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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.
Chỉ báo Pine Script®
của 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.
Chỉ báo Pine Script®
của 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.**
Chỉ báo Pine Script®
của Golkar22
Wickless Liquidity Draw PRO [Reggie_W]Wickless Liquidity Draw PRO Wickless Liquidity Draw PRO is an advanced institutional liquidity tracker designed to identify, monitor, and analyze high-probability price magnets known as "Single Prints" or "Wickless/Tailless" candles. Unlike standard support and resistance, these specific price levels represent inefficiencies in the market auction—gaps where price was delivered so aggressively that no wick was formed. Institutional algorithms frequently revisit these levels to "rebalance" the auction, making them powerful draw-on-liquidity targets. This indicator does not just plot lines; it provides a statistical engine to help you understand when and how often these targets are hit, giving you a quantifiable edge in your trading model. 🎯 Key Features 1. Automated Target Detection • Wickless Targets (Bearish Flow): Identifies candles where High == Max(Open, Close). These are often revisited to sweep buy-side liquidity. • Tailless Targets (Bullish Flow): Identifies candles where Low == Min(Open, Close). These are revisited to sweep sell-side liquidity. • Dynamic Ray Management: Automatically manages up to 5,000 historical rays, extending them until they are tested by price. 2. Institutional Data Dashboard Stop guessing and start measuring. The PRO dashboard offers two powerful modes: • Standard Stats: Displays the Mean, Median, and Mode duration (in bars) it takes for price to sweep or break a level. • Frequency Matrix (Heatmap): A detailed ranking of the top 10 most common durations for liquidity sweeps. Example: You might see that your asset has a 90% probability of sweeping a Wickless level within 3 bars. 3. "Smart" Metrics & Outlier Filtering Markets contain noise. The PRO edition includes a proprietary Outlier Filter (IQR Method). • Toggle between "Standard" and "Filtered" calculations. • "Filtered" mode removes extreme anomalies (e.g., a target hit after 5,000 bars) to give you the true statistical expectancy of a trade setup. 4. Visual Strength Fading Not all liquidity is created equal. Fresh levels are often more reactive than stale ones. • Ray Fading: Old, untested rays slowly fade in transparency, allowing you to visually prioritize fresh, high-probability targets at a glance. 🧠 How It Works (The Logic) In ICT (Inner Circle Trader) and Smart Money Concepts (SMC), price moves to do two things: 1. Rebalance Inefficiency (Fair Value Gaps) 2. Seek Liquidity (Stops) A "Wickless" candle is a specific type of inefficiency. Because price moved away from the level instantly without trading back (no wick), it leaves a "pocket" of low-volume liquidity. The Strategy: 1. The Setup: A Wickless/Tailless candle forms. The indicator plots a ray. 2. The Draw: If market structure aligns, this ray becomes a magnet. 3. The Execution: Use the Dashboard to align your trade duration. If the dashboard shows the "Mode" time to sweep is 5 bars, and you are on Bar 2, statistical probability suggests a sweep is imminent. 📊 Dashboard Breakdown • Tot T (Total Touched): How many targets were swept (price touched the line). • Tot C (Total Crossed): How many targets were broken (candle closed beyond the line). • Touch-to-Cross: Advanced metric showing the average delay between a "Sweep" and a full "Breakout." • Hit Rate: See exactly what % of targets are revisited by the market. ⚙️ Settings & Customization • Lookback Period: Customize how far back the system analyzes (up to 10,000 bars). • Max Rays: Control memory usage by limiting active lines. • Fade Duration: Adjust how quickly older lines fade out. • Alerts: Fully integrated alerts for Touches and Crosses on both Upper and Lower targets. Risk Disclaimer: Trading involves substantial risk. This tool provides statistical analysis of historical price action and does not guarantee future performance. Use it to enhance your edge, not as a blind signal generator.
Chỉ báo Pine Script®
của Reggie_W
MTF OHLC AMD [Pro+]MTF OHLC AMD It's an extension of MTF - OHLC - AMD. The Pro version offers access to many features: SMT -Shows correlations between multiple instruments (e.g., Pair 2, Pair 3). -Auto-matching of pairs to highlight synchronized movements. -Does not include SMT with DXY. HTF Projection (High Time Frame) -Projects higher timeframe levels directly onto the current chart. -Supports multiple HTFs (e.g., 1H, 4H, Daily, Weekly) with customizable number of candles. -Shows mid lines and key candle levels for HTFs. -Full visual customization: candle body, border, and spike colors for bull and bear. -Options for labels above/below candles and PSP display. -Manage offsets for candle distance and visual sizing. Multi-Timeframe and Separators -Displays levels and period separators across multiple timeframes: for example, on 1m chart, you can see 15m and 4H references. -Ideal for strategies combining MTF, HTF, and LTF. Manipulation Detection (AMD) -Identifies accumulation, manipulation, and distribution zones. -Activates manipulation signal when a candle wipes out the previous High or Low and closes back within the range. -Highlights CISD zones related to manipulation or HTF SMT. Advanced Level Analysis -Tracks daily levels with minimum distance between them. Visual for HTF - MTF - LTF Mode 1 tf → TF1 → TF2 → TF3 → TF4 "1m → 15m → 30m → 1h → 4h" "3m → 30m → 4h → D → W" "5m → 1h → D → M → 3M" "15m → 4h → W → M → 3M" "30m → 4h → W → M → 3M" "1h → D → M → 3M" "4h → W → M" "D → M" "W → M" Mode 2 tf → TF1 → TF2 → TF3 → TF4 "1m → 15m → 30m → 1h → 4h" "3m → 30m → 1h → 4h → D" "5m → 1h → 4h → D → W" "15m → 1h → 4h → D → W" "30m → 1h → 4h → D → W" "1h → 4h → D → W → M" "4h → D → W → M" "D → W → M" "W → M" Model SMT: Same TF but Correlated Pairs Model Manual: use the manually set TF (HTF 1 - HTF 2 - HTF 3 - HTF 4)" With this indicator, you'll have a clearer view of what it can do to the price. For example, if we're bullish and see manipulation on the highs in HTF and CISD confirmation in LTF, we can predict that the price will fall to the TP level. If you like my work support me Disclaimer This script is provided for educational and informational purposes only. It does not constitute financial advice, investment advice, or a recommendation to buy or sell any financial instrument. The author takes no responsibility for any losses or damages resulting from the use of this script. Trading involves risk, and you are solely responsible for your trading decisions.
Chỉ báo Pine Script®
của Giovanni-1-
2
Smart Trader winning//@version=6 indicator('Smart Trader winning', overlay = true, max_labels_count = 500) // Inputs emaLength = input.int(20, 'EMA Length') buyColor = input.color(color.teal, 'Buy Arrow Color') sellColor = input.color(color.red, 'Sell Arrow Color') // Price and EMA ema = ta.ema(close, emaLength) // Volume Delta deltaVolume = volume * (close - open) / (high - low + 0.0001) // Buy / Sell Condition buyCond = ta.crossover(close, ema) sellCond = ta.crossunder(close, ema) // Plot EMA plot(ema, color = color.fuchsia, linewidth = 2) // Labels for Buy / Sell if buyCond label.new(bar_index, low, text = '▲ Buy', color = buyColor, style = label.style_label_up, textcolor = color.white) if sellCond label.new(bar_index, high, text = '▼ Sell', color = sellColor, style = label.style_label_down, textcolor = color.white) // Delta Volume Table (on chart right side) var table t = table.new(position.top_right, 2, 2, border_width = 1) buyVol = buyCond ? volume : na sellVol = sellCond ? volume : na table.cell(t, 0, 0, 'Buy Vol', bgcolor = color.new(color.green, 80)) table.cell(t, 1, 0, str.tostring(buyVol, format.volume), bgcolor = color.new(color.green, 90)) table.cell(t, 0, 1, 'Sell Vol', bgcolor = color.new(color.red, 80)) table.cell(t, 1, 1, str.tostring(sellVol, format.volume), bgcolor = color.new(color.red, 90)) // Background Highlight for Trade Zone bgcolor(buyCond ? color.new(color.green, 85) : na) bgcolor(sellCond ? color.new(color.red, 85) : na)
Chỉ báo Pine Script®
của SmartTrader-20
Smart Trader winning//@version=6 indicator('Smart Trader winning', overlay = true, max_labels_count = 500) // Inputs emaLength = input.int(20, 'EMA Length') buyColor = input.color(color.teal, 'Buy Arrow Color') sellColor = input.color(color.red, 'Sell Arrow Color') // Price and EMA ema = ta.ema(close, emaLength) // Volume Delta deltaVolume = volume * (close - open) / (high - low + 0.0001) // Buy / Sell Condition buyCond = ta.crossover(close, ema) sellCond = ta.crossunder(close, ema) // Plot EMA plot(ema, color = color.fuchsia, linewidth = 2) // Labels for Buy / Sell if buyCond label.new(bar_index, low, text = '▲ Buy', color = buyColor, style = label.style_label_up, textcolor = color.white) if sellCond label.new(bar_index, high, text = '▼ Sell', color = sellColor, style = label.style_label_down, textcolor = color.white) // Delta Volume Table (on chart right side) var table t = table.new(position.top_right, 2, 2, border_width = 1) buyVol = buyCond ? volume : na sellVol = sellCond ? volume : na table.cell(t, 0, 0, 'Buy Vol', bgcolor = color.new(color.green, 80)) table.cell(t, 1, 0, str.tostring(buyVol, format.volume), bgcolor = color.new(color.green, 90)) table.cell(t, 0, 1, 'Sell Vol', bgcolor = color.new(color.red, 80)) table.cell(t, 1, 1, str.tostring(sellVol, format.volume), bgcolor = color.new(color.red, 90)) // Background Highlight for Trade Zone bgcolor(buyCond ? color.new(color.green, 85) : na) bgcolor(sellCond ? color.new(color.red, 85) : na)
Chỉ báo Pine Script®
của SmartTrader-20
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.
Chỉ báo Pine Script®
của billal-kashif
Speed Coding BTC Pro SystemSpeed Coding BTC Pro System is an advanced TradingView automation strategy designed for Bitcoin trading. It sends Buy/Sell signals automatically from TradingView to your exchange or trading bot using Webhook API integration. To activate automation, the client only needs to fill in the following 4 inputs: ⸻ 1) Apikey The Apikey is your unique security key used to authorize and connect the strategy with your automation system or trading bot. ✅ What to enter: • Paste the API Key provided by your trading bridge / bot / automation panel. ⚠️ Important: • Do not share your API key with anyone. • Incorrect API key will stop order execution. ⸻ 2) Symbol The Symbol defines which trading pair or instrument the automation will trade. ✅ Examples (depends on exchange format): • BTCUSDT • BTCUSD • BTCUSDT.P • XBTUSD 📌 Note: Always enter the exact symbol name supported by your exchange or automation bridge. ⸻ 3) Strategy Tag The Strategy Tag is a label used to identify this strategy’s signals inside your automation system. It helps manage multiple strategies or multiple client accounts easily. ✅ Recommended Tags: • SC_BTC_PRO • SPEED_BTC_SYSTEM • SCALP_BTC_PRO • SPEEDCODING_BTC 📌 Best Practice: Keep the same tag for one client to maintain clean tracking. ⸻ 4) Qty The Qty defines the order size or trade quantity. ✅ Example: • 0.01 BTC (as shown in your settings) ⚠️ Note: Quantity depends on account balance and exchange minimum order rules. ✅ How Automation Works 1. The strategy generates a Buy/Sell or Long/Short signal on TradingView 2. TradingView sends the signal through Webhook Alert 3. Your connected bot/bridge receives the message 4. Orders are placed automatically on the exchange ⸻ ✅ Client Safety Recommendations • Always test in Demo/Paper Trading first • Confirm correct Symbol and Qty before live trading • Run one test alert to verify webhook connection
Chiến lược Pine Script®
của Speed_Coding_infotech
SAI RAM Pro"ॐ SAI RAM Pro" is an ultra-dense, Indian-market-oriented super-indicator that combines ICT HTF visualization, CPR, Episodic Pivots, dynamic S/R, multi-MA systems, premium risk & position sizing dashboard — basically a full trading cockpit in one Pine Script, best suited for screen-real-estate-rich traders who can handle extreme information density. This is not a simple signal generator. It is a professional-grade trading workstation packed into one Pine Script indicator. Its goal is to give an experienced trader almost everything needed for intraday / positional decision making in one glance: Multiple classical + modern price levels Multi-timeframe context (ICT style higher timeframe candles) Momentum & trend filters Volume & volatility context Episodic Pivot (explosive move) detection CPR (Central Pivot Range) deep version Risk & position sizing calculator + live dashboard Visual trade management lines (entry, SL, targets, trailing, breakeven) Very strong Indian trader spiritual / motivational watermark It tries to be all-in-one cockpit for someone who trades Nifty/Banknifty options or futures aggressively. Big Picture – What You Actually See on Chart Very crowded chart overlays Multiple EMAs (9 / 50 / 200 or custom lengths & types) VWAP 52-week high/low/average Daily CPR + deep CPR logic Pivot Points (many types: Traditional, Fib, Camarilla, Woodie…) Dynamic Support/Resistance boxes + volume-weighted zones ICT-style higher timeframe candles (30m, 1h, 4h, Daily…) projected on current chart FVG (Fair Value Gaps) & Imbalance boxes from HTF Clear Trend double channel (REMA based with glow effect) Signal / Pattern highlights Episodic Pivot (EP Pro) – strong volume + body + range explosion candles Angel Power RSI-MA based trend change arrows Strong volume squares RSI & volume colored candles Risk Management & Trade Dashboard (most unique part) Live lines: Entry, SL, R1/R2/R3, Breakeven, Trailing SL Full premium RMC dashboard showing: Capital, segment (Nifty/Banknifty/Gold/Options…), direction, lots Position value, risk amount, 1R %, R1/R2/R3 profits Current unrealized P&L Auto or manual position sizing logic Very detailed labels on every level with RR info Small but always visible elements Top/middle/bottom dashboard with ADX, ATR, RSI, India VIX + trade/no-trade decisions Spiritual watermark (ॐ Sri ಸಾಯಿ ರಾಮ್‌ + mantra + motivational quote) If you plan to actually use it live, I strongly recommend: Turning off 60–70% of the features initially (hide most HTF candles, disable some MAs, hide pivot points, etc.) Focus mainly on: EP Pro signals + CPR levels + RMC dashboard + one strong trend filter (Clear Trend or Angel Power) Use it on 5-min or 15-min charts — 1-min will be pure chaos If you plan to actually use it live, I strongly recommend: Turning off 60–70% of the features initially (hide most HTF candles, disable some MAs, hide pivot points, etc.) Focus mainly on: EP Pro signals + CPR levels + RMC dashboard + one strong trend filter (Clear Trend or Angel Power) Use it on 5-min or 15-min charts — 1-min will be pure chaos
Chỉ báo Pine Script®
của vipsbnglur369
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).
Chỉ báo Pine Script®
của 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.
Chỉ báo Pine Script®
của MaxMaserati
4
Buyers & sellers Candle Control Dominance Zone @MaxMaserati 3.0Description The Buyers & Sellers Candle Control Dominance Zone is a surgical price-action tool designed to identify and project key supply and demand zones derived from candle anatomy across multiple timeframes. By splitting candles into "Sellers Control" (upper wick/shadow) and "Buyers Control" (lower wick/shadow) regions, this script visualizes exactly where price rejection and absorption are occurring. With the new HTF Engine, you can now view these institutional rejection zones from a Higher Timeframe (e.g., 4H) while trading on a Lower Timeframe (e.g., 15m). How it Works The indicator identifies specific "Control Zones" based on the battle between buyers and sellers: Live Control (Current & HTF): Real-time monitoring of the developing candle. See a 4H wick forming live while watching the 1m chart. Last Closed Control (Current & HTF): Projects the zones from the most recently completed candle. Dominance Zones (BuBC & BeBC): BuBC (Bullish Body Close): A "Dominance Zone" triggered when a candle closes above the previous candle's high. Signifies strong bullish momentum. BeBC (Bearish Body Close): A "Dominance Zone" triggered when a candle closes below the previous candle's low. Signifies aggressive selling pressure. Key Features Multi-Timeframe (MTF) Overlay: Plot 4H, Daily, or Weekly control zones directly on your lower timeframe scalping charts. Smart Labeling: HTF labels automatically update to show the zone type (e.g., "Sellers Control (Live) ") and whether the last candle was a Dominance candle (BuBC/BeBC). Dynamic Extension: Zones are projected forward to help you catch retests of rejection levels. Alerts Included: Built-in alerts trigger when price crosses into a Dominance Zone (BuBC/BeBC), allowing you to set it and forget it. Can be use as: Support & Resistance: Use Buyers Control zones (lower wicks) as demand zones for longs and Sellers Control zones (upper wicks) as supply zones for shorts. Trend Confirmation: A BuBC zone often acts as a launchpad for continued upside. If price falls back into a BuBC zone and rejects, it is a high-probability continuation signal. Fractal Entry: Use the HTF zones to find the "Big Picture" levels, then use the Current TF zones to refine your entry with precision. Settings Display Filter: Toggle Current TF zones (Live, Closed, BuBC, BeBC) independently. Higher Timeframe Settings: Enable/Disable HTF overlay and select your preferred timeframe (e.g., 240 for 4H). Visuals: Fully adjustable transparency, colors, and extension lengths to keep your chart clean.
Chỉ báo Pine Script®
của MaxMaserati
Manual Checklist📋 Manual Trading Checklist This indicator is used to support disciplined, rule-based trading by displaying a manual checklist directly on the chart. 🎯 Purpose The goal of this indicator is to keep your trade criteria visible at all times, helping you: - Stay consistent with your trading rules - Reduce emotional or impulsive decisions - Clearly define bias before entering a trade ℹ️ Important Note The checklist items and their text cannot be edited. All items are predefined, based on the checklist I personally use before entering a trade. Each item can only be enabled or disabled by selecting its state: 🟢 Bullish 🔴 Bearish ⚪ Neutral This is intentional, to enforce consistency and avoid changing rules mid-trade. ✅ Features - On-chart checklist displayed as a floating label - Manual status selection per item (Bullish / Bearish / Neutral) - Instant updates when inputs are changed - Works on any symbol and timeframe - No calculations, no signals, no automation 🧾 Checklist Items - Trend Change Candle - Overall Trend - Volume - Distance from SMA 20 - Gaps - Support / Resistance - CCI - Checklist Summary (final bias) 🎨 Customization - Text position: Top / Middle / Bottom & Left / Center / Right - Vertical offset for fine positioning - Text size: Huge / Large / Normal / Small - Fully customizable text color 🛠 How to Use - Add the indicator to your chart - Open Settings → Inputs - Set each checklist item to Bullish, Bearish, or Neutral - Use the Checklist Summary as your final trade bias Note: This indicator is fully manual and intended as a decision-support tool only.
Chỉ báo Pine Script®
của ItamarE7237
Triple SMA📌 Triple SMA Indicator (20 / 50 / 200) Triple SMA is a simple and beginner-friendly Moving Average indicator that shows SMA 20, SMA 50, and SMA 200 together on one chart. No need to add multiple indicators — everything is included in one clean tool. Perfect for crypto, forex, and stock trading. ⭐ Why Traders Use This Indicator ✅ Shows trend direction clearly ✅ Helps identify bullish & bearish markets ✅ Clean chart — no clutter ✅ Works on any timeframe 🔧 What You Get 📈 Three Important SMAs SMA 20 → short-term trend SMA 50 → mid-term trend SMA 200 → long-term market direction ⚙️ Full Custom Control Change length for each SMA separately Set different colors & line thickness Show or hide any SMA easily 🔄 Optional Smoothing (Advanced – Optional) EMA, WMA, VWMA, SMMA SMA + Bollinger Bands (Default: OFF for clean charts) 🧠 How Beginners Can Use It Price above SMA 200 → market bullish ✅ Price below SMA 200 → market bearish ✅ SMA 20 above SMA 50 above SMA 200 → strong uptrend SMA 20 below SMA 50 below SMA 200 → strong downtrend Use it for trend confirmation, not as a standalone buy/sell signal. 🎯 Best For ✔ Beginners ✔ Swing traders ✔ Trend traders ✔ Crypto / Forex / Stocks ⚠️ Disclaimer This indicator is for educational purposes only. Always use proper risk management.
Chỉ báo Pine Script®
của Leo524
Price to Volume Change - Last 2 BarsPrice to Volume Change measures how efficiently price is moving relative to changes in trading activity between the last two bars. It calculates the percentage change in price and volume, then displays their ratio in a table directly on the chart. The ratio reveals whether price movement is supported by participation (Default Values): 1–3 (Green) : Balanced move — price change is proportionate to volume change (healthy expansion). Above 3 (Red) : Price is moving more than volume — potential inefficiency, exhaustion, or low-participation move. Below 1 (Gray) : Volume is expanding faster than price — possible absorption or compression. This helps identify whether market moves are confirmed by participation or occurring on weak underlying activity. Note : Usually used for Penny Stock indication of continuation of growth (Long entry only). Best used in daily chart once the stock is found and before trading day starts.
Chỉ báo Pine Script®
của yuval3000
Silver: India MCX vs US COMEX vs China SHFE (USD/oz)Silver: MCX vs COMEX vs SHFE (ex-VAT) – USD/oz Comparison This indicator is designed to visually compare silver prices across major global futures markets by normalizing them into a common reference unit: USD per troy ounce. It helps users study relative pricing, regional premiums, and inter-market behavior between India, the US, and China. 🌍 Markets Compared MCX Silver (India) – quoted in INR per kilogram COMEX Silver (USA) – quoted in USD per troy ounce (used as reference) SHFE Silver (China) – quoted in CNY per kilogram 🔄 Methodology Overview (high-level, non-code) MCX and SHFE prices are converted into USD per troy ounce using prevailing FX rates. COMEX silver is used as the global benchmark. China VAT adjustment: SHFE silver futures prices are VAT-inclusive; a standard 13% VAT is removed to obtain an ex-VAT economic price for comparison. A standard conversion factor is used to normalize kilograms to troy ounces. All calculations are performed consistently across the selected timeframe. 📊 What the Indicator Displays 1️⃣ Normalized Silver Prices (USD/oz) Line plots showing: MCX Silver (USD/oz equivalent) COMEX Silver (USD/oz) SHFE Silver ex-VAT (USD/oz equivalent) This allows direct comparison without unit or currency distortion. 2️⃣ Regional Premium / Discount (%) MCX premium or discount relative to COMEX SHFE (ex-VAT) premium or discount relative to COMEX Positive values indicate regional prices trading above COMEX; negative values indicate discounts. 🎯 Intended Use Inter-market analysis and study Understanding regional demand/supply stress Observing structural premiums and discounts Educational and analytical purposes This indicator does not generate buy/sell signals and is not a trading system. ⚠️ Important Notes Futures markets differ in trading hours, liquidity, and regulations. Persistent premiums or discounts may reflect: Import/export policies Local supply constraints Currency movements Capital controls Values may differ depending on the chart symbol and timeframe used. 📚 Disclaimer This indicator is provided for informational and educational purposes only. It does not constitute financial advice or a recommendation to trade or invest.
Chỉ báo Pine Script®
của rajatgupta238
1
Blagirev Fractal Wave Detector - v3.0 It's concept work basing on empirical data which I've discovered through charts and some fundamentals from Ilya Prigozin and Mandesbrot theory concerning inlinar world, fractals and chaos theory. I'm elaborating and investigating the fractals and its relation with market moving. For any comment and feedback are welcome Indicator shows upcomming waves which can disrupt and create new structure for the price. Indicator works on m5 for Red Waves and for H1 for Green Waves. Triangle indicated upcomming waves impluse. More and bigger triangle shows power and speed of impluse of the wave. 3 Triangle means that fractal wave has started and reached several levels of the prices.
Chỉ báo Pine Script®
của vblagirev