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.
"scalping" için komut dosyalarını ara
Hilly 2.0 Advanced Crypto Scalping Strategy - 1 & 5 Min ChartsHow to Use
Copy the Code: Copy the script above.
Paste in TradingView: Open TradingView, go to the Pine Editor (bottom of the chart), paste the code, and click “Add to Chart.”
Check for Errors: Verify no errors appear in the Pine Editor console. The script uses Pine Script v5 (@version=5).
Select Timeframe:
1-Minute Chart: Use defaults (emaFastLen=7, emaSlowLen=14, rsiLen=10, rsiOverbought=80, rsiOversold=20, slPerc=0.5, tpPerc=1.0, useCandlePatterns=false).
5-Minute Chart: Adjust to emaFastLen=9, emaSlowLen=21, rsiLen=14, rsiOverbought=75, rsiOversold=25, slPerc=0.8, tpPerc=1.5, useCandlePatterns=true.
Apply to Chart: Use a liquid crypto pair (e.g., BTC/USDT, ETH/USDT on Binance or Coinbase).
Verify Signals:
Green “BUY” or “EMA BUY” labels and triangle-up arrows below candles.
Red “SELL” or “EMA SELL” labels and triangle-down arrows above candles.
Green/red background highlights for signal candles.
Arrows use size.normal for consistent visibility.
Backtest: Use TradingView’s Strategy Tester to evaluate performance over 1–3 months, checking Net Profit, Win Rate, and Drawdown.
Demo Test: Run on a demo account to confirm signal visibility and performance before trading with real funds.
AMF PG Strategy_v2The AMF PG Strategy (Praetorian Guard) is an advanced trading system designed to seamlessly adapt to market conditions. Its unique structure balances precise entries with intelligent protection, giving traders confidence in both trending and volatility environments.
Key points include:
Adaptive Core (AMF Engine) – A dynamic framework that automatically adjusts for clearer long- and short-term opportunities and generates a robust tracking line.
Praetorian Guard – A built-in protective shield that activates in extreme conditions and helps stabilize performance when markets become turbulent.
Versatility – Effective across multiple timeframes, from scalping to swing trading, without constant parameter adjustments.
Clarity – Clear visual signals and color-coded monitoring for instant decision-making.
This strategy is designed for traders who want more than just entries and exits; it offers a command center for disciplined, adaptable, and resilient trading.
Disclaimer:
It should be noted that no strategy is guaranteed. This strategy does not provide buy-sell-hold advice. Responsibility rests with the user.
Version 2: Bugs overlooked in Version 1 have been corrected and improvements have been made.
Sniper Swing — Short TF (Clean Signals) [v6]📘 How to Use the Sniper Swing Indicator
1. What It Does
It looks for short-term swing breaks in price.
It uses an oscillator (RSI/Stoch) and swing pivots to confirm moves.
It gives you 3 clear signals only:
BUY → Enter long (expecting price to go up).
Gay bear → Enter short (expecting price to go down).
EXIT → Close your trade (long or short).
Candles also change color:
Green = in a BUY trade.
Red = in a Gay bear trade.
Neutral (gray/none) = no trade.
2. When to Use
Works best on short timeframes (1m–5m) for scalping/intraday.
Use on liquid markets (MES/ES, NQ, SPY, BTC, ETH).
Avoid dead hours with no volume (like overnight futures lull or midday chop).
3. How to Trade With It
A. BUY trade
Wait for a BUY triangle below the candle.
Confirm:
Candle turned green.
Price broke a recent swing high.
Oscillator shows strength (indicator does this for you).
Enter long at the close of that candle.
Place your stop-loss:
At the yellow stop line (auto trailing stop), or
Just below the last swing low.
Stay in while candles are green.
Exit when:
An orange X appears, or
Price hits your stop.
B. Gay bear (short) trade
Wait for a Gay bear triangle above the candle.
Confirm:
Candle turned red.
Price broke a recent swing low.
Oscillator shows weakness.
Enter short at the close of that candle.
Place stop-loss:
At the yellow stop line, or
Just above the last swing high.
Stay in while candles are red.
Exit on an orange X or stop hit.
4. Pro Tips for New Traders
Only take one signal at a time → don’t double dip.
Quality > Quantity: ignore weak, sideways markets. Best signals happen during trends.
Start small: trade micros (MES) or small position sizes.
Use alerts: set TradingView alerts for BUY/Gay bear/EXIT so you don’t miss setups.
Think of the indicator like a navigator: it tells you the likely path, but you’re the driver → always manage risk.
5. Quick Mental Checklist
Signal? (BUY or Gay bear triangle)
Confirmed? (candle color + swing break)
Enter? (on close)
Stop? (yellow line or swing)
Exit? (orange X or stop)
Perp Imbalance Zones • Pro (clean)USD Premium (perp vs spot) → (Perp − Spot) / Spot.
Imbalance (z-score of that premium) → how extreme the current premium is relative to its own history over lenPrem bars.
Hysteresis state machine → flips to a SHORT bias when perp-long pressure is extreme; flips to LONG bias when perp-short pressure is extreme. It exits only after the imbalance cools (prevents whipsaw).
Price stretch filter (±σ) → optional Bollinger check so signals only fire when price is already stretched.
HTF confirmation (optional) → require higher-timeframe imbalance to agree with the current-TF bias.
Gradient visuals → line + background tint deepen as |z| grows (more extreme pressure).
What you see on the pane
A single line (z):
Above 0 = perp richer than spot (perp longs pressing).
Below 0 = perp cheaper than spot (perp shorts pressing).
Guides: dotted levels at ±enterZ (entry) and ±exitZ (cool-off/exit).
Background tint:
Red when state = SHORT bias (perp longs heavy).
Blue when state = LONG bias (perp shorts heavy).
Tint intensity scales with |z| (via hotZ).
Labels (optional): prints when bias flips.
Alerts (optional): “Enter SHORT/LONG bias” and “Exit bias”.
How to use it (playbook)
Attach & set symbols
Put the script on your chart.
Set Spot symbol and Perp symbol to the venue you trade (e.g., BINANCE:BTCUSDT + BINANCE:BTCUSDTPERP).
Read the bias
SHORT bias (red background): perp longs over-extended. Look for short entries if price is at resistance, σ-stretched, or your PA system agrees.
LONG bias (blue background): perp shorts over-extended. Look for long entries at support/σ-stretched down.
Entries
Use the bias flip as a context/confirm. Combine with your structure trigger (OB/level sweep, rejection wick, micro-break in market structure, etc.).
If useSigma=true, only trade when price is already ≥ upper band (shorts) or ≤ lower band (longs).
Exits
Bias auto-exits when |z| falls below exitZ.
You can also take profits at your levels or when the line fades back toward 0 while price mean-reverts to the middle band.
Tuning (what each knob does)
enterZ / exitZ (signal strictness + hysteresis)
Higher enterZ → fewer, cleaner signals (e.g., 1.8–2.2).
exitZ should be lower than enterZ (e.g., 0.6–1.0) to prevent flicker.
lenPrem (context window for z)
Larger (50–100) = steadier baseline, fewer signals.
Smaller (20–30) = more reactive, more signals.
smoothLen (EMA on z)
2–3 = snappier; 5–7 = smoother/laggier but cleaner.
useSigma, bbLen, bbK (price-stretch filter)
On filters chop. Try bbLen=100, bbK=1.0–1.5.
Off if you want more frequent signals or you already gate with your own σ/Keltner.
useHTF, htfTF, htfZmin (trend/confirmation)
Turn on to require higher-TF imbalance agreement (e.g., trading 1H → confirm with 4H htfTF=240, htfZmin≈0.6–1.0).
hotZ (visual intensity)
Lower (2.0–2.5) heats up faster; higher (4.0) is more subtle.
Ready-made presets
Conservative swing (fewer, higher-conviction):
enterZ=2.0, exitZ=1.0, lenPrem=60–80, smoothLen=5, useSigma=true, bbK=1.5, useHTF=true (240/0.8).
Balanced intraday (default feel):
enterZ=1.6–1.8, exitZ=0.8–1.0, lenPrem=50, smoothLen=3–4, useSigma=true, bbK=1.0–1.25, useHTF=false/true depending on trendiness.
Aggressive scalping (more signals):
enterZ=1.2–1.4, exitZ=0.6–0.8, lenPrem=20–30, smoothLen=2–3, useSigma=false, useHTF=false.
Practical tips
Don’t trade the line in isolation. Use it to time trades into your levels: VWAP bands, Monday high/low, prior POC/VAH/VAL, order blocks, etc.
Perp-led reversals often snap—be ready to scale out quickly back to mid-bands.
Venue matters. Keep spot & perp from the same exchange family to avoid cross-venue quirks.
Alerts: enable after you’ve tuned thresholds for your timeframe so you only get high-quality pings.
Swing Oracle Stock// (\_/)
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📌 Swing Oracle Stock – Professional Cycle & Trend Detection Indicator
The Swing Oracle Stock is an advanced market analysis tool designed to highlight price cycles, trend shifts, and key trading zones with precision. It combines trendline dynamics, normalized oscillators, and multi-timeframe confirmation into a single comprehensive indicator.
🔑 Key Features
NDOS (Normalized Dynamic Oscillator System):
Measures price strength relative to recent highs and lows to detect overbought, neutral, and oversold zones.
Dynamic Trendline (EMA8 or SMA231):
Flexible source selection for adapting to different trading styles (scalping vs. swing).
Multi-Timeframe H1 Confirmation:
Adds higher-timeframe validation to improve signal reliability.
Automated Buy & Sell Signals:
Triggered only on significant crossovers above/below defined levels.
Weekly Cycles (7-day M5 projection):
Tracks recurring time-based market cycles to anticipate reversal points.
Intuitive Visualization:
Colored zones (high, low, neutral) for quick market context.
Optional background and candlestick coloring for better clarity.
Multi-Timeframe Cross Table:
Automatically compares SMA50 vs. EMA200 across multiple timeframes (1m → 4h), showing clear status:
⭐️⬆️ UP = bullish trend confirmation
💀⬇️ Drop = bearish trend confirmation
📊 Built-in Statistical Tools
Normalized difference between short and long EMA.
Projected normalized mean levels plotted directly on the main chart.
Dynamic analysis of price distance from SMA50 to capture market “waves.”
🎯 Use Cases
Spot trend reversals with multi-timeframe confirmation.
Identify powerful breakout and breakdown zones.
Time entries and exits based on trend + cycle confluence.
Enhance market timing for swing trades, scalps, or long-term positions.
⚡ Swing Oracle Stock brings together cycle detection, oscillator normalization, and multi-timeframe confirmation into one streamlined indicator for traders who want a professional edge.
AMF PG Strategy AMF Command Center Strategy (Praetorian Guard)
The AMF PG Strategy (Praetorian Guard) is an advanced trading system built to adapt seamlessly across market conditions. Its unique structure balances precision entries with intelligent protection, giving traders confidence in both trending and volatile environments.
Key highlights include:
Adaptive Core (AMF Engine) – A dynamic framework that automatically adjusts and generates a powerful tracking line for clearer long and short opportunities.
Praetorian Guard – A built-in protective shield that activates in extreme conditions, helping stabilize performance when markets become turbulent.
Versatility – Effective across multiple timeframes, from scalping to swing trading, without constant parameter adjustments.
Clarity – Clean visual signals and color-coded tracking for instant decision-making.
This strategy was designed for traders who want more than just entries and exits — it offers a command center for disciplined, adaptive, and resilient trading.
1H Candlestick vs EMA Crossover# Description — 1H Candlestick vs EMA Crossover (Pine Script)
This indicator is built in **TradingView Pine Script v5** and is designed to track the relationship between the **1‑hour candlestick close** and the **1‑hour Exponential Moving Average (EMA)**. It works on any chart timeframe but always pulls in **1H data** using `request. security`.
### Core Features
* **Customizable EMA length** (default = 200)
* **Plots the 1H EMA** as an orange line on your chart
* Optionally shows the **1H close** as a faint gray line for reference
* Detects and highlights when the **1H candle close crosses above or below the 1H EMA**
* **Arrows**: Green triangles appear below the bar when a bullish crossover happens (1H close > EMA); red triangles appear above the bar when a bearish crossover happens (1H close < EMA)
* **Alerts**: Built‑in `alert condition` statements let you create TradingView alerts whenever a crossover occurs
### How to Use
1. Adjust the EMA length if you want a faster or slower moving average.
2. Enable alerts: Right‑click the chart → Add Alert → choose this indicator and select either “crossed ABOVE EMA” or “crossed BELOW EMA.”
### Trading Applications
* **Trend Confirmation**: Use the 1H EMA as a higher‑timeframe filter while trading on lower timeframes.
* **Entry/Exit Signals**: Crossovers can mark potential entry points for trend continuation or reversals.
* **Scalping/Intraday**: Even on a 5m or 15m chart, you can overlay the 1H EMA to align your trades with the bigger trend.
This makes the indicator a simple yet powerful tool for aligning trades with higher‑timeframe momentum and avoiding false signals from lower‑timeframe noise.
EMA20 Cross Strategy with countertrades and signalsEMA20 Cross Strategy Documentation
Overview
The EMA20 Cross Strategy with Counter-Trades and Instant Signals is a Pine Script (version 6) trading strategy designed for the TradingView platform. It implements an Exponential Moving Average (EMA) crossover system to generate buy and sell signals, with optional trend filtering, session-based trading, instant signal processing, and visual/statistical feedback. The strategy supports counter-trades (closing opposing positions before entering new ones) and operates with a fixed trade size in EUR.
Features
EMA Crossover Mechanism:
Uses a short-term EMA (configurable length, default: 1) and a long-term EMA (default: 20) to detect crossovers.
A buy signal is generated when the short EMA crosses above the long EMA.
A sell signal is generated when the short EMA crosses below the long EMA.
Instant Signals:
If enabled (useInstantSignals), signals are based on the current price crossing the short EMA, rather than waiting for the candle close.
This allows faster trade execution but may increase sensitivity to price fluctuations.
Trend Filter:
Optionally filters trades based on the trend direction (useTrendFilter).
Long trades are allowed only when the short EMA (or price, for instant signals) is above the long EMA.
Short trades are allowed only when the short EMA (or price) is below the long EMA.
Session Filter:
Restricts trading to specific market hours (sessionStart, default: 09:00–17:00) if enabled (useSessionFilter).
Ensures trades occur only during active market sessions, reducing exposure to low-liquidity periods.
Customizable Timeframe:
The EMA calculations can use a higher timeframe (e.g., 5m, 15m, 1H, 4H, 1D, default: 1H) via request.security.
This allows the strategy to base signals on longer-term trends while operating on a shorter-term chart.
Trade Management:
Fixed trade size of €100,000 per trade (tradeAmount), with a maximum quantity cap (maxQty = 10,000) to prevent oversized trades.
Counter-trades: Closes short positions before entering a long position and vice versa.
Trades are executed with a minimum quantity of 1 to ensure valid orders.
Visualization:
EMA Lines: The short EMA is colored based on the last signal (green for buy, red for sell, gray for neutral), and the long EMA is orange.
Signal Markers: Displays buy/sell signals as arrows (triangles) above/below candles if enabled (showSignalShapes).
Background/Candle Coloring: Optionally colors the chart background or candles green (bullish) or red (bearish) based on the trend (useColoredBars).
Statistics Display:
If enabled (useStats), a label on the chart shows:
Total closed trades
Open trades
Win rate (%)
Number of winning/losing trades
Profit factor (gross profit / gross loss)
Net profit
Maximum drawdown
Configuration Inputs
EMA Short Length (emaLength): Length of the short-term EMA (default: 1).
Trend EMA Length (trendLength): Length of the long-term EMA (default: 20).
Enable Trend Filter (useTrendFilter): Toggles trend-based filtering (default: true).
Color Candles (useColoredBars): Colors candles instead of the background (default: true).
Enable Session Filter (useSessionFilter): Restricts trading to specified hours (default: false).
Trading Session (sessionStart): Defines trading hours (default: 09:00–17:00).
Show Statistics (useStats): Displays performance stats on the chart (default: true).
Show Signal Arrows (showSignalShapes): Displays buy/sell signals as arrows (default: true).
Use Instant Signals (useInstantSignals): Generates signals based on live price action (default: false).
EMA Timeframe (emaTimeframe): Timeframe for EMA calculations (options: 5m, 15m, 1H, 4H, 1D; default: 1H).
Strategy Logic
Signal Generation:
Standard Mode: Signals are based on EMA crossovers (short EMA crossing long EMA) at candle close.
Instant Mode: Signals are based on the current price crossing the short EMA, enabling faster reactions.
Trade Execution:
On a buy signal, closes any short position and opens a long position.
On a sell signal, closes any long position and opens a short position.
Position size is calculated as the minimum of €100,000 or available equity, divided by the current price, capped at 10,000 units.
Filters:
Trend Filter: Ensures trades align with the trend direction (if enabled).
Session Filter: Restricts trades to user-defined market hours (if enabled).
Visual Feedback
EMA Lines: Provide a clear view of the short and long EMAs, with the short EMA’s color reflecting the latest signal.
Signal Arrows: Large green triangles (buy) below candles or red triangles (sell) above candles for easy signal identification.
Chart Coloring: Highlights bullish (green) or bearish (red) trends via background or candle colors.
Statistics Label: Displays key performance metrics in a label above the chart for quick reference.
Usage Notes
Initial Capital: €100,000 (configurable via initial_capital).
Currency: EUR (set via currency).
Order Processing: Orders are processed at candle close (process_orders_on_close=true) unless instant signals are enabled.
Dynamic Requests: Allows dynamic timeframe adjustments for EMA calculations (dynamic_requests=true).
Platform: Designed for TradingView, compatible with any market supported by the platform (e.g., stocks, forex, crypto).
Example Use Case
Scenario: Trading on a 5-minute chart with a 1-hour EMA timeframe, trend filter enabled, and session filter set to 09:00–17:00.
Behavior: The strategy will:
Calculate EMAs on the 1-hour timeframe.
Generate buy signals when the short EMA crosses above the long EMA (and price is above the long EMA).
Generate sell signals when the short EMA crosses below the long EMA (and price is below the long EMA).
Execute trades only during 09:00–17:00.
Display green/red candles and performance stats on the chart.
Limitations
Instant Signals: May lead to more frequent signals, increasing the risk of false positives in volatile markets.
Fixed Trade Size: Does not adjust dynamically based on market conditions beyond equity and max quantity limits.
Session Filter: Simplified and may not account for complex session rules or holidays.
Statistics: Displayed on-chart, which may clutter the view in smaller charts.
Customization
Adjust emaLength and trendLength to suit different market conditions (e.g., shorter for scalping, longer for swing trading).
Toggle useInstantSignals for faster or more stable signal generation.
Modify sessionStart to align with specific market hours.
Disable useStats or showSignalShapes for a cleaner chart.
This strategy is versatile for both manual and automated trading, offering flexibility for various markets and trading styles while providing clear visual and statistical feedback.
VWAP MTF Scalping ModuleThe VWAP MTF indicator allows you to visualize anchored VWAP across multiple timeframes, while maintaining a clean and responsive display.
Designed for intraday traders, scalpers, and swing traders, this module offers a clear view of volume-weighted average price zones across key timeframes (1m, 5m, 15m, 1h... customizable).
Multi-Timeframe HTS Retest Strategy v6Multi-Timeframe HTS Retest Strategy v6 is a trend-following tool designed to detect high-probability retest entries aligned with higher timeframe direction. The indicator applies HTS bands (short & long) on both the current and higher timeframe (4x–8x multiplier) to confirm market bias.
A strong trend is validated when HTS bands separate on the higher timeframe. On the lower timeframe, the strategy tracks price behavior relative to the bands: after breaking outside, price must retest either the fast (blue) or slow (red) band, confirmed by a rejection candle. This generates precise BUY or SELL retest signals.
Features include flexible average methods (RMA, EMA, SMA, etc.), customizable cross detection (final cross, 4 crosses, or both), volume-based retest conditions, and clear visual signals (dots for trend start, triangles for retests). Alerts are integrated for automation.
This strategy is suitable for forex, crypto, indices, and stocks, supporting both scalping and swing trading.
Vagas-dctang(8~13)Overview
The Vegas Tunnel EMA 8-13 is a refined technical analysis indicator that utilizes two key exponential moving averages (8-period and 13-period EMAs) to create a dynamic tunnel system for identifying trend direction and potential support/resistance zones. This indicator is specifically designed to help traders visualize price action within the context of short-term trend dynamics.
Key Features
✅ Dual EMA Tunnel System: Creates a visual tunnel between 8 EMA (fast) and 13 EMA (slow) to identify trend channels ✅ Dynamic Support Detection: The tunnel acts as dynamic support during uptrends and resistance during downtrends ✅ Trend Confirmation: Price position relative to the tunnel helps confirm the current market trend ✅ Entry/Exit Signals: Tunnel crossovers and price interactions provide clear trading signals ✅ Multi-Timeframe Compatible: Works effectively across various timeframes from scalping to swing trading
How It Works
The Vegas Tunnel EMA 8-13 operates on the principle that shorter-period EMAs react more quickly to price changes, creating a responsive tunnel system:
Bullish Tunnel: When 8 EMA > 13 EMA, the tunnel indicates an upward trend with potential support zones
Bearish Tunnel: When 8 EMA < 13 EMA, the tunnel indicates a downward trend with potential resistance zones
Tunnel Width: The distance between EMAs indicates trend strength and volatility
Price Interaction: Bounces off the tunnel boundaries suggest trend continuation, while breaks may signal reversals
Trading Applications
Trend Following: Use tunnel direction to align trades with the prevailing trend
Support/Resistance Trading: Enter long positions when price bounces off tunnel support, short when rejected at resistance
Breakout Strategy: Trade tunnel breaks as potential trend continuation or reversal signals
Risk Management: Use tunnel boundaries as dynamic stop-loss levels
Advantages Over Traditional Moving Averages
Reduced Noise: The tunnel system filters out minor price fluctuations
Visual Clarity: Easy identification of trend channels and key levels
Faster Response: 8-13 period combination provides quicker signals than longer-term systems
Versatile Application: Suitable for various trading styles and market conditions
Best Practices
Combine with volume analysis for stronger signal confirmation
Consider higher timeframe tunnel direction for context
Use proper risk management with position sizing
Backtest on your preferred instruments and timeframes
This indicator is ideal for traders seeking a clean, effective tool for trend analysis and dynamic support/resistance identification in fast-moving markets.
Sequential Pattern Strength [QuantAlgo]🟢 Overview
The Sequential Pattern Strength indicator measures the power and sustainability of consecutive price movements by tracking unbroken sequences of up or down closes. It incorporates sequence quality assessment, price extension analysis, and automatic exhaustion detection to help traders identify when strong trends are losing momentum and approaching potential reversal or continuation points.
🟢 How It Works
The indicator's key insight lies in its sequential pattern tracking system, where pattern strength is measured by analyzing consecutive price movements and their sustainability:
if close > close
upSequence := upSequence + 1
downSequence := 0
else if close < close
downSequence := downSequence + 1
upSequence := 0
The system calculates sequence quality by measuring how "perfect" the consecutive moves are:
perfectMoves = math.max(upSequence, downSequence)
totalMoves = math.abs(bar_index - ta.valuewhen(upSequence == 1 or downSequence == 1, bar_index, 0))
sequenceQuality = totalMoves > 0 ? perfectMoves / totalMoves : 1.0
First, it tracks price extension from the sequence starting point:
priceExtension = (close - sequenceStartPrice) / sequenceStartPrice * 100
Then, pattern exhaustion is identified when sequences become overextended:
isExhausted = math.abs(currentSequence) >= maxSequence or
math.abs(priceExtension) > resetThreshold * math.abs(currentSequence)
Finally, the pattern strength combines sequence length, quality, and price movement with momentum enhancement:
patternStrength = currentSequence * sequenceQuality * (1 + math.abs(priceExtension) / 10)
enhancedSignal = patternStrength + momentum * 10
signal = ta.ema(enhancedSignal, smooth)
This creates a sequence-based momentum indicator that combines consecutive movement analysis with pattern sustainability assessment, providing traders with both directional signals and exhaustion insights for entry/exit timing.
🟢 Signal Interpretation
Positive Values (Above Zero): Sequential pattern strength indicating bullish momentum with consecutive upward price movements and sustained buying pressure = Long/Buy opportunities
Negative Values (Below Zero): Sequential pattern strength indicating bearish momentum with consecutive downward price movements and sustained selling pressure = Short/Sell opportunities
Zero Line Crosses: Pattern transitions between bullish and bearish regimes, indicating potential trend changes or momentum shifts when sequences break
Upper Threshold Zone: Area above maximum sequence threshold (2x maxSequence) indicating extremely strong bullish patterns approaching exhaustion levels
Lower Threshold Zone: Area below negative threshold (-2x maxSequence) indicating extremely strong bearish patterns approaching exhaustion levels
Smart Structure Breaks & Order BlocksOverview (What it does)
The indicator “Smart Structure Breaks & Order Blocks” detects market structure using swing highs and lows, identifies Break of Structure (BOS) events, and automatically draws order blocks (OBs) from the origin candle. These zones extend to the right and change color/outline when mitigated or invalidated. By formalizing and automating part of discretionary analysis, it provides consistent zone recognition.
Main Components
Swing Detection: ta.pivothigh/ta.pivotlow identify confirmed swing points.
BOS Detection: Determines if the recent swing high/low is broken by close (strict mode) or crossover.
OB Creation: After a BOS, the opposite candle (bearish for bullish BOS, bullish for bearish BOS) is used to generate an order block zone.
Zone Management: Limits the number of zones, extends them to the right, and tracks tagged (mitigated) or invalidated states.
Input Parameters
Left/Right Pivot (default 6/6): Number of bars required on each side to confirm a swing. Higher values = smoother swings.
Max Zones (default 4): Maximum zones stored per direction (bull/bear). Oldest zones are overwritten.
Zone Confirmation Lookback (default 3): Ensures OB origin candle validity by checking recent highs/lows.
Show Swing Points (default ON): Displays triangles on swing highs/lows.
Require close for BOS? (default ON): Strict BOS (close required) vs loose BOS (line crossover).
Use candle body for zones (default OFF): Zones drawn from candle body (ON) or wick (OFF).
Signal Definition & Logic
Swing Updates: Latest confirmed pivots update lastHighLevel / lastLowLevel.
BOS (Break of Structure):
Bullish – close breaks last swing high.
Bearish – close breaks last swing low.
Only one valid BOS per swing (avoids duplicates).
OB Detection:
Bullish BOS → previous bearish candle with lowest low forms the OB.
Bearish BOS → previous bullish candle with highest high forms the OB.
Zones: Bull = green, Bear = red, semi-transparent, extended to the right.
Zone States:
Mitigated: Price touches the zone → border highlighted.
Invalidated:
Bull zone → close below → turns red.
Bear zone → close above → turns green.
Chart Appearance
Swing High: red triangle above bar
Swing Low: green triangle below bar
Bull OB: green zone (border highlighted on touch)
Bear OB: red zone (border highlighted on touch)
Invalid Zones: Bull zones turn reddish, Bear zones turn greenish
Practical Use (Trading Assistance)
Trend Following Entries: Buy pullbacks into green OBs in uptrends, sell rallies into red OBs in downtrends.
Focus on First Touch: First mitigation after BOS often has higher reaction probability.
Confluence: Combine with higher timeframe trend, volume, session levels, key price levels (previous highs/lows, VWAP, etc.).
Stops/Targets:
Bull – stop below zone, partial take profit at swing high or resistance.
Bear – stop above zone, partial take profit at swing low or support.
Parameter Tuning (per market/timeframe)
Pivot (6/6 → 4/4/8/8): Lower for scalping (3–5), medium for day trading (5–8), higher for swing trading (8–14). Increase to reduce noise.
Strict Break: ON to reduce false breaks in ranging markets; OFF for earlier signals.
Body Zones: ON for assets with long wicks, OFF for cleaner OBs in liquid instruments.
Zone Confirmation (default 3): Increase for stricter OB origin, fewer zones.
Max Zones (default 4 → 6–10): Increase for higher volatility, decrease to avoid clutter.
Strengths
Standardizes BOS and OB detection that is usually subjective.
Tracks mitigation and invalidation automatically.
Adaptable: allows body/wick zone switching for different instruments.
Limitations
Pivot-based: Signals appear only after pivots confirm (slight lag).
Zones reflect past balance: Can fail after new events (news, earnings, macro data).
Range-heavy markets: More false BOS; consider stricter settings.
Backtesting: This script is for drawing/visual aid; trading rules must be defined separately.
Workflow Example
Identify higher timeframe trend (4H/Daily).
On lower TF (15–60m), wait for BOS and new OB.
Enter on first mitigation with confirmation candle.
Stop beyond zone; targets based on R multiples and swing points.
FAQ
Q: Why are zones invalidated quickly?
A: Flow reversal after BOS. Adjust pivots higher, enable Strict mode, or switch to Body zones to reduce noise.
Q: What does “tagged” mean?
A: Price touched the zone once = mitigated. Implies some orders in that zone may have been filled.
Q: Body or Wick zones?
A: Wick zones are fine in clean markets. For volatile pairs with long wicks, body zones provide more realistic areas.
Customization Tips (Code perspective)
Zone storage: Currently ring buffer ((idx+1) % zoneLimit). Could prioritize keeping unmitigated zones.
Automated testing: Add strategy.entry/exit for rule-based backtests.
Multi-timeframe: Use request.security() for higher timeframe swings/BOS.
Visualization: Add labels for BOS bars, tag zones with IDs, count touches.
Summary
This indicator formalizes the cycle Swing → BOS → OB creation → Mitigation/Invalidation, providing consistent structure analysis and zone tracking. By tuning sensitivity and strictness, and combining with higher timeframe context, it enhances pullback/continuation trading setups. Always combine with proper risk management.
50% of Previous 1H Candle (Color Logic)📌 Script Title: 50% Midpoint of Previous 1H Candle (Color Coded)
📝 Description:
This indicator draws a horizontal line at the 50% (midpoint) of the most recently closed 1-hour candle, helping traders visualize intraday support/resistance and sentiment bias.
🔹 Key Features:
Plots the midpoint of the last 1H candle as a horizontal line.
Color-coded line and label:
🟢 Green: Previous candle was bullish
🔴 Red: Previous candle was bearish
⚪ Gray: Neutral (doji or equal open/close)
Displays the exact price level with a floating label.
Works on any lower timeframe chart (e.g., 5m, 15m, 30m).
Automatically updates every hour after the 1H candle closes.
📈 Use Cases:
Trade around the 1H midpoint as a dynamic pivot zone.
Confirm or fade price breakouts/rejections at this level.
Use it with trendlines, supply/demand zones, or VWAP.
🔍 Technical Notes:
The midpoint is calculated using:
Midpoint = (High + Low) / 2
from the most recent closed 1H candle.
Color logic is based on whether the 1H candle closed above or below its open.
🚀 Enhancement Ideas (future updates):
Add optional alerts on cross of the midpoint.
Show multiple historical midpoint levels.
Input toggle to enable/disable color coding.
Whether you’re scalping intraday or watching for reaction zones, this tool gives you a clean, real-time level to anchor your trades around.
Happy trading! 💹
— Built with ❤️ in Pine Script v6
Advanced Range Analyzer ProAdvanced Range Analyzer Pro – Adaptive Range Detection & Breakout Forecasting
Overview
Advanced Range Analyzer Pro is a comprehensive trading tool designed to help traders identify consolidations, evaluate their strength, and forecast potential breakout direction. By combining volatility-adjusted thresholds, volume distribution analysis, and historical breakout behavior, the indicator builds an adaptive framework for navigating sideways price action. Instead of treating ranges as noise, this system transforms them into opportunities for mean reversion or breakout trading.
How It Works
The indicator continuously scans price action to identify active range environments. Ranges are defined by volatility compression, repeated boundary interactions, and clustering of volume near equilibrium. Once detected, the indicator assigns a strength score (0–100), which quantifies how well-defined and compressed the consolidation is.
Breakout probabilities are then calculated by factoring in:
Relative time spent near the upper vs. lower range boundaries
Historical breakout tendencies for similar structures
Volume distribution inside the range
Momentum alignment using auxiliary filters (RSI/MACD)
This creates a live probability forecast that updates as price evolves. The tool also supports range memory, allowing traders to analyze the last completed range after a breakout has occurred. A dynamic strength meter is displayed directly above each consolidation range, providing real-time insight into range compression and breakout potential.
Signals and Breakouts
Advanced Range Analyzer Pro includes a structured set of visual tools to highlight actionable conditions:
Range Zones – Gradient-filled boxes highlight active consolidations.
Strength Meter – A live score displayed in the dashboard quantifies compression.
Breakout Labels – Probability percentages show bias toward bullish or bearish continuation.
Breakout Highlights – When a breakout occurs, the range is marked with directional confirmation.
Dashboard Table – Displays current status, strength, live/last range mode, and probabilities.
These elements update in real time, ensuring that traders always see the current state of consolidation and breakout risk.
Interpretation
Range Strength : High scores (70–100) indicate strong consolidations likely to resolve explosively, while low scores suggest weak or choppy ranges prone to false signals.
Breakout Probability : Directional bias greater than 60% suggests meaningful breakout pressure. Equal probabilities indicate balanced compression, favoring mean-reversion strategies.
Market Context : Ranges aligned with higher timeframe trends often resolve in the dominant direction, while counter-trend ranges may lead to reversals or liquidity sweeps.
Volatility Insight : Tight ranges with low ATR imply imminent expansion; wide ranges signal extended consolidation or distribution phases.
Strategy Integration
Advanced Range Analyzer Pro can be applied across multiple trading styles:
Breakout Trading : Enter on probability shifts above 60% with confirmation of volume or momentum.
Mean Reversion : Trade inside ranges with high strength scores by fading boundaries and targeting equilibrium.
Trend Continuation : Focus on ranges that form mid-trend, anticipating continuation after consolidation.
Liquidity Sweeps : Use failed breakouts at boundaries to capture reversals.
Multi-Timeframe : Apply on higher timeframes to frame market context, then execute on lower timeframes.
Advanced Techniques
Combine with volume profiles to identify areas of institutional positioning within ranges.
Track sequences of strong consolidations for trend development or exhaustion signals.
Use breakout probability shifts in conjunction with order flow or momentum indicators to refine entries.
Monitor expanding/contracting range widths to anticipate volatility cycles.
Custom parameters allow fine-tuning sensitivity for different assets (crypto, forex, equities) and trading styles (scalping, intraday, swing).
Inputs and Customization
Range Detection Sensitivity : Controls how strictly ranges are defined.
Strength Score Settings : Adjust weighting of compression, volume, and breakout memory.
Probability Forecasting : Enable/disable directional bias and thresholds.
Gradient & Fill Options : Customize range visualization colors and opacity.
Dashboard Display : Toggle live vs last range, info table size, and position.
Breakout Highlighting : Choose border/zone emphasis on breakout events.
Why Use Advanced Range Analyzer Pro
This indicator provides a data-driven approach to trading consolidation phases, one of the most common yet underutilized market states. By quantifying range strength, mapping probability forecasts, and visually presenting risk zones, it transforms uncertainty into clarity.
Whether you’re trading breakouts, fading ranges, or mapping higher timeframe context, Advanced Range Analyzer Pro delivers a structured, adaptive framework that integrates seamlessly into multiple strategies.
Intrabar Volume Delta — RealTime + History (Stocks/Crypto/Forex)Intrabar Volume Delta Grid — RealTime + History (Stocks/Crypto/Forex)
# Short Description
Shows intrabar Up/Down volume, Delta (absolute/relative) and UpShare% in a compact grid for both real-time and historical bars. Includes an MTF (M1…D1) dashboard, contextual coloring, density controls, and alerts on Δ and UpShare%. Smart historical splitting (“History Mode”) for Crypto/Futures/FX.
---
# What it does (Quick)
* **UpVol / DownVol / Δ / UpShare%** — visualizes order-flow inside each candle.
* **Real-time** — accumulates intrabar volume live by tick-direction.
* **History Mode** — splits Up/Down on closed bars via simple or range-aware logic.
* **MTF Dashboard** — one table view across M1, M5, M15, M30, H1, H4, D1 (Vol, Up/Down, Δ%, Share, Trend).
* **Contextual opacity** — stronger signals appear bolder.
* **Label density** — draw every N-th bar and limit to last X bars for performance.
* **Alerts** — thresholds for |Δ|, Δ%, and UpShare%.
---
# How it works (Real-Time vs History)
* **Real-time (open bar):** volume increments into **UpVolRT** or **DownVolRT** depending on last price move (↑ goes to Up, ↓ to Down). This approximates live order-flow even when full tick history isn’t available.
* **History (closed bars):**
* **None** — no split (Up/Down = 0/0). Safest for equities/indices with unreliable tick history.
* **Approx (Close vs Open)** — all volume goes to candle direction (green → Up 100%, red → Down 100%). Fast but yields many 0/100% bars.
* **Price Action Based** — splits by Close position within High-Low range; strength = |Close−mid|/(High−Low). Above mid → more Up; below mid → more Down. Falls back to direction if High==Low.
* **Auto** — **Stocks/Index → None**, **Crypto/Futures/FX → Approx**. If you see too many 0/100 bars, switch to **Price Action Based**.
---
# Rows & Meaning
* **Volume** — total bar volume (no split).
* **UpVol / DownVol** — directional intrabar volume.
* **Delta (Δ)** — UpVol − DownVol.
* **Absolute**: raw units
* **Relative (Δ%)**: Δ / (Up+Down) × 100
* **Both**: shows both formats
* **UpShare%** — UpVol / (Up+Down) × 100. >50% bullish, <50% bearish.
* Helpful icons: ▲ (>65%), ▼ (<35%).
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# MTF Dashboard (🔧 Enable Dashboard)
A single table with **Vol, Up, Down, Δ%, Share, Trend (🔼/🔽/⏭️)** for selected timeframes (M1…D1). Great for a fast “panorama” read of flow alignment across horizons.
---
# Inputs (Grouped)
## Display
* Toggle rows: **Volume / Up / Down / Delta / UpShare**
* **Delta Display**: Absolute / Relative / Both
## Realtime & History
* **History Mode**: Auto / None / Approx / Price Action Based
* **Compact Numbers**: 1.2k, 1.25M, 3.4B…
## Theme & UI
* **Theme Mode**: Auto / Light / Dark
* **Row Spacing**: vertical spacing between rows
* **Top Row Y**: moves the whole grid vertically
* **Draw Guide Lines**: faint dotted guides
* **Text Size**: Tiny / Small / Normal / Large
## 🔧 Dashboard Settings
* **Enable Dashboard**
* **📏 Table Text Size**: Tiny…Huge
* **🦓 Zebra Rows**
* **🔲 Table Border**
## ⏰ Timeframes (for Dashboard)
* **M1…D1** toggles
## Contextual Coloring
* **Enable Contextual Coloring**: opacity by signal strength
* **Δ% cap / Share offset cap**: saturation caps
* **Min/Max transparency**: solid vs faint extremes
## Label Density & Size
* **Show every N-th bar**: draw labels only every Nth bar
* **Limit to last X bars**: keep labels only in the most recent X bars
## Colors
* Up / Down / Text / Guide
## Alerts
* **Delta Threshold (abs)** — |Δ| in volume units
* **UpShare > / <** — bullish/bearish thresholds
* **Enable Δ% Alert**, **Δ% > +**, **Δ% < −** — relative delta levels
---
# How to use (Quick Start)
1. Add the indicator to your chart (overlay=false → separate pane).
2. **History Mode**:
* Crypto/Futures/FX → keep **Auto** or switch to **Price Action Based** for richer history.
* Stocks/Index → prefer **None** or **Price Action Based** for safer splits.
3. **Label Density**: start with **Limit to last X bars = 30–150** and **Show every N-th bar = 2–4**.
4. **Contextual Coloring**: keep on to emphasize strong Δ% / Share moves.
5. **Dashboard**: enable and pick only the TFs you actually use.
6. **Alerts**: set thresholds (ideas below).
---
# Alerts (in TradingView)
Add alert → pick this indicator → choose any of:
* **Delta exceeds threshold** (|Δ| > X)
* **UpShare above threshold** (UpShare% > X)
* **UpShare below threshold** (UpShare% < X)
* **Relative Delta above +X%**
* **Relative Delta below −X%**
**Starter thresholds (tune per symbol & TF):**
* **Crypto M1/M5**: Δ% > +25…35 (bullish), Δ% < −25…−35 (bearish)
* **FX (tick volume)**: UpShare > 60–65% or < 40–35%
* **Stocks (liquid)**: set **Absolute Δ** by typical volume scale (e.g., 50k / 100k / 500k)
---
# Notes by Market Type
* **Crypto/Futures**: 24/7 and high liquidity — **Price Action Based** often gives nicer history splits than Approx.
* **Forex (FX)**: TradingView volume is typically **tick volume** (not true exchange volume). Treat Δ/Share as tick-based flow, still very useful intraday.
* **Stocks/Index**: historical tick detail can be limited. **None** or **Price Action Based** is a safer default. If you see too many 0/100% shares, switch away from Approx.
---
# “All Timeframes” accuracy
* Works on **any TF** (M1 → D1/W1).
* **Real-time accuracy** is strong for the open bar (live accumulation).
* **Historical accuracy** depends on your **History Mode** (None = safest, Approx = fastest/simplest, Price Action Based = more nuanced).
* The MTF dashboard uses `request.security` and therefore follows the same logic per TF.
---
# Trade Ideas (Use-Cases)
* **Scalping (M1–M5)**: a spike in Δ% + UpShare>65% + rising total Vol → momentum entries.
* **Intraday (M5–M30–H1)**: when multiple TFs show aligned Δ%/Share (e.g., M5 & M15 bullish), join the trend.
* **Swing (H4–D1)**: persistent Δ% > 0 and UpShare > 55–60% → structural accumulation bias.
---
# Advantages
* **True-feeling live flow** on the open bar.
* **Adaptable history** (three modes) to match data quality.
* **Clean visual layout** with guides, compact numbers, contextual opacity.
* **MTF snapshot** for quick bias read.
* **Performance controls** (last X bars, every N-th bar).
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# Limitations & Care
* **FX uses tick volume** — interpret Δ/Share accordingly.
* **History Mode is an approximation** — confirm with trend/structure/liquidity context.
* **Illiquid symbols** can produce noisy or contradictory signals.
* **Too many labels** can slow charts → raise N, lower X, or disable guides.
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# Best Practices (Checklist)
* Crypto/Futures: prefer **Price Action Based** for history.
* Stocks: **None** or **Price Action Based**; be cautious with **Approx**.
* FX: pair Δ% & UpShare% with session context (London/NY) and volatility.
* If labels overlap: tweak **Row Spacing** and **Text Size**.
* In the dashboard, keep only the TFs you actually act on.
* Alerts: start around **Δ% 25–35** for “punchy” moves, then refine per asset.
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# FAQ
**1) Why do some closed bars show 0%/100% UpShare?**
You’re on **Approx** history mode. Switch to **Price Action Based** for smoother splits.
**2) Δ% looks strong but price doesn’t move — why?**
Δ% is an **order-flow** measure. Price also depends on liquidity pockets, sessions, news, higher-timeframe structure. Use confirmations.
**3) Performance slowdown — what to do?**
Lower **Limit to last X bars** (e.g., 30–100), increase **Show every N-th bar** (2–6), or disable **Draw Guide Lines**.
**4) Dashboard values don’t “match” the grid exactly?**
Dashboard is multi-TF via `request.security` and follows the history logic per TF. Differences are normal.
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# Short “Store” Marketing Blurb
Intrabar Volume Delta Grid reveals the order-flow inside every candle (Up/Down, Δ, UpShare%) — live and on history. With smart history splitting, an MTF dashboard, contextual emphasis, and flexible alerts, it helps you spot momentum and bias across Crypto, Forex (tick volume), and Stocks. Tidy labels and compact numbers keep the panel readable and fast.
Extreme Zone Volume ProfileExtreme Zone Volume Profile (EZVP)
Originality & Innovation
The Extreme Zone Volume Profile (EZVP) revolutionizes traditional volume profile analysis by applying statistical zone classification to volume distribution. Unlike standard volume profiles that display raw volume data, EZVP segments the price range into statistically meaningful zones based on percentile thresholds, allowing traders to instantly identify where volume concentration suggests strong support/resistance versus areas of potential breakout.
Technical Methodology
Core Algorithm:
Distributes volume across user-defined bins (20-200) over a lookback period
Calculates volume-weighted price levels for each bin
Applies percentile-based zone classification to the price range (not volume ranking)
Zone B (extreme zones): Outer percentile tails representing potential rejection areas
Zone A (significant zones): Secondary percentile bands indicating strong interest levels
Center Zone: Bulk trading range where most price discovery occurs
Mathematical Foundation:
The script uses price-range percentiles rather than volume percentiles. If the total price range is divided into 100%, Zone B captures the extreme price tails (default 2.5% each end ≈ 2 standard deviations), Zone A captures the next significant bands (default 14% each ≈ 1 standard deviation), leaving the center for normal distribution trading.
Key Calculations:
POC (Point of Control): Price level with maximum volume accumulation
Volume-weighted mean price: Total volume × price / total volume
Median price: Geometric center of the price range
Rightward-projected bars: Volume bars extend forward from current time to avoid historical chart clutter
Trading Applications
Zone Interpretation:
Zone B (Red/Green): Extreme price levels where volume suggests strong rejection potential. Price reaching these zones often indicates overextension and possible reversal points.
Zone A (Orange/Teal): Significant support/resistance areas with substantial volume interest. These levels often act as intermediate targets or consolidation zones.
Center (Gray): Fair value area where most trading occurs. Price tends to return to this range during normal market conditions.
Strategic Usage:
Reversal Trading: Look for rejection signals when price enters Zone B areas
Breakout Confirmation: Volume expansion beyond Zone B boundaries suggests genuine breakouts
Support/Resistance: Zone A boundaries often provide reliable entry/exit levels
Mean Reversion: Price tends to gravitate toward the volume-weighted mean and POC lines
Unique Value Proposition
EZVP addresses three key limitations of traditional volume profiles:
Visual Clarity: Standard profiles can be cluttered and difficult to interpret quickly. EZVP's color-coded zones provide instant visual feedback about price significance.
Statistical Framework: Rather than relying on subjective interpretation of volume nodes, EZVP applies objective percentile-based classification, making support/resistance identification more systematic.
Forward-Looking Display: Rightward-projecting bars keep historical price action clean while maintaining current market structure visibility.
Configuration Guide
Lookback Period (10-1000): Controls the historical depth of volume calculation. Shorter periods for intraday scalping, longer for swing trading.
Number of Bins (20-200): Resolution of volume distribution. Higher values provide more granular analysis but may create noise on lower timeframes.
Zone Percentages:
Zone B: Extreme threshold (default 2.5% = ~2σ statistical significance)
Zone A: Significant threshold (default 14% = ~1σ statistical significance)
Visual Controls: Toggle individual elements (POC, median, mean, zone lines) to customize display complexity for your trading style.
Technical Requirements
Pine Script v6 compatible
Maximum bars back: 5000 (ensures sufficient historical data)
Maximum boxes: 500 (supports high-resolution bin counts)
Maximum lines: 50 (accommodates all zone and reference lines)
This indicator synthesizes volume profile theory with statistical zone analysis, providing a quantitative framework for identifying high-probability support/resistance levels based on volume distribution patterns rather than arbitrary price levels.
5m Exit AlertsThese can help a lot with Daytrading if you don't have a price target in mind when there's no clear resistance / support nearby, and you don't trust the market enough to hold it as a swing trade.
Keep in mind that its main purpose is to give you a "warning" that it might be good to look at your screen, instead of guaranteeing you "now is the best time to exit". You won't reach high winning stats by blindly following this alert.
"A Exit LONG":
(I'm using letters instead of numbers for all Exit alerts to make sure I don't accidentally confuse Enter and Exit alerts).
There are 4 conditions that might trigger it. The reasons show up in the exit alert message (unfortunately only as a number, since alert messages can't have "dynamic text" in TradingView), and can also be displayed as symbols in the chart (see image above - make sure to enable "Show Signals" in the indicator settings first though).
Here are the conditions sorted from best to worst:
Technical reversal: Bearish Hammer candle with Volume > 2 * avg volume (of last 30 candles), when 5m candle closed. Reversal very likely. This is usually the best time to take your gains for the rest of the day.
EMA 3/8 cross: standard 5m EMA 3/8 cross, indicating a trend reversal, or at least a pullback. Can also be helpful to detect double tops / double bottoms.
Trailing Stop Loss: Crossed below 30m EMA 8, 5m candle closed. This is a "fallback" alert in case EMA 3 was already below EMA 8 before you set up the alert. It's not unlikely that the stock might go further down to VWAP, so depending on the chart and market this might be a good opportunity to save the gains you have left.
"Final" Stop Loss: Crossed below VWAP. Usually not a good sign. If you entered around VWAP your losses shouldn't be big yet, but if you plan on holding the stock the Daily chart and market outlook should better be quite convincing, and you wouldn't have needed to use this alert in the first place.
Keep in mind these work of course best if you picked a "good" stock: clear movement, tidy price action, high volume. Otherwise alerts are more likely to be triggered redundantly.
Always consider how the market and stock looks like, then decide whether to exit or not! Usually it makes sense to wait a bit to see f. e. whether the stock bounces off the 30m EMA 8, and it's just a pullback.
"B Enter SHORT":
Similar, but for shorts...
"C 1m Scalp LONG" + "D 1m Scalp SHORT":
Simple Scalping alert for EMA 3/8 cross on a 1m chart - but without needing to use a 1m chart to set it up!
Unfortunately it's not as accurate as manually setting this alert up on a 1m chart. It might be an advantage though that it sometimes is triggered 1-2 min later, since this means there are less redundant triggerings.
It can be useful esp. on high momentum trades, but I honestly haven't used it in a looong while.
"X Candle Close":
same as in 5m Entry indicator: triggered when 5m candle is confirmed
"Z Trend Change: UP" + "Z Trend Change: DOWN":
This one is meant to be used only on SPY: It alerts you when SPY is changing its trending direction, which might mean entering or closing existing trades.
I have therefore set it up to never end (by setting it to "Once Per Bar Close" in the alert settings).
It's based on DMI positive or negative being > 25. I had it based on VWAP at the beginning, but there were days where it was triggered every 5 minutes...
More infos: www.reddit.com
Moon Scalper v3 + VSAMoon Scalper v3 is a high-precision scalping indicator optimized for the 15-minute chart. It delivers clean buy/sell signals with TP1 (1:1 risk-reward) exits using layered confirmations:
• **Volatility Bands** — SMA + multiplier detect expansion zones
• **EMA Filter (200)** — ensures trades align with trend
• **RSI Range Filter** — avoids extreme overbought/oversold traps (buy: 52–62, sell: 38–48)
• **Volume Spike Filter** — filters for institutional activity (vol > 1.4×SMA)
• **VSA Confirmation** — requires wide-spread, high-volume bars with reclaim (volume × 1.4, spread × 1.5, reclaim 50%)
**Usage Notes:**
Best used on 15m timeframe for liquid pairs (e.g., BTCUSDT, ETHUSDT). Signals appear as “BUY” / “SELL” labels on chart. Defaults yield high TP1 hit rate; use only during active sessions (e.g., London/NY) for best accuracy.
**Disclaimer:**
This indicator is for educational purposes only. Past performance is not a guarantee of future results. Always backtest before live trading and manage risk responsibly.
Maiko Range Scalper (Sideways BB + RSI) – v4 cleanPurpose
It’s a range scalping strategy for crypto. It tries to take small, repeatable trades inside a sideways market: buy near the bottom of the range, sell near the middle/top (and the reverse for shorts).
Core idea (two timeframes)
Define the trading range on a higher timeframe (HTF)
You choose the HTF (e.g., 15m or 1h).
The script finds the highest high and lowest low over a lookback window (e.g., last 96 HTF candles) → these become HTF Resistance and HTF Support.
It also calculates the midline (average of support/resistance).
Trade signals on your lower timeframe (LTF)
You run the strategy on a fast chart (e.g., 1m or 5m).
Entries are only allowed inside the HTF range.
Entry logic (mean reversion)
Indicators on the LTF:
Bollinger Bands (length & std dev configurable).
RSI (length & thresholds configurable).
Optional VWAP proximity filter (price must be within X% of VWAP).
Long setup:
Price touches/under-cuts the lower Bollinger band AND RSI ≤ threshold (default 30) AND price is inside the HTF range (and passes VWAP filter if enabled).
Short setup:
Price touches/exceeds the upper Bollinger band AND RSI ≥ threshold (default 70) AND price is inside the HTF range (and passes VWAP filter if enabled).
Exits and risk
Stop-loss: placed just outside the HTF range with a configurable buffer %:
Long SL = HTF Support × (1 − buffer).
Short SL = HTF Resistance × (1 + buffer).
Take-profit (selectable):
Mid band (the Bollinger basis) → conservative, faster exits.
Opposite band / HTF boundary → more aggressive, higher RR but more give-backs.
Position sizing
A simple cap: maximum position size = percent of account equity (e.g., 20%).
The script calculates quantity from that cap and current price.
Plots you’ll see on the chart
HTF Resistance (red) and HTF Support (green) via plot().
HTF Midline (gray dashed) drawn with a line.new() object (because plot() cannot do dashed).
Bollinger basis/upper/lower on the LTF.
Optional VWAP line (only shown if you enable the filter).
Signal markers (green triangle up for Long setups, red triangle down for Short setups).
Alerts
Two alertconditions:
“Long Setup” – when a long entry condition appears.
“Short Setup” – when a short entry condition appears.
Create alerts from these to get notified in real time.
How to use it (quick start)
Add to a 1m or 5m chart of a liquid coin (BTC, ETH, SOL).
Set HTF timeframe (start with 1h) and lookback (e.g., 96 = ~4 days on 1h).
Keep default Bollinger/RSI first; tune later.
Choose TP mode:
“Mid band” for quick scalps.
“Opposite band/Range” if the range is very clean and you want bigger targets.
Set SL buffer (0.15–0.30% is common; adjust for volatility).
Set Max position % to control size (e.g., 20%).
(Optional) Enable VWAP filter to skip stretched moves.
When it works best
Clearly sideways markets with visible support/resistance on the HTF.
High-liquidity pairs where spreads/fees are small relative to your scalp target.
Limitations & safety notes
True breakouts will invalidate mean-reversion logic—your SL outside the range is there to cut losses fast.
Fees can eat into small scalps—prefer limit orders, rebates, and liquid pairs.
Backtest results vary by exchange data; always forward-test on small size.
If you want, I can:
Add an ATR-based stop/target option.
Provide a study-only version (signals/alerts, no trading engine).
Pre-set risk to your €5,000 plan (e.g., ~0.5% max loss/trade) with calculated qty.
Balance & Reversal Indicator [SYNC & TRADE]ndicator Description: "Balance & Reversal Indicator "
Purpose of the Indicator
The "Balance & Reversal Indicator " indicator is designed for analyzing market activity in cryptocurrency and other financial markets. It assists traders in identifying potential trend reversal points, detecting market equilibrium zones, and evaluating the balance between buying and selling volumes. The indicator is suitable for both short-term and long-term trading, offering flexible settings to adapt to various trading styles and timeframes.
What Does the Indicator Provide?
Volume Analysis: Calculates buy and sell volumes, along with the Long/Short Ratio, to assess current market dynamics.
Reversal Signals: Generates signals for potential Long (buy) and Short (sell) reversals based on customizable levels, ranging from "Potential Reversal" to "Maximum Signal."
Equilibrium Zones: Identifies zones where the market is in balance, useful for recognizing neutral market conditions.
Flexible Calculation Methods: Supports four volume calculation methods (Tick Based, Candle Based, Delta Based, Price Movement) to suit different trading approaches.
Auto and Manual Sensitivity: Offers "Auto" mode for timeframe-based sensitivity or "Manual" mode for custom sensitivity settings.
Data Visualization: Displays key metrics (total volume, buy/sell volumes, ratio, and percentages) via a comparison table and on-chart labels for easy interpretation.
Volume Unit Customization: Allows volume display in USDT, Active contracts, or other units for enhanced flexibility.
How to Use the Indicator?
Adding to the Chart:
Find "Balance & Reversal Indicator " in the TradingView library and add it to your chart.
The indicator appears in a separate panel below the chart, keeping price data unobstructed (overlay=false).
Configuring Settings:
Calculation Method: Choose one of four volume analysis methods:
Tick Based: Analyzes price movement within a candle.
Candle Based: Evaluates candle direction (up/down).
Delta Based: Considers the difference between open and close prices.
Price Movement: Assesses movement strength based on candle body and wick sizes.
Sensitivity Mode:
In "Auto" mode, sensitivity adjusts automatically based on the timeframe (e.g., higher for minute charts, lower for daily charts).
In "Manual" mode, set sensitivity manually (from 0.1 to 1.0).
Reversal Levels (Long/Short): Configure levels for Long and Short signals with associated ranges. For example, Long Reversal Level 1 = -30% with a 5% range triggers signals between -35% and -30%.
Equilibrium Levels: Set levels for neutral market zones (e.g., ±7% for Equilibrium Level 1).
Messages: Customize signal messages to align with your trading style.
Analysis Period (Start/End Time): Define the time range for volume calculations.
Volume Unit: Select USDT, Active (active contracts), or Contracts for volume display.
Interpreting Signals:
Comparison Table (Top-Right Corner): Displays analysis results for all four calculation methods (Long/Short Ratio, Buy %, Sell %, Signal), enabling method comparison.
On-Chart Labels: Show total volume, buy/sell volumes, Long/Short Ratio, buy/sell percentages, current method, and sensitivity.
Color-Coded Signals:
Green: Potential Long (buy) opportunity.
Red: Potential Short (sell) opportunity.
Yellow: Market in equilibrium zone.
Chart Levels: Horizontal lines indicate reversal levels (green for Long, red for Short, yellow for equilibrium) with a transparency gradient for clarity.
Applying in Trading:
Use reversal signals to enter positions. For example, a "Maximum Long Signal" may indicate a strong buying opportunity.
Equilibrium zones help avoid trading during low-volatility periods.
Compare methods in the table to confirm signals.
Adjust settings to match your timeframe and asset. For instance, use "Tick Based" with high sensitivity for scalping on minute charts or "Price Movement" with low sensitivity for long-term trading.
Recommendations:
Test the indicator on historical data to optimize settings for your asset and strategy.
Combine indicator signals with other technical analysis tools (e.g., support/resistance levels or trend indicators) for greater accuracy.
Regularly update the time range (Start/End Time) to ensure relevant data analysis.
Who Is This Indicator For?
"Balance & Reversal Indicator " is ideal for traders who:
Trade on cryptocurrency exchanges and want to analyze trading volumes.
Seek reversal points for entering Long or Short positions.
Prefer customizable settings and the ability to compare different analysis methods.
Operate across various timeframes, from minutes to months.
Note: This indicator is not financial advice. Always conduct your own analysis and consider risks before making trading decisions.
© TradingStrategyCourses, 2025. All rights reserved.
Intraday Scalping Trading System with AlertsThis is a unique script in the way it signals and alert on Volume Imbalances and VWAP based out on ATR. Many professional traders consider Volume Imbalance as a great indicator to identify stock movement.
I didn't find any indicator or all these option together so created one for us.
1. Fully controllable with toggle buttons.
2. Choose you best Trading directional signals with filters as per your sentiments -
2. EMA crossings
- EMA crossings + VWAP confirmation
- EMA crossings + SuperTrend Confirmation
3. Highest and Lowest volumes visually appeared
4. OHLCs Daily, Weekly and Monthly line options
5. First Candle Range - you can choose First candle range and it's time frame (default IST 9:15 but you can customize in pinescript as per your preferred Time Zone or just hide with toggle button.
