srd786-Intraday VWAP Price Action IndicatorDISCLAIMER
This Pine Script indicator does not constitute financial advice; it is just intended for educational and informational purposes. It functions as a tool for technical analysis that could help traders spot possible trading opportunities. It is crucial to remember that participating in financial markets has a number of risks that might result in large losses and are not suitable for all investors.
Users are encouraged to conduct their own thorough investigation and analysis prior to using this indicator. Avoiding trading with money that one cannot afford to lose is essential. It is also advised to seek advice from a certified financial expert. Users must use suitable risk management techniques and recognize that past success does not guarantee future outcomes.
Any losses, damages, or other consequences resulting from the usage of this indicator are not the author's responsibility. The user is ultimately responsible for all trading decisions, therefore using this tool is at their own risk.
INTRODUCTION
The “srd786-Intraday VWAP Price Action Indicator” is a sophisticated Pine Script (version 6) trading tool designed for intraday traders who focus on New York session trading hours. This indicator combines multiple technical analysis concepts including Volume Weighted Average Price (VWAP), Average True Range (ATR) for risk management, swing point detection for support/resistance identification, and momentum analysis through RSI. The primary objective is to generate high-probability long and short signals based on price action confluence with trend, momentum, and key structural levels.
1.
VWAP (Volume Weighted Average Price): Shows the "fair" average price based on both price and trading volume.
2.
ATR (Average True Range): Measures how much the price typically moves each day.
3.
Trend Analysis: Identifies whether the market is going up, down, or sideways.
4.
Momentum Indicators: Shows how strong the current price movement is.
5.
Support & Resistance: Identifies key price levels where the price might stop or reverse.
6.
Swing Points: Finds significant turning points in the price.
This indicator is specifically optimized for the New York trading session (9:30 AM to 4:00 PM ET), making it particularly suitable for traders who focus on US market hours. It provides a complete trading framework that includes not only signal generation but also precise trade management levels including entry prices, stop-loss orders, and profit targets based on a configurable reward-to-risk ratio.
The philosophy behind this indicator is confluence-based trading. Rather than relying on a single indicator or condition, it requires multiple factors to align before generating a trade signal. This approach filters out lower-probability setups and focuses only on high-quality opportunities where price action, trend direction, momentum, and key technical levels all point in the same direction.
CORE CONCEPT AND METHODOLOGY
Volume Weighted Average Price (VWAP)
VWAP is the cornerstone of this indicator's trading methodology. Unlike a simple moving average that treats all price bars equally, VWAP incorporates volume data into its calculation, giving more weight to bars with higher trading volume. This makes VWAP a more accurate representation of the true average price where the most significant trading activity occurred.
The calculation of VWAP is performed using the built-in 'ta.vwap()' function, which computes the cumulative volume-weighted average price from the beginning of the session. For intraday traders, VWAP serves as a critical reference point that indicates whether the current price is trading at a premium (above VWAP) or discount (below VWAP) relative to the session's volume-weighted average.
In this indicator, the VWAP source is configurable through the 'vwapSource' parameter, with the default being HLC3 (High + Low + Close / 3). This source selection allows traders to experiment with different price types such as typical price, weighted close, or even custom sources to suit their trading style and market preferences.
Average True Range (ATR) for Risk Management
The Average True Range, calculated using 'ta.atr()', measures market volatility by decomposing the current range of price movement. ATR does not indicate price direction;
instead, it quantifies the degree of price movement or volatility over a specified period. In this indicator, ATR serves dual purposes: determining the distance for limit orders and calculating stop-loss levels.
The 'atrLength' parameter (default: 14) controls the lookback period for the ATR calculation. A shorter length makes the indicator more responsive to recent volatility, while a longer length provides a smoother average that may be more suitable for less volatile markets. The 'atrMultiplier' (default: 1.5) determines how many ATR units away the stop-loss is placed from the entry price, allowing traders to adjust their risk exposure based on current market conditions.
Swing Detection and Support/Resistance
Swing points represent significant turning points in price action where the market has temporarily exhausted its directional momentum. This indicator uses pivot high and pivot low calculations to identify swing highs and swing lows, which then form the basis for dynamic support and resistance levels.
The 'swingLength' parameter (default: 5) defines how many bars to the left and right of a potential pivot point must be lower (for pivot highs) or higher (for pivot lows) to confirm the swing point. This lookback period helps filter out minor price fluctuations and focuses on more significant structural levels.
Support and resistance levels are stored in arrays ('swingHighArray' and 'SwingLowArray'), with the most recent swing points serving as the primary reference levels. The 'srLookback' parameter (default: 20) controls the overall lookback window and also determines how many
swing points to maintain in each array, ensuring that only relevant historical levels are considered.
Breakout Detection
When a price moves past a major support or resistance level, this is known as a price breakout. This price breakout suggests that there is a possibility of a new trend direction heading forward.Breakout detection eliminates noise, as little price fluctuations or volatility may momentarily drive prices past a threshold without authentic conviction.Detection of breakouts affirms robustness when the price above the threshold by 2%, indicating genuine market interest, and mitigates whipsaws to prevent placing trades based on transient price swings.
The Breakout Tolerance parameter, set by default to 2%, regulates the breakout tolerance for the indicator. A price closure above the current high plus a minor tolerance buffer (usually 2%) indicates a potential continuation of upward movement, classified as a Bullish Breakout. Conversely, when the price closes below the recent low plus a minor tolerance buffer (usually 2%), it suggests that the price may continue to decline, which is classified as a Bearish Breakout Down.
Trend Identification
Trend determination is accomplished through an Exponential Moving Average (EMA) with a configurable length ('trendMaLength', default: 9). The indicator classifies trend into three
states: BULLISH (price above EMA with confirmation from the previous bar), BEARISH (price below EMA with confirmation), and SIDEWAYS (price crossing or near the EMA).
The EMA is chosen over simple moving averages because it responds more quickly to recent price changes while still providing enough smoothing to filter out noise. The confirmation requirement (both current and previous bar must be on the same side of the EMA) reduces false signals during periods of choppy price action.
Momentum Analysis
Momentum is measured using the Relative Strength Index (RSI) with a configurable length ('momentumLength', default: 9). RSI values are categorized into five states to provide nuanced momentum readings: STRONG BULL (RSI above 70), BUILDING (RSI between 55 and 70), NEUTRAL (RSI between 45 and 55), WEAKENING (RSI below 45), and STRONG BEAR (RSI below 30).
This momentum categorization allows traders to distinguish between strong trending conditions (STRONG BULL/BEAR) and transitions (BUILDING/WEAKENING), providing context for trade signals and helping to avoid entering positions during momentum divergences.
CONFIGURATION PARAMETERS
VWAP Settings
The 'vwapSource' parameter determines which price value is used in the VWAP calculation. The default value of 'hlc3' (High + Low + Close / 3) provides a balanced representation of each bar's price action. Traders can modify this to use typical price ('high + low + close / 3'), weighted close ('high + low + close + close / 4'), or other price types depending on their analytical preferences.
ATR Settings
The 'atrLength' parameter sets the lookback period for the Average True Range calculation. The default of 14 periods is standard across most trading platforms and timeframes, providing a good balance between responsiveness and smoothness. The 'atrMultiplier' parameter (default: 1.5) scales the ATR value to determine stop-loss distances. A multiplier of 1.5 means the stop-loss is placed 1.5 ATR units away from the entry price, providing enough buffer to accommodate normal volatility while limiting risk.
Trade Settings
The 'rrRatio' parameter (default: 3.0) establishes the reward-to-risk ratio for trade targets. A ratio of 2.0 means the profit target is twice the distance of the stop-loss from the entry price. The 'limitOrderDistance' parameter (default: 0.5) determines how far below (for long trades)
or above (for short trades) the current close the limit order is placed, measured in ATR units. This allows traders to enter positions at better prices while waiting for pullbacks.
Swing Detection Settings
The 'swingLength' parameter (default: 5) controls pivot identification sensitivity. Higher values identify more significant swing points but may miss shorter-term opportunities. The 'showSwings' boolean parameter toggles the visual display of swing high and low points on the chart.
Support & Resistance Settings
The 'srLookback' parameter (default: 20) defines how many bars back to search for swing points and support/resistance levels. The 'breakoutTolerance' parameter (default: 0.02 or 2%) adds a small buffer to breakout detection to account for minor penetration of support/resistance levels due to price spikes or slippage.
Trend & Momentum Settings
The 'trendMaLength' parameter (default: 9) sets the EMA length for trend determination, while 'momentumLength' (default: 9) sets the RSI lookback period. Both should be at least 5 periods for meaningful calculations.
Table Settings
The 'showTable' parameter (default: true) enables the display of two information tables that provide real-time data on Indicator values and trade levels.
SIGNAL GENERATION LOGIC
Long Signal Conditions
A long signal is generated when all the following conditions are simultaneously true:
1.
Session Filter: The trade must occur during New York session hours (9:30 AM - 4:00 PM ET).
2.
Trend Confirmation: The trend must be BULLISH (price above EMA with confirmation).
3.
Price Position: Current price must be above VWAP, indicating bullish price action.
4.
Breakout or No Resistance: Either price is breaking out above resistance level with tolerance, or there is no prior resistance level to overcome.
5.
Momentum Alignment: Momentum must be either STRONG BULL or BUILDING.
This confluence of conditions ensures that long trades are only taken when the market is trending higher, price is confirming strength by trading above VWAP, and momentum is supportive of continued upward movement.
Short Signal Conditions
A short signal is generated when all the following conditions are simultaneously true:
1.
Session Filter: The trade must occur during New York session hours
2.
Trend Confirmation: The trend must be BEARISH (price below EMA with confirmation)
3.
Price Position: Current price must be below VWAP, indicating bearish price action
4.
Breakout or No Support: Either price is breaking down below support level with tolerance, or there is no prior support level to overcome
5.
Momentum Alignment: Momentum must be either STRONG BEAR or WEAKENING
Similar to long signals, short trades require alignment across multiple timeframes and analytical approaches, filtering out counter-trend trades and focusing on high-probability setups.
TRADE MANAGEMENT FRAMEWORK
Entry Price Calculation
For long trades, the limit order price is calculated as: 'Close - (ATR Value × Limit Order Distance)'. This places the entry price below the current close, allowing traders to buy on dips while maintaining a favorable entry price. For short trades, the limit order is placed above the current close: 'Close + (ATR Value × Limit Order Distance)'.
The limit order distance is expressed in ATR units, making it adaptive to current volatility conditions. In more volatile markets, the limit order will be placed further from the current price, while in calmer markets, it will be closer.
Stop-Loss Placement
Stop-loss levels are calculated using the ATR multiplier to ensure adaptive risk management. For long trades: 'Entry Price - (ATR Value × ATR Multiplier)'. For short trades: 'Entry Price + (ATR Value × ATR Multiplier)'.
This adaptive approach to stop-loss placement means that in volatile markets, stops are wider to avoid being stopped out by normal price fluctuations, while in quieter markets, stops are tighter to limit potential losses. The default multiplier of 1.5 provides approximately 1.5 times the average true range of protection.
Target Price Calculation
Profit targets are determined by the reward-to-risk ratio: 'Entry Price + (ATR Stop Distance × RR Ratio)' for long trades and 'Entry Price - (ATR Stop Distance × RR Ratio)' for short trades. The default ratio of 2.0 means the target is twice the distance of the stop-loss, providing a favorable risk-reward profile.
New York Session Tracking
The indicator includes specialized logic for tracking the New York session open price. When a new NY session begins (determined by the 'isNewNySession' variable), the current open price is recorded and maintained throughout the session. This provides a reference point for measuring intraday directional bias from the session's starting level.
INFORMATION TABLES
Indicators Table
This table displays the current price, VWAP value, NY session open price, support level,resistance level, ATR, ATR-scaled stop distance, current trend classification, momentum state with RSI value, and breakout status. All values are color-coded based on their bullish or bearish implications. The VWAP cell is color-coded green if price is above VWAP (bullish) and red if below (bearish), providing instant visual confirmation of price's position relative to this critical level.
Trade Levels Table
This table shows current signal status (LONG, SHORT, or WAIT), limit order distance in ATR units, calculated limit order price, stop-loss level, and target price with the reward-to-risk ratio displayed. The signal cell is highlighted in green for long signals and red for short signals.
ALERT CONDITIONS
The indicator includes four alert conditions that can be configured in TradingView:
1.
LONG Signal: Triggers when a long signal is generated, providing entry price, stop-loss, and target information.
2.
SHORT Signal: Triggers when a short signal is generated with corresponding trade details.
3.
Breakout Up: Notifies when price breaks out above resistance level.
4.
Breakout Down: Notifies when price breaks down below support level.
These alerts enable traders to receive notifications via TradingView's alert system without continuously monitoring the charts.
USAGE EXAMPLES AND TRADING SCENARIOS
Strong Bullish Trend with VWAP Support
In this scenario, price has been trading above the 9-period EMA for multiple bars, confirming a bullish trend. The current price is above VWAP, indicating buyers are willing to pay a premium. A recent swing low has established a support level, and RSI is reading 65, indicating building momentum without being overextended. When price breaks above the recent swing high resistance with a 2% tolerance, the indicator generates a long signal. The trader places a limit order below the current bar's close (0.5 ATR units) and sets the stop-loss 1.5 ATR units below the entry, with a target 2.0 times the stop distance away.
Short Setup During Volatile Session
During a particularly volatile NY session, price gaps down below VWAP early in the day. The 9-period EMA is declining, and both current and previous bars are below it, confirming a bearish trend. The RSI has dropped to 28, indicating strong bearish momentum. A recent swing high serves as resistance, and when price breaks below the swing low support level, the indicator generates a short signal. The trader enters on a limit order placed 0.5 ATR units above the current price, with the stop-loss 1.5 ATR units above the entry and the target at a 2.0 reward-to-risk ratio.
Avoiding Counter-Trend Trades
Consider a scenario where price is above VWAP and the RSI reads 72 (overbought), but the price is below the 9-period EMA and the previous bar was also below the EMA. In this case, the trend is classified as BEARISH (or SIDEWAYS) despite the bullish price position relative to VWAP. The indicator will not generate a long signal because the trend condition is not met, protecting the trader from what could be a bear trap or continuation pattern.
No Prior Levels Scenario
At the beginning of a trading session or after significant volatility has cleared prior swing points, there may be no established support or resistance levels in the lookback window. In this case, the breakout condition 'or na(resistanceLevel)' allows long signals to be generated without requiring a resistance level to be broken, enabling traders to participate in emerging trends without waiting for prior levels to form.
BEST PRACTICES AND TIPS
Timeframe Selection
This indicator is optimized for intraday timeframes (1-minute to 60-minute charts) and specifically for NY session trading. Higher timeframes may produce more reliable signals but fewer opportunities, while lower timeframes will generate more signals but with potentially lower reliability. Traders should backtest on their preferred timeframe before trading live.
Market Conditions
The indicator performs best in trending markets with clear directional bias. During ranging or sideways markets, the trend condition may oscillate frequently, and VWAP may oscillate around price, reducing signal quality. Consider filtering signals or reducing position size during low-volatility, range-bound conditions.
Parameter Optimization
While the default parameters have been selected for general applicability, traders should consider optimizing certain parameters for specific markets or instruments. For highly volatile instruments like crude oil or natural gas, increasing the 'atrMultiplier' to 2.0 or 2.5 may provide more appropriate risk management. For less volatile instruments like certain forex pairs, reducing the multiplier to 1.0 or 1.2 may improve signal quality.
Multiple Timeframe Analysis
For enhanced performance, traders can analyze the trend on a higher timeframe (such as 15-minute or hourly) while taking signals on a lower timeframe (such as 5-minute or 1-minute). This multi-timeframe approach ensures that signals are aligned with the larger trend direction.
Risk Management
While the indicator provides calculated stop-loss levels, traders should consider their overall position sizing and portfolio risk. The ATR-based stops provide a market-adaptive approach, but individual risk tolerance and account size should ultimately determine position sizing. The 2.0 reward-to-risk ratio is fixed but can be adjusted based on personal preferences or the specific characteristics of the instrument being traded.
INTEGRATION WITH TRADINGVIEW
Adding the Indicator
To add this indicator to a TradingView chart, paste the code into the Pine Script editor and click "Add to Chart." The indicator will appear in the chart's sidebar and begin calculating immediately once sufficient historical data is available.
Configuring Alerts
To set up alerts, right-click on any of the alert conditions in the indicator's settings panel (long signal, short signal, breakout up, or breakout down) and select "Add Alert." Configure the alert frequency and notification methods (push notification, email, webhook, etc.) according to your preferences.
Customization
All input parameters can be adjusted through the indicator's settings panel without modifying the source code. Traders can experiment with different VWAP sources, ATR lengths and multipliers, swing detection parameters, and table display options to suit their trading style and market preferences.
LIMITATIONS AND CONSIDERATIONS
Session Dependency
The indicator is specifically designed for NY session trading and will not generate signals outside these hours. Traders focused on other sessions or 24-hour markets may need to modify the session string to match their trading hours.
Historical Data Requirements
The indicator requires sufficient historical data to accurately calculate swing points and support/resistance levels. On lower timeframe charts with limited history, the initial signals may be less reliable until adequate swing points are identified.
Lag in Swing Detection
By definition, swing points are confirmed after the price has moved away from them, introducing some lag into support/resistance identification. Traders should be aware that the most recent swing point may not be confirmed until several bars after it occurs.
Not Financial Advice
This indicator is a technical analysis tool and should not be construed as financial advice. Traders are responsible for their own research and risk management decisions. Past performance of any trading system does not guarantee future results.
SUMMARY
The code follows a logical flow:
•
Version and Declaration: Pine Script version 6 indicator declaration with overlay enabled
•
Input Parameters: All user-configurable settings grouped by category
•
Session Logic: New York session tracking and open price recording
•
Core Calculations: VWAP, ATR, EMA, RSI, swing points
•
Support/Resistance Logic: Array-based storage and retrieval of swing levels
•
Trend and Momentum Classification: Categorization of current market state
•
Signal Generation: Confluence-based long and short conditions
•
Trade Level Calculations: Entry, stop-loss, and target pricing
•
Visual Plots: Hidden plots for alert data access
•
Information Tables: Real-time display of key values
•
Alert Conditions: Four configurable alert triggers
This structured approach ensures clarity, maintainability, and extensibility for future modifications or enhancements.
חפש סקריפטים עבור "indicators"
Market State Fear & Greed Bubble Index V1Market State Fear & Greed Bubble Index V1
📊 Comprehensive Market Sentiment Analyzer
This advanced indicator measures market psychology through a multi-dimensional scoring system, combining demand/supply pressure, trend momentum, and statistical extremes to identify fear/greed cycles and trading opportunities.
🎯 Core Features
Five-Factor Fear & Greed Score
Weighted sentiment analysis:
Demand/Supply (25%): Real-time buying/selling pressure
RSI (25%): Momentum extremes
KDJ (20%): Overbought/oversold detection
Bollinger Band % (20%): Statistical positioning
ADX Trend (10%): Trend strength confirmation
Multi-Layer Market State Detection
Extreme Fear/Greed: Statistical bubble identification
Trend Bias: Bullish/Bearish/Neutral classification
Confidence Scoring: Setup reliability assessment
Reversal Alerts: Early trend change signals
Visual Dashboard
Top-right information panel displays:
Fear & Greed Score (0-100)
Market State Classification
Trend Bias & Confidence
Signal Quality & Alerts
📈 Key Components
Fear & Greed Gauge
0-30: Extreme Fear (buying opportunities)
30-47: Fear (accumulation zones)
47-70: Neutral (consolidation)
70-90: Greed (caution zones)
90-100: Extreme Greed (selling opportunities)
Deviation Zones
Red Zone (±17.065): Critical reversal areas
Yellow Zone (±34.135): Warning levels
Blue Zone (±47.72): Statistical extremes where reversals are highly likely. These occur when asset prices are in a bubble that's about to pop.
Signal Types
Buy/Sell Labels: Primary entry/exit signals
Scalp Signals: Short-term opportunities
Bottom/Top Detectors: Extreme reversal zones
Whale Indicators: Institutional activity markers
🚀 Trading Applications
Extreme Fear Setups Conditions:
Fear & Greed Score < 34.135
BB% < 0 or < J-inverted line
RSI < 34.135
Confidence score > 68%
Bullish divergence present
Action: Accumulation positions, scaled entries
Extreme Greed Setup Conditions:
Fear & Greed Score > 68.2
BB% > 100 or > 80 with divergence
RSI > 68.2
ADX showing trend exhaustion
Multiple timeframe resistance
Action: Profit-taking, protective stops
Trend Following
Bullish Conditions:
Sentiment score rising from fear zones
DMI+ above DMI- and rising
Confidence > 75%
Volume supporting moves
Bearish Conditions:
Sentiment declining from greed zones
DMI- above DMI+ and rising
Distribution patterns
Multiple resistance failures
⚙️ Customization Options
Adjustable Parameters:
DMI Settings: DI lengths, ADX smoothing
KDJ Periods: Customizable sensitivity
BB% Range: Statistical band adjustments
Smoothing Options: Demand/Supply filtering
Alert Thresholds: Custom signal levels
Visual Customization:
Color schemes for different market states
Line thickness and style preferences
Information panel display options
Alert sound/visual preferences
📊 Signal Interpretation
Primary Signals:
Green 'B': Strong buy opportunity
Red 'S': Strong sell opportunity
White 'Scalp': Short-term trade
Trade Area: Accumulation/distribution zones
Visual Markers:
🔥: Bullish momentum building
🐻: Bear exhaustion building
🐳: Whale/institutional activity
Color-coded fills: Market state visualization
Confidence Levels:
≥80%: High reliability setups
60-79%: Moderate confidence
<60%: Low confidence, avoid or reduce size
⚠️ Risk Management Guidelines
Critical Rules:
Never trade against extreme sentiment (Extreme Fear → buy, Extreme Greed → sell)
Require multiple confirmation signals
Use confidence scores for position sizing
Avoid When:
Conflicting signals between components
Low volume participation
Confidence score < 50%
Major news events pending
Extreme volatility conditions
💡 Advanced Strategies
Sentiment Cycle Trading
Identify sentiment extremes
Wait for confirmation reversals
Enter with trend confirmation
Exit at opposite sentiment extreme
Use confidence scores and fear & greed scores to scale:
Fear & greed scores < 30 = buy area
Fear & greed score > 60 = sell area
Trend Momentum
Exit: At extreme greed with divergence
Enter: At extreme fear with divergence
📊 Market State Classification
Five Primary States:
EXTREME FEAR (BB% <0, RSI <34, Score <34)
FEAR (Score 34-47, bearish momentum)
NEUTRAL (Score 47-70, consolidation)
GREED (Score 70-90, bullish momentum)
EXTREME GREED (Score >90, BB% >100)
State Transitions:
Fear → Neutral: Early accumulation
Neutral → Greed: Trend development
Greed → Extreme Greed: Distribution
Extreme → Reversal: Trend change
🔍 Information Panel Guide
Real-Time Metrics:
FEAR & GREED: Current sentiment score
Market State: Classification and bias
Trend Bias: Bullish/Bearish/Neutral
Confidence: Setup reliability percentage
Momentum: Current directional strength
Volatility: Market condition assessment
Signal Quality: Trade recommendation
Reversal Imminent: Early warning alerts
🌟 Unique Advantages
Psychological Edge:
Quantifies market emotion through multiple indicators
Identifies bubbles before they pop
Provides statistical confidence for each setup
Combines technical extremes with sentiment analysis
Offers clear visual cues for decision making
Professional Features:
Multi-timeframe sentiment analysis
Real-time confidence scoring
Comprehensive alert system
Institutional activity detection
Clear risk/reward visualization
📚 Educational Value
This indicator teaches:
Market psychology cycles
Statistical extreme identification
Multi-indicator confirmation
Risk quantification methods
Professional trade management
Perfect for traders seeking to understand and profit from market sentiment cycles.
Disclaimer: For educational purposes. Trading involves risk. Past performance doesn't guarantee future results.
Market Structure Buy and Sells This indicator is based on these two indicators:
- Next Candle Predictor with Auto Hedging by HackWarrior
- Market Structure by odnac
How It Works
The Entry (Breakout): The script tracks the most recent Swing Highs and Lows. When price closes above a Swing High, it triggers a Buy Signal. When it closes below a Swing Low, it triggers a Sell Signal.
The Stop Loss (Signal #1): Unlike standard indicators that use a fixed pip amount, this uses "Signal #1"—a volatility-based calculation that finds the recent wave bottom (for buys) or wave top (for sells) to set a logical, market-based stop loss.
The Take Profit: Once the risk is defined by Signal #1, the indicator automatically projects a target based on your desired Risk:Reward Ratio (default is 1:1).
Key Features
Visual Trade Boxes: Instantly see your Profit (Green) and Loss (Red) zones on the chart the moment a signal triggers.
RSI "C" Exit (Optional): A toggleable safety switch that allows you to exit trades early if the RSI becomes overbought or oversold, protecting your gains before a reversal.
Live Backtest Table: A real-time dashboard in the corner of your chart that tracks Total Trades, Wins, Losses, and Win Rate so you can see how the strategy performs on any timeframe.
Integrated Alerts: Full support for alerts on both Buy and Sell signals.
NQ-Market Momentum CompassNQ-Market Momentum Compass: User Guide
Overview
NQ-Market Momentum Compass is a comparative momentum tool that helps you visualize the relative strength between Nasdaq futures (NQ) and a volume-weighted composite of other major US index futures (ES, RTY, and YM). This indicator plots two oscillator lines that move above and below zero, making it easy to identify momentum shifts and potential divergences between tech-heavy Nasdaq and the broader market.
What You're Looking At
The indicator displays two main components:
NQ Oscillator (Blue Line): Shows the percentage change in NQ futures over your selected lookback period.
Composite Oscillator (Orange Line): Shows the volume-weighted average percentage change of S&P 500 (ES), Russell 2000 (RTY), and Dow Jones (YM) futures over the same period.
Zero Line (Gray): The center reference line dividing positive and negative momentum.
How It Works
Core Calculation
The indicator calculates percentage change over a lookback period:
For each index, it computes: (current_price - price_n_bars_ago) / price_n_bars_ago * 100
The NQ line shows this calculation for Nasdaq futures
The composite line weights the other indices by their relative trading volumes
Volume Weighting
Instead of a simple average, the composite line incorporates trading volume to give more weight to indices with higher participation. This provides a more accurate representation of overall market momentum.
How to Interpret the Indicator
Basic Interpretation
Above Zero: Price is higher than it was at the lookback period ago (positive momentum)
Below Zero: Price is lower than it was at the lookback period ago (negative momentum)
Steepness: Indicates the strength of the momentum (steeper = stronger momentum)
Comparative Analysis
When Lines Move Together: NQ is moving in harmony with the broader market
When Lines Diverge:
NQ above composite: Tech/growth is outperforming the broader market
Composite above NQ: Broader market is outperforming tech/growth
Key Signals to Watch
Crossovers Between Lines: Potential shift in sector leadership
NQ crossing above composite: Tech starting to outperform
NQ crossing below composite: Tech starting to underperform
Zero-Line Crossovers: Change in overall momentum direction
Crossing above zero: Shift to positive momentum
Crossing below zero: Shift to negative momentum
Divergences: When one line makes a new high/low while the other doesn't, suggesting potential reversal
Practical Applications
Market Rotation Analysis: Identify shifts between tech and broader market leadership
Trend Confirmation: Validate trends by checking if both oscillators are in agreement
Early Warning System: Spot when tech starts to diverge from the broader market
Relative Strength Analysis: Determine which segment of the market has stronger momentum
Customization Options
The indicator offers two main customization groups:
Calculation Settings:
Momentum Window: The lookback period for calculating percentage change (default: 20)
Price Smoothing: EMA smoothing applied to prices before calculation (default: 5)
Display Settings:
NQ Line Color: Customize the color of the NQ oscillator line
Composite Line Color: Customize the color of the composite oscillator line
Tips for New Users
Start with the Defaults: The default settings (20-period momentum window, 5-period smoothing) work well across most timeframes
Focus on Relationships: The absolute values matter less than the relationship between the two lines
Use Multiple Timeframes: Check the oscillator on both short and longer timeframes for confirmation
Watch for Extremes: When either line reaches unusually high or low values, expect potential reversion
Combine with Other Indicators: For best results, use alongside trend and volatility indicators
This oscillator is particularly useful for traders who want to understand the intermarket dynamics between tech stocks and the broader market, helping to identify sector rotation and potential trading opportunities.
[GYTS] Volatility Toolkit Volatility Toolkit
🌸 Part of GoemonYae Trading System (GYTS) 🌸
🌸 --------- INTRODUCTION --------- 🌸
💮 What is Volatility Toolkit?
Volatility Toolkit is a comprehensive volatility analysis indicator featuring academically-grounded range-based estimators. Unlike simplistic measures like ATR, these estimators extract maximum information from OHLC data — resulting in estimates that are 5-14× more statistically efficient than traditional close-to-close methods.
The indicator provides two configurable estimator slots, weighted aggregation, adaptive threshold detection, and regime identification — all with flexible smoothing options via
GYTS FiltersToolkit integration.
💮 Why Use This Indicator?
Standard volatility measures (like simple standard deviation) are highly inefficient, requiring large amounts of data to produce stable estimates. Academic research has shown that range-based estimators extract far more information from the same price data:
• Statistical Efficiency — Yang-Zhang achieves up to 14× the efficiency of close-to-close variance, meaning you can achieve the same estimation accuracy with far fewer bars
• Drift Independence — Rogers-Satchell and Yang-Zhang correctly isolate variance even in strongly trending markets where simpler estimators become biased
• Gap Handling — Yang-Zhang properly accounts for overnight gaps, critical for equity markets
• Regime Detection — Built-in threshold modes identify when volatility enters elevated or suppressed states
↑ Overview showing Yang-Zhang volatility with dynamic threshold bands and regime background colouring
🌸 --------- HOW IT WORKS --------- 🌸
💮 Core Concept
The toolkit groups volatility estimators by their output scale to ensure valid comparisons and aggregations:
• Log-Return Scale (σ) — Close-to-Close, Parkinson, Garman-Klass, Rogers-Satchell, Yang-Zhang. These are comparable and can be aggregated. Annualisable via √(periods_per_year) scaling.
• Price Unit Scale ($) — ATR. Measures volatility in absolute price terms, directly usable for stop-loss placement.
• Percentage Scale (%) — Chaikin Volatility. Measures the rate of change of the trading range — whether volatility is expanding or contracting.
Only estimators with the same scale can be meaningfully compared or aggregated. The indicator enforces this and warns when mixing incompatible scales.
💮 Range-Based Estimator Overview
Range-based estimators utilise High, Low, Open, and Close prices to extract significantly more information about the underlying diffusion process than close-only methods:
• Parkinson (1980) — Uses High-Low range. ~5× more efficient than close-to-close. Assumes zero drift.
• Garman-Klass (1980) — Incorporates Open and Close. ~7.4× more efficient. Assumes zero drift, no gaps.
• Rogers-Satchell (1991) — Drift-independent. Superior in trending markets where Parkinson/GK become biased.
• Yang-Zhang (2000) — Composite estimator handling both drift and overnight gaps. Up to 14× more efficient.
💮 Theoretical Background
• Parkinson, M. (1980). The Extreme Value Method for Estimating the Variance of the Rate of Return. Journal of Business, 53 (1), 61–65. DOI
• Garman, M.B. & Klass, M.J. (1980). On the Estimation of Security Price Volatilities from Historical Data. Journal of Business, 53 (1), 67–78. DOI
• Rogers, L.C.G. & Satchell, S.E. (1991). Estimating Variance from High, Low and Closing Prices. Annals of Applied Probability, 1 (4), 504–512. DOI
• Yang, D. & Zhang, Q. (2000). Drift-Independent Volatility Estimation Based on High, Low, Open, and Close Prices. Journal of Business, 73 (3), 477–491. DOI
🌸 --------- KEY FEATURES --------- 🌸
💮 Feature Reference
Estimators (8 options across 3 scale groups):
• Close-to-Close — Classical benchmark using closing prices only. Least efficient but useful as baseline. Log-return scale.
• Parkinson — Range-based (High-Low), ~5× more efficient than close-to-close. Assumes zero drift. Log-return scale.
• Garman-Klass — OHLC-optimised, ~7.4× more efficient. Assumes zero drift, no gaps. Log-return scale.
• Rogers-Satchell — Drift-independent, handles trending markets where Parkinson/GK become biased. Log-return scale.
• Yang-Zhang — Gap-aware composite, most comprehensive (up to 14× efficient). Uses internal rolling variance (unsmoothed). Log-return scale.
• Std Dev — Standard deviation of log returns. Log-return scale.
• ATR — Average True Range in absolute price units. Useful for stop-loss placement. Price unit scale.
• Chaikin — Rate of change of range. Measures volatility expansion/contraction, not level. Percentage scale.
Smoothing Filters (10 options via FiltersToolkit):
• SMA / EMA — Classical moving averages
• Super Smoother (2-Pole / 3-Pole) — Ehlers IIR filter with excellent noise reduction
• Ultimate Smoother (2-Pole / 3-Pole) — Near-zero lag in passband
• BiQuad — Second-order IIR with configurable Q factor
• ADXvma — Adaptive smoothing, flat during ranging periods
• MAMA — MESA Adaptive Moving Average (cycle-adaptive)
• A2RMA — Adaptive Autonomous Recursive MA
Threshold Modes:
• Static — Fixed threshold values you define (e.g., 0.025 annualised)
• Dynamic — Adaptive bands: baseline ± (standard deviation × multiplier)
• Percentile — Threshold at Nth percentile of recent history (e.g., 80th percentile for high)
Visual Features:
• Level-based colour gradient — Line colour shifts with percentile rank (warm = high vol, cool = low vol)
• Fill to zero — Gradient fill intensity proportional to volatility level
• Threshold fills — Intensity-scaled fills when thresholds are breached
• Regime background — Chart background indicates HIGH/NORMAL/LOW volatility state
• Legend table — Displays estimator names, parameters, current values with percentile ranks (P##)
💮 Dual Estimator Slots
Compare two volatility estimators side-by-side. Each slot independently configures:
• Estimator type (8 options across three scale groups)
• Lookback period and smoothing filter
• Colour palette and visual style
This enables direct comparison between estimators (e.g., Yang-Zhang vs Rogers-Satchell) or between different parameterisations of the same estimator.
↑ Yang-Zhang (reddish) and Rogers-Satchell (greenish)
💮 Flexible Smoothing via FiltersToolkit
All estimators (except Yang-Zhang, which uses internal rolling variance) support configurable smoothing through 10 filter types. Using Infinite Impulse Response (IIR) filters instead of SMA avoids the "drop-off artefact" where volatility readings crash when old spikes exit the window.
Example: Same estimator (Parkinson) with different smoothing filters
Add two instances of Volatility Toolkit to your chart:
• Instance 1: Parkinson with SMA smoothing (lookback 14)
• Instance 2: Parkinson with Super Smoother 2-Pole (lookback 14)
Notice how SMA creates sharp drops when volatile bars exit the window, while Super Smoother maintains a gradual transition.
↑ Two Parkinson estimators — SMA (red mono-colour, showing drop-off artefacts) vs Super Smoother (turquoise mono colour, with smooth transitions)
↑ Garman-Klass with BiQuad (orangy) and 2-pole SuperSmoother filters (greenish)
💮 Weighted Aggregation
Combine multiple estimators into a single weighted average. The indicator automatically:
• Validates scale compatibility (only same-scale estimators can be aggregated)
• Normalises weights (so 2:1 means 67%:33%)
• Displays clear warnings when scales differ
Example: Robust volatility estimate
Combine Yang-Zhang (handles gaps) with Rogers-Satchell (handles drift) using equal weights:
• E1: Yang-Zhang (14)
• E2: Rogers-Satchell (14)
• Aggregation: Enabled, weights 1:1
The aggregated line (with "fill to zero" enabled) provides a more robust estimate by averaging two complementary methodologies.
↑ Yang-Zhang + Rogers-Satchell with aggregation line (thicker) showing combined estimate (notice how opening gaps are handled differently)
Example: Trend-weighted aggregation
In strongly trending markets, weight Rogers-Satchell more heavily since it's drift-independent:
• Estimator 1: Garman-Klass (faster, higher weight in ranging)
• Estimator 2: Rogers-Satchell (drift-independent, higher weight in trends)
• Aggregation: weights 1:2 (favours RS during trends)
💮 Adaptive Threshold Detection
Three threshold modes for identifying volatility regime shifts. Threshold breaches are visualised with intensity-scaled fills that grow stronger the further volatility exceeds the threshold.
Example: Dynamic thresholds for regime detection
Configure dynamic thresholds to automatically adapt to market conditions:
• High Threshold Mode: Dynamic (baseline + 2× std dev)
• Low Threshold Mode: Dynamic (baseline - 2× std dev)
• Show threshold fills: Enabled
This creates adaptive bands that widen during volatile periods and narrow during calm periods.
Example: Percentile-based thresholds
Use percentile mode for context-aware regime detection:
• High Threshold Mode: Percentile (96th)
• Low Threshold Mode: Percentile (4th)
• Percentile Lookback: 500
This identifies when volatility enters the top/bottom 4% of its recent distribution.
↑ Different threshold settings, where the dynamic and percentile methods show adaptive bands that widen during volatile periods, with fill intensity varying by breach magnitude. Regime detection (see next) is enabled too.
💮 Regime Background Colouring
Optional background colouring indicates the current volatility regime:
• High Volatility — Warm/alert background colour
• Normal — No background (neutral)
• Low Volatility — Cool/calm background colour
Select which source (Estimator 1, Estimator 2, or Aggregation) drives the regime display.
Example: Regime filtering for trade decisions
Use regime background to filter trading signals from other indicators:
• Regime Source: Aggregation
• Background Transparency: 90 (subtle)
When the background shows HIGH volatility (warm), consider tighter stops. When LOW (cool), watch for breakout setups.
↑ Regime background emphasis for breakout strategies. Note the interesting A2RMA smoothing for this case.
🌸 --------- USAGE GUIDE --------- 🌸
💮 Getting Started
1. Add the indicator to your chart
2. Estimator 1 defaults to Yang-Zhang (14) — the most comprehensive estimator for gapped markets
3. Keep "Annualise Volatility" enabled to express values in standard annualised form
4. Observe the legend table for current values and percentile ranks (P##). Hover over the table cells to see a little more info in the tooltip.
💮 Choosing an Estimator
• Trending equities with gaps — Yang-Zhang. Handles both drift and overnight gaps optimally.
• Crypto (24/7 trading) — Rogers-Satchell. Drift-independent without Yang-Zhang's multi-period lag.
• Ranging markets — Garman-Klass or Parkinson. Simpler, no drift adjustment needed.
• Price-based stops — ATR. Output in price units, directly usable for stop distances.
• Regime detection — Combine any estimator with threshold modes enabled.
💮 Interpreting Output
• Value (P##) — The volatility reading with percentile rank. "0.1523 (P75)" means 0.1523 annualised volatility at the 75th percentile of recent history.
• Colour gradient — Warmer colours = higher percentile (elevated volatility), cooler colours = lower percentile.
• Threshold fills — Intensity indicates how far beyond the threshold the current reading is.
• ⚠️ HIGH / 🔻 LOW — Table indicators when thresholds are breached.
🌸 --------- ALERTS --------- 🌸
💮 Direction Change Alerts
• Estimator 1/2 direction change — Triggers when volatility inflects (rising to falling or vice versa)
💮 Cross Alerts
• E1 crossed E2 — Triggers when the two estimator lines cross
💮 Threshold Alerts
• E1/E2/Aggr High Volatility — Triggers when volatility breaches the high threshold
• E1/E2/Aggr Low Volatility — Triggers when volatility falls below the low threshold
💮 Regime Change Alerts
• E1/E2/Aggr Regime Change — Triggers when the volatility regime transitions (High ↔ Normal ↔ Low)
🌸 --------- LIMITATIONS --------- 🌸
• Drift bias in Parkinson/GK — These estimators overestimate variance in trending conditions. Switch to Rogers-Satchell or Yang-Zhang for trending markets.
• Yang-Zhang minimum lookback — Requires at least 2 bars (enforced internally). Cannot produce instantaneous readings like other estimators.
• Flat candles — Single-tick bars produce near-zero variance readings. Use higher timeframes for illiquid assets.
• Discretisation bias — Estimates degrade when ticks-per-bar is very small. Consider higher timeframes for thinly traded instruments.
• Scale mixing — Different scale groups (log-return, price unit, percentage) cannot be meaningfully compared or aggregated. The indicator warns but does not prevent display.
🌸 --------- CREDITS --------- 🌸
💮 Academic Sources
• Parkinson, M. (1980). The Extreme Value Method for Estimating the Variance of the Rate of Return. Journal of Business, 53 (1), 61–65. DOI
• Garman, M.B. & Klass, M.J. (1980). On the Estimation of Security Price Volatilities from Historical Data. Journal of Business, 53 (1), 67–78. DOI
• Rogers, L.C.G. & Satchell, S.E. (1991). Estimating Variance from High, Low and Closing Prices. Annals of Applied Probability, 1 (4), 504–512. DOI
• Yang, D. & Zhang, Q. (2000). Drift-Independent Volatility Estimation Based on High, Low, Open, and Close Prices. Journal of Business, 73 (3), 477–491. DOI
• Wilder, J.W. (1978). New Concepts in Technical Trading Systems . Trend Research.
💮 Libraries Used
• VolatilityToolkit Library — Range-based estimators, smoothing, and aggregation functions
• FiltersToolkit Library — Advanced smoothing filters (Super Smoother, Ultimate Smoother, BiQuad, etc.)
• ColourUtilities Library — Colour palette management and gradient calculations
Crypto Swing Pro [All-in-One] v2 [R2D2]1. Introduction
Crypto Swing Pro (CSP) is a professional-grade technical analysis suite designed for high-volatility cryptocurrency markets. It consolidates the top five institutional-grade indicators—RSI, EMAs, OBV, MACD, and Bollinger Bands—into a single overlay.
New in v2.0: The script now includes a fully integrated Alert System. You no longer need to stare at the chart all day. You can set the script to email you or ping your phone exactly when a MACD Cross occurs or when Volatility Squeezes, ensuring you never miss a move.
2. Installation
1. Open TradingView: Go to your chart.
2. Open Pine Editor: Click the tab at the bottom of the screen.
3. Paste Code: Delete existing code and paste the v2.0 script above.
4. Save: Name it CSP v2.
5. Add to Chart: Click "Add to Chart".
3. How to Set Up Alerts
This is the most powerful feature of v2.0. You can set alerts for specific conditions without needing to write code.
1. Click the "Alert" Button: Located on the top menu bar of TradingView (looks like an alarm clock).
2. Condition: In the "Condition" dropdown menu, select CSP v2.
3. Select Trigger: A second dropdown will appear. Choose the specific signal you want to track:
MACD Buy Signal: Triggers when MACD crosses bullish.
RSI Oversold (<30): Triggers when price is mathematically cheap.
Volatility Squeeze: Triggers when a big move is imminent.
Price Cross Over 200 EMA: Triggers on major trend reversals.
4. Options: Select "Once Per Bar Close" (Recommended to avoid false signals during the candle fluctuation).
5. Notify: Check "Notify in App" or "Send Email".
6. Create: Click Create. You will now be notified even if you are asleep.
4. The Dashboard (HUD)
The on-screen table gives you an instant "Health Check" of the asset.
Indicator Status Meaning
RSI (14) Green (<30) Oversold. Look for long entries.
Red (>70) Overbought. Look to take profit.
MACD BULLISH Momentum is up.
TREND UPTREND Price is above the 200 EMA (White Line).
VOLATILITY SQUEEZE CRITICAL: Market is coiling. A breakout is coming soon.
VOLUME ACCUMULATION Whales are buying (OBV is rising).
5. Configuration & Visuals
Hover over the indicator name on the chart and click the Settings (Gear) icon.
Toggle Indicators: Uncheck any indicator (like Bollinger Bands or EMA 20) to hide them if you want a cleaner view. The Dashboard will still calculate them in the background.
Dashboard Position: Move the table to any corner or turn it off entirely if it blocks your price view.
Color Themes: Adjust the RSI background colors or EMA colors to fit your chart theme (Light/Dark mode).
6. Best Practices
The "Squeeze" Play: If you get a Volatility Squeeze alert, do not enter immediately. Wait for the price to break out of the Bollinger Bands. The squeeze is the "Get Ready" signal; the breakout is the "Go" signal.
The "Trend" Filter: If the 200 EMA (White Line) is above the price (Downtrend), ignore all "MACD Buy" alerts. Trade with the macro trend, not against it.
Quantum RCI FusionDescription:
Overview: The Quantum Momentum Engine Quantum RCI Fusion is a sophisticated momentum oscillator designed to solve the #1 problem of classic indicators: false signals in sideways markets. At the core of this script is the Rank Correlation Index (RCI), a powerful statistical tool based on Spearman’s correlation. Unlike RSI or Stochastic which only look at price levels, the RCI evaluates the "quality" of a trend by measuring the temporal correlation of price ranks.
This script is not just a line drawing: it is a complete trading ecosystem that fuses three RCI timeframes, volatility filters, and a real-time Risk Management simulation.
🛠 How It Works: The "Fusion" Logic
The strength of this indicator lies in the synergy between its components. It is not a simple mashup, but a filtered logical system:
Triple RCI Engine (Fast, Mid, Slow):
Fast (13) & Mid (18): These generate the Crossover signal for precise entry timing.
Slow (30) - The "Trend Shield": The true innovation. It acts as a directional shield; if the baseline is bullish, the script protects Long positions by ignoring premature exit signals, allowing you to ride the full trend.
HMA Smoothing: Raw price data passes through a Hull Moving Average before the RCI calculation. This drastically reduces market "noise" without sacrificing the responsiveness typical of the RCI.
Intelligent Filters (Anti-Whipsaw):
ADX Integration: Signals are blocked if the ADX is below the threshold (default 20), preventing trading in flat/ranging markets.
Momentum Impulse: Requires a minimum variation (Delta) in the RCI to confirm that the move has real drive and is not just random fluctuation.
🛡 Risk Management & Simulation
Since timing is useless without risk management, Quantum RCI Fusion includes a Dashboard and sophisticated exit logic:
Multiple Exits:
Take Profit / Stop Loss: Based on dynamic ATR multipliers.
Shield Break: Safety exit if the underlying trend (Slow RCI) changes direction.
Emergency: Immediate close if momentum sharply reverses across the zero line.
Live Dashboard: Monitors Win Rate, virtual PnL, and Trade Status (Long/Short/Scanning) in real-time directly on the chart, removing the need for external backtesters.
🚀 How to Use It
Setup: Add the script to a separate pane below your price chart.
Entry Signals:
LONG (Green Triangle): RCI Fast crosses Mid upwards + Oversold Zone (< -80) + ADX > 20 + Bullish Shield.
SHORT (Red Triangle): RCI Fast crosses Mid downwards + Overbought Zone (> 80) + ADX > 20 + Bearish Shield.
Customization:
Scalping: Reduce RCI lengths (e.g., 8/12/20) and disable the "Trend Shield" for quick entries and exits.
Swing Trading: Keep defaults and use the ATR Trailing logic to manage positions on H4 or Daily timeframes.
⚖️ Notes & Credits
Originality: This script enhances the standard RCI by implementing Array-based calculations (optimized for Pine v6), proprietary HMA smoothing, and unique "Trend Shield" logic.
Open Source: The code is released under the MPL 2.0 license. Credits to the Pine community for the foundational mathematical formulas of Spearman's correlation.
Disclaimer: The statistics shown in the dashboard are simulations based on live data and do not guarantee future profits. You are responsible for your own trading decisions.
🖼 Instructions for the Publication Chart (Preview)
To ensure your script gets approved and attracts users, follow these steps for the cover image:
Symbol: Use a volatile and liquid asset, e.g., BTCUSD or XAUUSD (Gold), on a 1H or 4H timeframe.
Clean Layout: Remove all other indicators from the chart (no Moving Averages on price, no Bollinger Bands). The focus must be solely on your script in the bottom pane.
Visualization:
Ensure the Dashboard (stats table) is clearly visible and does not obscure the most recent candle.
The chart should show at least one clear BUY and one clear SELL signal, ideally with the exit icons (the "X" or flags) visible to demonstrate the exit logic.
CVD Divergence Detector# CVD Divergence Detector
Clean, focused divergence detection using **Cumulative Volume Delta (CVD)** - one of the most reliable reversal signals in trading.
## 🎯 What It Does
Identifies divergences between **price action** and **volume delta**:
**🔻 Bearish Divergence**: Price makes Higher High, but CVD doesn't → Expect reversal DOWN
**🔺 Bullish Divergence**: Price makes Lower Low, but CVD doesn't → Expect reversal UP
## ✨ Key Features
### Two Detection Modes
**1. Confirmed Divergences** (High Accuracy)
- Solid red/green lines
- Labels: 🔻 Bear / 🔺 Bull
- Fully confirmed pivots (9 bars default)
- Win rate: ~70-80%
**2. Early Warning Mode** ⚡ (Fast Signals)
- Dashed yellow lines
- Labels: ⚠️ Early Bear / ⚠️ Early Bull
- Fires 6+ bars earlier (3 bars default)
- Win rate: ~55-65%
### Smart Filtering
- Minimum bars between signals (prevents spam)
- Minimum CVD strength requirement (filters weak signals)
- Adjustable pivot periods for any timeframe
### Four Alert Types
- 🔻 Confirmed Bearish Divergence
- 🔺 Confirmed Bullish Divergence
- ⚠️ Early Bearish Warning
- ⚠️ Early Bullish Warning
## ⚙️ Recommended Settings
**15m Day Trading** (Best for most traders):
```
Pivot Left/Right: 9
Early Warning Right: 3
Min Bars Between: 40
Min CVD Diff: 5%
Anchor TF: 1D
```
**5m Scalping**:
```
Pivot Left/Right: 7
Early Warning Right: 2
Min Bars Between: 60
Min CVD Diff: 5%
```
**1H Swing Trading**:
```
Pivot Left/Right: 12-14
Early Warning Right: 4-5
Min Bars Between: 30
Min CVD Diff: 8%
```
## 💡 Trading Strategies
### Strategy 1: Early Entry (Scalpers)
- ⚠️ Early warning → Enter immediately
- Stop: Just beyond pivot
- Target: 1:2 R/R minimum
- Trades/day: 3-8
### Strategy 2: Scale In (Day Traders)
- ⚠️ Early warning → 25% position
- 🔻 Confirmed → Add 75%
- Move stop to breakeven
- Trades/week: 5-15
### Strategy 3: Confirmation Only (Swing Traders)
- Wait for 🔻 confirmed signal only
- Wider stops (1-2 ATR)
- Hold for bigger moves
- Trades/month: 8-20
## 🎯 How to Use
1. **Install** indicator on your chart
2. **Choose** your timeframe (15m recommended to start)
3. **Enable** Early Warning for faster signals OR disable for confirmed only
4. **Set alerts** for your preferred divergence types
5. **Combine** with support/resistance for best results
## 🔧 Tuning Guide
**Too many signals?**
- Increase Pivot Right to 12-15
- Increase Min Bars Between to 60
- Increase Min CVD Diff to 8-10%
**Signals too slow?**
- Enable Early Warning
- Decrease Early Warning Right to 2
- Decrease Pivot Right to 6-7
**Want cleaner chart?**
- Turn off labels (lines only)
- Disable early warnings (confirmed only)
## ⚠️ Important Notes
**Requirements:**
- Volume data required (works on futures, stocks, crypto)
- May not work on some forex pairs (broker-dependent)
**Performance:**
- No indicator is 100% accurate
- Always use proper risk management
- Combine with price action and S/R levels
- Quality over quantity - don't trade every signal
**Best Results:**
- Divergence AT support/resistance = high probability
- Divergence + trend reversal pattern = confluence
- Multiple timeframe confirmation = strongest signals
## 📊 What Makes This Different?
**Other divergence indicators:**
- Use RSI, MACD, or other oscillators
- Don't show actual order flow
- Often give false signals
**This indicator:**
- Uses real CVD (Cumulative Volume Delta)
- Shows actual buying/selling pressure
- Filters for quality (not quantity)
- Two modes: fast OR accurate (your choice)
- No clutter - just clean divergence lines
## 🚀 Quick Start
1. Add to chart
2. Default settings work well for 15m
3. Watch for 1 week before trading
4. Start with small size
5. Track your results
## 📈 Typical Performance
| Mode | Win Rate | Avg R/R | Best For |
|------|----------|---------|----------|
| Early Warning | 55-65% | 1:1.5 | Scalping |
| Confirmed | 70-80% | 1:2 | Swing trading |
| Both (Scale In) | 65-75% | 1:3 | Day trading |
| With Confluence | 75-85% | 1:3+ | All styles |
## 💬 Tips from Pro Traders
- "Use early warnings for entries, confirmed for validation"
- "Best at major S/R levels - skip divergences in the middle of nowhere"
- "Lower timeframes = more signals but lower quality"
- "On 15m chart, early warnings give you 1.5 hour head start"
- "Combine with volume spikes for highest probability"
## 🔔 Alert Setup
1. Click Alert button (⏰)
2. Choose "CVD Divergence Detector"
3. Select alert type
4. Configure notifications
5. Done!
## ⚙️ Settings Explained
**Delta Source:**
- Anchor Timeframe: Higher TF for CVD calculation (1D for day trading)
- Custom Lower TF: Advanced users only
**Pivot Logic:**
- Pivot Left/Right: How many bars to confirm pivot
- Early Warning Right: How fast early signals fire
- Min Bars Between: Prevents signal spam
- Min CVD Diff %: Filters weak divergences
**Visual:**
- Show Lines/Labels: Toggle display
- Colors: Customize to your preference
- Label Size: Adjust for readability
## ❓ FAQ
**Q: No signals appearing?**
- Check volume data is available
- Lower Min CVD Diff to 2-3%
- Lower Pivot Right to 5-7
**Q: Too many signals?**
- Increase filters (see Tuning Guide above)
- Turn off early warnings
- Use confirmed only
**Q: Signals too late?**
- Enable Early Warning mode
- Decrease Early Warning Right to 2-3
**Q: Works on crypto/forex?**
- Crypto: Yes (major pairs)
- Forex: Sometimes (depends on broker volume data)
- Futures/Stocks: Yes (best performance)
## 📚 Learn More
For detailed strategies, examples, and advanced techniques, check the full user guide.
---
**Remember:** This is a tool, not a crystal ball. Combine with:
- Price action analysis
- Support/resistance levels
- Risk management
- Proper position sizing
**The best trade is the one you don't force.** 🎯
---
## 📝 Version Info
**v1.0** - Initial Release
- Confirmed divergence detection
- Early warning mode
- Smart filtering system
- Four alert types
- Clean visual design
---
**Questions? Suggestions?** Drop a comment below! 👇
**Found this helpful?** Like and follow for more professional indicators! ⭐
Refined Liquidity Flow IndicatorRefined Liquidity Flow Indicator - How It Works
The Refined Liquidity Flow Indicator is designed to help traders identify the flow of liquidity into and out of the market based on multiple technical factors. It combines price movement, market sentiment, volatility, and volume to give a comprehensive view of market conditions. The indicator gives buy and sell signals by calculating the flow of liquidity based on these factors.
Key Components of the Indicator:
Liquidity Flow Calculation:
The core of the indicator is the liquidity flow calculation, which is based on several factors:
Liquidity Flow=(V×ΔP)+(α×ATR)+(β×RSI)+(γ×ΔP)
Where:
𝑉 is the volume (the amount of trading activity).
ΔP is the price change (the difference between the current and previous closing price).
ATR (Average True Range) is used to measure market volatility.
RSI (Relative Strength Index) reflects market sentiment.
𝛼 𝛽 𝛾
are adjustable weights (parameters) that allow you to control how much influence each factor has on the liquidity flow calculation.
Key Indicators:
Volume (V): The amount of trades occurring in the market. A high volume indicates more activity, which is essential for confirming liquidity flow.
Price Change (ΔP): The difference between the current price and the previous price, which helps assess the strength and direction of the market move.
ATR (Average True Range): A measure of market volatility, indicating how much the price fluctuates over a specified period. A higher ATR suggests greater volatility, which often corresponds with a greater flow of liquidity.
RSI (Relative Strength Index): A momentum oscillator that measures whether a market is overbought or oversold. The RSI can help determine whether the market sentiment is bullish or bearish.
How to Use the Indicator:
Set Up: After adding the Refined Liquidity Flow Indicator to your chart, you can adjust the following settings directly from the indicator's settings panel:
α: Weight for volatility (ATR).
β: Weight for market sentiment (RSI).
γ: Weight for price change.
ATR Length: Customize the period for the ATR.
RSI Length: Customize the period for the RSI.
SMA Length: Customize the period for the Simple Moving Average.
Interpreting Signals:
Green Signal (Liquidity In): Indicates that liquidity is entering the market. This often signals a potential buy opportunity when the price is moving upwards with strong volume and market sentiment.
Red Signal (Liquidity Out): Indicates that liquidity is leaving the market. This typically signals a potential sell opportunity when the price is moving downwards with strong volume and market sentiment.
Fine-Tuning for Your Strategy:
By adjusting the weights and the lengths of the indicators, you can fine-tune the indicator to match your trading style. For example, if you want to give more weight to price movements, you can increase γ. If you want to focus more on market sentiment, adjust β.
VixTrixVixTrix - Because markets move in both directions.
VixTrix was born from a fundamental limitation in traditional volatility indicators: they only measure downside panic, completely missing the greed-driven extremes that form market tops.
How It Works:
Dual-Component Analysis:
vixBear = Panic selling intensity (distance from recent highs)
vixBull = FOMO buying intensity (distance from recent lows)
Oscillator = vixBear - vixBull = Net fear/greed imbalance
When the oscillator is positive, fear dominates (potential bottom forming). When negative, greed dominates (potential top forming).
Professional-Grade Filtering:
The magic happens with the symmetric RMS (Root Mean Square) bands. Unlike fixed percentage bands or standard deviation, RMS:
Creates mathematically symmetric positive/negative thresholds
Naturally adapts to changing volatility regimes
Provides statistical significance to extremes
VixTrix also adds selectable MA smoothing for the RMS calculation:
WMA (default): Balanced – middle-ground approach
VWMA: Volume-weighted – filters low-volume noise
EMA: Responsive – catches quick reversals
SMA: Stable – for swing trading
HMA: Fast and smooth – ideal for day trading
Signals require triple confirmation:
Statistical Extreme: Oscillator beyond RMS band
Price Action Confirmation: Correct candle color (bullish for bottoms, bearish for tops)
Momentum Continuation: Oscillator still moving toward extreme (exhaustion)
This multi-filter approach reduces premature entries and false signals while maintaining early positioning at potential reversal points.
Why This Matters for Your Trading:
In bull markets, traditional fear indicators sit near zero, giving no warning of impending tops.
VixTrix identifies when greed becomes excessive – when FOMO buying reaches statistical extremes that often precede corrections.
In range-bound markets, VixTrix excels at identifying overreactions in both directions, providing high-probability mean reversion opportunities.
During crashes, it captures the panic selling with the same precision as VixFix, but with better timing through its momentum confirmation.
VixTrix spots continuations through:
"No Signal" = Healthy Trend – Oscillator stays between RMS bands (no exhaustion)
Failed Extremes – Touches band but no triple confirmation = trend likely continues
Hidden Divergence – Price makes higher low while oscillator makes shallower low = uptrend continues
Controlled Emotions – Oscillator negative but not extreme in uptrends (greed present but not excessive)
Key Insight: When VixTrix doesn't give a signal during a pullback, institutions aren't panicking – they're just pausing before resuming the trend.
Green columns = Bullish exhaustion (potential bottoms)
Red columns = Bearish exhaustion (potential tops)
Golden RMS bands = Dynamic thresholds adapting to current volatility
Background highlights = Active signal conditions
The Result: A professional-grade oscillator that works in all market conditions – trending up, trending down, or ranging – by measuring the complete emotional spectrum driving price action.
On Balance Volume [BrightSideTrading]
# On Balance Volume - Complete User Guide
## Overview
This enhanced OBV indicator provides clean, actionable volume analysis with intelligent signal filtering. It combines On-Balance Volume (OBV) with a smoothed signal line to identify shifts in buying and selling pressure without chart clutter.
**Key Features:**
- Real-time OBV and signal line visualization
- Smart crossover detection with confirmation filtering
- Z-Score momentum analysis
- Customizable signal alerts with V-shaped markers
- Window-normalized option for detrended analysis
---
## What is On-Balance Volume (OBV)?
OBV is a volume-based momentum indicator that accumulates volume on up days and subtracts volume on down days. It answers a fundamental question: **Is volume flowing in (buying) or out (selling)?**
**Formula:**
- If Close > Previous Close: OBV = Previous OBV + Volume
- If Close < Previous Close: OBV = Previous OBV - Volume
- If Close = Previous Close: OBV = Previous OBV (unchanged)
**What it tells you:**
- **Rising OBV** = Accumulation (smart money buying)
- **Falling OBV** = Distribution (smart money selling)
- **OBV above zero line** = Net positive buying pressure
- **OBV below zero line** = Net negative selling pressure
---
## Interface & Settings
### **MAIN VISUALIZATION**
**OBV Line (Green/Red Ribbon)**
- Green when OBV is above the signal line (bullish trend)
- Red when OBV is below the signal line (bearish trend)
- Toggles between window-normalized (detrended) and raw values
**Signal Line (Orange)**
- Smoothed average of OBV
- Crossovers with OBV generate buy/sell signals
- Default: 21-period SMA
**V-Shaped Markers**
- Green upward V = Bullish crossover (buy signal)
- Red downward V = Bearish crossover (sell signal)
- Appears at the OBV value when signal is triggered
**Zero Line (Yellow)**
- Center equilibrium point for volume balance
- Acts as support/resistance for OBV
- Separates buying pressure (above) from selling pressure (below)
---
### **SOURCE GROUP**
**Source**
- **Default:** Close
- **Options:** Open, High, Low, or any custom value
- Controls which price value triggers OBV direction changes
- Most traders use Close for standard OBV calculation
---
### **SIGNAL SMOOTHING GROUP**
**Show Signal?**
- **Default:** ON
- Toggle visibility of the signal line
- Disable if you prefer to see raw OBV only
**Smoothing Type**
- **SMA (Simple Moving Average)** - Default, standard smoothing
- **EMA (Exponential Moving Average)** - Faster response, weights recent bars more heavily
- **Choose SMA** for consistent, traditional OBV signals
- **Choose EMA** for faster trend identification (more whipsaws possible)
**Smoothing Length**
- **Default:** 21 bars
- **Range:** 1-200 bars
- **Lower values** (5-14): Faster signals, more noise
- **Higher values** (30-50): Slower signals, fewer false alarms
- **Recommendation:** Use 21-25 for most timeframes
---
### **SIGNAL FILTERING GROUP**
This is your primary control for signal quality and frequency.
**Show Signal Markers?**
- **Default:** ON
- Toggle the V-shaped buy/sell markers on/off
- Disable if markers distract from your analysis
**Signal Filter Type**
- **None** - Shows every single crossover (noisy, best for skilled traders)
- **Confirmation Bars** - Waits N bars before confirming signal (recommended)
- **Strength-Based** - Only signals during strong momentum (filters weakest moves)
#### **CONFIRMATION BARS MODE** (Recommended)
Best for reducing false signals while staying responsive to real moves.
**Confirmation Bars**
- **Default:** 2 bars
- **Range:** 1-10 bars
- Waits for the signal to hold for N consecutive bars after crossover
- **Setting 1:** Every crossover (same as "None")
- **Setting 2:** Wait 1 bar confirmation (good balance)
- **Setting 3:** Wait 2 bars confirmation (filters 50% of noise)
- **Setting 4+:** Very selective, misses quick reversals
**How it works:**
1. OBV crosses signal line → Confirmation counter starts
2. If OBV stays on correct side for 2 bars → V-marker appears
3. If OBV crosses back → Counter resets, no signal
#### **STRENGTH-BASED MODE**
Only signals when momentum is statistically significant.
**Min Z-Score Strength**
- **Default:** 0.3
- **Range:** 0.0-3.0
- Requires OBV deviation from its mean to reach this threshold
- **Setting 0.1-0.3:** More signals, lower quality
- **Setting 0.5-0.8:** Moderate signals, good quality
- **Setting 1.0+:** Only the strongest momentum shifts
**How it works:**
- Calculates how far OBV is from its 50-bar average (Z-score)
- Only shows signals when this distance is meaningful
- Automatically avoids weak, choppy market conditions
---
### **VISUALS & COLORS GROUP**
**Highlight Crossovers?**
- **Default:** ON
- Master toggle for all signal markers
- Turn OFF to see only the OBV/signal lines
**Apply Ribbon Filling?**
- **Default:** ON
- Colors the space between OBV and signal line
- Green fill = OBV above signal (bullish)
- Red fill = OBV below signal (bearish)
- Provides clear visual trend confirmation
- Turn OFF for minimal chart clutter
---
### **STATS & ZONES GROUP**
**Use Window-Normalized OBV (visual only)?**
- **Default:** ON
- Removes long-term trend from OBV for clearer short-term signals
- Detrends the indicator to highlight recent momentum changes
- **ON:** Better for swing trading and identifying reversals
- **OFF:** Better for trend-following strategies
- Note: Z-Score always uses raw OBV for statistical accuracy
**OBV Normalize Window**
- **Default:** 200 bars
- Lookback period for detrending calculation
- Larger values = more aggressive detrending
- Adjust if you want OBV to oscillate more/less around zero
**Show Z-Score (OBV)?**
- **Default:** ON
- Displays statistical momentum indicator below main chart
- Ranges from -3 to +3 (most data within -2 to +2)
- High Z-Score = Strong buying momentum
- Low Z-Score = Strong selling momentum
**Z-Score Lookback**
- **Default:** 50 bars
- Period for calculating Z-Score mean and standard deviation
- Larger = smoother Z-Score, slower response
- Smaller = noisier Z-Score, faster response
**Show ROC (OBV Momentum)?**
- **Default:** OFF
- Rate of Change indicator for OBV velocity
- Useful for identifying momentum turning points
- Enable if you want to see speed of volume changes
**ROC Lookback**
- **Default:** 14 bars
- Period for ROC calculation
**Show Z-Score StdDev Zones?**
- **Default:** ON
- Shaded regions around zero line showing statistical boundaries
- Inner Zone (±1 Z) = Normal variation
- Outer Zone (±2 Z) = Extreme moves, potential reversals
- Helps identify overbought/oversold volume conditions
**Inner Zone (±Z)**
- **Default:** 1.0
- First boundary for standard deviation zones
- Most normal trading occurs within ±1
**Outer Zone (±Z)**
- **Default:** 2.0
- Second boundary for extreme conditions
- Crossing these zones indicates significant momentum shift
---
## Trading Strategy Examples
### **Strategy 1: Signal Line Crossovers (Beginner)**
**Setup:**
- Signal Filter Type: **Confirmation Bars**
- Confirmation Bars: **2-3**
- Show Signal Markers: **ON**
**Rules:**
1. **BUY signal** (green V): When OBV crosses above signal line and holds for 2-3 bars
- Confirms buying pressure is building
- Look for price to follow within 1-3 bars
2. **SELL signal** (red V): When OBV crosses below signal line and holds for 2-3 bars
- Confirms selling pressure is increasing
- Expect price decline
3. **Exit:** Take profits at next signal or use price support/resistance
**Best For:** Swing trading, intraday reversals, timeframes 5m-1h
---
### **Strategy 2: Zero Line Bounce (Intermediate)**
**Setup:**
- Signal Filter Type: **Strength-Based**
- Min Z-Score Strength: **0.5**
- Show Z-Score StdDev Zones: **ON**
**Rules:**
1. **Watch OBV approach zero line** during established trends
- OBV bouncing repeatedly off zero = trend is healthy
- OBV breaking through zero = trend reversal imminent
2. **Enter on bounce:** Buy when OBV bounces from zero line in uptrend
3. **Exit on break:** Close position when OBV breaks below zero line
4. **Confirm with Z-Score:** Only take trades when Z-Score shows momentum (|Z| > 0.5)
**Best For:** Trend traders, identifying trend strength, medium timeframes 15m-4h
---
### **Strategy 3: Momentum Extremes (Advanced)**
**Setup:**
- Signal Filter Type: **None**
- Show Z-Score StdDev Zones: **ON**
- Outer Zone: **2.0**
**Rules:**
1. **Identify extremes:** When Z-Score breaks outer zone (±2.0)
- Indicator is in extreme territory
- Likely overextended
2. **Fade extremes:** Take opposite position when Z-Score hits extreme
- High Z (>2.0) = OBV overbought, expect pullback
- Low Z (<-2.0) = OBV oversold, expect bounce
3. **Confirm:** Wait for crossover signal to enter
4. **Target:** Outer zone of opposite side or zero line
**Best For:** Range trading, mean reversion, experienced traders only
---
## Reading the Indicator in Different Markets
### **Strong Uptrend**
- OBV consistently above signal line (green)
- OBV well above zero line, rising higher lows
- Z-Score positive, trending upward
- **Action:** Buy dips to signal line, sell at resistance
### **Strong Downtrend**
- OBV consistently below signal line (red)
- OBV well below zero line, making lower highs
- Z-Score negative, trending downward
- **Action:** Sell rallies to signal line, cover at support
### **Consolidation/Choppy Market**
- OBV whipsaws around signal line frequently
- Crossovers occur every few bars
- Z-Score oscillating between -1 and +1
- **Action:** Increase confirmation bars to 3-4, or switch to strength-based filter
### **Accumulation (Bottom Formation)**
- OBV rising while price is flat or falling
- Volume flowing in despite downtrend (bullish divergence)
- Z-Score climbing while price lows hold
- **Action:** Expect breakout up; prepare buy near support
### **Distribution (Top Formation)**
- OBV falling while price is flat or rising
- Volume flowing out despite uptrend (bearish divergence)
- Z-Score falling while price continues higher
- **Action:** Expect breakdown down; prepare short near resistance
---
## Parameter Tuning Guide
### **Aggressive Settings (More Signals)**
- Smoothing Length: 14
- Signal Filter: None or Confirmation Bars: 1
- Min Z-Score: 0.1
- Best for: Day trading, high volatility stocks
- Risk: More false signals
### **Balanced Settings (Recommended)**
- Smoothing Length: 21
- Signal Filter: Confirmation Bars: 2
- Min Z-Score: 0.3
- Best for: Swing trading, most market conditions
- Risk/Reward: Moderate
### **Conservative Settings (Fewer Signals)**
- Smoothing Length: 30-40
- Signal Filter: Confirmation Bars: 3-4 or Strength-Based: 0.7+
- Min Z-Score: 0.8
- Best for: Position trading, high-conviction trades only
- Risk: May miss some moves
---
## Common Questions & Troubleshooting
**Q: Why are there more sell signals than buy signals?**
A: This reflects the actual market action. Markets often decline faster than they rise (fear > greed). Confirm signals with price action and support/resistance.
**Q: The indicator keeps whipsawing, should I hide it?**
A: Increase Confirmation Bars to 3-4 or switch to Strength-Based filter. Market conditions matter—choppy markets require stricter filters.
**Q: What's the difference between normalized and raw OBV?**
A: Normalized (detrended) shows shorter-term momentum by removing long-term trends. Raw OBV shows absolute accumulation/distribution over the full period. Use normalized for swing signals, raw for trend confirmation.
**Q: My signals come too late. How do I get faster entry?**
A: Reduce Smoothing Length (try 14 instead of 21), use EMA instead of SMA, or set Confirmation Bars to 1. Trade-off: More false signals.
**Q: Can I use this for day trading?**
A: Yes, on 1m-5m charts with aggressive settings. Use Confirmation Bars: 1 and focus on Z-Score > 0.5 entries only.
**Q: Should I trade every signal?**
A: No. Filter signals using: price near support/resistance, multiple indicators confirming, and Z-Score showing momentum. Best signals occur at key levels.
---
## Best Practices
1. **Always confirm with price action:** OBV signals work best when price is near support, resistance, or moving average. Don't trade signals in a vacuum.
2. **Use volume context:** Check if volume is increasing or decreasing on the signal. Strong signals have volume confirmation (increasing volume on OBV spikes).
3. **Adjust settings per timeframe:**
- 1m-5m: Smoothing 12, Confirmation 1, Z-Score 0.2
- 15m-1h: Smoothing 20, Confirmation 2, Z-Score 0.3
- 4h-1d: Smoothing 25, Confirmation 3, Z-Score 0.5
4. **Watch the zero line:** It's your friend. OBV behavior at the zero line reveals trend strength. Bounces = healthy trend. Breaks = reversal.
5. **Risk management:** No indicator is perfect. Use proper position sizing and stop losses. OBV should confirm your thesis, not be the only reason to trade.
6. **Combine with other indicators:**
- Price moving averages for trend confirmation
- RSI or Stochastic for overbought/oversold levels
- Support/resistance for entry/exit zones
- MACD for momentum divergences
---
## Disclaimer
This indicator is for educational and informational purposes only. It is not financial advice. Past performance does not guarantee future results. Always conduct your own research and consult with a financial advisor before making trading decisions. Trading carries risk, including potential loss of principal.
---
## Version History
**Version 1.0** - Initial release with enhanced signal filtering, Z-Score analysis, and customizable parameters.
BTC Fear & Greed Incremental StrategyIMPORTANT: READ SETUP GUIDE BELOW OR IT WON'T WORK
# BTC Fear & Greed Incremental Strategy — TradeMaster AI (Pure BTC Stack)
## Strategy Overview
This advanced Bitcoin accumulation strategy is designed for long-term hodlers who want to systematically take profits during greed cycles and accumulate during fear periods, while preserving their core BTC position. Unlike traditional strategies that start with cash, this approach begins with a specified BTC allocation, making it perfect for existing Bitcoin holders who want to optimize their stack management.
## Key Features
### 🎯 **Pure BTC Stack Mode**
- Start with any amount of BTC (configurable)
- Strategy manages your existing stack, not new purchases
- Perfect for hodlers who want to optimize without timing markets
### 📊 **Fear & Greed Integration**
- Uses market sentiment data to drive buy/sell decisions
- Configurable thresholds for greed (selling) and fear (buying) triggers
- Automatic validation to ensure proper 0-100 scale data source
### 🐂 **Bull Year Optimization**
- Smart quarterly selling during bull market years (2017, 2021, 2025)
- Q1: 1% sells, Q2: 2% sells, Q3/Q4: 5% sells (configurable)
- **NO SELLING** during non-bull years - pure accumulation mode
- Preserves BTC during early bull phases, maximizes profits at peaks
### 🐻 **Bear Market Intelligence**
- Multi-regime detection: Bull, Early Bear, Deep Bear, Early Bull
- Different buying strategies based on market conditions
- Enhanced buying during deep bear markets with configurable multipliers
- Visual regime backgrounds for easy market condition identification
### 🛡️ **Risk Management**
- Minimum BTC allocation floor (prevents selling entire stack)
- Configurable position sizing for all trades
- Multiple safety checks and validation
### 📈 **Advanced Visualization**
- Clean 0-100 scale with 2 decimal precision
- Three main indicators: BTC Allocation %, Fear & Greed Index, BTC Holdings
- Real-time portfolio tracking with cash position display
- Enhanced info table showing all key metrics
## How to Use
### **Step 1: Setup**
1. Add the strategy to your BTC/USD chart (daily timeframe recommended)
2. **CRITICAL**: In settings, change the "Fear & Greed Source" from "close" to a proper 0-100 Fear & Greed indicator
---------------
I recommend Crypto Fear & Greed Index by TIA_Technology indicator
When selecting source with this indicator, look for "Crypto Fear and Greed Index:Index"
---------------
3. Set your "Starting BTC Quantity" to match your actual holdings
4. Configure your preferred "Start Date" (when you want the strategy to begin)
### **Step 2: Configure Bull Year Logic**
- Enable "Bull Year Logic" (default: enabled)
- Adjust quarterly sell percentages:
- Q1 (Jan-Mar): 1% (conservative early bull)
- Q2 (Apr-Jun): 2% (moderate mid bull)
- Q3/Q4 (Jul-Dec): 5% (aggressive peak targeting)
- Add future bull years to the list as needed
### **Step 3: Fine-tune Thresholds**
- **Greed Threshold**: 80 (sell when F&G > 80)
- **Fear Threshold**: 20 (buy when F&G < 20 in bull markets)
- **Deep Bear Fear Threshold**: 25 (enhanced buying in bear markets)
- Adjust based on your risk tolerance
### **Step 4: Risk Management**
- Set "Minimum BTC Allocation %" (default 20%) - prevents selling entire stack
- Configure sell/buy percentages based on your position size
- Enable bear market filters for enhanced timing
### **Step 5: Monitor Performance**
- **Orange Line**: Your BTC allocation percentage (target: fluctuate between 20-100%)
- **Blue Line**: Actual BTC holdings (should preserve core position)
- **Pink Line**: Fear & Greed Index (drives all decisions)
- **Table**: Real-time portfolio metrics including cash position
## Reading the Indicators
### **BTC Allocation Percentage (Orange Line)**
- **100%**: All portfolio in BTC, no cash available for buying
- **80%**: 80% BTC, 20% cash ready for fear buying
- **20%**: Minimum allocation, maximum cash position
### **Trading Signals**
- **Green Buy Signals**: Appear during fear periods with available cash
- **Red Sell Signals**: Appear during greed periods in bull years only
- **No Signals**: Either allocation limits reached or non-bull year
## Strategy Logic
### **Bull Years (2017, 2021, 2025)**
- Q1: Conservative 1% sells (preserve stack for later)
- Q2: Moderate 2% sells (gradual profit taking)
- Q3/Q4: Aggressive 5% sells (peak targeting)
- Fear buying active (accumulate on dips)
### **Non-Bull Years**
- **Zero selling** - pure accumulation mode
- Enhanced fear buying during bear markets
- Focus on rebuilding stack for next bull cycle
## Important Notes
- **This is not financial advice** - backtest thoroughly before use
- Designed for **long-term holders** (4+ year cycles)
- **Requires proper Fear & Greed data source** - validate in settings
- Best used on **daily timeframe** for major trend following
- **Cash calculations**: Use allocation % and BTC holdings to calculate available cash: `Cash = (Total Portfolio × (1 - Allocation%/100))`
## Risk Disclaimer
This strategy involves active trading and position management. Past performance does not guarantee future results. Always do your own research and never invest more than you can afford to lose. The strategy is designed for educational purposes and long-term Bitcoin accumulation thesis.
---
*Developed by Sol_Crypto for the Bitcoin community. Happy stacking! 🚀*
Super-AO with Risk Management Strategy Template - 11-29-25Super-AO Strategy with Advanced Risk Management Template
Signal Lynx | Free Scripts supporting Automation for the Night-Shift Nation 🌙
1. Overview
Welcome to the Super-AO Strategy. This is more than just a buy/sell indicator; it is a complete, open-source Risk Management (RM) Template designed for the Pine Script community.
At its core, this script implements a robust swing-trading strategy combining the SuperTrend (for macro direction) and the Awesome Oscillator (for momentum). However, the real power lies under the hood: a custom-built Risk Management Engine that handles trade states, prevents repainting, and manages complex exit conditions like Staged Take Profits and Advanced Adaptive Trailing Stops (AATS).
We are releasing this code to help traders transition from simple indicators to professional-grade strategy structures.
2. Quick Action Guide (TL;DR)
Best Timeframe: 4 Hours (H4) and above. Designed for Swing Trading.
Best Assets: "Well-behaved" assets with clear liquidity (Major Forex pairs, BTC, ETH, Indices).
Strategy Type: Trend Following + Momentum Confirmation.
Key Feature: The Risk Management Engine is modular. You can strip out the "Super-AO" logic and insert your own strategy logic into the template easily.
Repainting: Strictly Non-Repainting. The engine calculates logic based on confirmed candle closes.
3. Detailed Report: How It Works
A. The Strategy Logic: Super-AO
The entry logic is based on the convergence of two classic indicators:
SuperTrend: Determines the overall trend bias (Green/Red).
Awesome Oscillator (AO): Measures market momentum.
The Signal:
LONG (+2): SuperTrend is Green AND AO is above the Zero Line AND AO is Rising.
SHORT (-2): SuperTrend is Red AND AO is below the Zero Line AND AO is Falling.
By requiring momentum to agree with the trend, this system filters out many false signals found in ranging markets.
B. The Risk Management (RM) Engine
This script features a proprietary State Machine designed by Signal Lynx. Unlike standard strategies that simply fire orders, this engine separates the Signal from the Execution.
Logic Injection: The engine listens for a specific integer signal: +2 (Buy) or -2 (Sell). This makes the code a Template. You can delete the Super-AO section, write your own logic, and simply pass a +2 or -2 to the RM_EngineInput variable. The engine handles the rest.
Trade States: The engine tracks the state of the trade (Entry, In-Trade, Exiting) to prevent signal spamming.
Aggressive vs. Conservative:
Conservative Mode: Waits for a full trend reversal before taking a new trade.
Aggressive Mode: Allows for re-entries if the trend is strong and valid conditions present themselves again (Pyramiding Type 1).
C. Advanced Exit Protocols
The strategy does not rely on a single exit point. It employs a "Layered Defense" approach:
Hard Stop Loss: A fixed percentage safety net.
Staged Take Profits (Scaling Out): The script allows you to set 3 distinct Take Profit levels. For example, you can close 10% of your position at TP1, 10% at TP2, and let the remaining 80% ride the trend.
Trailing Stop: A standard percentage-based trailer.
Advanced Adaptive Trailing Stop (AATS): This is a highly sophisticated volatility stop. It calculates market structure using Hirashima Sugita (HSRS) levels and Bollinger Bands to determine the "floor" and "ceiling" of price action.
If volatility is high: The stop loosens to prevent wicking out.
If volatility is low: The stop tightens to protect profit.
D. Repainting Protection
Many Pine Script strategies look great in backtesting but fail in live trading because they rely on "real-time" price data that disappears when the candle closes.
This Risk Management engine explicitly pulls data from the previous candle close (close , high , low ) for its calculations. This ensures that the backtest results you see match the reality of live execution.
4. For Developers & Modders
We encourage you to tear this code apart!
Look for the section titled // Super-AO Strategy Logic.
Replace that block with your own RSI, MACD, or Price Action logic.
Ensure your logic outputs a 2 for Buy and -2 for Sell.
Connect it to RM_EngineInput.
You now have a fully functioning Risk Management system for your custom strategy.
5. About Signal Lynx
Automation for the Night-Shift Nation 🌙
This code has been in action since 2022 and is a known performer in PineScript v5. We provide this open source to help the community build better, safer automated systems.
If you are looking to automate your strategies, please take a look at Signal Lynx in your search.
License: Mozilla Public License 2.0 (Open Source). If you make beneficial modifications, please release them back to the community!
Moving VWAP-KAMA CloudMoving VWAP-KAMA Cloud
Overview
The Moving VWAP-KAMA Cloud is a high-conviction trend filter designed to solve a major problem with standard indicators: Noise. By combining a smoothed Volume Weighted Average Price (MVWAP) with Kaufman’s Adaptive Moving Average (KAMA), this indicator creates a "Value Zone" that identifies the true structural trend while ignoring choppy price action.
Unlike brittle lines that break constantly, this cloud is "slow" by design—making it exceptionally powerful for spotting genuine trend reversals and filtering out fakeouts.
How It Works
This script uses a unique "Double Smoothing" architecture:
The Anchor (MVWAP): We take the standard VWAP and smooth it with a 30-period EMA. This represents the "Fair Value" baseline where volume has supported price over time.
The Filter (KAMA): We apply Kaufman's Adaptive Moving Average to the already smoothed MVWAP. KAMA is unique because it flattens out during low-volatility (choppy) periods and speeds up during high-momentum trends.
The Cloud:
Green/Teal Cloud: Bullish Structure (MVWAP > KAMA)
Purple Cloud: Bearish Structure (MVWAP < KAMA)
🔥 The "Reversal Slingshot" Strategy
Backtests reveal a powerful behavior during major trend changes, particularly after long bear markets:
The Resistance Phase: During a long-term downtrend, price will repeatedly rally into the Purple Cloud and get rejected. The flattened KAMA line acts as a "concrete ceiling," keeping the bearish trend intact.
The Breakout & Flip: When price finally breaks above the cloud with conviction, and the cloud flips Green, it signals a structural regime change.
The "Slingshot" Retest: Often, immediately after this flip, price will drop back into the top of the cloud. This is the "Slingshot" moment. The old resistance becomes new, hardened support.
The Rally: From this support bounce, stocks often launch into a sustained, multi-month bull run. This setup has been observed repeatedly at the bottom of major corrections.
How to Use This Indicator
1. Dynamic Support & Resistance
The KAMA Wall: When price retraces into the cloud, the KAMA line often flattens out, acting as a hard "floor" or "wall." A break of this wall usually signals a genuine trend change, not just a stop hunt.
2. Trend Confirmation (Regime Filter)
Bullish Regime: If price is holding above the cloud, only look for Long setups.
Bearish Regime: If price is holding below the cloud, only look for Short setups.
No-Trade Zone: If price is stuck inside the cloud, the market is traversing fair value. Stand aside until a clear winner emerges.
3. Multi-Timeframe Versatility
While designed for trend confirmation on higher timeframes (4H, Daily), this indicator adapts beautifully to lower timeframes (5m, 15m) for intraday scalping.
On Lower Timeframes: The cloud reacts much faster, acting as a dynamic "VWAP Band" that helps intraday traders stay on the right side of momentum during the session.
Settings
Moving VWAP Period (30): The lookback period for the base VWAP smoothing.
KAMA Settings (10, 10, 30): Controls the sensitivity of the adaptive filter.
Cloud Transparency: Adjust to keep your chart clean.
Alerts Included
Price Cross Over/Under MVWAP
Price Cross Over/Under KAMA
Cloud Flip (Bullish/Bearish Trend Change)
Tip for Traders
This is not a signal entry indicator. It is a Trend Conviction tool. Use it to filter your entries from faster indicators (like RSI or MACD). If your fast indicator signals "Buy" but the cloud is Purple, the probability is low. Wait for the Cloud Flip
Debt-Cycle vs Bitcoin-CycleDebt-Cycle vs Bitcoin-Cycle Indicator
The Debt-Cycle vs Bitcoin-Cycle indicator is a macro-economic analysis tool that compares traditional financial market cycles (debt/credit cycles) against Bitcoin market cycles. It uses Z-score normalization to track the relative positioning of global financial conditions versus cryptocurrency market sentiment, helping identify potential turning points and divergences between traditional finance and digital assets.
Key Features
Dual-Cycle Analysis: Simultaneously tracks traditional financial cycles and Bitcoin-specific cycles
Z-Score Normalization: Standardizes diverse data sources for meaningful comparison
Multi-Asset Coverage: Analyzes currencies, commodities, bonds, monetary aggregates, and on-chain metrics
Divergence Detection: Identifies when Bitcoin cycles move independently from traditional finance
21-Day Timeframe: Optimized for Long-term cycle analysis
What It Measures
Finance-Cycle (White Line)
Tracks traditional financial market health through:
Currencies: USD strength (DXY), global currency weights (USDWCU, EURWCU)
Commodities: Oil, gold, natural gas, agricultural products, and Bitcoin price
Corporate Bonds: Investment-grade spreads, high-yield spreads, credit conditions
Monetary Aggregates: M2 money supply, foreign exchange reserves (weighted by currency)
Treasury Bonds: Yield curve (2Y/10Y, 3M/10Y), term premiums, long-term rates
Bitcoin-Cycle (Orange Line)
Tracks Bitcoin market positioning through:
On-Chain Metrics:
MVRV Ratio (Market Value to Realized Value)
NUPL (Net Unrealized Profit/Loss)
Profit/Loss Address Distribution
Technical Indicators:
Bitcoin price Z-score
Moving average deviation
Relative Strength:
ETH/BTC ratio (altcoin strength indicator)
Visual Elements
White Line: Finance-Cycle indicator (positive = expansionary conditions, negative = contractionary)
Orange Line: Bitcoin-Cycle indicator (positive = bullish positioning, negative = bearish)
Zero Line: Neutral reference point
Interpretation
Cycle Alignment
Both positive: Risk-on environment, favorable for crypto
Both negative: Risk-off environment, caution warranted
Divergence: Potential opportunities or warning signals
Divergence Signals
Finance positive, Bitcoin negative: Bitcoin may be undervalued relative to macro conditions
Finance negative, Bitcoin positive: Bitcoin may be overextended or decoupling from traditional finance
Important Limitations
This indicator uses some technical and macro data but still has significant gaps:
⚠️ Limited monetary data - missing:
Funding rates (repo, overnight markets)
Comprehensive bond spread analysis
Collateral velocity and quality metrics
Central bank balance sheet details
⚠️ Basic economic coverage - missing:
GDP growth rates
Inflation expectations
Employment data
Manufacturing indices
Consumer confidence
⚠️ Simplified on-chain analysis - missing:
Exchange flow data
Whale wallet movements
Mining difficulty adjustments
Hash rate trends
Network fee dynamics
⚠️ No sentiment data - missing:
Fear & Greed Index
Options positioning
Futures open interest
Social media sentiment
The indicator provides a high-level cycle comparison but should be combined with comprehensive fundamental analysis, detailed on-chain research, and proper risk management.
Settings
Offset: Adjust the horizontal positioning of the indicators (default: 0)
Timeframe: Fixed at 21 days for optimal cycle detection
Use Cases
Macro-crypto correlation analysis: Understand when Bitcoin moves with or against traditional markets
Cycle timing: Identify potential tops and bottoms in both cycles
Risk assessment: Gauge overall market conditions across asset classes
Divergence trading: Spot opportunities when cycles diverge significantly
Portfolio allocation: Balance traditional and crypto assets based on cycle positioning
Technical Notes
Uses Z-score normalization with varying lookback periods (40-60 bars)
Applies HMA (Hull Moving Average) smoothing to reduce noise
Asymmetric multipliers for upside/downside movements in certain metrics
Requires access to FRED economic data, Glassnode, CoinMetrics, and IntoTheBlock feeds
21-day timeframe optimized for cycle analysis
Strategy Applications
This indicator is particularly useful for:
Cross-asset allocation - Decide between traditional finance and crypto exposure
Cycle positioning - Identify where we are in credit/debt cycles vs. Bitcoin cycles
Regime changes - Detect shifts in market leadership and correlation patterns
Risk management - Reduce exposure when both cycles turn negative
Disclaimer: This indicator is a cycle analysis tool and should not be used as the sole basis for investment decisions. It has limited coverage of monetary conditions, economic fundamentals, and on-chain metrics. The indicator provides directional insight but cannot predict exact timing or magnitude of market moves. Always conduct thorough research, consider multiple data sources, and maintain proper risk management in all investment decisions.
JokaBAR
This script combines my own liquidity/liq-levels engine with open-source code from BigBeluga’s Volumatic indicators:
• “Volumatic Variable Index Dynamic Average ”
• “Volumatic Support/Resistance Levels ”
The original code is published under the Mozilla Public License 2.0 and is reused here accordingly.
What this script does
Joka puts Volumatic trend logic, dynamic support/resistance and a custom liquidation-levels module into a single overlay. The idea is to give traders one clean view of trend direction, key reactive zones and potential liquidation areas where leveraged positions can be forced out of the market.
Volumatic logic is used to build a dynamic average and adaptive levels that react to volume and volatility. On top of that, the script plots configurable liquidation zones for different leverage tiers (e.g. 5x, 10x, 25x, 50x, 100x).
How to use it
Apply the script on pairs where leverage is actually used (perpetual futures / margin).
Use the Volumatic average as a trend filter (above = long bias, below = short bias).
Treat Volumatic support/resistance levels as key reaction zones for entries, partials and stops.
Read the liquidation levels as context: clusters show where forced liquidations can fuel strong moves and bounces.
Keep the chart clean — this tool is designed to be used without stacking extra indicators on top.
The script is published as open-source in line with TradingView House Rules so that other traders can study, tweak and build on it.
MACD crossover while RSI Oversold/Overbought# MACD Crossover with RSI Overbought/Oversold Indicator Explained
## Indicator Overview
This is a trading signal system that combines two classic technical indicators: **MACD (Moving Average Convergence Divergence)** and **RSI (Relative Strength Index)**. Its core logic is: MACD crossover signals are only triggered when RSI is in extreme zones (overbought/oversold), thereby filtering out many false signals and improving trading accuracy.
## Core Principles
### 1. **Dual Confirmation Mechanism**
This indicator doesn't use MACD or RSI alone, but requires both conditions to be met simultaneously:
- **Short Signal (Orange Triangle)**: MACD bearish crossover (fast line crosses below signal line) + RSI was overbought (≥71)
- **Long Signal (Green Triangle)**: MACD bullish crossover (fast line crosses above signal line) + RSI was oversold (≤29)
### 2. **RSI Memory Function**
The indicator checks the RSI values of the current and past 5 candlesticks. As long as any one of them reaches the overbought/oversold level, the condition is satisfied. This design avoids overly strict requirements, as RSI may have already left the extreme zone before the MACD crossover occurs.
```pine
wasOversold = rsi <= 29 or rsi <= 29 or ... or rsi <= 29
wasOverbought = rsi >= 71 or rsi >= 71 or ... or rsi >= 71
```
## Parameter Settings
### MACD Parameters
- **Fast MA**: 12 periods (adjustable 7-∞)
- **Slow MA**: 26 periods (adjustable 7-∞)
- **Signal Line**: 9 periods
### RSI Parameters
- **Oversold Threshold**: 29 (traditional 30)
- **Overbought Threshold**: 71 (traditional 70)
- **Calculation Period**: 14
## Visual Elements
### 1. **Signal Markers**
- 🔻 **Orange Downward Triangle**: Appears above the candlestick, labeled "overbought", indicating a shorting opportunity
- 🔺 **Green Upward Triangle**: Appears below the candlestick, labeled "oversold", indicating a long opportunity
### 2. **Price Level Lines**
- **Orange Dashed Line**: Extends rightward from the high of the short signal, serving as a potential resistance level
- **Green Dashed Line**: Extends rightward from the low of the long signal, serving as a potential support level
Each time a new signal appears, the old level line is deleted, keeping only the most recent reference line.
## Trading Logic Explained
### Short Signal Scenario
1. Price rises, RSI surges above 71 (market overheated)
2. Momentum subsequently weakens, MACD fast line crosses below signal line
3. Indicator draws an orange triangle at the high, alerting to reversal risk
4. Orange dashed line marks the high point of the short entry position
### Long Signal Scenario
1. Price falls, RSI drops below 29 (market oversold)
2. Selling pressure exhausted, MACD fast line crosses above signal line
3. Indicator draws a green triangle at the low, suggesting a rebound opportunity
4. Green dashed line marks the low point of the long entry position
## Advantages and Limitations
### ✅ Advantages
- **Filters Noise**: Reduces false signals through dual confirmation
- **Captures Reversals**: Catches trend reversals in extreme conditions
- **Visual Clarity**: Level lines help identify support/resistance
- **Built-in Alerts**: Can set up message push notifications
### ⚠️ Limitations
- **Lag**: Both indicators are lagging, signals may be delayed
- **Poor Performance in Ranging Markets**: Prone to whipsaws during consolidation
- **Needs Other Analysis**: Should not be the sole decision-making basis
- **Parameter Sensitivity**: Different markets and timeframes may require parameter adjustments
## Practical Trading Suggestions
1. **Confirm Trend Context**: Counter-trend signals carry high risk in strong trending markets
2. **Combine with Candlestick Patterns**: Confirm with patterns (such as engulfing, hammer candles)
3. **Set Stop Losses**: Use level lines as stop-loss references (long stop below green line, short stop above orange line)
4. **Watch Volume**: Signals accompanied by high volume are more reliable
5. **Multi-Timeframe Verification**: Signals appearing simultaneously on daily and 4-hour charts are more credible
## Summary
This indicator follows the "mean reversion from extremes" philosophy, seeking reversal opportunities when market sentiment becomes excessive. It's suitable for auxiliary judgment, particularly in swing trading and position trading strategies. But remember, no indicator is perfect—always combine risk management and multi-dimensional analysis when making trading decisions
Momentum Squeeze Candle [Darwinian]# Momentum Squeeze Candle
Professional squeeze detection indicator with Wyckoff accumulation/distribution analysis and multi-method momentum signals.
## Overview
Identifies volatility compression (squeeze) periods and provides intelligent momentum direction signals based on institutional accumulation/distribution patterns.
## Features
6 Squeeze Detection Methods:
• BB + KC (Classic) - John Carter's TTM Squeeze
• ATR Ratio - Volatility compression detection
• Choppiness Index - Ranging vs trending analysis
• BB Width - Bollinger Band contraction
• Volume Contraction - Drying volume detection
• Hybrid Multi-Method - Ensemble approach (3+ methods must agree)
Smart Momentum Direction:
• Priority 1: Wyckoff signals (ATR compression + volume analysis)
• Priority 2: RSI momentum (55/45 thresholds)
• Priority 3: Hybrid slope + momentum confirmation
Visual Indicators:
• Blue candle coloring during squeeze
• Green circles = Bullish momentum (accumulation detected)
• Red circles = Bearish momentum (distribution detected)
• Optional BB/KC band overlay
## How It Works
Wyckoff Accumulation (Bullish):
ATR compressing + volume drying + price holding above MA = Smart money accumulating
→ Green circle signals
Wyckoff Distribution (Bearish):
ATR expanding + volume surging + price failing below MA = Smart money distributing
→ Red circle signals
## Recommended Settings
Swing Trading (Daily/4H):
Method: BB + KC or Hybrid | Sensitivity: 1.2-1.5
Day Trading (15m-1H):
Method: ATR Ratio or BB Width | Sensitivity: 0.8-1.0
Scalping (1m-5m):
Method: Volume Contraction | Sensitivity: 0.7-0.9
High Probability:
Method: Hybrid Multi-Method | Min Score: 4/5 | Sensitivity: 1.5
## Key Advantages
✓ Multiple squeeze detection algorithms for different market conditions
✓ Wyckoff methodology for institutional activity detection
✓ Priority-based momentum system reduces false signals
✓ Clean, optimized code (70% faster than typical indicators)
✓ Fully customizable sensitivity and visual settings
## Usage
1. Choose squeeze detection method based on your trading style
2. Watch for blue candles (squeeze active)
3. Monitor momentum signals:
- Green circles below bars = Accumulation phase (bullish)
- Red circles below bars = Distribution phase (bearish)
4. Trade the breakout in the direction of momentum signals
## Notes
• All inputs hidden from status line by default for clean charts
• Works on all timeframes and asset classes
• Combine with your trading strategy for confirmation
• Best results when multiple priority signals align
Perfect for traders looking to identify consolidation periods and predict breakout direction using institutional accumulation/distribution patterns.
chart Pattern & Candle sticks Strategy# **XAUUSD Pattern & Candle Strategy - Complete Description**
## **Overview**
This Pine Script indicator is a comprehensive multi-factor trading system specifically designed for **XAUUSD (Gold) scalping and swing trading**. It combines classical technical analysis methods including candlestick patterns, chart patterns, moving averages, and volume analysis to generate high-probability buy/sell signals with automatic stop-loss and take-profit levels.
***
## **Core Components**
### **1. Moving Average System (Triple MA)**
**Purpose:** Identifies trend direction and momentum
- **Fast MA (20-period)** - Short-term price action
- **Medium MA (50-period)** - Intermediate trend
- **Slow MA (200-period)** - Long-term trend direction
**How it works:**
- **Bullish alignment**: MA20 > MA50 > MA200 (all pointing up)
- **Bearish alignment**: MA20 < MA50 < MA200 (all pointing down)
- **Crossover signals**: When Fast MA crosses Medium MA, it triggers buy/sell signals
- **Choice of SMA or EMA**: Adjustable based on preference
**Visual indicators:**
- Blue line = Fast MA
- Orange line = Medium MA
- Light red line = Slow MA
- Green background tint = Bullish trend
- Red background tint = Bearish trend
---
### **2. Candlestick Pattern Recognition (13 Patterns)**
**Purpose:** Identifies reversal and continuation signals based on price action
#### **Bullish Patterns (Signal potential upward moves):**
1. **Hammer** 🔨
- Long lower wick (2x body size)
- Small body at top
- Indicates rejection of lower prices (buyers stepping in)
- Best at support levels
2. **Inverted Hammer**
- Long upper wick
- Small body at bottom
- Shows buying pressure despite initial selling
3. **Bullish Engulfing** 📈
- Green candle completely engulfs previous red candle
- Strong reversal signal
- Body must be 1.2x larger than previous
4. **Morning Star** ⭐
- 3-candle pattern
- Red candle → Small indecision candle → Large green candle
- Powerful reversal at bottoms
5. **Piercing Line** ⚡
- Green candle closes above 50% of previous red candle
- Indicates strong buying interest
6. **Bullish Marubozu**
- Almost no wicks (95% body)
- Very strong bullish momentum
- Body must be 1.3x average size
#### **Bearish Patterns (Signal potential downward moves):**
7. **Shooting Star** 💫
- Long upper wick
- Small body at bottom
- Indicates rejection of higher prices (sellers in control)
- Best at resistance levels
8. **Hanging Man**
- Similar to hammer but appears at top
- Warning of potential reversal down
9. **Bearish Engulfing** 📉
- Red candle completely engulfs previous green candle
- Strong reversal signal
10. **Evening Star** 🌙
- 3-candle pattern (opposite of Morning Star)
- Green → Small → Large red candle
- Powerful top reversal
11. **Dark Cloud Cover** ☁️
- Red candle closes below 50% of previous green candle
- Indicates strong selling pressure
12. **Bearish Marubozu**
- Almost no wicks, pure red body
- Very strong bearish momentum
#### **Neutral Pattern:**
13. **Doji**
- Open and close nearly equal (tiny body)
- Indicates indecision
- Often precedes major moves
**Detection Logic:**
- Compares body size, wick ratios, and position relative to previous candles
- Uses 14-period average body size as reference
- All patterns validated against volume confirmation
***
### **3. Chart Pattern Recognition**
**Purpose:** Identifies major support/resistance and reversal patterns
#### **Patterns Detected:**
**Double Bottom** 📊 (Bullish)
- Two lows at approximately same level
- Indicates strong support
- Breakout above neckline triggers buy signal
- Most reliable at major support zones
**Double Top** 📊 (Bearish)
- Two highs at approximately same level
- Indicates strong resistance
- Breakdown below neckline triggers sell signal
- Most reliable at major resistance zones
**Support & Resistance Levels**
- Automatically plots recent pivot highs (resistance)
- Automatically plots recent pivot lows (support)
- Uses 3-bar strength for validation
- Levels shown as dashed horizontal lines
**Price Action Patterns**
- **Uptrend detection**: Higher highs + higher lows
- **Downtrend detection**: Lower highs + lower lows
- Confirms overall market structure
***
### **4. Volume Analysis**
**Purpose:** Confirms signal strength and filters false signals
**Metrics tracked:**
- **Volume MA (20-period)**: Baseline average volume
- **High volume threshold**: 1.5x the volume average
- **Volume increase**: Current volume > previous 2 bars
**How it's used:**
- All buy/sell signals **require volume confirmation**
- High volume = institutional participation
- Low volume signals are filtered out
- Prevents whipsaw trades during quiet periods
**Visual indicator:**
- Dashboard shows "High" volume in orange when active
- "Normal" shown in gray during low volume
***
### **5. Signal Generation Logic**
**BUY SIGNALS triggered when ANY of these occur:**
1. **Candlestick + Volume**
- Bullish candle pattern detected
- High volume confirmation
- Price above Fast MA
2. **MA Crossover + Volume**
- Fast MA crosses above Medium MA
- High volume confirmation
3. **Double Bottom Breakout**
- Price breaks above support level
- Volume confirmation present
4. **Trend Continuation**
- Uptrend structure intact (higher highs/lows)
- All MAs in bullish alignment
- Price above Fast MA
- Volume confirmation
**SELL SIGNALS triggered when ANY of these occur:**
1. **Candlestick + Volume**
- Bearish candle pattern detected
- High volume confirmation
- Price below Fast MA
2. **MA Crossunder + Volume**
- Fast MA crosses below Medium MA
- High volume confirmation
3. **Double Top Breakdown**
- Price breaks below resistance level
- Volume confirmation present
4. **Trend Continuation**
- Downtrend structure intact (lower highs/lows)
- All MAs in bearish alignment
- Price below Fast MA
- Volume confirmation
***
### **6. Risk Management System**
**Automatic Stop Loss Calculation:**
- Based on ATR (Average True Range) - 14 periods
- **Formula**: Entry price ± (ATR × SL Multiplier)
- **Default multiplier**: 1.5 (adjustable)
- Adapts to market volatility automatically
**Automatic Take Profit Calculation:**
- **Formula**: Entry price ± (ATR × TP Multiplier)
- **Default multiplier**: 2.5 (adjustable)
- **Default Risk:Reward ratio**: 1:1.67
- Higher TP multiplier = more aggressive targets
**Position Management:**
- Tracks ONE position at a time (no pyramiding)
- Automatically closes position when:
- Stop loss is hit
- Take profit is reached
- Opposite MA crossover occurs
- Prevents revenge trading and over-leveraging
**Visual Representation:**
- **Red horizontal line** = Stop Loss level
- **Green horizontal line** = Take Profit level
- Lines remain on chart while position is active
- Automatically disappear when position closes
***
### **7. Visual Elements**
**On-Chart Displays:**
1. **Moving Average Lines**
- Fast MA (Blue, thick)
- Medium MA (Orange, thick)
- Slow MA (Red, thin)
2. **Support/Resistance**
- Green crosses = Support levels
- Red crosses = Resistance levels
3. **Buy/Sell Arrows**
- Large GREEN "BUY" label below bars
- Large RED "SELL" label above bars
4. **Pattern Labels** (Small markers)
- "Hammer", "Bull Engulf", "Morning Star" (green, below bars)
- "Shooting Star", "Bear Engulf", "Evening Star" (red, above bars)
- "Double Bottom" / "Double Top" (blue/orange)
5. **Signal Detail Labels** (Medium size)
- Shows signal reason (e.g., "Bullish Candle", "MA Cross Up")
- Displays Entry, SL, and TP prices
- Color-coded (green for long, red for short)
6. **Background Coloring**
- Light green tint = Bullish MA alignment
- Light red tint = Bearish MA alignment
***
### **8. Information Dashboard**
**Top-right corner table showing:**
| Metric | Description |
|--------|-------------|
| **Position** | Current trade status (LONG/SHORT/None) |
| **MA Trend** | Overall trend direction (Bullish/Bearish/Neutral) |
| **Volume** | Current volume status (High/Normal) |
| **Pattern** | Last detected candlestick pattern |
| **ATR** | Current volatility measurement |
**Purpose:**
- Quick at-a-glance market assessment
- Real-time position tracking
- No need to check multiple indicators
***
### **9. Alert System**
**Complete alert coverage for:**
✅ **Entry Alerts**
- "Buy Signal" - Triggers when buy conditions met
- "Sell Signal" - Triggers when sell conditions met
✅ **Exit Alerts**
- "Long TP Hit" - Take profit reached on long position
- "Long SL Hit" - Stop loss triggered on long position
- "Short TP Hit" - Take profit reached on short position
- "Short SL Hit" - Stop loss triggered on short position
**How to use:**
1. Click "Create Alert" button
2. Select desired alert from dropdown
3. Set notification method (popup, email, SMS, webhook)
4. Never miss a trade opportunity
***
## **Recommended Settings**
### **For Scalping (Quick trades):**
- **Timeframe**: 5-minute
- **Fast MA**: 9
- **Medium MA**: 21
- **Slow MA**: 50
- **SL Multiplier**: 1.0
- **TP Multiplier**: 2.0
- **Volume Threshold**: 1.5x
### **For Swing Trading (Longer holds):**
- **Timeframe**: 1-hour or 4-hour
- **Fast MA**: 20
- **Medium MA**: 50
- **Slow MA**: 200
- **SL Multiplier**: 2.0
- **TP Multiplier**: 3.0
- **Volume Threshold**: 1.3x
### **Best Trading Hours for XAUUSD:**
- **Asian Session**: 00:00 - 08:00 GMT (lower volatility)
- **London Session**: 08:00 - 16:00 GMT (high volatility) ⭐
- **New York Session**: 13:00 - 21:00 GMT (highest volume) ⭐
- **London-NY Overlap**: 13:00 - 16:00 GMT (BEST for scalping) 🔥
***
## **How to Use This Strategy**
### **Step 1: Setup**
1. Open TradingView
2. Load XAUUSD chart
3. Select timeframe (5m, 15m, 1H, or 4H)
4. Add indicator from Pine Editor
5. Adjust settings based on your trading style
### **Step 2: Wait for Signals**
- Watch for GREEN "BUY" or RED "SELL" labels
- Check the signal reason in the detail label
- Verify dashboard shows favorable conditions
- Confirm volume is "High" (not required but preferred)
### **Step 3: Enter Trade**
- Enter at market or limit order near signal price
- Note the displayed Entry, SL, and TP prices
- Set your broker's SL/TP to match indicator levels
### **Step 4: Manage Position**
- Watch for SL/TP lines on chart
- Monitor dashboard for trend changes
- Exit manually if opposite MA crossover occurs
- Let SL/TP do their job (don't move them!)
### **Step 5: Review & Learn**
- Track win rate over 20+ trades
- Adjust multipliers if needed
- Note which patterns work best for you
- Refine entry timing
***
## **Key Advantages**
✅ **Multi-confirmation approach** - Reduces false signals significantly
✅ **Automatic risk management** - No manual calculation needed
✅ **Adapts to volatility** - ATR-based SL/TP adjusts to market conditions
✅ **Volume filtered** - Ensures institutional participation
✅ **Visual clarity** - Easy to understand at a glance
✅ **Complete alert system** - Never miss opportunities
✅ **Pattern education** - Learn patterns as they appear
✅ **Works on all timeframes** - Scalping to swing trading
***
## **Limitations & Considerations**
⚠️ **Not a holy grail** - No strategy wins 100% of trades
⚠️ **Requires practice** - Demo trade first to understand signals
⚠️ **Market conditions matter** - Works best in trending or volatile markets
⚠️ **News events** - Avoid trading during major economic releases
⚠️ **Slippage on 5m** - Fast markets may have execution delays
⚠️ **Pattern subjectivity** - Some patterns may trigger differently than expected
***
## **Risk Management Rules**
1. **Never risk more than 1-2% per trade**
2. **Maximum 3 positions per day** (avoid overtrading)
3. **Don't trade during major news** (NFP, FOMC, etc.)
4. **Use proper position sizing** (0.01 lot per $100 for micro accounts)
5. **Keep trade journal** (track patterns, win rate, mistakes)
6. **Stop trading after 3 consecutive losses** (psychological reset)
7. **Don't move stop loss further away** (accept losses)
8. **Take partial profits** at 1:1 R:R if desired
***
## **Expected Performance**
**Realistic expectations:**
- **Win rate**: 50-65% (depending on market conditions and timeframe)
- **Risk:Reward**: 1:1.67 default (adjustable to 1:2 or 1:3)
- **Signals per day**: 3-8 on 5m, 1-3 on 1H
- **Best months**: High volatility periods (news events, economic uncertainty)
- **Drawdowns**: Expect 3-5 losing trades in a row occasionally
***
## **Customization Options**
All inputs are adjustable in settings panel:
**Moving Averages:**
- Type (SMA or EMA)
- All three period lengths
**Volume:**
- Volume MA length
- High volume multiplier threshold
**Chart Patterns:**
- Pattern strength (bars for pivot detection)
- Show/hide pattern labels
**Risk Management:**
- ATR period
- Stop loss multiplier
- Take profit multiplier
**Display:**
- Toggle pattern labels
- Customize colors (in code)
***
## **Conclusion**
This is a **professional-grade, multi-factor trading system** that combines the best of classical technical analysis with modern risk management. It's designed to give clear, actionable signals while automatically handling the complex calculations of stop loss and take profit levels.
**Best suited for traders who:**
- Understand basic technical analysis
- Can follow rules consistently
- Prefer systematic approach over gut feeling
- Want visual confirmation before entering trades
- Value proper risk management
**Start with demo trading** for at least 20-30 trades to understand how the signals work in different market conditions. Once comfortable and profitable on demo, transition to live trading with minimal risk per trade.
Happy trading! 📈🎯
LibWghtLibrary "LibWght"
This is a library of mathematical and statistical functions
designed for quantitative analysis in Pine Script. Its core
principle is the integration of a custom weighting series
(e.g., volume) into a wide array of standard technical
analysis calculations.
Key Capabilities:
1. **Universal Weighting:** All exported functions accept a `weight`
parameter. This allows standard calculations (like moving
averages, RSI, and standard deviation) to be influenced by an
external data series, such as volume or tick count.
2. **Weighted Averages and Indicators:** Includes a comprehensive
collection of weighted functions:
- **Moving Averages:** `wSma`, `wEma`, `wWma`, `wRma` (Wilder's),
`wHma` (Hull), and `wLSma` (Least Squares / Linear Regression).
- **Oscillators & Ranges:** `wRsi`, `wAtr` (Average True Range),
`wTr` (True Range), and `wR` (High-Low Range).
3. **Volatility Decomposition:** Provides functions to decompose
total variance into distinct components for market analysis.
- **Two-Way Decomposition (`wTotVar`):** Separates variance into
**between-bar** (directional) and **within-bar** (noise)
components.
- **Three-Way Decomposition (`wLRTotVar`):** Decomposes variance
relative to a linear regression into **Trend** (explained by
the LR slope), **Residual** (mean-reversion around the
LR line), and **Within-Bar** (noise) components.
- **Local Volatility (`wLRLocTotStdDev`):** Measures the total
"noise" (within-bar + residual) around the trend line.
4. **Weighted Statistics and Regression:** Provides a robust
function for Weighted Linear Regression (`wLinReg`) and a
full suite of related statistical measures:
- **Between-Bar Stats:** `wBtwVar`, `wBtwStdDev`, `wBtwStdErr`.
- **Residual Stats:** `wResVar`, `wResStdDev`, `wResStdErr`.
5. **Fallback Mechanism:** All functions are designed for reliability.
If the total weight over the lookback period is zero (e.g., in
a no-volume period), the algorithms automatically fall back to
their unweighted, uniform-weight equivalents (e.g., `wSma`
becomes a standard `ta.sma`), preventing errors and ensuring
continuous calculation.
---
**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.
wSma(source, weight, length)
Weighted Simple Moving Average (linear kernel).
Parameters:
source (float) : series float Data to average.
weight (float) : series float Weight series.
length (int) : series int Look-back length ≥ 1.
Returns: series float Linear-kernel weighted mean; falls back to
the arithmetic mean if Σweight = 0.
wEma(source, weight, length)
Weighted EMA (exponential kernel).
Parameters:
source (float) : series float Data to average.
weight (float) : series float Weight series.
length (simple int) : simple int Look-back length ≥ 1.
Returns: series float Exponential-kernel weighted mean; falls
back to classic EMA if Σweight = 0.
wWma(source, weight, length)
Weighted WMA (linear kernel).
Parameters:
source (float) : series float Data to average.
weight (float) : series float Weight series.
length (int) : series int Look-back length ≥ 1.
Returns: series float Linear-kernel weighted mean; falls back to
classic WMA if Σweight = 0.
wRma(source, weight, length)
Weighted RMA (Wilder kernel, α = 1/len).
Parameters:
source (float) : series float Data to average.
weight (float) : series float Weight series.
length (simple int) : simple int Look-back length ≥ 1.
Returns: series float Wilder-kernel weighted mean; falls back to
classic RMA if Σweight = 0.
wHma(source, weight, length)
Weighted HMA (linear kernel).
Parameters:
source (float) : series float Data to average.
weight (float) : series float Weight series.
length (int) : series int Look-back length ≥ 1.
Returns: series float Linear-kernel weighted mean; falls back to
classic HMA if Σweight = 0.
wRsi(source, weight, length)
Weighted Relative Strength Index.
Parameters:
source (float) : series float Price series.
weight (float) : series float Weight series.
length (simple int) : simple int Look-back length ≥ 1.
Returns: series float Weighted RSI; uniform if Σw = 0.
wAtr(tr, weight, length)
Weighted ATR (Average True Range).
Implemented as WRMA on *true range*.
Parameters:
tr (float) : series float True Range series.
weight (float) : series float Weight series.
length (simple int) : simple int Look-back length ≥ 1.
Returns: series float Weighted ATR; uniform weights if Σw = 0.
wTr(tr, weight, length)
Weighted True Range over a window.
Parameters:
tr (float) : series float True Range series.
weight (float) : series float Weight series.
length (int) : series int Look-back length ≥ 1.
Returns: series float Weighted mean of TR; uniform if Σw = 0.
wR(r, weight, length)
Weighted High-Low Range over a window.
Parameters:
r (float) : series float High-Low per bar.
weight (float) : series float Weight series.
length (int) : series int Look-back length ≥ 1.
Returns: series float Weighted mean of range; uniform if Σw = 0.
wBtwVar(source, weight, length, biased)
Weighted Between Variance (biased/unbiased).
Parameters:
source (float) : series float Data series.
weight (float) : series float Weight series.
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population (biased); false → sample.
Returns:
variance series float The calculated between-bar variance (σ²btw), either biased or unbiased.
sumW series float The sum of weights over the lookback period (Σw).
sumW2 series float The sum of squared weights over the lookback period (Σw²).
wBtwStdDev(source, weight, length, biased)
Weighted Between Standard Deviation.
Parameters:
source (float) : series float Data series.
weight (float) : series float Weight series.
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population (biased); false → sample.
Returns: series float σbtw uniform if Σw = 0.
wBtwStdErr(source, weight, length, biased)
Weighted Between Standard Error.
Parameters:
source (float) : series float Data series.
weight (float) : series float Weight series.
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population (biased); false → sample.
Returns: series float √(σ²btw / N_eff) uniform if Σw = 0.
wTotVar(mu, sigma, weight, length, biased)
Weighted Total Variance (= between-group + within-group).
Useful when each bar represents an aggregate with its own
mean* and pre-estimated σ (e.g., second-level ranges inside a
1-minute bar). Assumes the *weight* series applies to both the
group means and their σ estimates.
Parameters:
mu (float) : series float Group means (e.g., HL2 of 1-second bars).
sigma (float) : series float Pre-estimated σ of each group (same basis).
weight (float) : series float Weight series (volume, ticks, …).
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population (biased); false → sample.
Returns:
varBtw series float The between-bar variance component (σ²btw).
varWtn series float The within-bar variance component (σ²wtn).
sumW series float The sum of weights over the lookback period (Σw).
sumW2 series float The sum of squared weights over the lookback period (Σw²).
wTotStdDev(mu, sigma, weight, length, biased)
Weighted Total Standard Deviation.
Parameters:
mu (float) : series float Group means (e.g., HL2 of 1-second bars).
sigma (float) : series float Pre-estimated σ of each group (same basis).
weight (float) : series float Weight series (volume, ticks, …).
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population (biased); false → sample.
Returns: series float σtot.
wTotStdErr(mu, sigma, weight, length, biased)
Weighted Total Standard Error.
SE = √( total variance / N_eff ) with the same effective sample
size logic as `wster()`.
Parameters:
mu (float) : series float Group means (e.g., HL2 of 1-second bars).
sigma (float) : series float Pre-estimated σ of each group (same basis).
weight (float) : series float Weight series (volume, ticks, …).
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population (biased); false → sample.
Returns: series float √(σ²tot / N_eff).
wLinReg(source, weight, length)
Weighted Linear Regression.
Parameters:
source (float) : series float Data series.
weight (float) : series float Weight series.
length (int) : series int Look-back length ≥ 2.
Returns:
mid series float The estimated value of the regression line at the most recent bar.
slope series float The slope of the regression line.
intercept series float The intercept of the regression line.
wResVar(source, weight, midLine, slope, length, biased)
Weighted Residual Variance.
linear regression – optionally biased (population) or
unbiased (sample).
Parameters:
source (float) : series float Data series.
weight (float) : series float Weighting series (volume, etc.).
midLine (float) : series float Regression value at the last bar.
slope (float) : series float Slope per bar.
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population variance (σ²_P), denominator ≈ N_eff.
false → sample variance (σ²_S), denominator ≈ N_eff - 2.
(Adjusts for 2 degrees of freedom lost to the regression).
Returns:
variance series float The calculated residual variance (σ²res), either biased or unbiased.
sumW series float The sum of weights over the lookback period (Σw).
sumW2 series float The sum of squared weights over the lookback period (Σw²).
wResStdDev(source, weight, midLine, slope, length, biased)
Weighted Residual Standard Deviation.
Parameters:
source (float) : series float Data series.
weight (float) : series float Weight series.
midLine (float) : series float Regression value at the last bar.
slope (float) : series float Slope per bar.
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population (biased); false → sample.
Returns: series float σres; uniform if Σw = 0.
wResStdErr(source, weight, midLine, slope, length, biased)
Weighted Residual Standard Error.
Parameters:
source (float) : series float Data series.
weight (float) : series float Weight series.
midLine (float) : series float Regression value at the last bar.
slope (float) : series float Slope per bar.
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population (biased); false → sample.
Returns: series float √(σ²res / N_eff); uniform if Σw = 0.
wLRTotVar(mu, sigma, weight, midLine, slope, length, biased)
Weighted Linear-Regression Total Variance **around the
window’s weighted mean μ**.
σ²_tot = E_w ⟶ *within-group variance*
+ Var_w ⟶ *residual variance*
+ Var_w ⟶ *trend variance*
where each bar i in the look-back window contributes
m_i = *mean* (e.g. 1-sec HL2)
σ_i = *sigma* (pre-estimated intrabar σ)
w_i = *weight* (volume, ticks, …)
ŷ_i = b₀ + b₁·x (value of the weighted LR line)
r_i = m_i − ŷ_i (orthogonal residual)
Parameters:
mu (float) : series float Per-bar mean m_i.
sigma (float) : series float Pre-estimated σ_i of each bar.
weight (float) : series float Weight series w_i (≥ 0).
midLine (float) : series float Regression value at the latest bar (ŷₙ₋₁).
slope (float) : series float Slope b₁ of the regression line.
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population; false → sample.
Returns:
varRes series float The residual variance component (σ²res).
varWtn series float The within-bar variance component (σ²wtn).
varTrd series float The trend variance component (σ²trd), explained by the linear regression.
sumW series float The sum of weights over the lookback period (Σw).
sumW2 series float The sum of squared weights over the lookback period (Σw²).
wLRTotStdDev(mu, sigma, weight, midLine, slope, length, biased)
Weighted Linear-Regression Total Standard Deviation.
Parameters:
mu (float) : series float Per-bar mean m_i.
sigma (float) : series float Pre-estimated σ_i of each bar.
weight (float) : series float Weight series w_i (≥ 0).
midLine (float) : series float Regression value at the latest bar (ŷₙ₋₁).
slope (float) : series float Slope b₁ of the regression line.
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population; false → sample.
Returns: series float √(σ²tot).
wLRTotStdErr(mu, sigma, weight, midLine, slope, length, biased)
Weighted Linear-Regression Total Standard Error.
SE = √( σ²_tot / N_eff ) with N_eff = Σw² / Σw² (like in wster()).
Parameters:
mu (float) : series float Per-bar mean m_i.
sigma (float) : series float Pre-estimated σ_i of each bar.
weight (float) : series float Weight series w_i (≥ 0).
midLine (float) : series float Regression value at the latest bar (ŷₙ₋₁).
slope (float) : series float Slope b₁ of the regression line.
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population; false → sample.
Returns: series float √((σ²res, σ²wtn, σ²trd) / N_eff).
wLRLocTotStdDev(mu, sigma, weight, midLine, slope, length, biased)
Weighted Linear-Regression Local Total Standard Deviation.
Measures the total "noise" (within-bar + residual) around the trend.
Parameters:
mu (float) : series float Per-bar mean m_i.
sigma (float) : series float Pre-estimated σ_i of each bar.
weight (float) : series float Weight series w_i (≥ 0).
midLine (float) : series float Regression value at the latest bar (ŷₙ₋₁).
slope (float) : series float Slope b₁ of the regression line.
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population; false → sample.
Returns: series float √(σ²wtn + σ²res).
wLRLocTotStdErr(mu, sigma, weight, midLine, slope, length, biased)
Weighted Linear-Regression Local Total Standard Error.
Parameters:
mu (float) : series float Per-bar mean m_i.
sigma (float) : series float Pre-estimated σ_i of each bar.
weight (float) : series float Weight series w_i (≥ 0).
midLine (float) : series float Regression value at the latest bar (ŷₙ₋₁).
slope (float) : series float Slope b₁ of the regression line.
length (int) : series int Look-back length ≥ 2.
biased (bool) : series bool true → population; false → sample.
Returns: series float √((σ²wtn + σ²res) / N_eff).
wLSma(source, weight, length)
Weighted Least Square Moving Average.
Parameters:
source (float) : series float Data series.
weight (float) : series float Weight series.
length (int) : series int Look-back length ≥ 2.
Returns: series float Least square weighted mean. Falls back
to unweighted regression if Σw = 0.
Ehlers Phasor Analysis (PHASOR)# PHASOR: Phasor Analysis (Ehlers)
## Overview and Purpose
The Phasor Analysis indicator, developed by John Ehlers, represents an advanced cycle analysis tool that identifies the phase of the dominant cycle component in a time series through complex signal processing techniques. This sophisticated indicator uses correlation-based methods to determine the real and imaginary components of the signal, converting them to a continuous phase angle that reveals market cycle progression. Unlike traditional oscillators, the Phasor provides unwrapped phase measurements that accumulate continuously, offering unique insights into market timing and cycle behavior.
## Core Concepts
* **Complex Signal Analysis** — Uses real and imaginary components to determine cycle phase
* **Correlation-Based Detection** — Employs Ehlers' correlation method for robust phase estimation
* **Unwrapped Phase Tracking** — Provides continuous phase accumulation without discontinuities
* **Anti-Regression Logic** — Prevents phase angle from moving backward under specific conditions
Market Applications:
* **Cycle Timing** — Precise identification of cycle peaks and troughs
* **Market Regime Analysis** — Distinguishes between trending and cycling market conditions
* **Turning Point Detection** — Advanced warning system for potential market reversals
## Common Settings and Parameters
| Parameter | Default | Function | When to Adjust |
|-----------|---------|----------|----------------|
| Period | 28 | Fixed cycle period for correlation analysis | Match to expected dominant cycle length |
| Source | Close | Price series for phase calculation | Use typical price or other smoothed series |
| Show Derived Period | false | Display calculated period from phase rate | Enable for adaptive period analysis |
| Show Trend State | false | Display trend/cycle state variable | Enable for regime identification |
## Calculation and Mathematical Foundation
**Technical Formula:**
**Stage 1: Correlation Analysis**
For period $n$ and source $x_t$:
Real component correlation with cosine wave:
$$R = \frac{n \sum x_t \cos\left(\frac{2\pi t}{n}\right) - \sum x_t \sum \cos\left(\frac{2\pi t}{n}\right)}{\sqrt{D_{cos}}}$$
Imaginary component correlation with negative sine wave:
$$I = \frac{n \sum x_t \left(-\sin\left(\frac{2\pi t}{n}\right)\right) - \sum x_t \sum \left(-\sin\left(\frac{2\pi t}{n}\right)\right)}{\sqrt{D_{sin}}}$$
where $D_{cos}$ and $D_{sin}$ are normalization denominators.
**Stage 2: Phase Angle Conversion**
$$\theta_{raw} = \begin{cases}
90° - \arctan\left(\frac{I}{R}\right) \cdot \frac{180°}{\pi} & \text{if } R \neq 0 \\
0° & \text{if } R = 0, I > 0 \\
180° & \text{if } R = 0, I \leq 0
\end{cases}$$
**Stage 3: Phase Unwrapping**
$$\theta_{unwrapped}(t) = \theta_{unwrapped}(t-1) + \Delta\theta$$
where $\Delta\theta$ is the normalized phase difference.
**Stage 4: Ehlers' Anti-Regression Condition**
$$\theta_{final}(t) = \begin{cases}
\theta_{final}(t-1) & \text{if regression conditions met} \\
\theta_{unwrapped}(t) & \text{otherwise}
\end{cases}$$
**Derived Calculations:**
Derived Period: $P_{derived} = \frac{360°}{\Delta\theta_{final}}$ (clamped to )
Trend State:
$$S_{trend} = \begin{cases}
1 & \text{if } \Delta\theta \leq 6° \text{ and } |\theta| \geq 90° \\
-1 & \text{if } \Delta\theta \leq 6° \text{ and } |\theta| < 90° \\
0 & \text{if } \Delta\theta > 6°
\end{cases}$$
> 🔍 **Technical Note:** The correlation-based approach provides robust phase estimation even in noisy market conditions, while the unwrapping mechanism ensures continuous phase tracking across cycle boundaries.
## Interpretation Details
* **Phasor Angle (Primary Output):**
- **+90°**: Potential cycle peak region
- **0°**: Mid-cycle ascending phase
- **-90°**: Potential cycle trough region
- **±180°**: Mid-cycle descending phase
* **Phase Progression:**
- Continuous upward movement → Normal cycle progression
- Phase stalling → Potential cycle extension or trend development
- Rapid phase changes → Cycle compression or volatility spike
* **Derived Period Analysis:**
- Period < 10 → High-frequency cycle dominance
- Period 15-40 → Typical swing trading cycles
- Period > 50 → Trending market conditions
* **Trend State Variable:**
- **+1**: Long trend conditions (slow phase change in extreme zones)
- **-1**: Short trend or consolidation (slow phase change in neutral zones)
- **0**: Active cycling (normal phase change rate)
## Applications
* **Cycle-Based Trading:**
- Enter long positions near -90° crossings (cycle troughs)
- Enter short positions near +90° crossings (cycle peaks)
- Exit positions during mid-cycle phases (0°, ±180°)
* **Market Timing:**
- Use phase acceleration for early trend detection
- Monitor derived period for cycle length changes
- Combine with trend state for regime-appropriate strategies
* **Risk Management:**
- Adjust position sizes based on cycle clarity (derived period stability)
- Implement different risk parameters for trending vs. cycling regimes
- Use phase velocity for stop-loss placement timing
## Limitations and Considerations
* **Parameter Sensitivity:**
- Fixed period assumption may not match actual market cycles
- Requires cycle period optimization for different markets and timeframes
- Performance degrades when multiple cycles interfere
* **Computational Complexity:**
- Correlation calculations over full period windows
- Multiple mathematical transformations increase processing requirements
- Real-time implementation requires efficient algorithms
* **Market Conditions:**
- Most effective in markets with clear cyclical behavior
- May provide false signals during strong trending periods
- Requires sufficient historical data for correlation analysis
Complementary Indicators:
* MESA Adaptive Moving Average (cycle-based smoothing)
* Dominant Cycle Period indicators
* Detrended Price Oscillator (cycle identification)
## References
1. Ehlers, J.F. "Cycle Analytics for Traders." Wiley, 2013.
2. Ehlers, J.F. "Cybernetic Analysis for Stocks and Futures." Wiley, 2004.
US Construction Spending & Manufacturing Employment YoY % ChangeUsage Notes: Timeframe: Use a monthly chart, as TTLCONS and MANEMP are monthly data. Other timeframes result in interpolation.
Data Availability: As of October 2025, TTLCONS is available until July 2025 and MANEMP until August 2025 (automatically via TradingView).
The Unsung Heroes: Why C&M Are the True Indicators
Imagine the economy is a highly sensitive vehicle. Quarterly reported GDP is like a quarterly glance at the odometer—it's slow, often delayed, and clearly refers to the past. Anyone who wants to predict future developments needs something much faster.
This is where construction and manufacturing come into play. These two sectors are the machine builders of the economy and provide us with real-time feedback. They form the backbone of economic forecasting for several important reasons:
1. Monetary policy indicators: Both sectors are highly sensitive to monetary policy developments, such as interest rate changes. If developers are unable to finance large residential or commercial projects and manufacturers postpone capital-intensive factory expansions, for example, declines in construction demand would quickly affect other sectors.
2. The backbone of the secondary sector: These industries constitute the secondary sector of the economy, meaning they are concerned with the actual transformation and production of goods, not just the extraction of raw materials or the provision of intangible services. One could argue that while they only account for about 15% of GDP in the US, their impact is massive and cyclical.
3. The timeliness advantage: Forget quarterly lags. Both construction output and manufacturing employment data are released monthly. This timely, frequent data allows analysts to assess economic momentum much more quickly than if they had to wait for delayed GDP reports.
In the US, some analysts have even titled their articles with the bold claim: "Housing construction is the business cycle." Fluctuations in housing construction are frequent and large, and a decline in activity is almost always accompanied by a subsequent decline in GDP.
Multi-Timeframe Trend Indicator with Signals═══════════════════════════════════════════════════════════════
Multi-Timeframe Trend Indicator with Signals
by Zakaria Safri
═══════════════════════════════════════════════════════════════
⚠️ IMPORTANT DISCLAIMERS:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
• This indicator may REPAINT on unconfirmed bars
• Signals appear in real-time but may change or disappear
• FOR EDUCATIONAL PURPOSES ONLY - NOT FINANCIAL ADVICE
• Past performance does not guarantee future results
• Always do your own research and use proper risk management
• The Risk Management feature is VISUAL ONLY - does not execute trades
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📊 OVERVIEW:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
This indicator combines multiple technical analysis tools to help identify
potential trend directions and entry/exit points across different timeframes.
It uses SuperTrend, EMAs, ADX, RSI, and Keltner Channels to generate signals.
🎯 KEY FEATURES:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📍 SIGNAL TYPES:
• All Signals: Shows all SuperTrend crossovers
• Filtered Signals: Additional EMA filter for potentially higher quality signals
• Signals use barstate.isconfirmed to reduce (but not eliminate) repainting
📈 TREND ANALYSIS:
• Trend Ribbon: 8 EMAs creating a visual trend direction indicator
• Trend Cloud: EMA 150/250 cloud for long-term trend context
• Chaos Trend Line: Dynamic support/resistance trend line
• Multi-timeframe dashboard showing trend across 8 timeframes (3m to Daily)
📊 TECHNICAL INDICATORS:
• Keltner Channels: Dynamic price channels
• RSI Background: Visual overbought/oversold zones
• Candlestick Coloring: Three modes (CleanScalper/Trend Ribbon/Moving Average)
• ADX-based trend strength analysis for MTF dashboard
🎯 VISUAL TOOLS:
• Order Blocks: Supply/demand zones (optional)
• Channel Breakouts: Pivot-based support/resistance levels
• Reversal Signals: RSI-based potential reversal indicators
• Visual TP/SL Lines: For reference only - does NOT execute trades
📊 DASHBOARD:
• Real-time multi-timeframe trend analysis
• Volatility indicator (Very Low to Very High)
• Current RSI value with color coding
• Customizable position and size
⚙️ SETTINGS:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
MAIN SETTINGS:
• Sensitivity: Controls signal frequency (lower = more signals)
• Signal Type: Choose between All Signals or Filtered Signals
• Factor: ATR multiplier for SuperTrend calculation
TREND SETTINGS:
• Toggle Trend Ribbon, Trend Cloud, Chaos Trend, Order Blocks
• Moving Average: Customizable EMA (default 200)
ADVANCED SETTINGS:
• Candlestick coloring with 3 different modes
• Overbought/Oversold background coloring
• Channel breakout levels
• Show/hide signals
RISK MANAGEMENT (VISUAL ONLY):
• ⚠️ Does NOT execute trades automatically
• Shows potential Take Profit levels (TP1, TP2, TP3)
• Shows potential Stop Loss level
• Adjustable TP strength multiplier
• For educational reference only
📖 HOW TO USE:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
1. SIGNAL INTERPRETATION:
• "Buy" signals appear below candles when conditions are met
• "Sell" signals appear above candles when conditions are met
• Wait for bar close confirmation to avoid repainting
• Use multiple timeframes for confluence
2. TREND CONFIRMATION:
• Check the multi-timeframe dashboard for trend alignment
• Use Trend Ribbon for visual trend direction
• Trend Cloud shows longer-term market bias
• Green candles = potential uptrend, Red = potential downtrend
3. ENTRY/EXIT STRATEGY:
• Combine signals with other analysis tools
• Check volatility status before entering trades
• Use support/resistance levels for confirmation
• The visual TP/SL lines are for planning only
4. RISK MANAGEMENT:
• Always use stop losses (indicator shows suggested levels only)
• Position size according to your risk tolerance
• Never risk more than you can afford to lose
• The indicator does NOT manage trades automatically
⚠️ LIMITATIONS & RISKS:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
REPAINTING:
• Signals may appear and disappear on unconfirmed bars
• Always wait for bar close before taking action
• Historical performance may look better than real-time results
FALSE SIGNALS:
• No indicator is 100% accurate
• Signals can fail in ranging/choppy markets
• Use additional confirmation methods
• Consider market context and fundamentals
VISUAL TP/SL:
• Lines are for reference/planning only
• Does NOT place or manage actual trades
• You must manually set your own stop losses
• TP levels are calculated estimates, not guarantees
🔧 TECHNICAL DETAILS:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
• Version: Pine Script v5
• Overlay: Yes (displays on main chart)
• Anti-repaint measures: Uses barstate.isconfirmed on signals
• Security function: Uses lookahead protection for higher timeframes
• Dynamic requests: Enabled for MTF analysis
• Max labels: 500
📚 COMPONENTS EXPLAINED:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
SUPERTREND:
• Core signal generator using ATR-based bands
• Crossovers indicate potential trend changes
• Adjustable via Sensitivity and Factor inputs
EMA FILTER:
• Uses 200 EMA as trend filter (customizable)
• Filtered signals require price above/below EMA
• Helps reduce false signals in ranging markets
ADX TREND QUALITY:
• Measures trend strength across timeframes
• Used in multi-timeframe dashboard
• Shows Bullish/Bearish/Neutral states
KELTNER CHANNELS:
• Multiple bands showing volatility zones
• Color-coded based on RSI levels
• Helps identify overbought/oversold conditions
ORDER BLOCKS:
• Identifies supply/demand zones
• Based on price structure and pivots
• Can extend to the right for projection
💡 BEST PRACTICES:
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✓ Use multiple timeframe confirmation
✓ Wait for bar close before acting on signals
✓ Combine with support/resistance analysis
✓ Check overall market conditions
✓ Use proper risk management (1-2% per trade)
✓ Backtest on your specific market/timeframe
✓ Paper trade before using real money
✓ Keep a trading journal
✓ Adjust settings to your trading style
✗ Don't rely solely on this indicator
✗ Don't ignore risk management
✗ Don't trade on unconfirmed signals
✗ Don't overtrade every signal
✗ Don't use without understanding how it works
✗ Don't expect the TP/SL feature to trade for you
📞 SUPPORT & UPDATES:
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Creator: Zakaria Safri
Version: 4.3 (Compliance Update)
For questions or feedback, please use TradingView's comment section.
⚖️ FINAL DISCLAIMER:
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This indicator is provided for EDUCATIONAL and INFORMATIONAL purposes only.
It is NOT financial advice, investment advice, or a recommendation to buy/sell.
Trading involves substantial risk of loss. Past performance, whether actual or
indicated by historical tests of strategies, is not indicative of future results.
The creator assumes NO responsibility for your trading results. You are solely
responsible for your own investment decisions and due diligence.
Always consult with a qualified financial advisor before making investment decisions.
By using this indicator, you acknowledge and accept these risks and limitations.
