Seasonality Heatmap [QuantAlgo]🟢 Overview
The Seasonality Heatmap analyzes years of historical data to reveal which months and weekdays have consistently produced gains or losses, displaying results through color-coded tables with statistical metrics like consistency scores (1-10 rating) and positive occurrence rates. By calculating average returns for each calendar month and day-of-week combination, it identifies recognizable seasonal patterns (such as which months or weekdays tend to rally versus decline) and synthesizes this into actionable buy low/sell high timing possibilities for strategic entries and exits. This helps traders and investors spot high-probability seasonal windows where assets have historically shown strength or weakness, enabling them to align positions with recurring bull and bear market patterns.
🟢 How It Works
1. Monthly Heatmap
How % Return is Calculated:
The indicator fetches monthly closing prices (or Open/High/Low based on user selection) and calculates the percentage change from the previous month:
(Current Month Price - Previous Month Price) / Previous Month Price × 100
Each cell in the heatmap represents one month's return in a specific year, creating a multi-year historical view
Colors indicate performance intensity: greener/brighter shades for higher positive returns, redder/brighter shades for larger negative returns
What Averages Mean:
The "Avg %" row displays the arithmetic mean of all historical returns for each calendar month (e.g., averaging all Januaries together, all Februaries together, etc.)
This metric identifies historically recurring patterns by showing which months have tended to rise or fall on average
Positive averages indicate months that have typically trended upward; negative averages indicate historically weaker months
Example: If April shows +18.56% average, it means April has averaged a 18.56% gain across all years analyzed
What Months Up % Mean:
Shows the percentage of historical occurrences where that month had a positive return (closed higher than the previous month)
Calculated as:
(Number of Months with Positive Returns / Total Months) × 100
Values above 50% indicate the month has been positive more often than negative; below 50% indicates more frequent negative months
Example: If October shows "64%", then 64% of all historical Octobers had positive returns
What Consistency Score Means:
A 1-10 rating that measures how predictable and stable a month's returns have been
Calculated using the coefficient of variation (standard deviation / mean) - lower variation = higher consistency
High scores (8-10, green): The month has shown relatively stable behavior with similar outcomes year-to-year
Medium scores (5-7, gray): Moderate consistency with some variability
Low scores (1-4, red): High variability with unpredictable behavior across different years
Example: A consistency score of 8/10 indicates the month has exhibited recognizable patterns with relatively low deviation
What Best Means:
Shows the highest percentage return achieved for that specific month, along with the year it occurred
Reveals the maximum observed upside and identifies outlier years with exceptional performance
Useful for understanding the range of possible outcomes beyond the average
Example: "Best: 2016: +131.90%" means the strongest January in the dataset was in 2016 with an 131.90% gain
What Worst Means:
Shows the most negative percentage return for that specific month, along with the year it occurred
Reveals maximum observed downside and helps understand the range of historical outcomes
Important for risk assessment even in months with positive averages
Example: "Worst: 2022: -26.86%" means the weakest January in the dataset was in 2022 with a 26.86% loss
2. Day-of-Week Heatmap
How % Return is Calculated:
Calculates the percentage change from the previous day's close to the current day's price (based on user's price source selection)
Returns are aggregated by day of the week within each calendar month (e.g., all Mondays in January, all Tuesdays in January, etc.)
Each cell shows the average performance for that specific day-month combination across all historical data
Formula:
(Current Day Price - Previous Day Close) / Previous Day Close × 100
What Averages Mean:
The "Avg %" row at the bottom aggregates all months together to show the overall average return for each weekday
Identifies broad weekly patterns across the entire dataset
Calculated by summing all daily returns for that weekday across all months and dividing by total observations
Example: If Monday shows +0.04%, Mondays have averaged a 0.04% change across all months in the dataset
What Days Up % Mean:
Shows the percentage of historical occurrences where that weekday had a positive return
Calculated as:
(Number of Positive Days / Total Days Observed) × 100
Values above 50% indicate the day has been positive more often than negative; below 50% indicates more frequent negative days
Example: If Fridays show "54%", then 54% of all Fridays in the dataset had positive returns
What Consistency Score Means:
A 1-10 rating measuring how stable that weekday's performance has been across different months
Based on the coefficient of variation of daily returns for that weekday across all 12 months
High scores (8-10, green): The weekday has shown relatively consistent behavior month-to-month
Medium scores (5-7, gray): Moderate consistency with some month-to-month variation
Low scores (1-4, red): High variability across months, with behavior differing significantly by calendar month
Example: A consistency score of 7/10 for Wednesdays means they have performed with moderate consistency throughout the year
What Best Means:
Shows which calendar month had the strongest average performance for that specific weekday
Identifies favorable day-month combinations based on historical data
Format shows the month abbreviation and the average return achieved
Example: "Best: Oct: +0.20%" means Mondays averaged +0.20% during October months in the dataset
What Worst Means:
Shows which calendar month had the weakest average performance for that specific weekday
Identifies historically challenging day-month combinations
Useful for understanding which month-weekday pairings have shown weaker performance
Example: "Worst: Sep: -0.35%" means Tuesdays averaged -0.35% during September months in the dataset
3. Optimal Timing Table/Summary Table
→ Best Month to BUY: Identifies the month with the lowest average return (most negative or least positive historically), representing periods where prices have historically been relatively lower
Based on the observation that buying during historically weaker months may position for subsequent recovery
Shows the month name, its average return, and color-coded performance
Example: If May shows -0.86% as "Best Month to BUY", it means May has historically averaged -0.86% in the analyzed period
→ Best Month to SELL: Identifies the month with the highest average return (most positive historically), representing periods where prices have historically been relatively higher
Based on historical strength patterns in that month
Example: If July shows +1.42% as "Best Month to SELL", it means July has historically averaged +1.42% gains
→ 2nd Best Month to BUY: The second-lowest performing month based on average returns
Provides an alternative timing option based on historical patterns
Offers flexibility for staged entries or when the primary month doesn't align with strategy
Example: Identifies the next-most favorable historical buying period
→ 2nd Best Month to SELL: The second-highest performing month based on average returns
Provides an alternative exit timing based on historical data
Useful for staged profit-taking or multiple exit opportunities
Identifies the secondary historical strength period
Note: The same logic applies to "Best Day to BUY/SELL" and "2nd Best Day to BUY/SELL" rows, which identify weekdays based on average daily performance across all months. Days with lowest averages are marked as buying opportunities (historically weaker days), while days with highest averages are marked for selling (historically stronger days).
🟢 Examples
Example 1: NVIDIA NASDAQ:NVDA - Strong May Pattern with High Consistency
Analyzing NVIDIA from 2015 onwards, the Monthly Heatmap reveals May averaging +15.84% with 82% of months being positive and a consistency score of 8/10 (green). December shows -1.69% average with only 40% of months positive and a low 1/10 consistency score (red). The Optimal Timing table identifies December as "Best Month to BUY" and May as "Best Month to SELL." A trader recognizes this high-probability May strength pattern and considers entering positions in late December when prices have historically been weaker, then taking profits in May when the seasonal tailwind typically peaks. The high consistency score in May (8/10) provides additional confidence that this pattern has been relatively stable year-over-year.
Example 2: Crypto Market Cap CRYPTOCAP:TOTALES - October Rally Pattern
An investor examining total crypto market capitalization notices September averaging -2.42% with 45% of months positive and 5/10 consistency, while October shows a dramatic shift with +16.69% average, 90% of months positive, and an exceptional 9/10 consistency score (blue). The Day-of-Week heatmap reveals Mondays averaging +0.40% with 54% positive days and 9/10 consistency (blue), while Thursdays show only +0.08% with 1/10 consistency (yellow). The investor uses this multi-layered analysis to develop a strategy: enter crypto positions on Thursdays during late September (combining the historically weak month with the less consistent weekday), then hold through October's historically strong period, considering exits on Mondays when intraweek strength has been most consistent.
Example 3: Solana BINANCE:SOLUSDT - Extreme January Seasonality
A cryptocurrency trader analyzing Solana observes an extraordinary January pattern: +59.57% average return with 60% of months positive and 8/10 consistency (teal), while May shows -9.75% average with only 33% of months positive and 6/10 consistency. August also displays strength at +59.50% average with 7/10 consistency. The Optimal Timing table confirms May as "Best Month to BUY" and January as "Best Month to SELL." The Day-of-Week data shows Sundays averaging +0.77% with 8/10 consistency (teal). The trader develops a seasonal rotation strategy: accumulate SOL positions during May weakness, hold through the historically strong January period (which has shown this extreme pattern with reasonable consistency), and specifically target Sunday exits when the weekday data shows the most recognizable strength pattern.
Ciclos
Herd Flow Oscillator — Volume Distribution Herd Flow Oscillator — Scientific Volume Distribution (herd-accurate rev)
A composite order-flow oscillator designed to surface true herding behavior — not just random bursts of buying or selling.
It’s built to detect when market participants start acting together, showing persistent, one-sided activity that statistically breaks away from normal market randomness.
Unlike traditional volume or momentum indicators, this tool doesn’t just look for “who’s buying” or “who’s selling.”
It tries to quantify crowd behavior by blending multiple statistical tests that describe how collective sentiment and coordination unfold in price and volume dynamics.
What it shows
The Herd Flow Oscillator works as a multi-layer detector of crowd-driven flow in the market. It examines how signed volume (buy vs. sell pressure) evolves, how persistent it is, and whether those actions are unusually coordinated compared to random expectations.
HerdFlow Composite (z) — the main signal line, showing how statistically extreme the current herding pressure is.
When this crosses above or below your set thresholds, it suggests a high probability of collective buying or selling.
You can optionally reveal component panels for deeper insight into why herding is detected:
DVI (Directional Volume Imbalance): Measures the ratio of bullish vs. bearish volume.
If it’s strongly positive, more volume is hitting the ask (buying); if negative, more is hitting the bid (selling).
LSV-style Herd Index : Inspired by academic finance measures of “herding.”
It compares how often volume is buying vs. selling versus what would happen by random chance.
If the result is significantly above chance, it means traders are collectively biased in one direction.
O rder-Flow Persistence (ρ 1..K): Averages autocorrelation of signed volume over several lags.
In simpler terms: checks if buying/selling pressure tends to continue in the same direction across bars.
Positive persistence = ongoing coordination, not just isolated trades.
Runs-Test Herding (−Z) : Statistical test that checks how often trade direction flips.
When there are fewer direction changes than expected, it means trades are clustering — a hallmark of herd behavior.
Skew (signed volume): Measures whether signed volume is heavily tilted to one side.
A positive skew means more aggressive buying bursts; a negative skew means more intense selling bursts.
CVD Slope (z): Looks at the slope of the Cumulative Volume Delta — essentially how quickly buy/sell pressure is accelerating.
It’s a short-term flow acceleration measure.
Shapes & background
▲ “BH” at the bottom = Bull Herding; ▼ “BH-” at the top = Bear Herding.
These markers appear when all conditions align to confirm a herding regime.
Persistence and clustering both confirm coordinated downside flow.
Core Windows
Primary Window (N) — the main sample length for herding calculations.
It’s like the "memory span" for detecting coordinated behavior. A longer N means smoother, more reliable signals.
Short Window (Nshort) — used for short-term measurements like imbalance and slope.
Smaller values react faster but can be noisy; larger values are steadier but slower.
Long Window (Nlong) — used for z-score normalization (statistical scaling).
This helps the indicator understand what’s “normal” behavior over a longer horizon, so it can spot when things deviate too far.
Autocorr lags (acLags) — how many steps to check when measuring persistence.
Higher values (e.g., 3–5) look further back to see if trends are truly continuing.
Calculation Options
Price Proxy for Tick Rule — defines how to decide if a trade is “buy” or “sell.”
hlc3 (average of high, low, and close) works as a neutral, smooth price proxy.
Use ATR for scaling — keeps signals comparable across assets and timeframes by dividing by volatility (ATR).
Prevents high-volatility periods from dominating the signal.
Median Filter (bars) — smooths out erratic data spikes without heavily lagging the response.
Odd values like 3 or 5 work best.
Signal Thresholds
Composite z-threshold — determines how extreme behavior must be before it counts as “herding.”
Higher values = fewer, more confident signals.
Imbalance threshold — the minimum directional volume imbalance to trigger interest.
Plotting
Show component panels — useful for analysts and developers who want to inspect the math behind signals.
Fill strong herding zones — purely visual aid to highlight key periods of coordinated trading.
How to use it (practical tips)
Understand the purpose: This is not just a “buy/sell” tool.
It’s a behavioral detector that identifies when traders or algorithms start acting in the same direction.
Timeframe flexibility:
15m–1h: reveals short-term crowd shifts.
4h–1D: better for swing-trade context and institutional positioning.
Combine with structure or trend:
When HerdFlow confirms a bullish regime during a breakout or retest, it adds confidence.
Conversely, a bearish cluster at resistance may hint at a crowd-driven rejection.
Threshold tuning:
To make it more selective, increase zThr and imbThr.
To make it more sensitive, lower those thresholds but expand your primary window N for smoother results.
Cross-market consistency:
Keep “Use ATR for scaling” enabled to maintain consistency across different instruments or timeframes.
Denoising:
A small median filter (3–5 bars) removes flicker from volume spikes but still preserves the essential crowd patterns.
Reading the components (why signals fire)
Each sub-metric describes a unique “dimension” of crowd behavior:
DVI: how imbalanced buying vs selling is.
Herd Index: how biased that imbalance is compared to random expectation.
Persistence (ρ): how continuous those flows are.
Runs-Test: how clumped together trades are — clustering means the crowd’s acting in sync.
Skew: how lopsided the volume distribution is — sudden surges of one-sided aggression.
CVD Slope: how strongly accelerating the current directional flow is.
When all of these line up, you’re seeing evidence that market participants are collectively moving in the same direction — i.e., true herding.
QUANTUM MOMENTUMOverview
Quantum Momentum is a sophisticated technical analysis tool designed to help traders identify relative strength between assets through advanced momentum comparison. This cyberpunk-themed indicator visualizes momentum dynamics between your current trading symbol and any comparison asset of your choice, making it ideal for pairs trading, crypto correlation analysis, and multi-asset portfolio management.
Key Features
📊 Multi-Asset Momentum Comparison
Dual Symbol Analysis: Compare momentum between your chart symbol and any other tradable asset
Real-Time Tracking: Monitor relative momentum strength as market conditions evolve
Difference Visualization: Clear histogram display showing which asset has stronger momentum
🎯 Multiple Momentum Calculation Methods
Choose from four different momentum calculation types:
ROC (Rate of Change): Traditional percentage-based momentum measurement
RSI (Relative Strength Index): Oscillator-based momentum from 0-100 range
Percent Change: Simple percentage change over the lookback period
Raw Change: Absolute price change in native currency units
📈 Advanced Trend Filtering System
Enable optional trend filters to align momentum signals with prevailing market direction:
SMA (Simple Moving Average): Classic trend identification
EMA (Exponential Moving Average): Responsive trend detection
Price Action: Identifies trends through higher highs/lows or lower highs/lows patterns
ADX (Average Directional Index): Measures trend strength with customizable threshold
🎨 Futuristic Cyberpunk Design
Neon Color Scheme: Eye-catching cyan, magenta, and matrix green color palette
Glowing Visual Effects: Enhanced visibility with luminescent plot lines
Dynamic Background Shading: Subtle trend state visualization
Real-Time Data Table: Sleek information panel displaying current momentum values and trend status
How It Works
The indicator calculates momentum for both your current chart symbol and a comparison symbol (default: BTC/USDT) using your selected method and lookback period. The difference between these momentum values reveals which asset is exhibiting stronger momentum at any given time.
Positive Difference (Green): Your chart symbol has stronger momentum than the comparison asset
Negative Difference (Pink/Red): The comparison asset has stronger momentum than your chart symbol
When the trend filter is enabled, the indicator will only display signals that align with the detected market trend, helping filter out counter-trend noise.
Settings Guide
Symbol Settings
Compare Symbol: Choose any tradable asset to compare against (e.g., major indices, cryptocurrencies, forex pairs)
Momentum Settings
Momentum Length: Lookback period for momentum calculations (default: 14 bars)
Momentum Type: Select your preferred momentum calculation method
Display Options
Toggle visibility of current symbol momentum line
Toggle visibility of comparison symbol momentum line
Toggle visibility of momentum difference histogram
Optional zero line reference
Trend Filter Settings
Use Trend Filter: Enable/disable trend-based signal filtering
Trend Method: Choose from SMA, EMA, Price Action, or ADX
Trend Length: Period for trend calculations (default: 50)
ADX Threshold: Minimum ADX value to confirm trend strength (default: 25)
Best Use Cases
✅ Pairs Trading: Identify divergences in momentum between correlated assets
✅ Crypto Market Analysis: Compare altcoin momentum against Bitcoin or Ethereum
✅ Stock Market Rotation: Track sector or index relative strength
✅ Forex Strength Analysis: Monitor currency pair momentum relationships
✅ Multi-Timeframe Confirmation: Use alongside other indicators for confluence
✅ Mean Reversion Strategies: Spot extreme momentum divergences for potential reversals
Visual Indicators
⚡ Cyan Line: Your chart symbol's momentum
⚡ Magenta Line: Comparison symbol's momentum
📊 Green/Pink Histogram: Momentum difference (positive = green, negative = pink)
▲ Green Triangle: Bullish trend detected (when filter enabled)
▼ Red Triangle: Bearish trend detected (when filter enabled)
◈ Yellow Diamond: Neutral/sideways trend (when filter enabled)
Pro Tips
💡 Look for crossovers between the momentum lines as potential trade signals
💡 Combine with volume analysis for stronger confirmation
💡 Use momentum divergence (price making new highs/lows while momentum doesn't) for reversal signals
💡 Enable trend filter during ranging markets to reduce false signals
💡 Experiment with different momentum types to find what works best for your trading style
Technical Requirements
TradingView Pine Script Version: v6
Chart Type: Works on all chart types
Indicator Placement: Separate pane (overlay=false)
Data Requirements: Needs access to comparison symbol data
Forecast PriceTime Oracle [CHE] Forecast PriceTime Oracle — Prioritizes quality over quantity by using Power Pivots via RSI %B metric to forecast future pivot highs/lows in price and time
Summary
This indicator identifies potential pivot highs and lows based on out-of-bounds conditions in a modified RSI %B metric, then projects future occurrences by estimating time intervals and price changes from historical medians. It provides visual forecasts via diagonal and horizontal lines, tracks achievement with color changes and symbols, and displays a dashboard for statistical overview including hit rates. Signals are robust due to median-based aggregation, which reduces outlier influence, and optional tolerance settings for near-misses, making it suitable for anticipating reversals in ranging or trending markets.
Motivation: Why this design?
Standard pivot detection often lags or generates false signals in volatile conditions, missing the timing of true extrema. This design leverages out-of-bounds excursions in RSI %B to capture "Power Pivots" early—focusing on quality over quantity by prioritizing significant extrema rather than every minor swing—then uses historical deltas in time and price to forecast the next ones, addressing the need for proactive rather than reactive analysis. It assumes that pivot spacing follows statistical patterns, allowing users to prepare entries or exits ahead of confirmation.
What’s different vs. standard approaches?
- Reference baseline: Diverges from traditional ta.pivothigh/low, which require fixed left/right lengths and confirm only after bars close, often too late for dynamic markets.
- Architecture differences:
- Detects extrema during OOB runs rather than post-bar symmetry.
- Aggregates deltas via medians (or alternatives) over a user-defined history, capping arrays to manage resources.
- Applies tolerance thresholds for hit detection, with options for percentage, absolute, or volatility-adjusted (ATR) flexibility.
- Freezes achieved forecasts with visual states to avoid clutter.
- Practical effect: Charts show proactive dashed projections instead of retrospective dots; the dashboard reveals evolving hit rates, helping users gauge reliability over time without manual calculation.
How it works (technical)
The indicator first computes a smoothed RSI over a specified length, then applies Bollinger Bands to derive %B, flagging out-of-bounds below zero or above one hundred as potential run starts. During these runs, it tracks the extreme high or low price and bar index. Upon exit from the OOB state, it confirms the Power Pivot at that extreme and records the time delta (bars since prior) and price change percentage to rolling arrays.
For forecasts, it calculates the median (or selected statistic) of recent deltas, subtracts the confirmation delay (bars from apex to exit), and projects ahead by that adjusted amount. Price targets use the median change applied to the origin pivot value. Lines are drawn from the apex to the target bar and price, with a short horizontal at the endpoint. Arrays store up to five active forecasts, pruning oldest on overflow.
Tolerance adjusts hit checks: for highs, if the high reaches or exceeds the target (adjusted by tolerance); for lows, if the low drops to or below. Once hit, the forecast freezes, changing colors and symbols, and extends the horizontal to the hit bar. Persistent variables maintain last pivot states across bars; arrays initialize empty and grow until capped at history length.
Parameter Guide
Source: Specifies the data input for the RSI computation, influencing how price action is captured. Default is close. For conservative signals in noisy environments, switch to high; using low boosts responsiveness but may increase false positives.
RSI Length: Sets the smoothing period for the RSI calculation, with longer values helping to filter out whipsaws. Default is 32. Opt for shorter lengths like 14 to 21 on faster timeframes for quicker reactions, or extend to 50 or more in strong trends to enhance stability at the cost of some lag.
BB Length: Defines the period for the Bollinger Bands applied to %B, directly affecting how often out-of-bounds conditions are triggered. Default is 20. Align it with the RSI length: shorter periods detect more potential runs but risk added noise, while longer ones provide better filtering yet might overlook emerging extrema.
BB StdDev: Controls the multiplier for the standard deviation in the bands, where wider settings reduce false out-of-bounds alerts. Default is 2.0. Narrow it to 1.5 for highly volatile assets to catch more signals, or broaden to 2.5 or higher to emphasize only major movements.
Show Price Forecast: Enables or disables the display of diagonal and target lines along with their updates. Default is true. Turn it off for simpler chart views, or keep it on to aid in trade planning.
History Length: Determines the number of recent pivot samples used for median-based statistics, where more history leads to smoother but potentially less current estimates. Default is 50. Start with a minimum of 5 to build data; limit to 100 to 200 to prevent outdated regimes from skewing results.
Max Lookahead: Limits the number of bars projected forward to avoid overly extended lines. Default is 500. Reduce to 100 to 200 for intraday focus, or increase for longer swing horizons.
Stat Method: Selects the aggregation technique for time and price deltas: Median for robustness against outliers, Trimmed Mean (20%) for a balanced trim of extremes, or 75th Percentile for a conservative upward tilt. Default is Median. Use Median for even distributions; switch to Percentile when emphasizing potential upside in trending conditions.
Tolerance Type: Chooses the approach for flexible hit detection: None for exact matches, Percentage for relative adjustments, Absolute for fixed point offsets, or ATR for scaling with volatility. Default is None. Begin with Percentage at 0.5 percent for currency pairs, or ATR for adapting to cryptocurrency swings.
Tolerance %: Provides the relative buffer when using Percentage mode, forgiving small deviations. Default is 0.5. Set between 0.2 and 1.0 percent; higher values accommodate gaps but can overstate hit counts.
Tolerance Points: Establishes a fixed offset in price units for Absolute mode. Default is 0.0010. Tailor to the asset, such as 0.0001 for forex pairs, and validate against past wick behavior.
ATR Length: Specifies the period for the Average True Range in dynamic tolerance calculations. Default is 14. This is the standard setting; shorten to 10 to reflect more recent volatility.
ATR Multiplier: Adjusts the ATR scale for tolerance width in ATR mode. Default is 0.5. Range from 0.3 for tighter precision to 0.8 for greater leniency.
Dashboard Location: Positions the summary table on the chart. Default is Bottom Right. Consider Top Left for better visibility on mobile devices.
Dashboard Size: Controls the text scaling for dashboard readability. Default is Normal. Choose Tiny for dense overlays or Large for detailed review sessions.
Text/Frame Color: Sets the color scheme for dashboard text and borders. Default is gray. Align with your chart theme, opting for lighter shades on dark backgrounds.
Reading & Interpretation
Forecast lines appear as dashed diagonals from confirmed pivots to projected targets, with solid horizontals at endpoints marking price levels. Open targets show a target symbol (🎯); achieved ones switch to a trophy symbol (🏆) in gray, with lines fading to gray. The dashboard summarizes median time/price deltas, sample counts, and hit rates—rising rates indicate improving forecast alignment. Colors differentiate highs (red) from lows (lime); frozen states signal validated projections.
Practical Workflows & Combinations
- Trend following: Enter long on low forecast hits during uptrends (higher highs/lower lows structure); filter with EMA crossovers to ignore counter-trend signals.
- Reversal setups: Short above high projections in overextended rallies; use volume spikes as confirmation to reduce false breaks.
- Exits/Stops: Trail stops to prior pivot lows; conservative on low hit rates (below 50%), aggressive above 70% with tight tolerance.
- Multi-TF: Apply on 1H for entries, 4H for time projections; combine with Ichimoku clouds for confluence on targets.
- Risk management: Position size inversely to delta uncertainty (wider history = smaller bets); avoid low-liquidity sessions.
Behavior, Constraints & Performance
Confirmation occurs on OOB exit, so live-bar pivots may adjust until close, but projections update only on events to minimize repaint. No security or HTF calls, so no external lookahead issues. Arrays cap at history length with shifts; forecasts limited to five active, pruning FIFO. Loops iterate over small fixed sizes (e.g., up to 50 for stats), efficient on most hardware. Max lines/labels at 500 prevent overflow.
Known limits: Sensitive to OOB parameter tuning—too tight misses runs; assumes stationary pivot stats, which may shift in regime changes like low vol. Gaps or holidays distort time deltas.
Sensible Defaults & Quick Tuning
Defaults suit forex/crypto on 1H–4H: RSI 32/BB 20 for balanced detection, Median stats over 50 samples, None tolerance for exactness.
- Too many false runs: Increase BB StdDev to 2.5 or RSI Length to 50 for filtering.
- Lagging forecasts: Shorten History Length to 20; switch to 75th Percentile for forward bias.
- Missed near-hits: Enable Percentage tolerance at 0.3% to capture wicks without overcounting.
- Cluttered charts: Reduce Max Lookahead to 200; disable dashboard on lower TFs.
What this indicator is—and isn’t
This is a forecasting visualization layer for pivot-based analysis, highlighting statistical projections from historical patterns. It is not a standalone system—pair with price action, volume, and risk rules. Not predictive of all turns; focuses on OOB-derived extrema, ignoring volume or news impacts.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
LEGEND IsoPulse Fusion • Universal Volume Trend Buy Sell RadarLEGEND IsoPulse Fusion • Universal Volume Trend Buy Sell Radar
One line summary
LEGEND IsoPulse Fusion reads intent from price and volume together, learns which features matter most on your symbol, blends them into a single signed Fusion line in a stable unit range, and emits clear Buy Sell Close events with a structure gate and a liquidity safety gate so you act only when the tape is favorable.
What this script is and why it exists
Many traders keep separate windows for trend, volume, volatility, and regime filters. The result can feel fragmented. This script merges two complementary engines into one consistent view that is easy to read and simple to act on.
LEGEND Tensor estimates directional quality from five causally computed features that are normalized for stationarity. The features are Flow, Tail Pressure with Volume Mix, Path Curvature, Streak Persistence, and Entropy Order.
IsoPulse transforms raw volume into two decaying reservoirs for buy effort and sell effort using body location and wick geometry, then measures price travel per unit volume for efficiency, and detects volume bursts with a recency memory.
Both engines are mapped into the same unit range and fused by a regime aware mixer. When the tape is orderly the mixer leans toward trend features. When the tape is messy but a true push appears in volume efficiency with bursts the mixer allows IsoPulse to speak louder. The outcome is a single Fusion line that lives in a familiar range with calm behavior in quiet periods and expressive pushes when energy concentrates.
What makes it original and useful
Two reservoir volume split . The script assigns a portion of the bar volume to up effort and down effort using body location and wick geometry together. Effort decays through time using a forgetting factor so memory is present without becoming sticky.
Efficiency of move . Price travel per unit volume is often more informative than raw volume or raw range. The script normalizes both sides and centers the efficiency so it becomes signed fuel when multiplied by flow skew.
Burst detection with recency memory . Percent rank of volume highlights bursts. An exponential memory of how recently bursts clustered converts isolated blips into useful context.
Causal adaptive weighting . The LEGEND features do not receive static weights. The script learns, causally, which features have correlated with future returns on your symbol over a rolling window. Only positive contributions are allowed and weights are normalized for interpretability.
Regime aware fusion . Entropy based order and persistence create a mixer that blends IsoPulse with LEGEND. You see a single line rather than two competing panels, which reduces decision conflict.
How to read the screen in seconds
Fusion area . The pane fills above and below zero with a soft gradient. Deeper fill means stronger conviction. The white Fusion line sits on top for precise crossings.
Entry guides and exit guides . Two entry guides draw symmetrically at the active fused entry level. Two exit guides sit inside at a fraction of the entry. Think of them as an adaptive envelope.
Letters . B prints once when the script flips from flat to long. S prints once when the script flips from flat to short. C prints when a held position ends on the appropriate side. T prints when the structure gate first opens. A prints when the liquidity safety flag first appears.
Price bar paint . Bars tint green while long and red while short on the chart to mirror your virtual position.
HUD . A compact dashboard in the corner shows Fusion, IsoPulse, LEGEND, active entry and exit levels, regime status, current virtual position, and the vacuum z value with its avoid threshold.
What signals actually mean
Buy . A Buy prints when the Fusion line crosses above the active entry level while gates are open and the previous state was flat.
Sell . A Sell prints when the Fusion line crosses below the negative entry level while gates are open and the previous state was flat.
Close . A Close prints when Fusion cools back inside the exit envelope or when an opposite cross would occur or when a gate forces a stop, and the previous state was a hold.
Gates . The Trend gate requires sufficient entropy order or significant persistence. The Avoid gate uses a liquidity vacuum z score. Gates exist to protect you from weak tape and poor liquidity.
Inputs and practical tuning
Every input has a tooltip in the script. This section provides a concise reference that you can keep in mind while you work.
Setup
Core window . Controls statistics across features. Scalping often prefers the thirties or low fifties. Intraday often prefers the fifties to eighties. Swing often prefers the eighties to low hundreds. Smaller responds faster with more noise. Larger is calmer.
Smoothing . Short EMA on noisy features. A small value catches micro shifts. A larger value reduces whipsaw.
Fusion and thresholds
Weight lookback . Sample size for weight learning. Use at least five times the horizon. Larger is slower and more confident. Smaller is nimble and more reactive.
Weight horizon . How far ahead return is measured to assess feature value. Smaller favors quick reversion impulses. Larger favors continuation.
Adaptive thresholds . Entry and exit levels from rolling percentiles of the absolute LEGEND score. This self scales across assets and timeframes.
Entry percentile . Eighty selects the top quintile of pushes. Lower to seventy five for more signals. Raise for cleanliness.
Exit percentile . Mid fifties keeps trades honest without overstaying. Sixty holds longer with wider give back.
Order threshold . Minimum structure to trade. Zero point fifteen is a reasonable start. Lower to trade more. Raise to filter chop.
Avoid if Vac z . Liquidity safety level. One point two five is a good default on liquid markets. Thin markets may prefer a slightly higher setting to avoid permanent avoid mode.
IsoPulse
Iso forgetting per bar . Memory for the two reservoirs. Values near zero point nine eight to zero point nine nine five work across many symbols.
Wick weight in effort split . Balance between body location and wick geometry. Values near zero point three to zero point six capture useful behavior.
Efficiency window . Travel per volume window. Lower for snappy symbols. Higher for stability.
Burst percent rank window . Window for percent rank of volume. Around one hundred to three hundred covers most use cases.
Burst recency half life . How long burst clusters matter. Lower for quick fades. Higher for cluster memory.
IsoPulse gain . Pre compression gain before the atan mapping. Tune until the Fusion line lives inside a calm band most of the time with expressive spikes on true pushes.
Continuation and Reversal guides . Visual rails for IsoPulse that help you sense continuation or exhaustion zones. They do not force events.
Entry sensitivity and exit fraction
Entry sensitivity . Loose multiplies the fused entry level by a smaller factor which prints more trades. Strict multiplies by a larger factor which selects fewer and cleaner trades. Balanced is neutral.
Exit fraction . Exit level relative to the entry level in fused unit space. Values around one half to two thirds fit most symbols.
Visuals and UX
Columns and line . Use both to see context and precise crossings. If you present a very clean chart you can turn columns off and keep the line.
HUD . Keep it on while you learn the script. It teaches you how the gates and thresholds respond to your market.
Letters . B S C T A are informative and compact. For screenshots you can toggle them off.
Debug triggers . Show raw crosses even when gates block entries. This is useful when you tune the gates. Turn them off for normal use.
Quick start recipes
Scalping one to five minutes
Core window in the thirties to low fifties.
Horizon around five to eight.
Entry percentile around seventy five.
Exit fraction around zero point five five.
Order threshold around zero point one zero.
Avoid level around one point three zero.
Tune IsoPulse gain until normal Fusion sits inside a calm band and true squeezes push outside.
Intraday five to thirty minutes
Core window around fifty to eighty.
Horizon around ten to twelve.
Entry percentile around eighty.
Exit fraction around zero point five five to zero point six zero.
Order threshold around zero point one five.
Avoid level around one point two five.
Swing one hour to daily
Core window around eighty to one hundred twenty.
Horizon around twelve to twenty.
Entry percentile around eighty to eighty five.
Exit fraction around zero point six zero to zero point seven zero.
Order threshold around zero point two zero.
Avoid level around one point two zero.
How to connect signals to your risk plan
This is an indicator. You remain in control of orders and risk.
Stops . A simple choice is an ATR multiple measured on your chart timeframe. Intraday often prefers one point two five to one point five ATR. Swing often prefers one point five to two ATR. Adjust to symbol behavior and personal risk tolerance.
Exits . The script already prints a Close when Fusion cools inside the exit envelope. If you prefer targets you can mirror the entry envelope distance and convert that to points or percent in your own plan.
Position size . Fixed fractional or fixed risk per trade remains a sound baseline. One percent or less per trade is a common starting point for testing.
Sessions and news . Even with self scaling, some traders prefer to skip the first minutes after an open or scheduled news. Gate with your own session logic if needed.
Limitations and honest notes
No look ahead . The script is causal. The adaptive learner uses a shifted correlation, crosses are evaluated without peeking into the future, and no lookahead security calls are used. If you enable intrabar calculations a letter may appear then disappear before the close if the condition fails. This is normal for any cross based logic in real time.
No performance promises . Markets change. This is a decision aid, not a prediction machine. It will not win every sequence and it cannot guarantee statistical outcomes.
No dependence on other indicators . The chart should remain clean. You can add personal tools in private use but publications should keep the example chart readable.
Standard candles only for public signals . Non standard chart types can change event timing and produce unrealistic sequences. Use regular candles for demonstrations and publications.
Internal logic walkthrough
LEGEND feature block
Flow . Current return normalized by ATR then smoothed by a short EMA. This gives directional intent scaled to recent volatility.
Tail pressure with volume mix . The relative sizes of upper and lower wicks inside the high to low range produce a tail asymmetry. A volume based mix can emphasize wick information when volume is meaningful.
Path curvature . Second difference of close normalized by ATR and smoothed. This captures changes in impulse shape that can precede pushes or fades.
Streak persistence . Up and down close streaks are counted and netted. The result is normalized for the window length to keep behavior stable across symbols.
Entropy order . Shannon entropy of the probability of an up close. Lower entropy means more order. The value is oriented by Flow to preserve sign.
Causal weights . Each feature becomes a z score. A shifted correlation against future returns over the horizon produces a positive weight per feature. Weights are normalized so they sum to one for clarity. The result is angle mapped into a compact unit.
IsoPulse block
Effort split . The script estimates up effort and down effort per bar using both body location and wick geometry. Effort is integrated through time into two reservoirs using a forgetting factor.
Skew . The reservoir difference over the sum yields a stable skew in a known range. A short EMA smooths it.
Efficiency . Move size divided by average volume produces travel per unit volume. Normalization and centering around zero produce a symmetric measure.
Bursts and recency . Percent rank of volume highlights bursts. An exponential function of bars since last burst adds the notion of cluster memory.
IsoPulse unit . Skew multiplied by centered efficiency then scaled by the burst factor produces the raw IsoPulse that is angle mapped into the unit range.
Fusion and events
Regime factor . Entropy order and streak persistence form a mixer. Low structure favors IsoPulse. Higher structure favors LEGEND. The blend is convex so it remains interpretable.
Blended guides . Entry and exit guides are blended in the same way as the line so they stay consistent when regimes change. The envelope does not jump unexpectedly.
Virtual position . The script maintains state. Buy and Sell require a cross while flat and gates open. Close requires an exit or force condition while holding. Letters print once at the state change.
Disclosures
This script and description are educational. They do not constitute investment advice. Markets involve risk. You are responsible for your own decisions and for compliance with local rules. The logic is causal and does not look ahead. Signals on non standard chart types can be misleading and are not recommended for publication. When you test a strategy wrapper, use realistic commission and slippage, moderate risk per trade, and enough trades to form a meaningful sample, then document those assumptions if you share results.
Closing thoughts
Clarity builds confidence. The Fusion line gives a single view of intent. The letters communicate action without clutter. The HUD confirms context at a glance. The gates protect you from weak tape and poor liquidity. Tune it to your instrument, observe it across regimes, and use it as a consistent lens rather than a prediction oracle. The goal is not to trade every wiggle. The goal is to pick your spots with a calm process and to stand aside when the tape is not inviting.
Wyckoff Accumulation / Distribution Detector (v3)🌱 Spring (Bullish Wyckoff Signature)
🧠 Definition
A Spring happens when price dips below a well-defined support level, usually near the end of an accumulation phase, then quickly reverses back above support.
This is not ordinary volatility — it's usually intentional by large operators (“Composite Man”) to:
Trigger stop-losses of weak holders
Create the illusion of a breakdown to scare late sellers in
Absorb all remaining supply at low prices
Launch the next markup leg once weak hands are flushed out
🧭 Typical Spring Characteristics
Feature Behavior
Location Near the bottom of a trading range after a decline
Price Action Temporary breakdown below support, then sharp reversal above
Volume Usually low to average on the break, indicating lack of real selling pressure. Sometimes a volume surge on the reversal as strong hands step in
Candle Often shows a long lower wick, closes back inside the range
Intent Shakeout of weak holders, allow institutions to accumulate more quietly
📈 Why It's Bullish
Springs typically mark the final test of supply. If price can dip below support and immediately recover, it means:
Selling pressure is exhausted (no follow-through)
Strong hands are absorbing remaining shares
A bullish breakout is often imminent
🪤 Upthrust (Bearish Wyckoff Signature)
🧠 Definition
An Upthrust is the mirror image of a Spring. It happens when price pokes above a resistance level, usually near the end of a distribution phase, but then fails to hold above it and falls back inside the range.
This is typically smart money distributing to eager buyers:
Late breakout traders pile in
Institutions sell into that strength
Price collapses back into the range, trapping breakout buyers
🧭 Typical Upthrust Characteristics
Feature Behavior
Location Near the top of a trading range after a rally
Price Action Temporary breakout above resistance, then quick reversal down
Volume Frequently low on the breakout, suggesting a lack of real buying interest — or sometimes high but with no progress, showing hidden selling
Candle Often shows a long upper wick, closes back inside the range
Intent Trap breakout buyers, provide liquidity for institutional sellers to unload near highs
📉 Why It's Bearish
Upthrusts show demand failure and supply swamping:
Buyers cannot sustain the breakout.
The sharp reversal signals large players are exiting.
Typically precedes markdown phases or sharp declines.
📝 Trading Implications
Spring → Often followed by a sign of strength rally → good long entry if confirmed with volume expansion and follow-through.
Upthrust → Often followed by a sign of weakness → short setups, especially if the next rally fails at lower highs.
The script looks for:
🌱 Spring:
Price makes a low below recent pivot support,
Closes back above,
Does so on low volume → likely a shakeout.
🪤 Upthrust:
Price makes a high above recent pivot resistance,
Closes back below,
On low volume → likely a bull trap.
Combined OP Lines and Daily High/Low
This Pine Script v6 indicator for TradingView ("Combined OP Lines and Daily High/Low") overlays the chart and visualizes in UTC+02:00 (manually adjust for DST):
OP Lines: At 0:00 (new day) and 6:00 AM, draws black horizontal lines at the opening price (extend right), vertical black markers, and labels ("OP 0:00"/"OP 6:00"). Old elements are deleted.
Previous Day High/Low: Blue thick horizontal lines (extend right) with labels ("Daily High/Low: "), based on request.security (daily TF, high/low ).
Useful for day trading: Marks intraday sessions and prior-day extremes as support/resistance. Purely visual, dynamically updated, efficient (resource management). Limitations: Fixed timezone, no alerts, colors could be optimized.
Volume Rate of Change (VROC)# Volume Rate of Change (VROC)
**What it is:** VROC measures the rate of change in trading volume over a specified period, typically expressed as a percentage. Formula: `((Current Volume - Volume n periods ago) / Volume n periods ago) × 100`
## **Obvious Uses**
**1. Confirming Price Trends**
- Rising VROC with rising prices = strong bullish trend
- Rising VROC with falling prices = strong bearish trend
- Validates that price movements have conviction behind them
**2. Spotting Divergences**
- Price makes new highs but VROC doesn't = weakening momentum
- Price makes new lows but VROC doesn't = potential reversal
**3. Identifying Breakouts**
- Sudden VROC spikes often accompany legitimate breakouts from consolidation patterns
- Helps distinguish real breakouts from false ones
**4. Overbought/Oversold Conditions**
- Extreme VROC readings (very high or very low) suggest exhaustion
- Mean reversion opportunities when volume extremes occur
---
## **Non-Obvious Uses**
**1. Smart Money vs. Dumb Money Detection**
- Declining VROC during price rallies may indicate retail FOMO while institutions distribute
- Rising VROC during selloffs with price stability suggests institutional accumulation
**2. News Impact Measurement**
- Compare VROC before/after earnings or announcements
- Low VROC on "significant" news = market doesn't care (fade the move)
- High VROC = genuine market reaction (respect the move)
**3. Market Regime Changes**
- Persistent shifts in average VROC levels can signal transitions between bull/bear markets
- Declining baseline VROC over months = waning market participation/topping process
**4. Intraday Liquidity Profiling**
- VROC patterns across trading sessions identify best execution times
- Avoid trading when VROC is abnormally low (wider spreads, poor fills)
**5. Sector Rotation Analysis**
- Compare VROC across sector ETFs to identify where capital is flowing
- Rising VROC in defensive sectors + falling VROC in cyclicals = risk-off rotation
**6. Options Expiration Effects**
- VROC typically drops significantly post-options expiration
- Helps avoid false signals from mechanically-driven volume changes
**7. Algorithmic Activity Detection**
- Unusual VROC patterns (regular spikes at specific times) may indicate algo programs
- Can front-run or avoid periods of heavy algorithmic interference
**8. Liquidity Crisis Early Warning**
- Sharp, sustained VROC decline across multiple assets = liquidity withdrawal
- Can precede market stress events before price volatility emerges
**9. Cryptocurrency Wash Trading Detection**
- Comparing VROC across exchanges for same asset
- Discrepancies suggest artificial volume on certain platforms
**10. Pair Trading Optimization**
- Use relative VROC between correlated pairs
- Enter when VROC divergence is extreme, exit when it normalizes
The key to advanced VROC usage is context: combining it with price action, market structure, and other indicators rather than using it in isolation.
XAUUSD 5-Min ORB + FVG (09:30–10:30, 1/day, 5% risk, ORB SL)5 min orb stratgey thta buys when it breaks above the range and sells when it breaks below
CRT Efficiency Backtester (Romeo Style)30 day look back period CRT Efficiency Backtester (Romeo Style)
Time Line Indicator - by LMTime Line Indicator – by LM
Description:
The Time Line Indicator is a simple, clean, and customizable tool designed to visualize specific time periods within each hour directly in a dedicated indicator pane. It allows traders to mark important intraday minute ranges across multiple past hours, providing a clear visual reference for time-based analysis. This indicator is perfect for identifying recurring hourly windows, session patterns, or custom time-based events in your charts.
Unlike traditional overlays, this indicator does not interfere with price candles and draws its lines in a separate pane at the bottom of your chart for clarity.
Key Features:
Custom Hourly Lines:
Draw horizontal lines for a specific minute range within each hour, e.g., from the 45th minute to the 15th minute of the next hour.
Multi-Hour Support:
Choose how many past hours to display. The indicator will replicate the line for each selected hourly period, following the same minute logic.
Automatic Start/End Logic:
If your chosen start minute is in the previous hour, the line correctly begins at that time.
The end minute can cross into the next hour when applicable.
If the selected end minute does not yet exist in the current chart data, the line will extend to the latest available bar.
Dedicated Indicator Pane:
Lines appear in a fixed, non-intrusive y-axis within the indicator pane (overlay=false), keeping your price chart clean.
Customizable Appearance:
Line Color: Choose any color to match your chart theme.
Line Thickness: Adjust the width of the lines for better visibility.
Inputs:
Input Name Type Default Description
Line Color Color Orange The color of the horizontal lines.
Line Thickness Integer 2 The thickness of each line (1–5).
Start Minute Integer 5 The minute within the hour where the line begins (0–59).
End Minute Integer 25 The minute within the hour where the line ends (0–59).
Hours Back Integer 3 Number of past hours to display lines for.
Use Cases:
Intraday Analysis: Quickly visualize recurring minute ranges across multiple hours.
Session Tracking: Mark critical time windows for trading sessions or market events.
Pattern Recognition: Easily identify time-based patterns or setups without cluttering the price chart.
How It Works:
The indicator calculates the nearest bars corresponding to your start and end minutes.
It draws horizontal lines at a fixed y-axis value within the indicator pane.
Lines are drawn for each selected past hour, replicating the chosen minute span.
All logic respects the actual chart data; lines never extend into the future beyond the most recent bar.
Notes:
Overlay is set to false, so lines appear in a dedicated pane below the price chart.
The indicator is fully compatible with any timeframe. Lines adjust automatically to match the chart’s bar spacing.
You can change the number of hours displayed at any time without affecting existing lines.
If you want, I can also draft a shorter “TradingView Store / Public Library description” version under 500 characters for the “Short Description” field — concise and punchy for users scrolling through indicators.
Londen & New York Sessies (UTC+2)This script highlights the London and New York trading sessions on the chart, adjusted for UTC+2 timezone. It's designed to help traders easily visualize the most active and liquid periods of the Forex and global markets directly on their TradingView charts. The London session typically provides strong volatility, while the New York session brings increased momentum and overlaps with London for powerful trading opportunities. Ideal for intraday and session-based strategies.
CJ7 and the ES Buy 10 minwelcome all to help make this a better script
welcome all to help make this a better script
welcome all to help make this a better script
welcome all to help make this a better script
Wyckoff Stage Approximator (MTF Alerts)Wyckoff Stage Approximator (MTF Context)
This indicator is a powerful tool designed for traders who use a top-down, multi-timeframe approach based on Wyckoff principles. Its primary function is to identify the market's current stage—consolidation (Stage 1) or trend (Stage 2)—on a higher Context (C) timeframe and project that analysis onto your lower Validation (V) and Entry (E) charts.
This ensures you are always trading in alignment with the "big picture" trend, preventing you from taking low-probability trades based on lower-timeframe noise.
Core Concept: Top-Down Analysis
The script solves a common problem for multi-timeframe traders: losing sight of the primary trend. By locking the background color to your chosen Context timeframe (e.g., 15-minute), you are constantly reminded of the market's true state.
🟡 Yellow Background (Stage 1): The Context timeframe is in consolidation. This is a time to be patient and wait for a clear directional bias to emerge.
🟢 Green Background (Stage 2 - Markup): The Context timeframe is in a confirmed uptrend. This is your green light to look for bullish pullback opportunities on your lower timeframes.
🔴 Red Background (Stage 2 - Markdown): The Context timeframe is in a confirmed downtrend. This is your signal to look for bearish rally opportunities.
How It Works
The indicator uses a combination of moving averages and trend strength to objectively define each stage:
Trend Alignment: It checks if the 5 EMA, 10 EMA, and 20 EMA are properly stacked above or below the 50 SMA to determine the potential trend direction.
Trend Strength: It uses the ADX to measure the strength of the trend. A trend is only confirmed as Stage 2 if the ADX is above a user-defined threshold (default is 23), filtering out weak or choppy moves.
Stage Definition: Any period that is not a confirmed, strong Stage 2 Markup or Markdown is classified as a Stage 1 consolidation phase.
Key Features
Multi-Timeframe (MTF) Projection: Select your master "Context" timeframe, and its analysis will be displayed on any chart you view.
Customizable Inputs: Easily adjust the moving average lengths and ADX threshold to fit your specific strategy and the asset you are trading.
Clear Visual Cues: The intuitive background coloring makes it easy to assess the market environment at a glance.
Stage Transition Alerts: Set up specific alerts to be notified the moment your Context timeframe shifts from a Stage 1 consolidation to a Stage 2 trend, ensuring you never miss a potential setup.
How to Use This Indicator
Add the indicator to your chart.
In the settings, set the "Context Timeframe" to your highest timeframe (e.g., "15" for 15-minute).
Create alerts for the "Stage 1 -> Stage 2" conditions.
When you receive an alert, it signals that a potential trend is beginning on your Context chart.
Switch to your lower Validation and Entry timeframes. The background color will confirm the higher-timeframe trend, giving you the confidence to look for your specific entry patterns.
Disclaimer: This tool is designed for confluence and environmental analysis. It is not a standalone signal generator. It should be used in conjunction with your own price action, volume, or order flow analysis to validate trade entries.
Mark the New York trading session hours（纽约交易时间段标注）Apply background shading for New York time.
（纽约时间背景着色）
04：00 ~ 09：00
09：00 ~ 09：30
09：30 ~ 12：00
No shading needed after 12 AM as I'll be asleep.
（12点我睡觉了就不着色了。）
Pump-Smart Shorting StrategyThis strategy is built to keep your portfolio hedged as much as possible while maximizing profitability. Shorts are opened after pumps cool off and on new highs (when safe), and closed quickly during strong upward moves or if stop loss/profit targets are hit. It uses visual overlays to clearly show when hedging is on, off, or blocked due to momentum, ensuring you’re protected in most market conditions but never short against the pump. Fast re-entry keeps the hedge active with minimal downtime.
Pump Detection:
RSI (Relative Strength Index): Calculated over a custom period (default 14 bars). If RSI rises above a threshold (default 70), the strategy considers the market to be in a pump (strong upward momentum).
Volume Spike: The current volume is compared to a 20-bar simple moving average of volume. If it exceeds the average by 1.5× and price increases at least 5% in one bar, pump conditions are triggered.
Price Jump: Measured by (close - close ) / close . A single-bar change > 5% helps confirm rapid momentum.
Pump Zone (No Short): If any of these conditions is true, an orange or red background is shown and shorts are blocked.
Cooldown and Re-Entry:
Cooldown Detection: After the pump ends, RSI must fall below a set value (default ≤ 60), and either volume returns towards average or price momentum is less than half the original spike (oneBarUp <= pctUp/2).
barsWait Parameter: You can specify a waiting period after cooldown before a short is allowed.
Short Entry After Pump/Cooldown: When these cooldown conditions are met, and no short is active, a blue background is shown and a short position is opened at the next signal.
New High Entry:
Lookback New High: If the current high is greater than the highest high in the last N bars (default 20), and pump is NOT active, a short can be opened.
Take Profit (TP) & Stop Loss (SL):
Take Profit: Short is closed if price falls to a threshold below the entry (minProfitPerc, default 2%).
Stop Loss: Short is closed if price rises to a threshold above the entry (stopLossPerc, default 6%).
Preemptive Exit:
Any time a pump is detected while a short position is open, the strategy closes the short immediately to avoid losses.
Visual Feedback:
Orange Background: Market is pumping, do not short.
Red Background: Other conditions block shorts (cooldown or waiting).
Blue Background: Shorts allowed.
Triangles/Circles: Mark entries, pump start/end, for clear trading signals.
ICT Killzones & MacrosICT Killzones & Macros (v1.1.5) — configurable ICT session windows + refined “macro” windows with live High/Low levels, optional extensions, next-window previews, and lightweight opening-price lines. Built to be clock-robust, timezone-aware, and performant on intraday charts.
Tip: All times are interpreted in your chosen IANA timezone (default: America/New_York) and auto-handle DST. You can rename, recolor, enable/disable, and retime every window.
What it plots
- Killzones (5) : Asia (19:00–02:00), London (02:00–05:00), NY AM (07:00–09:30), London Close (10:00–12:00), NY PM (13:30–16:00) — full-height boxes with optional header.
- Macros (8) (defaults tailored for common ICT “refined” windows): Asia-1 (18:00–21:00), Asia-2 (21:00–00:00), London-1 (01:00–04:00), AM-1 (09:45–10:15), AM-2 (10:45–11:15), Lunch (12:00–13:00), PM-1 (13:30–14:30), Power Hour (15:10–16:00).
- Live High/Low lines for the current Macro/Killzone window.
- Optional HL extension to the right until price crosses or the trading day rolls (style selectable).
- “Next” previews : earliest upcoming Macro and Killzone header; optional next-window background band.
- Opening Prices (3 lightweight time lines) : defaults 00:00, 08:30, 09:30 with right-edge labels, scoped to a session you choose (auto-cleans at session end).
- Key inputs & styling
- General : Timezone (IANA), “Sessions to show” (per window) to keep only the last N completed windows.
- Header : height (ticks), gap (ticks), fill opacity, border width/style, text size/color, toggle “Next Macro/Killzone” headers.
- Boxes : global fill opacity, global border width/style (used by both Macros & Killzones).
- High/Low : show HL, HL line style, extend on/off + extension style, optional extension labels.
- Opening Prices : enable Time 1/2/3, set HH:MM for each, session window, per-line colors, style (dotted/dashed/solid), width.
- Per-window controls : each Macro/Killzone has Enable, Session (HHMM-HHMM), Label, Fill color.
How to use (quick start)
- Set Timezone to your preference (default America/New_York).
- Toggle on the Macros and Killzones you trade. Adjust session times if needed.
- (Optional) Turn on Extend High/Low to project levels until crossed/day-roll.
- (Optional) Enable Next… headers to see the next upcoming window at a glance.
- (Optional) Configure Opening Prices (00:00 / 08:30 / 09:30 by default) and the session over which they appear.
Behavior & notes
- Time windows are computed by clock, not by guessing bar timestamps, making them robust across brokers and timeframes.
- With HL extension on, the current window’s levels extend until crossed or the end of the trading day (in your timezone). With it off, completed windows keep static HL markers (limited by “Sessions to show”).
- “Sessions to show” applies per Macro/Killzone to automatically prune older windows and keep charts snappy.
- Opening-price lines exist only within the chosen “Opening Prices Session” and are removed when it ends (keeps charts clean).
Defaults (color cues)
Killzones: Asia (blue), London (purple), NY AM (green), London Close (yellow), NY PM (orange).
Macros: neutral greys with Lunch and PM accents out of the box (all customizable).
Performance tips
- Reduce “Sessions to show” if you scroll far back in history.
- Disable “Next…” previews and/or extension labels on very slow machines.
- Narrow the “Opening Prices Session” window to exactly when you need those lines.
Changelog highlights
- v1.1.5 : Internal refinements and stability.
- v1.1.3 : Live High/Low lines for current windows + optional extension.
- v1.1.2 : Added “next Killzone” preview (to match “next Macro”).
- v1.1.0 : Defaults updated (5 KZ, 8 Macros). Removed “snap-to-killzone” behavior.
- v1.0.0 : Independent Macro vs. Killzone rendering; cleaner header logic.
- Known limitations
If your chart warns about drawings, trim “Sessions to show”.
If your broker session times differ from NY hours, adjust the sessions or change the indicator timezone.
Credits & intent
Inspired by ICT timing concepts; provided for education/mark-up, not financial advice.
Built to be flexible so you can mirror your personal playbook and journaling workflow.
HTF Cross Breakout [CHE] HTF Cross Breakout — Detects higher timeframe close crossovers for breakout signals, anchors VWAP for trend validation, and flags continuations or traps with visual extensions for delta percent and stop levels.
Summary
This indicator spots moments when the current chart's close price crosses a higher timeframe close, marking potential breakouts only when the current bar shows directional strength. It anchors a volume-weighted average price line from the breakout point to track trend health, updating labels to show if the move continues or reverses into a trap. Extensions add a dotted line linking the breakout level to the current close with percent change display, plus a stop-loss marker at the VWAP end. Signals gain robustness from higher timeframe confirmation and anti-repainting options, reducing noise in live bars compared to simple crossover tools.
Motivation: Why this design?
Traders often face false breakouts from intrabar wiggles on lower timeframes, especially without higher timeframe alignment, leading to whipsaws in volatile sessions. This design uses higher timeframe close as a stable reference for crossover detection, combined with anchored volume weighting to gauge sustained momentum. It addresses these by enforcing bar confirmation and directional filters, providing clearer entry validation and risk points without overcomplicating the chart.
What’s different vs. standard approaches?
Reference baseline
Standard crossover indicators like moving average crosses operate solely on the chart timeframe, ignoring higher timeframe context and lacking volume anchoring.
Architecture differences
- Higher timeframe data pulls via security calls with optional repainting control for stability.
- Anchored VWAP resets at each signal, accumulating from the breakout bar only.
- Label dynamics update in real-time for continuation checks, with extensions for visual delta and stop computation.
- Event-driven line finalization prunes old elements after a set bar extension.
Practical effect
Charts show persistent lines and labels that extend live but finalize cleanly on new events, avoiding clutter. This matters for spotting trap reversals early via label color shifts, and extensions provide quick risk visuals without manual calculations, improving decision speed in trend trades.
How it works (technical)
The indicator first determines a higher timeframe based on user selection, pulling its close price securely. It checks for crossovers or crossunders of the current close against this higher close, but only triggers on confirmed bars with matching directional opens and closes. On a valid event, a horizontal line and label mark the higher close level, while a dashed VWAP line starts accumulating typical price times volume from that bar onward. During the active phase, the breakout line extends to the current bar, the label repositions and updates text based on whether the current close holds above or below the level for bulls or bears. A background tint warns if the close deviates adversely from the current VWAP. Extensions draw a vertical dotted line at the last bar between the breakout level and close, placing a midpoint label with percent difference; separately, a label at the VWAP end shows a computed stop price. Persistent variables track the active state and accumulators, resetting on new events after briefly extending old elements. Repaint risk from security calls is mitigated by confirmed bar gating or user opt-in.
Parameter Guide
Plateau Length (reserved for future, currently unused): Sets a length for potential plateau detection in extensions; default 3, minimum 1. Higher values would increase stability but are not active yet—leave at default to avoid tuning.
Line Width: Controls thickness of breakout, VWAP, and extension lines; default 2, range 1 to 5. Thicker lines improve visibility on busy charts but may obscure price action—use 1 for clean views, 3 or more for emphasis.
+Bars after next HTF event (finalize old, then delete): Extends old lines and labels by this many bars before deletion on new signals; default 20, minimum 0. Shorter extensions keep charts tidy but risk cutting visuals prematurely; longer aids review but builds clutter over time.
Evaluate label only on HTF close (prevents gray traps intrabar): When true, label updates wait for higher timeframe confirmation; default true. Enabling reduces intrabar flips for stabler signals, though it may delay feedback—disable for faster live trading at repaint cost.
Allow Repainting: Permits real-time security data without confirmation offset; default false. False ensures historical accuracy but lags live bars; true speeds updates but can repaint on HTF closes.
Timeframe Type: Chooses HTF method—Auto Timeframe (dynamic steps up), Multiplier (chart multiple), or Manual (fixed string); default Auto Timeframe. Auto adapts to chart scale for convenience; Multiplier suits custom scaling like 5 times current; Manual for precise like 1D on any chart.
Multiplier for Alternate Resolution: Scales chart timeframe when Multiplier type selected; default 5, minimum 1. Values near 1 mimic current resolution for subtle shifts; higher like 10 jumps to broader context, increasing signal rarity.
Manual Resolution: Direct timeframe string like 60 for 1H when Manual type; default 60. Match to trading horizon—shorter for swing, longer for positional—to balance frequency and reliability.
Show Extension 1: Toggles dotted line and delta percent label between breakout level and current close; default true. Disable to simplify for basic use, enable for precise momentum tracking.
Dotted Line Width: Thickness for Extension 1 line; default 2, range 1 to 5. Align with main Line Width for consistency.
Text Size: Size for delta percent label; options tiny, small, normal, large; default normal. Smaller reduces overlap on dense charts; larger aids glance reads.
Decimals for Δ%: Precision in percent change display; default 2, range 0 to 6. Fewer decimals speed reading; more suit low-volatility assets.
Positive Δ Color: Hue for upward percent changes; default lime. Choose contrasting for visibility.
Negative Δ Color: Hue for downward percent changes; default red. Pair with positive for quick polarity scan.
Dotted Line Color: Color for Extension 1 line; default gray. Neutral tones blend well; brighter for emphasis.
Background Transparency (0..100): Opacity for delta label background; default 90. Higher values fade for subtlety; lower solidifies for readability.
Show Extension 2: Toggles stop-loss label at VWAP end; default true. Turn off for entry focus only.
Stop Method: Percent from VWAP end or fixed ticks; options Percent, Ticks; default Percent. Percent scales with price levels; Ticks suits tick-based instruments.
Stop %: Distance as fraction of VWAP for Percent method; default 1.0, step 0.05, minimum 0.0. Tighter like 0.5 reduces risk but increases stops; wider like 2.0 allows breathing room.
Stop Ticks: Tick count offset for Ticks method; default 20, minimum 0. Adjust per asset volatility—fewer for tight control.
Price Decimals: Rounding for stop price text; default 4, range 0 to 10. Match syminfo.precision for clean display.
Text Size: Size for stop label; options tiny, small, normal, large; default normal. Scale to chart zoom.
Text Color: Foreground for stop text; default white. Ensure contrast with background.
Inherit VWAP Color (BG tint): Bases stop label background on VWAP hue; default true. True maintains theme; false allows custom black base.
BG Transparency (0..100): Opacity for stop label background; default 0. Zero for no tint; up to 100 for full fade.
Reading & Interpretation
Breakout lines appear green for bullish crosses or red for bearish, extending live until a new event finalizes them briefly then deletes. Labels start blank, updating to Bull Cont. or Bear Cont. in matching colors if holding the level, or gray Bull Trap/Bear Trap on reversal. VWAP dashes yellow for bulls, orange for bears, sloping with accumulated volume weight—deviations trigger faint red background warnings. Extension 1's dotted vertical shows at the last bar, with midpoint label green/red for positive/negative percent from breakout to close. Extension 2 places a left-aligned label at VWAP end with stop price and method note, tinted to VWAP for context.
Practical Workflows & Combinations
For trend following, enter long on green Bull Cont. labels above VWAP with higher highs confirmation, filtering via rising structure; short on red Bear Cont. below. Pair with volume surges or RSI above 50 for bulls to avoid traps. For exits, trail stops using the Extension 2 level, tightening on warnings or gray labels—aggressive on continuations, conservative post-trap. In multi-timeframe setups, use default Auto on 15m charts for 1H signals, scaling multiplier to 4 for daily context on hourly; test on forex/stocks where volume is reliable, avoiding low-liquidity assets.
Behavior, Constraints & Performance
Signals confirm on bar close with HTF gating when strict mode active, but live bars may update if repainting enabled—opt false for backtest fidelity, true for intraday speed. Security calls risk minor repaints on HTF closes, mitigated by confirmation offsets. Resources cap at 1000 bars back, 50 lines/labels total, with event prunes to stay under budgets—no loops, minimal arrays. Limits include VWAP lag in low-volume periods and dependency on accurate HTF data; gaps or holidays may skew anchors.
Sensible Defaults & Quick Tuning
Defaults suit 5m-1H charts on liquid assets: Auto HTF, no repaint, 1% stops. For choppy markets with excess signals, enable strict eval and bump multiplier to 10 for rarer triggers. If sluggish in trends, shorten extend bars to 10 and allow repainting for quicker visuals. On high-vol like crypto, widen stop % to 2.0 and use Ticks method; for stables like indices, tighten to 0.5% and keep Percent.
What this indicator is—and isn’t
This is a signal visualization layer for breakout confirmation and basic risk marking, best as a filter in discretionary setups. It isn’t a standalone system or predictive oracle—combine with price structure, news awareness, and sizing rules for real edges.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
Mayer Mutiple | QRMayer Multiple | QR — Publication Description
What it does
Mayer Multiple | QR is a cycle/valuation style oscillator that measures how far price sits above or below its longer-term average and normalizes that distance by current volatility. It helps you spot overheated extensions and deep discounts relative to trend, with adaptive bands that expand/contract as conditions change.
How it works (principle)
The script compares price to a long lookback moving average (default uses a 200-period average of ohlc4) and turns that gap into an oscillator.
It then computes a rolling standard deviation of that oscillator to build dynamic upper/lower bands (±1σ, ±2σ, ±3σ).
When the oscillator rises above the upper bands, the move is statistically stretched (potential distribution/risk). When it falls below the lower bands, it’s statistically depressed (potential accumulation/opportunity).
A small baseline band around zero (scaled from volatility) provides a quick trend-bias read without crowding the view.
Why this matters: Classic “Mayer Multiple” tools use a fixed threshold over a single moving average. This version is volatility-aware: its bands adapt to the market’s current dispersion, reducing false signals in quiet regimes and avoiding constant “overheat” flags in high-vol regimes.
What you see on the chart
White oscillator line: volatility-normalized deviation from the long-term average.
Adaptive bands:
Upper 1/2/3σ (shaded blue tones) = progressively more extended.
Lower 1/2/3σ (shaded green tones) = progressively more discounted.
Baseline ribbon: subtle band around zero for quick bias.
Background highlights: optional flashes when the oscillator exceeds the ±3σ extremes.
All visuals are generated by this script alone; no other indicator is required to understand usage.
How to use it
Context: Use on higher timeframes to gauge where price sits versus its long-term “fair value corridor.”
Signal reading:
Above +1σ/+2σ/+3σ: extension → consider de-risking, trailing stops, or waiting for mean reversion.
Below −1σ/−2σ/−3σ: discount → consider scaling in, watching for trend resumption cues.
Confluence: Treat it as a condition, not a trigger. Pair with structure (higher highs/lows), breadth, or momentum for entries/exits.
Regime awareness: As volatility rises, bands widen; prioritize trend context over single print extremes.
Inputs you can tune
Color mode: preset palettes for lines/fills/backgrounds.
Dynamic Threshold Length: lookback for the volatility (σ) calculation driving the adaptive bands.
Source: price input used for the long-term reference.
Band toggles: show/hide ±1σ / ±2σ / ±3σ envelopes to reduce clutter.
Originality & value
Adaptive, volatility-aware implementation of a Mayer-style concept: rather than one fixed threshold, it scales to current regime, keeping readings comparable across cycles.
Clear, clean presentation (oscillator + bands + optional background) designed for publication with a clean chart so the script’s output is immediately identifiable.
Offers actionable context (stretch/discount zones) while leaving trade execution to the user’s process.
Limitations & good practices
Best used for context and risk framing, not stand-alone entries.
Adaptive bands depend on the lookback you choose; very short windows can overfit, very long windows can lag.
Extremes can persist in strong trends—don’t fade momentum blindly.
Disclaimer
This tool is for research and education only and not investment advice. Markets involve risk. Past performance does not predict or guarantee future results. Use prudent risk management and test settings on your instruments/timeframes.
Puell Multiple Variants [OperationHeadLessChicken]"Puell Multiple Variants" includes three related indicators for analysing Bitcoin miner revenue dynamics:
Classic Puell Multiple – the original indicator showing how current miner revenue compares to its long-term average.
Halving-Corrected Puell Multiple – applies a compensation factor to adjust for miner revenue reductions after each halving, allowing easier comparison to a consistent overvalued threshold.
Revenue RSI – a novel approach applying the Relative Strength Index to miner revenue to identify potential over- and undervalued conditions.
Each component can be shown or hidden individually.
All parameters are fully adjustable via input settings.
LGS - Vertical LinesThe script allows you to configure 5 vertical lines, to be displayed at the selected hour and minute.
Squeeze Weekday Frequency [CHE] Squeeze Weekday Frequency — Tracks historical frequency of low-volatility squeezes by weekday to inform timing of low-risk setups.
Summary
This indicator monitors periods of unusually low volatility, defined as when the average true range falls below a percentile threshold, and tallies their occurrences across each weekday. By aggregating these counts over the chart's history, it reveals patterns in squeeze frequency, helping traders avoid or target specific days for reduced noise. The approach uses persistent counters to ensure accurate daily tallies without duplicates, providing a robust view of weekday biases in volatility regimes.
Motivation: Why this design?
Traders often face inconsistent signal quality due to varying volatility patterns tied to the trading calendar, such as quieter mid-week sessions or busier Mondays. This indicator addresses that by binning low-volatility events into weekday buckets, allowing users to spot recurring low-activity days where trends may develop with less whipsaw. It focuses on historical aggregation rather than real-time alerts, emphasizing pattern recognition over prediction.
What’s different vs. standard approaches?
- Reference baseline: Traditional volatility trackers like simple moving averages of range or standalone Bollinger Band squeezes, which ignore temporal distribution.
- Architecture differences:
- Employs array-based persistent counters for each weekday to accumulate events without recounting.
- Includes duplicate prevention via day-key tracking to handle sparse data.
- Features on-demand sorting and conditional display modes for focused insights.
- Practical effect: Charts show a persistent table of ranked weekdays instead of transient plots, making it easier to glance at biases like higher squeezes on Fridays, which reduces the need for manual logging and highlights calendar-driven edges.
How it works (technical)
The indicator first computes the average true range over a specified lookback period to gauge recent volatility. It then ranks this value against its own history within a sliding window to identify squeezes when the rank drops below the threshold. Each bar's timestamp is resolved to a weekday using the selected timezone, and a unique day identifier is generated from the date components.
On detecting a squeeze and valid price data, it checks against a stored last-marked day for that weekday to avoid multiple counts per day. If it's a new occurrence, the corresponding weekday counter in an array increments. Total days and data-valid days are tracked separately for context.
At the chart's last bar, it sums all counters to compute shares, sorts weekdays by their squeeze proportions, and populates a table with the selected subset. The table alternates row colors and highlights the peak weekday. An info label above the final bar summarizes totals and the top day. Background shading applies a faint red to squeeze bars for visual confirmation. State persists via variable arrays initialized once, ensuring counts build incrementally without resets.
Parameter Guide
ATR Length — Sets the lookback for measuring average true range, influencing squeeze sensitivity to short-term swings. Default: 14. Trade-offs/Tips: Shorter values increase responsiveness but raise false positives in chop; longer smooths for stability, potentially missing early squeezes.
Percentile Window (bars) — Defines the history length for ranking the current ATR, balancing recent relevance with sample size. Default: 252. Trade-offs/Tips: Narrower windows adapt faster to regime shifts but amplify noise; wider ones stabilize ranks yet lag in fast markets—aim for 100-500 bars on daily charts.
Squeeze threshold (PR < x) — Determines the cutoff for low-volatility classification; lower values flag rarer, tighter squeezes. Default: 10.0. Trade-offs/Tips: Tighter thresholds (under 5) yield fewer but higher-quality signals, reducing clutter; looser (over 20) captures more events at the cost of relevance.
Timezone — Selects the reference for weekday assignment; exchange default aligns with asset's session. Default: Exchange. Trade-offs/Tips: Use custom for cross-market analysis, but verify alignment to avoid offset errors in global pairs.
Show — Toggles the results table visibility for quick on/off of the display. Default: true. Trade-offs/Tips: Disable in multi-indicator setups to save screen space; re-enable for periodic reviews.
Pos — Positions the table on the chart pane for optimal viewing. Default: Top Right. Trade-offs/Tips: Bottom options suit long-term charts; test placements to avoid overlapping price action.
Font — Adjusts text size in the table for readability at different zooms. Default: normal. Trade-offs/Tips: Smaller fonts fit more data but strain eyes on small screens; larger for presentations.
Dark — Applies a dark color scheme to the table for contrast against chart backgrounds. Default: true. Trade-offs/Tips: Toggle false for light themes; ensures legibility without manual recoloring.
Display — Filters table rows to show all, top three, or bottom three weekdays by squeeze share. Default: All. Trade-offs/Tips: Use "Top 3" for focus on high-frequency days in active trading; "All" for full audits.
Reading & Interpretation
Red-tinted backgrounds mark individual squeeze bars, indicating current low-volatility conditions. The table's summary row shows the highest squeeze count, its percentage of total events, and the associated weekday in teal. Detail rows list selected weekdays with their absolute counts, proportional shares, and a left arrow for the peak day—higher percentages signal days where squeezes cluster, suggesting potential for calmer trend development. The info label reports overall days observed, valid data days, and reiterates the top weekday with its count. Drifting counts toward zero on a weekday imply rarity, while elevated ones point to habitual low-activity sessions.
Practical Workflows & Combinations
- Trend following: Scan for squeezes on high-frequency weekdays as entry filters, confirming with higher highs or lower lows in the structure; pair with momentum oscillators to time breaks.
- Exits/Stops: On low-squeeze days, widen stops for breathing room, tightening them during peak squeeze periods to guard against false breaks—use the table's percentages as a regime proxy.
- Multi-asset/Multi-TF: Defaults work across forex and indices on hourly or daily frames; for stocks, adjust percentile window to 100 for shorter histories. Scale thresholds up by 5-10 points for high-vol assets like crypto to maintain signal sparsity.
Behavior, Constraints & Performance
- Repaint/confirmation: Counts update only on confirmed bars via day-key changes, with no future references—live bars may shade red tentatively but tallies finalize at session close.
- security()/HTF: Not used, so no higher-timeframe repaint risks; all computations stay in the chart's resolution.
- Resources: Relies on a fixed-size array of seven elements and small loops for sorting and table fills, capped at 5000 bars back—efficient for most charts but may slow on very long intraday histories.
- Known limits: Ignores weekends and holidays implicitly via data presence; early chart bars lack full percentile context, leading to initial undercounting; assumes continuous sessions, so gaps in data (e.g., news halts) skew totals.
Sensible Defaults & Quick Tuning
Start with the built-in values for broad-market daily charts: ATR at 14, window at 252, threshold at 10. For noisier environments, lower the threshold to 5 and shorten the window to 100 to prioritize rare squeezes. If too few events appear, raise the threshold to 15 and extend ATR to 20 for broader capture. To combat overcounting in sparse data, widen the window to 500 while keeping others stock—monitor the info label's data-days count before trusting patterns.
What this indicator is—and isn’t
This serves as a statistical overlay for spotting calendar-based volatility biases, aiding in session selection and filter design. It is not a standalone signal generator, predictive model, or risk manager—integrate it with price action, volume, and broader strategy rules for decisions.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
