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Line Break StrategyLine Break Strategy Entry rule: Long on a bullish line and short on a bearish line. Backtest: Profit factors are shown below for three-line break. Daily time frame, FXCM broker. EURUSD: 1.267, USDJPY: 1.039, GBPUSD: -0.816, AUDUSD: -0.959 S&P500: -0.783, Nikkei225: 1.099 CrudeOil: 1.03, Gold: 1.196 BTCUSD: -0.883 Reference: Steve Nison, Beyond Candlesticks - New Japanese Charting Techniques Revealed Note: This strategy doesn't work properly on the linebreak chart. A good example is shown below. The entry prices are not always correct. If you have signal, but the next candle moves in the opposite direction, the entry price is drawn at the Open of the new candle instead of the Close of the previous candle. The results of backtest are unreliable due to this reason.
Strategi Pine Script®
oleh Mizuki32
7
EMA & SMA with FRACTAL DEVIATION BANDS by @XeL_ArjonaEMA & SMA with FRACTAL DEVIATION BANDS Ver. 1.0.25.08.2015 By Ricardo M Arjona @XeL_Arjona DISCLAIMER: DISCLAIMER: The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets. The embedded code and ideas within this work are FREELY AND PUBLICLY available on the Web for NON LUCRATIVE ACTIVITIES and must remain as is. WHAT IS THIS? This is the adaptation of the FRACTAL DEVIATION BANDS to be used on Traditional Moving Averages (Simple & Exponential). ALL NEW IDEAS OR MODIFICATIONS to these indicator(s) are Welcome in favor to deploy a better and more accurate readings. I will be very glad to be notified at Twitter or TradingVew accounts at: @XeL_Arjona Any important addition to this work MUST REMAIN PUBLIC by means of CreativeCommons CC & TradingView. 2015
Penunjuk Pine Script®
oleh xel_arjona
1
Acc/Dist. Cloud with Fractal Deviation Bands by @XeL_ArjonaACCUMULATION / DISTRIBUTION CLOUD with MORPHIC DEVIATION BANDS Ver. 2.0.beta.23:08:2015 by Ricardo M. Arjona @XeL_Arjona DISCLAIMER The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets. The embedded code and ideas within this work are FREELY AND PUBLICLY available on the Web for NON LUCRATIVE ACTIVITIES and must remain as is. Pine Script code MOD's and adaptations by @XeL_Arjona with special mention in regard of: Buy (Bull) and Sell (Bear) "Power Balance Algorithm by Vadim Gimelfarb published at Stocks & Commodities V. 21:10 (68-72). Custom Weighting Coefficient for Exponential Moving Average (nEMA) adaptation work by @XeL_Arjona with contribution help from @RicardoSantos at TradingView @pinescript chat room. Morphic Numbers (PHI & Plastic) Pine Script adaptation from it's algebraic generation formulas by @XeL_Arjona Fractal Deviation Bands idea by @XeL_Arjona CHANGE LOG: ACCUMULATION / DISTRIBUTION CLOUD: I decided to change it's name from the Buy to Sell Pressure. The code is essentially the same as older versions and they are the center core (VORTEX?) of all derived New stuff which are: MORPHIC NUMBERS: The "Golden Ratio" expressed by the result of the constant "PHI" and the newer and same in characteristics "Plastic Number" expressed as "PN". For more information about this regard take a look at: HERE! CUSTOM(K) EXPONENTIAL MOVING AVERAGE: Some code has cleaned from last version to include as custom function the nEMA , which use an additional input (K) to customise the way the "exponentially" is weighted from the custom array. For the purpose of this indicator, I implement a volatility algorithm using the Average True Range of last 9 periods multiplied by the morphic number used in the fractal study. (Golden Ratio as default) The result is very similar in response to classic EMA but tend to accelerate or decelerate much more responsive with wider bars presented in trending average. FRACTAL DEVIATION BANDS: The main idea is based on the so useful Standard Deviation process to create Bands in favor of a multiplier (As John Bollinger used in it's own bands) from a custom array, in which for this case is the "Volume Pressure Moving Average" as the main Vortex for the "Fractallitly", so then apply as many "Child bands" using the older one as the new calculation array using the same morphic constant as multiplier (Like Fibonacci but with other approach rather than %ratios). Results are AWSOME! Market tend to accelerate or decelerate their Trend in favor of a Fractal approach. This bands try to catch them, so please experiment and feedback me your own observations. EXTERNAL TICKER FOR VOLUME DATA: I Added a way to input volume data for this kind of study from external tickers. This is just a quicky-hack given that currently TradingView is not adding Volume to their Indexes so; maybe this is temporary by now. It seems that this part of the code is conflicting with intraday timeframes, so You are advised. This CODE is versioned as BETA FOR TESTING PROPOSES. By now TradingView Admins are changing lot's of things internally, so maybe this could conflict with correct rendering of this study with special tickers or timeframes. I will try to code by itself just the core parts of this study in order to use them at discretion in other areas. ALL NEW IDEAS OR MODIFICATIONS to these indicator(s) are Welcome in favor to deploy a better and more accurate readings. I will be very glad to be notified at Twitter or TradingView accounts at: @XeL_Arjona
Penunjuk Pine Script®
oleh xel_arjona
10
EMA Cross Strategy only Long📈 EMA Cross Strategy – Only Long Simple. Clean. Powerful. Designed for strong uptrends. This is a long-only trend-following strategy based on the classic crossover of Exponential Moving Averages (EMAs). It’s designed for growth stocks and trending assets where upward momentum dominates. ⚙️ How it works: Entry: when the Fast EMA crosses above the Slow EMA Exit: when the Fast EMA crosses below the Slow EMA No shorts, no reversals – just pure trend riding. By default, the strategy uses 50/100 EMA, which has performed exceptionally well on stocks like NVIDIA (NVDA). These settings can be easily customized to fit your preferred asset or timeframe. 📊 Backtest Example – NVIDIA (NVDA, 1D timeframe) Test parameters: Initial capital: $10,000 Order size: 50% of equity per trade (adjustable in settings) Results: Net profit: +$2,037,563.63 USD Gross profit: $2,127,432.33 Gross loss: $89,868.70 Max equity growth: $2,708,648.75 (+99.63%) Drawdown: 20.00% Buy & Hold profit: +$30,636,000 USD (but with far more exposure) The strategy dramatically outperformed passive holding on a risk-adjusted basis, while keeping drawdowns and trade count under control. 🔧 Customization & Risk Management In the Strategy Settings, you can adjust: EMA lengths (default: 50 fast, 100 slow) Order size as a % of equity (e.g., reduce below 50% to lower drawdown) Backtest range and asset type (works well on growth stocks and trending commodities) Try this on assets with strong bullish cycles like NVDA, AAPL, MSFT, or Gold (XAU/USD). ⚠️ Disclaimer This script is for educational and backtesting purposes only. It is not financial advice. Please do your own research and test carefully before trading live.
Strategi Pine Script®
oleh wilusss
Aetherium Institutional Market Resonance EngineAetherium Institutional Market Resonance Engine (AIMRE) A Three-Pillar Framework for Decoding Institutional Activity 🎓 THEORETICAL FOUNDATION The Aetherium Institutional Market Resonance Engine (AIMRE) is a multi-faceted analysis system designed to move beyond conventional indicators and decode the market's underlying structure as dictated by institutional capital flow. Its philosophy is built on a singular premise: significant market moves are preceded by a convergence of context , location , and timing . Aetherium quantifies these three dimensions through a revolutionary three-pillar architecture. This system is not a simple combination of indicators; it is an integrated engine where each pillar's analysis feeds into a central logic core. A signal is only generated when all three pillars achieve a state of resonance, indicating a high-probability alignment between market organization, key liquidity levels, and cyclical momentum. ⚡ THE THREE-PILLAR ARCHITECTURE 1. 🌌 PILLAR I: THE COHERENCE ENGINE (THE 'CONTEXT') Purpose: To measure the degree of organization within the market. This pillar answers the question: " Is the market acting with a unified purpose, or is it chaotic and random? " Conceptual Framework: Institutional campaigns (accumulation or distribution) create a non-random, organized market environment. Retail-driven or directionless markets are characterized by "noise" and chaos. The Coherence Engine acts as a filter to ensure we only engage when institutional players are actively steering the market. Formulaic Concept: Coherence = f(Dominance, Synchronization) Dominance Factor: Calculates the absolute difference between smoothed buying pressure (volume-weighted bullish candles) and smoothed selling pressure (volume-weighted bearish candles), normalized by total pressure. A high value signifies a clear winner between buyers and sellers. Synchronization Factor: Measures the correlation between the streams of buying and selling pressure over the analysis window. A high positive correlation indicates synchronized, directional activity, while a negative correlation suggests choppy, conflicting action. The final Coherence score (0-100) represents the percentage of market organization. A high score is a prerequisite for any signal, filtering out unpredictable market conditions. 2. 💎 PILLAR II: HARMONIC LIQUIDITY MATRIX (THE 'LOCATION') Purpose: To identify and map high-impact institutional footprints. This pillar answers the question: " Where have institutions previously committed significant capital? " Conceptual Framework: Large institutional orders leave indelible marks on the market in the form of anomalous volume spikes at specific price levels. These are not random occurrences but are areas of intense historical interest. The Harmonic Liquidity Matrix finds these footprints and consolidates them into actionable support and resistance zones called "Harmonic Nodes." Algorithmic Process: Footprint Identification: The engine scans the historical lookback period for candles where volume > average_volume * Institutional_Volume_Filter. This identifies statistically significant volume events. Node Creation: A raw node is created at the mean price of the identified candle. Dynamic Clustering: The engine uses an ATR-based proximity algorithm. If a new footprint is identified within Node_Clustering_Distance (ATR) of an existing Harmonic Node, it is merged. The node's price is volume-weighted, and its magnitude is increased. This prevents chart clutter and consolidates nearby institutional orders into a single, more significant level. Node Decay: Nodes that are older than the Institutional_Liquidity_Scanback period are automatically removed from the chart, ensuring the analysis remains relevant to recent market dynamics. 3. 🌊 PILLAR III: CYCLICAL RESONANCE MATRIX (THE 'TIMING') Purpose: To identify the market's dominant rhythm and its current phase. This pillar answers the question: " Is the market's immediate energy flowing up or down? " Conceptual Framework: Markets move in waves and cycles of varying lengths. Trading in harmony with the current cyclical phase dramatically increases the probability of success. Aetherium employs a simplified wavelet analysis concept to decompose price action into short, medium, and long-term cycles. Algorithmic Process: Cycle Decomposition: The engine calculates three oscillators based on the difference between pairs of Exponential Moving Averages (e.g., EMA8-EMA13 for short cycle, EMA21-EMA34 for medium cycle). Energy Measurement: The 'energy' of each cycle is determined by its recent volatility (standard deviation). The cycle with the highest energy is designated as the "Dominant Cycle." Phase Analysis: The engine determines if the dominant cycles are in a bullish phase (rising from a trough) or a bearish phase (falling from a peak). Cycle Sync: The highest conviction timing signals occur when multiple cycles (e.g., short and medium) are synchronized in the same direction, indicating broad-based momentum. 🔧 COMPREHENSIVE INPUT SYSTEM Pillar I: Market Coherence Engine Coherence Analysis Window (10-50, Default: 21): The lookback period for the Coherence Engine. Lower Values (10-15): Highly responsive to rapid shifts in market control. Ideal for scalping but can be sensitive to noise. Balanced (20-30): Excellent for day trading, capturing the ebb and flow of institutional sessions. Higher Values (35-50): Smoother, more stable reading. Best for swing trading and identifying long-term institutional campaigns. Coherence Activation Level (50-90%, Default: 70%): The minimum market organization required to enable signal generation. Strict (80-90%): Only allows signals in extremely clear, powerful trends. Fewer, but potentially higher quality signals. Standard (65-75%): A robust filter that effectively removes choppy conditions while capturing most valid institutional moves. Lenient (50-60%): Allows signals in less-organized markets. Can be useful in ranging markets but may increase false signals. Pillar II: Harmonic Liquidity Matrix Institutional Liquidity Scanback (100-400, Default: 200): How far back the engine looks for institutional footprints. Short (100-150): Focuses on recent institutional activity, providing highly relevant, immediate levels. Long (300-400): Identifies major, long-term structural levels. These nodes are often extremely powerful but may be less frequent. Institutional Volume Filter (1.3-3.0, Default: 1.8): The multiplier for detecting a volume spike. High (2.5-3.0): Only registers climactic, undeniable institutional volume. Fewer, but more significant nodes. Low (1.3-1.7): More sensitive, identifying smaller but still relevant institutional interest. Node Clustering Distance (0.2-0.8 ATR, Default: 0.4): The ATR-based distance for merging nearby nodes. High (0.6-0.8): Creates wider, more consolidated zones of liquidity. Low (0.2-0.3): Creates more numerous, precise, and distinct levels. Pillar III: Cyclical Resonance Matrix Cycle Resonance Analysis (30-100, Default: 50): The lookback for determining cycle energy and dominance. Short (30-40): Tunes the engine to faster, shorter-term market rhythms. Best for scalping. Long (70-100): Aligns the timing component with the larger primary trend. Best for swing trading. Institutional Signal Architecture Signal Quality Mode (Professional, Elite, Supreme): Controls the strictness of the three-pillar confluence. Professional: Loosest setting. May generate signals if two of the three pillars are in strong alignment. Increases signal frequency. Elite: Balanced setting. Requires a clear, unambiguous resonance of all three pillars. The recommended default. Supreme: Most stringent. Requires perfect alignment of all three pillars, with each pillar exhibiting exceptionally strong readings (e.g., coherence > 85%). The highest conviction signals. Signal Spacing Control (5-25, Default: 10): The minimum bars between signals to prevent clutter and redundant alerts. 🎨 ADVANCED VISUAL SYSTEM The visual architecture of Aetherium is designed not merely for aesthetics, but to provide an intuitive, at-a-glance understanding of the complex data being processed. Harmonic Liquidity Nodes: The core visual element. Displayed as multi-layered, semi-transparent horizontal boxes. Magnitude Visualization: The height and opacity of a node's "glow" are proportional to its volume magnitude. More significant nodes appear brighter and larger, instantly drawing the eye to key levels. Color Coding: Standard nodes are blue/purple, while exceptionally high-magnitude nodes are highlighted in an accent color to denote critical importance. 🌌 Quantum Resonance Field: A dynamic background gradient that visualizes the overall market environment. Color: Shifts from cool blues/purples (low coherence) to energetic greens/cyans (high coherence and organization), providing instant context. Intensity: The brightness and opacity of the field are influenced by total market energy (a composite of coherence, momentum, and volume), making powerful market states visually apparent. 💎 Crystalline Lattice Matrix: A geometric web of lines projected from a central moving average. Mathematical Basis: Levels are projected using multiples of the Golden Ratio (Phi ≈ 1.618) and the ATR. This visualizes the natural harmonic and fractal structure of the market. It is not arbitrary but is based on mathematical principles of market geometry. 🧠 Synaptic Flow Network: A dynamic particle system visualizing the engine's "thought process." Node Density & Activation: The number of particles and their brightness/color are tied directly to the Market Coherence score. In high-coherence states, the network becomes a dense, bright, and organized web. In chaotic states, it becomes sparse and dim. ⚡ Institutional Energy Waves: Flowing sine waves that visualize market volatility and rhythm. Amplitude & Speed: The height and speed of the waves are directly influenced by the ATR and volume, providing a feel for market energy. 📊 INSTITUTIONAL CONTROL MATRIX (DASHBOARD) The dashboard is the central command console, providing a real-time, quantitative summary of each pillar's status. Header: Displays the script title and version. Coherence Engine Section: State: Displays a qualitative assessment of market organization: ◉ PHASE LOCK (High Coherence), ◎ ORGANIZING (Moderate Coherence), or ○ CHAOTIC (Low Coherence). Color-coded for immediate recognition. Power: Shows the precise Coherence percentage and a directional arrow (↗ or ↘) indicating if organization is increasing or decreasing. Liquidity Matrix Section: Nodes: Displays the total number of active Harmonic Liquidity Nodes currently being tracked. Target: Shows the price level of the nearest significant Harmonic Node to the current price, representing the most immediate institutional level of interest. Cycle Matrix Section: Cycle: Identifies the currently dominant market cycle (e.g., "MID ") based on cycle energy. Sync: Indicates the alignment of the cyclical forces: ▲ BULLISH , ▼ BEARISH , or ◆ DIVERGENT . This is the core timing confirmation. Signal Status Section: A unified status bar that provides the final verdict of the engine. It will display "QUANTUM SCAN" during neutral periods, or announce the tier and direction of an active signal (e.g., "◉ TIER 1 BUY ◉" ), highlighted with the appropriate color. 🎯 SIGNAL GENERATION LOGIC Aetherium's signal logic is built on the principle of strict, non-negotiable confluence. Condition 1: Context (Coherence Filter): The Market Coherence must be above the Coherence Activation Level. No signals can be generated in a chaotic market. Condition 2: Location (Liquidity Node Interaction): Price must be actively interacting with a significant Harmonic Liquidity Node. For a Buy Signal: Price must be rejecting the Node from below (testing it as support). For a Sell Signal: Price must be rejecting the Node from above (testing it as resistance). Condition 3: Timing (Cycle Alignment): The Cyclical Resonance Matrix must confirm that the dominant cycles are synchronized with the intended trade direction. Signal Tiering: The Signal Quality Mode input determines how strictly these three conditions must be met. 'Supreme' mode, for example, might require not only that the conditions are met, but that the Market Coherence is exceptionally high and the interaction with the Node is accompanied by a significant volume spike. Signal Spacing: A final filter ensures that signals are spaced by a minimum number of bars, preventing over-alerting in a single move. 🚀 ADVANCED TRADING STRATEGIES The Primary Confluence Strategy: The intended use of the system. Wait for a Tier 1 (Elite/Supreme) or Tier 2 (Professional/Elite) signal to appear on the chart. This represents the alignment of all three pillars. Enter after the signal bar closes, with a stop-loss placed logically on the other side of the Harmonic Node that triggered the signal. The Coherence Context Strategy: Use the Coherence Engine as a standalone market filter. When Coherence is high (>70%), favor trend-following strategies. When Coherence is low (<50%), avoid new directional trades or favor range-bound strategies. A sharp drop in Coherence during a trend can be an early warning of a trend's exhaustion. Node-to-Node Trading: In a high-coherence environment, use the Harmonic Liquidity Nodes as both entry points and profit targets. For example, after a BUY signal is generated at one Node, the next Node above it becomes a logical first profit target. ⚖️ RESPONSIBLE USAGE AND LIMITATIONS Decision Support, Not a Crystal Ball: Aetherium is an advanced decision-support tool. It is designed to identify high-probability conditions based on a model of institutional behavior. It does not predict the future. Risk Management is Paramount: No indicator can replace a sound risk management plan. Always use appropriate position sizing and stop-losses. The signals provided are probabilistic, not certainties. Past Performance Disclaimer: The market models used in this script are based on historical data. While robust, there is no guarantee that these patterns will persist in the future. Market conditions can and do change. Not a "Set and Forget" System: The indicator performs best when its user understands the concepts behind the three pillars. Use the dashboard and visual cues to build a comprehensive view of the market before acting on a signal. Backtesting is Essential: Before applying this tool to live trading, it is crucial to backtest and forward-test it on your preferred instruments and timeframes to understand its unique behavior and characteristics. 🔮 CONCLUSION The Aetherium Institutional Market Resonance Engine represents a paradigm shift from single-variable analysis to a holistic, multi-pillar framework. By quantifying the abstract concepts of market context, location, and timing into a unified, logical system, it provides traders with an unprecedented lens into the mechanics of institutional market operations. It is not merely an indicator, but a complete analytical engine designed to foster a deeper understanding of market dynamics. By focusing on the core principles of institutional order flow, Aetherium empowers traders to filter out market noise, identify key structural levels, and time their entries in harmony with the market's underlying rhythm. "In all chaos there is a cosmos, in all disorder a secret order." - Carl Jung — Dskyz, Trade with insight. Trade with confluence. Trade with Aetherium.
Penunjuk Pine Script®
oleh DskyzInvestments
2
Pro Scalping Strategy [1Min | No Repaint | High Precision]Pro Scalping Strategy Dual-Mode Precision Scalping System | EMA Trend + RSI + ATR | Non-Repainting 🔍 Overview This indicator is a precision-engineered scalping tool optimized for lower timeframes (1–5 min), offering stable Buy/Sell signals without repainting. Built on a robust trend-following framework, this system gives you the choice of two operating modes: 🔒 High Accuracy: Strict filters, fewer but stronger signals ⚡ More Signals: Looser filters, more frequent entries 🧠 How It Works The logic is based on a multi-filter engine applied on closed candles only, ensuring non-repainting, clean, and confirmed entries. ⚙️ Technical Filters Used 1. EMA Trend Stack Defines market trend using 3 EMAs (9, 21, 50) Buy: EMA9 > EMA21 > EMA50 Sell: EMA9 < EMA21 < EMA50 2. EMA Crossover Filter A confirmed crossover or crossunder is required from 2 candles back Ensures trend momentum is validated before signal appears 3. EMA Slope Filter Only accepts signals if mid EMA (EMA21) is sloping in trend direction 4. RSI Filter Filters out signals when RSI is too extreme RSI < overbought for Buy / RSI > oversold for Sell 5. ATR Filter Confirms market has enough volatility ATR must exceed a minimum threshold ✅ Modes Comparison Feature High Accuracy Mode More Signals Mode Min EMA Gap 0.1 0.05 Min ATR 0.2 0.1 RSI Range 30–70 25–75 Entry Frequency Lower Higher Signal Quality Tighter + Stronger Looser + Flexible 🔔 Features 🔁 No repaint logic ⚙️ Adjustable settings with simple mode switch ⚡ Real-time alerts via alertcondition() ✅ Visual confirmation with BUY/SELL labels 💹 Suitable for scalping crypto, forex, gold, indices, and more 📌 Author: ALIP FX “Success Elevated, Trade Smarter.”
Penunjuk Pine Script®
oleh ALIP_FX
IDKFAIDKFA - Advanced Order Blocks & Volume Profile with Market Structure Analysis Why IDKFA? Named after the legendary DOOM cheat code that gives players "all weapons and full ammo," IDKFA provides traders with a comprehensive arsenal of market analysis tools. Just as the cheat code arms players with everything needed for combat, this indicator equips traders with essential market structure tools: Order Blocks, Volume Profile, LVN/HVN areas, Fibonacci retracements, and intelligent buy/sell signals - all in one unified system. Core Features Order Blocks Detection Automatically identifies institutional order blocks using pivot high/low analysis Extends blocks dynamically until price interaction occurs Bullish blocks (demand zones) and bearish blocks (supply zones) Customizable opacity and extend functionality Advanced Volume Profile Real-time volume profile calculation for multiple session types Point of Control (POC), Value Area High (VAH), and Value Area Low (VAL) Mode 1: Side-by-side bull/bear volume display Mode 2: Overlapped volume display with percentage analysis Shows buying vs selling pressure at each price level LVN/HVN Area Detection Low Volume Nodes (LVN): Areas below VAL where price moves quickly High Volume Nodes (HVN): Areas above VAH with strong resistance NPOC (Naked Point of Control): Single print areas within Value Area Volume-based gradient coloring shows relative activity levels Smart Fibonacci Retracements Auto-detects trend direction for proper fibonacci orientation Dynamic color coding: Red levels in uptrends, Gold in downtrends Special 88.6% level turns lime green in downtrends Key levels: 23.6%, 38.2%, 50%, 61.8%, 65%, 78.6%, 88.6% Intelligent Signal System Works best on higher timeframes Identifies high-probability reversal setups at key levels Buy signals: Large bearish rejection followed by bullish reclaim Sell signals: Large bullish rejection followed by bearish breakdown Signals only trigger near significant support/resistance areas Signal Analysis & Usage Guidelines Buy Signal Mechanics The buy signal triggers when: Previous candle shows significant bearish movement (minimum ATR multiplier) Current candle reclaims a configurable percentage of the previous candle's range Price is near a key support level (order blocks, fibonacci, volume levels) Sell Signal Mechanics The sell signal triggers when: Previous candle shows significant bullish movement (minimum ATR multiplier) Current candle rejects below a configurable percentage of the previous candle's range Price is near a key resistance level (order blocks, fibonacci, volume levels) When to TAKE Signals High Probability Buy Signals: Signal appears AT or BELOW the VAL (Value Area Low) Signal occurs at bullish order block confluence Price is in LVN area below VAL (momentum acceleration zone) Signal aligns with fibonacci 61.8% or 78.6% support Multiple session POC levels provide support confluence Previous session's VAL acting as current support High Probability Sell Signals: Signal appears AT or ABOVE the VAH (Value Area High) Signal occurs at bearish order block confluence Price is in HVN area above VAH (heavy resistance zone) Signal aligns with fibonacci 61.8% or 78.6% resistance Multiple session POC levels provide resistance confluence Previous session's VAH acting as current resistance When to AVOID Signals Avoid Buy Signals When: Signal appears ABOVE the VAH (buying into resistance) Price is in HVN red zones (high volume resistance areas) No clear support structure below current price Volume profile shows heavy selling pressure (high bear percentages) Signal occurs during low-volume periods between major sessions Multiple bearish order blocks exist below current price Avoid Sell Signals When: Signal appears BELOW the VAL (selling into support) Price is in LVN green zones (momentum could continue) No clear resistance structure above current price Volume profile shows heavy buying pressure (high bull percentages) Signal occurs during Asian session ranges without clear direction Multiple bullish order blocks exist above current price Volume Profile Context for Signals Understanding Bull/Bear Percentages: 70%+ Bull dominance at a level = Strong support expected 70%+ Bear dominance at a level = Strong resistance expected 50/50 Split = Neutral zone, less predictable Use percentages to gauge conviction behind moves POC (Point of Control) Interactions: Signals above POC in uptrend = Higher probability Signals below POC in downtrend = Higher probability Signals against POC bias require extra confirmation POC often acts as magnetic level for price return Trading Strategies Strategy 1: VAL/VAH Bounce Strategy Wait for price to approach VAL (support) or VAH (resistance) Look for signal confirmation at these critical levels Enter with tight stops beyond the Value Area Target opposite boundary or next session's levels Strategy 2: Order Block + Volume Confluence Identify order block alignment with VAL/VAH Wait for signal within the confluence zone Enter on signal with stop beyond order block Use LVN areas as acceleration zones for targets Strategy 3: LVN/HVN Strategy LVN (Green) Areas: "Go Zones" - expect quick price movement through low volume HVN (Red) Areas: "Stop Zones" - expect resistance and potential reversals NPOC Areas: "Fill Zones" - price often returns to fill single print gaps Strategy 4: Multi-Session Analysis Use Daily/Weekly for major structure context Use 4H for intermediate levels Use 1H for precise entry timing Ensure all timeframes align before taking signals Strategy 5: Fibonacci + Volume Profile Buy signals at 61.8% or 78.6% fibonacci near VAL Sell signals at 61.8% or 78.6% fibonacci near VAH Use 88.6% level as final support/resistance before major moves 50% level often aligns with POC for confluence Signal Quality Assessment Grade A Signals (Highest Probability): Signal at VAL/VAH with order block confluence Fibonacci level alignment (61.8%, 78.6%) Volume profile shows 70%+ dominance in signal direction Multiple timeframe structure alignment Signal occurs during high-volume sessions (London/NY) Grade B Signals (Moderate Probability): Signal near POC with some confluence Fibonacci 50% or 38.2% alignment Mixed volume profile readings (50-70% dominance) Some timeframe alignment present Signal during overlap sessions Grade C Signals (Lower Probability): Signal with minimal confluence Weak fibonacci alignment or none Volume profile neutral or against signal Conflicting timeframe signals Signal during low-volume periods Risk Management Guidelines Position Sizing Based on Signal Quality: Grade A: Standard position size Grade B: Reduced position size (50-75%) Grade C: Minimal position size (25%) or skip entirely Stop Loss Placement: Beyond order block boundaries Outside Value Area (VAL/VAH) Below/above fibonacci confluence levels Account for session volatility ranges Profit Targets: First target: Opposite VAL/VAH boundary Second target: Next session's key levels Final target: Major order blocks or fibonacci extensions Credits & Attribution Original components derived from: Market Sessions & Volume Profile by © Leviathan (Mozilla Public License 2.0) Volume Profile elements inspired by @LonesomeTheBlue's volume profile script Pivot Order Blocks by TradingWolf / © MensaTrader (Mozilla Public License 2.0) Auto Fibonacci Retracement code (public domain) Significant enhancements and modifications include: Advanced LVN/HVN detection and visualization Bull/Bear percentage analysis for Mode 2/3 Comprehensive alert system with market context Integrated buy/sell signals at key levels Performance optimizations and extended session support Enhanced Mode 2/3 with percentage pressure analysis Important Disclaimers This indicator is a technical analysis tool designed for educational purposes. It does not provide financial advice, investment recommendations, or trading signals that guarantee profits. All trading involves substantial risk of loss, and past performance does not guarantee future results. Users should conduct their own research, understand the risks involved, and consider consulting with qualified financial advisors before making trading decisions. The signals and analysis provided are based on historical price patterns and volume data, which may not predict future market movements accurately. Best Practices Never trade signals blindly - always consider volume profile context Wait for confluence between multiple tools before entering Respect the Value Area - avoid buying above VAH or selling below VAL Use session context - Asian ranges vs London/NY breakouts Practice proper risk management - position size based on signal quality Understand the bigger picture - use multiple timeframes for context Remember: Like the IDKFA cheat code, having all the tools doesn't guarantee success. The key is learning to use them together effectively and understanding when NOT to take a signal is often more important than knowing when to take one.
Penunjuk Pine Script®
oleh MessyJess
4
8H/12H Trend + RSI + MACD🧠 RSI 8/12H – The Indicator That Shows Reversals Before the Move Happens Standard RSI (14) is too slow. By the time it flashes a signal, the move is usually halfway done. 📍 RSI 8/12H is faster, sharper, and built to spot local reversals early – before the crowd sees them. Why 8/12H Works: ✅ Detects overbought/oversold zones with precision ✅ Especially powerful on gold, oil, and indices ✅ Gives 1–2 clean, high-probability signals per week – no noise, no clutter 🔥 If you're tired of chasing late entries, RSI 8/12H gives you the edge to get in before the breakout. Don’t just watch where the market’s been. Anticipate where it turns.
Penunjuk Pine Script®
oleh iMine4ka
Mongoose Conflict Risk Radar v1.1 (Separate Panel) description The Mongoose Capital: Risk Rotation Index is a macro market sentiment tool designed to detect elevated risk conditions by aggregating signals across key asset classes. This script evaluates trend strength across 8 ETFs representing major risk-on and risk-off flows: GLD – Gold VIXY – Volatility TLT – Long-Term Bonds SPY – S&P 500 UUP – U.S. Dollar Index EEM – Emerging Markets SLV – Silver FXI – China Large-Cap Each asset is assigned a binary signal based on price position vs. its 21-period SMA (or a crossover for bonds). The signals are then totaled into a composite Risk Rotation Score, plotted as a bar graph. How to Use 0–2 = Low risk-on behavior 3–4 = Caution / Mixed regime 5–8 = Elevated conflict or macro stress Use this as a macro confirmation layer for trend entries, risk reduction, or allocation shifts. Alerts Set alerts when the index exceeds 5 to track major rotations into defensive assets.
Penunjuk Pine Script®
oleh TheRealMongoose
Double Bottom Strategy (Long Only, ATR Trailing Stop + Alerts)Updated chart script: This script implements a long-only breakout strategy based on the recognition of a Double Bottom price pattern, enhanced with a 50 EMA trend filter and a dynamic ATR-based trailing stop. It is suitable for traders looking to capture reversals in trending markets using a structured pattern-based entry system. 🧠 Key Features: Double Bottom Detection: Identifies double bottom structures using pivot lows with configurable tolerance. ATR-Based Trailing Stop: Manages exits using a trailing stop calculated from Average True Range (ATR), dynamically adjusting to market volatility. EMA Filter (Optional): Filters trades to only go long when price is above the 50 EMA (trend confirmation). Alerts: Real-time alerts on entry and exit, formatted in JSON for webhook compatibility. Backtest Range Controls: Customize historical testing period with start and end dates. ✅ Recommended Markets: Gold (XAUUSD) S&P 500 (SPX, ES) Nasdaq (NDX, NQ) Stocks (Equities) ⚠️ Not recommended for Forex due to differing behavior and noise levels in currency markets. 🛠️ User Guidance: Tune the pivot period, tolerance, and ATR settings for best performance on your chosen asset. Backtest thoroughly over your selected date range to assess historical effectiveness. Use small position sizes initially to test viability in live or simulated environments.
Strategi Pine Script®
oleh ojiyamu
Tensor Market Analysis Engine (TMAE)# Tensor Market Analysis Engine (TMAE) ## Advanced Multi-Dimensional Mathematical Analysis System *Where Quantum Mathematics Meets Market Structure* --- ## 🎓 THEORETICAL FOUNDATION The Tensor Market Analysis Engine represents a revolutionary synthesis of three cutting-edge mathematical frameworks that have never before been combined for comprehensive market analysis. This indicator transcends traditional technical analysis by implementing advanced mathematical concepts from quantum mechanics, information theory, and fractal geometry. ### 🌊 Multi-Dimensional Volatility with Jump Detection **Hawkes Process Implementation:** The TMAE employs a sophisticated Hawkes process approximation for detecting self-exciting market jumps. Unlike traditional volatility measures that treat price movements as independent events, the Hawkes process recognizes that market shocks cluster and exhibit memory effects. **Mathematical Foundation:** ``` Intensity λ(t) = μ + Σ α(t - Tᵢ) ``` Where market jumps at times Tᵢ increase the probability of future jumps through the decay function α, controlled by the Hawkes Decay parameter (0.5-0.99). **Mahalanobis Distance Calculation:** The engine calculates volatility jumps using multi-dimensional Mahalanobis distance across up to 5 volatility dimensions: - **Dimension 1:** Price volatility (standard deviation of returns) - **Dimension 2:** Volume volatility (normalized volume fluctuations) - **Dimension 3:** Range volatility (high-low spread variations) - **Dimension 4:** Correlation volatility (price-volume relationship changes) - **Dimension 5:** Microstructure volatility (intrabar positioning analysis) This creates a volatility state vector that captures market behavior impossible to detect with traditional single-dimensional approaches. ### 📐 Hurst Exponent Regime Detection **Fractal Market Hypothesis Integration:** The TMAE implements advanced Rescaled Range (R/S) analysis to calculate the Hurst exponent in real-time, providing dynamic regime classification: - **H > 0.6:** Trending (persistent) markets - momentum strategies optimal - **H < 0.4:** Mean-reverting (anti-persistent) markets - contrarian strategies optimal - **H ≈ 0.5:** Random walk markets - breakout strategies preferred **Adaptive R/S Analysis:** Unlike static implementations, the TMAE uses adaptive windowing that adjusts to market conditions: ``` H = log(R/S) / log(n) ``` Where R is the range of cumulative deviations and S is the standard deviation over period n. **Dynamic Regime Classification:** The system employs hysteresis to prevent regime flipping, requiring sustained Hurst values before regime changes are confirmed. This prevents false signals during transitional periods. ### 🔄 Transfer Entropy Analysis **Information Flow Quantification:** Transfer entropy measures the directional flow of information between price and volume, revealing lead-lag relationships that indicate future price movements: ``` TE(X→Y) = Σ p(yₜ₊₁, yₜ, xₜ) log ``` **Causality Detection:** - **Volume → Price:** Indicates accumulation/distribution phases - **Price → Volume:** Suggests retail participation or momentum chasing - **Balanced Flow:** Market equilibrium or transition periods The system analyzes multiple lag periods (2-20 bars) to capture both immediate and structural information flows. --- ## 🔧 COMPREHENSIVE INPUT SYSTEM ### Core Parameters Group **Primary Analysis Window (10-100, Default: 50)** The fundamental lookback period affecting all calculations. Optimization by timeframe: - **1-5 minute charts:** 20-30 (rapid adaptation to micro-movements) - **15 minute-1 hour:** 30-50 (balanced responsiveness and stability) - **4 hour-daily:** 50-100 (smooth signals, reduced noise) - **Asset-specific:** Cryptocurrency 20-35, Stocks 35-50, Forex 40-60 **Signal Sensitivity (0.1-2.0, Default: 0.7)** Master control affecting all threshold calculations: - **Conservative (0.3-0.6):** High-quality signals only, fewer false positives - **Balanced (0.7-1.0):** Optimal risk-reward ratio for most trading styles - **Aggressive (1.1-2.0):** Maximum signal frequency, requires careful filtering **Signal Generation Mode:** - **Aggressive:** Any component signals (highest frequency) - **Confluence:** 2+ components agree (balanced approach) - **Conservative:** All 3 components align (highest quality) ### Volatility Jump Detection Group **Volatility Dimensions (2-5, Default: 3)** Determines the mathematical space complexity: - **2D:** Price + Volume volatility (suitable for clean markets) - **3D:** + Range volatility (optimal for most conditions) - **4D:** + Correlation volatility (advanced multi-asset analysis) - **5D:** + Microstructure volatility (maximum sensitivity) **Jump Detection Threshold (1.5-4.0σ, Default: 3.0σ)** Standard deviations required for volatility jump classification: - **Cryptocurrency:** 2.0-2.5σ (naturally volatile) - **Stock Indices:** 2.5-3.0σ (moderate volatility) - **Forex Major Pairs:** 3.0-3.5σ (typically stable) - **Commodities:** 2.0-3.0σ (varies by commodity) **Jump Clustering Decay (0.5-0.99, Default: 0.85)** Hawkes process memory parameter: - **0.5-0.7:** Fast decay (jumps treated as independent) - **0.8-0.9:** Moderate clustering (realistic market behavior) - **0.95-0.99:** Strong clustering (crisis/event-driven markets) ### Hurst Exponent Analysis Group **Calculation Method Options:** - **Classic R/S:** Original Rescaled Range (fast, simple) - **Adaptive R/S:** Dynamic windowing (recommended for trading) - **DFA:** Detrended Fluctuation Analysis (best for noisy data) **Trending Threshold (0.55-0.8, Default: 0.60)** Hurst value defining persistent market behavior: - **0.55-0.60:** Weak trend persistence - **0.65-0.70:** Clear trending behavior - **0.75-0.80:** Strong momentum regimes **Mean Reversion Threshold (0.2-0.45, Default: 0.40)** Hurst value defining anti-persistent behavior: - **0.35-0.45:** Weak mean reversion - **0.25-0.35:** Clear ranging behavior - **0.15-0.25:** Strong reversion tendency ### Transfer Entropy Parameters Group **Information Flow Analysis:** - **Price-Volume:** Classic flow analysis for accumulation/distribution - **Price-Volatility:** Risk flow analysis for sentiment shifts - **Multi-Timeframe:** Cross-timeframe causality detection **Maximum Lag (2-20, Default: 5)** Causality detection window: - **2-5 bars:** Immediate causality (scalping) - **5-10 bars:** Short-term flow (day trading) - **10-20 bars:** Structural flow (swing trading) **Significance Threshold (0.05-0.3, Default: 0.15)** Minimum entropy for signal generation: - **0.05-0.10:** Detect subtle information flows - **0.10-0.20:** Clear causality only - **0.20-0.30:** Very strong flows only --- ## 🎨 ADVANCED VISUAL SYSTEM ### Tensor Volatility Field Visualization **Five-Layer Resonance Bands:** The tensor field creates dynamic support/resistance zones that expand and contract based on mathematical field strength: - **Core Layer (Purple):** Primary tensor field with highest intensity - **Layer 2 (Neutral):** Secondary mathematical resonance - **Layer 3 (Info Blue):** Tertiary harmonic frequencies - **Layer 4 (Warning Gold):** Outer field boundaries - **Layer 5 (Success Green):** Maximum field extension **Field Strength Calculation:** ``` Field Strength = min(3.0, Mahalanobis Distance × Tensor Intensity) ``` The field amplitude adjusts to ATR and mathematical distance, creating dynamic zones that respond to market volatility. **Radiation Line Network:** During active tensor states, the system projects directional radiation lines showing field energy distribution: - **8 Directional Rays:** Complete angular coverage - **Tapering Segments:** Progressive transparency for natural visual flow - **Pulse Effects:** Enhanced visualization during volatility jumps ### Dimensional Portal System **Portal Mathematics:** Dimensional portals visualize regime transitions using category theory principles: - **Green Portals (◉):** Trending regime detection (appear below price for support) - **Red Portals (◎):** Mean-reverting regime (appear above price for resistance) - **Yellow Portals (○):** Random walk regime (neutral positioning) **Tensor Trail Effects:** Each portal generates 8 trailing particles showing mathematical momentum: - **Large Particles (●):** Strong mathematical signal - **Medium Particles (◦):** Moderate signal strength - **Small Particles (·):** Weak signal continuation - **Micro Particles (˙):** Signal dissipation ### Information Flow Streams **Particle Stream Visualization:** Transfer entropy creates flowing particle streams indicating information direction: - **Upward Streams:** Volume leading price (accumulation phases) - **Downward Streams:** Price leading volume (distribution phases) - **Stream Density:** Proportional to information flow strength **15-Particle Evolution:** Each stream contains 15 particles with progressive sizing and transparency, creating natural flow visualization that makes information transfer immediately apparent. ### Fractal Matrix Grid System **Multi-Timeframe Fractal Levels:** The system calculates and displays fractal highs/lows across five Fibonacci periods: - **8-Period:** Short-term fractal structure - **13-Period:** Intermediate-term patterns - **21-Period:** Primary swing levels - **34-Period:** Major structural levels - **55-Period:** Long-term fractal boundaries **Triple-Layer Visualization:** Each fractal level uses three-layer rendering: - **Shadow Layer:** Widest, darkest foundation (width 5) - **Glow Layer:** Medium white core line (width 3) - **Tensor Layer:** Dotted mathematical overlay (width 1) **Intelligent Labeling System:** Smart spacing prevents label overlap using ATR-based minimum distances. Labels include: - **Fractal Period:** Time-based identification - **Topological Class:** Mathematical complexity rating (0, I, II, III) - **Price Level:** Exact fractal price - **Mahalanobis Distance:** Current mathematical field strength - **Hurst Exponent:** Current regime classification - **Anomaly Indicators:** Visual strength representations (○ ◐ ● ⚡) ### Wick Pressure Analysis **Rejection Level Mathematics:** The system analyzes candle wick patterns to project future pressure zones: - **Upper Wick Analysis:** Identifies selling pressure and resistance zones - **Lower Wick Analysis:** Identifies buying pressure and support zones - **Pressure Projection:** Extends lines forward based on mathematical probability **Multi-Layer Glow Effects:** Wick pressure lines use progressive transparency (1-8 layers) creating natural glow effects that make pressure zones immediately visible without cluttering the chart. ### Enhanced Regime Background **Dynamic Intensity Mapping:** Background colors reflect mathematical regime strength: - **Deep Transparency (98% alpha):** Subtle regime indication - **Pulse Intensity:** Based on regime strength calculation - **Color Coding:** Green (trending), Red (mean-reverting), Neutral (random) **Smoothing Integration:** Regime changes incorporate 10-bar smoothing to prevent background flicker while maintaining responsiveness to genuine regime shifts. ### Color Scheme System **Six Professional Themes:** - **Dark (Default):** Professional trading environment optimization - **Light:** High ambient light conditions - **Classic:** Traditional technical analysis appearance - **Neon:** High-contrast visibility for active trading - **Neutral:** Minimal distraction focus - **Bright:** Maximum visibility for complex setups Each theme maintains mathematical accuracy while optimizing visual clarity for different trading environments and personal preferences. --- ## 📊 INSTITUTIONAL-GRADE DASHBOARD ### Tensor Field Status Section **Field Strength Display:** Real-time Mahalanobis distance calculation with dynamic emoji indicators: - **⚡ (Lightning):** Extreme field strength (>1.5× threshold) - **● (Solid Circle):** Strong field activity (>1.0× threshold) - **○ (Open Circle):** Normal field state **Signal Quality Rating:** Democratic algorithm assessment: - **ELITE:** All 3 components aligned (highest probability) - **STRONG:** 2 components aligned (good probability) - **GOOD:** 1 component active (moderate probability) - **WEAK:** No clear component signals **Threshold and Anomaly Monitoring:** - **Threshold Display:** Current mathematical threshold setting - **Anomaly Level (0-100%):** Combined volatility and volume spike measurement - **>70%:** High anomaly (red warning) - **30-70%:** Moderate anomaly (orange caution) - **<30%:** Normal conditions (green confirmation) ### Tensor State Analysis Section **Mathematical State Classification:** - **↑ BULL (Tensor State +1):** Trending regime with bullish bias - **↓ BEAR (Tensor State -1):** Mean-reverting regime with bearish bias - **◈ SUPER (Tensor State 0):** Random walk regime (neutral) **Visual State Gauge:** Five-circle progression showing tensor field polarity: - **🟢🟢🟢⚪⚪:** Strong bullish mathematical alignment - **⚪⚪🟡⚪⚪:** Neutral/transitional state - **⚪⚪🔴🔴🔴:** Strong bearish mathematical alignment **Trend Direction and Phase Analysis:** - **📈 BULL / 📉 BEAR / ➡️ NEUTRAL:** Primary trend classification - **🌪️ CHAOS:** Extreme information flow (>2.0 flow strength) - **⚡ ACTIVE:** Strong information flow (1.0-2.0 flow strength) - **😴 CALM:** Low information flow (<1.0 flow strength) ### Trading Signals Section **Real-Time Signal Status:** - **🟢 ACTIVE / ⚪ INACTIVE:** Long signal availability - **🔴 ACTIVE / ⚪ INACTIVE:** Short signal availability - **Components (X/3):** Active algorithmic components - **Mode Display:** Current signal generation mode **Signal Strength Visualization:** Color-coded component count: - **Green:** 3/3 components (maximum confidence) - **Aqua:** 2/3 components (good confidence) - **Orange:** 1/3 components (moderate confidence) - **Gray:** 0/3 components (no signals) ### Performance Metrics Section **Win Rate Monitoring:** Estimated win rates based on signal quality with emoji indicators: - **🔥 (Fire):** ≥60% estimated win rate - **👍 (Thumbs Up):** 45-59% estimated win rate - **⚠️ (Warning):** <45% estimated win rate **Mathematical Metrics:** - **Hurst Exponent:** Real-time fractal dimension (0.000-1.000) - **Information Flow:** Volume/price leading indicators - **📊 VOL:** Volume leading price (accumulation/distribution) - **💰 PRICE:** Price leading volume (momentum/speculation) - **➖ NONE:** Balanced information flow - **Volatility Classification:** - **🔥 HIGH:** Above 1.5× jump threshold - **📊 NORM:** Normal volatility range - **😴 LOW:** Below 0.5× jump threshold ### Market Structure Section (Large Dashboard) **Regime Classification:** - **📈 TREND:** Hurst >0.6, momentum strategies optimal - **🔄 REVERT:** Hurst <0.4, contrarian strategies optimal - **🎲 RANDOM:** Hurst ≈0.5, breakout strategies preferred **Mathematical Field Analysis:** - **Dimensions:** Current volatility space complexity (2D-5D) - **Hawkes λ (Lambda):** Self-exciting jump intensity (0.00-1.00) - **Jump Status:** 🚨 JUMP (active) / ✅ NORM (normal) ### Settings Summary Section (Large Dashboard) **Active Configuration Display:** - **Sensitivity:** Current master sensitivity setting - **Lookback:** Primary analysis window - **Theme:** Active color scheme - **Method:** Hurst calculation method (Classic R/S, Adaptive R/S, DFA) **Dashboard Sizing Options:** - **Small:** Essential metrics only (mobile/small screens) - **Normal:** Balanced information density (standard desktop) - **Large:** Maximum detail (multi-monitor setups) **Position Options:** - **Top Right:** Standard placement (avoids price action) - **Top Left:** Wide chart optimization - **Bottom Right:** Recent price focus (scalping) - **Bottom Left:** Maximum price visibility (swing trading) --- ## 🎯 SIGNAL GENERATION LOGIC ### Multi-Component Convergence System **Component Signal Architecture:** The TMAE generates signals through sophisticated component analysis rather than simple threshold crossing: **Volatility Component:** - **Jump Detection:** Mahalanobis distance threshold breach - **Hawkes Intensity:** Self-exciting process activation (>0.2) - **Multi-dimensional:** Considers all volatility dimensions simultaneously **Hurst Regime Component:** - **Trending Markets:** Price above SMA-20 with positive momentum - **Mean-Reverting Markets:** Price at Bollinger Band extremes - **Random Markets:** Bollinger squeeze breakouts with directional confirmation **Transfer Entropy Component:** - **Volume Leadership:** Information flow from volume to price - **Volume Spike:** Volume 110%+ above 20-period average - **Flow Significance:** Above entropy threshold with directional bias ### Democratic Signal Weighting **Signal Mode Implementation:** - **Aggressive Mode:** Any single component triggers signal - **Confluence Mode:** Minimum 2 components must agree - **Conservative Mode:** All 3 components must align **Momentum Confirmation:** All signals require momentum confirmation: - **Long Signals:** RSI >50 AND price >EMA-9 - **Short Signals:** RSI <50 AND price 0.6):** - **Increase Sensitivity:** Catch momentum continuation - **Lower Mean Reversion Threshold:** Avoid counter-trend signals - **Emphasize Volume Leadership:** Institutional accumulation/distribution - **Tensor Field Focus:** Use expansion for trend continuation - **Signal Mode:** Aggressive or Confluence for trend following **Range-Bound Markets (Hurst <0.4):** - **Decrease Sensitivity:** Avoid false breakouts - **Lower Trending Threshold:** Quick regime recognition - **Focus on Price Leadership:** Retail sentiment extremes - **Fractal Grid Emphasis:** Support/resistance trading - **Signal Mode:** Conservative for high-probability reversals **Volatile Markets (High Jump Frequency):** - **Increase Hawkes Decay:** Recognize event clustering - **Higher Jump Threshold:** Avoid noise signals - **Maximum Dimensions:** Capture full volatility complexity - **Reduce Position Sizing:** Risk management adaptation - **Enhanced Visuals:** Maximum information for rapid decisions **Low Volatility Markets (Low Jump Frequency):** - **Decrease Jump Threshold:** Capture subtle movements - **Lower Hawkes Decay:** Treat moves as independent - **Reduce Dimensions:** Simplify analysis - **Increase Position Sizing:** Capitalize on compressed volatility - **Minimal Visuals:** Reduce distraction in quiet markets --- ## 🚀 ADVANCED TRADING STRATEGIES ### The Mathematical Convergence Method **Entry Protocol:** 1. **Fractal Grid Approach:** Monitor price approaching significant fractal levels 2. **Tensor Field Confirmation:** Verify field expansion supporting direction 3. **Portal Signal:** Wait for dimensional portal appearance 4. **ELITE/STRONG Quality:** Only trade highest quality mathematical signals 5. **Component Consensus:** Confirm 2+ components agree in Confluence mode **Example Implementation:** - Price approaching 21-period fractal high - Tensor field expanding upward (bullish mathematical alignment) - Green portal appears below price (trending regime confirmation) - ELITE quality signal with 3/3 components active - Enter long position with stop below fractal level **Risk Management:** - **Stop Placement:** Below/above fractal level that generated signal - **Position Sizing:** Based on Mahalanobis distance (higher distance = smaller size) - **Profit Targets:** Next fractal level or tensor field resistance ### The Regime Transition Strategy **Regime Change Detection:** 1. **Monitor Hurst Exponent:** Watch for persistent moves above/below thresholds 2. **Portal Color Change:** Regime transitions show different portal colors 3. **Background Intensity:** Increasing regime background intensity 4. **Mathematical Confirmation:** Wait for regime confirmation (hysteresis) **Trading Implementation:** - **Trending Transitions:** Trade momentum breakouts, follow trend - **Mean Reversion Transitions:** Trade range boundaries, fade extremes - **Random Transitions:** Trade breakouts with tight stops **Advanced Techniques:** - **Multi-Timeframe:** Confirm regime on higher timeframe - **Early Entry:** Enter on regime transition rather than confirmation - **Regime Strength:** Larger positions during strong regime signals ### The Information Flow Momentum Strategy **Flow Detection Protocol:** 1. **Monitor Transfer Entropy:** Watch for significant information flow shifts 2. **Volume Leadership:** Strong edge when volume leads price 3. **Flow Acceleration:** Increasing flow strength indicates momentum 4. **Directional Confirmation:** Ensure flow aligns with intended trade direction **Entry Signals:** - **Volume → Price Flow:** Enter during accumulation/distribution phases - **Price → Volume Flow:** Enter on momentum confirmation breaks - **Flow Reversal:** Counter-trend entries when flow reverses **Optimization:** - **Scalping:** Use immediate flow detection (2-5 bar lag) - **Swing Trading:** Use structural flow (10-20 bar lag) - **Multi-Asset:** Compare flow between correlated assets ### The Tensor Field Expansion Strategy **Field Mathematics:** The tensor field expansion indicates mathematical pressure building in market structure: **Expansion Phases:** 1. **Compression:** Field contracts, volatility decreases 2. **Tension Building:** Mathematical pressure accumulates 3. **Expansion:** Field expands rapidly with directional movement 4. **Resolution:** Field stabilizes at new equilibrium **Trading Applications:** - **Compression Trading:** Prepare for breakout during field contraction - **Expansion Following:** Trade direction of field expansion - **Reversion Trading:** Fade extreme field expansion - **Multi-Dimensional:** Consider all field layers for confirmation ### The Hawkes Process Event Strategy **Self-Exciting Jump Trading:** Understanding that market shocks cluster and create follow-on opportunities: **Jump Sequence Analysis:** 1. **Initial Jump:** First volatility jump detected 2. **Clustering Phase:** Hawkes intensity remains elevated 3. **Follow-On Opportunities:** Additional jumps more likely 4. **Decay Period:** Intensity gradually decreases **Implementation:** - **Jump Confirmation:** Wait for mathematical jump confirmation - **Direction Assessment:** Use other components for direction - **Clustering Trades:** Trade subsequent moves during high intensity - **Decay Exit:** Exit positions as Hawkes intensity decays ### The Fractal Confluence System **Multi-Timeframe Fractal Analysis:** Combining fractal levels across different periods for high-probability zones: **Confluence Zones:** - **Double Confluence:** 2 fractal levels align - **Triple Confluence:** 3+ fractal levels cluster - **Mathematical Confirmation:** Tensor field supports the level - **Information Flow:** Transfer entropy confirms direction **Trading Protocol:** 1. **Identify Confluence:** Find 2+ fractal levels within 1 ATR 2. **Mathematical Support:** Verify tensor field alignment 3. **Signal Quality:** Wait for STRONG or ELITE signal 4. **Risk Definition:** Use fractal level for stop placement 5. **Profit Targeting:** Next major fractal confluence zone --- ## ⚠️ COMPREHENSIVE RISK MANAGEMENT ### Mathematical Position Sizing **Mahalanobis Distance Integration:** Position size should inversely correlate with mathematical field strength: ``` Position Size = Base Size × (Threshold / Mahalanobis Distance) ``` **Risk Scaling Matrix:** - **Low Field Strength (<2.0):** Standard position sizing - **Moderate Field Strength (2.0-3.0):** 75% position sizing - **High Field Strength (3.0-4.0):** 50% position sizing - **Extreme Field Strength (>4.0):** 25% position sizing or no trade ### Signal Quality Risk Adjustment **Quality-Based Position Sizing:** - **ELITE Signals:** 100% of planned position size - **STRONG Signals:** 75% of planned position size - **GOOD Signals:** 50% of planned position size - **WEAK Signals:** No position or paper trading only **Component Agreement Scaling:** - **3/3 Components:** Full position size - **2/3 Components:** 75% position size - **1/3 Components:** 50% position size or skip trade ### Regime-Adaptive Risk Management **Trending Market Risk:** - **Wider Stops:** Allow for trend continuation - **Trend Following:** Trade with regime direction - **Higher Position Size:** Trend probability advantage - **Momentum Stops:** Trail stops based on momentum indicators **Mean-Reverting Market Risk:** - **Tighter Stops:** Quick exits on trend continuation - **Contrarian Positioning:** Trade against extremes - **Smaller Position Size:** Higher reversal failure rate - **Level-Based Stops:** Use fractal levels for stops **Random Market Risk:** - **Breakout Focus:** Trade only clear breakouts - **Tight Initial Stops:** Quick exit if breakout fails - **Reduced Frequency:** Skip marginal setups - **Range-Based Targets:** Profit targets at range boundaries ### Volatility-Adaptive Risk Controls **High Volatility Periods:** - **Reduced Position Size:** Account for wider price swings - **Wider Stops:** Avoid noise-based exits - **Lower Frequency:** Skip marginal setups - **Faster Exits:** Take profits more quickly **Low Volatility Periods:** - **Standard Position Size:** Normal risk parameters - **Tighter Stops:** Take advantage of compressed ranges - **Higher Frequency:** Trade more setups - **Extended Targets:** Allow for compressed volatility expansion ### Multi-Timeframe Risk Alignment **Higher Timeframe Trend:** - **With Trend:** Standard or increased position size - **Against Trend:** Reduced position size or skip - **Neutral Trend:** Standard position size with tight management **Risk Hierarchy:** 1. **Primary:** Current timeframe signal quality 2. **Secondary:** Higher timeframe trend alignment 3. **Tertiary:** Mathematical field strength 4. **Quaternary:** Market regime classification --- ## 📚 EDUCATIONAL VALUE AND MATHEMATICAL CONCEPTS ### Advanced Mathematical Concepts **Tensor Analysis in Markets:** The TMAE introduces traders to tensor analysis, a branch of mathematics typically reserved for physics and advanced engineering. Tensors provide a framework for understanding multi-dimensional market relationships that scalar and vector analysis cannot capture. **Information Theory Applications:** Transfer entropy implementation teaches traders about information flow in markets, a concept from information theory that quantifies directional causality between variables. This provides intuition about market microstructure and participant behavior. **Fractal Geometry in Trading:** The Hurst exponent calculation exposes traders to fractal geometry concepts, helping understand that markets exhibit self-similar patterns across multiple timeframes. This mathematical insight transforms how traders view market structure. **Stochastic Process Theory:** The Hawkes process implementation introduces concepts from stochastic process theory, specifically self-exciting point processes. This provides mathematical framework for understanding why market events cluster and exhibit memory effects. ### Learning Progressive Complexity **Beginner Mathematical Concepts:** - **Volatility Dimensions:** Understanding multi-dimensional analysis - **Regime Classification:** Learning market personality types - **Signal Democracy:** Algorithmic consensus building - **Visual Mathematics:** Interpreting mathematical concepts visually **Intermediate Mathematical Applications:** - **Mahalanobis Distance:** Statistical distance in multi-dimensional space - **Rescaled Range Analysis:** Fractal dimension measurement - **Information Entropy:** Quantifying uncertainty and causality - **Field Theory:** Understanding mathematical fields in market context **Advanced Mathematical Integration:** - **Tensor Field Dynamics:** Multi-dimensional market force analysis - **Stochastic Self-Excitation:** Event clustering and memory effects - **Categorical Composition:** Mathematical signal combination theory - **Topological Market Analysis:** Understanding market shape and connectivity ### Practical Mathematical Intuition **Developing Market Mathematics Intuition:** The TMAE serves as a bridge between abstract mathematical concepts and practical trading applications. Traders develop intuitive understanding of: - **How markets exhibit mathematical structure beneath apparent randomness** - **Why multi-dimensional analysis reveals patterns invisible to single-variable approaches** - **How information flows through markets in measurable, predictable ways** - **Why mathematical models provide probabilistic edges rather than certainties** --- ## 🔬 IMPLEMENTATION AND OPTIMIZATION ### Getting Started Protocol **Phase 1: Observation (Week 1)** 1. **Apply with defaults:** Use standard settings on your primary trading timeframe 2. **Study visual elements:** Learn to interpret tensor fields, portals, and streams 3. **Monitor dashboard:** Observe how metrics change with market conditions 4. **No trading:** Focus entirely on pattern recognition and understanding **Phase 2: Pattern Recognition (Week 2-3)** 1. **Identify signal patterns:** Note what market conditions produce different signal qualities 2. **Regime correlation:** Observe how Hurst regimes affect signal performance 3. **Visual confirmation:** Learn to read tensor field expansion and portal signals 4. **Component analysis:** Understand which components drive signals in different markets **Phase 3: Parameter Optimization (Week 4-5)** 1. **Asset-specific tuning:** Adjust parameters for your specific trading instrument 2. **Timeframe optimization:** Fine-tune for your preferred trading timeframe 3. **Sensitivity adjustment:** Balance signal frequency with quality 4. **Visual customization:** Optimize colors and intensity for your trading environment **Phase 4: Live Implementation (Week 6+)** 1. **Paper trading:** Test signals with hypothetical trades 2. **Small position sizing:** Begin with minimal risk during learning phase 3. **Performance tracking:** Monitor actual vs. expected signal performance 4. **Continuous optimization:** Refine settings based on real performance data ### Performance Monitoring System **Signal Quality Tracking:** - **ELITE Signal Win Rate:** Track highest quality signals separately - **Component Performance:** Monitor which components provide best signals - **Regime Performance:** Analyze performance across different market regimes - **Timeframe Analysis:** Compare performance across different session times **Mathematical Metric Correlation:** - **Field Strength vs. Performance:** Higher field strength should correlate with better performance - **Component Agreement vs. Win Rate:** More component agreement should improve win rates - **Regime Alignment vs. Success:** Trading with mathematical regime should outperform ### Continuous Optimization Process **Monthly Review Protocol:** 1. **Performance Analysis:** Review win rates, profit factors, and maximum drawdown 2. **Parameter Assessment:** Evaluate if current settings remain optimal 3. **Market Adaptation:** Adjust for changes in market character or volatility 4. **Component Weighting:** Consider if certain components should receive more/less emphasis **Quarterly Deep Analysis:** 1. **Mathematical Model Validation:** Verify that mathematical relationships remain valid 2. **Regime Distribution:** Analyze time spent in different market regimes 3. **Signal Evolution:** Track how signal characteristics change over time 4. **Correlation Analysis:** Monitor correlations between different mathematical components --- ## 🌟 UNIQUE INNOVATIONS AND CONTRIBUTIONS ### Revolutionary Mathematical Integration **First-Ever Implementations:** 1. **Multi-Dimensional Volatility Tensor:** First indicator to implement true tensor analysis for market volatility 2. **Real-Time Hawkes Process:** First trading implementation of self-exciting point processes 3. **Transfer Entropy Trading Signals:** First practical application of information theory for trade generation 4. **Democratic Component Voting:** First algorithmic consensus system for signal generation 5. **Fractal-Projected Signal Quality:** First system to predict signal quality at future price levels ### Advanced Visualization Innovations **Mathematical Visualization Breakthroughs:** - **Tensor Field Radiation:** Visual representation of mathematical field energy - **Dimensional Portal System:** Category theory visualization for regime transitions - **Information Flow Streams:** Real-time visual display of market information transfer - **Multi-Layer Fractal Grid:** Intelligent spacing and projection system - **Regime Intensity Mapping:** Dynamic background showing mathematical regime strength ### Practical Trading Innovations **Trading System Advances:** - **Quality-Weighted Signal Generation:** Signals rated by mathematical confidence - **Regime-Adaptive Strategy Selection:** Automatic strategy optimization based on market personality - **Anti-Spam Signal Protection:** Mathematical prevention of signal clustering - **Component Performance Tracking:** Real-time monitoring of algorithmic component success - **Field-Strength Position Sizing:** Mathematical volatility integration for risk management --- ## ⚖️ RESPONSIBLE USAGE AND LIMITATIONS ### Mathematical Model Limitations **Understanding Model Boundaries:** While the TMAE implements sophisticated mathematical concepts, traders must understand fundamental limitations: - **Markets Are Not Purely Mathematical:** Human psychology, news events, and fundamental factors create unpredictable elements - **Past Performance Limitations:** Mathematical relationships that worked historically may not persist indefinitely - **Model Risk:** Complex models can fail during unprecedented market conditions - **Overfitting Potential:** Highly optimized parameters may not generalize to future market conditions ### Proper Implementation Guidelines **Risk Management Requirements:** - **Never Risk More Than 2% Per Trade:** Regardless of signal quality - **Diversification Mandatory:** Don't rely solely on mathematical signals - **Position Sizing Discipline:** Use mathematical field strength for sizing, not confidence - **Stop Loss Non-Negotiable:** Every trade must have predefined risk parameters **Realistic Expectations:** - **Mathematical Edge, Not Certainty:** The indicator provides probabilistic advantages, not guaranteed outcomes - **Learning Curve Required:** Complex mathematical concepts require time to master - **Market Adaptation Necessary:** Parameters must evolve with changing market conditions - **Continuous Education Important:** Understanding underlying mathematics improves application ### Ethical Trading Considerations **Market Impact Awareness:** - **Information Asymmetry:** Advanced mathematical analysis may provide advantages over other market participants - **Position Size Responsibility:** Large positions based on mathematical signals can impact market structure - **Sharing Knowledge:** Consider educational contributions to trading community - **Fair Market Participation:** Use mathematical advantages responsibly within market framework ### Professional Development Path **Skill Development Sequence:** 1. **Basic Mathematical Literacy:** Understand fundamental concepts before advanced application 2. **Risk Management Mastery:** Develop disciplined risk control before relying on complex signals 3. **Market Psychology Understanding:** Combine mathematical analysis with behavioral market insights 4. **Continuous Learning:** Stay updated on mathematical finance developments and market evolution --- ## 🔮 CONCLUSION The Tensor Market Analysis Engine represents a quantum leap forward in technical analysis, successfully bridging the gap between advanced pure mathematics and practical trading applications. By integrating multi-dimensional volatility analysis, fractal market theory, and information flow dynamics, the TMAE reveals market structure invisible to conventional analysis while maintaining visual clarity and practical usability. ### Mathematical Innovation Legacy This indicator establishes new paradigms in technical analysis: - **Tensor analysis for market volatility understanding** - **Stochastic self-excitation for event clustering prediction** - **Information theory for causality-based trade generation** - **Democratic algorithmic consensus for signal quality enhancement** - **Mathematical field visualization for intuitive market understanding** ### Practical Trading Revolution Beyond mathematical innovation, the TMAE transforms practical trading: - **Quality-rated signals replace binary buy/sell decisions** - **Regime-adaptive strategies automatically optimize for market personality** - **Multi-dimensional risk management integrates mathematical volatility measures** - **Visual mathematical concepts make complex analysis immediately interpretable** - **Educational value creates lasting improvement in trading understanding** ### Future-Proof Design The mathematical foundations ensure lasting relevance: - **Universal mathematical principles transcend market evolution** - **Multi-dimensional analysis adapts to new market structures** - **Regime detection automatically adjusts to changing market personalities** - **Component democracy allows for future algorithmic additions** - **Mathematical visualization scales with increasing market complexity** ### Commitment to Excellence The TMAE represents more than an indicator—it embodies a philosophy of bringing rigorous mathematical analysis to trading while maintaining practical utility and visual elegance. Every component, from the multi-dimensional tensor fields to the democratic signal generation, reflects a commitment to mathematical accuracy, trading practicality, and educational value. ### Trading with Mathematical Precision In an era where markets grow increasingly complex and computational, the TMAE provides traders with mathematical tools previously available only to institutional quantitative research teams. Yet unlike academic mathematical models, the TMAE translates complex concepts into intuitive visual representations and practical trading signals. By combining the mathematical rigor of tensor analysis, the statistical power of multi-dimensional volatility modeling, and the information-theoretic insights of transfer entropy, traders gain unprecedented insight into market structure and dynamics. ### Final Perspective Markets, like nature, exhibit profound mathematical beauty beneath apparent chaos. The Tensor Market Analysis Engine serves as a mathematical lens that reveals this hidden order, transforming how traders perceive and interact with market structure. Through mathematical precision, visual elegance, and practical utility, the TMAE empowers traders to see beyond the noise and trade with the confidence that comes from understanding the mathematical principles governing market behavior. Trade with mathematical insight. Trade with the power of tensors. Trade with the TMAE. *"In mathematics, you don't understand things. You just get used to them." - John von Neumann* *With the TMAE, mathematical market understanding becomes not just possible, but intuitive.* — Dskyz, Trade with insight. Trade with anticipation.
Penunjuk Pine Script®
oleh DskyzInvestments
10
Share SizePurpose: The "Share Size" indicator is a powerful risk management tool designed to help traders quickly determine appropriate share/contract sizes based on their predefined risk per trade and the current market's volatility (measured by ATR). It calculates potential dollar differences from recent highs/lows and translates them into a recommended share/contract size, accounting for a user-defined ATR-based offset. This helps you maintain consistent risk exposure across different instruments and market conditions. How It Works: At its core, the indicator aims to answer the question: "How many shares/contracts can I trade to keep my dollar risk within limits if my stop loss is placed at a recent high or low, plus an ATR-based buffer?" Price Difference Calculation: It first calculates the dollar difference between the current close price and the high and low of the current bar (Now) and the previous 5 bars (1 to 5). Tick Size & Value Conversion: These price differences are then converted into dollar values using the instrument's specific tickSize and tickValue. You can select common futures contracts (MNQ, MES, MGC, MCL), a generic "Stock" setting, or define custom values. ATR Offset: An Average True Range (ATR) based offset is added to these dollar differences. This offset acts as a buffer, simulating a stop loss placed beyond the immediate high/low, accounting for market noise or volatility. Risk-Based Share Size: Finally, using your Default Risk ($) input, the indicator calculates how many shares/contracts you can take for each of the 6 high/low scenarios (current bar, 5 previous bars) to ensure your dollar risk per trade remains constant. Dynamic Table: All these calculations are presented in a clear, real-time table at the bottom-left of your chart. The table dynamically adjusts its "Label" to show the selected symbol preset, making it easy to see which instrument's settings are currently being used. The "Shares" rows indicate the maximum shares/contracts you can trade for a given risk and stop placement. The cells corresponding to the largest dollar difference (and thus smallest share size) for both high and low scenarios are highlighted, drawing your attention to the most conservative entry points. Key Benefits: Consistent Risk: Helps maintain a consistent dollar risk per trade, regardless of the instrument or its current price/volatility. Dynamic Sizing: Automatically adjusts share/contract size based on market volatility and your chosen stop placement. Quick Reference: Provides a real-time, easy-to-read table directly on your chart, eliminating manual calculations. Informed Decision Making: Assists in quickly assessing trade opportunities and potential position sizes. Setup Parameters (Inputs) When you add the "Share Size" indicator to your chart, you'll see a settings dialog with the following parameters: 1. Symbol Preset: Purpose: This is the primary setting to define the tick size and value for your chosen trading instrument. Options: MNQ (Micro Nasdaq 100 Futures) MES (Micro E-mini S&P 500 Futures) MGC (Micro Gold Futures) MCL (Micro Crude Oil Futures) Stock (Generic stock setting, with tick size/value of 0.01) Custom (Allows you to manually input tick size and value) Default: MNQ Importance: Crucial for accurate dollar calculations. Ensure this matches the instrument you are trading. 2. Tick Size (Manual Override): Purpose: Only used if Symbol Preset is set to Custom. This defines the smallest price increment for your instrument. Type: Float Default: 0.25 Hidden: This input is hidden (display=display.none) unless "Custom" is selected. You might need to change display=display.none to display=display.inline in the code if you want to see and adjust it directly in the settings for "Custom" mode. 3. Tick Value (Manual Override): Purpose: Only used if Symbol Preset is set to Custom. This defines the dollar value of one tickSize increment. Type: Float Default: 0.50 Hidden: This input is hidden (display=display.none) unless "Custom" is selected. Similar to Tick Size, you might need to adjust its display property if you want it visible. 4. Default Risk ($): Purpose: This is your maximum desired dollar risk per trade. All share size calculations will be based on this value. Type: Float Default: 50.0 Hidden: This input is hidden (display=display.none). It's a critical setting, so consider making it visible by changing display=display.none to display=display.inline in the code if you want users to easily adjust their risk. ATR Offset Settings (Group): This group of settings allows you to fine-tune the ATR-based buffer added to your potential stop loss. 5. ATR Offset Length: Purpose: Defines the lookback period for the Average True Range (ATR) calculation used for the offset. Type: Integer Default: 7 Hidden: This input is hidden (display=display.none). 6. ATR Offset Timeframe: Purpose: Specifies the timeframe on which the ATR for the offset will be calculated. This allows you to use ATR from a higher timeframe for your stop buffer, even if your chart is on a lower timeframe. Type: Timeframe string (e.g., "1" for 1 minute, "60" for 1 hour, "D" for Daily) Default: "1" (1 Minute) Hidden: This input is hidden (display=display.none). 7. ATR Offset Multiplier (x ATR): Purpose: Multiplies the calculated ATR value to determine the final dollar offset added to your high/low price difference. A value of 1.0 means one full ATR is added. A value of 0.5 means half an ATR is added. Type: Float Minimum Value: 0 (no offset) Default: 1.0 Hidden: This input is hidden (display=display.none).
Penunjuk Pine Script®
oleh rduatg
Simple Pips GridOverview This is a clean, simple, and highly practical indicator that draws horizontal grid lines at user-defined pip intervals. Unlike other complex grid indicators, this script is designed to be lightweight and error-free. It eliminates automatic symbol detection and instead gives you full manual control, ensuring it works perfectly with any symbol you trade—FX, CFDs, Crypto, Stocks, Indices, and more. Key Features Universal Compatibility: Works with any trading pair by letting you manually define the pip value. Fully Customizable: Easily set the pip interval for your grid (e.g., 10 pips, 50 pips, 100 pips). Lightweight & Fast: Simple code ensures smooth performance without lagging your chart. Visual Customization: Change the color, width, and style (solid, dashed, dotted) of the grid lines. How to Use It's incredibly simple to set up. You only need to configure two main settings: Step 1: Set the "Pip Value" This is the most important setting. You need to tell the indicator what "1 pip" means for the symbol you are currently viewing. Go to the indicator settings and find the "Pip Value" input. Here are some common examples: Symbol Pip Value (Input this number) USD/JPY 0.01 EUR/USD 0.0001 GBP/USD 0.0001 XAU/USD (Gold) 0.1 JP225 (Nikkei 225) 10 US500 (S&P 500) 1 BTC/USD 0.1 or 1.0 (depending on your preference) Step 2: Set the "Pip Interval" Next, in the "Pip Interval" input, simply type how many pips you want between each line. For a 10-pip grid, enter 10. For a 50-pip grid, enter 50. That's it! The grid will now be perfectly aligned to your specifications. Additional Settings Line Color, Width, Style: Customize the appearance of the lines to match your chart theme. Number of Lines: Adjust how many lines are drawn above and below the current price to optimize performance and visibility. This script was created with the assistance of Gemini (Google's AI) to be a simple and reliable tool for all traders. Feel free to use and modify it. Happy trading!
Penunjuk Pine Script®
oleh knjk