AI MEDEA FORECASTAI MEDEA searches for similar historical patterns and uses them to generate predictions. The longer it runs, the more data it gathers and the better the predictions become.
Important:
The indicator must remain enabled to:
- Collect predictions and check their accuracy
- Have as much data as possible for comparison
- Provide more accurate results
Recommendation:
Let the indicator run for several days on different timeframes (15m, 30m, 1H, 4H). The accuracy table will show the actual accuracy only after gathering enough predictions.
Penunjuk dan strategi
Volume Weighted Standard DeviationThis indicator calculates the Standard Deviation and decomposes total volatility into its core components, allowing to analyze the underlying character of the market.
Key Features:
Volatility Decomposition: The indicator separates volatility based on the 'Estimate Bar Statistics' option.
Standard Mode (Estimate Bar Statistics = OFF): Calculates a simple (Volume-Weighted) Standard Deviation of the selected Source.
Decomposition Mode (Estimate Bar Statistics = ON): The indicator uses a statistical model ('Estimator') to calculate within-bar volatility (choppiness, noise) and between-bar volatility (trending moves). (Assumption: In this mode, the Source input is ignored, and an estimated mean for each bar is used instead).
Dual Display Modes: The indicator offers two modes to visualize this information:
Absolute Mode: Plots the total standard deviation as a stacked area chart, showing the proportional contribution of the 'Between' and 'Within' components.
Normalized Mode: Plots the direct ratio of each component's variance (from 0 to 1), making it easy to identify which character is dominant.
Calculation Options: The volatility calculation can be optionally Volume weighted. An optional Normalize Volatility setting performs the calculation in logarithmic space, making volatility comparable across different price scales.
Volatility Pivot Detection: Includes a built-in pivot detector that identifies significant turning points (highs and lows) in the total volatility line. (Note: This is only visible in 'Absolute Mode').
Note on Confirmation (Lag): Pivot signals are confirmed using a lookback method. A pivot is only plotted after the Pivot Right Bars input has passed, which introduces an inherent lag.
Multi-Timeframe (MTF) Capability:
MTF Volatility Lines: The volatility lines can be calculated on a higher timeframe, with standard options to handle gaps (Fill Gaps) and prevent repainting (Wait for...).
Limitation: The Pivot detection (Calculate Pivots) is disabled if a Higher Timeframe (HTF) is selected.
Integrated Alerts: Includes 6 alerts for:
Volatility character changes (e.g., 'Trend Character Emerging', 'Character Change from Trend to Choppy').
Volatility pivot (high or low) detection.
DISCLAIMER
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
Blue Algo📘 Blue Algo - Bitcoin Trading Indicator
Blue Algo is a professional trading indicator specifically designed for Bitcoin (BTC) on the 15-minute timeframe. It combines proprietary algorithms with intelligent signal generation to identify high-probability trading opportunities.
🎯 KEY FEATURES:
- Advanced Signal System: Generates precise buy/sell signals using proprietary price analysis methods
- 5-Level Take Profit Strategy: Automated TP levels at $400, $800, $1,200, $1,600, and $2,000 price movement from entry (chart points, not dollar profit)
- Risk Management: Maximum stop loss capped at $1,700 price movement to protect capital (chart points, not dollar loss)
- Peak Profit Tracking: Monitors the highest profit reached during each trade
- Real-time Alerts: Instant notifications for entries, stop loss, and all TP levels
- Comprehensive Statistics Panel: Displays win rate, profit factor, net profit, and trade performance
- Customizable Lot Size: Adjust position size with automatic point value calculation for actual dollar profit/loss
- Visual Trade Lines: Clear entry, SL, and TP lines with price labels
📊 STATISTICS TRACKED:
- Total Trades, Winning/Losing Trades
- Win Rate Percentage
- Net Profit & Profit Factor (in dollars based on lot size)
- Best Peak Profit (highest unrealized profit)
- Worst SL Trade
- Current Risk:Reward Ratio
⚙️ SETTINGS:
- Show Old Trades: Toggle historical trade visibility
- Statistics Panel Position: Top, Middle, or Bottom
- Lot Size: Customizable from 0.001 BTC (determines dollar value per point movement)
🎨 TRADING LOGIC:
LONG Entry: Generated when the proprietary algorithm detects optimal bullish momentum conditions
SHORT Entry: Triggered when the system identifies high-probability bearish setups
The indicator uses advanced price action analysis combined with multi-factor confirmation to filter out false signals and capture high-quality trading opportunities.
📌 IMPORTANT NOTE:
The TP levels ($400, $800, etc.) and SL ($1,700) represent Bitcoin PRICE MOVEMENT on the chart, not profit/loss amounts. Your actual profit or loss in dollars is calculated by multiplying the price movement by your lot size. For example, with 0.1 BTC lot size, a $400 price movement = $40 actual profit.
⚠️ REQUIREMENTS:
- Only works on Bitcoin (BTC) pairs
- Must use 15-minute timeframe
- Warning messages appear if conditions aren't met
💡 PERFECT FOR:
Traders seeking a systematic approach to Bitcoin trading with clear entry/exit rules and comprehensive performance tracking.
🔒 NO REPAINT - CONFIRMED SIGNALS ONLY
✅ All signals generated after candle close
✅ No disappearing or changing signals
✅ Backtesting = Real-time performance
✅ 100% Reliable alerts
What you see is what you get - Trade with confidence!
---
Note: This indicator is for educational purposes. Always practice proper risk management and never risk more than you can afford to lose.
Volume Weighted Price OscillatorThis indicator calculates the Percentage Price Oscillator (PPO), a momentum oscillator similar to the MACD. It displays the distance between two moving averages as a percentage, making it comparable across different assets. This implementation enhances the PPO with optional volume weighting and a built-in divergence engine.
Key Features:
Customizable MA & Volume Weighting: Both the fast and slow moving averages (and the signal line) can be customized using different MA types (e.g., EMA, SMA, WMA). An option (Volume weighted) applies volume weighting to all three MAs.
MACD-Style Display: Provides the three core components: the PPO line (momentum), a signal line (trigger), and a histogram (momentum acceleration). The histogram is color-coded to show increasing or decreasing momentum.
Full Divergence Suite (Class A, B, C): A built-in divergence engine automatically detects and plots all three major divergence classes between price and the PPO line:
Regular (A): Signals potential trend reversals.
Hidden (B): Signals potential trend continuations.
Exaggerated (C): Signals weakness at double tops/bottoms.
Divergence Filtering and Visualization:
Price Tolerance Filter: Divergence detection is enhanced with a percentage-based price tolerance (pivPrcTol) to filter out insignificant market noise.
Persistent Visualization: Divergence markers are plotted for the entire duration of the signal and are visually anchored to the PPO level of the confirming pivot.
Note on Confirmation (Lag): Divergence signals rely on a pivot confirmation method to ensure they do not repaint.
The Start of a- divergence is only detected after the confirming pivot is fully formed (a delay based on Pivot Right Bars).
The End of a divergence is detected either instantly (if the signal is invalidated by price action) or with a delay (when a new, non-divergent pivot is confirmed).
Multi-Timeframe (MTF) Capability:
MTF PPO Lines: The PPO, signal line, and histogram can be calculated on a higher timeframe, with standard options to handle gaps (Fill Gaps) and prevent repainting (Wait for...).
Limitation: The Divergence detection engine (pivDiv) is disabled if a timeframe other than the chart's timeframe is selected. Divergences are only calculated on the active chart timeframe.
Integrated Alerts: Includes 18 comprehensive alerts for:
The start and end of all 6 divergence types.
The PPO line crossing its signal line.
The PPO line crossing the zero line.
The histogram changing direction (reverting).
DISCLAIMER
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
Quantura - Supply & Demand Zone DetectionIntroduction
“Quantura – Supply & Demand Zone Detection” is an advanced indicator designed to automatically detect and visualize institutional supply and demand zones, as well as breaker blocks, directly on the chart. The tool helps traders identify key areas of market imbalance and potential reversal or continuation zones, based on price structure, volume, and ATR dynamics.
Originality & Value
This indicator provides a unique and adaptive method of zone detection that goes beyond simple pivot or candle-based logic. It merges multiple layers of confirmation—volume sensitivity, ATR filters, and swing structure—while dynamically tracking how zones evolve as the market progresses. Unlike traditional supply and demand indicators, this script also detects and plots Breaker Zones when previous imbalances are violated, giving traders an extra layer of market context.
The key values of this tool include:
Automated detection of high-probability supply and demand zones.
Integration of both volume and ATR filters for precision and adaptability.
Dynamic zone merging and updating based on price evolution.
Identification of breaker blocks (invalidated zones) to visualize market structure shifts.
Optional bullish and bearish trade signals when zones are retested.
Clear, visually optimized plotting for efficient chart interpretation.
Functionality & Core Logic
The indicator continuously scans recent price data for swing highs/lows and combines them with optional volume and ATR conditions to validate potential zones.
Demand Zones are formed when price action indicates accumulation or a strong bullish rejection from a low area.
Supply Zones are created when distribution or strong bearish rejection occurs near local highs.
Breaker Blocks appear when existing zones are invalidated by price, helping traders visualize potential market structure shifts.
Bullish and bearish signals appear when price re-enters an active zone or breaks through a breaker block.
Parameters & Customization
Demand Zones / Supply Zones: Enable or disable each individually.
Breaker Zones: Activate breaker block detection for invalidated zones.
Volume Filter: Optional filter to only confirm zones when volume exceeds its long-term average by a user-defined multiplier.
ATR Filter: Optional filter for volatility confirmation, ensuring zones form under strong momentum conditions.
Swing Length: Controls the number of bars used to detect structural pivots.
Sensitivity Controls: Adjustable ATR and volume multipliers to fine-tune detection responsiveness.
Signals: Toggle for on-chart bullish (▲) and bearish (▼) signal plotting when price interacts with zones.
Color Customization: User-defined bullish and bearish colors for both standard and breaker zones.
Core Calculations
Zones are detected using pivot highs and lows with a defined lookback and lookahead period.
Additional filters apply if ATR and volume are enabled, requiring conditions like “ATR > average * multiplier” and “Volume > average * multiplier.”
Detected zones are merged if overlapping, keeping the chart clean and logical.
When price breaks through a zone, the original box is closed, and a new breaker zone is plotted automatically.
Bullish and bearish markers appear when zones are retested from the opposite side.
Visualization & Display
Demand zones are shaded in semi-transparent bullish color (default: blue).
Supply zones are shaded in semi-transparent bearish color (default: red).
Breaker zones appear when previous imbalances are broken, helping to spot structural shifts.
Optional arrows (▲ / ▼) indicate potential buy or sell reactions on zone interaction.
Use Cases
Identify institutional areas of accumulation (demand) or distribution (supply).
Detect potential breakout traps and market structure shifts using breaker zones.
Combine with other tools such as volume profile, EMA, or liquidity indicators for deeper confirmation.
Observe retests and reactions of zones to anticipate possible reversals or continuations.
Apply multi-timeframe analysis to align higher timeframe zones with lower timeframe entries.
Limitations & Recommendations
The indicator does not predict future price movement; it highlights structural imbalances only.
Performance depends on chosen swing length and sensitivity — users should optimize parameters for each market.
Works best in volatile markets where supply and demand imbalances are clearly expressed.
Should be used as part of a broader trading framework, not as a standalone signal generator.
Markets & Timeframes
The “Quantura – Supply & Demand Zone Detection” indicator is suitable for all asset classes including cryptocurrencies, Forex, indices, commodities, and equities. It performs reliably across multiple timeframes, from intraday scalping to higher timeframe swing analysis.
Author & Access
Developed 100% by Quantura. Published as a protected source script indicator. Access is free.
Important
This description complies with TradingView’s Script Publishing and House Rules. It clearly explains the indicator’s originality, underlying logic, functionality, and intended use without unrealistic claims or performance guarantees.
Chaikin Money FlowThis indicator provides an implementation of the classic Chaikin Money Flow (CMF), a volume-weighted oscillator designed to measure money flow pressure. It is enhanced with a customizable signal line and a built-in divergence detection engine.
Key Features:
Full Divergence Suite (Class A, B, C): The primary feature is the integrated divergence engine. It automatically detects and plots all three major types of divergences:
Regular (A): Signals potential trend reversals.
Hidden (B): Signals potential trend continuations.
Exaggerated (C): Signals weakness at double tops/bottoms.
Divergence Filtering and Visualization:
Price Tolerance Filter: Divergence detection is enhanced with a percentage-based price tolerance (pivPrcTol) to filter out insignificant market noise, leading to more robust signals.
Persistent Visualization: Divergence markers are plotted for the entire duration of the signal and are visually anchored to the CMF level of the confirming pivot.
Customizable Signal Line: Includes an optional moving average of the CMF, which serves as a signal line. The type of MA (Signal Smoothing) and its length can be customized. This signal line can also be optionally volume-weighted (Volume weighted).
Note on Confirmation (Lag): Divergence signals rely on a pivot confirmation method to ensure they do not repaint.
The Start of a- divergence is only detected after the confirming pivot is fully formed (a delay based on Pivot Right Bars).
The End of a divergence is detected either instantly (if the signal is invalidated by price action) or with a delay (when a new, non-divergent pivot is confirmed).
Multi-Timeframe (MTF) Capability:
MTF CMF & Signal Lines: The CMF and its signal line can be calculated on a higher timeframe, with standard options to handle gaps (Fill Gaps) and prevent repainting (Wait for...).
Limitation: The Divergence detection engine (pivDiv) is disabled if a timeframe other than the chart's timeframe is selected. Divergences are only calculated on the active chart timeframe.
Integrated Alerts: Includes 16 comprehensive alerts for:
The start and end of all 6 divergence types.
The CMF crossing its signal line.
The CMF crossing the zero line.
DISCLAIMER
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
Accumulation Distribution LineThis indicator provides an implementation of the classic Accumulation/Distribution Line (ADL). It enhances the standard indicator with a built-in divergence detection engine.
Key Features:
Full Divergence Suite (Class A, B, C): The primary feature is the integrated divergence engine. It automatically detects and plots all three major types of divergences:
Regular (A): Signals potential trend reversals.
Hidden (B): Signals potential trend continuations.
Exaggerated (C): Signals weakness at double tops/bottoms.
Divergence Filtering and Visualization:
Price Tolerance Filter: Divergence detection is enhanced with a percentage-based price tolerance (pivPrcTol) to filter out insignificant market noise, leading to more robust signals.
Persistent Visualization: Divergence markers are plotted for the entire duration of the signal and are visually anchored to the ADL level of the confirming pivot.
Note on Confirmation (Lag): Divergence signals rely on a pivot confirmation method to ensure they do not repaint.
The Start of a- divergence is only detected after the confirming pivot is fully formed (a delay based on Pivot Right Bars).
The End of a divergence is detected either instantly (if the signal is invalidated by price action) or with a delay (when a new, non-divergent pivot is confirmed).
Multi-Timeframe (MTF) Capability:
MTF ADL Line: The ADL line itself can be calculated on a higher timeframe, with standard options to handle gaps (Fill Gaps) and prevent repainting (Wait for...).
Limitation: The Divergence detection engine (pivDiv) is disabled if a timeframe other than the chart's timeframe is selected. Divergences are only calculated on the active chart timeframe.
Integrated Alerts: Includes 12 comprehensive alerts that trigger on the start and end of all 6 divergence types (e.g., "Regular Bullish Started", "Regular Bullish Ended").
DISCLAIMER
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
ICT ADR/AWR/AMR Levels | Trade Symmetry🌟 ICT ADR/AWR/AMR Levels
📋 Overview
This advanced technical analysis tool calculates and displays Average Daily Range (ADR), Average Weekly Range (AWR), and Average Monthly Range (AMR) levels. The indicator incorporates smart detection technology that automatically maintains monthly level visibility when historical data becomes unavailable.
✨ Key Features
🕒 Precise Time Alignment
True Daily Opens (TDO) aligned with 00:00 UTC
True Weekly Opens (TWO) at 00:00 UTC (configurable Monday/Sunday start)
True Monthly Opens (TMO) at 00:00 UTC on month start
Customizable period start times and parameters
📊 Comprehensive Multi-Timeframe Analysis
Daily Levels (ADR): Base level with multiple extensions including Fibonacci ratios
Weekly Levels (AWR): Weekly range projections and key levels
Monthly Levels (AMR): Monthly range calculations with automatic fallback system
🔄 Intelligent Level Management
Smart Detection: Automatically switches between historical and current monthly levels
Continuous Visibility: Ensures reference levels remain visible regardless of data availability
Seamless Operation: No manual adjustment needed for level transitions
⚙️ Extensive Customization
Adjustable lookback periods for all timeframes
Independent control over each level type and extension
Complete visual customization (colors, styles, widths)
Flexible labeling and display options
Configurable vertical separation lines
🏷️ Advanced Display Options
Clean, organized label placement
Optional price display in labels
Historical period tracking
Overlapping label merging capability
Adjustable label sizing and positioning
🚀 How to Use
Initial Setup: Enable desired timeframes (Daily/Weekly/Monthly)
Range Configuration: Set appropriate averaging periods for each timeframe
Level Selection: Choose which extension levels to display
Visual Settings: Customize colors and styles to match your trading workspace
Automatic Operation: The indicator intelligently manages level transitions
💡 Practical Applications
Identify potential support and resistance areas across multiple timeframes
Establish realistic profit targets based on historical volatility
Plan trade entries and exits around significant time-based levels
Analyze market volatility patterns across different time horizons
Incorporate institutional trading concepts into your analysis
IPDA Time High/L🧭 IPDA Time Pivot High/Low (3•6•9)
Precision timing meets liquidity delivery.
🔹 Concept
This tool is built on the idea that price is delivered by time, not structure — a core belief in Zeussy/Smart Money–style analysis.
Certain time signatures, known as IPDA times (where the digits of hour and minute reduce to 3, 6, or 9), often align with reversals, traps, or accelerations in market delivery.
These times represent rhythmic energy cycles in algorithmic delivery, marking when liquidity is often redistributed.
🔹 What the Indicator Does
Scans your selected time window (default: 9:00–11:00, New York).
Identifies candles forming micro pivots — a candle that’s higher or lower than both its immediate neighbors.
Filters only those pivots that occur at IPDA times (digital roots of 3, 6, or 9).
Prints a clean, minimal time label (HH:MM) above or below each qualifying candle.
Labels dynamically adjust to your chart’s timezone and vertical spacing for clarity.
🔹 Why It’s Useful
These moments often align with:
Engineered traps during liquidity hunts.
Session transitions (e.g., London → NY Open).
Delivery shifts where price changes direction into the Draw on Liquidity (DOL).
By highlighting only precise, time-based pivots, this indicator helps traders:
Anticipate timing-based reversals,
Align narrative with smart-money delivery cycles,
And build refined entries within the NY AM session.
🔹 How to Use
Apply the indicator to your chart.
Set the timezone (default: America/New_York).
Focus on your session window (e.g., 09:00–11:00).
Observe when price reaches your POI or liquidity pool during an IPDA time — those candles are often where manipulation or delivery begins.
Combine with your own narrative tools (SMT, CISD, DOL, POI) for confirmation.
🔹 Features
Automatic timezone alignment
Adjustable session hours
Transparent, minimalistic time labels
Custom label size & offset for clean chart aesthetics
Works on all intraday timeframes
🔹 Philosophy
“Price is delivered by time, not structure.”
— Zeussy
This indicator was designed for traders who study timing as a function of delivery,
not just structure — allowing you to see when the algorithm intends to act.
ApexFlow👑 ApexFlow Trading Guide: Capturing the Smart Money Flow
ApexFlow is a comprehensive tool built on the philosophy of Smart Money Concepts (SMC). It helps you filter market noise and focus on three core elements professional traders use: Structure, Liquidity, and Context.
1. 🧭 Understanding Market Structure: BOS and ChoCH
ApexFlow automatically marks key price pivots and structure shifts, which is essential for determining the prevailing trend and spotting potential reversals.
BOS (Break of Structure): This signal confirms that the current trend is continuing. In an uptrend, price has broken a previous Swing High; in a downtrend, it has broken a Swing Low.
Action: If you are trading with the trend (Long in an uptrend, Short in a downtrend), hold or consider adding to your position.
ChoCH (Change of Character): This is an early warning that the trend's direction might be reversing.
Action: Wait for price to pull back after a ChoCH and look for an entry in the new direction indicated by the signal. This is a counter-trend or reversal trade setup.
2. 🌊 Trading Liquidity Zones: FVG and Sweeps
Smart money often drives price to areas where liquidity rests, primarily Fair Value Gaps (FVG) and Swing High/Low levels. ApexFlow highlights these targets.
A. Fair Value Gaps (FVG)
FVGs are price imbalances that often act as magnet zones. Price frequently returns to these areas to "mitigate" or fill the gap.
Observation: These appear as colored boxes (Bullish FVG or Bearish FVG) on the chart.
Strategy: Look for price to pull back into an active FVG box.
Long Entry: Seek confirmation (like bullish candle patterns) as price hits the lower boundary or the mean threshold of a Bullish FVG.
Short Entry: Seek confirmation as price hits the upper boundary or the mean threshold of a Bearish FVG.
B. Liquidity Sweeps (SFP)
A Sweep occurs when price momentarily pushes beyond a major Swing High or Low (collecting stop-losses) and then quickly reverses, indicating a large market participant has taken an opposing position.
Observation: Marked by 'Sweep' labels near pivot points.
Strategy:
Bullish Sweep (Bear Trap): Price sweeps below a Swing Low and immediately closes back above the level. This is a powerful setup for a Long entry.
Bearish Sweep (Bull Trap): Price sweeps above a Swing High and immediately closes back below the level. This is a powerful setup for a Short entry.
3. 📉 Context and Confluence: Filtering Trades
ApexFlow includes several tools to provide essential context, ensuring you only take the highest probability trades.
A. The UT Bot Signal
The indicator includes a simple volatility-based trend filter (labeled 'Buy' and 'Sell' below/above bars).
Use it as a Filter: Only take Long setups (FVG entries, Bullish Sweeps) when the UT Bot is displaying a 'Buy' signal or green bar coloring. Only take Short setups when a 'Sell' signal or red bar coloring is active.
B. Multi-Timeframe (MTF) Support/Resistance
ApexFlow can draw Support and Resistance (S/R) lines from higher timeframes onto your current chart.
Use it as a Target or Barrier: If you are Long, a major MTF Resistance level can be your Take-Profit target. If a setup occurs right at a major MTF S/R level, be cautious, as the level may act as a strong barrier.
💰 The ApexFlow Confluence Formula
The most profitable trades occur when all three layers align. Look for this Triple Confluence setup:
Structure Setup: A ChoCH or BOS signals a change or continuation in the direction of your intended trade.
Liquidity Trigger: The price reacts exactly as expected off a Liquidity Zone (e.g., a Bullish Sweep at a Swing Low OR a perfect mitigation of a Bullish FVG).
Context Confirmation: The UT Bot signal (or bar color) is green for Longs or red for Shorts, confirming the general trend direction.
Example Long Trade:
Entry: You see a Bullish ChoCH and the price pulls back into a Bullish FVG while the UT Bot is green.
Stop-Loss: Place your stop just below the FVG zone.
Take-Profit: Target the next major unmitigated Bearish FVG or a clean Swing High (Resistance) level.
EMA20TREND NOV25The indicator plots entry signals for both long and short trades, based on the a clear trend and test of EMA20 followed by a continuity candle.
VOODOORFVGS v1.1Voodoo Doors - Multi-Timeframe FVG & Range Analysis
Voodoo Doors is a comprehensive trading indicator designed to identify and track critical Fair Value Gaps (FVGs) and price ranges
across multiple timeframes. This powerful tool combines time-based FVG detection with Opening/Closing Range analysis to highlight
high-probability trading zones.
Key Features:
🚪 First Presented FVGs (FPVG)
Track up to 3 customizable FVGs that occur at specific times throughout the trading day:
- FPVG 1 (Default: 9:31 AM) - Early session gap detection
- FPVG 2 (Default: 1:31 PM) - Midday reversal zones
- FPVG 3 (Default: 6:15 AM) - Pre-market opportunities
Each FPVG includes:
- Historical tracking (up to 30 days)
- Age labels showing gap freshness
- Customizable fill colors, borders, and mid-lines
- Auto-extension to current bar
- Progressive transparency for older gaps
⚡ 15-Second Lower Timeframe FVGs
Precision intraday analysis during critical hours:
- 10am FVG - Morning volatility capture
- 11am FVG - Late morning momentum shifts
- Real-time detection using 15-second data
- Directional labels (↑/↓) for quick identification
📊 Opening Range (OR)
30-second precision Opening Range levels:
- Default: 9:30 AM market open
- High/Low and Equilibrium (EQ) levels
- Configurable historical tracking (up to 5 sessions)
- Price touch alerts available
- Extended or fixed-length projection
🔴 Closing Range (CR)
End-of-day price action analysis:
- Default: 3:59 PM (15:59)
- Captures final market positioning
- Independent styling from OR levels
- Optional extension into next session
🎯 Custom Range (CUR)
Flexible user-defined range detection:
- Any time, any timeframe
- Perfect for capturing specific news events
- Fully customizable colors and styles
- Alert functionality for level touches
Visual Customization:
Every element is fully customizable:
- Line styles: Solid, Dashed, Dotted
- Individual color controls for fills, borders, and mid-lines
- Adjustable transparency (0-100%)
- Line width controls
- Historical opacity settings
Professional Features:
✅ Non-repainting - all signals are final✅ Multi-timeframe support with automatic detection✅ Efficient array management for
historical data✅ Market session awareness (excludes weekends)✅ Optional information table showing global market open times✅ Alert
system for price touching key levels✅ Up to 500 drawing objects supported
Best Used For:
- ICT trading methodology (FVG mitigation)
- Range breakout/breakdown strategies
- Session transition trading
- Multi-timeframe confluence analysis
- Smart money tracking
Timezone:
Default UTC-4 (New York time) - fully adjustable in settings
Recommended Timeframes:
---
Note: This indicator uses lower timeframe data requests and requires TradingView Premium/Pro+ for full functionality.
Volume Weighted Linear Regression BandThe Volume-Weighted Linear Regression Band (VWLRBd) is a volatility channel that uses a Linear Regression line as its dynamic baseline. Its primary feature is the decomposition of total volatility into two distinct components, visualized as layered bands.
Key Features:
Volatility Decomposition: The indicator separates volatility based on the 'Estimate Bar Statistics' option.
Standard Mode (Estimate Bar Statistics = OFF): The indicator functions as a standard (Volume-Weighted) Linear Regression Channel. It plots a single set of bands based on the standard deviation of the residuals (the error between the Source price and the regression line).
Decomposition Mode (Estimate Bar Statistics = ON): The indicator uses a statistical model ('Estimator') to calculate within-bar volatility. (Assumption: In this mode, the Source input is ignored, and an estimated mean for each bar is used for the regression). This mode displays two sets of bands:
Inner Bands: Show only the contribution of the 'residual' (trend noise) volatility, calculated proportionally.
Outer Bands: Show the total volatility (the sum of residual and within-bar components).
Regression Baseline (Linear / Exponential): The central line is a (Volume-Weighted) Linear Regression curve. An optional 'Normalize' mode performs all calculations in logarithmic space, transforming the baseline into an Exponential Regression Curve and the bands into constant percentage deviations, suitable for analyzing growth assets.
Volume Weighting: An option (Volume weighted) allows for volume to be incorporated into the calculation of both the regression baseline and the volatility decomposition, giving more influence to high-participation bars.
Multi-Timeframe (MTF) Engine: The indicator includes an MTF conversion block. When a Higher Timeframe (HTF) is selected, advanced options become available: Fill Gaps handles data gaps, and Wait for timeframe to close prevents repainting by ensuring the indicator only updates when the HTF bar closes.
Integrated Alerts: Includes a full set of built-in alerts for the source price crossing over or under the central regression line and the outermost calculated volatility band.
DISCLAIM_
For Informational/Educational Use Only: This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset.
Use at Your Own Risk: All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk.
No Guarantee of Performance: Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability.
No Liability: The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator.
Signals Are Not Recommendations: The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
SuperOscCore Rules for Taking Action with SuperOsc:
Focus on Confluence Zones (The Strongest Signal) 🎯: The colored areas that appear in the upper or lower parts of the oscillator window are called Confluence Zones. This is the moment when all components of the indicator point strongly in the same direction.
If you see a Blue-Green Area: This is a Bullish Confluence, meaning buying pressure is at its peak. Consider opening a Long (Buy) position. 🟢
If you see a Red Area: This is a Bearish Confluence, meaning selling pressure is dominant. Consider opening a Short (Sell) position. 🔴
Check the Smart Money Flow (Momentum Confirmation) 💰: Look at the bars centered around the zero line in the oscillator. These bars indicate the instantaneous status of momentum.
Above Zero (Blue-Green): Strong buying momentum. ⬆️
Below Zero (Red): Strong selling momentum. ⬇️
The crossing of the zero line by these bars is a quick confirmation signal that momentum is rapidly changing direction.
Use the Score Line for Timing ⏱️: The crossovers between the main line (Score) and its smoother average (Signal line) are used to fine-tune your position entry moment.
Long Position Entry: Take action when the Score line crosses above the Signal line. 🚀
Short Position Entry: Take action when the Score line crosses below the Signal line. 📉
Exit Strategy 🛑:
Consider closing your position when you see one of the clearest signals that the trend is weakening:
Confluence Zone Disappears: When the colored area (Blue-Green or Red) fades away, you know the strong trend alignment has ended. 🙅
Reverse Crossover: The main (Score) line crosses the Signal line in the opposite direction of your trade. ↩️
LazyLine Color Change: A change in the color of the supporting line on your price chart (LazyLine) is a final exit signal indicating a shift in the primary trend. 🎨
With SuperOsc, you can turn complex market data into clear, action-oriented signals. Good luck! ✨
Daniel.Yer Volume Breakout Signal🧠 Summary – Daniel.Yer Volume Breakout Signal
The indicator only works on time frames of minutes.
An indicator that detects high-volume breakouts after the market opens and highlights potential entry zones.
Based on sampling the opening volume window and comparing it to the session’s volume peak.
Visually marks preparation areas (colored background) and plots BUY/SELL triangles for confirmation candles.
Includes real-time alert conditions for leading tickers: SPY, AAPL, MSFT, META, AMD, TSLA, NVDA, PLTR, GOOG, and AMZN.
Optimized for day trading — provides actionable alerts even when the user is offline.
DT MarkerThis indicators helps you identify the trend with ease by marking Dow Theory based HH-HL, LH-LL... Making things easy and helping you enter trades with smaller SL on the Retracements...
LibVPrfLibrary "LibVPrf"
This library provides an object-oriented framework for volume
profile analysis in Pine Script®. It is built around the `VProf`
User-Defined Type (UDT), which encapsulates all data, settings,
and statistical metrics for a single profile, enabling stateful
analysis with on-demand calculations.
Key Features:
1. **Object-Oriented Design (UDT):** The library is built around
the `VProf` UDT. This object encapsulates all profile data
and provides methods for its full lifecycle management,
including creation, cloning, clearing, and merging of profiles.
2. **Volume Allocation (`AllotMode`):** Offers two methods for
allocating a bar's volume:
- **Classic:** Assigns the entire bar's volume to the close
price bucket.
- **PDF:** Distributes volume across the bar's range using a
statistical price distribution model from the `LibBrSt` library.
3. **Buy/Sell Volume Splitting (`SplitMode`):** Provides methods
for classifying volume into buying and selling pressure:
- **Classic:** Classifies volume based on the bar's color (Close vs. Open).
- **Dynamic:** A specific model that analyzes candle structure
(body vs. wicks) and a short-term trend factor to
estimate the buy/sell share at each price level.
4. **Statistical Analysis (On-Demand):** Offers a suite of
statistical metrics calculated using a "Lazy Evaluation"
pattern (computed only when requested via `get...` methods):
- **Central Tendency:** Point of Control (POC), VWAP, and Median.
- **Dispersion:** Value Area (VA) and Population Standard Deviation.
- **Shape:** Skewness and Excess Kurtosis.
- **Delta:** Cumulative Volume Delta, including its
historical high/low watermarks.
5. **Structural Analysis:** Includes a parameter-free method
(`getSegments`) to decompose a profile into its fundamental
unimodal segments, allowing for modality detection (e.g.,
identifying bimodal profiles).
6. **Dynamic Profile Management:**
- **Auto-Fitting:** Profiles set to `dynamic = true` will
automatically expand their price range to fit new data.
- **Manipulation:** The resolution, price range, and Value Area
of a dynamic profile can be changed at any time. This
triggers a resampling process that uses a **linear
interpolation model** to re-bucket existing volume.
- **Assumption:** Non-dynamic profiles are fixed and will throw
a `runtime.error` if `addBar` is called with data
outside their initial range.
7. **Bucket-Level Access:** Provides getter methods for direct
iteration and analysis of the raw buy/sell volume and price
boundaries of each individual price bucket.
---
**DISCLAIMER**
This library is provided "AS IS" and for informational and
educational purposes only. It does not constitute financial,
investment, or trading advice.
The author assumes no liability for any errors, inaccuracies,
or omissions in the code. Using this library to build
trading indicators or strategies is entirely at your own risk.
As a developer using this library, you are solely responsible
for the rigorous testing, validation, and performance of any
scripts you create based on these functions. The author shall
not be held liable for any financial losses incurred directly
or indirectly from the use of this library or any scripts
derived from it.
create(buckets, rangeUp, rangeLo, dynamic, valueArea, allot, estimator, cdfSteps, split, trendLen)
Construct a new `VProf` object with fixed bucket count & range.
Parameters:
buckets (int) : series int number of price buckets ≥ 1
rangeUp (float) : series float upper price bound (absolute)
rangeLo (float) : series float lower price bound (absolute)
dynamic (bool) : series bool Flag for dynamic adaption of profile ranges
valueArea (int) : series int Percentage of total volume to include in the Value Area (1..100)
allot (series AllotMode) : series AllotMode Allocation mode `classic` or `pdf` (default `classic`)
estimator (series PriceEst enum from AustrianTradingMachine/LibBrSt/1) : series LibBrSt.PriceEst PDF model when `model == PDF`. (deflault = 'uniform')
cdfSteps (int) : series int even #sub-intervals for Simpson rule (default 20)
split (series SplitMode) : series SplitMode Buy/Sell determination (default `classic`)
trendLen (int) : series int Look‑back bars for trend factor (default 3)
Returns: VProf freshly initialised profile
method clone(self)
Create a deep copy of the volume profile.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object to copy
Returns: VProf A new, independent copy of the profile
method clear(self)
Reset all bucket tallies while keeping configuration intact.
Namespace types: VProf
Parameters:
self (VProf) : VProf profile object
Returns: VProf cleared profile (chaining)
method merge(self, srcABuy, srcASell, srcRangeUp, srcRangeLo, srcCvd, srcCvdHi, srcCvdLo)
Merges volume data from a source profile into the current profile.
If resizing is needed, it performs a high-fidelity re-bucketing of existing
volume using a linear interpolation model inferred from neighboring buckets,
preventing aliasing artifacts and ensuring accurate volume preservation.
Namespace types: VProf
Parameters:
self (VProf) : VProf The target profile object to merge into.
srcABuy (array) : array The source profile's buy volume bucket array.
srcASell (array) : array The source profile's sell volume bucket array.
srcRangeUp (float) : series float The upper price bound of the source profile.
srcRangeLo (float) : series float The lower price bound of the source profile.
srcCvd (float) : series float The final Cumulative Volume Delta (CVD) value of the source profile.
srcCvdHi (float) : series float The historical high-water mark of the CVD from the source profile.
srcCvdLo (float) : series float The historical low-water mark of the CVD from the source profile.
Returns: VProf `self` (chaining), now containing the merged data.
method addBar(self, offset)
Add current bar’s volume to the profile (call once per realtime bar).
classic mode: allocates all volume to the close bucket and classifies
by `close >= open`. PDF mode: distributes volume across buckets by the
estimator’s CDF mass. For `split = dynamic`, the buy/sell share per
price is computed via context-driven piecewise s(u).
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object
offset (int) : series int To offset the calculated bar
Returns: VProf `self` (method chaining)
method setBuckets(self, buckets)
Sets the number of buckets for the volume profile.
Behavior depends on the `isDynamic` flag.
- If `dynamic = true`: Works on filled profiles by re-bucketing to a new resolution.
- If `dynamic = false`: Only works on empty profiles to prevent accidental changes.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object
buckets (int) : series int The new number of buckets
Returns: VProf `self` (chaining)
method setRanges(self, rangeUp, rangeLo)
Sets the price range for the volume profile.
Behavior depends on the `dynamic` flag.
- If `dynamic = true`: Works on filled profiles by re-bucketing existing volume.
- If `dynamic = false`: Only works on empty profiles to prevent accidental changes.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object
rangeUp (float) : series float The new upper price bound
rangeLo (float) : series float The new lower price bound
Returns: VProf `self` (chaining)
method setValueArea(self, valueArea)
Set the percentage of volume for the Value Area. If the value
changes, the profile is finalized again.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object
valueArea (int) : series int The new Value Area percentage (0..100)
Returns: VProf `self` (chaining)
method getBktBuyVol(self, idx)
Get Buy volume of a bucket.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object
idx (int) : series int Bucket index
Returns: series float Buy volume ≥ 0
method getBktSellVol(self, idx)
Get Sell volume of a bucket.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object
idx (int) : series int Bucket index
Returns: series float Sell volume ≥ 0
method getBktBnds(self, idx)
Get Bounds of a bucket.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object
idx (int) : series int Bucket index
Returns:
up series float The upper price bound of the bucket.
lo series float The lower price bound of the bucket.
method getPoc(self)
Get POC information.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object
Returns:
pocIndex series int The index of the Point of Control (POC) bucket.
pocPrice. series float The mid-price of the Point of Control (POC) bucket.
method getVA(self)
Get Value Area (VA) information.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object
Returns:
vaUpIndex series int The index of the upper bound bucket of the Value Area.
vaUpPrice series float The upper price bound of the Value Area.
vaLoIndex series int The index of the lower bound bucket of the Value Area.
vaLoPrice series float The lower price bound of the Value Area.
method getMedian(self)
Get the profile's median price and its bucket index. Calculates the value on-demand if stale.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object.
Returns:
medianIndex series int The index of the bucket containing the Median.
medianPrice series float The Median price of the profile.
method getVwap(self)
Get the profile's VWAP and its bucket index. Calculates the value on-demand if stale.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object.
Returns:
vwapIndex series int The index of the bucket containing the VWAP.
vwapPrice series float The Volume Weighted Average Price of the profile.
method getStdDev(self)
Get the profile's volume-weighted standard deviation. Calculates the value on-demand if stale.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object.
Returns: series float The Standard deviation of the profile.
method getSkewness(self)
Get the profile's skewness. Calculates the value on-demand if stale.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object.
Returns: series float The Skewness of the profile.
method getKurtosis(self)
Get the profile's excess kurtosis. Calculates the value on-demand if stale.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object.
Returns: series float The Kurtosis of the profile.
method getSegments(self)
Get the profile's fundamental unimodal segments. Calculates on-demand if stale.
Uses a parameter-free, pivot-based recursive algorithm.
Namespace types: VProf
Parameters:
self (VProf) : VProf The profile object.
Returns: matrix A 2-column matrix where each row is an pair.
method getCvd(self)
Cumulative Volume Delta (CVD) like metric over all buckets.
Namespace types: VProf
Parameters:
self (VProf) : VProf Profile object.
Returns:
cvd series float The final Cumulative Volume Delta (Total Buy Vol - Total Sell Vol).
cvdHi series float The running high-water mark of the CVD as volume was added.
cvdLo series float The running low-water mark of the CVD as volume was added.
VProf
VProf Bucketed Buy/Sell volume profile plus meta information.
Fields:
buckets (series int) : int Number of price buckets (granularity ≥1)
rangeUp (series float) : float Upper price range (absolute)
rangeLo (series float) : float Lower price range (absolute)
dynamic (series bool) : bool Flag for dynamic adaption of profile ranges
valueArea (series int) : int Percentage of total volume to include in the Value Area (1..100)
allot (series AllotMode) : AllotMode Allocation mode `classic` or `pdf`
estimator (series PriceEst enum from AustrianTradingMachine/LibBrSt/1) : LibBrSt.PriceEst Price density model when `model == PDF`
cdfSteps (series int) : int Simpson integration resolution (even ≥2)
split (series SplitMode) : SplitMode Buy/Sell split strategy per bar
trendLen (series int) : int Look‑back length for trend factor (≥1)
maxBkt (series int) : int User-defined number of buckets (unclamped)
aBuy (array) : array Buy volume per bucket
aSell (array) : array Sell volume per bucket
cvd (series float) : float Final Cumulative Volume Delta (Total Buy Vol - Total Sell Vol).
cvdHi (series float) : float Running high-water mark of the CVD as volume was added.
cvdLo (series float) : float Running low-water mark of the CVD as volume was added.
poc (series int) : int Index of max‑volume bucket (POC). Is `na` until calculated.
vaUp (series int) : int Index of upper Value‑Area bound. Is `na` until calculated.
vaLo (series int) : int Index of lower value‑Area bound. Is `na` until calculated.
median (series float) : float Median price of the volume distribution. Is `na` until calculated.
vwap (series float) : float Profile VWAP (Volume Weighted Average Price). Is `na` until calculated.
stdDev (series float) : float Standard Deviation of volume around the VWAP. Is `na` until calculated.
skewness (series float) : float Skewness of the volume distribution. Is `na` until calculated.
kurtosis (series float) : float Excess Kurtosis of the volume distribution. Is `na` until calculated.
segments (matrix) : matrix A 2-column matrix where each row is an pair. Is `na` until calculated.
Connors Double Seven (with options)Rules (original, long-only)
Trade only when Close > 200-day SMA.
Entry: Buy when Close makes a 7-day low.
Exit: Sell when Close makes a 7-day high.
Multi-Timeframe Fibonacci + Open Levels🟣 Multi-Timeframe Fibonacci Levels + Open Levels | Trade Symmetry
This indicator automatically plots Fibonacci levels derived from higher timeframe candle ranges — all at once, directly on your current chart.
It helps you quickly visualize confluence zones and reaction levels where institutional traders are likely to participate.
⚙️ Features
✅ Multi-timeframe Fibonacci Levels — Daily, Weekly, Monthly, Quarterly & Yearly
✅ Automatic Bullish/Bearish detection based on previous candle
✅ Dynamic overlap detection (combines overlapping Fib levels into a single clean label)
✅ Configurable Fibonacci levels, colors, and styles
✅ Optional Open-Price Levels (Daily, Weekly, Monthly)
✅ Clean memory management to keep your chart lightweight
🧠 How to Use
• Add it to any timeframe — it will automatically overlay higher timeframe Fibs.
• Use overlapping or aligned Fib zones as confluence areas.
• Combine with structure or liquidity indicators for high-probability setups.
💡 Inspired by
The concept of higher-timeframe Fibonacci confluences used in Smart Money Concepts (SMC) and ICT-style analysis.
LibBrStLibrary "LibBrSt"
This is a library for quantitative analysis, designed to estimate
the statistical properties of price movements *within* a single
OHLC bar, without requiring access to tick data. It provides a
suite of estimators based on various statistical and econometric
models, allowing for analysis of intra-bar volatility and
price distribution.
Key Capabilities:
1. **Price Distribution Models (`PriceEst`):** Provides a selection
of estimators that model intra-bar price action as a probability
distribution over the range. This allows for the
calculation of the intra-bar mean (`priceMean`) and standard
deviation (`priceStdDev`) in absolute price units. Models include:
- **Symmetric Models:** `uniform`, `triangular`, `arcsine`,
`betaSym`, and `t4Sym` (Student-t with fat tails).
- **Skewed Models:** `betaSkew` and `t4Skew`, which adjust
their shape based on the Open/Close position.
- **Model Assumptions:** The skewed models rely on specific
internal constants. `betaSkew` uses a fixed concentration
parameter (`BETA_SKEW_CONCENTRATION = 4.0`), and `t4Sym`/`t4Skew`
use a heuristic scaling factor (`T4_SHAPE_FACTOR`)
to map the distribution.
2. **Econometric Log-Return Estimators (`LogEst`):** Includes a set of
econometric estimators for calculating the volatility (`logStdDev`)
and drift (`logMean`) of logarithmic returns within a single bar.
These are unit-less measures. Models include:
- **Parkinson (1980):** A High-Low range estimator.
- **Garman-Klass (1980):** An OHLC-based estimator.
- **Rogers-Satchell (1991):** An OHLC estimator that accounts
for non-zero drift.
3. **Distribution Analysis (PDF/CDF):** Provides functions to work
with the Probability Density Function (`pricePdf`) and
Cumulative Distribution Function (`priceCdf`) of the
chosen price model.
- **Note on `priceCdf`:** This function uses analytical (exact)
calculations for the `uniform`, `triangular`, and `arcsine`
models. For all other models (e.g., `betaSkew`, `t4Skew`),
it uses **numerical integration (Simpson's rule)** as
an approximation of the cumulative probability.
4. **Mathematical Functions:** The library's Beta distribution
models (`betaSym`, `betaSkew`) are supported by an internal
implementation of the natural log-gamma function, which is
based on the Lanczos approximation.
---
**DISCLAIMER**
This library is provided "AS IS" and for informational and
educational purposes only. It does not constitute financial,
investment, or trading advice.
The author assumes no liability for any errors, inaccuracies,
or omissions in the code. Using this library to build
trading indicators or strategies is entirely at your own risk.
As a developer using this library, you are solely responsible
for the rigorous testing, validation, and performance of any
scripts you create based on these functions. The author shall
not be held liable for any financial losses incurred directly
or indirectly from the use of this library or any scripts
derived from it.
priceStdDev(estimator, offset)
Estimates **σ̂** (standard deviation) *in price units* for the current
bar, according to the chosen `PriceEst` distribution assumption.
Parameters:
estimator (series PriceEst) : series PriceEst Distribution assumption (see enum).
offset (int) : series int To offset the calculated bar
Returns: series float σ̂ ≥ 0 ; `na` if undefined (e.g. zero range).
priceMean(estimator, offset)
Estimates **μ̂** (mean price) for the chosen `PriceEst` within the
current bar.
Parameters:
estimator (series PriceEst) : series PriceEst Distribution assumption (see enum).
offset (int) : series int To offset the calculated bar
Returns: series float μ̂ in price units.
pricePdf(estimator, price, offset)
Probability-density under the chosen `PriceEst` model.
**Returns 0** when `p` is outside the current bar’s .
Parameters:
estimator (series PriceEst) : series PriceEst Distribution assumption (see enum).
price (float) : series float Price level to evaluate.
offset (int) : series int To offset the calculated bar
Returns: series float Density value.
priceCdf(estimator, upper, lower, steps, offset)
Cumulative probability **between** `upper` and `lower` under
the chosen `PriceEst` model. Outside-bar regions contribute zero.
Uses a fast, analytical calculation for Uniform, Triangular, and
Arcsine distributions, and defaults to numerical integration
(Simpson's rule) for more complex models.
Parameters:
estimator (series PriceEst) : series PriceEst Distribution assumption (see enum).
upper (float) : series float Upper Integration Boundary.
lower (float) : series float Lower Integration Boundary.
steps (int) : series int # of sub-intervals for numerical integration (if used).
offset (int) : series int To offset the calculated bar.
Returns: series float Probability mass ∈ .
logStdDev(estimator, offset)
Estimates **σ̂** (standard deviation) of *log-returns* for the current bar.
Parameters:
estimator (series LogEst) : series LogEst Distribution assumption (see enum).
offset (int) : series int To offset the calculated bar
Returns: series float σ̂ (unit-less); `na` if undefined.
logMean(estimator, offset)
Estimates μ̂ (mean log-return / drift) for the chosen `LogEst`.
The returned value is consistent with the assumptions of the
selected volatility estimator.
Parameters:
estimator (series LogEst) : series LogEst Distribution assumption (see enum).
offset (int) : series int To offset the calculated bar
Returns: series float μ̂ (unit-less log-return).
尼森周期英文版Please help me translate the following text into Chinese: "Added Bitcoin cycles, part of a multi-version model, incorporated M2, and more top/bottom signals."
LibPvotLibrary "LibPvot"
This is a library for advanced technical analysis, specializing
in two core areas: the detection of price-oscillator
divergences and the analysis of market structure. It provides
a back-end engine for signal detection and a toolkit for
indicator plotting.
Key Features:
1. **Complete Divergence Suite (Class A, B, C):** The engine detects
all three major types of divergences, providing a full spectrum of
analytical signals:
- **Regular (A):** For potential trend reversals.
- **Hidden (B):** For potential trend continuations.
- **Exaggerated (C):** For identifying weakness at double tops/bottoms.
2. **Advanced Signal Filtering:** The detection logic uses a
percentage-based price tolerance (`prcTol`). This feature
enables the practical detection of Exaggerated divergences
(which rarely occur at the exact same price) and creates a
"dead zone" to filter insignificant noise from triggering
Regular divergences.
3. **Pivot Synchronization:** A bar tolerance (`barTol`) is used
to reliably match price and oscillator pivots that do not
align perfectly on the same bar, preventing missed signals.
4. **Signal Invalidation Logic:** Features two built-in invalidation
rules:
- An optional `invalidate` parameter automatically terminates
active divergences if the price or the oscillator breaks
the level of the confirming pivot.
- The engine also discards 'half-pivots' (e.g., a price pivot)
if a corresponding oscillator pivot does not appear within
the `barTol` window.
5. **Stateful Plotting Helpers:** Provides helper functions
(`bullDivPos` and `bearDivPos`) that abstract away the
state management issues of visualizing persistent signals.
They generate gap-free, accurately anchored data series
ready to be used in `plotshape` functions, simplifying
indicator-side code.
6. **Rich Data Output:** The core detection functions (`bullDiv`, `bearDiv`)
return a comprehensive 9-field data tuple. This includes the
boolean flags for each divergence type and the precise
coordinates (price, oscillator value, bar index) of both the
starting and the confirming pivots.
7. **Market Structure & Trend Analysis:** Includes a
`marketStructure` function to automatically identify pivot
highs/lows, classify their relationship (HH, LH, LL, HL),
detect structure breaks, and determine the current trend
state (Up, Down, Neutral) based on pivot sequences.
---
**DISCLAIMER**
This library is provided "AS IS" and for informational and
educational purposes only. It does not constitute financial,
investment, or trading advice.
The author assumes no liability for any errors, inaccuracies,
or omissions in the code. Using this library to build
trading indicators or strategies is entirely at your own risk.
As a developer using this library, you are solely responsible
for the rigorous testing, validation, and performance of any
scripts you create based on these functions. The author shall
not be held liable for any financial losses incurred directly
or indirectly from the use of this library or any scripts
derived from it.
bullDiv(priceSrc, oscSrc, leftLen, rightLen, depth, barTol, prcTol, persist, invalidate)
Detects bullish divergences (Regular, Hidden, Exaggerated) based on pivot lows.
Parameters:
priceSrc (float) : series float Price series to check for pivots (e.g., `low`).
oscSrc (float) : series float Oscillator series to check for pivots.
leftLen (int) : series int Number of bars to the left of a pivot (default 5).
rightLen (int) : series int Number of bars to the right of a pivot (default 5).
depth (int) : series int Maximum number of stored pivot pairs to check against (default 2).
barTol (int) : series int Maximum bar distance allowed between the price pivot and the oscillator pivot (default 3).
prcTol (float) : series float The percentage tolerance for comparing pivot prices. Used to detect Exaggerated
divergences and filter out market noise (default 0.05%).
persist (bool) : series bool If `true` (default), the divergence flag stays active for the entire duration of the signal.
If `false`, it returns a single-bar pulse on detection.
invalidate (bool) : series bool If `true` (default), terminates an active divergence if price or oscillator break
below the confirming pivot low.
Returns: A tuple containing comprehensive data for a detected bullish divergence.
regBull series bool `true` if a Regular bullish divergence (Class A) is active.
hidBull series bool `true` if a Hidden bullish divergence (Class B) is active.
exgBull series bool `true` if an Exaggerated bullish divergence (Class C) is active.
initPivotPrc series float Price value of the initial (older) pivot low.
initPivotOsz series float Oscillator value of the initial pivot low.
initPivotBar series int Bar index of the initial pivot low.
lastPivotPrc series float Price value of the last (confirming) pivot low.
lastPivotOsz series float Oscillator value of the last pivot low.
lastPivotBar series int Bar index of the last pivot low.
bearDiv(priceSrc, oscSrc, leftLen, rightLen, depth, barTol, prcTol, persist, invalidate)
Detects bearish divergences (Regular, Hidden, Exaggerated) based on pivot highs.
Parameters:
priceSrc (float) : series float Price series to check for pivots (e.g., `high`).
oscSrc (float) : series float Oscillator series to check for pivots.
leftLen (int) : series int Number of bars to the left of a pivot (default 5).
rightLen (int) : series int Number of bars to the right of a pivot (default 5).
depth (int) : series int Maximum number of stored pivot pairs to check against (default 2).
barTol (int) : series int Maximum bar distance allowed between the price pivot and the oscillator pivot (default 3).
prcTol (float) : series float The percentage tolerance for comparing pivot prices. Used to detect Exaggerated
divergences and filter out market noise (default 0.05%).
persist (bool) : series bool If `true` (default), the divergence flag stays active for the entire duration of the signal.
If `false`, it returns a single-bar pulse on detection.
invalidate (bool) : series bool If `true` (default), terminates an active divergence if price or oscillator break
above the confirming pivot high.
Returns: A tuple containing comprehensive data for a detected bearish divergence.
regBear series bool `true` if a Regular bearish divergence (Class A) is active.
hidBear series bool `true` if a Hidden bearish divergence (Class B) is active.
exgBear series bool `true` if an Exaggerated bearish divergence (Class C) is active.
initPivotPrc series float Price value of the initial (older) pivot high.
initPivotOsz series float Oscillator value of the initial pivot high.
initPivotBar series int Bar index of the initial pivot high.
lastPivotPrc series float Price value of the last (confirming) pivot high.
lastPivotOsz series float Oscillator value of the last pivot high.
lastPivotBar series int Bar index of the last pivot high.
bullDivPos(regBull, hidBull, exgBull, rightLen, yPos)
Calculates the plottable data series for bullish divergences. It manages
the complex state of a persistent signal's plotting window to ensure
gap-free and accurately anchored visualization.
Parameters:
regBull (bool) : series bool The regular bullish divergence flag from `bullDiv`.
hidBull (bool) : series bool The hidden bullish divergence flag from `bullDiv`.
exgBull (bool) : series bool The exaggerated bullish divergence flag from `bullDiv`.
rightLen (int) : series int The same `rightLen` value used in `bullDiv` for correct timing.
yPos (float) : series float The series providing the base Y-coordinate for the shapes (e.g., `low`).
Returns: A tuple of three `series float` for plotting bullish divergences.
regBullPosY series float Contains the static anchor Y-value for Regular divergences where a shape should be plotted; `na` otherwise.
hidBullPosY series float Contains the static anchor Y-value for Hidden divergences where a shape should be plotted; `na` otherwise.
exgBullPosY series float Contains the static anchor Y-value for Exaggerated divergences where a shape should be plotted; `na` otherwise.
bearDivPos(regBear, hidBear, exgBear, rightLen, yPos)
Calculates the plottable data series for bearish divergences. It manages
the complex state of a persistent signal's plotting window to ensure
gap-free and accurately anchored visualization.
Parameters:
regBear (bool) : series bool The regular bearish divergence flag from `bearDiv`.
hidBear (bool) : series bool The hidden bearish divergence flag from `bearDiv`.
exgBear (bool) : series bool The exaggerated bearish divergence flag from `bearDiv`.
rightLen (int) : series int The same `rightLen` value used in `bearDiv` for correct timing.
yPos (float) : series float The series providing the base Y-coordinate for the shapes (e.g., `high`).
Returns: A tuple of three `series float` for plotting bearish divergences.
regBearPosY series float Contains the static anchor Y-value for Regular divergences where a shape should be plotted; `na` otherwise.
hidBearPosY series float Contains the static anchor Y-value for Hidden divergences where a shape should be plotted; `na` otherwise.
exgBearPosY series float Contains the static anchor Y-value for Exaggerated divergences where a shape should be plotted; `na` otherwise.
marketStructure(highSrc, lowSrc, leftLen, rightLen, srcTol)
Analyzes the market structure by identifying pivot points, classifying
their sequence (e.g., Higher Highs, Lower Lows), and determining the
prevailing trend state.
Parameters:
highSrc (float) : series float Price series for pivot high detection (e.g., `high`).
lowSrc (float) : series float Price series for pivot low detection (e.g., `low`).
leftLen (int) : series int Number of bars to the left of a pivot (default 5).
rightLen (int) : series int Number of bars to the right of a pivot (default 5).
srcTol (float) : series float Percentage tolerance to consider two pivots as 'equal' (default 0.05%).
Returns: A tuple containing detailed market structure information.
pivType series PivType The type of the most recently formed pivot (e.g., `hh`, `ll`).
lastPivHi series float The price level of the last confirmed pivot high.
lastPivLo series float The price level of the last confirmed pivot low.
lastPiv series float The price level of the last confirmed pivot (either high or low).
pivHiBroken series bool `true` if the price has broken above the last pivot high.
pivLoBroken series bool `true` if the price has broken below the last pivot low.
trendState series TrendState The current trend state (`up`, `down`, or `neutral`).
