Trend Channel [Gu5]SMA 200 determines the trend
Bullish trend, green candles. Down trend, red candles.
If the market value is narrow to the SMA200 channel, yellow candles.
Setting recommended for SMA Range
BTCUSD = 100
EURUSD = 1000
SPX = 100
ETHUSD = 10
Cerca negli script per "trend"
MSignal Trend Continuation Indicator Msignal Trend Continuation Indicator
Alerts continuation trading patterns and signals trades that take advantage of price action turning points.
It seeks to find near term support and resistance levels and then identifies places on the chart to entry, and take profit of the established short term trend.
The indicator is based in price action and market timing algorithms to determine these turning points at significant price levels in the markets.
That way, you can be sure you have chance to enter in the market at the best level of the trend and take a high probability trade and ride the best part of the trend.
Once the MSignal indicator has spotted a continuation pattern, it clearly displays a Buy or Sell signal on your chart, showing you exactly where possible entry to continue with the trend.
ITekSignal Full v1.0 Trend REVERSAL and CONTINUATION ITekSignal Trading System helps you identify trend reversals — quickly and accurately.
There’s a price action pattern that occurs in every market and on every time-frame.
This price pattern shows a fight for balance, between seller and buyers…
When the pattern is completed, that means the fight for balance has ended.
And you’d know which side has won: Seller or Buyers, Supply or Demand, Bulls or Bears.
Once ITekSignal indicator has spotted a reversal, it clearly displays these Buy or Sell alerts on your charts… showing you exactly where possible reversals may occur.
ITekSignal Indicator will draw an up/down arrow on your chart, telling you there’s a trade opportunity for you to consider. So we’d enter the market for a ride of the new trend.
The indicator is also capable of detecting CONTINUATION pattern (in addition to REVERSAL patterns)
ITekSignal indicator gives you all kinds of alerts you’ll ever need:
Trend Reversal alert & Trend Continuation alerts
Contact the Author for Subscription
@iteksignal
iteksignal@gmail.com
VWAL Cloud + 200 Trend (v6) — Desh Videsh TradingDescription:
Visualize market trends easily with the VWAL Cloud + 200 Trend Indicator! This indicator is designed for traders who want a clear, intuitive view of trend direction using volume-weighted average lines (VWAL).
Features:
VWAL Cloud :
Shows the short-to-medium term trend zone.
Turns green when the cloud is above the 200-period VWAL (bullish).
Turns red when the cloud is below the 200-period VWAL (bearish).
Gray when the trend is neutral or mixed.
VWAL 200 Line:
Represents the long-term trend filter.
Helps identify overall market direction.
Trend Label:
Displays “TREND: BULL / BEAR / NEUTRAL” on the latest bar for quick visual reference.
How to Use:
Bullish Trend: Cloud above VWAL-200 → look for long setups.
Bearish Trend: Cloud below VWAL-200 → look for short setups.
Neutral Trend: Cloud overlapping VWAL-200 → avoid taking directional trades.
Customizable Inputs:
Cloud periods: can be changed as per your strategy
VWAL 200 period: adjust to suit longer-term trend detection
Cloud & line colors for personal preferences
Trendline Breakouts With Targets [ omerprıme ]Indicator Explanation (English)
This indicator is designed to detect trendline breakouts and provide early trading signals when the price breaks key support or resistance levels.
Trendline Detection
The indicator identifies recent swing highs and lows to construct dynamic trendlines.
These trendlines act as support in an uptrend and resistance in a downtrend.
Breakout Confirmation
When the price closes above a resistance trendline, the indicator generates a bullish breakout signal.
When the price closes below a support trendline, it generates a bearish breakout signal.
Filtering False Signals
To reduce false breakouts, additional conditions (such as candle confirmation, volume filters, or price momentum) can be applied.
Only significant and confirmed breakouts are highlighted.
Trading Logic
Buy signals are triggered when the price breaks upward through resistance with confirmation.
Sell signals are triggered when the price breaks downward through support with confirmation.
Trendlines Breakouts Pro V1.2 - 4TP [Wukong Algo]Trendlines Breakouts Pro
Trading method “High Tight Trendline Breakout”. This is a simple but effective and flexible method that can support many other methods such as: support and resistance, supply and demand, volume profile...
Automatically connect TradingView and MetaTrader 5 (MT5) for automatic trading and order management via PineConnector
The system includes a risk management grid including the levels: Stop Loss (SL), Break-even (BE), Trail Trigger, Trailing Stop, TP1 (1/4), TP2 (2/4), TP3 (3/4), TP4 (4/4). This grid helps you easily monitor and manage orders on TradingView in parallel with automatic order management on MT5.
Focus on tight capital and risk management, reduce emotion and stress when trading
Suitable for all markets: Forex, Gold, Crypto, Stocks, as long as you use MT5 and TradingView
If you do not need to trade automatically via MT5, the Trendlines Breakokuts Pro can also be used as an effective indicator in visual order management on TradingView charts, helps maintain discipline and good trading psychology (less Stress or FOMO)
Trendlines Breakouts Pro System User Guide
Step 1 - Draw trendline AB. Just click to select 2 points A, B on the chart
This is a straight line at the border of a chart pattern or support/resistance zone on the chart that you determine has high potential when it is broken, the price will have strong momentum and you will enter the order (Entry). The trendline AB can be a diagonal line or a horizontal line.
Step 2 - Entry Window: Set the time allowed for transactions
You can choose the earliest and latest time allowed for trading signals, called Entry Window. This means that the system will not allow trading outside the Entry Window. This option allows you to manage trading times as you wish, avoiding bad times for trading such as sideways, choppy, high volatility, news
Step 3 - Set up the input parameters for trading
You choose the direction you want to wait for trading: Wait Long (Buy), Wait Short (Sell), Turn Off, Hidden
You enter the ID of your PineConnector account if you want to trade automatically from TradingView to MT5
You enter the order parameters: Lotsize per order, Stop Loss (SL%), BE(%), Trail Trigger (%), TP1(%), TP2(%), TP3(%), TP4(%)
You enter the safe filter parameters for Entry: max distance from entry to swing high/low, max distance from entry to trendline's breakpoint C, max entries per trendlines
See more details in the screenshots
Step 4 - Set up automatic trading from TradingView via MT5
If you do not need automatic trading in MT5, skip this step. Entry signals and risk management grids will still be displayed on the TradingView chart for you to see, but there is no connection and automatic trading signal shooting and automatic order management from TradingView to MT5 via PineConnector.
We need to create an Alert in TradingView and attach it to this Indicator so that the Alert's trading signals are transmitted via MetaTrader 5 (MT5) via PineConnector.
When trading, you need to turn on 3 software at the same time to be able to connect to each other to operate: TradingView, MetaTrader 5 (MT5), PineConnector
See more details in the screenshots
Step 5 - Complete setup, and wait for trading signals
You have completed the setup steps for the Indicator, ready when there is a trading signal
You do not need to sit in front of the screen all day if you do not want. The system has been set up to execute and manage orders automatically.
Of course, sometimes you should still check your transaction status, in case of unexpected problems such as lost internet connection.
If you still have questions about this Indicator, please email tuanwukongvn@gmail.com for support.
Trend & Volatility ZoneUnlock the power of trend and volatility with the Dynamic Trend Zone, a complete trading suite for TradingView. Designed to help traders of all levels identify the direction and strength of market trends, this tool provides clean, actionable signals to remove guesswork and enhance your trading decisions.
Our system is built on a sophisticated logic that combines a smooth trend-following moving average with volatility bands based on the Average True Range (ATR). This creates an intuitive visual guide to the market's current state.
How It Works
The indicator is composed of two key elements:
The Trend Core: A central, responsive moving average acts as the baseline for determining the primary trend direction.
The Volatility Zone: Dynamic bands that expand and contract based on market volatility (ATR). These bands define the boundaries of the trend. When the price closes outside these bands, it signals a potential new trend is beginning.
The background color changes to provide an at-a-glance understanding of the market:
Blue Zone: Indicates a confirmed uptrend.
Red Zone: Indicates a confirmed downtrend.
Key Features
Visual Trend Zones: The colored background makes it effortless to see if the market is bullish or bearish, helping you stay on the right side of the trend.
Precise Entry Signals: Never miss a potential trend shift.
A green upward arrow appears when the trend officially flips from bearish to bullish, suggesting a buy opportunity.
A red downward arrow appears when the trend switches from bullish to bearish, highlighting a potential sell signal.
Fully Integrated Backtesting Strategy: This script isn't just an indicator; it's a complete, ready-to-use strategy. You can instantly backtest its performance on any asset and timeframe to validate its effectiveness.
Customizable Risk Management: The strategy includes optional Stop Loss and Take Profit parameters (in percent), allowing you to test different risk management approaches.
Highly Customizable Settings: Tailor the indicator to your preferred trading style by adjusting the sensitivity of the trend line and the width of the volatility zones.
Built-in Date Filter: Focus your backtesting on specific market conditions with a simple-to-use date filter, allowing you to analyze performance from any given start date.
How to Use
For a Long Position (Buy): Wait for the background to turn blue and a green arrow to appear below a candle. This signals that bullish momentum is taking control.
For a Short Position (Sell): Wait for the background to turn red and a red arrow to appear above a candle. This indicates that bearish momentum is building.
Confirmation: For best results, use these signals in conjunction with your own analysis, such as identifying key support/resistance levels or confirming with higher timeframe trends.
Customizable Settings
Trend Line Length: Controls the responsiveness of the central trend line. A lower value is faster; a higher value is smoother.
ATR Period: Sets the lookback period for calculating volatility.
ATR Multiplier: Adjusts the width of the trend zones. A higher value requires a stronger price move to signal a trend change.
Stop Loss % / Take Profit %: Define your risk-reward parameters for the backtesting strategy.
Disclaimer: The Dynamic Trend Zone is a tool designed for market analysis and backtesting. It is not financial advice. All forms of trading involve substantial risk, and past performance is not indicative of future results. Please use this tool responsibly as part of a well-rounded trading plan and risk management strategy.
Tzotchev Trend Measure [EdgeTools]Are you still measuring trend strength with moving averages? Here is a better variant at scientific level:
Tzotchev Trend Measure: A Statistical Approach to Trend Following
The Tzotchev Trend Measure represents a sophisticated advancement in quantitative trend analysis, moving beyond traditional moving average-based indicators toward a statistically rigorous framework for measuring trend strength. This indicator implements the methodology developed by Tzotchev et al. (2015) in their seminal J.P. Morgan research paper "Designing robust trend-following system: Behind the scenes of trend-following," which introduced a probabilistic approach to trend measurement that has since become a cornerstone of institutional trading strategies.
Mathematical Foundation and Statistical Theory
The core innovation of the Tzotchev Trend Measure lies in its transformation of price momentum into a probability-based metric through the application of statistical hypothesis testing principles. The indicator employs the fundamental formula ST = 2 × Φ(√T × r̄T / σ̂T) - 1, where ST represents the trend strength score bounded between -1 and +1, Φ(x) denotes the normal cumulative distribution function, T represents the lookback period in trading days, r̄T is the average logarithmic return over the specified period, and σ̂T represents the estimated daily return volatility.
This formulation transforms what is essentially a t-statistic into a probabilistic trend measure, testing the null hypothesis that the mean return equals zero against the alternative hypothesis of non-zero mean return. The use of logarithmic returns rather than simple returns provides several statistical advantages, including symmetry properties where log(P₁/P₀) = -log(P₀/P₁), additivity characteristics that allow for proper compounding analysis, and improved validity of normal distribution assumptions that underpin the statistical framework.
The implementation utilizes the Abramowitz and Stegun (1964) approximation for the normal cumulative distribution function, achieving accuracy within ±1.5 × 10⁻⁷ for all input values. This approximation employs Horner's method for polynomial evaluation to ensure numerical stability, particularly important when processing large datasets or extreme market conditions.
Comparative Analysis with Traditional Trend Measurement Methods
The Tzotchev Trend Measure demonstrates significant theoretical and empirical advantages over conventional trend analysis techniques. Traditional moving average-based systems, including simple moving averages (SMA), exponential moving averages (EMA), and their derivatives such as MACD, suffer from several fundamental limitations that the Tzotchev methodology addresses systematically.
Moving average systems exhibit inherent lag bias, as documented by Kaufman (2013) in "Trading Systems and Methods," where he demonstrates that moving averages inevitably lag price movements by approximately half their period length. This lag creates delayed signal generation that reduces profitability in trending markets and increases false signal frequency during consolidation periods. In contrast, the Tzotchev measure eliminates lag bias by directly analyzing the statistical properties of return distributions rather than smoothing price levels.
The volatility normalization inherent in the Tzotchev formula addresses a critical weakness in traditional momentum indicators. As shown by Bollinger (2001) in "Bollinger on Bollinger Bands," momentum oscillators like RSI and Stochastic fail to account for changing volatility regimes, leading to inconsistent signal interpretation across different market conditions. The Tzotchev measure's incorporation of return volatility in the denominator ensures that trend strength assessments remain consistent regardless of the underlying volatility environment.
Empirical studies by Hurst, Ooi, and Pedersen (2013) in "Demystifying Managed Futures" demonstrate that traditional trend-following indicators suffer from significant drawdowns during whipsaw markets, with Sharpe ratios frequently below 0.5 during challenging periods. The authors attribute these poor performance characteristics to the binary nature of most trend signals and their inability to quantify signal confidence. The Tzotchev measure addresses this limitation by providing continuous probability-based outputs that allow for more sophisticated risk management and position sizing strategies.
The statistical foundation of the Tzotchev approach provides superior robustness compared to technical indicators that lack theoretical grounding. Fama and French (1988) in "Permanent and Temporary Components of Stock Prices" established that price movements contain both permanent and temporary components, with traditional moving averages unable to distinguish between these elements effectively. The Tzotchev methodology's hypothesis testing framework specifically tests for the presence of permanent trend components while filtering out temporary noise, providing a more theoretically sound approach to trend identification.
Research by Moskowitz, Ooi, and Pedersen (2012) in "Time Series Momentum in the Cross Section of Asset Returns" found that traditional momentum indicators exhibit significant variation in effectiveness across asset classes and time periods. Their study of multiple asset classes over decades revealed that simple price-based momentum measures often fail to capture persistent trends in fixed income and commodity markets. The Tzotchev measure's normalization by volatility and its probabilistic interpretation provide consistent performance across diverse asset classes, as demonstrated in the original J.P. Morgan research.
Comparative performance studies conducted by AQR Capital Management (Asness, Moskowitz, and Pedersen, 2013) in "Value and Momentum Everywhere" show that volatility-adjusted momentum measures significantly outperform traditional price momentum across international equity, bond, commodity, and currency markets. The study documents Sharpe ratio improvements of 0.2 to 0.4 when incorporating volatility normalization, consistent with the theoretical advantages of the Tzotchev approach.
The regime detection capabilities of the Tzotchev measure provide additional advantages over binary trend classification systems. Research by Ang and Bekaert (2002) in "Regime Switches in Interest Rates" demonstrates that financial markets exhibit distinct regime characteristics that traditional indicators fail to capture adequately. The Tzotchev measure's five-tier classification system (Strong Bull, Weak Bull, Neutral, Weak Bear, Strong Bear) provides more nuanced market state identification than simple trend/no-trend binary systems.
Statistical testing by Jegadeesh and Titman (2001) in "Profitability of Momentum Strategies" revealed that traditional momentum indicators suffer from significant parameter instability, with optimal lookback periods varying substantially across market conditions and asset classes. The Tzotchev measure's statistical framework provides more stable parameter selection through its grounding in hypothesis testing theory, reducing the need for frequent parameter optimization that can lead to overfitting.
Advanced Noise Filtering and Market Regime Detection
A significant enhancement over the original Tzotchev methodology is the incorporation of a multi-factor noise filtering system designed to reduce false signals during sideways market conditions. The filtering mechanism employs four distinct approaches: adaptive thresholding based on current market regime strength, volatility-based filtering utilizing ATR percentile analysis, trend strength confirmation through momentum alignment, and a comprehensive multi-factor approach that combines all methodologies.
The adaptive filtering system analyzes market microstructure through price change relative to average true range, calculates volatility percentiles over rolling windows, and assesses trend alignment across multiple timeframes using exponential moving averages of varying periods. This approach addresses one of the primary limitations identified in traditional trend-following systems, namely their tendency to generate excessive false signals during periods of low volatility or sideways price action.
The regime detection component classifies market conditions into five distinct categories: Strong Bull (ST > 0.3), Weak Bull (0.1 < ST ≤ 0.3), Neutral (-0.1 ≤ ST ≤ 0.1), Weak Bear (-0.3 ≤ ST < -0.1), and Strong Bear (ST < -0.3). This classification system provides traders with clear, quantitative definitions of market regimes that can inform position sizing, risk management, and strategy selection decisions.
Professional Implementation and Trading Applications
The indicator incorporates three distinct trading profiles designed to accommodate different investment approaches and risk tolerances. The Conservative profile employs longer lookback periods (63 days), higher signal thresholds (0.2), and reduced filter sensitivity (0.5) to minimize false signals and focus on major trend changes. The Balanced profile utilizes standard academic parameters with moderate settings across all dimensions. The Aggressive profile implements shorter lookback periods (14 days), lower signal thresholds (-0.1), and increased filter sensitivity (1.5) to capture shorter-term trend movements.
Signal generation occurs through threshold crossover analysis, where long signals are generated when the trend measure crosses above the specified threshold and short signals when it crosses below. The implementation includes sophisticated signal confirmation mechanisms that consider trend alignment across multiple timeframes and momentum strength percentiles to reduce the likelihood of false breakouts.
The alert system provides real-time notifications for trend threshold crossovers, strong regime changes, and signal generation events, with configurable frequency controls to prevent notification spam. Alert messages are standardized to ensure consistency across different market conditions and timeframes.
Performance Optimization and Computational Efficiency
The implementation incorporates several performance optimization features designed to handle large datasets efficiently. The maximum bars back parameter allows users to control historical calculation depth, with default settings optimized for most trading applications while providing flexibility for extended historical analysis. The system includes automatic performance monitoring that generates warnings when computational limits are approached.
Error handling mechanisms protect against division by zero conditions, infinite values, and other numerical instabilities that can occur during extreme market conditions. The finite value checking system ensures data integrity throughout the calculation process, with fallback mechanisms that maintain indicator functionality even when encountering corrupted or missing price data.
Timeframe validation provides warnings when the indicator is applied to unsuitable timeframes, as the Tzotchev methodology was specifically designed for daily and higher timeframe analysis. This validation helps prevent misapplication of the indicator in contexts where its statistical assumptions may not hold.
Visual Design and User Interface
The indicator features eight professional color schemes designed for different trading environments and user preferences. The EdgeTools theme provides an institutional blue and steel color palette suitable for professional trading environments. The Gold theme offers warm colors optimized for commodities trading. The Behavioral theme incorporates psychology-based color contrasts that align with behavioral finance principles. The Quant theme provides neutral colors suitable for analytical applications.
Additional specialized themes include Ocean, Fire, Matrix, and Arctic variations, each optimized for specific visual preferences and trading contexts. All color schemes include automatic dark and light mode optimization to ensure optimal readability across different chart backgrounds and trading platforms.
The information table provides real-time display of key metrics including current trend measure value, market regime classification, signal strength, Z-score, average returns, volatility measures, filter threshold levels, and filter effectiveness percentages. This comprehensive dashboard allows traders to monitor all relevant indicator components simultaneously.
Theoretical Implications and Research Context
The Tzotchev Trend Measure addresses several theoretical limitations inherent in traditional technical analysis approaches. Unlike moving average-based systems that rely on price level comparisons, this methodology grounds trend analysis in statistical hypothesis testing, providing a more robust theoretical foundation for trading decisions.
The probabilistic interpretation of trend strength offers significant advantages over binary trend classification systems. Rather than simply indicating whether a trend exists, the measure quantifies the statistical confidence level associated with the trend assessment, allowing for more nuanced risk management and position sizing decisions.
The incorporation of volatility normalization addresses the well-documented problem of volatility clustering in financial time series, ensuring that trend strength assessments remain consistent across different market volatility regimes. This normalization is particularly important for portfolio management applications where consistent risk metrics across different assets and time periods are essential.
Practical Applications and Trading Strategy Integration
The Tzotchev Trend Measure can be effectively integrated into various trading strategies and portfolio management frameworks. For trend-following strategies, the indicator provides clear entry and exit signals with quantified confidence levels. For mean reversion strategies, extreme readings can signal potential turning points. For portfolio allocation, the regime classification system can inform dynamic asset allocation decisions.
The indicator's statistical foundation makes it particularly suitable for quantitative trading strategies where systematic, rules-based approaches are preferred over discretionary decision-making. The standardized output range facilitates easy integration with position sizing algorithms and risk management systems.
Risk management applications benefit from the indicator's ability to quantify trend strength and provide early warning signals of potential trend changes. The multi-timeframe analysis capability allows for the construction of robust risk management frameworks that consider both short-term tactical and long-term strategic market conditions.
Implementation Guide and Parameter Configuration
The practical application of the Tzotchev Trend Measure requires careful parameter configuration to optimize performance for specific trading objectives and market conditions. This section provides comprehensive guidance for parameter selection and indicator customization.
Core Calculation Parameters
The Lookback Period parameter controls the statistical window used for trend calculation and represents the most critical setting for the indicator. Default values range from 14 to 63 trading days, with shorter periods (14-21 days) providing more sensitive trend detection suitable for short-term trading strategies, while longer periods (42-63 days) offer more stable trend identification appropriate for position trading and long-term investment strategies. The parameter directly influences the statistical significance of trend measurements, with longer periods requiring stronger underlying trends to generate significant signals but providing greater reliability in trend identification.
The Price Source parameter determines which price series is used for return calculations. The default close price provides standard trend analysis, while alternative selections such as high-low midpoint ((high + low) / 2) can reduce noise in volatile markets, and volume-weighted average price (VWAP) offers superior trend identification in institutional trading environments where volume concentration matters significantly.
The Signal Threshold parameter establishes the minimum trend strength required for signal generation, with values ranging from -0.5 to 0.5. Conservative threshold settings (0.2 to 0.3) reduce false signals but may miss early trend opportunities, while aggressive settings (-0.1 to 0.1) provide earlier signal generation at the cost of increased false positive rates. The optimal threshold depends on the trader's risk tolerance and the volatility characteristics of the traded instrument.
Trading Profile Configuration
The Trading Profile system provides pre-configured parameter sets optimized for different trading approaches. The Conservative profile employs a 63-day lookback period with a 0.2 signal threshold and 0.5 noise sensitivity, designed for long-term position traders seeking high-probability trend signals with minimal false positives. The Balanced profile uses a 21-day lookback with 0.05 signal threshold and 1.0 noise sensitivity, suitable for swing traders requiring moderate signal frequency with acceptable noise levels. The Aggressive profile implements a 14-day lookback with -0.1 signal threshold and 1.5 noise sensitivity, optimized for day traders and scalpers requiring frequent signal generation despite higher noise levels.
Advanced Noise Filtering System
The noise filtering mechanism addresses the challenge of false signals during sideways market conditions through four distinct methodologies. The Adaptive filter adjusts thresholds based on current trend strength, increasing sensitivity during strong trending periods while raising thresholds during consolidation phases. The Volatility-based filter utilizes Average True Range (ATR) percentile analysis to suppress signals during abnormally volatile conditions that typically generate false trend indications.
The Trend Strength filter requires alignment between multiple momentum indicators before confirming signals, reducing the probability of false breakouts from consolidation patterns. The Multi-factor approach combines all filtering methodologies using weighted scoring to provide the most robust noise reduction while maintaining signal responsiveness during genuine trend initiations.
The Noise Sensitivity parameter controls the aggressiveness of the filtering system, with lower values (0.5-1.0) providing conservative filtering suitable for volatile instruments, while higher values (1.5-2.0) allow more signals through but may increase false positive rates during choppy market conditions.
Visual Customization and Display Options
The Color Scheme parameter offers eight professional visualization options designed for different analytical preferences and market conditions. The EdgeTools scheme provides high contrast visualization optimized for trend strength differentiation, while the Gold scheme offers warm tones suitable for commodity analysis. The Behavioral scheme uses psychological color associations to enhance decision-making speed, and the Quant scheme provides neutral colors appropriate for quantitative analysis environments.
The Ocean, Fire, Matrix, and Arctic schemes offer additional aesthetic options while maintaining analytical functionality. Each scheme includes optimized colors for both light and dark chart backgrounds, ensuring visibility across different trading platform configurations.
The Show Glow Effects parameter enhances plot visibility through multiple layered lines with progressive transparency, particularly useful when analyzing multiple timeframes simultaneously or when working with dense price data that might obscure trend signals.
Performance Optimization Settings
The Maximum Bars Back parameter controls the historical data depth available for calculations, with values ranging from 5,000 to 50,000 bars. Higher values enable analysis of longer-term trend patterns but may impact indicator loading speed on slower systems or when applied to multiple instruments simultaneously. The optimal setting depends on the intended analysis timeframe and available computational resources.
The Calculate on Every Tick parameter determines whether the indicator updates with every price change or only at bar close. Real-time calculation provides immediate signal updates suitable for scalping and day trading strategies, while bar-close calculation reduces computational overhead and eliminates signal flickering during bar formation, preferred for swing trading and position management applications.
Alert System Configuration
The Alert Frequency parameter controls notification generation, with options for all signals, bar close only, or once per bar. High-frequency trading strategies benefit from all signals mode, while position traders typically prefer bar close alerts to avoid premature position entries based on intrabar fluctuations.
The alert system generates four distinct notification types: Long Signal alerts when the trend measure crosses above the positive signal threshold, Short Signal alerts for negative threshold crossings, Bull Regime alerts when entering strong bullish conditions, and Bear Regime alerts for strong bearish regime identification.
Table Display and Information Management
The information table provides real-time statistical metrics including current trend value, regime classification, signal status, and filter effectiveness measurements. The table position can be customized for optimal screen real estate utilization, and individual metrics can be toggled based on analytical requirements.
The Language parameter supports both English and German display options for international users, while maintaining consistent calculation methodology regardless of display language selection.
Risk Management Integration
Effective risk management integration requires coordination between the trend measure signals and position sizing algorithms. Strong trend readings (above 0.5 or below -0.5) support larger position sizes due to higher probability of trend continuation, while neutral readings (between -0.2 and 0.2) suggest reduced position sizes or range-trading strategies.
The regime classification system provides additional risk management context, with Strong Bull and Strong Bear regimes supporting trend-following strategies, while Neutral regimes indicate potential for mean reversion approaches. The filter effectiveness metric helps traders assess current market conditions and adjust strategy parameters accordingly.
Timeframe Considerations and Multi-Timeframe Analysis
The indicator's effectiveness varies across different timeframes, with higher timeframes (daily, weekly) providing more reliable trend identification but slower signal generation, while lower timeframes (hourly, 15-minute) offer faster signals with increased noise levels. Multi-timeframe analysis combining trend alignment across multiple periods significantly improves signal quality and reduces false positive rates.
For optimal results, traders should consider trend alignment between the primary trading timeframe and at least one higher timeframe before entering positions. Divergences between timeframes often signal potential trend reversals or consolidation periods requiring strategy adjustment.
Conclusion
The Tzotchev Trend Measure represents a significant advancement in technical analysis methodology, combining rigorous statistical foundations with practical trading applications. Its implementation of the J.P. Morgan research methodology provides institutional-quality trend analysis capabilities previously available only to sophisticated quantitative trading firms.
The comprehensive parameter configuration options enable customization for diverse trading styles and market conditions, while the advanced noise filtering and regime detection capabilities provide superior signal quality compared to traditional trend-following indicators. Proper parameter selection and understanding of the indicator's statistical foundation are essential for achieving optimal trading results and effective risk management.
References
Abramowitz, M. and Stegun, I.A. (1964). Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables. Washington: National Bureau of Standards.
Ang, A. and Bekaert, G. (2002). Regime Switches in Interest Rates. Journal of Business and Economic Statistics, 20(2), 163-182.
Asness, C.S., Moskowitz, T.J., and Pedersen, L.H. (2013). Value and Momentum Everywhere. Journal of Finance, 68(3), 929-985.
Bollinger, J. (2001). Bollinger on Bollinger Bands. New York: McGraw-Hill.
Fama, E.F. and French, K.R. (1988). Permanent and Temporary Components of Stock Prices. Journal of Political Economy, 96(2), 246-273.
Hurst, B., Ooi, Y.H., and Pedersen, L.H. (2013). Demystifying Managed Futures. Journal of Investment Management, 11(3), 42-58.
Jegadeesh, N. and Titman, S. (2001). Profitability of Momentum Strategies: An Evaluation of Alternative Explanations. Journal of Finance, 56(2), 699-720.
Kaufman, P.J. (2013). Trading Systems and Methods. 5th Edition. Hoboken: John Wiley & Sons.
Moskowitz, T.J., Ooi, Y.H., and Pedersen, L.H. (2012). Time Series Momentum. Journal of Financial Economics, 104(2), 228-250.
Tzotchev, D., Lo, A.W., and Hasanhodzic, J. (2015). Designing robust trend-following system: Behind the scenes of trend-following. J.P. Morgan Quantitative Research, Asset Management Division.
Adaptive Trend Following Suite [Alpha Extract]A sophisticated multi-filter trend analysis system that combines advanced noise reduction, adaptive moving averages, and intelligent market structure detection to deliver institutional-grade trend following signals. Utilizing cutting-edge mathematical algorithms and dynamic channel adaptation, this indicator provides crystal-clear directional guidance with real-time confidence scoring and market mode classification for professional trading execution.
🔶 Advanced Noise Reduction
Filter Eliminates market noise using sophisticated Gaussian filtering with configurable sigma values and period optimization. The system applies mathematical weight distribution across price data to ensure clean signal generation while preserving critical trend information, automatically adjusting filter strength based on volatility conditions.
advancedNoiseFilter(sourceData, filterLength, sigmaParam) =>
weightSum = 0.0
valueSum = 0.0
centerPoint = (filterLength - 1) / 2
for index = 0 to filterLength - 1
gaussianWeight = math.exp(-0.5 * math.pow((index - centerPoint) / sigmaParam, 2))
weightSum += gaussianWeight
valueSum += sourceData * gaussianWeight
valueSum / weightSum
🔶 Adaptive Moving Average Core Engine
Features revolutionary volatility-responsive averaging that automatically adjusts smoothing parameters based on real-time market conditions. The engine calculates adaptive power factors using logarithmic scaling and bandwidth optimization, ensuring optimal responsiveness during trending markets while maintaining stability during consolidation phases.
// Calculate adaptive parameters
adaptiveLength = (periodLength - 1) / 2
logFactor = math.max(math.log(math.sqrt(adaptiveLength)) / math.log(2) + 2, 0)
powerFactor = math.max(logFactor - 2, 0.5)
relativeVol = avgVolatility != 0 ? volatilityMeasure / avgVolatility : 0
adaptivePower = math.pow(relativeVol, powerFactor)
bandwidthFactor = math.sqrt(adaptiveLength) * logFactor
🔶 Intelligent Market Structure Analysis
Employs fractal dimension calculations to classify market conditions as trending or ranging with mathematical precision. The system analyzes price path complexity using normalized data arrays and geometric path length calculations, providing quantitative market mode identification with configurable threshold sensitivity.
🔶 Multi-Component Momentum Analysis
Integrates RSI and CCI oscillators with advanced Z-score normalization for statistical significance testing. Each momentum component receives independent analysis with customizable periods and significance levels, creating a robust consensus system that filters false signals while maintaining sensitivity to genuine momentum shifts.
// Z-score momentum analysis
rsiAverage = ta.sma(rsiComponent, zAnalysisPeriod)
rsiDeviation = ta.stdev(rsiComponent, zAnalysisPeriod)
rsiZScore = (rsiComponent - rsiAverage) / rsiDeviation
if math.abs(rsiZScore) > zSignificanceLevel
rsiMomentumSignal := rsiComponent > 50 ? 1 : rsiComponent < 50 ? -1 : rsiMomentumSignal
❓How It Works
🔶 Dynamic Channel Configuration
Calculates adaptive channel boundaries using three distinct methodologies: ATR-based volatility, Standard Deviation, and advanced Gaussian Deviation analysis. The system automatically adjusts channel multipliers based on market structure classification, applying tighter channels during trending conditions and wider boundaries during ranging markets for optimal signal accuracy.
dynamicChannelEngine(baselineData, channelLength, methodType) =>
switch methodType
"ATR" => ta.atr(channelLength)
"Standard Deviation" => ta.stdev(baselineData, channelLength)
"Gaussian Deviation" =>
weightArray = array.new_float()
totalWeight = 0.0
for i = 0 to channelLength - 1
gaussWeight = math.exp(-math.pow((i / channelLength) / 2, 2))
weightedVariance += math.pow(deviation, 2) * array.get(weightArray, i)
math.sqrt(weightedVariance / totalWeight)
🔶 Signal Processing Pipeline
Executes a sophisticated 10-step signal generation process including noise filtering, trend reference calculation, structure analysis, momentum component processing, channel boundary determination, trend direction assessment, consensus calculation, confidence scoring, and final signal generation with quality control validation.
🔶 Confidence Transformation System
Applies sigmoid transformation functions to raw confidence scores, providing 0-1 normalized confidence ratings with configurable threshold controls. The system uses steepness parameters and center point adjustments to fine-tune signal sensitivity while maintaining statistical robustness across different market conditions.
🔶 Enhanced Visual Presentation
Features dynamic color-coded trend lines with adaptive channel fills, enhanced candlestick visualization, and intelligent price-trend relationship mapping. The system provides real-time visual feedback through gradient fills and transparency adjustments that immediately communicate trend strength and direction changes.
🔶 Real-Time Information Dashboard
Displays critical trading metrics including market mode classification (Trending/Ranging), structure complexity values, confidence scores, and current signal status. The dashboard updates in real-time with color-coded indicators and numerical precision for instant market condition assessment.
🔶 Intelligent Alert System
Generates three distinct alert types: Bullish Signal alerts for uptrend confirmations, Bearish Signal alerts for downtrend confirmations, and Mode Change alerts for market structure transitions. Each alert includes detailed messaging and timestamp information for comprehensive trade management integration.
🔶 Performance Optimization
Utilizes efficient array management and conditional processing to maintain smooth operation across all timeframes. The system employs strategic variable caching, optimized loop structures, and intelligent update mechanisms to ensure consistent performance even during high-volatility market conditions.
This indicator delivers institutional-grade trend analysis through sophisticated mathematical modelling and multi-stage signal processing. By combining advanced noise reduction, adaptive averaging, intelligent structure analysis, and robust momentum confirmation with dynamic channel adaptation, it provides traders with unparalleled trend following precision. The comprehensive confidence scoring system and real-time market mode classification make it an essential tool for professional traders seeking consistent, high-probability trend following opportunities with mathematical certainty and visual clarity.
Draw Trend LinesSometimes the simplest indicators help traders make better decisions. This indicator draws simple trend lines, the same lines you would draw manually.
To trade with an edge, traders need to interpret the recent price action, whether it's noisy or choppy, or it's trending. Trend Lines will help traders with that interpretation.
The lines drawn are:
1. lower tops
2. higher bottoms
Because trends are defined as higher lows, or lower highs.
When you see "Wedges", formed by prices chopping between top and bottom trend lines, that's noisy environment not to be traded. When you learn to "stop yourself", you already have an edge.
Often when you see a trend, it's still not too late. Trend will continue until it doesn't. But the caveat is a very steep trend is unlikely to continue, because buying volume is extremely unbalanced to cause the steep trend, and that volume will run out of energy. (Same on the sell side of course)
Trends can reverse, and when price action breaks the trend line, Breakout/Breakdown traders can take this as an entry signal.
Enjoy, and good trading!
TrendPilot AI v2 — Adaptive Trend Day Trading StrategyOverview
TrendPilot AI v2 is a structured, rules-based day trading strategy that identifies and follows market momentum using a sophisticated blend of technical indicators. Optimized for 15-minute and higher timeframes on high market cap cryptocurrencies (AAVE, SOL, ETH, BCH, BTC) to minimize manipulation risks, it adapts to changing market conditions with dynamic risk management and controlled re-entry logic to maximize trend participation while minimizing noise.
Core Logic
Multiple EMA Trend Confirmation — Uses three Exponential Moving Averages (fast, medium, slow) to detect robust bullish, bearish, or neutral trends, ensuring trades align with the prevailing market direction.
ADX Momentum Filter — Employs an ADX-based filter to confirm strong trends, avoiding entries in choppy or low-momentum markets.
Smart Entry Filter — Optional ATR-based buffer (period 14, multiplier 1.5) around the fast EMA prevents entries at overextended prices, enhancing trade precision.
Flexible Exit System — Offers multiple exit options: fixed take-profit (default 1.7 offset), trend-reversal exits, or ATR-based trailing stops (period 14, multiplier 2.0), with secure modes requiring candle closes for confirmation to gain Max Profit.
Controlled Re-Entry Logic — Allows re-entries after take-profit or price-based stop-loss with configurable wait periods (default 6 bars), max attempts (default 2), and EMA touch requirements (fast, medium, or slow).
State-Aware Risk Management — Tracks trend states and recent exits to adapt entries, with daily trade limits (default 5 long/short) and loss cooldowns (default 2 stop-losses) for disciplined trading.
How to Use & Configuration
Markets & Timeframes
Works with high market cap cryptocurrencies (AAVE, SOL, ETH, BCH, BTC).
Optimized for intraday charts (15m–4h) but adaptable to higher timeframes (e.g., 1h, 4h).
Trade Direction Settings
Dual Trades — Trades both long and short, quickly re-aligning after trend reversals.
Long Only — Ignores bearish signals, ideal for bullish markets or strong uptrends.
Short Only — Ignores bullish signals, suited for bearish markets or downtrends.
Risk Management Settings
Stop Loss Types
Trend Reversal — Closes positions when an opposite trend signal is confirmed (default).
Fixed Offset — Static stop at 3.5 offset from entry price (adjustable).
ATR Based — Dynamic trailing stop using ATR (period 14, multiplier 2.0), adjusting to market volatility.
Secure SL Mode — Optional setting to trigger price-based stops only on candle closes, reducing false exits.
Maximum recommended risk per trade is 5–10% of account equity.
Trade size is configurable (default 20 units) to match individual risk appetite.
Take Profit Options
Fixed Offset — Predefined target at 1.7 offset from entry (adjustable, e.g., 2.5 for SOL).
Secure TP Mode — Exits only when a candle closes beyond the target, ensuring reliable profit capture.
Trend Reversal — Exits on opposite trend signals when fixed TP is disabled, ideal for riding longer trends.
Trade Management Controls
Smart Entry Filter — Optional ATR-based buffer (period 14, multiplier 1.5) prevents chasing overextended prices.
Max Re-Entries — Limits continuation trades per trend cycle (default 2).
Daily Trade Limits — Caps long/short trades per day (default 5 each) for disciplined trading.
Daily Loss Cooldown — Pauses trading after a set number of stop-losses (default 2) per day.
Max Bars in Trade — Closes positions after a set duration (default 1440 bars) to prevent stale trades.
Configuration Steps
Apply the strategy to your chosen symbol (e.g., AAVE/USDT, SOL/USDT) and timeframe (15m or higher).
Select Trade Direction mode (Dual, Long Only, or Short Only).
Set Stop Loss (Trend Reversal, Fixed Offset, or ATR Based) and Take Profit (fixed or trend-reversal).
Adjust Smart Entry Filter, Max Re-Entries, Daily Limits, and Loss Cooldown as needed.
Test across multiple market conditions using the performance panel (top-right, showing Total Trades, Wins, Losses, Win Rate).
Enables automated trading via webhook integration with platforms like Binance Futures.
Set up alerts for long/short entries (🟢 Long, 🔴 Short) and exits (🎯 Max TP, 🛑 Max SL, 🚨 Force Exit).
Backtesting Guidance
Use realistic commission (default 0.01%) and slippage (default 2 ticks) matching your broker and instrument.
Validate performance over long historical periods (e.g., 3–6 months) to ensure >100 trades across different market regimes.
Avoid curve-fitting by testing on multiple high market cap coins (AAVE, SOL, ETH, BCH, BTC) and avoiding over-optimization.
EMA and ATR parameters are set to balanced, industry-standard values for realistic backtesting.
Best Practices, Defaults & Disclaimer
Best Practices
Use consistent and conservative position sizing (default 20 units).
Match commission and slippage to your broker’s actual rates.
Enable secure TP/SL modes for entries and exits to reduce false signals.
Test across different symbols, timeframes, and market phases before live trading.
Keep parameters simple to avoid overfitting.
Default Settings (Recommended Starting Point)
Initial Capital: $10,000
Order Size: Fixed, 20 units
Commission: 0.01%
Slippage: 2 ticks
Take Profit Offset: 1.7 (adjustable, e.g., 2.5 for SOL)
Stop Loss Type: Trend Reversal (default), Fixed Offset (3.5), or ATR Based (period 14, multiplier 2.0)
Smart Entry Filter: ATR period 14, multiplier 1.5 (optional)
Max Re-Entries: 2 per trend cycle
Daily Trade Limits: 5 long, 5 short
Daily Loss Cooldown: 2 stop-losses
Max Bars in Trade: 1440 bars
Subscription Information
TrendPilot AI v2 is an invite-only strategy, accessible only to approved subscribers.
Benefits include full access to all features, priority support, and regular updates.
Access is limited to ensure a high-quality user experience.
Compliance Status
No functional warnings in the script.
The script uses closed candle logic, ensuring no repainting or lookahead issues.
Designed for realistic backtesting with a $10,000 account and sustainable risk (≤5–10% per trade).
Disclaimer
This strategy is intended for educational and analytical purposes only. Trading involves substantial risk, and past performance does not guarantee future results. You are solely responsible for your own trading decisions and risk management.
Developed by: TrendPilotAI Team
For questions, setup guidance, or enhancement suggestions, contact TrendPilotAI Team via TradingView.
Trend Strength Oscillator📌 Trend Strength Oscillator
📄 Description
Trend Strength Oscillator measures the directional strength of price relative to an adaptive dynamic trend band. It evaluates how far the current price is from the midpoint of a trend channel and normalizes this value by recent volatility range, allowing traders to detect trend strength, direction, and potential exhaustion in any market condition.
📌 Features
🔹 Adaptive Trend Band Logic: Uses a modified ATR and time-dependent spread formula to dynamically adjust upper and lower trend bands.
🔹 Trendline Midpoint Calculation: The central trendline is defined as the average between upper and lower bands.
🔹 Relative Positioning: Measures how far the close is from the center of the band as a percentage.
🔹 Range Normalization: Uses a normalized range to account for recent volatility, reducing noise in the oscillator reading.
🔹 Oscillator Output (±100 scale):
+100 indicates strong bullish momentum
-100 indicates strong bearish momentum
0 is the neutral centerline
🛠️ How to Use
✅ Trend Strength > +50: Indicates a strong bullish phase.
✅ Trend Strength < -50: Indicates a strong bearish phase.
⚠️ Crossing above 0: Potential bullish trend initiation.
⚠️ Crossing below 0: Potential bearish trend initiation.
📉 Values near 0: Suggest trend weakness or ranging conditions.
Best suited timeframes: 1H, 4H, Daily
Ideal combination with: RSI, MACD, volume-based oscillators, moving average crosses
✅ TradingView House Rules Compliance
This indicator is written in Pine Script v5 and fully open-source.
The script does not repaint, does not generate false alerts, and does not access external or private data.
It is intended strictly as a technical analysis tool, and not a buy/sell signal generator.
Users are encouraged to combine this tool with other confirmations and independent judgment in trading decisions.
=========================================================
📌 Trend Strength Oscillator
📄 설명 (Description)
Trend Strength Oscillator는 가격이 동적 추세 밴드 내 어디에 위치해 있는지를 정량적으로 분석하여, 추세의 방향성과 강도를 시각적으로 보여주는 오실레이터 지표입니다. 최근 변동성을 반영한 밴드를 기반으로 가격 위치를 정규화하여, 과매수·과매도 상태나 추세의 소멸 가능성까지 탐지할 수 있도록 설계되었습니다.
📌 주요 특징 (Features)
🔹 적응형 추세 밴드 계산: ATR과 시간 경과를 기반으로 상단/하단 밴드를 동적으로 조정
🔹 중심 추세선 산출: 상단과 하단 밴드의 평균값을 중심선으로 활용하여 기준 축 제공
🔹 상대 위치 계산: 현재 종가가 중심선에서 얼마나 떨어져 있는지를 정규화하여 추세 강도 계산
🔹 변동성 기반 정규화: 최근 밴드 범위를 기준으로 상대 거리를 0~100 사이 값으로 변환
🔹 오실레이터 출력 (범위: ±100):
+100에 가까울수록 강한 상승 추세
-100에 가까울수록 강한 하락 추세
0에 가까울수록 횡보 구간 가능성
🛠️ 사용법 (How to Use)
✅ +50 이상: 강한 상승 추세 지속 중
✅ -50 이하: 강한 하락 추세 지속 중
⚠️ 0선 돌파 상향: 상승 추세 시작 가능성
⚠️ 0선 돌파 하향: 하락 추세 시작 가능성
🟡 0 근처 유지: 추세 약화 또는 횡보장 가능성
추천 시간대: 1시간봉, 4시간봉, 일봉
보조 지표로 추천: RSI, MACD, OBV, 이동평균 크로스 등과 함께 활용 시 효과적
✅ 트레이딩뷰 하우스룰 준수사항 (TradingView House Rules Compliance)
본 지표는 Pine Script v5로 작성된 오픈소스 공개용 스크립트입니다.
리페인트(Repaint) 현상이 없으며, **허위 경고(Spam Alerts)**나 성능 저하 요소도 없습니다.
외부 데이터 접근 없이 완전히 자체 계산으로 동작합니다.
이 지표는 투자 판단을 돕기 위한 분석용 도구이며, 직접적인 매수·매도 신호로 사용해서는 안 됩니다.
모든 트레이딩은 사용자의 독립적인 판단과 책임 하에 이루어져야 합니다.
Trend Band Oscillator📌 Trend Band Oscillator
📄 Description
Trend Band Oscillator is a momentum-based trend indicator that calculates the spread between two EMAs and overlays it with a volatility filter using a standard deviation band. It helps traders visualize not only the trend direction but also the strength and stability of the trend.
📌 Features
🔹 EMA Spread Calculation: Measures the difference between a fast and slow EMA to quantify short-term vs mid-term trend dynamics.
🔹 Volatility Band Overlay: Applies an EMA of standard deviation to the spread to filter noise and highlight valid momentum shifts.
🔹 Color-Based Visualization: Positive spread values are shown in lime (bullish), negative values in fuchsia (bearish) for quick directional insight.
🔹 Upper/Lower Bands: Help detect potential overbought/oversold conditions or strong trend continuation.
🔹 Zero Line Reference: A horizontal baseline at zero helps identify trend reversals and neutral zones.
🛠️ How to Use
✅ Spread > 0: Indicates a bullish trend. Consider maintaining or entering long positions.
✅ Spread < 0: Indicates a bearish trend. Consider maintaining or entering short positions.
⚠️ Spread exceeds bands: May signal overextension or strong momentum; consider using with additional confirmation indicators.
🔄 Band convergence: Suggests weakening trend and potential transition to a ranging market.
Recommended timeframes: 1H, 4H, Daily
Suggested complementary indicators: RSI, MACD, OBV, SuperTrend
✅ TradingView House Rules Compliance
This script is open-source and published under Pine Script v5.
It does not repaint, spam alerts, or cause performance issues.
It is designed as an analytical aid only and should not be considered financial advice.
All calculations are transparent, and no external data sources or insecure functions are used.
====================================================================
📌 Trend Band Oscillator
📄 설명 (Description)
Trend Band Oscillator는 두 개의 EMA 간 스프레드(차이)를 기반으로 한 모멘텀 중심의 추세 오실레이터입니다. 여기에 표준편차 기반의 변동성 밴드를 적용하여, 추세의 방향뿐 아니라 강도와 안정성까지 시각적으로 분석할 수 있도록 설계되었습니다.
📌 주요 특징 (Features)
🔹 EMA 기반 스프레드 계산: Fast EMA와 Slow EMA의 차이를 활용해 시장 추세를 정량적으로 표현합니다.
🔹 표준편차 필터링: Spread에 대해 EMA 및 표준편차 기반의 밴드를 적용해 노이즈를 줄이고 유효한 추세를 강조합니다.
🔹 컬러 기반 시각화: 오실레이터 값이 양수일 경우 초록색, 음수일 경우 마젠타 색으로 추세 방향을 직관적으로 파악할 수 있습니다.
🔹 밴드 범위 시각화: 상·하위 밴드를 통해 스프레드의 평균 편차 범위를 보여주며, 추세의 강약과 포화 여부를 진단할 수 있습니다.
🔹 제로 라인 표시: 추세 전환 가능 지점을 시각적으로 확인할 수 있도록 중심선(0선)을 제공합니다.
🛠️ 사용법 (How to Use)
✅ 오실레이터가 0 이상 유지: 상승 추세 구간이며, 롱 포지션 유지 또는 진입 검토
✅ 오실레이터가 0 이하 유지: 하락 추세 구간이며, 숏 포지션 유지 또는 진입 검토
⚠️ 상·하위 밴드를 이탈: 일시적인 과매수/과매도 혹은 강한 추세 발현 가능성 있음 → 다른 보조지표와 함께 필터링 권장
🔄 밴드 수렴: 추세가 약해지고 있음을 나타냄 → 변동성 하락 또는 방향성 상실 가능성 있음
권장 적용 시간대: 1시간봉, 4시간봉, 일봉
보조 적용 지표: RSI, MACD, OBV, SuperTrend 등과 함께 사용 시 신호 필터링에 유리
✅ 트레이딩뷰 하우스룰 준수사항 (TV House Rules Compliance)
이 지표는 **무료 공개용(Open-Source)**이며, Pine Script Version 5로 작성되어 있습니다.
과도한 리페인트, 비정상적 반복 경고(alert spam), 실시간 성능 저하 등의 요소는 포함되어 있지 않습니다.
사용자는 본 지표를 투자 결정의 참고용 보조 도구로 활용해야 하며, 독립적인 매매 판단이 필요합니다.
데이터 소스 및 계산 방식은 완전히 공개되어 있으며, 외부 API나 보안 취약점을 유발하는 구성 요소는 없습니다.
Two Poles Trend Finder MTF [BigBeluga]🔵 OVERVIEW
Two Poles Trend Finder MTF is a refined trend-following overlay that blends a two-pole Gaussian filter with a multi-timeframe dashboard. It provides a smooth view of price dynamics along with a clear summary of trend directions across multiple timeframes—perfect for traders seeking alignment between short and long-term momentum.
🔵 CONCEPTS
Two-Pole Filter: A smoothing algorithm that responds faster than traditional moving averages but avoids the noise of short-term fluctuations.
var float f = na
var float f_prev1 = na
var float f_prev2 = na
// Apply two-pole Gaussian filter
if bar_index >= 2
f := math.pow(alpha, 2) * source + 2 * (1 - alpha) * f_prev1 - math.pow(1 - alpha, 2) * f_prev2
else
f := source // Warm-up for first bars
// Shift state
f_prev2 := f_prev1
f_prev1 := f
Trend Detection Logic: Trend direction is determined by comparing the current filtered value with its value n bars ago (shifted comparison).
MTF Alignment Dashboard: Trends from 5 configurable timeframes are monitored and visualized as colored boxes:
• Green = Uptrend
• Magenta = Downtrend
Summary Arrow: An average trend score from all timeframes is used to plot an overall arrow next to the asset name.
🔵 FEATURES
Two-Pole Gaussian Filter offers ultra-smooth trend curves while maintaining responsiveness.
Multi-Timeframe Trend Detection:
• Default: 1H, 2H, 4H, 12H, 1D (fully customizable)
• Each timeframe is assessed independently using the same trend logic.
Visual Trend Dashboard positioned at the bottom-right of the chart with color-coded trend blocks.
Dynamic Summary Arrow shows overall market bias (🢁 / 🢃) based on majority of uptrends/downtrends.
Bold + wide trail plot for the filter value with gradient coloring based on directional bias.
🔵 HOW TO USE
Use the multi-timeframe dashboard to identify aligned trends across your preferred trading horizons.
Confirm trend strength or weakness by observing filter slope direction .
Look for dashboard consensus (e.g., 4 or more timeframes green] ) as confirmation for breakout, continuation, or trend reentry strategies.
Combine with volume or price structure to enhance entry timing.
🔵 CONCLUSION
Two Poles Trend Finder MTF delivers a clean and intuitive trend-following solution with built-in multi-timeframe awareness. Whether you’re trading intra-day or positioning for swing setups, this tool helps filter out market noise and keeps you focused on directional consensus.
EMA Trend Dashboard
Trend Indicator using 3 custom EMA lines. Displays a table with 5 rows(position configurable)
-First line shows relative position of EMA lines to each other and outputs Bull, Weak Bull, Flat, Weak Bear, or Bear. EMA line1 should be less than EMA line2 and EMA line 2 should be less than EMA line3. Default is 9,21,50.
-Second through fourth line shows the slant of each EMA line. Up, Down, or Flat. Threshold for what is considered a slant is configurable. Also added a "steep" threshold configuration for steep slants.
-Fifth line shows exhaustion and is a simple, configurable calculation of the distance between EMA line1 and EMA line2.
--Lines one and five change depending on its value but ALL other colors are able to be changed.
--Default is somewhat set to work well with Micro E-mini Futures but this indicator can be changed to work on anything. I created it to help get a quick overview of short-term trend on futures. I used ChatGPT to help but I am still not sure if it actually took longer because of it.
Wavelet-Trend ML Integration [Alpha Extract]Alpha-Extract Volatility Quality Indicator
The Alpha-Extract Volatility Quality (AVQ) Indicator provides traders with deep insights into market volatility by measuring the directional strength of price movements. This sophisticated momentum-based tool helps identify overbought and oversold conditions, offering actionable buy and sell signals based on volatility trends and standard deviation bands.
🔶 CALCULATION
The indicator processes volatility quality data through a series of analytical steps:
Bar Range Calculation: Measures true range (TR) to capture price volatility.
Directional Weighting: Applies directional bias (positive for bullish candles, negative for bearish) to the true range.
VQI Computation: Uses an exponential moving average (EMA) of weighted volatility to derive the Volatility Quality Index (VQI).
Smoothing: Applies an additional EMA to smooth the VQI for clearer signals.
Normalization: Optionally normalizes VQI to a -100/+100 scale based on historical highs and lows.
Standard Deviation Bands: Calculates three upper and lower bands using standard deviation multipliers for volatility thresholds.
Signal Generation: Produces overbought/oversold signals when VQI reaches extreme levels (±200 in normalized mode).
Formula:
Bar Range = True Range (TR)
Weighted Volatility = Bar Range × (Close > Open ? 1 : Close < Open ? -1 : 0)
VQI Raw = EMA(Weighted Volatility, VQI Length)
VQI Smoothed = EMA(VQI Raw, Smoothing Length)
VQI Normalized = ((VQI Smoothed - Lowest VQI) / (Highest VQI - Lowest VQI) - 0.5) × 200
Upper Band N = VQI Smoothed + (StdDev(VQI Smoothed, VQI Length) × Multiplier N)
Lower Band N = VQI Smoothed - (StdDev(VQI Smoothed, VQI Length) × Multiplier N)
🔶 DETAILS
Visual Features:
VQI Plot: Displays VQI as a line or histogram (lime for positive, red for negative).
Standard Deviation Bands: Plots three upper and lower bands (teal for upper, grayscale for lower) to indicate volatility thresholds.
Reference Levels: Horizontal lines at 0 (neutral), +100, and -100 (in normalized mode) for context.
Zone Highlighting: Overbought (⋎ above bars) and oversold (⋏ below bars) signals for extreme VQI levels (±200 in normalized mode).
Candle Coloring: Optional candle overlay colored by VQI direction (lime for positive, red for negative).
Interpretation:
VQI ≥ 200 (Normalized): Overbought condition, strong sell signal.
VQI 100–200: High volatility, potential selling opportunity.
VQI 0–100: Neutral bullish momentum.
VQI 0 to -100: Neutral bearish momentum.
VQI -100 to -200: High volatility, strong bearish momentum.
VQI ≤ -200 (Normalized): Oversold condition, strong buy signal.
🔶 EXAMPLES
Overbought Signal Detection: When VQI exceeds 200 (normalized), the indicator flags potential market tops with a red ⋎ symbol.
Example: During strong uptrends, VQI reaching 200 has historically preceded corrections, allowing traders to secure profits.
Oversold Signal Detection: When VQI falls below -200 (normalized), a lime ⋏ symbol highlights potential buying opportunities.
Example: In bearish markets, VQI dropping below -200 has marked reversal points for profitable long entries.
Volatility Trend Tracking: The VQI plot and bands help traders visualize shifts in market momentum.
Example: A rising VQI crossing above zero with widening bands indicates strengthening bullish momentum, guiding traders to hold or enter long positions.
Dynamic Support/Resistance: Standard deviation bands act as dynamic volatility thresholds during price movements.
Example: Price reversals often occur near the third standard deviation bands, providing reliable entry/exit points during volatile periods.
🔶 SETTINGS
Customization Options:
VQI Length: Adjust the EMA period for VQI calculation (default: 14, range: 1–50).
Smoothing Length: Set the EMA period for smoothing (default: 5, range: 1–50).
Standard Deviation Multipliers: Customize multipliers for bands (defaults: 1.0, 2.0, 3.0).
Normalization: Toggle normalization to -100/+100 scale and adjust lookback period (default: 200, min: 50).
Display Style: Switch between line or histogram plot for VQI.
Candle Overlay: Enable/disable VQI-colored candles (lime for positive, red for negative).
The Alpha-Extract Volatility Quality Indicator empowers traders with a robust tool to navigate market volatility. By combining directional price range analysis with smoothed volatility metrics, it identifies overbought and oversold conditions, offering clear buy and sell signals. The customizable standard deviation bands and optional normalization provide precise context for market conditions, enabling traders to make informed decisions across various market cycles.
Trend Finder Using Pull Back Method {Darkoexe}This indicator predicts trends using pull backs structure to predict the trend direction. It builds off the flag pattern concept but it uses precise precise measurements to determine trend direction.
A pull back occurs every time the price direction switches then closes either below or above the open of the previous candle depending on the type of pull back, bullish or bearish.
For an up trend to be a defined, when a bullish pull back occurs and does not go below the previous low, if the price then passes above the start of the pull back, an up trend signal will be printed. Only bullish pull backs will be displayed during an up trend.
For a down trend to be defined, when a bearish pull back occurs and does not go above the previous high, if the price then passes below the start of the pull back, a down trend signal will be printed. Only bearish pull backs will be displayed during a down trend.
If the conditions for an up trend or down trend are not met, no trend will be printed. Both bearish and bullish pull backs will be displayed during a no trend.
All the labels colors can be changed.
//Darkoexe
Trend Table ZeeZeeMonMulti-Timeframe Trend Indicator
Overview
This indicator identifies trends across multiple higher timeframes and displays them in a widget on the right side of the chart. It serves as an alternative trend-filtering tool, helping traders align with the dominant market direction. Unlike traditional moving average-based trend detection (e.g., price above/below a 200 MA), this indicator assesses whether higher timeframes are genuinely trending by analyzing swing highs and lows.
Trend Definition
Uptrend: Higher highs and higher lows.
Downtrend: Lower highs and lower lows.
A trend reversal occurs when a prior high/low is breached (e.g., in a downtrend, breaking the last high signals an uptrend).
Customization Options
Lookback Period: Adjusts the sensitivity for identifying swing highs/lows (pivot points). A shorter lookback detects more frequent pivots.
Historical Pivot Visibility: Toggle to display past swing highs/lows for verification.
Support/Resistance Lines: Show dynamic levels from recent pivots on higher timeframes. Breaching these lines indicates potential trend changes.
Purpose
Helps traders:
Confirm higher timeframe trends before entering trades.
Monitor proximity to trend reversals.
Fine-tune pivot sensitivity for optimal trend detection.
Note: Works best as a supplementary trend filter alongside other trading strategies.
Trend vs Range DetectorMarkets often oscillate between trend phases and range-bound consolidations. Accurately identifying which environment you're in can dramatically improve your strategy's performance — whether you're a breakout trader, trend follower, or mean reversion specialist.
This Pine Script helps do exactly that — with zero clutter, no chart overlays, and a simple, clean table at the top-right corner telling you one thing:
👉 Is the market trending or range-bound?
⚙️ How It Works
The script uses two core metrics to classify the market environment:
1. Slope Sensitivity of Moving Average
A simple moving average (default: 50-period) is used.
The absolute slope of the moving average is calculated.
If the slope exceeds a user-defined sensitivity value, it indicates directional momentum.
2. ATR-to-Price Range Ratio
Measures volatility by comparing Average True Range (ATR) to the total high-low price range over the same period.
A higher ATR relative to the range indicates directional volatility — a trending behavior.
A low ratio signals a choppy or sideways market.
If both conditions are met, the table displays "Trending." If either condition fails, it shows "Range-Bound."
🧠 Why This Matters
Trend Traders: Know when to lean into momentum plays.
Mean Reversion Traders: Avoid whipsaw conditions or capitalize on sideways action.
Volatility Filters: Use this signal to apply different strategies to different market types.
🛠️ User Controls
Moving Average Length: Adjust trend sensitivity by length (default: 50)
Slope Sensitivity: Tune how steep a trend needs to be to qualify
ATR/Range Threshold: Calibrate what defines a volatile enough trend move
Toggle Table On/Off: Keep the chart clean if needed
🧼 Clean Visuals
No lines, no bands, no background colors.
Just a concise table in the top-right corner.
Perfect for scalpers, swing traders, or overlaying on busy strategies.
🔄 Real-Time + Historical
The script dynamically updates with every bar, so it works in real time and shows accurate historical context across any symbol or timeframe.
If you’re someone who wants a minimalist yet powerful insight into market context, this tool can be a game-changer.
Ehlers Adaptive Trend Indicator [Alpha Extract]Ehlers Adaptive Trend Indicator
The Ehlers Adaptive Trend Indicator combines Ehlers' advanced digital signal processing techniques with dynamic volatility bands to identify robust trend conditions and potential reversals. This powerful tool helps traders visualize trend strength, adaptive support/resistance levels, and momentum shifts across various market conditions.
🔶 CALCULATION
The indicator employs a sophisticated adaptive algorithm that responds to changing market conditions:
• Ehlers Filter : Calculates a weighted average based on momentum differences to create an adaptive trend baseline.
• Dynamic Bands : Volatility-adjusted bands that expand and contract based on recent price action.
• Trend Level : A dynamic support/resistance level that adapts to the current trend direction.
• Smoothed Volatility : Market volatility measured and smoothed to provide reliable band width.
Formula:
• Ehlers Basis = Weighted average of price, with weights determined by momentum differences
• Volatility = Standard deviation of price over Ehlers Length period
• Smoothed Volatility = EMA of volatility over Smoothing Length
• Upper Band = Ehlers Basis + Smoothed Volatility × Sensitivity
• Lower Band = Ehlers Basis - Smoothed Volatility × Sensitivity
• Trend Level = Adaptive support in uptrends, resistance in downtrends
🔶 DETAILS
Visual Features :
• Ehlers Basis Line (Yellow): The core adaptive trend reference that serves as the primary trend indicator.
• Trend Level Line (Dynamic Color): Changes between green (bullish) and red (bearish) based on the current trend state.
• Fill Areas : Transparent green fill during bullish trends and transparent red fill during bearish trends for clear visual identification.
• Bar Coloring : Optional price bar coloring that reflects the current trend direction for enhanced visualization.
Interpretation :
• **Bullish Signal**: Price crosses above the upper band, triggering a trend change with the Trend Level becoming dynamic support.
• **Bearish Signal**: Price drops below the lower band, confirming a trend change with the Trend Level becoming dynamic resistance.
• **Trend Continuation**: Trend Level rises in bullish markets and falls in bearish markets, providing adaptive trailing support/resistance.
🔶 EXAMPLES
The chart demonstrates:
• Bullish Trend Identification : When price breaks above the upper band, the indicator shifts to bullish mode with green trend level and fill.
• Bearish Trend Identification : When price falls below the lower band, the indicator shifts to bearish mode with red trend level and fill.
• Trend Persistence : Trend Level adapts to market movement, rising during uptrends to provide dynamic support and falling during downtrends to act as resistance.
Example Snapshots :
• During a strong uptrend, the Trend Level continuously adjusts upward, keeping traders in the trend while filtering out minor retracements.
• During trend reversals, clear color changes and Trend Level shifts provide early warning of potential direction changes.
🔶 SETTINGS
Customization Options :
• Ehlers Length (p1) (Default: 30): Controls the primary adaptive calculation period, balancing responsiveness with stability.
• Momentum Length (p2) (Default: 25): Determines the lag for momentum calculations used in the adaptive weighting.
• Smoothing Length (Default: 10): Adjusts the volatility smoothing period—higher values provide more stable bands.
• Sensitivity (Default: 1.0): Multiplier for band width—higher values increase distance between bands, lower values tighten them.
• Visual Settings : Customizable colors for bullish and bearish trends, basis line, and optional bar coloring.
The Ehlers Adaptive Trend Indicator combines John Ehlers' digital signal processing expertise with modern volatility analysis to create a robust trend-following system that adapts to changing market conditions, helping traders stay on the right side of the market.
Trend Zone Moving Averages📈 Trend Zone Moving Averages
The Trend Zone Moving Averages indicator helps traders quickly identify market trends using the 50SMA, 100SMA, and 200SMA. With dynamic background colors, customizable settings, and real-time alerts, this tool provides a clear view of bullish, bearish, and extreme trend conditions.
🔹 Features:
Trend Zones with Dynamic Background Colors
Green → Bullish Trend (50SMA > 100SMA > 200SMA, price above 50SMA)
Red → Bearish Trend (50SMA < 100SMA < 200SMA, price below 50SMA)
Yellow → Neutral Trend (Mixed signals)
Dark Green → Extreme Bullish (Price above all three SMAs)
Dark Red → Extreme Bearish (Price below all three SMAs)
Customizable Moving Averages
Toggle 50SMA, 100SMA, and 200SMA on/off from the settings.
Perfect for traders who prefer a cleaner chart.
Real-Time Trend Alerts
Get instant notifications when the trend changes:
🟢 Bullish Zone Alert – When price enters a bullish trend.
🔴 Bearish Zone Alert – When price enters a bearish trend.
🟡 Neutral Zone Alert – When trend shifts to neutral.
🌟 Extreme Bullish Alert – When price moves above all SMAs.
⚠️ Extreme Bearish Alert – When price drops below all SMAs.
✅ Perfect for Any Market
Works on stocks, forex, crypto, and commodities.
Adaptable for day traders, swing traders, and investors.
⚙️ How to Use: Trend Zone Moving Averages Strategy
This strategy helps traders identify and trade with the trend using the Trend Zone Moving Averages indicator. It works across stocks, forex, crypto, and commodities.
🟢 Bullish Trend Strategy (Green Background)
Objective: Look for buying opportunities when the market is in an uptrend.
Entry Conditions:
✅ Background is Green (Bullish Zone).
✅ Price is above the 50SMA (confirming strength).
✅ Price pulls back to the 50SMA and bounces OR breaks above a key resistance level.
Stop Loss:
🔹 Place below the most recent swing low or just under the 50SMA.
Take Profit:
🔹 First target at the next resistance level or recent swing high.
🔹 Second target if price continues higher—trail stops to lock in profits.
🔴 Bearish Trend Strategy (Red Background)
Objective: Look for shorting opportunities when the market is in a downtrend.
Entry Conditions:
✅ Background is Red (Bearish Zone).
✅ Price is below the 50SMA (confirming weakness).
✅ Price pulls back to the 50SMA and rejects OR breaks below a key support level.
Stop Loss:
🔹 Place above the most recent swing high or just above the 50SMA.
Take Profit:
🔹 First target at the next support level or recent swing low.
🔹 Second target if price keeps falling—trail stops to secure profits.
🌟 Extreme Trend Strategy (Dark Green / Dark Red Background)
Objective: Trade with momentum when the market is in a strong trend.
Entry Conditions:
✅ Dark Green Background → Extreme Bullish: Price is above all three SMAs (strong uptrend).
✅ Dark Red Background → Extreme Bearish: Price is below all three SMAs (strong downtrend).
Trade Execution:
🔹 For longs (Dark Green): Look for breakout entries above resistance or pullbacks to the 50SMA.
🔹 For shorts (Dark Red): Look for breakdown entries below support or rejections at the 50SMA.
Risk Management:
🔹 Use tighter stop losses and trail profits aggressively to maximize gains.
🟡 Neutral Trend Strategy (Yellow Background)
Objective: Avoid trading or wait for a breakout.
What to Do:
🔹 Avoid trading in this zone—price is indecisive.
🔹 Wait for confirmation (background turns green/red) before taking a trade.
🔹 Use alerts to notify you when the trend resumes.
📌 Final Tips
Use this strategy with price action for extra confirmation.
Combine with support/resistance levels to improve accuracy.
Set alerts for trend changes so you never miss an opportunity.
Enjoy!
Gradient Trend Filter STRATEGY [ChartPrime/PineIndicators]This strategy is based on the Gradient Trend Filter indicator developed by ChartPrime. Full credit for the concept and indicator goes to ChartPrime.
The Gradient Trend Filter Strategy is designed to execute trades based on the trend analysis and filtering system provided by the Gradient Trend Filter indicator. It integrates a noise-filtered trend detection system with a color-gradient visualization, helping traders identify trend strength, momentum shifts, and potential reversals.
How the Gradient Trend Filter Strategy Works
1. Noise Filtering for Smoother Trends
To reduce false signals caused by market noise, the strategy applies a three-stage smoothing function to the source price. This function ensures that trend shifts are detected more accurately, minimizing unnecessary trade entries and exits.
The filter is based on an Exponential Moving Average (EMA)-style smoothing technique.
It processes price data in three successive passes, refining the trend signal before generating trade entries.
This filtering technique helps eliminate minor fluctuations and highlights the true underlying trend.
2. Multi-Layered Trend Bands & Color-Based Trend Visualization
The Gradient Trend Filter constructs multiple trend bands around the filtered trend line, acting as dynamic support and resistance zones.
The mid-line changes color based on the trend direction:
Green for uptrends
Red for downtrends
A gradient cloud is formed around the trend line, dynamically shifting colors to provide early warning signals of trend reversals.
The outer bands function as potential support and resistance, helping traders determine stop-loss and take-profit zones.
Visualization elements used in this strategy:
Trend Filter Line → Changes color between green (bullish) and red (bearish).
Trend Cloud → Dynamically adjusts color based on trend strength.
Orange Markers → Appear when a trend shift is confirmed.
Trade Entry & Exit Conditions
This strategy automatically enters trades based on confirmed trend shifts detected by the Gradient Trend Filter.
1. Trade Entry Rules
Long Entry:
A bullish trend shift is detected (trend direction changes to green).
The filtered trend value crosses above zero, confirming upward momentum.
The strategy enters a long position.
Short Entry:
A bearish trend shift is detected (trend direction changes to red).
The filtered trend value crosses below zero, confirming downward momentum.
The strategy enters a short position.
2. Trade Exit Rules
Closing a Long Position:
If a bearish trend shift occurs, the strategy closes the long position.
Closing a Short Position:
If a bullish trend shift occurs, the strategy closes the short position.
The trend shift markers (orange diamonds) act as a confirmation signal, reinforcing the validity of trade entries and exits.
Customization Options
This strategy allows traders to adjust key parameters for flexibility in different market conditions:
Trade Direction: Choose between Long Only, Short Only, or Long & Short .
Trend Length: Modify the length of the smoothing function to adapt to different timeframes.
Line Width & Colors: Customize the visual appearance of trend lines and cloud colors.
Performance Table: Enable or disable the equity performance table that tracks historical trade results.
Performance Tracking & Reporting
A built-in performance table is included to monitor monthly and yearly trading performance.
The table calculates monthly percentage returns, displaying them in a structured format.
Color-coded values highlight profitable months (blue) and losing months (red).
Tracks yearly cumulative performance to assess long-term strategy effectiveness.
Traders can use this feature to evaluate historical performance trends and optimize their strategy settings accordingly.
How to Use This Strategy
Identify Trend Strength & Reversals:
Use the trend line and cloud color changes to assess trend strength and detect potential reversals.
Monitor Momentum Shifts:
Pay attention to gradient cloud color shifts, as they often appear before the trend line changes color.
This can indicate early momentum weakening or strengthening.
Act on Trend Shift Markers:
Use orange diamonds as confirmation signals for trend shifts and trade entry/exit points.
Utilize Cloud Bands as Support/Resistance:
The outer bands of the cloud serve as dynamic support and resistance, helping with stop-loss and take-profit placement.
Considerations & Limitations
Trend Lag: Since the strategy applies a smoothing function, entries may be slightly delayed compared to raw price action.
Volatile Market Conditions: In high-volatility markets, trend shifts may occur more frequently, leading to higher trade frequency.
Optimized for Trend Trading: This strategy is best suited for trending markets and may produce false signals in sideways (ranging) conditions.
Conclusion
The Gradient Trend Filter Strategy is a trend-following system based on the Gradient Trend Filter indicator by ChartPrime. It integrates noise filtering, trend visualization, and gradient-based color shifts to help traders identify strong market trends and potential reversals.
By combining trend filtering with a multi-layered cloud system, the strategy provides clear trade signals while minimizing noise. Traders can use this strategy for long-term trend trading, momentum shifts, and support/resistance-based decision-making.
This strategy is a fully automated system that allows traders to execute long, short, or both directions, with customizable settings to adapt to different market conditions.
Credit for the original concept and indicator goes to ChartPrime.
MT-Trend Zone IdentifierTrend Zone Identifier – A Dynamic Market Trend Mapping Tool
Overview
The Trend Zone Identifier is an advanced TradingView indicator that helps traders visualize different market trend phases. By leveraging Pivot Points, Moving Averages (MA), ADX (Average Directional Index), and Retest Confirmation, this tool identifies uptrend, downtrend, and ranging (sideways) conditions dynamically.
This indicator is designed to segment the market into clear trend zones, allowing traders to distinguish between confirmed trends, trend transitions (pending zones), and ranging markets. It provides an intuitive visual overlay to enhance market structure analysis and assist in decision-making.
Key Features
✔ Trend Zone Identification – Classifies price action into Uptrend (Green), Downtrend (Red), Pending Confirmation (Light Colors), and Sideways Market (Gray/Neutral)
✔ Pivot-Based Breakout & Breakdown Detection – Uses pivot highs/lows to determine trend shifts
✔ Moving Average & ADX Validation – Ensures the trend is backed by MA structure and ADX trend strength
✔ Pullback Confirmation – Allows trend confirmation based on price retesting key levels
✔ Extreme Volatility & Gaps Filtering – Optional ATR-based extreme movement filtering to avoid false signals
✔ Multi-Timeframe Support – Option to integrate higher timeframe trend validation
✔ Customizable Sensitivity – Fine-tune MA smoothing, ADX thresholds, pivot detection, and pullback range
How It Works
1. Trend Classification
• Uptrend (Green): Price is above a key MA, ADX confirms strength, and a pivot breakout occurs
• Downtrend (Red): Price is below a key MA, ADX confirms strength, and a pivot breakdown occurs
• Pending Trend (Light Colors): Initial trend breakout or breakdown is detected but requires further confirmation
• Sideways/Ranging (Gray): ADX signals a weak trend, and price remains within a neutral zone
2. Retest & Confirmation Logic
• A trend is only confirmed after a breakout or breakdown followed by a successful retest
• If the market fails the retest, the indicator resets to a neutral state
3. Custom Filters for Optimization
• Enable or disable volume filtering for confirmation
• Adjust pivot sensitivity to detect major or minor swing points
• Choose to require consecutive bars confirming the breakout/breakdown
Ideal Use Cases
🔹 Swing traders who want to capture trend transitions early
🔹 Trend-following traders who rely on confirmed market cycles
🔹 Range traders looking to identify sideways market zones
🔹 Algorithmic traders who need clean trend segmentation for automated strategies
Final Thoughts
The Trend Zone Identifier is a versatile market structure indicator that helps traders define trend cycles visually and avoid trading against weak trends. By providing clear breakout, breakdown, and retest conditions, it enhances market clarity and reduces decision-making errors.
➡ Add this to your TradingView workspace and start analyzing market trends like a pro! 🚀
