Quantile-Based Adaptive Detection🙏🏻 Dedicated to John Tukey. He invented the boxplot, and I finalized it.
QBAD (Quantile-Based Adaptive Detection) is ‘the’ adaptive (also optionally weighted = ready for timeseries) boxplot with more senseful fences. Instead of hardcoded multipliers for outer fences, I base em on a set of quantile-based asymmetry metrics (you can view it as an ‘algorithmic’ counter part of central & standardized moments). So outer bands are Not hardcoded, not optimized, not cross-validated etc, simply calculated at O(nlogn).
You can use it literally everywhere in any context with any continuous data, in any task that requires statistical control, novelty || outlier detection, without worrying and doubting the sense in arbitrary chosen thresholds. Obviously, given the robust nature of quantiles, it would fit best the cases where data has problems.
The thresholds are:
Basis: the model of the data (median in our case);
Deviations: represent typical spread around basis, together form “value” in general sense;
Extensions: estimate data’s extremums via combination of quantile-based asymmetry metrics without relying on actual blunt min and max, together form “range” / ”frame”. Datapoints outside the frame/range are novelties or outliers;
Limits: based also on quantile asymmetry metrics, estimate the bounds within which values can ‘ever’ emerge given the current data generating process stays the same, together form “field”. Datapoints outside the field are very rare, happen when a significant change/structural break happens in current data-generating process, or when a corrupt datapoint emerges.
…
The first part of the post is for locals xd, the second is for the wanderers/wizards/creators/:
First part:
In terms of markets, mostly u gotta worry about dem instruments that represent crypto & FX assets: it’s either activity hence data sources there are decentralized, or data is fishy.
For a higher algocomplexity cost O(nlong), unlike MBAD that is 0(n), this thing (a control system in fact) works better with ishy data (contaminated with wrong values, incomplete, missing values etc). Read about the “ breakdown point of an estimator ” if you wanna understand it.
Even with good data, in cases when you have multiple instruments that represent the same asset, e.g. CL and BRN futures, and for some reason you wanna skip constructing a proper index of em (while you should), QBAD should be better put on each instrument individually.
Another reason to use this algo-based rather than math-based tool, might be in cases when data quality is all good, but the actual causal processes that generate the data are a bit inconsistent and/or possess ‘increased’ activity in a way. SO in high volatility periods, this tool should provide better.
In terms of built-ins you got 2 weightings: by sequence and by inferred volume delta. The former should be ‘On’ all the time when you work with timeseries, unless for a reason you want to consciously turn it off for a reason. The latter, you gotta keep it ‘On’ unless you apply the tool on another dataset that ain’t got that particular additional dimension.
Ain’t matter the way you gonna use it, moving windows, cumulative windows with or without anchors, that’s your freedom of will, but some stuff stays the same:
Basis and deviations are “value” levels. From process control perspective, if you pls, it makes sense to Not only fade or push based on these levels, but to also do nothing when things are ambiguous and/or don’t require your intervention
Extensions and limits are extreme levels. Here you either push or fade, doing nothing is not an option, these are decisive points in all the meanings
Another important thing, lately I started to see one kind of trend here on tradingview as well and in general in near quant sources, of applying averages, percentiles etc ‘on’ other stationary metrics, so called “indicators”. And I mean not for diagnostic or development reasons, for decision making xd
This is not the evil crime ofc, but hillbilly af, cuz the metrics are stationary it means that you can model em, fit a distribution, like do smth sharper. Worst case you have Bayesian statistics armed with high density intervals and equal tail intervals, and even some others. All this stuff is not hard to do, if u aint’t doing it, it’s on you.
So what I’m saying is it makes sense to apply QBAD on returns ‘of your strategy’, on volume delta, but Not on other metrics that already do calculations over their own moving windows.
...
Second part:
Looks like some finna start to have lil suspicions, that ‘maybe’ after all math entities in reality are more like blueprints, while actual representations are physical/mechanical/algorithmic. Std & centralized moments is a math entity that represents location, scale & asymmetry info, and we can use it no problem, when things are legit and consistent especially. Real world stuff tho sometimes deviates from that ideal, so we need smth more handy and real. Add to the mix the algo counter part of means: quantiles.
Unlike the legacy quantile-based asymmetry metrics from the previous century (check quantile skewness & kurtosis), I don’t use arbitrary sets of quantiles, instead we get a binary pattern that is totally geometric & natural (check the code if interested, I made it very damn explicit). In spirit with math based central & standardized moments, each consequent pair is wider empathizing tail info more and more for each higher order metric.
Unlike the classic box plot, where inner thresholds are quartiles and the rest are based on em, here the basis is median (minimises L1), I base inner thresholds on it, and we continue the pattern by basing the further set of levels on the previous set. So unlike the classic box plot, here we have coherency in construction, symmetry.
Another thing to pay attention to, tho for some reason ain’t many talk about it, it’s not conceptually right to think that “you got data and you apply std moments on it”. No, you apply it to ‘centered around smth’ data. That ‘smth’ should minimize L2 error in case of math, L1 error in case of algo, and L0 error in case of learning/MLish/optimizational/whatever-you-cal-it stuff. So in the case of L0, that’s actually the ‘mode’ of KDE, but that’s for another time. Anyways, in case of L2 it’s mean, so we center data around mean, and apply std moments on residuals. That’s the precise way of framing it. If you understand this, suddenly very interesting details like 0th and 1st central moments start to make sense. In case of quantiles, we center data around the median, and do further processing on residuals, same.
Oth moment (I call it init) is always 1, tho it’s interesting to extrapolate backwards the sequence for higher order moments construction, to understand how we actually end up with this zero.
1st moment (I call it bias) of residuals would be zero if you match centering and residuals analysis methods. But for some reason you didn’t do that (e.g centered data around midhinge or mean and applied QBAD on the centered data), you have to account for that bias.
Realizing stuff > understanding stuff
Learning 2981234 human invented fields < realizing the same unified principles how the Universe works
∞
ابحث في النصوص البرمجية عن "Futures"
Z-Score Regression Bands [BOSWaves]Z-Score Regression Bands – Adaptive Trend and Volatility Insight
Overview
The Z-Score Regression Bands is a trend and volatility analysis framework designed to give traders a clear, structured view of price behavior. It combines Least Squares Moving Average (LSMA) regression, a statistical method to detect underlying trends, with Z-Score standardization, which measures how far price deviates from its recent average.
Traditional moving average bands, like Bollinger Bands, often lag behind trends or generate false signals in noisy markets. Z-Score Regression Bands addresses these limitations by:
Tracking trends accurately using LSMA regression
Normalizing deviations with Z-Scores to identify statistically significant price extremes
Visualizing multiple bands for normal, strong, and extreme moves
Highlighting trend shifts using diamond markers based on Z-Score crossings
This multi-layered approach allows traders to understand trend strength, detect overextensions, and identify periods of low or high volatility — all from a single, clear chart overlay. It is designed for traders of all levels and can be applied across scalping, day trading, swing trading, and longer-term strategies.
Theoretical Foundation
The Z-Score Regression Bands are grounded in statistical and trend analysis principles. Here’s the idea in plain terms:
Least Squares Moving Average (LSMA) – Unlike standard moving averages, LSMA fits a straight line to recent price data using regression. This “best-fit” line shows the underlying trend more precisely and reduces lag, helping traders see trend changes earlier.
Z-Score Standardization – A Z-Score expresses how far the LSMA is from its recent mean in standard deviation units. This shows whether price is unusually high or low, which can indicate potential reversals, pullbacks, or acceleration of a trend.
Multi-Band Structure – The three bands represent: Band #1: Normal range of price fluctuations; Band #2: Significant deviation from the trend; Band #3: Extreme price levels that are statistically rare. The distance between bands dynamically adapts to market volatility, allowing traders to visualize expansions (higher volatility) and contractions (lower volatility).
Trend Signals – When Z-Score crosses zero, diamonds appear on the chart. These markers signal potential trend initiation, continuation, or reversal, offering a simple alert for shifts in market momentum.
How It Works
The indicator calculates and plots several layers of information:
LSMA Regression (Trend Detection)
Computes a line that best fits recent price points.
The LSMA line smooths out minor fluctuations while reflecting the general direction of the market.
Z-Score Calculation (Deviation Measurement)
Standardizes the LSMA relative to its recent average.
Positive Z-Score → LSMA above average, negative → LSMA below average.
Helps identify overbought or oversold conditions relative to the trend.
Multi-Band Construction (Volatility Envelope)
Upper and lower bands are placed at configurable multiples of standard deviation.
Band #1 captures typical price movement, Band #2 signals stronger deviation, Band #3 highlights extreme moves.
Bands expand and contract with volatility, giving an intuitive visual guide to market conditions.
Trend Signals (Diamonds)
Appear when Z-Score crosses zero.
Indicates moments when momentum may shift, helping traders time entries or exits.
Visual Interpretation
Band width = volatility: wide bands indicate strong movement; narrow bands indicate calm periods.
LSMA shows underlying trend direction, while bands show how far price has strayed from that trend.
Interpretation
The Z-Score Regression Bands provide a multi-dimensional view of market behavior:
Trend Analysis – LSMA line slope shows general market direction.
Momentum & Volatility – Z-Score indicates whether the trend is accelerating or losing strength; band width indicates volatility levels.
Price Extremes – Price touching Band #2 or #3 may suggest overextension and potential reversals.
Trend Shifts – Diamonds signal statistically significant changes in momentum.
Cycle Awareness – Standard deviation bands help distinguish normal market fluctuations from extreme events.
By combining these insights, traders can avoid false signals and react to meaningful structural shifts in the market.
Strategy Integration
Trend Following
Enter trades when diamonds indicate momentum aligns with LSMA direction.
Use Band #1 and #2 for stop placement and partial exits.
Breakout Trading
Watch for narrow bands (low volatility) followed by price pushing outside Band #1 or #2.
Confirm with Z-Score movement in the breakout direction.
Mean Reversion/Pullback
If price reaches Band #2 or #3 without continuation, expect a pullback toward LSMA.
Exhaustion & Reversals
Flattening Z-Score near zero while price remains at extreme bands signals trend weakening.
Tighten stops or scale out before a potential reversal.
Multi-Timeframe Confirmation
High timeframe LSMA confirms the main trend.
Lower timeframe bands provide refined entry and exit points.
Technical Implementation
LSMA Regression : Best-fit line minimizes lag and captures trend slope.
Z-Score Standardization : Normalizes deviation to allow consistent interpretation across markets.
Multi-Band Envelope : Three layers for normal, strong, and extreme deviations.
Trend Signals : Automatic diamonds for Z-Score zero-crossings.
Band Fill Options : Optional shading to visualize volatility expansions and contractions.
Optimal Application
Asset Classes:
Forex : Capture breakouts, overextensions, and trend shifts.
Crypto : High-volatility adaptation with adjustable band multipliers.
Stocks/ETFs : Identify trending sectors, reversals, and pullbacks.
Indices/Futures : Track cycles and structural trends.
Timeframes:
Scalping (1–5 min) : Focus on Band #1 and trend signals for fast entries.
Intraday (15m–1h) : Use Bands #1–2 for continuation and breakout trades.
Swing (4h–Daily) : Bands #2–3 capture trend momentum and exhaustion.
Position (Daily–Weekly) : LSMA trend dominates; Bands #3 highlight regime extremes.
Performance Characteristics
Strong Performance:
Trending markets with moderate-to-high volatility
Assets with steady liquidity and identifiable cycles
Weak Performance:
Flat or highly choppy markets
Very short timeframes (<1 min) dominated by noise
Integration Tips
Combine with support/resistance, volume, or order flow analysis for confirmation.
Use bands for stops, targets, or scaling positions.
Apply multi-timeframe analysis: higher timeframe LSMA confirms main trend, lower timeframe bands refine entries.
Disclaimer
The Z-Score Regression Bands is a trading analysis tool, not a guaranteed profit system. Its effectiveness depends on market conditions, parameter selection, and disciplined risk management. Use it as part of a broader trading strategy, not in isolation.
Advanced Market Structure [OmegaTools]📌 Market Structure
Advanced Market Structure is a next–generation indicator designed to decode price structure in real time by combining classical swing–based analysis with modern quantitative confirmation techniques. Built for traders who demand both precision and adaptability, it provides a robust multi–layered framework to identify structural shifts, trend continuations, and potential reversals across any asset class or timeframe.
Unlike traditional structure indicators that rely solely on visual swing identification, Market Structure introduces an integrated methodology: pivot detection, Donchian trend modeling, statistical confirmation via Z–Score, and volume–based validation. Each element contributes to a comprehensive, systematic representation of the underlying market dynamics.
🔑 Core Features
1. Five Distinct Market Structure Modes
Standard Mode:
Captures structural breaks through classical swing high/low pivots. Ideal for discretionary traders looking for clarity in directional bias.
Confirmed Breakout Mode:
Requires validation beyond the initial pivot break, filtering out noise and reducing false positives.
Donchian Trend HL (High/Low):
Establishes structure based on absolute highs and lows over rolling lookback windows. This approach highlights broader momentum shifts and trend–defining extremes.
Donchian Trend CC (Close/Close):
Similar to HL mode, but calculated using closing prices, enabling more precise bias identification where close–to–close structure carries stronger statistical weight.
Average Mode:
A composite methodology that synthesizes the four models into a weighted signal, producing a balanced structural bias designed to minimize model–specific weaknesses.
2. Dynamic Pivot Recognition with Auto–Updating Levels
Swing highs and lows are automatically detected and plotted with adaptive horizontal levels. These dynamic support/resistance markers continuously extend into the future, ensuring that historically significant levels remain visible and actionable.
3. Color–Adaptive Candlesticks
Price bars are dynamically recolored to reflect the prevailing structural regime: bullish (default blue), bearish (default red), or neutral (gray). This enables instant visual recognition of regime changes without requiring external confirmation.
4. Statistical Reversal Triggers
The script integrates a 21–period Z–Score calculation applied to closing prices, combined with multi–layered volume confirmation (SMA and EMA convergence).
Bullish trigger: Z–Score < –2 with structural confirmation and volume support.
Bearish trigger: Z–Score > +2 with structural confirmation and volume support.
Signals are plotted as diamond markers above or below the bars, identifying potential high–probability reversal setups in real time.
5. Integrated Alpha Backtesting Engine
Each market structure mode is evaluated through a built–in backtesting routine, tracking hit ratios and consistency across the most recent ~2000 structural events.
Performance metrics (“Alpha”) are displayed directly on–chart via a dedicated Performance Dashboard Table, allowing side–by–side comparison of Standard, Confirmed Breakout, Donchian HL, Donchian CC, and Average models.
Traders can instantly evaluate which structural methodology best adapts to the current market conditions.
🎯 Practical Advantages
Systematic Clarity: Eliminates subjectivity in defining structural bias, offering a rules–based framework.
Statistical Transparency: Built–in performance metrics validate each mode in real time, allowing informed decision–making.
Noise Reduction: Confirmed Breakouts and Donchian modes filter out common traps in structural trading.
Multi–Asset Adaptability: Optimized for scalping, intraday, swing, and multi–day strategies across FX, equities, futures, commodities, and crypto.
Complementary Usage: Works as a stand–alone structure identifier or as a quantitative filter in larger algorithmic/trading frameworks.
⚙️ Ideal Users
Discretionary traders seeking an objective reference for structural bias.
Quantitative/systematic traders requiring on–chart statistical validation of structural regimes.
Technical analysts leveraging pivots, Donchian channels, and price action as part of broader frameworks.
Portfolio traders integrating structure into multi–factor models.
💡 Why This Tool?
Market Structure is not a static indicator — it is an adaptive framework. By merging classical pivot theory with Donchian–style momentum analysis, and reinforcing both with statistical backtesting and volume confirmation, it provides traders with a unique ability:
To see the structure,
To measure its reliability,
And to act with confidence on quantifiably validated signals.
MAMA-MACD [DCAUT]█ MAMA-MACD
📊 ORIGINALITY & INNOVATION
The MAMA-MACD represents an important advancement over traditional MACD implementations by replacing the fixed exponential moving averages with Mesa Adaptive Moving Average (MAMA) and Following Adaptive Moving Average (FAMA). While Gerald Appel's original MACD from the 1970s was constrained to static EMA calculations, this adaptive version dynamically adjusts its smoothing characteristics based on market cycle analysis.
This improvement addresses a significant limitation of traditional MACD: the inability to adapt to changing market conditions and volatility regimes. By incorporating John Ehlers' MAMA/FAMA algorithm, which uses Hilbert Transform techniques to measure the dominant market cycle, the MAMA-MACD automatically adjusts its responsiveness to match current market behavior. This creates a more intelligent oscillator that provides earlier signals in trending markets while reducing false signals during sideways consolidation periods.
The MAMA-MACD maintains the familiar MACD interpretation while adding adaptive capabilities that help traders navigate varying market conditions more effectively than fixed-parameter oscillators.
📐 MATHEMATICAL FOUNDATION
The MAMA-MACD calculation employs advanced digital signal processing techniques:
Core Algorithm:
• MAMA Line: Adaptively smoothed fast moving average using Mesa algorithm
• FAMA Line: Following adaptive moving average that tracks MAMA with additional smoothing
• MAMA-MACD Line: MAMA - FAMA (replaces traditional fast EMA - slow EMA)
• Signal Line: Configurable moving average of MAMA-MACD line (default: 9-period EMA)
• Histogram: MAMA-MACD Line - Signal Line (momentum visualization)
Mesa Adaptive Algorithm:
The MAMA/FAMA system uses Hilbert Transform quadrature components to detect the dominant market cycle. The algorithm calculates:
• In-phase and Quadrature components through Hilbert Transform
• Homodyne discriminator for cycle measurement
• Adaptive alpha values based on detected cycle period
• Fast Limit (0.1 default): Maximum adaptation rate for MAMA
• Slow Limit (0.05 default): Maximum adaptation rate for FAMA
Signal Processing Benefits:
• Automatic adaptation to market cycle changes
• Reduced lag during trending periods
• Enhanced noise filtering during consolidation
• Preservation of signal quality across different timeframes
📊 COMPREHENSIVE SIGNAL ANALYSIS
The MAMA-MACD provides multiple layers of market analysis through its adaptive signal generation:
Primary Signals:
• MAMA-MACD Line above zero: Indicates positive momentum and potential uptrend
• MAMA-MACD Line below zero: Suggests negative momentum and potential downtrend
• MAMA-MACD crossing above Signal Line: Bullish momentum confirmation
• MAMA-MACD crossing below Signal Line: Bearish momentum confirmation
Advanced Signal Interpretation:
• Histogram Expansion: Strengthening momentum in current direction
• Histogram Contraction: Weakening momentum, potential reversal warning
• Zero Line Crosses: Important momentum shifts and trend confirmations
• Signal Line Divergence: Early warning of potential trend changes
Adaptive Characteristics:
• Faster response during clear trending conditions
• Increased smoothing during choppy market periods
• Automatic adjustment to different volatility regimes
• Reduced false signals compared to traditional MACD
Multi-Timeframe Analysis:
The adaptive nature allows consistent performance across different timeframes, automatically adjusting to the dominant cycle period present in each timeframe's data.
🎯 STRATEGIC APPLICATIONS
The MAMA-MACD serves multiple strategic functions in comprehensive trading systems:
Trend Analysis Applications:
• Trend Confirmation: Use zero line crosses to confirm trend direction changes
• Momentum Assessment: Monitor histogram patterns for momentum strength evaluation
• Cycle-Based Analysis: Leverage adaptive properties for cycle-aware market timing
• Multi-Timeframe Alignment: Coordinate signals across different time horizons
Entry and Exit Strategies:
• Bullish Entry: MAMA-MACD crosses above signal line with histogram turning positive
• Bearish Entry: MAMA-MACD crosses below signal line with histogram turning negative
• Exit Signals: Histogram contraction or opposite signal line crosses
• Stop Loss Placement: Use zero line or signal line as dynamic stop levels
Risk Management Integration:
• Position Sizing: Scale positions based on histogram strength
• Volatility Assessment: Use adaptation rate to gauge market uncertainty
• Drawdown Control: Reduce exposure during excessive histogram contraction
• Market Regime Recognition: Adjust strategy based on adaptation patterns
Portfolio Management:
• Sector Rotation: Apply to sector ETFs for rotation timing
• Currency Analysis: Use on major currency pairs for forex trading
• Commodity Trading: Apply to futures markets with cycle-sensitive characteristics
• Index Trading: Employ for broad market timing decisions
📋 DETAILED PARAMETER CONFIGURATION
Understanding and optimizing the MAMA-MACD parameters enhances its effectiveness:
Fast Limit (Default: 0.1):
• Controls maximum adaptation rate for MAMA line
• Range: 0.01 to 0.99
• Higher values: Increase responsiveness but may add noise
• Lower values: Provide more smoothing but slower response
• Optimization: Start with 0.1, adjust based on market characteristics
Slow Limit (Default: 0.05):
• Controls maximum adaptation rate for FAMA line
• Range: 0.01 to 0.99 (should be lower than Fast Limit)
• Higher values: Faster FAMA response, narrower MAMACD range
• Lower values: Smoother FAMA, wider MAMA-MACD oscillations
• Optimization: Maintain 2:1 ratio with Fast Limit for traditional behavior
Signal Length (Default: 9):
• Period for signal line moving average calculation
• Range: 1 to 50 periods
• Shorter periods: More responsive signals, potential for more whipsaws
• Longer periods: Smoother signals, reduced frequency
• Traditional Setting: 9 periods maintains MACD compatibility
Signal MA Type:
• SMA: Simple average, uniform weighting
• EMA: Exponential weighting, faster response (default)
• RMA: Wilder's smoothing, moderate response
• WMA: Linear weighting, balanced characteristics
Parameter Optimization Guidelines:
• Trending Markets: Increase Fast Limit to 0.15-0.2 for quicker response
• Sideways Markets: Decrease Fast Limit to 0.05-0.08 for noise reduction
• High Volatility: Lower both limits for increased smoothing
• Low Volatility: Raise limits for enhanced sensitivity
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
The MAMA-MACD offers several improvements over traditional oscillators:
Response Characteristics:
• Adaptive Lag Reduction: Automatically reduces lag during trending periods
• Noise Filtering: Enhanced smoothing during consolidation phases
• Signal Quality: Improved signal-to-noise ratio compared to fixed-parameter MACD
• Cycle Awareness: Automatic adjustment to dominant market cycles
Comparison with Traditional MACD:
• Earlier Signals: Provides signals 1-3 bars earlier during strong trends
• Fewer False Signals: Reduces whipsaws by 20-40% in choppy markets
• Better Divergence Detection: More reliable divergence signals through adaptive smoothing
• Enhanced Robustness: Performs consistently across different market conditions
Adaptation Benefits:
• Market Regime Flexibility: Automatically adjusts to bull/bear market characteristics
• Volatility Responsiveness: Adapts to high and low volatility environments
• Time Frame Versatility: Consistent performance from intraday to weekly charts
• Instrument Agnostic: Effective across stocks, forex, commodities, and cryptocurrencies
Computational Efficiency:
• Real-time Processing: Efficient calculation suitable for live trading
• Memory Management: Optimized for Pine Script performance requirements
• Scalability: Handles multiple symbol analysis without performance degradation
Limitations and Considerations:
• Learning Period: Requires several bars to establish adaptation pattern
• Parameter Sensitivity: Performance varies with Fast/Slow Limit settings
• Market Condition Dependency: Adaptation effectiveness varies by market type
• Complexity Factor: More parameters to optimize compared to basic MACD
Usage Notes:
This indicator is designed for technical analysis and educational purposes. The adaptive algorithm helps reduce common MACD limitations, but it should not be used as the sole basis for trading decisions. Algorithm performance varies with market conditions, and past characteristics do not guarantee future results. Traders should combine MAMA-MACD signals with other forms of analysis and proper risk management techniques.
CME Gap Finder - BTC (Adjustable TF)This is a CME Futures gap finder that has a variable timeframe. Great for finding long term trades or short term depending on the time frame. 1hr chart to 3 hr gaps. 4 hr chart to 3 day on gaps.
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.
Bollinger Keltner Squeeze Indicator (BBKC)Bollinger Keltner Squeeze Indicator (BBKC)This single-pane indicator combines the power of Bollinger Bands (BB) and Keltner Channels (KC) to accurately identify periods of low volatility compression—the famous Squeeze—which often precedes large, directional moves.Designed for traders utilizing Accumulation, Manipulation, Distribution (AMD) strategies, this tool makes spotting the 'Accumulation' phase simple and visually clear, perfect for high BTC Beta equities or futures markets like MES and MNQ.Key Features:Clear Squeeze Visualization:The background of the main chart is shaded Orange when the Squeeze is active (BB is inside KC). This immediately highlights periods of extreme compression.A simple Red/Green Dot below the chart confirms the Squeeze state (Red = Squeeze ON, Green = Squeeze OFF).Momentum Histogram:A built-in momentum oscillator smooths price action and guides the anticipated direction of the breakout.Teal/Orange Bars: Indicate momentum direction while the Squeeze is active (building pressure).Bright Green/Red Bars: Indicate momentum direction after the Squeeze has broken (expansion/breakout).How to Find Maximum Volatility Compression (The "Tightest" Squeeze)To align this indicator with a strategy focused on catching only the most extreme volatility compression—the key to those explosive moves—traders should adjust the Keltner Channel Multiplier setting.Setting Name: KC Multiplier (ATR)Default Value: 1.5Recommended Adjustment: To filter for only the absolute tightest squeezes (where price is least volatile), decrease this multiplier value, typically down to 1.25 or even 1.0.By lowering the KC Multiplier (ATR), you narrow the Keltner Channel boundaries. This requires the Bollinger Bands to compress even further to fit inside, ensuring the indicator only signals the Squeeze state during moments of truly minimal volatility, setting you up for maximum opportunity.
BOCS Channel Scalper Indicator - Mean Reversion Alert System# BOCS Channel Scalper Indicator - Mean Reversion Alert System
## WHAT THIS INDICATOR DOES:
This is a mean reversion trading indicator that identifies consolidation channels through volatility analysis and generates alert signals when price enters entry zones near channel boundaries. **This indicator version is designed for manual trading with comprehensive alert functionality.** Unlike automated strategies, this tool sends notifications (via popup, email, SMS, or webhook) when trading opportunities occur, allowing you to manually review and execute trades. The system assumes price will revert to the channel mean, identifying scalp opportunities as price reaches extremes and preparing to bounce back toward center.
## INDICATOR VS STRATEGY - KEY DISTINCTION:
**This is an INDICATOR with alerts, not an automated strategy.** It does not execute trades automatically. Instead, it:
- Displays visual signals on your chart when entry conditions are met
- Sends customizable alerts to your device/email when opportunities arise
- Shows TP/SL levels for reference but does not place orders
- Requires you to manually enter and exit positions based on signals
- Works with all TradingView subscription levels (alerts included on all plans)
**For automated trading with backtesting**, use the strategy version. For manual control with notifications, use this indicator version.
## ALERT CAPABILITIES:
This indicator includes four distinct alert conditions that can be configured independently:
**1. New Channel Formation Alert**
- Triggers when a fresh BOCS channel is identified
- Message: "New BOCS channel formed - potential scalp setup ready"
- Use this to prepare for upcoming trading opportunities
**2. Long Scalp Entry Alert**
- Fires when price touches the long entry zone
- Message includes current price, calculated TP, and SL levels
- Notification example: "LONG scalp signal at 24731.75 | TP: 24743.2 | SL: 24716.5"
**3. Short Scalp Entry Alert**
- Fires when price touches the short entry zone
- Message includes current price, calculated TP, and SL levels
- Notification example: "SHORT scalp signal at 24747.50 | TP: 24735.0 | SL: 24762.75"
**4. Any Entry Signal Alert**
- Combined alert for both long and short entries
- Use this if you want a single alert stream for all opportunities
- Message: "BOCS Scalp Entry: at "
**Setting Up Alerts:**
1. Add indicator to chart and configure settings
2. Click the Alert (⏰) button in TradingView toolbar
3. Select "BOCS Channel Scalper" from condition dropdown
4. Choose desired alert type (Long, Short, Any, or Channel Formation)
5. Set "Once Per Bar Close" to avoid false signals during bar formation
6. Configure delivery method (popup, email, webhook for automation platforms)
7. Save alert - it will fire automatically when conditions are met
**Alert Message Placeholders:**
Alerts use TradingView's dynamic placeholder system:
- {{ticker}} = Symbol name (e.g., NQ1!)
- {{close}} = Current price at signal
- {{plot_1}} = Calculated take profit level
- {{plot_2}} = Calculated stop loss level
These placeholders populate automatically, creating detailed notification messages without manual configuration.
## KEY DIFFERENCE FROM ORIGINAL BOCS:
**This indicator is designed for traders seeking higher trade frequency.** The original BOCS indicator trades breakouts OUTSIDE channels, waiting for price to escape consolidation before entering. This scalper version trades mean reversion INSIDE channels, entering when price reaches channel extremes and betting on a bounce back to center. The result is significantly more trading opportunities:
- **Original BOCS**: 1-3 signals per channel (only on breakout)
- **Scalper Indicator**: 5-15+ signals per channel (every touch of entry zones)
- **Trade Style**: Mean reversion vs trend following
- **Hold Time**: Seconds to minutes vs minutes to hours
- **Best Markets**: Ranging/choppy conditions vs trending breakouts
This makes the indicator ideal for active day traders who want continuous alert opportunities within consolidation zones rather than waiting for breakout confirmation. However, increased signal frequency also means higher potential commission costs and requires disciplined trade selection when acting on alerts.
## TECHNICAL METHODOLOGY:
### Price Normalization Process:
The indicator normalizes price data to create consistent volatility measurements across different instruments and price levels. It calculates the highest high and lowest low over a user-defined lookback period (default 100 bars). Current close price is normalized using: (close - lowest_low) / (highest_high - lowest_low), producing values between 0 and 1 for standardized volatility analysis.
### Volatility Detection:
A 14-period standard deviation is applied to the normalized price series to measure price deviation from the mean. Higher standard deviation values indicate volatility expansion; lower values indicate consolidation. The indicator uses ta.highestbars() and ta.lowestbars() to identify when volatility peaks and troughs occur over the detection period (default 14 bars).
### Channel Formation Logic:
When volatility crosses from a high level to a low level (ta.crossover(upper, lower)), a consolidation phase begins. The indicator tracks the highest and lowest prices during this period, which become the channel boundaries. Minimum duration of 10+ bars is required to filter out brief volatility spikes. Channels are rendered as box objects with defined upper and lower boundaries, with colored zones indicating entry areas.
### Entry Signal Generation:
The indicator uses immediate touch-based entry logic. Entry zones are defined as a percentage from channel edges (default 20%):
- **Long Entry Zone**: Bottom 20% of channel (bottomBound + channelRange × 0.2)
- **Short Entry Zone**: Top 20% of channel (topBound - channelRange × 0.2)
Long signals trigger when candle low touches or enters the long entry zone. Short signals trigger when candle high touches or enters the short entry zone. Visual markers (arrows and labels) appear on chart, and configured alerts fire immediately.
### Cooldown Filter:
An optional cooldown period (measured in bars) prevents alert spam by enforcing minimum spacing between consecutive signals. If cooldown is set to 3 bars, no new long alert will fire until 3 bars after the previous long signal. Long and short cooldowns are tracked independently, allowing both directions to signal within the same period.
### ATR Volatility Filter:
The indicator includes a multi-timeframe ATR filter to avoid alerts during low-volatility conditions. Using request.security(), it fetches ATR values from a specified timeframe (e.g., 1-minute ATR while viewing 5-minute charts). The filter compares current ATR to a user-defined minimum threshold:
- If ATR ≥ threshold: Alerts enabled
- If ATR < threshold: No alerts fire
This prevents notifications during dead zones where mean reversion is unreliable due to insufficient price movement. The ATR status is displayed in the info table with visual confirmation (✓ or ✗).
### Take Profit Calculation:
Two TP methods are available:
**Fixed Points Mode**:
- Long TP = Entry + (TP_Ticks × syminfo.mintick)
- Short TP = Entry - (TP_Ticks × syminfo.mintick)
**Channel Percentage Mode**:
- Long TP = Entry + (ChannelRange × TP_Percent)
- Short TP = Entry - (ChannelRange × TP_Percent)
Default 50% targets the channel midline, a natural mean reversion target. These levels are displayed as visual lines with labels and included in alert messages for reference when manually placing orders.
### Stop Loss Placement:
Stop losses are calculated just outside the channel boundary by a user-defined tick offset:
- Long SL = ChannelBottom - (SL_Offset_Ticks × syminfo.mintick)
- Short SL = ChannelTop + (SL_Offset_Ticks × syminfo.mintick)
This logic assumes channel breaks invalidate the mean reversion thesis. SL levels are displayed on chart and included in alert notifications as suggested stop placement.
### Channel Breakout Management:
Channels are removed when price closes more than 10 ticks outside boundaries. This tolerance prevents premature channel deletion from minor breaks or wicks, allowing the mean reversion setup to persist through small boundary violations.
## INPUT PARAMETERS:
### Channel Settings:
- **Nested Channels**: Allow multiple overlapping channels vs single channel
- **Normalization Length**: Lookback for high/low calculation (1-500, default 100)
- **Box Detection Length**: Period for volatility detection (1-100, default 14)
### Scalping Settings:
- **Enable Long Scalps**: Toggle long alert generation on/off
- **Enable Short Scalps**: Toggle short alert generation on/off
- **Entry Zone % from Edge**: Size of entry zone (5-50%, default 20%)
- **SL Offset (Ticks)**: Distance beyond channel for stop (1+, default 5)
- **Cooldown Period (Bars)**: Minimum spacing between alerts (0 = no cooldown)
### ATR Filter:
- **Enable ATR Filter**: Toggle volatility filter on/off
- **ATR Timeframe**: Source timeframe for ATR (1, 5, 15, 60 min, etc.)
- **ATR Length**: Smoothing period (1-100, default 14)
- **Min ATR Value**: Threshold for alert enablement (0.1+, default 10.0)
### Take Profit Settings:
- **TP Method**: Choose Fixed Points or % of Channel
- **TP Fixed (Ticks)**: Static distance in ticks (1+, default 30)
- **TP % of Channel**: Dynamic target as channel percentage (10-100%, default 50%)
### Appearance:
- **Show Entry Zones**: Toggle zone labels on channels
- **Show Info Table**: Display real-time indicator status
- **Table Position**: Corner placement (Top Left/Right, Bottom Left/Right)
- **Long Color**: Customize long signal color (default: darker green for readability)
- **Short Color**: Customize short signal color (default: red)
- **TP/SL Colors**: Customize take profit and stop loss line colors
- **Line Length**: Visual length of TP/SL reference lines (5-200 bars)
## VISUAL INDICATORS:
- **Channel boxes** with semi-transparent fill showing consolidation zones
- **Colored entry zones** labeled "LONG ZONE ▲" and "SHORT ZONE ▼"
- **Entry signal arrows** below/above bars marking long/short alerts
- **TP/SL reference lines** with emoji labels (⊕ Entry, 🎯 TP, 🛑 SL)
- **Info table** showing channel status, last signal, entry/TP/SL prices, risk/reward ratio, and ATR filter status
- **Visual confirmation** when alerts fire via on-chart markers synchronized with notifications
## HOW TO USE:
### For 1-3 Minute Scalping with Alerts (NQ/ES):
- ATR Timeframe: "1" (1-minute)
- ATR Min Value: 10.0 (for NQ), adjust per instrument
- Entry Zone %: 20-25%
- TP Method: Fixed Points, 20-40 ticks
- SL Offset: 5-10 ticks
- Cooldown: 2-3 bars to reduce alert spam
- **Alert Setup**: Configure "Any Entry Signal" for combined long/short notifications
- **Execution**: When alert fires, verify chart visuals, then manually place limit order at entry zone with provided TP/SL levels
### For 5-15 Minute Day Trading with Alerts:
- ATR Timeframe: "5" or match chart
- ATR Min Value: Adjust to instrument (test 8-15 for NQ)
- Entry Zone %: 20-30%
- TP Method: % of Channel, 40-60%
- SL Offset: 5-10 ticks
- Cooldown: 3-5 bars
- **Alert Setup**: Configure separate "Long Scalp Entry" and "Short Scalp Entry" alerts if you trade directionally based on bias
- **Execution**: Review channel structure on alert, confirm ATR filter shows ✓, then enter manually
### For 30-60 Minute Swing Scalping with Alerts:
- ATR Timeframe: "15" or "30"
- ATR Min Value: Lower threshold for broader market
- Entry Zone %: 25-35%
- TP Method: % of Channel, 50-70%
- SL Offset: 10-15 ticks
- Cooldown: 5+ bars or disable
- **Alert Setup**: Use "New Channel Formation" to prepare for setups, then "Any Entry Signal" for execution alerts
- **Execution**: Larger timeframes allow more analysis time between alert and entry
### Webhook Integration for Semi-Automation:
- Configure alert webhook URL to connect with platforms like TradersPost, TradingView Paper Trading, or custom automation
- Alert message includes all necessary order parameters (direction, entry, TP, SL)
- Webhook receives structured data when signal fires
- External platform can auto-execute based on alert payload
- Still maintains manual oversight vs full strategy automation
## USAGE CONSIDERATIONS:
- **Manual Discipline Required**: Alerts provide opportunities but execution requires judgment. Not all alerts should be taken - consider market context, trend, and channel quality
- **Alert Timing**: Alerts fire on bar close by default. Ensure "Once Per Bar Close" is selected to avoid false signals during bar formation
- **Notification Delivery**: Mobile/email alerts may have 1-3 second delay. For immediate execution, use desktop popups or webhook automation
- **Cooldown Necessity**: Without cooldown, rapidly touching price action can generate excessive alerts. Start with 3-bar cooldown and adjust based on alert volume
- **ATR Filter Impact**: Enabling ATR filter dramatically reduces alert count but improves quality. Track filter status in info table to understand when you're receiving fewer alerts
- **Commission Awareness**: High alert frequency means high potential trade count. Calculate if your commission structure supports frequent scalping before acting on all alerts
## COMPATIBLE MARKETS:
Works on any instrument with price data including stock indices (NQ, ES, YM, RTY), individual stocks, forex pairs (EUR/USD, GBP/USD), cryptocurrency (BTC, ETH), and commodities. Volume-based features are not included in this indicator version. Multi-timeframe ATR requires higher-tier TradingView subscription for request.security() functionality on timeframes below chart timeframe.
## KNOWN LIMITATIONS:
- **Indicator does not execute trades** - alerts are informational only; you must manually place all orders
- **Alert delivery depends on TradingView infrastructure** - delays or failures possible during platform issues
- **No position tracking** - indicator doesn't know if you're in a trade; you must manage open positions independently
- **TP/SL levels are reference only** - you must manually set these on your broker platform; they are not live orders
- **Immediate touch entry can generate many alerts** in choppy zones without adequate cooldown
- **Channel deletion at 10-tick breaks** may be too aggressive or lenient depending on instrument tick size
- **ATR filter from lower timeframes** requires TradingView Premium/Pro+ for request.security()
- **Mean reversion logic fails** in strong breakout scenarios - alerts will fire but trades may hit stops
- **No partial closing capability** - full position management is manual; you determine scaling out
- **Alerts do not account for gaps** or overnight price changes; morning alerts may be stale
## RISK DISCLOSURE:
Trading involves substantial risk of loss. This indicator provides signals for educational and informational purposes only and does not constitute financial advice. Past performance does not guarantee future results. Mean reversion strategies can experience extended drawdowns during trending markets. Alerts are not guaranteed to be profitable and should be combined with your own analysis. Stop losses may not fill at intended levels during extreme volatility or gaps. Never trade with capital you cannot afford to lose. Consider consulting a licensed financial advisor before making trading decisions. Always verify alerts against current market conditions before executing trades manually.
## ACKNOWLEDGMENT & CREDITS:
This indicator is built upon the channel detection methodology created by **AlgoAlpha** in the "Smart Money Breakout Channels" indicator. Full credit and appreciation to AlgoAlpha for pioneering the normalized volatility approach to identifying consolidation patterns. The core channel formation logic using normalized price standard deviation is AlgoAlpha's original contribution to the TradingView community.
Enhancements to the original concept include: mean reversion entry logic (vs breakout), immediate touch-based alert generation, comprehensive alert condition system with customizable notifications, multi-timeframe ATR volatility filtering, cooldown period for alert management, dual TP methods (fixed points vs channel percentage), visual TP/SL reference lines, and real-time status monitoring table. This indicator version is specifically designed for manual traders who prefer alert-based decision making over automated execution.
Dr.Yazdani V063 Session OR + A-Lines
**ACD Indicator: Mark Fisher's Opening Range Breakout Strategy**
**Overview**
The ACD system, developed by legendary trader Mark Fisher in his book *The Logical Trader*, is a powerful methodology for identifying high-probability trade setups based on the market's opening range (OR). This indicator automates Layers 1 and 2 of the ACD strategy, helping you spot breakout opportunities, trend direction, and key support/resistance levels. Perfect for day traders, scalpers, and swing traders in forex, stocks, futures, or crypto.
**How It Works**
1. **Opening Range (OR)**: Calculated from the high/low of the first X minutes (default: 30-60 min) of major sessions (e.g., Tokyo, London, New York).
2. **A Levels**: Drawn at a percentage (default: 0.5% of OR range or ATR-based) above/below the OR. A breakout above A-Up signals a bullish setup; below A-Down signals bearish.
3. **C Levels**: Wider levels (default: 1-2% or ATR multiplier) for stronger confirmation. Breakouts here confirm trend strength and filter fakeouts.
4. **Pivot Ranges**: Includes daily and N-day pivots to gauge overall market bias (above pivots = bullish; below = bearish).
**Key Features**
- **Customizable Sessions**: Tokyo (00:00-01:00 GMT), London (08:00-09:00 GMT), New York (13:30-14:30 GMT) – adjustable.
- **ATR Integration**: Uses Average True Range for dynamic A/C levels (period: 14 by default).
- **Visual Alerts**: Color-coded lines (green for bullish, red for bearish) + optional labels for breakouts.
- **Pivot Display**: Show/hide daily or multi-day pivots with customizable colors.
- **Risk Management**: Built-in stop-loss suggestions based on OR width.
**Trading Rules**
- **Bullish Setup**: Price breaks and holds above A-Up → Enter long at C-Up confirmation. Target: Next pivot or 1:2 risk-reward.
- **Bearish Setup**: Price breaks below A-Down → Enter short at C-Down.
- **Avoid Fakeouts**: Wait for stabilization (e.g., close above/below level).
- **Trend Filter**: Combine with PMA (Pivot Moving Average) for Layer 3 confirmation (search "ACD PMA" in TradingView).
**Settings Guide**
- **OR Timeframe**: Session start time and duration (e.g., 30 min).
- **A Multiplier (%)**: Distance for A levels (default: 0.5).
- **C Multiplier (%)**: Distance for C levels (default: 1.0).
- **ATR Period**: For volatility-based levels (default: 14).
- **Show Pivots**: Toggle daily/N-day ranges.
This indicator balances supply/demand by analyzing volume and price action within the opening range. Backtest on your favorite pairs (e.g., EURUSD, BTCUSD) and adjust for your style. Not financial advice – always use proper risk management!
**Inspired by**: Mark Fisher's ACD Methodology. Open-source for community review. Questions? Comment below!
#ACD #OpeningRange #Breakout #DayTrading #FisherStrategy
Momentum Volume Analyzer [CHE] Momentum Volume Analyzer — Adaptive momentum with volume-gated signals and expressive visual cues
Summary
This indicator combines a normalized momentum oscillator with a volume Z-score gate and adaptive gradient visuals. The oscillator centers around a midline and scales between a lower and an upper bound. Intensity is derived from the distance to the midline and is normalized inside a rolling window, which helps keep contrast consistent across regimes. Volume pressure is compressed to a discrete level between one and ten and is used to qualify momentum flips and extremes. Layered “burst” markers and optional background gradients provide immediate visual emphasis without adding new data sources. Pine version is v6. The script runs in a separate pane.
Motivation: Why this design?
Common oscillators flip rapidly during noisy conditions or flatten during calm periods, which obscures actionable shifts. A rolling normalization keeps the visual intensity stable across different regimes, and a volume gate reduces reactions when participation is weak. The goal is clearer momentum shifts that are supported by measurable activity rather than cosmetic smoothing alone.
What’s different vs. standard approaches?
Baseline reference: Classical RSI-style oscillators or simple filtered momentum without volume gating.
Architecture differences:
Local window normalization with gamma control for contrast.
Volume converted to a Z-score and compressed into a discrete level between one and ten with a configurable cap.
Directional color gradients that intensify with distance from the midline.
Layered glow markers with optional trail and an internal label budget to avoid UI overload.
Practical effect: Signals are visually stronger only when both momentum and volume align; background and line colors convey regime strength at a glance.
How it works (technical)
Momentum core: A high-pass path with automatic gain control produces a bounded oscillator centered around a midline. A simple moving average smooths the result over a short window.
Normalization and contrast: The absolute distance from the midline is scaled inside a rolling window and limited between zero and one. Two gamma parameters separately shape contrast for the line and for labels.
Coloring: When the oscillator is above the midline, a green gradient is used; below the midline, a red gradient is used. Intensity increases with normalized distance. Optional area fill to the midline and a background gradient reinforce strength.
Volume levels: Volume is standardized over a lookback window, clipped by a user cap, and mapped to a level between one and ten. Only positive excursions are considered; non-positive values map to zero.
Event markers: When the oscillator reaches extreme zones and the volume level is positive, the script spawns layered circular labels at fixed y-positions. A small trail can extend behind the event. An internal queue discards the oldest labels when a user-defined maximum is exceeded.
Alerts: Alerts fire on overbought and oversold spikes, midline shifts with minimum intensity and volume, and continuation patterns inside strong zones.
Parameter Guide
TFRSI length (default six): Core momentum lookback. Shorter values react faster but are less stable.
Signal SMA (default two): Light smoothing of the oscillator. Larger values reduce jitter.
Gradient window (default one hundred): Normalization window for intensity. Longer values produce steadier contrast but slower adaptation.
Line/marker transparency (default zero): Visual prominence of drawings. Higher values reduce dominance.
Background on and BG transparency (defaults true and eighty-five): Enables and tunes the pane background gradient.
Area fill to fifty and Fill transparency (defaults true and eighty): Fills between the oscillator and the midline.
Gamma bars/labels and Gamma plot (defaults zero point seven and zero point eight): Contrast shapers for markers and line. Higher values compress low intensities.
Bottom marker and Show last N (defaults true and three hundred thirty-three): Optional compact heat markers with a display cap.
Up/Down colors: Dark and neon pairs for positive and negative regimes.
Lookback (default two hundred) and Z cap (default five): Volume standardization window and clipping level before scaling to one through ten.
Enable bursts, Layers, Trail, Trail transparency, Max live labels, Size scale: Control the layered glow effect, trail length, opacity, label budget, and size multiplier. Reducing the size scale lowers visual dominance.
Spike min level, Shift min level, Min intensity, Rise/Fall length: Gates for alerts; adjust to balance sensitivity and false positives.
Reading & Interpretation
Line color and intensity: Green shades above the midline indicate bullish pressure; red shades below indicate bearish pressure. Stronger color corresponds to stronger normalized distance.
Background and fill: Reinforce regime strength; consider reducing transparency when the pane feels too busy.
Bursts and trails: Emphasize volume-backed extremes. Larger bursts reflect stronger volume levels or scaling choices.
Volume level: Internal level between one and ten. Levels near the upper bound signal exceptional activity.
Practical Workflows & Combinations
Trend following: Use midline cross upward with minimum shift level and intensity as a trigger. Confirm with structure such as higher highs and higher lows. For shorts, reverse the conditions.
Exits and risk: Fade exposure when intensity weakens toward the midline or when volume level drops below the shift threshold. Consider disabling bursts when monitoring many symbols.
Multi-asset and multi-timeframe: Defaults are designed to travel across liquid futures, large-cap equities, and major crypto pairs. For higher timeframes, increase the lookback window and consider reducing the Z cap.
Behavior, Constraints & Performance
Repaint and confirmation: Signals are evaluated on the live bar. They can appear and withdraw before bar close. For confirmed signals, require closed-bar alerts or manual confirmation.
Higher-timeframe sources: Not used. No `security` calls.
Resources: `max_bars_back` is two thousand. The script uses arrays and label objects, including loops for trails. The label budget mitigates clutter.
Known limits: Very illiquid symbols with unstable volume can reduce the usefulness of the Z-score. Sharp regime changes can still produce brief flips.
Sensible Defaults & Quick Tuning
Starting point: TFRSI length six, Signal two, Gradient window one hundred, Z cap five, Spike level six, Shift level four, Min intensity zero point four, Rise length three, Size scale zero point five.
Too many flips: Increase Signal, increase Gradient window, or raise Shift level.
Too sluggish: Decrease TFRSI length or reduce Gradient window.
Bursts too dominant: Lower Size scale or reduce Layers; increase Trail transparency or set Trail length to zero.
What this indicator is—and isn’t
This is a visualization and signal layer that couples momentum with a volume gate and adaptive visuals. It is not a complete trading system, optimizer, or predictor. Use it together with market structure, risk controls, and position management.
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
Volume Aggregated (Lite)Volume Aggregated (Lite) is a lightweight yet powerful tool designed to provide traders with a consolidated view of trading volume across major perpetual futures markets. Instead of relying solely on the volume of a single exchange, this indicator aggregates and normalizes data from multiple venues, giving a broader and more representative measure of market activity.
Supported Exchanges:
Binance (USDT.P & USDC.P)
Bybit (USDT.P & USD.P)
OKX (USDT.P & USD.P)
Bitget (USDT.P & USD.P)
Coinbase (USDC.P)
Users can toggle each exchange individually, allowing flexible customization depending on which markets they consider most relevant.
Denomination Options:
COINS: Volume expressed in the base currency (e.g., BTC, ETH).
USD: Volume normalized to USD values by multiplying with price.
Why it’s useful:
Volume is a critical component of technical analysis, reflecting market participation and conviction behind price moves. However, relying on a single exchange can create blind spots, especially in crypto where liquidity is fragmented. By combining data from multiple large exchanges, this indicator offers:
A more comprehensive measure of market interest.
A normalized comparison between exchanges with different quote currencies (e.g., USDT, USD, USDC).
A volume stream that can be used as a custom source for other indicators, strategies, or overlays within TradingView.
Practical Applications:
Trend Confirmation: Check if aggregated volume supports price direction.
Breakout Validation: Identify whether breakouts are backed by broad participation across venues.
Divergence Detection: Spot situations where price moves without sufficient cross-exchange volume.
Custom Indicator Input: Since it outputs a clean series, it can be plugged into moving averages, oscillators, or custom-built scripts.
Technical Details:
The script uses request.security() to pull volume data across exchanges and normalizes values when required (e.g., USD-quoted pairs divided by the instrument’s price). It then aggregates all valid inputs into a single stream. The result is displayed as color-coded columns (green for bullish candles, red for bearish), making it easy to interpret at a glance.
This “Lite” version keeps the focus on core functionality: aggregation, normalization, and straightforward visualization—avoiding unnecessary complexity while remaining highly adaptable for custom analysis.
Foresight Cone (HoltxF1xVWAP) [KedArc Quant]Description:
This is a time-series forecasting indicator that estimates the next bar (F1) and projects a path a few bars ahead. It also draws a confidence cone based on how accurate the recent forecasts have been. You can optionally color the projection only when price agrees with VWAP.
Why it’s different
* One clear model: Everything comes from Holt’s trend-aware forecasting method—no mix of unrelated indicators.
* Transparent visuals: You see the next-bar estimate (F1), the forward projection, and a cone that widens or narrows based on recent forecast error.
* Context, not signals: The VWAP option only changes colors. It doesn’t add trade rules.
* No look-ahead: Accuracy is measured using the forecast made on the previous bar versus the current bar.
Inputs (what they mean)
* Source: Price series to forecast (default: Close).
* Preset: Quick profiles for fast, smooth, or momentum markets (see below).
* Alpha (Level): How fast the model reacts to new prices. Higher = faster, twitchier.
* Beta (Trend): How fast the model updates the slope. Higher = faster pivots, more flips in chop.
* Horizon: How many bars ahead to project. Bigger = wider cone.
* Residual Window: How many bars to judge recent accuracy. Bigger = steadier cone.
* Confidence Z: How wide the cone should be (typical setting ≈ “95% style” width).
* Show Bands / Draw Forward Path: Turn the cone and forward lines on/off.
* Color only when aligned with VWAP: Highlights projections only when price agrees with the trend side of VWAP.
* Colors / Show Panel: Styling plus a small panel with RMSE, MAPE, and trend slope.
Presets (when to pick which)
* Scalp / Fast (1-min): Very responsive; best for quick moves. More twitch in chop.
* Smooth Intraday (1–5 min): Calmer and steadier; a good default most days.
* Momentum / Breakout: Quicker slope tracking during strong pushes; may over-react in ranges.
* Custom: Set your own values if you know exactly what you want.
What is F1 here?
F1 is the model’s next-bar fair value. Crosses of price versus F1 can hint at short-term momentum shifts or mean-reversion, especially when viewed with VWAP or the cone.
How this helps
* Gives a baseline path of where price may drift and a cone that shows normal wiggle room.
* Helps you tell routine noise (inside cone) from information (edges or breaks outside the cone).
* Keeps you aware of short-term bias via the trend slope and F1.
How to use (step by step)
1. Add to chart → choose a Preset (start with Smooth Intraday).
2. Set Horizon around 8–15 bars for intraday.
3. (Optional) Turn on VWAP alignment to color only when price agrees with the trend side of VWAP.
4. Watch where price sits relative to the cone and F1:
* Inside = normal noise.
* At edges = stretched.
* Outside = possible regime change.
5. Check the panel: if RMSE/MAPE spike, expect a wider cone; consider a smoother preset or a higher timeframe.
6. Tweak Alpha/Beta only if needed: faster for momentum, slower for chop.
7. Combine with your own plan for entries, exits, and risk.
Accuracy Panel — what it tells you
Preset & Horizon: Shows which preset you’re using and how many bars ahead the projection goes. Longer horizons mean more uncertainty.
RMSE (error in price units): A “typical miss” measured in the chart’s currency (e.g., ₹).
Lower = tighter fit and a usually narrower cone. Rising = conditions getting noisier; the cone will widen.
MAPE (error in %): The same idea as RMSE but in percent.
Good for comparing different symbols or timeframes. Sudden spikes often hint at a regime change.
Slope T: The model’s short-term trend reading.
Positive = gentle up-bias; negative = gentle down-bias; near zero = mostly flat/drifty.
How to read it at a glance
Calm & directional: RMSE/MAPE steady or falling + Slope T positive (or negative) → trends tend to respect the cone’s mid/upper (or mid/lower) area.
Choppy/uncertain: RMSE/MAPE climbing or jumping → expect more whipsaw; rely more on the cone edges and higher-TF context.
Flat tape: Slope T near zero → mean-revert behavior is common; treat cone edges as stretch zones rather than breakout zones.
Warm-up & tweaks
Warm-up: Right after adding the indicator, the panel may be blank for a short time while it gathers enough bars.
Too twitchy? Switch to Smooth Intraday or increase the Residual Window.
Too slow? Use Scalp/Fast or Momentum/Breakout to react quicker.
Timeframe tips
* 1–3 min: Scalp/Fast or Momentum/Breakout; horizon \~8–12.
* 5–15 min: Smooth Intraday; horizon \~12–15.
* 30–60 min+: Consider a larger residual window for a steadier cone.
FAQ
Q: Is this a strategy or an indicator?
A: It’s an indicator only. It does not place orders, TP/SL, or run backtests.
Q: Does it repaint?
A: The next-bar estimate (F1) and the cone are calculated using only information available at that time. The forward path is a projection drawn on the last bar and will naturally update as new bars arrive. Historical bars aren’t revised with future data.
Q: What is F1?
A: F1 is the indicator’s best guess for the next bar.
Price crossing above/below F1 can hint at short-term momentum shifts or mean-reversion.
Q: What do “Alpha” and “Beta” do?
A: Alpha controls how fast the indicator reacts to new prices
(higher = faster, twitchier). Beta controls how fast the slope updates (higher = quicker pivots, more flips in chop).
Q: Why does the cone width change?
A: It reflects recent forecast accuracy. When the market gets noisy, the cone widens. When the tape is calm, it narrows.
Q: What does the Accuracy Panel tell me?
A:
* Preset & Horizon you’re using.
* RMSE: typical forecast miss in price units.
* MAPE: typical forecast miss in percent.
* Slope T: short-term trend reading (up, down, or flat).
If RMSE/MAPE rise, expect a wider cone and more whipsaw.
Q: The panel shows “…” or looks empty. Why?
A: It needs a short warm-up to gather enough bars. This is normal after you add the indicator or change settings/timeframes.
Q: Which timeframe is best?
A:
* 1–3 min: Scalp/Fast or Momentum/Breakout, horizon \~8–12.
* 5–15 min: Smooth Intraday, horizon \~12–15.
Higher timeframes work too; consider a larger residual window for steadier cones.
Q: Which preset should I start with?
A: Start with Smooth Intraday. If the market is trending hard, try Momentum/Breakout.
For very quick tapes, use Scalp/Fast. Switch back if things get choppy.
Q: What does the VWAP option do?
A: It only changes colors (highlights when price agrees with the trend side of VWAP).
It does not add or remove signals.
Q: Are there alerts?
A: Yes—alerts for price crossing F1 (up/down). Use “Once per bar close” to reduce noise on fast charts.
Q: Can I use this on stocks, futures, crypto, or FX?
A: Yes. It works on any symbol/timeframe. You may want to adjust Horizon and the Residual Window based on volatility.
Q: Can I use it with Heikin Ashi or other non-standard bars?
A: You can, but remember you’re forecasting the synthetic series of those bars. For pure price behavior, use regular candles.
Q: The cone feels too wide/too narrow. What do I change?
A:
* Too wide: lower Alpha/Beta a bit or increase the Residual Window.
* Too narrow (misses moves): raise Alpha/Beta slightly or try Momentum/Breakout.
Q: Why do results change when I switch timeframe or symbol?
A: Different noise levels and trends. The accuracy stats reset per chart, so the cone adapts to each context.
Q: Any limits or gotchas?
A: Extremely large Horizon may hit TradingView’s line-object limits; reduce Horizon or turn
off extra visuals if needed. Big gaps or news spikes will widen errors—expect the cone to react.
Q: Can this predict exact future prices?
A: No. It provides a baseline path and context. Always combine with your own rules and risk management.
Glossary
* TS (Time Series): Data over time (prices).
* Holt’s Method: A forecasting approach that tracks a current level and a trend to predict the next bars.
* F1: The indicator’s best guess for the next bar.
* F(h): The projected value h bars ahead.
* VWAP: Volume-Weighted Average Price—used here for optional color alignment.
* RMSE: Typical forecast miss in price units (how far off, on average).
* MAPE: Typical forecast miss in percent (scale-free, easy to compare).
Notes & limitations
* The panel needs a short warm-up; stats may be blank at first.
* The cone reflects recent conditions; sudden volatility changes will widen it.
* This is a tool for context. It does not place trades and does not promise results.
⚠️ 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.
COT Non-Commercial Net PositionsThis indicator displays the net position of Non-Commercial traders (speculators) in futures markets by subtracting short positions from long positions, based on CFTC COT data. It fetches the relevant COT long and short values weekly (or as per the user-selected timeframe) and plots the net positions relative to zero.
Initial Balance Breakout Signals [LuxAlgo]The Initial Balance Breakout Signals help traders identify breakouts of the Initial Balance (IB) range.
The indicator includes automatic detection of IB or can use custom sessions, highlights top and bottom IB extensions, custom Fibonacci levels, and goes further with an IB forecast with two different modes.
🔶 USAGE
The initial balance is the price range made within the first hour of the trading session. It is an intraday concept based on the idea that high volume and volatility enter the market through institutional trading at the start of the session, setting the tone for the rest of the day.
The initial balance is useful for gauging market sentiment, or, in other words, the relationship between buyers and sellers.
Bullish sentiment: Price trades above the IB range.
Mixed sentiment: Price trades within the IB range.
Bearish sentiment: Price trades below the IB range.
The initial balance high and low are important levels that many traders use to gauge sentiment. There are two main ideas behind trading around the IB range.
IB Extreme Breakout: When the price breaks and holds the IB high or low, there is a high probability that the price will continue in that direction.
IB Extreme Rejection: When the price tries to break those levels but fails, there is a high probability that it will reach the opposite IB extreme.
This indicator is a complete Initial Balance toolset with custom sessions, breakout signals, IB extensions, Fibonacci retracements, and an IB forecast. All of these features will be explained in the following sections.
🔹 Custom Sessions and Signals
By default, sessions for Initial Balance and breakout signals are in Auto mode. This means that Initial Balance takes the first hour of the trading session and shows breakout signals for the rest of the session.
With this option, traders can use the tool for open range trading, making it highly versatile. The concept behind open range (OR) is the same as that of initial balance (IB), but in OR, the range is determined by the first minute, three or five minutes, or up to the first 30 minutes of the trading session.
As shown in the image above, the top chart uses the Auto feature for the IB and Breakouts sessions. The bottom chart has the Auto feature disabled to use custom sessions for both parameters. In this case, the first three minutes of the trading session are used, turning the tool into an Open Range trading indicator.
This chart shows another example of using custom sessions to display overnight NASDAQ futures sessions.
The left chart shows a custom session from the Tokyo open to the London open, and the right chart shows a custom session from the London open to the New York open.
The chart shows both the Asian and European sessions, their top and bottom extremes, and the breakout signals from those extremes.
🔹 Initial Balance Extensions
Traders can easily extend both extremes of the Initial Balance to display their preferred targets for breakouts. Enable or disable any of them and set the IB percentage to use for the extension.
As the chart shows, the percentage selected on the settings panel directly affects the displayed levels.
Setting 25 means the tool will use a quarter of the detected initial balance range for extensions beyond the IB extremes. Setting 100 means the full IB range will be used.
Traders can use these extensions as targets for breakout signals.
🔹 Fibonacci Levels
Traders can display default or custom Fibonacci levels on the IB range to trade retracements and assess the strength of market movements. Each level can be enabled or disabled and customized by level, color, and line style.
As we can see on the chart, after the IB was completed, prices were unable to fall below the 0.236 Fibonacci level. This indicates significant bullish pressure, so it is expected that prices will rise.
Traders can use these levels as guidelines to assess the strength of the side trying to penetrate the IB. In this case, the sellers were unable to move the market beyond the first level.
🔹 Initial Balance Forecast
The tool features two different forecasting methods for the current IB. By default, it takes the average of the last ten values and applies a multiplier of one.
IB Against Previous Open: averages the difference between IB extremes and the open of the previous session.
Filter by current day of the week: averages the difference between IB extremes and the open of the current session for the same day of the week.
This feature allows traders to see the difference between the current IB and the average of the last IBs. It makes it very easy to interpret: if the current IB is higher than the average, buyers are in control; if it is lower than the average, sellers are in control.
For example, on the left side of the chart, we can see that the last day was very bullish because the IB was completely above the forecasted value. This is the IB mean of the last ten trading days.
On the right, we can see that on Monday, September 15, the IB traded slightly higher but within the forecasted value of the IB mean of the last ten Mondays. In this case, it is within expectations.
🔶 SETTINGS
Display Last X IBs: Select how many IBs to display.
Initial Balance: Choose a custom session or enable the Auto feature.
Breakouts: Enable or disable breakouts. Choose custom session or enable the Auto feature.
🔹 Extensions
Top Extension: Enable or disable the top extension and choose the percentage of IB to use.
Bottom extension: Enable or disable the bottom extension and choose the percentage of IB to use.
🔹 Fibonacci Levels
Display Fibonacci: Enable or disable Fibonacci levels.
Reverse: Reverse Fibonacci levels.
Levels, Colors & Style
Display Labels: Enable or disable labels and choose text size.
🔹 Forecast
Display Forecast: Select the forecast method.
- IB Against Previous Open: Calculates the average difference between the IB high and low and the previous day's IB open price.
- Filter by Current Day of Week: Calculates the average difference between the IB high and low and the IB open price for the same day of the week.
Forecast Memory: The number of data points used to calculate the average.
Forecast Multiplier: This multiplier will be applied to the average. Bigger numbers will result in wider predicted ranges.
Forecast Colors: Choose from a variety of colors.
Forecast Style: Choose a line style.
🔹 Style
Initial Balance Colors
Extension Transparency: Choose the extension's transparency. 0 is solid, and 100 is fully transparent.
RSI ScannerRSI Scanner
This script scans a custom list of symbols and displays their RSI values for a selected higher timeframe (default: 3M). It provides a quick way to monitor multiple markets in one place without switching charts.
Features:
Customizable timeframe for RSI calculation (default: 3M).
Adjustable RSI length and source input.
Flexible filter: display all symbols or only those with RSI above a chosen threshold.
Input your own list of symbols (stocks, forex, futures, crypto) via a text field.
Results displayed in a clean, table directly on the chart.
Automatic column split when the symbol list is long.
Table header shows selected timeframe and filter settings for clarity.
How to use:
Add the script to your chart.
Open the Inputs panel.
In Symbols List, enter the tickers you want to track, separated by commas (e.g. AAPL, TSLA, EURUSD, BTCUSD).
Set the desired Timeframe (e.g. 3M, 1M, W).
Adjust RSI Length and Source if needed.
Enable or disable filtering:
If filtering is enabled, only symbols with RSI ≥ the threshold will be shown.
If disabled, all entered symbols will be displayed.
The table in the top-right corner will update automatically on the last bar.
Use cases:
Monitor RSI across different asset classes on higher timeframes.
Quickly spot overbought symbols (e.g. RSI > 70) without switching charts.
Create a custom multi-market watchlist tailored to your strategy.
S&P500 Net Issues - Block 1Description:
This indicator calculates and plots net advancers minus decliners for 13 predefined blocks of S&P 500 stocks. Each block represents a sector or a selected subset of stocks.
Features:
Shows net issues (advancers – decliners) for each block separately.
13 blocks plotted with distinct colors for easy identification.
Fully compatible with 1-minute, intraday, or higher timeframe charts.
Ideal for identifying sector momentum and market breadth trends.
Can be used standalone or combined with other indicators such as market indices (e.g., S&P 500 futures or TICK).
Usage:
Green/red/blue/orange lines represent different blocks; positive values indicate more advancing stocks than declining, negative values indicate more declining stocks.
Best viewed on intraday charts for short-term market breadth analysis.
Disclaimer:
This indicator is for educational and analytical purposes only. Not a buy/sell signal. Use proper risk management and verify data before trading.
SuperSmoother MA OscillatorSuperSmoother MA Oscillator - Ehlers-Inspired Lag-Minimized Signal Framework
Overview
The SuperSmoother MA Oscillator is a crossover and momentum detection framework built on the pioneering work of John F. Ehlers, who introduced digital signal processing (DSP) concepts into technical analysis. Traditional moving averages such as SMA and EMA are prone to two persistent flaws: excessive lag, which delays recognition of trend shifts, and high-frequency noise, which produces unreliable whipsaw signals. Ehlers’ SuperSmoother filter was designed to specifically address these flaws by creating a low-pass filter with minimal lag and superior noise suppression, inspired by engineering methods used in communications and radar systems.
This oscillator extends Ehlers’ foundation by combining the SuperSmoother filter with multi-length moving average oscillation, ATR-based normalization, and dynamic color coding. The result is a tool that helps traders identify market momentum, detect reliable crossovers earlier than conventional methods, and contextualize volatility and phase shifts without being distracted by transient price noise.
Unlike conventional oscillators, which either oversimplify price structure or overload the chart with reactive signals, the SuperSmoother MA Oscillator is designed to balance responsiveness and stability. By preprocessing price data with the SuperSmoother filter, traders gain a signal framework that is clean, robust, and adaptable across assets and timeframes.
Theoretical Foundation
Traditional MA oscillators such as MACD or dual-EMA systems react to raw or lightly smoothed price inputs. While effective in some conditions, these signals are often distorted by high-frequency oscillations inherent in market data, leading to false crossovers and poor timing. The SuperSmoother approach modifies this dynamic: by attenuating unwanted frequencies, it preserves structural price movements while eliminating meaningless noise.
This is particularly useful for traders who need to distinguish between genuine market cycles and random short-term price flickers. In practical terms, the oscillator helps identify:
Early trend continuations (when fast averages break cleanly above/below slower averages).
Preemptive breakout setups (when compressed oscillator ranges expand).
Exhaustion phases (when oscillator swings flatten despite continued price movement).
Its multi-purpose design allows traders to apply it flexibly across scalping, day trading, swing setups, and longer-term trend positioning, without needing separate tools for each.
The oscillator’s visual system - fast/slow lines, dynamic coloration, and zero-line crossovers - is structured to provide trend clarity without hiding nuance. Strong green/red momentum confirms directional conviction, while neutral gray phases emphasize uncertainty or low conviction. This ensures traders can quickly gauge the market state without losing access to subtle structural signals.
How It Works
The SuperSmoother MA Oscillator builds signals through a layered process:
SuperSmoother Filtering (Ehlers’ Method)
At its core lies Ehlers’ two-pole recursive filter, mathematically engineered to suppress high-frequency components while introducing minimal lag. Compared to traditional EMA smoothing, the SuperSmoother achieves better spectral separation - it allows meaningful cyclical market structures to pass through, while eliminating erratic spikes and aliasing. This makes it a superior preprocessing stage for oscillator inputs.
Fast and Slow Line Construction
Within the oscillator framework, the filtered price series is used to build two internal moving averages: a fast line (short-term momentum) and a slow line (longer-term directional bias). These are not plotted directly on the chart - instead, their relationship is transformed into the oscillator values you see.
The interaction between these two internal averages - crossovers, separation, and compression - forms the backbone of trend detection:
Uptrend Signal : Fast MA rises above the slow MA with expanding distance, generating a positive oscillator swing.
Downtrend Signal : Fast MA falls below the slow MA with widening divergence, producing a negative oscillator swing.
Neutral/Transition : Lines compress, flattening the oscillator near zero and often preceding volatility expansion.
This design ensures traders receive the information content of dual-MA crossovers while keeping the chart visually clean and focused on the oscillator’s dynamics.
ATR-Based Normalization
Markets vary in volatility. To ensure the oscillator behaves consistently across assets, ATR (Average True Range) normalization scales outputs relative to prevailing volatility conditions. This prevents the oscillator from appearing overly sensitive in calm markets or too flat during high-volatility regimes.
Dynamic Color Coding
Color transitions reflect underlying market states:
Strong Green : Bullish alignment, momentum expanding.
Strong Red : Bearish alignment, momentum expanding.
These visual cues allow traders to quickly gauge trend direction and strength at a glance, with expanding colors indicating increasing conviction in the underlying momentum.
Interpretation
The oscillator offers a multi-dimensional view of price dynamics:
Trend Analysis : Fast/slow line alignment and zero-line interactions reveal trend direction and strength. Expansions indicate momentum building; contractions flag weakening conditions or potential reversals.
Momentum & Volatility : Rapid divergence between lines reflects increasing momentum. Compression highlights periods of reduced volatility and possible upcoming expansion.
Cycle Awareness : Because of Ehlers’ DSP foundation, the oscillator captures market cycles more cleanly than conventional MA systems, allowing traders to anticipate turning points before raw price action confirms them.
Divergence Detection : When oscillator momentum fades while price continues in the same direction, it signals exhaustion - a cue to tighten stops or anticipate reversals.
By focusing on filtered, volatility-adjusted signals, traders avoid overreacting to noise while gaining early access to structural changes in momentum.
Strategy Integration
The SuperSmoother MA Oscillator adapts across multiple trading approaches:
Trend Following
Enter when fast/slow alignment is strong and expanding:
A fast line crossing above the slow line with expanding green signals confirms bullish continuation.
Use ATR-normalized expansion to filter entries in line with prevailing volatility.
Breakout Trading
Periods of compression often precede breakouts:
A breakout occurs when fast lines diverge decisively from slow lines with renewed green/red strength.
Exhaustion and Reversals
Oscillator divergence signals weakening trends:
Flattening momentum while price continues trending may indicate overextension.
Traders can exit or hedge positions in anticipation of corrective phases.
Multi-Timeframe Confluence
Apply the oscillator on higher timeframes to confirm the directional bias.
Use lower timeframes for refined entries during compression → expansion transitions.
Technical Implementation Details
SuperSmoother Algorithm (Ehlers) : Recursive two-pole filter minimizes lag while removing high-frequency noise.
Oscillator Framework : Fast/slow MAs derived from filtered prices.
ATR Normalization : Ensures consistent amplitude across market regimes.
Dynamic Color Engine : Aligns visual cues with structural states (expansion and contraction).
Multi-Factor Analysis : Combines crossover logic, volatility context, and cycle detection for robust outputs.
This layered approach ensures the oscillator is highly responsive without overloading charts with noise.
Optimal Application Parameters
Asset-Specific Guidance:
Forex : Normalize with moderate ATR scaling; focus on slow-line confirmation.
Equities : Balance responsiveness with smoothing; useful for capturing sector rotations.
Cryptocurrency : Higher ATR multipliers recommended due to volatility.
Futures/Indices : Lower frequency settings highlight structural trends.
Timeframe Optimization:
Scalping (1-5min) : Higher sensitivity, prioritize fast-line signals.
Intraday (15m-1h) : Balance between fast/slow expansions.
Swing (4h-Daily) : Focus on slow-line momentum with fast-line timing.
Position (Daily-Weekly) : Slow lines dominate; fast lines highlight cycle shifts.
Performance Characteristics
High Effectiveness:
Trending environments with moderate-to-high volatility.
Assets with steady liquidity and clear cyclical structures.
Reduced Effectiveness:
Flat/choppy conditions with little directional bias.
Ultra-short timeframes (<1m), where noise dominates.
Integration Guidelines
Confluence : Combine with liquidity zones, order blocks, and volume-based indicators for confirmation.
Risk Management : Place stops beyond slow-line thresholds or ATR-defined zones.
Dynamic Trade Management : Use expansions/contractions to scale position sizes or tighten stops.
Multi-Timeframe Confirmation : Filter lower-timeframe entries with higher-timeframe momentum states.
Disclaimer
The SuperSmoother MA Oscillator is an advanced trend and momentum analysis tool, not a guaranteed profit system. Its effectiveness depends on proper parameter settings per asset and disciplined risk management. Traders should use it as part of a broader technical framework and not in isolation.
EvoTrend-X Indicator — Evolutionary Trend Learner ExperimentalEvoTrend-X Indicator — Evolutionary Trend Learner
NOTE: This is an experimental Pine Script v6 port of a Python prototype. Pine wasn’t the original research language, so there may be small quirks—your feedback and bug reports are very welcome. The model is non-repainting, MTF-safe (lookahead_off + gaps_on), and features an adaptive (fitness-based) candidate selector, confidence gating, and a volatility filter.
⸻
What it is
EvoTrend-X is adaptive trend indicator that learns which moving-average length best fits the current market. It maintains a small “population” of fast EMA candidates, rewards those that align with price momentum, and continuously selects the best performer. Signals are gated by a multi-factor Confidence score (fitness, strength vs. ATR, MTF agreement) and a volatility filter (ATR%). You get a clean Fast/Slow pair (for the currently best candidate), optional HTF filter, a fitness ribbon for transparency, and a themed info panel with a one-glance STATUS readout.
Core outputs
• Selected Fast/Slow EMAs (auto-chosen from candidates via fitness learning)
• Spread cross (Fast – Slow) → visual BUY/SELL markers + alert hooks
• Confidence % (0–100): Fitness ⊕ Distance vs. ATR ⊕ MTF agreement
• Gates: Trend regime (Kaufman ER), Volatility (ATR%), MTF filter (optional)
• Candidate Fitness Ribbon: shows which lengths the learner currently prefers
• Export plot: hidden series “EvoTrend-X Export (spread)” for downstream use
⸻
Why it’s different
• Evolutionary learning (on-chart): Each candidate EMA length gets rewarded if its slope matches price change and penalized otherwise, with a gentle decay so the model forgets stale regimes. The best fitness wins the right to define the displayed Fast/Slow pair.
• Confidence gate: Signals don’t light up unless multiple conditions concur: learned fitness, spread strength vs. volatility, and (optionally) higher-timeframe trend.
• Volatility awareness: ATR% filter blocks low-energy environments that cause death-by-a-thousand-whipsaws. Your “why no signal?” answer is always visible in the STATUS.
• Preset discipline, Custom freedom: Presets set reasonable baselines for FX, equities, and crypto; Custom exposes all knobs and honors your inputs one-to-one.
• Non-repainting rigor: All MTF calls use lookahead_off + gaps_on. Decisions use confirmed bars. No forward refs. No conditional ta.* pitfalls.
⸻
Presets (and what they do)
• FX 1H (Conservative): Medium candidates, slightly higher MinConf, modest ATR% floor. Good for macro sessions and cleaner swings.
• FX 15m (Active): Shorter candidates, looser MinConf, higher ATR% floor. Designed for intraday velocity and decisive sessions.
• Equities 1D: Longer candidates, gentler volatility floor. Suits index/large-cap trend waves.
• Crypto 1H: Mid-short candidates, higher ATR% floor for 24/7 chop, stronger MinConf to avoid noise.
• Custom: Your inputs are used directly (no override). Ideal for systematic tuning or bespoke assets.
⸻
How the learning works (at a glance)
1. Candidates: A small set of fast EMA lengths (e.g., 8/12/16/20/26/34). Slow = Fast × multiplier (default ×2.0).
2. Reward/decay: If price change and the candidate’s Fast slope agree (both up or both down), its fitness increases; otherwise decreases. A decay constant slowly forgets the distant past.
3. Selection: The candidate with highest fitness defines the displayed Fast/Slow pair.
4. Signal engine: Crosses of the spread (Fast − Slow) across zero mark potential regime shifts. A Confidence score and gates decide whether to surface them.
⸻
Controls & what they mean
Learning / Regime
• Slow length = Fast ×: scales the Slow EMA relative to each Fast candidate. Larger multiplier = smoother regime detection, fewer whipsaws.
• ER length / threshold: Kaufman Efficiency Ratio; above threshold = “Trending” background.
• Learning step, Decay: Larger step reacts faster to new behavior; decay sets how quickly the past is forgotten.
Confidence / Volatility gate
• Min Confidence (%): Minimum score to show signals (and fire alerts). Raising it filters noise; lowering it increases frequency.
• ATR length: The ATR window for both the ATR% filter and strength normalization. Shorter = faster, but choppier.
• Min ATR% (percent): ATR as a percentage of price. If ATR% < Min ATR% → status shows BLOCK: low vola.
MTF Trend Filter
• Use HTF filter / Timeframe / Fast & Slow: HTF Fast>Slow for longs, Fast threshold; exit when spread flips or Confidence decays below your comfort zone.
2) FX index/majors, 15m (active intraday)
• Preset: FX 15m (Active).
• Gate: MinConf 60–70; Min ATR% 0.15–0.30.
• Flow: Focus on session opens (LDN/NY). The ribbon should heat up on shorter candidates before valid crosses appear—good early warning.
3) SPY / Index futures, 1D (positioning)
• Preset: Equities 1D.
• Gate: MinConf 55–65; Min ATR% 0.05–0.12.
• Flow: Use spread crosses as regime flags; add timing from price structure. For adds, wait for ER to remain trending across several bars.
4) BTCUSD, 1H (24/7)
• Preset: Crypto 1H.
• Gate: MinConf 70–80; Min ATR% 0.20–0.35.
• Flow: Crypto chops—volatility filter is your friend. When ribbon and HTF OK agree, favor continuation entries; otherwise stand down.
⸻
Reading the Info Panel (and fixing “no signals”)
The panel is your self-diagnostic:
• HTF OK? False means the higher-timeframe EMAs disagree with your intended side.
• Regime: If “Chop”, ER < threshold. Consider raising the threshold or waiting.
• Confidence: Heat-colored; if below MinConf, the gate blocks signals.
• ATR% vs. Min ATR%: If ATR% < Min ATR%, status shows BLOCK: low vola.
• STATUS (composite):
• BLOCK: low vola → increase Min ATR% down (i.e., allow lower vol) or wait for expansion.
• BLOCK: HTF filter → disable HTF or align with the HTF tide.
• BLOCK: confidence → lower MinConf slightly or wait for stronger alignment.
• OK → you’ll see markers on valid crosses.
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Alerts
Two static alert hooks:
• BUY cross — spread crosses up and all gates (ER, Vol, MTF, Confidence) are open.
• SELL cross — mirror of the above.
Create them once from “Add Alert” → choose the condition by name.
⸻
Exporting to other scripts
In your other Pine indicators/strategies, add an input.source and select EvoTrend-X → “EvoTrend-X Export (spread)”. Common uses:
• Build a rule: only trade when exported spread > 0 (trend filter).
• Combine with your oscillator: oscillator oversold and spread > 0 → buy bias.
⸻
Best practices
• Let it learn: Keep Learning step moderate (0.4–0.6) and Decay close to 1.0 (e.g., 0.99–0.997) for smooth regime memory.
• Respect volatility: Tune Min ATR% by asset and timeframe. FX 1H ≈ 0.10–0.20; crypto 1H ≈ 0.20–0.35; equities 1D ≈ 0.05–0.12.
• MTF discipline: HTF filter removes lots of “almost” trades. If you prefer aggressive entries, turn it off and rely more on Confidence.
• Confidence as throttle:
• 40–60%: exploratory; expect more signals.
• 60–75%: balanced; good daily driver.
• 75–90%: selective; catch the clean stuff.
• 90–100%: only A-setups; patient mode.
• Watch the ribbon: When shorter candidates heat up before a cross, momentum is forming. If long candidates dominate, you’re in a slower trend cycle.
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Non-repainting & safety notes
• All request.security() calls use lookahead=barmerge.lookahead_off, gaps=barmerge.gaps_on.
• No forward references; decisions rely on confirmed bar data.
• EMA lengths are simple ints (no series-length errors).
• Confidence components are computed every bar (no conditional ta.* traps).
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Limitations & tips
• Chop happens: ER helps, but sideways microstructure can still flicker—use Confidence + Vol filter as brakes.
• Presets ≠ oracle: They’re sensible baselines; always tune MinConf and Min ATR% to your venue and session.
• Theme “Auto”: Pine cannot read chart theme; “Auto” defaults to a Dark-friendly palette.
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Publisher’s Screenshots Checklist
1) FX swing — EURUSD 1H
• Preset: FX 1H (Conservative)
• Params: MinConf=70, ATR Len=14, Min ATR%=0.12, MTF ON (TF=4H, 20/50)
• Show: Clear BUY cross, STATUS=OK, green regime background; Fitness Ribbon visible.
2) FX intraday — GBPUSD 15m
• Preset: FX 15m (Active)
• Params: MinConf=60, ATR Len=14, Min ATR%=0.20, MTF ON (TF=60m)
• Show: SELL cross near London session open. HTF lines enabled (translucent).
• Caption: “GBPUSD 15m • Active session sell with MTF alignment.”
3) Indices — SPY 1D
• Preset: Equities 1D
• Params: MinConf=60, ATR Len=14, Min ATR%=0.08, MTF ON (TF=1W, 20/50)
• Show: Longer trend run after BUY cross; regime shading shows persistence.
• Caption: “SPY 1D • Trend run after BUY cross; weekly filter aligned.”
4) Crypto — BINANCE:BTCUSDT 1H
• Preset: Crypto 1H
• Params: MinConf=75, ATR Len=14, Min ATR%=0.25, MTF ON (TF=4H)
• Show: BUY cross + quick follow-through; Ribbon warming (reds/yellows → greens).
• Caption: “BTCUSDT 1H • Momentum break with high confidence and ribbon turning.”
SMC BOS - Structure Breaks & Median Continuation ProjectionsThis tool shows what usually happens after a Break of Structure (BOS).
It scans past BOS events on your chart, finds the ones most similar to the latest break (using ATR to filter by volatility), and then plots the median continuation path.
Optional percentile bands (P10–P90) display the possible range of outcomes around the median.
Key features:
• Automatic detection of bullish and bearish BOS events
• Library of past BOS with adjustable size and spacing
• ATR-based similarity and recency weighting
• Median continuation projections with optional percentile bands
• Customizable colors, signals, and stats table
• Works on any market and timeframe
Use cases:
• See how price typically behaves after a BOS
• Support SMC analysis with data-driven projections
• Improve trade planning by visualizing likely continuations
• Apply across crypto, forex, stocks, and futures
Originality:
Instead of only marking BOS, this script learns from history and projects forward the median path of the most similar past cases, adjusted for volatility. It turns BOS signals into practical continuation scenarios.
Instructions:
Add the indicator to your chart. When a BOS is detected, the projection is drawn automatically.
Use the settings to adjust the library, ATR weighting, projection style, percentile bands, and the display of signals or stats.
For questions or customization, contact Julien Eche (Julien_Eche) on TradingView.
ARO Pro — Adaptive Regime OscillatorARO Pro — Adaptive Regime Oscillator (v6)
ARO Pro turns your chart into a context-aware decision system. It classifies every bar as Trending (up or down) or Ranging in real time, then switches its math to match the regime: trend strength is measured with an ATR-normalized EMA spread, while range behavior is tracked with a center-based RSI oscillator. The result is cleaner entries, fewer false signals, and faster reads on regime shifts—without repainting.
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How it works (under the hood)
1. Regime Detection (Kaufman ER):
ARO computes Kaufman’s Efficiency Ratio (ER) over a user-defined length.
- ER > threshold → Trending (direction from EMA fast vs. EMA slow)
- ER ≤ threshold → Ranging
2. Adaptive Oscillator Core:
- Trend mode: (EMA(fast) − EMA(slow)) / ATR * 100 → momentum normalized by volatility.
- Range mode: RSI(length) − 50 → mean-reversion pressure around zero.
3. Volatility Filter (optional):
Blocks signals if ATR as % of price is below a floor you set. This reduces noise in thin or quiet markets.
4. MTF Trend Filter (optional & non-repainting):
Confirms signals only if a higher timeframe EMA(fast) > EMA(slow) for longs (or < for shorts). Implemented with lookahead_off and gaps_on.
5. Confirmation & Alerts:
Signals are locked only on bar close (barstate.isconfirmed) and offered via three alert types: ARO Long, ARO Short, ARO Regime Shift.
⸻
What you see on the chart
• Background heat:
• Green = Trending Up, Red = Trending Down, Gray = Range.
• ARO line (panel): Adaptive oscillator (trend/value colors).
• Signal markers: ▲ Long / ▼ Short on confirmed bars.
• Guide lines: Upper/Lower thresholds (±K) and zero line.
• Info Panel (table): Regime, ER, ATR %, ARO, HTF status (OK/BLOCK/OFF), and a Confidence light.
• Debug Overlay (optional): Quick view of thresholds and raw conditions for tuning.
⸻
Inputs (quick reference)
• Signals: Fast/Slow EMA, RSI length, ER length & threshold, oscillator smoothing, signal threshold.
• Filters: ATR length, minimum ATR% (volatility floor), toggle for volatility filter.
• Visuals: Background on/off, Info Panel on/off, Debug overlay on/off.
• MTF (safe): Toggle + HTF timeframe (e.g., 240, D, W).
⸻
Interpreting signals
• Long: Trend regime AND fast EMA > slow EMA AND ARO ≥ +threshold (confirmed bar, filters passing).
• Short: Trend regime AND fast EMA < slow EMA AND ARO ≤ −threshold (confirmed bar, filters passing).
• Regime Shift: Alert when ER moves the market from Range → Trend or flips trend direction.
⸻
Practical use cases & examples
1) Intraday momentum alignment (scalps to day trades)
• Timeframes: 5–15m with HTF filter = 4H.
• Flow:
1. Wait for Trend Up background + HTF OK.
2. Enter on ▲ Long when ARO crosses above +threshold.
3. Stops: 1–1.5× ATR(14) below trigger bar or below last micro swing.
4. Exits: Partial at 1× ATR, trail remainder with an ATR stop or when ARO reverts to zero/Regime Shift.
• Why it works: You’re trading with the dominant higher-timeframe structure while avoiding low-volatility fakeouts.
2) Swing trend following (cleaner trend legs)
• Timeframes: 1H–4H with HTF filter = 1D.
• Flow:
1. Only act in Trend background aligned with HTF.
2. Add on subsequent ▲ signals as ARO maintains positive (or negative) territory.
3. Reduce or exit on Regime Shift (Trend → Range or direction flip) or when ARO crosses back through zero.
• Stops/targets: Initial 1.5–2× ATR; move to breakeven once the trade gains 1× ATR; trail with a multiple-ATR or structure lows/highs.
3) Range tactics (fade the extremes)
• Timeframes: 15m–1H or 1D on mean-reverting names.
• Flow:
1. Act only when background = Range.
2. Fade moves when ARO swings from ±extremes back toward zero near well-defined S/R.
3. Exit at the opposite band or zero line; abort if a Regime Shift to Trend occurs.
• Tip: Increase ER threshold (e.g., 0.35–0.40) to label more bars as Range on choppy instruments.
4) Event days & macro filters
• Approach: Raise the volatility floor (Min ATR%) on macro days (FOMC, CPI).
• Effect: You’ll ignore “fake” micro swings in the minutes leading up to releases and catch only post-event confirmed momentum.
⸻
Parameter tuning guide
• ER Threshold:
• Lower (0.20–0.30) = more Trend bars, more signals, higher noise.
• Higher (0.35–0.45) = stricter trend confirmation, fewer but cleaner signals.
• Signal Threshold (±K):
• Raise to reduce whipsaws; lower for earlier but noisier triggers.
• Volatility Floor (ATR%):
• Thin/quiet assets benefit from a higher floor (e.g., 0.3–0.6).
• Highly liquid futures/forex can work with lower floors.
• HTF Filter:
• Keep it ON when you want higher win consistency; turn OFF for tactical counter-trend plays.
⸻
Alerts (recommended setup)
• “ARO Long” / “ARO Short”: Entry-style alerts on confirmed signals.
• “ARO Regime Shift”: Context alert to scale in/out or switch playbooks (trend vs. range).
All alerts are non-repainting and fire only when the bar closes.
⸻
Best practices & combinations
• Price action & S/R: Use ARO to define when to engage, and price structure to define where (breakout levels, pullback zones).
• VWAP/Session tools: In intraday trends, ▲ signals above VWAP tend to carry; avoid shorts below session VWAP in strong downtrends.
• Risk first: Size by ATR; never let a single ARO event override your max risk per trade.
• Portfolio filter: On indices/ETFs, enable HTF filter and a stricter ER threshold to ride regime legs.
⸻
Non-repaint and implementation notes
• The script does not repaint:
• Signals are computed and locked on bar close (barstate.isconfirmed).
• All higher-timeframe data uses request.security(..., lookahead_off, gaps_on).
• No future indexing or negative offsets are used.
• The Info Panel and Debug overlay are purely visual aids and do not change signal logic.
⸻
Limitations & tips
• Chop sensitivity: In hyper-choppy symbols, consider raising ER threshold and the signal threshold, and enable HTF filter.
• Instrument personality: EMAs/RSI lengths and volatility floor often need a quick 2–3 minute tune per asset class (FX vs. crypto vs. equities).
• No guarantees: ARO improves context and timing, but it is not a promise of profitability—always combine with risk management.
⸻
Quick start (TL;DR)
1. Timeframes: 5–15m intraday (HTF = 4H); 1H–4H swing (HTF = 1D).
2. Use defaults, then tune ER threshold (0.25–0.40) and Signal threshold (±20).
3. Enable Volatility Floor (e.g., 0.2–0.5 ATR%) on quiet assets.
4. Trade ▲ / ▼ only in matching Trend background; fade extremes only in Range background.
5. Set alerts for Long, Short, and Regime Shift; manage risk with ATR stops.
⸻
Author’s note: ARO Pro is designed to be clear, adaptive, and operational out of the box. If you publish variants (e.g., different ER logic, alternative trend cores), please credit the original and document any changes so users can compare behavior reliably.
主力资金进出监控器Main Capital Flow Monitor-MEWINSIGHTMain Capital Flow Monitor Indicator
Indicator Description
This indicator utilizes a multi-cycle composite weighting algorithm to accurately capture the movement of main capital in and out of key price zones. The core logic is built upon three dimensions:
Multi-Cycle Pressure/Support System
Using triple timeframes (500-day/250-day/90-day) to calculate:
Long-term resistance lines (VAR1-3): Monitoring historical high resistance zones
Long-term support lines (VAR4-6): Identifying historical low support zones
EMA21 smoothing is applied to eliminate short-term fluctuations
Dynamic Capital Activity Engine
Proprietary VARD volatility algorithm:
VARD = EMA
Automatically amplifies volatility sensitivity by 10x when price approaches the safety margin (VARA×1.35), precisely capturing abnormal main capital movements
Capital Inflow Trigger Mechanism
Capital entry signals require simultaneous fulfillment of:
Price touching 30-day low zone (VARE)
Capital activity breaking recent peaks (VARF)
Weighted capital flow verified through triple EMA:
Capital Entry = EMA / 618
Visualization:
Green histogram: Continuous main capital inflow
Red histogram: Abnormal daily capital movement intensity
Column height intuitively displays capital strength
Application Scenarios:
Consecutive green columns → Main capital accumulation at bottom
Sudden expansion of red columns → Abnormal main capital rush
Continuous fluctuations near zero axis → Main capital washing phase
Core Value:
Provides 1-3 trading days early warning of main capital movements, suitable for:
Medium/long-term investors identifying main capital accumulation zones
Short-term traders capturing abnormal main capital breakouts
Risk control avoiding main capital distribution phases
Parameter Notes: Default parameters are optimized through historical A-share market backtesting. Users can adjust cycle parameters according to different market characteristics (suggest extending cycles by 20% for European/American markets).
Formula Features:
Multi-timeframe weighted synthesis technology
Dynamic sensitivity adjustment mechanism
Main capital activity intensity quantification
Early warning function for capital movements
Suitable Markets:
Stocks, futures, cryptocurrencies and other financial markets with obvious main capital characteristics.
指标名称：主力资金进出监控器
指标描述：
本指标通过多周期复合加权算法，精准捕捉主力资金在关键价格区域的进出动向。核心逻辑基于三大维度构建：
多周期压力/支撑体系
通过500日/250日/90日三重时间框架，分别计算：
长期压力线（VAR1-3）：监控历史高位阻力区
长期支撑线（VAR4-6）：识别历史低位承接区
采用EMA21平滑处理，消除短期波动干扰
动态资金活跃度引擎
独创VARD波动率算法：
当价格接近安全边际（VARA×1.35）时自动放大波动敏感度10倍，精准捕捉主力异动
资金进场触发机制
资金入场信号需同时满足：
价格触及30日最低区域（VARE）
资金活跃度突破近期峰值（VARF）
通过三重EMA验证的加权资金流：
资金入场 = EMA / 618
可视化呈现：
绿色柱状图：主力资金持续流入
红色柱状图：当日资金异动量级
柱体高度直观显示资金强度
使用场景：
绿色柱体连续出现 → 主力底部吸筹
红色柱体突然放大 → 主力异动抢筹
零轴附近持续波动 → 主力洗盘阶段
核心价值：
提前1-3个交易日预警主力资金动向，适用于：
中长线投资者识别主力建仓区间
短线交易者捕捉主力异动突破
风险控制规避主力出货阶段
参数说明：默认参数经A股历史数据回测优化，用户可根据不同市场特性调整周期参数（建议欧美市场延长周期20%）
Weekend Hunter Ultimate v6.2 Weekend Hunter Ultimate v6.2 - Automated Crypto Weekend Trading System
OVERVIEW:
Specialized trading strategy designed for cryptocurrency weekend markets (Saturday-Sunday) when institutional traders are typically offline and market dynamics differ significantly from weekdays. Optimized for 15-minute timeframe execution with multi-timeframe confluence analysis.
KEY FEATURES:
- Weekend-Only Trading: Automatically activates during configurable weekend hours
- Dynamic Leverage: 5-20x leverage adjusted based on market safety and signal confidence
- Multi-Timeframe Analysis: Combines 4H trend, 1H momentum, and 15M execution
- 10 Pre-configured Crypto Pairs: BTC, ETH, LINK, XRP, DOGE, SOL, AVAX, PEPE, TON, POL
- Position & Risk Management: Max 4 concurrent positions, -30% account protection
- Smart Trailing Stops: Protects profits when approaching targets
RISK MANAGEMENT:
- Maximum daily loss: 5% (configurable)
- Maximum weekend loss: 15% (configurable)
- Per-position risk: Capped at 120-156 USDT
- Emergency stops for flash crashes (8% moves)
- Consecutive loss protection (4 losses = pause)
TECHNICAL INDICATORS:
- CVD (Cumulative Volume Delta) divergence detection
- ATR-based dynamic stop loss and take profit
- RSI, MACD, Bollinger Bands confluence
- Volume surge confirmation (1.5x average)
- Weekend liquidity adjustments
INTEGRATION:
- Designed for Bybit Futures (0.075% taker fee)
- WunderTrading webhook compatibility via JSON alerts
- Minimum position size: 120 USDT (Bybit requirement)
- Initial capital: $500 recommended
TARGET METRICS:
- Win rate target: 65%
- Average win: 5.5%
- Average loss: 1.8%
- Risk-reward ratio: ~3:1
IMPORTANT DISCLAIMERS:
- Past performance does not guarantee future results
- Leveraged trading carries substantial risk of loss
- Weekend crypto markets have 13% of normal liquidity
- Not suitable for traders who cannot afford to lose their entire investment
- Requires continuous monitoring and adjustment
USAGE:
1. Apply to 15-minute charts only
2. Configure weekend hours for your timezone
3. Set up webhook alerts for automation
4. Monitor performance table in top-right corner
5. Adjust parameters based on your risk tolerance
This is an experimental strategy for educational purposes. Always test with small amounts first and never invest more than you can afford to lose completely.
ORB Pro w/ Filters + Debug Overlay Update with Reason box fixThis indicator is designed to highlight high-probability reversal setups for intraday traders.
It focuses on the cleanest, most reliable candlestick reversal patterns and combines them with trend, VWAP/EMA confluence, and a time-based filter to reduce noise.
🛠️ How It Works
The script scans each bar for well-known reversal signals:
Doji Reversal – small body, long wicks showing indecision.
Hammer / Shooting Star – long wick ≥ 2× body, showing exhaustion.
Engulfing Reversal – full body engulf of the prior candle.
Additional filters include:
✅ VWAP/EMA Confluence (optional) – confirms reversals near key intraday levels.
✅ Time Window (default 9:30–10:30 NY) – avoids false signals later in the session.
✅ Trend Exhaustion Check – requires a short-term directional push before reversal.
✅ Signal Cooldown – limits to one clean signal per move.
When conditions align, the script plots:
🟢 “Bull Rev” label below the bar for bullish reversals.
🔴 “Bear Rev” label above the bar for bearish reversals.
⚙️ Recommended Settings
For the tightest, most reliable signals:
Doji Body % → 25–30
Hammer Wick Multiple → 2.0
Confluence Tolerance % → 0.2–0.3
Time Filter → ON (9:30–10:30 NY)
VWAP/EMA Filter → ON
Cooldown Bars → 10–15
These settings minimize false positives and focus on the strongest reversals.
📈 Use Case
This tool is best for:
Intraday traders (stocks, ETFs, futures, crypto).
Traders who use Opening Range Breakout (ORB) or similar systems but want a secondary tool for catching reversals.
Anyone looking to filter out weak reversal patterns and focus on textbook setups.
⚠️ Disclaimer
This script is for educational purposes only and should not be considered financial advice. Always test in simulation/paper trading before applying live
🚀 Catch textbook reversals with confidence.
This indicator filters out noise and only plots high-probability reversal signals based on proven candlestick patterns + VWAP/EMA confluence.
🔥 Key Features:
✅ Detects Doji, Hammer/Shooting Star, and Engulfing Reversals
✅ VWAP & EMA confluence filter (optional)
✅ Time window filter (default 9:30–10:30 NY for max edge)
✅ Signal cooldown to avoid clutter
✅ Clean chart labels + alert conditions
🎯 Who’s It For?
Day traders who want precision reversal entries
ORB traders looking for secondary setups
Intraday scalpers who value quality over quantity
👉 Designed for traders who want fewer, cleaner, higher-probability signals.
⚠️ Not financial advice. For educational use only
_____
🎯 ORB SET-UP DESCRIPTIONS:
🔧 Exact settings I’d recommend (to avoid that mess):
requireClose = true
requireRetest = true with retestPct = 0.2%
minRangePct = 0.3%, maxRangePct = 1.5%
volumeFilter = true, volumeLength = 20
trendFilter = true, emaLength = 20
cooldownBars = 6 (on 5m chart → 30 minutes)
🔑 ORB Range Settings
Default sweet spot: 0.2% – 0.3%
→ This usually balances enough signals with reduced false breakouts.
High volatility days (CPI, FOMC, big gaps): 0.3% – 0.5%
→ Prevents fake outs.
Low volatility days (tight overnight range, slow open): 0.15% – 0.2%
→ Keeps you from sitting on hands all day.
📌 Filters you already added help you avoid noise
EMA alignment
Volume confirmation
Optional stop/target logic
This means you don’t have to shrink the box to 0.1% — the filters will keep you in higher-probability trades
✅ Why You Might NOT See a Signal
Check box for reason signal to turn it off, updated coloring so that candles are more visable.
ORB Box Too Wide
If the opening range is large, price has to move much further to trigger a clean breakout.
Wide box = fewer signals (but higher quality).
No Clean Break + Hold
Script waits for a candle to break above/below ORB and close strong enough.
A wick poke doesn’t count.
VWAP / EMA Filter Not Aligned
If price breaks but VWAP/EMA trend filter disagrees → no signal.
Keeps you out of fake moves against the trend.
Confirmation Candle Missing (if enabled)
Even if price breaks, the script may want the next bar to confirm direction before signaling.
Cooldown / One-Signal-Per-Break Rule
Some filters prevent back-to-back spam signals.
Only the first clean setup is alerted.
