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ML-Enhanced Multi-Indicator Composite Signal🤖 ML-Enhanced Multi-Indicator Composite Signal Revolutionary AI-Powered Trading Indicator with Adaptive Learning Transform your trading with cutting-edge machine learning technology that automatically optimizes indicator weights based on real market performance! 🎯 What Makes This Indicator Special? This isn't just another composite indicator. It's an intelligent trading system that learns from market data and continuously adapts to improve signal accuracy. Unlike static indicators with fixed weights, this AI-powered tool dynamically adjusts the importance of each technical indicator based on their actual prediction success rates. ⚡ Key Features 🤖 Adaptive Machine Learning Engine Automatically tracks prediction accuracy for each indicator Dynamically adjusts weights based on performance Continuous learning and adaptation to market conditions Configurable learning parameters for fine-tuning 📊 Multi-Indicator Fusion SuperTrend: Trend direction and momentum Moving Averages: Price trend confirmation (SMA/EMA/WMA/RMA) VWAP: Volume-weighted price levels Linear Regression: Mathematical trend analysis 🎯 Intelligent Signal Generation Strong Buy/Buy/Sell/Strong Sell signals Configurable threshold levels Signal smoothing to reduce noise Smart signal timing to avoid repetitive alerts 📈 Performance Analytics Dashboard Real-time accuracy tracking for each indicator Weight distribution visualization ML vs. Equal weights comparison Learning progress monitoring 🚀 How It Works 1. Data Collection Phase The indicator continuously monitors the performance of each technical component, storing predictions and actual market outcomes. 2. Learning Phase Using configurable learning periods (20-500 bars), the ML engine calculates accuracy rates for each indicator's predictions. 3. Weight Optimization Based on performance data, the system automatically adjusts weights using a configurable learning rate, ensuring better-performing indicators have more influence. 4. Signal Generation The optimized composite signal triggers buy/sell alerts when crossing predefined thresholds, with visual signals and background coloring. ⚙️ Customization Options Machine Learning Parameters Learning Period: 20-500 bars (default: 100) Prediction Horizon: 1-20 bars (default: 5) Learning Rate: 0.01-1.0 (default: 0.1) Minimum Weight: Prevents any indicator from becoming irrelevant Performance Smoothing: Reduces noise in accuracy calculations Traditional Settings SuperTrend: Period and multiplier adjustment Moving Average: Type selection and length VWAP: Source customization Linear Regression: Length and source options Signal Configuration Threshold Levels: Customizable buy/sell trigger points Signal Smoothing: Reduces false signals Manual Override: Option to use fixed weights instead of ML 📱 Visual Features Signal Line Display Dynamic color coding based on signal strength Threshold level lines for clear entry/exit points Background coloring for quick market sentiment assessment Performance Table Real-time accuracy metrics for each indicator Current weight distribution showing ML optimization Performance comparison between ML and equal weights Learning progress indicator Signal Shapes 🚀 Strong Buy: Large green triangle with text 📈 Buy: Standard green triangle 📉 Sell: Standard red triangle 💥 Strong Sell: Large red triangle with text 🎓 Best Practices & Usage Tips For Beginners Start with default ML settings Allow 100+ bars for proper learning Focus on Strong Buy/Sell signals initially Monitor the performance table to understand ML adaptation For Advanced Traders Adjust learning rate based on market volatility Customize prediction horizon for your trading timeframe Fine-tune threshold levels for your risk tolerance Combine with additional confirmation indicators Recommended Settings by Timeframe Scalping (1m-5m): Learning Period: 50, Prediction Horizon: 3 Day Trading (15m-1h): Learning Period: 100, Prediction Horizon: 5 Swing Trading (4h-1D): Learning Period: 200, Prediction Horizon: 10 🔔 Alert System Set up comprehensive alerts for: Strong Buy/Sell signals with maximum consensus Regular Buy/Sell signals for standard entries Custom message templates with price and signal strength Email, SMS, and webhook compatibility ⚠️ Important Notes Learning Period: Allow sufficient data for ML optimization (minimum 50 bars recommended) Market Conditions: Performance may vary during high volatility or trending vs. ranging markets Backtesting: Test thoroughly on historical data before live trading Risk Management: Always use proper position sizing and stop losses 🏆 Why Choose This Indicator? ✅ Adaptive Intelligence: Unlike static indicators, this tool evolves with market conditions ✅ Transparent Performance: See exactly how well each component is performing ✅ Comprehensive Analytics: Make informed decisions with detailed performance metrics ✅ Professional Grade: Developed by experienced traders for serious market participants ✅ Continuous Innovation: Regular updates and improvements based on user feedback 📊 Performance Tracking The indicator provides unprecedented transparency into its decision-making process: Individual indicator accuracy rates Weight evolution over time Improvement metrics vs. baseline Learning curve visualization Transform your trading with the power of adaptive machine learning. Let the market data guide your strategy optimization automatically! Tags: Machine Learning, AI Trading, Composite Signal, Multi-Indicator, Adaptive Algorithm, Signal Generation, Trading Automation, Technical Analysis Category: Trend Following, Oscillators, Signal Generators
Индикатор Pine Script®
от QuantCreative
435
BNF 25/50 MA Pullback Screener (Uptrend-Below / Downtrend-Above)Buy candidates: stocks in an uptrend (25MA > 50MA, optional rising slopes) that are currently pulled back below the MAs. • Sell/short candidates: stocks in a downtrend (25MA < 50MA, optional falling slopes) that are currently pushed above the MAs. It plots the MAs, paints the background for trend context, drops signals on the chart, shows a status panel, and exposes alert conditions so you can screen your watchlist via alerts.
Индикатор Pine Script®
от jackson_g_sheehan
RSI ROC Signals with Price Action# RSI ROC Signals with Price Action ## Overview The RSI ROC (Rate of Change) Signals indicator is an advanced momentum-based trading system that combines RSI velocity analysis with price action confirmation to generate high-probability buy and sell signals. This indicator goes beyond traditional RSI analysis by measuring the speed of RSI changes and requiring price confirmation before triggering signals. ## Core Concept: RSI Rate of Change (ROC) ### What is RSI ROC? RSI ROC measures the **velocity** or **acceleration** of the RSI indicator, providing insights into momentum shifts before they become apparent in traditional RSI readings. **Formula**: `RSI ROC = ((Current RSI - Previous RSI) / Previous RSI) × 100` ### Why RSI ROC is Superior to Standard RSI: 1. **Early Momentum Detection**: Identifies momentum shifts before RSI reaches traditional overbought/oversold levels 2. **Velocity Analysis**: Measures the speed of momentum changes, not just absolute levels 3. **Reduced False Signals**: Filters out weak momentum moves that don't sustain 4. **Dynamic Thresholds**: Adapts to market volatility rather than using fixed RSI levels 5. **Leading Indicator**: Provides earlier signals compared to traditional RSI crossovers ## Signal Generation Logic ### 🟢 Buy Signal Process (3-Stage System): #### Stage 1: Trigger Activation - **RSI ROC** > threshold (default 7%) - RSI accelerating upward - **Price ROC** > 0 - Price moving higher - Records the **trigger high** (highest point during trigger) #### Stage 2: Invalidation Check - Signal invalidated if **RSI ROC** drops below negative threshold - Prevents false signals during momentum reversals #### Stage 3: Confirmation - **Price breaks above trigger high** - Price action confirmation - **Current candle is green** (close > open) - Bullish price action - **State alternation** - Ensures no consecutive duplicate signals ### 🔴 Sell Signal Process (3-Stage System): #### Stage 1: Trigger Activation - **RSI ROC** < negative threshold (default -7%) - RSI accelerating downward - **Price ROC** < 0 - Price moving lower - Records the **trigger low** (lowest point during trigger) #### Stage 2: Invalidation Check - Signal invalidated if **RSI ROC** rises above positive threshold - Prevents false signals during momentum reversals #### Stage 3: Confirmation - **Price breaks below trigger low** - Price action confirmation - **Current candle is red** (close < open) - Bearish price action - **State alternation** - Ensures no consecutive duplicate signals ## Key Features ### 🎯 **Smart Signal Management** - **State Alternation**: Prevents signal clustering by alternating between buy/sell states - **Trigger Invalidation**: Automatically cancels weak signals that lose momentum - **Price Confirmation**: Requires actual price breakouts, not just momentum shifts - **No Repainting**: Signals are confirmed and won't disappear or change ### ⚙️ **Customizable Parameters** #### **RSI Length (Default: 14)** - Standard RSI calculation period - Shorter periods = more sensitive to price changes - Longer periods = smoother, less noisy signals #### **Lookback Period (Default: 1)** - Period for ROC calculations - 1 = compares to previous bar (most responsive) - Higher values = smoother momentum detection #### **RSI ROC Threshold (Default: 7%)** - Minimum RSI velocity required for signal trigger - Lower values = more signals, potentially more noise - Higher values = fewer but higher-quality signals ### 📊 **Visual Signals** - **Green Arrow Up**: Buy signal below price bar - **Red Arrow Down**: Sell signal above price bar - **Clean Chart**: No additional lines or oscillators cluttering the view - **Size Options**: Customizable arrow sizes for visibility preferences ## Advantages Over Traditional Indicators ### vs. Standard RSI: ✅ **Earlier Signals**: Detects momentum changes before RSI reaches extremes ✅ **Dynamic Thresholds**: Adapts to market conditions vs. fixed 30/70 levels ✅ **Velocity Focus**: Measures momentum speed, not just position ✅ **Better Timing**: Combines momentum with price action confirmation ### vs. Moving Average Crossovers: ✅ **Leading vs. Lagging**: RSI ROC is forward-looking vs. backward-looking MAs ✅ **Volatility Adaptive**: Automatically adjusts to market volatility ✅ **Fewer Whipsaws**: Built-in invalidation logic reduces false signals ✅ **Momentum Focus**: Captures acceleration, not just direction changes ### vs. MACD: ✅ **Price-Normalized**: RSI ROC works consistently across different price ranges ✅ **Simpler Logic**: Clear trigger/confirmation process vs. complex crossovers ✅ **Built-in Filters**: Automatic signal quality control ✅ **State Management**: Prevents over-trading through alternation logic ## Trading Applications ### 📈 **Trend Following** - Use in trending markets to catch momentum continuations - Combine with trend filters for directional bias - Excellent for breakout strategies ### 🔄 **Swing Trading** - Ideal timeframes: 4H, Daily, Weekly - Captures major momentum shifts - Perfect for position entries/exits ### ⚡ **Scalping (Advanced Users)** - Lower timeframes: 1m, 5m, 15m - Reduce threshold for more frequent signals - Combine with volume confirmation ### 🎯 **Momentum Strategies** - Perfect for momentum-based trading systems - Identifies acceleration phases in trends - Complements breakout and continuation patterns ## Optimization Guidelines ### **Conservative Settings (Lower Risk)** - RSI Length: 21 - ROC Threshold: 10% - Lookback: 2 ### **Standard Settings (Balanced)** - RSI Length: 14 (default) - ROC Threshold: 7% (default) - Lookback: 1 (default) ### **Aggressive Settings (Higher Frequency)** - RSI Length: 7 - ROC Threshold: 5% - Lookback: 1 ## Best Practices ### 🎯 **Entry Strategy** 1. Wait for signal arrow confirmation 2. Consider market context (trend, support/resistance) 3. Use proper position sizing based on volatility 4. Set stop-loss below/above trigger levels ### 🛡️ **Risk Management** 1. **Stop Loss**: Place beyond trigger high/low levels 2. **Position Sizing**: Use 1-2% risk per trade 3. **Market Context**: Avoid counter-trend signals in strong trends 4. **Time Filters**: Consider avoiding signals near major news events ### 📊 **Backtesting Recommendations** 1. Test on multiple timeframes and instruments 2. Analyze win rate vs. average win/loss ratio 3. Consider transaction costs in backtesting 4. Optimize threshold values for different market conditions ## Technical Specifications - **Pine Script Version**: v6 - **Signal Type**: Non-repainting, confirmed signals - **Calculation Basis**: RSI velocity with price action confirmation - **Update Frequency**: Real-time on bar close - **Memory Management**: Efficient state tracking with minimal resource usage ## Ideal For: - **Momentum Traders**: Captures acceleration phases - **Swing Traders**: Medium-term position entries/exits - **Breakout Traders**: Confirms momentum behind breakouts - **System Traders**: Mechanical signal generation with clear rules This indicator represents a significant evolution in momentum analysis, combining the reliability of RSI with the precision of rate-of-change analysis and the confirmation of price action. It's designed for traders who want sophisticated momentum detection with built-in quality controls.
Индикатор Pine Script®
от padavans
Power Law Divergence in % - For Bitcoin Only_JPBitcoin Power Law Divergence The Bitcoin Power Law Divergence is a representation of Bitcoin prices first proposed by Giovanni Santostasi, Ph.D. It plots BTCUSD daily closes on a log10-log10 scale, and fits a linear regression channel to the data. This channel helps traders visualise when the price is historically in a zone prone to tops or located within a discounted zone subject to future growth. Giovanni Santostasi, Ph.D. originated the Bitcoin Power-Law Theory; this implementation places it directly on a TradingView chart. The white line shows the daily closing price, while the cyan line is the best-fit regression. A channel is constructed from the linear fit root mean squared error (RMSE), we can observe how price has repeatedly oscillated between each channel areas through every bull-bear cycle. DETAILS One of the advantages of the Power Law Theory proposed by Giovanni Santostasi is its ability to explain multiple behaviors of Bitcoin. We describe some key points below. Power-Law Overview A power law has the form y = A·xⁿ, and Bitcoin’s key variables follow this pattern across many orders of magnitude. Empirically, price rises roughly with t⁶, hash-rate with t¹² and the number of active addresses with t³. When we plot these on log-log axes they appear as straight lines, revealing a scale-invariant system whose behaviour repeats proportionally as it grows.
Индикатор Pine Script®
от Sahebson
Adaptive Heikin Ashi [CHE]Adaptive Heikin Ashi — volatility-aware HA with fewer fake flips Summary Adaptive Heikin Ashi is a volatility-aware reinterpretation of classic Heikin Ashi that continuously adjusts its internal smoothing based on the current ATR regime, which means that in quiet markets the indicator reacts more quickly to genuine directional changes, while in turbulent phases it deliberately increases its smoothing to suppress jitter and color whipsaws, thereby reducing “noise” and cutting down on fake flips without resorting to heavy fixed smoothing that would lag everywhere. Motivation: why adapt at all? Classic Heikin Ashi replaces raw OHLC candles with a smoothed construction that averages price and blends each new candle with the previous HA state, which typically cleans up trends and improves visual coherence, yet its fixed smoothing amount treats calm and violent markets the same, leading to the usual dilemma where a setting that looks crisp in a narrow range becomes too nervous in a spike, and a setting that tames high volatility feels unnecessarily sluggish as soon as conditions normalize; by allowing the smoothing weight to expand and contract with volatility, Adaptive HA aims to keep candles readable across shifting regimes without constant manual retuning. What is different from normal Heikin Ashi? Fixed vs. adaptive blend: Classic HA implicitly uses a fixed 50/50 blend for the open update (`HA_open_t = 0.5 HA_open_{t-1} + 0.5 HA_close_{t-1}`), while this script replaces the constant 0.5 with a dynamic weight `w_t` that oscillates around 0.5 as a function of observed volatility, which turns the open update into an EMA-like filter whose “alpha” automatically changes with market conditions. Volatility as the steering signal: The script measures volatility via ATR and compares it to a rolling baseline (SMA of ATR over the same length), producing a normalized deviation that is scaled by sensitivity, clamped to ±1 for stability, and then mapped to a bounded weight interval ` `, so the adaptation is strong enough to matter but never runs away. Outcome that matters to traders: In high volatility, the weight shifts upward toward the prior HA open, which strengthens smoothing exactly where classic HA tends to “chatter,” while in low volatility the weight shifts downward toward the most recent HA close, which speeds up reaction so quiet trends do not feel artificially delayed; this is the practical mechanism by which noise and fake signals are reduced without accepting blanket lag. How it works 1. HA close matches classic HA: `HA_close_t = (Open_t + High_t + Low_t + Close_t) / 4` 2. Volatility normalization: `ATR_t` is computed over `atr_length`, its baseline is `ATR_SMA_t = SMA(ATR, atr_length)`, and the raw deviation is `(ATR_t / ATR_SMA_t − 1)`, which is then scaled by `adapt_sensitivity` and clamped to ` ` to obtain `v_t`, ensuring that pathological spikes cannot destabilize the weighting. 3. Adaptive weight around 0.5: `w_t = 0.5 + oscillation_range v_t`, giving `w_t ∈ `, so with a default `range = 0.20` the weight stays between 0.30 and 0.70, which is wide enough to matter but narrow enough to preserve HA identity. 4. EMA-like open update: On the very first bar the open is seeded from a stable combination of the raw open and close, and thereafter the update is `HA_open_t = w_t HA_open_{t−1} + (1 − w_t) HA_close_{t−1}`, which is equivalent to an EMA where higher `w_t` means heavier inertia (more smoothing) and lower `w_t` means stronger pull to the latest price information (more responsiveness). 5. High and low follow classic HA composition: `HA_high_t = max(High_t, max(HA_open_t, HA_close_t))`, `HA_low_t = min(Low_t, min(HA_open_t, HA_close_t))`, thereby keeping visual semantics consistent with standard HA so that your existing reading of bodies, wicks, and transitions still applies. Why this reduces noise and fake signals in practice Fake flips in HA typically occur when a fixed blending rule is forced to process candles during a volatility surge, producing rapid alternations around pivots or within wide intrabar ranges; by increasing smoothing exactly when ATR jumps relative to its baseline, the adaptive open stabilizes the candle body progression and suppresses transient color changes, while in the opposite scenario of compressed ranges, the reduced smoothing allows small but persistent directional pressure to reflect in candle color earlier, which reduces the tendency to enter late after multiple slow transitions. Parameter guide (what each input really does) ATR Length (default 14): controls both the ATR and its baseline window, where longer values dampen the adaptation by making the baseline slower and the deviation smaller, which is helpful for noisy lower timeframes, while shorter values make the regime detector more reactive. Oscillation Range (default 0.20): sets the maximum distance from 0.5 that the weight may travel, so increasing it towards 0.25–0.30 yields stronger smoothing in turbulence and faster response in calm periods, whereas decreasing it to 0.10–0.15 keeps the behavior closer to classical HA and is useful if your strategy already includes heavy downstream smoothing. Adapt Sensitivity (default 6.0): multiplies the normalized ATR deviation before clamping, such that higher sensitivity accelerates adaptation to regime shifts, while lower sensitivity produces gradual transitions; negative values intentionally invert the mapping (higher vol → less smoothing) and are generally not recommended unless you are testing a counter-intuitive hypothesis. Reading the candles and the optional diagnostic You interpret colors and bodies just like with normal HA, but you can additionally enable the Adaptive Weight diagnostic plot to see the regime in real time, where values drifting up toward the upper bound indicate a turbulent context that is being deliberately smoothed, and values gliding down toward the lower bound indicate a calm environment in which the indicator chooses to move faster, which can be valuable for discretionary confirmation when deciding whether a fresh color shift is likely to stick. Practical workflows and combinations Trend-following entries: use color continuity and body expansion as usual, but expect fewer spurious alternations around news spikes or into liquidity gaps; pairing with structure (swing highs/lows, breaks of internal ranges) keeps entries disciplined. Exit management: when the diagnostic weight remains elevated for an extended period, you can be stricter with exit triggers because flips are less likely to be accidental noise; conversely, when the weight is depressed, consider earlier partials since the indicator is intentionally more nimble. Multi-asset, multi-TF: the adaptation is especially helpful if you rotate instruments with very different vol profiles or hop across timeframes, since you will not need to retune a fixed smoothing parameter every time conditions change. Behavior, constraints, and performance The script does not repaint historical bars and uses only past information on closed candles, yet just like any candle-based visualization the current live bar will update until it closes, so you should avoid acting on mid-bar flips without a rule that accounts for bar close; there are no `security()` calls or higher-timeframe lookups, which keeps performance light and execution deterministic, and the clamping of the volatility signal ensures numerical stability even during extreme ATR spikes. Sensible defaults and quick tuning Start with the defaults (`ATR 14`, `Range 0.20`, `Sensitivity 6.0`) and observe the weight plot across a few volatile events; if you still see too many flips in turbulence, either raise `Range` to 0.25 or trim `Sensitivity` to 4–5 so that the weight can move high but does not overreact, and if the indicator feels too slow in quiet markets, lower `Range` toward 0.15 or raise `Sensitivity` to 7–8 to bias the weight a bit more aggressively downward when conditions compress. What this indicator is—and is not Adaptive Heikin Ashi is a context-aware visualization layer that improves the signal-to-noise ratio and reduces fake flips by modulating smoothing with volatility, but it is not a complete trading system, it does not predict the future, and it should be combined with structure, risk controls, and position management that fit your market and timeframe; always forward-test on your instruments, and remember that even adaptive smoothing can delay recognition at sharp turning points when volatility remains elevated. Disclaimer The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context. Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved. By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk. Best regards and happy trading Chervolino
Индикатор Pine Script®
от chervolino
1
Synthesis DeFi - Fractals - Daily - v7.0This is a free trial version of SynthesisDeFi.com fractals. A simplified fractal analysis indicator that identifies key market structure points on daily timeframes. This tool automatically detects trend reversals and plots fractal highs and lows with connecting lines, helping traders visualize major support and resistance levels Why use Synthesis DeFi fractals? Harmonic Patterns Wycoff Elliot Waves Dow Theory Created by Oliver Fujimori | SynthesisDeFi.com Perfect for swing traders and position traders focused on daily market structure analysis
Индикатор Pine Script®
от Synthesis_DeFi
Liquidity + FVG + OB Markings (Fixed v6)This indicator is built for price-action traders. It automatically finds and plots three key structures on your chart: Liquidity Levels – swing highs & lows that often get targeted by price. Fair-Value Gaps (FVG) – inefficient price gaps between candles. Order-Blocks (OB) – zones created by strong, high-volume impulsive candles. It also provides alerts and a small information table so you can quickly gauge the current market context.
Индикатор Pine Script®
от shiyamsunder87
8
TOP-RSI Double Confirm + Heiken Ashi + Buy/Sell Labels v01📊 RSI Double Confirm + Heiken Ashi + Labels 🔎 Concept This indicator combines a Zero-based RSI filter with strict candle close confirmation, overlays Heiken Ashi candles for clearer trend visualization, and adds Buy/Sell labels directly on the chart for easier interpretation. ⚙️ Components 1. RSI Double Confirm RSI is calculated from OHLC4 (open+high+low+close)/4. The RSI value is shifted by -50 to center it around zero (above 0 = bullish, below 0 = bearish). Uses user-defined thresholds: Overbought (OB) and Oversold (OS). 📌 Entry conditions: Buy Signal → RSI crosses upward through OS and the last closed candle is higher than the previous candle. Sell Signal → RSI crosses downward through OB and the last closed candle is lower than the previous candle. 2. Heiken Ashi Candles Custom Heiken Ashi values are calculated: haOpen, haClose, haHigh, haLow. Candles are colored green (if haClose > haOpen) or red (if haClose < haOpen). Helps smooth price action and highlight trend direction. 3. Alerts alertcondition is set for both Buy and Sell signals. Users can create TradingView alerts that trigger whenever a new signal appears. 4. Signals & Labels A green up arrow is plotted under the candle when a Buy signal is triggered. A red down arrow is plotted above the candle when a Sell signal is triggered. Additionally, labels ("Buy" or "Sell") are added at the respective candle to make signals more visible. 📝 How to Use Add the indicator to your chart (it overlays directly on price). Adjust inputs: OB (Overbought) → e.g. 20 OS (Oversold) → e.g. -20 RSI Length → e.g. 7 Watch for signals: Buy Signal → Green arrow + "Buy" label → potential bullish entry. Sell Signal → Red arrow + "Sell" label → potential bearish entry. Set up alerts in TradingView to be notified when new signals appear. ✅ Benefits Combines RSI confirmation + Heiken Ashi trend filter + Clear chart labels. Reduces false signals by requiring both RSI cross and strict close confirmation. Easy to interpret visually with arrows and text labels. ⚠️ Notes This indicator is meant as a signal confirmation tool, not a standalone strategy. Best used alongside support/resistance analysis, price action, or volume. Does not provide automatic stop loss / take profit levels → risk management must be applied by the trader.
Индикатор Pine Script®
от Topview1817
2