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Market Liquidity IndicatorThe strategy identifies institutional "Ignition" points where price breaks a key macro level (VWAP) with significant volume and order flow support. It assumes that a clean breakout, backed by high relative volume (RVOL) and aggressive buying/selling pressure (CVD Slope), will result in a sustainable trend. Risk is managed via a "Profit-Only Trailing Stop" mechanism, which enforces a hard floor for losses but allows profits to run uncapped until the trend bends Timeframe: This strategy is hardcoded to look at 1-minute data for its decision engine (RVOL/CVD), regardless of the chart timeframe. However, it is recommended to run it on a 5-minute chart for visual clarity. Execution: GOL (Green Arrow): Go Long. GOS (Red Arrow): Go Short. Exits: 1 Brick = 0.1% of Entry Price. Trailing Stop Loss: Retrace from Extreme High/Low ± 3 Bricks. Stop Out: +/- 3 Bricks from Entry Price Works well with Stocks - 5 min TF. For Index 10 min TF works well. However do play around to get your best fit. Happy Profitable Trading! Have fun!
Pine Script® インジケーター
razcadsの投稿
Multi-Strategy Filter: Pivot/Breakout/VWAP/RSI/MACDStrategy Overview: Multi-Confirmation Technical Scanner This filter is a high-probability trend-following system that combines three core trading methodologies: Pivot Points (for institutional levels), Breakout Trading (for price action momentum), and VWAP (for volume-weighted value tracking). To ensure accuracy and avoid false breakouts, a signal is only generated when at least three of these core strategies align, further validated by a "Sweet Spot" RSI (momentum confirmation without being overbought) and a bullish MACD crossover. This multi-layered approach identifies stocks with strong institutional support and significant upward momentum.
Pine Script® インジケーター
fimasanの投稿
GCM Apex Predator AlgoTitle: GCM Apex Predator Algo Overview The GCM Apex Predator is a high-performance, multi-engine trading system designed for traders who demand precision and clarity. Whether you are a fast-paced scalper or a patient swing trader, this algorithm adapts to market conditions using a sophisticated "Apex Score" momentum engine combined with institutional-grade volume and trend filters. Key Features • Triple Engine Logic: Switch seamlessly between Scalper Mode (Fast), Trend Mode (Swing), or a Hybrid setup that captures both micro-moves and macro-trends. • Apex Score Momentum: A proprietary loop-based engine that calculates the "persistence" of price action. It filters out "fake" moves by ensuring momentum is backed by structural strength. • Institutional Filters: Includes built-in ADX Trend Power and Relative Volume filters to keep you out of "chop" and only in high-probability trades. • Dynamic Risk Management: Automatically calculates and draws Entry, Stop Loss (SL), and Take Profit (TP) zones using ATR-based volatility, giving you a professional "desk" feel. • Corporate Dashboard: A real-time HUD (Heads-Up Display) that monitors Trend Bias, ADX Power, Apex Momentum, and VWAP positioning at a glance. How to Use 1. Select Your Mode: Use the "Scalper Mode" for lower timeframes (1m, 5m) or "Trend Mode" for higher timeframes (1h, 4h). 2. The "Sniper" Signal: Look for the Gold Circle symbols. These represent "Sniper" entries where all engines (Trend, Volume, and Apex) align for a high-conviction move. 3. Market Structure: Pay attention to the dashed reversal lines. These project potential structural shifts based on fast-reversal HMA logic. Alerts This indicator is fully optimized for Any alert() function call. You can set one single alert to receive detailed notifications like: • 🎯 SNIPER LONG: BTCUSD @ 65000 • ⚡ SCALP BUY: EURUSD @ 1.0850 Disclaimer Trading involves significant risk. This tool is for educational and technical analysis purposes. Past performance does not guarantee future results.
Pine Script® インジケーター
uniGramの投稿
1
Adaptive Pullbacks ML v2.5Adaptive Pullbacks ML - Context-Aware Trend Trading Overview Adaptive Pullbacks ML is a sophisticated trend-following tool that solves the biggest problem in pullback trading: "Is this a dip to buy, or the start of a reversal?" Unlike standard indicators that use fixed percentages or static moving averages, this script uses a 5-Dimensional k-Nearest Neighbors (k-NN) machine learning engine to learn the specific characteristics of successful pullbacks for the asset you are trading. The 5-Dimensional ML Engine The market is dynamic. A pullback depth that works in a low-volatility lunch session might fail during a high-volatility news event. This indicator tracks 5 key dimensions for every pullback: Depth (ATR Normalized): How deep is the pullback relative to volatility? Trend Slope: Is the trend steep (parabolic) or flat (grinding)? ADX: How strong is the directional energy? VWAP Distance: Is price extended or close to value? Time of Day: Is this a morning drive or an afternoon fade? When a new pullback occurs, the k-NN engine finds the 5 most similar historical events across these dimensions and predicts the probability of success. Core Features 1. Fractal Normalization The indicator speaks the language of ATR (Average True Range). It doesn't care if you trade the 15-second chart or the Daily chart. A "1.5 ATR Pullback" is a statistically comparable event across all timeframes, allowing for robust, scale-invariant analysis. 2. HTF Stats Bridge (Higher Timeframe Data) You can trade on lower timeframes (e.g., 1-minute) while using statistics derived from higher timeframes (e.g., 15-minute). This ensures your signals are based on significant market structure, not microstructure noise. 3. Smart Zones The indicator plots dynamic "Value Zones" based on learning: Cyan Zone (Avg Depth): The "Sweet Spot". High probability bounce area. Yellow Zone (Sigma): The "Extension". Price is stretching elastic limits. Red Zone (Deep): The "Danger/Opportunity". Statistical anomaly. 4. PQS & k-NN Filters Two layers of filtering protect your capital: PQS (Probability Qualification Score): Based on raw win-rate of the zone. k-NN Probability: Based on similarity to past winners. Settings Guide Stats Timeframe: The timeframe to learn from (Leave empty for Chart). Trend/Trigger Settings: Define what constitutes a trend for your strategy. k-Neighbors: Number of historical twins to compare (Default: 5). Min PQS / k-NN: Thresholds for filtering weak signals. Disclaimer: This tool is for educational purposes. Past performance of the k-NN engine does not guarantee future results.
Pine Script® インジケーター
Selfsimilarityの投稿
1
Clean EMA VWAP Trend Pullback - SrPyeA clean, confirmation-based trend pullback indicator using EMA and VWAP alignment. Designed to reduce noise and highlight high-probability continuation setups. Best used on 1–2 minute charts during high-liquidity sessions. This indicator is designed as a confirmation tool, not a standalone trading system. Good For NY Session 9:30am - 11:00am - After Lunch 1:00pm- 3:00pm OR Optional Alerts - Sr.Pye
Pine Script® インジケーター
fnunez914の投稿
BTC ETF Average Inflow Cost BasisConcept Since the historic launch of Bitcoin Spot ETFs on January 11, 2024, institutional flows have become a major driver of price action. This indicator aims to visualize the aggregate Cost Basis (average entry price) of the major Bitcoin ETFs relative to the underlying asset. It serves as an on-chain proxy for institutional positioning, helping traders identify critical support levels where ETF inflows have historically concentrated. How it Works The script aggregates daily volume data from the top Bitcoin ETFs (IBIT, FBTC, ARKB, GBTC, BITB) and compares it against the Bitcoin price (BTCUSDT). ETF Cost Basis (Pink Line): This is calculated as a Cumulative Volume-Weighted Average Price (VWAP), anchored specifically to the ETF launch date (Jan 11, 2024). Formula: It accumulates (BTC Price * Total ETF Volume) and divides it by the Cumulative Total ETF Volume. This creates a dynamic level representing the "breakeven" price for the aggregate volume traded through these funds. True Market Mean (Gray Line): This represents the simple cumulative average of the Bitcoin price since the ETF launch date. It acts as a neutral baseline for the post-ETF market era. How to Use Institutional Support: The Cost Basis line often acts as a strong dynamic support level during corrections. When price revisits this level, it suggests the market is returning to the average institutional entry price. Trend Filter: Price > Cost Basis: The market is in a net profit state relative to ETF flows (Bullish/Trend continuation). Price < Cost Basis: The market is in a net loss state (Bearish/Capitulation risk). Confluence: The intersection of the Cost Basis and the True Market Mean can signal pivotal moments of trend reset. Features Data Aggregation: Pulls data from 5 major ETFs via request.security without repainting (using closed bars). Dashboard: Includes a table in the top-right corner displaying real-time values for Price, Cost Basis, and Market Mean. Customization: You can toggle individual ETF Moving Averages in the settings (disabled by default due to price scale differences between BTC and ETF shares). Disclaimer This tool is for educational purposes only and attempts to estimate institutional cost basis using volume proxies. It does not represent financial advice.
Pine Script® インジケーター
carlosbucciの投稿