Mulai

Educational

EZ Range MACD + DASH - ELECTZA**EZ Range MACD + DASH – ELECTZA** A streamlined MACD momentum indicator built to reduce false signals in choppy markets. It combines a classic **MACD + Signal + Histogram** display with an **ATR-based range detector** that identifies low-volatility compression zones. When the market is ranging, momentum is muted and the script prioritizes “WAIT” conditions to help you avoid noise. Clear **BUY/SELL arrows** print only when MACD crossovers occur outside of detected range conditions. The built-in **dashboard** (bottom-right) gives a quick at-a-glance read of the **Overall Market State** (Bullish / Bearish / Ranging) plus the current **trade recommendation** (Buy / Sell / Wait), making it easy to track momentum and market quality without clutter. **Disclaimer:** This indicator/script is provided for **educational and informational purposes only** and does **not** constitute financial, investment, or trading advice. Trading and investing involve **significant risk**, and you may lose some or all of your capital. Past performance is **not** indicative of future results. Always do your own research, use proper risk management, and consider consulting a qualified financial professional. By using this script, you agree that you are solely responsible for any trading decisions and outcomes.
Indikator Pine Script®
oleh ElectZA
SMC: Multi-TF Bias & HTF BOS with SessionsOverview The HTF BOS (Session) - Precision Lines is a comprehensive trading tool designed for Smart Money Concepts (SMC) and price action traders. It identifies Higher Timeframe (HTF) Break of Structure (BOS) levels while filtering them based on specific trading sessions. Additionally, it features a built-in Bias Dashboard that tracks trend alignment across three different timeframes to help you stay on the right side of the market. Key Features 1. Precision HTF BOS Tracking Unlike standard indicators that only mark the breakout candle, this script uses high-precision pivot detection to identify the exact origin of a structural high or low. Tam Yapışık Çizgiler (Precise Lines): The BOS lines are drawn exactly from the pivot point to the breakout point, providing a clean and professional look on your chart. HTF Integration: You can track structure from a higher timeframe (e.g., 4H) while trading on a lower timeframe (e.g., 15m or 5m). 2. Session Filtering (Time Sensitivity) Structural breaks are most reliable when they happen during high-volume periods. The script includes a Session Filter (London & New York). If enabled, the indicator will only plot BOS levels that occur during your specified trading hours, helping you avoid "fake-outs" or noise during low-liquidity periods (Asian session/After-hours). 3. Multi-Timeframe Bias Dashboard Stay aware of the "Big Picture" without constantly switching charts. The dashboard monitors three custom timeframes (e.g., Daily, 4H, 1H) and determines if the structure is Bullish or Bearish. Strong Buy/Sell Signals: When all three timeframes align, the status cell highlights as "BUY" or "SELL." Wait Status: If timeframes are in conflict, the dashboard suggests "WAIT," encouraging disciplined trading. How to Use Define Your Bias: Set your three Bias Timeframes in the settings to match your higher-level strategy. Set Your BOS TF: Choose the timeframe you want structural breaks to be calculated from (usually one or two steps above your entry chart). Adjust Sensitivity: Use the "Pivot Sensitivity" setting to filter between minor and major structural points. Confirm with Session: Enable the session filter to ensure you are only trading breaks that occur during the NY or London sessions. Settings Bias Dashboard Settings: Customize the TFs and pivot sensitivity for trend analysis. BOS & Session Settings: Set your target HTF for drawings and define your trading window (NY Timezone supported). Visual Settings: Full control over colors (Bullish/Bearish), table positioning, and text sizes.
Indikator Pine Script®
oleh FXmans
ElectZA MACD Range Momentum Filter**ElectZA MACD Range Momentum Filter (EZ_RangeMACD)** is a clean MACD-style momentum tool that helps you avoid choppy, low-volatility periods. It uses **ATR compression** to detect when price is likely ranging (and visually shades those zones), then **filters signals** so buy/sell triggers only appear when the market is *not* in a range. You get a color-coded histogram (gray in ranges, green/red in trends), classic MACD + signal lines, and optional crossover/crossunder markers to highlight higher-quality momentum shifts. **Disclaimer:** This indicator/script is provided for **educational and informational purposes only** and does **not** constitute financial, investment, or trading advice. Trading and investing involve **significant risk**, and you may lose some or all of your capital. Past performance is **not** indicative of future results. Always do your own research, test strategies on a demo account, and consider seeking advice from a qualified financial professional. By using this script, you agree that you are solely responsible for any trading decisions and outcomes.
Indikator Pine Script®
oleh ElectZA
Session Liquidity Reversion Strategy (Asia Range False Breakout)Overview This strategy is based on a session-driven liquidity hypothesis rather than a simple indicator combination. During the Asian trading session, many markets enter a low-liquidity equilibrium, forming a relatively narrow price range. When higher-volume participants enter during the London and New York sessions, price often performs false expansions beyond this Asian range before reverting back toward fair value. This script systematically identifies and trades those failed session expansions. Core Concept The strategy operates in three distinct phases: Asia Session Range Formation The high and low of the Asian session are recorded. This range represents a temporary balance area formed under reduced participation. Range Locking Once the Asian session ends, the range is frozen. No repainting or forward-looking calculations are used. False Breakout Detection & Reversion During the London/New York session, price must break beyond the Asia range and fail to hold. A momentum filter (RSI) confirms rejection strength. Trades are entered only after price closes back inside the range, targeting reversion rather than continuation. This approach avoids chasing breakouts and instead focuses on liquidity traps and failed expansions. Risk Management & Assumptions Risk parameters are intentionally conservative and realistic: Position sizing uses percentage of equity Default risk per trade is approximately 2% Stop losses are ATR-based, adapting to volatility Risk-to-reward is fixed and configurable Realistic commission and slippage are included One trade per session is allowed to avoid over-exposure No martingale, grid, or averaging logic is used. Usage Notes Recommended timeframes: 5m – 30m Designed for: Forex, Indices, Crypto Performance will vary by instrument and session volatility All parameters are configurable for research and optimization This strategy is intended for educational and research purposes, demonstrating how session-based liquidity behavior can be tested systematically using Pine Script.
Strategi Pine Script®
oleh JaxonJackFX
Retail Forex Sentiment Fear/Greed CurrencyPairsRetail Forex Sentiment Fear/Greed CurrencyPairs Overview The Retail Forex Sentiment Indicator provides sentiment data for major and cross currency pairs. This indicator displays retail trader positioning using retail brokers data, showing what percentage of retail traders are long or short on each forex pair. Important: Indicator Split Notice --------------------------------- Due to TradingView's limitation of 40 data requests per indicator, the original Retail Sentiment Indicator has been split into TWO separate indicators you will find on TradingView: 1. This indicator - Specialized for Forex currency pairs (30+ pairs) [2. Retail Sentiment Indicator - Multi-Asset CFD & Fear/Greed Index - For indices, commodities, cryptocurrencies, and Fear/Greed indices Please look at both indicators to access all available sentiment data. Methodology and Scale Calculation --------------------------------- This indicator operates on a **-50 to +50 scale** with zero representing perfect market equilibrium. Scale Interpretation: - **Zero (0)**: Market balance - exactly 50% of traders long, 50% short - **Positive values**: Majority long (buying) pressure - Example: If 63% of traders are long, the indicator shows +13 (63 - 50 = +13) - **Negative values**: Majority short (selling) pressure - Example: If 92% of traders are short, the indicator shows -42 (50 - 92 = -42) Features -------- - **Auto-Detection**: Automatically loads sentiment data based on the current chart symbol - **Manual Selection**: Choose from 30+ supported currency pairs when auto-detection is unavailable - **Visual Zones**: Clear greed/fear zones with color-coded backgrounds (green for fear zone, red for greed zone - contrarian colors) - **Daily Updates**: Live sentiment data from retail CFD providers Supported Currency Pairs ======================== Major Pairs ----------- - EURUSD (most traded pair globally) - GBPUSD (Cable) USD Pairs --------- - USDJPY, USDCHF, USDCAD - USDPLN PLN (Polish Zloty) Pairs ------------------------ - USDPLN, EURPLN, GBPPLN, CHFPLN EUR Cross Pairs --------------- - EURJPY, EURCHF, EURCAD, EURAUD, EURNZD, EURGBP GBP Cross Pairs --------------- - GBPJPY, GBPCHF, GBPCAD, GBPAUD, GBPNZD AUD (Australian Dollar) Pairs ----------------------------- - AUDUSD, AUDJPY, AUDCHF, AUDNZD, AUDCAD NZD (New Zealand Dollar) Pairs ------------------------------ - NZDUSD, NZDJPY, NZDCHF, NZDCAD CAD Cross Pairs --------------- - CADJPY, CADCHF CHF Cross Pairs --------------- - CHFJPY How to Use ---------- 1. **Auto Mode** (Default): Enable "Auto-load Sentiment Data" checkbox to automatically display sentiment for the current chart's currency pair 2. **Manual Mode**: Disable auto-load and select from the dropdown menu for specific currency pairs 3. **Interpretation**: - Values above 0 (green line) indicate retail traders are net long (greed/bullish sentiment) - Values below 0 (red line) indicate retail traders are net short (fear/bearish sentiment) - Extreme zones (+35 to +50 and -35 to -50) indicate strong positioning Trading Strategy & Market Philosophy ==================================== Contrarian Trading Approach --------------------------- The primary purpose of this indicator is based on the fundamental market principle that **the majority of retail forex traders are wrong most of the time**, and currency pairs typically move opposite to the positions held by the majority of retail participants. Key Strategy Guidelines: - **Contrarian Signal**: When the majority of retail traders are positioned on one side, consider opportunities in the opposite direction - **Trend Exhaustion Signal**: When retail traders finally flip to trade WITH an established trend after being wrong for extended period, this often signals trend exhaustion Interpretation Examples: - High greed readings (majority long) -> Consider short opportunities - High fear readings (majority short) -> Consider long opportunities - Sudden sentiment flip during established trends -> Potential trend reversal signal Forex-Specific Notes ==================== Currency Correlations --------------------- When analyzing forex sentiment, consider that: - USD pairs often move together (if retail is long EURUSD, they're often short USDJPY) - Cross pairs can provide confirmation signals - Comparing sentiment across related pairs can reveal broader positioning Auto-Detection Support ---------------------- The indicator supports automatic detection of various broker ticker formats including: - Standard pairs (EURUSD, GBPUSD, etc.) - CME Futures symbols (6E, 6B, JY, etc.) - Micro futures (M6E, M6B, MJY, etc.) This functionality is powered by regex pattern matching. However, for some CME futures pairs—particularly those involving JPY, CAD, and CHF—auto-detection may not work properly. In such cases, disable the auto-load checkbox and manually select the ticker from the dropdown menu. Technical Notes --------------- - Built with PineScript v6 - Dynamic symbol detection with fallback options - Optimized for performance with minimal resource usage - Color-coded visualization with customizable zones Data Sources ------------ This indicator uses curated sentiment data from retail CFD providers. Data is updated regularly and sourced from reputable financial data providers. Data Infrastructure Status -------------------------- Current Data Upload Process: Please note that sentiment data uploads may occasionally experience minor interruptions. However, this should not pose significant issues as sentiment data typically changes gradually rather than rapidly. Acknowledgments --------------- We extend our gratitude to **TradingView** for enabling the use of custom data feeds based on GitHub repositories, making this comprehensive forex sentiment analysis possible. Disclaimer ---------- This indicator is for educational and informational purposes only. Sentiment data should be used as part of a comprehensive trading strategy and not as the sole basis for trading decisions. Past performance does not guarantee future results. The contrarian approach described is a market theory and may not always produce profitable results. Forex trading involves significant risk of loss.
Indikator Pine Script®
oleh OpenTrading_ai
ICT Pro [KTY]Hi, I'm Kim Thank You 👋 KTY = Kim Thank You (김땡큐) 【ICT Pro】📊 Essential ICT tools for Smart Money trading. 5 core features to identify institutional order flow and high-probability trade setups. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💡 NEW TO THIS INDICATOR? Open Settings and hover over the (i) icon on each feature for detailed tooltips. Check the 📚 User Guide section at the bottom of Settings for quick reference. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 FEATURES ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ✅ Order Block (OB) Price zones where Smart Money executed large buy/sell orders, acting as strong support/resistance levels. - Bullish OB: Last bearish candle before an up move → Support - Bearish OB: Last bullish candle before a down move → Resistance 📈 Box Display Info - Vol: Volume at OB formation - (%): Upper/Lower volume balance ratio - Closer to 100% = Balanced buy/sell - Lower = Strong one-sided order flow → Stronger S/R zone 📍 OB Body Lines - Dotted lines showing candle body position within OB - Use for precise entry points ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ✅ Liquidity Zone Areas where stop-loss orders are clustered around swing highs/lows, becoming targets for Smart Money. - Buyside Liquidity: Stop-losses above highs where shorts get liquidated - Sellside Liquidity: Stop-losses below lows where longs get liquidated - Liquidity Sweep: Price hunts stops then reverses sharply 📈 Box Display Info - (%): Relative size compared to recent volume - Higher = More stop orders clustered - More likely to be a major target for Smart Money 💡 Quick reversal after liquidity break = Reversal signal ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ✅ Fair Value Gap (FVG) A gap created when price moves rapidly between 3 candles, where price tends to return to fill this zone. - Bullish FVG: Forms during sharp rallies → Acts as support on pullbacks - Bearish FVG: Forms during sharp drops → Acts as resistance on bounces - CE (Consequent Encroachment): 50% level of FVG, key reaction level 📈 Box Display Info - (%): Relative size compared to recent volume - Higher = FVG formed by stronger move - Acts as stronger S/R zone 💡 FVG overlapping with OB = Higher reliability ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ✅ Market Structure Analyzes price swing highs/lows to identify current trend and reversal points. - CHoCH (Change of Character): Trend reversal signal - first sign of direction change - BOS (Break of Structure): Trend continuation signal - structure break in existing direction ⚙️ Structure Options - INTERNAL: Short-term structure (fast reaction, more signals) - EXTERNAL: Long-term structure (slower reaction, higher reliability) - ALL: Display both internal + external structure 💡 CHoCH = Look for reversal | BOS = Trend continues ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ✅ Trend Candles Candle colors change based on market structure (BOS/CHoCH) direction. - Bullish Color: After bullish structure break - Bearish Color: After bearish structure break 💡 Color change = Potential trend shift 💡 Quickly identify overall market direction at a glance ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📈 HIGHER RELIABILITY SETUPS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ - Higher timeframe = More reliable signals - Multiple features pointing to same price zone (e.g. OB + FVG overlap = Strong confluence) - Trend Candles + Market Structure direction aligned - Quick reversal after Liquidity sweep ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💡 TRADING TIPS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1. Identify Liquidity targets first 2. Wait for price to reach OB or FVG zone 3. Confirm with Market Structure (CHoCH/BOS) 4. Enter at OB body lines or FVG CE level 5. Stop loss below/above the zone ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚠️ DISCLAIMER This indicator is for educational purposes only. Not financial advice. Always do your own research. Past performance does not guarantee future results.
Indikator Pine Script®
oleh Kim-Thank_You
14
Multi-Indicator Scoring System# Multi-Indicator Scoring System ## Overview This indicator combines five technical analysis tools (RSI, MACD, EMA trends, and Volume) into a single unified scoring system that generates clear BUY and SELL signals. Instead of analyzing multiple indicators separately and dealing with conflicting signals, this script calculates one comprehensive 0-100% score that shows current market strength at a glance. ## Purpose and Originality **Problem it solves:** Traders using multiple indicators individually often face contradictory signals. For example, RSI might show oversold conditions while MACD indicates bearish momentum, or price is above EMA but volume is weak. This creates confusion and leads to poor trading decisions or missed opportunities. **Solution:** This script uses a weighted scoring algorithm that only generates signals when multiple technical components mathematically agree. Each indicator contributes weighted points based on its reliability in crypto markets, and the combined score filters out noise by requiring multi-indicator confirmation before triggering a signal. **What makes it original:** Unlike simple indicator overlays that just display multiple tools side-by-side, this script: - Uses a mathematically weighted scoring system where each component has justified importance - Requires conditional alignment—signals only appear when components agree, not just individual crossovers - Normalizes complex multi-indicator data into one intuitive percentage - Includes built-in volume confirmation to filter low-conviction setups This approach mirrors professional algorithmic trading systems that use multi-factor quantitative models. ## How Components Work Together The script analyzes five technical components and assigns weighted points to each: ### 1. RSI (Relative Strength Index) - Weight: 25 points - **Period:** 14 - **Function:** Identifies overbought and oversold conditions - **Scoring logic:** - RSI < 30 (oversold) → +25 points (bullish reversal signal) - RSI > 70 (overbought) → -25 points (bearish reversal signal) - RSI between 30-70 → 0 points (neutral) - **Why 25 points:** RSI is highly reliable for detecting potential reversal zones in cryptocurrency markets ### 2. MACD (Moving Average Convergence Divergence) - Weight: 25 points - **Parameters:** Fast=12, Slow=26, Signal=9 - **Function:** Detects momentum shifts and trend changes - **Scoring logic:** - MACD line > Signal line → +25 points (bullish momentum) - MACD line < Signal line → -25 points (bearish momentum) - **Why 25 points:** MACD is the gold standard for momentum confirmation across timeframes ### 3. EMA Short-Term Trend (21 vs 50) - Weight: 25 points - **Function:** Confirms immediate trend direction - **Calculation:** Compares EMA 21 to EMA 50, plus price position relative to EMA 21 - **Scoring logic:** - EMA 21 > EMA 50 AND Price > EMA 21 → +25 points (strong uptrend) - EMA 21 < EMA 50 AND Price < EMA 21 → -25 points (strong downtrend) - Mixed conditions → 0 points (no clear trend) - **Why 25 points:** Short-term trend alignment is critical for accurate entry timing ### 4. EMA Long-Term Context (200) - Weight: 15 points - **Function:** Validates overall market structure - **Calculation:** Price position relative to 200-period EMA - **Scoring logic:** - Price > EMA 200 → +15 points (bull market context) - Price < EMA 200 → -15 points (bear market context) - **Why 15 points:** Lower weight because long-term trend changes more slowly ### 5. Volume Confirmation - Weight: 10 points (Bonus) - **Function:** Confirms genuine market interest versus noise - **Calculation:** Current volume compared to 20-period SMA - **Scoring logic:** - Volume > 1.5× average → +10 bonus points - Volume ≤ 1.5× average → 0 bonus points - **Why 10 points:** Volume adds conviction but shouldn't override technical setup ### Score Aggregation Formula **Why these thresholds?** Backtesting on BTC/ETH showed optimal risk/reward at 65/35 levels. Lower thresholds (50%) produce too many false signals, while higher thresholds (80%) miss opportunities. The 65/35 balance provides good sensitivity with acceptable accuracy. ## How to Use This Indicator ### Visual Components **On Chart:** - **Green triangle (▲) below candle** = BUY signal (score crossed above 65%) - **Red triangle (▼) above candle** = SELL signal (score crossed below 35%) - Clean display with no background colors or extra lines **Dashboard Table (top-right corner):** - **Header:** "CRYPTO SIGNAL" - **SCORE:** Current percentage (0-100%) - Green color = Bullish zone (65%+) - Red color = Bearish zone (35%-) - Orange color = Neutral zone (36-64%) - **SIGNAL:** Current status (BUY/SELL/WAIT) ### Interpreting the Score - **70-100% (Strong Bullish):** All or most indicators agree market is going up. Consider long positions. - **65-69% (BUY Signal Zone):** Enough confirmation for entry. BUY signals trigger here. - **36-64% (Neutral Zone):** No clear direction. Wait for clearer setup or maintain existing positions. - **31-35% (SELL Signal Zone):** Enough confirmation for exit. SELL signals trigger here. - **0-30% (Strong Bearish):** All or most indicators agree market is going down. Avoid longs or consider shorts. ### Step-by-Step Usage 1. **Add to chart:** Click "Add to favorites" then add from your indicators list 2. **Check the score:** Look at the dashboard table in the top-right corner 3. **Wait for signals:** - Green triangle appears = Consider buying - Red triangle appears = Consider selling - No triangle = Wait patiently for clearer setup 4. **Confirm with price action:** Best results when signals appear at support/resistance levels 5. **Use risk management:** Always set stop losses (3-5% below entry for longs) 6. **Set alerts (optional):** Right-click indicator → "Add alert" → Choose "BUY Signal" or "SELL Signal" ### Best Practices **Recommended Timeframes:** - **4-Hour (4H):** Best for swing trading, optimal signal frequency (3-7 per month), lowest false signal rate - **Daily (1D):** Best for position trading, very high reliability, ideal for patient traders - **1-Hour (1H):** More signals but noisier, only for experienced traders - **Below 15 minutes:** Not recommended, too many false signals **Recommended Markets:** - Bitcoin (BTCUSDT, BTCUSD) - Most reliable - Ethereum (ETHUSDT, ETHUSD) - Excellent results - Major altcoins (SOL, XRP, ADA, etc.) - Works well on top 20 by market cap **Risk Management:** - Position size: Risk only 1-2% of account per trade - Stop loss: Place 3-5% below entry (BUY) or above entry (SELL) - Take profit: Target 2-3× your risk distance - Trail stops: Move to breakeven after 1:1 profit achieved **Advanced Tips:** - Combine signals with support/resistance levels for higher probability setups - Check multiple timeframes: if 4H and 1D both show BUY, signal is stronger - Wait for candle close before acting on signals - Ignore signals against the higher timeframe trend direction - Only trade signals accompanied by volume spikes (check dashboard) ## Default Settings The indicator uses pre-optimized parameters based on backtesting: - RSI Period: 14 - MACD: 12, 26, 9 - EMA Short-term: 21, 50 - EMA Long-term: 200 - Volume threshold: 1.5× average - Signal thresholds: BUY ≥65%, SELL ≤35% These settings are designed for cryptocurrency markets on 4H and 1D timeframes and do not require adjustment for most users. ## Limitations and Disclaimers **What this indicator CANNOT do:** - Predict black swan events (exchange hacks, major regulations, etc.) - Work effectively during extreme market manipulation - Replace proper risk management and stop losses - Guarantee profits (no indicator can) - Account for fundamental news (Fed decisions, major announcements) **When signals may be less reliable:** - Low volume periods (weekends, holidays) - High-impact news events - Extreme volatility (>10% daily price moves) - Prolonged sideways/ranging markets **Important warnings:** - This is a technical analysis tool, not financial advice - Past performance does not guarantee future results - Always use stop losses to protect capital - Test the indicator with small positions first - Do your own research before trading ## Technical Specifications - **Pine Script Version:** v5 - **Type:** Overlay indicator - **Signals:** Non-repainting (confirmed at candle close only) - **Calculation frequency:** Every bar recalculates based on current values - **Alerts:** Available for BUY and SELL threshold crossings - **Resource usage:** Optimized for efficient runtime performance ## Additional Notes - Signals appear only once when threshold is crossed (no repeated signals during same trend) - Volume filter helps eliminate low-conviction signals - Works on any cryptocurrency pair with sufficient liquidity - Can be combined with other indicators for additional confirmation - Suitable for both beginners (simple visual signals) and experienced traders (customizable for deeper analysis) --- **This indicator provides educational value by demonstrating how multi-indicator confirmation systems work and how weighted scoring can reduce false signals compared to using individual indicators alone.**
Indikator Pine Script®
oleh Golkar22
EUR/USD: EUR USD 5 MIN SCALPING by Scalper Pro Systems// DISCLAIMER: // This script is for educational purposes only. It is not financial advice. // Past performance does not guarantee future results. // Use this tool at your own risk. EUR/USD: EUR USD 5 MIN SCALPING by Scalper Pro Systems Overview This is a plug-and-play scalping system designed specifically for the EUR/USD 5-Minute chart . Created by Scalper Pro Systems , it simplifies intraday trading by automatically generating Buy/Sell signals with precise Take Profit and Stop Loss levels. How It Works The strategy uses a "Safety First" approach to find stable entries: 1. Trend Filter (EMA 200): Ensures you only trade with the main trend (Buy only if price is above; Sell only if price is below). 2. Entry Trigger (EMA 9 & 21): Identifies short-term momentum shifts. 3. Noise Filter (RSI): Prevents entering trades when momentum is weak or exhausted. Main Features 🟢🔴 Clear Signals: Draws Green (Buy) and Red (Sell) boxes directly on the chart. 📉📈 Auto TP & SL: Instantly calculates your Stop Loss (based on recent swing lows/highs) and Take Profit (1.5x risk) and displays the exact price numbers. ⏱️ Live Tracking: The system tracks the trade for you and marks exactly when and where the Target or Stop Loss was hit. 📊 Dashboard: Shows Signal Time, Entry Price, TP, and SL in a clean information box. Best Settings Timeframe: 5 Minutes Asset: EUR/USD (Can also be used on Gold/XAUUSD or Indices) Session: Best used during London or New York sessions. Risk Warning Trading involves risk. This tool helps visualize a strategy but does not guarantee profits. Always manage your risk.
Indikator Pine Script®
oleh billal-kashif
Bubble Risk ModelThe question of whether markets can be objectively assessed for overextension has occupied financial researchers for decades. Charles Kindleberger, in his seminal work "Manias, Panics, and Crashes" (1978), documented that speculative bubbles follow remarkably consistent patterns across centuries and asset classes. Yet identifying these patterns in real time remains notoriously difficult. The Bubble Risk Model attempts to address this challenge not by predicting crashes, but by systematically measuring the statistical characteristics that historically precede fragile market conditions. The theoretical foundation draws from two distinct research traditions. The first is the work on regime-switching models pioneered by James Hamilton (1989), who demonstrated that economic time series often exhibit discrete shifts between different behavioral states. The second is the literature on tail risk and market fragility, most notably articulated by Nassim Taleb in "The Black Swan" (2007), which emphasizes that extreme events carry disproportionate importance and that traditional risk measures systematically underestimate their probability. Rather than attempting to build a probabilistic model requiring assumptions about underlying distributions, the Bubble Risk Model operates as a deterministic state-inference system. This distinction matters. Lawrence Rabiner's foundational tutorial on Hidden Markov Models (1989) established the mathematical framework for inferring hidden states from observable data through Bayesian updating. The present model borrows the conceptual architecture of states and transitions but replaces probabilistic inference with rule-based logic. States are not computed through forward-backward algorithms but inferred through deterministic thresholds. This trade-off sacrifices theoretical elegance for practical robustness and interpretability. The measurement framework rests on four empirically grounded components. The first captures trailing twelve-month returns, reflecting the well-documented momentum effect identified by Jegadeesh and Titman (1993), who found that securities with strong past performance tend to continue outperforming over intermediate horizons. The second component measures trend persistence as the proportion of positive daily returns over a quarterly window, drawing on the research by Campbell and Shiller (1988) showing that price trends exhibit serial correlation that deviates from random walk assumptions. The third normalizes the distance between current prices and their long-term moving average by volatility, addressing the cross-sectional comparability problem noted by Fama and French (1992) when analyzing assets with different variance characteristics. The fourth component calculates return efficiency as the ratio of returns to realized volatility, a concept related to the Sharpe ratio but stripped of distributional assumptions that often fail in practice. The aggregation methodology deliberately prioritizes worst-case scenarios. Rather than averaging component scores, the model uses quantile-based aggregation with an explicit tail penalty. This design choice reflects the asymmetric error costs in bubble detection: failing to identify fragility carries greater consequences than occasional false positives. The approach aligns with the precautionary principle advocated by Taleb and colleagues in their work on fragility and antifragility (2012), which argues that systems exposed to tail risks require conservative assessment frameworks. Normalization presents a particular challenge. Raw metrics like year-over-year returns are not directly comparable across asset classes with different volatility profiles. The model addresses this through percentile ranking over multiple historical windows, typically two and five years. This dual-window approach provides regime stability, preventing the normalization from adapting too quickly during extended bull markets where elevated readings become statistically normal. The methodology draws on the concept of lookback bias documented by Lo and MacKinlay (1990), who demonstrated that single-window statistical measures can produce misleading results when market regimes shift. The state machine introduces controlled inertia into the system. Once the model enters a particular state, transitions become progressively more difficult as the state matures. This transition resistance mechanism prevents rapid oscillation near threshold boundaries, a problem that plagues many indicator-based systems. The concept parallels the hysteresis effects described in economic literature by Dixit (1989), where systems exhibit path dependence and resist returning to previous states even when underlying conditions change. Volatility regime detection adds contextual interpretation. Research by Engle (1982) on autoregressive conditional heteroskedasticity established that volatility clusters, with periods of high volatility tending to follow other high-volatility periods. The model scales its maturity thresholds inversely with volatility: in calm markets, states mature slowly and persist longer; in turbulent markets, information decays faster and states become more transient. This adaptive behavior reflects the empirical observation that low-volatility environments often precede significant market dislocations, as documented by Brunnermeier and Pedersen (2009) in their work on liquidity spirals. The confidence metric addresses internal model consistency. When individual components diverge substantially, the overall score becomes less reliable regardless of its absolute level. This approach draws on ensemble methods in machine learning, where disagreement among predictors signals increased uncertainty. Dietterich (2000) provides theoretical justification for this principle, demonstrating that ensemble disagreement correlates with prediction error. Distribution drift detection monitors whether the model's calibration remains valid. By comparing recent score distributions to longer historical baselines, the model can identify when market structure has shifted sufficiently to potentially invalidate its historical percentile rankings. This self-diagnostic capability reflects the concern raised by Andrews (1993) about parameter instability in time series models, where structural breaks can render previously estimated relationships unreliable. The cross-asset analysis extends the framework beyond individual securities. By calculating scores for multiple asset classes simultaneously and measuring their correlation, the model distinguishes between idiosyncratic overextension affecting a single asset and systemic conditions affecting markets broadly. This differentiation matters for portfolio construction, as documented by Longin and Solnik (2001), who found that correlations between international equity markets increase significantly during periods of market stress. Several limitations deserve explicit acknowledgment. The model cannot identify timing. Overextended conditions can persist far longer than rational analysis might suggest, a phenomenon documented by Shiller (2000) in his analysis of speculative episodes. The model provides no mechanism for determining when fragile conditions will resolve. Additionally, the cross-asset analysis lacks lead-lag detection, meaning it cannot distinguish whether assets became overextended simultaneously or sequentially. Finally, the rule-based nature of state inference means the model cannot express graduated probability assessments; states are discrete rather than continuous. The philosophical stance underlying the model is one of epistemic humility. It does not claim to identify bubbles definitively or predict their collapse. Instead, it provides a systematic framework for measuring characteristics that have historically been associated with fragile market conditions. The distinction between information and action remains the user's responsibility. States describe current conditions; how to respond to those conditions requires judgment that no quantitative model can provide. Practical guide for traders This section translates the model's outputs into actionable intelligence for both retail traders managing personal portfolios and professional traders operating within institutional frameworks. The interpretation differs not in kind but in scale and consequence. Understanding the score The primary output is a continuous score ranging from zero to one. Lower scores indicate elevated bubble risk; higher scores suggest more sustainable market conditions. This inverse relationship may seem counterintuitive but reflects the model's construction: it measures how extreme current conditions are relative to historical norms, with extremity mapping to fragility. A score above 0.50 generally indicates normal market conditions where standard investment approaches remain appropriate. Scores between 0.30 and 0.50 represent an elevated zone where caution is warranted but not alarm. Scores below 0.30 enter the extreme territory where historical precedent suggests increased fragility. These thresholds are not magical boundaries but represent statistical rarity: a score below 0.30 indicates conditions that occur in roughly the bottom quintile of historical observations. For retail traders, a score in the normal range means continuing with established strategies without modification. In the elevated range, this might mean pausing new position additions while maintaining existing holdings. In the extreme range, retail traders should consider whether their portfolio could withstand a significant drawdown and whether their time horizon permits waiting for recovery. For professional traders, the score integrates into broader risk frameworks: normal conditions permit full risk budgets, elevated conditions might trigger reduced position sizing or tighter stop losses, and extreme conditions could warrant defensive positioning or increased hedging activity. Reading the states The model classifies conditions into three discrete states: Normal, Elevated, and Extreme. These states differ from the continuous score by incorporating persistence and transition resistance. A market can have a score temporarily dipping below 0.30 without triggering an Extreme state if the condition proves transient. The Normal state indicates business as usual. Market conditions fall within historical norms across all measured dimensions. For retail traders, this means standard portfolio management applies. For professional traders, full strategy deployment remains appropriate with normal risk parameters. The Elevated state signals heightened attention. At least one dimension of market behavior has moved outside normal ranges, though not to extreme levels. Retail traders should review portfolio concentration and ensure diversification remains intact. Professional traders might reduce leverage slightly, tighten risk limits, or increase monitoring frequency. The Extreme state represents statistically rare conditions. Multiple dimensions show readings that historically occur infrequently. Retail traders should seriously evaluate whether they can tolerate potential drawdowns and consider reducing exposure to volatile assets. Professional traders should implement defensive protocols, potentially reducing gross exposure, increasing cash allocations, or adding protective positions. Interpreting transitions State transitions carry more information than states themselves. The model tracks whether conditions are entering, persisting in, or exiting particular states. An Entry into Extreme represents the most important signal. It indicates a regime shift from normal or elevated conditions into territory associated with historical fragility. For retail traders, this warrants immediate portfolio review. For professional traders, this typically triggers predefined defensive protocols. Persistence in a state indicates stability. Whether Normal or Extreme, persistence suggests the current regime has become established. For retail traders, persistence in Extreme over extended periods actually reduces immediate concern; the dangerous moment was the entry, not the continuation. For professional traders, persistent Extreme states require maintained vigilance but do not necessarily demand additional action beyond what the initial entry triggered. An Exit from Extreme suggests improving conditions. For retail traders, this might warrant cautious return to normal positioning over time. For professional traders, exits permit gradual normalization of risk budgets, though institutional memory typically counsels slower reentry than the mathematical signal might suggest. Duration and its meaning The model distinguishes between Tactical, Accelerating, and Structural durations in critical zones. Tactical duration (10-39 bars in critical territory) represents short-term overextension. Many Tactical episodes resolve without significant market disruption. Retail traders should note the condition but need not take dramatic action. Professional traders might implement modest hedges or reduce marginal positions. Accelerating indicates Tactical duration combined with actively deteriorating scores. This combination historically precedes more significant corrections. Retail traders should consider lightening positions in their most volatile holdings. Professional traders typically implement more substantial hedges. Structural duration (40+ bars in critical territory) indicates persistent overextension that has become a market feature rather than a temporary condition. Paradoxically, Structural conditions are both more concerning and less immediately actionable than Accelerating conditions. The market has demonstrated ability to sustain extreme readings. Retail traders should maintain heightened awareness but recognize that timing remains impossible. Professional traders often find Structural conditions require strategy adaptation rather than simple defensive positioning. Confidence and what it tells you The Confidence reading indicates internal model consistency. High confidence means all four underlying components agree in their assessment. Low confidence means components diverge significantly. High confidence combined with Extreme state represents the clearest signal. The model is both indicating fragility and agreeing with itself about that assessment. Retail and professional traders alike should treat this combination with maximum seriousness. Low confidence in any state reduces signal reliability. For retail traders, low confidence suggests waiting for clearer conditions before making significant portfolio changes. For professional traders, low confidence warrants increased skepticism about the score and potentially reduced position sizing in either direction. Alignment and model health The Alignment indicator monitors whether the model's calibration remains valid relative to recent market behavior. Good alignment means recent score distributions match longer-term historical patterns. The model's percentile rankings remain meaningful. Both retail and professional traders can interpret scores at face value. Degraded alignment indicates that recent market behavior has shifted somewhat from historical norms. Scores remain interpretable but with reduced precision. Retail traders should apply wider uncertainty bands to their interpretation. Professional traders might reduce position sizing slightly or require additional confirmation before acting. Poor alignment signals significant distribution shift. The model may be comparing current conditions to an increasingly irrelevant historical baseline. Retail traders should rely more heavily on other information sources during Poor alignment periods. Professional traders typically reduce model weight in their decision frameworks until alignment recovers. Volatility regime context The volatility regime provides essential context for score interpretation. Low volatility combined with Extreme state creates maximum concern. Research consistently shows that low-volatility environments can precede significant market dislocations. The market's apparent calm masks underlying fragility. Retail traders should recognize that low volatility does not mean low risk; it often means compressed risk premiums that will eventually normalize, potentially violently. Professional traders typically maintain or increase defensive positioning despite the market's calm appearance. High volatility combined with Extreme state is actually less immediately concerning than low volatility. The market has already acknowledged stress; risk premiums have expanded; potential sellers may have already sold. Retail traders should resist the urge to panic sell during high-volatility extremes, as much of the adjustment may have already occurred. Professional traders recognize that high-volatility extremes often represent better entry points than low-volatility extremes. Normal volatility requires no regime adjustment to interpretation. Scores mean what they appear to mean. Cross-asset analysis When enabled, the model calculates scores for multiple asset classes simultaneously, enabling systemic versus idiosyncratic risk assessment. Systemic risk (multiple assets in Extreme with high correlation) indicates market-wide fragility. Diversification benefits are reduced precisely when most needed. Retail traders should recognize that their portfolio's apparent diversification may not protect them during systemic events. Professional traders implement cross-asset hedges and consider tail-risk protection. Broad risk (multiple assets in Extreme with low correlation) suggests widespread but potentially unrelated overextension. Diversification may still provide some protection. Retail traders can take modest comfort in genuine diversification. Professional traders analyze which assets might offer relative value. Isolated risk (single asset in Extreme while others remain Normal) indicates asset-specific rather than market-wide conditions. Retail traders holding the affected asset should evaluate their position specifically. Professional traders may find relative value opportunities going long unaffected assets against the extended one. Scattered risk represents a few assets showing elevation without clear pattern. This typically warrants monitoring rather than action for both retail and professional traders. Parameter guidance The Short Percentile parameter (default 504 bars, approximately two years) controls the shorter normalization window. Increasing this value makes the model more conservative, requiring more extreme readings to flag concern. Retail traders should generally leave this at default. Professional traders might increase it for assets with shorter reliable history. The Long Percentile parameter (default 1260 bars, approximately five years) controls the longer normalization window. This provides regime stability. Again, default settings suit most applications. The Critical Threshold (default 0.30) determines where the Extreme state boundary lies. Lowering this value makes the model less sensitive, flagging fewer Extreme conditions. Raising it increases sensitivity. Retail traders seeking fewer false alarms might lower this to 0.25. Professional traders seeking earlier warning might raise it to 0.35. The Structural Duration parameter (default 40 bars) determines when Tactical conditions become Structural. Shorter values provide earlier Structural classification. Longer values require more persistence before reclassification. The State Maturity and Transition Resistance parameters control how readily the model changes states. Higher values create more stable states with fewer transitions. Lower values create more responsive but potentially noisier state changes. Default settings balance responsiveness against stability. The Adaptive Smoothing parameters control how the model filters noise. In extreme zones, longer smoothing periods reduce whipsaws but increase lag. In normal zones, shorter periods maintain responsiveness. Most traders should leave these at defaults. What the model cannot do The model cannot predict when overextended conditions will resolve. Markets can remain irrational longer than any trader can remain solvent, as the saying goes. Extended Extreme readings may persist for months or even years before any correction materializes. The model cannot distinguish between healthy bull markets and dangerous bubbles in their early stages. Both initially appear as strong returns and positive momentum. The model begins flagging concern only when statistical extremity develops, which may occur well into an advance. The model cannot account for fundamental changes in market structure. If a new paradigm genuinely justifies higher valuations (rare but not impossible), the model will continue flagging extremity against historical norms that may no longer apply. The Alignment indicator provides partial protection against this failure mode but cannot eliminate it. The model cannot replace judgment. It provides systematic measurement of conditions that have historically preceded fragility. Whether and how to act on that measurement remains entirely the trader's responsibility. Retail traders must still evaluate their personal circumstances, time horizons, and risk tolerance. Professional traders must still integrate model output with fundamental analysis, portfolio constraints, and client mandates. References Andrews, D.W.K. (1993). Tests for Parameter Instability and Structural Change with Unknown Change Point. Econometrica, 61(4). Brunnermeier, M.K., & Pedersen, L.H. (2009). Market Liquidity and Funding Liquidity. Review of Financial Studies, 22(6). Campbell, J.Y., & Shiller, R.J. (1988). Stock Prices, Earnings, and Expected Dividends. Journal of Finance, 43(3). Dietterich, T.G. (2000). Ensemble Methods in Machine Learning. Multiple Classifier Systems. Dixit, A. (1989). Entry and Exit Decisions under Uncertainty. Journal of Political Economy, 97(3). Engle, R.F. (1982). Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation. Econometrica, 50(4). Fama, E.F., & French, K.R. (1992). The Cross-Section of Expected Stock Returns. Journal of Finance, 47(2). Hamilton, J.D. (1989). A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica, 57(2). Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1). Kindleberger, C.P. (1978). Manias, Panics, and Crashes: A History of Financial Crises. Basic Books. Lo, A.W., & MacKinlay, A.C. (1990). Data-Snooping Biases in Tests of Financial Asset Pricing Models. Review of Financial Studies, 3(3). Longin, F., & Solnik, B. (2001). Extreme Correlation of International Equity Markets. Journal of Finance, 56(2). Rabiner, L.R. (1989). A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition. Proceedings of the IEEE, 77(2). Shiller, R.J. (2000). Irrational Exuberance. Princeton University Press. Taleb, N.N. (2007). The Black Swan: The Impact of the Highly Improbable. Random House. Taleb, N.N., & Douady, R. (2012). Mathematical Definition, Mapping, and Detection of (Anti)Fragility. Quantitative Finance, 13(11).
Indikator Pine Script®
oleh EdgeTools
Best Buying & Selling Flip Zone @MaxMaserati 3.0Best Buying & Selling Flip Zone 3.0 🐂🐻 Best Buying & Selling Flip Zone 3.0 is an advanced, multi-timeframe Price Action tool designed to identify high-probability institutional supply and demand zones. By analyzing candle range and body size (Expander vs. Normal candles), this indicator categorizes market structure shifts into three distinct tiers of strength (A+++, A++, A+). It includes a built-in Trade Manager, Volume Tracking, and a unique "Defender/Attacker" Multi-Timeframe (MTF) entry confirmation system. 🚀 Key Features Multi-Timeframe Analysis: Monitor Higher Timeframe (HTF) zones while trading on a Lower Timeframe (LTF). Tiered Setup Grading: Automatically classifies zones based on the strength of the candle engulfing action (King Slayer, Crusher, Drift). Smart Entry Confirmation: The script can wait for price to tap an HTF zone and then automatically search for a confirmation pattern on the current timeframe before signaling a trade. Built-in Trade Management: Visualizes Entry, Stop Loss (SL), and Take Profit (TP) levels with customizable Risk:Reward ratios. Volume Tracking: Monitors the volume utilized to create a zone and tracks "remaining" volume as price tests the zone. Zone Deletion Logic: Automatically removes zones that have been invalidated by either a wick or a candle close. 🧠 How It Works: The "A-Grade" Logic The indicator analyzes candles based on their body-to-range ratio to define "Expander" (Explosive move) vs. "Normal" candles. It then looks for engulfing behaviors to create zones: A+++ (King Slayer): Logic: A Bullish Expander engulfs a Bearish Expander (or vice versa). Significance: This is the strongest signal, indicating a massive shift in momentum where aggressive buyers completely overwhelmed aggressive sellers. A++ (Crusher): Logic: A Bullish Expander engulfs a Bearish Normal candle. Significance: Strong momentum overcoming standard price action. High probability. A+ (Drift): Logic: A Bullish Normal candle engulfs a Bearish Normal candle. Significance: A standard flip zone. Good for continuation plays but less aggressive than KS or CR setups. 🛠️ Functionality Guide 1. General Filters & Timeframes Higher Timeframe: Select a timeframe higher than your chart (e.g., Select 4H while trading on 15m). The indicator will draw the major zones from the 4H. Deletion Logic: Wick (Hard): Zone is removed immediately if price touches the invalidation level. Close (Soft): Zone is removed only if a candle closes past the invalidation level. 2. LTF Entry Confirmation (The "Master" Switch) When Show LTF Entry Logic is enabled, the indicator does not signal immediately upon an HTF zone creation. Instead: It waits for the price to retraced and touch the HTF zone. Once touched, it scans the current timeframe for a valid flip setup (KS, CR, or DR). It creates a tighter entry box and draws trade lines only when this confirmation occurs. 3. Trade Management Risk:Reward: Set your desired RR (e.g., 2.0). SL Padding: Add breathing room (ticks) to your Stop Loss. SL Source: Choose between a safer Stop Loss (based on the HTF zone) or a tighter Stop Loss (based on the LTF confirmation candle). 4. Volume Stats Labels display the volume involved in the zone's creation. As price taps the zone, the volume is "depleted" from the label, giving you insight into the remaining order flow absorption. 🎨 Visual Customization Colors: Fully customizable colors for Buyers (Green) and Sellers (Red) zones across all three strength tiers. Labels: Toggle technical names, touch counts, and timeframe labels. Lines: Option to show "Aggressive Open Lines" to mark the exact opening price of the flip zone extended forward. ⚠️ Disclaimer This tool is for educational purposes and chart analysis assistance only. Past performance of a setup (A+++/King Slayer) does not guarantee future results. Always manage risk and use this in conjunction with your own trading strategy.
Indikator Pine Script®
oleh MaxMaserati
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