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Price Action Dynamics Oscillator (PADO)1 minute ago Price Action Dynamics Oscillator (PADO) Indicator Overview and Technical Deep Dive Concept and Philosophy The Price Action Dynamics Oscillator (PADO) is a sophisticated technical analysis tool designed to provide multi-dimensional insights into market behavior by decomposing price action into manipulation and distribution metrics. The indicator goes beyond traditional momentum or trend indicators by introducing a nuanced approach to understanding market microstructure. Key Architectural Components 1. Timeframe and Depth Selection Pivot Depth Options: Short Term (Length: 12 periods) Intermediate Term (Length: 20 periods) Long Term (Length: 100 periods) This flexible configuration allows traders to adapt the indicator's sensitivity to different market conditions and trading styles. 2. Core Calculation Methodology Manipulation Metrics Calculates manipulation differently for green (bullish) and red (bearish) candles Normalized against Average True Range (ATR) for consistent comparison across different volatility environments Green Candle Manipulation: (Open - Low) / ATR Red Candle Manipulation: (High - Open) / ATR Distribution Metrics Measures the directional strength and potential momentum shift Green Candle Distribution: (Close - Open) Red Candle Distribution: (Open - Close) 3. Normalization and Smoothing Uses Simple Moving Average (SMA) for smoothing Dynamic length calculation based on price range distance Ensures minimum SMA length of 2 to prevent calculation errors Unique Features Visualization Toggles Traders can selectively display: Manipulation data Distribution data Long-term reference lines Valuation metrics Strategy signals Valuation Comparative Analysis Compares current manipulation and distribution metrics to 1000-bar long-term averages Color-coded visualization for quick interpretation Blue: Manipulation above average Purple: Manipulation below average Orange: Distribution above average Yellow: Distribution below average Strategy Deployment Generates a composite strategy signal by comparing manipulation and distribution valuations Uses Exponential Moving Average (EMA) for smoother signal generation Incorporates volatility bands for context-aware signal interpretation Quadrant Analysis Classifies market state into four quadrants based on manipulation and distribution valuations: Q1: Low Manipulation, High Distribution Q2: High Manipulation, High Distribution Q3: Low Manipulation, Low Distribution Q4: High Manipulation, Low Distribution Each quadrant is color-coded to provide visual market state representation. Warning Signals Manipulation Warning: When strategy crosses below low volatility band Distribution Warning: When strategy crosses above high volatility band Visual Indicators Bar coloration based on strategy momentum Multiple color states representing different market dynamics Recommended Use Cases Intraday and swing trading Multi-timeframe market analysis Volatility and momentum assessment Trend reversal and continuation identification Potential Limitations Complexity might require significant trader education Performance can vary across different market conditions Requires careful parameter optimization Recommended Settings Best used on liquid markets with clear price action Ideal for: Forex Futures Large-cap stocks Cryptocurrency pairs Customization and Optimization Traders should: Backtest across multiple assets Adjust timeframe settings Calibrate visualization toggles Use in conjunction with other technical indicators Licensing Mozilla Public License 2.0 Open-source and modification-friendly Conclusion The PADO represents an advanced approach to market analysis, blending traditional technical analysis with innovative metrics for deeper market understanding. PADO Quadrant Color Analysis: Deep Dive Quadrant Color Scheme Breakdown Quadrant 1: Lime Green Background (RGB: 0, 255, 21, 90) Condition: val_manip < 1 AND val_distr > 1 Market Interpretation: Low Manipulation Pressure High Distribution Activity Potential Scenario: Smart money might be gradually distributing positions Trading Implications: Caution for current trend followers Potential preparation for trend change Increased probability of consolidation or reversal Quadrant 2: Bright Blue Background (RGB: 0, 191, 255, 90) Condition: val_manip > 1 AND val_distr > 1 Market Interpretation: High Manipulation Pressure High Distribution Activity Potential Scenario: Strong institutional involvement Potential market transition phase Significant volume and momentum Trading Implications: High volatility expected Increased market uncertainty Potential for sharp price movements Requires careful risk management Quadrant 3: Light Gray Background (RGB: 252, 252, 252, 90) Condition: val_manip < 1 AND val_distr < 1 Market Interpretation: Low Manipulation Pressure Low Distribution Activity Potential Scenario: Market consolidation Reduced institutional activity Potential low-volatility period Trading Implications: Range-bound market Reduced trading opportunities Potential setup for future breakout Ideal for mean reversion strategies Quadrant 4: Light Yellow Background (Hex: #f6ff0019) Condition: val_manip > 1 AND val_distr < 1 Market Interpretation: High Manipulation Pressure Low Distribution Activity Potential Scenario: Accumulation of positions Trading Implications: Increased probability of directional move soon Color Psychology and Technical Significance Color Selection Rationale Lime Green (Q1): Represents potential growth and transition Bright Blue (Q2): Signifies high energy and institutional activity Light Gray (Q3): Indicates neutrality and consolidation Transparent Green (Q4): Suggests emerging trend potential Advanced Interpretation Guidelines Color Transition Analysis Observe how the quadrant colors change Rapid color shifts might indicate: Market regime changes Shifts in institutional sentiment Potential trend acceleration or reversal Technical Implementation Notes Calculation Snippet pinescriptCopyq1 = (val_manip < 1) and (val_distr > 1) q2 = (val_manip > 1) and (val_distr > 1) q3 = (val_manip < 1) and (val_distr < 1) q4 = (val_manip > 1) and (val_distr < 1) bgcolor(q1 ? color.rgb(0, 255, 21, 90): q2 ? color.rgb(0, 191, 255, 90): q3 ? color.rgb(252, 252, 252, 90): q4 ? #f6ff0019:na) Alpha Channel (Transparency) 90 and 0x19 values ensure background color doesn't overwhelm chart Allows underlying price action to remain visible Subtle visual cue without significant chart obstruction Practical Trading Recommendations Never Trade Solely on Quadrant Colors Use as a complementary analysis tool Combine with other technical and fundamental indicators Timeframe Considerations Validate quadrant signals across multiple timeframes Longer timeframes provide more reliable signals Risk Management Set appropriate stop-loss levels Use position sizing strategies Be prepared for false signals Recommended Workflow Identify current quadrant Assess overall market context Confirm with other indicators Execute with proper risk management
Penunjuk Pine Script®
oleh Kill_Streak
VAMA - Volume Adjusted Moving Average [jpkxyz]VAMA is a moving average that adapts to volume, giving more weight to price movements backed by higher relative volume. This VAMA (Volume Adjusted Moving Average) indicator implementation emphasizes visual clarity. It is based on the VAMA script by @allanster Dual VAMA lines (Fast/Slow) with dynamic coloring: Single-color scheme switches between green (bullish) and red (bearish) Color changes on crossovers rather than relative position Configurable line widths (set to 1 for clean appearance) Visual enhancements: Optional fill between VAMA lines (50% transparency) Crossover dots can be toggled Fills and dots match the current trend color Customization parameters: Independent source inputs for Fast/Slow lines Adjustable VI Factor (volume influence) Sample size control Strict/non-strict calculation toggle The code maintains efficient computation while prioritizing visual feedback for trend changes. It's designed for clear signal identification without visual clutter. Notable style choices: Consistent color theming throughout all visual elements Simplified color transitions (only at crossovers) Subtle transparency for fill areas Minimal dot size for crossover markers VAMA (Volume Adjusted Moving Average) Technical Analysis: Core Calculation: 1. Volume Influence (v2i): v2i = volume / ((total_volume/total_periods) * volume_factor) - total_volume: Sum of volume over sample period - total_periods: Either full history (nvb=0) or specified sample size - volume_factor: Controls sensitivity to volume deviation 2. Price Weighting: weighted_price = source_price * v2i 3. Accumulation Process: - Iterates through length*10 periods - Accumulates weighted prices and volume influence values - Continues until volume influence sum >= specified length or strict rule triggers 4. Final VAMA Value: vama = (weighted_sum - (volume_sum - length) * last_price) / length Parameters: - SampleN: Historical reference length (0=full history) - Length: Base period for calculation - VI Factor: Volume influence multiplier (>0.01) - Strict: Forces exact length period completion when true - Source: Input price data
Penunjuk Pine Script®
oleh jpkxyz
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)
Perpustakaan Pine Script®
oleh crypto_pumpppp
Infinity Market Grid -AynetConcept Imagine viewing the market as a dynamic grid where price, time, and momentum intersect to reveal infinite possibilities. This indicator leverages: Grid-Based Market Flow: Visualizes price action as a grid with zones for: Accumulation Distribution Breakout Expansion Volatility Compression Predictive Dynamic Layers: Forecasts future price zones using historical volatility and momentum. Tracks event probabilities like breakout, fakeout, and trend reversals. Data Science Visuals: Uses heatmap-style layers, moving waveforms, and price trajectory paths. Interactive Alerts: Real-time alerts for high-probability market events. Marks critical zones for "buy," "sell," or "wait." Key Features Market Layers Grid: Creates dynamic "boxes" around price using fractals and ATR-based volatility. These boxes show potential future price zones and probabilities. Volatility and Momentum Waves: Overlay volatility oscillators and momentum bands for directional context. Dynamic Heatmap Zones: Colors the chart dynamically based on breakout probabilities and risk. Price Path Prediction: Tracks price trajectory as a moving "wave" across the grid. How It Works Grid Box Structure: Upper and lower price levels are based on ATR (volatility) and plotted dynamically. Dashed green/red lines show the grid for potential price expansion zones. Heatmap Zones: Colors the background based on probabilities: Green: High breakout probability. Blue: High consolidation probability. Price Path Prediction: Forecasts future price movements using momentum. Plots these as a dynamic "wave" on the chart. Momentum and Volatility Waves: Shows the relationship between momentum and volatility as oscillating waves. Helps identify when momentum exceeds volatility (potential breakouts). Buy/Sell Signals: Triggers when price approaches grid edges with strong momentum. Provides alerts and visual markers. Why Is It Revolutionary? Grid and Wave Synergy: Combines structural price zones (grid boxes) with real-time momentum and volatility waves. Predictive Analytics: Uses momentum-based forecasting to visualize what’s next, not just what’s happening. Dynamic Heatmap: Creates a living map of breakout/consolidation zones in real-time. Scalable for Any Market: Works seamlessly with forex, crypto, and stocks by adjusting the ATR multiplier and box length. This indicator is not just a tool but a framework for understanding market dynamics at a deeper level. Let me know if you'd like to take it even further — for example, adding machine learning-inspired probability models or multi-timeframe analysis! 🚀
Penunjuk Pine Script®
oleh Aynet-London
Enhanced Volume Flow Analysis Pro ♾️ IFEnhanced Volume Flow Analysis Pro (EVFA Pro) A Comprehensive Guide to Understanding and Using Volume Flow Analysis Introduction The Enhanced Volume Flow Analysis Pro (EVFA Pro) represents a sophisticated approach to understanding market dynamics through the lens of volume analysis. This advanced technical indicator has been designed to peel back the layers of market activity, revealing the intricate dance between institutional and retail traders. By combining volume analysis, participant behavior patterns, and market condition recognition, EVFA Pro provides traders with a deeper understanding of market movements and potential opportunities. Understanding the Core Framework At its heart, EVFA Pro works by analyzing and categorizing trading volume based on several key characteristics. The indicator examines not just the raw volume, but also the context in which that volume occurs. It considers factors such as price movement, historical patterns, and market conditions to classify trading activity as either institutional or retail in nature. The framework adapts dynamically to different market environments. Whether you're trading stocks, ETFs, cryptocurrencies, or commodities, the indicator automatically adjusts its parameters to match the typical behavior patterns of each asset class. This adaptability extends to different trading styles as well, with optimizations for everything from quick-paced scalping to longer-term position trading. Market Participant Analysis One of the most powerful aspects of EVFA Pro is its ability to distinguish between institutional and retail trading activity. The indicator accomplishes this through a sophisticated analysis of volume patterns, order flow, and price action. Institutional trading typically leaves distinct footprints in the market - large, well-organized volume patterns that often occur at strategic price levels. EVFA Pro identifies these patterns and separates them from the more scattered, emotion-driven patterns typical of retail trading. The indicator maintains a constant watch on participation rates from both groups. When institutional participation rises above normal levels, it could signal the beginning of a significant move. Similarly, spikes in retail activity, especially when combined with certain price patterns, might indicate potential market turning points. Reading Market Conditions Market conditions are not static, and EVFA Pro recognizes this fundamental truth. The indicator continuously evaluates market conditions, classifying them into four main categories: normal, volatile, ranging, and trending. This classification isn't merely descriptive - it directly influences how the indicator interprets various patterns and signals. In volatile markets, the indicator becomes more conservative in its pattern recognition, requiring stronger confirmation before signaling potential opportunities. During ranging periods, it adjusts to look for shorter-term movements and potential breakout scenarios. In trending markets, the focus shifts to finding continuation patterns and potential exhaustion points. Pattern Recognition and Signal Generation Pattern recognition in EVFA Pro goes beyond simple technical patterns. The indicator looks for complex interactions between volume, price, and participant behavior. It identifies accumulation patterns - periods where institutional buyers are actively building positions, often while keeping price movements relatively subtle to avoid drawing attention. Similarly, it recognizes distribution patterns, where larger players are gradually reducing positions. Signal generation involves a sophisticated weighing of multiple factors. Volume strength, institutional participation, trend alignment, and price momentum all play roles in determining signal strength. This multi-factor approach helps reduce false signals and provides a more reliable indication of potential market moves. Visual Analysis Tools The visual components of EVFA Pro have been carefully designed to present complex information in an intuitive format. The main chart overlay uses color-coded volume bars to show the relative participation of institutional and retail traders. The intensity of these colors varies with volume significance, helping traders quickly identify potentially important market activity. The information table provides a real-time summary of market conditions, participant activity, and detected patterns. This dashboard-style display allows traders to quickly assess market conditions and potential opportunities without needing to analyze multiple indicators. Practical Application in Trading To use EVFA Pro effectively, traders should integrate it into a comprehensive trading strategy. The indicator works best when its signals are considered alongside other forms of analysis and risk management tools. Strong signals from EVFA Pro might suggest potential opportunities, but traders should always consider the broader market context, their own risk tolerance, and their overall trading plan. The indicator's alerts system can help traders stay informed of potentially significant market developments. However, these alerts should be viewed as starting points for analysis rather than automatic trading signals. Each alert provides specific information about the type of pattern or condition detected, allowing traders to quickly assess whether further investigation is warranted. Advanced Features and Customization EVFA Pro offers extensive customization options to suit different trading styles and preferences. Traders can adjust sensitivity levels, color schemes, and display options to match their needs. The indicator also includes special considerations for different trading sessions, allowing for more accurate analysis during pre-market, regular trading hours, and after-hours periods. Market Application and Interpretation Success with EVFA Pro comes from understanding not just what it shows, but why it shows what it does. The indicator's patterns and signals reflect real market dynamics - the actions and reactions of different types of traders. By understanding these underlying dynamics, traders can make more informed decisions about market opportunities and risks. Disclaimer This indicator and documentation are provided for educational and informational purposes only. Trading in financial markets involves substantial risk of loss and is not suitable for every investor. The analysis provided by the Enhanced Volume Flow Analysis Pro indicator should not be considered as financial advice or a recommendation to make any specific trade or investment. Users of this indicator should understand that: 1. Past performance is not indicative of future results 2. All trading decisions and their outcomes are the responsibility of the individual trader 3. This tool should be used as part of a comprehensive trading strategy that includes proper risk management and due diligence 4. Markets can be highly unpredictable, and no technical analysis tool can guarantee success Users should carefully consider their investment objectives, level of experience, and risk appetite before using this indicator. It is strongly recommended to consult with a qualified financial advisor before making any investment decisions.
Penunjuk Pine Script®
oleh Infinitefutures
Chaikin DivergenceOverview The Chaikin Divergence is a powerful technical indicator designed to enhance the traditional Chaikin Oscillator by incorporating divergence detection between the oscillator and price action. This advanced tool not only plots the Chaikin Oscillator but also identifies and highlights bullish and bearish divergences, providing traders with valuable insights into potential trend reversals and momentum shifts. Key Features Chaikin Oscillator Plotting: Visual representation of the Chaikin Oscillator, aiding in the analysis of market momentum based on volume and price. Divergence Detection: Bullish Divergence: Indicates potential upward reversals when price forms lower lows while the oscillator forms higher lows. Bearish Divergence: Signals possible downward reversals when price creates higher highs while the oscillator forms lower highs. Customizable Settings: Fast Length & Slow Length: Adjust the periods for the Exponential Moving Averages (EMA) used in the oscillator calculation. Pivot Detection Parameters: Define the sensitivity of pivot high and pivot low detection with adjustable left and right bars. Bars Lookback for Divergence: Set the number of bars to look back for identifying divergences. Color Customization: Choose distinct colors for bullish and bearish divergence labels to match your trading preferences. Visual Indicators: Divergence Labels: Clear and distinct labels (arrows or dots) on the chart indicating the type and location of divergences. Zero Line: A dashed zero line to reference the oscillator’s crossing points. Chaikin Oscillator Calculation: The indicator calculates the Chaikin Oscillator by subtracting the slow EMA of the Accumulation/Distribution Line (ta.accdist) from the fast EMA. This oscillates around the zero line, indicating buying and selling pressure. Pivot Detection: Utilizes ta.pivothigh and ta.pivotlow functions to identify significant pivot points in price action. These pivot points serve as reference points for divergence analysis. Divergence Identification: Bullish Divergence: Detected when a recent pivot low in price is lower than the previous pivot low, while the corresponding oscillator value is higher than the previous oscillator pivot. Bearish Divergence: Identified when a recent pivot high in price is higher than the previous pivot high, but the oscillator value is lower than the previous oscillator pivot. Label Plotting: When a divergence is detected, the indicator plots a label (arrow or dot) on the chart at the pivot point, signaling the type of divergence. Adding the Indicator: Open TradingView and navigate to the chart where you want to apply the indicator. Open the Pine Editor, paste the Chaikin Oscillator with Divergences script, and add it to your chart. Configuring Settings: Fast Length & Slow Length: Adjust these to modify the sensitivity of the Chaikin Oscillator. Shorter periods make the oscillator more responsive to price changes. Left Bars for Pivots & Right Bars for Pivots: Define how many bars to the left and right are considered when identifying pivot points. Increasing these values makes pivot detection less sensitive. Bars Lookback for Divergence: Set how far back the indicator should search for previous pivot points when identifying divergences. A higher value allows detection over a longer timeframe. Bullish/Bearish Divergence Colors: Choose colors that stand out against your chart background for easy identification of divergence signals. Interpreting Signals: Bullish Divergence Labels: Appear when there's a potential upward reversal, signaling a possible buying opportunity. Bearish Divergence Labels: Show up when a downward reversal might be imminent, indicating a possible selling opportunity. Oscillator Crosses Zero: Pay attention to when the oscillator crosses the zero line, as this can also signal changes in momentum. Combining with Other Indicators: For enhanced trading strategies, combine divergence signals with other technical indicators or chart patterns to confirm potential trade setups.
Penunjuk Pine Script®
oleh zaqwasick
Pulse DPO: Major Cycle Tops and Bottoms█  OVERVIEW Pulse DPO is an oscillator designed to highlight Major Cycle Tops and Bottoms . It works on any market driven by cycles. It operates by removing the short-term noise from the price action and focuses on the market's cyclical nature. This indicator uses a Normalized version of the Detrended Price Oscillator (DPO) on a 0-100 scale, making it easier to identify major tops and bottoms. Credit: The DPO was first developed by William Blau in 1991. █  HOW TO READ IT Pulse DPO oscillates in the range between 0 and 100. A value in the upper section signals an OverBought (OB) condition, while a value in the lower section signals an OverSold (OS) condition. Generally, the triggering of OB and OS conditions don't necessarily translate into swing tops and bottoms, but rather suggest caution on approaching a market that might be overextended. Nevertheless, this indicator has been customized to trigger the signal only during remarkable top and bottom events. I suggest using it on the Daily Time Frame , but you're free to experiment with this indicator on other time frames. The indicator has Built-in Alerts to signal the crossing of the Thresholds. Please don't act on an isolated signal, but rather integrate it to work in conjunction with the indicators present in your Trading Plan. █  OB SIGNAL ON: ENTERING OVERBOUGHT CONDITION When Pulse DPO crosses Above the Top Threshold it Triggers ON the OB signal. At this point the oscillator line shifts to OB color. When Pulse DPO enters the OB Zone, please beware! In this Area the Major Players usually become Active Sellers to the Public. While the OB signal is On, it might be wise to Consider Selling a portion or the whole Long Position. Please note that even though this indicator aims to focus on major tops and bottoms, a strong trending market might trigger the OB signal and stay with it for a long time. That's especially true on young markets and on bubble-mode markets. █  OB SIGNAL OFF: EXITING OVERBOUGHT CONDITION When Pulse DPO crosses Below the Top Threshold it Triggers OFF the OB signal. At this point the oscillator line shifts to its normal color. When Pulse DPO exits the OB Zone, please beware because a Major Top might just have occurred. In this Area the Major Players usually become Aggressive Sellers. They might wind up any remaining Long Positions and Open new Short Positions. This might be a good area to Open Shorts or to Close/Reverse any remaining Long Position. Whatever you choose to do, it's usually best to act quickly because the market is prone to enter into panic mode. █  OS SIGNAL ON: ENTERING OVERSOLD CONDITION When Pulse DPO crosses Below the Bottom Threshold it Triggers ON the OS signal. At this point the oscillator line shifts to OS color. When Pulse DPO enters the OS Zone, please beware because in this Area the Major Players usually become Active Buyers accumulating Long Positions from the desperate Public. While the OS signal is On, it might be wise to Consider becoming a Buyer or to implement a Dollar-Cost Averaging (DCA) Strategy to build a Long Position towards the next Cycle. In contrast to the tops, the OS state usually takes longer to resolve a major bottom. █  OS SIGNAL OFF: EXITING OVERSOLD CONDITION When Pulse DPO crosses Above the Bottom Threshold it Triggers OFF the OS signal. At this point the oscillator line shifts to its normal color. When Pulse DPO exits the OS Zone, please beware because a Major Bottom might already be in place. In this Area the Major Players become Aggresive Buyers. They might wind up any remaining Short Positions and Open new Long Positions. This might be a good area to Open Longs or to Close/Reverse any remaining Short Positions. █  WHY WOULD YOU BE INTERESTED IN THIS INDICATOR? This indicator is built over a solid foundation capable of signaling Major Cycle Tops and Bottoms across many markets. Let's see some examples: Early Bitcoin Years: From 0 to 1242 This chart is in logarithmic mode in order to properly display various exponential cycles. Pulse DPO is properly signaling the major early highs from 9-Jun-2011 at 31.50, to the next one on 9-Apr-2013 at 240 and the epic top from 29-Nov-2013 at 1242. Due to the massive price movements, the OB condition stays pinned during most of the exponential price action. But as you can see, the OB condition quickly vanishes once the Cycle Top has been reached. As the market matures, the OB condition becomes more exceptional and triggers much closer from the Cycle Top. With regards to Cycle Bottoms, the early bottom of 2 after having peaked at 31.50 doesn’t get captured by the indicator. That is the only cycle bottom that escapes the Pulse DPO when the bottom threshold is set at a value of 5. In that event, the oscillator low reached 6.95. Bitcoin Adoption Spreading: From 257 to 73k This chart is in logarithmic mode in order to properly display various exponential cycles. Pulse DPO is properly signaling all the major highs from 17-Dec-2017 at 19k, to the next one on 14-Apr-2021 at 64k and the most recent top from 9-Nov-2021 at 68k. During the massive run of 2017, the OB condition still stayed triggered for a few weeks on each swing top. But on the next cycles it started to signal only for a few days before each swing top actually happened. The OB condition during the last cycle top triggered only for 3 days. Therefore the signal grows in focus as the market matures. At the time of publishing this indicator, Bitcoin printed a new All Time High (ATH) on 13-Mar-2024 at 73k. That run didn’t trigger the OB condition. Therefore, if the indicator is correct the Bitcoin market still has some way to grow during the next months. With regards to Cycle Bottoms, the bottom of 3k after having peaked at19k got captured within the wide OS zone. The bottom of 15k after having peaked at 68k got captured too within the OS accumulation area. Gold Pulse DPO behaves surprisingly well on a long standing market such as Gold. Moving back to the 197x years it’s been signaling most Cycle Tops and Bottoms with precision. During the last cycle, it shows topping at 2k and bottoming at 1.6k. The current price action is signaling OB condition in the range of 2.5k to 2.7k. Looking at past cycles, it tends to trigger on and off at multiple swing tops until reaching the final cycle top. Therefore this might indicate the first wave within a potential gold run. Oil On the Oil market, we can see that most of the cycle tops and bottoms since the 80s got signaled. The only exception being the low from 2020 which didn’t trigger. EURUSD On Forex markets the Pulse DPO also behaves as expected. Looking back at EURUSD we can see the marketing triggering OB and OS conditions during major cycle tops and bottoms from recent times until the 80s. S&P 500 On the S&P 500 the Pulse DPO catched the lows from 2016 and 2020. Looking at present price action, the recent ATH didn’t trigger the OB condition. Therefore, the indicator is allowing room for another leg up during the next months. Amazon On the Amazon chart the Pulse DPO is mirroring pretty accurately the major swings. Scrolling back to the early 2000s, this chart resembles early exponential swings in the crypto space. Tesla Moving onto a younger tech stock, Pulse DPO captures pretty accurately the major tops and bottoms. The chart is shown in logarithmic scale to better display the magnitude of the moves. █  SETTINGS This indicator is ideal for identifying major market turning points while filtering out short-term noise. You are free to adjust the parameters to align with your preferred trading style. Parameters : This section allows you to customize any of the Parameters that shape the Oscillator. Oscillator Length: Defines the period for calculating the Oscillator. Offset: Shifts the oscillator calculation by a certain number of periods, which is typically half the Oscillator Length. Lookback Period: Specifies how many bars to look back to find tops and bottoms for normalization. Smoothing Length: Determines the length of the moving average used to smooth the oscillator. Thresholds : This section allows you to customize the Thresholds that trigger the OB and OS conditions. Top: Defines the value of the Top Threshold. Bottom: Defines the value of the Bottom Threshold.
Penunjuk Pine Script®
oleh gliderfund
4
Leonid's Bitcoin Full Cycle Simple SMA IndicatorThis is a straight-forward and customizable indicator to track Bitcoin cycles, specifically used for helping investors understand where to buy and sell. This is done by using a two year SMA period as the base calculation. With that calculation you create lower and upper bounds for bull market peaks and bear market bottoms. The novel idea here is that you can customize the SMA "strength" for both the upper and lower bounds as alpha decays over time and price get's less volatile with adoption increasing. The multiples are customizable for both the upper and lower bounds along with a mid-line that will adjust based on the settings input. Indicators don't always have to rely on crazy math or outlandish ideas to be useful, sometimes even the simplest of inputs can give investors (especially those that are new) a great base case for their strategy. Something being simple does not diminish the idea or strength behind the data. How to use this indicator: This script must be used on INDEX:BTCUSD (Bitcoin All-Time History Index) with the y-axis being set to Logarithmic scale. Details & how to interpret: The price is colored green when Bitcoin enters a "value zone" meaning it is heavily oversold and likely near a bottom for the bear market cycle. The price is colored red when Bitcoin enters an "overbought zone" meaning it is heavily overbought and is likely near a top for the bull market cycle. Along with the upper and lower bound I have plotted a mid-line (in orange) to establish a neutral zone which helps depict what phase of the cycle we're in (under mid-line = bearish/accumulation phase, over mid-line = bullish/distribution phase). The inputs for the upper and lower bound are customizable and will need to be adjusted over time as alpha decay will occur as time goes on. Currently the numbers are as follows: 0.2 for the lower bound 4.675 for the upper bound Both inputs can be modified depending on your risk tolerance. Mathematically it is safe to assume these numbers will decrease as time goes on and volatility during cycle peaks & troughs is reduced. I've also plotted an upper bound "heat zone" which is shaded in green, this area is great for signaling when you should be preparing to begin taking profits. It takes the upper bound and subtracts the lower bound to derive the band. All the colors are customizable and this indicator is best used on a line chart but can be customized to use on a bar chart/candlestick as well. Simple Moving Averages are a very basic indicator but are often extremely powerful because the majority of traders/investors are looking at such levels which creates a psychological/herd effect. Another good example is the law of round numbers. Regardless this script can be adapted with EMAs or additional standard deviations if necessary. If you have any questions or concerns please don't hesitate to message me.
Penunjuk Pine Script®
oleh LeonidBTC
CRT candles Multi-Timeframe Intrabar(open Source ) # CRT candles Multi-Timeframe Intrabar Indicator( open source ) This advanced indicator visualizes Candle Range Theory (CRT) across multiple timeframes, providing traders with a comprehensive view of market structure and potential high-probability setups. ## Key Features: - Supports 7 timeframes: 30 minutes, 1 hour, 2 hours, 4 hours, daily, weekly, and monthly - Customizable color schemes for each timeframe - Options to display mid-level (50%) lines for each range - Bullish and bearish touch detection with customizable label display - End-of-line labels for easy identification of CRT levels - Flexible alert system for touch detections on each timeframe - Adjustable minimum and maximum bar count for range validity - Options for wick touch and body touch detection ## How It Works: The indicator plots CRT ranges for each selected timeframe, identifying potential accumulation, manipulation, and distribution phases. It detects when price touches these levels, providing visual cues and optional alerts for potential trade setups. snapshot ## Customization: Users can fine-tune the indicator's appearance and functionality through various input options, including: - Toggling timeframes on/off snapshot - Adjusting colors for range lines and mid-levels - Controlling label display and count - Setting alert preferences - Adjusting line widths and label offsets ## Usage: This indicator is designed for traders familiar with Candle Range Theory and multi-timeframe analysis. It can be used to identify potential entry and exit points, confirm trends, and spot potential reversals across different timeframes. ## Note: This indicator is for educational and informational purposes only. Always combine with other forms of analysis and proper risk management when making trading decisions. ## Credits: Inspired by Romeo's Candle Range Theory and developed to provide a comprehensive multi-timeframe analysis tool.
Penunjuk Pine Script®
oleh GoldForexDoc
9
Support, Resistance & Liquidity Pool ZonesSupport, Resistance & Liquidity Pool Zones This indicator automatically detects and plots support and resistance levels based on pivot points and highlights liquidity pool zones, areas where the trading volume exceeds the average over a set number of bars. It is designed to help traders identify key price levels and liquidity traps that can trigger significant market reactions. Key Features: Support & Resistance Levels: The indicator identifies pivot highs and pivot lows as potential resistance and support levels, respectively. You can customize the number of levels shown on the chart, making it easier to focus on the most recent and relevant price levels. Liquidity Pool Zones: The script detects liquidity pool zones, which are areas with above-average trading volume. These zones often act as regions of interest where price accumulation or distribution occurs, potentially leading to significant price moves. Liquidity zones are shaded to help traders visually identify areas of high interest in the market. Customizable Settings: You can adjust the pivot period to fine-tune how the indicator calculates support and resistance. Control the number of support/resistance levels displayed on the chart and the period used to detect liquidity pools. Customize the colors for support, resistance, and liquidity zones to match your charting preferences. Alerts: The script includes built-in alerts for when the price breaks above resistance or falls below support, helping traders catch key breakout opportunities. How It Works: The script calculates support and resistance levels using pivot highs and lows based on the user-defined pivot period. It monitors liquidity pool zones by comparing the current trading volume with the average volume over a customizable period. When the volume exceeds the set threshold, a liquidity pool zone is highlighted, providing insight into where the market may accumulate or distribute. Alerts are triggered when the price breaks above the first resistance level or falls below the first support level, giving traders immediate notification of key market events. How to Use: Tune the Pivot Period: Adjust the pivot period to your preferred time horizon (default: 10 bars). Set Liquidity Pool Parameters: Customize the number of bars considered for liquidity pool detection and the volume multiplier to detect high-volume zones. Monitor Breakouts: Use the built-in alerts to catch potential breakout or breakdown opportunities near support and resistance levels. This script is ideal for traders looking for an easy-to-use tool to visualize support and resistance levels and liquidity pools, aiding in decision-making and trade management.
Penunjuk Pine Script®
oleh teja50516
Bitcoin Cycle Master [InvestorUnknown]The "Bitcoin Cycle Master" indicator is designed for in-depth, long-term analysis of Bitcoin's price cycles, using several key metrics to track market behavior and forecast potential price tops and bottoms. The indicator integrates multiple moving averages and on-chain metrics, offering a comprehensive view of Bitcoin’s historical and projected performance. Each of its components plays a crucial role in identifying critical cycle points: Top Cap: This is a multiple of the Average Cap, which is calculated as the cumulative sum of Bitcoin’s price (price has a longer history than Market Cap) divided by its age in days. Top Cap serves as an upper boundary for speculative price peaks, multiplied by a factor of 35. Time_dif() => date = ta.valuewhen(bar_index == 0, time, 0) sec_r = math.floor(date / 1000) min_r = math.floor(sec_r / 60) h_r = math.floor(min_r / 60) d_r = math.floor(h_r / 24) // Launch of BTC start = timestamp(2009, 1, 3, 00, 00) sec_rb = math.floor(start / 1000) min_rb = math.floor(sec_rb / 60) h_rb = math.floor(min_rb / 60) d_rb = math.floor(h_rb / 24) difference = d_r - d_rb AverageCap() => ta.cum(btc_price) / (Time_dif() + btc_age) TopCap() => // To calculate Top Cap, it is first necessary to calculate Average Cap, which is the cumulative sum of Market Cap divided by the age of the market in days. // This creates a constant time-based moving average of market cap. // Once Average cap is calculated, those values are multiplied by 35. The result is Top Cap. // For AverageCap the BTC price was used instead of the MC because it has more history // (the result should have minimal if any deviation since MC would have to be divided by Supply) AverageCap() * 35 Delta Top: Defined as the difference between the Realized Cap and the Average Cap, this metric is further multiplied by a factor of 7. Delta Top provides a historically reliable signal for Bitcoin market cycle tops. DeltaTop() => // Delta Cap = Realized Cap - Average Cap // Average Cap is explained in the Top Cap section above. // Once Delta Cap is calculated, its values over time are then multiplied by 7. The result is Delta Top. (RealizedPrice() - AverageCap()) * 7 Terminal Price: Derived from Coin Days Destroyed, Terminal Price normalizes Bitcoin’s historical price behavior by its finite supply (21 million bitcoins), offering an adjusted price forecast as all bitcoins approach being mined. The original formula for Terminal Price didn’t produce expected results, hence the calculation was adjusted slightly. CVDD() => // CVDD stands for Cumulative Value Coin Days Destroyed. // Coin Days Destroyed is a term used for bitcoin to identify a value of sorts to UTXO’s (unspent transaction outputs). They can be thought of as coins moving between wallets. (MCR - TV) / 21000000 TerminalPrice() => // Theory: // Before Terminal price is calculated, it is first necessary to calculate Transferred Price. // Transferred price takes the sum of > Coin Days Destroyed and divides it by the existing supply of bitcoin and the time it has been in circulation. // The value of Transferred Price is then multiplied by 21. Remember that there can only ever be 21 million bitcoin mined. // This creates a 'terminal' value as the supply is all mined, a kind of reverse supply adjustment. // Instead of heavily weighting later behavior, it normalizes historical behavior to today. By normalizing by 21, a terminal value is created // Unfortunately the theoretical calculation didn't produce results it should, in pinescript. // Therefore the calculation was slightly adjusted/improvised TransferredPrice = CVDD() / (Supply * math.log(btc_age)) tp = TransferredPrice * 210000000 * 3 Realized Price: Calculated as the Market Cap Realized divided by the current supply of Bitcoin, this metric shows the average value of Bitcoin based on the price at which coins last moved, giving a market consensus price for long-term holders. CVDD (Cumulative Value Coin Days Destroyed): This on-chain metric analyzes Bitcoin’s UTXOs (unspent transaction outputs) and the velocity of coins moving between wallets. It highlights key market dynamics during prolonged accumulation or distribution phases. Balanced Price: The Balanced Price is the difference between the Realized Price and the Terminal Price, adjusted by Bitcoin's supply constraints. This metric provides a useful signal for identifying oversold market conditions during bear markets. BalancedPrice() => // It is calculated by subtracting Transferred Price from Realized Price RealizedPrice() - (TerminalPrice() / (21 * 3)) Each component can be toggled individually, allowing users to focus on specific aspects of Bitcoin’s price cycle and derive meaningful insights from its long-term behavior. The combination of these models provides a well-rounded view of both speculative peaks and long-term value trends. Important consideration: Top Cap did historically provide reliable signals for cycle peaks, however it may not be a relevant indication of peaks in the future.
Penunjuk Pine Script®
oleh InvestorUnknown
5
Swiss Knife [MERT]Introduction The Swiss Knife indicator is a comprehensive trading tool designed to provide a multi-dimensional analysis of the market. By integrating a wide array of technical indicators across multiple timeframes, it offers traders a holistic view of market sentiment, momentum, and potential reversal points. This indicator is particularly useful for traders looking to combine trend analysis, momentum indicators, volume data, and price action into a single, easy-to-read format. --- Key Features Multi-Timeframe Analysis : Evaluates indicators on Daily , 4-Hour , 1-Hour , and 15-Minute timeframes. Comprehensive Indicator Suite : Incorporates MACD , Awesome Oscillator (AO) , Parabolic SAR , SuperTrend , DPO , RSI , Stochastic Oscillator , Bollinger Bands , Ichimoku Cloud , Chande Momentum Oscillator (CMO) , Donchian Channels , ADX , volume-based momentum indicators, Fractals , and divergence detection. Market Sentiment Scoring : Aggregates signals from multiple indicators to provide an overall sentiment score. Visual Aids : Displays EMA lines, trendlines, divergence signals, and a sentiment table directly on the chart. Super Trend Reversal Signals : Identifies potential market reversal points by assessing the momentum of automated trading bots. --- Explanation of Each Indicator Moving Average Convergence Divergence (MACD) - Purpose : Measures the relationship between two moving averages of price. - Interpretation : A positive histogram suggests bullish momentum; a negative histogram indicates bearish momentum. Awesome Oscillator (AO) - Purpose : Gauges market momentum by comparing recent market movements to historic ones. - Interpretation : Above zero indicates bullish momentum; below zero indicates bearish momentum. Parabolic SAR (SAR) - Purpose : Identifies potential reversal points in price direction. - Interpretation : Dots below price suggest an uptrend; dots above price suggest a downtrend. SuperTrend - Purpose : Determines the prevailing market trend. - Interpretation : Provides buy or sell signals based on price movements relative to the SuperTrend line. Detrended Price Oscillator (DPO) - Purpose : Removes trend from price to identify cycles. - Interpretation : Values above zero suggest price is above the moving average; values below zero indicate it is below. Relative Strength Index (RSI) - Purpose : Measures the speed and change of price movements. - Interpretation : Values above 50 indicate bullish momentum; values below 50 indicate bearish momentum. Stochastic Oscillator - Purpose : Compares a particular closing price to a range of its prices over a certain period. - Interpretation : Values above 50 indicate bullish conditions; values below 50 indicate bearish conditions. Bollinger Bands (BB) - Purpose : Measures market volatility and provides relative price levels. - Interpretation : Price above the middle band suggests bullishness; below the middle band suggests bearishness. Ichimoku Cloud - Purpose : Provides support and resistance levels, trend direction, and momentum. - Interpretation : Bullish signals when price is above the cloud; bearish signals when price is below the cloud. Chande Momentum Oscillator (CMO) - Purpose : Measures momentum on both up and down days. - Interpretation : Values above 50 indicate strong upward momentum; values below -50 indicate strong downward momentum. Donchian Channels - Purpose : Identifies volatility and potential breakouts. - Interpretation : Price above the upper band suggests bullish breakout; below the lower band suggests bearish breakout. Average Directional Index (ADX) - Purpose : Measures the strength of a trend. - Interpretation : DI+ above DI- indicates bullish trend; DI- above DI+ indicates bearish trend. Volume Momentum Indicators (VolMom, CumVolMom, POCMom) - Purpose : Analyze volume to assess buying and selling pressure. - Interpretation : Positive values suggest bullish volume momentum; negative values indicate bearish volume momentum. Fractals - Purpose : Identify potential reversal points in the market. - Interpretation : Up fractals may indicate a future downtrend; down fractals may indicate a future uptrend. Divergence Detection - Purpose : Identifies divergences between price and various indicators (RSI, MACD, Stochastic, OBV, MFI, A/D Line). - Interpretation : Bullish divergences suggest potential upward reversal; bearish divergences suggest potential downward reversal. - Note : This functionality utilizes the library from Divergence Indicator . --- Coloring Scheme Background Color - Purpose : Reflects the overall market sentiment by combining sentiment scores from all indicators across different timeframes. - Interpretation : - Green Shades : Indicate bullish market sentiment. - Red Shades : Indicate bearish market sentiment. - Intensity : The strength of the color corresponds to the strength of the sentiment score. Sentiment Table - Purpose : Displays the status of each indicator across different timeframes. - Interpretation : - Green Cell : The indicator suggests a bullish signal. - Red Cell : The indicator suggests a bearish signal. - Percentage Score : Indicates the overall bullish or bearish sentiment on that timeframe. Exponential Moving Averages (EMAs) - Purpose : Provide dynamic support and resistance levels. - Colors : - EMA 10 : Lime - EMA 20 : Yellow - EMA 50 : Orange - EMA 100 : Red - EMA 200 : Purple Trendlines - Purpose : Visual representation of support and resistance levels based on pivot points. - Interpretation : - Upward Trendlines : Colored green , indicating support levels. - Downward Trendlines : Colored red , indicating resistance levels. - Note : Trendlines are drawn using the library from Simple Trendlines . --- Utility of Market Sentiment The indicator aggregates signals from multiple technical indicators across various timeframes to compute an overall market sentiment score . This comprehensive approach helps traders understand the prevailing market conditions by: Confirming Trends : Multiple indicators pointing in the same direction can confirm the strength of a trend. Identifying Reversals : Divergences and fractals can signal potential turning points. Timeframe Alignment : Aligning signals across different timeframes can enhance the probability of successful trades. --- Divergences Divergence occurs when the price of an asset moves in the opposite direction of a technical indicator, suggesting a potential reversal. - Bullish Divergence : Price makes a lower low, but the indicator makes a higher low. - Bearish Divergence : Price makes a higher high, but the indicator makes a lower high. The indicator detects divergences for: RSI MACD Stochastic Oscillator On-Balance Volume (OBV) Money Flow Index (MFI) Accumulation/Distribution Line (A/D Line) By identifying these divergences, traders can spot early signs of trend reversals and adjust their strategies accordingly. --- Trendlines Trendlines are essential tools for identifying support and resistance levels. The indicator automatically draws trendlines based on pivot points: - Upward Trendlines (Support) : Connect higher lows, indicating an uptrend. - Downward Trendlines (Resistance) : Connect lower highs, indicating a downtrend. These trendlines help traders visualize the trend direction and potential breakout or reversal points. --- Super Trend Reversals (ST Reversal) The core idea behind the Super Trend Reversals indicator is to assess the momentum of automated trading bots (often referred to as 'Supertrend bots') that enter the market during critical turning points. Specifically, the indicator is tuned to identify when the market is nearing bottoms or peaks, just before it shifts direction based on the triggered Supertrend signals. This approach helps traders: Engage Early : Enter the market as reversal momentum builds up. Optimize Entries and Exits : Enter under favorable conditions and exit before momentum wanes. By capturing these reversal points, traders can enhance their trading performance. --- Conclusion The Swiss Knife indicator serves as a versatile tool that combines multiple technical analysis methods into a single, comprehensive indicator. By assessing various aspects of the market—including trend direction, momentum, volume, and price action—it provides traders with valuable insights to make informed trading decisions. --- Citations - Divergence Detection Library : Divergence Indicator by DevLucem - Trendline Drawing Library : Simple Trendlines by HoanGhetti --- Note : This indicator is intended for informational purposes and should be used in conjunction with other analysis techniques. Always perform due diligence before making trading decisions. ---
Penunjuk Pine Script®
oleh mertenes3
10
Tian Di Grid Merge Version 6.0 Strategy Introduction: 1. We know that the exchange can only set a maximum of 100 grids. However, our grid strategy can set a maximum of 350 grids. 2. We have added the modes of proportional and differential warehousing. 3. It should be noted that we have not set any filtering conditions, which means that when the price falls below the grid, we will execute a buy action at the closing price, and when the price falls above the grid, we will execute a sell action; 4. We suggest limiting the trading time cycle to 5 meters, as sometimes errors may appear on TV due to the dense grid or the inability to draw so many grids; 5. Please ensure that the minimum spacing between each grid is not less than 0.1%, as this is extremely difficult to profit from, and on the other hand, it may not function due to excessively dense spacing; 6. The maximum number of grids is 350, and the minimum number is currently 3; matters needing attention: Don't choose to go long or short together, and don't choose to go even short or short; Closing position setting: It is recommended to select it to avoid order accumulation; Unable to trade: If unable to trade normally, switch to a 1m cycle; Number of cells: Calculate it yourself, 350 is just the maximum number of cells that can be adjusted; Grid spacing: minimum 0.1%, below which no profit can be made; Position value: default is 100u, which is the amount already leveraged; Multiple investment: The order amount for each order is the same, and there is no need for multiple investment; Open both long and short positions: You can open multiple positions for one account and open one position for one account. Do not open both long and short positions for the same target at the same time
Strategi Pine Script®
oleh zhiming
8
VWAP PressureKey Features and Utility: Intrabar Focus: Unlike standard VWAP, which provides a cumulative average throughout the day, the Intrabar VWAP focuses on volume-weighted price calculations within shorter time frames. This allows traders to see how price and volume interact moment-to-moment, offering a granular view of market sentiment. Market Pressure Analysis: The indicator examines the difference between a smoothed weighted average price of the close and intrabar price movements. This analysis helps in identifying the market pressure at high volume areas. When the market exhibits high volume at low prices within a bar, it suggests accumulation, whereas high volume at high prices indicates distribution. Momentum and Pressure Shift Signals: By applying a modified MACD calculation to the smoothed difference, the indicator provides signals on shifts in market pressure. Positive values indicate upward price momentum (buying pressure), while negative values suggest downward momentum (selling pressure).
Penunjuk Pine Script®
oleh mertenes3
Uptrick: Momentum-Volatility Composite Signal### Title: Uptrick: Momentum-Volatility Composite Signal ### Overview The "Uptrick: Momentum-Volatility Composite Signal" is an innovative trading tool designed to offer traders a sophisticated synthesis of momentum, volatility, volume flow, and trend detection into a single comprehensive indicator. This tool stands out by providing an integrated view of market dynamics, which is critical for identifying potential trading opportunities with greater precision and confidence. Its unique approach differentiates it from traditional indicators available on the TradingView platform, making it a valuable asset for traders aiming to enhance their market analysis. ### Unique Features This indicator integrates multiple crucial elements of market behavior: - Momentum Analysis : Utilizes Rate of Change (ROC) metrics to assess the speed and strength of market movements. - Volatility Tracking : Incorporates Average True Range (ATR) metrics to measure market volatility, aiding in risk assessment. - Volume Flow Analysis : Analyzes shifts in volume to detect buying or selling pressure, adding depth to market understanding. - Trend Detection : Uses the difference between short-term and long-term Exponential Moving Averages (EMA) to detect market trends, providing insights into potential reversals or confirmations. Customization and Inputs The Uptrick indicator offers a variety of user-defined settings tailored to fit different trading styles and strategies, enhancing its adaptability across various market conditions: Rate of Change Length (rocLength) : This setting defines the period over which momentum is calculated. Shorter periods may be preferred by day traders who need to respond quickly to market changes, while longer periods could be better suited for position traders looking at more extended trends. ATR Length (atrLength) : Adjusts the timeframe for assessing volatility. A shorter ATR length can help day traders manage the quick shifts in market volatility, whereas longer lengths might be more applicable for swing or position traders who deal with longer-term market movements. Volume Flow Length (volumeFlowLength): Determines the analysis period for volume flow to identify buying or selling pressure. Day traders might opt for shorter periods to catch rapid volume changes, while longer periods could serve swing traders to understand the accumulation or distribution phases better. Short EMA Length (shortEmaLength): Specifies the period for the short-term EMA, crucial for trend detection. Shorter lengths can aid day traders in spotting immediate trend shifts, whereas longer lengths might help swing traders in identifying more sustainable trend changes. Long EMA Length (longEmaLength): Sets the period for the long-term EMA, which is useful for observing longer-term market trends. This setting is particularly valuable for position traders who need to align with the broader market direction. Composite Signal Moving Average Length (maLength): This parameter sets the smoothing period for the composite signal's moving average, helping to reduce noise in the signal output. A shorter moving average length can be beneficial for day traders reacting to market conditions swiftly, while a longer length might help swing and position traders in smoothing out less significant fluctuations to focus on significant trends. These customization options ensure that traders can fine-tune the Uptrick indicator to their specific trading needs, whether they are scanning for quick opportunities or analyzing more prolonged market trends. ### Functionality Details The indicator operates through a sophisticated algorithm that integrates multiple market dimensions: 1. Momentum and Volatility Calculation : Combines ROC and ATR to gauge the market’s momentum and stability. 2. Volume and Trend Analysis : Integrates volume data with EMAs to provide a comprehensive view of current market trends and potential shifts. 3. Signal Composite : Each component is normalized and combined into a composite signal, offering traders a nuanced perspective on when to enter or exit trades. The indicator performs its calculations as follows: Momentum and Volatility Calculation: roc = ta.roc(close, rocLength) atr = ta.atr(atrLength) Volume and Trend Analysis: volumeFlow = ta.cum(volume) - ta.ema(ta.cum(volume), volumeFlowLength) emaShort = ta.ema(close, shortEmaLength) emaLong = ta.ema(close, longEmaLength) emaDifference = emaShort - emaLong Composite Signal Calculation: Normalizes each component (ROC, ATR, volume flow, EMA difference) and combines them into a composite signal: rocNorm = (roc - ta.sma(roc, rocLength)) / ta.stdev(roc, rocLength) atrNorm = (atr - ta.sma(atr, atrLength)) / ta.stdev(atr, atrLength) volumeFlowNorm = (volumeFlow - ta.sma(volumeFlow, volumeFlowLength)) / ta.stdev(volumeFlow, volumeFlowLength) emaDiffNorm = (emaDifference - ta.sma(emaDifference, longEmaLength)) / ta.stdev(emaDifference, longEmaLength) compositeSignal = (rocNorm + atrNorm + volumeFlowNorm + emaDiffNorm) / 4 ### Originality The originality of the Uptrick indicator lies in its ability to merge diverse market metrics into a unified signal. This multi-faceted approach goes beyond traditional indicators by offering a deeper, more holistic analysis of market conditions, providing traders with insights that are not only based on price movements but also on underlying market dynamics. ### Practical Application The Uptrick indicator excels in environments where understanding the interplay between volume, momentum, and volatility is crucial. It is especially useful for: - Day Traders : Can leverage real-time data to make quick decisions based on sudden market changes. - Swing Traders : Benefit from understanding medium-term trends to optimize entry and exit points. - Position Traders : Utilize long-term market trend data to align with overall market movements. ### Best Practices To maximize the effectiveness of the Uptrick indicator, consider the following: - Combine with Other Indicators : Use alongside other technical tools like RSI or MACD for additional validation. - Adapt Settings to Market Conditions : Adjust the indicator settings based on the asset and market volatility to improve signal accuracy. - Risk Management : Implement robust risk management strategies, including setting stop-loss orders based on the volatility measured by the ATR. ### Practical Examples and Demonstrations - Example for Day Trading : In a volatile market, a trader notices a sharp increase in the momentum score coinciding with a surge in volume but stable volatility, signaling a potential bullish breakout. - Example for Swing Trading : On a 4-hour chart, the indicator shows a gradual alignment of decreasing volatility and increasing buying volume, suggesting a strengthening upward trend suitable for a long position. ### Alerts and Their Uses - Alert Configurations : Set alerts for when the composite score crosses predefined thresholds to capture potential buy or sell events. - Strategic Application : Use alerts to stay informed of significant market moves without the need to continuously monitor the markets, enabling timely and informed trading decisions. Technical Notes Efficiency and Compatibility: The indicator is designed for efficiency, running smoothly across different trading platforms including TradingView, and can be easily integrated with existing trading setups. It leverages advanced mathematical models for normalizing and smoothing data, ensuring consistent and reliable signal quality across different market conditions. Limitations : The effectiveness of the Uptrick indicator can vary significantly across different market conditions and asset classes. It is designed to perform best in liquid markets where data on volume, volatility, and price trends are readily available and reliable. Traders should be aware that in low-liquidity or highly volatile markets, the signals might be less reliable and require additional confirmation. Usage Recommendations : While the Uptrick indicator is a powerful tool, it is recommended to use it in conjunction with other analysis methods to confirm signals. Traders should also continuously monitor the performance and adjust settings as needed to align with their specific trading strategies and market conditions. ### Conclusion The "Uptrick: Momentum-Volatility Composite Signal" is a revolutionary tool that offers traders an advanced methodology for analyzing market dynamics. By combining momentum, volatility, volume, and trend detection into a single, cohesive indicator, it provides a powerful, actionable insight into market movements, making it an indispensable tool for traders aiming to optimize their trading strategies.
Penunjuk Pine Script®
oleh Uptrick
Volume-Price PercentileDescription: The "Volume-Price Percentile Live" indicator is designed to provide real-time analysis of the relationship between volume percentiles and price percentiles on any given timeframe. This tool helps traders assess market activity by comparing how current volume levels rank relative to historical volume data and how current price movements (specifically high-low ranges) rank relative to historical price data. The indicator visualizes the ratio of volume percentile to price percentile as a histogram, allowing traders to gauge the relative strength of volume against price movements in real time. Functionality: Volume Percentile: Calculates the percentile rank of the current volume within a user-defined rolling period (default is 30 bars). This percentile indicates where the current volume stands in comparison to historical volumes over the specified period. Price Percentile: Calculates the percentile rank of the current candle's high-low difference within a user-defined rolling period (default is 30 bars). This percentile reflects the current price movement's strength relative to past movements over the specified period. Percentile Ratio (VP Ratio): The indicator plots the ratio of the volume percentile to the price percentile. This ratio helps identify periods when volume is significantly higher or lower relative to price movement, providing insights into potential market imbalances or strength. Real-Time Data: By fetching data from a lower timeframe (e.g., 1-minute), the indicator updates continuously within the current timeframe, offering live, intra-candle updates. This ensures that traders can see the histogram change in real-time as new data becomes available, without waiting for the current candle to close. How to Use: Adding the Indicator: To use this indicator, add it to your chart on TradingView by selecting it from the Indicators list once it is published publicly. Setting Parameters: Volume Period Length: This input sets the rolling window length for calculating the volume percentile (default is 30). You can adjust it based on the desired sensitivity or historical period relevance. Candle Period Length: This input sets the rolling window length for calculating the price percentile based on the high-low difference of candles (default is 30). Adjust this to match your trading style or analysis period. Interpreting the Histogram: The histogram represents the volume percentile divided by the price percentile. Above 1: A value greater than 1 indicates that volume is relatively strong compared to price movement, which may suggest high activity or potential accumulation/distribution phases. Below 1: A value less than 1 suggests that price movement is relatively stronger than volume, indicating potential weakness in volume relative to price moves. Near 1: Values close to 1 suggest a balanced relationship between volume and price movement. Application: Use this indicator to identify potential breakout or breakdown scenarios, assess the strength of price movements, and confirm trends. When volume percentile consistently leads price percentile, it might signal sustained interest and support for the current price trend. Conversely, if volume percentile lags significantly, it might warn of potential trend weakness. Best Practices: Multiple Timeframe Analysis: While the indicator provides real-time updates on any timeframe, consider using it alongside higher timeframe analysis to confirm trends and volume behavior across different periods. Customization: Adjust the period lengths based on the asset’s typical volume and price behavior, as well as your trading strategy (e.g., short-term scalping vs. long-term trend following). Complement with Other Indicators: Use this indicator in conjunction with other volume-based tools, trend indicators, or momentum oscillators to gain a comprehensive view of market dynamics.
Penunjuk Pine Script®
oleh orkhanrustamov
1 (or) 5-Minute Scalping Strategy - KGP1-Minute Scalping Strategy - KGP Overview: This indicator is designed for short-term traders who engage in 1 (or) 5-minute scalping. It combines several technical analysis tools to provide buy and sell signals, helping traders make informed decisions quickly. Key Features: VWAP (Volume Weighted Average Price): Purpose: VWAP provides the average price a security has traded at throughout the day, based on both volume and price. Usage: Helps identify the overall trend and potential entry points. When the price is above VWAP, it indicates a bullish trend; when below, it indicates a bearish trend. RSI (Relative Strength Index): Purpose: RSI measures the speed and change of price movements, indicating overbought or oversold conditions. Usage: The RSI values between 30 and 70 are used to filter trades. A value above 70 indicates overbought conditions, while below 30 indicates oversold conditions. Custom OBV (On Balance Volume): Purpose: OBV uses volume flow to predict changes in stock price. Usage: Helps confirm the strength of a trend. Increasing OBV indicates accumulation (buying pressure), while decreasing OBV indicates distribution (selling pressure). Multi-Timeframe Analysis: Purpose: Confirms signals by analyzing RSI on a higher timeframe (5-minute chart). Usage: Ensures that signals on the 1-minute chart align with the broader trend on the 5-minute chart, reducing false signals. Signals: Buy Signal: Triggered when the price crosses above the VWAP, and the RSI is between 50 and 70 on both the 1-minute and 5-minute charts. Visual Cue: A green “BUY” label appears below the bar.' Sell Signal: Triggered when the price crosses below the VWAP, and the RSI is between 30 and 50 on both the 1-minute and 5-minute charts. Visual Cue: A red “SELL” label appears above the bar. Alerts: Buy Alert: Notifies you when a buy signal is detected. Sell Alert: Notifies you when a sell signal is detected. Additional Visuals: VWAP Line: Plotted in blue to show the average price based on volume. OBV Line: Plotted in purple to indicate volume flow. RSI Line: Plotted in orange with horizontal lines at 70 (overbought) and 30 (oversold) levels.
Penunjuk Pine Script®
oleh UnknownUnicorn22987934
Cumulative Net VolumeCumulative Calculation: Summarizes the net volume (buying minus selling volume) cumulatively, providing a running total that reflects the aggregate trading pressure. Custom Timeframe Flexibility: Users can choose to analyze the volume on a custom timeframe, enhancing adaptability for various trading strategies. Color-Coded Visualization: Features an intuitive color scheme where green indicates a net buying dominance and red signals net selling dominance, making it easier to interpret shifts in market dynamics. Versatility: Suitable for all types of assets available on TradingView including cryptocurrencies like Bitcoin, stocks, forex, and more. Utility: This tool is particularly useful for identifying trends in buying or selling pressure, which could be pivotal during significant market events or when assessing the potential for a trend reversal. By understanding the accumulation and distribution phases through the cumulative net volume, traders can make more informed decisions. Perfect for both novice traders looking to get a grip on volume analysis and seasoned professionals seeking an edge in their trading tactics.
Penunjuk Pine Script®
oleh bariskurt007
Linear and Logarithmic Fibonacci Levels and (Price&Time) FansIntroduction The Fibonacci Retracement tool is a go-to for traders looking to spot potential support and resistance levels. By measuring the distance between swing highs and lows, you can apply Fibonacci ratios like 0.236, 0.382, and 0.618 to predict key market levels. Traditionally, these levels are set by dividing this distance into equal parts—known as Linear Levels. A more refined approach, Logarithmic Price and Time Levels, divides the distance into proportionally equal segments. Plus, this indicator now includes Fibonacci fans, adding another layer of analysis by projecting potential price levels using trendlines based on Fibonacci ratios. This tool makes it easier to identify both Linear and Logarithmic levels while also leveraging Fibonacci fans for a more complete market view. Applications Logarithmic Levels and Fibonacci fans are ideal for volatile markets. In crypto, they’re especially effective for BTCUSDT (check out the wick from January 23, 2024). They also help spot accumulation and distribution patterns in high-volume altcoins like FETUSDT . In traditional markets, they’re useful for tracking stocks like TSLA and NVDA with extreme price swings, as well as indices in inflation-affected markets like XU100 , or recession-hit currency pairs like JPYUSD . How to Use This indicator is intuitive and similar to TradingView’s Fibonacci Tool. Select your reference levels (Level 1 and Level 0), then tweak the settings to customize your analysis, including adding Fibonacci fans for extra insights. Why It’s Different Unlike TradingView’s tool, which forces you to switch to a logarithmic scale (messing with other indicators and trend lines), this indicator lets you view both Linear and Logarithmic levels—and Fibonacci fans on Price and Time Series—without changing your chart’s scale. The original Fibonacci Code was derived from zekicanozkanli, modified and upgraded to plot fib front and back fans as well. Due to TV Max Plot restrictions I need to publish just Front and Back and Front Fibs separately.
Penunjuk Pine Script®
oleh AutomatedTradingAlgorithms
Linear and Logarithmic Fibonacci Levels and FansIntroduction The Fibonacci Retracement tool is a go-to for traders looking to spot potential support and resistance levels. By measuring the distance between swing highs and lows, you can apply Fibonacci ratios like 0.236, 0.382, and 0.618 to predict key market levels. Traditionally, these levels are set by dividing this distance into equal parts—known as Linear Levels. A more refined approach, Logarithmic Levels, divides the distance into proportionally equal segments. Plus, this indicator now includes Fibonacci fans, adding another layer of analysis by projecting potential price levels using trendlines based on Fibonacci ratios. This tool makes it easier to identify both Linear and Logarithmic levels while also leveraging Fibonacci fans for a more complete market view. Applications Logarithmic Levels and Fibonacci fans are ideal for volatile markets. In crypto, they’re especially effective for BTCUSDT (check out the wick from January 23, 2024). They also help spot accumulation and distribution patterns in high-volume altcoins like FETUSDT . In traditional markets, they’re useful for tracking stocks like TSLA and NVDA with extreme price swings, as well as indices in inflation-affected markets like XU100 , or recession-hit currency pairs like JPYUSD . How to Use This indicator is intuitive and similar to TradingView’s Fibonacci Tool. Select your reference levels (Level 1 and Level 0), then tweak the settings to customize your analysis, including adding Fibonacci fans for extra insights. Why It’s Different Unlike TradingView’s tool, which forces you to switch to a logarithmic scale (messing with other indicators and trend lines), this indicator lets you view both Linear and Logarithmic levels—and Fibonacci fans—without changing your chart’s scale. The original Fibonacci Code was derived from zekicanozkanli, modified and upgraded to plot fib fans as well.
Penunjuk Pine Script®
oleh AutomatedTradingAlgorithms
BTC - Power Law OscillatorDescription: The BTC - Power Law Oscillator is a technical analysis tool designed to help traders and investors identify potential overbought and oversold conditions in the Bitcoin market. This oscillator is based on a power law model that approximates Bitcoin's historical price trajectory, providing a framework for understanding deviations from this trajectory over time. Key Features: Exponential Model: The oscillator uses an exponential model that represents Bitcoin's price growth over time since its inception on January 3, 2009. This model is mathematically expressed as: price=exp(5.71×ln(days since inception)−38.16) This captures the long-term growth trend of Bitcoin, allowing for the analysis of deviations from this model. Deviation Analysis: The Power Law Oscillator measures the percentage deviation of Bitcoin's closing price from the model price. This deviation is expressed as a percentage to illustrate how far the current price is from the expected model trajectory. Normalization: The oscillator values are normalized to a 0-100 range. A quadratic transformation is applied to enhance sensitivity to higher values, allowing for better visualization and interpretation of extreme conditions. Bands and Zones: Upper Band (50): Indicates the 20% threshold. Values above this band suggest overbought conditions, where Bitcoin's price may be significantly above the expected trajectory. Lower Band (15): Indicates the 5% threshold. Values below this band suggest oversold conditions, where Bitcoin's price may be significantly below the expected trajectory. Top Zone: The area above the upper band is shaded red, highlighting potential sell or caution areas. Bottom Zone: The area below the lower band is shaded green, highlighting potential buy or accumulation areas. Benefits: Trend Analysis: Helps identify long-term trends and potential reversals by analyzing price deviations from a theoretical model based on historical growth. Market Timing: Assists in market timing decisions by indicating overbought and oversold conditions with visual bands and zones. Enhanced Sensitivity: The quadratic normalization enhances sensitivity to changes in the oscillator, providing clearer signals for traders. Usage Tips: Complementary Tool: Use this oscillator in conjunction with other technical indicators and fundamental analysis for more comprehensive market insights. Risk Management: Always employ sound risk management strategies when trading, as no single indicator can guarantee accurate predictions. Market Context: Consider the broader market context, as Bitcoin's volatility can lead to significant short-term fluctuations. The BTC - Power Law Oscillator provides a unique perspective on Bitcoin's price movements by leveraging a mathematical model to understand historical growth trends and deviations. Use this tool to gain deeper insights into market dynamics and enhance your trading strategy.
Penunjuk Pine Script®
oleh jfurtado141