (default: 0.618 to 0.786). This zone represents a high-probability area for price reversals, making it an ideal entry point for trades.
A-B-C Pattern: Marks the latest swing points as A (swing high), B (swing low), and C (projected take-profit level) with dashed lines and labels. A solid line connects A to B to C, visually illustrating the price movement from entry to target.
Take-Profit Zones: Projects three customizable take-profit levels (TP1, TP2, TP3) based on Fibonacci extensions (default: 1.272, 1.618, 2.0) from the A-B swing, helping traders plan exits with favorable risk-reward ratios.
How It Works
SwiftEdge combines several technical components to create a cohesive trading system:
Swing Point Detection: Identifies significant swing highs (A) and swing lows (B) using a dynamic lookback period that adjusts to the selected timeframe. On lower timeframes like 1-minute charts, an ATR-based filter reduces noise by requiring price movements to exceed a threshold (0.5 * ATR(14)).
Trend Analysis: Uses an Exponential Moving Average (EMA) to determine the trend direction (default: 50-period EMA on 1H). The indicator marks uptrends (price above EMA) in green and downtrends (price below EMA) in red, ensuring trades align with the market's direction.
Fibonacci Levels: Applies Fibonacci retracement to define the OTE zone between A and B, and Fibonacci extensions to project take-profit levels (C) beyond the initial swing. This approach leverages the natural tendency of markets to respect Fibonacci ratios for reversals and extensions.
Visual Clarity: Displays only the latest A-B-C pattern with three dashed lines (A, B, C) and a solid connecting line, ensuring the chart remains uncluttered and easy to interpret.
The combination of these elements creates a structured setup where the OTE zone (between A and B) serves as an entry point, while the projected C level offers a target, all within the context of the prevailing trend. This synergy makes SwiftEdge a powerful tool for traders seeking to combine price action, trend analysis, and Fibonacci strategies.
How to Use
Add the Indicator: Apply the indicator to your chart via TradingView's indicator menu.
Identify the Trend: The OTE zone and A-B-C pattern will be colored green in uptrends (price above EMA) or red in downtrends (price below EMA). Use this to determine the market direction.
Entry Point: Look for price reversals within the OTE zone (between A and B). This zone is typically between the 0.618 and 0.786 Fibonacci retracement levels of the A-B swing, making it a high-probability area for entries.
Stop-Loss: Place your stop-loss below the OTE zone in an uptrend (or above in a downtrend) to protect against false breakouts.
Take-Profit Targets: Use the projected take-profit zones (TP1, TP2, TP3) as potential exit levels. These are based on Fibonacci extensions and can be toggled on/off in the settings.
Customization:
Adjust the Fibonacci levels for the OTE zone (Fibonacci Level 1 and Fibonacci Level 2) to suit your strategy.
Modify the take-profit levels (Fibonacci Extension Level for TP1/TP2/TP3) to target different extension ratios.
Change the lookback period (Base Lookback Period) and EMA period (Base EMA Period) to fine-tune swing point detection and trend sensitivity.
Customize colors for uptrends, downtrends, and A-B-C lines to match your preferences.
What Makes It Unique
SwiftEdge stands out by integrating swing point detection, Fibonacci-based OTE zones, and A-B-C price patterns into a single, visually intuitive indicator. Unlike standalone Fibonacci tools or trend indicators, SwiftEdge combines these elements to provide a complete trading setup: it identifies entry zones (OTE), confirms trend direction (EMA), and projects take-profit targets (Fibonacci extensions). The dynamic timeframe adjustment ensures consistent performance across all chart intervals, while the clean A-B-C visualization (with only the latest pattern displayed) prevents chart clutter, making it easier to focus on the most relevant price levels.
Notes
This indicator is designed for traders familiar with price action and Fibonacci strategies. It does not guarantee profits and should be used in conjunction with other analysis tools and proper risk management.
Performance may vary depending on market conditions and timeframe. Test the indicator on a demo account before using it in live trading.
Dual-Phase Trend Regime Oscillator (Zeiierman)█ Overview
Trend Regime: Dual-Phase Oscillator (Zeiierman) is a volatility-sensitive trend classification tool that dynamically switches between two oscillators, one optimized for low volatility, the other for high volatility.
By analyzing standard deviation-based volatility states and applying correlation-derived oscillators, this indicator reveals not only whether the market is trending but also what kind of trend regime it is in —Bullish or Bearish —and how that regime reacts to market volatility.
█ Its Uniqueness
Most trend indicators assume a static market environment; they don't adjust their logic when the underlying volatility shifts. That often leads to false signals in choppy conditions or late entries in trending phases.
Trend Regime: Dual-Phase Oscillator solves this by introducing volatility-aware adaptability. It switches between a slow, stable oscillator in calm markets and a fast, reactive oscillator in volatile ones, ensuring the right sensitivity at the right time.
█ How It Works
⚪ Volatility State Engine
Calculates returns-based volatility using standard deviation of price change
Smooths the current volatility with a moving average
Builds a volatility history window and performs median clustering to determine typical "Low" and "High" volatility zones
Dynamically assigns the chart to one of two internal volatility regimes: Low or High
⚪ Dual Oscillators
In Low Volatility, it uses a Slow Trend Oscillator (longer lookback, smoother)
In High Volatility, it switches to a Fast Trend Oscillator (shorter lookback, responsive)
Both oscillators use price-time correlation as a measure of directional strength
The output is normalized between 0 and 1, allowing for consistent interpretation
⚪ Trend Regime Classification
The active oscillator is compared to a neutral threshold (0.5)
If above: Bullish Regime, if below: Bearish Regime, else: Neutral
The background and markers update to reflect regime changes visually
Triangle markers highlight bullish/bearish regime shifts
█ How to Use
⚪ Identify Current Trend Regime
Use the background color and chart table to immediately recognize whether the market is trending up or down.
⚪ Trade Regime Shifts
Use triangle markers (▲ / ▼) to spot fresh regime entries, which are ideal for confirming breakouts within trends.
⚪ Pullback Trading
Look for pullbacks when the trend is in a stable condition and the slow oscillator remains consistently near the upper or lower threshold. Watch for moments when the fast oscillator retraces back toward the midline, or slightly above/below it — this often signals a potential pullback entry in the direction of the prevailing trend.
█ Settings Explained
Length (Slow Trend Oscillator) – Used in calm conditions. Longer = smoother signals
Length (Fast Trend Oscillator) – Used in volatile conditions. Shorter = more responsive
Volatility Refit Interval – Controls how often the system recalculates Low/High volatility levels
Current Volatility Period – Lookback used for immediate volatility measurement
Volatility Smoothing Length – Applies an SMA to the raw volatility to reduce noise
-----------------
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.
Dskyz (DAFE) Aurora Divergence – Quant Master Dskyz (DAFE) Aurora Divergence – Quant Master
Introducing the Dskyz (DAFE) Aurora Divergence – Quant Master , a strategy that’s your secret weapon for mastering futures markets like MNQ, NQ, MES, and ES. Born from the legendary Aurora Divergence indicator, this fully automated system transforms raw divergence signals into a quant-grade trading machine, blending precision, risk management, and cyberpunk DAFE visuals that make your charts glow like a neon skyline. Crafted with care and driven by community passion, this strategy stands out in a sea of generic scripts, offering traders a unique edge to outsmart institutional traps and navigate volatile markets.
The Aurora Divergence indicator was a cult favorite for spotting price-OBV divergences with its aqua and fuchsia orbs, but traders craved a system to act on those signals with discipline and automation. This strategy delivers, layering advanced filters (z-score, ATR, multi-timeframe, session), dynamic risk controls (kill switches, adaptive stops/TPs), and a real-time dashboard to turn insights into profits. Whether you’re a newbie dipping into futures or a pro hunting reversals, this strat’s got your back with a beginner guide, alerts, and visuals that make trading feel like a sci-fi mission. Let’s dive into every detail and see why this original DAFE creation is a must-have.
Why Traders Need This Strategy
Futures markets are a battlefield—fast-paced, volatile, and riddled with institutional games that can wipe out undisciplined traders. From the April 28, 2025 NQ 1k-point drop to sneaky ES slippage, the stakes are high. Meanwhile, platforms are flooded with unoriginal, low-effort scripts that promise the moon but deliver noise. The Aurora Divergence – Quant Master rises above, offering:
Unmatched Originality: A bespoke system built from the ground up, with custom divergence logic, DAFE visuals, and quant filters that set it apart from copycat clutter.
Automation with Precision: Executes trades on divergence signals, eliminating emotional slip-ups and ensuring consistency, even in chaotic sessions.
Quant-Grade Filters: Z-score, ATR, multi-timeframe, and session checks filter out noise, targeting high-probability reversals.
Robust Risk Management: Daily loss and rolling drawdown kill switches, plus ATR-based stops/TPs, protect your capital like a fortress.
Stunning DAFE Visuals: Aqua/fuchsia orbs, aurora bands, and a glowing dashboard make signals intuitive and charts a work of art.
Community-Driven: Evolved from trader feedback, this strat’s a labor of love, not a recycled knockoff.
Traders need this because it’s a complete, original system that blends accessibility, sophistication, and style. It’s your edge to trade smarter, not harder, in a market full of traps and imitators.
1. Divergence Detection (Core Signal Logic)
The strategy’s core is its ability to detect bullish and bearish divergences between price and On-Balance Volume (OBV), pinpointing reversals with surgical accuracy.
How It Works:
Price Slope: Uses linear regression over a lookback (default: 9 bars) to measure price momentum (priceSlope).
OBV Slope: OBV tracks volume flow (+volume if price rises, -volume if falls), with its slope calculated similarly (obvSlope).
Bullish Divergence: Price slope negative (falling), OBV slope positive (rising), and price above 50-bar SMA (trend_ma).
Bearish Divergence: Price slope positive (rising), OBV slope negative (falling), and price below 50-bar SMA.
Smoothing: Requires two consecutive divergence bars (bullDiv2, bearDiv2) to confirm signals, reducing false positives.
Strength: Divergence intensity (divStrength = |priceSlope * obvSlope| * sensitivity) is normalized (0–1, divStrengthNorm) for visuals.
Why It’s Brilliant:
- Divergences catch hidden momentum shifts, often exploited by institutions, giving you an edge on reversals.
- The 50-bar SMA filter aligns signals with the broader trend, avoiding choppy markets.
- Adjustable lookback (min: 3) and sensitivity (default: 1.0) let you tune for different instruments or timeframes.
2. Filters for Precision
Four advanced filters ensure signals are high-probability and market-aligned, cutting through the noise of volatile futures.
Z-Score Filter:
Logic: Calculates z-score ((close - SMA) / stdev) over a lookback (default: 50 bars). Blocks entries if |z-score| > threshold (default: 1.5) unless disabled (useZFilter = false).
Impact: Avoids trades during extreme price moves (e.g., blow-off tops), keeping you in statistically safe zones.
ATR Percentile Volatility Filter:
Logic: Tracks 14-bar ATR in a 100-bar window (default). Requires current ATR > 80th percentile (percATR) to trade (tradeOk).
Impact: Ensures sufficient volatility for meaningful moves, filtering out low-volume chop.
Multi-Timeframe (HTF) Trend Filter:
Logic: Uses a 50-bar SMA on a higher timeframe (default: 60min). Longs require price > HTF MA (bullTrendOK), shorts < HTF MA (bearTrendOK).
Impact: Aligns trades with the bigger trend, reducing counter-trend losses.
US Session Filter:
Logic: Restricts trading to 9:30am–4:00pm ET (default: enabled, useSession = true) using America/New_York timezone.
Impact: Focuses on high-liquidity hours, avoiding overnight spreads and erratic moves.
Evolution:
- These filters create a robust signal pipeline, ensuring trades are timed for optimal conditions.
- Customizable inputs (e.g., zThreshold, atrPercentile) let traders adapt to their style without compromising quality.
3. Risk Management
The strategy’s risk controls are a masterclass in balancing aggression and safety, protecting capital in volatile markets.
Daily Loss Kill Switch:
Logic: Tracks daily loss (dayStartEquity - strategy.equity). Halts trading if loss ≥ $300 (default) and enabled (killSwitch = true, killSwitchActive).
Impact: Caps daily downside, crucial during events like April 27, 2025 ES slippage.
Rolling Drawdown Kill Switch:
Logic: Monitors drawdown (rollingPeak - strategy.equity) over 100 bars (default). Stops trading if > $1000 (rollingKill).
Impact: Prevents prolonged losing streaks, preserving capital for better setups.
Dynamic Stop-Loss and Take-Profit:
Logic: Stops = entry ± ATR * multiplier (default: 1.0x, stopDist). TPs = entry ± ATR * 1.5x (profitDist). Longs: stop below, TP above; shorts: vice versa.
Impact: Adapts to volatility, keeping stops tight but realistic, with TPs targeting 1.5:1 reward/risk.
Max Bars in Trade:
Logic: Closes trades after 8 bars (default) if not already exited.
Impact: Frees capital from stagnant trades, maintaining efficiency.
Kill Switch Buffer Dashboard:
Logic: Shows smallest buffer ($300 - daily loss or $1000 - rolling DD). Displays 0 (red) if kill switch active, else buffer (green).
Impact: Real-time risk visibility, letting traders adjust dynamically.
Why It’s Brilliant:
- Kill switches and ATR-based exits create a safety net, rare in generic scripts.
- Customizable risk inputs (maxDailyLoss, dynamicStopMult) suit different account sizes.
- Buffer metric empowers disciplined trading, a DAFE signature.
4. Trade Entry and Exit Logic
The entry/exit rules are precise, filtered, and adaptive, ensuring trades are deliberate and profitable.
Entry Conditions:
Long Entry: bullDiv2, cooldown passed (canSignal), ATR filter passed (tradeOk), in US session (inSession), no kill switches (not killSwitchActive, not rollingKill), z-score OK (zOk), HTF trend bullish (bullTrendOK), no existing long (lastDirection != 1, position_size <= 0). Closes shorts first.
Short Entry: Same, but for bearDiv2, bearTrendOK, no long (lastDirection != -1, position_size >= 0). Closes longs first.
Adaptive Cooldown: Default 2 bars (cooldownBars). Doubles (up to 10) after a losing trade, resets after wins (dynamicCooldown).
Exit Conditions:
Stop-Loss/Take-Profit: Set per trade (ATR-based). Exits on stop/TP hits.
Other Exits: Closes if maxBarsInTrade reached, ATR filter fails, or kill switch activates.
Position Management: Ensures no conflicting positions, closing opposites before new entries.
Built To Be Reliable and Consistent:
- Multi-filtered entries minimize false signals, a stark contrast to basic scripts.
- Adaptive cooldown prevents overtrading, especially after losses.
- Clean position handling ensures smooth execution, even in fast markets.
5. DAFE Visuals
The visuals are a DAFE hallmark, blending function with clean flair to make signals intuitive and charts stunning.
Aurora Bands:
Display: Bands around price during divergences (bullish: below low, bearish: above high), sized by ATR * bandwidth (default: 0.5).
Colors: Aqua (bullish), fuchsia (bearish), with transparency tied to divStrengthNorm.
Purpose: Highlights divergence zones with a glowing, futuristic vibe.
Divergence Orbs:
Display: Large/small circles (aqua below for bullish, fuchsia above for bearish) when bullDiv2/bearDiv2 and canSignal. Labels show strength (0–1).
Purpose: Pinpoints entries with eye-catching clarity.
Gradient Background:
Display: Green (bullish), red (bearish), or gray (neutral), 90–95% transparent.
Purpose: Sets the market mood without clutter.
Strategy Plots:
- Stop/TP Lines: Red (stops), green (TPs) for active trades.
- HTF MA: Yellow line for trend context.
- Z-Score: Blue step-line (if enabled).
- Kill Switch Warning: Red background flash when active.
What Makes This Next-Level?:
- Visuals make complex signals (divergences, filters) instantly clear, even for beginners.
- DAFE’s unique aesthetic (orbs, bands) sets it apart from generic scripts, reinforcing originality.
- Functional plots (stops, TPs) enhance trade management.
6. Metrics Dashboard
The top-right dashboard (2x8 table) is your command center, delivering real-time insights.
Metrics:
Daily Loss ($): Current loss vs. day’s start, red if > $300.
Rolling DD ($): Drawdown vs. 100-bar peak, red if > $1000.
ATR Threshold: Current percATR, green if ATR exceeds, red if not.
Z-Score: Current value, green if within threshold, red if not.
Signal: “Bullish Div” (aqua), “Bearish Div” (fuchsia), or “None” (gray).
Action: “Consider Buying”/“Consider Selling” (signal color) or “Wait” (gray).
Kill Switch Buffer ($): Smallest buffer to kill switch, green if > 0, red if 0.
Why This Is Important?:
- Consolidates critical data, making decisions effortless.
- Color-coded metrics guide beginners (e.g., green action = go).
- Buffer metric adds transparency, rare in off-the-shelf scripts.
7. Beginner Guide
Beginner Guide: Middle-right table (shown once on chart load), explains aqua orbs (bullish, buy) and fuchsia orbs (bearish, sell).
Key Features:
Futures-Optimized: Tailored for MNQ, NQ, MES, ES with point-value adjustments.
Highly Customizable: Inputs for lookback, sensitivity, filters, and risk settings.
Real-Time Insights: Dashboard and visuals update every bar.
Backtest-Ready: Fixed qty and tick calc for accurate historical testing.
User-Friendly: Guide, visuals, and dashboard make it accessible yet powerful.
Original Design: DAFE’s unique logic and visuals stand out from generic scripts.
How to Use
Add to Chart: Load on a 5min MNQ/ES chart in TradingView.
Configure Inputs: Adjust instrument, filters, or risk (defaults optimized for MNQ).
Monitor Dashboard: Watch signals, actions, and risk metrics (top-right).
Backtest: Run in strategy tester to evaluate performance.
Live Trade: Connect to a broker (e.g., Tradovate) for automation. Watch for slippage (e.g., April 27, 2025 ES issues).
Replay Test: Use bar replay (e.g., April 28, 2025 NQ drop) to test volatility handling.
Disclaimer
Trading futures involves significant risk of loss and is not suitable for all investors. Past performance is not indicative of future results. Backtest results may not reflect live trading due to slippage, fees, or market conditions. Use this strategy at your own risk, and consult a financial advisor before trading. Dskyz (DAFE) Trading Systems is not responsible for any losses incurred.
Backtesting:
Frame: 2023-09-20 - 2025-04-29
Fee Typical Range (per side, per contract)
CME Exchange $1.14 – $1.20
Clearing $0.10 – $0.30
NFA Regulatory $0.02
Firm/Broker Commis. $0.25 – $0.80 (retail prop)
TOTAL $1.60 – $2.30 per side
Round Turn: (enter+exit) = $3.20 – $4.60 per contract
Final Notes
The Dskyz (DAFE) Aurora Divergence – Quant Master isn’t just a strategy—it’s a movement. Crafted with originality and driven by community passion, it rises above the flood of generic scripts to deliver a system that’s as powerful as it is beautiful. With its quant-grade logic, DAFE visuals, and robust risk controls, it empowers traders to tackle futures with confidence and style. Join the DAFE crew, light up your charts, and let’s outsmart the markets together!
(This publishing will most likely be taken down do to some miscellaneous rule about properly displaying charting symbols, or whatever. Once I've identified what part of the publishing they want to pick on, I'll adjust and repost.)
Use it with discipline. Use it with clarity. Trade smarter.
**I will continue to release incredible strategies and indicators until I turn this into a brand or until someone offers me a contract.
Created by Dskyz, powered by DAFE Trading Systems. Trade fast, trade bold.
Dskyz (DAFE) Quantum Sentiment Flux - Beginners Dskyz (DAFE) Quantum Sentiment Flux - Beginners:
Welcome to the Dskyz (DAFE) Quantum Sentiment Flux - Beginners , a strategy and concept that’s your ultimate wingman for trading futures like MNQ, NQ, MES, and ES. This gem combines lightning-fast momentum signals, market sentiment smarts, and bulletproof risk management into a system so intuitive, even newbies can trade like pros. With clean DAFE visuals, preset modes for every vibe, and a revamped dashboard that’s basically a market GPS, this strategy makes futures trading feel like a high-octane sci-fi mission.
Built on the Dskyz (DAFE) legacy of Aurora Divergence, the Quantum Sentiment Flux is designed to empower beginners while giving seasoned traders a lean, sentiment-driven edge. It uses fast/slow EMA crossovers for entries, filters trades with VIX, SPX trends, and sector breadth, and keeps your account safe with adaptive stops and cooldowns. Tuned for more action with faster signals and a slick bottom-left dashboard, this updated version is ready to light up your charts and outsmart institutional traps. Let’s dive into why this strat’s a must-have and break down its brilliance.
Why Traders Need This Strategy
Futures markets are a wild ride—fast moves, volatility spikes (like the April 28, 2025 NQ 1k-point drop), and institutional games that can wreck unprepared traders. Beginners often get lost in complex systems or burned by impulsive trades. The Quantum Sentiment Flux is the antidote, offering:
Dead-Simple Setup: Preset modes (Aggressive, Balanced, Conservative) auto-tune signals, risk, and sizing, so you can trade without a quant degree.
Sentiment Superpower: VIX filter, SPX trend, and sector breadth visuals keep you aligned with market health, dodging chop and riding trends.
Ironclad Safety: Tighter ATR-based stops, 2:1 take-profits, and preset cooldowns protect your capital, even in chaotic sessions.
Next-Level Visuals: Green/red entry triangles, vibrant EMAs, a sector breadth background, and a beefed-up dashboard make signals and context pop.
DAFE Swagger: The clean aesthetics, sleek dashboard—ties it to Dskyz’s elite brand, making your charts a work of art.
Traders need this because it’s a plug-and-play system that blends beginner-friendly simplicity with pro-level market awareness. Whether you’re just starting or scalping 5min MNQ, this strat’s your key to trading with confidence and style.
Strategy Components
1. Core Signal Logic (High-Speed Momentum)
The strategy’s engine is a momentum-based system using fast and slow Exponential Moving Averages (EMAs), now tuned for faster, more frequent trades.
How It Works:
Fast/Slow EMAs: Fast EMA (Aggressive: 5, Balanced: 7, Conservative: 9 bars) and slow EMA (12/14/18 bars) track short-term vs. longer-term momentum.
Crossover Signals:
Buy: Fast EMA crosses above slow EMA, and trend_dir = 1 (fast EMA > slow EMA + ATR * strength threshold).
Sell: Fast EMA crosses below slow EMA, and trend_dir = -1 (fast EMA < slow EMA - ATR * strength threshold).
Strength Filter: ma_strength = fast EMA - slow EMA must exceed an ATR-scaled threshold (Aggressive: 0.15, Balanced: 0.18, Conservative: 0.25) for robust signals.
Trend Direction: trend_dir confirms momentum, filtering out weak crossovers in choppy markets.
Evolution:
Faster EMAs (down from 7–10/21–50) catch short-term trends, perfect for active futures markets.
Lower strength thresholds (0.15–0.25 vs. 0.3–0.5) make signals more sensitive, boosting trade frequency without sacrificing quality.
Preset tuning ensures beginners get optimized settings, while pros can tweak via mode selection.
2. Market Sentiment Filters
The strategy leans hard into market sentiment with a VIX filter, SPX trend analysis, and sector breadth visuals, keeping trades aligned with the big picture.
VIX Filter:
Logic: Blocks long entries if VIX > threshold (default: 20, can_long = vix_close < vix_limit). Shorts are always allowed (can_short = true).
Impact: Prevents longs during high-fear markets (e.g., VIX spikes in crashes), while allowing shorts to capitalize on downturns.
SPX Trend Filter:
Logic: Compares S&P 500 (SPX) close to its SMA (Aggressive: 5, Balanced: 8, Conservative: 12 bars). spx_trend = 1 (UP) if close > SMA, -1 (DOWN) if < SMA, 0 (FLAT) if neutral.
Impact: Provides dashboard context, encouraging trades that align with market direction (e.g., longs in UP trend).
Sector Breadth (Visual):
Logic: Tracks 10 sector ETFs (XLK, XLF, XLE, etc.) vs. their SMAs (same lengths as SPX). Each sector scores +1 (bullish), -1 (bearish), or 0 (neutral), summed as breadth (-10 to +10).
Display: Green background if breadth > 4, red if breadth < -4, else neutral. Dashboard shows sector trends (↑/↓/-).
Impact: Faster SMA lengths make breadth more responsive, reflecting sector rotations (e.g., tech surging, energy lagging).
Why It’s Brilliant:
- VIX filter adds pro-level volatility awareness, saving beginners from panic-driven losses.
- SPX and sector breadth give a 360° view of market health, boosting signal confidence (e.g., green BG + buy signal = high-probability trade).
- Shorter SMAs make sentiment visuals react faster, perfect for 5min charts.
3. Risk Management
The risk controls are a fortress, now tighter and more dynamic to support frequent trading while keeping accounts safe.
Preset-Based Risk:
Aggressive: Fast EMAs (5/12), tight stops (1.1x ATR), 1-bar cooldown. High trade frequency, higher risk.
Balanced: EMAs (7/14), 1.2x ATR stops, 1-bar cooldown. Versatile for most traders.
Conservative: EMAs (9/18), 1.3x ATR stops, 2-bar cooldown. Safer, fewer trades.
Impact: Auto-scales risk to match style, making it foolproof for beginners.
Adaptive Stops and Take-Profits:
Logic: Stops = entry ± ATR * atr_mult (1.1–1.3x, down from 1.2–2.0x). Take-profits = entry ± ATR * take_mult (2x stop distance, 2:1 reward/risk). Longs: stop below entry, TP above; shorts: vice versa.
Impact: Tighter stops increase trade turnover while maintaining solid risk/reward, adapting to volatility.
Trade Cooldown:
Logic: Preset-driven (Aggressive/Balanced: 1 bar, Conservative: 2 bars vs. old user-input 2). Ensures bar_index - last_trade_bar >= cooldown.
Impact: Faster cooldowns (especially Aggressive/Balanced) allow more trades, balanced by VIX and strength filters.
Contract Sizing:
Logic: User sets contracts (default: 1, max: 10), no preset cap (unlike old 7/5/3 suggestion).
Impact: Flexible but risks over-leverage; beginners should stick to low contracts.
Built To Be Reliable and Consistent:
- Tighter stops and faster cooldowns make it a high-octane system without blowing up accounts.
- Preset-driven risk removes guesswork, letting newbies trade confidently.
- 2:1 TPs ensure profitable trades outweigh losses, even in volatile sessions like April 27, 2025 ES slippage.
4. Trade Entry and Exit Logic
The entry/exit rules are simple yet razor-sharp, now with VIX filtering and faster signals:
Entry Conditions:
Long Entry: buy_signal (fast EMA crosses above slow EMA, trend_dir = 1), no position (strategy.position_size = 0), cooldown passed (can_trade), and VIX < 20 (can_long). Enters with user-defined contracts.
Short Entry: sell_signal (fast EMA crosses below slow EMA, trend_dir = -1), no position, cooldown passed, can_short (always true).
Logic: Tracks last_entry_bar for visuals, last_trade_bar for cooldowns.
Exit Conditions:
Stop-Loss/Take-Profit: ATR-based stops (1.1–1.3x) and TPs (2x stop distance). Longs exit if price hits stop (below) or TP (above); shorts vice versa.
No Other Exits: Keeps it straightforward, relying on stops/TPs.
5. DAFE Visuals
The visuals are pure DAFE magic, blending clean function with informative metrics utilized by professionals, now enhanced by faster signals and a responsive breadth background:
EMA Plots:
Display: Fast EMA (blue, 2px), slow EMA (orange, 2px), using faster lengths (5–9/12–18).
Purpose: Highlights momentum shifts, with crossovers signaling entries.
Sector Breadth Background:
Display: Green (90% transparent) if breadth > 4, red (90%) if breadth < -4, else neutral.
Purpose: Faster breadth_sma_len (5–12 vs. 10–50) reflects sector shifts in real-time, reinforcing signal strength.
- Visuals are intuitive, turning complex signals into clear buy/sell cues.
- Faster breadth background reacts to market rotations (e.g., tech vs. energy), giving a pro-level edge.
6. Sector Breadth Dashboard
The new bottom-left dashboard is a game-changer, a 3x16 table (black/gray theme) that’s your market command center:
Metrics:
VIX: Current VIX (red if > 20, gray if not).
SPX: Trend as “UP” (green), “DOWN” (red), or “FLAT” (gray).
Trade Longs: “OK” (green) if VIX < 20, “BLOCK” (red) if not.
Sector Breadth: 10 sectors (Tech, Financial, etc.) with trend arrows (↑ green, ↓ red, - gray).
Placeholder Row: Empty for future metrics (e.g., ATR, breadth score).
Purpose: Consolidates regime, volatility, market trend, and sector data, making decisions a breeze.
- VIX and SPX metrics add context, helping beginners avoid bad trades (e.g., no longs if “BLOCK”).
Sector arrows show market health at a glance, like a cheat code for sentiment.
Key Features
Beginner-Ready: Preset modes and clear visuals make futures trading a breeze.
Sentiment-Driven: VIX filter, SPX trend, and sector breadth keep you in sync with the market.
High-Frequency: Faster EMAs, tighter stops, and short cooldowns boost trade volume.
Safe and Smart: Adaptive stops/TPs and cooldowns protect capital while maximizing wins.
Visual Mastery: DAFE’s clean flair, EMAs, dashboard—makes trading fun and clear.
Backtestable: Lean code and fixed qty ensure accurate historical testing.
How to Use
Add to Chart: Load on a 5min MNQ/ES chart in TradingView.
Pick Preset: Aggressive (scalping), Balanced (versatile), or Conservative (safe). Balanced is default.
Set Contracts: Default 1, max 10. Stick low for safety.
Check Dashboard: Bottom-left shows preset, VIX, SPX, and sectors. “OK” + green breadth = strong buy.
Backtest: Run in strategy tester to compare modes.
Live Trade: Connect to Tradovate or similar. Watch for slippage (e.g., April 27, 2025 ES issues).
Replay Test: Try April 28, 2025 NQ drop to see VIX filter and stops in action.
Why It’s Brilliant
The Dskyz (DAFE) Quantum Sentiment Flux - Beginners is a masterpiece of simplicity and power. It takes pro-level tools—momentum, VIX, sector breadth—and wraps them in a system anyone can run. Faster signals and tighter stops make it a trading machine, while the VIX filter and dashboard keep you ahead of market chaos. The DAFE visuals and bottom-left command center turn your chart into a futuristic cockpit, guiding you through every trade. For beginners, it’s a safe entry to futures; for pros, it’s a scalping beast with sentiment smarts. This strat doesn’t just trade—it transforms how you see the market.
Final Notes
This is more than a strategy—it’s your launchpad to mastering futures with Dskyz (DAFE) flair. The Quantum Sentiment Flux blends accessibility, speed, and market savvy to help you outsmart the game. Load it, watch those triangles glow, and let’s make the markets your canvas!
Official Statement from Pine Script Team
(see TradingView help docs and forums):
"This warning may appear when you call functions such as ta.sma inside a request.security in a loop. There is no runtime impact. If you need to loop through a dynamic list of tickers, this cannot be avoided in the present version... Values will still be correct. Ignore this warning in such contexts."
(This publishing will most likely be taken down do to some miscellaneous rule about properly displaying charting symbols, or whatever. Once I've identified what part of the publishing they want to pick on, I'll adjust and repost.)
Use it with discipline. Use it with clarity. Trade smarter.
**I will continue to release incredible strategies and indicators until I turn this into a brand or until someone offers me a contract.
Created by Dskyz, powered by DAFE Trading Systems. Trade fast, trade bold.
Schaff Trend Cycle (STC) - t0rdn3Schaff Trend Cycle (STC)
By t0rdn3 (original STC by , now with more descriptive naming)
Description
The Schaff Trend Cycle (STC) is a momentum-based oscillator that combines the speed of a fast EMA crossover with cyclical normalization. Developed by Doug Schaff, it identifies market turning points more responsively than MACD or RSI.
How It Works
1. EMA Difference : Calculates the difference between two EMAs of the source series (default: close).
2. Cycle Percentage : Normalizes that difference to a 0–100 range over the cycle period.
3. Smoothing : Applies exponential smoothing twice—first to the cycle percentage, then to its normalized cycles—to reduce noise.
4. Final STC Line : Produces a smoothed oscillator oscillating between 0 and 100.
Alerts
- "STC turned down above 75" : Fires once when STC makes a local peak above the upper threshold ( 75 ).
- "STC turned up below 25" : Fires once when STC makes a local trough below the lower threshold ( 25 ).
Inputs
Cycle Period : 12 — Lookback in bars for normalization
Fast EMA Length : 26 — Period of the fast EMA
Slow EMA Length : 50 — Period of the slow EMA
Smoothing Factor : 0.5 — Exponential smoothing coefficient (0–1)
Usage
Readings above 75 indicate an overbought cycle; readings below 25 indicate an oversold cycle. Crossings of the 50 midline can confirm trend direction:
- STC rising through 50 → bullish shift
- STC falling through 50 → bearish shift
Combine STC with price action or other trend filters to improve signal quality. You can adjust the cycle period and EMA lengths to match different timeframes or instruments.
Market Breadth Peaks & Troughs IndicatorIndicator Overview
Market Breadth (S5TH) visualizes extremes of market strength and weakness by overlaying -
a 200-period EMA (long-term trend)
a 5-period EMA (short-term trend, user-adjustable)
on the percentage of S&P 500 constituents trading above their 200-day SMA (INDEX:S5TH).
Peaks (▼) and troughs (▲) are detected with prominence filters so you can quickly spot overbought and oversold conditions.
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1. Core Logic
Component Description
Breadth series INDEX:S5TH — % of S&P 500 stocks above their 200-SMA
Long EMA 200-EMA to capture the primary trend
Short EMA 5-EMA (default, editable) for short-term swings
Peak detection ta.pivothigh + prominence ⇒ major peaks marked with red ▼
Trough detection (200 EMA) ta.pivotlow + prominence + value < longTroughLvl ⇒ blue ▲
Trough detection (5 EMA) ta.pivotlow + prominence + value < shortTroughLvl ⇒ green ▲
Background shading Pink when 200 EMA slope is down and 5 EMA sits below 200 EMA
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2. Adjustable Parameters (input())
Group Variable Default Purpose
Symbol breadthSym INDEX:S5TH Breadth index
Long EMA longLen 200 Period of long EMA
Short EMA shortLen 5 Period of short EMA
Pivot width (long) pivotLen 20 Bars left/right for 200-EMA peaks/troughs
Pivot width (short) pivotLenS 10 Bars for 5-EMA troughs
Prominence (long) promThresh 0.5 %-pt Depth filter for 200-EMA pivots
Prominence (short) promThreshS 3.0 %-pt Depth filter for 5-EMA pivots
Trough level (long) longTroughLvl 50 % Max value to accept a 200-EMA trough
Trough level (short) shortTroughLvl 30 % Max value to accept a 5-EMA trough
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3. Signal Guide
Marker / Color Meaning Typical reading
Red ▼ Major breadth peak Overbought / possible top
Blue ▲ Deep 200-EMA trough End of mid-term correction
Green ▲ Shallow 5-EMA trough (early) Short-term rebound setup
Pink background Long-term down-trend and short-term weak Risk-off phase
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4. Typical Use Cases
1. Counter-trend timing
• Fade greed: trim longs on red ▼
• Buy fear: scale in on green ▲; add on blue ▲
2. Trend filter
• Avoid new longs while the background is pink; wait for a trough & recovery.
3. Risk management
• Reduce exposure when peaks appear, reload partial size on confirmed troughs.
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5. Notes & Tips
• INDEX:S5TH is sourced from TradingView and may be back-adjusted when index membership changes.
• Fine-tune pivotLen, promThresh, and level thresholds to match current volatility before relying on alerts or automated rules.
• Slope thresholds (±0.10 %-pt) that trigger background shading can also be customized for different market regimes.
Cointegration Buy and Sell Signals [EdgeTerminal]The Cointegration Buy And Sell Signals is a sophisticated technical analysis tool to spot high-probability market turning points — before they fully develop on price charts.
Most reversal indicators rely on raw price action, visual patterns, or basic and common indicator logic — which often suffer in noisy or trending markets. In most cases, they lag behind the actual change in trend and provide useless and late signals.
This indicator is rooted in advanced concepts from statistical arbitrage, mean reversion theory, and quantitative finance, and it packages these ideas in a user-friendly visual format that works on any timeframe and asset class.
It does this by analyzing how the short-term and long-term EMAs behave relative to each other — and uses statistical filters like Z-score, correlation, volatility normalization, and stationarity tests to issue highly selective Buy and Sell signals.
This tool provides statistical confirmation of trend exhaustion, allowing you to trade mean-reverting setups. It fades overextended moves and uses signal stacking to reduce false entries. The entire indicator is based on a very interesting mathematically grounded model which I will get into down below.
Here’s how the indicator works at a high level:
EMAs as Anchors: It starts with two Exponential Moving Averages (EMAs) — one short-term and one long-term — to track market direction.
Statistical Spread (Regression Residuals): It performs a rolling linear regression between the short and long EMA. Instead of using the raw difference (short - long), it calculates the regression residual, which better models their natural relationship.
Normalize the Spread: The spread is divided by historical price volatility (ATR) to make it scale-invariant. This ensures the indicator works on low-priced stocks, high-priced indices, and crypto alike.
Z-Score: It computes a Z-score of the normalized spread to measure how “extreme” the current deviation is from its historical average.
Dynamic Thresholds: Unlike most tools that use fixed thresholds (like Z = ±2), this one calculates dynamic thresholds using historical percentiles (e.g., top 10% and bottom 10%) so that it adapts to the asset's current behavior to reduce false signals based on market’s extreme volatility at a certain time.
Z-Score Momentum: It tracks the direction of the Z-score — if Z is extreme but still moving away from zero, it's too early. It waits for reversion to start (Z momentum flips).
Correlation Check: Uses a rolling Pearson correlation to confirm the two EMAs are still statistically related. If they diverge (low correlation), no signal is shown.
Stationarity Filter (ADF-like): Uses the volatility of the regression residual to determine if the spread is stationary (mean-reverting) — a key concept in cointegration and statistical arbitrage. It’s not possible to build an exact ADF filter in Pine Script so we used the next best thing.
Signal Control: Prevents noisy charts and overtrading by ensuring no back-to-back buy or sell signals. Each signal must alternate and respect a cooldown period so you won’t be overwhelmed and won’t get a messy chart.
Important Notes to Remember:
The whole idea behind this indicator is to try to use some stat arb models to detect shifting patterns faster than they appear on common indicators, so in some cases, some assumptions are made based on historic values.
This means that in some cases, the indicator can “jump” into the conclusion too quickly. Although we try to eliminate this by using stationary filters, correlation checks, and Z-score momentum detection, there is still a chance some signals that are generated can be too early, in the stock market, that's the same as being incorrect. So make sure to use this with other indicators to confirm the movement.
How To Use The Indicator:
You can use the indicator as a standalone reversal system, as a filter for overbought and oversold setups, in combination with other trend indicators and as a part of a signal stack with other common indicators for divergence spotting and fade trades.
The indicator produces simple buy and sell signals when all criteria is met. Based on our own testing, we recommend treating these signals as standalone and independent from each other . Meaning that if you take position after a buy signal, don’t wait for a sell signal to appear to exit the trade and vice versa.
This is why we recommend using this indicator with other advanced or even simple indicators as an early confirmation tool.
The Display Table:
The floating diagnostic table in the top-right corner of the chart is a key part of this indicator. It's a live statistical dashboard that helps you understand why a signal is (or isn’t) being triggered, and whether the market conditions are lining up for a potential reversal.
1. Z-Score
What it shows: The current Z-score value of the volatility-normalized spread between the short EMA and the regression line of the long EMA.
Why it matters: Z-score tells you how statistically extreme the current relationship is. A Z-score of:
0 = perfectly average
> +2 = very overbought
< -2 = very oversold
How to use it: Look for Z-score reaching extreme highs or lows (beyond dynamic thresholds). Watch for it to start reversing direction, especially when paired with green table rows (see below)
2. Z-Score Momentum
What it shows: The rate of change (ROC) of the Z-score:
Zmomentum=Zt − Zt − 1
Why it matters: This tells you if the Z-score is still stretching out (e.g., getting more overbought/oversold), or reverting back toward the mean.
How to use it: A positive Z-momentum after a very low Z-score = potential bullish reversal A negative Z-momentum after a very high Z-score = potential bearish reversal. Avoid signals when momentum is still pushing deeper into extremes
3. Correlation
What it shows: The rolling Pearson correlation coefficient between the short EMA and long EMA.
Why it matters: High correlation (closer to +1) means the EMAs are still statistically connected — a key requirement for cointegration or mean reversion to be valid.
How to use it: Look for correlation > 0.7 for reliable signals. If correlation drops below 0.5, ignore the Z-score — the EMAs aren’t moving together anymore
4. Stationary
What it shows: A simplified "Yes" or "No" answer to the question:
“Is the spread statistically stable (stationary) and mean-reverting right now?”
Why it matters: Mean reversion strategies only work when the spread is stationary — that is, when the distance between EMAs behaves like a rubber band, not a drifting cloud.
How to use it: A "Yes" means the indicator sees a consistent, stable spread — good for trading. "No" means the market is too volatile, disjointed, or chaotic for reliable mean reversion. Wait for this to flip to "Yes" before trusting signals
5. Last Signal
What it shows: The last signal issued by the system — either "Buy", "Sell", or "None"
Why it matters: Helps avoid confusion and repeated entries. Signals only alternate — you won’t get another Buy until a Sell happens, and vice versa.
How to use it: If the last signal was a "Buy", and you’re watching for a Sell, don’t act on more bullish signals. Great for systems where you only want one position open at a time
6. Bars Since Signal
What it shows: How many bars (candles) have passed since the last Buy or Sell signal.
Why it matters: Gives you context for how long the current condition has persisted
How to use it: If it says 1 or 2, a signal just happened — avoid jumping in late. If it’s been 10+ bars, a new opportunity might be brewing soon. You can use this to time exits if you want to fade a recent signal manually
Indicator Settings:
Short EMA: Sets the short-term EMA period. The smaller the number, the more reactive and more signals you get.
Long EMA: Sets the slow EMA period. The larger this number is, the smoother baseline, and more reliable trend bases are generated.
Z-Score Lookback: The period or bars used for mean & std deviation of spread between short and long EMAs. Larger values result in smoother signals with fewer false positives.
Volatility Window: This value normalizes the spread by historical volatility. This allows you to prevent scale distortion, showing you a cleaner and better chart.
Correlation Lookback: How many periods or how far back to test correlation between slow and long EMAs. This filters out false positives when EMAs lose alignment.
Hurst Lookback: The multiplier to approximate stationarity. Lower leads to more sensitivity to regime change, higher produces a more stricter filtering.
Z Threshold Percentile: This value sets how extreme Z-score must be to trigger a signal. For example, 90 equals only top/bottom 10% of extremes, 80 = more frequent.
Min Bars Between Signals: This hard stop prevents back-to-back signals. The idea is to avoid over-trading or whipsaws in volatile markets even when Hurst lookback and volatility window values are not enough to filter signals.
Some More Recommendations:
We recommend trying different EMA pairs (10/50, 21/100, 5/20) for different asset behaviors. You can set percentile to 85 or 80 if you want more frequent but looser signals. You can also use the Z-score reversion monitor for powerful confirmation.
