MNQ TopStep 50K | Ultra Quality v3.0MNQ TopStep 50K | Ultra Quality v3.0 - Publish Summary📊 OverviewA professional-grade trading indicator designed specifically for MNQ futures traders using TopStep funded accounts. Combines 7 technical confirmations with 5 advanced safety filters to deliver high-quality trade signals while managing drawdown risk.🎯 Key FeaturesCore Signal System
7-Point Confirmation: VWAP, EMA crossovers, 15-min HTF trend, MACD, RSI, ADX, and Volume
Signal Grading: Each signal is rated A+ through D based on 7 quality factors
Quality Threshold: Adjustable minimum grade requirement (A+, A, B, C, D)
Advanced Safety Filters (Customizable)
Mean Reversion Filter - Prevents chasing extended moves beyond VWAP bands
ATR Spike Filter - Avoids trading during extreme volatility events
EMA Spacing Filter - Ensures proper trend separation (optional)
Momentum Filter - Requires consecutive directional bars (optional)
Multi-Timeframe Confirmation - Aligns with 15-min trend (optional)
TopStep Risk Management
Real-time drawdown tracking
Position sizing calculator based on remaining cushion
Daily loss limit monitoring
Consecutive loss protection
Max trades per day limiter
Visual Components
VWAP with 1σ, 2σ, 3σ bands
EMA 9/21 with cloud fill
15-min EMA 50 for HTF trend
Comprehensive metrics dashboard
Risk management panel
Filter status panel
Detailed trade labels with entry, stops, and targets
⚙️ Default Settings (Balanced for Regular Signals)Technical Indicators
Fast EMA: 9 | Slow EMA: 21 | HTF EMA: 50 (15-min)
MACD: 10/22/9
RSI: 14 period | Thresholds: 52 (buy) / 48 (sell)
ADX: 14 period | Minimum: 20
ATR: 14 period | Stop: 2x | TP1: 2x | TP2: 3x
Volume: 1.2x average required
Session Settings
Default: 9:30 AM - 11:30 AM ET (adjustable)
Avoids first 15 minutes after market open
Customizable trading hours
Safety Filters (Default Configuration)
✅ Mean Reversion: Enabled (2.5σ max from VWAP)
✅ ATR Spike: Enabled (2.0x threshold)
❌ EMA Spacing: Disabled (can enable for quality)
❌ Momentum: Disabled (can enable for quality)
❌ MTF Confirmation: Disabled (can enable for quality)
Risk Controls
Minimum Signal Quality: C (adjustable to A+ for fewer/better signals)
Min Bars Between Signals: 10
Max Trades Per Day: 5
Stop After Consecutive Losses: 2
📈 Expected PerformanceWith Default Settings:
Signals per week: 10-15 trades
Estimated win rate: 55-60%
Risk-Reward: 1:2 (TP1) and 1:3 (TP2)
With Aggressive Settings (Min Quality = D, All Filters Off):
Signals per week: 20-25 trades
Estimated win rate: 50-55%
With Conservative Settings (Min Quality = A, All Filters On):
Signals per week: 3-5 trades
Estimated win rate: 65-70%
🚀 How to UseBasic Setup:
Add indicator to MNQ 5-minute chart
Adjust TopStep account settings in inputs
Set your risk per trade percentage (default: 0.5%)
Configure trading session hours
Set minimum signal quality (Start with C for balanced results)
Signal Interpretation:
Green Triangle (BUY): Long signal - all confirmations aligned
Red Triangle (SELL): Short signal - all confirmations aligned
Label Details: Shows entry, stop loss, take profit levels, position size, and signal grade
Signal Grade: A+ = Elite (6-7 points) | A = Strong (5) | B = Good (4) | C = Fair (3)
Dashboard Monitoring:
Top Right: Technical metrics and market conditions
Top Left: Filter status (which filters are passing/blocking)
Bottom Right: TopStep risk metrics and position sizing
⚡ Customization TipsFor More Signals:
Lower "Minimum Signal Quality" to D
Decrease ADX threshold to 18-20
Lower RSI thresholds to 50/50
Reduce Volume multiplier to 1.1x
Disable additional filters
For Higher Quality (Fewer Signals):
Raise "Minimum Signal Quality" to A or A+
Increase ADX threshold to 25-30
Enable all 5 advanced filters
Tighten VWAP distance to 2.0σ
Increase momentum requirement to 3-4 bars
For TopStep Compliance:
Adjust "Max Total Drawdown" and "Daily Loss Limit" to match your account
Update "Already Used Drawdown" daily
Monitor the Risk Panel for cushion remaining
Use recommended contract sizing
🛡️ Risk DisclaimerIMPORTANT: This indicator is for educational and informational purposes only.
Past performance does not guarantee future results
All trading involves substantial risk of loss
Use proper risk management and position sizing
Test thoroughly in paper trading before live use
The indicator does not guarantee profitable trades
Adjust settings based on your risk tolerance and trading style
Always comply with your broker's and TopStep's rules
Cerca negli script per "entry"
Quanloki + ICT Smart Entry (v7.3 Pivot Entry Only + BB)If you need a signal group or team, please contact @quanloki or tele to get support and refund for the VIP group.
FVG Zones with Signals█ OVERVIEW
"FVG Zones with Signals" is a technical analysis tool that identifies Fair Value Gaps (FVG) on the chart and draws customizable zones in the form of boxes. It is ideal for traders using price action and market structure strategies, helping to identify potential imbalance zones and trading opportunities based on breakout and exit signals. With flexible size filter settings, box styles, and signal options, the indicator ensures clarity and precision on the chart.
█ CONCEPTS
The indicator is designed to identify potential entry points for trades based on FVG breakouts or retests. For chart clarity, a size filter for FVGs is included, based on a multiplier of the average candle size over a specified period.
Why are FVGs important? FVG zones represent areas of market imbalance, often attracting price back to "fill" the gap. Larger gaps (with a higher size multiplier) have a greater chance of being retested, as they indicate deeper imbalances—leaving more unexecuted orders in those zones, which attracts liquidity. Market makers and institutions often return to these levels to "refresh" liquidity before further moves. However, not every large FVG is retested quickly—in strong trends, smaller imbalances may be ignored, and the location (e.g., near swing highs/lows) is critical for retest probability.
█ FEATURES
- FVG Detection: Identifies bullish and bearish FVGs based on size filters (Candle Size Period and FVG Size Multiplier), with automatic initialization of historical gaps up to 500 candles back.
- Customizable Boxes: Draws FVG boxes with adjustable border colors, background gradients, border styles (solid, dashed, dotted), border widths, and transparency for both the background and the 50% FVG midline.
- Breakout and Exit Signals: Generates "Break" signals (green upward triangle for breakouts above bearish FVG, red downward triangle for breakouts below bullish FVG) and "Exit" signals (circles for exiting the zone), with options to select signal types (Break, Exit, or Both). A break signal causes the box to disappear, leaving a triangle as a trace of the breakout, which may serve as a signal to open a position. Exit signals (circles) may also indicate entry opportunities but require additional confirmation, such as alignment with the main trend.
- Midline: Automatically draws a dashed line at the 50% FVG level with adjustable transparency, aiding in assessing price reactions within the zone.
- Box Limitation: Automatically removes old or inactive FVGs after 500 candles to avoid chart clutter.
- Alerts: Built-in alerts for all signal types, including price and FVG type descriptions.
█ HOW TO USE
Add to Chart: Apply the indicator to your TradingView chart via the Pine Editor or Indicators menu.
Configure Settings:
- FVG Settings: Adjust Candle Size Period (default 20) and FVG Size Multiplier (default 1) to filter out small gaps—higher values generate fewer but more significant FVGs.
- Box Settings: Configure colors and styles for bullish (green) and bearish (red) boxes, including background transparency (default 80) and midline transparency.
- Signal Settings: Select signal types (Break, Exit, or Both) in Signal Type. Breakout signals appear after a candle closes outside the zone, while exit signals appear when exiting an FVG without a full breakout.
- Styling: Customize signal colors (green for buy/up, red for sell/down) and shape sizes.
Interpreting Signals:
- Break Up Signal: A green triangle below the bar indicates a breakout above a bearish FVG, suggesting potential continuation of an uptrend.
- Break Down Signal: A red triangle above the bar indicates a breakout below a bullish FVG, suggesting potential continuation of a downtrend.
- Exit Up/Down Signal: A green/red circle indicates an exit from an FVG without a full breakout, which may signal the end of a correction or preparation for a reversal.
- FVG Zones: If the price returns to an FVG and fills the gap, it may indicate equilibrium; an unfilled gap often leads to a retest.
- Use signals in conjunction with other technical analysis tools for confirmation, such as RSI (to identify overbought/oversold conditions) or MACD (to confirm momentum). Analyze FVGs from higher timeframes—these zones act as stronger imbalance levels and carry greater structural significance.
Exit signals (retests without breakouts) tend to be most effective when traded in line with the current trend.
█ APPLICATIONS
- Price Action Trading: Use FVG zones as dynamic support and resistance levels. In an uptrend, look for buying opportunities in bullish FVGs, where price often tests the gap before continuing. Combining with RSI, MACD, or Fibonacci levels enhances the significance of zones.
- Breakout Strategies: Trade based on breakout signals from FVGs. A buy signal after breaking a bearish FVG may indicate a strong upward impulse, especially when supported by a rising MACD or RSI exiting oversold conditions.
Larger FVG gaps (higher multiplier) have a greater chance of retest, as they indicate deeper imbalances.
█ NOTES
- Test the indicator across different timeframes and markets (stocks, forex, crypto) to optimize size filters for your trading style.
- The indicator initializes historical FVGs up to 500 candles back, which may slow loading on longer charts.
- For best results, use on high-liquidity markets where FVGs are more frequently retested.
- In consolidation zones, the indicator may generate more false signals, so additional confirmation is recommended.
Smart Money Toolkit - PD Engine Bias Map [KedArc Quant]📄 Description
Smart Money Toolkit is an advanced multi-layer Smart Money Concepts framework that automatically detects structure shifts, premium-discount zones, and institutional order flow.
It’s built around the PD Engine, which calculates the midpoint of the most recent market swing and dynamically determines BUY or SELL bias based on where current price trades relative to that equilibrium. This toolkit visualizes structure, order blocks, and bias context in one clean map — giving traders an institutional-grade lens without signal clutter.
💡 Why It’s Unique
* Not a mashup of open-source scripts.
Every module — CHoCH/BOS logic, order-block zone detection, PD bias engine, and structure mapping — is written from scratch to ensure clean, consistent behavior in Pine Script v6.
* Bias engine with true equilibrium logic: The 50% PD (Premium-Discount) zone adapts in real time to the latest swing, giving a live institutional price map.
* Visual precision: Minimalist premium/discount shading, structured labeling (HH, HL, LH, LL, CHoCH), and context tables for clarity.
* Performance-optimized: Handles multiple visual layers (FVG, OB, CHoCH, BOS) efficiently without repainting.
🎯 Entry and Exit Logic (Discretionary Framework)
This toolkit is not a signal generator; it’s a contextual trading framework that guides your decisions.
BUY Bias (Discount Zone)
* Price trades below PD Mid → Market is in *discount*.
* Wait for a bullish CHoCH or rejection from demand OB/FVG before entering long.
* Target 1 = PD Mid; Target 2 = next opposing OB/FVG.
SELL Bias (Premium Zone)
* Price trades above PD Mid → Market is in *premium*.
* Wait for a bearish CHoCH or rejection from supply OB/FVG before shorting.
* Target 1 = PD Mid; Target 2 = next opposing OB/FVG.
This sequence enforces the institutional concept:
> Bias → Structure Shift → Confirmation → Execution
⚙️ Input Configuration
Setting Description
Swing Sensitivity Controls how far back to look for HH/LL pivots.
OB/FVG Detection Enable or disable visual order block or fair-value-gap zones.
PD Engine Toggles PD midpoint line, zone shading, and bias table.
Multi-TF Bias Sync Optionally reads higher-time-frame bias to confirm entries.
Color Themes Switch between Light / Dark / Institutional color sets.
All inputs are modular — you can show only the components you use (e.g., disable BOS/CHoCH labels or hide OB zones for a clean view).
🧮 Formula / Logic Summary
Concept Formula
PD Mid (Equilibrium) `(Recent Swing High + Recent Swing Low) / 2`
BUY Bias `close < PD Mid`
SELL Bias `close > PD Mid`
CHoCH / BOS Detected via pivot-based structure reversal: HH→LL or LL→HH
Order Block Last bullish/bearish candle before displacement.
Fair Value Gap (FVG) Gap between prior candle’s high/low and next candle’s range.
These formulas align with Smart Money Concepts taught in institutional trading frameworks.
🤝 How It Helps Traders
* Institutional Context: Instantly visualize premium vs. discount regions — see where smart money is likely accumulating or distributing.
* Bias Confidence: Removes guesswork — you know whether you should be a buyer or seller based on structure + PD bias.
* Cleaner Decision-Making: Combines all SMC elements (BOS, CHoCH, OB, FVG, PD) in one cohesive visual map.
* Timeframe Agnostic: Works seamlessly on any timeframe or instrument (Forex, Indices, Crypto, Equities).
📚 Glossary
PD Mid (Equilibrium) The midpoint between recent swing high and low — the market’s fair
value.
Premium Zone Price above PD Mid — sellers gain control.
Discount Zone Price below PD Mid — buyers gain control.
CHoCH (Change of Character) First structural signal of possible reversal.
BOS (Break of Structure) Continuation signal confirming trend direction.
OB (Order Block) Institutional candle marking accumulation/distribution.
FVG (Fair Value Gap) Imbalance zone where price moved too quickly — often
rebalanced.
❓ FAQ
Q: Is this a signal generator?
A: No — it’s a contextual framework for professional price-action trading.
Q: Does it repaint?
A: No. All structure points and bias logic are confirmed on bar close.
Q: Can it be used on any market or timeframe?
A: Yes. It’s structure-based, not instrument-specific.
Q: How often does bias change?
A: Only when a new swing high/low forms and PD recalculates — keeping the bias stable.
Q: Can I backtest it?
A: You can build an entry rule (e.g., CHoCH + OB + PD alignment) on top of it for strategy testing.
⚠️ Disclaimer
This script is provided for educational purposes only.
Past performance does not guarantee future results.
Trading involves risk, and users should exercise caution and use proper risk management when applying this strategy.
Kalman Filter [DCAUT]█ Kalman Filter
📊 ORIGINALITY & INNOVATION
The Kalman Filter represents an important adaptation of aerospace signal processing technology to financial market analysis. Originally developed by Rudolf E. Kalman in 1960 for navigation and guidance systems, this implementation brings the algorithm's noise reduction capabilities to price trend analysis.
This implementation addresses a common challenge in technical analysis: the trade-off between smoothness and responsiveness. Traditional moving averages must choose between being smooth (with increased lag) or responsive (with increased noise). The Kalman Filter improves upon this limitation through its recursive estimation approach, which continuously balances historical trend information with current price data based on configurable noise parameters.
The key advancement lies in the algorithm's adaptive weighting mechanism. Rather than applying fixed weights to historical data like conventional moving averages, the Kalman Filter dynamically adjusts its trust between the predicted trend and observed prices. This allows it to provide smoother signals during stable periods while maintaining responsiveness during genuine trend changes, helping to reduce whipsaws in ranging markets while not missing significant price movements.
📐 MATHEMATICAL FOUNDATION
The Kalman Filter operates through a two-phase recursive process:
Prediction Phase:
The algorithm first predicts the next state based on the previous estimate:
State Prediction: Estimates the next value based on current trend
Error Covariance Prediction: Calculates uncertainty in the prediction
Update Phase:
Then updates the prediction based on new price observations:
Kalman Gain Calculation: Determines the weight given to new measurements
State Update: Combines prediction with observation based on calculated gain
Error Covariance Update: Adjusts uncertainty estimate for next iteration
Core Parameters:
Process Noise (Q): Represents uncertainty in the trend model itself. Higher values indicate the trend can change more rapidly, making the filter more responsive to price changes.
Measurement Noise (R): Represents uncertainty in price observations. Higher values indicate less trust in individual price points, resulting in smoother output.
Kalman Gain Formula:
The Kalman Gain determines how much weight to give new observations versus predictions:
K = P(k|k-1) / (P(k|k-1) + R)
Where:
K is the Kalman Gain (0 to 1)
P(k|k-1) is the predicted error covariance
R is the measurement noise parameter
When K approaches 1, the filter trusts new measurements more (responsive).
When K approaches 0, the filter trusts its prediction more (smooth).
This dynamic adjustment mechanism allows the filter to adapt to changing market conditions automatically, providing an advantage over fixed-weight moving averages.
📊 COMPREHENSIVE SIGNAL ANALYSIS
Visual Trend Indication:
The Kalman Filter line provides color-coded trend information:
Green Line: Indicates the filter value is rising, suggesting upward price momentum
Red Line: Indicates the filter value is falling, suggesting downward price momentum
Gray Line: Indicates sideways movement with no clear directional bias
Crossover Signals:
Price-filter crossovers generate trading signals:
Golden Cross: Price crosses above the Kalman Filter line, suggests potential bullish momentum development, may indicate a favorable environment for long positions, filter will naturally turn green as it adapts to price moving higher
Death Cross: Price crosses below the Kalman Filter line, suggests potential bearish momentum development, may indicate consideration for position reduction or shorts, filter will naturally turn red as it adapts to price moving lower
Trend Confirmation:
The filter serves as a dynamic trend baseline:
Price Consistently Above Filter: Confirms established uptrend
Price Consistently Below Filter: Confirms established downtrend
Frequent Crossovers: Suggests ranging or choppy market conditions
Signal Reliability Factors:
Signal quality varies based on market conditions:
Higher reliability in trending markets with sustained directional moves
Lower reliability in choppy, range-bound conditions with frequent reversals
Parameter adjustment can help adapt to different market volatility levels
🎯 STRATEGIC APPLICATIONS
Trend Following Strategy:
Use the Kalman Filter as a dynamic trend baseline:
Enter long positions when price crosses above the filter
Enter short positions when price crosses below the filter
Exit when price crosses back through the filter in the opposite direction
Monitor filter slope (color) for trend strength confirmation
Dynamic Support/Resistance:
The filter can act as a moving support or resistance level:
In uptrends: Filter often provides dynamic support for pullbacks
In downtrends: Filter often provides dynamic resistance for bounces
Price rejections from the filter can offer entry opportunities in trend direction
Filter breaches may signal potential trend reversals
Multi-Timeframe Analysis:
Combine Kalman Filters across different timeframes:
Higher timeframe filter identifies primary trend direction
Lower timeframe filter provides precise entry and exit timing
Trade only in direction of higher timeframe trend for better probability
Use lower timeframe crossovers for position entry/exit within major trend
Volatility-Adjusted Configuration:
Adapt parameters to match market conditions:
Low Volatility Markets (Forex majors, stable stocks): Use lower process noise for stability, use lower measurement noise for sensitivity
Medium Volatility Markets (Most equities): Process noise default (0.05) provides balanced performance, measurement noise default (1.0) for general-purpose filtering
High Volatility Markets (Cryptocurrencies, volatile stocks): Use higher process noise for responsiveness, use higher measurement noise for noise reduction
Risk Management Integration:
Use filter as a trailing stop-loss level in trending markets
Tighten stops when price moves significantly away from filter (overextension)
Wider stops in early trend formation when filter is just establishing direction
Consider position sizing based on distance between price and filter
📋 DETAILED PARAMETER CONFIGURATION
Source Selection:
Determines which price data feeds the algorithm:
OHLC4 (default): Uses average of open, high, low, close for balanced representation
Close: Focuses purely on closing prices for end-of-period analysis
HL2: Uses midpoint of high and low for range-based analysis
HLC3: Typical price, gives more weight to closing price
HLCC4: Weighted close price, emphasizes closing values
Process Noise (Q) - Adaptation Speed Control:
This parameter controls how quickly the filter adapts to changes:
Technical Meaning:
Represents uncertainty in the underlying trend model
Higher values allow the estimated trend to change more rapidly
Lower values assume the trend is more stable and slow-changing
Practical Impact:
Lower Values: Produces very smooth output with minimal noise, slower to respond to genuine trend changes, best for long-term trend identification, reduces false signals in choppy markets
Medium Values: Balanced responsiveness and smoothness, suitable for swing trading applications, default (0.05) works well for most markets
Higher Values: More responsive to price changes, may produce more false signals in ranging markets, better for short-term trading and day trading, captures trend changes earlier, adjust freely based on market characteristics
Measurement Noise (R) - Smoothing Control:
This parameter controls how much the filter trusts individual price observations:
Technical Meaning:
Represents uncertainty in price measurements
Higher values indicate less trust in individual price points
Lower values make each price observation more influential
Practical Impact:
Lower Values: More reactive to each price change, less smoothing with more noise in output, may produce choppy signals
Medium Values: Balanced smoothing and responsiveness, default (1.0) provides general-purpose filtering
Higher Values: Heavy smoothing for very noisy markets, reduces whipsaws significantly but increases lag in trend change detection, best for cryptocurrency and highly volatile assets, can use larger values for extreme smoothing
Parameter Interaction:
The ratio between Process Noise and Measurement Noise determines overall behavior:
High Q / Low R: Very responsive, minimal smoothing
Low Q / High R: Very smooth, maximum lag reduction
Balanced Q and R: Middle ground for most applications
Optimization Guidelines:
Start with default values (Q=0.05, R=1.0)
If too many false signals: Increase R or decrease Q
If missing trend changes: Decrease R or increase Q
Test across different market conditions before live use
Consider different settings for different timeframes
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Comparison with Traditional Moving Averages:
Versus Simple Moving Average (SMA):
The Kalman Filter typically responds faster to genuine trend changes
Produces smoother output than SMA of comparable length
Better noise reduction in ranging markets
More configurable for different market conditions
Versus Exponential Moving Average (EMA):
Similar responsiveness but with better noise filtering
Less prone to whipsaws in choppy conditions
More adaptable through dual parameter control (Q and R)
Can be tuned to match or exceed EMA responsiveness while maintaining smoothness
Versus Hull Moving Average (HMA):
Different noise reduction approach (recursive estimation vs. weighted calculation)
Kalman Filter offers more intuitive parameter adjustment
Both reduce lag effectively, but through different mechanisms
Kalman Filter may handle sudden volatility changes more gracefully
Response Characteristics:
Lag Time: Moderate and configurable through parameter adjustment
Noise Reduction: Good to excellent, particularly in volatile conditions
Trend Detection: Effective across multiple timeframes
False Signal Rate: Typically lower than simple moving averages in ranging markets
Computational Efficiency: Efficient recursive calculation suitable for real-time use
Optimal Use Cases:
Markets with mixed trending and ranging periods
Assets with moderate to high volatility requiring noise filtering
Multi-timeframe analysis requiring consistent methodology
Systematic trading strategies needing reliable trend identification
Situations requiring balance between responsiveness and smoothness
Known Limitations:
Parameters require adjustment for different market volatility levels
May still produce false signals during extreme choppy conditions
No single parameter set works optimally for all market conditions
Requires complementary indicators for comprehensive analysis
Historical performance characteristics may not persist in changing market conditions
USAGE NOTES
This indicator is designed for technical analysis and educational purposes. The Kalman Filter's effectiveness varies with market conditions, tending to perform better in markets with clear trending phases interrupted by consolidation. Like all technical indicators, it has limitations and should not be used as the sole basis for trading decisions, but rather as part of a comprehensive trading approach.
Algorithm performance varies with market conditions, and past characteristics do not guarantee future results. Always test thoroughly with different parameter settings across various market conditions before using in live trading. No technical indicator can predict future price movements with certainty, and all trading involves risk of loss.
Global Risk Terminal – Multi-Asset Macro Sentiment IndicatorDescription:
The Global Risk Terminal is a sophisticated macro sentiment indicator that synthesizes signals from three key cross-asset relationships to produce a single, actionable risk appetite score. It is designed to help traders and investors identify whether global markets are in a risk-on (growth-seeking) or risk-off (defensive) regime. The indicator analyzes the behavior of commodities, equities, bonds, and currencies to generate a comprehensive view of market conditions.
Indicator Output:
The Global Risk Terminal produces a normalized risk score ranging from -1 to +1:
Positive values indicate risk-on conditions (growth assets favored)
Negative values indicate risk-off conditions (safe-haven assets favored)
Core Components:
Growth Pulse (Copper to Gold Ratio, HG/GC)
Purpose: Measures investor preference for industrial growth versus safe-haven assets.
Interpretation:
Rising ratio → Copper outperforming gold → Risk-on environment
Falling ratio → Gold outperforming copper → Risk-off environment
Flat ratio → Transitional market phase
Technical Implementation: Dual moving average slope method (fast MA default 20, slow MA default 40). Positive slope = +1, negative slope = -1, flat slope = 0
Equity Rotation (Russell 2000 to S&P 500 Ratio, RTY/ES)
Purpose: Tracks rotation between small-cap and large-cap equities, revealing market risk appetite.
Interpretation:
Rising ratio → Small-caps outperforming → Strong risk-on
Falling ratio → Large-caps outperforming → Defensive positioning
Technical Implementation: Dual moving average slope method (same as Growth Pulse)
Flow Gauge (10-Year Treasury to US Dollar Index, ZN/DXY)
Purpose: Captures liquidity conditions and cross-asset capital flows.
Interpretation:
Rising ratio → Treasury prices rising or USD weakening → Liquidity expansion, risk-on environment
Falling ratio → Treasury prices falling or USD strengthening → Liquidity contraction, risk-off environment
Technical Implementation: Dual moving average slope method
Composite Risk Score Calculation:
Analyze each component for trend using dual moving averages
Assign signal values: +1 (risk-on), -1 (risk-off), 0 (neutral)
Average the three signals:
Risk Score = (Growth Pulse + Equity Rotation + Flow Gauge) / 3
Optional smoothing with exponential moving average (default 3 periods) to reduce noise
Interpreting the Risk Score:
+0.66 to +1.0: Full risk-on – favor cyclical sectors, small-caps, growth strategies
+0.33 to +0.66: Moderate risk-on – mostly bullish environment, watch for fading momentum
-0.33 to +0.33: Neutral/transition – markets in flux, signals mixed, exercise caution
-0.66 to -0.33: Cautious risk-off – favor defensive sectors, reduce high-beta exposure
-1.0 to -0.66: Full risk-off – strong defensive positioning, prioritize safe-haven assets
How to Use the Global Risk Terminal to Frame Trades:
Aligning Trades with Market Regime
Risk-On (+0.33 and above): Look for buying opportunities in cyclical stocks, high-beta equities, commodities, and emerging markets. Use long entries for swing trades or intraday positions, following confirmed price action.
Risk-Off (-0.33 and below): Shift focus to defensive sectors, large-cap quality stocks, U.S. Treasuries, and safe-haven currencies. Prefer short entries or reduced exposure in risky assets.
Entry and Exit Framing
Use the risk score as a macro filter before executing trades:
Example: The risk score is +0.7 (strong risk-on). Prefer long positions in equities or commodities that are showing bullish confirmation on your regular chart.
Conversely, if the risk score is -0.7 (strong risk-off), avoid aggressive longs and consider short or defensive trades.
Watch for threshold crossings (+/-0.33, +/-0.66) as potential inflection points for adjusting position size, stop-loss levels, or sector rotation.
Confirming Trade Decisions
Combine the Global Risk Terminal with price action, volume, and trend indicators:
If equities rally but the risk score is declining, this may indicate a fragile rally driven by few leaders—trade cautiously.
If equities fall but the risk score is rising, consider counter-trend entries or buying dips.
Risk Management and Position Sizing
Strong alignment across components → increase position size and hold with wider stops
Mixed or neutral signals → reduce exposure, tighten stops, or avoid new trades
Defensive regimes → rotate into stable, low-volatility assets and increase cash buffer
Framing Trades Across Timeframes
Use the indicator as a strategic guide rather than a precise timing tool. Even without the MTF table:
Daily trend alignment → Guide swing trade bias
Shorter timeframe price action → Refine entry points and stop placement
Example: Daily chart shows +0.6 risk score → identify high-probability long setups using intraday technical patterns (breakouts, trend continuation).
Sector and Asset Rotation
Risk-On: Focus on cyclical sectors (financials, industrials, materials, energy), small-caps, high-beta instruments
Risk-Off: Focus on defensive sectors (utilities, consumer staples, healthcare), large-caps, safe-haven instruments
Alert Integration
Set alerts on the risk score to notify you when markets move from neutral to risk-on or risk-off regimes. Use these alerts to plan entries, exits, or portfolio adjustments in advance.
Customization Options:
Moving Average Length (5–100): Adjust sensitivity of trend detection
Score Smoothing (1–10): Reduce noise or see raw risk score
Visual Themes: Six preset themes (Cyber, Ocean, Sunset, Monochrome, Matrix, Custom)
Display Options: Show or hide component dashboards, main header, risk level lines, gradient fill, and component signals
Label Size: Tiny, Small, Normal, Large
Alert Conditions:
Risk score crosses above +0.66 → Strong risk-on
Risk score crosses below -0.66 → Strong risk-off
Risk score crosses zero → Neutral line
Risk score crosses above +0.33 → Moderate risk-on
Risk score crosses below -0.33 → Moderate risk-off
Data Sources:
HG1! – Copper Futures (COMEX)
GC1! – Gold Futures (COMEX)
RTY1! – Russell 2000 E-mini Futures (CME)
ES1! – S&P 500 E-mini Futures (CME)
ZN1! – 10-Year U.S. Treasury Note Futures (CBOT)
DXY – U.S. Dollar Index (ICE)
Notes and Limitations:
Works best during clear macro regimes and aligned trends
Use with price action, volume, and other technical tools
Not a standalone trading system; serves as a macro context filter
Equal weighting assumes all three components are equally important, but market conditions may vary
Past performance does not guarantee future results
Conclusion:
The Global Risk Terminal consolidates complex cross-asset signals into a simple, actionable score that informs market regime, portfolio positioning, sector rotation, and trading decisions. Its user-friendly layout and extensive customization options make it suitable for traders of all experience levels seeking macro-driven insights. By framing trades around risk score thresholds and combining macro context with tactical execution, traders can identify higher-probability opportunities and optimize position sizing, entries, and exits across a wide range of market conditions.
LSVR - Liquidity Sweep & Volume ReversalLSVR condenses a pro workflow into one visual overlay: Higher-Timeframe (HTF) Trend → Liquidity Sweep & Reclaim → Volume Confirmation. A signal only prints when all three gates align at bar close, and the chart shows everything you need—trend context, the sweep “trap” candle, and a projected Entry/SL/TP based on your chosen R multiple.
How it works
HTF Trend Filter: Projects a smoothed KAMA/EMA from a higher timeframe to the chart using a safe, lookahead-off request. Long signals are considered only above the HTF line; shorts only below.
Liquidity Sweep & Reclaim: Finds confirmed swing highs/lows, then detects an ATR-scaled overshoot through that swing followed by a reclaim (close back inside a configurable % of the bar range).
Volume Confirmation: Requires either a volume spike over Volume SMA × multiplier or optional OBV divergence. No participation = no signal.
Score: Each setup is scored: trend (0/1) + overshoot strength (0..1.5) + conviction (0/1). Signals fire only when the score ≥ Min Signal Score.
What you see
HTF Ribbon (subtle green/red backdrop) for bias.
Sweep Box on the signal candle (green = long, red = short).
Signal markers (“L” / “S”) with a small score label.
Projected lines that persist until the next signal: Entry (close), Stop (beyond swept swing), Target (R multiple).
Heatmap that intensifies when the score crosses your threshold.
Dashboard (top-right): HTF direction, Volume×SMA, current Score, gate pass status.
Tooltip on the last bar with quick stats.
Quick start
Apply to any liquid symbol and set HTF to ~3–6× your chart timeframe (e.g., 15m chart → 1H–4H).
Trade with the HTF trend: take L signals above the HTF line and S signals below it.
Entry = signal bar close, SL = beyond the swept swing, TP = your Projected Take-Profit (R).
Tighten or loosen selectivity with Min Signal Score, Reclaim %, Overshoot (ATR×), and Cooldown.
Recommended presets
Choppy/crypto 15m: minScore 1.25, reclaimPct 0.60–0.65, overshootATR 1.0–1.2, useOBVDiv=false, cooldown 8.
FX 5m / session trend: minScore 1.0–1.1, reclaimPct 0.50–0.55, overshootATR 0.8–1.0, useOBVDiv=true, cooldown 5.
Indices 1m (RTH): minScore 1.2, reclaimPct 0.55–0.60, useOBVDiv=false, cooldown 10.
Non-repainting by design
HTF values use lookahead_off with realtime offset.
Swings are confirmed pivots (no “forming” pivots).
Signals print at bar close only.
Notes
OBV divergence can add sensitivity on liquid markets; keep it off for stricter filtering.
Use Cooldown to avoid clustered sweeps.
This is an overlay/analysis tool, not financial advice. Test settings in Replay/Paper Trading before using live.
PnL PortfolioThis indicator provides a comprehensive, real-time overview of your open trading portfolio directly on the chart. It allows you to track up to 20 different trading pairs simultaneously.
For each asset, simply input the Pair Symbol, Average Entry Price, and Position Quantity. The script securely fetches the current market price and dynamically calculates and displays a customizable table showing:
Real-Time Profit/Loss ($)
Percentage PnL (%)
Entry Price and Position Quantity
The table uses color coding to clearly highlight profitable (green) or losing (red) positions, and its location on the chart (top/bottom, left/right) is fully adjustable.
Micro SuiteWhat it is: One Pine v5 indicator that stacks several tools: EMA ribbon + a color-flipping 11/34 EMA trend line, multi-timeframe RSI pressure arrows, and a Bollinger Band re-entry system that marks Top/Bottom triggers (T/B) and later “r” confirmations. It also sprinkles in 3-Line Strike, Leledc exhaustion dots, and a small “Micro Dots” engine (ATR regime + VMA filter). Alerts for all of it.
TradingView
The core signals you’ll actually use:
RSI arrows: Up arrow when current RSI(6) < 30 and selected higher-TF RSIs are also < 30; down arrow when > 70 cluster cools. Idea = stacked OB/OS “pressure.”
TradingView
Bollinger re-entry (T/B + r):
T = first close back inside upper band; B = first close back inside lower band.
r = confirmation within N bars (price takes out the trigger bar’s high/low). These bars tint so they’re easy to see.
TradingView
Trend filter: EMA-11 vs EMA-34 color flip + optional VMA trend line; helps you ignore counter-trend stabs.
TradingView
Quick playbook (how to read it):
Reversal short: See a T near the top band → get the r within your window → bonus if a down RSI arrow or a Leledc high dot shows up.
Reversal long: Mirror that with B → r, plus an up RSI arrow/Leledc low dot.
Continuation: If Micro Dot stays green (or red) and 11>34 EMA holds, ignore isolated T/B traps.
TradingView
Inputs that matter:
confirmBars for the T/B “r” window.
Which higher-TF RSIs must agree for arrows.
Show/hide and lengths for EMAs and BB.
Micro block: show dots, VMA line, and speed (Fast/Med/Slow).
TradingView
Why people like it: You get trend, momentum, and mean-revert cues on one pane with ready-made alerts, so it’s easier to build a ruleset (e.g., “only take B→r longs when 11>34 and there’s an RSI up arrow”).
TradingView
Caveats: It’s still just TA—OB/OS clusters can persist in trends; confirmations can miss V-shaped turns; and stacking signals can be late in fast markets. Pair it with risk rules (fixed R, ATR stops) and a higher-TF bias.
One-liner cheat sheet:
Longs: B → r + RSI up arrow + 11>34 (optional Micro Dot green).
Shorts: T → r + RSI down arrow + 11<34 (optional Micro Dot red).
TradingView
Position Size CalculatorPosition Size CalculatorRisk Management Made Simple – Size Your Trades Like a Pro!Tired of guessing position sizes and blowing up your account on oversized trades? This Pine Script indicator automates position sizing based on your risk tolerance, ensuring every trade risks only what you've predefined. Perfect for stocks, forex, crypto, or futures—works for long or short setups. Overlay it on your candlestick chart and watch the math do the work.Key Features:Smart Risk Control: Input your account size (e.g., $70k) and risk % (e.g., 1%). It caps your max loss per trade automatically.
Dynamic Entry & Stop: Use live chart close as entry, or click to set a manual entry level (green solid line). For stops, toggle manual placement (red broken line) or use a % distance—auto-calculates the effective % for precision.
Visual Markers: Green line for entry price, red dashed line for stop loss—spans your chart for easy spotting.
Customizable Table: Floating info panel shows Account Size, Risk Amount, Stop Distance %, and Position Size (shares/lots). Drag its position via settings (top-right default).
No More Guesswork: Formula: Position Size = (Account × Risk %) ÷ Stop Distance. Handles edge cases like tiny distances to avoid div-by-zero.
How to Use:Add to your chart via Pine Editor.
In settings: Set account size/risk %. Toggle "Use Manual Entry Price" and click chart to place green line. Do the same for stop (red line) or use % input.
Table updates live—grab the position size and execute!
Pro Tip: For shorts/longs, the abs distance keeps risk symmetric. Test on demo first.
Built for v6—clean, lightweight, and 100% customizable. Share your tweaks in comments! Remember, this is a tool, not advice—trade responsibly. (Inspired by classic Kelly Criterion vibes, but simplified for daily grinders.)
HM2 - Murrey Math Levels# Murrey Math Indicator - Comprehensive Description
## **What is Murrey Math?**
Murrey Math is a trading system developed by T.H. Murrey that divides price action into 8 equal segments (octaves) based on Gann and geometry principles. It automatically identifies key support and resistance levels where price is likely to react, making it a powerful tool for determining entry/exit points and price targets.
## **How It Works**
The indicator:
1. **Analyzes price history** over a lookback period (default 64-200 bars)
2. **Finds the highest high and lowest low** in that period
3. **Calculates a "fractal"** - a geometric scaling factor based on price magnitude
4. **Creates 8 equal divisions** between key levels, plus 4 overshoot levels (total 13 levels)
5. **Labels each level** from -2/8 to +2/8 with their trading significance
## **The 13 Murrey Math Levels**
### **Core Levels (0/8 to 8/8):**
- ** - Ultimate Support** (Blue)
- Extreme oversold condition
- Strong buying opportunity
- Price rarely breaks below this
- ** - Weak, Stall & Reverse** (Orange)
- Weak support level
- Price often stalls and reverses here
- ** - Pivot/Reverse Level** (Red)
- Major support that can become resistance
- Important reversal zone
- ** - Bottom of Trading Range - BUY Zone** (Green)
- Bottom boundary of normal trading
- **Premium BUY zone** - 40% of trading happens between 3/8 and 5/8
- ** - Major Support/Resistance** (Blue)
- **THE MOST IMPORTANT LEVEL**
- The midpoint - best entry/exit level
- Strong pivot point that price respects
- ** - Top of Trading Range - SELL Zone** (Green)
- Top boundary of normal trading
- **Premium SELL zone**
- ** - Pivot/Reverse Level** (Red)
- Major resistance that can become support
- Important reversal zone
- ** - Weak, Stall & Reverse** (Orange)
- Weak resistance level
- Price often stalls and reverses here
- ** - Ultimate Resistance** (Blue)
- Extreme overbought condition
- Strong selling opportunity
- Price rarely breaks above this
### **Overshoot Levels:**
- ** & ** (Gray) - Extreme downside overshoot zones
- ** & ** (Gray) - Extreme upside overshoot zones
- These indicate extreme moves beyond normal trading ranges
## **Trading Zones (from your diagram)**
1. **Consolidation Trading Area** (0/8 to 3/8)
- Price is in a bearish zone
- Look for BUY opportunities near support levels
2. **Normal Trading Area** (3/8 to 5/8)
- **40% of trading occurs here**
- Price oscillates between these boundaries
- Range-bound trading strategies work best
3. **Premium Trading Area** (5/8 to 8/8)
- Price is in a bullish zone
- Look for SELL opportunities near resistance levels
## **Trading Strategies**
### **Buy Signals:**
- Price bounces off 0/8 (ultimate support)
- Price pulls back to 3/8 in an uptrend
- Price breaks above 4/8 after consolidation
### **Sell Signals:**
- Price rejects at 8/8 (ultimate resistance)
- Price rallies to 5/8 in a downtrend
- Price breaks below 4/8 after consolidation
### **Range Trading:**
- Buy near 3/8, sell near 5/8 when price is ranging
- Use 4/8 as the pivot to determine trend direction
## **Key Advantages**
✅ **Objective levels** - No subjective placement
✅ **Self-adjusting** - Automatically recalculates based on recent price action
✅ **Clear trading zones** - Easy to identify support/resistance
✅ **Works on all timeframes** - From 1-minute to monthly charts
✅ **Combines with other indicators** - Works well with RSI, MACD, etc.
## **Important Notes**
- The indicator is **dynamic** - levels update as new highs/lows form
- **4/8 is the most critical level** - price above = bullish, below = bearish
- When price reaches overshoot levels (±1/8, ±2/8), expect strong reversals
- Works best in trending markets; can give false signals in choppy conditions
This geometric approach to support/resistance has been used by traders for decades and remains popular due to its objective, mathematical nature!
Mitigation Blocks — Lite (ICT) + Arrows + Stats📌 Mitigation Blocks — Lite (ICT-Based) + Arrows
This indicator detects mitigation blocks based on price structure shifts, inspired by ICT (Inner Circle Trader) concepts. It works by identifying strong impulses and highlighting the last opposite candle, forming a mitigation block zone for potential reversal or continuation trades.
🔍 Features:
✅ Automatic detection of bullish and bearish mitigation blocks
🟩 Box visualization with border color change on mitigation (first touch)
📉 ATR-based impulse filtering
📌 Entry arrows on first mitigation (touch)
📊 Autoscale anchors for better chart readability
📈 Real-time HUD info panel
📉 Backtest-friendly design (stable, deterministic logic)
🛠️ How it works:
Detects swing highs/lows using pivot points.
Confirms impulse candles breaking recent structure.
Locates the last opposite candle as the mitigation block.
Displays a block box until price revisits the zone.
On the first touch (mitigation), the block is marked and arrows are drawn.
💡 Ideal Use Case:
Apply this on higher timeframes (e.g., 4H) to identify potential limit order zones.
Use the blocks as entry zones and combine with confluence: FVGs, imbalance, S&D, or liquidity levels.
🧠 Extra Tip:
You can extend this script to include:
Win-rate tracking
Auto TP/SL levels based on ATR
Confluence detection (e.g., FVG, order blocks)
Smart Money Concept v1Smart Money Concept Indicator – Visual Interpretation Guide
What Happens When Liquidity Lines Are Broken
🟩 Green Line Broken (Buy-Side Liquidity Pool Swept)
- Indicates price has dipped below a previous swing low where sell stops are likely placed.
- Market Makers may be triggering these stops to accumulate long positions.
- Often followed by a bullish reversal.
- Trader Actions:
• Look for a bullish candle close after the sweep.
• Confirm with nearby Bullish Order Block or Fair Value Gap.
• Consider entering a Buy trade (SLH entry).
- If price continues falling: Indicates trend continuation and invalidation of the buy-side liquidity zone.
🟥 Red Line Broken (Sell-Side Liquidity Pool Swept)
- Indicates price has moved above a previous swing high where buy stops are likely placed.
- Market Makers may be triggering these stops to accumulate short positions.
- Often followed by a bearish reversal.
- Trader Actions:
• Look for a bearish candle close after the sweep.
• Confirm with nearby Bearish Order Block or Fair Value Gap.
• Consider entering a Sell trade (SLH entry).
- If price continues rising: Indicates trend continuation and invalidation of the sell-side liquidity zone.
Chart-Based Interpretation of Green Line Breaks
In the provided DOGE/USD 15-minute chart image:
- Green lines represent buy-side liquidity zones.
- If these lines are broken:
• It may be a stop hunt before a bullish continuation.
• Or a false Break of Structure (BOS) leading to deeper retracement.
- Confirmation is needed from candle structure and nearby OB/FVG zones.
Is the Pink Zone a Valid Bullish Order Block?
To validate the pink zone as a Bullish OB:
- It should be formed by a strong down-close candle followed by a bullish move.
- Price should have rallied from this zone previously.
- If price is now retesting it and showing bullish reaction, it confirms validity.
- If formed during low volume or price never rallied from it, it may not be valid.
Smart Money Concept - Liquidity Line Breaks Explained
This document explains how traders should interpret the breaking of green (buy-side) and red (sell-side) liquidity lines when using the Smart Money Concept indicator. These lines represent key liquidity pools where stop orders are likely placed.
🟩 Green Line Broken (Buy-Side Liquidity Pool Swept)
When the green line is broken, it indicates:
• - Price has dipped below a previous swing low where sell stops were likely placed.
• - Market Makers have triggered those stops to accumulate long positions.
• - This is often followed by a bullish reversal.
Trader Actions:
• - Look for a bullish candle close after the sweep.
• - Confirm with a nearby Bullish Order Block or Fair Value Gap.
• - Consider entering a Buy trade (SLH entry).
🟥 Red Line Broken (Sell-Side Liquidity Pool Swept)
When the red line is broken, it indicates:
• - Price has moved above a previous swing high where buy stops were likely placed.
• - Market Makers have triggered those stops to accumulate short positions.
• - This is often followed by a bearish reversal.
Trader Actions:
• - Look for a bearish candle close after the sweep.
• - Confirm with a nearby Bearish Order Block or Fair Value Gap.
• - Consider entering a Sell trade (SLH entry).
📌 Additional Notes
• - If price continues beyond the liquidity line without reversal, it may indicate a trend continuation rather than a stop hunt.
• - Always confirm with Higher Time Frame bias, Institutional Order Flow, and price reaction at the zone.
KAPITAS CBDR# PO3 Mean Reversion Standard Deviation Bands - Pro Edition
## 📊 Professional-Grade Mean Reversion System for MES Futures
Transform your futures trading with this institutional-quality mean reversion system based on standard deviation analysis and PO3 (Power of Three) methodology. Tested on **7,264 bars** of real MES data with **proven profitability across all 5 strategies**.
---
## 🎯 What This Indicator Does
This indicator plots **dynamic standard deviation bands** around a moving average, identifying extreme price levels where institutional accumulation/distribution occurs. Based on statistical probability and market structure theory, it helps you:
✅ **Identify high-probability entry zones** (±1, ±1.5, ±2, ±2.5 STD)
✅ **Target realistic profit zones** (first opposite STD band)
✅ **Time your entries** with session-based filters (London/US)
✅ **Manage risk** with built-in stop loss levels
✅ **Choose your strategy** from 5 backtested approaches
---
## 🏆 Backtested Performance (Per Contract on MES)
### Strategy #1: Aggressive (±1.5 → ∓0.5) 🥇
- **Total Profit:** $95,287 over 1,452 trades
- **Win Rate:** 75%
- **Profit Factor:** 8.00
- **Target:** 80 ticks ($100) | **Stop:** 30 ticks ($37.50)
- **Best For:** Active traders, 3-5 setups/day
### Strategy #2: Mean Reversion (±1 → Mean) 🥈
- **Total Profit:** $90,000 over 2,322 trades
- **Win Rate:** 85% (HIGHEST)
- **Profit Factor:** 11.34 (BEST)
- **Target:** 40 ticks ($50) | **Stop:** 20 ticks ($25)
- **Best For:** Scalpers, 6-8 setups/day
### Strategy #3: Conservative (±2 → ∓1) 🥉
- **Total Profit:** $65,500 over 726 trades
- **Win Rate:** 70%
- **Profit Factor:** 7.04
- **Target:** 120 ticks ($150) | **Stop:** 40 ticks ($50)
- **Best For:** Patient traders, 1-3 setups/day, HIGHEST $/trade
*Full statistics for all 5 strategies included in documentation*
---
## 📈 Key Features
### Dynamic Standard Deviation Bands
- **±0.5 STD** - Intraday mean reversion zones
- **±1.0 STD** - Primary reversion zones (68% of price action)
- **±1.5 STD** - Extended zones (optimal balance)
- **±2.0 STD** - Extreme zones (95% of price action)
- **±2.5 STD** - Ultra-extreme zones (rare events)
- **Mean Line** - Dynamic equilibrium
### Temporal Session Filters
- **London Session** (3:00-11:30 AM ET) - Orange background
- **US Session** (9:30 AM-4:00 PM ET) - Blue background
- **Optimal Entry Window** (10:30 AM-12:00 PM ET) - Green highlight
- **Best Exit Window** (3:00-4:00 PM ET) - Red highlight
### Visual Trade Signals
- 🟢 **Green zones** = Enter LONG (price at lower bands)
- 🔴 **Red zones** = Enter SHORT (price at upper bands)
- 🎯 **Target lines** = Exit zones (opposite bands)
- ⛔ **Stop levels** = Risk management
### Smart Alerts
- Alert when price touches entry bands
- Alert on optimal time windows
- Alert when targets hit
- Customizable for each strategy
---
## 💡 How to Use
### Step 1: Choose Your Strategy
Select from 5 backtested approaches based on your:
- Risk tolerance (higher STD = larger stops)
- Trading frequency (lower STD = more setups)
- Time availability (different session focuses)
- Personality (scalper vs swing trader)
### Step 2: Apply to Chart
- **Timeframe:** 15-minute (tested and optimized)
- **Symbol:** MES, ES, or other liquid futures
- **Settings:** Adjust band colors, widths, alerts
### Step 3: Wait for Setup
Price touches your chosen entry band during optimal windows:
- **BEST:** 10:30 AM-12:00 PM ET (88% win rate!)
- **GOOD:** 12:00-3:00 PM ET (75-82% win rate)
- **AVOID:** Friday after 1 PM, FOMC Wed 2-4 PM
### Step 4: Execute Trade
- Enter when price touches band
- Set stop at indicated level
- Target first opposite band
- Exit at target or stop (no exceptions!)
### Step 5: Manage Risk
- **For $50K funded account ($250 limit): Use 2 MES contracts**
- Stop after 3 consecutive losses
- Reduce size in low-probability windows
- Track cumulative daily P&L
---
## 📅 Optimal Trading Windows
### By Time of Day
- **10:30 AM-12:00 PM ET:** 88% win rate (BEST) ⭐⭐⭐
- **12:00-1:30 PM ET:** 82% win rate (scalping)
- **1:30-3:00 PM ET:** 76% win rate (afternoon)
- **3:00-4:00 PM ET:** Best EXIT window
### By Day of Week
- **Wednesday:** 82% win rate (BEST DAY) ⭐⭐⭐
- **Tuesday:** 78% win rate (highest volume)
- **Thursday:**
SuperTrend Optimizer Remastered[CHE] SuperTrend Optimizer Remastered — Grid-ranked SuperTrend with additive or multiplicative scoring
Summary
This indicator evaluates a fixed grid of one hundred and two SuperTrend parameter pairs and ranks them by a simple flip-to-flip return model. It auto-selects the currently best-scoring combination and renders its SuperTrend in real time, with optional gradient coloring for faster visual parsing. The original concept is by KioseffTrading Thanks a lot for it.
For years I wanted to shorten the roughly two thousand three hundred seventy-one lines; I have now reduced the core to about three hundred eighty lines without triggering script errors. The simplification is generalizable to other indicators. A multiplicative return mode was added alongside the existing additive aggregation, enabling different rankings and often more realistic compounding behavior.
Motivation: Why this design?
SuperTrend is sensitive to its factor and period. Picking a single pair statically can underperform across regimes. This design sweeps a compact parameter grid around user-defined lower bounds, measures flip-to-flip outcomes, and promotes the combination with the strongest cumulative return. The approach keeps the visual footprint familiar while removing manual trial-and-error. The multiplicative mode captures compounding effects; the additive mode remains available for linear aggregation.
Originally (by KioseffTrading)
Very long script (~2,371 lines), monolithic structure.
SuperTrend optimization with additive (cumulative percentage-sum) scoring only.
Heavier use of repetitive code; limited modularity and fewer UI conveniences.
No explicit multiplicative compounding option; rankings did not reflect sequence-sensitive equity growth.
Now (remastered by CHE)
Compact core (~380 lines) with the same functional intent, no compile errors.
Adds multiplicative (compounding) scoring alongside additive, changing rankings to reflect real equity paths and penalize drawdown sequences.
Fixed 34×3 grid sweep, live ranking, gradient-based bar/wick/line visuals, top-table display, and an optional override plot.
Cleaner arrays/state handling, last-bar table updates, and reusable simplification pattern that can be applied to other indicators.
What’s different vs. standard approaches?
Baseline: A single SuperTrend with hand-picked inputs.
Architecture differences:
Fixed grid of thirty-four factor offsets across three ATR offsets.
Per-combination flip-to-flip backtest with additive or multiplicative aggregation.
Live ranking with optional “Best” or “Worst” table output.
Gradient bar, wick, and line coloring driven by consecutive trend counts.
Optional override plot to force a specific SuperTrend independent of ranking.
Practical effect: Charts show the currently best-scoring SuperTrend, not a static choice, plus an on-chart table of top performers for transparency.
How it works (technical)
For each parameter pair, the script computes SuperTrend value and direction. It monitors direction transitions and treats a change from up to down as a long entry and the reverse as an exit, measuring the move between entry and exit using close prices. Results are aggregated per pair either by summing percentage changes or by compounding return factors and then converting to percent for comparison. On the last bar, open trades are included as unrealized contributions to ranking. The best combination’s line is plotted, with separate styling for up and down regimes. Consecutive regime counts are normalized within a rolling window and mapped to gradients for bars, wicks, and lines. A two-column table reports the best or worst performers, with an optional row describing the parameter sweep.
Parameter Guide
Factor (Lower Bound) — Starting SuperTrend factor; the grid adds offsets between zero and three point three. Default three point zero. Higher raises distance to price and reduces flips.
ATR Period (Lower Bound) — Starting ATR length; the grid adds zero, one, and two. Default ten. Longer reduces noise at the cost of responsiveness.
Best vs Worst — Ranks by top or bottom cumulative return. Default Best. Use Worst for stress tests.
Calculation Mode — Additive sums percents; Multiplicative compounds returns. Multiplicative is closer to equity growth and can change the leaderboard.
Show in Table — “Top Three” or “All”. Fewer rows keep charts clean.
Show “Parameters Tested” Label — Displays the effective sweep ranges for auditability.
Plot Override SuperTrend — If enabled, the override factor and ATR are plotted instead of the ranked winner.
Override Factor / ATR Period — Values used when override is on.
Light Mode (for Table) — Adjusts table colors for bright charts.
Gradient/Coloring controls — Toggles for gradient bars and wick coloring, window length for normalization, gamma for contrast, and transparency settings. Use these to emphasize or tone down visual intensity.
Table Position and Text Size — Places the table and sets typography.
Reading & Interpretation
The auto SuperTrend plots one line for up regimes and one for down regimes. Color intensity reflects consecutive trend persistence within the chosen window. A small square at the bottom encodes the same gradient as a compact status channel. Optional wick coloring uses the same gradient for maximum contrast. The performance table lists parameter pairs and their cumulative return under the chosen aggregation; positive values are tinted with the up color, negative with the down color. “Long” labels mark flips that open a long in the simplified model.
Practical Workflows & Combinations
Trend following: Use the auto line as your primary bias. Enter on flips aligned with structure such as higher highs and higher lows. Filter with higher-timeframe trend or volatility contraction.
Exits/Stops: Consider conservative exits when color intensity fades or when the opposite line is approached. Aggressive traders can trail near the plotted line.
Override mode: When you want stability across instruments, enable override and standardize factor and ATR; keep the table visible for sanity checks.
Multi-asset/Multi-TF: Defaults travel well on liquid instruments and intraday to daily timeframes. Heavier assets may prefer larger lower bounds or multiplicative mode.
Behavior, Constraints & Performance
Repaint/confirmation: Signals are based on SuperTrend direction; confirmation is best assessed on closed bars to avoid mid-bar oscillation. No higher-timeframe requests are used.
Resources: One hundred and two SuperTrend evaluations per bar, arrays for state, and a last-bar table render. This is efficient for the grid size but avoid stacking many instances.
Known limits: The flip model ignores costs, slippage, and short exposure. Rapid whipsaws can degrade both aggregation modes. Gradients are cosmetic and do not change logic.
Sensible Defaults & Quick Tuning
Start with the provided lower bounds and “Top Three” table.
Too many flips → raise the lower bound factor or period.
Too sluggish → lower the bounds or switch to additive mode.
Rankings feel unstable → prefer multiplicative mode and extend the normalization window.
Visuals too strong → increase gradient transparency or disable wick coloring.
What this indicator is—and isn’t
This is a parameter-sweep and visualization layer for SuperTrend selection. It is not a complete trading system, not predictive, and does not include position sizing, transaction costs, or risk management. Combine with market structure, higher-timeframe context, and explicit risk controls.
Attribution and refactor note: The original work is by KioseffTrading. The script has been refactored from approximately two thousand three hundred seventy-one lines to about three hundred eighty core lines, retaining behavior without compiler errors. The general simplification pattern is reusable for other indicators.
Metadata
Name/Tag: SuperTrend Optimizer Remastered
Pine version: v6
Overlay or separate pane: true (overlay)
Core idea/principle: Grid-based SuperTrend selection by cumulative flip returns with additive or multiplicative aggregation.
Primary outputs/signals: Auto-selected SuperTrend up and down lines, optional override lines, gradient bar and wick colors, “Long” labels, performance table.
Inputs with defaults: See Parameter Guide above.
Metrics/functions used: SuperTrend, ATR, arrays, barstate checks, windowed normalization, gamma-based contrast adjustment, table API, gradient utilities.
Special techniques: Fixed grid sweep, compounding vs linear aggregation, last-bar UI updates, gradient encoding of persistence.
Performance/constraints: One hundred and two SuperTrend calls, arrays of length one hundred and two, label budget, last-bar table updates, no higher-timeframe requests.
Recommended use-cases/workflows: Trend bias selection, quick parameter audits, override standardization across assets.
Compatibility/assets/timeframes: Standard OHLC charts across intraday to daily; liquid instruments recommended.
Limitations/risks: Costs and slippage omitted; mid-bar instability possible; not suitable for synthetic chart types.
Debug/diagnostics: Ranking table, optional tested-range label; internal counters for consecutive trends.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
ICT Venom Trading Model [TradingFinder] SMC NY Session 2025SetupIntroduction
The ICT Venom Model is one of the most advanced strategies in the ICT framework, designed for intraday trading on major US indices such as US100, US30, and US500. This model is rooted in liquidity theory, time and price dynamics, and institutional order flow.
The Venom Model focuses on detecting Liquidity Sweeps, identifying Fair Value Gaps (FVG), and analyzing Market Structure Shifts (MSS). By combining these ICT core concepts, traders can filter false breakouts, capture sharp reversals, and align their entries with the real institutional liquidity flow during the New York Session.
Key Highlights of ICT Venom Model :
Intraday focus : Optimized for US indices (US100, US30, US500).
Time element : Critical window is 08:00–09:30 AM (Venom Box).
Liquidity sweep logic : Price grabs liquidity at 09:30 AM open.
Confirmation tools : MSS, CISD, FVG, and Order Blocks.
Dual setups : Works in both Bullish Venom and Bearish Venom conditions.
At its core, the ICT Venom Strategy is a framework that explains how institutional players manipulate liquidity pools by engineering false breakouts around the initial range of the market. Between 08:00 and 09:30 AM New York time, a range called the “Venom Box” is formed.
This range acts as a trap for retail traders, and once the 09:30 AM market open occurs, price usually sweeps either the high or the low of this box to collect stop-loss liquidity. After this liquidity grab, the market often reverses sharply, giving birth to a classic Bullish Venom Setup or Bearish Venom Setup
The Venom Model (ICT Venom Trading Strategy) is not just a pattern recognition tool but a precise institutional trading model based on time, liquidity, and market structure. By understanding the Initial Balance Range, watching for Liquidity Sweeps, and entering trades from FVG zones or Order Blocks, traders can anticipate market reversals with high accuracy. This strategy is widely respected among ICT followers because it offers both risk management discipline and clear entry/exit conditions. In short, the Venom Model transforms liquidity manipulation into actionable trading opportunities.
Bullish Setup :
Bearish Setup :
🔵 How to Use
The ICT Venom Model is applied by observing price behavior during the early hours of the New York session. The first step is to define the Initial Range, also called the Venom Box, which is formed between 08:00 and 09:30 AM EST. This range marks the high and low points where institutional traders often create traps for retail participants. Once the official market opens at 09:30 AM, price usually sweeps either the top or bottom of this box to collect liquidity.
After this liquidity grab, the market tends to reverse in alignment with the true directional bias. To confirm the setup, traders look for signals such as a Market Structure Shift (MSS), Change in State of Delivery (CISD), or the appearance of a Fair Value Gap (FVG). These elements validate the reversal and provide precise levels for trade execution.
🟣 Bullish Setup
In a Bullish Venom Setup, the market first sweeps the low of the Venom Box after 09:30 AM, triggering sell-side liquidity collection. This downward move is often sharp and deceptive, designed to stop out retail long positions and attract new sellers. Once liquidity is taken, the market typically shifts direction, forming an MSS or CISD that signals a reversal to the upside.
Traders then wait for price to retrace into a Fair Value Gap or a demand-side Order Block created during the reversal leg. This retracement offers the ideal entry point for long positions. Stop-loss placement should be just below the liquidity sweep low, while profit targets are set at the Venom Box high and, if momentum continues, at higher session or daily highs.
🟣 Bearish Setup
In a Bearish Venom Setup, the process is similar but reversed. After the Initial Range is defined, if price breaks above the Venom Box high following the 09:30 AM open, it signals a false breakout designed to collect buy-side liquidity. This move usually traps eager buyers and clears out stop-losses above the high.
After the liquidity sweep, confirmation comes through an MSS or CISD pointing to a reversal downward. At this stage, traders anticipate a retracement into a Fair Value Gap or a supply-side Order Block formed during the reversal. Short entries are taken within this zone, with stop-loss positioned just above the liquidity sweep high. The logical profit targets include the Venom Box low and, in stronger bearish momentum, deeper session or daily lows.
🔵 Settings
Refine Order Block : Enables finer adjustments to Order Block levels for more accurate price responses.
Mitigation Level OB : Allows users to set specific reaction points within an Order Block, including: Proximal: Closest level to the current price. 50% OB: Midpoint of the Order Block. Distal: Farthest level from the current price.
FVG Filter : The Judas Swing indicator includes a filter for Fair Value Gap (FVG), allowing different filtering based on FVG width: FVG Filter Type: Can be set to "Very Aggressive," "Aggressive," "Defensive," or "Very Defensive." Higher defensiveness narrows the FVG width, focusing on narrower gaps.
Mitigation Level FVG : Like the Order Block, you can set price reaction levels for FVG with options such as Proximal, 50% OB, and Distal.
CISD : The Bar Back Check option enables traders to specify the number of past candles checked for identifying the CISD Level, enhancing CISD Level accuracy on the chart.
🔵 Conclusion
The ICT Venom Model is more than just a reversal setup; it is a complete intraday trading framework that blends liquidity theory, time precision, and market structure analysis. By focusing on the Initial Range between 08:00 and 09:30 AM New York time and observing how price reacts at the 09:30 AM open, traders can identify liquidity sweeps that reveal institutional intentions.
Whether in a Bullish Venom Setup or a Bearish Venom Setup, the model allows for precise entries through Fair Value Gaps (FVGs) and Order Blocks, while maintaining clear risk management with well-defined stop-loss and target levels.
Ultimately, the ICT Venom Model provides traders with a structured way to filter false moves and align their trades with institutional order flow. Its strength lies in transforming liquidity manipulation into actionable opportunities, giving intraday traders an edge in timing, accuracy, and consistency. For those who master its logic, the Venom Model becomes not only a strategy for entry and exit, but also a deeper framework for understanding how liquidity truly drives price in the New York session.
Adaptive Machine Learning Trading System [PhenLabs]📊Adaptive ML Trading System
Version: PineScript™v6
📌Description
The Adaptive ML Trading System is a sophisticated machine learning indicator that combines ensemble modeling with advanced technical analysis. This system uses XGBoost, Random Forest, and Neural Network algorithms to generate high-confidence trading signals while incorporating robust risk management features. Traders benefit from objective, data-driven decision-making that adapts to changing market conditions.
🚀Points of Innovation
• Machine Learning Ensemble - Three integrated models (XGBoost, Random Forest, Neural Network)
• Confidence-Based Trading - Only executes trades when ML confidence exceeds threshold
• Dynamic Risk Management - ATR-based stop loss and max drawdown protection
• Adaptive Position Sizing - Volatility-adjusted position sizing with confidence weighting
• Real-Time Performance Metrics - Live tracking of win rate, Sharpe ratio, and performance
• Multi-Timeframe Feature Analysis - Adaptive lookback periods for different market regimes
🔧Core Components
• ML Ensemble Engine - Weighted combination of XGBoost, Random Forest, and Neural Network outputs
• Feature Normalization System - Advanced preprocessing with custom tanh/sigmoid activation
• Risk Management Module - Dynamic position sizing and drawdown protection
• Performance Dashboard - Real-time metrics and risk status monitoring
• Alert System - Comprehensive alert conditions for entries, exits, and risk events
🔥Key Features
• High-confidence ML signals with customizable confidence thresholds
• Multiple trading modes (Conservative, Balanced, Aggressive) for different risk profiles
• Integrated stop loss and risk management with ATR-based calculations
• Real-time performance metrics including win rate and Sharpe ratio
• Comprehensive alert system with entry, exit, and risk management notifications
• Visual confidence bands and threshold indicators for easy signal interpretation
🎨Visualization
• ML Signal Line - Primary signal output ranging from -1 to +1
• Confidence Bands - Visual representation of model confidence levels
• Threshold Lines - Customizable buy/sell threshold levels
• Position Histogram - Current market position visualization
• Performance Tables - Real-time metrics display in customizable positions
📖Usage Guidelines
Model Configuration
• Confidence Threshold: Default 0.55, Range 0.5-0.95 - Minimum confidence for signals
• Model Sensitivity: Default 0.9, Range 0.1-2.0 - Adjusts signal sensitivity
• Ensemble Mode: Conservative/Balanced/Aggressive - Trading style preference
• Signal Threshold: Default 0.55, Range 0.3-0.9 - ML signal threshold for entries
Risk Management
• Position Size %: Default 10%, Range 1-50% - Portfolio percentage per trade
• Max Drawdown %: Default 15%, Range 5-30% - Maximum allowed drawdown
• Stop Loss ATR: Default 2.0, Range 0.5-5.0 - Stop loss in ATR multiples
• Dynamic Sizing: Default true - Volatility-based position adjustment
Display Settings
• Show Signals: Default true - Display entry/exit signals
• Show Threshold Signals: Default true - Display ±0.6 threshold crosses
• Show Confidence Bands: Default true - Display ML confidence levels
• Performance Dashboard: Default true - Show metrics table
✅Best Use Cases
• Swing trading with 1-5 day holding periods
• Trend-following strategies in established trends
• Volatility breakout trading during high-confidence periods
• Risk-adjusted position sizing for portfolio management
• Multi-timeframe confirmation for existing strategies
⚠️Limitations
• Requires sufficient historical data for accurate ML predictions
• May experience low confidence periods in choppy markets
• Performance varies across different asset classes and timeframes
• Not suitable for very short-term scalping strategies
• Requires understanding of basic risk management principles
💡What Makes This Unique
• True machine learning ensemble with multiple model types
• Confidence-based trading rather than simple signal generation
• Integrated risk management with dynamic position sizing
• Real-time performance tracking and metrics
• Adaptive parameters that adjust to market conditions
🔬How It Works
Feature Calculation: Computes 20+ technical features from price/volume data
Feature Normalization: Applies custom normalization for ML compatibility
Ensemble Prediction: Combines XGBoost, Random Forest, and Neural Network outputs
Signal Generation: Produces confidence-weighted trading signals
Risk Management: Applies position sizing and stop loss rules
Execution: Generates alerts and visual signals based on thresholds
💡Note:
This indicator works best on daily and 4-hour timeframes for most assets. Ensure you understand the risk management settings before live trading. The system includes automatic risk-off modes that halt trading during excessive drawdown periods.
Relative Performance Indicator - TrendSpider StyleRelative Performance Indicator - TrendSpider Style
📈 Overview
This Relative Performance (RP) indicator measures how your stock is performing compared to a benchmark index, displayed as a percentile ranking from 0-100. Based on TrendSpider's methodology, it answers the critical question: "Is this stock a leader or a laggard?"
Unlike simple ratio charts, this indicator uses percentile ranking to normalize relative performance, making it easy to identify when a stock is showing exceptional strength (>80) or concerning weakness (<20) compared to its historical relationship with the benchmark.
✨ Key Features
Three Calculation Modes:
Quarterly: 3-month relative performance for swing trading
Yearly: Weighted 4-quarter performance for position trading
TechRank: Composite of 6 technical indicators for multi-factor analysis
Clean Visual Design:
Green fills above 80 (strong outperformance)
Red fills below 20 (significant underperformance)
Dotted median line at 50 for quick reference
Current value label for instant reading
Flexible Benchmarks:
Compare against major indices (SPY, QQQ, IWM)
Sector ETFs for within-sector analysis
Custom symbols for specialized comparisons
Built-in Alerts:
Strong performance zone entry (>80)
Weak performance zone entry (<20)
Median crossovers (50 level)
📊 How To Use
Buy Signals:
RP crosses above 80: Stock entering leadership status
RP holding above 60: Maintaining relative strength
RP rising while price consolidating: Accumulation phase
Sell/Avoid Signals:
RP drops below 50: Losing relative strength
RP below 20: Significant underperformance
RP falling while price rising: Bearish divergence
Sector Rotation:
Compare multiple assets to find strongest sectors
Rotate into high RP assets (>70)
Exit low RP positions (<30)
🎯 Reading The Values
80-100: Exceptional outperformance - Strong buy/hold
60-80: Moderate outperformance - Hold positions
40-60: Market perform - No edge
20-40: Underperformance - Caution/reduce
0-20: Severe underperformance - Avoid/exit
⚙️ Calculation Method
Calculates percentage performance of both your stock and the benchmark
Finds the performance differential
Ranks this differential against historical values using percentile analysis
Normalizes to 0-100 scale for easy interpretation
This percentile approach adapts to different market conditions and volatility regimes, providing consistent signals whether in trending or choppy markets.
💡 Pro Tips
For Growth Stocks: Use quarterly mode with QQQ as benchmark
For Value Stocks: Use yearly mode with SPY as benchmark
For Small Caps: Compare against IWM, not SPY
For Sector Analysis: Use sector ETFs (XLK, XLF, XLE, etc.)
Combine with Price Action: High RP + price breakout = powerful signal
⚠️ Important Notes
RP is relative, not absolute - stocks can fall with high RP if the market falls harder
Choose appropriate benchmarks for meaningful comparisons
Best used in conjunction with price action and volume analysis
Historical lookback period affects sensitivity (adjustable in settings)
🔧 Customization
Fully customizable visual settings, thresholds, calculation periods, and smoothing options. Adjust the normalization lookback period (default 252 days) to fine-tune sensitivity to your trading timeframe.
📌 Credit
Inspired by TrendSpider's Relative Performance implementation, adapted for TradingView with enhanced customization options and Pine Script v6 optimization.
Tags to include: relativeperformance, relativestrength, percentile, ranking, sectorrotation, benchmark, outperformance, trendspider, marketbreadth, strengthindicator
Category: Momentum Indicators / Trend Analysis
Feel free to modify this description to match your style or add any specific points you want to emphasize!
CNagda-MomentumX - Institutional FlowMomentumX is designed to empower traders with a deeper understanding of market movements by focusing on Institutional Flow and advanced market structure analytics. The core goal is to identify and visualize where major market participants are operating, and to translate these complex footprints into clear, actionable trading signals — all in real time.
Real-time institutional activity mapping
Actionable entry and exit signals based on live market structure
Intuitive dashboard and dynamic chart visuals
Fully customizable modules for trend, liquidity, and order blocks
Core Logic Design
At the heart of MomentumX lies a robust algorithmic engine built to capture and surface institutional trading behavior. By leveraging advanced mathematical models, the indicator calculates institutional volume ratios and price momentum to pinpoint aggressive moves from large participants.
Institutional Volume & Price Momentum:
Utilizes custom volume indicators and price change analysis to detect strong buying or selling pressure, filtering out retail noise.
Liquidity Grab Detection & Activity Zones:
The script identifies liquidity grabs by monitoring abrupt price sweeps at major support/resistance levels—often where institutions trigger stop hunts or reversals. All critical activity zones are automatically color-coded on the chart for instant recognition.
Dashboard Visualization:
A fully dynamic dashboard table overlays live scores for accumulation, distribution, strength, and weakness—giving traders a real-time scan of market health.
Trendline & Order Block Architecture:
The logic auto-detects pivot highs/lows to draw smart trendlines, while the order block system highlights key reversal areas and breaker zones—making market structure clear and actionable.
MomentumX is packed with high-performance modules, each engineered to simplify complex market behavior and enhance decision-making for traders:
Institutional Flow Signals:
Instantly identifies spots where institutional players drive momentum, using unique volume and price activity analytics.
Bullish/Bearish Liquidity Grab Detection:
Marks abrupt price moves that signal stop hunts or reversals, letting traders anticipate snap-backs or trend shifts.
Trendline Auto-Detection:
Smartly draws trendlines based on significant swing highs and lows, automatically adjusting as price evolves.
Order Block System (Rejection/Breaker):
Spots and highlights key reversal zones with order block rectangles, confirming rejections or breakouts at strategic levels.
Dashboard and Bar Coloring:
A clean dashboard overlay presents live market scores, while dynamic bar coloring makes trend, strength, and high-activity periods instantly visible.
User Input Toggles for Each Module:
Every major feature is fully customizable—enable or disable modules to match individual trading setups or preferences.
Scripting/Development
MomentumX’s scripting process is modular, enabling clarity, scalability, and fast optimization throughout development:
Initialization & Inputs:
Start by defining all user input options, module toggles, color settings, and calculation parameters—ensuring maximum flexibility early on.
Core Calculation Functions:
Script advanced institutional volume and price momentum algorithms. Build out swing length logic, market state filters, and activity scoring methods.
Detection Engines:
Develop and integrate engines for liquidity grabs, automated trendline detection, and order block identification—each with dedicated functions for speed and precision.
Visual Overlays & Plotting:
Implement powerful plotting logic for colored bars, score dashboards, trendlines, reversal zones, and liquidity markers—making every data point clear and actionable on the chart.
Testing Handlers:
Add diagnostic panels and debug outputs to refine calculations and assure accuracy in every market environment.
Sample Trade Setups (Usage)
Cnagda MomentumX delivers clarity for multiple trading styles by providing timely, actionable setups grounded in institutional behavior and market structure. Here’s how traders can leverage the indicator for confident decision-making:
Liquidity Grab Reversal
Enter trades around detected liquidity grabs when price sweeps major support/resistance and the dashboard signals a momentum shift.
Example: Wait for a bullish/Bearish grab near market lows/high, with institutional flow turning positive/negative—enter long/short for potential mean reversion.
Order Block Breakout
Trade breakouts when price cleanly rejects or flips key order block zones highlighted on the chart.
Example: Short at a marked breaker block after a rejection signal, confirmed by a downward institutional activity spike.
Trendline Continuation
Ride established market moves by entering on trendline confirmations plotted by the auto-detect system.
Example: Go long after a trendline retest, confirmed by a green bar color and dashboard strength score.
Dashboard Confirmation
Combine dashboard metrics (strength, accumulation, distribution) with bar color overlays for multi-factor entries.
Example: Enter trades only when all market signals align in real time for maximum probability.
For Short Entry check -- Weakness : For Long Entry Check - Strength With Other Indications
MomentumX is not just another indicator – it’s your edge for reading the market like an insider. By transparently mapping institutional flow, uncovering hidden liquidity zones, and color-coding every major structure shift, MomentumX transforms complexity into actionable clarity. Whether you’re scalping, swing trading, or investing, you’ll gain a decisive, real-time advantage on every chart.
Embrace smarter decisions, adapt to changing market conditions instantly, and join a new generation of technically empowered traders.
Customize, observe, and let the market reveal opportunities in a way you’ve never experienced before.
Happy Trading
MACD Forecast [Titans_Invest]MACD Forecast — The Future of MACD in Trading
The MACD has always been one of the most powerful tools in technical analysis.
But what if you could see where it’s going, instead of just reacting to what has already happened?
Introducing MACD Forecast — the natural evolution of the MACD Full , now taken to the next level. It’s the world’s first MACD designed not only to analyze the present but also to predict the future behavior of momentum.
By combining the classic MACD structure with projections powered by Linear Regression, this indicator gives traders an anticipatory, predictive view, redefining what’s possible in technical analysis.
Forget lagging indicators.
This is the smartest, most advanced, and most accurate MACD ever created.
🍟 WHY MACD FORECAST IS REVOLUTIONARY
Unlike the traditional MACD, which only reflects current and past price dynamics, the MACD Forecast uses regression-based projection models to anticipate where the MACD line, signal line, and histogram are heading.
This means traders can:
• See MACD crossovers before they happen.
• Spot trend reversals earlier than most.
• Gain an unprecedented timing advantage in both discretionary and automated trading.
In other words: this indicator lets you trade ahead of time.
🔮 FORECAST ENGINE — POWERED BY LINEAR REGRESSION
At its core, the MACD Forecast integrates Linear Regression (ta.linreg) to project the MACD’s future behavior with exceptional accuracy.
Projection Modes:
• Flat Projection: Assumes trend continuity at the current level.
• LinReg Projection: Applies linear regression across N periods to mathematically forecast momentum shifts.
This dual system offers both a conservative and adaptive view of market direction.
📐 ACCURACY WITH FULL CUSTOMIZATION
Just like the MACD Full, this new version comes with 20 customizable buy-entry conditions and 20 sell-entry conditions — now enhanced with forecast-based rules that anticipate crossovers and trend reversals.
You’re not just reacting — you’re strategizing ahead of time.
⯁ HOW TO USE MACD FORECAST❓
The MACD Forecast is built on the same foundation as the classic MACD, but with predictive capabilities.
Step 1 — Spot Predicted Crossovers:
Watch for forecasted bullish or bearish crossovers. These signals anticipate when the MACD line will cross the signal line in the future, letting you prepare trades before the move.
Step 2 — Confirm with Histogram Projection:
Use the projected histogram to validate momentum direction. A rising histogram signals strengthening bullish momentum, while a falling projection points to weakening or bearish conditions.
Step 3 — Combine with Multi-Timeframe Analysis:
Use forecasts across multiple timeframes to confirm signal strength (e.g., a 1h forecast aligned with a 4h forecast).
Step 4 — Set Entry Conditions & Automation:
Customize your buy/sell rules with the 20 forecast-based conditions and enable automation for bots or alerts.
Step 5 — Trade Ahead of the Market:
By preparing for future momentum shifts instead of reacting to the past, you’ll always stay one step ahead of lagging traders.
🤖 BUILT FOR AUTOMATION AND BOTS 🤖
Whether for manual trading, quantitative strategies, or advanced algorithms, the MACD Forecast was designed to integrate seamlessly with automated systems.
With predictive logic at its core, your strategies can finally react to what’s coming, not just what already happened.
🥇 WHY THIS INDICATOR IS UNIQUE 🥇
• World’s first MACD with Linear Regression Forecasting
• Predictive Crossovers (before they appear on the chart)
• Maximum flexibility with Long & Short combinations — 20+ fully configurable conditions for tailor-made strategies
• Fully automatable for quantitative systems and advanced bots
This isn’t just an update.
It’s the final evolution of the MACD.
______________________________________________________
🔹 CONDITIONS TO BUY 📈
______________________________________________________
• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
🔹 MACD > Signal Smoothing
🔹 MACD < Signal Smoothing
🔹 Histogram > 0
🔹 Histogram < 0
🔹 Histogram Positive
🔹 Histogram Negative
🔹 MACD > 0
🔹 MACD < 0
🔹 Signal > 0
🔹 Signal < 0
🔹 MACD > Histogram
🔹 MACD < Histogram
🔹 Signal > Histogram
🔹 Signal < Histogram
🔹 MACD (Crossover) Signal
🔹 MACD (Crossunder) Signal
🔹 MACD (Crossover) 0
🔹 MACD (Crossunder) 0
🔹 Signal (Crossover) 0
🔹 Signal (Crossunder) 0
🔮 MACD (Crossover) Signal Forecast
🔮 MACD (Crossunder) Signal Forecast
______________________________________________________
______________________________________________________
🔸 CONDITIONS TO SELL 📉
______________________________________________________
• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND or OR .
🔸 MACD > Signal Smoothing
🔸 MACD < Signal Smoothing
🔸 Histogram > 0
🔸 Histogram < 0
🔸 Histogram Positive
🔸 Histogram Negative
🔸 MACD > 0
🔸 MACD < 0
🔸 Signal > 0
🔸 Signal < 0
🔸 MACD > Histogram
🔸 MACD < Histogram
🔸 Signal > Histogram
🔸 Signal < Histogram
🔸 MACD (Crossover) Signal
🔸 MACD (Crossunder) Signal
🔸 MACD (Crossover) 0
🔸 MACD (Crossunder) 0
🔸 Signal (Crossover) 0
🔸 Signal (Crossunder) 0
🔮 MACD (Crossover) Signal Forecast
🔮 MACD (Crossunder) Signal Forecast
______________________________________________________
______________________________________________________
🔮 Linear Regression Function 🔮
______________________________________________________
• Our indicator includes MACD forecasts powered by linear regression.
Forecast Types:
• Flat: Assumes prices will stay the same.
• Linreg: Makes a 'Linear Regression' forecast for n periods.
Technical Information:
• Function: ta.linreg()
Parameters:
• source: Source price series.
• length: Number of bars (period).
• offset : Offset.
• return: Linear regression curve.
______________________________________________________
______________________________________________________
⯁ UNIQUE FEATURES
______________________________________________________
Linear Regression: (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
Linear Regression (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
______________________________________________________
📜 SCRIPT : MACD Forecast
🎴 Art by : @Titans_Invest & @DiFlip
👨💻 Dev by : @Titans_Invest & @DiFlip
🎑 Titans Invest — The Wizards Without Gloves 🧤
✨ Enjoy!
______________________________________________________
o Mission 🗺
• Inspire Traders to manifest Magic in the Market.
o Vision 𐓏
• To elevate collective Energy 𐓷𐓏
🎗️ In memory of João Guilherme — your light will live on forever.
RXTrend█ OVERVIEW
The "RXTrend" indicator is a technical analysis tool based on a unique approach to trend identification using RSI values from overbought and oversold zones. Designed for traders seeking a precise tool to identify key market levels and trend direction, the indicator offers flexible settings, dynamic trend lines, candlestick coloring, and buy/sell signals, supported by alerts for key events.
█ CONCEPTS
"RXTrend" leverages the Relative Strength Index (RSI) to identify overbought and oversold zones, which are often significant areas on the chart due to potentially higher volume, increased volatility, or acting as pivot points. To address this, I created an indicator that uses RSI values from these zones, mapping them to price levels to determine the trend. Additionally, for a clearer market picture, boxes are added to highlight overbought and oversold zones on the chart, and candlestick coloring is based on the direction of the RSI moving average. This provides further confirmation of the trend direction and identifies potential correction or reversal points. The indicator is universal and works across all markets (stocks, forex, cryptocurrencies) and timeframes.
█ FEATURES
- RSI Calculation: Calculates RSI based on the closing price over a specified period, with a default length of 14.
- Trend Line: A smoothed trend line based on mapping RSI values from overbought (for downtrends) or oversold (for uptrends) zones to price levels. RSI values are transformed into prices using the price range from a selected period (default: 50 bars) and then smoothed to form the trend line. The line changes color based on the trend direction (blue for uptrend, orange for downtrend).
- Candlestick Coloring: Option to color candles based on the direction of the RSI moving average (RSI MA). Candle colors align with the trend and box colors (blue for uptrend, orange for downtrend, gray for neutral).
- Overbought and Oversold Zones: Identifies overbought (RSI > OB) and oversold (RSI < OS) levels, drawing dynamic boxes on the price chart to reflect these zones. Boxes update in real-time, adjusting to new highs and lows.
- Buy and Sell Signals: Generates buy signals (blue "Buy" labels) when the price crosses above the smoothed oversold line and sell signals (orange "Sell" labels) when the price crosses below the smoothed overbought line.
- Shadow Fill: Option to fill the space between the trend line and price (HL2) with adjustable transparency, aiding visual trend assessment.
Alerts: Built-in alerts for:
- Buy and sell signals.
- Appearance of new overbought/oversold boxes.
- RSI MA direction change (candle color change to uptrend or downtrend).
Customization: Allows adjustment of RSI length, overbought/oversold levels, smoothing period, colors, box and label transparency, and the option to keep boxes after RSI returns to normal.
█ HOW TO USE
Add to Chart: Apply the indicator to your TradingView chart via the Pine Editor or Indicators menu.
Configure Settings:
RSI Settings:
- RSI Length: Sets the RSI calculation period (default: 14).
- Overbought Level (OB): Sets the overbought threshold (default: 70).
- Oversold Level (OS): Sets the oversold threshold (default: 30).
Price Settings:
- Price Range Lookback: Defines the period for calculating the price range (default: 50).
Candle Coloring:
- Color Candles: Enables/disables candle coloring based on RSI MA direction.
- RSI MA Length: Sets the RSI moving average period (default: 21).
Smoothing Settings:
- Smoothing Length: Degree of trend line smoothing (default: 5).
Colors:
- Trend Colors: Customize colors for uptrend (default: blue), downtrend (default: orange), and shadow fill.
Box Settings:
- Box Transparency: Adjusts box transparency (0-100).
- Box Colors: Sets colors for overbought (orange) and oversold (blue) zones.
- Keep Boxes: Determines if boxes remain after RSI returns to normal.
Signals:
- Show Buy/Sell Signals: Enables/disables signal label display.
- Label Transparency: Adjusts signal label transparency.
Interpreting Signals:
- Trend Line: Shows market direction (blue for uptrend, orange for downtrend).
- Buy Signals: Blue "Buy" label appears when the price crosses above the smoothed oversold line, signaling a potential uptrend.
- Sell Signals: Orange "Sell" label appears when the price crosses below the smoothed overbought line, signaling a potential downtrend.
- Overbought/Oversold Boxes: Orange boxes indicate overbought zones (RSI > OB), blue boxes indicate oversold zones (RSI < OS). Boxes expand dynamically in real-time.
- Candlestick Coloring: Candle colors align with the trend and box colors, reflecting RSI MA direction.
- Alerts: Set up alerts in TradingView for buy/sell signals, new overbought/oversold boxes, or RSI MA direction changes.
- Combining with Other Tools: Use the indicator alongside support/resistance levels, Fair Value Gaps (FVG), or other indicators to confirm signals.
█ APPLICATIONS
The "RXTrend" indicator is designed to identify key market zones and trend direction, making it useful for trend-following and reversal strategies. It enables:
- Trend Confirmation: Candlestick coloring and the trend line help assess the dominant market direction, supporting entry or exit decisions. The trend line can act as a significant support/resistance level, and a price bounce from it may provide a good entry point, especially when confirmed by Fibonacci levels. Additionally, the appearance of overbought/oversold boxes combined with a change in candle color (RSI MA direction) may indicate an impending correction. This allows analysis of potential market overextension and correction endings, enabling multiple entries within a trend.
- Overbought and Oversold Zone Identification: Boxes highlight potential reversal or correction points, especially when combined with support/resistance levels or FVG.
- Signal-Based Strategies: Buy and sell signals can be used as entry points in a trend or as warnings of potential reversals.
█ NOTES
- The indicator is universal and works across all markets and timeframes due to its RSI-based and price-mapping logic.
- Adjust settings (e.g., RSI length, OB/OS levels, smoothing) to suit your trading style and timeframe.
- Use in conjunction with other technical analysis tools to enhance signal accuracy.
BayesStack RSI [CHE]BayesStack RSI — Stacked RSI with Bayesian outcome stats and gradient visualization
Summary
BayesStack RSI builds a four-length RSI stack and evaluates it with a simple Bayesian success model over a rolling window. It highlights bull and bear stack regimes, colors price with magnitude-based gradients, and reports per-regime counts, wins, and estimated win rate in a compact table. Signals seek to be more robust through explicit ordering tolerance, optional midline gating, and outcome evaluation that waits for events to mature by a fixed horizon. The design focuses on readable structure, conservative confirmation, and actionable context rather than raw oscillator flips.
Motivation: Why this design?
Classical RSI signals flip frequently in volatile phases and drift in calm regimes. Pure threshold rules often misclassify shallow pullbacks and stacked momentum phases. The core idea here is ordered, spaced RSI layers combined with outcome tracking. By requiring a consistent order with a tolerance and optionally gating by the midline, regime identification becomes clearer. A horizon-based maturation check and smoothed win-rate estimate provide pragmatic feedback about how often a given stack has recently worked.
What’s different vs. standard approaches?
Reference baseline: Traditional single-length RSI with overbought and oversold rules or simple crossovers.
Architecture differences:
Four fixed RSI lengths with strict ordering and a spacing tolerance.
Optional requirement that all RSI values stay above or below the midline for bull or bear regimes.
Outcome evaluation after a fixed horizon, then rolling counts and a prior-smoothed win rate.
Dispersion measurement across the four RSIs with a percent-rank diagnostic.
Gradient coloring of candles and wicks driven by stack magnitude.
A last-bar statistics table with counts, wins, win rate, dispersion, and priors.
Practical effect: Charts emphasize sustained momentum alignment instead of single-length crosses. Users see when regimes start, how strong alignment is, and how that regime has recently performed for the chosen horizon.
How it works (technical)
The script computes RSI on four lengths and forms a “stack” when they are strictly ordered with at least the chosen tolerance between adjacent lengths. A bull stack requires a descending set from long to short with positive spacing. A bear stack requires the opposite. Optional gating further requires all RSI values to sit above or below the midline.
For evaluation, each detected stack is checked again after the horizon has fully elapsed. A bull event is a success if price is higher than it was at event time after the horizon has passed. A bear event succeeds if price is lower under the same rule. Rolling sums over the training window track counts and successes; a pair of priors stabilizes the win-rate estimate when sample sizes are small.
Dispersion across the four RSIs is measured and converted to a percent rank over a configurable window. Gradients for bars and wicks are normalized over a lookback, then shaped by gamma controls to emphasize strong regimes. A statistics table is created once and updated on the last bar to minimize overhead. Overlay markers and wick coloring are rendered to the price chart even though the indicator runs in a separate pane.
Parameter Guide
Source — Input series for RSI. Default: close. Tips: Use typical price or hlc3 for smoother behavior.
Overbought / Oversold — Guide levels for context. Defaults: seventy and thirty. Bounds: fifty to one hundred, zero to fifty. Tips: Narrow the band for faster feedback.
Stacking tolerance (epsilon) — Minimum spacing between adjacent RSIs to qualify as a stack. Default: zero point twenty-five RSI points. Trade-off: Higher values reduce false stacks but delay entries.
Horizon H — Bars ahead for outcome evaluation. Default: three. Trade-off: Longer horizons reduce noise but delay success attribution.
Rolling window — Lookback for counts and wins. Default: five hundred. Trade-off: Longer windows stabilize the win rate but adapt more slowly.
Alpha prior / Beta prior — Priors used to stabilize the win-rate estimate. Defaults: one and one. Trade-off: Larger priors reduce variance with sparse samples.
Show RSI 8/13/21/34 — Toggle raw RSI lines. Default: on.
Show consensus RSI — Weighted combination of the four RSIs. Default: on.
Show OB/OS zones — Draw overbought, oversold, and midline. Default: on.
Background regime — Pane background tint during bull or bear stacks. Default: on.
Overlay regime markers — Entry markers on price when a stack forms. Default: on.
Show statistics table — Last-bar table with counts, wins, win rate, dispersion, priors, and window. Default: on.
Bull requires all above fifty / Bear requires all below fifty — Midline gate. Defaults: both on. Trade-off: Stricter regimes, fewer but cleaner signals.
Enable gradient barcolor / wick coloring — Gradient visuals mapped to stack magnitude. Defaults: on. Trade-off: Clearer regime strength vs. extra rendering cost.
Collection period — Normalization window for gradients. Default: one hundred. Trade-off: Shorter values react faster but fluctuate more.
Gamma bars and shapes / Gamma plots — Curve shaping for gradients. Defaults: zero point seven and zero point eight. Trade-off: Higher values compress weak signals and emphasize strong ones.
Gradient and wick transparency — Visual opacity controls. Defaults: zero.
Up/Down colors (dark and neon) — Gradient endpoints. Defaults: green and red pairs.
Fallback neutral candles — Directional coloring when gradients are off. Default: off.
Show last candles — Limit for gradient squares rendering. Default: three hundred thirty-three.
Dispersion percent-rank length / High and Low thresholds — Window and cutoffs for dispersion diagnostics. Defaults: two hundred fifty, eighty, and twenty.
Table X/Y, Dark theme, Text size — Table anchor, theme, and typography. Defaults: right, top, dark, small.
Reading & Interpretation
RSI stack lines: Alignment and spacing convey regime quality. Wider spacing suggests stronger alignment.
Consensus RSI: A single line that summarizes the four lengths; use as a smoother reference.
Zones: Overbought, oversold, and midline provide context rather than standalone triggers.
Background tint: Indicates active bull or bear stack.
Markers: “Bull Stack Enter” or “Bear Stack Enter” appears when the stack first forms.
Gradients: Brighter tones suggest stronger stack magnitude; dull tones suggest weak alignment.
Table: Count and Wins show sample size and successes over the window. P(win) is a prior-stabilized estimate. Dispersion percent rank near the high threshold flags stretched alignment; near the low threshold flags tight clustering.
Practical Workflows & Combinations
Trend following: Enter only on new stack markers aligned with structure such as higher highs and higher lows for bull, or lower lows and lower highs for bear. Use the consensus RSI to avoid chasing into overbought or oversold extremes.
Exits and stops: Consider reducing exposure when dispersion percent rank reaches the high threshold or when the stack loses ordering. Use the table’s P(win) as a context check rather than a direct signal.
Multi-asset and multi-timeframe: Defaults travel well on liquid assets from intraday to daily. Combine with higher-timeframe structure or moving averages for regime confirmation. The script itself does not fetch higher-timeframe data.
Behavior, Constraints & Performance
Repaint and confirmation: Stack markers evaluate on the live bar and can flip until close. Alert behavior follows TradingView settings. Outcome evaluation uses matured events and does not look into the future.
HTF and security: Not used. Repaint paths from higher-timeframe aggregation are avoided by design.
Resources: max bars back is two thousand. The script uses rolling sums, percent rank, gradient rendering, and a last-bar table update. Shapes and colored wicks add draw overhead.
Known limits: Lag can appear after sharp turns. Very small windows can overfit recent noise. P(win) is sensitive to sample size and priors. Dispersion normalization depends on the collection period.
Sensible Defaults & Quick Tuning
Start with the shipped defaults.
Too many flips: Increase stacking tolerance, enable midline gates, or lengthen the collection period.
Too sluggish: Reduce stacking tolerance, shorten the collection period, or relax midline gates.
Sparse samples: Extend the rolling window or increase priors to stabilize P(win).
Visual overload: Disable gradient squares or wick coloring, or raise transparency.
What this indicator is—and isn’t
This is a visualization and context layer for RSI stack regimes with simple outcome statistics. It is not a complete trading system, not predictive, and not a signal generator on its own. Use it with market structure, risk controls, and position management that fit your process.
Metadata
- Pine version: v6
- Overlay: false (price overlays are drawn via forced overlay where applicable)
- Primary outputs: Four RSI lines, consensus line, OB/OS guides, background tint, entry markers, gradient bars and wicks, statistics table
- Inputs with defaults: See Parameter Guide
- Metrics and functions used: RSI, rolling sums, percent rank, dispersion across RSI set, gradient color mapping, table rendering, alerts
- Special techniques: Ordered RSI stacking with tolerance, optional midline gating, horizon-based outcome maturation, prior-stabilized win rate, gradient normalization with gamma shaping
- Performance and constraints: max bars back two thousand, rendering of shapes and table on last bar, no higher-timeframe data, no security calls
- Recommended use-cases: Regime confirmation, momentum alignment, post-entry management with dispersion and recent outcome context
- Compatibility: Works across assets and timeframes that support RSI
- Limitations and risks: Sensitive to parameter choices and market regime changes; not a standalone strategy
- Diagnostics: Statistics table, dispersion percent rank, gradient intensity
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Best regards and happy trading
Chervolino.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
BBKC Combined Channels OverlayBBKC Combined Channels Overlay (Volatility & Mean Reversion)This indicator provides a clean, single-view envelope combining the Bollinger Bands (BB) and Keltner Channels (KC) directly onto your price chart. It is an essential tool for traders operating with Volatility Compression (The Squeeze) and Mean Reversion strategies in fast-moving markets like Futures, High BTC Beta Equities, and Crypto. The goal of this tool is twofold: to visually frame the market's current volatility state and to identify high-probability entry points based on expansion or extreme contraction. How to Use the BBKC Overlay: Spotting the Squeeze (Accumulation Phase):The Squeeze is identified when the Bollinger Bands (BB) contract and fit inside the Keltner Channels (KC).The area is clearly marked with a subtle Orange Background Highlight on the main chart. This is the Accumulation phase, signaling low volatility before a potential large directional move. Trading Mean Reversion: When price pushes aggressively outside the outermost bands (the BB Upper/Lower), it signals an extreme volatility expansion and over-extension. This is a strong setup for mean reversion—a high-probability trade targeting a snap-back towards the central Basis Line (SMA).Customizing for Extreme Compression: For traders looking only for the tightest, highest-probability Squeezes, adjust the following setting: KC Multiplier (ATR): Lower this value from the default of 1.5 down to 1.25 or 1.0. This narrows the KC, forcing the Bollinger Bands to contract even further to trigger the Squeeze signal, thus filtering for only the most minimal volatility. Recommended Synergy: For a complete volatility system, pair this BBKC Combined Channels Overlay (your visualization tool) with the BBKC Squeeze Indicator (the sub-pane momentum histogram).Overlay (Main Chart): Shows where the Squeeze is occurring and identifies mean reversion targets. Squeeze Indicator (Lower Pane): Shows if the Squeeze is active and the directional momentum building up, helping you time the breakout entry for the Manipulation/Distribution phase.
