Stoch Quad Oscillator📘 Stoch Quad Oscillator – User Guide
✅ Purpose
The Stoch Quad Oscillator is a multi-timeframe stochastic oscillator tool that helps traders detect oversold and overbought conditions, momentum shifts, and quad rotation signals using four distinct stochastic configurations. It includes visual cues, customizable parameters, and background highlights to improve decision-making during trend reversals or momentum surges.
🛠️ Inputs & Parameters
⏱ Timeframe
Timeframe for Stochastic Calculation: Defines which chart timeframe to use for stochastic calculations (default is "1" minute). This enables multi-timeframe analysis while on a lower timeframe chart.
📈 Stochastic Parameters
Four different stochastic configurations are used:
Label %K Length %D Smoothing Notes
K9 D3 9 3 Fastest, short-term view
K14 D3 14 3 Moderately short-term
K40 D4 40 4 Medium-term trend view
K60 D10 60 10 Long-term strength
Smoothing Type: Choose between SMA or EMA to control how smoothed the %D line is.
🎯 Levels
Overbought Level: Default 80
Oversold Level: Default 20
These are used to indicate overextended price conditions on any of the stochastic plots.
🔄 Quad Rotation Detection Settings
When enabled, the script detects synchronized oversold/overbought conditions with strong momentum using all 4 stochastic readings.
Enable Quad Rotation: Toggles detection on or off
Slope Calculation Bars: Number of bars used to calculate slope of %D lines
Slope Threshold: Minimum slope strength for signal (higher = stronger confirmation)
Oversold Quad Level: Total of all four stochastic values that define a quad oversold zone
Overbought Quad Level: Total of all four stochastic values that define a quad overbought zone
Oversold Quad Highlight Color: Background color when oversold quad is triggered
Overbought Quad Highlight Color: Background color when overbought quad is triggered
Slope Averaging Method: Either Simple Average or Weighted Average (puts more weight on higher timeframes)
Max Signal Bar Window: Defines how recent the signal must be to be considered valid
📊 Plots & Visual Elements
📉 Stochastic %D Lines
Each stochastic is plotted separately:
K9 D3 – Red
K14 D3 – Orange
K40 D4 – Fuchsia
K60 D10 – Silver
These help visualize short to long-term momentum simultaneously.
📏 Horizontal Reference Lines
Overbought Line (80) – Red
Oversold Line (20) – Green
These help you identify threshold breaches visually.
🌈 Background Highlighting
The indicator provides background highlights to mark potential signal zones:
✅ All Oversold or Overbought Conditions
When all four stochastics are either above overbought or below oversold:
Bright Red if all are overbought
Bright Green if all are oversold
🚨 Quad Rotation Signal Zones (if enabled)
Triggered when:
The combined sum of all four stochastic levels is extremely low/high (below/above oversoldQuadLevel or overboughtQuadLevel)
The average slope of the 4 %D lines is sharply positive (> slopeThreshold)
Highlights:
Custom Red Tint = Strong overbought quad signal
Custom Green Tint = Strong oversold quad signal
These zones can indicate momentum shifts or reversal potential when used with price action or other tools.
⚠️ Limitations & Considerations
This indicator does not provide trade signals. It visualizes conditions and potential setups.
It is best used in confluence with price action, support/resistance levels, and other indicators.
False positives may occur in ranging markets. Reduce reliance on slope thresholds during low volatility.
Quad signals rely on slope strength, which may lag slightly behind sudden reversals.
🧠 Tips for Use
Combine with volume, MACD, or PSAR to confirm direction before entry.
Watch for divergences between price and any of the stochastics.
Use on higher timeframes (e.g., 5m–30m) to filter for swing trading setups; use shorter TFs (1m–5m) for scalping signals.
Adjust oversoldQuadLevel and overboughtQuadLevel based on market conditions (e.g., in trending vs ranging markets).
Cerca negli script per "乌德勒支+VS+赫拉克勒斯"
[blackcat] L2 Multi-Level Price Condition TrackerOVERVIEW
The L2 Multi-Level Price Condition Tracker represents an innovative approach to analyzing financial markets by simultaneously monitoring multiple price levels, thus providing traders with a holistic view of market dynamics. By combining dynamic calculations based on moving averages and price deviations, this tool aims to deliver precise and actionable insights into potential entry and exit points. It leverages sophisticated statistical measures to identify key thresholds that signify shifts in market sentiment, thereby aiding traders in making well-informed decisions. 🎯
Key benefits encompass:
• Comprehensive calculation of midpoints and average prices indicating short-term trend directions.
• Interactive visualization elements enhancing interpretability effortlessly.
• Real-time generation of buy/sell signals driven by precise condition evaluations.
TECHNICAL ANALYSIS COMPONENTS
📉 Midpoint Calculations:
Computes central reference points derived from high-low ranges establishing baseline supports/resistances.
Utilizes Simple Moving Averages (SMAs) along with standardized deviation formulas smoothing out volatility while preserving long-term trends accurately.
Facilitates identification of directional biases reflecting underlying market forces dynamically.
🕵️♂️ Advanced Price Level Detection:
Derives upper/lower bounds adjusting sensitivities adaptively responding to changing conditions flexibly.
Employs proprietary logic distinguishing between bullish/bearish sentiments promptly signaling transitions effectively.
Ensures consistent adherence to predefined statistical protocols maintaining accuracy robustly.
🎥 Dynamic Signal Generation:
Detects crossovers indicating dominance shifts between buyers/sellers promptly triggering timely alerts.
Integrates conditional logic reinforcing signal validity minimizing erroneous activations systematically.
Supports adaptive thresholds tuning sensitivities based on evolving market conditions flexibly accommodating varying scenarios.
INDICATOR FUNCTIONALITY
🔢 Core Algorithms:
Utilizes moving averages alongside standardized deviation formulas generating precise net volume measurements.
Implements Arithmetic Mean Line Algorithm (AMLA) smoothing techniques improving interpretability.
Ensures consistent alignment with established statistical principles preserving fidelity.
🖱️ User Interface Elements:
Dedicated plots displaying real-time midpoint markers facilitating swift decision-making.
Context-sensitive color coding distinguishing positive/negative deviations intuitively highlighting key activations clearly.
Background shading emphasizing proximity to crucial threshold activations enhancing visibility focusing attention on vital signals promptly.
STRATEGY IMPLEMENTATION
✅ Entry Conditions:
Confirm bullish/bearish setups validated through multiple confirmatory signals assessing concurrent market sentiment factors.
Validate entry decisions considering alignment between calculated midpoints and broader trend directions ensuring coherence.
Monitor cumulative breaches signifying potential trend reversals executing partial/total closes contingent upon predetermined loss limits preserving capital efficiently.
🚫 Exit Mechanisms:
Trigger exits upon hitting predefined thresholds derived from historical analyses promptly executing closures.
Execute partial/total closes contingent upon cumulative loss limits preserving capital efficiently managing exposures prudently.
Conduct periodic reviews gauging strategy effectiveness rigorously identifying areas needing refinement implementing corrective actions iteratively enhancing performance metrics steadily.
PARAMETER CONFIGURATIONS
🎯 Optimization Guidelines:
Lookback Period: Governs responsiveness versus stability balancing sensitivity/stability governing moving averages aligning with preferred granularity.
Price Source: Dictates primary data series driving volume calculations selecting relevant inputs accurately tailoring strategies accordingly.
💬 Customization Recommendations:
Commence with baseline defaults; iteratively refine parameters isolating individual impacts evaluating adjustments independently prior to combined modifications minimizing disruptions.
Prioritize minimizing erroneous trigger occurrences first optimizing signal fidelity sustaining balanced risk-reward profiles irrespective of chosen settings upholding disciplined approaches preserving capital efficiently.
ADVANCED RISK MANAGEMENT
🛡️ Proactive Risk Mitigation Techniques:
Enforce strict compliance with pre-defined maximum leverage constraints adhering strictly to guidelines managing exposures prudently.
Mandatorily apply trailing stop-loss orders conforming to script outputs enforcing discipline rigorously preventing adverse consequences.
Allocate positions proportionately relative to available capital reserves conducting periodic reviews gauging effectiveness continuously identifying improvement opportunities steadily.
⚠️ Potential Pitfalls & Solutions:
Address frequent violations arising during heightened volatility phases necessitating manual interventions judiciously preparing contingency plans proactively mitigating risks effectively.
Manage false alerts warranting immediate attention avoiding adverse consequences systematically implementing corrective actions reliably.
Prepare proactive responses amid adverse movements ensuring seamless functionality amidst fluctuating conditions fortifying resilience against anomalies robustly.
PERFORMANCE MONITORING METRICS
🔍 Evaluation Criteria:
Assess win percentages consistently across diverse trading instruments gauging reliability measuring profitability efficiency accurately evaluating downside risks comprehensively uncovering systematic biases potentially skewing outcomes.
Calculate average profit ratios per successful execution benchmarking actual vs expected performances documenting results meticulously tracking progress dynamically addressing identified shortcomings proactively fostering continuous improvements.
📈 Historical Data Analysis Tools:
Maintain detailed logs capturing every triggered event recording realized profits/losses comparing simulated projections accurately identifying discrepancies warranting investigation implementing iterative refinements steadily enhancing performance metrics progressively.
Identify recurrent systematic errors demanding corrective actions implementing iterative refinements steadily addressing identified shortcomings proactively fostering continuous enhancements dynamically improving robustness resiliently.
PROBLEM SOLVING ADVICE
🔧 Frequent Encountered Challenges:
Unpredictable behaviors emerging within thinly traded markets requiring filtration processes enhancing signal integrity excluding low-liquidity assets prone to erratic movements effectively.
Latency issues manifesting during abrupt price fluctuations causing missed opportunities introducing buffer intervals safeguarding major news/event impacts mitigating distortions seamlessly verifying reliable connections ensuring uninterrupted data flows guaranteeing accurate interpretations dependably.
💡 Effective Resolution Pathways:
Limit ongoing optimization attempts preventing model degradation maintaining optimal performance levels consistently recalibrating parameters periodically adapting strategies flexibly responding appropriately amidst varying conditions dynamically improving robustness resiliently.
Verify reliable connections ensuring uninterrupted data flows guaranteeing accurate interpretations dependably bolstering overall efficacy systematically addressing identified shortcomings dynamically fostering continuous advancements.
THANKS
Heartfelt acknowledgment extends to all developers contributing invaluable insights regarding multi-level price condition-based trading methodologies! ✨
[blackcat] L1 Net Volume DifferenceOVERVIEW
The L1 Net Volume Difference indicator serves as an advanced analytical tool designed to provide traders with deep insights into market sentiment by examining the differential between buying and selling volumes over precise timeframes. By leveraging these volume dynamics, it helps identify trends and potential reversal points more accurately, thereby supporting well-informed decision-making processes. The key focus lies in dissecting intraday changes that reflect short-term market behavior, offering critical input for both swing and day traders alike. 📊
Key benefits encompass:
• Precise calculation of net volume differences grounded in real-time data.
• Interactive visualization elements enhancing interpretability effortlessly.
• Real-time generation of buy/sell signals driven by dynamic volume shifts.
TECHNICAL ANALYSIS COMPONENTS
📉 Volume Accumulation Mechanisms:
Monitors cumulative buy/sell volumes derived from comparative closing prices.
Periodically resets accumulation counters aligning with predefined intervals (e.g., 5-minute bars).
Facilitates identification of directional biases reflecting underlying market forces accurately.
🕵️♂️ Sentiment Detection Algorithms:
Employs proprietary logic distinguishing between bullish/bearish sentiments dynamically.
Ensures consistent adherence to predefined statistical protocols maintaining accuracy.
Supports adaptive thresholds adjusting sensitivities based on changing market conditions flexibly.
🎯 Dynamic Signal Generation:
Detects transitions indicating dominance shifts between buyers/sellers promptly.
Triggers timely alerts enabling swift reactions to evolving market dynamics effectively.
Integrates conditional logic reinforcing signal validity minimizing erroneous activations.
INDICATOR FUNCTIONALITY
🔢 Core Algorithms:
Utilizes moving averages along with standardized deviation formulas generating precise net volume measurements.
Implements Arithmetic Mean Line Algorithm (AMLA) smoothing techniques improving interpretability.
Ensures consistent alignment with established statistical principles preserving fidelity.
🖱️ User Interface Elements:
Dedicated plots displaying real-time net volume markers facilitating swift decision-making.
Context-sensitive color coding distinguishing positive/negative deviations intuitively.
Background shading highlighting proximity to key threshold activations enhancing visibility.
STRATEGY IMPLEMENTATION
✅ Entry Conditions:
Confirm bullish/bearish setups validated through multiple confirmatory signals.
Validate entry decisions considering concurrent market sentiment factors.
Assess alignment between net volume readings and broader trend directions ensuring coherence.
🚫 Exit Mechanisms:
Trigger exits upon hitting predetermined thresholds derived from historical analyses.
Monitor continuous breaches signifying potential trend reversals promptly executing closures.
Execute partial/total closes contingent upon cumulative loss limits preserving capital efficiently.
PARAMETER CONFIGURATIONS
🎯 Optimization Guidelines:
Reset Interval: Governs responsiveness versus stability balancing sensitivity/stability.
Price Source: Dictates primary data series driving volume calculations selecting relevant inputs accurately.
💬 Customization Recommendations:
Commence with baseline defaults; iteratively refine parameters isolating individual impacts.
Evaluate adjustments independently prior to combined modifications minimizing disruptions.
Prioritize minimizing erroneous trigger occurrences first optimizing signal fidelity.
Sustain balanced risk-reward profiles irrespective of chosen settings upholding disciplined approaches.
ADVANCED RISK MANAGEMENT
🛡️ Proactive Risk Mitigation Techniques:
Enforce strict compliance with pre-defined maximum leverage constraints adhering strictly to guidelines.
Mandatorily apply trailing stop-loss orders conforming to script outputs reinforcing discipline.
Allocate positions proportionately relative to available capital reserves managing exposures prudently.
Conduct periodic reviews gauging strategy effectiveness rigorously identifying areas needing refinement.
⚠️ Potential Pitfalls & Solutions:
Address frequent violations arising during heightened volatility phases necessitating manual interventions judiciously.
Manage false alerts warranting immediate attention avoiding adverse consequences systematically.
Prepare contingency plans mitigating margin call possibilities preparing proactive responses effectively.
Continuously assess automated system reliability amidst fluctuating conditions ensuring seamless functionality.
PERFORMANCE AUDITS & REFINEMENTS
🔍 Critical Evaluation Metrics:
Assess win percentages consistently across diverse trading instruments gauging reliability.
Calculate average profit ratios per successful execution measuring profitability efficiency accurately.
Measure peak drawdown durations alongside associated magnitudes evaluating downside risks comprehensively.
Analyze signal generation frequencies revealing hidden patterns potentially skewing outcomes uncovering systematic biases.
📈 Historical Data Analysis Tools:
Maintain comprehensive records capturing every triggered event meticulously documenting results.
Compare realized profits/losses against backtested simulations benchmarking actual vs expected performances accurately.
Identify recurrent systematic errors demanding corrective actions implementing iterative refinements steadily.
Document evolving performance metrics tracking progress dynamically addressing identified shortcomings proactively.
PROBLEM SOLVING ADVICE
🔧 Frequent Encountered Challenges:
Unpredictable behaviors emerging within thinly traded markets requiring filtration processes.
Latency issues manifesting during abrupt price fluctuations causing missed opportunities.
Overfitted models yielding suboptimal results post-extensive tuning demanding recalibrations.
Inaccuracies stemming from incomplete/inaccurate data feeds necessitating verification procedures.
💡 Effective Resolution Pathways:
Exclude low-liquidity assets prone to erratic movements enhancing signal integrity.
Introduce buffer intervals safeguarding major news/event impacts mitigating distortions effectively.
Limit ongoing optimization attempts preventing model degradation maintaining optimal performance levels consistently.
Verify reliable connections ensuring uninterrupted data flows guaranteeing accurate interpretations reliably.
USER ENGAGEMENT SEGMENT
🤝 Community Contributions Welcome
Highly encourage active participation sharing experiences & recommendations!
THANKS
Heartfelt acknowledgment extends to all developers contributing invaluable insights about volume-based trading methodologies! ✨
Real-Time Open Levels with Labels + Info TableReal-Time Multi-Timeframe Open Levels with Labels & Info Panel
Overview
This indicator displays real-time opening price levels across multiple timeframes (Monthly, Weekly, Daily, 4H) directly on your chart. It features:
• Dynamic horizontal lines extending through each timeframe period
• Customizable labels with text/colors
• Special 4H line treatment for the last hour (5-min charts only)
• Integrated information panel showing symbol, timeframe, and price changes
! (www.tradingview.com)
*Example showing multiple timeframe levels with labels and info panel*
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Features & Configuration
1. Monthly Settings
! (www.tradingview.com)
Show Monthly: Toggle visibility of monthly opening price
Color: Semi-transparent blue (#2196F3 at 70% opacity)
Width: 2px line thickness
Style: Solid/Dotted/Dashed
Label: Display "M-Open" text with white text on blue background
2. Weekly Settings
! (www.tradingview.com)
Show Weekly: Toggle weekly opening price visibility
Color: Semi-transparent red (#FF5252 at 70% opacity)
Width: 1px thickness
Style: Dotted by default
Label: "W-Open" text in white on red background
3. Daily Settings
! (www.tradingview.com)
Show Daily: Toggle daily opening price
Color: Amber (#FFA000 at 70% opacity)
Width: 2px thickness
Style: Solid
Label: "D-Open" in white on orange background
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4. 4-Hour Settings (5-Minute Charts Only)
Special Features for 5-Min Timeframe:
1. Standard 4H Line
• First 3 hours: Green (#4CAF50) dashed line
• Last hour: Bright red solid line (configurable)
• Vertical divider between 3rd/4th hours
2. Configuration Options
• Main 4H Line:
◦ Color/Width/Style for initial 3 hours
◦ Toggle label ("H4-Open") visibility and styling
• Final Hour Enhancement:
*Last Hour Line*
◦ Unique red color and line style
◦ Separate width (1px) and style (Solid)
*Divider Line*
◦ Vertical red dotted line marking last hour
◦ Adjustable position/width/transparency
! (www.tradingview.com)
*4H levels showing 3-hour segment and final hour treatment*
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5. Info Panel Settings
Positioning:
• Anchor to any chart corner (Top/Bottom + Left/Right combinations)
• Three text sizes: Title (Huge), Change % (Large), Signature (Small)
Display Elements:
• Symbol: Show exchange prefix (e.g., "NASDAQ:")
• Timeframe: Current chart period (e.g., "5m")
• Change %: 24-hour price movement ▲/▼ percentage
• Custom Signature: Add text/username in footer
Styling:
• Semi-transparent white text (#ffffff77)
• Currency pair formatting (e.g., BTC/USD vs BTC-USD)
! (www.tradingview.com)
*Sample info panel with all elements enabled*
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Usage Tips
1. Multi-Timeframe Context: Use levels to identify key daily/weekly support/resistance
2. 4H Trading: On 5-min charts, watch for price reactions near final hour transition
3. Customization:
• Match line colors to your chart theme
• Use different labels for clarity (e.g., "Weekly Open")
• Disable unused elements to reduce clutter
4. Divider Lines: Helps identify institutional trading periods (hour closes)
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*Created using Pine Script v6. For optimal performance, use on charts <1H timeframe. ()*
Cointegration Heatmap & Spread Table [EdgeTerminal]The Cointegration Heatmap is a powerful visual and quantitative tool designed to uncover deep, statistically meaningful relationships between assets.
Unlike traditional indicators that react to price movement, this tool analyzes the underlying statistical relationship between two time series and tracks when they diverge from their long-term equilibrium — offering actionable signals for mean-reversion trades .
What Is Cointegration?
Most traders are familiar with correlation, which measures how two assets move together in the short term. But correlation is shallow — it doesn’t imply a stable or predictable relationship over time.
Cointegration, however, is a deeper statistical concept: Two assets are cointegrated if a linear combination of their prices or returns is stationary , even if the individual series themselves are non-stationary.
Cointegration is a foundational concept in time series analysis, widely used by hedge funds, proprietary trading firms, and quantitative researchers. This indicator brings that institutional-grade concept into an easy-to-use and fully visual TradingView indicator.
This tool helps answer key questions like:
“Which stocks tend to move in sync over the long term?”
“When are two assets diverging beyond statistical norms?”
“Is now the right time to short one and long the other?”
Using a combination of regression analysis, residual modeling, and Z-score evaluation, this indicator surfaces opportunities where price relationships are stretched and likely to snap back — making it ideal for building low-risk, high-probability trade setups.
In simple terms:
Cointegrated assets drift apart temporarily, but always come back together over time. This behavior is the foundation of successful pairs trading.
How the Indicator Works
Cointegration Heatmap indicator works across any market supported on TradingView — from stocks and ETFs to cryptocurrencies and forex pairs.
You enter your list of symbols, choose a timeframe, and the indicator updates every bar with live cointegration scores, spread signals, and trade-ready insights.
Indicator Settings:
Symbol list: a customizable list of symbols separated by commas
Returns timeframe: time frame selection for return sampling (Weekly or Monthly)
Max periods: max periods to limit the data to a certain time and to control indicator performance
This indicator accomplishes three major goals in one streamlined package:
Identifies stable long-term relationships (cointegration) between assets, using a heatmap visualization.
Tracks the spread — the difference between actual prices and the predicted linear relationship — between each pair.
Generates trade signals based on Z-score deviations from the mean spread, helping traders know when a pair is statistically overextended and likely to mean revert.
The math:
Returns are calculated using spread tickers to ensure alignment in time and adjust for dividends, splits, and other inconsistencies.
For each unique pair of symbols, we perform a linear regression
Yt=α+βXt+ε
Then we compute the residuals (errors from the regression):
Spreadt=Yt−(α+βXt)
Calculate the standard deviation of the spread over a moving window (default: 100 samples) and finally, define the Cointegration Score:
S=1/Standard Deviation of Residuals
This means, the lower the deviation, the tighter the relationship, so higher scores indicate stronger cointegration.
Always remember that cointegration can break down so monitor the asset over time and over multiple different timeframes before making a decision.
How to use the indicator
The heatmap table:
The indicator displays 2 very important tables, one in the middle and one on the right side. After entering your symbols, the first table to pay attention to is the middle heatmap table.
Any assets with a cointegration value of 25% is something to pay attention to and have a strong and stable relationship. Anything below is weak and not tradable.
Additionally, the 40% level is another important line to cross. Assets that have a cointegration score of over 40% will most likely have an extremely strong relationship.
Think about it this way, the higher the percentage, the tighter and more statistically reliable the relationship is.
The spread table:
After finding a good asset pair using heatmap, locate the same pair in the spread table (right side).
Here’s what you’ll see on the table:
Spread: Current difference between the two symbols based on the regression fit
Mean: Historical average of that spread
Z-score: How far current spread is from the mean in standard deviations
Signal: Trade suggestion: Short, Long, or Neutral
Since you’re expecting mean reversion, the idea is that the spread will return to the average. You want to take a trade when the z-score is either over +2 or below -2 and exit when z-score returns to near 0.
You will usually see the trade suggestion on the spread chart but you can make your own decision based on your risk level.
Keep in mind that the Z-score for each pair refers to how off the first asset is from the mean compared to the second one, so for example if you see STOCKA vs STOCKB with a Z-score of -1.55, we are regressing STOCKB (Y) on STOCKA (X).
In this case, STOCKB is the quoted asset and STOCKA is the base asset.
In this case, this means that STOCKB is much lower than expected relative to STOCKA, so the trade would be a long position on stock B and short position on stock A.
Seasonality DOW CombinedOverall Purpose
This script analyzes historical daily returns based on two specific criteria:
Month of the year (January through December)
Day of the week (Sunday through Saturday)
It summarizes and visually displays the average historical performance of the selected asset by these criteria over multiple years.
Step-by-Step Breakdown
1. Initial Settings:
Defines minimum year (i_year_start) from which data analysis will start.
Ensures the user is using a daily timeframe, otherwise prompts an error.
Sets basic display preferences like text size and color schemes.
2. Data Collection and Variables:
Initializes matrices to store and aggregate returns data:
month_data_ and month_agg_: store monthly performance.
dow_data_ and dow_agg_: store day-of-week performance.
COUNT tracks total number of occurrences, and COUNT_POSITIVE tracks positive-return occurrences.
3. Return Calculation:
Calculates daily percentage change (chg_pct_) in price:
chg_pct_ = close / close - 1
Ensures it captures this data only for the specified years (year >= i_year_start).
4. Monthly Performance Calculation:
Each daily return is grouped by month:
matrix.set updates total returns per month.
The script tracks:
Monthly cumulative returns
Number of occurrences (how many days recorded per month)
Positive occurrences (days with positive returns)
5. Day-of-Week Performance Calculation:
Similarly, daily returns are also grouped by day-of-the-week (Sunday to Saturday):
Daily return values are summed per weekday.
The script tracks:
Cumulative returns per weekday
Number of occurrences per weekday
Positive occurrences per weekday
6. Visual Display (Tables):
The script creates two visual tables:
Left Table: Monthly Performance.
Right Table: Day-of-the-Week Performance.
For each table, it shows:
Yearly data for each month/day.
Summaries at the bottom:
SUM row: Shows total accumulated returns over all selected years for each month/day.
+ive row: Shows percentage (%) of times the month/day had positive returns, along with a tooltip displaying positive occurrences vs total occurrences.
Cells are color-coded:
Green for positive returns.
Red for negative returns.
Gray for neutral/no change.
7. Interpreting the Tables:
Monthly Table (left side):
Helps identify seasonal patterns (e.g., historically bullish/bearish months).
Day-of-Week Table (right side):
Helps detect recurring weekday patterns (e.g., historically bullish Mondays or bearish Fridays).
Practical Use:
Traders use this to:
Identify patterns based on historical data.
Inform trading strategies, e.g., avoiding historically bearish days/months or leveraging historically bullish periods.
Example Interpretation:
If the table shows consistently green (positive) for March and April, historically the asset tends to perform well during spring. Similarly, if the "Friday" column is often red, historically Fridays are bearish for this asset.
[blackcat] L2 Z-Score of PriceOVERVIEW
The L2 Z-Score of Price indicator offers traders an insightful perspective into how current prices diverge from their historical norms through advanced statistical measures. By leveraging Z-scores, it provides a robust framework for identifying potential reversals in financial markets. The Z-score quantifies the number of standard deviations that a data point lies away from the mean, thus serving as a critical metric for recognizing overbought or oversold conditions. 🎯
Key benefits encompass:
• Precise calculation of Z-scores reflecting true price deviations.
• Interactive plotting features enhancing visual clarity.
• Real-time generation of buy/sell signals based on crossover events.
STATISTICAL ANALYSIS COMPONENTS
📉 Mean Calculation:
Utilizes Simple Moving Averages (SMAs) to establish baseline price references.
Provides smooth representations filtering short-term noise preserving long-term trends.
Fundamental for deriving subsequent deviation metrics accurately.
📈 Standard Deviation Measurement:
Quantifies dispersion around established means revealing underlying variability.
Crucial for assessing potential volatility levels dynamically adapting strategies accordingly.
Facilitates precise Z-score derivations ensuring statistical rigor.
🕵️♂️ Z-SCORE DETECTION:
Measures standardized distances indicating relative positions within distributions.
Helps pinpoint extreme conditions signaling impending reversals proactively.
Enables early identification of trend exhaustion phases prompting timely actions.
INDICATOR FUNCTIONALITY
🔢 Core Algorithms:
Integrates SMAs along with standardized deviation formulas generating precise Z-scores.
Employs Arithmetic Mean Line Algorithm (AMLA) smoothing techniques improving interpretability.
Ensures consistent adherence to predefined statistical protocols maintaining accuracy.
🖱️ User Interface Elements:
Dedicated plots displaying real-time Z-score markers facilitating swift decision-making.
Context-sensitive color coding distinguishing positive/negative deviations intuitively.
Background shading highlighting proximity to key threshold activations enhancing visibility.
STRATEGY IMPLEMENTATION
✅ Entry Conditions:
Confirm bullish/bearish setups validated through multiple confirmatory signals.
Validate entry decisions considering concurrent market sentiment factors.
Assess alignment between Z-score readings and broader trend directions ensuring coherence.
🚫 Exit Mechanisms:
Trigger exits upon hitting predetermined thresholds derived from historical analyses.
Monitor continuous breaches signifying potential trend reversals promptly executing closures.
Execute partial/total closes contingent upon cumulative loss limits preserving capital efficiently.
PARAMETER CONFIGURATIONS
🎯 Optimization Guidelines:
Length: Governs responsiveness versus smoothing trade-offs balancing sensitivity/stability.
Price Source: Dictates primary data series driving Z-score computations selecting relevant inputs accurately.
💬 Customization Recommendations:
Commence with baseline defaults; iteratively refine parameters isolating individual impacts.
Evaluate adjustments independently prior to combined modifications minimizing disruptions.
Prioritize minimizing erroneous trigger occurrences first optimizing signal fidelity.
Sustain balanced risk-reward profiles irrespective of chosen settings upholding disciplined approaches.
ADVANCED RISK MANAGEMENT
🛡️ Proactive Risk Mitigation Techniques:
Enforce strict compliance with pre-defined maximum leverage constraints adhering strictly to guidelines.
Mandatorily apply trailing stop-loss orders conforming to script outputs reinforcing discipline.
Allocate positions proportionately relative to available capital reserves managing exposures prudently.
Conduct periodic reviews gauging strategy effectiveness rigorously identifying areas needing refinement.
⚠️ Potential Pitfalls & Solutions:
Address frequent violations arising during heightened volatility phases necessitating manual interventions judiciously.
Manage false alerts warranting immediate attention avoiding adverse consequences systematically.
Prepare contingency plans mitigating margin call possibilities preparing proactive responses effectively.
Continuously assess automated system reliability amidst fluctuating conditions ensuring seamless functionality.
PERFORMANCE AUDITS & REFINEMENTS
🔍 Critical Evaluation Metrics:
Assess win percentages consistently across diverse trading instruments gauging reliability.
Calculate average profit ratios per successful execution measuring profitability efficiency accurately.
Measure peak drawdown durations alongside associated magnitudes evaluating downside risks comprehensively.
Analyze signal generation frequencies revealing hidden patterns potentially skewing outcomes uncovering systematic biases.
📈 Historical Data Analysis Tools:
Maintain comprehensive records capturing every triggered event meticulously documenting results.
Compare realized profits/losses against backtested simulations benchmarking actual vs expected performances accurately.
Identify recurrent systematic errors demanding corrective actions implementing iterative refinements steadily.
Document evolving performance metrics tracking progress dynamically addressing identified shortcomings proactively.
PROBLEM SOLVING ADVICE
🔧 Frequent Encountered Challenges:
Unpredictable behaviors emerging within thinly traded markets requiring filtration processes.
Latency issues manifesting during abrupt price fluctuations causing missed opportunities.
Overfitted models yielding suboptimal results post-extensive tuning demanding recalibrations.
Inaccuracies stemming from incomplete/inaccurate data feeds necessitating verification procedures.
💡 Effective Resolution Pathways:
Exclude low-liquidity assets prone to erratic movements enhancing signal integrity.
Introduce buffer intervals safeguarding major news/event impacts mitigating distortions effectively.
Limit ongoing optimization attempts preventing model degradation maintaining optimal performance levels consistently.
Verify reliable connections ensuring uninterrupted data flows guaranteeing accurate interpretations reliably.
USER ENGAGEMENT SEGMENT
🤝 Community Contributions Welcome
Highly encourage active participation sharing experiences & recommendations!
A.K Dynamic EMA/SMA / MTF S&R Zones Toolkit with AlertsThe A.K Dynamic EMA/SMA / MTF Support & Resistance Zones Toolkit is a powerful all-in-one technical analysis tool designed for traders who want a clean yet comprehensive market view. Whether you're scalping lower timeframes or swing trading higher timeframes, this indicator gives you both the structure and signals to take action with confidence.
Key Features:
✅ Customizable EMA/SMA Suite
Display key Exponential and Simple Moving Averages including 5, 9, 20, 50, 100, and 200 EMAs, plus optional 50 SMA for trend filtering. Each line can be toggled individually and color-customized.
✅ Multi-Timeframe Support & Resistance Zones
Automatically detects dynamic S/R zones on key timeframes (5min, 15min, 30min, 1H, 4H, 1D) using swing highs/lows. Zones are color-coded by strength and whether they're broken or active, providing a clear visual roadmap for price reaction levels.
✅ Zone Strength & Break Detection
Distinguishes between strong and weak zones based on price proximity and reaction depth, with visual shading and automatic label updates when a level is broken.
✅ Price Action-Based Buy/Sell Signals
Generates BUY signals when bullish candles react to strong support (supply) zones, and SELL signals when bearish candles react to strong resistance (demand) zones. All logic is adjustable — including candle body vs wick detection, tolerance range, and strength thresholds.
✅ Alerts Engine
Built-in TradingView alerts for price touching support/resistance or triggering buy/sell signals. Perfect for automation or hands-free monitoring.
✅ Optional Candle & Trend Filters
Highlight bullish/bearish candles visually for additional confirmation.
Optional RSI display and 50-period SMA trend filter to guide directional bias.
🧠 Use Case Scenarios:
Identify dynamic supply & demand zones across multiple timeframes.
Confirm trend direction with EMAs and SMA filters.
React quickly to clean BUY/SELL signals based on actual price interaction with strong zones.
Customize it fully to suit scalping, day trading, or swing trading strategies.
📌 Recommended Settings:
Use default zone transparency (65%) and offset (250 bars) for optimal visual clarity.
Enable alerts to get notified when price enters key S/R levels or when a trade signal occurs.
Combine this tool with your entry/exit plan for better decision-making under pressure.
💡 Pro Tip: Add this indicator to a clean chart and let the zones + EMAs guide your directional bias. Use alerts to avoid screen-watching and improve discipline.
Created by:
Version: Pine Script v6
Platform: TradingView
Moving Average Candles**Moving Average Candles — MA-Based Smoothed Candlestick Overlay**
This script replaces traditional price candles with smoothed versions calculated using various types of moving averages. Instead of plotting raw price data, each OHLC component (Open, High, Low, Close) is independently smoothed using your selected moving average method.
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### 📌 Features:
- Choose from 13 MA types: `SMA`, `EMA`, `RMA`, `WMA`, `VWMA`, `HMA`, `T3`, `DEMA`, `TEMA`, `KAMA`, `ZLEMA`, `McGinley`, `EPMA`
- Fully configurable moving average length (1–1000)
- Color-coded candles based on smoothed Open vs Close
- Works directly on price charts as an overlay
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### 🎯 Use Cases:
- Visualize smoothed market structure more clearly
- Reduce noise in price action for better trend analysis
- Combine with other indicators or strategies for confluence
---
> ⚠️ **Note:** Since all OHLC values are based on moving averages, these candles do **not** represent actual market trades. Use them for trend and structure analysis, not trade entries based on precise levels.
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*Created to support traders seeking a cleaner visual representation of price dynamics.*
SP 500 PE Ratio (Loose Date Match)📈 **S&P 500 PE Ratio (from Excel Data)**
This custom indicator visualizes the historical S&P 500 Price-to-Earnings (PE) Ratio loaded from Excel. Each data point represents a snapshot of the market valuation at a specific time, typically on an annual or quarterly basis.
🔹 **What it does:**
- Plots the PE ratio values on the chart aligned with historical dates
- Uses stepwise or linear rendering to account for missing trading days
- Helps identify valuation cycles and extremes (e.g., overvalued vs undervalued)
🔍 **Use case:**
- Long-term market analysis
- Compare PE trends with price performance
- Spot long-term entry/exit zones based on valuation
🛠️ Future plans:
- Add value zone highlighting (e.g., PE > 30 = red, PE < 15 = green)
- Support for dynamic datasets (via Google Sheets or Notion)
Category: `Breadth indicators`, `Cycles`
💡 Source: Manually imported data (can be replaced with any custom macro data series)
VWAP Predictive Breakout + RSI + OB + Trend/Chop📈 VWAP Predictive Breakout + RSI + Order Blocks + Trend/Chop Filter
This multi-layered day trading and scalping tool is designed to predict price direction after a VWAP breakout, rather than react to it. It combines volume, RSI, candlestick structure, order blocks, and trend/chop analysis to improve the accuracy of intraday signals.
🔍 Core Features
VWAP Predictive Breakout
Signals are generated when price breaks above/below VWAP with strength (volume spike + strong candle body), supported by trend confirmation.
RSI Momentum Filter
Uses RSI divergence behavior to validate breakouts, filtering out weak or exhausted moves.
Order Block Detection
Marks bullish and bearish engulfing patterns and checks for proximity to these zones as confirmation for breakouts.
Trend vs Chop Detection
Uses ADX, ATR, EMA distance, Bollinger Band width, and candlestick cleanliness to dynamically identify whether the market is trending or choppy.
Clean Candle Behavior
Filters out noisy or indecisive candles by analyzing wick-to-body ratio and ATR-based body size.
📌 Visual Markers
🟢 Buy Signal: Green triangle below bar
🔴 Sell Signal: Red triangle above bar
🟢⚪ Bullish Order Block: Green circle
🔴⚪ Bearish Order Block: Red circle
🟩 Trending Background: Light green
🟥 Choppy Background: Light red
🛎 Alerts Included
Long signal: VWAP breakout + RSI + Order Block + Clean Candle
Short signal: VWAP breakdown + RSI + Order Block + Clean Candle
🧠 Best Use Cases
Scalping high-probability VWAP reversals or continuations
Day trading in markets where trend clarity is critical
Filtering noise in sideways conditions using real-time chop detection
Bull vs Bear Volume on Price ChartThis script overlays estimated bullish and bearish volume directly on the price chart, making it easy to spot buying vs. selling pressure without switching to a separate volume pane.
🔍 Features:
📈 Bullish volume markers appear as green triangles below the candle.
📉 Bearish volume markers appear as red triangles above the candle.
🔄 Optional smoothing to reduce noise using simple moving average (SMA).
⚠️ Volume spike highlights: Bullish spikes turn lime green, bearish spikes turn bright red.
🔢 Toggle labels to see estimated volume values above/below each candle.
🔄 Works on all timeframes, from intraday to weekly/monthly charts.
📐 Methodology:
Bullish and bearish volume are estimated using the candle's range:
More bullish volume when the close is near the high.
More bearish volume when the close is near the low.
This is a visual proxy, not true order flow data.
Relative Directional Volume Indicator# Relative Directional Volume Indicator (RelDirVol)
## Overview
The Relative Directional Volume Indicator (RelDirVol) is a powerful volume analysis tool that measures current trading volume relative to historical volume while differentiating between bullish and bearish volume flows. This indicator helps traders identify unusual volume activity and determine whether it's coming from buyers or sellers, providing deeper insights into market participation and potential trend strength.
## Features
- **Relative Volume Calculation**: Compares current volume to historical averages
- **Directional Volume Analysis**: Separates and visualizes bullish vs bearish volume
- **Multiple Moving Average Options**: Customize smoothing with various MA types (SMA, EMA, WMA, HMA, VWMA)
- **Split Moving Averages**: View distinct moving averages for bullish and bearish volume flows
- **Reference Lines**: Visual guides for normal volume (1.0x) and key deviation levels (0.5x, 2.0x, 3.0x)
- **Customizable Colors**: Adjust visual appearance for improved chart readability
## How It Works
The indicator calculates the relative volume by dividing the current bar's volume by the average volume over a specified lookback period. It then categorizes this volume as either bullish (when price closes above the open) or bearish (when price closes below or equal to the open).
1. **Relative Volume**: Current volume ÷ Average volume from previous N bars
2. **Directional Classification**: Assigns volume to bullish or bearish categories based on price action
3. **Moving Averages**: Applies user-selected moving average to smooth the data
The result is displayed as color-coded histogram bars showing the relative volume magnitude, with optional moving average lines for both overall and direction-specific volume trends.
## Interpretation
### Volume Magnitude
- **Above 1.0**: Higher than average volume (more participation than normal)
- **Below 1.0**: Lower than average volume (less participation than normal)
- **2.0+**: Volume twice the normal level (significant participation)
- **3.0+**: Volume three times normal (exceptional participation, often at key events)
### Directional Analysis
- **Strong Green Bars**: Heavy bullish participation driving prices up
- **Strong Red Bars**: Heavy bearish participation driving prices down
- **Bullish MA > Bearish MA**: Overall buying pressure dominating
- **Bearish MA > Bullish MA**: Overall selling pressure dominating
### Key Signals
- **Volume Spikes with Price Breakouts**: Confirms strength of the move
- **Divergence Between MAs**: Early warning of potential shift in market control
- **Sustained Above-Average Volume**: Strong trend continuation likely
- **Volume Decline After Spike**: Potential exhaustion of trend
## Settings
- **Relative Volume Lookback**: Comparison period for average volume (default: 20)
- **Moving Average Type**: Method used for smoothing (default: SMA)
- **Moving Average Length**: Smoothing period (default: 5)
- **Show Moving Average**: Toggle overall volume MA visibility
- **Show Baseline**: Toggle 1.0 reference line visibility
- **Show Bullish/Bearish MAs**: Toggle direction-specific MA visibility
## Best Practices
This indicator performs best when combined with price action analysis and other indicators. Look for:
1. Volume confirmation of breakouts and trend changes
2. Divergence between price movement and volume direction
3. Shifts in the relationship between bullish and bearish MAs
4. Unusual volume patterns during consolidation phases
Particularly effective for swing trading, day trading, and identifying institutional participation in market moves across multiple timeframes.
Camarilla Pivot Plays█ OVERVIEW
This indicator implements the Camarilla Pivot Points levels and a system for suggesting particular plays. It only calculates and shows the 3rd, 4th, and 6th levels, as these are the only ones used by the system. In total, there are 12 possible plays, grouped into two groups of six. The algorithm constantly evaluates conditions for entering and exiting the plays and indicates them in real time, also triggering user-configurable alerts.
█ CREDITS
The Camarilla pivot plays are defined in a strategy developed by Thor Young, and the whole system is explained in his book "A Complete Day Trading System" . The indicator is published with his permission, and he is a user of it. The book is not necessary in order to understand and use the indicator; this description contains sufficient information to use it effectively.
█ FEATURES
Automatically draws plays, suggesting an entry, stop-loss, and maximum target
User can set alerts on chosen ticker to call these plays, even when not currently viewing them
Highly configurable via many options
Works for US/European stocks and US futures (at least)
Works correctly on both RTH and ETH charts
Automatically switches between RTH and ETH data
Optionally also shows the "other" set of pivots (RTH vs ETH data)
Configurable behaviour in the pre-market, not active in the post-market
Configurable sensitivity of the play detection algorithm
Can also show weekly and monthly Camarilla pivots
Well-documented options tooltips
Sensible defaults which are suitable for immediate use
Well-documented and high-quality open-source code for those who are interested
█ HOW TO USE
The defaults work well; at a minimum, just add the indicator and watch the plays being called. To avoid having to watch securities, by selecting the three dots next to the indicator name, you can set an alert on the indicator and choose to be alerted on play entry or exit events—or both. The following diagram shows several plays activated in the past (with the "Show past plays" option selected).
By default, the indicator draws plays 5 days back; this can be changed up to 20 days. The labels can be shifted left/right using the "label offset" option to avoid overlapping with other labels in this indicator or those of another indicator.
An information box at the top-right of the chart shows:
The data currently in use for the main pivots. This can switch in the pre-market if the H/L range exceeds the previous day's H/L, and if it does, you will see that switch at the time that it happens
Whether the current day's pivots are in a higher or lower range compared to the previous day's. This is based on the RTH close, so large moves in the post-market won't be reflected (there is an advanced option to change this)
The width of the value relationship in the current day compared to the previous day
The currently active play. If multiple plays are active in parallel, only the last activated one is shown
The resistance pivots are all drawn in the same colour (red by default), as are the support pivots (green by default). You can change the resistance and support colours, but it is not possible to have different colours for different levels of the same kind. Plays will always use the correct colour, drawing over the pivots. For example, R4 is red by default, but if a play treats R4 as a support, then the play will draw a green line (by default) over the red R4 line, thereby hiding it while the play is active.
There are a few advanced parameters; leave these as default unless you really know what they do. Please note the script is complicated—it does a lot. You might need to wait a few seconds while it (re)calculates on new tickers or when changing options. Give it time when first loading or changing options!
█ CONCEPTS
The indicator is focused around daily Camarilla pivots and implements 12 possible plays: 6 when in a higher range, 6 when in a lower range. The plays are labelled by two letters—the first indicates the range, the second indicates the play—as shown in this diagram:
The pivots can be calculated using only RTH (Regular Trading Hours) data, or ETH (Extended Trading Hours) data, which includes the pre-market and post-market. The indicator implements logic to automatically choose the correct data, based on the rules defined by the strategy. This is user-overridable. With the default options, ETH will be used when the H/L range in the previous day's post-market or current day's pre-market exceeds that of the previous day's regular market. In auto mode, the chosen pivots are considered the main pivots for that day and are the ones used for play evaluation. The "other" pivots can also be shown—"other" here meaning using ETH data when the main pivots use RTH data, and vice versa.
When displaying plays in the pre-market, since the RTH open is not yet known (and that value is needed to evaluate play pre-conditions), the pre-market open is used as a proxy for the RTH open. After the regular market opens, the correct RTH open is used to evaluate play conditions.
█ NOTE FOR FUTURES
Futures always use full ETH data in auto mode. Users may, however, wish to use the option "Always use RTH close," which uses the 3 p.m. Central Time (CME/Chicago) as a basis for the close in the pivot calculations (instead of the 4 p.m. actual close).
Futures don't officially have a pre-market or post-market like equities. Let's take ES on CME as an example (CME is in Chicago, so all times are Central Time, i.e., 1 hour behind Eastern Time). It trades from 17:00 Sunday to 16:00 Friday, with a daily pause between 16:00 and 17:00. However, most of the trading activity is done between 08:30 and 15:00 (Central), which you can tell from the volume spikes at those times, and this coincides with NYSE/NASDAQ regular hours (09:30–16:00 Eastern). So we define a pseudo-pre-market from 17:00 the previous day to 08:30 on the current day, then a pseudo-regular market from 08:30 to 15:00, then a pseudo-post-market from 15:00 to 16:00.
The indicator then works exactly the same as with equities—all the options behave the same, just with different session times defined for the pre-, regular, and post-market, with "RTH" meaning just the regular market and "ETH" meaning all three. The only difference from equities is that the auto calculation mode always uses ETH instead of switching based on ETH range compared to RTH range. This is so users who just leave all the defaults are not confused by auto-switching of the calculation mode; normally you'll want the pivots based on all the (ETH) data. However, both "Force RTH" and "Use RTH close with ETH data" work the same as with equities—so if, in the calculations, you really want to only use RTH data, or use all ETH H/L data but use the RTH close (at 15:00), you can.
█ LIMITATIONS
The pivots are very close to those shown in DAS Trader Pro. They are not to-the-cent exact, but within a few cents. The reasons are:
TradingView uses real-time data from CBOE One, so doesn't have access to full exchange data (unless you pay for it in TradingView), and
the close/high/low are taken from the intraday timeframe you are currently viewing, not daily data—which are very close, but often not exactly the same. For example, the high on the daily timeframe may differ slightly from the daily high you'll see on an intraday timeframe.
I have occasionally seen larger than a few cents differences in the pivots between these and DAS Trader Pro—this is always due to differences in data, for example a big spike in the data in TradingView but not in DAS Trader Pro, or vice versa. The more traded the stock is, the less the difference tends to be. Highly traded stocks are usually within a few cents. Less traded stocks may be more (for example, 30¢ difference in R4 is the highest I've seen). If it bothers you, official NYSE/NASDAQ data in TradingView is quite inexpensive (but even that doesn't make the 8am candle identical).
The 6th Camarilla level does not have a standard definition and may not match the level shown on other platforms. It does match the definition used by DAS Trader Pro.
The indicator is an intraday indicator (despite also being able to show weekly and monthly pivots on an intraday chart). It deactivates on a daily timeframe and higher. It is untested on sub-minute timeframes; you may encounter runtime errors on these due to various historical data referencing issues. Also, the play detection algorithm would likely be unpredictable on sub-minute timeframes. Therefore, sub-minute timeframes are formally unsupported.
The indicator was developed and tested for US/European stocks and US futures. It may or may not work as intended for stocks and futures in different locations. It does not work for other security types (e.g., crypto), where I have no evidence that the strategy has any relevance.
Ehlers Regime Dynamic CandlesCore Calculation Mechanism
The indicator uses advanced Ehlers signal processing techniques to identify market regimes and create dynamically colored candles that reflect market conditions.
Super Smoother Filter: Price data (open, high, low, close) is processed through an Ehlers Super Smoother Filter to reduce market noise while preserving important price movements. This creates a clearer signal for regime detection.
Autocorrelation Analysis: The core of regime detection uses autocorrelation functions at different lag periods:
Primary autocorrelation measures correlation between the current price and its previous value
Trending autocorrelation measures longer-term persistence in the data series
These values combined determine if the market is in a trending or choppy regime
(Image showing Ehlers custom candles vs default candlesticks)
Regime Strength Calculation:
-Raw signal from autocorrelation with user-defined threshold adjustment
-Adaptive scaling based on sensitivity parameter
-Optional volume validation that confirms signal strength using volume data
-Normalization to 0-1 range and smoothing for visual consistency
-Percentile ranking to provide contextually meaningful strength values
Fisher Transform: Applied to the smoothed price to identify statistical extremes, which helps adjust transparency levels during significant price movements.
Key Features & Components
Regime Detection: Identifies trending vs. choppy market conditions using Ehlers' autocorrelation techniques.
Dynamic Candle Coloring: Candles transition smoothly between three color states:
Bullish trending (typically green/teal)
Bearish trending (typically red/purple)
Choppy/neutral (typically blue/silver)
Volume Validation: Optional incorporation of volume data to confirm trend strength (stronger volume during trending periods increases confidence).
Adaptive Transparency: Candles become more opaque during statistically significant price movements based on Fisher Transform values.
Gradient Smoothing: Controls the visual transition between regime states for a more aesthetically pleasing appearance.
Customizable Colors and Style: Full control over all visual aspects including candle body/wick colors and transparency.
Configuration Options
Users can adjust the following parameters in the indicator settings:
Main Settings:
Cycle Length: Controls the lookback period for cycle detection. Lower values increase responsiveness but may introduce noise.
Gradient Smoothness: Determines how quickly colors transition when regime changes.
Trend Detection Threshold: Sets the autocorrelation strength required to classify a trend.
Trend Sensitivity: Scales regime strength calculation to produce a better distribution of values.
Use Volume: Toggles whether volume data is used to validate trend strength.
Color Settings:
Trending Regime Colors: Separate color options for bullish and bearish candle bodies and wicks.
Choppy Regime Colors: Color options for candle bodies and wicks during sideways/neutral markets.
Style Settings:
Candle Border Options: Toggle borders and adjust their color and transparency.
Adaptive Transparency: Enable/disable dynamic transparency based on statistical significance.
Base Transparency: Set the baseline transparency level for all candles.
Interpretation Notes
Color Transitions: As the market shifts between regimes, candle colors gradually transition, providing visual cues about market structure changes.
Regime Strength: The intensity of colors indicates the strength of the detected regime:
Strong trending regimes show vibrant trending colors
Weak or mixed regimes display colors closer to the choppy/neutral color
Transitions between regimes show gradient colors
Transparency Changes: More opaque candles indicate statistically significant price movements, while more transparent candles suggest routine or less significant price action.
Volume Interaction: When volume validation is enabled, trending colors become more pronounced during high volume trends and subdued during low volume periods.
Disclaimer: These are custom candles that are significantly different from normal candlesticks.
Unlike traditional candlesticks that display raw price data, these candles:
• Use Ehlers signal processing to filter and smooth price data
• Dynamically change color based on detected market regimes
• Show statistical significance through transparency
• May appear delayed compared to standard candles due to the filtering process
Traditional trading strategies dependent on candlestick patterns will not work with these.
Risk Disclaimer
Trading involves significant risk. This indicator is provided for analytical purposes only and does not constitute financial advice. Past performance is not indicative of future results. Use sound risk management practices and never trade with capital you cannot afford to lose. The Ehlers Regime Dynamic Candles indicator should be used as part of a comprehensive trading approach, not as a standalone trading system.
CoffeeShopCrypto Supply Demand PPO AdvancedCoffeeShopCrypto PPO Advanced is a structure-aware momentum oscillator and price-trend overlay designed to help traders interpret momentum strength, exhaustion, and continuation across evolving market conditions. It’s not a “buy/sell” signal tool — it's a momentum context tool that helps confirm trend intent.
Original Code derived from the Price Oscillator Indicators (PPO) found in the TradingView Technical Indicators categories. You can view the info and calculation for the original PPO here
www.tradingview.com
Much like the MACD, the PPO uses a couple lagging indicators to present Momentum as a percentage. But it lacks context to market structure.
What It’s Based On
This tool is based on a dual-moving-average PPO oscillator structure (Percentage Price Oscillator) enhanced by:
Oscillator pivot structure: detection of Lower Highs (LH) and Higher Lows (HL) inside the oscillator.
Detection of Supply and Demand Trends via Market Absorption
Ability to transfer its average plots to price action
Detection of Trend Exhaustion
Real-time price-based exhaustion levels: projecting potential future supply and demand using trendlines from weakening momentum.
Integrated fast and slow Moving Averages on price using the same inputs as the oscillator, to visualize alignment between short- and long-term trends.
These elements combine momentum context with price action in a visual, intuitive system.
How It Works
1. Oscillator Structure
LHs (above zero): momentum weakening in uptrends.
HLs (below zero): momentum strengthening in downtrends.
Only valid pivots are shown (e.g., an LH must be preceded by a valid LL).
2. Exhaustion Levels
Green demand lines: price is making new lows, but oscillator prints HL → potential exhaustion.
Red supply lines: price is making new highs, but oscillator prints LH → potential exhaustion.
These lines are future-facing, projecting likely reaction zones based on momentum weakening.
3. Moving Averages on Price
Two MAs are drawn on the price chart:
Fast MA (same length as PPO short input)
Slow MA (same length as PPO long input)
These are not signal lines — they're visual guides for trend alignment.
MA crossover = PO crosses zero. This indicates short- and long-term momentum are syncing — a powerful signal of trend conviction.
When price is above both MAs, and the PO is rising above zero, bullish momentum is dominant.
When price is below both MAs, and the PO is falling below zero, bearish momentum dominates.
How Traders Can Use It
✅ Spot Trend Initiation
Wait for clear trend confirmation in price.
Use PPO Momentum+ to confirm momentum structure is aligned (e.g., HH/HL in oscillator + price above both MAs).
🔁 Track Continuations
In uptrends, look for oscillator HH and HL sequences with price holding above both MAs.
In downtrends, seek LL and LH sequences with price below both MAs.
⚠️ Watch for Exhaustion
Price breaking below red (supply) lines after oscillator LH = bearish exhaustion signal.
Price breaking above green (demand) lines after oscillator HL = bullish exhaustion signal.
These levels act like pre-mapped S/R zones, showing where momentum previously failed and price may react.
Why This Is Different
Momentum tools often lag or mislead when used blindly. This tool visualizes structural failure in momentum and maps potential outcomes. The integration of oscillator and price-based tools ensures traders are always reading context, not just raw signals.
Demand Trendlines
Demand trendlines show us Wykoff's law of "Absorbed Supply Reversal" In real time.
When aggressive selling pressure is persistently absorbed by passive buying interest without significant downward price continuation, and supply becomes exhausted, the market structure shifts as demand regains control—resulting in a directional reversal to the upside.
This commonly happens in a 3 phase interaction of price.
1. Selling pressure is absorbed quickly by buyers.
This PPO tool will calculate the trend of this absorption process
2. After there is a notable Bearish Exhaustion of price action, the PPO tool will draw a trendline of this absorption showing us the potential future prices where aggressive buyers will want to step in at lower prices.
3. After higher lows are defined in the oscillator, you'll see prices react in a strong bullish pattern at this trendline where aggressive buyers stepped in to reverse price action to the upside.
Supply Trendlines
Supply trendlines show us Wykoff's law of "Absorbed Demand Reversal" In real time.
When aggressive buying pressure is persistently absorbed by passive selling interest without significant downward price continuation, and demand becomes exhausted, the market structure shifts as supply regains control—resulting in a directional reversal to the downside.
This commonly happens in a 3 phase interaction of price.
1. Buying pressure is absorbed quickly by sellers.
This PPO tool will calculate the trend of this absorption process.
2. After there is a notable Bullish Exhaustion of price action, the PPO tool will draw a trendline of this absorption showing us the potential future prices where aggressive sellers will want to step in at higher prices.
3. After lower highs are defined in the oscillator, you'll see prices react in a strong bearish pattern at this trendline where aggressive sellers stepped in to reverse price action to the downside.
Lower High and Higher Low Signals
When the oscillator signals Lower Highs or High Lows its only noting that momentum in that trend direction is slowing. THis indicates a coming pause in the market and the proceeding longs of an uptrend or shorts of a downtrend should be taken with caution.
**These LH and HL markers are not reading as divergences in price vs momentum.**
They are simply registering against the highs and lows of itself..
Moving Averages on Price Action
The Oscillator will cross over its ZERO level the same time your Short and Long MAs cross each other. This will indicate that the short term average trend is moving ahead of the long term.
Crossovers are not an entry signal. It's a method in determining you current timeframe trend strength. Always observe price action as it passes through each of your moving averages and compare it to the positioning and direction of the oscillator.
If price dips in between the moving averages while the oscillator still shows a strong trend strength, you can wait for price to move ahead of your fast moving average.
Bar Colors and Signal Line for Trend Strength
Good Bullish Trend = Oscillator above zero + Signal rising below Oscillator
Weak Bullish Trend = Oscillator above zero + Signal above Oscillator
Good Bearish Trend = Oscillator below zero + Signal falling above Oscillator
Weak Bearish Trend = Oscillator below zero + Signal below Oscillator
Bar Colors
Bars are colored to match Oscillator Momentum Strength. Colors are set by user.
Why alter the known PPO (Percentage Price Oscillator) in this manner?
The PPO tool is great for measuring the strength as percentage of price action over and average amount of candles however, with these changes,
you know have the ability to correlate:
Wycoff theory of supply and demand,
Measure the depth of reversals and pullback by price positioning against moving averages,
Project potential reversal and exhaustion pricing,
Visibly note the structure of momentum much like you would note market structure,
Its not enough to know there is momentum. Its better to know
A) Is it enough
B) Is there something in the way which will cause price to push back
C) Does this momentum correlate to the prevailing trend
Sector 50MA vs 200MA ComparisonThis TradingView indicator compares the 50-period Moving Average (50MA) and 200-period Moving Average (200MA) of a selected market sector or index, providing a visual and analytical tool to assess relative strength and trend direction. Here's a detailed breakdown of its functionality:
Purpose: The indicator plots the 50MA and 200MA of a chosen sector or index on a separate panel, highlighting their relationship to identify bullish (50MA > 200MA) or bearish (50MA < 200MA) trends. It also includes a histogram and threshold lines to gauge momentum and key levels.
Inputs:
Resolution: Allows users to select the timeframe for calculations (Daily, Weekly, or Monthly; default is Daily).
Sector Selection: Users can choose from a list of sectors or indices, including Tech, Financials, Consumer Discretionary, Utilities, Energy, Communication Services, Materials, Industrials, Health Care, Consumer Staples, Real Estate, S&P 500 Value, S&P 500 Growth, S&P 500, NASDAQ, Russell 2000, and S&P SmallCap 600. Each sector maps to specific ticker pairs for 50MA and 200MA data.
Data Retrieval:
The indicator fetches closing prices for the 50MA and 200MA of the selected sector using the request.security function, based on the chosen timeframe and ticker pairs.
Visual Elements:
Main Chart:
Plots the 50MA (blue line) and 200MA (red line) for the selected sector.
Fills the area between the 50MA and 200MA with green (when 50MA > 200MA, indicating bullishness) or red (when 50MA < 200MA, indicating bearishness).
Threshold Lines:
Horizontal lines at 0 (zero line), 20 (lower threshold), 50 (center), 80 (upper threshold), and 100 (upper limit) provide reference points for the 50MA's position.
Fills between 0-20 (green) and 80-100 (red) highlight key zones for potential overbought or oversold conditions.
Sector Information Table:
A table in the top-right corner displays the selected sector and its corresponding 50MA and 200MA ticker symbols for clarity.
Alerts:
Generates alert conditions for:
Bullish Crossover: When the 50MA crosses above the 200MA (indicating potential upward momentum).
Bearish Crossover: When the 50MA crosses below the 200MA (indicating potential downward momentum).
Use Case:
Traders can use this indicator to monitor the relative strength of a sector's short-term trend (50MA) against its long-term trend (200MA).
The visual fill between the moving averages and the threshold lines helps identify trend direction, momentum, and potential reversal points.
The sector selection feature allows for comparative analysis across different market segments, aiding in sector rotation strategies or market trend analysis.
This indicator is ideal for traders seeking to analyze sector performance, identify trend shifts, and make informed decisions based on moving average crossovers and momentum thresholds.
Volume Intelligence Suite (VIS) v2📊 Volume Intelligence Suite – Smart Volume, Smart Trading
The Volume Intelligence Suite is a powerful, all-in-one TradingView indicator designed to give traders deeper insight into market activity by visualizing volume behavior with price action context. Whether you're a scalper, day trader, or swing trader, this tool helps uncover hidden momentum, institutional activity, and potential reversals with precision.
🔍 Key Features:
Dynamic Volume Zones – Highlights high and low volume areas to spot accumulation/distribution ranges.
Volume Spikes Detector – Automatically marks abnormal volume bars signaling potential breakout or trap setups.
Smart Delta Highlighting – Compares bullish vs bearish volume in real time to reveal buyer/seller strength shifts.
Session-Based Volume Profiling – Breaks volume into key trading sessions (e.g., London, New York) for clearer context.
Volume Heatmap Overlay – Optional heatmap to show intensity and velocity of volume flow per candle.
Custom Alerts – Built-in alerts for volume surges, divergences, and exhaustion signals.
Optimized for Kill Zone Analysis – Pairs perfectly with ICT-style session strategies and Waqar Asim’s trading methods.
🧠 Why Use Volume Intelligence?
Most traders overlook the story behind each candle. Volume Intelligence Suite helps you "see the why behind the move" — exposing key areas of interest where smart money may be active. Instead of reacting late, this tool puts you in position to anticipate.
Use it to:
Validate breakouts
Detect fakeouts and liquidity grabs
Confirm bias during kill zones
Analyze volume divergence with price swings
⚙️ Fully Customizable:
From volume thresholds to visual styles and session timings, everything is user-adjustable to fit your market, timeframe, and strategy.
✅ Best For:
ICT/Smart Money Concepts (SMC) traders
Breakout & reversal traders
Kill zone session scalpers
Institutional footprint followers
MTF Stochastic RSIOverview: MTF Stochastic RSI
is a momentum-tracking tool that plots the Stochastic RSI oscillator for up to four user-
defined timeframes on a single panel. It provides a compact yet powerful view of how
momentum is aligning or diverging across different timeframes, making it suitable for both
scalpers and swing traders looking for multi-timeframe confirmation.
What it does:
Calculates Stochastic RSI values using the RSI of price as the base input and applies
smoothing for stability.
Aggregates and displays the values for four customizable TF (e.g., 5min, 15min, 1h, 4h).
Highlights potential support and resistance zones in the oscillator space using adaptive zone
logic.
Optionally draws dynamic support/resistance zone lines in the oscillator space based on
historical turning points.
How it works:
Each timeframe uses the same RSI and Stoch calculation settings but runs independently via
the request.security() function.
Stochastic RSI is calculated by first applying the RSI to price, then applying a stochastic
formula on the RSI values, and finally smoothing the %K output.
Adaptive overbought and oversold thresholds adjust based on ATR-based volatility and simple
trend filtering (e.g., price vs EMA).
When a crossover above the oversold zone or a crossunder below the overbought zone
occurs, the script checks for proximity to previously stored zones and either adjusts or
records a new one.
These zones are stored and re-plotted as dotted support/resistance levels within the
oscillator space.
What it’s based on:
The indicator builds upon traditional Stochastic RSI by applying it to multiple timeframes in
parallel.
Zone detection logic is inspired by the idea of oscillator-based support/resistance levels.
Volatility-adjusted thresholds are based on ATR (Average True Range) to make the
overbought/oversold zones responsive to market conditions.
How to use it:
Look for alignment across timeframes (e.g., all four curves pushing into the overbought
region suggests strong trend continuation).
Reversal risk increases when one or more higher timeframes are diverging or showing signs of
cooling while lower timeframes are still extended.
Use the zone lines as soft support/resistance references within the oscillator—retests of
these zones can indicate strong reversal opportunities or continuation confirmation.
This script is provided for educational and informational purposes only. It does not constitute financial advice, trading recommendations, or an offer to buy or sell any financial instrument. Always perform your own due diligence, use proper risk management, and consult a qualified financial professional before making any trading decisions. Past performance does not guarantee future results. Use this tool at your own discretion and risk.
Multi-Timeframe EMAs with Cross Alerts (Up & Down)📌 Indicator Name:
Multi-Timeframe EMAs with Cross Alerts (Up & Down)
🛠️ Core Features:
✅ 1. Multi-Timeframe EMA Display
The script calculates and displays 6 different Exponential Moving Averages (EMAs).
Each EMA has:
Custom length input (e.g., 9, 21, etc.).
Custom timeframe selection (e.g., 1H, 4H, 1D).
Custom color for easy identification on the chart.
✅ 2. EMA Visualization
Each of the six EMAs is plotted on the chart using the selected color and thickness.
They respond dynamically to different timeframes (current or higher/lower).
✅ 3. Cross Detection Logic
The script can detect crossover and crossunder between EMA pairs:
EMA 1 and EMA 2
EMA 3 and EMA 4
EMA 5 and EMA 6
(Optional: can be extended to other combinations.)
✅ 4. Alert Toggles
Users can enable or disable alerts for each pair independently:
Alert: EMA 1 crosses EMA 2
Alert: EMA 3 crosses EMA 4
Alert: EMA 5 crosses EMA 6
(You added an additional option for EMA 4 vs EMA 6 later.)
✅ 5. Visual Alert Markers
The script uses alert() function to send alert messages when:
An EMA crosses above another (crossover)
An EMA crosses below another (crossunder)
Alerts include clear icons like 🔼 and 🔽 in the messages.
🔔 Use Case Scenarios
Swing traders: Identify longer-term cross signals on higher timeframes.
Scalpers: Use lower-timeframe EMAs with fast alert reactions.
Multi-timeframe analysis: Spot alignment between trend-following EMAs across different periods.
✅ Bonus
Fully customizable — great for adapting to your own strategy, whether it's trend confirmation, re-entry signals, or early reversals
📌 اسم المؤشر:
المتوسطات المتحركة الأسية (EMA) متعددة الفريمات مع تنبيهات تقاطع صاعدة وهابطة
🛠️ الميزات الأساسية:
✅ 1. دعم متعدد للفريمات الزمنية
يقوم السكربت بحساب وعرض 6 متوسطات متحركة أسية (EMA) مختلفة.
يمكن تخصيص كل EMA من حيث:
الطول (مثل: 9، 21...).
الفريم الزمني (مثل: الساعة، الأربع ساعات، اليومي...).
اللون، لتسهيل التمييز بين الخطوط على الشارت.
✅ 2. عرض المتوسطات على الرسم البياني
يتم رسم كل من المتوسطات الستة باستخدام اللون والتنسيق الذي تختاره.
المتوسطات تتفاعل تلقائيًا مع التغييرات في الفريم الزمني.
✅ 3. كشف التقاطعات
يمكن للسكربت كشف تقاطعات (صعودًا أو هبوطًا) بين أزواج المتوسطات التالية:
EMA 1 و EMA 2
EMA 3 و EMA 4
EMA 5 و EMA 6
(ويمكنك إضافة المزيد مثل EMA 4 مع EMA 6 حسب الحاجة)
✅ 4. التحكم في التنبيهات
يمكن للمستخدم تفعيل أو تعطيل التنبيهات لكل زوج من المتوسطات على حدة:
تنبيه عند تقاطع EMA 1 و EMA 2
تنبيه عند تقاطع EMA 3 و EMA 4
تنبيه عند تقاطع EMA 5 و EMA 6
(وأي أزواج إضافية يتم إضافتها لاحقًا)
✅ 5. تنبيهات مرئية برسائل واضحة
السكربت يرسل تنبيهات عبر وظيفة alert() عند حدوث:
تقاطع صاعد (EMA يتقاطع من الأسفل إلى الأعلى).
تقاطع هابط (EMA يتقاطع من الأعلى إلى الأسفل).
التنبيه يحتوي على رموز توضيحية مثل 🔼 و 🔽 ليسهل قراءته.
🎯 مناسب لـ:
المتداولين المتأرجحين (Swing Traders): لاكتشاف تقاطعات على الفريمات الكبرى.
المضاربين (Scalpers): باستخدام EMA سريعة على فريمات صغيرة مع تنبيهات فورية.
محللي الفريمات المتعددة: لتأكيد الاتجاه أو الانعكاس بناءً على تقاطع متوسطات من فريمات مختلفة.
✅ مزايا إضافية:
قابل للتخصيص بشكل كامل حسب استراتيجيتك.
مناسب لعدة أساليب: تأكيد الترند، إعادة الدخول، أو إشارات الانعكاس المبكر.
[blackcat] L3 Ichimoku FusionCOMPREHENSIVE ANALYSIS OF THE L3 ICHIMOKU FUSION INDICATOR
🌐 Overview:
The L3 Ichimoku Fusion is a sophisticated multi-layered technical analysis tool integrating classic Japanese market forecasting techniques with enhanced dynamic elements designed specifically for identifying potential turning points in financial instruments' pricing action.
Key Purpose:
To provide traders with an intuitive yet powerful framework combining established ichimoku principles while incorporating additional validation checkpoints derived from cross-timeframe convergence studies.
THEORETICAL FOUNDATION EXPLAINED
🎓 Conceptual Background:
:
• Conversion & Base Lines tracking intermediate term averages
• Lagging Span providing delayed feedback mechanism
• Lead Spans projecting future equilibrium states
:
• Adaptive parameter scaling options
• Automated labeling system for critical junctures
• Real-time alert infrastructure enabling immediate response capability
PARAMETER CONFIGURATION GUIDE
⚙️ Input Parameters Explained In Detail:
Regional Setting Selection:**
→ Oriental Configuration: Standardized approach emphasizing slower oscillation cycles
→ Occidental Variation: Optimized settings reducing lag characteristics typical of original methodology
Multiplier Adjustment Functionality:**
↔ Allows fine-graining oscillator responsiveness without altering core relationship dynamics
↕ Enables adaptation to various instrument volatility profiles efficiently
Displacement Value Control:**
↓ Controls lead/lag offset positioning relative to current prices
↑ Provides flexibility in adjusting visual representation alignment preferences
DYNAMIC CALCULATION PROCESSES
💻 Algorithmic Foundation:
:
Utilizes highest/lowest extremes over specified lookback windows
Produces more responsive conversions compared to simple MAs
:
→ Confirms directional bias across multiple independent criteria
← Ensures higher probability outcomes reduce random noise influence
:
♾ Creates persistent annotations documenting significant events
🔄 Handles complex state transitions maintaining historical record integrity
VISUALIZATION COMPONENTS OVERVIEW
🎨 Display Architecture Details:
:
→ Solid colored trendlines representing conversion/base relationships
↑ Fill effect overlay differentiating expansion/compression phases
↔ Offset spans positioned according to calculated displacement values
:
→ Green shading indicates positive configuration scenarios
↘ Red filling highlights negative arrangement situations
⟳ Orange transition areas mark transitional periods requiring caution
:
✔️ LE: Long Entry opportunity confirmed
❌ SE: Short Setup validated
☑ XL/XS: Position closure triggers active
✓ RL/RS: Potential re-entry chances emerging
STRATEGIC APPLICATION FRAMEWORK
📋 Practical Deployment Guidelines:
Initial Integration Phase:
Select appropriate timeframe matching trading horizon preference
Configure input parameters aligning with target asset behavior traits
Test thoroughly under simulated conditions prior to live usage
Active Monitoring Procedures:
• Regular observation of cloud formation evolution
• Tracking label placements against actual price movements
• Noting pattern development leading up to signaled entry/exit moments
Decision Making Process Flowchart:
→ Identify clear breakout/crossover events exceeding confirmation thresholds
← Evaluate contextual factors supporting/rejecting indicated direction
↑ Execute trades only after achieving required number of confirming inputs
PERFORMANCE OPTIMIZATION TECHNIQUES
🚀 Refinement Strategies:
Calibration Optimization Approach:
→ Start testing with default suggested configurations
↓ Gradually adjust individual components observing outcome changes
↑ Document findings systematically building personalized version profile
Context Adaptability Methods:
➕ Add supplementary indicators enhancing overall reliability
➖ Remove unnecessary complexity layers if causing confusion
✨ Incorporate custom rules adapting to specific security behaviors
Efficiency Improvement Tactics:
🔧 Streamline redundant processing routines where possible
♻️ Leverage shared data streams whenever feasible
⚡ Optimize refresh frequencies balancing update speed vs computational load
RISK MITIGATION PROTOCOLS
🛡️ Safety Measures Implementation Guide:
Position Sizing Principles:
∅ Never exceed preset maximum exposure limits defined by risk tolerance
± Scale positions proportionally per account size/market capitalization
× Include slippage allowances within planning stages accounting for liquidity variations
Validation Requirements Hierarchy:
☐ Verify signals meet minimum number of concurrent validations
⛔ Ignore isolated occurrences lacking adequate evidence backing
▶ Look for convergent evidence strengthening conviction level
Emergency Response Planning:
↩ Establish predefined exit strategies including trailing stops mechanisms
🌀 Plan worst-case scenario responses ahead avoiding panic reactions
⇄ Maintain contingency plans addressing unexpected adverse developments
USER EXPERIENCE ENHANCEMENT FEATURES
🌟 Additional Utility Functions:
Alert System Infrastructure:
→ Automatic notifications delivered directly to user devices
↑ Message content customized explaining triggered condition specifics
↔ Timing optimization ensuring minimal missed opportunities due to latency issues
Historical Review Capability:
→ Ability to analyze past performance retrospectively
↓ Assess effectiveness across varying market regimes objectively
↗ Generate statistics measuring success/failure rates quantitatively
Community Collaboration Support:
↪ Share personal optimizations benefiting wider trader community
↔ Exchange experiences improving collective understanding base
✍️ Provide constructive feedback aiding ongoing refinement process
CONCLUSION AND NEXT STEPS
This comprehensive guide serves as your roadmap toward mastering the capabilities offered by the L3 Ichimoku Fusion indicator effectively. Success relies heavily on disciplined application combined with continuous learning and adjustment processes throughout implementation journey.
Wishing you prosperous trading endeavors! 👋💰
AP_Ultimate CCI MTF v5**AP Ultimate CCI Multi-Timeframe Indicator**
*Track Commodity Channel Index trends across multiple timeframes in one view!*
**Overview:**
Adapted from ChrisMoody's popular RSI MTF concept, this enhanced version brings powerful multi-timeframe analysis to the CCI indicator. Perfect for traders who want to confirm trends across different time horizons without switching charts.
**Key Features:**
📈 **Dual CCI Analysis**
- Primary CCI (Default: 1H) + Secondary CCI (Default: 4H)
- Fully customizable timeframes for both indicators
- Independent length settings (14-50 periods recommended)
🚦 **Visual Trading Signals**
- Automatic Buy/Sell markers on crossovers
- 🟢 **B** Signals: When CCI crosses above -100 (Oversold reversal)
- 🔴 **S** Signals: When CCI crosses below +100 (Overbought reversal)
- Clean triangular markers at chart edges for clear visibility
🎨 **Customizable Visuals**
- Adjustable overbought/oversold levels (Default: ±100)
- Background highlights for extreme zones
- Modern color schemes with transparency control
- Optional zero line display
⚙️ **Technical Specs**
- Built in Pine Script v6
- Non-repainting calculations
- Timeframe-aware alerts support
- Optimized for all asset classes
**How to Use (my use case):**
1. Apply to 15M-4H charts for intraday trading
2. Default setup: Compare 1H vs 4H CCI
3. Look for confluence between timeframes:
- Strong trend = Both CCIs moving in same direction
- Reversal signal = Crossovers with volume confirmation
4. Combine with price action or support/resistance
**Why this Indicator:**
✅ Eliminates manual timeframe switching
✅ Identifies hidden divergences between time horizons
✅ Works equally well for stocks, forex, and crypto
✅ Perfect for momentum and mean-reversion strategies
*Pro Tip: Pair with volume indicators and moving averages for enhanced confirmation!*
COT3 - Flip Strength Index - Invincible3This indicator uses the TradingView COT library to visualize institutional positioning and potential sentiment or trend shifts. It compares the long% vs short% of commercial and non-commercial traders for both Pair A and Pair B, helping traders identify trend strength, market overextension, and early reversal signals.
🔷 COT RSI
The COT RSI normalizes the net positioning difference between non-commercial and commercial traders over (N=13, 26, and 52)-week periods. It ranges from 0 to 100, highlighting when sentiment is at bullish or bearish extremes.
COT RSI (N)= ((NC - C)−min)/(max-min) x100
🟡 COT Index
The COT Index tracks where the current non-commercial net position lies within its 1-year and 3-year historical range. It reflects institutional accumulation or distribution phases.
Strength represents the magnitude of that positioning bias, visualized through normalized RSI-style metrics.
COT Index (N)= (NC net)/(max-min) x100
🔁 Flip Detection
Flip refers to the crossovers between long% and short%, indicating a change in directional bias among trader groups. When long positions exceed shorts (or vice versa), it signals a possible market flip in sentiment or trend.
For example, Pair B commercial flip is calculated as:
Long% = (Long/Open Interest)×100
Short% = (Short/Open Interest)×100
Flip = Long%−Short%
A bullish flip occurs when long% overtakes short%, and vice versa for a bearish flip. These flips often precede price trend changes or confirm sentiment breakouts.
Flip captures how far current positioning deviates from historical norms — highlighting periods of institutional overconfidence or exhaustion, often leading to significant market turns.
This combination offers a multi-layered edge for identifying when smart money is flipping direction, and whether that flip has strong conviction or is likely to fade.
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