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震盪指標

Swing Trade AL/SAT + Güç Derecesi_huğurlu Weak signal → MACD crossover only. Moderate signal → MACD crossover + RSI confirmation. Strong signal → MACD crossover + RSI + Stoch RSI confirmation. BUY/SELL labels appear on the chart in different colors and sizes. This way, you can instantly see which signal is more reliable. Zayıf sinyal → sadece MACD kesişim var Orta sinyal → MACD kesişim + RSI teyidi. Güçlü sinyal → MACD kesişim + RSI + Stoch RSI teyidi.
Pine Script®指標
由hakantugurlu77提供
3
Stochastic RSI - WT Confluence Signal Detectors (TraderDemircan)Description What This Indicator Does: This indicator combines two powerful momentum oscillators—WaveTrend and Stochastic RSI—to identify high-probability trading signals through confluence. Instead of relying on a single indicator that may generate false signals, this tool only triggers buy/sell alerts when both oscillators simultaneously confirm extreme market conditions and trend reversals. This confluence approach significantly reduces noise and helps traders focus on the most reliable setups. Key Features: Dual-Oscillator Confluence: Generates signals only when both WaveTrend crossovers and Stochastic RSI extreme levels align Normalized Scale Display: Both oscillators are plotted on a unified -100 to +100 scale for easy visual comparison Visual Signal Confirmation: Clear intersection points marked with colored circles, plus optional candle coloring at crossover moments Customizable Thresholds: Adjust overbought/oversold levels for both oscillators to match your trading style and asset volatility Clean Visual Presentation: Optional area fill showing WaveTrend momentum difference, making divergences easier to spot How It Works: The indicator operates on a confluence principle where multiple conditions must align: For BUY Signals (Green): WaveTrend 1 crosses above WaveTrend 2 (bullish crossover) WaveTrend is in oversold territory (below -53 or -60) Stochastic RSI K-line is below 20 (oversold) For SELL Signals (Red): WaveTrend 1 crosses below WaveTrend 2 (bearish crossover) WaveTrend is in overbought territory (above 53 or 60) Stochastic RSI K-line is above 80 (overbought) WaveTrend Component: Uses the hlc3 price (average of high, low, close) to calculate a channel index that identifies market momentum waves. The two WaveTrend lines (WT1 and WT2) act similarly to MACD, where crossovers indicate momentum shifts. The oscillator ranges from approximately -100 to +100, with extreme values suggesting potential reversals. Stochastic RSI Component: Applies stochastic calculations to RSI values rather than raw price, creating a more sensitive momentum indicator. Values above 80 indicate overbought conditions (potential selling opportunity), while values below 20 indicate oversold conditions (potential buying opportunity). The indicator includes both K-line (faster) and D-line (slower, smoothed) for additional confirmation. Normalization Technology: To enable direct visual comparison, the Stochastic RSI (normally 0-100 scale) is normalized to match WaveTrend's -100 to +100 scale. This allows traders to see both oscillators' movements in relation to the same reference levels, making divergences and convergences more apparent. How to Use: For Trend Traders: Wait for confluence signals in the direction of the larger trend Use buy signals in uptrends as entry points during pullbacks Use sell signals in downtrends as entry points during bounces For Reversal Traders: Focus on confluence signals at major support/resistance levels Look for divergences between price and oscillators before confluence signals Consider stronger signals when both oscillators reach extreme levels (WT beyond ±60, Stoch beyond 20/80) For Scalpers: Lower the WaveTrend Channel Length (default 10) to 5-7 for more frequent signals Tighten overbought/oversold thresholds slightly (e.g., WT: ±50, Stoch: 30/70) Use on lower timeframes (5m, 15m) with strict stop losses Settings Guide: WaveTrend Parameters: Channel Length (10): Controls sensitivity. Lower = more signals but more noise. Higher = fewer but more reliable signals Average Length (21): Smoothing period for WT2. Higher values reduce whipsaws Overbought Levels (60/53): Two-tier system. Breaching 60 indicates strong overbought, 53 is moderate Oversold Levels (-60/-53): Mirror of overbought levels for downside extremes Stochastic RSI Parameters: K-Smooth (3): Smoothing for the K-line. Higher = smoother but delayed D-Smooth (3): Additional smoothing for the D-line signal RSI Period (14): Standard RSI calculation period Stoch Period (14): Stochastic calculation lookback Oversold (20) / Overbought (80): Classic thresholds for extreme conditions Visual Options: Show WT Difference Area: Displays the momentum difference between WT1 and WT2 as a blue shaded area Show WT Intersection Points: Marks crossover points with colored circles (red for bearish, green for bullish) Color Candles at Intersection: Changes candle colors at crossover moments (blue for bearish, yellow for bullish) Show Stoch Over Signals: Displays when Stochastic RSI breaches extreme levels What Makes This Original: While WaveTrend and Stochastic RSI are established indicators, this script's originality lies in: Confluence Logic: The specific combination requiring simultaneous confirmation from both oscillators in extreme zones, not just simple crossovers Normalization Approach: Displaying both oscillators on the same -100 to +100 scale for direct visual comparison, which is not standard Multi-Tier Overbought/Oversold: Using two levels (60/53) instead of one, allowing for nuanced signal strength assessment Integrated Visual System: Combining area fills, intersection markers, and candle coloring in a coordinated display that shows momentum flow at a glance Important Considerations: This is a momentum-based oscillator system, which performs best in ranging or trending markets with clear swings In strong trending markets, the oscillator may remain in extreme zones for extended periods (remain overbought during strong uptrends, oversold during strong downtrends) Confluence signals are intentionally rare to maintain quality—expect fewer signals than with single-indicator systems Always combine with price action analysis, support/resistance levels, and proper risk management Not recommended for extremely low volatility or thin markets where oscillators may produce erratic readings Best Timeframes: Intraday: 15m, 1H (with tighter parameters) Swing Trading: 4H, Daily (with default parameters) Position Trading: Daily, Weekly (with extended Channel Length 15-20) Typical Use Cases: Identifying exhaustion points in trending markets Timing entries during pullbacks in established trends Spotting potential reversal zones at key price levels Filtering out weak momentum signals during consolidation
Pine Script®指標
由TraderDemircan_提供
DAO - Demand Advanced Oscillator# DAO - Demand Advanced Oscillator ## 📊 Overview DAO (Demand Advanced Oscillator) is a powerful momentum oscillator that measures buying and selling pressure by analyzing consecutive high-low relationships. It helps identify market extremes, divergences, and potential trend reversals. **Values range from 0 to 1:** - **Above 0.70** = Overbought (potential reversal down) - **Below 0.30** = Oversold (potential reversal up) - **0.30 - 0.70** = Neutral zone --- ## ✨ Key Features ✅ **Automatic Divergence Detection** - Bullish divergences (price lower low + DAO higher low) - Bearish divergences (price higher high + DAO lower high) - Visual lines connecting divergence points ✅ **Multi-Timeframe Analysis** - View higher timeframe DAO on current chart - Perfect for trend alignment strategies ✅ **Signal Line (EMA)** - Customizable EMA for trend confirmation - Crossover signals for momentum shifts ✅ **Real-Time Statistics Dashboard** - Current DAO value - Market status (Overbought/Oversold/Neutral) - Trend direction indicator ✅ **Complete Alert System** - Overbought/Oversold signals - Bullish/Bearish divergences - Signal line crosses - Level crosses ✅ **Fully Customizable** - Adjustable periods and levels - Customizable colors and zones - Toggle features on/off --- ## 📈 Trading Signals ### 1. Divergences (Most Powerful) **Bullish Divergence:** - Price makes lower low - DAO makes higher low - Signal: Strong reversal up likely **Bearish Divergence:** - Price makes higher high - DAO makes lower high - Signal: Strong reversal down likely ### 2. Overbought/Oversold **Overbought (>0.70):** - Market may be overextended - Consider taking profits or looking for shorts - Can remain overbought in strong trends **Oversold (<0.30):** - Market may be oversold - Consider buying opportunities - Can remain oversold in strong downtrends ### 3. Signal Line Crossovers **Bullish Cross:** - DAO crosses above signal line - Momentum turning positive **Bearish Cross:** - DAO crosses below signal line - Momentum turning negative ### 4. Level Crosses **Cross Above 0.30:** Exiting oversold zone (potential uptrend) **Cross Below 0.70:** Exiting overbought zone (potential downtrend) --- ## ⚙️ Default Settings 📊 Oscillator Period: 14 Number of bars for calculation 📈 Signal Line Period: 9 EMA period for signal line 🔴 Overbought Level: 0.70 Upper threshold 🟢 Oversold Level: 0.30 Lower threshold 🎯 Divergence Detection: ON Auto divergence identification ⏰ Multi-Timeframe: OFF Higher TF overlay (optional) All parameters are fully customizable! --- ## 🔔 Alerts Six pre-configured alerts available: 1. DAO Overbought 2. DAO Oversold 3. DAO Bullish Divergence 4. DAO Bearish Divergence 5. DAO Signal Cross Up 6. DAO Signal Cross Down **Setup:** Right-click indicator → Add Alert → Choose condition --- ## 💡 How to Use ### Best Practices: ✅ Focus on divergences (strongest signals) ✅ Combine with support/resistance levels ✅ Use multiple timeframes for confirmation ✅ Wait for price action confirmation ✅ Practice proper risk management ### Avoid: ❌ Trading on indicator alone ❌ Fighting strong trends ❌ Ignoring market context ❌ Overtrading ### Recommended Settings by Trading Style: **Day Trading:** Period 7-10, All alerts ON **Swing Trading:** Period 14-21, Divergence alerts **Scalping:** Period 5-7, Signal crosses **Position Trading:** Period 21-30, Weekly/Daily TF --- ## 🌍 Markets & Timeframes **Works on all markets:** - Forex (all pairs) - Stocks (all exchanges) - Cryptocurrencies - Commodities - Indices - Futures **Works on all timeframes:** 1m to Monthly --- ## 📊 How It Works DAO calculates the ratio of buying pressure to total market pressure: 1. **Calculate Buying Pressure (DemandMax):** - If current high > previous high: DemandMax = difference - Otherwise: DemandMax = 0 2. **Calculate Selling Pressure (DemandMin):** - If previous low > current low: DemandMin = difference - Otherwise: DemandMin = 0 3. **Apply Smoothing:** - Calculate SMA of DemandMax over N periods - Calculate SMA of DemandMin over N periods 4. **Final Formula:** ``` DAO = SMA(DemandMax) / (SMA(DemandMax) + SMA(DemandMin)) ``` This produces a normalized value (0-1) representing market demand strength. --- ## 🎯 Trading Strategies ### Strategy 1: Divergence Trading - Wait for divergence label - Confirm at support/resistance - Enter on confirming candle - Stop loss beyond recent swing - Target: opposite level or 0.50 ### Strategy 2: Overbought/Oversold - Best for ranging markets - Wait for extreme readings - Enter on reversal from extremes - Target: middle line (0.50) ### Strategy 3: Trend Following - Identify trend direction first - Use DAO to time entries in trend direction only - Enter on pullbacks to oversold (uptrend) or overbought (downtrend) - Trade with the trend ### Strategy 4: Multi-Timeframe - Enable MTF feature - Trade only when both timeframes align - Higher TF = trend direction - Lower TF = precise entry --- ## 📂 Category **Primary:** Oscillators **Secondary:** Statistics, Volatility, Momentum --- ## 🏷️ Tags dao, oscillator, momentum, overbought-oversold, divergence, reversal, demand-indicator, price-exhaustion, statistics, volatility, forex, stocks, crypto, multi-timeframe, technical-analysis --- ## ⚠️ Disclaimer **This indicator is for educational purposes only.** It does not constitute financial advice. Trading involves substantial risk of loss. Always conduct your own research, use proper risk management, and consult with financial professionals before making trading decisions. Past performance does not guarantee future results. --- ## 📄 License Open source - Free to use for personal trading, modify as needed, and share with attribution. --- **Version:** 1.0 **Status:** Production Ready ✅ **Pine Script:** v5 **Trademark-Free:** 100% Safe to Publish --- *Made with 💙 for traders worldwide*
Pine Script®指標
由kostyanius提供
2
Trendlines with Breaks Oscillator [LuxAlgo]The Trendlines with Breaks Oscillator is an oscillator based on the Trendlines with Breaks indicator, and tracks the maximum distance on price from bullish and bearish trendline breakouts. The oscillator features divergences and trendline breakout detection. 🔶 USAGE This tool is based on our Trendlines with Breaks indicator, which detects bullish and bearish trendlines and highlights the breaks on the chart. Now, we bring you this tool as an oscillator. The oscillator calculates the maximum distance between the price and the break of each trendline, for both bullish and bearish cases, then calculates the delta between both. When the oscillator is above 0, the market is in an uptrend; when it is below 0, it is in a downtrend. An ascending slope indicates positive momentum, and a descending slope indicates negative momentum. Trendline breaks are displayed as green and red dots on the oscillator. A green dot corresponds to a bullish break of a descending trendline, and a red dot corresponds to a bearish break of an ascending trendline. The oscillator calculation depends on two parameters from the settings panel: short and long alpha length. These parameters are used to calculate a synthetic EMA with a variable alpha for both bullish and bearish breaks. The final result is the difference between the two averages. As shown in the image, using the same trend detection parameters but different alphas can produce very different results. The larger the alphas, the smoother the oscillator becomes, detecting bigger trends but making it less reactive. This tool features the same trendline detection system as the Trendlines with Breaks indicator, which is based on three main parameters: swing length, slope, and calculation method. As we can see in the image above, the data collected for the oscillator calculation will be different when using different parameters. A larger length detects larger trends. A larger slope or a different calculation method also impacts the final result. 🔹 Signal Line The signal line is a smoothed version of the oscillator; traders can choose the smoothing method and length used from the settings panel. In the image, the signal line crossings are displayed as vertical lines. As we can see, the market usually corrects downward after a bearish crossing and corrects upward after a bullish crossing. Traders can choose among 10 different smoothing methods for the signal line. In the image, we can see how different methods and lengths give different outputs. 🔹 Divergences The tool features a divergence detector that helps traders understand the strength behind price movements. Traders can adjust the detection length from the settings panel. As shown in the image, a bearish divergence occurs when the price prints higher highs, but the momentum on the histogram prints lower highs. A bullish divergence occurs when the price prints lower lows, but the histogram prints higher lows. By adjusting the length of the divergence detector, traders can filter out smaller divergences, allowing the tool to only detect more significant ones. The image above depicts divergences detected with different lengths; the larger the length, the bigger the divergences are detected. 🔶 SETTINGS 🔹 Trendlines Swing Detection Lookback: The size of the market structure used for trendline detection. Slope: Slope steepness, a value of 0 gives horizontal levels, values larger than 1 give a steeper slope Slope Calculation Method: Choose how the slope is calculated 🔹 Oscillator Short Alpha Length: Synthetic EMA short period Long Alpha Length: Synthetic EMA long period Smoothing Signal: Choose the smoothing method and period Divergences: Enable or disable divergences and select the detection length. 🔹 Style Bullish: Select bullish color. Bearish: Select bearish color.
Pine Script®指標
由LuxAlgo提供
7
Squeeze Momentum Early In and Out CandlesJohn Carter presented some candles called "Early In and Out Candles". Although I couldn't imitate the exact candles and warnings I create better indications and bars in my opinion. When the Candles are above Donchian MA then we have a bullish Momentum. When the Candles are bellow Donchian MA then we have bearish momentum. This indicator works best to get an WARNING to enter and close EARLY positions. Bullish: When the candles are Light Blue then we have early warning to enter. When the candles are Dark Blue then we have early warning to close the position. Bearish: When the candles are Red then we have early warning to enter. When the candles are Yellow then we have early warning to close the position. IMPORTANT NOTES: Always combine it with the Squeeze Pro indicator. Suggested Donchian MA: 5 (You can adjust it). Don't let candles only to be your closing indication once again there are EARLY WARNINGS therefore can move your stop loses to maximize your profits when you are exiting. I tested my self and I found that is the best strategy when we get Dark Blue candle in the Bullish move I move my stop loss little bit bellow the candle. Therefore here we go we have early warnings for In and Out. Thank you and Good Luck.
Pine Script®指標
由P1xsel提供
2
Algorithm Predator - ML-liteAlgorithm Predator - ML-lite This indicator combines four specialized trading agents with an adaptive multi-armed bandit selection system to identify high-probability trade setups. It is designed for swing and intraday traders who want systematic signal generation based on institutional order flow patterns , momentum exhaustion , liquidity dynamics , and statistical mean reversion . Core Architecture Why These Components Are Combined: The script addresses a fundamental challenge in algorithmic trading: no single detection method works consistently across all market conditions. By deploying four independent agents and using reinforcement learning algorithms to select or blend their outputs, the system adapts to changing market regimes without manual intervention. The Four Trading Agents 1. Spoofing Detector Agent 🎭 Detects iceberg orders through persistent volume at similar price levels over 5 bars Identifies spoofing patterns via asymmetric wick analysis (wicks exceeding 60% of bar range with volume >1.8× average) Monitors order clustering using simplified Hawkes process intensity tracking (exponential decay model) Signal Logic: Contrarian—fades false breakouts caused by institutional manipulation Best Markets: Consolidations, institutional trading windows, low-liquidity hours 2. Exhaustion Detector Agent ⚡ Calculates RSI divergence between price movement and momentum indicator over 5-bar window Detects VWAP exhaustion (price at 2σ bands with declining volume) Uses VPIN reversals (volume-based toxic flow dissipation) to identify momentum failure Signal Logic: Counter-trend—enters when momentum extreme shows weakness Best Markets: Trending markets reaching climax points, over-extended moves 3. Liquidity Void Detector Agent 💧 Measures Bollinger Band squeeze (width <60% of 50-period average) Identifies stop hunts via 20-bar high/low penetration with immediate reversal and volume spike Detects hidden liquidity absorption (volume >2× average with range <0.3× ATR) Signal Logic: Breakout anticipation—enters after liquidity grab but before main move Best Markets: Range-bound pre-breakout, volatility compression zones 4. Mean Reversion Agent 📊 Calculates price z-scores relative to 50-period SMA and standard deviation (triggers at ±2σ) Implements Ornstein-Uhlenbeck process scoring (mean-reverting stochastic model) Uses entropy analysis to detect algorithmic trading patterns (low entropy <0.25 = high predictability) Signal Logic: Statistical reversion—enters when price deviates significantly from statistical equilibrium Best Markets: Range-bound, low-volatility, algorithmically-dominated instruments Adaptive Selection: Multi-Armed Bandit System The script implements four reinforcement learning algorithms to dynamically select or blend agents based on performance: Thompson Sampling (Default - Recommended): Uses Bayesian inference with beta distributions (tracks alpha/beta parameters per agent) Balances exploration (trying underused agents) vs. exploitation (using proven winners) Each agent's win/loss history informs its selection probability Lite Approximation: Uses pseudo-random sampling from price/volume noise instead of true random number generation UCB1 (Upper Confidence Bound): Calculates confidence intervals using: average_reward + sqrt(2 × ln(total_pulls) / agent_pulls) Deterministic algorithm favoring agents with high uncertainty (potential upside) More conservative than Thompson Sampling Epsilon-Greedy: Exploits best-performing agent (1-ε)% of the time Explores randomly ε% of the time (default 10%, configurable 1-50%) Simple, transparent, easily tuned via epsilon parameter Gradient Bandit: Uses softmax probability distribution over agent preference weights Updates weights via gradient ascent based on rewards Best for Blend mode where all agents contribute Selection Modes: Switch Mode: Uses only the selected agent's signal (clean, decisive) Blend Mode: Combines all agents using exponentially weighted confidence scores controlled by temperature parameter (smooth, diversified) Lock Agent Feature: Optional manual override to force one specific agent Useful after identifying which agent dominates your specific instrument Only applies in Switch mode Four choices: Spoofing Detector, Exhaustion Detector, Liquidity Void, Mean Reversion Memory System Dual-Layer Architecture: Short-Term Memory: Stores last 20 trade outcomes per agent (configurable 10-50) Long-Term Memory: Stores episode averages when short-term reaches transfer threshold (configurable 5-20 bars) Memory Boost Mechanism: Recent performance modulates agent scores by up to ±20% Episode Transfer: When an agent accumulates sufficient results, averages are condensed into long-term storage Persistence: Manual restoration of learned parameters via input fields (alpha, beta, weights, microstructure thresholds) How Memory Works: Agent generates signal → outcome tracked after 8 bars (performance horizon) Result stored in short-term memory (win = 1.0, loss = 0.0) Short-term average influences agent's future scores (positive feedback loop) After threshold met (default 10 results), episode averaged into long-term storage Long-term patterns (weighted 30%) + short-term patterns (weighted 70%) = total memory boost Market Microstructure Analysis These advanced metrics quantify institutional order flow dynamics: Order Flow Toxicity (Simplified VPIN): Measures buy/sell volume imbalance over 20 bars: |buy_vol - sell_vol| / (buy_vol + sell_vol) Detects informed trading activity (institutional players with non-public information) Values >0.4 indicate "toxic flow" (informed traders active) Lite Approximation: Uses simple open/close heuristic instead of tick-by-tick trade classification Price Impact Analysis (Simplified Kyle's Lambda): Measures market impact efficiency: |price_change_10| / sqrt(volume_sum_10) Low values = large orders with minimal price impact ( stealth accumulation ) High values = retail-dominated moves with high slippage Lite Approximation: Uses simplified denominator instead of regression-based signed order flow Market Randomness (Entropy Analysis): Counts unique price changes over 20 bars / 20 Measures market predictability High entropy (>0.6) = human-driven, chaotic price action Low entropy (<0.25) = algorithmic trading dominance (predictable patterns) Lite Approximation: Simple ratio instead of true Shannon entropy H(X) = -Σ p(x)·log₂(p(x)) Order Clustering (Simplified Hawkes Process): Tracks self-exciting event intensity (coordinated order activity) Decays at 0.9× per bar, spikes +1.0 when volume >1.5× average High intensity (>0.7) indicates clustering (potential spoofing/accumulation) Lite Approximation: Simple exponential decay instead of full λ(t) = μ + Σ α·exp(-β(t-tᵢ)) with MLE Signal Generation Process Multi-Stage Validation: Stage 1: Agent Scoring Each agent calculates internal score based on its detection criteria Scores must exceed agent-specific threshold (adjusted by sensitivity multiplier) Agent outputs: Signal direction (+1/-1/0) and Confidence level (0.0-1.0) Stage 2: Memory Boost Agent scores multiplied by memory boost factor (0.8-1.2 based on recent performance) Successful agents get amplified, failing agents get dampened Stage 3: Bandit Selection/Blending If Adaptive Mode ON: Switch: Bandit selects single best agent, uses only its signal Blend: All agents combined using softmax-weighted confidence scores If Adaptive Mode OFF: Traditional consensus voting with confidence-squared weighting Signal fires when consensus exceeds threshold (default 70%) Stage 4: Confirmation Filter Raw signal must repeat for consecutive bars (default 3, configurable 2-4) Minimum confidence threshold: 0.25 (25%) enforced regardless of mode Trend alignment check: Long signals require trend_score ≥ -2, Short signals require trend_score ≤ 2 Stage 5: Cooldown Enforcement Minimum bars between signals (default 10, configurable 5-15) Prevents over-trading during choppy conditions Stage 6: Performance Tracking After 8 bars (performance horizon), signal outcome evaluated Win = price moved in signal direction, Loss = price moved against Results fed back into memory and bandit statistics Trading Modes (Presets) Pre-configured parameter sets: Conservative: 85% consensus, 4 confirmations, 15-bar cooldown Expected: 60-70% win rate, 3-8 signals/week Best for: Swing trading, capital preservation, beginners Balanced: 70% consensus, 3 confirmations, 10-bar cooldown Expected: 55-65% win rate, 8-15 signals/week Best for: Day trading, most traders, general use Aggressive: 60% consensus, 2 confirmations, 5-bar cooldown Expected: 50-58% win rate, 15-30 signals/week Best for: Scalping, high-frequency trading, active management Elite: 75% consensus, 3 confirmations, 12-bar cooldown Expected: 58-68% win rate, 5-12 signals/week Best for: Selective trading, high-conviction setups Adaptive: 65% consensus, 2 confirmations, 8-bar cooldown Expected: Varies based on learning Best for: Experienced users leveraging bandit system How to Use 1. Initial Setup (5 Minutes): Select Trading Mode matching your style (start with Balanced) Enable Adaptive Learning (recommended for automatic agent selection) Choose Thompson Sampling algorithm (best all-around performance) Keep Microstructure Metrics enabled for liquid instruments (>100k daily volume) 2. Agent Tuning (Optional): Adjust Agent Sensitivity multipliers (0.5-2.0): <0.8 = Highly selective (fewer signals, higher quality) 0.9-1.2 = Balanced (recommended starting point) 1.3 = Aggressive (more signals, lower individual quality) Monitor dashboard for 20-30 signals to identify dominant agent If one agent consistently outperforms, consider using Lock Agent feature 3. Bandit Configuration (Advanced): Blend Temperature (0.1-2.0): 0.3 = Sharp decisions (best agent dominates) 0.5 = Balanced (default) 1.0+ = Smooth (equal weighting, democratic) Memory Decay (0.8-0.99): 0.90 = Fast adaptation (volatile markets) 0.95 = Balanced (most instruments) 0.97+ = Long memory (stable trends) 4. Signal Interpretation: Green triangle (▲): Long signal confirmed Red triangle (▼): Short signal confirmed Dashboard shows: Active agent (highlighted row with ► marker) Win rate per agent (green >60%, yellow 40-60%, red <40%) Confidence bars (█████ = maximum confidence) Memory size (short-term buffer count) Colored zones display: Entry level (current close) Stop-loss (1.5× ATR) Take-profit 1 (2.0× ATR) Take-profit 2 (3.5× ATR) 5. Risk Management: Never risk >1-2% per signal (use ATR-based stops) Signals are entry triggers, not complete strategies Combine with your own market context analysis Consider fundamental catalysts and news events Use "Confirming" status to prepare entries (not to enter early) 6. Memory Persistence (Optional): After 50-100 trades, check Memory Export Panel Record displayed alpha/beta/weight values for each agent Record VPIN and Kyle threshold values Enable "Restore From Memory" and input saved values to continue learning Useful when switching timeframes or restarting indicator Visual Components On-Chart Elements: Spectral Layers: EMA8 ± 0.5 ATR bands (dynamic support/resistance, colored by trend) Energy Radiance: Multi-layer glow boxes at signal points (intensity scales with confidence, configurable 1-5 layers) Probability Cones: Projected price paths with uncertainty wedges (15-bar projection, width = confidence × ATR) Connection Lines: Links sequential signals (solid = same direction continuation, dotted = reversal) Kill Zones: Risk/reward boxes showing entry, stop-loss, and dual take-profit targets Signal Markers: Triangle up/down at validated entry points Dashboard (Configurable Position & Size): Regime Indicator: 4-level trend classification (Strong Bull/Bear, Weak Bull/Bear) Mode Status: Shows active system (Adaptive Blend, Locked Agent, or Consensus) Agent Performance Table: Real-time win%, confidence, and memory stats Order Flow Metrics: Toxicity and impact indicators (when microstructure enabled) Signal Status: Current state (Long/Short/Confirming/Waiting) with confirmation progress Memory Panel (Configurable Position & Size): Live Parameter Export: Alpha, beta, and weight values per agent Adaptive Thresholds: Current VPIN sensitivity and Kyle threshold Save Reminder: Visual indicator if parameters should be recorded What Makes This Original This script's originality lies in three key innovations: 1. Genuine Meta-Learning Framework: Unlike traditional indicator mashups that simply display multiple signals, this implements authentic reinforcement learning (multi-armed bandits) to learn which detection method works best in current conditions. The Thompson Sampling implementation with beta distribution tracking (alpha for successes, beta for failures) is statistically rigorous and adapts continuously. This is not post-hoc optimization—it's real-time learning. 2. Episodic Memory Architecture with Transfer Learning: The dual-layer memory system mimics human learning patterns: Short-term memory captures recent performance (recency bias) Long-term memory preserves historical patterns (experience) Automatic transfer mechanism consolidates knowledge Memory boost creates positive feedback loops (successful strategies become stronger) This architecture allows the system to adapt without retraining , unlike static ML models that require batch updates. 3. Institutional Microstructure Integration: Combines retail-focused technical analysis (RSI, Bollinger Bands, VWAP) with institutional-grade microstructure metrics (VPIN, Kyle's Lambda, Hawkes processes) typically found in academic finance literature and professional trading systems, not standard retail platforms. While simplified for Pine Script constraints, these metrics provide insight into informed vs. uninformed trading , a dimension entirely absent from traditional technical analysis. Mashup Justification: The four agents are combined specifically for risk diversification across failure modes: Spoofing Detector: Prevents false breakout losses from manipulation Exhaustion Detector: Prevents chasing extended trends into reversals Liquidity Void: Exploits volatility compression (different regime than trending) Mean Reversion: Provides mathematical anchoring when patterns fail The bandit system ensures the optimal tool is automatically selected for each market situation, rather than requiring manual interpretation of conflicting signals. Why "ML-lite"? Simplifications and Approximations This is the "lite" version due to necessary simplifications for Pine Script execution: 1. Simplified VPIN Calculation: Academic Implementation: True VPIN uses volume bucketing (fixed-volume bars) and tick-by-tick buy/sell classification via Lee-Ready algorithm or exchange-provided trade direction flags This Implementation: 20-bar rolling window with simple open/close heuristic (close > open = buy volume) Impact: May misclassify volume during ranging/choppy markets; works best in directional moves 2. Pseudo-Random Sampling: Academic Implementation: Thompson Sampling requires true random number generation from beta distributions using inverse transform sampling or acceptance-rejection methods This Implementation: Deterministic pseudo-randomness derived from price and volume decimal digits: (close × 100 - floor(close × 100)) + (volume % 100) / 100 Impact: Not cryptographically random; may have subtle biases in specific price ranges; provides sufficient variation for agent selection 3. Hawkes Process Approximation: Academic Implementation: Full Hawkes process uses maximum likelihood estimation with exponential kernels: λ(t) = μ + Σ α·exp(-β(t-tᵢ)) fitted via iterative optimization This Implementation: Simple exponential decay (0.9 multiplier) with binary event triggers (volume spike = event) Impact: Captures self-exciting property but lacks parameter optimization; fixed decay rate may not suit all instruments 4. Kyle's Lambda Simplification: Academic Implementation: Estimated via regression of price impact on signed order flow over multiple time intervals: Δp = λ × Δv + ε This Implementation: Simplified ratio: price_change / sqrt(volume_sum) without proper signed order flow or regression Impact: Provides directional indicator of impact but not true market depth measurement; no statistical confidence intervals 5. Entropy Calculation: Academic Implementation: True Shannon entropy requires probability distribution: H(X) = -Σ p(x)·log₂(p(x)) where p(x) is probability of each price change magnitude This Implementation: Simple ratio of unique price changes to total observations (variety measure) Impact: Measures diversity but not true information entropy with probability weighting; less sensitive to distribution shape 6. Memory System Constraints: Full ML Implementation: Neural networks with backpropagation, experience replay buffers (storing state-action-reward tuples), gradient descent optimization, and eligibility traces This Implementation: Fixed-size array queues with simple averaging; no gradient-based learning, no state representation beyond raw scores Impact: Cannot learn complex non-linear patterns; limited to linear performance tracking 7. Limited Feature Engineering: Advanced Implementation: Dozens of engineered features, polynomial interactions (x², x³), dimensionality reduction (PCA, autoencoders), feature selection algorithms This Implementation: Raw agent scores and basic market metrics (RSI, ATR, volume ratio); minimal transformation Impact: May miss subtle cross-feature interactions; relies on agent-level intelligence rather than feature combinations 8. Single-Instrument Data: Full Implementation: Multi-asset correlation analysis (sector ETFs, currency pairs, volatility indices like VIX), lead-lag relationships, risk-on/risk-off regimes This Implementation: Only OHLCV data from displayed instrument Impact: Cannot incorporate broader market context; vulnerable to correlated moves across assets 9. Fixed Performance Horizon: Full Implementation: Adaptive horizon based on trade duration, volatility regime, or profit target achievement This Implementation: Fixed 8-bar evaluation window Impact: May evaluate too early in slow markets or too late in fast markets; one-size-fits-all approach Performance Impact Summary: These simplifications make the script: ✅ Faster: Executes in milliseconds vs. seconds (or minutes) for full academic implementations ✅ More Accessible: Runs on any TradingView plan without external data feeds, APIs, or compute servers ✅ More Transparent: All calculations visible in Pine Script (no black-box compiled models) ✅ Lower Resource Usage: <500 bars lookback, minimal memory footprint ⚠️ Less Precise: Approximations may reduce statistical edge by 5-15% vs. academic implementations ⚠️ Limited Scope: Cannot capture tick-level dynamics, multi-order-book interactions, or cross-asset flows ⚠️ Fixed Parameters: Some thresholds hardcoded rather than dynamically optimized When to Upgrade to Full Implementation: Consider professional Python/C++ versions with institutional data feeds if: Trading with >$100K capital where precision differences materially impact returns Operating in microsecond-competitive environments (HFT, market making) Requiring regulatory-grade audit trails and reproducibility Backtesting with tick-level precision for strategy validation Need true real-time adaptation with neural network-based learning For retail swing/day trading and position management, these approximations provide sufficient signal quality while maintaining usability, transparency, and accessibility. The core logic—multi-agent detection with adaptive selection—remains intact. Technical Notes All calculations use standard Pine Script built-in functions ( ta.ema, ta.atr, ta.rsi, ta.bb, ta.sma, ta.stdev, ta.vwap ) VPIN and Kyle's Lambda use simplified formulas optimized for OHLCV data (see "Lite" section above) Thompson Sampling uses pseudo-random noise from price/volume decimal digits for beta distribution sampling No repainting: All calculations use confirmed bar data (no forward-looking) Maximum lookback: 500 bars (set via max_bars_back parameter) Performance evaluation: 8-bar forward-looking window for reward calculation (clearly disclosed) Confidence threshold: Minimum 0.25 (25%) enforced on all signals Memory arrays: Dynamic sizing with FIFO queue management Limitations and Disclaimers Not Predictive: This indicator identifies patterns in historical data. It cannot predict future price movements with certainty. Requires Human Judgment: Signals are entry triggers, not complete trading strategies. Must be confirmed with your own analysis, risk management rules, and market context. Learning Period Required: The adaptive system requires 50-100 bars minimum to build statistically meaningful performance data for bandit algorithms. Overfitting Risk: Restoring memory parameters from one market regime to a drastically different regime (e.g., low volatility to high volatility) may cause poor initial performance until system re-adapts. Approximation Limitations: Simplified calculations (see "Lite" section) may underperform academic implementations by 5-15% in highly efficient markets. No Guarantee of Profit: Past performance, whether backtested or live-traded, does not guarantee future performance. All trading involves risk of loss. Forward-Looking Bias: Performance evaluation uses 8-bar forward window—this creates slight look-ahead for learning (though not for signals). Real-time performance may differ from indicator's internal statistics. Single-Instrument Limitation: Does not account for correlations with related assets or broader market regime changes. Recommended Settings Timeframe: 15-minute to 4-hour charts (sufficient volatility for ATR-based stops; adequate bar volume for learning) Assets: Liquid instruments with >100k daily volume (forex majors, large-cap stocks, BTC/ETH, major indices) Not Recommended: Illiquid small-caps, penny stocks, low-volume altcoins (microstructure metrics unreliable) Complementary Tools: Volume profile, order book depth, market breadth indicators, fundamental catalysts Position Sizing: Risk no more than 1-2% of capital per signal using ATR-based stop-loss Signal Filtering: Consider external confluence (support/resistance, trendlines, round numbers, session opens) Start With: Balanced mode, Thompson Sampling, Blend mode, default agent sensitivities (1.0) After 30+ Signals: Review agent win rates, consider increasing sensitivity of top performers or locking to dominant agent Alert Configuration The script includes built-in alert conditions: Long Signal: Fires when validated long entry confirmed Short Signal: Fires when validated short entry confirmed Alerts fire once per bar (after confirmation requirements met) Set alert to "Once Per Bar Close" for reliability Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Pine Script®指標
由DskyzInvestments提供
14
Stochastic + Bollinger Bands Multi-Timeframe StrategyThis strategy fuses the Stochastic Oscillator from the 4-hour timeframe with Bollinger Bands from the 1-hour timeframe, operating on a 10-hour chart to capture a unique volatility rhythm and temporal alignment discovered through observational alpha. By blending momentum confirmation from the higher timeframe with short-term volatility extremes, the strategy leverages what some traders refer to as “rotating volatility” — a phenomenon where multi-timeframe oscillations sync to reveal hidden trade opportunities. 🧠 Strategy Logic ✅ Long Entry Condition: Stochastic on the 4H timeframe: %K crosses above %D Both %K and %D are below 20 (oversold zone) Bollinger Bands on the 1H timeframe: Price crosses above the lower Bollinger Band, indicating a potential reversal → A long trade is opened when both momentum recovery and volatility reversion align. ✅ Long Exit Condition: Stochastic on the 4H: %K crosses below %D Both %K and %D are above 80 (overbought zone) Bollinger Bands on the 1H: Price reaches or exceeds the upper Bollinger Band, suggesting exhaustion → The long trade is closed when either signal suggests a potential reversal or overextension. 🧬 Temporal Structure & Alpha This strategy is deployed on a 10-hour chart — a non-standard timeframe that may align more effectively with multi-timeframe mean reversion dynamics. This subtle adjustment exploits what some traders identify as “temporal drift” — the desynchronization of volatility across timeframes that creates hidden rhythm in price action. → For example, Stochastic on 4H (lookback 17) and Bollinger Bands on 1H (lookback 20) may periodically sync around 10H intervals, offering unique alpha windows. 📊 Indicator Components 🔹 Stochastic Oscillator (4H, Length 17) Detects momentum reversals using %K and %D crossovers Helps define overbought/oversold zones from a mid-term view 🔹 Bollinger Bands (1H, Length 20, ±2 StdDev) Measures price volatility using standard deviation around a moving average Entry occurs near lower band (support), exits near upper band (resistance) 🔹 Multi-Timeframe Logic Uses request.security() to safely reference 4H and 1H indicators from a 10H chart Avoids repainting by using closed higher-timeframe candles only 📈 Visualization A plot selector input allows toggling between: Stochastic Plot (%K & %D, with overbought/oversold levels) Bollinger Bands Plot (Upper, Basis, Lower from 1H data) This helps users visually confirm entry/exit triggers in real time. 🛠 Customization Fully configurable Stochastic and BB settings Timeframes are independently adjustable Strategy settings like position sizing, slippage, and commission are editable ⚠️ Disclaimer This strategy is intended for educational and informational purposes only. It does not constitute financial advice or a recommendation to buy or sell any asset. Market conditions vary, and past performance does not guarantee future results. Always test any trading strategy in a simulated environment and consult a licensed financial advisor before making real-world investment decisions.
Pine Script®策略
由RWCS_LTD提供
Market Profile Dominance Analyzer# Market Profile Dominance Analyzer ## 📊 OVERVIEW **Market Profile Dominance Analyzer** is an advanced multi-factor indicator that combines Market Profile methodology with composite dominance scoring to identify buyer and seller strength across higher timeframes. Unlike traditional volume profile indicators that only show volume distribution, or simple buyer/seller indicators that only compare candle colors, this script integrates six distinct analytical components into a unified dominance measurement system. This indicator helps traders understand **WHO controls the market** by analyzing price position relative to Market Profile key levels (POC, Value Area) combined with volume distribution, momentum, and trend characteristics. ## 🎯 WHAT MAKES THIS ORIGINAL ### **Hybrid Analytical Approach** This indicator uniquely combines two separate methodologies that are typically analyzed independently: 1. **Market Profile Analysis** - Calculates Point of Control (POC) and Value Area (VA) using volume distribution across price channels on higher timeframes 2. **Multi-Factor Dominance Scoring** - Weights six independent factors to produce a composite dominance index ### **Six-Factor Composite Analysis** The dominance score integrates: - Price position relative to POC (equilibrium assessment) - Price position relative to Value Area boundaries (acceptance/rejection zones) - Volume imbalance within Value Area (institutional bias detection) - Price momentum (directional strength) - Volume trend comparison (participation analysis) - Normalized Value Area position (precise location within fair value zone) ### **Adaptive Higher Timeframe Integration** The script features an intelligent auto-selection system that automatically chooses appropriate higher timeframes based on the current chart period, ensuring optimal Market Profile structure regardless of the trading timeframe being analyzed. ## 💡 HOW IT WORKS ### **Market Profile Construction** The indicator builds a Market Profile structure on a higher timeframe by: 1. **Session Identification** - Detects new higher timeframe sessions using `request.security()` to ensure accurate period boundaries 2. **Data Accumulation** - Stores high, low, and volume data for all bars within the current higher timeframe session 3. **Channel Distribution** - Divides the session's price range into configurable channels (default: 20 rows) 4. **Volume Mapping** - Distributes each bar's volume proportionally across all price channels it touched ### **Key Level Calculation** **Point of Control (POC)** - Identifies the price channel with the highest accumulated volume - Represents the price level where the most trading activity occurred - Serves as a magnetic level where price often returns **Value Area (VA)** - Starts at POC and expands both upward and downward - Includes channels until reaching the specified percentage of total volume (default: 70%) - Expansion algorithm compares adjacent volumes and prioritizes the direction with higher activity - Defines the "fair value" zone where most market participants agreed to trade ### **Dominance Score Formula** ``` Dominance Score = (price_vs_poc × 10) + (price_vs_va × 5) + (volume_imbalance × 0.5) + (price_momentum × 100) + (volume_trend × 5) + (va_position × 15) ``` **Component Breakdown:** - **price_vs_poc**: +1 if above POC, -1 if below (shows which side of equilibrium) - **price_vs_va**: +2 if above VAH, -2 if below VAL, 0 if inside VA - **volume_imbalance**: Percentage difference between upper and lower VA volumes - **price_momentum**: 5-period SMA of price change (directional acceleration) - **volume_trend**: Compares 5-period vs 20-period volume averages - **va_position**: Normalized position within Value Area (-1 to +1) The composite score is then smoothed using EMA with configurable sensitivity to reduce noise while maintaining responsiveness. ### **Market State Determination** - **BUYERS Dominant**: Smooth dominance > +10 (bullish control) - **SELLERS Dominant**: Smooth dominance < -10 (bearish control) - **NEUTRAL**: Between -10 and +10 (balanced market) ## 📈 HOW TO USE THIS INDICATOR ### **Trend Identification** - **Green background** indicates buyers are in control - look for long opportunities - **Red background** indicates sellers are in control - look for short opportunities - **Gray background** indicates neutral market - consider range-bound strategies ### **Signal Interpretation** **Buy Signals** (green triangle) appear when: - Dominance crosses above -10 from oversold conditions - Previous state was not already bullish - Suggests shift from seller to buyer control **Sell Signals** (red triangle) appear when: - Dominance crosses below +10 from overbought conditions - Previous state was not already bearish - Suggests shift from buyer to seller control ### **Value Area Context** Monitor the information table (top-right) to understand market structure: - **Price vs POC**: Shows if trading above/below equilibrium - **Volume Imbalance**: Positive values favor buyers, negative favors sellers - **Market State**: Current dominant force (BUYERS/SELLERS/NEUTRAL) ### **Multi-Timeframe Strategy** The auto-timeframe feature analyzes higher timeframe structure: - On 1-minute charts → analyzes 2-hour structure - On 5-minute charts → analyzes Daily structure - On 15-minute charts → analyzes Weekly structure - On Daily charts → analyzes Yearly structure This higher timeframe context helps avoid counter-trend trades against the dominant force. ### **Confluence Trading** Strongest signals occur when multiple factors align: 1. Price above VAH + positive volume imbalance + buyers dominant = Strong bullish setup 2. Price below VAL + negative volume imbalance + sellers dominant = Strong bearish setup 3. Price at POC + neutral state = Potential breakout/breakdown pivot ## ⚙️ INPUT PARAMETERS - **Higher Time Frame**: Select specific HTF or use 'Auto' for intelligent selection - **Value Area %**: Percentage of volume contained in VA (default: 70%) - **Show Buy/Sell Signals**: Toggle signal triangles visibility - **Show Dominance Histogram**: Toggle histogram display - **Signal Sensitivity**: EMA period for dominance smoothing (1-20, default: 5) - **Number of Channels**: Market Profile resolution (10-50, default: 20) - **Color Settings**: Customize buyer, seller, and neutral colors ## 🎨 VISUAL ELEMENTS - **Histogram**: Shows smoothed dominance score (green = buyers, red = sellers) - **Zero Line**: Neutral equilibrium reference - **Overbought/Oversold Lines**: ±50 levels marking extreme dominance - **Background Color**: Highlights current market state - **Information Table**: Displays key metrics (state, dominance, POC relationship, volume imbalance, timeframe, bars in session, total volume) - **Signal Shapes**: Triangle markers for buy/sell signals ## 🔔 ALERTS The indicator includes three alert conditions: 1. **Buyers Dominate** - Fires on buy signal crossovers 2. **Sellers Dominate** - Fires on sell signal crossovers 3. **Dominance Shift** - Fires when dominance crosses zero line ## 📊 BEST PRACTICES ### **Timeframe Selection** - **Scalping (1-5min)**: Focus on 2H-4H dominance shifts - **Day Trading (15-60min)**: Monitor Daily and Weekly structure - **Swing Trading (4H-Daily)**: Track Weekly and Monthly dominance ### **Confirmation Strategies** 1. **Trend Following**: Enter in direction of dominance above/below ±20 2. **Reversal Trading**: Fade extreme readings beyond ±50 when diverging with price 3. **Breakout Trading**: Look for dominance expansion beyond ±30 with increasing volume ### **Risk Management** - Avoid trading during NEUTRAL states (dominance between -10 and +10) - Use POC levels as logical stop-loss placement - Consider VAH/VAL as profit targets for mean reversion ## ⚠️ LIMITATIONS & WARNINGS **Data Requirements** - Requires sufficient historical data on current chart (minimum 100 bars recommended) - Lower timeframes may show fewer bars per HTF session initially - More accurate results after several complete HTF sessions have formed **Not a Standalone System** - This indicator analyzes market structure and participant control - Should be combined with price action, support/resistance, and risk management - Does not guarantee profitable trades - past dominance does not predict future results **Repainting Characteristics** - Higher timeframe levels (POC, VAH, VAL) update as new bars form within the session - Dominance score recalculates with each new bar - Historical signals remain fixed, but current session data is developing **Volume Limitations** - Uses exchange-provided volume data which varies by instrument type - Forex and some CFDs use tick volume (not actual transaction volume) - Most accurate on instruments with reliable volume data (stocks, futures, crypto) ## 🔍 TECHNICAL NOTES **Performance Optimization** - Uses `max_bars_back=5000` for extended historical analysis - Efficient array management prevents memory issues - Automatic cleanup of session data on new period **Calculation Method** - Market Profile uses actual volume distribution, not TPO (Time Price Opportunity) - Value Area expansion follows traditional Market Profile auction theory - All calculations occur on the chart's current symbol and timeframe ## 📚 EDUCATIONAL VALUE This indicator helps traders understand: - How institutional traders use Market Profile to identify fair value - The relationship between price, volume, and market acceptance - Multi-factor analysis techniques for assessing market conditions - The importance of higher timeframe structure in trade planning ## 🎓 RECOMMENDED READING To better understand the concepts behind this indicator: - "Mind Over Markets" by James Dalton (Market Profile foundations) - "Markets in Profile" by James Dalton (Value Area analysis) - Volume Profile analysis in institutional trading ## 💬 USAGE TERMS This indicator is provided as an educational and analytical tool. It does not constitute financial advice, investment recommendations, or trading signals. Users are responsible for their own trading decisions and should conduct their own research and due diligence. Trading involves substantial risk of loss. Past performance does not guarantee future results. Always use proper risk management and never risk more than you can afford to lose.
Pine Script®指標
由Smart-Day-Trader提供
Alpha-Weighted RSIDescription: The Alpha-Weighted RSI is a next-generation momentum oscillator that redefines the classic RSI by incorporating the mathematical principles of Lévy Flight. This advanced adaptation applies non-linear weighting to price changes, making the indicator more sensitive to significant market moves and less reactive to minor noise. It is designed for traders seeking a clearer, more powerful view of momentum and potential reversal zones. 🔍 Key Features & Innovations: Lévy Flight Alpha Weighting: At the core of this indicator is the Alpha parameter (1.0-2.0), which controls the sensitivity to price changes. Lower Alpha (e.g., 1.2): Makes the indicator highly responsive to recent price movements, ideal for capturing early trend shifts. Higher Alpha (e.g., 1.8): Creates a smoother, more conservative output that filters out noise, focusing on stronger momentum. Customizable Smoothing: The raw Lévy-RSI is smoothed by a user-selectable moving average (8 MA types supported: SMA, EMA, SMMA, etc.), allowing for further customization of responsiveness. Intuitive Centered Oscillator: The RSI is centered around a zero line, providing a clean visual separation between bullish and bearish territory. Dynamic Gradient Zones: Subtle, colour coded gradient fills in the overbought (>+25) and oversold (<-25) regions enhance visual clarity without cluttering the chart. Modern Histogram Display: Momentum is plotted as a sleek histogram that changes color between bright cyan (bullish) and magenta (bearish) based on its position relative to the zero line. 🎯 How to Use & Interpret: Zero-Line Crossovers: The most basic signals. A crossover above the zero line indicates building bullish momentum, while a crossover below suggests growing bearish momentum. Overbought/Oversold Levels: Use the +25/-25 and +35/-35 levels as dynamic zones. A reading above +25 suggests strong bullish momentum (overbought), while a reading below -25 indicates strong bearish momentum (oversold). Divergence Detection: Look for divergences between the Alpha-Weighted RSI and price action. For example, if price makes a new low but the RSI forms a higher low, it can signal a potential bullish reversal. Alpha Tuning: Adjust the Alpha parameter to match market volatility. In choppy markets, increase alpha to reduce noise. In trending markets, decrease alpha to become more responsive. ⚙️ Input Parameters: RSI Settings: Standard RSI inputs for Length and Calculation Source. Lévy Flight Settings: The crucial Alpha factor for response control. MA Settings: MA Type and MA Length for smoothing the final output. By applying Lévy Flight dynamics, this indicator offers a nuanced perspective on momentum, helping you stay ahead of the curve. Feedback is always welcome!
Pine Script®指標
由gordito03提供
Luminous Glide Momentum Indicator [wjdtks255]This indicator, named "Customized SuperSmoother MA Oscillator," applies a smoothing filter to price data using a SuperSmoother technique to reduce noise and enhance signal clarity. It calculates two moving averages on the smoothed data—a fast and a slow—whose difference forms the oscillator line. A signal line is derived by smoothing the oscillator with another moving average. The histogram visualizes the divergence between the oscillator and signal lines, indicating momentum strength and direction. How it works SuperSmoother Filter: Reduces price noise to provide smoother and more reliable signals than raw data. Fast and Slow Moving Averages: The fast MA reacts quicker to price changes, while the slow MA indicates longer trends. Oscillator: The difference between the fast and slow MAs signals shifts in momentum. Signal Line: A smoothed version of the oscillator used to generate crossovers. Histogram: Displays the distance between the oscillator and signal line, with color changes indicating bullish or bearish momentum. Trading Strategy Buy Signal: When the oscillator crosses above the signal line, it suggests increasing upward momentum, signaling a potential buy opportunity. Sell Signal: When the oscillator crosses below the signal line, it suggests increasing downward momentum, signaling a potential sell opportunity. Histogram Size and Color: Larger green bars indicate stronger bullish momentum; larger red bars indicate stronger bearish momentum. Usage Tips Combine this oscillator with other indicators or price action analysis to confirm trading signals. Adjust smoothing and moving average lengths according to your trading timeframe and the asset volatility. Use proper risk management to filter out potential false signals common in oscillators.
Pine Script®指標
由wjdtks255提供
EMA Cross + RSI + ADX - Autotrade Strategy V2Overview A versatile trend-following strategy combining EMA 9/21 crossovers with RSI momentum filtering and optional ADX trend strength confirmation. Designed for both cryptocurrency and traditional futures/options markets with built-in stop loss management and automated position reversals. Key Features Multi-Market Compatibility: Works on both crypto futures (Bitcoin, Ethereum) and traditional markets (NIFTY, Bank NIFTY, S&P 500 futures, equity options) Triple Confirmation System: EMA crossover + RSI filter + ADX strength (optional) Automated Risk Management: 2% stop loss with wick-touch detection Position Auto-Reversal: Opposite signals automatically close and reverse positions Webhook Ready: Six distinct alert messages for automation (Entry Buy/Sell, Close Long/Short, SL Hit Long/Short) Performance Metrics NIFTY Futures (15min): 50%+ win rate with ADX filter OFF Crypto Markets: Requires extensive backtesting before live deployment Optimal Timeframes: 15-minute to 1-hour charts (patience required for higher timeframes) Strategy Logic Entry Signals: LONG: EMA 9 crosses above EMA 21 + RSI > 55 + ADX > 20 (if enabled) SHORT: EMA 9 crosses below EMA 21 + RSI < 45 + ADX > 20 (if enabled) Exit Signals: Opposite EMA crossover (auto-closes current position) Stop loss hit at 2% from entry price (tracks candle wicks) Technical Indicators: Fast EMA: 9-period (short-term trend) Slow EMA: 21-period (primary trend) RSI: 14-period with 55/45 thresholds (momentum confirmation) ADX: 14-period with 20 threshold (trend strength filter - optional) Market-Specific Settings Traditional Markets (NIFTY, Bank NIFTY, S&P Futures, Options) Recommended Settings: ADX Filter: Turn OFF (less choppy, cleaner trends) Timeframe: 15-minute chart Win Rate: 50%+ on NIFTY Futures Why No ADX: Traditional markets have more institutional participation and smoother price action, making ADX unnecessary Cryptocurrency Markets (BTC, ETH, Altcoins) Recommended Settings: ADX Filter: Turn ON (ADX > 20) Timeframe: 15-minute to 1-hour Extensive backtesting required before live trading Why ADX: Crypto markets are highly volatile and prone to false breakouts; ADX filters low-quality chop Best Practices ✅ Backtest thoroughly on your specific instrument and timeframe ✅ Use larger timeframes (1H, 4H) for higher quality signals and better risk/reward ✅ Adjust RSI thresholds based on market volatility (try 52/48 for more signals, 60/40 for fewer but stronger) ✅ Monitor ADX effectiveness - disable for traditional markets, enable for crypto ✅ Proper position sizing - adjust default_qty_value based on your capital and instrument price ✅ Paper trade first - test for 2-4 weeks before risking real capital Risk Management Fixed 2% stop loss per trade (adjustable) Stop loss tracks candle wicks for accurate execution Positions auto-reverse on opposite signals (no manual intervention needed) 0.075% commission built into backtest (adjust for your broker) Customization Options All parameters are adjustable via inputs: EMA periods (default: 9/21) RSI length and thresholds (default: 14-period, 55/45 levels) ADX length and threshold (default: 14-period, 20 threshold) Stop loss percentage (default: 2%) Webhook Automation This strategy includes six distinct alert messages for automated trading: "Entry Buy" - Long position opened "Entry Sell" - Short position opened "Close Long" - Long position closed on opposite crossover "Close Short" - Short position closed on opposite crossover "SL Hit Long" - Long stop loss triggered "SL Hit Short" - Short stop loss triggered Compatible with Delta Exchange, Binance Futures, 3Commas, Alertatron, and other webhook platforms. Important Notes ⚠️ Crypto markets require extensive backtesting - volatility patterns differ significantly from traditional markets ⚠️ Higher timeframes = better results - 15min works but 1H/4H provide cleaner signals ⚠️ ADX toggle is critical - OFF for traditional markets, ON for crypto ⚠️ Not financial advice - always conduct your own research and use proper risk management ⚠️ Past performance ≠ future results - backtest results may not reflect live trading conditions Disclaimer This strategy is for educational and informational purposes only. Trading futures and options involves substantial risk of loss. Always backtest thoroughly, start with paper trading, and never risk more than you can afford to lose. The author assumes no responsibility for any trading losses incurred using this strategy.
Pine Script®策略
由varuns_back提供
5
ADX FAST and NOICE FREE DIThis tool is designed to identify trend strength and direction earlier than the traditional ADX/DI system. Instead of relying on the normal Wilder smoothing, this version applies momentum projection to ADX (Fast ADX) and then filters all directional movement signals through Hull smoothing to minimize market noise. The result: • Trends are detected faster • Pullbacks are filtered more cleanly • Sideways or weak structures become easy to avoid Recommended Usage: • Look for Fast ADX above the threshold to confirm trend environment • Use Noise-Free +DI and -DI to confirm trend direction (bullish / bearish dominance) • Background color highlights only when trend + direction are aligned This is not a buy/sell signal generator by itself; it is best used as a trend and market condition confirmation layer. Disclaimer: This script is provided for educational and informational purposes only. It does not constitute financial advice or a recommendation to buy or sell any security. Market conditions vary and past performance does not guarantee future results. Always perform your own analysis and risk management, and trade responsibly.
Pine Script®指標
由tejaspanarafire提供
Robust Scaled Dema | OquantOverview The Robust Scaled DEMA indicator is a tool designed for traders seeking to identify potential trend directions in financial markets. It combines the smoothing capabilities of a Double Exponential Moving Average (DEMA) with a robust scaling mechanism to normalize the data, making it more resilient to outliers and extreme price movements. This scaling helps in generating long and short signals based on predefined thresholds, visualized through color-coded plots and bars. The indicator aims to provide a balanced view of market momentum, reducing the impact of noise while highlighting significant shifts in price behavior. Key Factors/Components DEMA (Double Exponential Moving Average): Serves as the core smoothing component, reducing lag compared to simple averages by emphasizing recent price action more effectively. Robust Scaling Mechanism: Utilizes statistical measures like median and interquartile range to normalize the DEMA values, ensuring the indicator is less sensitive to extreme values or price spikes. Thresholds: User-defined upper and lower levels that trigger long or short signals when the scaled DEMA crosses them. Visual Elements: Includes plotted lines for the scaled DEMA and thresholds, plus color-coded candlestick bars for intuitive interpretation. Alerts: Built-in conditions for notifying users of potential entry points for long or short positions. How It Works The indicator starts by applying a DEMA to the chosen price source to create a smoothed representation of the market's direction. This smoothed value is then scaled using a robust statistical approach that accounts for the distribution of recent DEMA values, centering it around a median and adjusting for variability to minimize the influence of outliers. The resulting scaled metric is compared against user-set upper and lower thresholds: crossing above the upper suggests a bullish momentum (long signal), while dipping below the lower indicates bearish conditions (short signal). A state variable tracks these conditions to color the chart accordingly, helping traders visualize regime changes. Optional alerts fire on transitions. For Who Is Best/Recommended Use Cases This indicator is ideal for traders who employ trend-following or momentum-based strategies and need tools that perform well in non-normal market conditions, such as during high volatility or in assets prone to spikes. Use cases include identifying entry/exit points in trending environments, confirming breakouts, or integrating into multi-indicator systems for added confirmation. Quantitative traders or those backtesting strategies will appreciate its customizable parameters for optimization. Settings and Default Settings Source: The price data input for calculations, such as close, open, high, or low. Default: close. DEMA Length: Controls the period for the DEMA smoothing; shorter values increase responsiveness but may add noise, longer ones provide more lag but smoother signals. Default: 25. Robust Scaling Length: Defines the lookback period for the scaling statistics; affects how adaptive the normalization is to recent data distributions. Default: 40. Upper Threshold: The level above which a long signal is triggered; higher values make signals rarer but potentially more reliable. Default: 0.5. Lower Threshold: The level below which a short signal is triggered; lower values allow for more aggressive bearish detection. Default: 0. Conclusion The Robust Scaled DEMA offers an outlier-resistant alternative to traditional moving average indicators, empowering traders to navigate volatile markets. By blending exponential smoothing with statistical robustness, it provides actionable insights into trend shifts while minimizing false positives from extreme events.. ⚠️ Disclaimer: This indicator is intended for educational and informational purposes only. Trading/investing involves risk, and past performance does not guarantee future results. Always test and evaluate indicators/strategies before applying them in live markets. Use at your own risk.
Pine Script®指標
由oquant提供
2
HTF MACD Dual Zero Cross + First EMA PullbackThis script aims to get the trader on the right side of the momentum and get better entries by only alerting when price pulls back to the trader's specified EMA. This script isnt meant to catch tops or bottoms but to trade with the momentum once it starts. This script will alert whe nthe MACD and signal line both cross the zero line, after that the script waits for price to make a pullback and then alet either a sell or buy. Ive found this works best when you trade with the trend on a higher timeframe. You can use whatever MACD settings you prefer and really customize this to the asset youre trading. You can also change whether you get an alert based on a wick touch of the EMA or a candle close.
Pine Script®指標
由skylinegtr2789提供
Zone Tap Counter: Support & Resistance StrengthWhat is this indicator? This script is designed to help traders objectively monitor the strength and significance of price zones by counting and visualizing how many times price “taps” confirmed support and resistance levels. The indicator leverages swing high/low detection to automatically plot relevant zones and uses price tap frequency as an objective strength metric. How does it work? Zone Identification: The script uses the Pine Script functions ta.pivothigh and ta.pivotlow to detect confirmed swing highs and lows on your chart. Each swing high establishes a resistance zone, and each swing low establishes a support zone. Only confirmed pivots are used, ensuring all signals are strictly non-repainting. Tap Counting Logic: For every candle, the indicator checks whether price touches (comes within a small, user-set tolerance) of any currently tracked support or resistance zone. To avoid counting repeated taps in the same move, the script ensures only unique bar taps are registered. Each time price taps a zone, a counter for that zone is incremented. Both the tolerance for taps (percentage-based), and the depth/history of zones tracked are fully adjustable in settings. Visual Feedback: Zones with more taps are drawn darker (lower transparency), making it easy to spot the strongest/hardest-tested levels on the chart. A label on each zone displays the current tap count (e.g., "3x"), giving direct feedback about which support/resistance are most significant in the current view. Only recent zones (user-configurable) are shown to keep charts clear and useful. How to use it: Add the indicator to your TradingView chart. Set the swing length and tap tolerance in settings to match your market or timeframe (short swing length for scalping, longer swings for bigger structure). Watch for zones with high tap counts and darker lines: These zones represent areas where price has repeatedly reacted, suggesting they may be important for your trading decisions. You can adjust the minimum number of taps needed for a zone to be highlighted and the number of zones to display for your preferred visual clarity. Combine this tool with other analysis for confirmation—tap counts should not be seen as trading signals, but as supporting information. Originality & Calculation Details: This script does NOT simply merge or overlay existing indicators. The calculation method is original: it uses swing-based support/resistance and applies unique tap-count logic, designed for objective zone strength visualization. No repainting logic is present. All code and visualization methods are documented and transparent. Disclaimer: This indicator is for educational and analytical purposes only. It does not predict future price movement, guarantee profits, or recommend specific trades. Always use your own analysis and risk management. See TradingView’s House Rules for more details.
Pine Script®指標
由darshakssc提供
Twiggs Go Money Flow Enhanced [KingThies]█ OVERVIEW The Twiggs Money Flow (TMF) is a volume-weighted momentum oscillator that measures buying and sellistng pressure by analyzing where price closes within each bar's true range. It's an enhanced version of Chaikin Money Flow that uses Wilder's smoothing method, providing better trend persistence and smoother signals. The indicator oscillates around a zero listne: Values above zero indicate accumulation (buying pressure) Values below zero indicate distribution (sellistng pressure) TMF was developed by Colistn Twiggs as an improvement over traditional money flow indicators by incorporating true range calculations and Wilder's exponential moving average. █ CONCEPTS True Range Boundaries TMF calculates a modified true range for each bar by comparing the current bar's high and low with the previous close: True Range High = maximum of (previous close, current high) True Range Low = minimum of (previous close, current low) This accounts for overnight gaps and ensures price continuity between bars. Average Daily Value (ADV) The ADV represents the portion of volume attributable to buying versus sellistng: ADV = Volume × ((Close - TR Low) - (TR High - Close)) / True Range When price closes near the high of the true range, ADV is positive and large. When price closes near the low, ADV is negative and large. A close in the middle produces values near zero. Wilder's Moving Average Unlistke simple moving averages, Wilder's smoothing method gives more weight to recent values while maintaining memory of historical data: WMA = (Previous WMA × (Period - 1) + Current Value) / Period This creates smoother trends that are less prone to whipsaws than standard moving averages. Final Calculation TMF = Wilder's MA(ADV, Period) / Wilder's MA(Volume, Period) By dividing smoothed ADV by smoothed volume, TMF normalistzes the reading and makes it comparable across different securities and timeframes. █ HOW TO USE Zero listne Crossovers The most straightforward trading signals: A cross above zero suggests buyers are gaining control. Consider this a bullistsh signal, especially when confirmed by price action. A cross below zero suggests sellers are gaining control. Consider this a bearish signal. The longer TMF remains above or below zero, the stronger the trend. Extreme Values Strong positive or negative readings indicate intense buying or sellistng pressure: Sustained high positive values (above +0.4) suggest strong accumulation but may also indicate overbought conditions. Sustained low negative values (below -0.4) suggest strong distribution but may also indicate oversold conditions. These extremes work best when used in conjunction with price levels and support/resistance zones. Divergences Divergences between price and TMF often signal potential reversals: Bearish divergence: Price makes a higher high but TMF makes a lower high — suggests buying pressure is weakening despite rising prices. Bullistsh divergence: Price makes a lower low but TMF makes a higher low — suggests sellistng pressure is weakening despite fallistng prices. Trend Confirmation Use TMF to confirm the strength of existing trends: In an uptrend, TMF should remain mostly positive with occasional dips below zero. In a downtrend, TMF should remain mostly negative with occasional rises above zero. If TMF contradicts the price trend, consider the trend weak or potentially ending. █ FEATURES Period (default: 21) The lookback length for Wilder's moving average calculation: Shorter periods (10–15) make TMF more responsive to recent changes but increase noise and false signals. Longer periods (30–50) create smoother readings but lag price action more significantly. The default 21-period setting balances responsiveness with relistabilistty. Consider adjusting the period based on your trading timeframe and the volatilistty of the security you're analyzing. █ LIMITATIONS TMF is a lagging indicator due to its smoothing method. Signals may occur after optimal entry or exit points. In low-volume or illistquid markets, TMF can produce erratic readings that may not reflect true buying or sellistng pressure. Ranging or choppy markets often generate frequent zero-listne crosses that can lead to whipsaws. listke all volume-based indicators, TMF's relistabilistty depends on accurate volume data. For securities with unrelistable volume reporting, consider using price-based momentum indicators instead. █ NOTES This indicator uses area-style plotting in the original version to visualistze the magnitude of buying and sellistng pressure. The filled area makes it easy to see at a glance whether the market is in accumulation or distribution mode. TMF works on any timeframe but tends to be most relistable on daily charts where volume data is most accurate and meaningful. █ CREDITS Original indicator developed by LazyBear . Based on the Twiggs Money Flow concept from Incredible Charts: Incredible Charts – Twiggs Money Flow .
Pine Script®指標
由kingthies提供
RSI MTF Table - 12 Pairs (1,5,15) The relative strength index measures the speed and magnitude of an asset's recent price changes. Therefore, it is considered a momentum indicator in technical analysis. Essentially, the RSI is the ratio of the days an asset's value increases to decreases over a given period. Generally speaking, if the RSI is around 50, we do not expect strong movements. RSI above 65 or below 35 are areas we expect. In this context, this chart and the general momentum in 1-5-15 minutes allow us to quickly determine the parity we will trade. It is useful for intraday trading and scalping.
Pine Script®指標
由MICROTRADES提供