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ATR_XAUUSD-BITCOINT-US100_Daniel# ATR Daniel - Indicator Description ## 🇬🇧 ENGLISH VERSION ### ATR Daniel - Smart Trailing Stop Manager **ATR Daniel** is an intelligent trailing stop indicator that automatically adapts to your trading style and the asset you're trading. #### Key Features: **🎯 3 Trading Modes:** - **Swing Trading** - For position trading with wider stops - **Intraday** - For day trading with balanced parameters - **Scalping** - For quick trades with tight stops **📊 Automatic Asset Detection:** The indicator automatically recognizes 3 major assets and applies optimized parameters: - **XAUUSD (Gold)** - Lower volatility settings - **BTCUSDT (Bitcoin)** - Medium volatility settings - **NAS100USD (Nasdaq 100)** - Higher volatility settings **🔧 Flexible Configuration:** - **Auto Mode**: Applies optimal parameters based on detected asset and selected trading mode - **Manual Mode**: Customize ATR length and multiplier to your preferences - **Customizable Colors**: Choose your own line color - **ON/OFF Display**: Toggle line visibility as needed **📈 Visual Display:** - Dynamic trailing stop line that follows price action - Color changes based on trend direction (bullish/bearish) - Real-time info table showing: - Current asset - Trading mode - ATR value - Stop loss distance - Recommended SL price - Current trend direction - Signal arrows at trend reversals (optional) **💡 How It Works:** The indicator uses ATR (Average True Range) to calculate dynamic stop loss levels that adapt to market volatility. The trailing stop follows the price in trending markets while protecting your position. **Perfect for:** - Traders who want automated stop loss management - Multi-asset traders (Gold, Bitcoin, Nasdaq) - All trading styles (Swing, Intraday, Scalping) ---
Penunjuk Pine Script®
oleh Daniel_Conroy
Ben's BTC Macro Fair Value OscillatorBen's BTC Macro Fair Value Oscillator Overview The **BTC Macro Fair Value Oscillator** is a non-crypto fair value framework that uses macro asset relationships (equities, dollar, gold) to estimate Bitcoin's "macro-driven fair value" and identify mean-reversion opportunities. "Is BTC cheap or expensive right now?" on the 4 Hour Timeframe ONLY ### Key Features ✅ **Macro-driven**: Uses QQQ, DXY, XAUUSD instead of on-chain or crypto metrics ✅ **Dynamic weighting**: Assets weighted by rolling correlation strength ✅ **Mean-reversion signals**: Identifies when BTC is cheap/expensive vs macro ✅ **Validated parameters**: Optimized through 5-year backtest (Sharpe 6.7-9.9) ✅ **Visual transparency**: Live correlation panel, fair value bands, statistics ✅ **Non-repainting**: All calculations use confirmed historical data only ### What This Indicator Does - Builds a **synthetic macro composite** from traditional assets - Runs a **rolling regression** to predict BTC price from macro - Calculates **deviation z-score** (how far BTC is from macro fair value) - Generates **entry signals** when BTC is extremely cheap vs macro (dev < -2) - Generates **exit signals** when BTC returns to fair value (dev > 0) ### What This Indicator Is NOT ❌ Not a high-frequency trading system (sparse signals by design) ❌ Not optimized for absolute returns (optimized for Sharpe ratio) ❌ Not suitable as standalone trading system (best as overlay/confirmation) ❌ Not predictive of short-term price movements (mean-reversion timeframe: days to weeks) --- ## Core Concept ### The Premise Bitcoin doesn't trade in a vacuum. It's influenced by: - **Risk appetite** (equities: QQQ, SPX) - **Dollar strength** (DXY - inverse to risk assets) - **Safe haven flows** (Gold: XAUUSD) When macro conditions are "good for BTC" (risk-on, weak dollar, strong equities), BTC should trade higher. When macro conditions turn against it, BTC should trade lower. ### The Innovation Instead of looking at BTC in isolation, this indicator: 1. **Measures how strongly** BTC currently correlates with each macro asset 2. **Builds a weighted composite** of those macro returns (the "D" driver) 3. **Regresses BTC price on D** to estimate "macro fair value" 4. **Tracks the deviation** between actual price and fair value 5. **Signals mean reversion** when deviation becomes extreme ### The Edge The validated edge comes from: - **Extreme deviations predict future returns** (dev < -2 → +1.67% over 12 bars) - **Monotonic relationship** (more negative dev → higher forward returns) - **Works out-of-sample** (test Sharpe +83-87% better than training) - **Low correlation with buy & hold** (provides diversification value) --- ## Methodology ### Step 1: Macro Composite Driver D(t) The indicator builds a weighted composite of macro asset returns: **Process:** 1. Calculate **log returns** for BTC and each macro reference (QQQ, DXY, XAUUSD) 2. Compute **rolling correlation** between BTC and each reference over `corrLen` bars 3. **Weight each asset** by `|correlation|` if above `minCorrAbs` threshold, else 0 4. **Sign-adjust** weights (+1 for positive corr, -1 for negative) to handle inverse relationships 5. **Z-score normalize** each reference's returns over `fvWindow` 6. **Composite D(t)** = weighted sum of sign-adjusted z-scores **Formula:** ``` For each reference i: corr_i = correlation(BTC_returns, ref_i_returns, corrLen) weight_i = |corr_i| if |corr_i| >= minCorrAbs else 0 sign_i = +1 if corr_i >= 0 else -1 z_i = (ref_i_returns - mean) / std contrib_i = sign_i * z_i * weight_i D(t) = sum(contrib_i) / sum(weight_i) ``` **Key Insight:** D(t) represents "how good macro conditions are for BTC right now" in a normalized, correlation-weighted way. --- ### Step 2: Fair Value Regression Uses rolling linear regression to predict BTC price from D(t): **Model:** ``` BTC_price(t) = α + β * D(t) ``` **Calculation (Pine Script approach):** ``` corr_CD = correlation(BTC_price, D, fvWindow) sd_price = stdev(BTC_price, fvWindow) sd_D = stdev(D, fvWindow) cov = corr_CD * sd_price * sd_D var_D = variance(D, fvWindow) β = cov / var_D α = mean(BTC_price) - β * mean(D) fair_value(t) = α + β * D(t) ``` **Result:** A time-varying "macro fair value" line that adapts as correlations change. --- ### Step 3: Deviation Oscillator Measures how far BTC price has deviated from fair value: **Calculation:** ``` residual(t) = BTC_price(t) - fair_value(t) residual_std = stdev(residual, normWindow) deviation(t) = residual(t) / residual_std ``` **Interpretation:** - `dev = 0` → BTC at fair value - `dev = -2` → BTC is 2 standard deviations **cheap** vs macro - `dev = +2` → BTC is 2 standard deviations **rich** vs macro --- ### Step 4: Signal Generation **Long Entry:** `dev` crosses below `-2.0` (BTC extremely cheap vs macro) **Long Exit:** `dev` crosses above `0.0` (BTC returns to fair value) **No shorting** in default config (risk management choice - crypto volatility) --- ## How It Works ### Visual Components #### 1. Price Chart (Main Panel) **Fair Value Line (Orange):** - The estimated "macro-driven fair value" for BTC - Calculated from rolling regression on macro composite **Fair Value Bands:** - **±1σ** (light): 68% confidence zone - **±2σ** (medium): 95% confidence zone - **±3σ** (dark, dots): 99.7% confidence zone **Entry/Exit Markers:** - **Green "LONG" label** below bar: Entry signal (dev < -2) - **Red "EXIT" label** above bar: Exit signal (dev > 0) #### 2. Deviation Oscillator (Separate Pane) **Line plot:** - Shows current deviation z-score - **Green** when dev < -2 (cheap) - **Red** when dev > +2 (rich) - **Gray** when neutral **Histogram:** - Visual representation of deviation magnitude - Green bars = negative deviation (cheap) - Red bars = positive deviation (rich) **Threshold lines:** - **Green dashed at -2.0**: Entry threshold - **Red dashed at 0.0**: Exit threshold - **Gray solid at 0**: Fair value line #### 3. Correlation Panel (Top-Right) Shows live correlation and weighting for each macro asset: | Asset | Corr | Weight | |-------|------|--------| | QQQ | +0.45 | 0.45 | | DXY | -0.32 | 0.32 | | XAUUSD | +0.15 | 0.00 | | Avg \|Corr\| | 0.31 | 0.77 | **Reading:** - **Corr**: Current rolling correlation with BTC (-1 to +1) - **Weight**: How much this asset contributes to fair value (0 = excluded) - **Avg |Corr|**: Average correlation strength (should be > 0.2 for reliable signals) **Colors:** - Green/Red corr = positive/negative correlation - White weight = asset included, Gray = excluded (below minCorrAbs) #### 4. Statistics Label (Bottom-Right) ``` ━━━ BTC Macro FV ━━━ Dev: -2.34 Price: $103,192 FV: $110,500 Status: CHEAP ⬇ β: 103.52 ``` **Fields:** - **Dev**: Current deviation z-score - **Price**: Current BTC close price - **FV**: Current macro fair value estimate - **Status**: CHEAP (< -2), RICH (> +2), or FAIR - **β**: Current regression beta (sensitivity to macro) --- ## Installation & Setup ### TradingView Setup 1. Open TradingView and navigate to any **BTC chart** (BTCUSD, BTCUSDT, etc.) 2. Open **Pine Editor** (bottom panel) 3. Click **"+ New"** → **"Blank indicator"** 4. **Delete** all default code 5. **Copy** the entire Pine Script from `GHPT_optimized.pine` 6. **Paste** into the editor 7. Click **"Save"** and name it "BTC Macro Fair Value Oscillator" 8. Click **"Add to Chart"** ### Recommended Chart Settings **Timeframe:** 4h (validated timeframe) **Chart Type:** Candlestick or Heikin Ashi **Overlay:** Yes (indicator plots on price chart + separate pane) **Alternative Timeframes:** - Daily: Works but slower signals - 1h-2h: May work but not validated - < 1h: Not recommended (too noisy) ### Symbol Requirements **Primary:** BTC/USD or BTC/USDT on any exchange **Macro References:** Automatically fetched - QQQ (Nasdaq 100 ETF) - DXY (US Dollar Index) - XAUUSD (Gold spot) **Data Requirements:** - At least **90 bars** of history (warmup period) - Premium TradingView recommended for full historical data --- ## Reading the Indicator ### Identifying Signals #### Strong Long Signal (High Conviction) - ✅ Deviation < -2.0 (extreme undervaluation) - ✅ Avg |Corr| > 0.3 (strong macro relationships) - ✅ Price touching or below -2σ band - ✅ "LONG" label appears below bar **Interpretation:** BTC is extremely cheap relative to macro conditions. Historical data shows +1.67% average return over next 12 bars (48 hours at 4h timeframe). #### Moderate Long Signal (Lower Conviction) - ⚠️ Deviation between -1.5 and -2.0 - ⚠️ Avg |Corr| between 0.2-0.3 - ⚠️ Price approaching -2σ band **Interpretation:** BTC is cheap but not extreme. Consider as confirmation for other signals. #### Exit Signal - 🔴 Deviation crosses above 0 (returns to fair value) - 🔴 "EXIT" label appears above bar **Interpretation:** Mean reversion complete. Close long positions. #### Strong Short/Avoid Signal - 🔴 Deviation > +2.0 (extreme overvaluation) - 🔴 Avg |Corr| > 0.3 - 🔴 Price touching or above +2σ band **Interpretation:** BTC is expensive vs macro. Historical data shows -1.79% average return over next 12 bars. Consider exiting longs or reducing exposure. ### Regime Detection **Strong Regime (Reliable Signals):** - Avg |Corr| > 0.3 - Multiple assets weighted > 0 - Fair value line tracking price reasonably well **Weak Regime (Unreliable Signals):** - Avg |Corr| < 0.2 - Most weights = 0 (grayed out) - Fair value line diverging wildly from price - **Action:** Ignore signals until correlations strengthen
Penunjuk Pine Script®
oleh popularGnuofls7
Crypto Correlation Oscillator# Crypto Correlation Oscillator **Companion indicator for Tri-Align Crypto Trend** ## Overview The Crypto Correlation Oscillator helps you identify **alpha opportunities** and **market regime changes** by showing how closely your coin follows Bitcoin and other assets over time. It displays rolling correlations as an oscillator in a separate pane below your price chart. ## What It Does This indicator calculates **Pearson correlations** between different trading pairs on a rolling window (default: 100 bars). Correlations range from **-1.0** (perfect inverse relationship) to **+1.0** (perfect positive relationship), with **0** meaning no correlation. ### The 5 Correlation Lines 1. **Blue (thick line) - Coin vs BTC**: The most important metric - **High correlation (>0.7)**: Your coin is just following BTC - no independent movement - **Low correlation (<0.3)**: Your coin has **alpha** - it's moving independently from BTC - **Negative correlation**: Your coin moves opposite to BTC (rare but powerful) 2. **Purple - Coin/BTC vs BTC**: Inverse relationship check - **Negative values**: When BTC rises, your coin weakens relative to BTC - **Positive values**: When BTC rises, your coin strengthens against BTC 3. **Orange - Coin vs Coin/BTC**: Structural consistency check - Shows how well the Coin/USDT and Coin/BTC pairs maintain their mathematical relationship - Unusual values can indicate liquidity issues or market inefficiencies 4. **Light Red - Coin vs USDT.D** (optional): Stablecoin dominance correlation - Shows how your coin correlates with USDT dominance - Useful for understanding flight-to-safety dynamics 5. **Light Green - Coin vs BTC.D** (optional): Bitcoin dominance correlation - Shows how your coin correlates with BTC dominance - Helps identify altcoin season vs BTC dominance cycles ## How to Read It ### Finding Alpha Opportunities - **Low blue line (<0.3)**: Your coin is decoupled from BTC → potential alpha - **Blue line dropping**: Coin is gaining independence from BTC - **Blue line spiking to >0.9**: Coin is a "BTC clone" with no independent movement ### Regime Change Detection - **Blue line crossing 0.5**: Major shift in correlation behavior - **Purple line turning negative**: Coin starting to weaken when BTC rises (warning sign) - **Sharp correlation changes**: Market structure is shifting - adjust strategy ### Visual Zones - **Blue background**: High correlation zone (>0.7) - coin just following BTC - **Red background**: Inverse correlation zone (<-0.5) - coin moving opposite to BTC ### Reference Lines - **+1.0 / -1.0**: Perfect correlation boundaries (dotted gray) - **+0.5 / -0.5**: Moderate correlation thresholds (dotted gray) - **0.0**: Zero correlation line (solid gray) ## Dynamic Legend The legend table (top-right) automatically shows the actual symbol names based on your chart: - **Example on SOLUSDT**: Shows "SOL vs BTC", "SOL/BTC vs BTC", "SOL vs SOL/BTC", etc. - **Color boxes**: Match the plot colors for easy identification - **Live values**: Current correlation numbers update in real-time - **Tooltips**: Hover over labels for interpretation guidance ## Configuration ### Key Inputs - **Correlation Lookback** (default: 100): Number of bars for rolling correlation window - Shorter = more reactive, noisier - Longer = smoother, slower to detect changes - **Correlation Smoothing** (default: 5): EMA smoothing period for raw correlations - Reduces noise while preserving trends - **Symbol Detection**: Auto-detects symbols from your chart, or use manual overrides - **Dominance Pairs**: Toggle USDT.D and BTC.D correlations on/off ## Usage Tips 1. **Combine with main Tri-Align indicator**: Use correlation for context, Tri-Align for entry/exit signals 2. **Watch for divergences**: Correlation changing while price moves in sync can signal upcoming shift 3. **Adjust lookback period**: Use shorter (50-70) for day trading, longer (150-200) for position trading 4. **Focus on the blue line**: It's your primary alpha indicator ## Technical Details - **Calculation**: Pearson correlation coefficient with EMA smoothing - **Data source**: Close prices from `request.security()` (multi-timeframe capable) - **Update frequency**: Every bar on your selected timeframe - **Overlay**: False (displays in separate pane) ## Quick Interpretation Guide | Blue Line Value | Interpretation | Action | |----------------|----------------|--------| | > 0.9 | Coin is a BTC clone | Avoid - no alpha opportunity | | 0.7 - 0.9 | High correlation | Standard altcoin behavior | | 0.3 - 0.7 | Moderate correlation | Some independence emerging | | < 0.3 | Low correlation | **Strong alpha opportunity** | | < 0 | Inverse correlation | Rare - potential hedge asset | | Purple Line | Interpretation | |-------------|----------------| | Strongly negative | Coin weakens when BTC rises - risky | | Near zero | Coin/BTC pair moves independently of BTC | | Positive | Coin strengthens with BTC - ideal | ## Version History ### v1.0 (Initial Release) - Pearson correlation calculation with configurable lookback - 5 correlation pairs: Coin vs BTC, Coin/BTC vs BTC, Coin vs Coin/BTC, USDT.D, BTC.D - EMA smoothing to reduce noise - Visual zones for high/inverse correlation - Dynamic legend with symbol name extraction - Auto-symbol detection matching main Tri-Align indicator
Penunjuk Pine Script®
oleh Frey_Crypto
Log Regression Channel (Dezza Fixed v2)This custom indicator builds a curved Logarithmic Regression Channel designed for long-term Bitcoin and macro asset analysis. It performs a linear regression on the logarithm of price to estimate the market’s fair-value growth curve, then converts that back into price space to form upper and lower deviation bands. It helps identify where price sits relative to its long-term exponential trend — showing potential overvaluation (upper band) or undervaluation (lower band) zones. Best used on weekly or monthly charts to visualise market cycles and fair-value reversion. Adjustable inputs let you control lookback length, band width, and midline visibility.
Penunjuk Pine Script®
oleh batobato69
Log Regression Channel (Dezza)This custom indicator builds a curved Logarithmic Regression Channel designed for long-term Bitcoin and macro asset analysis. It performs a linear regression on the logarithm of price to estimate the market’s fair-value growth curve, then converts that back into price space to form upper and lower deviation bands. It helps identify where price sits relative to its long-term exponential trend — showing potential overvaluation (upper band) or undervaluation (lower band) zones. Best used on weekly or monthly charts to visualise market cycles and fair-value reversion. Adjustable inputs let you control lookback length, band width, and midline visibility.
Penunjuk Pine Script®
oleh batobato69
ROC & Momentum FusionROC & Momentum Fusion (by HabibiTrades ©) Purpose: “ROC & Momentum Fusion” combines the Rate of Change (ROC) with a MACD-style signal engine to identify early momentum reversals, confirmed trend shifts, and low-volatility choppy zones. It’s built for traders who want early momentum detection with the clarity of trend persistence — adaptable to any instrument and timeframe. ⚙️ How It Works Rate of Change (ROC): Measures the percentage speed of price change over time, showing the raw momentum strength. Signal Line (EMA): A short EMA of the ROC — responds faster to new directional shifts, similar to a MACD signal line. Histogram: Displays acceleration and deceleration between the ROC and its signal line. Persistent Trend States: When the ROC crosses the signal line or zero, the indicator enters a new momentum regime (bullish or bearish) and stays in that color until another flip occurs. Dynamic Choppy Zone: When ROC momentum fades within the zero buffer zone, the indicator turns orange, signaling a sideways or indecisive market. 🟢 Visual Regimes Regime Description Color Bullish Momentum ROC above zero or signal line 🟢 Neon Green Bearish Momentum ROC below zero or signal line 🔴 Neon Red Choppy / Neutral ROC hovering within ±threshold range 🟠 Neon Orange This color system makes it visually effortless to see whether the market is trending, reversing, or consolidating. 🧭 Adaptive Intelligence The script automatically adjusts to market type and session for consistent accuracy: Session Adaptive: Adjusts smoothing based on global sessions (Asian, London, New York, Sydney). Instrument Adaptive: Fine-tunes sensitivity automatically for major assets — NASDAQ (NQ), S&P 500 (ES), Gold (GC), Oil (CL), Bitcoin (BTC). Volatility Normalization: Optionally divides ROC by its own standard deviation to stabilize noisy assets and maintain consistent scaling. 🔔 Signals & Alerts Bullish Reversal: ROC crosses above its signal or zero line — early momentum flip. Bearish Reversal: ROC crosses below its signal or zero line — downward momentum flip. Alerts: Both reversal conditions include built-in alert triggers for automation and notifications. 🎨 Visual Features Main ROC Line: Adaptive EMA of ROC, color-coded by trend regime. Signal Line: Optional white EMA overlay for MACD-style crossovers. Histogram: Visual burst display of acceleration (green/red). Reversal Markers: Optional triangles marking exact crossover points. Threshold Lines: Highlight the zero and buffer zones for visual clarity. 🧩 Best Use Cases Identify early momentum shifts before price confirms them. Confirm trend continuation or exhaustion with color persistence. Detect choppy / low-volatility periods instantly. Works across all timeframes — from 1-minute scalping to weekly swings. Combine with structure, EMAs, or volume for confirmation. ⚙️ Recommended Settings Setting Default Description ROC Period 6 Core momentum length (lower = faster response). Signal EMA Length 3 MACD-style responsiveness (lower = more reactive). Zero Buffer Threshold 0.15 Defines the width of the neutral zone around zero. Choppy Zone Multiplier 1.0 Expands or tightens the orange zone sensitivity. These defaults have been optimized through real-market testing to balance responsiveness and smoothness across different asset classes. ⚠️ Notes The color regime is persistent, meaning once the line turns bullish or bearish, it remains in that state until momentum structurally flips. The orange zone represents momentum uncertainty and helps avoid false entries in range-bound markets. Works seamlessly on any timeframe and with any asset.
Penunjuk Pine Script®
oleh Habibitrades_
Bull Bear Indicator# Bull Bear Indicator - TradingView Script Description ## Overview The Bull Bear Indicator is a powerful visual tool that instantly identifies market sentiment by coloring all candlesticks based on their position relative to a moving average. This indicator helps traders quickly identify bullish and bearish market conditions at a glance. ## Key Features ### 🎨 Visual Bull/Bear Identification - **Green Candles**: Price is at or above the moving average (Bullish condition) - **Red Candles**: Price is below the moving average (Bearish condition) - Complete candle coloring including body, wicks, and borders for maximum clarity ### 📊 Flexible Moving Average Options - **MA Type**: Choose between Simple Moving Average (MA) or Exponential Moving Average (EMA) - **Timeframe**: Select Weekly or Daily timeframe for the moving average calculation - **Customizable Period**: Adjust the MA/EMA period (default: 50) ### 📈 Smooth Moving Average Line - Displays a smooth blue moving average line on the chart - Automatically adapts to your selected timeframe and MA type - Provides clear visual reference for trend identification ## How It Works The indicator calculates a moving average (MA or EMA) based on your selected timeframe (Weekly or Daily). It then compares the current price to this moving average: - **Bull Market**: When price ≥ Moving Average → Candles turn **GREEN** - **Bear Market**: When price < Moving Average → Candles turn **RED** ## Configuration Options 1. **MA Type**: Choose "MA" for Simple Moving Average or "EMA" for Exponential Moving Average 2. **Timeframe**: Select "Weekly" for weekly-based MA or "Daily" for daily-based MA 3. **MA Period**: Set the number of periods for the moving average calculation (default: 50) ## Use Cases - **Trend Identification**: Quickly identify overall market trend direction - **Entry/Exit Signals**: Use color changes as potential entry or exit signals - **Multi-Timeframe Analysis**: Combine with different chart timeframes for comprehensive analysis - **Visual Clarity**: Reduce chart clutter while maintaining essential trend information ## Best Practices - Use Weekly MA for longer-term trend identification - Use Daily MA for shorter-term trend analysis - Combine with other technical indicators for confirmation - Adjust the MA period based on your trading style and timeframe ## Technical Details - Built with Pine Script v6 - Overlay indicator (displays on main chart) - Optimized for performance - Compatible with all TradingView chart types --- **Note**: This indicator is for educational and informational purposes only. Always conduct your own analysis and risk management before making trading decisions.
Penunjuk Pine Script®
oleh mychaelgo
Scientific Correlation Testing FrameworkScientific Correlation Testing Framework - Comprehensive Guide Introduction to Correlation Analysis What is Correlation? Correlation is a statistical measure that describes the degree to which two assets move in relation to each other. Think of it like measuring how closely two dancers move together on a dance floor. Perfect Positive Correlation (+1.0): Both dancers move in perfect sync, same direction, same speed Perfect Negative Correlation (-1.0): Both dancers move in perfect sync but in opposite directions Zero Correlation (0): The dancers move completely independently of each other In financial markets, correlation helps us understand relationships between different assets, which is crucial for: Portfolio diversification Risk management Pairs trading strategies Hedging positions Market analysis Why This Script is Special This script goes beyond simple correlation calculations by providing: Two different correlation methods (Pearson and Spearman) Statistical significance testing to ensure results are meaningful Rolling correlation analysis to track how relationships change over time Visual representation for easy interpretation Comprehensive statistics table with detailed metrics Deep Dive into the Script's Components 1. Input Parameters Explained- Symbol Selection: This allows you to select the second asset to compare with the chart's primary asset Default is Apple (NASDAQ:AAPL), but you can change this to any symbol Example: If you're viewing a Bitcoin chart, you might set this to "NASDAQ:TSLA" to see if Bitcoin and Tesla are correlated Correlation Window (60): This is the number of periods used to calculate the main correlation Larger values (e.g., 100-500) provide more stable, long-term correlation measures Smaller values (e.g., 10-50) are more responsive to recent price movements 60 is a good balance for most daily charts (about 3 months of trading days) Rolling Correlation Window (20): A shorter window to detect recent changes in correlation This helps identify when the relationship between assets is strengthening or weakening Default of 20 is roughly one month of trading days Return Type: This determines how price changes are calculated Simple Returns: (Today's Price - Yesterday's Price) / Yesterday's Price Easy to understand: "The asset went up 2% today" Log Returns: Natural logarithm of (Today's Price / Yesterday's Price) More mathematically elegant for statistical analysis Better for time-additive properties (returns over multiple periods) Less sensitive to extreme values. Confidence Level (95%): This determines how certain we want to be about our results 95% confidence means we accept a 5% chance of being wrong (false positive) Higher confidence (e.g., 99%) makes the test more strict Lower confidence (e.g., 90%) makes the test more lenient 95% is the standard in most scientific research Show Statistical Significance: When enabled, the script will test if the correlation is statistically significant or just due to random chance. Display options control what you see on the chart: Show Pearson/Spearman/Rolling Correlation: Toggle each correlation type on/off Show Scatter Plot: Displays a scatter plot of returns (limited to recent points to avoid performance issues) Show Statistical Tests: Enables the detailed statistics table Table Text Size: Adjusts the size of text in the statistics table 2.Functions explained- calcReturns(): This function calculates price returns based on your selected method: Log Returns: Formula: ln(Price_t / Price_t-1) Example: If a stock goes from $100 to $101, the log return is ln(101/100) = ln(1.01) ≈ 0.00995 or 0.995% Benefits: More symmetric, time-additive, and better for statistical modeling Simple Returns: Formula: (Price_t - Price_t-1) / Price_t-1 Example: If a stock goes from $100 to $101, the simple return is (101-100)/100 = 0.01 or 1% Benefits: More intuitive and easier to understand rankArray(): This function calculates the rank of each value in an array, which is used for Spearman correlation: How ranking works: The smallest value gets rank 1 The second smallest gets rank 2, and so on For ties (equal values), they get the average of their ranks Example: For values Sorted: Ranks: (the two 2s tie for ranks 1 and 2, so they both get 1.5) Why this matters: Spearman correlation uses ranks instead of actual values, making it less sensitive to outliers and non-linear relationships. pearsonCorr(): This function calculates the Pearson correlation coefficient: Mathematical Formula: r = (nΣxy - ΣxΣy) / √ Where x and y are the two variables, and n is the sample size What it measures: The strength and direction of the linear relationship between two variables Values range from -1 (perfect negative linear relationship) to +1 (perfect positive linear relationship) 0 indicates no linear relationship Example: If two stocks have a Pearson correlation of 0.8, they have a strong positive linear relationship When one stock goes up, the other tends to go up in a fairly consistent proportion spearmanCorr(): This function calculates the Spearman rank correlation: How it works: Convert each value in both datasets to its rank Calculate the Pearson correlation on the ranks instead of the original values What it measures: The strength and direction of the monotonic relationship between two variables A monotonic relationship is one where as one variable increases, the other either consistently increases or decreases It doesn't require the relationship to be linear When to use it instead of Pearson: When the relationship is monotonic but not linear When there are significant outliers in the data When the data is ordinal (ranked) rather than interval/ratio Example: If two stocks have a Spearman correlation of 0.7, they have a strong positive monotonic relationship When one stock goes up, the other tends to go up, but not necessarily in a straight-line relationship tStatistic(): This function calculates the t-statistic for correlation: Mathematical Formula: t = r × √((n-2)/(1-r²)) Where r is the correlation coefficient and n is the sample size What it measures: How many standard errors the correlation is away from zero Used to test the null hypothesis that the true correlation is zero Interpretation: Larger absolute t-values indicate stronger evidence against the null hypothesis Generally, a t-value greater than 2 (in absolute terms) is considered statistically significant at the 95% confidence level criticalT() and pValue(): These functions provide approximations for statistical significance testing: criticalT(): Returns the critical t-value for a given degrees of freedom (df) and significance level The critical value is the threshold that the t-statistic must exceed to be considered statistically significant Uses approximations since Pine Script doesn't have built-in statistical distribution functions pValue(): Estimates the p-value for a given t-statistic and degrees of freedom The p-value is the probability of observing a correlation as strong as the one calculated, assuming the true correlation is zero Smaller p-values indicate stronger evidence against the null hypothesis Standard interpretation: p < 0.01: Very strong evidence (marked with **) p < 0.05: Strong evidence (marked with *) p ≥ 0.05: Weak evidence, not statistically significant stdev(): This function calculates the standard deviation of a dataset: Mathematical Formula: σ = √(Σ(x-μ)²/(n-1)) Where x is each value, μ is the mean, and n is the sample size What it measures: The amount of variation or dispersion in a set of values A low standard deviation indicates that the values tend to be close to the mean A high standard deviation indicates that the values are spread out over a wider range Why it matters for correlation: Standard deviation is used in calculating the correlation coefficient It also provides information about the volatility of each asset's returns Comparing standard deviations helps understand the relative riskiness of the two assets. 3.Getting Price Data- price1: The closing price of the primary asset (the chart you're viewing) price2: The closing price of the secondary asset (the one you selected in the input parameters) Returns are used instead of raw prices because: Returns are typically stationary (mean and variance stay constant over time) Returns normalize for price levels, allowing comparison between assets of different values Returns represent what investors actually care about: percentage changes in value 4.Information Table- Creates a table to display statistics Only shows on the last bar to avoid performance issues Positioned in the top right of the chart Has 2 columns and 15 rows Populating the Table The script then populates the table with various statistics: Header Row: "Metric" and "Value" Sample Information: Sample size and return type Pearson Correlation: Value, t-statistic, p-value, and significance Spearman Correlation: Value, t-statistic, p-value, and significance Rolling Correlation: Current value Standard Deviations: For both assets Interpretation: Text description of the correlation strength The table uses color coding to highlight important information: Green for significant positive results Red for significant negative results Yellow for borderline significance Color-coded headers for each section => Practical Applications and Interpretation How to Interpret the Results Correlation Strength 0.0 to 0.3 (or 0.0 to -0.3): Weak or no correlation The assets move mostly independently of each other Good for diversification purposes 0.3 to 0.7 (or -0.3 to -0.7): Moderate correlation The assets show some tendency to move together (or in opposite directions) May be useful for certain trading strategies but not extremely reliable 0.7 to 1.0 (or -0.7 to -1.0): Strong correlation The assets show a strong tendency to move together (or in opposite directions) Can be useful for pairs trading, hedging, or as a market indicator Statistical Significance p < 0.01: Very strong evidence that the correlation is real Marked with ** in the table Very unlikely to be due to random chance p < 0.05: Strong evidence that the correlation is real Marked with * in the table Unlikely to be due to random chance p ≥ 0.05: Weak evidence that the correlation is real Not marked in the table Could easily be due to random chance Rolling Correlation The rolling correlation shows how the relationship between assets changes over time If the rolling correlation is much different from the long-term correlation, it suggests the relationship is changing This can indicate: A shift in market regime Changing fundamentals of one or both assets Temporary market dislocations that might present trading opportunities Trading Applications 1. Portfolio Diversification Goal: Reduce overall portfolio risk by combining assets that don't move together Strategy: Look for assets with low or negative correlations Example: If you hold tech stocks, you might add some utilities or bonds that have low correlation with tech 2. Pairs Trading Goal: Profit from the relative price movements of two correlated assets Strategy: Find two assets with strong historical correlation When their prices diverge (one goes up while the other goes down) Buy the underperforming asset and short the outperforming asset Close the positions when they converge back to their normal relationship Example: If Coca-Cola and Pepsi are highly correlated but Coca-Cola drops while Pepsi rises, you might buy Coca-Cola and short Pepsi 3. Hedging Goal: Reduce risk by taking an offsetting position in a negatively correlated asset Strategy: Find assets that tend to move in opposite directions Example: If you hold a portfolio of stocks, you might buy some gold or government bonds that tend to rise when stocks fall 4. Market Analysis Goal: Understand market dynamics and interrelationships Strategy: Analyze correlations between different sectors or asset classes Example: If tech stocks and semiconductor stocks are highly correlated, movements in one might predict movements in the other If the correlation between stocks and bonds changes, it might signal a shift in market expectations 5. Risk Management Goal: Understand and manage portfolio risk Strategy: Monitor correlations to identify when diversification benefits might be breaking down Example: During market crises, many assets that normally have low correlations can become highly correlated (correlation convergence), reducing diversification benefits Advanced Interpretation and Caveats Correlation vs. Causation Important Note: Correlation does not imply causation Example: Ice cream sales and drowning incidents are correlated (both increase in summer), but one doesn't cause the other Implication: Just because two assets move together doesn't mean one causes the other to move Solution: Look for fundamental economic reasons why assets might be correlated Non-Stationary Correlations Problem: Correlations between assets can change over time Causes: Changing market conditions Shifts in monetary policy Structural changes in the economy Changes in the underlying businesses Solution: Use rolling correlations to monitor how relationships change over time Outliers and Extreme Events Problem: Extreme market events can distort correlation measurements Example: During a market crash, many assets may move in the same direction regardless of their normal relationship Solution: Use Spearman correlation, which is less sensitive to outliers Be cautious when interpreting correlations during extreme market conditions Sample Size Considerations Problem: Small sample sizes can produce unreliable correlation estimates Rule of Thumb: Use at least 30 data points for a rough estimate, 60+ for more reliable results Solution: Use the default correlation length of 60 or higher Be skeptical of correlations calculated with small samples Timeframe Considerations Problem: Correlations can vary across different timeframes Example: Two assets might be positively correlated on a daily basis but negatively correlated on a weekly basis Solution: Test correlations on multiple timeframes Use the timeframe that matches your trading horizon Look-Ahead Bias Problem: Using information that wouldn't have been available at the time of trading Example: Calculating correlation using future data Solution: This script avoids look-ahead bias by using only historical data Best Practices for Using This Script 1. Appropriate Parameter Selection Correlation Window: For short-term trading: 20-50 periods For medium-term analysis: 50-100 periods For long-term analysis: 100-500 periods Rolling Window: Should be shorter than the main correlation window Typically 1/3 to 1/2 of the main window Return Type: For most applications: Log Returns (better statistical properties) For simplicity: Simple Returns (easier to interpret) 2. Validation and Testing Out-of-Sample Testing: Calculate correlations on one time period Test if they hold in a different time period Multiple Timeframes: Check if correlations are consistent across different timeframes Economic Rationale: Ensure there's a logical reason why assets should be correlated 3. Monitoring and Maintenance Regular Review: Correlations can change, so review them regularly Alerts: Set up alerts for significant correlation changes Documentation: Keep notes on why certain assets are correlated and what might change that relationship 4. Integration with Other Analysis Fundamental Analysis: Combine correlation analysis with fundamental factors Technical Analysis: Use correlation analysis alongside technical indicators Market Context: Consider how market conditions might affect correlations Conclusion This Scientific Correlation Testing Framework provides a comprehensive tool for analyzing relationships between financial assets. By offering both Pearson and Spearman correlation methods, statistical significance testing, and rolling correlation analysis, it goes beyond simple correlation measures to provide deeper insights. For beginners, this script might seem complex, but it's built on fundamental statistical concepts that become clearer with use. Start with the default settings and focus on interpreting the main correlation lines and the statistics table. As you become more comfortable, you can adjust the parameters and explore more advanced applications. Remember that correlation analysis is just one tool in a trader's toolkit. It should be used in conjunction with other forms of analysis and with a clear understanding of its limitations. When used properly, it can provide valuable insights for portfolio construction, risk management, and pair trading strategy development.
Penunjuk Pine Script®
oleh kingshukghosh71
21 SMA over 200 SMA Bullish Cross Highlighter21 SMA Over 200 SMA — Momentum Cross for BTC Scalpers A precise and lightweight indicator designed to highlight when short-term momentum aligns with the broader Bitcoin trend. It visualizes when the 21-period Simple Moving Average (SMA) crosses above the 200-period SMA, often signaling the beginning of a sustained directional move — especially effective on the 1-minute BTC chart during trending market conditions. Core Concept When the 21 SMA crosses above the 200 SMA on Bitcoin during an active uptrend, the probability increases that price will continue rising as short-term traders and algorithms join the move. This indicator helps you identify that momentum shift in real time and react before the breakout gains full traction. Features Clear visual label for every bullish cross (21↑200) Optional bearish cross labels (21↓200) Optimized for 1m, 5m, and 15m BTC charts Lightweight and efficient — ideal for multi-chart scalping layouts Built-in alert conditions for manual alert setup Excellent synergy with VRVP (Visible Range Volume Profile) for confirming volume-based breakout zones Suggested Use Focus on the 1-minute Bitcoin chart for early signals. When a bullish cross appears, use VRVP to locate high-volume nodes or breakout levels for precise entries. Confirm alignment on 5m or 15m charts before executing. Combine with RSI, Stoch RSI, or volume analysis to refine timing and manage risk. Trading Insight The 21/200 SMA relationship has long been a trusted tool for trend identification. When both averages slope upward and the cross occurs above a strong VRVP volume zone, it often marks the start of a new impulsive leg in BTC ideal for short-term scalps or the first confirmation of a broader trend continuation. Created for disciplined BTC scalpers who value structured setups, clarity, and confirmation through data rather than noise.
Penunjuk Pine Script®
oleh nutsara682
FluxVector Liquidity Universal Trendline FluxVector Liquidity Trendline FFTL Summary in one paragraph FFTL is a single adaptive trendline for stocks ETFs FX crypto and indices on one minute to daily. It fires only when price action pressure and volatility curvature align. It is original because it fuses a directional liquidity pulse from candle geometry and normalized volume with realized volatility curvature and an impact efficiency term to modulate a Kalman like state without ATR VWAP or moving averages. Add it to a clean chart and use the colored line plus alerts. Shapes can move while a bar is open and settle on close. For conservative alerts select on bar close. Scope and intent • Markets. Major FX pairs index futures large cap equities liquid crypto top ETFs • Timeframes. One minute to daily • Default demo used in the publication. SPY on 30min • Purpose. Reduce false flips and chop by gating the line reaction to noise and by using a one bar projection • Limits. This is a strategy. Orders are simulated on standard candles only Originality and usefulness • Unique fusion. Directional Liquidity Pulse plus Volatility Curvature plus Impact Efficiency drives an adaptive gain for a one dimensional state • Failure mode addressed. One or two shock candles that break ordinary trendlines and saw chop in flat regimes • Testability. All windows and gains are inputs • Portable yardstick. Returns use natural log units and range is bar high minus low • Protected scripts. Not used. Method disclosed plainly here Method overview in plain language Base measures • Return basis. Natural log of close over prior close. Average absolute return over a window is a unit of motion Components • Directional Liquidity Pulse DLP. Measures signed participation from body and wick imbalance scaled by normalized volume and variance stabilized • Volatility Curvature. Second difference of realized volatility from returns highlights expansion or compression • Impact Efficiency. Price change per unit range and volume boosts gain during efficient moves • Energy score. Z scores of the above form a single energy that controls the state gain • One bar projection. Current slope extended by one bar for anticipatory checks Fusion rule Weighted sum inside the energy score then logistic mapping to a gain between k min and k max. The state updates toward price plus a small flow push. Signal rule • Long suggestion and order when close is below trend and the one bar projection is above the trend • Short suggestion and flip when close is above trend and the one bar projection is below the trend • WAIT is implicit when neither condition holds • In position states end on the opposite condition What you will see on the chart • Colored trendline teal for rising red for falling gray for flat • Optional projection line one bar ahead • Optional background can be enabled in code • Alerts on price cross and on slope flips Inputs with guidance Setup • Price source. Close by default Logic • Flow window. Typical range 20 to 80. Higher smooths the pulse and reduces flips • Vol window. Typical range 30 to 120. Higher calms curvature • Energy window. Typical range 20 to 80. Higher slows regime changes • Min gain and Max gain. Raise max to react faster. Raise min to keep momentum in chop UI • Show 1 bar projection. Colors for up down flat Properties visible in this publication • Initial capital 25000 • Base currency USD • Commission percent 0.03 • Slippage 5 • Default order size method percent of equity value 3% • Pyramiding 0 • Process orders on close off • Calc on every tick off • Recalculate after order is filled off Realism and responsible publication • No performance claims • Intrabar reminder. Shapes can move while a bar forms and settle on close • Strategy uses standard candles only Honest limitations and failure modes • Sudden gaps and thin liquidity can still produce fast flips • Very quiet regimes reduce contrast. Use larger windows and lower max gain • Session time uses the exchange time of the chart if you enable any windows later • Past results never guarantee future outcomes Open source reuse and credits • None
Strategi Pine Script®
oleh exlux
Grok's xAI Signal (GXS) Indicator for BTC V6Grok's xAI Signal (GXS) Indicator: A Simple Guide Imagine trying to decide if Bitcoin is a "buy," "sell," or "wait" without staring at 10 different charts. The GXS Indicator does that for you—it's like a smart dashboard for BTC traders, overlaying signals right on your price chart. It boils down complex market clues into one easy score (from -1 "super bearish" to +1 "super bullish") and flashes green/red arrows or shaded zones when action's needed. No fancy math overload; just clear visuals like tiny triangles for trades, colored clouds for trends, and a bottom "mood bar" (green=up vibe, red=down, gray=meh). At its core, GXS mixes three big-picture checks: Price Momentum (50% weight): Quick scans of RSI (overbought/oversold vibes), MACD (speed of ups/downs), EMAs (is price riding the trend wave?), and Bollinger Bands (is the market squeezing for a breakout?). This catches short-term "hot or not" energy. Network Health (30% weight): A simple "NVT" hack using trading volume vs. price to spot if BTC feels undervalued (buy hint) or overhyped (sell warning). It's like checking if the crowd's too excited or chill. Trend Strength (20% weight): ADX filter ensures signals only fire in "trending" markets (not choppy sideways noise), plus a MACD boost for extra momentum nudge. Why this approach? BTC's wild—pure price charts give false alarms in flat times, while ignoring volume/network ignores the "why" behind moves. GXS blends old-school TA (reliable for patterns) with on-chain smarts (crypto-specific "under the hood" data) and a trend gate (skips 70% of bad trades). It's conservative: Signals need the score to cross ±0.08 and a strong trend, reducing noise for swing/position traders. Result? Fewer emotional guesses, more "wait for confirmation" patience—perfect for volatile assets like BTC where hype kills. Quick Tips to Tweak for Better Results Start with defaults, then experiment on historical charts (backtest via TradingView's strategy tester if pairing with one): Fewer False Signals: Bump thresholds to ±0.15 (buy/sell)—trades only on stronger conviction, cutting whipsaws by 20-30% in choppy markets. Or raise ADX thresh to 28 for "only big trends." Faster/Slower Response: Shorten EMAs (e.g., 5/21) or RSI (10) for quicker scalps; lengthen (12/50) for swing holds. Test on 4H/daily BTC. Volume Sensitivity: If NVT flips too often, extend its length to 20—smooths on-chain noise in bull runs. Visual Polish: Crank cloud opacity to 80% for subtler fills; toggle off EMAs if they clutter. Enable table for score breakdowns during live trades. Risk Tip: Always pair with stops (e.g., 2-3% below signals). On BTC, tweak in bull markets (looser thresh) vs. bears (tighter). In short, GXS is your BTC "sixth sense"—balanced, not black-box. Tweak small, track win rate, and let trends lead. Happy trading!
Penunjuk Pine Script®
oleh ralis24
Broad Market for Crypto + index# Broad Market Indicator for Crypto ## Overview The Broad Market Indicator for Crypto helps traders assess the strength and divergence of individual cryptocurrency assets relative to the overall market. By comparing price deviations across multiple assets, this indicator reveals whether a specific coin is moving in sync with or diverging from the broader crypto market trend. ## How It Works This indicator calculates percentage deviations from simple moving averages (SMA) for both individual assets and an equal-weighted market index. The core methodology: 1. **Deviation Calculation**: For each asset, the indicator measures how far the current price has moved from its SMA over a specified lookback period (default: 24 hours). The deviation is expressed as a percentage: `(Current Price - SMA) / SMA × 100` 2. **Market Index Construction**: An equal-weighted index is built from selected cryptocurrencies (up to 15 assets). The default composition includes major crypto assets: BTC, ETH, BNB, SOL, XRP, ADA, AVAX, LINK, DOGE, and TRX. 3. **Comparative Analysis**: The indicator displays both the current instrument's deviation and the market index deviation on the same panel, making it easy to spot relative strength or weakness. ## Key Features - **Customizable Asset Selection**: Choose up to 15 different cryptocurrencies to include in your market index - **Flexible Configuration**: Toggle individual assets on/off for display and index calculation - **Current Instrument Tracking**: Automatically plots the deviation of whatever chart you're viewing - **Visual Clarity**: Color-coded lines for easy differentiation between assets, with the market index shown as a filled area - **Adjustable Lookback Period**: Modify the SMA period to match your trading timeframe ## How to Use ### Identifying Market Divergences - When the current instrument deviates significantly above the index, it shows relative strength - When it deviates below, it indicates relative weakness - Assets clustering around zero suggest neutral market conditions ### Trend Confirmation - If both the index and your asset are rising together (positive deviation), it confirms a broad market uptrend - Divergence between asset and index can signal unique fundamental factors or early trend changes ### Entry/Exit Signals - Extreme deviations from the index may indicate overbought/oversold conditions relative to the market - Convergence back toward the index line can signal mean reversion opportunities ## Settings - **Lookback Period**: Adjust the SMA calculation period (default: 24 hours) - **Asset Configuration**: Select which cryptocurrencies to monitor and include in the index - **Display Options**: Show/hide individual assets, current instrument, and market index - **Color Customization**: Personalize colors for better visual analysis ## Best Practices - Use on higher timeframes (4H, Daily) for more reliable signals - Combine with volume analysis for confirmation - Consider fundamental news when assets show extreme divergence - Adjust the asset basket to match your trading focus (DeFi, L1s, memecoins, etc.) ## Technical Notes - The indicator uses `request.security()` to fetch data from multiple symbols - Deviations are calculated independently for each asset - The zero line represents perfect alignment with the moving average - Index calculation automatically adjusts based on active assets ## Default Assets 1. BTC (Bitcoin) - BINANCE:BTCUSDT 2. ETH (Ethereum) - BINANCE:ETHUSDT 3. BNB (Binance Coin) - BINANCE:BNBUSDT 4. SOL (Solana) - BINANCE:SOLUSDT 5. XRP (Ripple) - BINANCE:XRPUSDT 6. ADA (Cardano) - BINANCE:ADAUSDT 7. AVAX (Avalanche) - BINANCE:AVAXUSDT 8. LINK (Chainlink) - BINANCE:LINKUSDT 9. DOGE (Dogecoin) - BINANCE:DOGEUSDT 10. TRX (Tron) - BINANCE:TRXUSDT Additional slots (11-15) are available for custom asset selection. --- This indicator is particularly useful for cryptocurrency traders seeking to understand market breadth and identify opportunities where specific assets are diverging from overall market sentiment.
Penunjuk Pine Script®
oleh AlekMel
Relative Valuation OscillatorRelative Valuation Oscillator (RVO) Description The Valuation_OTC.pine script is a Relative Valuation Oscillator for TradingView that compares the current asset against a reference asset (like Bitcoin, S&P 500, or Gold) to determine if it's relatively overvalued or undervalued. Key Features: 1. Multiple Calculation Methods: Simple Ratio - Compares price ratio deviation from average Percentage Difference - Direct percentage comparison between assets Ratio Z-Score - Statistical measure (standard deviations from mean) Rate of Change Comparison - Compares momentum/performance Normalized Ratio - 0-100 scale centered at zero 2. Customizable Settings: Reference asset selection (default: BTC/USDT) Adjustable lookback period (10-500 bars) Optional smoothing with configurable period Overbought/oversold level thresholds (default: ±1.5) 3. Trading Signals: Overvalued - Oscillator above overbought level (red zone) Undervalued - Oscillator below oversold level (green zone) Neutral - Between thresholds Crossover alerts for key levels Divergence detection (bullish/bearish) 4. Visual Components: Color-coded oscillator line (green when positive, red when negative) Optional signal line for additional smoothing Background shading for valuation zones Information table showing current metrics and status Shape markers for crossovers and divergences 5. Alert Conditions: Overvalued/undervalued alerts Zero-line crossovers Divergence signals This indicator is useful for pairs trading, relative strength analysis, and identifying when an asset is trading at extremes relative to a benchmark asset.
Penunjuk Pine Script®
oleh dragos_cocos_dev
Hyper SAR Reactor Trend StrategyHyperSAR Reactor Adaptive PSAR Strategy Summary Adaptive Parabolic SAR strategy for liquid stocks, ETFs, futures, and crypto across intraday to daily timeframes. It acts only when an adaptive trail flips and confirmation gates agree. Originality comes from a logistic boost of the SAR acceleration using drift versus ATR, plus ATR hysteresis, inertia on the trail, and a bear-only gate for shorts. Add to a clean chart and run on bar close for conservative alerts. Scope and intent • Markets: large cap equities and ETFs, index futures, major FX, liquid crypto • Timeframes: one minute to daily • Default demo: BTC on 60 minute • Purpose: faster yet calmer PSAR that resists chop and improves short discipline • Limits: this is a strategy that places simulated orders on standard candles Originality and usefulness • Novel fusion: PSAR AF is boosted by a logistic function of normalized drift, trail is monotone with inertia, entries use ATR buffers and optional cooldown, shorts are allowed only in a bear bias • Addresses false flips in low volatility and weak downtrends • All controls are exposed in Inputs for testability • Yardstick: ATR normalizes drift so settings port across symbols • Open source. No links. No solicitation Method overview Components • Adaptive AF: base step plus boost factor times logistic strength • Trail inertia: one sided blend that keeps the SAR monotone • Flip hysteresis: price must clear SAR by a buffer times ATR • Volatility gate: ATR over its mean must exceed a ratio • Bear bias for shorts: price below EMA of length 91 with negative slope window 54 • Cooldown bars optional after any entry • Visual SAR smoothing is cosmetic and does not drive orders Fusion rule Entry requires the internal flip plus all enabled gates. No weighted scores. Signal rule • Long when trend flips up and close is above SAR plus buffer times ATR and gates pass • Short when trend flips down and close is below SAR minus buffer times ATR and gates pass • Exit uses SAR as stop and optional ATR take profit per side Inputs with guidance Reactor Engine • Start AF 0.02. Lower slows new trends. Higher reacts quicker • Max AF 1. Typical 0.2 to 1. Caps acceleration • Base step 0.04. Typical 0.01 to 0.08. Raises speed in trends • Strength window 18. Typical 10 to 40. Drift estimation window • ATR length 16. Typical 10 to 30. Volatility unit • Strength gain 4.5. Typical 2 to 6. Steepness of logistic • Strength center 0.45. Typical 0.3 to 0.8. Midpoint of logistic • Boost factor 0.03. Typical 0.01 to 0.08. Adds to step when strength rises • AF smoothing 0.50. Typical 0.2 to 0.7. Adds inertia to AF growth • Trail smoothing 0.35. Typical 0.15 to 0.45. Adds inertia to the trail • Allow Long, Allow Short toggles Trade Filters • Flip confirm buffer ATR 0.50. Typical 0.2 to 0.8. Raise to cut flips • Cooldown bars after entry 0. Typical 0 to 8. Blocks re entry for N bars • Vol gate length 30 and Vol gate ratio 1. Raise ratio to trade only in active regimes • Gate shorts by bear regime ON. Bear bias window 54 and Bias MA length 91 tune strictness Risk • TP long ATR 1.0. Set to zero to disable • TP short ATR 0.0. Set to 0.8 to 1.2 for quicker shorts Usage recipes Intraday trend focus Confirm buffer 0.35 to 0.5. Cooldown 2 to 4. Vol gate ratio 1.1. Shorts gated by bear regime. Intraday mean reversion focus Confirm buffer 0.6 to 0.8. Cooldown 4 to 6. Lower boost factor. Leave shorts gated. Swing continuation Strength window 24 to 34. ATR length 20 to 30. Confirm buffer 0.4 to 0.6. Use daily or four hour charts. Properties visible in this publication Initial capital 10000. Base currency USD. Order size Percent of equity 3. Pyramiding 0. Commission 0.05 percent. Slippage 5 ticks. Process orders on close OFF. Bar magnifier OFF. Recalculate after order filled OFF. Calc on every tick OFF. No security calls. Realism and responsible publication No performance claims. Past results never guarantee future outcomes. Shapes can move while a bar forms and settle on close. Strategies execute only on standard candles. Honest limitations and failure modes High impact events and thin books can void assumptions. Gap heavy symbols may prefer longer ATR. Very quiet regimes can reduce contrast and invite false flips. Open source reuse and credits Public domain building blocks used: PSAR concept and ATR. Implementation and fusion are original. No borrowed code from other authors. Strategy notice Orders are simulated on standard candles. No lookahead. Entries and exits Long: flip up plus ATR buffer and all gates true Short: flip down plus ATR buffer and gates true with bear bias when enabled Exit: SAR stop per side, optional ATR take profit, optional cooldown after entry Tie handling: stop first if both stop and target could fill in one bar
Strategi Pine Script®
oleh exlux
HermesHERMES STRATEGY - TRADINGVIEW DESCRIPTION OVERVIEW Hermes is an adaptive trend-following strategy that uses dual ALMA (Arnaud Legoux Moving Average) filters to identify high-quality entry and exit points. It's designed for swing and position traders who want smooth, low-lag signals with minimal whipsaws. Unlike traditional moving averages that operate on price, Hermes analyzes price returns (percentage changes) to create signals that work consistently across any asset class and price range. HOW IT WORKS DUAL ALMA SYSTEM The strategy uses two ALMA lines applied to price returns: • Fast ALMA (Blue Line): Short-term trend signal (default: 80 periods) • Slow ALMA (Black Line): Long-term baseline trend (default: 250 periods) ALMA is superior to simple or exponential moving averages because it provides: • Smoother curves with less noise • Significantly reduced lag • Natural resistance to outliers and flash crashes TRADING LOGIC BUY SIGNAL: • Fast ALMA crosses above Slow ALMA (bullish regime) • Price makes new N-bar high (momentum confirmation) • Optional: Price above 200 EMA (macro trend filter) • Optional: ALMA lines sufficiently separated (strength filter) SELL SIGNAL: • Fast ALMA crosses below Slow ALMA (bearish regime) • Optional: Price makes new N-bar low (momentum confirmation) The strategy stays in position during the entire bullish regime, allowing you to ride trends for weeks or months. VISUAL INDICATORS LINES: • Blue Line: Fast ALMA (short-term signal) • Black Line: Slow ALMA (long-term baseline) TRADE MARKERS: • Green Triangle Up: Buy executed • Red Triangle Down: Sell executed • Orange "M": Buy blocked by momentum filter • Purple "W": Buy blocked by weak crossover strength KEY PARAMETERS ALMA SETTINGS: • Short Period (default: 30) - Fast signal responsiveness • Long Period (default: 250) - Baseline stability • ALMA Offset (default: 0.90) - Balance between lag and smoothness • ALMA Sigma (default: 7.5) - Gaussian curve width ENTRY/EXIT FILTERS: • Buy Lookback (default: 7) - Bars for momentum confirmation (required) • Sell Lookback (default: 0) - Exit momentum bars (0 = disabled for faster exits) • Min Crossover Strength (default: 0.0) - Required ALMA separation (0 = disabled) • Use Macro Filter (default: true) - Only enter above 200 EMA BEST PRACTICES RECOMMENDED ASSETS - Works well on: • Cryptocurrencies (Bitcoin, Ethereum, etc.) • Major indices (S&P 500, Nasdaq) • Large-cap stocks • Commodities (Gold, Oil) RECOMMENDED TIMEFRAMES: • Daily: Primary timeframe for swing trading • 4-Hour: More active trading (increase trade frequency) • Weekly: Long-term position trading PARAMETER TUNING: • More trades: Lower Short Period (60-80) • Fewer trades: Raise Short Period (100-120) • Faster exits: Set Sell Lookback = 0 • Safer entries: Enable Macro Filter (Use Macro Filter = true) STRATEGY ADVANTAGES 1. Low Lag - ALMA provides faster signals than traditional moving averages 2. Smooth Signals - Minimal whipsaws compared to crossover strategies 3. Asset Agnostic - Same parameters work across different markets 4. Trend Capture - Stays positioned during entire bullish regimes 5. Risk Management - Multiple filters prevent poor entries 6. Visual Clarity - Easy to interpret regime and filter states WHEN TO USE HERMES BEST FOR: • Trending markets (crypto bull runs, equity uptrends) • Swing trading (hold days to weeks) • Position trading (hold weeks to months) • Clear trend identification • Risk-managed exposure NOT SUITABLE FOR: • Ranging/sideways markets • Scalping or day trading • High-frequency trading • Mean reversion strategies RISK DISCLAIMER This indicator is for educational purposes only. Past performance does not guarantee future results. Always use proper position sizing and risk management. Test thoroughly on historical data before live trading. CREDITS Inspired by Giovanni Santostasi's Power Law Volatility Indicator, generalized for universal application across all assets using adaptive ALMA filtering. Strategy by Hermes Trading Systems QUICK START 1. Add indicator to chart 2. Use on daily timeframe for best results 3. Look for green buy signals when blue line crosses above black line 4. Exit on red sell signals when blue line crosses below black line 5. Adjust parameters based on your trading style: • Conservative: Enable Macro Filter, increase Buy Lookback to 10 • Aggressive: Disable Macro Filter, lower Short Period to 60 • Default settings work well for most assets
Strategi Pine Script®
oleh aicccia
3
PRO Scalper(EN) ## What it is **PRO Scalper** is an intraday price–action and liquidity map that helps you see where the market is likely to move **now**, not just where it has been. It combines five building blocks that professional scalpers often watch together: 1. **Session Volume-Weighted Average Price (VWAP)** — the intraday “fair value” anchor. 2. **Opening Range** — the first minutes of the session that set the day’s balance. 3. **Trend filter** — higher-timeframe bias using **Exponential Moving Averages (EMA)** and optional **Average Directional Index (ADX)** strength. 4. **Two independent Supply/Demand zone engines** — zones are drawn from confirmed swing pivots, with midlines and **touch counters**. 5. **Order-flow style visuals**: * **Delta bubbles** (green/red circles) show where buying or selling pressure was unusually strong, using a safe **delta proxy** (no external feeds). * **Liquidity densities** (subtle rectangular bands) highlight clusters of large activity that often act as magnets or barriers and disappear when “eaten” by strong moves. This mix gives you a **complete intraday picture**: the mean (VWAP), the day’s initial balance (Opening Range), the higher-timeframe push (trend filter), the nearby fuel or brakes (zones), and the live pressure points (bubbles and densities). --- ## Why these components * **VWAP** tracks where the bulk of traded value sits. Price tends to rotate around it or accelerate away from it — a perfect compass for scalps. * **Opening Range** frames the early auction. Many intraday breaks, fades and retests start at its boundaries. * **EMA bias + ADX strength** separates trending conditions from chop, so you can keep only the zones that agree with the bigger push. * **Pivot-based zones (two pairs at once)** are simple, objective and fast. Midlines help with confirmations; touch counters quantify how many times the zone was tested. * **Bubbles and densities** add the “effort” layer: where the push appeared and where liquidity is concentrated. You see **where** a move is likely to continue or fail. Together they reduce ambiguity: **context + level + effort** — all on one screen. --- ## How it works (plain language) * **VWAP** resets each day and is calculated as the cumulative sum of typical price multiplied by volume divided by total volume. * **Opening Range** is either automatic (a multiple of your chart timeframe) or a manual number of minutes. While it is forming, the highest high and lowest low are captured and plotted as the range. * **Trend filter** * **EMA Fast** and **EMA Slow** define directional bias. * **ADX (optional)** adds “trend strength”: only when the Average Directional Index is above the chosen threshold do we treat the move as strong. You can source this from a higher timeframe. * **Zones** * There are **two independent pairs** of pivots at the same time (for example 10-left 10-right and 5-left 5-right). * Each detected pivot creates a **Supply** (from a swing high) or **Demand** (from a swing low) box. Box depth = **zone depth × Average True Range** for adaptive sizing; the boxes **extend forward**. * Midline (optional dashed line inside the box) is the “balance” of the zone. * **“Only in trend”** mode can hide boxes that go against the higher-timeframe bias. * The **touch counter** increases when price revisits the box. Labels show the pair name and the number of touches. * **Bubbles** * A safe **delta proxy** measures bar pressure (for example, range-weighted close vs open). * A **quantile filter** shows only unusually large pressure: choose lookback and percentile, and the script draws a circle sized by intensity (green = bullish pressure, red = bearish). * **Densities** * The script marks heavy activity clusters as **subtle bands** around price (depth = fraction of Average True Range). * If price **breaks** a density with volume above its moving average, the band **disappears** (“eaten”), which often precedes continuation. --- ## How to use — practical playbooks > Recommended chart: crypto or index futures, one to five minutes. Use **one hour** or **fifteen minutes** for the higher-timeframe bias. ### 1) Trend pullback scalp (continuation) 1. Enable **Only in trend** zones. 2. In an uptrend: wait for a pullback into a **Demand** zone that overlaps with VWAP or sits just below the Opening Range midpoint. 3. Look for **green bubbles** near the zone’s bottom or a fresh **density** under price. 4. Enter on a candle closing **back above the zone midline**. 5. Stop-loss: below the bottom of the zone or a small multiple of Average True Range. 6. Targets: previous swing high, Opening Range high, fixed risk multiples, or VWAP. Mirror the logic for downtrends using Supply zones, red bubbles and densities above price. ### 2) Reversion with liquidity sweep (fade) 1. Bias neutral or countertrend allowed. 2. Price **wicks through** a zone boundary (or an Opening Range line) and **closes back inside** the zone. 3. The bubble color often flips (absorption). 4. Enter toward the **inside** of the zone; stop beyond the sweep wick; first target = zone midline, second = opposite side of the zone or VWAP. ### 3) Opening Range break and retest 1. Wait for the Opening Range to complete. 2. A break with a large bubble suggests intent. 3. Look for a **retest** into a nearby zone aligned with VWAP. 4. Trade continuation toward the next zone or the session extremes. ### 4) Density “eaten” continuation 1. When a density band **disappears** on high volume, it often means the resting liquidity was consumed. 2. Trade in the direction of the break, toward the nearest opposing zone. --- ## Settings — quick guide **Core** * *ATR Length* — used for zone and density depths. * *Show VWAP / Show Opening Range*. * *Opening Range*: Auto (multiple of timeframe minutes) or Manual minutes. **Trend Filter** * *Mode*: Off, EMA only, or EMA with ADX strength. * *Use higher timeframe* and its value. * *EMA Fast / EMA Slow*, *ADX Length*, *ADX threshold*. * *Plot EMA filter* to display the moving averages. **Zones (two pairs)** * *Pivot A Left / Right* and *Pivot B Left / Right*. * *Zone depth × ATR*, *Extend bars*. * *Show zone midline*, *Only in trend zones*. * Labels automatically show the touch counters. **Bubbles** * *Show Bubbles*. * *Quantile lookback* and *Quantile percent* (higher percent = stricter filter, fewer bubbles). **Densities** * *Metric*: absolute delta proxy or raw volume. * *Quantile lookback / percent*. * *Depth × ATR*, *Extend bars*, *Merge distance* (in ATR), * *Break condition*: volume moving average length and multiplier, * *Midline for densities* (optional dashed line). --- ## Tips and risk management * This script **does not use external order-flow feeds**. Delta is a **proxy** suitable for TradingView; tune quantiles per symbol and timeframe. * Do not trade every bubble. Combine **context (trend + VWAP + Opening Range)** with **level (zone)** and **effort (bubble/density)**. * Set stop-losses beyond the zone or at a fraction of Average True Range. Predefine risk per trade. * Backtest your rules with a strategy script before using real funds. * Markets differ. Parameters that work on Bitcoin may not transfer to low-liquidity altcoins or stocks. * Nothing here is financial advice. Scalping is high-risk; slippage and over-trading can quickly damage your account. --- ## What makes PRO Scalper unique * Two **independent** zone engines run in parallel, so you can see both **larger structure** and **fine intraday levels** at the same time. * Clean **“only in trend” rendering** — zones and midlines against the bias can be hidden, reducing clutter and hesitation. * **Touch counters** convert “feel” into numbers. * **Self-contained order-flow visuals** (bubbles and densities) that require no extra data sources. * Careful defaults: subtle colors for densities, clearer zones, and responsive auto Opening Range. --- (RU) ## Что это такое **PRO Scalper** — это индикатор для внутридневной торговли, который показывает **контекст и ликвидность прямо сейчас**. Он объединяет пять модулей, которыми профессиональные скальперы пользуются вместе: 1. **VWAP** — средневзвешенная по объему цена за сессию, «справедливая стоимость» дня. 2. **Opening Range** — первая часть сессии, задающая баланс дня. 3. **Фильтр тренда** — направление старшего таймфрейма по **экспоненциальным средним** и при желании по силе тренда **Average Directional Index**. 4. **Две независимые системы зон спроса/предложения** — зоны строятся от подтвержденных экстремумов (пивотов), имеют **среднюю линию** и **счетчик касаний**. 5. **Визуализация «ордер-флоу»**: * **Пузыри дельты** (зеленые/красные круги) — места повышенного покупательного/продажного давления, рассчитанные через безопасный **прокси-дельты**. * **Плотности ликвидности** (ненавязчивые прямоугольные ленты) — скопления объема, которые нередко притягивают цену или удерживают ее и исчезают, когда «разъедаются» сильным движением. Итог — **полная картинка момента**: среднее (VWAP), баланс дня (Opening Range), старшая сила (фильтр тренда), ближайшие уровни топлива/тормозов (зоны), текущие точки усилия (пузыри и плотности). --- ## Почему именно эти элементы * **VWAP** показывает, где сосредоточена стоимость; цена либо вращается вокруг него, либо быстро уходит — идеальный ориентир скальпера. * **Opening Range** фиксирует ранний аукцион — от его границ часто начинаются пробои, возвраты и ретесты. * **EMA + ADX** отделяют тренд от «пилы», позволяя оставлять на графике только зоны по направлению старшего таймфрейма. * **Зоны от пивотов** просты, объективны и быстры; средняя линия помогает подтверждать разворот, счетчик касаний переводит субъективность в цифры. * **Пузыри и плотности** добавляют слой «усилия»: где именно возник толчок и где сконцентрирована ликвидность. Комбинация **контекста + уровня + усилия** уменьшает двусмысленность и ускоряет принятие решения. --- ## Как это работает (простыми словами) * **VWAP** каждый день стартует заново: сумма «типичной цены × объем» делится на суммарный объем. * **Opening Range** — автоматический (кратный минутам вашего таймфрейма) или вручную заданный период; пока он формируется, фиксируются максимум и минимум. * **Фильтр тренда** * Две экспоненциальные средние задают направление. * **ADX** (по желанию) добавляет «силу». Источник можно взять со старшего таймфрейма. * **Зоны** * Одновременно работает **две пары** пивотов (например 10-лево 10-право и 5-лево 5-право). * От пивота строится зона **предложения** (от максимума) или **спроса** (от минимума). Глубина зоны = **коэффициент × Average True Range**; зона тянется вперед. * Внутри рисуется **средняя линия** (по желанию). * Режим **«только по тренду»** скрывает зоны против старшего направления. * **Счетчик касаний** увеличивается, когда цена снова входит в зону; подпись показывает пару и количество касаний. * **Пузыри** * Используется безопасный **прокси-дельты** — измерение «напряжения» внутри свечи. * Через **квантильный фильтр** выводятся только необычно сильные места: настраиваются окно и процент квантиля; размер кружка — сила, цвет: зеленый покупатели, красный продавцы. * **Плотности** * Крупные активности отмечаются **ненавязчивыми прямоугольниками** (глубина — доля Average True Range). * Если плотность **пробивается** объемом выше среднего, она **исчезает** — часто это предвещает продолжение. --- ## Как пользоваться — практические схемы > Рекомендация: крипто или фьючерсы, таймфрейм 1–5 минут. Для старшего фильтра удобно взять **1 час** или **15 минут**. ### 1) Скальп на откат по тренду 1. Включите **«только по тренду»**. 2. В восходящем тренде дождитесь отката в **зону спроса**, желательно рядом с **VWAP** или серединой **Opening Range**. 3. Подтверждение — **зеленые пузыри** у нижней границы зоны или свежая **плотность** под ценой. 4. Вход после закрытия свечи **выше средней линии** зоны. 5. Стоп-лосс: за нижнюю границу зоны или небольшой множитель Average True Range. 6. Цели: предыдущий максимум, верх Opening Range, фиксированные R-множители, либо VWAP. Для нисходящего тренда зеркально: зоны предложения, красные пузыри и плотности над ценой. ### 2) Контрдвижение с «выбиванием ликвидности» 1. Нейтральный или контртрендовый режим. 2. Цена **выносит хвостом** границу зоны (или линию Opening Range) и **закрывается обратно внутри**. 3. Цвет пузыря часто меняется (поглощение). 4. Вход внутрь зоны; стоп — за хвост выбивания; цели: средняя линия, противоположная граница зоны или VWAP. ### 3) Пробой Opening Range + ретест 1. Дождитесь завершения диапазона. 2. Сильный пробой с крупным пузырем — признак намерения. 3. Ищите **ретест** в зоне по тренду рядом с линией диапазона и VWAP. 4. Торгуйте продолжение к следующей зоне. ### 4) Продолжение после «съеденной» плотности 1. Когда прямоугольник плотности **исчезает** на повышенном объеме, это значит, что ликвидность поглощена. 2. Торгуйте в сторону пробоя к ближайшей противоположной зоне. --- ## Настройки — краткая шпаргалка **Core** — Длина Average True Range (для размеров зон и плотностей). — Включение VWAP и Opening Range. — Длина Opening Range: автоматическая (кратная минутам ТФ) или ручная. **Trend Filter** — Режим: выкл., только средние, либо средние + ADX. — Источник со старшего таймфрейма и его значение. — Длины средних, длина ADX и порог силы. — Показать/скрыть линий средних. **Zones (две пары одновременно)** — Пара A: лев/прав; Пара B: лев/прав. — Глубина зоны × Average True Range, продление по барам. — Средняя линия, режим **«только по тренду»**. — Подписи со счетчиком касаний. **Bubbles** — Вкл./выкл., окно поиска и процент квантиля (чем выше процент — тем реже пузыри). **Densities** — Метрика: абсолютная прокси-дельты или чистый объем. — Окно/квантиль, глубина × Average True Range, продление, — Порог объединения (в Average True Range), — Условие «разъедания» по объему, — Средняя линия плотности (по желанию). --- ## Советы и риски * Индикатор **не использует внешние потоки ордер-флоу**. Дельта — **прокси**, подходящая для TradingView; подбирайте квантили под инструмент и таймфрейм. * Не торгуйте каждый пузырь. Склейте **контекст (тренд + VWAP + Opening Range)** с **уровнем (зона)** и **усилием (пузырь/плотность)**. * Стоп-лосс — за границей зоны или по Average True Range. Риск на сделку задавайте заранее. * Перед реальными деньгами протестируйте правила в стратегии. * Разные рынки ведут себя по-разному; настройки из Биткоина могут не подойти малоликвидным альткоинам или акциям. * Это не инвестиционная рекомендация. Скальпинг — высокий риск; проскальзывание и переизбыток сделок быстро наносят ущерб капиталу. --- ## Чем уникален PRO Scalper * Две **одновременные** системы зон показывают и **крупную структуру**, и **точные локальные уровни**. * Режим **«только по тренду»** чистит экран от лишних уровней и ускоряет решение. * **Счетчики касаний** дают количественную опору. * **Самодостаточные визуализации усилия** (пузыри и плотности) — без сторонних источников данных. * Аккуратная цветовая схема: плотности — мягко, зоны — ясно; Opening Range — адаптивный. Пусть он станет вашей «картой местности» для быстрых и дисциплинированных решений внутри дня.
Penunjuk Pine Script®
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