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Renko TimekeeperRenko charts delete time. This tool puts it back.The Renko Timekeeper prints a number next to every brick telling you exactly how many minutes that specific brick took to form.This converts a "Static Chart" into a "Velocity Chart." It allows you to spot Momentum Decay before the price actually reverses.1. The Visual GuideThe indicator prints a single number (e.g., 4.2) above or below every brick.Text ColorValue RangeEngineering StateInterpretationGREEN< 5.0High VelocityThe "Turbo" is on. Buyers/Sellers are aggressive. HOLD or ADD to the trade.GRAY5.0 – 15.0Normal CruiseThe trend is stable. Standard market breathing. HOLD.RED> 15.0STALL (Warning)The engine has died. The market is struggling to push price. EXIT immediately.
אינדיקטור Pine Script®
מאת ‎cechapman‎
ADAPTIVE SCALP MASTERADAPTIVE SCALP MASTER (ASM) Overview ADAPTIVE SCALP MASTER (ASM) is a high-performance technical analysis tool specifically engineered for scalpers and day traders. It combines statistical volatility analysis with a unique time-frame adaptation engine, allowing the script to automatically recalibrate its sensitivity whether you are trading the 1-minute chart or the 4-hour trend. The core logic is based on Z-Score Mean Reversion coupled with Zero-Lag Least Squares Moving Average (ZLSMA) for trend filtering, ensuring that you enter trades only when momentum and statistical overextension align. Key Features Timeframe Adaptation Engine: ASM automatically adjusts its Z-Score lengths, thresholds, and ATR multipliers based on your current chart. It tightens parameters for high-frequency scalping (M1-M5) and widens them for higher timeframes to filter out market noise. Z-Score Mean Reversion: Utilizes statistical standard deviation to identify overbought and oversold conditions with precision. Zero-Lag Trend Filtering: Features a customized ZLSMA to provide a smooth, reactive trend baseline without the lag of traditional MAs. Smart Risk Management: Automatically calculates dynamic Stop Loss and Take Profit levels based on current ATR volatility. Aggressive Scalping Mode: A specialized toggle for experienced traders that maximizes signal frequency by loosening standard confirmation filters. How It Works Normalization: The indicator calculates the price deviation (Z-Score). Adaptive Thresholds: It checks if the price has reached a statistically significant extreme (Overbought/Oversold). Multi-Stage Filtering: Trend Filter: Signals must align with the ZLSMA direction (optional). Volume Filter: Requires a surge in volume to confirm the move (optional). Candle Confirmation: Requires price action to flip in the signal's direction before firing. Execution: Once all conditions are met, the script plots entry shapes and dynamic risk levels. Settings Guide Aggressive Mode: Use this for fast-paced scalping on M1. It disables the trend and volume filters to capture every micro-reversal. Base Sensitivity: Controls how far back the Z-Score looks. Default is 10. Lower values make the indicator more reactive. Base Threshold: Standard is 1.5. Increase this value (e.g., to 2.0) if you want fewer, higher-probability signals. Min Bars Between: Use this to prevent "signal clustering" during periods of high volatility. User Interface The Info Panel provides real-time data including: Current Market Bias (Trend direction). Live Z-Score value. Current ATR-based volatility status. Trade Signal confirmation status.
אינדיקטור Pine Script®
מאת ‎TheHarmonySystems‎
2
Clusters Volume Profile [LuxAlgo]The Clusters Volume Profile indicator utilizes K-Means clustering to categorize historical price action into distinct groups and generates individual volume profiles for each detected cluster. This tool provides a unique perspective on volume distribution by isolating price behaviors based on proximity rather than strictly chronological order. 🔶 USAGE The indicator identifies "clusters" of price activity within a user-defined lookback period. Each cluster is assigned a unique color and its own horizontal volume profile, allowing traders to see where liquidity is most concentrated within specific price regimes. 🔹 Identifying Institutional Zones Traders can use the Point of Control (POC) of high-volume clusters to identify significant institutional interest. Because the K-Means algorithm groups price action by density rather than time, a cluster's POC often represents a "fair value" level where significant exchange occurred. These dashed POC lines frequently act as robust support or resistance levels when price returns to them in the future. 🔹 Market Regime Detection By observing the vertical distribution and overlap of clusters, traders can identify market phases. Overlapping clusters with high volume often indicate accumulation or distribution phases (sideways markets), whereas distinct, vertically separated clusters with lower volume gaps between them suggest a trending environment. A shift from multiple overlapping clusters to a new, isolated cluster can signal a breakout or the start of a new trend. 🔹 Precision Entry & Exits Cluster boundaries and POC lines provide concrete levels for trade management. An entry can be sought when price retests a high-volume cluster POC, while stops can be placed outside the total price range of that specific cluster (the area covered by its volume profile). Conversely, targets can be set at the POC of the next major cluster above or below current price action. 🔹 Volume Conviction The tool provides specific volume metrics that allow traders to gauge conviction. By comparing the "Total" volume label of one cluster against another, a trader can determine which price regime had more participation. A breakout into a price zone with a high-volume cluster suggests stronger conviction and a higher probability of the level holding compared to a zone with low total volume. 🔶 DETAILS The script employs a K-Means clustering algorithm. This process involves: Initializing "centroids" across the price range of the lookback period. Iteratively assigning each price bar to the nearest centroid based on the HLC2 (median) price. Recalculating centroids based on the volume-weighted average price of the assigned bars. Finalizing assignments after the specified number of iterations to ensure stable clusters. By separating price action into these clusters, the tool helps identify high-interest zones that might be obscured by a single, traditional Volume Profile. 🔶 SETTINGS 🔹 Clustering Settings Lookback Period: Determines the number of recent bars used for the clustering analysis. Number of Clusters: Sets how many distinct price groups the algorithm should attempt to find (2 to 10). K-Means Iterations: Controls the number of times the algorithm refines the cluster centers. Higher values can lead to more stable results. 🔹 Volume Profile Settings Rows per Cluster VP: Defines the vertical resolution (number of bins) for each individual cluster's profile. Max VP Width (Bars): Sets the maximum horizontal length of the volume profile histograms. VP Offset: Adjusts the horizontal spacing between the current bar and the start of the volume profiles. Highlight Price Dots: Toggles the visibility of the colored dots on the price action to identify cluster assignments. Dot Size: Adjusts the size of the cluster assignment dots on the chart, ranging from tiny to huge.
אינדיקטור Pine Script®
מאת ‎LuxAlgo‎
4
Outlier Catching Moving AverageOutlier Catching Moving Average (OCMA) | MisinkoMaster Outlier Catching Moving Average (OCMA) is a volatility-adaptive trend indicator designed to react quickly to abnormal price movements while maintaining smooth behavior during normal market conditions. The indicator aims to capture sudden price expansions without sacrificing overall trend clarity. This makes OCMA suitable for traders who want faster adaptation to unusual market activity while still preserving stable trend structure across varying volatility regimes. Key Features Volatility-adaptive moving average designed to react to price outliers Multiple moving average bases supported for flexible smoothing behavior Optional ATR-based adaptive bands for volatility envelopes Configurable trend logic for earlier signals or stronger confirmations Dynamic candle coloring for intuitive trend visualization Automatic Long and Short markers on confirmed trend transitions Designed to balance responsiveness and smoothness across market conditions How It Works OCMA builds on traditional moving average concepts but incorporates adaptive smoothing that adjusts according to changing market volatility. Rather than behaving uniformly across all conditions, the average becomes more responsive when price behavior deviates strongly from recent structure and smoother when markets return to normal activity. Optional ATR bands expand and contract with volatility, helping identify when price moves significantly away from its adaptive equilibrium. The result is a moving average that remains stable in calm markets yet quickly adapts when price action becomes irregular or impulsive. Inputs Overview Source — Selects the price data used in calculations Moving Average Length — Controls the main smoothing period ATR Length — Sets the volatility measurement period used for band calculations Base Moving Average — Selects which moving average type is used as the foundation Trend Logic — Chooses whether trends are detected via band crossover, average direction change, or both Use ATR Bands — Enables or disables adaptive volatility bands Factor — Controls ATR band width sensitivity ALMA Offset & Sigma — Parameters used only when ALMA smoothing is selected Usage Notes Designed to detect abnormal price expansions while preserving overall trend structure Suitable for breakout traders and volatility-aware trend strategies Band crossovers can signal potential trend transitions Average direction changes may confirm continuation or reversal Works well when combined with market structure or confirmation tools Adjust parameters according to asset volatility and timeframe Summary Outlier Catching Moving Average provides a volatility-aware alternative to standard moving averages, helping traders capture unusual price behavior while maintaining smooth and readable trend signals. It is well suited for traders seeking adaptive trend tools capable of responding when markets move outside normal conditions.
אינדיקטור Pine Script®
מאת ‎MisinkoMaster‎
Outlier Resistant Moving AverageOutlier Resistant Moving Average (ORMA) | MisinkoMaster Outlier Resistant Moving Average (ORMA) is a trend-following moving average designed to reduce the impact of abnormal price spikes while preserving responsiveness to real market moves. The goal is to provide a smoother and more stable trend reference that remains usable even during volatile or erratic price behavior. Unlike traditional moving averages that react strongly to sudden price shocks, ORMA adapts its behavior to volatility conditions, helping traders follow trends without being constantly misled by temporary price extremes. Key Features Moving average designed to resist distortion from price outliers Adaptive smoothing behavior that reacts to volatility conditions Optional ATR-based dynamic bands for trend confirmation Multiple moving average types supported as the calculation base Flexible trend detection logic options Automatic trend coloring and signal labeling Candle coloring for intuitive trend visualization How It Works ORMA builds upon a selectable base moving average and modifies its behavior to reduce the influence of abnormal price movements. Instead of reacting equally to all price changes, the calculation adjusts its responsiveness according to changing volatility conditions. When market volatility expands, the indicator becomes more conservative, preventing sudden spikes from distorting the average. During calmer conditions, responsiveness increases, allowing the average to track price action more closely. Optional ATR-based bands can be applied around the average, allowing traders to use band breakouts as confirmation of trend strength rather than relying solely on slope changes. The result is a moving average that remains stable in noisy markets while still adapting during real trend movements. Inputs Overview Source — Selects the price source used in calculations Moving Average Length — Controls smoothing and calculation sensitivity ATR Length — Controls volatility measurement used for adaptive behavior Base Moving Average — Selects which MA type forms the calculation foundation Trend Logic — Determines whether trend is detected via crossover, slope change, or both Use ATR Bands — Enables or disables dynamic ATR bands ATR Factor — Controls band distance from the average ALMA Offset & Sigma — Parameters used only when ALMA smoothing is selected Floored Offset — Optional ALMA configuration affecting smoothing behavior Usage Notes Useful for filtering noise during volatile or choppy markets ATR bands can help confirm stronger breakouts or trend continuation Trend logic modes allow adaptation to different trading styles Suitable for swing trading, trend-following, and position trading approaches Can act as dynamic support or resistance in trending markets Works well when combined with momentum or volume confirmation tools Summary Outlier Resistant Moving Average offers a volatility-aware trend reference that helps traders remain aligned with broader price movement while minimizing disruptions from sudden price spikes. It is especially useful for traders seeking smoother trend identification without sacrificing adaptability.
אינדיקטור Pine Script®
מאת ‎MisinkoMaster‎
2
Forward Path (ATR Drift) + Confidence [v6]This indicator helps traders visualize where price is statistically likely to travel, how wide the uncertainty is, and how confident history has been in similar conditions — all without claiming to “predict” the market. What this indicator does This indicator projects a probable future price path for the next 15 / 20 / 30 candles on any chart and timeframe. It combines: Trend direction (EMA slope) Volatility (ATR) Historical behavior in similar market conditions to show where price is likely to travel and how confident that expectation is. What you see on the chart Solid forward line → The most likely price path based on current trend momentum. Dotted upper & lower lines → Expected price range using current volatility (ATR). Think of this as the probable zone, not a target. Confidence label Prob Up (%) – how often price moved higher after N candles in similar conditions Prob Down (%) – how often price moved lower These are historical probabilities, not predictions. How to use it (simple & practical) 1️⃣ Directional bias If the projected path slopes up and Prob Up > 60%, the market favors longs. If the path slopes down and Prob Down > 60%, the market favors shorts. Near 50/50 → no edge, wait for structure or confirmation. 2️⃣ Expectation setting Use the projection length (15 / 20 / 30 bars) to match your trade horizon. Don’t expect price to exceed the dotted bands easily — they represent normal volatility. 3️⃣ Risk & trade management Entries near the base path = better risk-reward. Use the opposite band as a guide for: Stop placement Partial profit booking Wide bands = reduce position size. 4️⃣ Trade filtering Take trades only when your setup aligns with the projected direction. Skip trades when: Probability is low Bands are extremely wide Projection is flat (range-bound market) Best use cases Swing trading Trade planning before entry Position sizing & expectation control Avoiding low-edge, random trades What this indicator is NOT ❌ A price predictor ❌ A buy/sell signal generator ❌ A replacement for price action It is a decision-support tool designed to visualize direction, uncertainty, and historical confidence.
אינדיקטור Pine Script®
מאת ‎saksenarohit‎
RSI Primed [ChartPrime] with AlertRSI Primed with Alert Signal alert functionality added to the original version. Signal logic is as follows: 1. Uses EMA100 slope to filter trend direction 2. During EMA100 bullish trend, triggers oversold zone alert when RSI-MA turns in the oversold zone, consider buying the pullback; 3. During EMA100 bearish trend, triggers overbought zone alert when RSI-MA turns in the overbought zone, consider shorting the bounce; 4. Signal alerts are for reference only to improve chart monitoring efficiency. Not recommended for direct entry conditions - should be considered in conjunction with other factors. RSI Primed with Alert 在原版基础上增加信号警报功能，信号逻辑如下： 1. 使用EMA100的斜率来过滤趋势方向 2. EMA100多头趋势时，RSI-MA在超卖区拐头时发出超卖区警报，可以考虑回调做多； 3. EMA100空头趋势时，RSI-MA在超买区拐头时发出超买区警报，可以考虑反弹做空； 4. 信号警报仅作为提高盯盘效率的参考，不建议直接用于入场条件，需参考其他条件综合考虑。
אינדיקטור Pine Script®
מאת ‎barryzhang‎
Moving Average Momentum Bands📊 MA Momentum Bands - Crossover Detection with Predictive Signals Overview Advanced moving average system with intelligent crossover detection and early warning predictive signals. Designed to catch trend changes with precise timing while filtering out choppy market noise. Key Features 📈 4 Customizable Moving Averages Choose from EMA, SMA, SMMA (RMA), WMA, or VWMA Adjustable periods and colors Visual fill zones between MA pairs ✓ Confirmed Crossover Signals Fires on actual MA crossover with confirmation filters Slope Filter: Requires slow MA to be trending (filters choppy markets) Acceleration Filter: Detects momentum shifts and deceleration (catches reversals) Highly configurable thresholds for different trading styles ⚠ Predictive Signals (Optional) Early warning system fires 1-8 bars BEFORE actual crossover Velocity-based calculation estimates when crossover will occur Smart debouncing prevents signal spam (fires once per setup) Auto-resets after crossover or when prediction fails 🔍 Debug Table Real-time metrics: MA slope, acceleration, velocity, distance "Bars Until Cross" prediction countdown Perfect for fine-tuning settings How It Works Confirmed Signals (✓ triangles): Fast MA crosses Slow MA Slow MA must be trending (slope > threshold) OR decelerating Filters ensure quality signals in trending markets Predictive Signals (⚠ triangles): Calculates MA velocities (rate of change) Estimates bars until crossover based on approach speed Fires early warning when crossover imminent Only fires once per setup (no spam) Best Use Cases Swing Trading: Catch trend changes early with predictive signals Trend Following: Use confirmed signals for high-probability entries Multi-Timeframe: Combine with higher TF analysis for confirmation Filter for Other Strategies: Add MA crossover confirmation to your existing system Recommended Settings Conservative (Fewer, Higher Quality Signals): Slope Threshold: 0.002-0.005 Acceleration Filter: ON Predict Bars Ahead: 5-8 Balanced (Default): Slope Threshold: 0.001-0.002 Acceleration Filter: ON Predict Bars Ahead: 3-5 Aggressive (More Signals, Earlier Entries): Slope Threshold: 0.0001 Acceleration Filter: OFF Predict Bars Ahead: 1-3 Quick Start Add to chart - confirmed signals work immediately Adjust slope/acceleration filters to match your timeframe Enable predictive signals for early entries Use debug table to fine-tune settings Set up alerts for hands-free trading Alerts Included Bullish/Bearish MA Cross (confirmed) Predictive Bullish/Bearish Cross (early warning) Perfect for traders who want to catch trend changes early while avoiding false signals in choppy markets!
אינדיקטור Pine Script®
מאת ‎c_bergfeldt‎
Neural Probability Channel [AlgoPoint]The Neural Probability Channel (NPC) is a next-generation volatility and trend analysis tool designed to overcome the limitations of traditional bands (like Bollinger Bands) and smoothing filters (like standard Moving Averages). Unlike traditional indicators that rely on linear deviation or simple averages, the NPC utilizes a Rational Quadratic Kernel—a concept derived from machine learning regression models—to calculate a non-repainting, highly adaptive baseline (Fair Value). This allows the indicator to distinguish between market noise and genuine trend shifts with superior accuracy. The volatility bands are dynamically calculated using a hybrid of Standard Error (Mean Deviation) and ATR, ensuring the channels adapt organically to market conditions—expanding during high-impact moves and contracting during consolidation. How It Works - The Neural Baseline (Center Line): Instead of a standard Moving Average, the NPC uses a Rational Quadratic Kernel weighting system. This assigns "importance" to price data based on both recency and similarity. It acts as a "Center of Gravity" for price, providing a smoother yet responsive trend detection line without the lag associated with SMAs or EMAs. Crucially, the math is causal (no lookahead), meaning it does not repaint. - Adaptive Volatility Bands: The channel width is not fixed. It uses a Hybrid Volatility Model: - Inner Channel: Represents the "Probability Zone" (approx. 70% confidence). Price staying here indicates a stable trend. - Outer Channel: Represents "Extreme Deviation" (Statistical Anomalies). When price touches or breaches these outer bands, it is statistically overextended (Overbought/Oversold). Signal Generation: - Reversion Signals: Generated when price breaches the Outer Bands and closes back inside. This suggests a "Snap-back" or Mean Reversion event. - Trend Confirmation: The color of the baseline and the fill zones changes based on the slope of the Kernel, giving an instant visual read on market bias. How to Use It - Mean Reversion Strategy: Look for price action extending beyond the Outer Bands (Thinner lines). If price leaves a wick and closes back inside, it signals a high-probability reversal toward the Neural Baseline. - Green Signal: Potential Long (Reversal from Lows). - Red Signal: Potential Short (Reversal from Highs). - Trend Following: Use the Neural Baseline (Thick Center Line) as a dynamic support/resistance level. If price is holding above the baseline and the cloud is green, the trend is Bullish. If price is holding below the baseline and the cloud is red, the trend is Bearish. - Squeeze Detection: When the Inner and Outer bands compress significantly, it indicates low volatility and often precedes an explosive breakout. Settings - Lookback Window: Determines the depth of the Kernel analysis. - Smoothness (Bandwidth): Higher values create a smoother baseline (better for trends), while lower values make it more reactive (better for scalping). - Regression Alpha: Controls the weight distribution of the Kernel. - Channel Multipliers: Adjust the width of the Inner and Outer bands to fit your specific asset's volatility profile.
אינדיקטור Pine Script®
מאת ‎Iamalala‎
10
AI Heavy Buyer Scanner V6 - 100min to Close100 minutes before the end of daily trading, scan US-traded stocks and ETFs with a market cap > $50B and ETFs (including 3x leveraged). Locate Japanese candlesticks on an intraday chart where the following conditions are met: 1. The price has increased by at least 1% from the daily opening price. 2. The candlestick has a lower shadow that is at least 1% longer than the price. 3. The daily trading volume up to this time is 10% higher than the daily average of the last 100 days. Send an instant alert
אינדיקטור Pine Script®
מאת ‎Izik68‎
Session LinesSession Lines is an intraday indicator that marks global trading sessions and their key levels. It shows each session’s range, high, and low so traders can clearly see where price moved and which levels may matter next. It’s built for futures, forex, and index traders who use session structure and prior highs/lows as reference points. Draws a box around each session’s price range Fully customizable session names, times, timezones, and colors Supports up to three sessions (commonly Tokyo, London, and New York) Session Information (Optional) Session range displayed in ticks Average price for the session Session name label inside the box Session Open & Close Optional dashed lines marking session open and close Useful for tracking acceptance and rejection during the session Session High & Low Levels Live High / Low Tracking Tracks the session high and low as price develops Lines update in real time during the session Extended High / Low Lines After a session ends, its high and low can be extended forward Extension length is adjustable in days Helps identify common reaction and liquidity levels High / Low Labels Optional labels for each session’s high and low Can be shown live or only after the session finishes Adjustable text size and horizontal offset Intended Use Marking Asia, London, and New York ranges Watching reactions to prior session highs and lows Using session ranges as context for breakouts or reversals Keeping key intraday levels on the chart without manual drawing
אינדיקטור Pine Script®
מאת ‎charleyRT‎
Ehlers Adaptive Trend FilterEHLERS ADAPTIVE TREND FILTER | Lag-Compensated SuperSmoother Based on John Ehlers' "Smoothing The Data" (2014), this indicator extends the SuperSmoother with hybrid Butterworth filters and dynamic lag compensation. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ KEY FEATURES: ✓ 3 FILTER MODES (lag-measured empirically) • 2p+2p (Fast): 62 bars lag — responsive, great for scalping • 3p+2p (Hybrid): 70 bars lag — RECOMMENDED, best risk/reward • 3p+3p (Smooth): 88 bars lag — ultra-smooth for macro trends ✓ LAG-COMPENSATED MOMENTUM Automatically extends momentum lookback to account for filter delay. Keeps momentum signals responsive despite heavy smoothing. ✓ CONFIRMATION-BASED REVERSALS Requires 2+ bars confirmation before signaling reversals. ~60% fewer false signals than single-bar detection. Reduces whipsaws on volatile assets. ✓ VOLATILITY-ADAPTIVE THRESHOLDS Automatically scales all deviation levels based on asset volatility. Works seamlessly across: - Crypto (20%+ volatility) - Equities (10-15% volatility) - Forex (2-5% volatility) - Bonds (<2% volatility) ✓ MULTI-TIMEFRAME AUTO-CALIBRATION Automatically optimizes filter periods for your trading style: - Scalping (<1H): 2p+2p (Fast) - Swing Trading (1D): 3p+2p (Hybrid) ← Default - Position Trading (1W+): 3p+3p (Smooth) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ WHAT YOU GET IN THE DASHBOARD: • TREND STATUS: Good/Bad (signal above/below baseline) • MOMENTUM: Strong/Steady/Weak/Opposing (lag-compensated) • MOMENTUM TREND: Increasing/Decreasing/Stable • SUPPORT BASELINE: Bull Reversal/Bear Reversal/Aligned • SUPPORT SLOPE: Positive/Negative/Neutral (with %) • SAFETY MARGIN: % distance from baseline • PRICE DEVIATION: Extended/Expanding/On Course/Lagging • TECHNICAL RATING: Perfect/Transition/Dangerous/Critical • VOLATILITY: Live % + historical baseline • FILTER CONFIG: Active mode + exact lag metric • THRESHOLD LEVELS: Adaptive or Fixed mode • ANALYSIS MODE: Auto-calibrated or Manual ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ PERFORMANCE (Backtested 2020-2024): ES 1D (3p+2p Hybrid): ✓ 68% Win Rate | 2.2:1 Profit Factor ✓ 12% Max Drawdown | Avg Trade: +45 points BTC 4H (3p+2p Hybrid): ✓ 62% Win Rate | 1.9:1 Profit Factor ✓ 18% Max Drawdown | Avg Trade: +$280 EURUSD 1H (2p+2p Fast): ✓ 55% Win Rate | 1.7:1 Profit Factor ✓ 8% Max Drawdown | Avg Trade: +45 pips ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ HOW TO USE: 1. Add indicator to chart (any asset, any timeframe) 2. Select Filter Configuration: → 3p+2p (Hybrid) recommended for most traders 3. Read the dashboard (bottom-right table) 4. Trade signals: → ENTER: Trend Status = "Good" + Momentum = "Strong" → EXIT: Trend Status = "Bad" OR background highlight appears 5. Combine with your own trade plan (entries, sizing, risk management) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ WHY THIS INDICATOR? Most traders face a painful choice: → Fast MA (like EMA20): Responsive but too many false signals → Slow MA (like EMA100): Smooth but miss 20% of moves Ehlers SuperSmoother solves this using 40+ years of digital signal processing research. Butterworth filters preserve trend direction while removing high-frequency noise more efficiently than moving averages. The innovation: LAG COMPENSATION By measuring the exact delay of each filter and dynamically adjusting momentum lookback windows, you get BOTH clean trends AND responsive signals. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ TECHNICAL DETAILS: Filter Type: Ehlers 2-Pole & 3-Pole SuperSmoother (Butterworth) Lag Compensation: Empirically measured via step response Momentum Adjustment: 1.0x (2p+2p) / 1.15x (3p+2p) / 1.45x (3p+3p) Volatility Model: 75th percentile of rolling 252-day returns Reversal Confirmation: 2-bar minimum (reduces noise) Repainting: NO (Pine Script v6, confirmed bars only) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ DISCLAIMER: This indicator is for educational and analytical purposes only. NOT financial advice, investment recommendations, or profit guarantees. • Past performance does NOT guarantee future results • All trading involves risk, including loss of principal • Test extensively on historical data before live trading • "Safety" and "Risk" metrics measure technical deviation, NOT capital protection • Start with small position sizes and proper risk management ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ REFERENCE: Ehlers, J. (2014). "Smoothing The Data." Stocks & Commodities Magazine. Oppenheim & Schafer. "Discrete-Time Signal Processing" (3rd ed.)
אינדיקטור Pine Script®
מאת ‎TrendMatrix_Labs‎
Daily RVOL (Raw) SMA/EMA + Surge Marker - TP## Daily RVOL (Raw) SMA/EMA + Surge Marker (TP) This indicator helps you spot **unusual institutional-style participation** by measuring **Daily Relative Volume (RVOL)** and highlighting **sudden RVOL “surges”** compared to the prior day. ### What it shows **RVOL (raw)** is a ratio: **RVOL = Today’s Daily Volume ÷ Average Daily Volume (lookback)** * **1.00x** = normal volume * **1.50x** = ~50% above normal * **2.00x** = ~2x normal The “Average Daily Volume” baseline can be calculated using either: * **SMA** (simple average), or * **EMA** (faster-reacting average) The baseline uses **completed daily bars only**, so it won’t be distorted by a partially completed day. ### Surge Marker (Circle) The circle prints when **today’s RVOL jumps significantly vs yesterday’s RVOL**: **RVOL Surge % = (RVOL Today ÷ RVOL Prev − 1) × 100** So if your surge threshold is **80%**, the circle triggers when: **RVOL Today ≥ 1.80 × RVOL Prev** This is meant to detect **volume acceleration**—not just “high volume,” but a **step-change** in participation. ### How to use it (in plain English) Think of RVOL as a **crowd-size meter**, and the surge circle as a **“big money showed up today”** alert. It does **not** directly label buy vs sell—it highlights **participation**. Direction comes from price action and context. ### Bullish vs Bearish clues (price + volume together) Use the circle as a clue, then read the candle and key levels: **Potential bullish signs** * Breakout/reclaim of resistance + surge circle (strong confirmation) * Strong up day (wide range, closes near highs) + surge circle * **High volume down-close that *does NOT* break lower lows** (holds support) → Often means selling pressure was absorbed and price held the line. This can be a **bullish “support/absorption” tell**, especially if the next day confirms with strength. **Potential bearish signs** * Breakdown below support + surge circle (distribution confirmation) * Rejection at resistance on surge circle (supply showing up) * **High volume up-close that *fails to make higher highs* / can’t push through resistance** → Often suggests buying effort was met by strong supply (selling into strength). This can be a **bearish “stall/failure” tell**, especially if the next day confirms with weakness. ### Suggested settings * **RVOL Length:** 20 is a solid default * **SMA vs EMA:** * SMA = smoother baseline * EMA = reacts faster to recent volume changes * **Surge Threshold:** * **80–150%** = rare “shock” participation (fewer, stronger signals) * **40–80%** = balanced signals * **10–40%** = more signals, more noise ### Best practice Use RVOL + surge circles as **confirmation**, not a standalone entry/exit: * Combine with trend, support/resistance, and candle structure. * The surge circle says **“participation surged”**—price action tells you **whether it’s accumulation (support) or distribution (supply).** *(Educational use only. Not financial advice.)*
אינדיקטור Pine Script®
מאת ‎TradersPod‎
Vertical Event Lines - BTC Halving & Custom DatesThis indicator plots vertical lines and labels for Bitcoin halving dates and any custom events you define directly on the price chart. It is designed as a clean, lightweight event-timeline overlay so you can instantly see where key dates occur relative to price action. Main features Built-in Bitcoin halving dates (2012, 2016, 2020, 2024), plus 8 additional custom event slots with freely configurable date/time, name and color. Vertical lines are positioned using xloc.bar_time , ensuring each event is anchored to the exact timestamp in the chart’s timeframe and timezone. Past and current events: A label is created once, on the first bar that crosses the event time, and placed near the bar’s high for consistent readability across symbols and timeframes. Future events: A separate label is shown at the bottom of the chart, making future dates clearly visible even to the right of the last bar. These labels update only on the most recent bar to keep the script efficient. Flexible styling: Global controls for line width, line style and label size, with per-event color selection and optional per-event overrides of global width and style. How to use Add the script to any chart (BTC or other symbols). It works on all timeframes. Use the Global settings to configure default line style, line width and label appearance (size, orientation, text color). In each Event X section, enable the event and set: Date/time in YYYY-MM-DD HH:MM format Event name Color Optional custom width/style When scrolling through time: Events left of the last bar show a vertical line and a one-time label at the crossing bar. Events right of the last bar show a vertical line and a bottom label that remains visible in the future. This script is intended as a visual reference tool only . It does not generate trading signals, alerts or backtests.
אינדיקטור Pine Script®
מאת ‎oanstein‎
Timebender - Day SeparatorTimebender — NY Anchored Day Separator Many traders rely on broker-based day boundaries, which often do not align with New York time — the primary liquidity clock for FX and macro-driven markets. When the trading day is anchored incorrectly, it can distort the reading of weekly structure, session behavior, and intraday narrative. This script provides a clear and configurable way to anchor trading days to a user-defined timezone and visually separate them on the chart. What This Script Does Highlights individual trading days using background shading Draws vertical separators at the exact start of each shifted trading day Allows independent toggling of background highlights and separator lines Supports day-specific coloring so each trading day is immediately recognizable Enables manual timezone shifting so traders can align charts to New York regardless of broker feed What Makes It Different Most day separators rely strictly on exchange time. This script detects calendar transitions from a manually shifted timestamp, allowing traders to define their own day boundary. This is particularly useful for traders who anchor their analysis to New York time rather than broker session clocks. Combining optional background shading with precision separators also allows traders to switch between a macro view (highlighted days) and a minimal execution view (lines only) without loading multiple indicators. How It Works (High-Level) The script internally offsets the chart’s timestamp by the number of hours specified in the timezone setting. It then detects when a new calendar day begins from that adjusted time and renders the visual separator accordingly. Because the calculation is based on shifted time rather than exchange time, the indicator maintains consistent day structure across brokers. How To Use Set the timezone shift to match the session you anchor your analysis to. Example: New York is typically UTC-5 or UTC-4 during daylight saving time. Enable background highlighting for a broader structural view. Use vertical separators when a cleaner chart is preferred for execution. Customize colors to match your chart template. Who This Script Is For FX traders Session-based traders ICT-style market structure traders Traders using multiple brokers Anyone who wants consistent day boundaries across charts Notes This script is designed as a chart-organization utility. It does not generate trade signals or provide market predictions.
אינדיקטור Pine Script®
מאת ‎bon_appetrade‎
Deep AILibrary "Deeptest" Comprehensive quantitative backtesting library with 112+ metrics: Sharpe/Sortino ratios, drawdown analysis, Monte Carlo simulation, Walk-Forward Analysis, VaR/CVaR, benchmark comparison, and interactive table rendering for TradingView strategies @version 1.0.1 (01.01.2026) ============================================================================ CHANGELOG ============================================================================ v1.0.1 (01.01.2026) - Added textSize parameter to runDeeptest() for controlling table text size - New values: size.auto, size.small, size.tiny, size.normal, size.large - Applies to all tables: main, stress test, drawdowns, recoveries, trades v1.0.0 (31.12.2025) - Initial release - 112+ backtesting metrics - Monte Carlo simulation and Walk-Forward Analysis - Interactive table rendering with tooltips ============================================================================ TABLE OF CONTENTS ============================================================================ SECTION 1: File Header & Metadata SECTION 2: Constants & Configuration SECTION 3: Type Definitions SECTION 4: Core Calculation Functions - Array Utilities SECTION 5: Core Calculation Functions - Return Extraction SECTION 6: Core Calculation Functions - Sharpe & Sortino SECTION 7: Core Calculation Functions - Performance Metrics SECTION 8: Core Calculation Functions - Drawdown Analysis SECTION 9: Core Calculation Functions - Recovery Analysis SECTION 10: Core Calculation Functions - Trade Analysis SECTION 11: Core Calculation Functions - Statistical Distribution SECTION 12: Core Calculation Functions - Risk Metrics SECTION 13: Core Calculation Functions - Benchmark Comparison SECTION 14: Core Calculation Functions - Time-Based Metrics SECTION 15: Core Calculation Functions - Rolling Statistics SECTION 16: Core Calculation Functions - Strategy Integration SECTION 17: Core Calculation Functions - Walk Forward Analysis SECTION 18: Core Calculation Functions - Monte Carlo Simulation SECTION 19: Core Calculation Functions - Out-of-Sample Analysis SECTION 20: Formatting Utilities - Value Formatting SECTION 21: Formatting Utilities - Duration Formatting SECTION 22: Formatting Utilities - Frequency Formatting SECTION 23: Formatting Utilities - Date Formatting SECTION 24: Tooltip Builders - Main Table Metrics SECTION 25: Tooltip Builders - Complementary Metrics SECTION 26: Tooltip Builders - Stress Test Metrics SECTION 27: Tooltip Builders - Period Analysis Cards SECTION 28: Table Rendering - Structure Helpers SECTION 29: Table Rendering - Main Deeptest Table SECTION 30: Table Rendering - Cell Renderers - Complementary Row SECTION 31: Table Rendering - Stress Test Table SECTION 32: Table Rendering - Period Analysis Cards SECTION 33: Main Entry Point ============================================================================ API REFERENCE ============================================================================ Main Export: ------------ runDeeptest() - Complete backtest analysis orchestrator ============================================================================ KEY FEATURES ============================================================================ - Comprehensive backtesting metrics (112+ functions) - Rolling window analysis with statistical distributions - Advanced risk metrics (Sharpe, Sortino, Calmar, Martin, VaR, CVaR) - Drawdown and recovery analysis - Monte Carlo simulation and Walk-Forward Analysis - Trade analysis (top/worst trades, consecutive streaks) - Benchmark comparison (Alpha, Beta, R², Buy & Hold) - Interactive table rendering with tooltips ============================================================================ USAGE EXAMPLE ============================================================================ ╔══════════════════════════════════════════════════════════════════════════════╗ ║ PROGRESSIVE USAGE EXAMPLES ║ ╠══════════════════════════════════════════════════════════════════════════════╣ ║ Three examples demonstrating increasing complexity: ║ ║ 1. MINIMAL - "Hello World" with basic MA crossover ║ ║ 2. BALANCED - Production ready with risk management & filters ║ ║ 3. PROFESSIONAL - Full-featured with trailing stops & session filters ║ ╚══════════════════════════════════════════════════════════════════════════════╝ ╔══════════════════════════════════════════════════════════════════════════════╗ ║ EXAMPLE 1: MINIMAL (The "Hello World") ║ ╠══════════════════════════════════════════════════════════════════════════════╣ ║ The simplest possible integration - just 3 lines to get started: ║ ║ 1. Import the library ║ ║ 2. Write your strategy logic ║ ║ 3. Call runDeeptest() ║ ╚══════════════════════════════════════════════════════════════════════════════╝ //@version=6 strategy("MA Crossover ", overlay=true) // ═══════════════════════════════════════════════════════════════════════════ // ⮟ Import Deeptest (Direct import - no namespace prefix needed) // ═══════════════════════════════════════════════════════════════════════════ import Fractalyst/Deeptest/1 as * // ──────────────────────────────────────────────────────────────────────────── // Strategy Logic: Simple Moving Average Crossover // ──────────────────────────────────────────────────────────────────────────── fastMA = ta.sma(close, 10) // Fast MA: 10 periods slowMA = ta.sma(close, 30) // Slow MA: 30 periods // Plot MAs for visualization plot(fastMA, "Fast MA", color=color.blue) plot(slowMA, "Slow MA", color=color.orange) // Entry: Long when fast MA crosses above slow MA if ta.crossover(fastMA, slowMA) strategy.entry("Long", strategy.long) // Exit: Close when fast MA crosses below slow MA if ta.crossunder(fastMA, slowMA) strategy.close("Long") // ═══════════════════════════════════════════════════════════════════════════ // ⮟ Run backtest analysis (all parameters use smart defaults) // ═══════════════════════════════════════════════════════════════════════════ DT.runDeeptest() ╔══════════════════════════════════════════════════════════════════════════════╗ ║ EXAMPLE 2: BALANCED (Production Ready) ║ ╠══════════════════════════════════════════════════════════════════════════════╣ ║ Adds essential production features: ║ ║ • User-configurable inputs ║ ║ • ADX trend filter to avoid choppy markets ║ ║ • Stop loss / Take profit for risk management ║ ║ • Custom backtest parameters ║ ╚══════════════════════════════════════════════════════════════════════════════╝ //@version=6 strategy("MA Crossover ", overlay=true) import Fractalyst/Deeptest/1 as * // ──────────────────────────────────────────────────────────────────────────── // INPUT PARAMETERS // ──────────────────────────────────────────────────────────────────────────── fastLen = input.int(10, "Fast MA Period", minval=1) slowLen = input.int(30, "Slow MA Period", minval=1) riskPct = input.float(2.0, "Risk %", minval=0.1) / 100 slPct = input.float(5.0, "Stop Loss %", minval=0.1) / 100 tpPct = input.float(10.0, "Take Profit %", minval=0.1) / 100 adxThresh = input.int(20, "ADX Trend Threshold") // ──────────────────────────────────────────────────────────────────────────── // INDICATORS // ──────────────────────────────────────────────────────────────────────────── fastMA = ta.sma(close, fastLen) slowMA = ta.sma(close, slowLen) adx = ta.adx(14) = ta.dmi(14, 14) // ──────────────────────────────────────────────────────────────────────────── // FILTERS // ──────────────────────────────────────────────────────────────────────────── trendConfirmed = adx > adxThresh and diPlus > diMinus // ──────────────────────────────────────────────────────────────────────────── // STRATEGY LOGIC // ──────────────────────────────────────────────────────────────────────────── // Entry: MA crossover + trend confirmation if ta.crossover(fastMA, slowMA) and trendConfirmed strategy.entry("Long", strategy.long) // Exit: MA crossunder if ta.crossunder(fastMA, slowMA) strategy.close("Long") // Risk management: Stop loss and take profit if strategy.position_size > 0 strategy.exit("RM", "Long", stop=strategy.position_avg_price * (1 - slPct), limit=strategy.position_avg_price * (1 + tpPct)) // ═══════════════════════════════════════════════════════════════════════════ // ⮟ Run backtest with custom parameters // ═══════════════════════════════════════════════════════════════════════════ DT.runDeeptest( riskPerTrade = 1.0, // ← 1% risk per trade targetMaxDDPct = 15.0, // ← 15% max drawdown target showStressTest = true, // ← Enable stress test table showPeriodCards = true, // ← Enable period cards wfaWindows = 12, // ← Walk-forward windows mcSimulations = 1000, // ← Monte Carlo runs bullColor = color.new(#00b9ff, 0), bearColor = color.new(#ff0051, 0), benchmarkSymbol = "SPX", // ← Compare to S&P; 500 periodCardMode = "drawdowns", // ← Show drawdown periods tradeSortBy = "return" // ← Sort by return % ) ╔══════════════════════════════════════════════════════════════════════════════╗ ║ EXAMPLE 3: PROFESSIONAL (Full-Featured) ║ ╠══════════════════════════════════════════════════════════════════════════════╣ ║ Complete professional implementation: ║ ║ • Organized input groups for better UX ║ ║ • Multiple filters: ADX trend, ATR volatility, Session timing ║ ║ • Trailing stop to lock in profits ║ ║ • Position highlighting for visual feedback ║ ║ • Full parameter customization with inline documentation ║ ╚══════════════════════════════════════════════════════════════════════════════╝ //@version=6 runDeeptest(targetMaxDDPct, bullColor, bearColor, tableBg, headerBg, borderColor, textPrimary, textMuted, textSize, showComplementaryRow, showStressTestTable, showDrawdownRecoveryCards, showTradeCards)   Parameters:      targetMaxDDPct (float)      bullColor (color)      bearColor (color)      tableBg (color)      headerBg (color)      borderColor (color)      textPrimary (color)      textMuted (color)      textSize (string)      showComplementaryRow (bool)      showStressTestTable (bool)      showDrawdownRecoveryCards (bool)      showTradeCards (bool) ThresholdConfig   ThresholdConfig - Configuration for metric thresholds and corresponding colors   Fields:      sharpeExc (series float)      sharpeGood (series float)      sharpeOk (series float)      sharpeBear (series color)      sharpeNeutral (series color)      sharpeOrange (series color)      sharpeBull (series color)      ddSevere (series float)      ddMod (series float)      ddMild (series float)      ddSevereColor (series color)      ddModColor (series color)      ddOrange (series color)      ddGoodColor (series color)      rorHigh (series float)      rorMod (series float)      rorLow (series float)      rorHighColor (series color)      rorModColor (series color)      rorOrange (series color)      rorLowColor (series color)      r2Poor (series float)      r2Mod (series float)      r2Good (series float)      r2PoorColor (series color)      r2ModColor (series color)      r2Orange (series color)      r2GoodColor (series color)      kurtHigh (series float)      kurtMod (series float)      kurtOk (series float)      kurtHighColor (series color)      kurtModColor (series color)      kurtOrange (series color)      kurtGoodColor (series color)      skewVNeg (series float)      skewModNeg (series float)      skewPos (series float)      skewVPos (series float)      skewVNegColor (series color)      skewModNegColor (series color)      skewNeutral (series color)      skewPosColor (series color)      payoffPoor (series float)      payoffBE (series float)      payoffGood (series float)      payoffPoorColor (series color)      payoffBEColor (series color)      payoffOrange (series color)      payoffGoodColor (series color)      pfPoor (series float)      pfBE (series float)      pfGood (series float)      pfPoorColor (series color)      pfBEColor (series color)      pfOrange (series color)      pfGoodColor (series color)      ulcerHigh (series float)      ulcerLow (series float)      ulcerHighColor (series color)      ulcerModColor (series color)      ulcerOrange (series color)      ulcerLowColor (series color)      wrLow (series float)      wrOk (series float)      wrHigh (series float)      wrLowColor (series color)      wrOkColor (series color)      wrOrange (series color)      wrHighColor (series color)      cagrPoor (series float)      cagrOk (series float)      cagrGood (series float)      cagrPoorColor (series color)      cagrOkColor (series color)      cagrOrange (series color)      cagrGoodColor (series color)      pInsig (series float)      pMod (series float)      pSig (series float)      pInsigColor (series color)      pModColor (series color)      pOrange (series color)      pSigColor (series color)      calmarPoor (series float)      calmarBE (series float)      calmarGood (series float)      calmarPoorColor (series color)      calmarBEColor (series color)      calmarOrange (series color)      calmarGoodColor (series color)      betaHigh (series float)      betaLow (series float)      betaHighColor (series color)      betaLowColor (series color)      betaGoodColor (series color) Stats   Stats - Comprehensive backtest statistics container   Fields:      totalTrades (series int)      winTrades (series int)      lossTrades (series int)      evenTrades (series int)      winRate (series float)      lossRate (series float)      avgWinPct (series float)      avgLossPct (series float)      avgTradePct (series float)      profitFactor (series float)      payoffRatio (series float)      expectancy (series float)      grossProfit (series float)      grossLoss (series float)      netProfit (series float)      netProfitPct (series float)      compEffect (series float)      sharpe (series float)      sortino (series float)      calmar (series float)      martin (series float)      maxDrawdown (series float)      maxDrawdownPct (series float)      currentDrawdown (series float)      currentDrawdownPct (series float)      avgDrawdownPct (series float)      maxEquity (series float)      minEquity (series float)      cagr (series float)      monthlyReturn (series float)      maxConsecWins (series int)      maxConsecLosses (series int)      avgTradeDuration (series float)      avgWinDuration (series float)      avgLossDuration (series float)      timeInMarketPct (series float)      tradesPerMonth (series float)      tradesPerYear (series float)      skewness (series float)      kurtosis (series float)      var95 (series float)      cvar95 (series float)      ulcerIndex (series float)      riskOfRuin (series float)      pValue (series float)      zScore (series float)      alpha (series float)      beta (series float)      buyHoldReturn (series float)      equityRSquared (series float)      firstTradeTime (series int)      lastTradeTime (series int)      tradingPeriodDays (series float) RollingWindowSummary   RollingWindowSummary - Summary of metrics for a single rolling analysis window   Fields:      windowIndex (series int)      startTrade (series int)      endTrade (series int)      effectiveCount (series int)      minValue (series float)      maxValue (series float)      metricValue (series float) RollingStats   RollingStats - Statistical distribution of rolling window metrics   Fields:      windowSize (series int) : Number of trades in rolling window      expectancyMin (series float) : Minimum rolling expectancy      expectancyMax (series float) : Maximum rolling expectancy      sharpeMin (series float) : Minimum rolling Sharpe      sharpeMax (series float) : Maximum rolling Sharpe      sortinoMin (series float) : Minimum rolling Sortino      sortinoMax (series float) : Maximum rolling Sortino      expectancyWindows (array) : Per-window summaries for expectancy      sharpeWindows (array) : Per-window summaries for Sharpe      sortinoWindows (array) : Per-window summaries for Sortino      expectancyMean (series float) : Mean expectancy across rolling windows      expectancyStdDev (series float) : Standard deviation of expectancy      expectancyPct90 (series float) : 90th percentile expectancy      expectancyPct50 (series float) : 50th percentile expectancy (median)      expectancyPct10 (series float) : 10th percentile expectancy      sharpeMean (series float) : Mean Sharpe across rolling windows      sharpeStdDev (series float) : Standard deviation of Sharpe      sharpePct90 (series float) : 90th percentile Sharpe      sharpePct50 (series float) : 50th percentile Sharpe      sharpePct10 (series float) : 10th percentile Sharpe      sortinoMean (series float) : Mean Sortino across rolling windows      sortinoStdDev (series float) : Standard deviation of Sortino      sortinoPct90 (series float) : 90th percentile Sortino      sortinoPct50 (series float) : 50th percentile Sortino      sortinoPct10 (series float) : 10th percentile Sortino
ספריית Pine Script®
מאת ‎DeepEx_Paradigma‎
USDT + USDC DominanceUSDT + USDC Dominance USDT/USDC Dominance Indicator This indicator measures the relative dominance of USDT and USDC on the market. It calculates the share of each stablecoin compared to the total of the two, and displays it as a percentage. USDT Dominance (%) = (USDT value / (USDT value + USDC value)) × 100 USDC Dominance (%) = 100 − USDT Dominance The indicator plots both dominance values on the chart, allowing you to see which stablecoin has a higher share at any given time. It can help identify shifts in market preference between USDT and USDC. Optional features: Horizontal 50% line for reference. Highlight when USDT or USDC exceeds 50% dominance. Works with price or market capitalization data depending on available data sources.
אינדיקטור Pine Script®
מאת ‎axisbhp‎
Simple Trend + Signal (No Bug)//@version=5indicator("Simple Trend + Signal (No Bug)", overlay=true) // === INPUTS ===fastEMA = input.int(20, "Fast EMA")slowEMA = input.int(50, "Slow EMA")lookback = input.int(20, "Zone Lookback") // === TREND ===emaFast = ta.ema(close, fastEMA)emaSlow = ta.ema(close, slowEMA) trendUp = emaFast > emaSlowtrendDown = emaFast < emaSlow // === ZONES ===highestHigh = ta.highest(high, lookback)lowestLow = ta.lowest(low, lookback) // === SIGNALS ===buySignal = trendUp and close <= emaFastsellSignal = trendDown and close >= emaFast // === PLOTS ===plot(emaFast, color=color.green, linewidth=2)plot(emaSlow, color=color.red, linewidth=2) plot(highestHigh, color=color.new(color.blue, 70))plot(lowestLow, color=color.new(color.orange, 70)) plotshape(buySignal, title="BUY", location=location.belowbar, color=color.green, style=shape.labelup, text="BUY")plotshape(sellSignal, title="SELL", location=location.abovebar, color=color.red, style=shape.labeldown, text="SELL")
אינדיקטור Pine Script®
מאת ‎blissfulAccoun8911‎