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Volume

Filter Volume1. Indicator Name Filter Volume 2. One-line Introduction A regression-based trend filter that quantifies and visualizes market direction and strength using price behavior. 3. Overall Description Filter Volume+ is a trend-detection indicator that uses linear regression to evaluate the dominant direction of price movement over a given period. It compares historical regression values to determine whether the market is in a bullish, bearish, or neutral state. The indicator applies a percentage threshold to filter out weak or indecisive trends, highlighting only significant movements. Each trend state is visualized through distinct colors: bullish (greenish), bearish (reddish), and neutral (gray), with intensity reflecting trend strength. To reduce noise and create smooth visual signals, a three-step smoothing process is applied to the raw trend intensity. Users can customize the regression source, lookback period, and sensitivity, allowing the indicator to adapt to various assets and timeframes. This tool is especially useful in filtering entry signals based on clear directional bias, making it suitable for trend-following or confirmation strategies. 4. Key Benefits (Title + Description) ✅ Quantified Trend Strength Only displays trend signals when a statistically significant direction is detected using linear regression comparisons. ✅ Visual Clarity with Color Coding Each market state (bullish, bearish, neutral) is represented with distinct colors and transparency, enabling fast interpretation. ✅ Custom Regression Source Users can define the data input (e.g., close, open, indicator output) for regression calculation, increasing strategic flexibility. ✅ Multi-Level Smoothing Applies three layers of smoothing (via moving averages) to eliminate noise and produce a stable, flowing trend curve. ✅ Area Fill Visualization Plots a colored band between the trend value and zero-line, helping users quickly gauge the market's dominant force. ✅ Adjustable Sensitivity Settings Includes tolerance and lookback controls, allowing traders to fine-tune how reactive or conservative the trend detection should be. 5. Indicator User Guide 📌 Basic Concept Filter Volume+ assesses the direction of price by comparing regression values over a selected period. If the percentage of upward comparisons exceeds a threshold, a bullish state is shown; if downward comparisons dominate, it shows a bearish state. ⚙️ Settings Overview Lookback Period (n): The number of bars to compare for trend analysis Range Tolerance (%): Minimum threshold for declaring a strong trend Regression Source: The data used for regression (e.g., close, open) Linear Regression Length: Number of bars used to compute each regression value Bull/Bear Color: Custom colors for bullish and bearish trends 📈 Example Timing When the trend line stays above zero and the green color intensity increases → trend gaining strength After a neutral phase (gray), the color shifts quickly to greenish → early trend reversal 📉 Example Timing When the trend line stays below zero with deepening red color → strong bearish continuation Sudden change from bullish to bearish color with rising intensity 🧪 Recommended Use Use as a trend confirmation filter alongside entry/exit strategies Ideal for swing or position trades in trending markets Combine with oscillators like RSI or MACD for improved signal validation 🔒 Cautions In ranging (sideways) markets, the color may change frequently – avoid relying solely on this indicator in those zones. Low-intensity colors (faded) suggest weak trends – better to stay on the sidelines. A short lookback period may cause over-sensitivity and false signals. When using non-price regression sources, expect the indicator to behave differently – test before deploying. +++
Pine Script® indicator
by c9indicator
QQE MOD + Integrated RSI 14 (2in1)This is a custom modification of the popular QQE MOD by Mihkel00. I have re-engineered the script to maximize utility for free TradingView users who are limited to 3 indicators per chart. Key Changes: Secondary Trend Line: The secondary line has been reprogrammed to function exactly like a Standard RSI (Length 14). 2-in-1 Efficiency: You no longer need to load a separate RSI indicator. This script now displays market momentum (QQE) and standard price strength (RSI 14) in a single pane. This modification frees up a valuable indicator slot, allowing you to add a third indicator of your choice without upgrading your plan.
Pine Script® indicator
by XAUUSD2026CHK
MTF EMA Hariss 369The strategy has been prepared in a simplistic manner and easy to understand the concept by any novice trader. Indicators used: Current Time frame 20 EMA- Gives clear look about current time frame dynamic support and resistance and trend as well. Higher Time Frame 20 EMA: Gives macro level trend, support and resistance Kama: Capture volatility and trend direction. RVOL: Main factor of price movement. Buy when price closes above current time frame 20 ema and current time frame 20 ema is above higher time frame 20 ema. Stop loss just below the low of last candle. One can use current time frame 20 ema, higher time frame 20 ema or kama as stop loss depending upon type of asset class and risk appetite. The ideal way is to keep 20 ema as trailing sl if one wants to trail with trend. Sell when price closes below current time frame 20 ema and current time frame 20 ema is lower than higher time frame 20 ema. Stop loss just above high of last candle. Ideal target is 1.5 or 2 times of stop loss. Entry and exit time depends on trading style. Eg. if you want to enter and exit in 5 min time frame, then choose 15 min or 1h as higher time frame as trend filter. Buy and sell signals are also plotted based on this strategy. One should always go with the higher time frame trend. Opting higher time frame trend filter always filters out market noises.
Pine Script® strategy
by Hariss369
MACD Momentum Structure & Wedge Sniper [MTF]🚀 MACD Market Structure: The All-in-One System This tool automates institutional price action analysis by filtering market noise using MACD momentum rather than simple candle wicks. 🔥 Key Features Noise-Free Structure: Identifies true Swing Highs (SH) and Swing Lows (SL) based on MACD peaks, ignoring fake-outs. Auto-Trendlines: Automatically draws purple trendlines connecting recent swings to visualize Wedges, Triangles, and Squeezes in real-time. Smart Zones: On a trend change (CHoCH), it automatically draws the Fixed Range Volume Profile to highlight the "Point of Control" (Institutional Entry Level). "Sniper" Entries: Signals entries only when price retests a Zone AND momentum confirms it on a lower timeframe (e.g., M1 crossover). MTF Dashboard: Monitors trends across 4 timeframes simultaneously so you never trade against the higher timeframe.
Pine Script® indicator
by Csmile_
5
CVD [able0.1]# CVD Overlay iOS Style - Complete User Guide ## 📖 Table of Contents 1. (#what-is-cvd) 2. (#installation-guide) 3. (#understanding-the-display) 4. (#reading-the-info-table) 5. (#settings--customization) 6. (#trading-strategies) 7. (#common-mistakes-to-avoid) --- ## 🎯 What is CVD? **CVD (Cumulative Volume Delta)** tracks the **difference between buying and selling pressure** over time. ### Simple Explanation: - **Positive CVD** (Orange) = More buying than selling = Bulls winning - **Negative CVD** (Gray) = More selling than buying = Bears winning - **Rising CVD** = Increasing buying pressure = Potential uptrend - **Falling CVD** = Increasing selling pressure = Potential downtrend ### Why It Matters: CVD helps you see **who's really in control** of the market - not just price movement, but actual buying/selling volume. --- ## 🚀 Installation Guide ### Step 1: Open Pine Editor 1. Go to TradingView 2. Click the **"Pine Editor"** tab at the bottom of the screen 3. Click **"New"** or open an existing script ### Step 2: Copy & Paste the Code 1. Select all existing code (Ctrl+A / Cmd+A) 2. Delete it 3. Copy the entire CVD iOS Style code 4. Paste it into Pine Editor ### Step 3: Add to Chart 1. Click **"Save"** button (or Ctrl+S / Cmd+S) 2. Click **"Add to Chart"** button 3. The indicator will appear on your chart! ### Step 4: Initial Setup - The indicator appears as an **overlay** on your price chart - You'll see an **orange/gray line** following price - An **info table** appears in the top-right corner --- ## 📊 Understanding the Display ### Main Chart Elements: #### 1. **CVD Line** (Orange/Gray) - **Orange Line** = Positive CVD (buying pressure) - **Gray Line** = Negative CVD (selling pressure) - This line moves with your price chart but shows volume delta #### 2. **CVD Zone** (Shaded Area) - Light shaded box around the CVD line - Shows the "range" of CVD movement - Helps visualize CVD boundaries #### 3. **Center Line** (Dotted) - Gray dotted line in the middle of the zone - Represents the "neutral" point - CVD crossing this = shift in market control #### 4. **Reference Asset Line** (Light Gray) - Shows Bitcoin (BTC) price movement for comparison - Helps you see if your asset moves with or against BTC - Can be changed to any asset you want #### 5. **CVD Label** - Shows current CVD value - Positioned above/below zone to avoid overlap - Updates in real-time #### 6. **Reset Background** (Very Light Gray) - Appears when CVD resets - Indicates a new calculation period --- ## 📋 Reading the Info Table The info table (top-right) shows **8 key metrics**: ### Row 1: **Header** ``` ╔═ CVD able ═╗ | 15m | ████████ | able ``` - **CVD able** = Indicator name + creator - **15m** = Current timeframe - **████████** = Visual decoration - **able** = Creator signature ### Row 2: **CVD Value** ``` CVD▲ | 7.39K | ████████ | █ █ █ ``` - **CVD▲** = CVD with trend arrow - ▲ = CVD increasing - ▼ = CVD decreasing - ► = CVD unchanged - **7.39K** = Actual CVD number - **Progress Bar** = Visual strength (darker = stronger) - **Vertical Bars** = Height shows intensity ### Row 3: **Delta** ``` ◆DELTA | -1.274K | ████░░░░ | ░ ░ ``` - **Delta** = Volume change THIS BAR ONLY - **Negative** = More selling this bar - **Positive** = More buying this bar - Shows **immediate** pressure (not cumulative) ### Row 4: **UP Volume** ``` UP↑ | -1.263K | ████████ | █ █ █ ``` - Total **buying volume** this bar - Higher = Stronger buying pressure - Green/Orange vertical bars = Bullish strength ### Row 5: **DOWN Volume** ``` DN↓ | 2.643K | ████████ | ░ ░ ░ ``` - Total **selling volume** this bar - Higher = Stronger selling pressure - Gray vertical bars = Bearish strength ### Row 6-7: **Reference Asset** (if enabled) ``` ══ REF ══ | ══════ | ████████ | █ █ PRICE▲ | 4130.300 | ████████ | █ █ ``` - **REF** = Reference asset header - **PRICE▲** = Reference price with trend - Shows if BTC (or chosen asset) is rising/falling - Compare with your chart to see correlation ### Row 8: **Market Status** ``` ◄STATUS► | NEUT | ████░░░░ | ▒ ▒ ``` - **BULL** = CVD positive + Delta positive = Strong buying - **BEAR** = CVD negative + Delta negative = Strong selling - **NEUT** = Mixed signals = Wait for clarity **Status Colors:** - **Orange background** = Bullish (good for long) - **Gray background** = Bearish (good for short) - **White background** = Neutral (no clear signal) --- ## ⚙️ Settings & Customization ### Main Settings (⚙️) #### **CVD Reset** - **None** = CVD never resets (from beginning of data) - **On Higher Timeframe** = Resets when HTF candle closes - 15m chart → Resets hourly - 1h chart → Resets daily - Recommended for most traders - **On Session Start** = Resets at market open - **On Visible Chart** = Resets from leftmost visible bar #### **Precision** - **Low (Fast)** = Uses 1m data, faster but less accurate - **Medium** = Uses 5m data, balanced (recommended) - **High** = Uses 15m data, most accurate but slower #### **Cumulative** - ✅ On = CVD accumulates over time (recommended) - ❌ Off = Shows only current bar delta #### **Show Labels** - ✅ On = Shows CVD value label on chart - ❌ Off = Cleaner chart, no label #### **Show Info Table** - ✅ On = Shows info table (recommended for beginners) - ❌ Off = Hide table for minimalist view --- ### 🎨 iOS Style Colors You can customize **every color** to match your chart theme: #### **Primary Colors** - **Primary (Orange)** = Main bullish color (#FF9500) - **Secondary (Gray)** = Main bearish color (#8E8E93) - **Background** = Table background (#FFFFFF) - **Text** = Text color (#1C1C1E) #### **Bullish/Bearish** - **Bullish (Orange)** = Positive CVD color - **Bearish (Gray)** = Negative CVD color - **Opacity** = Zone transparency (0-100%) - **Show Zone** = Enable/disable shaded area #### **Table Colors** (📋) - **Header Background** = Top row background - **Header Text** = Top row text color - **Cell Background** = Data cells background - **Cell Text** = Data cells text color - **Border** = Table border color - **Accent Background** = Special rows background - **Alert Background** = Warning/status background --- ### 📊 Reference Asset Settings #### **Enable** - ✅ On = Shows reference asset line - ❌ Off = Hide reference asset #### **Symbol** - Default: `BINANCE:BTCUSDT` - Can change to any asset: - `BINANCE:ETHUSDT` (Ethereum) - `SPX` (S&P 500) - `DXY` (US Dollar Index) - Any ticker symbol #### **Color & Width** - Customize line appearance - Width: 1-4 (thickness) --- ## 💡 Trading Strategies ### Strategy 1: CVD Divergence (Beginner-Friendly) **What to Look For:** - Price making **higher highs** but CVD making **lower highs** = Bearish divergence - Price making **lower lows** but CVD making **higher lows** = Bullish divergence **How to Trade:** 1. Wait for divergence to form 2. Look for confirmation (price reversal, candlestick pattern) 3. Enter trade in divergence direction 4. Stop loss beyond recent high/low **Example:** ``` Price: /\ /\ /\ (higher highs) CVD: /\ / \/ (lower highs) = Bearish signal ``` ### Strategy 2: CVD Trend Following (Intermediate) **What to Look For:** - **Strongly rising CVD** + **rising price** = Strong uptrend - **Strongly falling CVD** + **falling price** = Strong downtrend **How to Trade:** 1. Wait for CVD and price moving in same direction 2. Enter on pullbacks to support/resistance 3. Stay in trade while CVD trend continues 4. Exit when CVD trend breaks **Signals:** - CVD ▲▲▲ + Price ↑ = Go LONG - CVD ▼▼▼ + Price ↓ = Go SHORT ### Strategy 3: CVD + Reference Asset (Advanced) **What to Look For:** - Your asset **rising** but BTC (reference) **falling** = Relative strength - Your asset **falling** but BTC (reference) **rising** = Relative weakness **How to Trade:** 1. Compare CVD movement with BTC 2. If your CVD rises faster than BTC = Buy signal 3. If your CVD falls faster than BTC = Sell signal 4. Use for **pair trading** or **asset selection** ### Strategy 4: Volume Delta Confirmation **What to Look For:** - **Large positive Delta** = Strong buying this bar - **Large negative Delta** = Strong selling this bar **How to Trade:** 1. Price breaks resistance + Large positive Delta = Confirmed breakout 2. Price breaks support + Large negative Delta = Confirmed breakdown 3. Use Delta to **confirm** price moves, not predict them **Rules:** - Delta > 2x average = Very strong pressure - Delta near zero at key level = Weak move, likely false breakout --- ## 🎓 Reading Real Scenarios ### Scenario 1: Strong Buying Pressure ``` Table Shows: CVD▲ | 12.5K | ████████ | ████ (CVD rising) ◆DELTA | +2.8K | ████████ | ▲ (Positive delta) UP↑ | 3.1K | ████████ | ████ (High buy volume) DN↓ | 0.3K | ██░░░░░░ | ░ (Low sell volume) ◄STATUS► | BULL | ████████ | ████ (Orange background) ``` **Interpretation:** Strong buying, good for LONG trades ### Scenario 2: Distribution (Hidden Selling) ``` Table Shows: CVD► | 8.2K | ████░░░░ | ▒▒ (CVD flat) ◆DELTA | -1.5K | ████████ | ▼ (Negative delta) UP↑ | 0.8K | ███░░░░░ | ░ (Low buy volume) DN↓ | 2.3K | ████████ | ████ (High sell volume) ◄STATUS► | BEAR | ████████ | ░░░░ (Gray background) ``` **Interpretation:** Price may look stable, but selling increasing = Prepare for drop ### Scenario 3: Neutral/Choppy Market ``` Table Shows: CVD► | 5.1K | ████░░░░ | ▒ (CVD sideways) ◆DELTA | +0.2K | ██░░░░░░ | ─ (Small delta) UP↑ | 1.2K | ████░░░░ | ▒ (Medium buy) DN↓ | 1.0K | ████░░░░ | ▒ (Medium sell) ◄STATUS► | NEUT | ████░░░░ | ▒▒ (White background) ``` **Interpretation:** No clear direction = Stay out or reduce position size --- ## ⚠️ Common Mistakes to Avoid ### Mistake 1: Trading on CVD Alone - ❌ **Wrong:** "CVD is rising, I'll buy immediately" - ✅ **Right:** "CVD is rising, let me check price structure, support/resistance, and wait for confirmation" ### Mistake 2: Ignoring Delta - ❌ **Wrong:** Looking only at cumulative CVD - ✅ **Right:** Watch both CVD (trend) and Delta (momentum) - Delta shows **immediate** pressure changes ### Mistake 3: Wrong Timeframe - ❌ **Wrong:** Using 1m chart with High Precision (too slow) - ✅ **Right:** Match precision to timeframe: - 1m-5m → Low Precision - 15m-1h → Medium Precision - 4h+ → High Precision ### Mistake 4: Not Using Reset - ❌ **Wrong:** Using "None" reset for intraday trading - ✅ **Right:** Use "On Higher Timeframe" to see fresh CVD each session ### Mistake 5: Overtrading Neutral Status - ❌ **Wrong:** Forcing trades when STATUS = NEUT - ✅ **Right:** Only trade clear BULL or BEAR status ### Mistake 6: Ignoring Reference Asset - ❌ **Wrong:** Trading altcoin without checking BTC - ✅ **Right:** Always check if BTC CVD agrees with your asset --- ## 🔥 Pro Tips ### Tip 1: Multi-Timeframe Analysis - Check CVD on **3 timeframes**: - Lower TF (15m) = Entry timing - Current TF (1h) = Trade direction - Higher TF (4h) = Overall trend ### Tip 2: Volume Confirmation - Big price move + Small Delta = **Weak move** (likely reversal) - Small price move + Big Delta = **Strong accumulation** (continuation) ### Tip 3: CVD Reset Zones - Pay attention to **reset backgrounds** (light gray) - Often marks **session starts** = High volatility periods ### Tip 4: Divergence + Status - Bearish divergence + STATUS = BEAR = **Strongest short signal** - Bullish divergence + STATUS = BULL = **Strongest long signal** ### Tip 5: Color Psychology - **Orange** (Bullish) is **warm** = Buying energy - **Gray** (Bearish) is **cool** = Selling pressure - Train your eye to read colors instantly ### Tip 6: Table as Quick Scan - Glance at table without reading numbers: - **All orange** = Bullish - **All gray** = Bearish - **Mixed** = Wait --- ## 📱 Quick Reference Card | Signal | CVD | Delta | Status | Action | |--------|-----|-------|--------|--------| | **Strong Buy** | ▲▲ High | ++ Positive | BULL | Long Entry | | **Strong Sell** | ▼▼ Low | -- Negative | BEAR | Short Entry | | **Divergence Buy** | ▲ Rising | Price ▼ | → BULL | Long Setup | | **Divergence Sell** | ▼ Falling | Price ▲ | → BEAR | Short Setup | | **Neutral** | → Flat | ~0 Near Zero | NEUT | Stay Out | | **Accumulation** | → Flat | ++ Positive | NEUT→BULL | Watch for Breakout | | **Distribution** | → Flat | -- Negative | NEUT→BEAR | Watch for Breakdown | --- ## 🆘 Troubleshooting ### Issue: "Indicator not showing" - **Solution:** Make sure overlay=true in code, re-add to chart ### Issue: "Table overlaps with price" - **Solution:** Change table position in code or use TradingView's "Move" feature ### Issue: "CVD line too far from price" - **Solution:** This is normal! CVD is volume-based, not price-based. Focus on CVD direction, not position ### Issue: "Too many lines on chart" - **Solution:** Disable "Show Zone" and "Show Labels" in settings for cleaner view ### Issue: "Calculations too slow" - **Solution:** Change Precision to "Low (Fast)" or use higher timeframe ### Issue: "Reference asset not showing" - **Solution:** Check if "Enable" is ON and symbol is valid (e.g., BINANCE:BTCUSDT) --- ## 🎬 Getting Started Checklist - Install indicator on TradingView - Set precision to "Medium" - Set reset to "On Higher Timeframe" - Enable info table - Add reference asset (BTC) - Practice reading the table on demo account - Test on different timeframes (15m, 1h, 4h) - Compare CVD with your current strategy - Paper trade for 1 week before going live - Keep a trading journal of CVD signals --- ## 📚 Summary **CVD shows WHO is winning: Buyers or Sellers** **Key Points:** 1. **Orange/Rising CVD** = Buying pressure = Bullish 2. **Gray/Falling CVD** = Selling pressure = Bearish 3. **Delta** = Immediate momentum THIS BAR 4. **Status** = Overall market condition 5. **Always confirm** with price action & other indicators **Remember:** - CVD is a **tool**, not a crystal ball - Use with proper risk management - Practice makes perfect - Stay disciplined! --- **Created by: able** **Version:** iOS Style v1.0 **Contact:** For questions, refer to TradingView community Happy Trading! 🚀📈
Pine Script® indicator
by krittaphat6
Dynamic Equity Allocation Model//@version=6 indicator('Dynamic Equity Allocation Model', shorttitle = 'DEAM', overlay = false, precision = 1, scale = scale.right, max_bars_back = 500) // DYNAMIC EQUITY ALLOCATION MODEL // Quantitative framework for dynamic portfolio allocation between stocks and cash. // Analyzes five dimensions: market regime, risk metrics, valuation, sentiment, // and macro conditions to generate allocation recommendations (0-100% equity). // // Uses real-time data from TradingView including fundamentals (P/E, ROE, ERP), // volatility indicators (VIX), credit spreads, yield curves, and market structure. // INPUT PARAMETERS group1 = 'Model Configuration' model_type = input.string('Adaptive', 'Allocation Model Type', options = , group = group1, tooltip = 'Conservative: Slower to increase equity, Aggressive: Faster allocation changes, Adaptive: Dynamic based on regime') use_crisis_detection = input.bool(true, 'Enable Crisis Detection System', group = group1, tooltip = 'Automatic detection and response to crisis conditions') use_regime_model = input.bool(true, 'Use Market Regime Detection', group = group1, tooltip = 'Identify Bull/Bear/Crisis regimes for dynamic allocation') group2 = 'Portfolio Risk Management' target_portfolio_volatility = input.float(12.0, 'Target Portfolio Volatility (%)', minval = 3, maxval = 20, step = 0.5, group = group2, tooltip = 'Target portfolio volatility (Cash reduces volatility: 50% Equity = ~10% vol, 100% Equity = ~20% vol)') max_portfolio_drawdown = input.float(15.0, 'Maximum Portfolio Drawdown (%)', minval = 5, maxval = 35, step = 2.5, group = group2, tooltip = 'Maximum acceptable PORTFOLIO drawdown (not market drawdown - portfolio with cash has lower drawdown)') enable_portfolio_risk_scaling = input.bool(true, 'Enable Portfolio Risk Scaling', group = group2, tooltip = 'Scale allocation based on actual portfolio risk characteristics (recommended)') risk_lookback = input.int(252, 'Risk Calculation Period (Days)', minval = 60, maxval = 504, group = group2, tooltip = 'Period for calculating volatility and risk metrics') group3 = 'Component Weights (Total = 100%)' w_regime = input.float(35.0, 'Market Regime Weight (%)', minval = 0, maxval = 100, step = 5, group = group3) w_risk = input.float(25.0, 'Risk Metrics Weight (%)', minval = 0, maxval = 100, step = 5, group = group3) w_valuation = input.float(20.0, 'Valuation Weight (%)', minval = 0, maxval = 100, step = 5, group = group3) w_sentiment = input.float(15.0, 'Sentiment Weight (%)', minval = 0, maxval = 100, step = 5, group = group3) w_macro = input.float(5.0, 'Macro Weight (%)', minval = 0, maxval = 100, step = 5, group = group3) group4 = 'Crisis Detection Thresholds' crisis_vix_threshold = input.float(40, 'Crisis VIX Level', minval = 30, maxval = 80, group = group4, tooltip = 'VIX level indicating crisis conditions (COVID peaked at 82)') crisis_drawdown_threshold = input.float(15, 'Crisis Drawdown Threshold (%)', minval = 10, maxval = 30, group = group4, tooltip = 'Market drawdown indicating crisis conditions') crisis_credit_spread = input.float(500, 'Crisis Credit Spread (bps)', minval = 300, maxval = 1000, group = group4, tooltip = 'High yield spread indicating crisis conditions') group5 = 'Display Settings' show_components = input.bool(false, 'Show Component Breakdown', group = group5, tooltip = 'Display individual component analysis lines') show_regime_background = input.bool(true, 'Show Dynamic Background', group = group5, tooltip = 'Color background based on allocation signals') show_reference_lines = input.bool(false, 'Show Reference Lines', group = group5, tooltip = 'Display allocation percentage reference lines') show_dashboard = input.bool(true, 'Show Analytics Dashboard', group = group5, tooltip = 'Display comprehensive analytics table') show_confidence_bands = input.bool(false, 'Show Confidence Bands', group = group5, tooltip = 'Display uncertainty quantification bands') smoothing_period = input.int(3, 'Smoothing Period', minval = 1, maxval = 10, group = group5, tooltip = 'Smoothing to reduce allocation noise') background_intensity = input.int(95, 'Background Intensity (%)', minval = 90, maxval = 99, group = group5, tooltip = 'Higher values = more transparent background') // Styling Options color_scheme = input.string('EdgeTools', 'Color Theme', options = , group = 'Appearance', tooltip = 'Professional color themes') use_dark_mode = input.bool(true, 'Optimize for Dark Theme', group = 'Appearance') main_line_width = input.int(3, 'Main Line Width', minval = 1, maxval = 5, group = 'Appearance') // DATA RETRIEVAL // Market Data sp500 = request.security('SPY', timeframe.period, close) sp500_high = request.security('SPY', timeframe.period, high) sp500_low = request.security('SPY', timeframe.period, low) sp500_volume = request.security('SPY', timeframe.period, volume) // Volatility Indicators vix = request.security('VIX', timeframe.period, close) vix9d = request.security('VIX9D', timeframe.period, close) vxn = request.security('VXN', timeframe.period, close) // Fixed Income and Credit us2y = request.security('US02Y', timeframe.period, close) us10y = request.security('US10Y', timeframe.period, close) us3m = request.security('US03MY', timeframe.period, close) hyg = request.security('HYG', timeframe.period, close) lqd = request.security('LQD', timeframe.period, close) tlt = request.security('TLT', timeframe.period, close) // Safe Haven Assets gold = request.security('GLD', timeframe.period, close) usd = request.security('DXY', timeframe.period, close) yen = request.security('JPYUSD', timeframe.period, close) // Financial data with fallback values get_financial_data(symbol, fin_id, period, fallback) => data = request.financial(symbol, fin_id, period, ignore_invalid_symbol = true) na(data) ? fallback : data // SPY fundamental metrics spy_earnings_per_share = get_financial_data('AMEX:SPY', 'EARNINGS_PER_SHARE_BASIC', 'TTM', 20.0) spy_operating_earnings_yield = get_financial_data('AMEX:SPY', 'OPERATING_EARNINGS_YIELD', 'FY', 4.5) spy_dividend_yield = get_financial_data('AMEX:SPY', 'DIVIDENDS_YIELD', 'FY', 1.8) spy_buyback_yield = get_financial_data('AMEX:SPY', 'BUYBACK_YIELD', 'FY', 2.0) spy_net_margin = get_financial_data('AMEX:SPY', 'NET_MARGIN', 'TTM', 12.0) spy_debt_to_equity = get_financial_data('AMEX:SPY', 'DEBT_TO_EQUITY', 'FY', 0.5) spy_return_on_equity = get_financial_data('AMEX:SPY', 'RETURN_ON_EQUITY', 'FY', 15.0) spy_free_cash_flow = get_financial_data('AMEX:SPY', 'FREE_CASH_FLOW', 'TTM', 100000000) spy_ebitda = get_financial_data('AMEX:SPY', 'EBITDA', 'TTM', 200000000) spy_pe_forward = get_financial_data('AMEX:SPY', 'PRICE_EARNINGS_FORWARD', 'FY', 18.0) spy_total_debt = get_financial_data('AMEX:SPY', 'TOTAL_DEBT', 'FY', 500000000) spy_total_equity = get_financial_data('AMEX:SPY', 'TOTAL_EQUITY', 'FY', 1000000000) spy_enterprise_value = get_financial_data('AMEX:SPY', 'ENTERPRISE_VALUE', 'FY', 30000000000) spy_revenue_growth = get_financial_data('AMEX:SPY', 'REVENUE_ONE_YEAR_GROWTH', 'TTM', 5.0) // Market Breadth Indicators nya = request.security('NYA', timeframe.period, close) rut = request.security('IWM', timeframe.period, close) // Sector Performance xlk = request.security('XLK', timeframe.period, close) xlu = request.security('XLU', timeframe.period, close) xlf = request.security('XLF', timeframe.period, close) // MARKET REGIME DETECTION // Calculate Market Trend sma_20 = ta.sma(sp500, 20) sma_50 = ta.sma(sp500, 50) sma_200 = ta.sma(sp500, 200) ema_10 = ta.ema(sp500, 10) // Market Structure Score trend_strength = 0.0 trend_strength := trend_strength + (sp500 > sma_20 ? 1 : -1) trend_strength := trend_strength + (sp500 > sma_50 ? 1 : -1) trend_strength := trend_strength + (sp500 > sma_200 ? 2 : -2) trend_strength := trend_strength + (sma_50 > sma_200 ? 2 : -2) // Volatility Regime returns = math.log(sp500 / sp500 ) realized_vol_20d = ta.stdev(returns, 20) * math.sqrt(252) * 100 realized_vol_60d = ta.stdev(returns, 60) * math.sqrt(252) * 100 ewma_vol = ta.ema(math.pow(returns, 2), 20) realized_vol = math.sqrt(ewma_vol * 252) * 100 vol_premium = vix - realized_vol // Drawdown Calculation running_max = ta.highest(sp500, risk_lookback) current_drawdown = (running_max - sp500) / running_max * 100 // Regime Score regime_score = 0.0 // Trend Component (40%) if trend_strength >= 4 regime_score := regime_score + 40 regime_score else if trend_strength >= 2 regime_score := regime_score + 30 regime_score else if trend_strength >= 0 regime_score := regime_score + 20 regime_score else if trend_strength >= -2 regime_score := regime_score + 10 regime_score else regime_score := regime_score + 0 regime_score // Volatility Component (30%) if vix < 15 regime_score := regime_score + 30 regime_score else if vix < 20 regime_score := regime_score + 25 regime_score else if vix < 25 regime_score := regime_score + 15 regime_score else if vix < 35 regime_score := regime_score + 5 regime_score else regime_score := regime_score + 0 regime_score // Drawdown Component (30%) if current_drawdown < 3 regime_score := regime_score + 30 regime_score else if current_drawdown < 7 regime_score := regime_score + 20 regime_score else if current_drawdown < 12 regime_score := regime_score + 10 regime_score else if current_drawdown < 20 regime_score := regime_score + 5 regime_score else regime_score := regime_score + 0 regime_score // Classify Regime market_regime = regime_score >= 80 ? 'Strong Bull' : regime_score >= 60 ? 'Bull Market' : regime_score >= 40 ? 'Neutral' : regime_score >= 20 ? 'Correction' : regime_score >= 10 ? 'Bear Market' : 'Crisis' // RISK-BASED ALLOCATION // Calculate Market Risk parkinson_hl = math.log(sp500_high / sp500_low) parkinson_vol = parkinson_hl / (2 * math.sqrt(math.log(2))) * math.sqrt(252) * 100 garman_klass_vol = math.sqrt((0.5 * math.pow(math.log(sp500_high / sp500_low), 2) - (2 * math.log(2) - 1) * math.pow(math.log(sp500 / sp500 ), 2)) * 252) * 100 market_volatility_20d = math.max(ta.stdev(returns, 20) * math.sqrt(252) * 100, parkinson_vol) market_volatility_60d = ta.stdev(returns, 60) * math.sqrt(252) * 100 market_drawdown = current_drawdown // Initialize risk allocation risk_allocation = 50.0 if enable_portfolio_risk_scaling // Volatility-based allocation vol_based_allocation = target_portfolio_volatility / math.max(market_volatility_20d, 5.0) * 100 vol_based_allocation := math.max(0, math.min(100, vol_based_allocation)) // Drawdown-based allocation dd_based_allocation = 100.0 if market_drawdown > 1.0 dd_based_allocation := max_portfolio_drawdown / market_drawdown * 100 dd_based_allocation := math.max(0, math.min(100, dd_based_allocation)) dd_based_allocation // Combine (conservative) risk_allocation := math.min(vol_based_allocation, dd_based_allocation) // Dynamic adjustment current_equity_estimate = 50.0 estimated_portfolio_vol = current_equity_estimate / 100 * market_volatility_20d estimated_portfolio_dd = current_equity_estimate / 100 * market_drawdown vol_utilization = estimated_portfolio_vol / target_portfolio_volatility dd_utilization = estimated_portfolio_dd / max_portfolio_drawdown risk_utilization = math.max(vol_utilization, dd_utilization) risk_adjustment_factor = 1.0 if risk_utilization > 1.0 risk_adjustment_factor := math.exp(-0.5 * (risk_utilization - 1.0)) risk_adjustment_factor := math.max(0.5, risk_adjustment_factor) risk_adjustment_factor else if risk_utilization < 0.9 risk_adjustment_factor := 1.0 + 0.2 * math.log(1.0 / risk_utilization) risk_adjustment_factor := math.min(1.3, risk_adjustment_factor) risk_adjustment_factor risk_allocation := risk_allocation * risk_adjustment_factor risk_allocation else vol_scalar = target_portfolio_volatility / math.max(market_volatility_20d, 10) vol_scalar := math.min(1.5, math.max(0.2, vol_scalar)) drawdown_penalty = 0.0 if current_drawdown > max_portfolio_drawdown drawdown_penalty := (current_drawdown - max_portfolio_drawdown) / max_portfolio_drawdown drawdown_penalty := math.min(1.0, drawdown_penalty) drawdown_penalty risk_allocation := 100 * vol_scalar * (1 - drawdown_penalty) risk_allocation risk_allocation := math.max(0, math.min(100, risk_allocation)) // VALUATION ANALYSIS // Valuation Metrics actual_pe_ratio = spy_earnings_per_share > 0 ? sp500 / spy_earnings_per_share : spy_pe_forward actual_earnings_yield = nz(spy_operating_earnings_yield, 0) > 0 ? spy_operating_earnings_yield : 100 / actual_pe_ratio total_shareholder_yield = spy_dividend_yield + spy_buyback_yield // Equity Risk Premium (multi-method calculation) method1_erp = actual_earnings_yield - us10y method2_erp = actual_earnings_yield + spy_buyback_yield - us10y payout_ratio = spy_dividend_yield > 0 and actual_earnings_yield > 0 ? spy_dividend_yield / actual_earnings_yield : 0.4 sustainable_growth = spy_return_on_equity * (1 - payout_ratio) / 100 method3_erp = spy_dividend_yield + sustainable_growth * 100 - us10y implied_growth = spy_revenue_growth * 0.7 method4_erp = total_shareholder_yield + implied_growth - us10y equity_risk_premium = method1_erp * 0.35 + method2_erp * 0.30 + method3_erp * 0.20 + method4_erp * 0.15 ev_ebitda_ratio = spy_enterprise_value > 0 and spy_ebitda > 0 ? spy_enterprise_value / spy_ebitda : 15.0 debt_equity_health = spy_debt_to_equity < 1.0 ? 1.2 : spy_debt_to_equity < 2.0 ? 1.0 : 0.8 // Valuation Score base_valuation_score = 50.0 if equity_risk_premium > 4 base_valuation_score := 95 base_valuation_score else if equity_risk_premium > 3 base_valuation_score := 85 base_valuation_score else if equity_risk_premium > 2 base_valuation_score := 70 base_valuation_score else if equity_risk_premium > 1 base_valuation_score := 55 base_valuation_score else if equity_risk_premium > 0 base_valuation_score := 40 base_valuation_score else if equity_risk_premium > -1 base_valuation_score := 25 base_valuation_score else base_valuation_score := 10 base_valuation_score growth_adjustment = spy_revenue_growth > 10 ? 10 : spy_revenue_growth > 5 ? 5 : 0 margin_adjustment = spy_net_margin > 15 ? 5 : spy_net_margin < 8 ? -5 : 0 roe_adjustment = spy_return_on_equity > 20 ? 5 : spy_return_on_equity < 10 ? -5 : 0 valuation_score = base_valuation_score + growth_adjustment + margin_adjustment + roe_adjustment valuation_score := math.max(0, math.min(100, valuation_score * debt_equity_health)) // SENTIMENT ANALYSIS // VIX Term Structure vix_term_structure = vix9d > 0 ? vix / vix9d : 1 backwardation = vix_term_structure > 1.05 steep_backwardation = vix_term_structure > 1.15 // Safe Haven Flows gold_momentum = ta.roc(gold, 20) dollar_momentum = ta.roc(usd, 20) yen_momentum = ta.roc(yen, 20) treasury_momentum = ta.roc(tlt, 20) safe_haven_flow = gold_momentum * 0.3 + treasury_momentum * 0.3 + dollar_momentum * 0.25 + yen_momentum * 0.15 // Advanced Sentiment Analysis vix_percentile = ta.percentrank(vix, 252) vix_zscore = (vix - ta.sma(vix, 252)) / ta.stdev(vix, 252) vix_momentum = ta.roc(vix, 5) vvix_proxy = ta.stdev(vix_momentum, 20) * math.sqrt(252) risk_reversal_proxy = (vix - realized_vol) / realized_vol // Sentiment Score base_sentiment = 50.0 vix_adjustment = 0.0 if vix_zscore < -1.5 vix_adjustment := 40 vix_adjustment else if vix_zscore < -0.5 vix_adjustment := 20 vix_adjustment else if vix_zscore < 0.5 vix_adjustment := 0 vix_adjustment else if vix_zscore < 1.5 vix_adjustment := -20 vix_adjustment else vix_adjustment := -40 vix_adjustment term_structure_adjustment = backwardation ? -15 : steep_backwardation ? -30 : 5 vvix_adjustment = vvix_proxy > 2.0 ? -10 : vvix_proxy < 1.0 ? 10 : 0 sentiment_score = base_sentiment + vix_adjustment + term_structure_adjustment + vvix_adjustment sentiment_score := math.max(0, math.min(100, sentiment_score)) // MACRO ANALYSIS // Yield Curve yield_spread_2_10 = us10y - us2y yield_spread_3m_10 = us10y - us3m // Credit Conditions hyg_return = ta.roc(hyg, 20) lqd_return = ta.roc(lqd, 20) tlt_return = ta.roc(tlt, 20) hyg_duration = 4.0 lqd_duration = 8.0 tlt_duration = 17.0 hyg_log_returns = math.log(hyg / hyg ) lqd_log_returns = math.log(lqd / lqd ) hyg_volatility = ta.stdev(hyg_log_returns, 20) * math.sqrt(252) lqd_volatility = ta.stdev(lqd_log_returns, 20) * math.sqrt(252) hyg_yield_proxy = -math.log(hyg / hyg ) * 100 lqd_yield_proxy = -math.log(lqd / lqd ) * 100 tlt_yield = us10y hyg_spread = (hyg_yield_proxy - tlt_yield) * 100 lqd_spread = (lqd_yield_proxy - tlt_yield) * 100 hyg_distance = (hyg - ta.lowest(hyg, 252)) / (ta.highest(hyg, 252) - ta.lowest(hyg, 252)) lqd_distance = (lqd - ta.lowest(lqd, 252)) / (ta.highest(lqd, 252) - ta.lowest(lqd, 252)) default_risk_proxy = 2.0 - (hyg_distance + lqd_distance) credit_spread = hyg_spread * 0.5 + (hyg_volatility - lqd_volatility) * 1000 * 0.3 + default_risk_proxy * 200 * 0.2 credit_spread := math.max(50, credit_spread) credit_market_health = hyg_return > lqd_return ? 1 : -1 flight_to_quality = tlt_return > (hyg_return + lqd_return) / 2 // Macro Score macro_score = 50.0 yield_curve_score = 0 if yield_spread_2_10 > 1.5 and yield_spread_3m_10 > 2 yield_curve_score := 40 yield_curve_score else if yield_spread_2_10 > 0.5 and yield_spread_3m_10 > 1 yield_curve_score := 30 yield_curve_score else if yield_spread_2_10 > 0 and yield_spread_3m_10 > 0 yield_curve_score := 20 yield_curve_score else if yield_spread_2_10 < 0 or yield_spread_3m_10 < 0 yield_curve_score := 10 yield_curve_score else yield_curve_score := 5 yield_curve_score credit_conditions_score = 0 if credit_spread < 200 and not flight_to_quality credit_conditions_score := 30 credit_conditions_score else if credit_spread < 400 and credit_market_health > 0 credit_conditions_score := 20 credit_conditions_score else if credit_spread < 600 credit_conditions_score := 15 credit_conditions_score else if credit_spread < 1000 credit_conditions_score := 10 credit_conditions_score else credit_conditions_score := 0 credit_conditions_score financial_stability_score = 0 if spy_debt_to_equity < 0.5 and spy_return_on_equity > 15 financial_stability_score := 20 financial_stability_score else if spy_debt_to_equity < 1.0 and spy_return_on_equity > 10 financial_stability_score := 15 financial_stability_score else if spy_debt_to_equity < 1.5 financial_stability_score := 10 financial_stability_score else financial_stability_score := 5 financial_stability_score macro_score := yield_curve_score + credit_conditions_score + financial_stability_score macro_score := math.max(0, math.min(100, macro_score)) // CRISIS DETECTION crisis_indicators = 0 if vix > crisis_vix_threshold crisis_indicators := crisis_indicators + 1 crisis_indicators if vix > 60 crisis_indicators := crisis_indicators + 2 crisis_indicators if current_drawdown > crisis_drawdown_threshold crisis_indicators := crisis_indicators + 1 crisis_indicators if current_drawdown > 25 crisis_indicators := crisis_indicators + 1 crisis_indicators if credit_spread > crisis_credit_spread crisis_indicators := crisis_indicators + 1 crisis_indicators sp500_roc_5 = ta.roc(sp500, 5) tlt_roc_5 = ta.roc(tlt, 5) if sp500_roc_5 < -10 and tlt_roc_5 < -5 crisis_indicators := crisis_indicators + 2 crisis_indicators volume_spike = sp500_volume > ta.sma(sp500_volume, 20) * 2 sp500_roc_1 = ta.roc(sp500, 1) if volume_spike and sp500_roc_1 < -3 crisis_indicators := crisis_indicators + 1 crisis_indicators is_crisis = crisis_indicators >= 3 is_severe_crisis = crisis_indicators >= 5 // FINAL ALLOCATION CALCULATION // Convert regime to base allocation regime_allocation = market_regime == 'Strong Bull' ? 100 : market_regime == 'Bull Market' ? 80 : market_regime == 'Neutral' ? 60 : market_regime == 'Correction' ? 40 : market_regime == 'Bear Market' ? 20 : 0 // Normalize weights total_weight = w_regime + w_risk + w_valuation + w_sentiment + w_macro w_regime_norm = w_regime / total_weight w_risk_norm = w_risk / total_weight w_valuation_norm = w_valuation / total_weight w_sentiment_norm = w_sentiment / total_weight w_macro_norm = w_macro / total_weight // Calculate Weighted Allocation weighted_allocation = regime_allocation * w_regime_norm + risk_allocation * w_risk_norm + valuation_score * w_valuation_norm + sentiment_score * w_sentiment_norm + macro_score * w_macro_norm // Apply Crisis Override if use_crisis_detection if is_severe_crisis weighted_allocation := math.min(weighted_allocation, 10) weighted_allocation else if is_crisis weighted_allocation := math.min(weighted_allocation, 25) weighted_allocation // Model Type Adjustment model_adjustment = 0.0 if model_type == 'Conservative' model_adjustment := -10 model_adjustment else if model_type == 'Aggressive' model_adjustment := 10 model_adjustment else if model_type == 'Adaptive' recent_return = (sp500 - sp500 ) / sp500 * 100 if recent_return > 5 model_adjustment := 5 model_adjustment else if recent_return < -5 model_adjustment := -5 model_adjustment // Apply adjustment and bounds final_allocation = weighted_allocation + model_adjustment final_allocation := math.max(0, math.min(100, final_allocation)) // Smooth allocation smoothed_allocation = ta.sma(final_allocation, smoothing_period) // Calculate portfolio risk metrics (only for internal alerts) actual_portfolio_volatility = smoothed_allocation / 100 * market_volatility_20d actual_portfolio_drawdown = smoothed_allocation / 100 * current_drawdown // VISUALIZATION // Color definitions var color primary_color = #2196F3 var color bullish_color = #4CAF50 var color bearish_color = #FF5252 var color neutral_color = #808080 var color text_color = color.white var color bg_color = #000000 var color table_bg_color = #1E1E1E var color header_bg_color = #2D2D2D switch color_scheme // Apply color scheme 'Gold' => primary_color := use_dark_mode ? #FFD700 : #DAA520 bullish_color := use_dark_mode ? #FFA500 : #FF8C00 bearish_color := use_dark_mode ? #FF5252 : #D32F2F neutral_color := use_dark_mode ? #C0C0C0 : #808080 text_color := use_dark_mode ? color.white : color.black bg_color := use_dark_mode ? #000000 : #FFFFFF table_bg_color := use_dark_mode ? #1A1A00 : #FFFEF0 header_bg_color := use_dark_mode ? #2D2600 : #F5F5DC header_bg_color 'EdgeTools' => primary_color := use_dark_mode ? #4682B4 : #1E90FF bullish_color := use_dark_mode ? #4CAF50 : #388E3C bearish_color := use_dark_mode ? #FF5252 : #D32F2F neutral_color := use_dark_mode ? #708090 : #696969 text_color := use_dark_mode ? color.white : color.black bg_color := use_dark_mode ? #000000 : #FFFFFF table_bg_color := use_dark_mode ? #0F1419 : #F0F8FF header_bg_color := use_dark_mode ? #1E2A3A : #E6F3FF header_bg_color 'Behavioral' => primary_color := #808080 bullish_color := #00FF00 bearish_color := #8B0000 neutral_color := #FFBF00 text_color := use_dark_mode ? color.white : color.black bg_color := use_dark_mode ? #000000 : #FFFFFF table_bg_color := use_dark_mode ? #1A1A1A : #F8F8F8 header_bg_color := use_dark_mode ? #2D2D2D : #E8E8E8 header_bg_color 'Quant' => primary_color := #808080 bullish_color := #FFA500 bearish_color := #8B0000 neutral_color := #4682B4 text_color := use_dark_mode ? color.white : color.black bg_color := use_dark_mode ? #000000 : #FFFFFF table_bg_color := use_dark_mode ? #0D0D0D : #FAFAFA header_bg_color := use_dark_mode ? #1A1A1A : #F0F0F0 header_bg_color 'Ocean' => primary_color := use_dark_mode ? #20B2AA : #008B8B bullish_color := use_dark_mode ? #00CED1 : #4682B4 bearish_color := use_dark_mode ? #FF4500 : #B22222 neutral_color := use_dark_mode ? #87CEEB : #2F4F4F text_color := use_dark_mode ? #F0F8FF : #191970 bg_color := use_dark_mode ? #001F3F : #F0F8FF table_bg_color := use_dark_mode ? #001A2E : #E6F7FF header_bg_color := use_dark_mode ? #002A47 : #CCF2FF header_bg_color 'Fire' => primary_color := use_dark_mode ? #FF6347 : #DC143C bullish_color := use_dark_mode ? #FFD700 : #FF8C00 bearish_color := use_dark_mode ? #8B0000 : #800000 neutral_color := use_dark_mode ? #FFA500 : #CD853F text_color := use_dark_mode ? #FFFAF0 : #2F1B14 bg_color := use_dark_mode ? #2F1B14 : #FFFAF0 table_bg_color := use_dark_mode ? #261611 : #FFF8F0 header_bg_color := use_dark_mode ? #3D241A : #FFE4CC header_bg_color 'Matrix' => primary_color := use_dark_mode ? #00FF41 : #006400 bullish_color := use_dark_mode ? #39FF14 : #228B22 bearish_color := use_dark_mode ? #FF073A : #8B0000 neutral_color := use_dark_mode ? #00FFFF : #008B8B text_color := use_dark_mode ? #C0FF8C : #003300 bg_color := use_dark_mode ? #0D1B0D : #F0FFF0 table_bg_color := use_dark_mode ? #0A1A0A : #E8FFF0 header_bg_color := use_dark_mode ? #112B11 : #CCFFCC header_bg_color 'Arctic' => primary_color := use_dark_mode ? #87CEFA : #4169E1 bullish_color := use_dark_mode ? #00BFFF : #0000CD bearish_color := use_dark_mode ? #FF1493 : #8B008B neutral_color := use_dark_mode ? #B0E0E6 : #483D8B text_color := use_dark_mode ? #F8F8FF : #191970 bg_color := use_dark_mode ? #191970 : #F8F8FF table_bg_color := use_dark_mode ? #141B47 : #F0F8FF header_bg_color := use_dark_mode ? #1E2A5C : #E0F0FF header_bg_color // Transparency settings bg_transparency = use_dark_mode ? 85 : 92 zone_transparency = use_dark_mode ? 90 : 95 band_transparency = use_dark_mode ? 70 : 85 table_transparency = use_dark_mode ? 80 : 15 // Allocation color alloc_color = smoothed_allocation >= 80 ? bullish_color : smoothed_allocation >= 60 ? color.new(bullish_color, 30) : smoothed_allocation >= 40 ? primary_color : smoothed_allocation >= 20 ? color.new(bearish_color, 30) : bearish_color // Dynamic background var color dynamic_bg_color = na if show_regime_background if smoothed_allocation >= 70 dynamic_bg_color := color.new(bullish_color, background_intensity) dynamic_bg_color else if smoothed_allocation <= 30 dynamic_bg_color := color.new(bearish_color, background_intensity) dynamic_bg_color else if smoothed_allocation > 60 or smoothed_allocation < 40 dynamic_bg_color := color.new(primary_color, math.min(99, background_intensity + 2)) dynamic_bg_color bgcolor(dynamic_bg_color, title = 'Allocation Signal Background') // Plot main allocation line plot(smoothed_allocation, 'Equity Allocation %', color = alloc_color, linewidth = math.max(1, main_line_width)) // Reference lines (static colors for hline) hline_bullish_color = color_scheme == 'Gold' ? use_dark_mode ? #FFA500 : #FF8C00 : color_scheme == 'EdgeTools' ? use_dark_mode ? #4CAF50 : #388E3C : color_scheme == 'Behavioral' ? #00FF00 : color_scheme == 'Quant' ? #FFA500 : color_scheme == 'Ocean' ? use_dark_mode ? #00CED1 : #4682B4 : color_scheme == 'Fire' ? use_dark_mode ? #FFD700 : #FF8C00 : color_scheme == 'Matrix' ? use_dark_mode ? #39FF14 : #228B22 : color_scheme == 'Arctic' ? use_dark_mode ? #00BFFF : #0000CD : #4CAF50 hline_bearish_color = color_scheme == 'Gold' ? use_dark_mode ? #FF5252 : #D32F2F : color_scheme == 'EdgeTools' ? use_dark_mode ? #FF5252 : #D32F2F : color_scheme == 'Behavioral' ? #8B0000 : color_scheme == 'Quant' ? #8B0000 : color_scheme == 'Ocean' ? use_dark_mode ? #FF4500 : #B22222 : color_scheme == 'Fire' ? use_dark_mode ? #8B0000 : #800000 : color_scheme == 'Matrix' ? use_dark_mode ? #FF073A : #8B0000 : color_scheme == 'Arctic' ? use_dark_mode ? #FF1493 : #8B008B : #FF5252 hline_primary_color = color_scheme == 'Gold' ? use_dark_mode ? #FFD700 : #DAA520 : color_scheme == 'EdgeTools' ? use_dark_mode ? #4682B4 : #1E90FF : color_scheme == 'Behavioral' ? #808080 : color_scheme == 'Quant' ? #808080 : color_scheme == 'Ocean' ? use_dark_mode ? #20B2AA : #008B8B : color_scheme == 'Fire' ? use_dark_mode ? #FF6347 : #DC143C : color_scheme == 'Matrix' ? use_dark_mode ? #00FF41 : #006400 : color_scheme == 'Arctic' ? use_dark_mode ? #87CEFA : #4169E1 : #2196F3 hline(show_reference_lines ? 100 : na, '100% Equity', color = color.new(hline_bullish_color, 70), linestyle = hline.style_dotted, linewidth = 1) hline(show_reference_lines ? 80 : na, '80% Equity', color = color.new(hline_bullish_color, 40), linestyle = hline.style_dashed, linewidth = 1) hline(show_reference_lines ? 60 : na, '60% Equity', color = color.new(hline_bullish_color, 60), linestyle = hline.style_dotted, linewidth = 1) hline(50, '50% Balanced', color = color.new(hline_primary_color, 50), linestyle = hline.style_solid, linewidth = 2) hline(show_reference_lines ? 40 : na, '40% Equity', color = color.new(hline_bearish_color, 60), linestyle = hline.style_dotted, linewidth = 1) hline(show_reference_lines ? 20 : na, '20% Equity', color = color.new(hline_bearish_color, 40), linestyle = hline.style_dashed, linewidth = 1) hline(show_reference_lines ? 0 : na, '0% Equity', color = color.new(hline_bearish_color, 70), linestyle = hline.style_dotted, linewidth = 1) // Component plots plot(show_components ? regime_allocation : na, 'Regime', color = color.new(#4ECDC4, 70), linewidth = 1) plot(show_components ? risk_allocation : na, 'Risk', color = color.new(#FF6B6B, 70), linewidth = 1) plot(show_components ? valuation_score : na, 'Valuation', color = color.new(#45B7D1, 70), linewidth = 1) plot(show_components ? sentiment_score : na, 'Sentiment', color = color.new(#FFD93D, 70), linewidth = 1) plot(show_components ? macro_score : na, 'Macro', color = color.new(#6BCF7F, 70), linewidth = 1) // Confidence bands upper_band = plot(show_confidence_bands ? math.min(100, smoothed_allocation + ta.stdev(smoothed_allocation, 20)) : na, color = color.new(neutral_color, band_transparency), display = display.none, title = 'Upper Band') lower_band = plot(show_confidence_bands ? math.max(0, smoothed_allocation - ta.stdev(smoothed_allocation, 20)) : na, color = color.new(neutral_color, band_transparency), display = display.none, title = 'Lower Band') fill(upper_band, lower_band, color = show_confidence_bands ? color.new(neutral_color, zone_transparency) : na, title = 'Uncertainty') // DASHBOARD if show_dashboard and barstate.islast var table dashboard = table.new(position.top_right, 2, 20, border_width = 1, bgcolor = color.new(table_bg_color, table_transparency)) table.clear(dashboard, 0, 0, 1, 19) // Header header_color = color.new(header_bg_color, 20) dashboard_text_color = text_color table.cell(dashboard, 0, 0, 'DEAM', text_color = dashboard_text_color, bgcolor = header_color, text_size = size.normal) table.cell(dashboard, 1, 0, model_type, text_color = dashboard_text_color, bgcolor = header_color, text_size = size.normal) // Core metrics table.cell(dashboard, 0, 1, 'Equity Allocation', text_color = dashboard_text_color, text_size = size.small) table.cell(dashboard, 1, 1, str.tostring(smoothed_allocation, '##.#') + '%', text_color = alloc_color, text_size = size.small) table.cell(dashboard, 0, 2, 'Cash Allocation', text_color = dashboard_text_color, text_size = size.small) cash_color = 100 - smoothed_allocation > 70 ? bearish_color : primary_color table.cell(dashboard, 1, 2, str.tostring(100 - smoothed_allocation, '##.#') + '%', text_color = cash_color, text_size = size.small) // Signal signal_text = 'NEUTRAL' signal_color = primary_color if smoothed_allocation >= 70 signal_text := 'BULLISH' signal_color := bullish_color signal_color else if smoothed_allocation <= 30 signal_text := 'BEARISH' signal_color := bearish_color signal_color table.cell(dashboard, 0, 3, 'Signal', text_color = dashboard_text_color, text_size = size.small) table.cell(dashboard, 1, 3, signal_text, text_color = signal_color, text_size = size.small) // Market Regime table.cell(dashboard, 0, 4, 'Regime', text_color = dashboard_text_color, text_size = size.small) regime_color_display = market_regime == 'Strong Bull' or market_regime == 'Bull Market' ? bullish_color : market_regime == 'Neutral' ? primary_color : market_regime == 'Crisis' ? bearish_color : bearish_color table.cell(dashboard, 1, 4, market_regime, text_color = regime_color_display, text_size = size.small) // VIX table.cell(dashboard, 0, 5, 'VIX Level', text_color = dashboard_text_color, text_size = size.small) vix_color_display = vix < 20 ? bullish_color : vix < 30 ? primary_color : bearish_color table.cell(dashboard, 1, 5, str.tostring(vix, '##.##'), text_color = vix_color_display, text_size = size.small) // Market Drawdown table.cell(dashboard, 0, 6, 'Market DD', text_color = dashboard_text_color, text_size = size.small) market_dd_color = current_drawdown < 5 ? bullish_color : current_drawdown < 10 ? primary_color : bearish_color table.cell(dashboard, 1, 6, '-' + str.tostring(current_drawdown, '##.#') + '%', text_color = market_dd_color, text_size = size.small) // Crisis Detection table.cell(dashboard, 0, 7, 'Crisis Detection', text_color = dashboard_text_color, text_size = size.small) crisis_text = is_severe_crisis ? 'SEVERE' : is_crisis ? 'CRISIS' : 'Normal' crisis_display_color = is_severe_crisis or is_crisis ? bearish_color : bullish_color table.cell(dashboard, 1, 7, crisis_text, text_color = crisis_display_color, text_size = size.small) // Real Data Section financial_bg = color.new(primary_color, 85) table.cell(dashboard, 0, 8, 'REAL DATA', text_color = dashboard_text_color, bgcolor = financial_bg, text_size = size.small) table.cell(dashboard, 1, 8, 'Live Metrics', text_color = dashboard_text_color, bgcolor = financial_bg, text_size = size.small) // P/E Ratio table.cell(dashboard, 0, 9, 'P/E Ratio', text_color = dashboard_text_color, text_size = size.small) pe_color = actual_pe_ratio < 18 ? bullish_color : actual_pe_ratio < 25 ? primary_color : bearish_color table.cell(dashboard, 1, 9, str.tostring(actual_pe_ratio, '##.#'), text_color = pe_color, text_size = size.small) // ERP table.cell(dashboard, 0, 10, 'ERP', text_color = dashboard_text_color, text_size = size.small) erp_color = equity_risk_premium > 2 ? bullish_color : equity_risk_premium > 0 ? primary_color : bearish_color table.cell(dashboard, 1, 10, str.tostring(equity_risk_premium, '##.##') + '%', text_color = erp_color, text_size = size.small) // ROE table.cell(dashboard, 0, 11, 'ROE', text_color = dashboard_text_color, text_size = size.small) roe_color = spy_return_on_equity > 20 ? bullish_color : spy_return_on_equity > 10 ? primary_color : bearish_color table.cell(dashboard, 1, 11, str.tostring(spy_return_on_equity, '##.#') + '%', text_color = roe_color, text_size = size.small) // D/E Ratio table.cell(dashboard, 0, 12, 'D/E Ratio', text_color = dashboard_text_color, text_size = size.small) de_color = spy_debt_to_equity < 0.5 ? bullish_color : spy_debt_to_equity < 1.0 ? primary_color : bearish_color table.cell(dashboard, 1, 12, str.tostring(spy_debt_to_equity, '##.##'), text_color = de_color, text_size = size.small) // Shareholder Yield table.cell(dashboard, 0, 13, 'Dividend+Buyback', text_color = dashboard_text_color, text_size = size.small) yield_color = total_shareholder_yield > 4 ? bullish_color : total_shareholder_yield > 2 ? primary_color : bearish_color table.cell(dashboard, 1, 13, str.tostring(total_shareholder_yield, '##.#') + '%', text_color = yield_color, text_size = size.small) // Component Scores component_bg = color.new(neutral_color, 80) table.cell(dashboard, 0, 14, 'Components', text_color = dashboard_text_color, bgcolor = component_bg, text_size = size.small) table.cell(dashboard, 1, 14, 'Scores', text_color = dashboard_text_color, bgcolor = component_bg, text_size = size.small) table.cell(dashboard, 0, 15, 'Regime', text_color = dashboard_text_color, text_size = size.small) regime_score_color = regime_allocation > 60 ? bullish_color : regime_allocation < 40 ? bearish_color : primary_color table.cell(dashboard, 1, 15, str.tostring(regime_allocation, '##'), text_color = regime_score_color, text_size = size.small) table.cell(dashboard, 0, 16, 'Risk', text_color = dashboard_text_color, text_size = size.small) risk_score_color = risk_allocation > 60 ? bullish_color : risk_allocation < 40 ? bearish_color : primary_color table.cell(dashboard, 1, 16, str.tostring(risk_allocation, '##'), text_color = risk_score_color, text_size = size.small) table.cell(dashboard, 0, 17, 'Valuation', text_color = dashboard_text_color, text_size = size.small) val_score_color = valuation_score > 60 ? bullish_color : valuation_score < 40 ? bearish_color : primary_color table.cell(dashboard, 1, 17, str.tostring(valuation_score, '##'), text_color = val_score_color, text_size = size.small) table.cell(dashboard, 0, 18, 'Sentiment', text_color = dashboard_text_color, text_size = size.small) sent_score_color = sentiment_score > 60 ? bullish_color : sentiment_score < 40 ? bearish_color : primary_color table.cell(dashboard, 1, 18, str.tostring(sentiment_score, '##'), text_color = sent_score_color, text_size = size.small) table.cell(dashboard, 0, 19, 'Macro', text_color = dashboard_text_color, text_size = size.small) macro_score_color = macro_score > 60 ? bullish_color : macro_score < 40 ? bearish_color : primary_color table.cell(dashboard, 1, 19, str.tostring(macro_score, '##'), text_color = macro_score_color, text_size = size.small) // ALERTS // Major allocation changes alertcondition(smoothed_allocation >= 80 and smoothed_allocation < 80, 'High Equity Allocation', 'Equity allocation reached 80% - Bull market conditions') alertcondition(smoothed_allocation <= 20 and smoothed_allocation > 20, 'Low Equity Allocation', 'Equity allocation dropped to 20% - Defensive positioning') // Crisis alerts alertcondition(is_crisis and not is_crisis , 'CRISIS DETECTED', 'Crisis conditions detected - Reducing equity allocation') alertcondition(is_severe_crisis and not is_severe_crisis , 'SEVERE CRISIS', 'Severe crisis detected - Maximum defensive positioning') // Regime changes regime_changed = market_regime != market_regime alertcondition(regime_changed, 'Regime Change', 'Market regime has changed') // Risk management alerts risk_breach = enable_portfolio_risk_scaling and (actual_portfolio_volatility > target_portfolio_volatility * 1.2 or actual_portfolio_drawdown > max_portfolio_drawdown * 1.2) alertcondition(risk_breach, 'Risk Breach', 'Portfolio risk exceeds target parameters') // USAGE // The indicator displays a recommended equity allocation percentage (0-100%). // Example: 75% allocation = 75% stocks, 25% cash/bonds. // // The model combines market regime analysis (trend, volatility, drawdowns), // risk management (portfolio-level targeting), valuation metrics (P/E, ERP), // sentiment indicators (VIX term structure), and macro factors (yield curve, // credit spreads) into a single allocation signal. // // Crisis detection automatically reduces exposure when multiple warning signals // converge. Alerts available for major allocation shifts and regime changes. // // Designed for SPY/S&P 500 portfolio allocation. Adjust component weights and // risk parameters in settings to match your risk tolerance. View in Pine
Pine Script® indicator
by Alfred773
Moving VWAP-KAMA CloudMoving VWAP-KAMA Cloud Overview The Moving VWAP-KAMA Cloud is a high-conviction trend filter designed to solve a major problem with standard indicators: Noise. By combining a smoothed Volume Weighted Average Price (MVWAP) with Kaufman’s Adaptive Moving Average (KAMA), this indicator creates a "Value Zone" that identifies the true structural trend while ignoring choppy price action. Unlike brittle lines that break constantly, this cloud is "slow" by design—making it exceptionally powerful for spotting genuine trend reversals and filtering out fakeouts. How It Works This script uses a unique "Double Smoothing" architecture: The Anchor (MVWAP): We take the standard VWAP and smooth it with a 30-period EMA. This represents the "Fair Value" baseline where volume has supported price over time. The Filter (KAMA): We apply Kaufman's Adaptive Moving Average to the already smoothed MVWAP. KAMA is unique because it flattens out during low-volatility (choppy) periods and speeds up during high-momentum trends. The Cloud: Green/Teal Cloud: Bullish Structure (MVWAP > KAMA) Purple Cloud: Bearish Structure (MVWAP < KAMA) 🔥 The "Reversal Slingshot" Strategy Backtests reveal a powerful behavior during major trend changes, particularly after long bear markets: The Resistance Phase: During a long-term downtrend, price will repeatedly rally into the Purple Cloud and get rejected. The flattened KAMA line acts as a "concrete ceiling," keeping the bearish trend intact. The Breakout & Flip: When price finally breaks above the cloud with conviction, and the cloud flips Green, it signals a structural regime change. The "Slingshot" Retest: Often, immediately after this flip, price will drop back into the top of the cloud. This is the "Slingshot" moment. The old resistance becomes new, hardened support. The Rally: From this support bounce, stocks often launch into a sustained, multi-month bull run. This setup has been observed repeatedly at the bottom of major corrections. How to Use This Indicator 1. Dynamic Support & Resistance The KAMA Wall: When price retraces into the cloud, the KAMA line often flattens out, acting as a hard "floor" or "wall." A break of this wall usually signals a genuine trend change, not just a stop hunt. 2. Trend Confirmation (Regime Filter) Bullish Regime: If price is holding above the cloud, only look for Long setups. Bearish Regime: If price is holding below the cloud, only look for Short setups. No-Trade Zone: If price is stuck inside the cloud, the market is traversing fair value. Stand aside until a clear winner emerges. 3. Multi-Timeframe Versatility While designed for trend confirmation on higher timeframes (4H, Daily), this indicator adapts beautifully to lower timeframes (5m, 15m) for intraday scalping. On Lower Timeframes: The cloud reacts much faster, acting as a dynamic "VWAP Band" that helps intraday traders stay on the right side of momentum during the session. Settings Moving VWAP Period (30): The lookback period for the base VWAP smoothing. KAMA Settings (10, 10, 30): Controls the sensitivity of the adaptive filter. Cloud Transparency: Adjust to keep your chart clean. Alerts Included Price Cross Over/Under MVWAP Price Cross Over/Under KAMA Cloud Flip (Bullish/Bearish Trend Change) Tip for Traders This is not a signal entry indicator. It is a Trend Conviction tool. Use it to filter your entries from faster indicators (like RSI or MACD). If your fast indicator signals "Buy" but the cloud is Purple, the probability is low. Wait for the Cloud Flip
Pine Script® indicator
by SovereignCharts
HVPro Style IndicatorHVPro Style Indicator – Historical Volatility + Volume HVPro Style Indicator is a combined volatility-and-volume tool designed to help traders visualize market expansion and contraction phases. It calculates Historical Volatility (HV) using log-returns and a customizable lookback period, then smooths the result for a cleaner trend signal. The script also includes a volume histogram, scaled by a multiplier, with bar colors changing based on whether volatility is rising or falling. This makes it easy to spot moments when both volume and volatility align, often signaling trend transitions, breakouts, or exhaustion. Features ✔ Historical Volatility calculation (annualized) ✔ Smoothed HV for cleaner visual trends ✔ Volume histogram with customizable multiplier ✔ Volume bar color shifts based on HV direction ✔ User-controlled visibility for both HV and volume ✔ Lightweight and optimized for all timeframes How to Use Rising HV (green volume bars) can indicate trend expansion or breakout momentum. Falling HV (red bars) suggests contraction, ranging conditions, or volatility cooldown. Watch for volatility shifts combined with volume spikes for potential trade entries.
Pine Script® indicator
by akbarintec
HMA+RVOL Strategy Hariss 369The Hull Moving Average (HMA) is a smooth, fast, and highly responsive moving average created by Alan Hull. It reduces lag significantly while still maintaining smoothness, making it one of the most popular tools for trend detection and entries. It is widely used for trend filter. Hull Moving Average(HMA) with RVOL strengthens the trend as volume is prime factor of price movement. Trading with HMA: Simple method is buy when price closes above HMA , stop less below the low of last candle and target is 1.5 or 2 times of stop loss. The reverse is for sell. The HMA automatically turns to green on bull trend and red on bear trend for better visual confirmation. Adding RVOL to HMA is better method of trading. Buy signal is initiated when price closes above HMA and RVOL is greater than 1.2. Sell signal is initiated when price closes below 89 HMA and rovl is greater than 1.2. One can change the value of RVOL according to trading style and type asset being traded. It is a back tested strategy.
Pine Script® strategy
by Hariss369
ULTIMATE ORDER FLOW SYSTEM🔥 ULTIMATE ORDER FLOW SYSTEM Overview This comprehensive order flow analysis tool combines **Volume Profile**, **Cumulative Delta**, and **Large Order Detection** to identify high-probability trading setups. The script analyzes institutional order flow patterns and volume distribution to pinpoint key levels where price is likely to react. 📊 Core Components & Methodology 🔥 ULTIMATE ORDER FLOW SYSTEM Overview This comprehensive order flow analysis tool combines Volume Profile, Cumulative Delta, and Large Order Detection to identify high-probability trading setups. The script analyzes institutional order flow patterns and volume distribution to pinpoint key levels where price is likely to react. ________________________________________ 📊 Core Components & Methodology 1. Volume Profile Analysis The script constructs a horizontal volume profile by: • Dividing the price range into configurable rows (default: 20) • Accumulating volume at each price level over a lookback period (default: 50 bars) • Separating buy volume (green bars close > open) from sell volume (red bars) • Identifying three critical levels: o POC (Point of Control): Price level with highest traded volume - acts as a strong magnet o VAH/VAL (Value Area High/Low): Contains 70% of total volume - defines fair value zone o HVN (High Volume Nodes): Resistance zones where institutions accumulated positions o LVN (Low Volume Nodes): Thin zones that price moves through quickly - ideal targets Why This Matters: Institutional traders leave footprints through volume. HVN zones show where large players defended levels, making them reliable support/resistance. ________________________________________ 2. Cumulative Delta (Order Flow) Tracks the running total of buying vs selling pressure: • Bar Delta: Difference between buy and sell volume per candle • Cumulative Delta: Sum of all bar deltas - shows net directional pressure • Delta Moving Average: Smoothed delta (20-period) to identify trend • Delta Divergences: o Bullish: Price makes lower low, but delta makes higher low (absorption at bottom) o Bearish: Price makes higher high, but delta makes lower high (exhaustion at top) How It Works: When cumulative delta trends up while price consolidates, it signals accumulation. Delta divergences reveal when smart money is positioned opposite to retail expectations. ________________________________________ 3. Large Order Detection Identifies institutional-sized orders in real-time: • Compares current bar volume to 20-period moving average • Flags orders exceeding 2.5x average volume (configurable multiplier) • Distinguishes bullish (green circles below) vs bearish (red circles above) large orders Rationale: Sudden volume spikes at key levels indicate institutional participation - the "fuel" needed for breakouts or reversals. ________________________________________ 🎯 Trading Signal Logic Combined Setup Criteria The script generates SHORT and LONG signals when multiple conditions align: SHORT Signal Requirements: 1. Price reaches an HVN resistance zone (within 0.2%) 2. Large sell order detected (volume spike + red candle) 3. Cumulative delta is bearish OR bearish divergence present 4. 10-bar cooldown between signals (prevents overtrading) LONG Signal Requirements: 1. Price reaches an HVN support zone 2. Large buy order detected (volume spike + green candle) 3. Cumulative delta is bullish OR bullish divergence present 4. 10-bar cooldown enforced ________________________________________ 🔧 Customization Options Setting - Purpose - Recommendation Volume Profile Rows - Granularity of level detection - 20 (balanced) Lookback Period - Historical data analyzed - 50 bars (intraday), 200 (swing) Large Order Multiplier - Sensitivity to volume spikes - 2.5x (standard), 3.5x (conservative) HVN Threshold - Resistance zone detection - 1.3 (default) LVN Threshold - Target zone identification - 0.6 (default) Divergence Lookback - Pivot detection period - 5 bars (responsive) ________________________________________ 📈 Dashboard Indicators The real-time panel displays: • POC: Current Point of Control price • Location: Whether price is at HVN resistance • Orders: Current large buy/sell activity • Cumulative Δ: Net order flow value + trend direction • Divergence: Active bullish/bearish divergences • Bar Strength: % of candle volume that's directional (>65% = strong) • SETUP: Current trade signal (LONG/SHORT/WAIT) ________________________________________ 🎨 Visual System • Yellow POC Line: Highest volume level - primary pivot • Blue Value Area Box: Fair value zone (VAH to VAL) • Red HVN Zones: Resistance/support from institutional accumulation • Green LVN Zones: Low-liquidity targets for quick moves • Volume Bars: Green (buy pressure) vs Red (sell pressure) distribution • Triangles: LONG (green up) and SHORT (red down) entry signals • Diamonds: Divergence warnings (cyan=bullish, fuchsia=bearish) ________________________________________ 💡 How This Script Is Unique Unlike standalone volume profile or delta indicators, this script: 1. Synthesizes three complementary methods - volume structure, order flow momentum, and liquidity detection 2. Requires multi-factor confirmation - signals only trigger when price, volume, and delta align at key zones 3. Adapts to market regime - delta filters ensure you're trading with the dominant order flow direction 4. Provides context, not just signals - the dashboard helps you understand why a setup is forming ________________________________________ ⚙️ Best Practices Timeframes: • 5-15 min: Scalping (use 30-50 bar lookback) • 1-4 hour: Swing trading (use 100-200 bar lookback) Risk Management: • Enter on signal candle close • Stop loss: Beyond nearest HVN/LVN zone • Target 1: Next LVN level • Target 2: Opposite value area boundary Filters: • Avoid signals during major news events • Require bar delta strength >65% for aggressive entries • Wait for delta MA cross confirmation in ranging markets ________________________________________ 🚨 Alerts Available • Long Setup Trigger • Short Setup Trigger • Bullish/Bearish Divergence Detection • Large Buy/Sell Order Execution ________________________________________ 📚 Educational Context This methodology is based on principles used by professional order flow traders: • Market Profile Theory: Volume distribution reveals fair value • Tape Reading: Large orders show institutional intent • Auction Theory: Price seeks areas of liquidity imbalance (LVN zones) The script automates pattern recognition that discretionary traders spend years learning to identify manually. ________________________________________ ⚠️ Disclaimer This indicator is a trading tool, not a trading system. It identifies high-probability setups based on order flow analysis but requires proper risk management, market context, and trader discretion. Past performance does not guarantee future results. ________________________________________ Version: 6 (Pine Script) Type: Overlay + Separate Pane (Delta Panel) Resource Usage: Moderate (500 bars history, 500 lines/boxes) ________________________________________ For questions or support, please comment below. If you find this script valuable, please boost and favorite! 🚀 1. Volume Profile Analysis The script constructs a horizontal volume profile by: - Dividing the price range into configurable rows (default: 20) - Accumulating volume at each price level over a lookback period (default: 50 bars) - Separating buy volume (green bars close > open) from sell volume (red bars) - Identifying three critical levels: - POC (Point of Control): Price level with highest traded volume - acts as a strong magnet - VAH/VAL (Value Area High/Low): Contains 70% of total volume - defines fair value zone - HVN (High Volume Nodes): Resistance zones where institutions accumulated positions - LVN (Low Volume Nodes): Thin zones that price moves through quickly - ideal targets Why This Matters: Institutional traders leave footprints through volume. HVN zones show where large players defended levels, making them reliable support/resistance. --- 2. Cumulative Delta (Order Flow) Tracks the running total of buying vs selling pressure: - **Bar Delta**: Difference between buy and sell volume per candle - **Cumulative Delta**: Sum of all bar deltas - shows net directional pressure - **Delta Moving Average**: Smoothed delta (20-period) to identify trend - **Delta Divergences**: - **Bullish**: Price makes lower low, but delta makes higher low (absorption at bottom) - **Bearish**: Price makes higher high, but delta makes lower high (exhaustion at top) **How It Works**: When cumulative delta trends up while price consolidates, it signals accumulation. Delta divergences reveal when smart money is positioned opposite to retail expectations. --- ### 3. **Large Order Detection** Identifies **institutional-sized orders** in real-time: - Compares current bar volume to 20-period moving average - Flags orders exceeding 2.5x average volume (configurable multiplier) - Distinguishes bullish (green circles below) vs bearish (red circles above) large orders **Rationale**: Sudden volume spikes at key levels indicate institutional participation - the "fuel" needed for breakouts or reversals. --- ## 🎯 Trading Signal Logic ### Combined Setup Criteria The script generates **SHORT** and **LONG** signals when multiple conditions align: **SHORT Signal Requirements:** 1. Price reaches an HVN resistance zone (within 0.2%) 2. Large sell order detected (volume spike + red candle) 3. Cumulative delta is bearish OR bearish divergence present 4. 10-bar cooldown between signals (prevents overtrading) **LONG Signal Requirements:** 1. Price reaches an HVN support zone 2. Large buy order detected (volume spike + green candle) 3. Cumulative delta is bullish OR bullish divergence present 4. 10-bar cooldown enforced --- ## 🔧 Customization Options | Setting | Purpose | Recommendation | |---------|---------|----------------| | **Volume Profile Rows** | Granularity of level detection | 20 (balanced) | | **Lookback Period** | Historical data analyzed | 50 bars (intraday), 200 (swing) | | **Large Order Multiplier** | Sensitivity to volume spikes | 2.5x (standard), 3.5x (conservative) | | **HVN Threshold** | Resistance zone detection | 1.3 (default) | | **LVN Threshold** | Target zone identification | 0.6 (default) | | **Divergence Lookback** | Pivot detection period | 5 bars (responsive) | --- ## 📈 Dashboard Indicators The real-time panel displays: - **POC**: Current Point of Control price - **Location**: Whether price is at HVN resistance - **Orders**: Current large buy/sell activity - **Cumulative Δ**: Net order flow value + trend direction - **Divergence**: Active bullish/bearish divergences - **Bar Strength**: % of candle volume that's directional (>65% = strong) - **SETUP**: Current trade signal (LONG/SHORT/WAIT) --- ## 🎨 Visual System - **Yellow POC Line**: Highest volume level - primary pivot - **Blue Value Area Box**: Fair value zone (VAH to VAL) - **Red HVN Zones**: Resistance/support from institutional accumulation - **Green LVN Zones**: Low-liquidity targets for quick moves - **Volume Bars**: Green (buy pressure) vs Red (sell pressure) distribution - **Triangles**: LONG (green up) and SHORT (red down) entry signals - **Diamonds**: Divergence warnings (cyan=bullish, fuchsia=bearish) --- ## 💡 How This Script Is Unique Unlike standalone volume profile or delta indicators, this script: 1. **Synthesizes three complementary methods** - volume structure, order flow momentum, and liquidity detection 2. **Requires multi-factor confirmation** - signals only trigger when price, volume, and delta align at key zones 3. **Adapts to market regime** - delta filters ensure you're trading with the dominant order flow direction 4. **Provides context, not just signals** - the dashboard helps you understand *why* a setup is forming --- ## ⚙️ Best Practices **Timeframes:** - 5-15 min: Scalping (use 30-50 bar lookback) - 1-4 hour: Swing trading (use 100-200 bar lookback) **Risk Management:** - Enter on signal candle close - Stop loss: Beyond nearest HVN/LVN zone - Target 1: Next LVN level - Target 2: Opposite value area boundary **Filters:** - Avoid signals during major news events - Require bar delta strength >65% for aggressive entries - Wait for delta MA cross confirmation in ranging markets --- ## 🚨 Alerts Available - Long Setup Trigger - Short Setup Trigger - Bullish/Bearish Divergence Detection - Large Buy/Sell Order Execution --- ## 📚 Educational Context This methodology is based on principles used by professional order flow traders: - **Market Profile Theory**: Volume distribution reveals fair value - **Tape Reading**: Large orders show institutional intent - **Auction Theory**: Price seeks areas of liquidity imbalance (LVN zones) The script automates pattern recognition that discretionary traders spend years learning to identify manually. --- ## ⚠️ Disclaimer This indicator is a **trading tool, not a trading system**. It identifies high-probability setups based on order flow analysis but requires proper risk management, market context, and trader discretion. Past performance does not guarantee future results. --- **Version**: 6 (Pine Script) **Type**: Overlay + Separate Pane (Delta Panel) **Resource Usage**: Moderate (500 bars history, 500 lines/boxes) --- *For questions or support, please comment below. If you find this script valuable, please boost and favorite!* 🚀
Pine Script® indicator
by harshivsymposium
Dynamic 15-Ticker Dashboard • Real-Time ▲▼ Arrows • 2025Dynamic 15-Ticker Dashboard • Real-Time ▲▼ Arrows • 2025 Edition Free • Fully Open Source • Stable and Mobile-Friendly The cleanest, most reliable multi-ticker dashboard you will ever add — zero collapsing, zero lag, works on mobile too. Features • SPY always pinned at the top • Add up to 14 of your own tickers (just type → instantly appears) • Live price + direction arrows (▲ ▼) with automatic green/red coloring • RSI(14) with momentum arrows • Volume auto-formatted (K / M / B) with change arrows • 15 rows 100% stable — no disappearing table bug • Alternating dark rows for easy reading • Real-time updates on any timeframe Perfect for day traders, swing traders, or anyone who wants a consolidated watchlist without switching charts constantly. How to use Add to chart Type your tickers in the settings (leave blank to hide) Done — enjoy the clean, organized watchlist Zero requests, zero repainting, zero drama. Made for traders, by traders ♥ Open source — feel free to modify, share, or improve. If you like it, leave a comment and hit the ♥ button. Enjoy the view!
Pine Script® indicator
by GammaBulldog
VWAP, Vol & RTH Stats (Custom Layout)VWAP, Volume & RTH Stats Box This indicator displays a data table in the top-right corner of the chart designed for intraday liquidity analysis. It fetches the true "Daily" volume to ensure accuracy regardless of the timeframe used. It specifically isolates Regular Trading Hours (RTH) to calculate the daily range performance (Max Squeeze % and Max Drop %), filtering out pre-market noise to show the true strength of the move. Includes full customization for dimensions, margins, and colors.
Pine Script® indicator
by Giac94
Accumulation And Distribution Zones (Zeiierman)█ Overview Accumulation And Distribution Zones (Zeiierman) is a structural zone indicator that highlights where the market has recently been absorbing sell pressure (Accumulation) or releasing buy pressure (Distribution). The indicator tracks a refined sequence of swing highs and lows and measures how these swings tighten, expand, or step directionally. When they form staircase-style structures such as higher lows with compressing highs for Accumulation or lower highs with compressing lows for Distribution, the script marks these areas as shifts in market control. Once the full pattern completes, the indicator converts it into an Accumulation or Distribution zone. Each zone is based on a confirmed structural sequence rather than a single point, making it more reliable and reflective of actual market behavior. The indicator can also display a mini-volume profile within each zone and extend POC levels forward, showing where trading activity clustered most. Combined, these features reveal areas where price has recently shown acceptance, absorption, or rejection, helping you understand whether current price action is reacting to, breaking from, or retesting these important structural regions. █ How It Works ⚪ Swing Structure The indicator builds its foundation by detecting swing highs and lows using a configurable Swing Detection Window. Each confirmed swing is stored with its price, time, bar index, and direction. If two consecutive swings share the same direction, only the more extreme one is kept. This produces a clean structural sequence that removes noise and keeps only meaningful turning points. ⚪ Accumulation vs Distribution Pattern Logic Using the refined swing sequence, the script looks for staircase-style formations that signal shifts in control: Accumulation (bottoming): higher lows combined with compressing highs. Distribution (topping): lower highs combined with compressing lows. Two detection modes are available: Quick for compact 4-swing formations Slow for broader 6-swing structures When a full structural pattern completes, the indicator marks the zone and resets the swing buffer for the next formation. ⚪ Volume Profile Construction The price range between the zone’s upper and lower boundary is divided into several Rows. For every bar within the zone’s swing range, the bar’s volume is added to the appropriate price row. Volume is classified as: Bullish volume when close > open Bearish volume when close < open Each row is drawn as two horizontal segments (bull and bear), colored with smooth gradients based on your bull/bear color settings. This creates a compact profile that reveals where trading activity is concentrated inside the zone and whether buyers or sellers dominate those price levels. █ How to Use The indicator is designed to provide context and confluence, not raw buy/sell signals. ⚪ Spot Fresh Accumulation & Distribution Use newly printed zones as a map of where the market has recently: Absorbed selling and formed a floor (Accumulation below price). Absorbed buying and formed a cap (Distribution above price). In a trending environment, fresh accumulation zones below price are often areas to watch for pullbacks, while distribution zones above price can act as sell zones or targets. ⚪ Volume Profile Longer horizontal bars show where the market traded the most volume inside the zone. Bull-leaning rows inside an accumulation zone often signal strong buying interest during the formation. Bear-leaning rows inside a distribution zone highlight concentrated selling pressure. By combining this volume distribution with the zone label and the broader trend context, you can judge whether the structure is more likely to hold, break, or retest as the price approaches it again. ⚪ POC (Point of Control) Trading Extended POC zones (Regular or Faded) can be treated as dynamic support/resistance rails: When price revisits a prior accumulation POC and rejects it from above, the level may act as support. When price retests a distribution POC from below and fails to break through, it can act as resistance. ⚪ Combine with Your Own Strategy The script does not decide direction for you. You get the most value by combining it with: Your own trend filters (moving averages, higher timeframe structure, volatility measures). Your preferred entry models (reversal candles, momentum breaks, liquidity grabs, etc.). Higher-timeframe mapping. Think of this tool as a map of where the market did meaningful business. You decide how to trade around those areas. █ Settings Acc/Dist Ranges – Master switch for drawing all Accumulation and Distribution zones. Turn this off to temporarily hide boxes while leaving supporting logic active. Pattern – Shows or hides the swing-based pattern outline that formed each zone. Good for structural debugging and education. Pattern Sensitivity Quick – more responsive, detects smaller compact structures. Slow – stricter, focuses on wider and more established zones. Swing Detection Window – Pivot width used to confirm swing highs and lows. Larger values filter noise and produce bigger zones; smaller values pick up more minor structures. Volume Profile – Enables the embedded volume profile inside each zone. Rows – Number of price slices used to aggregate volume in the zone. Higher values give more detail but increase visual density. Switch Order – Flips the horizontal order of bull vs bear volume segments within each row. Extend Zones – Behaviour of POC and zone extension: None – No forward extension. Faded Zones – Store and draw up to four past POC zones as faded horizontal levels. Regular Zones – Extend POC boxes forward until price breaks out. ----------------- Disclaimer The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information. All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Pine Script® indicator
by Zeiierman
4
Momentum + Volume Percentile This advanced momentum indicator combines smoothed momentum analysis with percentile-based volume filtering to identify high-quality trading opportunities backed by significant market participation. How It Works: The indicator calculates momentum (rate of change) over a customizable period and applies multiple smoothing techniques to reduce noise. It then filters price action by highlighting only periods where volume exceeds a specified percentile threshold. The algorithm: Calculates raw momentum based on price changes over the specified period Applies customizable smoothing (SMA, EMA, WMA, or HMA) to the momentum values Computes a moving average of the smoothed momentum as a trend reference Analyzes volume over a lookback period to establish percentile rankings Highlights candles where volume exceeds the percentile threshold with color-coded backgrounds Distinguishes between bullish (green) and bearish (red) high-volume events
Pine Script® indicator
by andreapsoroulas21
Pso VP 2.0This indicator provides an advanced volume analysis tool that visualizes trading activity across different price levels and automatically identifies key support and resistance zones. How It Works: The Volume Profile analyzes historical price and volume data within a specified lookback period, distributing volume across horizontal price levels. Unlike traditional volume indicators that show volume over time, this tool displays volume at price, revealing where the most significant trading activity has occurred. The algorithm: Divides the price range into customizable horizontal bars (bins) Calculates and accumulates volume for each price level Identifies high-volume nodes that often act as support or resistance levels Uses percentile filtering to highlight the most significant trading areas Key Features: Automatic S/R Detection: Uses volume percentile filtering to identify the most significant price levels Dynamic Support/Resistance Lines: Automatically draws horizontal black lines at high-volume areas that typically act as price magnets or barriers Customizable Parameters: Full control over lookback period, number of price bars, percentile thresholds, profile width, opacity, and line projections Clean Aesthetic: Monochrome design for professional chart presentation
Pine Script® indicator
by andreapsoroulas21