Grid Tendence V1The “Grid Tendence V1” strategy is based on the classic Grid strategy, only in this case the entries and exits are made in favor of the trend, which allows to take advantage of large movements to maximize profits, since it is also possible to enter and exit with the balance with a controlled risk, because precisely the distance between each Grid works as a natural and adaptable stop loss and take profit. This fact helps to avoid overlapping entries and exits that would result from using stop loss and take profit as limit orders.
In this version of the script the entries and exits are always at market, and based on the percentage change of the price, not on the profit or loss of the current position.
The user will notice that the strategy setup is based on a controlled risk, risking 5% on each trade, a fairly standard commission and a modest initial capital, all this in order to protect the user of the strategy from unexpected or unrealistic results.
However, it is always recommended to optimize the parameters so that the strategy is effective for each asset and for each time frame.
Cerca negli script per "profit"
[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! ✨
Smart Fib StrategySmart Fibonacci Strategy
This advanced trading strategy combines the power of adaptive SMA entries with Fibonacci-based exit levels to create a comprehensive trend-following system that self-optimizes based on historical market conditions. Credit goes to Julien_Eche who created the "Best SMA Finder" which received an Editors Pick award.
Strategy Overview
The Smart Fibonacci Strategy employs a two-pronged approach to trading:
1. Intelligent Entries: Uses a self-optimizing SMA (Simple Moving Average) to identify optimal entry points. The system automatically tests multiple SMA lengths against historical data to determine which period provides the most robust trading signals.
2. Fibonacci-Based Exits: Implements ATR-adjusted Fibonacci bands to establish precise exit targets, with risk-management options ranging from conservative to aggressive.
This dual methodology creates a balanced system that adapts to changing market conditions while providing clear visual reference points for trade management.
Key Features
- **Self-Optimizing Entries**: Automatically calculates the most profitable SMA length based on historical performance
- **Adjustable Risk Parameters**: Choose between low-risk and high-risk exit targets
- **Directional Flexibility**: Trade long-only, short-only, or both directions
- **Visualization Tools**: Customizable display of entry lines and exit bands
- **Performance Statistics**: Comprehensive stats table showing key metrics
- **Smoothing Option**: Reduces noise in the Fibonacci bands for cleaner signals
Trading Rules
Entry Signals
- **Long Entry**: When price crosses above the blue center line (optimal SMA)
- **Short Entry**: When price crosses below the blue center line (optimal SMA)
### Exit Levels
- **Low Risk Option**: Exit at the first Fibonacci band (1.618 * ATR)
- **High Risk Option**: Exit at the second Fibonacci band (2.618 * ATR)
Strategy Parameters
Display Settings
- Toggle visibility of the stats table and indicator components
Strategy Settings
- Select trading direction (long, short, or both)
- Choose exit method (low risk or high risk)
- Set minimum trades threshold for SMA optimization
SMA Settings
- Option to use auto-optimized or fixed-length SMA
- Customize SMA length when using fixed option
Fibonacci Settings
- Adjust ATR period and SMA basis for Fibonacci bands
- Enable/disable smoothing function
- Customize Fibonacci ratio multipliers
Appearance Settings
- Modify colors, line widths, and transparency
Optimization Methodology
The strategy employs a sophisticated optimization algorithm that:
1. Tests multiple SMA lengths against historical data
2. Evaluates performance based on trade count, profit factor, and win rate
3. Calculates a "robustness score" that balances profitability with statistical significance
4. Selects the SMA length with the highest robustness score
This ensures that the strategy's entry signals are continuously adapting to the most effective parameters for current market conditions.
Risk Management
Position sizing is fixed at $2,000 per trade, allowing for consistent exposure across all trading setups. The Fibonacci-based exit system provides two distinct risk management approaches:
- **Conservative Approach**: Using the first Fibonacci band for exits produces more frequent but smaller wins
- **Aggressive Approach**: Using the second Fibonacci band allows for larger potential gains at the cost of increased volatility
Ideal Usage
This strategy is best suited for:
- Trending markets with clear directional moves
- Timeframes from 4H to Daily for most balanced results
- Instruments with moderate volatility (stocks, forex, commodities)
Traders can further enhance performance by combining this strategy with broader market analysis to confirm the prevailing trend direction.
[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!
Best SMA FinderThis script, Best SMA Finder, is a tool designed to identify the most robust simple moving average (SMA) length for a given chart, based on historical backtest performance. It evaluates hundreds of SMA values (from 10 to 1000) and selects the one that provides the best balance between profitability, consistency, and trade frequency.
What it does:
The script performs individual backtests for each SMA length using either "Long Only" or "Buy & Sell" logic, as selected by the user. For each tested SMA, it computes:
- Total number of trades
- Profit Factor (total profits / total losses)
- Win Rate
- A composite Robustness Score, which integrates Profit Factor, number of trades (log-scaled), and win rate.
Only SMA configurations that meet the user-defined minimum trade count are considered valid. Among all valid candidates, the script selects the SMA length with the highest robustness score and plots it on the chart.
How to use it:
- Choose the strategy type: "Long Only" or "Buy & Sell"
- Set the minimum trade count to filter out statistically irrelevant results
- Enable or disable the summary stats table (default: enabled)
The selected optimal SMA is plotted on the chart in blue. The optional table in the top-right corner shows the corresponding SMA length, trade count, Profit Factor, Win Rate, and Robustness Score for transparency.
Key Features:
- Exhaustive SMA optimization across 991 values
- Customizable trade direction and minimum trade filters
- In-chart visualization of results via table and plotted optimal SMA
- Uses a custom robustness formula to rank SMA lengths
Use cases:
Ideal for traders who want to backtest and auto-select a historically effective SMA without manual trial-and-error. Useful for swing and trend-following strategies across different timeframes.
📌 Limitations:
- Not a full trading strategy with position sizing or stop-loss logic
- Only one entry per direction at a time is allowed
- Designed for exploration and optimization, not as a ready-to-trade system
This script is open-source and built entirely from original code and logic. It does not replicate any closed-source script or reuse significant external open-source components.
MÈGAS ALGO : CNA (Cognitio Analysis) [INDICATOR]Overview
The CNA (Cognitio Analysis) is a comprehensive financial analysis tool designed to evaluate the overall health and potential of a market or company based on fundamental metrics. It aggregates data across five key metric groups—**Growth**, **Profitability**, **Cash Flow**, **Income**, and **Valuation**—to provide a final interpretation of market conditions. The indicator dynamically adapts to the selected fiscal period (Quarter, Year, or Trailing Twelve Months) and delivers insights into dominant trends and conflicting signals.
Key Features
1. Customizable Fiscal Period:
- Users can select between "Quarter", "Year", or "Trailing Twelve Months" (TTM) to analyze data for their desired timeframe.
2. Dynamic Table Visualization:
- Displays raw metric values, aggregated scores, and the final interpretation in an intuitive
table.
- Highlights the final interpretation with dynamic background colors (`color.teal` for bullish,
`color.red` for bearish, etc.).
3. Comprehensive Data Integration:
- Pulls financial data using TradingView's `request.financial()` function for metrics like
revenue, earnings, margins, and valuation ratios.
4. Normalization and Scoring:
- Normalizes data to create a consistent scoring system, ensuring accurate comparisons across
metrics.
How It Works
1. Metric Group Analysis
- Growth Metrics: Measures revenue growth, earnings per share (EPS) growth, and tax
efficiency.
- Profitability Metrics: Analyzes net profit margin, return on equity (ROE), and EBITDA margin.
- Cash Metrics: Assesses operating cash flow margin, free cash flow to operating cash flow
ratio, and cash flow coverage.
- Income Metrics: Examines gross profit margin, operating profit margin, and EBIT margin.
- Valuation Metrics: Evaluates price-to-earnings (P/E), price-to-sales (P/S), and enterprise
value-to-EBITDA (EV/EBITDA).
2. Dynamic Scoring System
- Metrics are normalized to ensure consistency across different scales.
- A geometric mean is used to calculate scores for each metric group, ensuring that all metrics
within a group contribute equally to the final score.
3. Dominant Trend Identification
- Scores from all five metric groups are aggregated to determine the **dominant trend** of the
market.
- The dominant trend is categorized as:
- Bullish: Strong fundamentals across most metrics.
- Bearish: Weak fundamentals across most metrics.
- Neutral: Balanced conditions with no clear direction.
- Unclear: Mixed signals dominate, requiring further monitoring.
4. Conflicting Signals Interpretation
- The indicator identifies scenarios where metrics conflict (e.g., high growth but low valuation).
- These conflicting signals provide nuanced insights into market conditions, highlighting rare opportunities or potential risks.
How to Use the Indicator
1. Select Fiscal Period:
- Choose between "FQ", "FY", or "TTM" to analyze data for the desired timeframe.
2. Review Metric Scores:
- Examine the scores for each metric group (Growth, Profitability, Cash, Income, Valuation) to
understand the underlying performance.
3. Interpret Final Output:
- The final interpretation provides a summary of the dominant trend and conflicting signals,
helping users make informed decisions.
4. Dynamic Coloring:
- Use the dynamic background colors in the table to quickly identify market sentiment
(bullish, bearish, neutral, or mixed).
Applications
- Identifying Opportunities:
- Look for bullish dominant trends combined with undervalued growth opportunities for
potential long positions.
- Avoiding Risks:
- Watch out for bearish dominant trends with overvaluation alerts to avoid potential losses.
- Monitoring Neutral Markets:
- Use the indicator to identify neutral markets and wait for clearer signals before making
decisions.
Conclusion
The CNA (Cognitio Analysis) is a powerful tool for traders and investors seeking to make informed decisions based on fundamental analysis. By combining detailed metric evaluations, dynamic scoring, and sentiment-based interpretations, this indicator provides a comprehensive view of market conditions. Whether you're identifying undervalued opportunities, avoiding overvalued risks, or monitoring neutral markets, this indicator equips you with the insights needed to navigate complex financial landscapes.
Please Note:
This indicator is provided for informational and educational purposes only. It is not financial advice, and it should not be considered a recommendation to buy, sell, or trade any financial instrument. Trading involves significant risks, including the potential loss of your entire investment. Always conduct your own research and consult with a licensed financial advisor before making any trading decisions.
The results and images provided are based on algorithms and historical/paid real-time market data but do not guarantee future results or accuracy. Use this tool at your own risk, and understand that past performance is not indicative of future outc
Heiken Ashi Supertrend ADXHeiken Ashi Supertrend ADX Indicator
Overview
This indicator combines the power of Heiken Ashi candles, Supertrend indicator, and ADX filter to identify strong trend movements across multiple timeframes. Designed primarily for the cryptocurrency market but adaptable to any tradable asset, this system focuses on capturing momentum in established trends while employing a sophisticated triple-layer stop loss mechanism to protect capital and secure profits.
Strategy Mechanics
Entry Signals
The strategy uses a unique blend of technical signals to identify high-probability trade entries:
Heiken Ashi Candles: Looks specifically for Heiken Ashi candles with minimal or no wicks, which signal strong momentum and trend continuation. These "full-bodied" candles represent periods where price moved decisively in one direction with minimal retracement. These are overlayed onto normal candes for more accuarte signalling and plotting
Supertrend Filter: Confirms the underlying trend direction using the Supertrend indicator (default factor: 3.0, ATR period: 10). Entries are aligned with the prevailing Supertrend direction.
ADX Filter (Optional) : Can be enabled to focus only on stronger trending conditions, filtering out choppy or ranging markets. When enabled, trades only trigger when ADX is above the specified threshold (default: 25).
Exit Signals
Positions are closed when either:
An opposing signal appears (Heiken Ashi candle with no wick in the opposite direction)
Any of the three stop loss mechanisms are triggered
Triple-Layer Stop Loss System
The strategy employs a sophisticated three-tier stop loss approach:
ATR Trailing Stop: Adapts to market volatility and locks in profits as the trend extends. This stop moves in the direction of the trade, capturing profit without exiting too early during normal price fluctuations.
Swing Point Stop: Uses natural market structure (recent highs/lows over a lookback period) to place stops at logical support/resistance levels, honoring the market's own rhythm.
Insurance Stop: A percentage-based safety net that protects against sudden adverse moves immediately after entry. This is particularly valuable when the swing point stop might be positioned too far from entry, providing immediate capital protection.
Optimization Features
Customizable Filters : All components (Supertrend, ADX) can be enabled/disabled to adapt to different market conditions
Adjustable Parameters : Fine-tune ATR periods, Supertrend factors, and ADX thresholds
Flexible Stop Loss Settings : Each of the three stop loss mechanisms can be individually enabled/disabled with customizable parameters
Best Practices for Implementation
[Recommended Timeframes : Works best on 4-hour charts and above, where trends develop more reliably
Market Conditions: Performs well across various market conditions due to the ADX filter's ability to identify meaningful trends
Performance Characteristics
When properly optimized, this has demonstrated profit factors exceeding 3 in backtesting. The approach typically produces generous winners while limiting losses through its multi-layered stop loss system. The ATR trailing stop is particularly effective at capturing extended trends, while the insurance stop provides immediate protection against adverse moves.
The visual components on the chart make it easy to follow the strategy's logic, with position status, entry prices, and current stop levels clearly displayed.
This indicator represents a complete trading system with clearly defined entry and exit rules, adaptive stop loss mechanisms, and built-in risk management through position sizing.
Heiken Ashi Supertrend ADX - StrategyHeiken Ashi Supertrend ADX Strategy
Overview
This strategy combines the power of Heiken Ashi candles, Supertrend indicator, and ADX filter to identify strong trend movements across multiple timeframes. Designed primarily for the cryptocurrency market but adaptable to any tradable asset, this system focuses on capturing momentum in established trends while employing a sophisticated triple-layer stop loss mechanism to protect capital and secure profits.
Strategy Mechanics
Entry Signals
The strategy uses a unique blend of technical signals to identify high-probability trade entries:
Heiken Ashi Candles: Looks specifically for Heiken Ashi candles with minimal or no wicks, which signal strong momentum and trend continuation. These "full-bodied" candles represent periods where price moved decisively in one direction with minimal retracement.
Supertrend Filter : Confirms the underlying trend direction using the Supertrend indicator (default factor: 3.0, ATR period: 10). Entries are aligned with the prevailing Supertrend direction.
ADX Filter (Optional) : Can be enabled to focus only on stronger trending conditions, filtering out choppy or ranging markets. When enabled, trades only trigger when ADX is above the specified threshold (default: 25).
Exit Signals
Positions are closed when either:
An opposing signal appears (Heiken Ashi candle with no wick in the opposite direction)
Any of the three stop loss mechanisms are triggered
Triple-Layer Stop Loss System
The strategy employs a sophisticated three-tier stop loss approach:
ATR Trailing Stop: Adapts to market volatility and locks in profits as the trend extends. This stop moves in the direction of the trade, capturing profit without exiting too early during normal price fluctuations.
Swing Point Stop : Uses natural market structure (recent highs/lows over a lookback period) to place stops at logical support/resistance levels, honoring the market's own rhythm.
Insurance Stop: A percentage-based safety net that protects against sudden adverse moves immediately after entry. This is particularly valuable when the swing point stop might be positioned too far from entry, providing immediate capital protection.
Optimization Features
Customizable Filters: All components (Supertrend, ADX) can be enabled/disabled to adapt to different market conditions
Adjustable Parameters: Fine-tune ATR periods, Supertrend factors, and ADX thresholds
Flexible Stop Loss Settings: Each of the three stop loss mechanisms can be individually enabled/disabled with customizable parameters
Best Practices for Implementation
Recommended Timeframes: Works best on 4-hour charts and above, where trends develop more reliably
Market Conditions: Performs well across various market conditions due to the ADX filter's ability to identify meaningful trends
Position Sizing: The strategy uses a percentage of equity approach (default: 3%) for position sizing
Performance Characteristics
When properly optimized, this strategy has demonstrated profit factors exceeding 3 in backtesting. The approach typically produces generous winners while limiting losses through its multi-layered stop loss system. The ATR trailing stop is particularly effective at capturing extended trends, while the insurance stop provides immediate protection against adverse moves.
The visual components on the chart make it easy to follow the strategy's logic, with position status, entry prices, and current stop levels clearly displayed.
This strategy represents a complete trading system with clearly defined entry and exit rules, adaptive stop loss mechanisms, and built-in risk management through position sizing.
DI+/- Cross Strategy with ATR SL and 2% TPDI+/- Cross Strategy with ATR Stop Loss and 2% Take Profit
📝 Script Description for Publishing:
This strategy is based on the directional movement of the market using the Average Directional Index (ADX) components — DI+ and DI- — to generate entry signals, with clearly defined risk and reward targets using ATR-based Stop Loss and Fixed Percentage Take Profit.
🔍 How it works:
Buy Signal: When DI+ crosses above 40, signaling strong bullish momentum.
Sell Signal: When DI- crosses above 40, indicating strong bearish momentum.
Stop Loss: Dynamically calculated using ATR × 1.5, to account for market volatility.
Take Profit: Fixed at 2% above/below the entry price, for consistent reward targeting.
🧠 Why it’s useful:
Combines momentum breakout logic with volatility-based risk management.
Works well on trending assets, especially when combined with higher timeframe filters.
Clean BUY and SELL visual labels make it easy to interpret and backtest.
✅ Tips for Use:
Use on assets with clear trends (e.g., major forex pairs, trending stocks, crypto).
Best on 30m – 4H timeframes, but can be customized.
Consider combining with other filters (e.g., EMA trend direction or Bollinger Bands) for even better accuracy.
RSI VWAP POC [Uncle Sam Trading]Category: Oscillators, Volume, Market Profile
Timeframe: Suitable for all timeframes
Markets: Crypto, Forex, Stocks, Commodities
Overview
The RSI VWAP POC indicator is a powerful and innovative oscillator that combines the Relative Strength Index (RSI), Volume-Weighted Average Price (VWAP), and Point of Control (POC) from market profile analysis. Designed to provide traders with clear, high-probability trading signals, this indicator helps you identify key market levels, spot overbought/oversold conditions, and time your entries and exits with precision. Whether you’re a day trader, swing trader, or scalper, this free tool adds significant value to your trading strategy by offering a unique blend of momentum, volume, and market profile insights.
How It Works
This indicator integrates three core components to deliver actionable insights:
RSI (Relative Strength Index): Measures momentum to identify overbought (above 70) and oversold (below 30) conditions, helping you anticipate potential reversals.
VWAP (Volume-Weighted Average Price): Calculates a volume-weighted price benchmark, which is used to compute a more accurate, volume-sensitive RSI. This ensures the indicator reflects true market dynamics.
POC (Point of Control): Derived from market profile analysis, the POC represents the price level with the highest traded volume in a session, acting as a critical support or resistance level.
The indicator plots a smoothed RSI based on VWAP, overlaid with market profile data on a user-defined higher timeframe (default: 4H). The POC is displayed as a red line, with aqua bars indicating the value area where the majority of trading volume occurred. When the RSI crosses the POC, the indicator generates clear buy and sell signals:
Strong Buy (SBU): RSI crosses above the POC in an oversold zone.
Strong Sell (SBD): RSI crosses below the POC in an overbought zone.
Additional features include:
Background colors to highlight bullish (green) or bearish (red) trends.
Shaded zones for overbought (70/60) and oversold (30/40) levels.
Customizable settings to fit your trading style and timeframe.
How This Indicator Adds Value
The RSI VWAP POC indicator offers several key benefits that enhance your trading performance:
High-Probability Signals: By combining RSI, VWAP, and POC, this indicator identifies trades at key market levels where price is likely to react, increasing your win rate.
Improved Timing: Clear buy and sell signals, such as ‘SBU’ and ‘SBD’, help you enter and exit trades at optimal points, maximizing profitability.
Risk Management: Overbought/oversold zones and trend confirmation via background colors help you avoid false signals, protecting your capital.
Versatility: Suitable for all markets (crypto, forex, stocks) and timeframes, making it a valuable tool for traders of all experience levels.
Time Efficiency: The indicator does the heavy lifting by analyzing momentum, volume, and market profile data, allowing you to focus on executing trades.
Real-World Performance Example: On a 1-hour Bitcoin chart with a 4-hour higher timeframe, this indicator identified a strong sell signal on April 6th at 12:00 ($82,000), leading to a 9% drop to $74,600. A subsequent strong buy signal on April 7th at 04:00 ($76,200) captured a 6% rise to $81,200 – a potential 25% profit with 5x leverage if exited at 5%.
How to Use
Add the Indicator: Search for “RSI VWAP POC ” in TradingView’s indicator library and add it to your chart.
Set Your Timeframe: The indicator works on any timeframe but is optimized for a 1-hour chart with a 4-hour higher timeframe (set in the settings).
Interpret Signals:
Look for ‘SBU’ (strong buy) labels when the RSI crosses above the POC in an oversold zone, indicating a potential buying opportunity.
Look for ‘SBD’ (strong sell) labels when the RSI crosses below the POC in an overbought zone, signaling a potential selling opportunity.
Use the background colors (green for bullish, red for bearish) to confirm the trend.
Combine with Your Strategy: Use the indicator alongside your existing analysis (e.g., support/resistance, candlestick patterns) for best results.
Settings and Customization
The indicator is highly customizable to suit your trading needs:
RSI Length (Default: 14): Adjust the sensitivity of the RSI. Use a shorter length (e.g., 10) for scalping, or a longer length (e.g., 20) for smoother signals.
EMA Smoothing Length (Default: 3): Smooths the RSI line. Increase to 5 or 7 for less choppy signals in volatile markets.
Higher Timeframe (Default: 240 minutes): Set to 240 (4 hours) for a 1-hour chart. Adjust based on your chart’s timeframe (e.g., 60 minutes for a 15-minute chart).
Value Area Percentage (Default: 100%): Defines the size of the value area around the POC. Lower to 70% for a tighter focus on key levels.
Overbought/Oversold Thresholds (Defaults: 70/30): Adjust these levels to match market conditions (e.g., 80/20 for trending markets).
Show POC Line (Default: True): Toggle the red POC line on or off.
Show Buy/Sell Signals: Enable ‘Show Strong Breakup Signals’ and ‘Show Strong Breakdown Signals’ to focus on high-probability trades.
Why Choose This Indicator?
The RSI VWAP POC indicator stands out by offering a unique combination of momentum, volume, and market profile analysis in a single, easy-to-use tool. It’s designed to help traders of all levels make informed decisions, reduce risk, and increase profitability. Whether you’re trading Bitcoin, forex pairs, or stocks, this indicator provides the clarity and precision you need to succeed.
Portfolio Monitor - DolphinTradeBot1️⃣ Overview
▪️This indicator unifies the value of all your investments—whether stocks, currencies, or cryptocurrencies—in your chosen currency. This tool not only provides a clear snapshot of your overall portfolio performance but also highlights the individual growth of each asset with intuitive visualizations and an easy-to-understand performance report.
2️⃣ What sets this indicator apart
▪️is its ability to convert values from various currency pairs into any currency you choose. This means you can monitor your portfolio's performance against any currency pair you prefer, offering a flexible and comprehensive view of your investments.
3️⃣ How Is It Work ?
🔍The indicator can be analyzed under two main categories: visual representations and tables.
1- Visual representations ;
The indicator includes three different types of lines:
1. 1 - Reference Line → This represents the cost of all assets we hold, based on the selected date.
1. 2 - Total Assets Line → Displays the real-time value of all assets in our possession, including cash value, in the selected trading pair.
The area between the reference line is filled with green and red. The section above the reference line is represented in green, while the section below is shown in red.
1. 3 - Performance Lines → These visualize the performance of the assets, starting from the reference line and taking into account their weights in the portfolio. (Note: The lines are scaled for visualization purposes, so their absolute values should not be considered.)
"The names of the lines are shown in the image below."⤵️
2- Tables
The indicator includes three different types of tables:
2. 1 - Analysis Table : It provides a superficial overview of wallet statistics and values.
▪️TOTAL ASSETS → The current equivalent of all assets in the target currency
▪️CASH VALUE → The current value of the amount "Cash Value", in the target currency.
▪️PORTFOLIO VALUE → The total value of assets excluding Cash, in the target currency.
▪️POSTFOLIO COST → The cost of assets excluding Cash, in the target currency.
▪️PORTFOLIO ABSOLUTE RETURN → It shows the profit or loss relative to the cost of assets
▪️PORTFOLIO RETURN % →It shows the profit or loss relative to the cost of assets on a percentage basis
2. 2 - Performance Table : It displays the names of assets excluding Cash and their profit amounts, sorted from highest to lowest profit. If "Show as Percentage" is selected in the settings, it shows the percentage profit or loss relative to the cost. Profits are represented in green, while losses are represented in red.
"You can see the visual showing the tables below"⤵️
4️⃣How to Use ?
1- Choose the date on which the visualization will begin (📌The start date only affects the exchange rate used for calculating the reference line in the target currency.)
2- If you have cash holdings, enter the amount and specify the currency.
3- Select the currency in which your portfolio value will be displayed.(Default value is USD)
4- To set up your portfolio;
SYMBOLS - QUANTITY - PURCHASE PRICE
Enter the symbols of your assets - the number of units you hold - and their cost levels.
5- If you have cash, be sure to include your cash balance. If you also hold other currencies, enter them as separate assets with their corresponding quantities and purchase prices.
6- If you want to see the percentage returns of the assets in the performance table relative to their cost, select the "Show as Percent" option.
7- If you want to see the performance visuals of the assets, click on the "Show Asset Performance" option.
You can find an image of the settings section where the numbers above are used as references below.⤵️
📌 NOTE → By default, a few assets and their values have been pre-added in the initial settings. This is to ensure that you don’t see an empty screen when adding the indicator to the chart. Please remember to enter your own assets and values. The default settings are only provided as an example.
AI Trend Momentum SniperThe AI Trend Momentum Sniper is a powerful technical analysis tool designed for day trading. This strategy combines multiple momentum and trend indicators to identify high-probability entry and exit points. The indicator utilizes a combination of Supertrend, MACD, RSI, ATR (Average True Range), and On-Balance Volume (OBV) to generate real-time signals for buy and sell opportunities.
Key Features:
Supertrend for detecting market direction (bullish or bearish).
MACD for momentum confirmation, highlighting changes in market momentum.
RSI to filter out overbought/oversold conditions and ensure high-quality trades.
ATR as a volatility filter to adjust for changing market conditions.
OBV (On-Balance Volume) to confirm volume strength and trend validity.
Dynamic Stop-Loss & Take-Profit based on ATR to manage risk and lock profits.
This indicator is tailored for intraday traders looking for quick market moves, especially in volatile and high liquidity assets like Bitcoin (BTC) and Ethereum (ETH). It helps traders capture short-term trends with efficient risk management tools.
How to Apply:
Set Your Chart: Apply the AI Trend Momentum Sniper to a 5-minute (M5) or 15-minute (M15) chart for optimal performance.
Buy Signal: When the indicator generates a green arrow below the bar, it indicates a buy signal based on positive trend and momentum alignment.
Sell Signal: A red arrow above the bar signals a sell condition when the trend and momentum shift bearish.
Stop-Loss and Take-Profit: The indicator automatically calculates dynamic stop-loss and take-profit levels based on the ATR value for each trade, ensuring proper risk management.
Alerts: Set up custom alerts for buy or sell signals, and get notified instantly when opportunities arise.
Best Markets for Use:
BTC/USDT, ETH/USDT – High liquidity and volatility.
Major altcoins with sufficient volume.
Avoid using it on low-liquidity assets where price action may become erratic.
Timeframes:
This indicator is best suited for lower timeframes (5-minute to 15-minute charts) to capture quick price movements in trending markets.
IU Bigger than range strategyDESCRIPTION
IU Bigger Than Range Strategy is designed to capture breakout opportunities by identifying candles that are significantly larger than the previous range. It dynamically calculates the high and low of the last N candles and enters trades when the current candle's range exceeds the previous range. The strategy includes multiple stop-loss methods (Previous High/Low, ATR, Swing High/Low) and automatically manages take-profit and stop-loss levels based on user-defined risk-to-reward ratios. This versatile strategy is optimized for higher timeframes and assets like BTC but can be fine-tuned for different instruments and intervals.
USER INPUTS:
Look back Length: Number of candles to calculate the high-low range. Default is 22.
Risk to Reward: Sets the target reward relative to the stop-loss distance. Default is 3.
Stop Loss Method: Choose between:(Default is "Previous High/Low")
- Previous High/Low
- ATR (Average True Range)
- Swing High/Low
ATR Length: Defines the length for ATR calculation (only applicable when ATR is selected as the stop-loss method) (Default is 14).
ATR Factor: Multiplier applied to the ATR to determine stop-loss distance(Default is 2).
Swing High/Low Length: Specifies the length for identifying swing points (only applicable when Swing High/Low is selected as the stop-loss method).(Default is 2)
LONG CONDITION:
The current candle’s range (absolute difference between open and close) is greater than the previous range.
The closing price is higher than the opening price (bullish candle).
SHORT CONDITIONS:
The current candle’s range exceeds the previous range.
The closing price is lower than the opening price (bearish candle).
LONG EXIT:
Stop-loss:
- Previous Low
- ATR-based trailing stop
- Recent Swing Low
Take-profit:
- Defined by the Risk-to-Reward ratio (default 3x the stop-loss distance).
SHORT EXIT:
Stop-loss:
- Previous High
- ATR-based trailing stop
- Recent Swing High
Take-profit:
- Defined by the Risk-to-Reward ratio (default 3x the stop-loss distance).
ALERTS:
Long Entry Triggered
Short Entry Triggered
WHY IT IS UNIQUE:
This strategy dynamically adapts to different market conditions by identifying candles that exceed the previous range, ensuring that it only enters trades during strong breakout scenarios.
Multiple stop-loss methods provide flexibility for different trading styles and risk profiles.
The visual representation of stop-loss and take-profit levels with color-coded plots improves trade monitoring and decision-making.
HOW USERS CAN BENEFIT FROM IT:
Ideal for breakout traders looking to capitalize on momentum-driven price moves.
Provides flexibility to customize stop-loss methods and fine-tune risk management parameters.
Helps minimize drawdowns with a strong risk-to-reward framework while maximizing profit potential.
Liquidity + Internal Market Shift StrategyLiquidity + Internal Market Shift Strategy
This strategy combines liquidity zone analysis with the internal market structure, aiming to identify high-probability entry points. It uses key liquidity levels (local highs and lows) to track the price's interaction with significant market levels and then employs internal market shifts to trigger trades.
Key Features:
Internal Shift Logic: Instead of relying on traditional candlestick patterns like engulfing candles, this strategy utilizes internal market shifts. A bullish shift occurs when the price breaks previous bearish levels, and a bearish shift happens when the price breaks previous bullish levels, indicating a change in market direction.
Liquidity Zones: The strategy dynamically identifies key liquidity zones (local highs and lows) to detect potential reversal points and prevent trades in weak market conditions.
Mode Options: You can choose to run the strategy in "Both," "Bullish Only," or "Bearish Only" modes, allowing for flexibility based on market conditions.
Stop-Loss and Take-Profit: Customizable stop-loss and take-profit levels are integrated to manage risk and lock in profits.
Time Range Control: You can specify the time range for trading, ensuring the strategy only operates during the desired period.
This strategy is ideal for traders who want to combine liquidity analysis with internal structure shifts for precise market entries and exits.
This description clearly outlines the strategy's logic, the flexibility it provides, and how it works. You can adjust it further to match your personal trading style or preferences!
Pivot Point Calculator PPC V2 by [KhedrFx]📈 Trade Smarter with the Pivot Point Calculator (PPC) by KhedrFx
Want to spot key price levels and make better trading decisions? The Pivot Point Calculator (PPC) by KhedrFx is your go-to TradingView tool for identifying potential support and resistance zones. Whether you’re a Scalper trader, day trader, swing trader, or long-term investor, this script helps you plan precise entries and exits with confidence.
🔹 How to Use Pivot Points in Trading
📊 Step 1: Identify Key Levels
The PPC automatically plots:
Pivot Point (P): The main level where sentiment shifts between bullish and bearish.
Support Levels (S1, S2, S3): Areas where price may bounce higher.
Resistance Levels (R1, R2, R3): Areas where price may face selling pressure.
These levels act as dynamic price zones, helping you anticipate potential market movements.
🔥 Step 2: Choose Your Trading Strategy
1️⃣ Breakout Trading
Buy when the price breaks above the pivot point (P) with strong momentum.
Sell when the price drops below the pivot point (P) with strong momentum.
Use R1, R2, or R3 as profit targets in an uptrend and S1, S2, or S3 in a downtrend.
2️⃣ Reversal (Bounce) Trading
Buy when the price pulls back to S1, S2, or S3 and shows bullish confirmation (e.g., candlestick patterns like a bullish engulfing or hammer).
Sell when the price rallies to R1, R2, or R3 and shows bearish confirmation (e.g., rejection wicks or a bearish engulfing pattern).
🎯 Step 3: Set Smart Stop-Loss & Take-Profit Levels
Stop-Loss: Place it slightly below support (for buy trades) or above resistance (for sell trades).
Take-Profit: Use the next pivot level as a target.
Extreme Zones: R3 and S3 often signal strong reversals or breakouts—watch them closely!
🚀 How to Get Started
1️⃣ Add the PPC script to your TradingView chart.
2️⃣ Choose a timeframe that fits your strategy (5m, 15m, 30m, 1H, 4H, Daily, or Weekly).
3️⃣ Use the pivot points and support/resistance levels to fine-tune your trade entries, exits, and risk management.
⚠️ Trade Responsibly
This tool helps you analyze the market, but it’s not a guarantee of profits. Always do your own research, manage risk, and trade with caution.
💡 Ready to take your trading to the next level? Try the Pivot Point Calculator (PPC) by KhedrFx and start trading with confidence today! 🚀
IU BBB(Big Body Bar) StrategyDESCRIPTION
The IU BBB (Big Body Bar) Strategy is a price action-based trading strategy that identifies high-momentum candles with significantly larger body sizes compared to the average. It enters trades when a strong bullish or bearish move occurs and manages risk using an ATR-based trailing stop-loss system.
USER INPUTS:
- Big Body Threshold – Defines how many times larger the candle body should be compared to the average body ( default is 4 ).
- ATR Length – The period for the Average True Range (ATR) used in the trailing stop-loss calculation ( default is 14 ).
- ATR Factor – Multiplier for ATR to determine the trailing stop distance ( default is 2 ).
LONG CONDITION:
- The current candle’s body is greater than the average body size multiplied by the Big Body Threshold.
- The closing price is higher than the opening price (bullish candle).
SHORT CONDITION:
- The current candle’s body is greater than the average body size multiplied by the Big Body Threshold.
- The closing price is lower than the opening price (bearish candle).
LONG EXIT:
- ATR-based trailing stop-loss dynamically adjusts, locking in profits as the price moves higher.
SHORT EXIT:
- ATR-based trailing stop-loss dynamically adjusts, securing profits as the price moves lower.
WHY IT IS UNIQUE:
- Unlike traditional momentum strategies, this system adapts to volatility by filtering trades based on relative candle size.
- It incorporates an ATR-based trailing stop-loss, ensuring risk management and profit protection.
- The strategy avoids choppy market conditions by only trading when significant momentum is present.
HOW USERS CAN BENEFIT FROM IT:
- Catch Strong Price Moves – The strategy helps traders enter trades when the market shows decisive momentum.
- Effective Risk Management – The ATR-based trailing stop ensures that winning trades remain profitable.
- Works Across Markets – Can be applied to stocks, forex, crypto, and indices with proper optimization.
- Fully Customizable – Users can adjust sensitivity settings to match their trading style and time frame.
Simple APF Strategy Backtesting [The Quant Science]Simple backtesting strategy for the quantitative indicator Autocorrelation Price Forecasting. This is a Buy & Sell strategy that operates exclusively with long orders. It opens long positions and generates profit based on the future price forecast provided by the indicator. It's particularly suitable for trend-following trading strategies or directional markets with an established trend.
Main functions
1. Cycle Detection: Utilize autocorrelation to identify repetitive market behaviors and cycles.
2. Forecasting for Backtesting: Simulate trades and assess the profitability of various strategies based on future price predictions.
Logic
The strategy works as follow:
Entry Condition: Go long if the hypothetical gain exceeds the threshold gain (configurable by user interface).
Position Management: Sets a take-profit level based on the future price.
Position Sizing: Automatically calculates the order size as a percentage of the equity.
No Stop-Loss: this strategy doesn't includes any stop loss.
Example Use Case
A trader analyzes a dayli period using 7 historical bars for autocorrelation.
Sets a threshold gain of 20 points using a 5% of the equity for each trade.
Evaluates the effectiveness of a long-only strategy in this period to assess its profitability and risk-adjusted performance.
User Interface
Length: Set the length of the data used in the autocorrelation price forecasting model.
Thresold Gain: Minimum value to be considered for opening trades based on future price forecast.
Order Size: percentage size of the equity used for each single trade.
Strategy Limit
This strategy does not use a stop loss. If the price continues to drop and the future price forecast is incorrect, the trader may incur a loss or have their capital locked in the losing trade.
Disclaimer!
This is a simple template. Use the code as a starting point rather than a finished solution. The script does not include important parameters, so use it solely for educational purposes or as a boilerplate.
FVG Breakout Lite by tradingbauhausExplanation of "FVG Breakout Lite by tradingbauhaus"
This script is a trading strategy built for TradingView that helps you spot and trade "Fair Value Gaps" (FVGs)—price areas where the market moved quickly, leaving a gap that might act as support or resistance later. It’s designed to catch breakout opportunities when the price moves strongly in one direction, with extra filters to make trades more reliable. Here’s how it works and how you can use it:
What It Does
1. Finds Fair Value Gaps (FVGs):
A "Bullish FVG" happens when the price jumps up quickly, leaving a gap below where it didn’t trade much (e.g., today’s low is higher than the high from two bars ago).
A "Bearish FVG" is the opposite: the price drops fast, leaving a gap above (e.g., today’s high is lower than the low from two bars ago).
The script draws colored boxes on your chart to show these gaps: green for bullish, red for bearish.
2. Spots Breakouts:
It looks for "strong" FVGs by comparing them to a trend (based on the highest highs and lowest lows over a set period).
If a bullish gap forms above the recent highs, or a bearish gap below the recent lows, it’s marked as a breakout opportunity.
3. Adds a Volume Check:
Trades only happen if the market’s volume is higher than usual (e.g., 1.2x the average volume over the last 20 bars). This helps ensure the breakout has real momentum behind it.
4. Trades Automatically:
Long Trades (Buy): If a bullish breakout FVG forms and volume is high, it buys at the current price.
Short Trades (Sell): If a bearish breakout FVG forms with high volume, it sells short.
Each trade comes with a stop loss (to limit losses) and a take profit (to lock in gains), both adjustable by you.
5. Shows Mitigation Lines (Optional):
If you turn on "Display Mitigation Zones," it draws lines at the edge of each breakout FVG. These lines show where the price might return to "fill" the gap later, helping you see key levels.
6. Includes Webull Costs:
The script factors in real trading fees from Webull, like tiny SEC and FINRA fees for selling, and a daily margin cost if you’re borrowing money to trade. These don’t show up on the chart but affect the strategy’s performance in backtesting.
How to Use It
1. Add to Your Chart:
Copy the script into TradingView’s Pine Editor, click "Add to Chart," and it’ll start drawing FVGs and running the strategy.
2. Customize Settings:
Trend Period (Default: 25): How many bars it looks back to define the trend. Longer periods mean fewer but stronger signals.
Volume Lookback (Default: 20) & Volume Threshold (Default: 1.2): Adjust how it measures "high volume." Increase the threshold for stricter trades.
Stop Loss % (Default: 1.5%) & Take Profit % (Default: 3%): Set how much you’re willing to lose or aim to gain per trade.
Margin Rate % (Default: 8.74%): Webull’s rate for borrowing money—lower it if your account qualifies for a better rate.
Display Mitigation Zones (Default: On): Toggle this to see or hide the gap lines.
Colors: Change the green (bullish) and red (bearish) shades to suit your chart.
3. Backtest It:
Go to the "Strategy Tester" tab in TradingView to see how it performs on past data. It’ll show trades, profits, losses, and Webull fees included.
4. Watch It Work:
Green boxes mean bullish FVGs; red boxes mean bearish FVGs. If volume spikes and the price breaks out, you’ll see trades happen automatically.
What to Expect
Visuals: You’ll see colored boxes for FVGs and optional lines showing where they start. These help you spot key price zones even if you’re not trading.
Trades: It’s selective—only trades when FVGs align with a breakout and volume confirms it. Expect fewer trades but with higher potential.
Risk: The stop loss keeps losses in check, while the take profit aims for a 2:1 reward-to-risk ratio by default (3% gain vs. 1.5% loss).
Costs: Webull’s fees are small but baked into the results, so you’re seeing a realistic picture of profits.
Tips for Users
Test it on a small timeframe (like 5-minute charts) for day trading or a larger one (like daily) for swing trading.
Play with the volume threshold—if you get too few trades, lower it (e.g., 1.1); if too many, raise it (e.g., 1.5).
Watch how price reacts to the mitigation lines—they’re often support or resistance zones traders target.
This strategy is lightweight, focused, and built for traders who like breakouts with a bit of confirmation. It’s not foolproof (no strategy is!), but it gives you a clear way to trade FVGs with some smart filters.
Aggressive Strategy for High IV Market### Strategic background
In a volatile high IV market, prices are volatile and market expectations of future uncertainty are high. This environment provides opportunities for aggressive trading strategies, but also comes with a high level of risk. In pursuit of a high Sharpe ratio (i.e., risk-adjusted return), we need to design a strategy that captures the benefits of market volatility while effectively controlling risk. Based on daily line cycles, I choose a combination of trend tracking and volatility filtering for highly volatile assets such as stocks, futures or cryptocurrencies.
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### Strategy framework
#### Data
- Use daily data, including opening, closing, high and low prices.
- Suitable for highly volatile markets such as technology stocks, cryptocurrencies or volatile index futures.
#### Core indicators
1. ** Trend Indicators ** :
Fast Exponential Moving Average (EMA_fast) : 10-day EMA, used to capture short-term trends.
- Slow Exponential Moving Average (EMA_slow) : 30-day EMA, used to determine the long-term trend.
2. ** Volatility Indicators ** :
Average true Volatility (ATR) : 14-day ATR, used to measure market volatility.
- ATR mean (ATR_mean) : A simple moving average of the 20-day ATR that serves as a volatility benchmark.
- ATR standard deviation (ATR_std) : The standard deviation of the 20-day ATR, which is used to judge extreme changes in volatility.
#### Trading logic
The strategy is based on a trend following approach of double moving averages and filters volatility through ATR indicators, ensuring that trading only in a high-volatility environment is in line with aggressive and high sharpe ratio goals.
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### Entry and exit conditions
#### Admission conditions
- ** Multiple entry ** :
- EMA_fast Crosses EMA_slow (gold cross), indicating that the short-term trend is turning upward.
-ATR > ATR_mean + 1 * ATR_std indicates that the current volatility is above average and the market is in a state of high volatility.
- ** Short Entry ** :
- EMA_fast Crosses EMA_slow (dead cross) downward, indicating that the short-term trend turns downward.
-ATR > ATR_mean + 1 * ATR_std, confirming high volatility.
#### Appearance conditions
- ** Long show ** :
- EMA_fast Enters the EMA_slow (dead cross) downward, and the trend reverses.
- or ATR < ATR_mean-1 * ATR_std, volatility decreases significantly and the market calms down.
- ** Bear out ** :
- EMA_fast Crosses the EMA_slow (gold cross) on the top, and the trend reverses.
- or ATR < ATR_mean-1 * ATR_std, the volatility is reduced.
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### Risk management
To control the high risk associated with aggressive strategies, set up the following mechanisms:
1. ** Stop loss ** :
- Long: Entry price - 2 * ATR.
- Short: Entry price + 2 * ATR.
- Dynamic stop loss based on ATR can adapt to market volatility changes.
2. ** Stop profit ** :
- Fixed profit target can be selected (e.g. entry price ± 4 * ATR).
- Or use trailing stop losses to lock in profits following price movements.
3. ** Location Management ** :
- Reduce positions appropriately in times of high volatility, such as dynamically adjusting position size according to ATR, ensuring that the risk of a single trade does not exceed 1%-2% of the account capital.
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### Strategy features
- ** Aggressiveness ** : By trading only in a high ATR environment, the strategy takes full advantage of market volatility and pursues greater returns.
- ** High Sharpe ratio potential ** : Trend tracking combined with volatility filtering to avoid ineffective trades during periods of low volatility and improve the ratio of return to risk.
- ** Daily line Cycle ** : Based on daily line data, suitable for traders who operate frequently but are not too complex.
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### Implementation steps
1. ** Data Preparation ** :
- Get the daily data of the target asset.
- Calculate EMA_fast (10 days), EMA_slow (30 days), ATR (14 days), ATR_mean (20 days), and ATR_std (20 days).
2. ** Signal generation ** :
- Check EMA cross signals and ATR conditions daily to generate long/short signals.
3. ** Execute trades ** :
- Enter according to the signal, set stop loss and profit.
- Monitor exit conditions and close positions in time.
4. ** Backtest and Optimization ** :
- Use historical data to backtest strategies to evaluate Sharpe ratios, maximum retracements, and win rates.
- Optimize parameters such as EMA period and ATR threshold to improve policy performance.
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### Precautions
- ** Trading costs ** : Highly volatile markets may result in frequent trading, and the impact of fees and slippage on earnings needs to be considered.
- ** Risk Control ** : Aggressive strategies may face large retracements and need to strictly implement stop losses.
- ** Scalability ** : Additional metrics (such as volume or VIX) can be added to enhance strategy robustness, or combined with machine learning to predict trends and volatility.
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### Summary
This is a trend following strategy based on dual moving averages and ATR, designed for volatile high IV markets. By entering into high volatility and exiting into low volatility, the strategy combines aggressive and risk-adjusted returns for traders seeking a high sharpe ratio. It is recommended to fully backtest before implementation and adjust the parameters according to the specific market.
ADX for BTC [PineIndicators]The ADX Strategy for BTC is a trend-following system that uses the Average Directional Index (ADX) to determine market strength and momentum shifts. Designed for Bitcoin trading, this strategy applies a customizable ADX threshold to confirm trend signals and optionally filters entries using a Simple Moving Average (SMA). The system features automated entry and exit conditions, dynamic trade visualization, and built-in trade tracking for historical performance analysis.
⚙️ Core Strategy Components
1️⃣ Average Directional Index (ADX) Calculation
The ADX indicator measures trend strength without indicating direction. It is derived from the Positive Directional Movement (+DI) and Negative Directional Movement (-DI):
+DI (Positive Directional Index): Measures upward price movement.
-DI (Negative Directional Index): Measures downward price movement.
ADX Value: Higher values indicate stronger trends, regardless of direction.
This strategy uses a default ADX length of 14 to smooth out short-term fluctuations while detecting sustainable trends.
2️⃣ SMA Filter (Optional Trend Confirmation)
The strategy includes a 200-period SMA filter to validate trend direction before entering trades. If enabled:
✅ Long Entry is only allowed when price is above a long-term SMA multiplier (5x the standard SMA length).
✅ If disabled, the strategy only considers the ADX crossover threshold for trade entries.
This filter helps reduce entries in sideways or weak-trend conditions, improving signal reliability.
📌 Trade Logic & Conditions
🔹 Long Entry Conditions
A buy signal is triggered when:
✅ ADX crosses above the threshold (default = 14), indicating a strengthening trend.
✅ (If SMA filter is enabled) Price is above the long-term SMA multiplier.
🔻 Exit Conditions
A position is closed when:
✅ ADX crosses below the stop threshold (default = 45), signaling trend weakening.
By adjusting the entry and exit ADX levels, traders can fine-tune sensitivity to trend changes.
📏 Trade Visualization & Tracking
Trade Markers
"Buy" label (▲) appears when a long position is opened.
"Close" label (▼) appears when a position is exited.
Trade History Boxes
Green if a trade is profitable.
Red if a trade closes at a loss.
Trend Tracking Lines
Horizontal lines mark entry and exit prices.
A filled trade box visually represents trade duration and profitability.
These elements provide clear visual insights into trade execution and performance.
⚡ How to Use This Strategy
1️⃣ Apply the script to a BTC chart in TradingView.
2️⃣ Adjust ADX entry/exit levels based on trend sensitivity.
3️⃣ Enable or disable the SMA filter for trend confirmation.
4️⃣ Backtest performance to analyze historical trade execution.
5️⃣ Monitor trade markers and history boxes for real-time trend insights.
This strategy is designed for trend traders looking to capture high-momentum market conditions while filtering out weak trends.
MACD Volume Strategy for XAUUSD (15m) [PineIndicators]The MACD Volume Strategy is a momentum-based trading system designed for XAUUSD on the 15-minute timeframe. It integrates two key market indicators: the Moving Average Convergence Divergence (MACD) and a volume-based oscillator to identify strong trend shifts and confirm trade opportunities. This strategy uses dynamic position sizing, incorporates leverage customization, and applies structured entry and exit conditions to improve risk management.
⚙️ Core Strategy Components
1️⃣ Volume-Based Momentum Calculation
The strategy includes a custom volume oscillator to filter trade signals based on market activity. The oscillator is derived from the difference between short-term and long-term volume trends using Exponential Moving Averages (EMAs)
Short EMA (default = 5) represents recent volume activity.
Long EMA (default = 8) captures broader volume trends.
Positive values indicate rising volume, supporting momentum-based trades.
Negative values suggest weak market activity, reducing signal reliability.
By requiring positive oscillator values, the strategy ensures momentum confirmation before entering trades.
2️⃣ MACD Trend Confirmation
The strategy uses the MACD indicator as a trend filter. The MACD is calculated as:
Fast EMA (16-period) detects short-term price trends.
Slow EMA (26-period) smooths out price fluctuations to define the overall trend.
Signal Line (9-period EMA) helps identify crossovers, signaling potential trend shifts.
Histogram (MACD – Signal) visualizes trend strength.
The system generates trade signals based on MACD crossovers around the zero line, confirming bullish or bearish trend shifts.
📌 Trade Logic & Conditions
🔹 Long Entry Conditions
A buy signal is triggered when all the following conditions are met:
✅ MACD crosses above 0, signaling bullish momentum.
✅ Volume oscillator is positive, confirming increased trading activity.
✅ Current volume is at least 50% of the previous candle’s volume, ensuring market participation.
🔻 Short Entry Conditions
A sell signal is generated when:
✅ MACD crosses below 0, indicating bearish momentum.
✅ Volume oscillator is positive, ensuring market activity is sufficient.
✅ Current volume is less than 50% of the previous candle’s volume, showing decreasing participation.
This multi-factor approach filters out weak or false signals, ensuring that trades align with both momentum and volume dynamics.
📏 Position Sizing & Leverage
Dynamic Position Calculation:
Qty = strategy.equity × leverage / close price
Leverage: Customizable (default = 1x), allowing traders to adjust risk exposure.
Adaptive Sizing: The strategy scales position sizes based on account equity and market price.
Slippage & Commission: Built-in slippage (2 points) and commission (0.01%) settings provide realistic backtesting results.
This ensures efficient capital allocation, preventing overexposure in volatile conditions.
🎯 Trade Management & Exits
Take Profit & Stop Loss Mechanism
Each position includes predefined profit and loss targets:
Take Profit: +10% of risk amount.
Stop Loss: Fixed at 10,100 points.
The risk-reward ratio remains balanced, aiming for controlled drawdowns while maximizing trade potential.
Visual Trade Tracking
To improve trade analysis, the strategy includes:
📌 Trade Markers:
"Buy" label when a long position opens.
"Close" label when a position exits.
📌 Trade History Boxes:
Green for profitable trades.
Red for losing trades.
📌 Horizontal Trade Lines:
Shows entry and exit prices.
Helps identify trend movements over multiple trades.
This structured visualization allows traders to analyze past performance directly on the chart.
⚡ How to Use This Strategy
1️⃣ Apply the script to a XAUUSD (Gold) 15m chart in TradingView.
2️⃣ Adjust leverage settings as needed.
3️⃣ Enable backtesting to assess past performance.
4️⃣ Monitor volume and MACD conditions to understand trade triggers.
5️⃣ Use the visual trade markers to review historical performance.
The MACD Volume Strategy is designed for short-term trading, aiming to capture momentum-driven opportunities while filtering out weak signals using volume confirmation.
Hanzo_Wave_Price %Hanzo_Wave_Price % is a custom indicator for the TradingView platform that combines RSI (Relative Strength Index) and Stochastic RSI while also displaying the percentage price change over a specified period. This indicator helps traders identify overbought and oversold conditions, analyze price waves, and forecast potential market movements.
How It Works
1. RSI and Stochastic RSI Calculation
RSI is calculated based on the selected price source (default: close) with a user-defined Main Line period.
Stochastic RSI is then applied and smoothed using a moving average.
The Main Line represents the smoothed Stochastic RSI, serving as a wave indicator to help identify potential entry and exit points.
2. Overbought and Oversold Zones
The 70 and 30 levels indicate overbought and oversold zones, displayed as dashed lines on the chart.
Additional 20% and 10% levels provide a visual reference for historical price changes, aiding in future predictions.
3. Percentage Price Change Calculation
The indicator calculates the percentage price change over a Barsback period (default: 30 candles).
Users can choose a multiplier (100 or 1000) for better visualization (1000 scales the values by dividing by 10).
The data is displayed as a colored area:
Red (Short) → Negative price change.
Green (Buy) → Positive price change.
Settings & Parameters
Multiplier 💪 – Selects the scaling factor (100 or 1000) for percentage values.
Main Line ✈️ – Stochastic smoothing period (smoothK).
Don't touch ✋ – Reserved value (do not modify).
RSI 🔴 – RSI calculation period.
Stochastic 🔵 – Stochastic RSI calculation period.
Source ⚠️ – Price source for calculations (default: close).
Price changes % 🔼🔽 – Enables percentage price change display.
Barsback ↩️ – Number of candles used to calculate price change.
Visual Representation
Gray Line (Takeprofit Line 🎯) – Smoothed Stochastic RSI.
Red Dashed Line (70) – Overbought zone.
Blue Dashed Line (30) – Oversold zone.
Percentage Price Change Display:
Green Fill → Price increase.
Red Fill → Price decrease.
Advantages
✅ Combined Analysis – Uses RSI and Stochastic RSI for more accurate market condition identification.
✅ Flexibility – Customizable parameters allow adaptation for different markets and strategies.
✅ Visual Clarity – Clearly defined zones and dynamic percentage change display.
✅ Additional Market Insights – The percentage price change helps assess market volatility.
Disadvantages
⚠ Lagging Signals – Smoothing may cause delayed response.
⚠ False Breakouts – The 70/30 levels may not always work effectively for all assets.
⚠ IMPORTANT!
This indicator is for informational and educational purposes only. Past performance does not guarantee future profits! Use it in combination with other technical analysis tools. 🚀
Example 1: Identifying a Long Position
📌 Scenario:
The asset price has dropped significantly (1-hour timeframe), and the Main Line (gray line) crosses below the 30 level. This signals oversold conditions, which may indicate a potential reversal or upward correction.
✅ How to Use:
1️⃣ Identifying the Entry Zone:
If the Main Line is below 30, consider looking for a long entry point.
2️⃣ Confirming the Signal:
Place a vertical line at the moment when the Main Line crosses the 30 level from below.
3️⃣ Confirmation on a Lower Timeframe:
Switch to a 30-minute timeframe and wait for the Main Line to cross above the 70 level.
Enter a long position at this point.
4️⃣ Analyzing Percentage Price Change:
Check the historical indicator behavior:
If a similar past movement resulted in a ~10% price increase (green fill), this may indicate potential upward momentum.
5️⃣ Setting Take-Profit:
Set a take-profit level at 10%, based on previous price movements.
Also, monitor when the Main Line crosses the 70 level, as this may signal a potential profit-taking point.
📊 Conclusion:
This method helps to precisely determine entry points by confirming signals across multiple timeframes and analyzing the historical volatility of the asset. 🚀
Example 2: Analyzing Percentage Price Change
📌 Scenario:
You have set the Barsback parameter to 30, and the indicator shows +3.5%. This means that over the last 30 candles, the price has increased by 3.5%.
However, such small changes might be visually difficult to notice. To improve visibility, you can enable the multiplier (1000), which will scale the displayed percentage change to 35%. This is purely for visual convenience—the actual price movement remains 3.5%.
✅ How to Use:
1️⃣ Identifying Trend Direction:
If the percentage change is positive (green area) → Uptrend.
If the percentage change is negative (red area) → Downtrend.
2️⃣ Analyzing Movement Strength:
Compare the current percentage change with previous waves to evaluate the strength of the movement.
For example:
If previous waves reached 10% or more, a current wave of 3.5% might indicate a weak trend or a local correction.
3️⃣ Additional Filtering with the Main Line (Gray Line):
Use the Main Line to confirm the trend.
If the percentage change shows an increase, but the Main Line is still below 30, further upward movement can be expected.
If the percentage change indicates a decline, but the Main Line is above 70, there is a higher probability of a downward reversal.
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