Empiece

Herramientas de Pine

SolQuant WatermarkSignificance The SolQuant Watermark is a layout management utility designed to improve chart ergonomics by organizing metadata into a persistent UI layer. By utilizing the Pine Script table functions, the tool ensures that essential contextual data remains anchored to the display area, preventing visual clutter during historical price action analysis. Calculations & Methodology Unlike standard labels or drawing objects which are anchored to specific price-time coordinates, this utility utilizes the Table API . Coordinate Independence: The table logic renders objects relative to the screen dimensions rather than the price scale. This ensures the information remains visible regardless of vertical or horizontal scrolling. Dynamic Metadata Injection: The script utilizes built-in variables ( syminfo.tickerid , timeframe.period ) to automatically update the UI with current asset data, ensuring data integrity across multiple chart layouts. Screen Real Estate Optimization: The layout engine uses an anchoring system (9-point grid) to prevent overlap with technical indicators or price action. Features 9-Point Anchor System: Allows for precision placement at any screen corner or center point to optimize workspace efficiency. Adaptive Scaling: Includes 5 pre-configured scale settings to maintain readability across various device resolutions. Visual Configuration: Full control over background opacity and border styles to align with specific "Dark Mode" or presentation philosophies. Usage Organization: Use the "Quote Text" field for internal notes or community identifiers. Contextual Awareness: Enable "Symbol Info" to keep track of assets and timeframes during multi-chart analysis sessions. Disclaimer This is a visual utility tool intended for chart organization. It does not provide trade signals or financial advice.
Indicador Pine Script®
por lost_sol_
Two MA Crossover with Buy/Sell Labels//@version=5 indicator("Two MA Crossover with Buy/Sell Labels", overlay=true) // === User Inputs === shortPeriod = input.int(10, title="Fast MA Period") longPeriod = input.int(100, title="Slow MA Period") maType = input.string("EMA", title="MA Type", options= ) // === Moving Average Function === ma(src, length) => maType == "EMA" ? ta.ema(src, length) : ta.sma(src, length) // === Calculate MAs === fastMA = ma(close, shortPeriod) slowMA = ma(close, longPeriod) // === Plot MAs === plot(fastMA, title="Fast MA", linewidth=2, color=color.green) plot(slowMA, title="Slow MA", linewidth=2, color=color.red) // === Crossover Conditions === buySignal = ta.crossover(fastMA, slowMA) sellSignal = ta.crossunder(fastMA, slowMA) // === Buy Label === if buySignal label.new(bar_index, low, "BUY 🚀", style=label.style_label_up, textcolor=color.white, color=color.green) // === Sell Label === if sellSignal label.new(bar_index, high, "SELL 🔻", style=label.style_label_down, textcolor=color.white, color=color.red)
Indicador Pine Script®
por johnwireko79
2/6 SOL 30M Sharp 3.04Excellent system, surpassing 90% of automated trading systems on the market! Backtesting Period: 2024/1/1 - 2026/2/5 Product: SOLUSDT.P (Perpetual Contract) Period: 30 minutes Total Trades: 4453 Sharpe Ratio: 3.045 (Excellent) Maximum Equity Backtesting Return: 13.84% Profitability Factor: 1.79 Winning Trades: 77.21% 120-Day Backtesting Return (No Leverage): 90% Recommended Leverage: 5x Liquidation Distance from Current Price: 20% Backtesting Forced Liquidation: 1.75% (Maximum Loss per Trade) Some may not understand why 1.75% is the maximum loss, thinking that even slight fluctuations would trigger forced liquidation. Actually, no! The biggest difference between this system and other systems lies in its 30-minute trading timeframe (one order per candlestick; if the trend spans eight candlesticks, eight orders will be placed to maximize profits and prevent pullbacks). (Order Logic) ✅ Long positions (buying) are entered when a trend is about to begin. These signals must be met simultaneously (you can think of it as seven green lights flashing at the same time): 1. Price breaks through the upper trendline (breaks through an "upper boundary line") 2. The trend is strong enough (bullish power > bearish power) 3. In an upward trend (SAR below the price) 4. Moving average momentum is upward (T3 is turning upward) 5. Strong momentum (RSI > 63) 6. Positive momentum (MACD histogram > 0) 7. Relatively low trading volume (volume > half of the 30-day moving average) 👉 In short: Breakout + Strong Trend + Strong Momentum + Excessive Volume → Only buy. ✅ Short selling (selling) complete mirror image: Break below the lower rail + stronger bearish momentum + downward momentum + weak RSI + volume exceeding the threshold → only sell.
Estrategia Pine Script®
por w919339492
Two MA Crossover with Buy/Sell Labels//@version=5 indicator("Two MA Crossover with Buy/Sell Labels", overlay=true) // === User Inputs === shortPeriod = input.int(10, title="Fast MA Period") longPeriod = input.int(100, title="Slow MA Period") maType = input.string("EMA", title="MA Type", options= ) // === Moving Average Function === ma(src, length) => maType == "EMA" ? ta.ema(src, length) : ta.sma(src, length) // === Calculate MAs === fastMA = ma(close, shortPeriod) slowMA = ma(close, longPeriod) // === Plot MAs === plot(fastMA, title="Fast MA", linewidth=2, color=color.green) plot(slowMA, title="Slow MA", linewidth=2, color=color.red) // === Crossover Conditions === buySignal = ta.crossover(fastMA, slowMA) sellSignal = ta.crossunder(fastMA, slowMA) // === Buy Label === if buySignal label.new(bar_index, low, "BUY 🚀", style=label.style_label_up, textcolor=color.white, color=color.green) // === Sell Label === if sellSignal label.new(bar_index, high, "SELL 🔻", style=label.style_label_down, textcolor=color.white, color=color.red)
Indicador Pine Script®
por johnwireko79
keen ea Strategy Concept: Trend-Following Mean Reversion This is a hybrid strategy that combines: Trend identification (using AMA - Adaptive Moving Average) Money flow analysis (using CMF - Chaikin Money Flow) Dynamic support/resistance (using Stiffness indicator) Exit timing (using dual EMAs) 📊 Indicator Roles & Logic 1. Primary Trend Filter: Adaptive Moving Average (AMA) Purpose: Identifies the underlying trend direction while reducing lag during ranging markets Logic: AMA adjusts its sensitivity based on market volatility (Efficiency Ratio) Configuration: Fast EMA (56-68): Reacts quickly to price changes Slow EMA (99-110): Provides stable trend direction ER Period (84): Measures market efficiency/trend strength 2. Entry Signal: Chaikin Money Flow (CMF) Purpose: Confirms entries with volume-based momentum Logic: Measures buying/selling pressure by comparing close price to daily range, weighted by volume Configuration: Length (59-60): Medium-term money flow analysis Entry Rule: CMF crossing above/below zero or specific thresholds 3. Dynamic Support/Resistance: Stiffness Indicator Purpose: Identifies potential reversal zones where price movement "stiffens" Logic: Measures the rate of price change slowdown (similar to momentum deceleration) Configuration: Stiffness Length (59-60): Lookback period for stiffness calculation Smoothing Length (15-17): Smoothes the stiffness signal Threshold (60): Trigger level for trade signals 4. Exit System: Dual EMA Crossover Purpose: Manages exits and trail stops Logic: Fast Exit EMA (40): Quick exit signal Slow Exit EMA (159-160): Confirms exit direction Exit Rule: Fast EMA crosses below Slow EMA (for longs)
Estrategia Pine Script®
por Klajdikaja
Phoenix: Iron Fortress [Trend Engine] v3.20 CNTitle: Phoenix: Iron Fortress v3.20 (Targeting Mod) Core Philosophy: "Virtualize the easy wins, Strike only on reversals." This strategy uses a unique Targeting Systemto filter out noise. It skips "easy" trends to save fees and only commits real capital when a true reversal structure is confirmed. Key Features: 1. 🎯 Virtual Entry (Targeting): Signals trigger a "Targeting State" instead of a real trade.  ✅ Virtual Win: If price drops to TP immediately -> Reset. (Profit captured virtually, 0 fees).  🔫 Real Release: Real entry fires ONLY if the trend goes against us (Accumulate) and then reverses (Down). 2. 🌐 Dual Trend Engine: Separate logic for DCA (Hull MA/Gaussian) to catch entries, and TP (VWAP) to ride trends. 3. 👻 Ghost DCA: Accumulates positions virtually during Targeting. When "Released", you enter with an optimized average price. Visual Guide:  🎯 Targeting Start | ➕ Virtual Accumulation | ✅ Virtual Win (No Trade)  🔫 FIRE (Real Entry) | 💰 Real TP Best For: Traders who hate paying fees for small chops and want to snipe high-probability reversals.
Estrategia Pine Script®
por ytj15348076666
MoonRush V2📌 MoonRush V2 – Trend, EMA, ATR & RSI Toolkit MoonRush V2 is a technical analysis indicator designed to help traders visualize market trend, volatility-based price zones, RSI extremes, and trade planning levels by combining multiple analytical tools into a single, configurable indicator. This indicator is for educational and analytical purposes only. It does not provide financial advice or guarantee trading results. 🔹 1. EMA Trend System MoonRush V2 uses a dual EMA system as its primary trend detection method: Fast EMA (default: 38) Slow EMA (default: 62) Optional EMA smoothing to reduce market noise Trend Definition Bullish Trend: Fast EMA crosses above Slow EMA Bearish Trend: Fast EMA crosses below Slow EMA If no crossover occurs, the previous trend state is maintained The indicator can optionally: Color EMA lines Color price bars Apply background shading Fill the area between EMAs All visual elements can be enabled or disabled via the ALL SWITCH panel. 🔹 2. Trend Visualization To improve chart readability: Green color represents bullish conditions Red color represents bearish conditions “BULL” and “BEAR” labels appear on EMA crossovers This allows traders to quickly identify the prevailing market direction. 🔹 3. River System (ATR-Based Zones) The River System is a volatility-based price zone framework built using: An EMA as the central reference line Long-period ATR to reflect broader market volatility The system generates: Support levels: S1 / S2 / S3 Resistance levels: R1 / R2 / R3 These levels are displayed as filled zones: Green zones indicate support areas Red zones indicate resistance areas They are intended to highlight areas where price may react or consolidate. 🔹 4. RSI Extreme Visualization MoonRush V2 integrates RSI analysis to identify extreme market conditions: Multiple Oversold levels (e.g., 20 / 30 / 40) Multiple Overbought levels (e.g., 60 / 70 / 80) When RSI reaches extreme values: Diamond and circular markers appear Signals are aligned with outer River levels (S3 / R3) This helps visualize potential exhaustion or pullback zones. 🔹 5. Overbought / Oversold Area Boxes When RSI remains: Above the Overbought threshold → a red price box is drawn Below the Oversold threshold → a green price box is drawn These boxes dynamically expand based on price highs and lows, highlighting price regions associated with RSI extremes directly on the chart. 🔹 6. Multi-Timeframe Trend Dashboard A built-in table displays trend and RSI information across multiple timeframes: Chart timeframe 1m / 5m / 15m / 30m 1h / 4h / 1D For each timeframe, the table shows: Trend direction (Bullish / Bearish) based on EMA alignment RSI value Color coding: Green background = RSI above 50 Red background = RSI below 50 This feature supports top-down and multi-timeframe analysis. 🔹 7. Entry Reference (EMA Crossover) Reference signals are generated when: EMA crossover occurs → BUY reference EMA crossunder occurs → SELL reference These signals are visual references only and are not automated trade orders. 🔹 8. TP / SL Projection (ATR-Based) The indicator can project potential trade management levels using ATR: Entry reference price Take Profit levels (TP1 / TP2 / TP3) Optional Stop Loss level All levels are volatility-adjusted and extend forward on the chart to assist with risk and reward planning. 🔹 9. Event & Statistics Table MoonRush V2 includes an informational event table that tracks: Number of signals generated per day Win / Loss outcomes (based on TP or SL interactions) Daily win rate Drawdown of the most recent signal Maximum drawdown for the day The data resets automatically each day and is displayed as a readable message table on the chart. ⚠️ Disclaimer MoonRush V2 is a technical analysis tool for educational use only. It does not constitute financial advice or investment recommendations. Users should test, adjust parameters, and manage risk according to their own strategy.
Indicador Pine Script®
por mooniexofficials
COT - Extreme Zones (Auto + FX/Metals/Crypto Dropdown)This indicator turns COT positioning into an easy-to-read oscillator that helps you track when market participants may be reaching positioning extremes. It pulls Commercial Long/Short and Non-Commercial Long/Short from COT reports, computes their net positions, and builds a divergence series (Commercial Net – Non-Commercial Net). That divergence is then normalized into a 0–100 index using a rolling Min/Max window (52/156/260 weeks are common choices). Why it’s useful COT extremes can highlight when positioning becomes one-sided. This tool helps you spot those moments quickly via clear, color-coded extreme zones—ideal for timing watchlists, mean-reversion setups, or adding context to trend trades. Modes Auto (chart): maps the correct COT/CFTC code automatically from the current chart symbol Dropdown selection: choose major FX currencies and (where available) Gold (XAU), Silver (XAG), and Bitcoin (BTC) Extras Adjustable extreme thresholds (default 80/20) Optional raw divergence in the data window Optional on-chart label showing the selected CFTC mapping
Indicador Pine Script®
por trademvment
MoonFlow SMCMoonFlow SMC An all-in-one Smart Money Concept (SMC) toolkit, combining essential SMC components into a single indicator. MoonFlow SMC is designed to help traders better visualize market structure and liquidity behavior through a clean, systematic, and easy-to-read presentation that minimizes chart clutter. 🔍 Key Features 🟦 Dynamic Demand / Supply Zones Automatically detects Supply & Demand zones from swing highs and lows Prevents unnecessary overlapping zones Clearly distinguishes Break of Structure (BOS) from Liquidity Sweeps 📈 SMC Signals (BOS-based) Displays LONG / SHORT signals only when a valid BOS occurs Liquidity sweeps are not used as entries to reduce false signals Designed to support and complement the trader’s own analysis 🎯 TP / SL System (ATR-based) Automatically calculates TP1 / TP2 / TP3 and SL using ATR Draws real-time lines and labels directly on the chart Applies only to entries generated by SMC conditions 📊 Performance Panel (SMC Event Table) Displays: Total number of orders Win / Loss count Win rate (Daily / Weekly / Monthly) Drawdown per order and per day Useful for system review and trading discipline evaluation 🔥 Trend Heat Gauge Measures price strength within the High–Low range (normalized 0–100) Presented as an intuitive gauge Helps assess market momentum and overall context 🟩 OVB / OVS Zones (RSI-based) Highlights Overbought / Oversold areas directly on the price chart Provides instant insight into market strength or consolidation phases 📐 Daily OHLC + Previous High / Low Displays current day Open / High / Low / Close Shows previous day High and Low Suitable for intraday trading and liquidity mapping 🎛️ Fully Customizable Enable or disable each module independently Adjust colors, label sizes, line styles, and logo position Designed to work alongside other indicators without clutter ⚠️ Disclaimer MoonFlow SMC is an analysis tool only. It is not an automated trading system and does not guarantee any results. Users should always manage risk appropriately and make their own trading decisions.
Indicador Pine Script®
por mooniexofficials
Seasonality-by-Atrader Seasonality Extended – Enhanced Historical Monthly Pattern Analysis This script is a comprehensive extension of the original Seasonality concept, designed to analyze historical monthly returns of any asset on TradingView. It introduces advanced filtering, visualization, and usability features that significantly expand upon the capabilities of the original version. Overview The script calculates month-over-month percentage changes for each year, starting from a user-defined year. Results are displayed both on the chart as projected return boxes and in a data-rich heatmap table that highlights monthly trends, average returns, standard deviation, and the percentage of positive months. Key Enhancements Year-Based Filtering Users can selectively include: Only years ending in specific digits (e.g., 1, 3, 7) Only every n-th year (e.g., every 4th year from a reference year) Both filters can be combined for precise cycle isolation Exclusion of Irregular Periods Specific months can be excluded from the analysis using a date-based input (e.g., 2008-10, 2020-03) This allows users to remove outliers or crisis periods from historical performance data Enhanced Heatmap Display Adapts to year filters automatically Resizable via input fields for width and height Table can be positioned (left, center, or right) Optional summary rows for averages, standard deviations, and percentage of positive months Custom Color Configuration Separate color selection for positive and negative returns Customizable gradient intensity threshold Asset Compatibility Works across all TradingView-supported asset classes (stocks, indices, futures, crypto, forex) Supports multi-decade data where available (e.g., TVC:DXY from the 1970s) On-Chart Seasonality Projection Displays expected return zones for the current month based on historical data Shows projected price range and statistical context (standard deviation, sample size) Use Cases Analyzing recurring seasonal behavior Isolating macro or election-cycle influences Informing strategic trade planning based on historical patterns Limitations Table size is adjusted via inputs only (no mouse drag-resize) Analysis is based on monthly timeframes exclusively Chart object count is limited by TradingView’s standard restrictions Summary This script offers a refined and practical approach to seasonality analysis by enabling deep historical filtering, cycle-specific inclusion, and comprehensive tabular and visual output. It is tailored for analysts and traders looking to integrate long-term seasonal tendencies into their decision-making framework.
Indicador Pine Script®
por trademvment
ETH 1HR backtested Sharpe ratio 1.9Backtesting Data Conclusions: Backtesting Period: 2023-01-01 ~ 2026-02-04 Initial Capital: 100 USDT Net Profit: +941.03 USDT (approx. +941%) Buy & Hold Profit: +71.25 USDT (approx. +71%) → The strategy significantly outperformed buy & hold (within the same period). Maximum Net Value Drawdown: 20.44% (Closing-to-Closing) Profit Factor: 2.074 Sharpe Ratio: 1.924 Total Trades: 2257 Win Rate: 86.71% (1957 profitable trades / 300 losing trades) Long Position Net Profit: +425.45; Short Position Net Profit: +515.57 → Profitable on both long and short positions, with short positions contributing more. This data set is a relatively impressive combination within the "high-frequency strategy" framework: high win rate + profit factor > 2 + drawdown of approximately 20% + Sharpe ratio close to 2. Trading timeframe: 1 hour Suggested leverage: 4-5x Suggested trading instruments: DOGE (backtested Sharpe ratio 1.0); SOL (backtested Sharpe ratio 0.9); ETH (backtested Sharpe ratio 1.9);
Estrategia Pine Script®
por w919339492
QUANTA - LAB GARCHInstitutional volatility modeling suite with GARCH estimation, VaR/CVaR risk metrics, and Basel III backtesting. Models Available: GARCH(1,1) — symmetric volatility clustering GJR-GARCH(1,1) — asymmetric leverage effect EGARCH(1,1) — log-variance specification Risk Metrics: VaR (95%/99%) with Student-t fat tails CVaR/Expected Shortfall (coherent risk measure) Multi-horizon VaR (1d, 5d, 10d) with persistence-adjusted scaling DoF estimation via method of moments (±15-25% uncertainty) Backtesting (Basel III Compliant): Kupiec unconditional coverage test Christoffersen independence test Traffic light system (Green/Yellow/Red zones) Diagnostics: ARCH-LM test for residual effects AIC/BIC information criteria Structural break detection (CUSUM-based) Jump/outlier detection Model confidence score (0-100) V3.6 Improvements: Adaptive grid search (~60% faster) High persistence warning (p > 0.98) Persistence-adjusted multi-horizon scaling (better than √T) Dashboard Includes: Real-time conditional volatility (annualized) Parameter estimates (α, β, γ, θ) Persistence and half-life Regime classification (Normal/Elevated/Crisis) Important: Grid search produces point estimates (no confidence intervals) Parameters may differ ±3-5% from true MLE NOT for illiquid assets or significant overnight gaps Screening tool only — validate with Python arch / R rugarch References: Bollerslev (1986), Nelson (1991), GJR (1993), Engle (1982), McNeil et al. (2015), Kupiec (1995), Christoffersen (1998)
Indicador Pine Script®
por CUIRIZQUANTLAB
QUANTA - LAB HMM REGIME DETECTION Two-state Hidden Markov Model for market regime detection based on Hamilton (1989) Markov-Switching framework. Methodology: Full Baum-Welch EM algorithm in log-space for numerical stability Real-time Hamilton filtering (no lookahead) for trading use Kim smoothing for historical analysis Multiple random restarts to avoid local optima Regime Classification: Mean-based: R1 = Bearish (lower μ), R2 = Bullish (higher μ) Volatility-based: R1 = Calm (lower σ), R2 = Turbulent (higher σ) Key Features: TRADING vs ANALYSIS mode (filtered vs smoothed probabilities) Gaussian assumption diagnostics (kurtosis, skewness, outliers) Data Quality Score (0-100) Regime Certainty Index (RCI) Mean separation t-statistic Expected regime duration and ergodic probabilities Degenerate model detection Dashboard Includes: Filtered probabilities (real-time, safe for trading) Emission parameters (μ₁, μ₂, σ₁, σ₂) Transition matrix (p₁₁, p₂₂) Model fit metrics (LogL, AIC, BIC) Critical Warnings: Smoothed ≠ Real-time (smoothed uses future info) Gaussian assumption: fat tails not captured K=2 regimes only — may oversimplify dynamics NOT for high-frequency (minimum 1H timeframe) Validate with Python hmmlearn / R / MATLAB References: Hamilton (1989) — Econometrica
Indicador Pine Script®
por CUIRIZQUANTLAB
QUANT - LAB ADF-GLS + COINT + VRT-WB [ERS] ADF-GLS + COINT + VRT-WB V9.2 INSTITUTIONAL Institutional-grade econometric suite for unit root testing, cointegration analysis, and mean-reversion detection. Unit Root Tests: ADF-GLS (Elliott, Rothenberg & Stock, 1996) with MAIC lag selection Phillips-Perron Z_t with Newey-West correction KPSS stationarity test (confirmatory) MZ-alpha test Cointegration (Bivariate): Engle-Granger two-step test (MacKinnon 2010 critical values) Johansen Trace test (Osterwald-Lenum 1992 CVs) Real-time spread Z-score with tick-by-tick updates Mean-Reversion: Variance Ratio Test (Lo-MacKinlay 1988) Mammen Wild Bootstrap for heteroskedasticity robustness Half-life estimation with 95% CI (delta method) Diagnostics: Ljung-Box Q(4) for residual autocorrelation ARCH(4) test for heteroskedasticity HAC standard errors (Newey-West) Important: Screening tool only — validate in Python/R/statsmodels Beta SE is BIASED (generated regressor problem) Johansen limited to bivariate systems Bootstrap p-value resolution ~2-5% NOT a trading system References: ERS (1996), Lo & MacKinlay (1988), Engle & Granger (1987), Johansen (1988), MacKinnon (2010)
Indicador Pine Script®
por CUIRIZQUANTLAB
FRACTAL-LAB Advanced fractal analysis suite for detecting market memory and deviations from random walk behavior. Features: Hurst Exponent proxy via variance scaling with dynamic confidence intervals DFA-Lite (two-scale Detrended Fluctuation Analysis) Lo-MacKinlay Variance Ratio test Volatility memory analysis on |returns| Quality scoring system (A-F grades) Regime classification: Persistent / Random Walk / Anti-Persistent Interpretation: H > 0.55 → Trending behavior (momentum) H ≈ 0.50 → Random walk (no predictability) H < 0.45 → Mean-reverting behavior Important: Screening tool only — validate results in Python/R Does not test for short-range dependence (Lo, 1991) Recommended sample size: N ≥ 300 bars NOT a trading system — for research and education only References: Hurst (1951), Lo & MacKinlay (1988), Peng et al. (1994)
Indicador Pine Script®
por CUIRIZQUANTLAB