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Market Phase MAMarket Phase MA is an advanced trend-following indicator designed to provide traders with a dynamically colored moving average that adapts to market conditions. It uses a powerful combination of Average True Range (ATR) and Average Directional Index (ADX) to classify market trends in real-time. The indicator integrates a fully customizable moving average (SMA or EMA) to highlight trend phases clearly and effectively. Key Features & Advantages: ✔ Adaptive Trend Classification: Detects uptrends, downtrends, and sideways markets using a refined mix of ATR and ADX for more precise trend identification. ✔ Color-Coded Moving Average: The moving average dynamically changes color based on trend classification, providing a clean visual representation of market sentiment. ✔ Advanced ATR & ADX Filtering: - ATR measures market volatility and identifies ranging periods. - ADX confirms trend strength, reducing false signals. - A weighted approach balances ATR and ADX, ensuring reliability. ✔ Fully Customizable Moving Average: Traders can select between SMA and EMA while adjusting the moving average length directly from the settings panel. ✔ Smooth & Responsive Adjustments: The smoothing factor can be fine-tuned to control signal sensitivity and noise reduction, making it suitable for scalping, swing trading, and long-term trend monitoring. What Makes It Unique: - Unlike traditional trend indicators, Market Phase MA provides **direct visual feedback** on a moving average rather than using a separate oscillator. - It **adapts dynamically** to market conditions instead of relying on fixed thresholds. - The combination of **volatility and trend strength analysis** enhances precision in identifying valid trends. - Users can optimize **reaction speed vs. reliability** with adjustable parameters for better decision-making. How to Use It: - Identify Market Phases: The moving average color shifts based on trend type—**teal** for uptrends, **red** for downtrends, and **gray** for sideways markets. - Confirm Trend Strength: Persistent color shifts indicate strong trends, while frequent changes may suggest market indecision. - Use as a Trade Confirmation Tool: Complement it with **support & resistance zones, price action analysis, and volume indicators** for stronger confirmation signals. Market Phase MA is designed for traders seeking a clear, efficient, and highly adaptable moving average trend detection system. Whether you are a day trader, swing trader, or long-term investor, this indicator will help you identify and follow trends with confidence.
Indicatore Pine Script®
di Julien_Eche
6
DeepSignalFilterHelpersLibrary "DeepSignalFilterHelpers" filter_intraday_intensity(useIiiFilter)   Parameters:      useIiiFilter (bool) filter_vwma(src, length, useVwmaFilter)   Parameters:      src (float)      length (int)      useVwmaFilter (bool) filter_nvi(useNviFilter)   Parameters:      useNviFilter (bool) filter_emv(length, emvThreshold, useEmvFilter, useMovingAvg)   EMV filter for filtering signals based on Ease of Movement   Parameters:      length (int) : The length of the EMV calculation      emvThreshold (float) : The EMV threshold      useEmvFilter (bool) : Whether to apply the EMV filter      useMovingAvg (bool) : Whether to use moving average as threshold   Returns: Filtered result indicating whether the signal should be used filter_adi(length, threshold, useAdiFilter, useMovingAvg)   ADI filter for filtering signals based on Accumulation/Distribution Index   Parameters:      length (int) : The length of the ADI moving average calculation      threshold (float) : The ADI threshold      useAdiFilter (bool) : Whether to apply the ADI filter      useMovingAvg (bool) : Whether to use moving average as threshold   Returns: Filtered result indicating whether the signal should be used filter_mfi(length, mfiThreshold, useMfiFilter, useMovingAvg)   MFI filter for filtering signals based on Money Flow Index   Parameters:      length (int) : The length of the MFI calculation      mfiThreshold (float) : The MFI threshold      useMfiFilter (bool) : Whether to apply the MFI filter      useMovingAvg (bool) : Whether to use moving average as threshold   Returns: Filtered result indicating whether the signal should be used detect_obv_states(obvThresholdStrong, obvThresholdModerate, lookbackPeriod, obvMode)   detect_obv_states: Identify OBV states with three levels (Strong, Moderate, Weak) over a configurable period   Parameters:      obvThresholdStrong (float) : Threshold for strong OBV movements      obvThresholdModerate (float) : Threshold for moderate OBV movements      lookbackPeriod (int) : Number of periods to analyze OBV trends      obvMode (string) : OBV mode to filter ("Strong", "Moderate", "Weak")   Returns: OBV state ("Strong Up", "Moderate Up", "Weak Up", "Positive Divergence", "Negative Divergence", "Consolidation", "Weak Down", "Moderate Down", "Strong Down") filter_obv(src, length, obvMode, threshold, useObvFilter, useMovingAvg)   filter_obv: Filter signals based on OBV states   Parameters:      src (float) : The source series (default: close)      length (int) : The length of the OBV moving average calculation      obvMode (string) : OBV mode to filter ("Strong", "Moderate", "Weak")      threshold (float) : Optional threshold for additional filtering      useObvFilter (bool) : Whether to apply the OBV filter      useMovingAvg (bool) : Whether to use moving average as threshold   Returns: Filtered result indicating whether the signal should be used filter_cmf(length, cmfThreshold, useCmfFilter, useMovingAvg)   CMF filter for filtering signals based on Chaikin Money Flow   Parameters:      length (int) : The length of the CMF calculation      cmfThreshold (float) : The CMF threshold      useCmfFilter (bool) : Whether to apply the CMF filter      useMovingAvg (bool) : Whether to use moving average as threshold   Returns: Filtered result indicating whether the signal should be used filter_vwap(useVwapFilter)   VWAP filter for filtering signals based on Volume-Weighted Average Price   Parameters:      useVwapFilter (bool) : Whether to apply the VWAP filter   Returns: Filtered result indicating whether the signal should be used filter_pvt(length, pvtThreshold, usePvtFilter, useMovingAvg)   PVT filter for filtering signals based on Price Volume Trend   Parameters:      length (int) : The length of the PVT moving average calculation      pvtThreshold (float) : The PVT threshold      usePvtFilter (bool) : Whether to apply the PVT filter      useMovingAvg (bool) : Whether to use moving average as threshold   Returns: Filtered result indicating whether the signal should be used filter_vo(shortLength, longLength, voThreshold, useVoFilter, useMovingAvg)   VO filter for filtering signals based on Volume Oscillator   Parameters:      shortLength (int) : The length of the short-term volume moving average      longLength (int) : The length of the long-term volume moving average      voThreshold (float) : The Volume Oscillator threshold      useVoFilter (bool) : Whether to apply the VO filter      useMovingAvg (bool) : Whether to use moving average as threshold   Returns: Filtered result indicating whether the signal should be used filter_cho(shortLength, longLength, choThreshold, useChoFilter, useMovingAvg)   CHO filter for filtering signals based on Chaikin Oscillator   Parameters:      shortLength (int) : The length of the short-term ADI moving average      longLength (int) : The length of the long-term ADI moving average      choThreshold (float) : The Chaikin Oscillator threshold      useChoFilter (bool) : Whether to apply the CHO filter      useMovingAvg (bool) : Whether to use moving average as threshold   Returns: Filtered result indicating whether the signal should be used filter_fi(length, fiThreshold, useFiFilter, useMovingAvg)   FI filter for filtering signals based on Force Index   Parameters:      length (int) : The length of the FI calculation      fiThreshold (float) : The Force Index threshold      useFiFilter (bool) : Whether to apply the FI filter      useMovingAvg (bool) : Whether to use moving average as threshold   Returns: Filtered result indicating whether the signal should be used filter_garman_klass_volatility(length, useGkFilter)   Parameters:      length (int)      useGkFilter (bool) filter_frama(src, length, useFramaFilter)   Parameters:      src (float)      length (int)      useFramaFilter (bool) filter_bollinger_bands(src, length, stdDev, useBollingerFilter)   Parameters:      src (float)      length (int)      stdDev (float)      useBollingerFilter (bool) filter_keltner_channel(src, length, atrMult, useKeltnerFilter)   Parameters:      src (float)      length (simple int)      atrMult (float)      useKeltnerFilter (bool) regime_filter(src, threshold, useRegimeFilter)   Regime filter for filtering signals based on trend strength   Parameters:      src (float) : The source series      threshold (float) : The threshold for the filter      useRegimeFilter (bool) : Whether to apply the regime filter   Returns: Filtered result indicating whether the signal should be used regime_filter_v2(src, threshold, useRegimeFilter)   Regime filter for filtering signals based on trend strength   Parameters:      src (float) : The source series      threshold (float) : The threshold for the filter      useRegimeFilter (bool) : Whether to apply the regime filter   Returns: Filtered result indicating whether the signal should be used filter_adx(src, length, adxThreshold, useAdxFilter)   ADX filter for filtering signals based on ADX strength   Parameters:      src (float) : The source series      length (simple int) : The length of the ADX calculation      adxThreshold (int) : The ADX threshold      useAdxFilter (bool) : Whether to apply the ADX filter   Returns: Filtered result indicating whether the signal should be used filter_volatility(minLength, maxLength, useVolatilityFilter)   Volatility filter for filtering signals based on volatility   Parameters:      minLength (simple int) : The minimum length for ATR calculation      maxLength (simple int) : The maximum length for ATR calculation      useVolatilityFilter (bool) : Whether to apply the volatility filter   Returns: Filtered result indicating whether the signal should be used filter_ulcer(src, length, ulcerThreshold, useUlcerFilter)   Ulcer Index filter for filtering signals based on Ulcer Index   Parameters:      src (float) : The source series      length (int) : The length of the Ulcer Index calculation      ulcerThreshold (float) : The Ulcer Index threshold (default: average Ulcer Index)      useUlcerFilter (bool) : Whether to apply the Ulcer Index filter   Returns: Filtered result indicating whether the signal should be used filter_stddev(src, length, stdDevThreshold, useStdDevFilter)   Standard Deviation filter for filtering signals based on Standard Deviation   Parameters:      src (float) : The source series      length (int) : The length of the Standard Deviation calculation      stdDevThreshold (float) : The Standard Deviation threshold (default: average Standard Deviation)      useStdDevFilter (bool) : Whether to apply the Standard Deviation filter   Returns: Filtered result indicating whether the signal should be used filter_macdv(src, shortLength, longLength, signalSmoothing, macdVThreshold, useMacdVFilter)   MACD-V filter for filtering signals based on MACD-V   Parameters:      src (float) : The source series      shortLength (simple int) : The short length for MACD calculation      longLength (simple int) : The long length for MACD calculation      signalSmoothing (simple int) : The signal smoothing length for MACD      macdVThreshold (float) : The MACD-V threshold (default: average MACD-V)      useMacdVFilter (bool) : Whether to apply the MACD-V filter   Returns: Filtered result indicating whether the signal should be used filter_atr(length, atrThreshold, useAtrFilter)   ATR filter for filtering signals based on Average True Range (ATR)   Parameters:      length (simple int) : The length of the ATR calculation      atrThreshold (float) : The ATR threshold (default: average ATR)      useAtrFilter (bool) : Whether to apply the ATR filter   Returns: Filtered result indicating whether the signal should be used filter_candle_body_and_atr(length, bodyThreshold, atrThreshold, useFilter)   Candle Body and ATR filter for filtering signals   Parameters:      length (simple int) : The length of the ATR calculation      bodyThreshold (float) : The threshold for candle body size (relative to ATR)      atrThreshold (float) : The ATR threshold (default: average ATR)      useFilter (bool) : Whether to apply the candle body and ATR filter   Returns: Filtered result indicating whether the signal should be used filter_atrp(length, atrpThreshold, useAtrpFilter)   ATRP filter for filtering signals based on ATR Percentage (ATRP)   Parameters:      length (simple int) : The length of the ATR calculation      atrpThreshold (float) : The ATRP threshold (default: average ATRP)      useAtrpFilter (bool) : Whether to apply the ATRP filter   Returns: Filtered result indicating whether the signal should be used filter_jma(src, length, phase, useJmaFilter)   Parameters:      src (float)      length (simple int)      phase (float)      useJmaFilter (bool) filter_cidi(src, rsiLength, shortMaLength, longMaLength, useCidiFilter)   Parameters:      src (float)      rsiLength (simple int)      shortMaLength (int)      longMaLength (int)      useCidiFilter (bool) filter_rsi(src, length, rsiThreshold, useRsiFilter)   Parameters:      src (float)      length (simple int)      rsiThreshold (float)      useRsiFilter (bool) filter_ichimoku_oscillator(length, threshold, useFilter)   Ichimoku Oscillator filter for filtering signals based on Ichimoku Oscillator   Parameters:      length (int) : The length of the Ichimoku Oscillator calculation      threshold (float) : The threshold for the filter (default: average Ichimoku Oscillator)      useFilter (bool) : Whether to apply the filter   Returns: Filtered result indicating whether the signal should be used filter_cmb_composite_index(src, shortLength, longLength, threshold, useFilter)   CMB Composite Index filter for filtering signals based on CMB Composite Index   Parameters:      src (float) : The source series      shortLength (simple int) : The short length for CMB calculation      longLength (simple int) : The long length for CMB calculation      threshold (float) : The threshold for the filter (default: average CMB Composite Index)      useFilter (bool) : Whether to apply the filter   Returns: Filtered result indicating whether the signal should be used filter_connors_rsi(src, rsiLength, rocLength, streakLength, threshold, useFilter)   Connors RSI filter for filtering signals based on Connors RSI   Parameters:      src (float) : The source series      rsiLength (simple int) : The length for RSI calculation      rocLength (int) : The length for ROC calculation      streakLength (simple int) : The length for streak calculation      threshold (float) : The threshold for the filter (default: average Connors RSI)      useFilter (bool) : Whether to apply the filter   Returns: Filtered result indicating whether the signal should be used filter_coppock_curve(src, roc1Length, roc2Length, wmaLength, threshold, useFilter)   Coppock Curve filter for filtering signals based on Coppock Curve   Parameters:      src (float) : The source series      roc1Length (int) : The length for the first ROC calculation      roc2Length (int) : The length for the second ROC calculation      wmaLength (int) : The length for the WMA calculation      threshold (float) : The threshold for the filter (default: average Coppock Curve)      useFilter (bool) : Whether to apply the filter   Returns: Filtered result indicating whether the signal should be used filter_pmo(src, pmoLength, smoothingLength, threshold, useFilter)   DecisionPoint Price Momentum Oscillator filter for filtering signals based on PMO   Parameters:      src (float) : The source series      pmoLength (simple int) : The length for PMO calculation      smoothingLength (simple int) : The smoothing length for PMO      threshold (float) : The threshold for the filter (default: average PMO Oscillator)      useFilter (bool) : Whether to apply the filter   Returns: Filtered result indicating whether the signal should be used filter_macd(src, shortLength, longLength, signalSmoothing, threshold, useFilter)   MACD filter for filtering signals based on MACD   Parameters:      src (float) : The source series      shortLength (simple int) : The short length for MACD calculation      longLength (simple int) : The long length for MACD calculation      signalSmoothing (simple int) : The signal smoothing length for MACD      threshold (float) : The threshold for the filter (default: average MACD)      useFilter (bool) : Whether to apply the filter   Returns: Filtered result indicating whether the signal should be used filter_macd_histogram(src, shortLength, longLength, signalSmoothing, threshold, useFilter)   MACD-Histogram filter for filtering signals based on MACD-Histogram   Parameters:      src (float) : The source series      shortLength (simple int) : The short length for MACD calculation      longLength (simple int) : The long length for MACD calculation      signalSmoothing (simple int) : The signal smoothing length for MACD      threshold (float) : The threshold for the filter (default: average MACD-Histogram)      useFilter (bool) : Whether to apply the filter   Returns: Filtered result indicating whether the signal should be used filter_kst(src, r1, r2, r3, r4, sm1, sm2, sm3, sm4, signalLength, threshold, useFilter)   Pring's Know Sure Thing filter for filtering signals based on KST   Parameters:      src (float) : The source series      r1 (int) : The first ROC length      r2 (int) : The second ROC length      r3 (int) : The third ROC length      r4 (int) : The fourth ROC length      sm1 (int) : The first smoothing length      sm2 (int) : The second smoothing length      sm3 (int) : The third smoothing length      sm4 (int) : The fourth smoothing length      signalLength (int) : The signal line smoothing length      threshold (float) : The threshold for the filter (default: average KST Oscillator)      useFilter (bool) : Whether to apply the filter   Returns: Filtered result indicating whether the signal should be used filter_special_k(src, r1, r2, r3, r4, sm1, sm2, sm3, sm4, threshold, useFilter)   Pring's Special K filter for filtering signals based on Special K   Parameters:      src (float) : The source series      r1 (int) : The first ROC length      r2 (int) : The second ROC length      r3 (int) : The third ROC length      r4 (int) : The fourth ROC length      sm1 (int) : The first smoothing length      sm2 (int) : The second smoothing length      sm3 (int) : The third smoothing length      sm4 (int) : The fourth smoothing length      threshold (float) : The threshold for the filter (default: average Special K)      useFilter (bool) : Whether to apply the filter   Returns: Filtered result indicating whether the signal should be used filter_roc_momentum(src, rocLength, momentumLength, threshold, useFilter)   ROC and Momentum filter for filtering signals based on ROC and Momentum   Parameters:      src (float) : The source series      rocLength (int) : The length for ROC calculation      momentumLength (int) : The length for Momentum calculation      threshold (float) : The threshold for the filter (default: average ROC and Momentum)      useFilter (bool) : Whether to apply the filter   Returns: Filtered result indicating whether the signal should be used filter_rrg_relative_strength(src, length, threshold, useFilter)   RRG Relative Strength filter for filtering signals based on RRG Relative Strength   Parameters:      src (float) : The source series      length (int) : The length for RRG Relative Strength calculation      threshold (float) : The threshold for the filter (default: average RRG Relative Strength)      useFilter (bool) : Whether to apply the filter   Returns: Filtered result indicating whether the signal should be used filter_alligator(useFilter)   Parameters:      useFilter (bool) filter_wyckoff(useFilter)   Parameters:      useFilter (bool) filter_squeeze_momentum(bbLength, bbStdDev, kcLength, kcMult, useFilter)   Parameters:      bbLength (int)      bbStdDev (float)      kcLength (simple int)      kcMult (float)      useFilter (bool) filter_atr_compression(length, atrThreshold, useFilter)   Parameters:      length (simple int)      atrThreshold (float)      useFilter (bool) filter_low_volume(length, useFilter)   Parameters:      length (int)      useFilter (bool) filter_nvi_accumulation(useFilter)   Parameters:      useFilter (bool) filter_ma_slope(src, length, slopeThreshold, useFilter)   Parameters:      src (float)      length (int)      slopeThreshold (float)      useFilter (bool) filter_adx_low(len, lensig, adxThreshold, useFilter)   Parameters:      len (simple int)      lensig (simple int)      adxThreshold (int)      useFilter (bool) filter_choppiness_index(length, chopThreshold, useFilter)   Parameters:      length (int)      chopThreshold (float)      useFilter (bool) filter_range_detection(length, useFilter)   Parameters:      length (int)      useFilter (bool)
Libreria Pine Script®
di crypto_pumpppp
Momentum Cloud.V33🌟 Introducing MomentumCloud.V33 🌟 MomentumCloud.V33 is a cutting-edge indicator designed to help traders capture market momentum with clarity and precision. This versatile tool combines moving averages, directional movement indexes (DMI), and volume analysis to provide real-time insights into trend direction and strength. Whether you’re a scalper, day trader, or swing trader, MomentumCloud.V33 adapts to your trading style and timeframe, making it an essential addition to your trading toolkit. 📈💡 🔧 Customizable Parameters: • Moving Averages: Adjust the periods of the fast (MA1) and slow (MA2) moving averages to fine-tune your trend analysis. • DMI & ADX: Customize the DMI length and ADX smoothing to focus on strong, actionable trends. • Volume Multiplier: Modify the cloud thickness based on trading volume, emphasizing trends with significant market participation. 📊 Trend Detection: • Color-Coded Clouds: • Green Cloud: Indicates a strong uptrend, suggesting buying opportunities. • Red Cloud: Indicates a strong downtrend, signaling potential short trades. • Gray Cloud: Reflects a range-bound market, helping you avoid low-momentum periods. • Dynamic Volume Integration: The cloud thickness adjusts dynamically with trading volume, highlighting strong trends supported by high market activity. 📈 Strength & Momentum Analysis: • Strength Filtering: The ADX component ensures that only strong trends are highlighted, filtering out market noise and reducing false signals. • Visual Momentum Gauge: The cloud color and thickness provide a quick visual representation of market momentum, enabling faster decision-making. 🔔 Alerts: • Custom Alerts: Set up alerts for when the trend shifts or reaches critical levels, keeping you informed without needing to constantly monitor the chart. 🎨 Visual Enhancements: • Gradient Cloud & Shadows: The indicator features a gradient-filled cloud with shadowed moving averages, enhancing both aesthetics and clarity on your charts. • Adaptive Visual Cues: MomentumCloud.V33’s color transitions and dynamic thickness provide an intuitive feel for the market’s rhythm. 🚀 Quick Guide to Using MomentumCloud.V33 1. Add the Indicator: Start by adding MomentumCloud.V33 to your chart. Customize the settings such as MA periods, DMI length, and volume multiplier to match your trading style. 2. Analyze the Market: Observe the color-coded cloud and its thickness to gauge market momentum and trend direction. The thicker the cloud, the stronger the trend. 3. Set Alerts: Activate alerts for trend changes or key levels to capture trading opportunities without needing to watch the screen continuously. ⚙️ How It Works: MomentumCloud.V33 calculates market momentum by combining moving averages, DMI, and volume. The cloud color changes based on the trend direction, while its thickness reflects the strength of the trend as influenced by trading volume. This integrated approach ensures you can quickly identify robust market movements, making it easier to enter and exit trades at optimal points. Settings Overview: • Moving Averages: Define the lengths for the fast and slow moving averages. • DMI & ADX: Adjust the DMI length and ADX smoothing to focus on significant trends. • Volume Multiplier: Customize the multiplier to control cloud thickness, highlighting volume-driven trends. 📚 How to Use MomentumCloud.V33: • Trend Identification: The direction and color of the cloud indicate the prevailing trend, while the cloud’s thickness suggests the trend’s strength. • Trade Execution: Use the green cloud to look for long entries and the red cloud for short positions. The gray cloud advises caution, as it represents a range-bound market. • Alerts: Leverage the custom alerts to stay on top of market movements and avoid missing critical trading opportunities. Unleash the power of trend and momentum analysis with MomentumCloud.V33! Happy trading! 📈🚀✨
Indicatore Pine Script®
di AR33_
Session MasterSession Master Indicator Overview The "Session Master" indicator is a unique tool designed to enhance trading decisions by providing visual cues and relevant information during the critical last 15 minutes of a trading session. It also integrates advanced trend analysis using the Average Directional Index (ADX) and Directional Movement Index (DI) to offer insights into market trends and potential entry/exit points. Originality and Functionality This script combines session timing, visual alerts, and trend analysis in a cohesive manner to give traders a comprehensive view of market behavior as the trading day concludes. Here’s a breakdown of its key features: Last 15 Minutes Highlight : The script identifies the last 15 minutes of the trading session and highlights this period with a semi-transparent blue background, helping traders focus on end-of-day price movements. Previous Session High and Low : The script dynamically plots the high and low of the previous trading session. These levels are crucial for identifying support and resistance and are highlighted with dashed lines and labeled for easy identification during the last 15 minutes of the current session. Directional Movement and Trend Analysis : Using a combination of ADX and DI, the script calculates and plots trend strength and direction. A 21-period Exponential Moving Average (EMA) is plotted with color coding (green for bullish and red for bearish) based on the DI difference, offering clear visual cues about the market trend. Technical Explanation Last 15 Minutes Highlight: The script checks the current time and compares it to the session’s last 15 minutes. If within this period, the background color is changed to a semi-transparent blue to alert the trader. Previous Session High and Low: The script retrieves the high and low of the previous daily session. During the last 15 minutes of the session, these levels are plotted as dashed lines and labeled appropriately. ADX and DI Calculation: The script calculates the True Range, Directional Movement (both positive and negative), and smoothes these values over a specified length (28 periods by default). It then computes the Directional Indicators (DI+ and DI-) and the ADX to gauge trend strength. The 21-period EMA is plotted with dynamic color changes based on the DI difference to indicate trend direction. How to Use Highlight Key Moments: Use the blue background highlight to concentrate on market movements in the critical last 15 minutes of the trading session. Identify Key Levels: Pay attention to the plotted high and low of the previous session as they often act as significant support and resistance levels. Assess Trend Strength: Use the ADX and DI values to understand the strength and direction of the market trend, aiding in making informed trading decisions. EMA for Entry/Exit: Use the color-coded 21-period EMA for potential entry and exit signals based on the trend direction indicated by the DI. Conclusion The "Session Master" indicator is a powerful tool designed to help traders make informed decisions during the crucial end-of-session period. By combining session timing, previous session levels, and advanced trend analysis, it provides a comprehensive overview that is both informative and actionable. This script is particularly useful for intraday traders looking to optimize their strategies around session close times.
Indicatore Pine Script®
di TradingConToto
1
Adaptive Price Channel StrategyThis strategy is an adaptive price channel strategy based on the Average True Range (ATR) indicator and the Average Directional Index (ADX). It aims to identify sideways markets and trends in the price movements and make trades accordingly. The strategy uses a length parameter for the ATR and ADX indicators, which determines the length of the calculation for these indicators. The strategy also uses an ATR multiplier, which is multiplied by the ATR to determine the upper and lower bounds of the price channel. The first step of the strategy is to calculate the highest high (HH) and lowest low (LL) over the specified length. The ATR is also calculated over the same length. Then the strategy calculates the positive directional indicator (+DI) and negative directional indicator (-DI) based on the up and down moves in the price, and uses these to calculate the ADX. If the ADX is less than 25, the market is considered to be in a sideways phase. In this case, if the price closes above the upper bound of the price channel (HH - ATR multiplier * ATR), the strategy enters a long position, and if the price closes below the lower bound of the price channel (LL + ATR multiplier * ATR), the strategy enters a short position. If the ADX is greater than or equal to 25 and the +DI is greater than the -DI, the market is considered to be in a bullish phase. In this case, if the price closes above the upper bound of the price channel, the strategy enters a long position. If the ADX is greater than or equal to 25 and the +DI is less than the -DI, the market is considered to be in a bearish phase. In this case, if the price closes below the lower bound of the price channel, the strategy enters a short position. The strategy exits a position after a certain number of bars have passed since the entry, as specified by the exit_length input. In summary, this strategy attempts to trade in accordance with the prevailing market conditions by identifying sideways markets and trends and making trades based on price movements within a dynamically-adjusted price channel. This strategy takes a read on the market and either takes a channel strategy or trades volatility based on current trend. Works well on 2, 3 ,4, 12 hour for BTC. It’s my first attempt and creating a strategy. I am very interested in constructive criticism. I will look into better risk management, maybe a trailing stop loss. Other suggestions welcome. This is my first attempt at a strategy. Here are the settings I used. Inputs Length 20 Exit 10 ATR 3.2 Dates I picked when I got into Crypto Properties Capital 1000 Order size 2 Contracts Pyramiding 1 Commission .05
Strategia Pine Script®
di HomeCryptoTrader
1
AdxCalcHourlyLibrary "AdxCalcHourly" getBars()   getBars: Returns the number of bars to use in the historical lookback period   Returns: simple int directionDown()   directionDown: Calculates the direction down for bar_index   Returns: series float directionUp()   directionUp: Calculates the direction up for bar_index   Returns: series float trueRangeMovingAverage()   trueRangeMovingAverage: Calculates the true range moving average over the historical lookback period   Returns: series float positiveDirectionalMovement()   positiveDirectionalMovement: Calculates the positive direction movement for bar_index   Returns: series float negativeDirectionalMovement()   negativeDirectionalMovement: Calculates the begative direction movement for bar_index   Returns: series float totalDirectionDown()   totalDirectionDown: Calculates the total direction down for the historical lookback period   Returns: series float totalDirectionUp()   totalDirectionUp: Calculates the total direction up for the historical lookback period   Returns: series float totalDirection()   totalDirection: Calculates the total direction movement for the historical lookback period   Returns: series float averageDirectionalIndex()   averageDirectionalIndex: Calculates the average directional index (ADX) based on the trend for the historical lookback period   Returns: series float getAdxHistoricalAverage()   getAdxHistoricalAverage: Calculates the average directional index (ADX) for the historical lookback period   Returns: series float getAdxHistoricalHigh()   getAdxHistoricalHigh: Calculates the historical high of the directional index (ADX) for the historical lookback period   Returns: series float getAdxHistoricalLow()   getAdxHistoricalLow: Calculates the historical low of the directional index (ADX) for the historical lookback period   Returns: series float getAdxOpinion()   getAdxOpinion: Calculatesa recomendation for the directional index (ADX) based on the historical lookback period   Returns: series float
Libreria Pine Script®
di antifragileer
Adaptive Average Vortex Index [lastguru]As a longtime fan of ADX, looking at Vortex Indicator I often wondered, where is the third line. I have rarely seen that anybody is calculating it. So, here it is: Average Vortex Index - an ADX calculated from Vortex Indicator. I interpret it similarly to the ADX indicator: higher values show stronger trend. If you discover other interpretation or have suggestions, comments are welcome. Both VI+ and VI- lines are also drawn. As I use adaptive length calculation in my other scripts (based on the libraries I've developed and published), I have also included the possibility to have an adaptive length here, so if you hate the idea of calculating ADX from VI, you can disable that line and just look at the adaptive Vortex Indicator. Note that as with all my oscillators, all the lines here are renormalized to -1..1 range unlike the original Vortex Indicator computation. To do that for VI+ and VI- lines, I subtract 1 from their values. It does not change the shape or the amplitude of the lines. Adaptation algorithms are roughly subdivided in two categories: classic Length Adaptations and Cycle Estimators (they are also implemented in separate libraries), all are selected in Adaptation dropdown. Length Adaptation used in the Adaptive Moving Averages and the Adaptive Oscillators try to follow price movements and accelerate/decelerate accordingly (usually quite rapidly with a huge range). Cycle Estimators, on the other hand, try to measure the cycle period of the current market, which does not reflect price movement or the rate of change (the rate of change may also differ depending on the cycle phase, but the cycle period itself usually changes slowly). VIDYA - based on VIDYA algorithm. The period oscillates from the Lower Bound up (slow) VIDYA-RS - based on Vitali Apirine's modification of VIDYA algorithm (he calls it Relative Strength Moving Average). The period oscillates from the Upper Bound down (fast) Kaufman Efficiency Scaling - based on Efficiency Ratio calculation originally used in KAMA Fractal Adaptation - based on FRAMA by John F. Ehlers MESA MAMA Cycle - based on MESA Adaptive Moving Average by John F. Ehlers Pearson Autocorrelation* - based on Pearson Autocorrelation Periodogram by John F. Ehlers DFT Cycle* - based on Discrete Fourier Transform Spectrum estimator by John F. Ehlers Phase Accumulation* - based on Dominant Cycle from Phase Accumulation by John F. Ehlers Length Adaptation usually take two parameters: Bound From (lower bound) and To (upper bound). These are the limits for Adaptation values. Note that the Cycle Estimators marked with asterisks(*) are very computationally intensive, so the bounds should not be set much higher than 50, otherwise you may receive a timeout error (also, it does not seem to be a useful thing to do, but you may correct me if I'm wrong). The Cycle Estimators marked with asterisks(*) also have 3 checkboxes: HP (Highpass Filter), SS (Super Smoother) and HW (Hann Window). These enable or disable their internal prefilters, which are recommended by their author - John F. Ehlers . I do not know, which combination works best, so you can experiment. If no Adaptation is selected ( None option), you can set Length directly. If an Adaptation is selected, then Cycle multiplier can be set. The oscillator also has the option to configure the internal smoothing function with Window setting. By default, RMA is used (like in ADX calculation). Fast Default option is using half the length for smoothing. Triangle , Hamming and Hann Window algorithms are some better smoothers suggested by John F. Ehlers. After the oscillator a Moving Average can be applied. The following Moving Averages are included: SMA , RMA, EMA , HMA , VWMA , 2-pole Super Smoother, 3-pole Super Smoother, Filt11, Triangle Window, Hamming Window, Hann Window, Lowpass, DSSS. Postfilter options are applied last: Stochastic - Stochastic Super Smooth Stochastic - Super Smooth Stochastic (part of MESA Stochastic ) by John F. Ehlers Inverse Fisher Transform - Inverse Fisher Transform Noise Elimination Technology - a simplified Kendall correlation algorithm "Noise Elimination Technology" by John F. Ehlers Momentum - momentum (derivative) Except for Inverse Fisher Transform , all Postfilter algorithms can have Length parameter. If it is not specified (set to 0), then the calculated Slow MA Length is used. If Filter/MA Length is less than 2 or Postfilter Length is less than 1, they are calculated as a multiplier of the calculated oscillator length. More information on the algorithms is given in the code for the libraries used. I am also very grateful to other TradingView community members (they are also mentioned in the library code) without whom this script would not have been possible.
Indicatore Pine Script®
di lastguru
5
Mawreez' Trend OscillatorA positive reading indicates an uptrend, a negative reading indicates a downtrend. For an uptrend, increasing values indicate that the trend is sustaining or strengthening while decreasing values indicate that the trend is stagnating or weakening. Vice versa for a downtrend. When the indicator reads 0, the price is not trending. This indicator is based on the existing DMI indicator, but familiarity with the DMI is not required. The author's goal was to make a less laggy, more intuitively interpretable indicator compared to the DMI. A comparison to the DMI is given above. The reader may see for themselves that trends are recognized quicker. A technical rundown of adjustments made to the DMI is given below. Instead of interpreting the ADX, a sensitivity setting is added and its default value is 25. The value of this sensitivity setting is subtracted from the ADX. Then, any ADX values which fell below 0 are set to 0. Now, just flip the value of the ADX when the -DI is greater than the +DI. The result is then plotted as a histogram. In addition, this indicator has less lag between price action and trend recognition. This is achieved by removing the EMA applied to the ADX, and instead applying lag-free smoothing to +DI and -DI before computing the ADX and then once more applying lag-free smoothing to the result of the computation.
Indicatore Pine Script®
di Mawreez
1
Combo Backtest 123 Reversal and ADXR This is combo strategies for get a cumulative signal. Result signal will return 1 if two strategies is long, -1 if all strategies is short and 0 if signals of strategies is not equal. First strategy This System was created from the Book "How I Tripled My Money In The Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies. The strategy buys at market, if close price is higher than the previous close during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50. The strategy sells at market, if close price is lower than the previous close price during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50. Secon strategy The Average Directional Movement Index Rating (ADXR) measures the strength of the Average Directional Movement Index (ADX). It's calculated by taking the average of the current ADX and the ADX from one time period before (time periods can vary, but the most typical period used is 14 days). Like the ADX, the ADXR ranges from values of 0 to 100 and reflects strengthening and weakening trends. However, because it represents an average of ADX, values don't fluctuate as dramatically and some analysts believe the indicator helps better display trends in volatile markets. WARNING: - For purpose educate only - This script to change bars colors.
Strategia Pine Script®
di HPotter
2
Average Directional Movement Index Rating Backtest The Average Directional Movement Index Rating (ADXR) measures the strength of the Average Directional Movement Index (ADX). It's calculated by taking the average of the current ADX and the ADX from one time period before (time periods can vary, but the most typical period used is 14 days). Like the ADX, the ADXR ranges from values of 0 to 100 and reflects strengthening and weakening trends. However, because it represents an average of ADX, values don't fluctuate as dramatically and some analysts believe the indicator helps better display trends in volatile markets. You can change long to short in the Input Settings WARNING: - For purpose educate only - This script to change bars colors.
Strategia Pine Script®
di HPotter
Average Directional Movement Index Rating Strategy The Average Directional Movement Index Rating (ADXR) measures the strength of the Average Directional Movement Index (ADX). It's calculated by taking the average of the current ADX and the ADX from one time period before (time periods can vary, but the most typical period used is 14 days). Like the ADX, the ADXR ranges from values of 0 to 100 and reflects strengthening and weakening trends. However, because it represents an average of ADX, values don't fluctuate as dramatically and some analysts believe the indicator helps better display trends in volatile markets. WARNING: - This script to change bars colors.
Indicatore Pine Script®
di HPotter
Average Directional Movement Index Rating The Average Directional Movement Index Rating (ADXR) measures the strength of the Average Directional Movement Index (ADX). It's calculated by taking the average of the current ADX and the ADX from one time period before (time periods can vary, but the most typical period used is 14 days). Like the ADX, the ADXR ranges from values of 0 to 100 and reflects strengthening and weakening trends. However, because it represents an average of ADX, values don't fluctuate as dramatically and some analysts believe the indicator helps better display trends in volatile markets.
Indicatore Pine Script®
di HPotter
2
AekFreedom Trading OscillatorAekFreedom Trading Oscillator: User Guide Overview The AekFreedom Trading Oscillator is a comprehensive, all-in-one technical analysis tool designed for TradingView. It consolidates a powerful suite of essential indicators into a single, highly customizable indicator pane. The primary goal is to reduce chart clutter and provide traders with a multi-faceted view of the market, combining momentum, trend strength, volatility, and divergence signals in one place. Core Features & Indicators This script includes the following fully customizable indicators: Relative Strength Index (RSI): A core momentum oscillator used to measure the speed and change of price movements. It features gradient fills for overbought (70-100) and oversold (0-30) zones, along with an optional smoothing moving average. Stochastic Oscillator: Another momentum indicator that compares a particular closing price of a security to a range of its prices over a certain period of time to identify overbought and oversold conditions. MACD (Moving Average Convergence Divergence): A trend-following momentum indicator that shows the relationship between two exponential moving averages (EMAs). It includes the MACD line, Signal line, and Histogram. Awesome Oscillator (AO): A momentum indicator that measures the market's driving force by comparing recent momentum with general momentum over a wider timeframe. ADX (Average Directional Index): An indicator used to quantify the strength of a trend, regardless of its direction (up or down). An ADX value over 25 typically suggests a strong trend. ATR (Average True Range): A key indicator for measuring market volatility. Advanced Divergence Engine One of the most powerful features of this script is its built-in Divergence Engine. It can automatically detect and display both Regular Bullish and Regular Bearish divergences. Supported Indicators: Divergence detection is available for RSI, Awesome Oscillator (AO), and the MACD Line. Visual Signals: When a divergence is found, the script will: Draw a line on the oscillator connecting the relevant pivot points. Display a "Bull" or "Bear" label directly below or above the signal for easy identification. Alerts: You can set up alerts in TradingView that will trigger whenever a new divergence signal appears. How to Use: Settings Panel The indicator is fully customizable via the settings panel. Indicator Visibility This is your main control panel for toggling visuals on and off to keep your chart clean. Show...: Check or uncheck any indicator (e.g., Show RSI & MA, Show Stochastic, Show ATR) to display or hide it instantly. Show... Divergence: Use these checkboxes (e.g., Show RSI Divergence) to control the visibility of the divergence lines and labels on the chart. Indicator-Specific Settings Each indicator has its own group of settings for fine-tuning its parameters. RSI / AO / MACD Settings: Here you can adjust standard parameters like Length, Source, etc. IMPORTANT: Each of these has a Calculate Divergence checkbox. You must enable this checkbox for the script to perform the resource-intensive calculation for that indicator's divergence. Stochastic Settings: Adjust the %K Length, %K Smoothing, and %D Smoothing. ADX Settings: Adjust the ADX Smoothing and DI Length. ATR Settings: Adjust the Length for the ATR calculation. 📌 How to Enable Divergence Signals (2 Steps): To see divergence for an indicator (e.g., MACD), you must do two things: Go to "MACD Settings" and check the box for Calculate Divergence. Go to "Indicator Visibility" and ensure the box for Show MACD Divergence is also checked.
Indicatore Pine Script®
di AekFreedom
FlowScape PredictorFlowScape Predictor is a non-repainting, regime-aware entry qualifier that turns complex market context into two readiness scores (Long & Short, each 0/25/50/75/100) and clean, confirmed-bar signals. It blends three orthogonal pillars so you act only when trend energy, momentum, and location agree: Regime (energy): ATR-normalized linear-regression slope of a smooth HMA → EMA baseline, gated by ADX to confirm when pressure is meaningful. Momentum (push): RSI slope alignment so price has directional follow-through, not just drift. Structure (location): proximity to pivot-confirmed swings, scaled by ATR, so “ready” appears near constructive pullbacks—not mid-trend chases. A soft ATR cloud wraps the baseline for context. A yellow Predictive Baseline extends beyond the last bar to visualize near-term trajectory. It is visual-only: scores/alerts never use it. What you see Baseline line that turns green/red when regime is strong in that direction; gray when weak. ATR cloud around the baseline (context for stretch and pullbacks). Scores (Long & Short, 0–100 in steps of 25) and optional “L/S” icons on bar close. Yellow Predictive Baseline that extends to the right for a few bars (visual trajectory of the smoothed baseline). The scoring system (simple and transparent) Each side (Long/Short) sums four binary checks, 25 points each: Regime aligned: trendStrong is true and LR slope sign favors that side. Momentum aligned: RSI side (>50 for Long, <50 for Short) and RSI slope confirms direction. Baseline side: price is above (Long) / below (Short) the baseline. Location constructive: distance from the last confirmed pivot is healthy (ATR-scaled; not overstretched). Valid totals are 0, 25, 50, 75, 100. Best-quality signal: 100/0 (your side/opposite) on bar close. Good, still valid: 75/0, especially when the missing block is only “location” right as price re-engages the cloud/baseline. Avoid: 75/25 or any opposition > 0 in a weak (gray) regime. The Predictive (Kalman) line — what it is and isn’t The yellow line is a visual forward extension of the smoothed baseline to help you see the current trajectory and time pullback resumptions. It does not predict price and is excluded from scores and alerts. How it’s built (plain English): We maintain a one-dimensional Kalman state x as a smoothed estimate of the baseline. Each bar we observe the current baseline z. The filter adjusts its trust using the Kalman gain K = P / (P + R) and updates: x := x + K*(z − x), then P := (1 − K)*P + Q. Q (process noise): Higher Q → expects faster change → tracks turns quicker (less smoothing). R (measurement noise): Higher R → trusts raw baseline less → smoother, steadier projection. What you control: Lead (how many bars forward to draw). Kalman Q/R (visual smoothness vs. responsiveness). Toggle the line on/off if you prefer a minimal chart. Important: The predictive line extends the baseline, not price. It’s a visual timing aid—don’t automate off it. How to use (step-by-step) Keep the chart clean and use a standard OHLC/candlestick chart. Read the regime: Prefer trades with green/red baseline (trendStrong = true). Check scores on bar close: Take Long 100 / Short 0 or Long 75 / Short 0 when the chart shows a tidy pullback re-engaging the cloud/baseline. Mirror the logic for shorts. Confirm location: If price is > ~1.5 ATR from its reference pivot, let it come back—avoid chasing. Set alerts: Add an alert on Long Ready or Short Ready; these fire on closed bars only. Risk management: Use ATR-buffered stops beyond the recent pivot; target fixed-R multiples (e.g., 1.5–3.0R). Manage the trade with the baseline/cloud if you trail. Best-practice playbook (quick rules) Green light: 100/0 (best) or 75/0 (good) on bar close in a colored (non-gray) regime. Location first: Prefer entries near the baseline/cloud right after a pullback, not far above/below it. Avoid mixed signals: Skip 75/25 and anything with opposition while the baseline is gray. Use the yellow line with discretion: It helps you see rhythm; it’s not a signal source. Timeframes & tuning (practical defaults) Intraday indices/FX (5m–15m): Demand 100/0 in chop; allow 75/0 when ADX is awake and pullback is clean. Crypto intraday (15m–1h): Prefer 100/0; 75/0 on the first pullback after a regime turn. Swing (1h–4h/D1): 75/0 is often sufficient; 100/0 is excellent (fewer but cleaner signals). If choppy: raise ADX threshold, raise the readiness bar (insist on 100/0), or lengthen the RSI slope window. What makes FlowScape different Energy-first regime filter: ATR-normalized LR slope + ADX gate yields a consistent read of trend quality across symbols and timeframes. Location-aware entries: ATR-scaled pivot proximity discourages mid-air chases, encouraging pullback timing. Separation of concerns: The predictive line is visual-only, while scores/alerts are confirmed on close for non-repainting behavior. One simple score per side: A single 0–100 readiness figure is easier to tune than juggling multiple indicators. Transparency & limitations Scores are coarse by design (25-point blocks). They’re a gatekeeper, not a promise of outcomes. Pivots confirm after right-side bars, so structure signals appear after swings form (non-repainting by design). Avoid using non-standard chart types (Heikin Ashi, Renko, Range, etc.) for signals; use a clean, standard chart. No lookahead, no higher-timeframe requests; alerts fire on closed bars only.
Indicatore Pine Script®
di Finntech1
1
Quantum Range Filter by MRKcoin### Quantum Range Filter by MRKcoin **Overview** This indicator is a sophisticated range detection tool designed based on the principles of quantitative multi-factor models. Instead of relying on a single condition, it assesses the market from three different dimensions to provide a more robust and reliable identification of range-bound (sideways) markets. When the background is highlighted in red, it indicates that the market is likely in a range phase, suggesting that trend-following strategies may be less effective, and mean-reversion (range trading) strategies could be more suitable. --- **Core Logic: A Multi-Factor Approach** The filter evaluates the market state using the following three independent factors: 1. **Momentum Volatility (RSI Bollinger Bandwidth):** * **Question:** Is the momentum of the market contracting? * **Method:** It measures the width of the Bollinger Bands applied to the RSI. A narrow bandwidth suggests that momentum is consolidating, which is a common characteristic of a range market. 2. **Price Volatility (ATR Ratio):** * **Question:** Is the actual price movement shrinking? * **Method:** It calculates the Average True Range (ATR) as a percentage of the closing price. A low ratio indicates that the price volatility itself is low, reinforcing the case for a range environment. 3. **Absence of Trend (ADX):** * **Question:** Is there a lack of a clear directional trend? * **Method:** It uses the Average Directional Index (ADX), a standard tool for measuring trend strength. A low ADX value provides active confirmation that the market is not in a trending phase. --- **How to Use** 1. **Range Detection:** The primary use is to identify ranging markets. The red highlighted background serves as a visual cue. 2. **Strategy Selection:** * **Inside the Red Zone:** Consider using range-trading strategies (e.g., buying at support, selling at resistance, using oscillators like RSI or Stochastics for overbought/oversold signals). Avoid using trend-following indicators like moving average crossovers, as they are prone to generating false signals in these conditions. * **Outside the Red Zone:** The market is likely trending. Trend-following strategies are more appropriate. 3. **Parameter Tuning (In Settings):** * **This is the key to adapting the filter to any market or timeframe.** Different assets (like BTC vs. ETH) and different timeframes have unique volatility characteristics. Don't hesitate to adjust the parameters to fit the specific chart you are analyzing. * **Range Detection Score:** This is the most important setting. It determines how many of the three factors must agree to classify the market as a range. The default is `2`, which provides a good balance. * If the filter seems **too sensitive** (highlighting too often), increase the score to `3`. * If the filter seems **not sensitive enough** (missing obvious ranges), decrease the score to `1`. * **Factor Thresholds:** For fine-tuning, adjust the thresholds for each factor. * **`RSI BB Width Threshold`:** If you want to detect even tighter momentum consolidations, *decrease* this value. * **`ATR Ratio Threshold`:** If you want to be stricter about price volatility, *decrease* this value. * **`ADX Threshold`:** To be more lenient on what constitutes a "trendless" market, *increase* this value (e.g., to 30). To be stricter, *decrease* it (e.g., to 20). * **Pro Tip:** Use the Debug Table (uncomment it in the script's code) to see the live values of each factor. This will give you a clear idea of how to set the thresholds for the specific asset you are trading. **Disclaimer** This indicator is a tool to assist in market analysis and should not be used as a standalone signal for making financial decisions. Always use it in conjunction with your own trading strategy, risk management, and analysis. Past performance is not indicative of future results. **Credits** * **Concept & Vision:** MRKcoin
Indicatore Pine Script®
di mrk2020
Liquidity Grab Detector (Stop Hunt Sniper) v2.2📌 Purpose This indicator detects Stop Hunts (Liquidity Grabs) — false breakouts above/below recent highs or lows — filtered by trend direction, volatility, and volume conditions. It is designed for scalpers and intraday traders who want to identify high-probability reversal zones. 🧠 How It Works 1. Key Logic Detects previous swing high / swing low over the Lookback Bars. Marks a false breakout when price moves beyond the level and closes back inside. Requires a volume spike on the breakout to confirm liquidity sweep. 2. Trend Filter (EMA 50) Bullish signals only if price is above EMA 50. Bearish signals only if price is below EMA 50. This removes most counter-trend stop hunts. 3. ADX Filter Signals appear only when ADX < Max ADX (low-trend conditions). This avoids false signals in strong trending markets. 📈 How to Use Green Arrows: Bullish stop hunt (potential long entry). Red Arrows: Bearish stop hunt (potential short entry). Works best in range conditions, liquidity zones, or near session highs/lows. Combine with order flow, volume profile, or price action for extra confirmation. Recommended Timeframes: 1m–15m for scalping; 30m–1h for intraday. Markets: Crypto, Forex, Indices. ⚙️ Inputs Lookback Bars — swing detection Volume Spike Multiplier EMA Length (trend filter) Min Retrace — how much price must return inside range Max ADX — trend filter sensitivity ⚠️ Disclaimer This script is for educational purposes only and does not constitute financial advice. Always test thoroughly before live trading.
Indicatore Pine Script®
di artemka3091
Trend Strength Oscillator📌 What Is the Trend Strength Oscillator? The Trend Strength Oscillator is a visual tool that helps traders understand the overall direction and strength of the market trend. Instead of using multiple indicators separately, this tool combines three trusted methods into one clear, color-coded bar chart. The bars change based on whether the market is strongly trending up, down, or just moving sideways. Imagine it as a traffic light for trading: • Green means it’s safe to consider buying (strong uptrend). • Red means consider selling or avoiding longs (strong downtrend). • Gray means wait, the market isn’t clearly trending. 🧠 How It Works — The 3 Main Components 1. EMA Slope The EMA (Exponential Moving Average) tracks the average price but reacts more quickly to changes. If the EMA is rising, it means the market is likely moving upward. If it’s falling, the trend is likely downward. 2. RSI Direction RSI (Relative Strength Index) measures momentum. This tool compares the RSI to its smoothed average. If the RSI is above its average, momentum is up. If it’s below, momentum is down. 3. ADX Strength ADX (Average Directional Index) measures how strong a trend is, not the direction. So even if EMA and RSI agree on a trend, the ADX must confirm it’s strong enough to be worth trading. Only when all three indicators agree do we consider it a strong trend. 🧮 What the Oscillator Shows The result of combining those components is a number that becomes a colored bar: • +2 means all three signals are bullish → green bar. • -2 means all three signals are bearish → red bar. • Anything else (e.g., mixed signals or weak ADX) → gray bar. This makes the chart super easy to read at a glance, even for beginners. 📈 How to Use It in Trading You can use the Trend Strength Oscillator in a few simple ways: • Entering Trades: Look for a green bar when you want to buy or go long. Look for a red bar when you want to sell or go short. These bars mean all systems are “go” in the same direction. • Avoiding Mistakes: If the bar is gray, it’s a warning that the market is undecided or weak. It’s often better to wait for a clearer signal rather than force a trade. • Managing Existing Trades: If you’re in a trade and the bar color shifts back to gray, that can be a clue that the trend is losing strength. You might tighten your stop-loss or take some profit. 🧭 Final Thoughts This indicator doesn’t give you a trade entry every few minutes. Instead, it helps you stay on the right side of strong moves and avoid choppy or sideways markets. It’s especially helpful for: • Trend-following traders • People who want clean, simple visuals • Beginners who get overwhelmed with too many indicators Let me know if you'd like to see this paired with another tool like volume or MACD, or if you’d like a chart screenshot to visualize how this looks live.
Indicatore Pine Script®
di SupertradeOfficial
SignalWatcherThis script provides real-time monitoring of multiple technical indicators and generates visual alerts and configurable alarms: Inputs & Mini-GUI MACD Settings: Activation, fast, slow and signal line lengths. RSI Settings: Activation, period length, overbought and oversold thresholds. ADX Settings: Activation, period length, smoothing and trend strength thresholds. Volume Settings: Activation, length of the volume MA, factor for detecting volume peaks. Global Alert: A single composite alert for all signals. Plot Settings: Activation and deactivation of the plot displays for RSI, MACD (lines) and ADX. Color and width selection for each line. Display Table: Activation of the status table. Calculations MACD: Generates macdLine and signalLine, detects crossovers (bullish) and crossunders (bearish). RSI: Calculates rsi_val, compares with rsi_ob and rsi_os to determine overbought/oversold. ADX: Uses ta.dmi() to determine adx_val and checks against adx_thresh for trend strength. Volume Spike: Exceptional trading activity detected by moving average (vol_ma) and factor (vol_factor). Alert conditions Six individual alertcondition() calls: MACD ↑/↓, RSI Overbought/Oversold, ADX Strong Trend, Volume Spike. Optional composite alert (enable_global): A single notification when one of the indicator signals strikes. Visual overlays Alarm overlay (bottom right): Red table with text lines for currently triggered signals. Status Table (bottom left): Overview of all indicators with current status (On/Off, Values, Thresholds). Plots in the chart RSI, MACD Line & Signal Line, ADX: Are displayed as lines if activated in the GUI; configurable colors & line thicknesses.
Indicatore Pine Script®
di N3SU
Toolbar-FrenToolbar-Fren is a comprehensive, data-rich toolbar designed to present a wide array of key metrics in a compact and intuitive format. The core philosophy of this indicator is to maximize the amount of relevant, actionable data available to the trader while occupying minimal chart space. It leverages a dynamic color-coded system to provide at-a-glance insights into market conditions, instantly highlighting positive/negative values, trend strength, and proximity to important technical levels. Features and Data Displayed The toolbar displays a vertical column of critical data points, primarily calculated on the Daily timeframe to give a broader market context. Each cell is color-coded for quick interpretation. DAY: The percentage change of the current price compared to the previous day's close. The cell is colored green for a positive change and red for a negative one. LOD: The current price's percentage distance from the Low of the Day. HOD The current price's percentage distance from the High of the Day. MA Distances (9/21 or 10/20, 50, 200) These cells show how far the current price is from key Daily moving averages (MAs). The values are displayed either as a percentage distance or as a multiple of the Average Daily Range (ADR), which can be toggled in the settings. The cells are colored green if the price is above the corresponding MA (bullish) and red if it is below (bearish). ADR Shows the 14-period Average Daily Range as a percentage of the current price. The cell background uses a smooth gradient from green (low volatility) to red (high volatility) to visualize the current daily range expansion. ADR%/50: A unique metric showing the distance from the Daily 50 SMA, measured in multiples of the 14-period Average True Range (ATR). This helps quantify how extended the price is from its mean. The cell is color-coded from green (close to the mean) to red (highly extended). RSI The standard 14-period Relative Strength Index calculated on the Daily timeframe. The background color changes to indicate potentially overbought (orange/red) or oversold (green) conditions. ADX The 14-period Average Directional Index (ADX) from the Daily timeframe, which measures trend strength. The cell is colored to reflect the strength of the trend (e.g., green for a strong trend, red for a weak/non-trending market). An arrow (▲/▼) is also displayed to indicate if the ADX value is sloping up or down. User Customization The indicator offers several options for personalization to fit your trading style and visual preferences: MA Type Choose between using Exponential Moving Averages (EMA 9/21) or Simple Moving Averages (SMA 10/20) for the primary MA calculations. MA Distance Display Toggle the display of moving average distances between standard percentage values and multiples of the Average Daily Range (ADR). Display Settings Fully customize the on-chart appearance by selecting the table's position (e.g., Top Right, Bottom Left) and the text size. An option for a larger top margin is also available. Colors Personalize the core Green, Yellow, Orange, and Red colors used throughout the indicator to match your chart's theme. Technical Parameters Fine-tune the length settings for the ADX and DI calculations.
Indicatore Pine Script®
di shftd
Q Impulse EntryQ Impulse Entry A directional entry system combining impulse breakouts, Elder's momentum confirmation, and ADX trend validation. Designed for clean trade setups with multi-step filtering, entry markers, and real-time alerts. 🔧 Core Logic This is not a basic mashup — each filter plays a distinct technical role: 1. Impulse Breakout Engine  • Detects sharp directional price breaks using ATR-adjusted dynamic zones  • Impulse window controls sensitivity to local highs/lows 2. Elder Momentum Filter  • Confirms signal using MACD histogram and EMA alignment  • Blocks entries when internal momentum contradicts price move 3. ADX Trend Strength Filter  • Uses threshold-based ADX logic to validate trend power  • Filters out noise in flat or weak markets The system requires all three filters to agree before confirming an entry. 📈 Visual Feedback • ⇑ / ⇓ arrows mark confirmed entry signals • Colored entry dots plotted at signal price help confirm timing and aid in multi-position layering • Impulse breakout zones and EMA are displayed for directional context • Clean layout, no repainting, designed for real-time use ⚙️ Configurable Inputs • Impulse Window — controls breakout signal sensitivity • ATR Multiplier — defines width of impulse breakout zones (Elder and ADX filters are embedded and fine-tuned) ✨ Highlights • Triple-filter signal logic = fewer false positives • Entry dots + arrows for visual clarity and scaling in • Lightweight, non-repainting, and alert-ready • Best suited for Forex and all timeframes • Ideal for breakout, trend-following, or hybrid systems • Built-in alerts and customizable zones • Always apply risk management suited to your capital and strategy Trade with clarity — stay for quality.
Indicatore Pine Script®
di Quantora
Bober XM v2.0# ₿ober XM v2.0 Trading Bot Documentation **Developer's Note**: While our previous Bot 1.3.1 was removed due to guideline violations, this setback only fueled our determination to create something even better. Rising from this challenge, Bober XM 2.0 emerges not just as an update, but as a complete reimagining with multi-timeframe analysis, enhanced filters, and superior adaptability. This adversity pushed us to innovate further and deliver a strategy that's smarter, more agile, and more powerful than ever before. Challenges create opportunity - welcome to Cryptobeat's finest work yet. ## !!!!You need to tune it for your own pair and timeframe and retune it periodicaly!!!!! ## Overview The ₿ober XM v2.0 is an advanced dual-channel trading bot with multi-timeframe analysis capabilities. It integrates multiple technical indicators, customizable risk management, and advanced order execution via webhook for automated trading. The bot's distinctive feature is its separate channel systems for long and short positions, allowing for asymmetric trade strategies that adapt to different market conditions across multiple timeframes. ### Key Features - **Multi-Timeframe Analysis**: Analyze price data across multiple timeframes simultaneously - **Dual Channel System**: Separate parameter sets for long and short positions - **Advanced Entry Filters**: RSI, Volatility, Volume, Bollinger Bands, and KEMAD filters - **Machine Learning Moving Average**: Adaptive prediction-based channels - **Multiple Entry Strategies**: Breakout, Pullback, and Mean Reversion modes - **Risk Management**: Customizable stop-loss, take-profit, and trailing stop settings - **Webhook Integration**: Compatible with external trading bots and platforms ### Strategy Components | Component | Description | |---------|-------------| | **Dual Channel Trading** | Uses either Keltner Channels or Machine Learning Moving Average (MLMA) with separate settings for long and short positions | | **MLMA Implementation** | Machine learning algorithm that predicts future price movements and creates adaptive bands | | **Pivot Point SuperTrend** | Trend identification and confirmation system based on pivot points | | **Three Entry Strategies** | Choose between Breakout, Pullback, or Mean Reversion approaches | | **Advanced Filter System** | Multiple customizable filters with multi-timeframe support to avoid false signals | | **Custom Exit Logic** | Exits based on OBV crossover of its moving average combined with pivot trend changes | ### Note for Novice Users This is a fully featured real trading bot and can be tweaked for any ticker — SOL is just an example. It follows this structure: 1. **Indicator** – gives the initial signal 2. **Entry strategy** – decides when to open a trade 3. **Exit strategy** – defines when to close it 4. **Trend confirmation** – ensures the trade follows the market direction 5. **Filters** – cuts out noise and avoids weak setups 6. **Risk management** – controls losses and protects your capital To tune it for a different pair, you'll need to start from scratch: 1. Select the timeframe (candle size) 2. Turn off all filters and trend entry/exit confirmations 3. Choose a channel type, channel source and entry strategy 4. Adjust risk parameters 5. Tune long and short settings for the channel 6. Fine-tune the Pivot Point Supertrend and Main Exit condition OBV This will generate a lot of signals and activity on the chart. Your next task is to find the right combination of filters and settings to reduce noise and tune it for profitability. ### Default Strategy values Default values are tuned for: Symbol BITGET:SOLUSDT.P 5min candle Filters are off by default: Try to play with it to understand how it works ## Configuration Guide ### General Settings | Setting | Description | Default Value | |---------|-------------|---------------| | **Long Positions** | Enable or disable long trades | Enabled | | **Short Positions** | Enable or disable short trades | Enabled | | **Risk/Reward Area** | Visual display of stop-loss and take-profit zones | Enabled | | **Long Entry Source** | Price data used for long entry signals | hl2 (High+Low/2) | | **Short Entry Source** | Price data used for short entry signals | hl2 (High+Low/2) | The bot allows you to trade long positions, short positions, or both simultaneously. Each direction has its own set of parameters, allowing for fine-tuned strategies that recognize the asymmetric nature of market movements. ### Multi-Timeframe Settings 1. **Enable Multi-Timeframe Analysis**: Toggle 'Enable Multi-Timeframe Analysis' in the Multi-Timeframe Settings section 2. **Configure Timeframes**: Set appropriate higher timeframes based on your trading style: - Timeframe 1: Default is now 15 minutes (intraday confirmation) - Timeframe 2: Default is 4 hours (trend direction) 3. **Select Sources per Indicator**: For each indicator (RSI, KEMAD, Volume, etc.), choose: - The desired timeframe (current, mtf1, or mtf2) - The appropriate price type (open, high, low, close, hl2, hlc3, ohlc4) ### Entry Strategies - **Breakout**: Enter when price breaks above/below the channel - **Pullback**: Enter when price pulls back to the channel - **Mean Reversion**: Enter when price is extended from the channel You can enable different strategies for long and short positions. ### Core Components ### Risk Management - **Position Size**: Control risk with percentage-based position sizing - **Stop Loss Options**: - Fixed: Set a specific price or percentage from entry - ATR-based: Dynamic stop-loss based on market volatility - Swing: Uses recent swing high/low points - **Take Profit**: Multiple targets with percentage allocation - **Trailing Stop**: Dynamic stop that follows price movement ## Advanced Usage Strategies ### Moving Average Type Selection Guide - **SMA**: More stable in choppy markets, good for higher timeframes - **EMA/WMA**: More responsive to recent price changes, better for entry signals - **VWMA**: Adds volume weighting for stronger trends, use with Volume filter - **HMA**: Balance between responsiveness and noise reduction, good for volatile markets ### Multi-Timeframe Strategy Approaches - **Trend Confirmation**: Use higher timeframe RSI (mtf2) for overall trend, current timeframe for entries - **Entry Precision**: Use KEMAD on current timeframe with volume filter on mtf1 - **False Signal Reduction**: Apply RSI filter on mtf1 with strict KEMAD settings ### Market Condition Optimization | Market Condition | Recommended Settings | |------------------|----------------------| | **Trending** | Use Breakout strategy with KEMAD filter on higher timeframe | | **Ranging** | Use Mean Reversion with strict RSI filter (mtf1) | | **Volatile** | Increase ATR multipliers, use HMA for moving averages | | **Low Volatility** | Decrease noise parameters, use pullback strategy | ## Webhook Integration The strategy features a professional webhook system that allows direct connectivity to your exchange or trading platform of choice through third-party services like 3commas, Alertatron, or Autoview. The webhook payload includes all necessary parameters for automated execution: - Entry price and direction - Stop loss and take profit levels - Position size - Custom identifier for webhook routing ## Performance Optimization Tips 1. **Start with Defaults**: Begin with the default settings for your timeframe before customizing 2. **Adjust One Component at a Time**: Make incremental changes and test the impact 3. **Match MA Types to Market Conditions**: Use appropriate moving average types based on the Market Condition Optimization table 4. **Timeframe Synergy**: Create logical relationships between timeframes (e.g., 5min chart with 15min and 4h higher timeframes) 5. **Periodic Retuning**: Markets evolve - regularly review and adjust parameters ## Common Setups ### Crypto Trend-Following - MLMA with EMA or HMA - Higher RSI thresholds (75/25) - KEMAD filter on mtf1 - Breakout entry strategy ### Stock Swing Trading - MLMA with SMA for stability - Volume filter with higher threshold - KEMAD with increased filter order - Pullback entry strategy ### Forex Scalping - MLMA with WMA and lower noise parameter - RSI filter on current timeframe - Use highest timeframe for trend direction only - Mean Reversion strategy ## Webhook Configuration - **Benefits**: - Automated trade execution without manual intervention - Immediate response to market conditions - Consistent execution of your strategy - **Implementation Notes**: - Requires proper webhook configuration on your exchange or platform - Test thoroughly with small position sizes before full deployment - Consider latency between signal generation and execution ### Backtesting Period Define a specific historical period to evaluate the bot's performance: | Setting | Description | Default Value | |---------|-------------|---------------| | **Start Date** | Beginning of backtest period | January 1, 2025 | | **End Date** | End of backtest period | December 31, 2026 | - **Best Practice**: Test across different market conditions (bull markets, bear markets, sideways markets) - **Limitation**: Past performance doesn't guarantee future results ## Entry and Exit Strategies ### Dual-Channel System A key innovation of the Bober XM is its dual-channel approach: - **Independent Parameters**: Each trade direction has its own channel settings - **Asymmetric Trading**: Recognizes that markets often behave differently in uptrends versus downtrends - **Optimized Performance**: Fine-tune settings for both bullish and bearish conditions This approach allows the bot to adapt to the natural asymmetry of markets, where uptrends often develop gradually while downtrends can be sharp and sudden. ### Channel Types #### 1. Keltner Channels Traditional volatility-based channels using EMA and ATR: | Setting | Long Default | Short Default | |---------|--------------|---------------| | **EMA Length** | 37 | 20 | | **ATR Length** | 13 | 17 | | **Multiplier** | 1.4 | 1.9 | | **Source** | low | high | - **Strengths**: - Reliable in trending markets - Less prone to whipsaws than Bollinger Bands - Clear visual representation of volatility - **Weaknesses**: - Can lag during rapid market changes - Less effective in choppy, non-trending markets #### 2. Machine Learning Moving Average (MLMA) Advanced predictive model using kernel regression (RBF kernel): | Setting | Description | Options | |---------|-------------|--------| | **Source MA** | Price data used for MA calculations | Any price source (low/high/close/etc.) | | **Moving Average Type** | Type of MA algorithm for calculations | SMA, EMA, WMA, VWMA, RMA, HMA | | **Trend Source** | Price data used for trend determination | Any price source (close default) | | **Window Size** | Historical window for MLMA calculations | 5+ (default: 16) | | **Forecast Length** | Number of bars to forecast ahead | 1+ (default: 3) | | **Noise Parameter** | Controls smoothness of prediction | 0.01+ (default: ~0.43) | | **Band Multiplier** | Multiplier for channel width | 0.1+ (default: 0.5-0.6) | - **Strengths**: - Predictive rather than reactive - Adapts quickly to changing market conditions - Better at identifying trend reversals early - **Weaknesses**: - More computationally intensive - Requires careful parameter tuning - Can be sensitive to input data quality ### Entry Strategies | Strategy | Description | Ideal Market Conditions | |----------|-------------|-------------------------| | **Breakout** | Enters when price breaks through channel bands, indicating strong momentum | High volatility, emerging trends | | **Pullback** | Enters when price retraces to the middle band after testing extremes | Established trends with regular pullbacks | | **Mean Reversion** | Enters at channel extremes, betting on a return to the mean | Range-bound or oscillating markets | #### Breakout Strategy (Default) - **Implementation**: Enters long when price crosses above the upper band, short when price crosses below the lower band - **Strengths**: Captures strong momentum moves, performs well in trending markets - **Weaknesses**: Can lead to late entries, higher risk of false breakouts - **Optimization Tips**: - Increase channel multiplier for fewer but more reliable signals - Combine with volume confirmation for better accuracy #### Pullback Strategy - **Implementation**: Enters long when price pulls back to middle band during uptrend, short during downtrend pullbacks - **Strengths**: Better entry prices, lower risk, higher probability setups - **Weaknesses**: Misses some strong moves, requires clear trend identification - **Optimization Tips**: - Use with trend filters to confirm overall direction - Adjust middle band calculation for market volatility #### Mean Reversion Strategy - **Implementation**: Enters long at lower band, short at upper band, expecting price to revert to the mean - **Strengths**: Excellent entry prices, works well in ranging markets - **Weaknesses**: Dangerous in strong trends, can lead to fighting the trend - **Optimization Tips**: - Implement strong trend filters to avoid counter-trend trades - Use smaller position sizes due to higher risk nature ### Confirmation Indicators #### Pivot Point SuperTrend Combines pivot points with ATR-based SuperTrend for trend confirmation: | Setting | Default Value | |---------|---------------| | **Pivot Period** | 25 | | **ATR Factor** | 2.2 | | **ATR Period** | 41 | - **Function**: Identifies significant market turning points and confirms trend direction - **Implementation**: Requires price to respect the SuperTrend line for trade confirmation #### Weighted Moving Average (WMA) Provides additional confirmation layer for entries: | Setting | Default Value | |---------|---------------| | **Period** | 15 | | **Source** | ohlc4 (average of Open, High, Low, Close) | - **Function**: Confirms trend direction and filters out low-quality signals - **Implementation**: Price must be above WMA for longs, below for shorts ### Exit Strategies #### On-Balance Volume (OBV) Based Exits Uses volume flow to identify potential reversals: | Setting | Default Value | |---------|---------------| | **Source** | ohlc4 | | **MA Type** | HMA (Options: SMA, EMA, WMA, RMA, VWMA, HMA) | | **Period** | 22 | - **Function**: Identifies divergences between price and volume to exit before reversals - **Implementation**: Exits when OBV crosses its moving average in the opposite direction - **Customizable MA Type**: Different MA types provide varying sensitivity to OBV changes: - **SMA**: Traditional simple average, equal weight to all periods - **EMA**: More weight to recent data, responds faster to price changes - **WMA**: Weighted by recency, smoother than EMA - **RMA**: Similar to EMA but smoother, reduces noise - **VWMA**: Factors in volume, helpful for OBV confirmation - **HMA**: Reduces lag while maintaining smoothness (default) #### ADX Exit Confirmation Uses Average Directional Index to confirm trend exhaustion: | Setting | Default Value | |---------|---------------| | **ADX Threshold** | 35 | | **ADX Smoothing** | 60 | | **DI Length** | 60 | - **Function**: Confirms trend weakness before exiting positions - **Implementation**: Requires ADX to drop below threshold or DI lines to cross ## Filter System ### RSI Filter - **Function**: Controls entries based on momentum conditions - **Parameters**: - Period: 15 (default) - Overbought level: 71 - Oversold level: 23 - Multi-timeframe support: Current, MTF1 (15min), or MTF2 (4h) - Customizable price source (open, high, low, close, hl2, hlc3, ohlc4) - **Implementation**: Blocks long entries when RSI > overbought, short entries when RSI < oversold ### Volatility Filter - **Function**: Prevents trading during excessive market volatility - **Parameters**: - Measure: ATR (Average True Range) - Period: Customizable (default varies by timeframe) - Threshold: Adjustable multiplier - Multi-timeframe support - Customizable price source - **Implementation**: Blocks trades when current volatility exceeds threshold × average volatility ### Volume Filter - **Function**: Ensures adequate market liquidity for trades - **Parameters**: - Threshold: 0.4× average (default) - Measurement period: 5 (default) - Moving average type: Customizable (HMA default) - Multi-timeframe support - Customizable price source - **Implementation**: Requires current volume to exceed threshold × average volume ### Bollinger Bands Filter - **Function**: Controls entries based on price relative to statistical boundaries - **Parameters**: - Period: Customizable - Standard deviation multiplier: Adjustable - Moving average type: Customizable - Multi-timeframe support - Customizable price source - **Implementation**: Can require price to be within bands or breaking out of bands depending on strategy ### KEMAD Filter (Kalman EMA Distance) - **Function**: Advanced trend confirmation using Kalman filter algorithm - **Parameters**: - Process Noise: 0.35 (controls smoothness) - Measurement Noise: 24 (controls reactivity) - Filter Order: 6 (higher = more smoothing) - ATR Length: 8 (for bandwidth calculation) - Upper Multiplier: 2.0 (for long signals) - Lower Multiplier: 2.7 (for short signals) - Multi-timeframe support - Customizable visual indicators - **Implementation**: Generates signals based on price position relative to Kalman-filtered EMA bands ## Risk Management System ### Position Sizing Automatically calculates position size based on account equity and risk parameters: | Setting | Default Value | |---------|---------------| | **Risk % of Equity** | 50% | - **Implementation**: - Position size = (Account equity × Risk %) ÷ (Entry price × Stop loss distance) - Adjusts automatically based on volatility and stop placement - **Best Practices**: - Start with lower risk percentages (1-2%) until strategy is proven - Consider reducing risk during high volatility periods ### Stop-Loss Methods Multiple stop-loss calculation methods with separate configurations for long and short positions: | Method | Description | Configuration | |--------|-------------|---------------| | **ATR-Based** | Dynamic stops based on volatility | ATR Period: 14, Multiplier: 2.0 | | **Percentage** | Fixed percentage from entry | Long: 1.5%, Short: 1.5% | | **PIP-Based** | Fixed currency unit distance | 10.0 pips | - **Implementation Notes**: - ATR-based stops adapt to changing market volatility - Percentage stops maintain consistent risk exposure - PIP-based stops provide precise control in stable markets ### Trailing Stops Locks in profits by adjusting stop-loss levels as price moves favorably: | Setting | Default Value | |---------|---------------| | **Stop-Loss %** | 1.5% | | **Activation Threshold** | 2.1% | | **Trailing Distance** | 1.4% | - **Implementation**: - Initial stop remains fixed until profit reaches activation threshold - Once activated, stop follows price at specified distance - Locks in profit while allowing room for normal price fluctuations ### Risk-Reward Parameters Defines the relationship between risk and potential reward: | Setting | Default Value | |---------|---------------| | **Risk-Reward Ratio** | 1.4 | | **Take Profit %** | 2.4% | | **Stop-Loss %** | 1.5% | - **Implementation**: - Take profit distance = Stop loss distance × Risk-reward ratio - Higher ratios require fewer winning trades for profitability - Lower ratios increase win rate but reduce average profit ### Filter Combinations The strategy allows for simultaneous application of multiple filters: - **Recommended Combinations**: - Trending markets: RSI + KEMAD filters - Ranging markets: Bollinger Bands + Volatility filters - All markets: Volume filter as minimum requirement - **Performance Impact**: - Each additional filter reduces the number of trades - Quality of remaining trades typically improves - Optimal combination depends on market conditions and timeframe ### Multi-Timeframe Filter Applications | Filter Type | Current Timeframe | MTF1 (15min) | MTF2 (4h) | |-------------|-------------------|-------------|------------| | RSI | Quick entries/exits | Intraday trend | Overall trend | | Volume | Immediate liquidity | Sustained support | Market participation | | Volatility | Entry timing | Short-term risk | Regime changes | | KEMAD | Precise signals | Trend confirmation | Major reversals | ## Visual Indicators and Chart Analysis The bot provides comprehensive visual feedback on the chart: - **Channel Bands**: Keltner or MLMA bands showing potential support/resistance - **Pivot SuperTrend**: Colored line showing trend direction and potential reversal points - **Entry/Exit Markers**: Annotations showing actual trade entries and exits - **Risk/Reward Zones**: Visual representation of stop-loss and take-profit levels These visual elements allow for: - Real-time strategy assessment - Post-trade analysis and optimization - Educational understanding of the strategy logic ## Implementation Guide ### TradingView Setup 1. Load the script in TradingView Pine Editor 2. Apply to your preferred chart and timeframe 3. Adjust parameters based on your trading preferences 4. Enable alerts for webhook integration ### Webhook Integration 1. Configure webhook URL in TradingView alerts 2. Set up receiving endpoint on your trading platform 3. Define message format matching the bot's output 4. Test with small position sizes before full deployment ### Optimization Process 1. Backtest across different market conditions 2. Identify parameter sensitivity through multiple tests 3. Focus on risk management parameters first 4. Fine-tune entry/exit conditions based on performance metrics 5. Validate with out-of-sample testing ## Performance Considerations ### Strengths - Adaptability to different market conditions through dual channels - Multiple layers of confirmation reducing false signals - Comprehensive risk management protecting capital - Machine learning integration for predictive edge ### Limitations - Complex parameter set requiring careful optimization - Potential over-optimization risk with so many variables - Computational intensity of MLMA calculations - Dependency on proper webhook configuration for execution ### Best Practices - Start with conservative risk settings (1-2% of equity) - Test thoroughly in demo environment before live trading - Monitor performance regularly and adjust parameters - Consider market regime changes when evaluating results ## Conclusion The ₿ober XM v2.0 represents a significant evolution in trading strategy design, combining traditional technical analysis with machine learning elements and multi-timeframe analysis. The core strength of this system lies in its adaptability and recognition of market asymmetry. ### Market Asymmetry and Adaptive Approach The strategy acknowledges a fundamental truth about markets: bullish and bearish phases behave differently and should be treated as distinct environments. The dual-channel system with separate parameters for long and short positions directly addresses this asymmetry, allowing for optimized performance regardless of market direction. ### Targeted Backtesting Philosophy It's counterproductive to run backtests over excessively long periods. Markets evolve continuously, and strategies that worked in previous market regimes may be ineffective in current conditions. Instead: - Test specific market phases separately (bull markets, bear markets, range-bound periods) - Regularly re-optimize parameters as market conditions change - Focus on recent performance with higher weight than historical results - Test across multiple timeframes to ensure robustness ### Multi-Timeframe Analysis as a Game-Changer The integration of multi-timeframe analysis fundamentally transforms the strategy's effectiveness: - **Increased Safety**: Higher timeframe confirmations reduce false signals and improve trade quality - **Context Awareness**: Decisions made with awareness of larger trends reduce adverse entries - **Adaptable Precision**: Apply strict filters on lower timeframes while maintaining awareness of broader conditions - **Reduced Noise**: Higher timeframe data naturally filters market noise that can trigger poor entries The ₿ober XM v2.0 provides traders with a framework that acknowledges market complexity while offering practical tools to navigate it. With proper setup, realistic expectations, and attention to changing market conditions, it delivers a sophisticated approach to systematic trading that can be continuously refined and optimized.
Strategia Pine Script®
di buble_lab
4
LANZ Strategy 4.0🔷 LANZ Strategy 4.0 — Trend Impulse Detection with Risk Management LANZ Strategy 4.0 is a multi-indicator trend strategy designed for short to medium-term trading on any asset or timeframe. It combines Parabolic SAR, Supertrend, ADX, and time zone highlighting to detect and confirm trend impulses, while managing entries with dynamic Stop Loss (SL) and Take Profit (TP) levels. 🧠 Core Components: Parabolic SAR: Identifies short-term trend reversals. Supertrend: Highlights trend continuation zones. ADX Filter: Ensures trend strength by filtering entries when ADX exceeds a defined threshold. Impulse Detection Logic: Detects and confirms movement impulses with a counter, only generating trade signals on confirmed sequences. Risk Management: Calculates dynamic SL/TP with a default risk-reward ratio of 1:2, minimum SL of 4 pts, and maximum of 12 pts. 📊 Visual Features: Trend lines from Supertrend and SAR. Colored background zones for different sessions (Asia, NY). Labels and lines for entry, SL, and TP. Movement number labels help visualize impulse progression. Alerts when a new impulse is confirmed. ⚙️ How It Works: The strategy waits for a confirmed impulse (i.e., change in SAR + Supertrend + ADX filter). Once a valid impulse is confirmed: A trade signal (BUY/SELL) is shown. SL and TP levels are calculated and drawn. The script monitors live price to determine if SL or TP is hit. Impulse counter advances to label movement progression. 🔔 Alerts: You will receive an alert each time a new valid impulse is confirmed, indicating a potential trading opportunity. 📝 Notes: Script is intended for discretionary or assisted trading, not automated execution. Works best during active sessions with visible trend direction. You can adjust ATR period, multiplier, SL padding, and impulse thresholds. Credits: Developed by LANZ combines established technical indicators and original impulse-count logic.
Indicatore Pine Script®
di rau_u_lanz