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Every Hour 1st/Last FVG vTDL OVERVIEW - Shoutout to Micheal J. Huddleston aka ICT This indicator identifies the first Fair Value Gap (FVG) that forms within each trading hour, providing traders with potential entry zones, reversal points, and unmitigated gap targets. Based on the concept that the first presented FVG of each hour represents a significant price delivery array where institutional order flow occurred. The indicator detects FVGs on a lower timeframe (1-minute default) and displays them as boxes on your chart, tracking which gaps get filled and which remain open as potential draw-on-liquidity targets. WHAT IS A FAIR VALUE GAP A Fair Value Gap is a 3-candle price pattern representing an imbalance between buyers and sellers: Bullish FVG: Forms when candle 3's low is above candle 1's high, leaving a gap Bearish FVG: Forms when candle 3's high is below candle 1's low, leaving a gap These gaps often act as magnets for price, which tends to return and "fill" the imbalance before continuing. They function as dynamic support and resistance zones. KEY FEATURES Detection Types FVG: Standard fair value gap detection with volume imbalance expansion Suspension FVG Blocks: Requires outside prints on both sides for more refined signals Hourly Display Modes First Only: Shows whichever FVG appears first each hour (bullish or bearish) Show Both: Shows first bullish AND first bearish FVG independently each hour Last FVG Tracking Optionally display the last FVG of each hour Useful for comparing how the hour developed Can extend into the next hour for continued tracking Breakaway Gap Detection Gaps not traded into during their formation hour extend forward Extended gaps display labels showing formation time and date These unmitigated gaps become price targets and reversal zones Gap Fill Modes Touch Box: Marks filled when price enters the gap Touch Midpoint: Marks filled when price reaches the 50 percent level Fill Completely: Marks filled when price fills the entire gap with visual progress HOW TO USE Entry Points The first FVG of each hour provides potential entry zones based on price reaction: When price returns to an FVG and shows rejection, enter in the direction of rejection The gap zone represents where institutional orders likely reside Use the boundaries of the gap for stop loss placement A clean rejection of the zone confirms it as valid support or resistance Reversal Points Unmitigated gaps that extend beyond their formation hour are high-probability reaction zones: Extended boxes with labels indicate unfilled gaps When price finally reaches these zones, expect a reaction The longer a gap remains unfilled, the stronger the expected response These zones act as magnets drawing price back to them Price Targets Use unmitigated gaps as draw-on-liquidity targets: Look for extended boxes above or below current price Price tends to seek out and fill imbalances The midpoint line often serves as a minimum target Multiple unfilled gaps in one direction suggest strong momentum potential FRAMING DIRECTIONAL BIAS The first presented FVG of each hour acts as a support or resistance zone. The direction of the FVG itself does not determine bias - it is how price reacts to that FVG that reveals the true market intention. Reading Price Reaction Price respects a bullish FVG as support and bounces higher = bullish bias confirmed Price respects a bearish FVG as resistance and rejects lower = bearish bias confirmed Price fails to hold a bullish FVG and breaks through = potential inversion, look for shorts Price fails to hold a bearish FVG and breaks through = potential inversion, look for longs Inversion Fair Value Gaps (IFVG) When price trades through an FVG and closes beyond it, that gap can invert its role: A bullish FVG that fails becomes resistance - use it as a short entry zone A bearish FVG that fails becomes support - use it as a long entry zone The inversion signals a shift in control from one side to the other Watch for price to retest the inverted gap before continuing Support and Resistance Framework Think of each hourly first FVG as a key level: Price above the FVG: the gap acts as potential support Price below the FVG: the gap acts as potential resistance Watch how price behaves when it returns to the gap zone A clean rejection confirms the level; a break through signals inversion SHORT-TERM SCALPING APPLICATION These FVGs provide scalping opportunities each hour: Identify the first FVG of the hour as your key level Wait for price to trade away from it and return Observe the reaction at the gap zone Enter in the direction of the reaction with tight risk Target the next FVG, midpoint, or nearby liquidity Trade Management Use the opposite side of the FVG box as your stop loss zone The midpoint of the gap often provides first target or decision point Scale out at nearby unmitigated gaps or key levels If the gap inverts, flip your bias and look for entries in the new direction MULTI-HOUR CONTEXT If price consistently respects FVGs as support across hours = uptrend context If price consistently respects FVGs as resistance across hours = downtrend context If FVGs keep inverting = choppy or transitional market Use higher timeframe direction to filter which reactions to trade Compare first and last FVG of each hour to see how momentum developed SESSION FILTERING The indicator automatically excludes unreliable periods: 4 PM to 5 PM New York time (market close hours 16-17) Weekend closed periods (Saturday and Sunday before 6 PM) All timestamps use New York timezone for consistency with futures market hours. SETTINGS GUIDE Detection Settings Detection Type: Choose between standard FVG or Suspension FVG Blocks Lower Timeframe: 15 seconds, 1 minute, or 5 minutes for gap detection Min FVG Size: Minimum gap size in ticks to filter noise Display Settings Hourly Display Mode: First Only shows one gap per hour; Show Both shows first bull and bear Show First FVG: Toggle visibility of first FVG boxes Show Last FVG: Toggle visibility of last FVG boxes Show Midpoint Lines: Display the 50 percent level of each gap Show Unfilled Breakaway Gaps: Extend boxes until price fills them Show Only Today: Reduce clutter by hiding older hourly boxes Gap Fill Detection Mode Touch Box: Gap marked filled when price enters the zone Touch Midpoint: Gap marked filled when price reaches 50 percent level Fill Completely: Gap marked filled only when fully closed, shows visual fill progress Recommended Settings by Style Scalping: 1 minute LTF, 4 tick minimum, Show Both mode, Touch Box fill Day Trading: 1 minute LTF, 4-8 tick minimum, First Only mode, Touch Midpoint fill Swing Context: 5 minute LTF, Show Unfilled Gaps enabled, Fill Completely mode COLOR CODING Blue boxes: First bullish FVG of the hour Red boxes: First bearish FVG of the hour Green boxes: Last bullish FVG of the hour Orange boxes: Last bearish FVG of the hour Black midpoint lines: 50 percent level of each gap Filled portion overlay: Shows visual progress in Fill Completely mode All colors are fully customizable in the settings menu. PRACTICAL TIPS The first FVG of each hour is a hidden PD array - treat it as a significant level Not every gap produces a tradeable reaction - wait for confirmation Gaps that remain unfilled for multiple hours carry more weight Use the Show Both mode to see both bullish and bearish opportunities each hour When multiple gaps cluster in one zone, that area becomes even more significant Inversions are powerful signals - a failed level often leads to acceleration NOTES Works on any instrument and timeframe Best used on intraday charts (1 minute to 15 minute) viewing 1 minute LTF gaps Combine with higher timeframe analysis for confluence These are probability zones, not guarantees - always use proper risk management The indicator handles HTF to LTF data fetching automatically
Indicador Pine Script®
por Trades-Dont-Lie
2
RSI Forecast Colorful [DiFlip]RSI Forecast Colorful Introducing one of the most complete RSI indicators available — a highly customizable analytical tool that integrates advanced prediction capabilities. RSI Forecast Colorful is an evolution of the classic RSI, designed to anticipate potential future RSI movements using linear regression. Instead of simply reacting to historical data, this indicator provides a statistical projection of the RSI’s future behavior, offering a forward-looking view of market conditions. ⯁ Real-Time RSI Forecasting For the first time, a public RSI indicator integrates linear regression (least squares method) to forecast the RSI’s future behavior. This innovative approach allows traders to anticipate market movements based on historical trends. By applying Linear Regression to the RSI, the indicator displays a projected trendline n periods ahead, helping traders make more informed buy or sell decisions. ⯁ Highly Customizable The indicator is fully adaptable to any trading style. Dozens of parameters can be optimized to match your system. All 28 long and short entry conditions are selectable and configurable, allowing the construction of quantitative, statistical, and automated trading models. Full control over signals ensures precise alignment with your strategy. ⯁ Innovative and Science-Based This is the first public RSI indicator to apply least-squares predictive modeling to RSI calculations. Technically, it incorporates machine-learning logic into a classic indicator. Using Linear Regression embeds strong statistical foundations into RSI forecasting, making this tool especially valuable for traders seeking quantitative and analytical advantages. ⯁ Scientific Foundation: Linear Regression Linear regression is a fundamental statistical method that models the relationship between a dependent variable y and one or more independent variables x. The general formula for simple linear regression is: y = β₀ + β₁x + ε where: y  = predicted variable (e.g., future RSI value) x  = explanatory variable (e.g., bar index or time) β₀ = intercept (value of y when x = 0) β₁ = slope (rate of change of y relative to x) ε   = random error term The goal is to estimate β₀ and β₁ by minimizing the sum of squared errors. This is achieved using the least squares method, ensuring the best linear fit to historical data. Once the coefficients are calculated, the model extends the regression line forward, generating the RSI projection based on recent trends. ⯁ Least Squares Estimation To minimize the error between predicted and observed values, we use the formulas: β₁ = Σ((xᵢ - x̄)(yᵢ - ȳ)) / Σ((xᵢ - x̄)²) β₀ = ȳ - β₁x̄ Σ denotes summation; x̄ and ȳ are the means of x and y; and i ranges from 1 to n (number of observations). These equations produce the best linear unbiased estimator under the Gauss–Markov assumptions — constant variance (homoscedasticity) and a linear relationship between variables. ⯁ Linear Regression in Machine Learning Linear regression is a foundational component of supervised learning. Its simplicity and precision in numerical prediction make it essential in AI, predictive algorithms, and time-series forecasting. Applying regression to RSI is akin to embedding artificial intelligence inside a classic indicator, adding a new analytical dimension. ⯁ Visual Interpretation Imagine a time series of RSI values like this: Time → RSI    → The regression line smooths these historical values and projects itself n periods forward, creating a predictive trajectory. This projected RSI line can cross the actual RSI, generating sophisticated entry and exit signals. In summary, the RSI Forecast Colorful indicator provides both the current RSI and the forecasted RSI, allowing comparison between past and future trend behavior. ⯁ Summary of Scientific Concepts Used Linear Regression: Models relationships between variables using a straight line. Least Squares: Minimizes squared prediction errors for optimal fit. Time-Series Forecasting: Predicts future values from historical patterns. Supervised Learning: Predictive modeling based on known output values. Statistical Smoothing: Reduces noise to highlight underlying trends. ⯁ Why This Indicator Is Revolutionary Scientifically grounded: Built on statistical and mathematical theory. First of its kind: The first public RSI with least-squares predictive modeling. Intelligent: Incorporates machine-learning logic into RSI interpretation. Forward-looking: Generates predictive, not just reactive, signals. Customizable: Exceptionally flexible for any strategic framework. ⯁ Conclusion By combining RSI and linear regression, the RSI Forecast Colorful allows traders to predict market momentum rather than simply follow it. It's not just another indicator: it's a scientific advancement in technical analysis technology. Offering 28 configurable entry conditions and advanced signals, this open-source indicator paves the way for innovative quantitative systems. ⯁ Example of simple linear regression with one independent variable This example demonstrates how a basic linear regression works when there is only one independent variable influencing the dependent variable. This type of model is used to identify a direct relationship between two variables. ⯁ In linear regression, observations (red) are considered the result of random deviations (green) from an underlying relationship (blue) between a dependent variable (y) and an independent variable (x) This concept illustrates that sampled data points rarely align perfectly with the true trend line. Instead, each observed point represents the combination of the true underlying relationship and a random error component. ⯁ Visualizing heteroscedasticity in a scatterplot with 100 random fitted values using Matlab Heteroscedasticity occurs when the variance of the errors is not constant across the range of fitted values. This visualization highlights how the spread of data can change unpredictably, which is an important factor in evaluating the validity of regression models. ⯁ The datasets in Anscombe’s quartet were designed to have nearly the same linear regression line (as well as nearly identical means, standard deviations, and correlations) but look very different when plotted This classic example shows that summary statistics alone can be misleading. Even with identical numerical metrics, the datasets display completely different patterns, emphasizing the importance of visual inspection when interpreting a model. ⯁ Result of fitting a set of data points with a quadratic function This example illustrates how a second-degree polynomial model can better fit certain datasets that do not follow a linear trend. The resulting curve reflects the true shape of the data more accurately than a straight line. ⯁ What Is RSI? The RSI (Relative Strength Index) is a technical indicator developed by J. Welles Wilder. It measures the velocity and magnitude of recent price movements to identify overbought and oversold conditions. The RSI ranges from 0 to 100 and is commonly used to identify potential reversals and evaluate trend strength. ⯁ How RSI Works RSI is calculated from average gains and losses over a set period (commonly 14 bars) and plotted on a 0–100 scale. It consists of three key zones: Overbought: RSI above 70 may signal an overbought market. Oversold: RSI below 30 may signal an oversold market. Neutral Zone: RSI between 30 and 70, indicating no extreme condition. These zones help identify potential price reversals and confirm trend strength. ⯁ Entry Conditions All conditions below are fully customizable and allow detailed control over entry signal creation. 📈 BUY 🧲 Signal Validity: Signal remains valid for X bars. 🧲 Signal Logic: Configurable using AND or OR. 🧲 RSI > Upper 🧲 RSI < Upper 🧲 RSI > Lower 🧲 RSI < Lower 🧲 RSI > Middle 🧲 RSI < Middle 🧲 RSI > MA 🧲 RSI < MA 🧲 MA > Upper 🧲 MA < Upper 🧲 MA > Lower 🧲 MA < Lower 🧲 RSI (Crossover) Upper 🧲 RSI (Crossunder) Upper 🧲 RSI (Crossover) Lower 🧲 RSI (Crossunder) Lower 🧲 RSI (Crossover) Middle 🧲 RSI (Crossunder) Middle 🧲 RSI (Crossover) MA 🧲 RSI (Crossunder) MA 🧲 MA (Crossover)Upper 🧲 MA (Crossunder)Upper 🧲 MA (Crossover) Lower 🧲 MA (Crossunder) Lower 🧲 RSI Bullish Divergence 🧲 RSI Bearish Divergence 🔮 RSI (Crossover) Forecast MA 🔮 RSI (Crossunder) Forecast MA 📉 SELL 🧲 Signal Validity: Signal remains valid for X bars. 🧲 Signal Logic: Configurable using AND or OR. 🧲 RSI > Upper 🧲 RSI < Upper 🧲 RSI > Lower 🧲 RSI < Lower 🧲 RSI > Middle 🧲 RSI < Middle 🧲 RSI > MA 🧲 RSI < MA 🧲 MA > Upper 🧲 MA < Upper 🧲 MA > Lower 🧲 MA < Lower 🧲 RSI (Crossover) Upper 🧲 RSI (Crossunder) Upper 🧲 RSI (Crossover) Lower 🧲 RSI (Crossunder) Lower 🧲 RSI (Crossover) Middle 🧲 RSI (Crossunder) Middle 🧲 RSI (Crossover) MA 🧲 RSI (Crossunder) MA 🧲 MA (Crossover)Upper 🧲 MA (Crossunder)Upper 🧲 MA (Crossover) Lower 🧲 MA (Crossunder) Lower 🧲 RSI Bullish Divergence 🧲 RSI Bearish Divergence 🔮 RSI (Crossover) Forecast MA 🔮 RSI (Crossunder) Forecast MA 🤖 Automation All BUY and SELL conditions can be automated using TradingView alerts. Every configurable condition can trigger alerts suitable for fully automated or semi-automated strategies. ⯁ Unique Features Linear Regression Forecast Signal Validity: Keep signals active for X bars Signal Logic: AND/OR configuration Condition Table: BUY/SELL Condition Labels: BUY/SELL Chart Labels: BUY/SELL markers above price Automation & Alerts: BUY/SELL Background Colors: bgcolor Fill Colors: fill Linear Regression Forecast Signal Validity: Keep signals active for X bars Signal Logic: AND/OR configuration Condition Table: BUY/SELL Condition Labels: BUY/SELL Chart Labels: BUY/SELL markers above price Automation & Alerts: BUY/SELL Background Colors: bgcolor Fill Colors: fill
Indicador Pine Script®
por DiFlip
Regime [CHE] Regime — Minimal HTF MACD histogram regime marker with a simple rising versus falling state. Summary Regime is a lightweight overlay that turns a higher-timeframe-style MACD histogram condition into a simple regime marker on your chart. It queries an imported core module to determine whether the histogram is rising and then paints a consistent marker color based on that boolean state. The output is intentionally minimal: no lines, no panels, no extra smoothing visuals, just a repeated marker that reflects the current regime. This makes it useful as a quick context filter for other signals rather than a standalone system. Motivation: Why this design? A common problem in discretionary and systematic workflows is clutter and over-interpretation. Many regime tools draw multiple plots, which can distract from price structure. This script reduces the regime idea to one stable question: is the MACD histogram rising under a given preset and smoothing length. The core logic is delegated to a shared module to keep the indicator thin and consistent across scripts that rely on the same definition. What’s different vs. standard approaches? Reference baseline: A standard MACD histogram plotted in a separate pane with manual interpretation. Architecture differences: Uses a shared library call for the regime decision, rather than re-implementing MACD logic locally. Uses a single boolean output to drive marker color, rather than plotting histogram bars. Uses fixed marker placement at the bottom of the chart for consistent visibility. Practical effect: You get a persistent “context layer” on price without dedicating a separate pane or reading histogram amplitude. The chart shows state, not magnitude. How it works (technical) 1. The script imports `chervolino/CoreMACDHTF/2` and calls `core.is_hist_rising()` on each bar. 2. Inputs provide the source series, a preset string for MACD-style parameters, and a smoothing length used by the library function. 3. The library returns a boolean `rising` that represents whether the histogram is rising according to the library’s internal definition. 4. The script maps that boolean to a color: yellow when rising, blue otherwise. 5. A circle marker is plotted on every bar at the bottom of the chart, colored by the current regime state. Only the most recent five hundred bars are displayed to limit visual load. Notes: The exact internal calculation details of `core.is_hist_rising()` are not shown in this code. Any higher timeframe mechanics, security usage, or confirmation behavior are determined by the imported library. (Unknown) Parameter Guide Source — Selects the price series used by the library call — Default: close — Tips: Use close for consistency; alternate sources may shift regime changes. Preset — Chooses parameter preset for the library’s MACD-style configuration — Default: 3,10,16 — Trade-offs: Faster presets tend to flip more often; slower presets tend to react later. Smoothing Length — Controls smoothing used inside the library regime decision — Default: 21 — Bounds: minimum one — Trade-offs: Higher values typically reduce noise but can delay transitions. (Library behavior: Unknown) Reading & Interpretation Yellow markers indicate the library considers the histogram to be rising at that bar. Blue markers indicate the library considers it not rising, which may include falling or flat conditions depending on the library definition. (Unknown) Because markers repeat on every bar, focus on transitions from one color to the other as regime changes. This tool is best read as context: it does not express strength, only direction of change as defined by the library. Practical Workflows & Combinations Trend following: Use yellow as a condition to allow long-side entries and blue as a condition to allow short-side entries, then trigger entries with your primary setup such as structure breaks or pullback patterns. (Optional) Exits and stops: Consider tightening management after a color transition against your position direction, but do not treat a single flip as an exit signal without price-based confirmation. (Optional) Multi-asset and multi-timeframe: Keep `Source` consistent across assets. Use the slower preset when instruments are noisy, and the faster preset when you need earlier context shifts. The best transferability depends on the imported library’s behavior. (Unknown) Behavior, Constraints & Performance Repaint and confirmation: This script itself uses no forward-looking indexing and no explicit closed-bar gating. It evaluates on every bar update. Any repaint or confirmation behavior may come from the imported library. If the library uses higher timeframe data, intrabar updates can change the state until the higher timeframe bar closes. (Unknown) security and HTF: Not visible here. The library name suggests HTF behavior, but the implementation is not shown. Treat this as potentially higher-timeframe-driven unless you confirm the library source. (Unknown) Resources: No loops, no arrays, no heavy objects. The plotting is one marker series with a five hundred bar display window. Known limits: This indicator does not convey histogram magnitude, divergence, or volatility context. A binary regime can flip in choppy phases depending on preset and smoothing. Sensible Defaults & Quick Tuning Starting point: Source: close Preset: 3,10,16 Smoothing Length: 21 Tuning recipes: Too many flips: choose the slower preset and increase smoothing length. Too sluggish: choose the faster preset and reduce smoothing length. Regime changes feel misaligned with your entries: keep the preset, switch the source back to close, and tune smoothing length in small steps. What this indicator is—and isn’t This is a minimal regime visualization and a context filter. It is not a complete trading system, not a risk model, and not a prediction engine. Use it together with price structure, execution rules, and position management. The regime definition depends on the imported library, so validate it against your market and timeframe before relying on it. Disclaimer The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context. Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved. By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk. Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts. Best regards and happy trading Chervolino MACD HTF Hardcoded
Indicador Pine Script®
por chervolino
Global Liquidity Score Global Liquidity Score – Simple Risk-On / Risk-Off Gauge This indicator measures overall market liquidity conditions using a single, normalized score. It takes several macro and crypto variables, standardizes each one (z-score), and combines them into one clear Liquidity Score Line. You only follow one line (your pink/white line). The background color shows the current liquidity regime. ⸻ What the indicator measures The algorithm looks at four major liquidity sources: 1. USD Liquidity (tightening or easing) • DXY (strong dollar = tighter global liquidity) • US10Y yield (higher yields = liquidity drain) 2. Risk Sentiment (risk-on vs risk-off) • VIX index (volatility) • S&P 500 index (SPX) 3. Credit Market Strength • High-yield ETFs: HYG, JNK • Investment-grade corporate credit: LQD Stronger credit = easier liquidity. Weaker credit = tightening risk. 4. Internal Crypto Liquidity • USDT dominance (higher = risk-off in crypto) • Bitcoin price • TOTAL2 (crypto market cap excluding BTC) These are all converted into z-scores and combined into one metric: Total Liquidity Score = USD Block + Risk Block − Credit Block − 0.5 × Crypto Block ⸻ How to read the colors The indicator uses background colors to show the liquidity regime: Color Meaning Dark Red Severe liquidity tightening / strong risk-off Red Mild-to-moderate tightening Green Liquidity easing / soft risk-on Dark Green Strong easing, high liquidity / risk-on Your pink/white line = the final liquidity score. You only need to follow that single line. ⸻ How to interpret the score 📉 Positive score → Liquidity Tightening (Risk-Off) • USD stronger • Yields rising • Volatility rising • Credit markets weakening • Crypto rotating to stablecoins 📈 Negative score → Liquidity Easing (Risk-On) • USD weakening • Yields falling • Stocks rising • Volatility low • Credit markets strong • Crypto beta assets outperform ⸻ What this indicator is NOT This is not a price predictor. It does not follow BTC directly. It tells you liquidity conditions, not immediate price direction. It answers the macro question: “Is liquidity flowing INTO the market or OUT of the market?” If liquidity is tightening (red), crypto rallies are harder to sustain. If liquidity is easing (green), crypto rallies have more fuel.
Indicador Pine Script®
por FTH33
Stochastic Hash Strat [Hash Capital Research]# Stochastic Hash Strategy by Hash Capital Research ## 🎯 What Is This Strategy? The **Stochastic Slow Strategy** is a momentum-based trading system that identifies oversold and overbought market conditions to capture mean-reversion opportunities. Think of it as a "buy low, sell high" approach with smart mathematical filters that remove emotion from your trading decisions. Unlike fast-moving indicators that generate excessive noise, this strategy uses **smoothed stochastic oscillators** to identify only the highest-probability setups when momentum truly shifts. --- ## 💡 Why This Strategy Works Most traders fail because they: - **Chase prices** after big moves (buying high, selling low) - **Overtrade** in choppy, directionless markets - **Exit too early** or hold losses too long This strategy solves all three problems: 1. **Entry Discipline**: Only trades when the stochastic oscillator crosses in extreme zones (oversold for longs, overbought for shorts) 2. **Cooldown Filter**: Prevents revenge trading by forcing a waiting period after each trade 3. **Fixed Risk/Reward**: Pre-defined stop-loss and take-profit levels ensure consistent risk management **The Math Behind It**: The stochastic oscillator measures where the current price sits relative to its recent high-low range. When it's below 25, the market is oversold (time to buy). When above 70, it's overbought (time to sell). The crossover with its moving average confirms momentum is shifting. --- ## 📊 Best Markets & Timeframes ### ⭐ OPTIMAL PERFORMANCE: **Crude Oil (WTI) - 12H Timeframe** - **Why it works**: Oil markets have predictable volatility patterns and respect technical levels **AAVE/USD - 4H to 12H Timeframe** - **Why it works**: DeFi tokens exhibit strong momentum cycles with clear extremes ### ✅ Also Works Well On: - **BTC/USD** (12H, Daily) - Lower frequency but high win rate - **ETH/USD** (8H, 12H) - Balanced volatility and liquidity - **Gold (XAU/USD)** (Daily) - Classic mean-reversion asset - **EUR/USD** (4H, 8H) - Lower volatility, requires patience ### ❌ Avoid Using On: - Timeframes below 4H (too much noise) - Low-liquidity altcoins (wide spreads kill performance) - Strongly trending markets without pullbacks (Bitcoin in 2021) - News-driven instruments during major events --- ## 🎛️ Understanding The Settings ### Core Stochastic Parameters **Stochastic Length (Default: 16)** - Controls the lookback period for price comparison - Lower = faster reactions, more signals (10-14 for volatile markets) - Higher = smoother signals, fewer trades (16-21 for stable markets) - **Pro tip**: Use 10 for crypto 4H, 16 for commodities 12H **Overbought Level (Default: 70)** - Threshold for short entries - Lower values (65-70) = more trades, earlier entries - Higher values (75-80) = fewer but higher-conviction trades - **Sweet spot**: 70 works for most assets **Oversold Level (Default: 25)** - Threshold for long entries - Higher values (25-30) = more trades, earlier entries - Lower values (15-20) = fewer but stronger bounce setups - **Sweet spot**: 20-25 depending on market conditions **Smooth K & Smooth D (Default: 7 & 3)** - Additional smoothing to filter out whipsaws - K=7 makes the indicator slower and more reliable - D=3 is the signal line that confirms the trend - **Don't change these unless you know what you're doing** --- ### Risk Management **Stop Loss % (Default: 2.2%)** - Automatically exits losing trades - Should be 1.5x to 2x your average market volatility - Too tight = death by a thousand cuts - Too wide = uncontrolled losses - **Calibration**: Check ATR indicator and set SL slightly above it **Take Profit % (Default: 7%)** - Automatically exits winning trades - Should be 2.5x to 3x your stop loss (reward-to-risk ratio) - This default gives 7% / 2.2% = 3.18:1 R:R - **The golden rule**: Never have R:R below 2:1 --- ### Trade Filters **Bar Cooldown Filter (Default: ON, 3 bars)** - **What it does**: Forces you to wait X bars after closing a trade before entering a new one - **Why it matters**: Prevents emotional revenge trading and overtrading in choppy markets - **Settings guide**: - 3 bars = Standard (good for most cases) - 5-7 bars = Conservative (oil, slow-moving assets) - 1-2 bars = Aggressive (only for experienced traders) **Exit on Opposite Extreme (Default: ON)** - Closes your long when stochastic hits overbought (and vice versa) - Acts as an early profit-taking mechanism - **Leave this ON** unless you're testing other exit strategies **Divergence Filter (Default: OFF)** - Looks for price/momentum divergences for additional confirmation - **When to enable**: Trending markets where you want fewer but higher-quality trades - **Keep OFF for**: Mean-reverting markets (oil, forex, most of the time) --- ## 🚀 Quick Start Guide ### Step 1: Set Up in TradingView 1. Open TradingView and navigate to your chart 2. Click "Pine Editor" at the bottom 3. Copy and paste the strategy code 4. Click "Add to Chart" 5. The strategy will appear in a separate pane below your price chart ### Step 2: Choose Your Market **If you're trading Crude Oil:** - Timeframe: 12H - Keep all default settings - Watch for signals during London/NY overlap (8am-11am EST) **If you're trading AAVE or crypto:** - Timeframe: 4H or 12H - Consider these adjustments: - Stochastic Length: 10-14 (faster) - Oversold: 20 (more aggressive) - Take Profit: 8-10% (higher targets) ### Step 3: Wait for Your First Signal **LONG Entry** (Green circle appears): - Stochastic crosses up below oversold level (25) - Price likely near recent lows - System places limit order at take profit and stop loss **SHORT Entry** (Red circle appears): - Stochastic crosses down above overbought level (70) - Price likely near recent highs - System places limit order at take profit and stop loss **EXIT** (Orange circle): - Position closes either at stop, target, or opposite extreme - Cooldown period begins ### Step 4: Let It Run The biggest mistake? **Interfering with the system.** - Don't close trades early because you're scared - Don't skip signals because you "have a feeling" - Don't increase position size after a big win - Don't revenge trade after a loss **Follow the system or don't use it at all.** --- ### Important Risks: 1. **Drawdown Pain**: You WILL experience losing streaks of 5-7 trades. This is mathematically normal. 2. **Whipsaw Markets**: Choppy, range-bound conditions can trigger multiple small losses. 3. **Gap Risk**: Overnight gaps can cause your actual fill to be worse than the stop loss. 4. **Slippage**: Real execution prices differ from backtested prices (factor in 0.1-0.2% slippage). --- ## 🔧 Optimization Guide ### When to Adjust Settings: **Market Volatility Increased?** - Widen stop loss by 0.5-1% - Increase take profit proportionally - Consider increasing cooldown to 5-7 bars **Getting Too Few Signals?** - Decrease stochastic length to 10-12 - Increase oversold to 30, decrease overbought to 65 - Reduce cooldown to 2 bars **Getting Too Many Losses?** - Increase stochastic length to 18-21 (slower, smoother) - Enable divergence filter - Increase cooldown to 5+ bars - Verify you're on the right timeframe ### A/B Testing Method: 1. **Run default settings for 50 trades** on your chosen market 2. Document: Win rate, profit factor, max drawdown, emotional tolerance 3. **Change ONE variable** (e.g., oversold from 25 to 20) 4. Run another 50 trades 5. Compare results 6. Keep the better version **Never change multiple settings at once** or you won't know what worked. --- ## 📚 Educational Resources ### Key Concepts to Learn: **Stochastic Oscillator** - Developed by George Lane in the 1950s - Measures momentum by comparing closing price to price range - Formula: %K = (Close - Low) / (High - Low) × 100 - Similar to RSI but more sensitive to price movements **Mean Reversion vs. Trend Following** - This is a **mean reversion** strategy (price returns to average) - Works best in ranging markets with defined support/resistance - Fails in strong trending markets (2017 Bitcoin, 2020 Tech stocks) - Complement with trend filters for better results **Risk:Reward Ratio** - The cornerstone of profitable trading - Winning 40% of trades with 3:1 R:R = profitable - Winning 60% of trades with 1:1 R:R = breakeven (after fees) - **This strategy aims for 45% win rate with 2.5-3:1 R:R** ### Recommended Reading: - *"Trading Systems and Methods"* by Perry Kaufman (Chapter on Oscillators) - *"Mean Reversion Trading Systems"* by Howard Bandy - *"The New Trading for a Living"* by Dr. Alexander Elder --- ## 🛠️ Troubleshooting ### "I'm not seeing any signals!" **Check:** - Is your timeframe 4H or higher? - Is the stochastic actually reaching extreme levels (check if your asset is stuck in middle range)? - Is cooldown still active from a previous trade? - Are you on a low-liquidity pair? **Solution**: Switch to a more volatile asset or lower the overbought/oversold thresholds. --- ### "The strategy keeps losing money!" **Check:** - What's your win rate? (Below 35% is concerning) - What's your profit factor? (Below 0.8 means serious issues) - Are you trading during major news events? - Is the market in a strong trend? **Solution**: 1. Verify you're using recommended markets/timeframes 2. Increase cooldown period to avoid choppy markets 3. Reduce position size to 5% while you diagnose 4. Consider switching to daily timeframe for less noise --- ### "My stop losses keep getting hit!" **Check:** - Is your stop loss tighter than the average ATR? - Are you trading during high-volatility sessions? - Is slippage eating into your buffer? **Solution**: 1. Calculate the 14-period ATR 2. Set stop loss to 1.5x the ATR value 3. Avoid trading right after market open or major news 4. Factor in 0.2% slippage for crypto, 0.1% for oil --- ## 💪 Pro Tips from the Trenches ### Psychological Discipline **The Three Deadly Sins:** 1. **Skipping signals** - "This one doesn't feel right" 2. **Early exits** - "I'll just take profit here to be safe" 3. **Revenge trading** - "I need to make back that loss NOW" **The Solution:** Treat your strategy like a business system. Would McDonald's skip making fries because the cashier "doesn't feel like it today"? No. Systems work because of consistency. --- ### Position Management **Scaling In/Out** (Advanced) - Enter 50% position at signal - Add 50% if stochastic reaches 10 (oversold) or 90 (overbought) - Exit 50% at 1.5x take profit, let the rest run **This is NOT for beginners.** Master the basic system first. --- ### Market Awareness **Oil Traders:** - OPEC meetings = volatility spikes (avoid or widen stops) - US inventory reports (Wed 10:30am EST) = avoid trading 2 hours before/after - Summer driving season = different patterns than winter **Crypto Traders:** - Monday-Tuesday = typically lower volatility (fewer signals) - Thursday-Sunday = higher volatility (more signals) - Avoid trading during exchange maintenance windows --- ## ⚖️ Legal Disclaimer This trading strategy is provided for **educational purposes only**. - Past performance does not guarantee future results - Trading involves substantial risk of loss - Only trade with capital you can afford to lose - No one associated with this strategy is a licensed financial advisor - You are solely responsible for your trading decisions **By using this strategy, you acknowledge that you understand and accept these risks.** --- ## 🙏 Acknowledgments Strategy development inspired by: - George Lane's original Stochastic Oscillator work - Modern quantitative trading research - Community feedback from hundreds of backtests Built with ❤️ for retail traders who want systematic, disciplined approaches to the markets. --- **Good luck, stay disciplined, and trade the system, not your emotions.**
Estrategia Pine Script®
por Hash_Capital
RSI Ensemble Confidence [CHE]RSI Ensemble Confidence — Measures RSI agreement across multiple lengths and price sources Summary This indicator does not just show you one RSI — it shows you how strongly dozens of different RSI variants agree with each other right now. The Confidence line (0–100) is the core idea: - High Confidence → almost all RSIs see the same thing → clean, reliable situation - Low Confidence → the RSIs contradict each other → the market is messy, RSI signals are questionable How it works (exactly as you wanted it described) 1. Multiple RSIs instead of just one The indicator builds a true ensemble: - 4 lengths (default 8, 14, 21, 34) - 6 price sources (Close, Open, High, Low, HL2, OHLC4 – individually switchable) → When everything is enabled, up to 24 different RSIs are calculated on every single bar. These 24 opinions form a real “vote” about the current market state. 2. Mean and dispersion From all active RSIs it calculates: - rsiMean → the average opinion of the entire ensemble (orange line) - rsiStd → how far the individual RSIs deviate from each other Small rsiStd = they all lie close together → strong agreement Large rsiStd = they are all over the place → contradiction 3. Confidence (0–100) The standard deviation is compared to the user parameter “Max expected StdDev” (default 20): - rsiStd = 0 → Confidence ≈ 100 - rsiStd = maxStd → Confidence ≈ 0 - Everything in between is scaled linearly If only one RSI is active, Confidence is automatically set to ~80 for practicality. What you see on the chart 1. Classic reference RSI – blue line (Close, length 14) → your familiar benchmark 2. Ensemble mean – orange line → the true consensus RSI ±1 StdDev band (optional) → shows dispersion directly: - narrow band = clean, consistent setup - wide band = the RSIs disagree → caution 3. Confidence line (aqua, 0–100) → your quality meter for any RSI signal 4. StdDev histogram (optional, fuchsia columns) → raw dispersion if you prefer the unscaled value 5. Background coloring - Greenish ≥ 80 → high agreement - Orange 60–80 → medium - Reddish < 40 → strong disagreement - Transparent below that 6. Two built-in alerts - High Confidence (crossover 80) - Low Confidence (crossunder 40) Why this indicator is practically useful 1. Perfect filter for all RSI strategies Only trade overbought/oversold, divergences, or failures when Confidence ≥ 70. Skip or reduce size when Confidence < 40. 2. Protection against overinterpretation You immediately see whether a “beautiful” RSI hook is confirmed by the other 23 variants — or whether it’s just one outlier fooling you. 3. Excellent regime detector Long periods of high Confidence = clean trends or clear overbought/oversold phases Constantly low Confidence = choppy, noisy market → RSI becomes almost useless 4. Turns gut feeling into numbers We all sometimes think “this setup somehow doesn’t feel right”. Now you have the exact number that says why. Disclaimer The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context. Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved. By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk. Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts. Best regards and happy trading Chervolino
Indicador Pine Script®
por chervolino
Range Oscillator Strategy + Stoch Confirm🔹 Short summary This is a free, educational long-only strategy built on top of the public “Range Oscillator” by Zeiierman (used under CC BY-NC-SA 4.0), combined with a Stochastic timing filter, an EMA-based exit filter and an optional risk-management layer (SL/TP and R-multiple exits). It is NOT financial advice and it is NOT a magic money machine. It’s a structured framework to study how range-expansion + momentum + trend slope can be combined into one rule-based system, often with intentionally RARE trades. ──────────────────────── 0. Legal / risk disclaimer ──────────────────────── • This script is FREE and public. I do not charge any fee for it. • It is for EDUCATIONAL PURPOSES ONLY. • It is NOT financial advice and does NOT guarantee profits. • Backtest results can be very different from live results. • Markets change over time; past performance is NOT indicative of future performance. • You are fully responsible for your own trades and risk. Please DO NOT use this script with money you cannot afford to lose. Always start in a demo / paper trading environment and make sure you understand what the logic does before you risk any capital. ──────────────────────── 1. About default settings and risk (very important) ──────────────────────── The script is configured with the following defaults in the `strategy()` declaration: • `initial_capital = 10000` → This is only an EXAMPLE account size. • `default_qty_type = strategy.percent_of_equity` • `default_qty_value = 100` → This means 100% of equity per trade in the default properties. → This is AGGRESSIVE and should be treated as a STRESS TEST of the logic, not as a realistic way to trade. TradingView’s House Rules recommend risking only a small part of equity per trade (often 1–2%, max 5–10% in most cases). To align with these recommendations and to get more realistic backtest results, I STRONGLY RECOMMEND you to: 1. Open **Strategy Settings → Properties**. 2. Set: • Order size: **Percent of equity** • Order size (percent): e.g. **1–2%** per trade 3. Make sure **commission** and **slippage** match your own broker conditions. • By default this script uses `commission_value = 0.1` (0.1%) and `slippage = 3`, which are reasonable example values for many crypto markets. If you choose to run the strategy with 100% of equity per trade, please treat it ONLY as a stress-test of the logic. It is NOT a sustainable risk model for live trading. ──────────────────────── 2. What this strategy tries to do (conceptual overview) ──────────────────────── This is a LONG-ONLY strategy designed to explore the combination of: 1. **Range Oscillator (Zeiierman-based)** - Measures how far price has moved away from an adaptive mean. - Uses an ATR-based range to normalize deviation. - High positive oscillator values indicate strong price expansion away from the mean in a bullish direction. 2. **Stochastic as a timing filter** - A classic Stochastic (%K and %D) is used. - The logic requires %K to be below a user-defined level and then crossing above %D. - This is intended to catch moments when momentum turns up again, rather than chasing every extreme. 3. **EMA Exit Filter (trend slope)** - An EMA with configurable length (default 70) is calculated. - The slope of the EMA is monitored: when the slope turns negative while in a long position, and the filter is enabled, it triggers an exit condition. - This acts as a trend-protection exit: if the medium-term trend starts to weaken, the strategy exits even if the oscillator has not yet fully reverted. 4. **Optional risk-management layer** - Percentage-based Stop Loss and Take Profit (SL/TP). - Risk/Reward (R-multiple) exit based on the distance from entry to SL. - Implemented as OCO orders that work *on top* of the logical exits. The goal is not to create a “holy grail” system but to serve as a transparent, configurable framework for studying how these concepts behave together on different markets and timeframes. ──────────────────────── 3. Components and how they work together ──────────────────────── (1) Range Oscillator (based on “Range Oscillator (Zeiierman)”) • The script computes a weighted mean price and then measures how far price deviates from that mean. • Deviation is normalized by an ATR-based range and expressed as an oscillator. • When the oscillator is above the **entry threshold** (default 100), it signals a strong move away from the mean in the bullish direction. • When it later drops below the **exit threshold** (default 30), it can trigger an exit (if enabled). (2) Stochastic confirmation • Classic Stochastic (%K and %D) is calculated. • An entry requires: - %K to be below a user-defined “Cross Level”, and - then %K to cross above %D. • This is a momentum confirmation: the strategy tries to enter when momentum turns up from a pullback rather than at any random point. (3) EMA Exit Filter • The EMA length is configurable via `emaLength` (default 70). • The script monitors the EMA slope: it computes the relative change between the current EMA and the previous EMA. • If the slope turns negative while the strategy holds a long position and the filter is enabled, it triggers an exit condition. • This is meant to help protect profits or cut losses when the medium-term trend starts to roll over, even if the oscillator conditions are not (yet) signalling exit. (4) Risk management (optional) • Stop Loss (SL) and Take Profit (TP): - Defined as percentages relative to average entry price. - Both are disabled by default, but you can enable them in the Inputs. • Risk/Reward Exit: - Uses the distance from entry to SL to project a profit target at a configurable R-multiple. - Also optional and disabled by default. These exits are implemented as `strategy.exit()` OCO orders and can close trades independently of oscillator/EMA conditions if hit first. ──────────────────────── 4. Entry & Exit logic (high level) ──────────────────────── A) Time filter • You can choose a **Start Year** in the Inputs. • Only candles between the selected start date and 31 Dec 2069 are used for backtesting (`timeCondition`). • This prevents accidental use of tiny cherry-picked windows and makes tests more honest. B) Entry condition (long-only) A long entry is allowed when ALL the following are true: 1. `timeCondition` is true (inside the backtest window). 2. If `useOscEntry` is true: - Range Oscillator value must be above `entryLevel`. 3. If `useStochEntry` is true: - Stochastic condition (`stochCondition`) must be true: - %K < `crossLevel`, then %K crosses above %D. If these filters agree, the strategy calls `strategy.entry("Long", strategy.long)`. C) Exit condition (logical exits) A position can be closed when: 1. `timeCondition` is true AND a long position is open, AND 2. At least one of the following is true: - If `useOscExit` is true: Oscillator is below `exitLevel`. - If `useMagicExit` (EMA Exit Filter) is true: EMA slope is negative (`isDown = true`). In that case, `strategy.close("Long")` is called. D) Risk-management exits While a position is open: • If SL or TP is enabled: - `strategy.exit("Long Risk", ...)` places an OCO stop/limit order based on the SL/TP percentages. • If Risk/Reward exit is enabled: - `strategy.exit("RR Exit", ...)` places an OCO order using a projected R-multiple (`rrMult`) of the SL distance. These risk-based exits can trigger before the logical oscillator/EMA exits if price hits those levels. ──────────────────────── 5. Recommended backtest configuration (to avoid misleading results) ──────────────────────── To align with TradingView House Rules and avoid misleading backtests: 1. **Initial capital** - 10 000 (or any value you personally want to work with). 2. **Order size** - Type: **Percent of equity** - Size: **1–2%** per trade is a reasonable starting point. - Avoid risking more than 5–10% per trade if you want results that could be sustainable in practice. 3. **Commission & slippage** - Commission: around 0.1% if that matches your broker. - Slippage: a few ticks (e.g. 3) to account for real fills. 4. **Timeframe & markets** - Volatile symbols (e.g. crypto like BTCUSDT, or major indices). - Timeframes: 1H / 4H / **1D (Daily)** are typical starting points. - I strongly recommend trying the strategy on **different timeframes**, for example 1D, to see how the behaviour changes between intraday and higher timeframes. 5. **No “caution warning”** - Make sure your chosen symbol + timeframe + settings do not trigger TradingView’s caution messages. - If you see warnings (e.g. “too few trades”), adjust timeframe/symbol or the backtest period. ──────────────────────── 5a. About low trade count and rare signals ──────────────────────── This strategy is intentionally designed to trade RARELY: • It is **long-only**. • It uses strict filters (Range Oscillator threshold + Stochastic confirmation + optional EMA Exit Filter). • On higher timeframes (especially **1D / Daily**) this can result in a **low total number of trades**, sometimes WELL BELOW 100 trades over the whole backtest. TradingView’s House Rules mention 100+ trades as a guideline for more robust statistics. In this specific case: • The **low trade count is a conscious design choice**, not an attempt to cherry-pick a tiny, ultra-profitable window. • The goal is to study a **small number of high-conviction long entries** on higher timeframes, not to generate frequent intraday signals. • Because of the low trade count, results should NOT be interpreted as statistically strong or “proven” – they are only one sample of how this logic would have behaved on past data. Please keep this in mind when you look at the equity curve and performance metrics. A beautiful curve with only a handful of trades is still just a small sample. ──────────────────────── 6. How to use this strategy (step-by-step) ──────────────────────── 1. Add the script to your chart. 2. Open the **Inputs** tab: - Set the backtest start year. - Decide whether to use Oscillator-based entry/exit, Stochastic confirmation, and EMA Exit Filter. - Optionally enable SL, TP, and Risk/Reward exits. 3. Open the **Properties** tab: - Set a realistic account size if you want. - Set order size to a realistic % of equity (e.g. 1–2%). - Confirm that commission and slippage are realistic for your broker. 4. Run the backtest: - Look at Net Profit, Max Drawdown, number of trades, and equity curve. - Remember that a low trade count means the statistics are not very strong. 5. Experiment: - Tweak thresholds (`entryLevel`, `exitLevel`), Stochastic settings, EMA length, and risk params. - See how the metrics and trade frequency change. 6. Forward-test: - Before using any idea in live trading, forward-test on a demo account and observe behaviour in real time. ──────────────────────── 7. Originality and usefulness (why this is more than a mashup) ──────────────────────── This script is not intended to be a random visual mashup of indicators. It is designed as a coherent, testable strategy with clear roles for each component: • Range Oscillator: - Handles mean vs. range-expansion states via an adaptive, ATR-normalized metric. • Stochastic: - Acts as a timing filter to avoid entering purely on extremes and instead waits for momentum to turn. • EMA Exit Filter: - Trend-slope-based safety net to exit when the medium-term direction changes against the position. • Risk module: - Provides practical, rule-based exits: SL, TP, and R-multiple exit, which are useful for structuring risk even if you modify the core logic. It aims to give traders a ready-made **framework to study and modify**, not a black box or “signals” product. ──────────────────────── 8. Limitations and good practices ──────────────────────── • No single strategy works on all markets or in all regimes. • This script is long-only; it does not short the market. • Performance can degrade when market structure changes. • Overfitting (curve fitting) is a real risk if you endlessly tweak parameters to maximise historical profit. Good practices: - Test on multiple symbols and timeframes. - Focus on stability and drawdown, not only on how high the profit line goes. - View this as a learning tool and a basis for your own research. ──────────────────────── 9. Licensing and credits ──────────────────────── • Core oscillator idea & base code: - “Range Oscillator (Zeiierman)” - © Zeiierman, licensed under CC BY-NC-SA 4.0. • Strategy logic, Stochastic confirmation, EMA Exit Filter, and risk-management layer: - Modifications by jokiniemi. Please respect both the original license and TradingView House Rules if you fork or republish any part of this script. ──────────────────────── 10. No payments / no vendor pitch ──────────────────────── • This script is completely FREE to use on TradingView. • There is no paid subscription, no external payment link, and no private signals group attached to it. • If you have questions, please use TradingView’s comment system or private messages instead of expecting financial advice. Use this script as a tool to learn, experiment, and build your own understanding of markets. ──────────────────────── 11. Example backtest settings used in screenshots ──────────────────────── To avoid any confusion about how the results shown in screenshots were produced, here is one concrete example configuration: • Symbol: BTCUSDT (or similar major BTC pair) • Timeframe: 1D (Daily) • Backtest period: from 2018 to the most recent data • Initial capital: 10 000 • Order size type: Percent of equity • Order size: 2% per trade • Commission: 0.1% • Slippage: 3 ticks • Risk settings: Stop Loss and Take Profit disabled by default, Risk/Reward exit disabled by default • Filters: Range Oscillator entry/exit enabled, Stochastic confirmation enabled, EMA Exit Filter enabled If you change any of these settings (symbol, timeframe, risk per trade, commission, slippage, filters, etc.), your results will look different. Please always adapt the configuration to your own risk tolerance, market, and trading style.
Estrategia Pine Script®
por jokiniemi
Algorithm Predator - ML-liteAlgorithm Predator - ML-lite This indicator combines four specialized trading agents with an adaptive multi-armed bandit selection system to identify high-probability trade setups. It is designed for swing and intraday traders who want systematic signal generation based on institutional order flow patterns , momentum exhaustion , liquidity dynamics , and statistical mean reversion . Core Architecture Why These Components Are Combined: The script addresses a fundamental challenge in algorithmic trading: no single detection method works consistently across all market conditions. By deploying four independent agents and using reinforcement learning algorithms to select or blend their outputs, the system adapts to changing market regimes without manual intervention. The Four Trading Agents 1. Spoofing Detector Agent 🎭 Detects iceberg orders through persistent volume at similar price levels over 5 bars Identifies spoofing patterns via asymmetric wick analysis (wicks exceeding 60% of bar range with volume >1.8× average) Monitors order clustering using simplified Hawkes process intensity tracking (exponential decay model) Signal Logic: Contrarian—fades false breakouts caused by institutional manipulation Best Markets: Consolidations, institutional trading windows, low-liquidity hours 2. Exhaustion Detector Agent ⚡ Calculates RSI divergence between price movement and momentum indicator over 5-bar window Detects VWAP exhaustion (price at 2σ bands with declining volume) Uses VPIN reversals (volume-based toxic flow dissipation) to identify momentum failure Signal Logic: Counter-trend—enters when momentum extreme shows weakness Best Markets: Trending markets reaching climax points, over-extended moves 3. Liquidity Void Detector Agent 💧 Measures Bollinger Band squeeze (width <60% of 50-period average) Identifies stop hunts via 20-bar high/low penetration with immediate reversal and volume spike Detects hidden liquidity absorption (volume >2× average with range <0.3× ATR) Signal Logic: Breakout anticipation—enters after liquidity grab but before main move Best Markets: Range-bound pre-breakout, volatility compression zones 4. Mean Reversion Agent 📊 Calculates price z-scores relative to 50-period SMA and standard deviation (triggers at ±2σ) Implements Ornstein-Uhlenbeck process scoring (mean-reverting stochastic model) Uses entropy analysis to detect algorithmic trading patterns (low entropy <0.25 = high predictability) Signal Logic: Statistical reversion—enters when price deviates significantly from statistical equilibrium Best Markets: Range-bound, low-volatility, algorithmically-dominated instruments Adaptive Selection: Multi-Armed Bandit System The script implements four reinforcement learning algorithms to dynamically select or blend agents based on performance: Thompson Sampling (Default - Recommended): Uses Bayesian inference with beta distributions (tracks alpha/beta parameters per agent) Balances exploration (trying underused agents) vs. exploitation (using proven winners) Each agent's win/loss history informs its selection probability Lite Approximation: Uses pseudo-random sampling from price/volume noise instead of true random number generation UCB1 (Upper Confidence Bound): Calculates confidence intervals using: average_reward + sqrt(2 × ln(total_pulls) / agent_pulls) Deterministic algorithm favoring agents with high uncertainty (potential upside) More conservative than Thompson Sampling Epsilon-Greedy: Exploits best-performing agent (1-ε)% of the time Explores randomly ε% of the time (default 10%, configurable 1-50%) Simple, transparent, easily tuned via epsilon parameter Gradient Bandit: Uses softmax probability distribution over agent preference weights Updates weights via gradient ascent based on rewards Best for Blend mode where all agents contribute Selection Modes: Switch Mode: Uses only the selected agent's signal (clean, decisive) Blend Mode: Combines all agents using exponentially weighted confidence scores controlled by temperature parameter (smooth, diversified) Lock Agent Feature: Optional manual override to force one specific agent Useful after identifying which agent dominates your specific instrument Only applies in Switch mode Four choices: Spoofing Detector, Exhaustion Detector, Liquidity Void, Mean Reversion Memory System Dual-Layer Architecture: Short-Term Memory: Stores last 20 trade outcomes per agent (configurable 10-50) Long-Term Memory: Stores episode averages when short-term reaches transfer threshold (configurable 5-20 bars) Memory Boost Mechanism: Recent performance modulates agent scores by up to ±20% Episode Transfer: When an agent accumulates sufficient results, averages are condensed into long-term storage Persistence: Manual restoration of learned parameters via input fields (alpha, beta, weights, microstructure thresholds) How Memory Works: Agent generates signal → outcome tracked after 8 bars (performance horizon) Result stored in short-term memory (win = 1.0, loss = 0.0) Short-term average influences agent's future scores (positive feedback loop) After threshold met (default 10 results), episode averaged into long-term storage Long-term patterns (weighted 30%) + short-term patterns (weighted 70%) = total memory boost Market Microstructure Analysis These advanced metrics quantify institutional order flow dynamics: Order Flow Toxicity (Simplified VPIN): Measures buy/sell volume imbalance over 20 bars: |buy_vol - sell_vol| / (buy_vol + sell_vol) Detects informed trading activity (institutional players with non-public information) Values >0.4 indicate "toxic flow" (informed traders active) Lite Approximation: Uses simple open/close heuristic instead of tick-by-tick trade classification Price Impact Analysis (Simplified Kyle's Lambda): Measures market impact efficiency: |price_change_10| / sqrt(volume_sum_10) Low values = large orders with minimal price impact ( stealth accumulation ) High values = retail-dominated moves with high slippage Lite Approximation: Uses simplified denominator instead of regression-based signed order flow Market Randomness (Entropy Analysis): Counts unique price changes over 20 bars / 20 Measures market predictability High entropy (>0.6) = human-driven, chaotic price action Low entropy (<0.25) = algorithmic trading dominance (predictable patterns) Lite Approximation: Simple ratio instead of true Shannon entropy H(X) = -Σ p(x)·log₂(p(x)) Order Clustering (Simplified Hawkes Process): Tracks self-exciting event intensity (coordinated order activity) Decays at 0.9× per bar, spikes +1.0 when volume >1.5× average High intensity (>0.7) indicates clustering (potential spoofing/accumulation) Lite Approximation: Simple exponential decay instead of full λ(t) = μ + Σ α·exp(-β(t-tᵢ)) with MLE Signal Generation Process Multi-Stage Validation: Stage 1: Agent Scoring Each agent calculates internal score based on its detection criteria Scores must exceed agent-specific threshold (adjusted by sensitivity multiplier) Agent outputs: Signal direction (+1/-1/0) and Confidence level (0.0-1.0) Stage 2: Memory Boost Agent scores multiplied by memory boost factor (0.8-1.2 based on recent performance) Successful agents get amplified, failing agents get dampened Stage 3: Bandit Selection/Blending If Adaptive Mode ON: Switch: Bandit selects single best agent, uses only its signal Blend: All agents combined using softmax-weighted confidence scores If Adaptive Mode OFF: Traditional consensus voting with confidence-squared weighting Signal fires when consensus exceeds threshold (default 70%) Stage 4: Confirmation Filter Raw signal must repeat for consecutive bars (default 3, configurable 2-4) Minimum confidence threshold: 0.25 (25%) enforced regardless of mode Trend alignment check: Long signals require trend_score ≥ -2, Short signals require trend_score ≤ 2 Stage 5: Cooldown Enforcement Minimum bars between signals (default 10, configurable 5-15) Prevents over-trading during choppy conditions Stage 6: Performance Tracking After 8 bars (performance horizon), signal outcome evaluated Win = price moved in signal direction, Loss = price moved against Results fed back into memory and bandit statistics Trading Modes (Presets) Pre-configured parameter sets: Conservative: 85% consensus, 4 confirmations, 15-bar cooldown Expected: 60-70% win rate, 3-8 signals/week Best for: Swing trading, capital preservation, beginners Balanced: 70% consensus, 3 confirmations, 10-bar cooldown Expected: 55-65% win rate, 8-15 signals/week Best for: Day trading, most traders, general use Aggressive: 60% consensus, 2 confirmations, 5-bar cooldown Expected: 50-58% win rate, 15-30 signals/week Best for: Scalping, high-frequency trading, active management Elite: 75% consensus, 3 confirmations, 12-bar cooldown Expected: 58-68% win rate, 5-12 signals/week Best for: Selective trading, high-conviction setups Adaptive: 65% consensus, 2 confirmations, 8-bar cooldown Expected: Varies based on learning Best for: Experienced users leveraging bandit system How to Use 1. Initial Setup (5 Minutes): Select Trading Mode matching your style (start with Balanced) Enable Adaptive Learning (recommended for automatic agent selection) Choose Thompson Sampling algorithm (best all-around performance) Keep Microstructure Metrics enabled for liquid instruments (>100k daily volume) 2. Agent Tuning (Optional): Adjust Agent Sensitivity multipliers (0.5-2.0): <0.8 = Highly selective (fewer signals, higher quality) 0.9-1.2 = Balanced (recommended starting point) 1.3 = Aggressive (more signals, lower individual quality) Monitor dashboard for 20-30 signals to identify dominant agent If one agent consistently outperforms, consider using Lock Agent feature 3. Bandit Configuration (Advanced): Blend Temperature (0.1-2.0): 0.3 = Sharp decisions (best agent dominates) 0.5 = Balanced (default) 1.0+ = Smooth (equal weighting, democratic) Memory Decay (0.8-0.99): 0.90 = Fast adaptation (volatile markets) 0.95 = Balanced (most instruments) 0.97+ = Long memory (stable trends) 4. Signal Interpretation: Green triangle (▲): Long signal confirmed Red triangle (▼): Short signal confirmed Dashboard shows: Active agent (highlighted row with ► marker) Win rate per agent (green >60%, yellow 40-60%, red <40%) Confidence bars (█████ = maximum confidence) Memory size (short-term buffer count) Colored zones display: Entry level (current close) Stop-loss (1.5× ATR) Take-profit 1 (2.0× ATR) Take-profit 2 (3.5× ATR) 5. Risk Management: Never risk >1-2% per signal (use ATR-based stops) Signals are entry triggers, not complete strategies Combine with your own market context analysis Consider fundamental catalysts and news events Use "Confirming" status to prepare entries (not to enter early) 6. Memory Persistence (Optional): After 50-100 trades, check Memory Export Panel Record displayed alpha/beta/weight values for each agent Record VPIN and Kyle threshold values Enable "Restore From Memory" and input saved values to continue learning Useful when switching timeframes or restarting indicator Visual Components On-Chart Elements: Spectral Layers: EMA8 ± 0.5 ATR bands (dynamic support/resistance, colored by trend) Energy Radiance: Multi-layer glow boxes at signal points (intensity scales with confidence, configurable 1-5 layers) Probability Cones: Projected price paths with uncertainty wedges (15-bar projection, width = confidence × ATR) Connection Lines: Links sequential signals (solid = same direction continuation, dotted = reversal) Kill Zones: Risk/reward boxes showing entry, stop-loss, and dual take-profit targets Signal Markers: Triangle up/down at validated entry points Dashboard (Configurable Position & Size): Regime Indicator: 4-level trend classification (Strong Bull/Bear, Weak Bull/Bear) Mode Status: Shows active system (Adaptive Blend, Locked Agent, or Consensus) Agent Performance Table: Real-time win%, confidence, and memory stats Order Flow Metrics: Toxicity and impact indicators (when microstructure enabled) Signal Status: Current state (Long/Short/Confirming/Waiting) with confirmation progress Memory Panel (Configurable Position & Size): Live Parameter Export: Alpha, beta, and weight values per agent Adaptive Thresholds: Current VPIN sensitivity and Kyle threshold Save Reminder: Visual indicator if parameters should be recorded What Makes This Original This script's originality lies in three key innovations: 1. Genuine Meta-Learning Framework: Unlike traditional indicator mashups that simply display multiple signals, this implements authentic reinforcement learning (multi-armed bandits) to learn which detection method works best in current conditions. The Thompson Sampling implementation with beta distribution tracking (alpha for successes, beta for failures) is statistically rigorous and adapts continuously. This is not post-hoc optimization—it's real-time learning. 2. Episodic Memory Architecture with Transfer Learning: The dual-layer memory system mimics human learning patterns: Short-term memory captures recent performance (recency bias) Long-term memory preserves historical patterns (experience) Automatic transfer mechanism consolidates knowledge Memory boost creates positive feedback loops (successful strategies become stronger) This architecture allows the system to adapt without retraining , unlike static ML models that require batch updates. 3. Institutional Microstructure Integration: Combines retail-focused technical analysis (RSI, Bollinger Bands, VWAP) with institutional-grade microstructure metrics (VPIN, Kyle's Lambda, Hawkes processes) typically found in academic finance literature and professional trading systems, not standard retail platforms. While simplified for Pine Script constraints, these metrics provide insight into informed vs. uninformed trading , a dimension entirely absent from traditional technical analysis. Mashup Justification: The four agents are combined specifically for risk diversification across failure modes: Spoofing Detector: Prevents false breakout losses from manipulation Exhaustion Detector: Prevents chasing extended trends into reversals Liquidity Void: Exploits volatility compression (different regime than trending) Mean Reversion: Provides mathematical anchoring when patterns fail The bandit system ensures the optimal tool is automatically selected for each market situation, rather than requiring manual interpretation of conflicting signals. Why "ML-lite"? Simplifications and Approximations This is the "lite" version due to necessary simplifications for Pine Script execution: 1. Simplified VPIN Calculation: Academic Implementation: True VPIN uses volume bucketing (fixed-volume bars) and tick-by-tick buy/sell classification via Lee-Ready algorithm or exchange-provided trade direction flags This Implementation: 20-bar rolling window with simple open/close heuristic (close > open = buy volume) Impact: May misclassify volume during ranging/choppy markets; works best in directional moves 2. Pseudo-Random Sampling: Academic Implementation: Thompson Sampling requires true random number generation from beta distributions using inverse transform sampling or acceptance-rejection methods This Implementation: Deterministic pseudo-randomness derived from price and volume decimal digits: (close × 100 - floor(close × 100)) + (volume % 100) / 100 Impact: Not cryptographically random; may have subtle biases in specific price ranges; provides sufficient variation for agent selection 3. Hawkes Process Approximation: Academic Implementation: Full Hawkes process uses maximum likelihood estimation with exponential kernels: λ(t) = μ + Σ α·exp(-β(t-tᵢ)) fitted via iterative optimization This Implementation: Simple exponential decay (0.9 multiplier) with binary event triggers (volume spike = event) Impact: Captures self-exciting property but lacks parameter optimization; fixed decay rate may not suit all instruments 4. Kyle's Lambda Simplification: Academic Implementation: Estimated via regression of price impact on signed order flow over multiple time intervals: Δp = λ × Δv + ε This Implementation: Simplified ratio: price_change / sqrt(volume_sum) without proper signed order flow or regression Impact: Provides directional indicator of impact but not true market depth measurement; no statistical confidence intervals 5. Entropy Calculation: Academic Implementation: True Shannon entropy requires probability distribution: H(X) = -Σ p(x)·log₂(p(x)) where p(x) is probability of each price change magnitude This Implementation: Simple ratio of unique price changes to total observations (variety measure) Impact: Measures diversity but not true information entropy with probability weighting; less sensitive to distribution shape 6. Memory System Constraints: Full ML Implementation: Neural networks with backpropagation, experience replay buffers (storing state-action-reward tuples), gradient descent optimization, and eligibility traces This Implementation: Fixed-size array queues with simple averaging; no gradient-based learning, no state representation beyond raw scores Impact: Cannot learn complex non-linear patterns; limited to linear performance tracking 7. Limited Feature Engineering: Advanced Implementation: Dozens of engineered features, polynomial interactions (x², x³), dimensionality reduction (PCA, autoencoders), feature selection algorithms This Implementation: Raw agent scores and basic market metrics (RSI, ATR, volume ratio); minimal transformation Impact: May miss subtle cross-feature interactions; relies on agent-level intelligence rather than feature combinations 8. Single-Instrument Data: Full Implementation: Multi-asset correlation analysis (sector ETFs, currency pairs, volatility indices like VIX), lead-lag relationships, risk-on/risk-off regimes This Implementation: Only OHLCV data from displayed instrument Impact: Cannot incorporate broader market context; vulnerable to correlated moves across assets 9. Fixed Performance Horizon: Full Implementation: Adaptive horizon based on trade duration, volatility regime, or profit target achievement This Implementation: Fixed 8-bar evaluation window Impact: May evaluate too early in slow markets or too late in fast markets; one-size-fits-all approach Performance Impact Summary: These simplifications make the script: ✅ Faster: Executes in milliseconds vs. seconds (or minutes) for full academic implementations ✅ More Accessible: Runs on any TradingView plan without external data feeds, APIs, or compute servers ✅ More Transparent: All calculations visible in Pine Script (no black-box compiled models) ✅ Lower Resource Usage: <500 bars lookback, minimal memory footprint ⚠️ Less Precise: Approximations may reduce statistical edge by 5-15% vs. academic implementations ⚠️ Limited Scope: Cannot capture tick-level dynamics, multi-order-book interactions, or cross-asset flows ⚠️ Fixed Parameters: Some thresholds hardcoded rather than dynamically optimized When to Upgrade to Full Implementation: Consider professional Python/C++ versions with institutional data feeds if: Trading with >$100K capital where precision differences materially impact returns Operating in microsecond-competitive environments (HFT, market making) Requiring regulatory-grade audit trails and reproducibility Backtesting with tick-level precision for strategy validation Need true real-time adaptation with neural network-based learning For retail swing/day trading and position management, these approximations provide sufficient signal quality while maintaining usability, transparency, and accessibility. The core logic—multi-agent detection with adaptive selection—remains intact. Technical Notes All calculations use standard Pine Script built-in functions ( ta.ema, ta.atr, ta.rsi, ta.bb, ta.sma, ta.stdev, ta.vwap ) VPIN and Kyle's Lambda use simplified formulas optimized for OHLCV data (see "Lite" section above) Thompson Sampling uses pseudo-random noise from price/volume decimal digits for beta distribution sampling No repainting: All calculations use confirmed bar data (no forward-looking) Maximum lookback: 500 bars (set via max_bars_back parameter) Performance evaluation: 8-bar forward-looking window for reward calculation (clearly disclosed) Confidence threshold: Minimum 0.25 (25%) enforced on all signals Memory arrays: Dynamic sizing with FIFO queue management Limitations and Disclaimers Not Predictive: This indicator identifies patterns in historical data. It cannot predict future price movements with certainty. Requires Human Judgment: Signals are entry triggers, not complete trading strategies. Must be confirmed with your own analysis, risk management rules, and market context. Learning Period Required: The adaptive system requires 50-100 bars minimum to build statistically meaningful performance data for bandit algorithms. Overfitting Risk: Restoring memory parameters from one market regime to a drastically different regime (e.g., low volatility to high volatility) may cause poor initial performance until system re-adapts. Approximation Limitations: Simplified calculations (see "Lite" section) may underperform academic implementations by 5-15% in highly efficient markets. No Guarantee of Profit: Past performance, whether backtested or live-traded, does not guarantee future performance. All trading involves risk of loss. Forward-Looking Bias: Performance evaluation uses 8-bar forward window—this creates slight look-ahead for learning (though not for signals). Real-time performance may differ from indicator's internal statistics. Single-Instrument Limitation: Does not account for correlations with related assets or broader market regime changes. Recommended Settings Timeframe: 15-minute to 4-hour charts (sufficient volatility for ATR-based stops; adequate bar volume for learning) Assets: Liquid instruments with >100k daily volume (forex majors, large-cap stocks, BTC/ETH, major indices) Not Recommended: Illiquid small-caps, penny stocks, low-volume altcoins (microstructure metrics unreliable) Complementary Tools: Volume profile, order book depth, market breadth indicators, fundamental catalysts Position Sizing: Risk no more than 1-2% of capital per signal using ATR-based stop-loss Signal Filtering: Consider external confluence (support/resistance, trendlines, round numbers, session opens) Start With: Balanced mode, Thompson Sampling, Blend mode, default agent sensitivities (1.0) After 30+ Signals: Review agent win rates, consider increasing sensitivity of top performers or locking to dominant agent Alert Configuration The script includes built-in alert conditions: Long Signal: Fires when validated long entry confirmed Short Signal: Fires when validated short entry confirmed Alerts fire once per bar (after confirmation requirements met) Set alert to "Once Per Bar Close" for reliability Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Indicador Pine Script®
por DskyzInvestments
9
Quasimodo Pattern Strategy Back Test [TradingFinder] QM Trading🔵 Introduction The QM pattern, also known as the Quasimodo pattern, is one of the popular patterns in price action, and it is often used by technical analysts. The QM pattern is used to identify trend reversals and provides a very good risk-to-reward ratio. One of the advantages of the QM pattern is its high frequency and visibility in charts. Additionally, due to its strength, it is highly profitable, and as mentioned, its risk-to-reward ratio is very good. The QM pattern is highly popular among traders in supply and demand, and traders also use this pattern. The Price Action QM pattern, like other Price Action patterns, has two types: Bullish QM and Bearish QM patterns. To identify this pattern, you need to be familiar with its types to recognize it. 🔵 Identifying the QM Pattern 🟣 Bullish QM In the bullish QM pattern, as you can see in the image below, an LL and HH are formed. As you can see, the neckline is marked as a dashed line. When the price reaches this range, it will start its upward movement. 🟣 Bearish QM The Price Action QM pattern also has a bearish pattern. As you can see in the image below, initially, an HH and LL are formed. The neckline in this image is the dashed line, and when the LL is formed, the price reaches this neckline. However, it cannot pass it, and the downward trend resumes. 🔵 How to Use The Quasimodo pattern is one of the clearest structures used to identify market reversals. It is built around the concept of a structural break followed by a pullback into an area of trapped liquidity. Instead of relying on lagging indicators, this pattern focuses purely on price action and how the market reacts after exhausting one side of liquidity. When understood correctly, it provides traders with precise entry points at the transition between trend phases. 🟣 Bullish Quasimodo A bullish Quasimodo forms after a clear downtrend when sellers start losing control. The market continues to make lower lows until a sudden higher high appears, signaling that buyers are entering with strength. Price then pulls back to retest the previous low, creating what is known as the Quasimodo low. This area often becomes the final trap for sellers before the market shifts upward. A visible rejection or displacement from this zone confirms bullish momentum. Traders usually place entries near this level, stops below the low, and targets at previous highs or the next resistance zone. Combining the setup with demand zones or Fair Value Gaps increases its accuracy. 🟣 Bearish Quasimodo A bearish Quasimodo forms near the top of an uptrend when buyers begin to lose strength. The market continues to make higher highs until a sudden lower low breaks the bullish structure, showing that selling pressure is entering the market. Price then retraces upward to retest the previous high, forming the Quasimodo high, where breakout buyers are often trapped. Once rejection appears at this level, it indicates a likely reversal. Traders can enter short near this area, with stop-losses placed above the high and targets near the next support or previous lows. The setup gains more reliability when aligned with supply zones, SMT divergence, or bearish Fair Value Gaps. 🔵 Setting Pivot Period : You can use this parameter to use your desired period to identify the QM pattern. By default, this parameter is set to the number 5. Take Profit Mode : You can choose your desired Take Profit in three ways. Based on the logic of the QM strategy, you can select two Take Profit levels, TP1 and TP2. You can also choose your take profit based on the Reward to Risk ratio. You must enter your desired R/R in the Reward to Risk Ratio parameter. Stop Loss Refine : The loss limit of the QM strategy is based on its logic on the Head pattern. You can refine it using the ATR Refine option to prevent Stop Hunt. You can enter your desired coefficient in the Stop Loss ATR Adjustment Coefficient parameter. Reward to Risk Ratio : If you set Take Profit Mode to R/R, you must enter your desired R/R here. For example, if your loss limit is 10 pips and you set R/R to 2, your take profit will be reached when the price is 20 pips away from your entry point. Stop Loss ATR Adjustment Coefficient : If you set Stop Loss Refine to ATR Refine, you must adjust your loss limit coefficient here. For example, if your buy position's loss limit is at the price of 1000, and your ATR is 10, if you set Stop Loss ATR Adjustment Coefficient to 2, your loss limit will be at the price of 980. Entry Level Validity : Determines how long the Entry level remains valid. The higher the level, the longer the entry level will remain valid. By default it is 2 and it can be set between 2 and 15. 🔵 Results The following examples show the backtest results of the Quasimodo (QM) strategy in action. Each image is based on specific settings for the symbol, timeframe, and input parameters, illustrating how the QM logic can generate signals under different market conditions. The detailed configuration for each backtest is also displayed on the image. ⚠ Important Note : Even with identical settings and the same symbol, results may vary slightly across different brokers due to data feed variations and pricing differences. Default Properties of Backtests : OANDA:XAUUSD | TimeFrame: 5min | Duration: 1 Year : BINANCE:BTCUSD | TimeFrame: 5min | Duration: 1 Year : CAPITALCOM:US30 | TimeFrame: 5min | Duration: 1 Year : NASDAQ:QQQ | TimeFrame: 5min | Duration: 5 Year : OANDA:EURUSD | TimeFrame: 5min | Duration: 5 Year : PEPPERSTONE:US500 | TimeFrame: 5min | Duration: 5 Year :
Estrategia Pine Script®
por TFlab
18
Realtime Squeeze Box [CHE] Realtime Squeeze Box — Detects lowvolatility consolidation periods and draws trimmed price range boxes in realtime to highlight potential breakout setups without clutter from outliers. Summary This indicator identifies "squeeze" phases where recent price volatility falls below a dynamic baseline threshold, signaling potential energy buildup for directional moves. By requiring a minimum number of consecutive bars in squeeze, it reduces noise from fleeting dips, making signals more reliable than simple threshold crosses. The core innovation is realtime box visualization: during active squeezes, it builds and updates a box capturing the price range while ignoring extreme values via quantile trimming, providing a cleaner view of consolidation bounds. This differs from static volatility bands by focusing on trimmed ranges and suppressing overlapping boxes, which helps traders spot genuine setups amid choppy markets. Overall, it aids in anticipating breakouts by combining volatility filtering with visual containment of price action. Motivation: Why this design? Traders often face whipsaws during brief volatility lulls that mimic true consolidations, leading to premature entries, or miss setups because standard volatility measures lag in adapting to changing market regimes. This design addresses that by using a hold requirement on consecutive lowvolatility bars to denoise signals, ensuring only sustained squeezes trigger visuals. The core idea—comparing rolling standard deviation to a smoothed baseline—creates a responsive yet stable filter for lowenergy periods, while the trimmed box approach isolates the core price cluster, making it easier to gauge breakout potential without distortion from spikes. What’s different vs. standard approaches? Reference baseline: Traditional squeeze indicators like the Bollinger Band Squeeze or TTM Squeeze rely on fixed multiples of bands or momentum oscillators crossing zero, which can fire on isolated bars or ignore range compression nuances. Architecture differences: Realtime box construction that updates barbybar during squeezes, using arrays to track and trim price values. Quantilebased outlier rejection to define box bounds, focusing on the bulk of prices rather than full range. Overlap suppression logic that skips redundant boxes if the new range intersects heavily with the prior one. Hold counter for consecutive bar validation, adding persistence before signaling. Practical effect: Charts show fewer, more defined orange boxes encapsulating tight price action, with a horizontal line extension marking the midpoint postsqueeze—visibly reducing clutter in sideways markets and highlighting "coiled" ranges that standard plots might blur with full highs/lows. This matters for quicker visual scanning of multitimeframe setups, as boxes selflimit to recent history and avoid piling up. How it works (technical) The indicator starts by computing a rolling average and standard deviation over a userdefined length on the chosen source price series. This deviation measure is then smoothed into a baseline using either a simple or exponential average over a longer window, serving as a reference for normal volatility. A squeeze triggers when the current deviation dips below this baseline scaled by a multiplier less than one, but only after a minimum number of consecutive bars confirm it, which resets the counter on breaks. Upon squeeze start, it clears a buffer and begins collecting source prices barbybar, limited to the first few bars to keep computation light. For visualization, if enabled, it sorts the buffer and finds a quantile threshold, then identifies the minimum value at or below that threshold to set upper and lower box bounds—effectively clamping the range to exclude tails above the quantile. The box draws from the start bar to the current one, updating its right edge and levels dynamically; if the new bounds overlap significantly with the last completed box, it suppresses drawing to avoid redundancy. Once the hold limit or squeeze ends, the box freezes: its final bounds become the last reference, a midpoint line extends rightward from the end, and a tiny circle label marks the point. Buffers and states reset on new squeezes, with historical boxes and lines capped to prevent overload. All logic runs on every bar but uses confirmed historical data for calculations, with realtime updates only affecting the active box's position—no future peeking occurs. Initialization seeds with null values, building states progressively from the first bars. Parameter Guide Source: Selects the price series (e.g., close, hl2) for deviation and box building; influences sensitivity to wicks or bodies. Default: close. Tradeoffs/Tips: Use hl2 for balanced range view in volatile assets; stick to close for pure directional focus—test on your timeframe to avoid oversmoothing trends. Length (Mean/SD): Sets window for average and deviation calculation; shorter values make detection quicker but noisier. Default: 20. Tradeoffs/Tips: Increase to 30+ for stability in higher timeframes, reducing false starts; below 10 risks overreacting to singlebar noise. Baseline Length: Defines smoothing window for the deviation baseline; longer periods create a steadier reference, filtering regime shifts. Default: 50. Tradeoffs/Tips: Pair with Length at 1:2 ratio for calm markets; shorten to 30 if baselines lag during fast volatility drops, but watch for added whips. Squeeze Multiplier (<1.0): Scales the baseline downward to set the squeeze threshold; lower values tighten criteria for rarer, stronger signals. Default: 0.8. Tradeoffs/Tips: Tighten to 0.6 for highvol assets like crypto to cut noise; loosen to 0.9 in forex for more frequent but shallower setups—balances hit rate vs. depth. Baseline via EMA (instead of SMA): Switches baseline smoothing to exponential for faster adaptation to recent changes vs. equalweighted simple average. Default: false. Tradeoffs/Tips: Enable in trending markets for quicker baseline drops; disable for uniform history weighting in rangebound conditions to avoid overreacting. SD: Sample (len1) instead of Population (len): Adjusts deviation formula to divide by length minus one for smallsample bias correction, slightly inflating values. Default: false. Tradeoffs/Tips: Use sample in short windows (<20) for more conservative thresholds; population suits long looks where bias is negligible, keeping signals tighter. Min. Hold Bars in Squeeze: Requires this many consecutive squeeze bars before confirming; higher denoise but may clip early setups. Default: 1. Tradeoffs/Tips: Bump to 35 for intraday to filter ticks; keep at 1 for swings where quick consolidations matter—trades off timeliness for reliability. Debug: Plot SD & Threshold: Toggles lines showing raw deviation and threshold for visual backtesting of squeeze logic. Default: false. Tradeoffs/Tips: Enable during tuning to eyeball crossovers; disable live to declutter—great for verifying multiplier impact without alerts. Tint Bars when Squeeze Active: Overlays semitransparent color on bars during open box phases for quick squeeze spotting. Default: false. Tradeoffs/Tips: Pair with low opacity for subtlety; turn off if using boxes alone, as tint can obscure candlesticks in dense charts. Tint Opacity (0..100): Controls background tint strength during active squeezes; higher values darken for emphasis. Default: 85. Tradeoffs/Tips: Dial to 60 for light touch; max at 100 risks hiding price action—adjust per chart theme for visibility. Stored Price (during Squeeze): Price series captured in the buffer for box bounds; defaults to source but allows customization. Default: close. Tradeoffs/Tips: Switch to high/low for wider boxes in gappy markets; keep close for midline focus—impacts trim effectiveness on outliers. Quantile q (0..1): Fraction of sorted prices below which tails are cut; higher q keeps more data but risks including spikes. Default: 0.718. Tradeoffs/Tips: Lower to 0.5 for aggressive trim in noisy assets; raise to 0.8 for fuller ranges—tune via debug to match your consolidation depth. Box Fill Color: Sets interior shade of squeeze boxes; semitransparent for layering. Default: orange (80% trans.). Tradeoffs/Tips: Soften with more transparency in multiindicator setups; bold for standalone use—ensures boxes pop without overwhelming. Box Border Color: Defines outline hue and solidity for box edges. Default: orange (0% trans.). Tradeoffs/Tips: Match fill for cohesion or contrast for edges; thin width keeps it clean—helps delineate bounds in zoomed views. Keep Last N Boxes: Limits historical boxes/lines/labels to this count, deleting oldest for performance. Default: 10. Tradeoffs/Tips: Increase to 50 for weekly reviews; set to 0 for unlimited (risks lag)—balances history vs. speed on long charts. Draw Box in Realtime (build/update): Enables live extension of boxes during squeezes vs. waiting for end. Default: true. Tradeoffs/Tips: Disable for confirmedonly views to mimic backtests; enable for proactive trading—adds minor repaint on live bars. Box: Max First N Bars: Caps buffer collection to initial squeeze bars, freezing after for efficiency. Default: 15. Tradeoffs/Tips: Shorten to 510 for fast intraday; extend to 20 in dailies—prevents bloated arrays but may truncate long squeezes. Reading & Interpretation Squeeze phases appear as orange boxes encapsulating the trimmed price cluster during lowvolatility holds—narrow boxes signal tight consolidations, while wider ones indicate looser ranges within the threshold. The box's top and bottom represent the quantilecapped high and low of collected prices, with the interior fill shading the containment zone; ignore extremes outside for "true" bounds. Postsqueeze, a solid horizontal line extends right from the box's midpoint, acting as a reference level for potential breakout tests—drifting prices toward or away from it can hint at building momentum. Tiny orange circles at the line's start mark completion points for easy scanning. Debug lines (if on) show deviation hugging or crossing the threshold, confirming hold logic; a persistent hug below suggests prolonged calm, while spikes above reset counters. Practical Workflows & Combinations Trend following: Enter long on squeezeend close above the box top (or midpoint line) confirmed by higher high in structure; filter with rising 50period average to avoid countertrend traps. Use boxes as support/resistance proxies—short below bottom in downtrends. Exits/Stops: Trail stops to the box midpoint during postsqueeze runs for conservative holds; go aggressive by exiting on retest of opposite box side. If debug shows repeated threshold grazes, tighten stops to curb drawdowns in ranging followups. Multiasset/MultiTF: Defaults work across stocks, forex, and crypto on 15min+ frames; scale Length proportionally (e.g., x2 on hourly). Layer with highertimeframe boxes for confluence—e.g., daily squeeze + 1H box for entry timing. (Unknown/Optional: Specific multiTF scaling recipes beyond proportional adjustment.) Behavior, Constraints & Performance Repaint/confirmation: Core calculations use historical closes, confirming on bar close; active boxes repaint their right edge and levels live during squeezes if enabled, but freeze irrevocably on hold limit or end—mitigates via barbybar buffer adds without future leaks. No lookahead indexes. security()/HTF: None used, so no external timeframe repaints; all native to chart resolution. Resources: Caps at 300 boxes/lines/labels total; small arrays (up to 20 elements) and short loops in sorting/minfinding keep it light—suitable for 10k+ bar charts without throttling. Persistent variables track state across bars efficiently. Known limits: May lag on ultrasharp volatility spikes due to baseline smoothing; gaps or thin markets can skew trims if buffer hits cap early; overlaps suppress visuals but might hide chained squeezes—(Unknown/Optional: Edge cases in nonstandard sessions). Sensible Defaults & Quick Tuning Start with defaults for most liquid assets on 1Hdaily: Length 20, Multiplier 0.8, Hold 1, Quantile 0.718—yields balanced detection without excess noise. For too many false starts (choppy charts), increase Hold to 3 and Baseline Length to 70 for stricter confirmation, reducing signals by 3050%. If squeezes feel sluggish or miss quick coils, shorten Length to 14 and enable EMA baseline for snappier adaptation, but monitor for added flips. In highvol environments like options, tighten Multiplier to 0.6 and Quantile to 0.6 to focus on core ranges; reverse for calm pairs by loosening to 0.95. Always backtest tweaks on your asset's history. What this indicator is—and isn’t This is a volatilityfiltered visualization tool for spotting and bounding consolidation phases, best as a signal layer atop price action and trend filters—not a standalone predictor of direction or strength. It highlights setups but ignores volume, momentum, or news context, so pair with discreteness rules like higher highs/lows. Never use it alone for entries; always layer risk management, such as 12% stops beyond box extremes, and position sizing based on account drawdown tolerance. Disclaimer The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context. Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved. By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk. Do not use this indicator on HeikinAshi, Renko, Kagi, PointandFigure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts. Best regards and happy trading Chervolino
Indicador Pine Script®
por chervolino
1
SevenDayHighLowTableWithBoxes [CHE]SevenDayHighLowTableWithBoxes — Seven-day day-range boxes with a weekday-aware “ghost” projection and a compact table that tracks recent extremes and per-weekday hit rates. Summary This indicator visualizes each trading day as a colored box and annotates the final high and low with compact markers. It maintains a rolling seven-day view and a five-column table showing day name, high, low, range, and a per-weekday projection hit statistic. A dashed “ghost” box projects a typical range for the current weekday using a running average and an adjustable scaling factor. The script is written in Pine v6, runs on the main chart (overlay true), and emphasizes stable object handling and closed-bar finalization at day boundaries. Motivation: Why this design? Intraday traders often need fast context for where today’s price sits relative to recent daily extremes, without switching timeframes. A simple daily high/low overlay is informative but lacks structure, sizing context, and continuity. By grouping bars into local days (configurable UTC offset), drawing explicit boxes, and projecting a weekday-typical range, the chart becomes easier to scan. The compact table gives a quick audit trail of the latest seven days while tracking how often the weekday projection would have covered the realized range. What’s different vs. standard approaches? Reference baseline: Plain daily high/low lines or session boxes without context. Architecture differences: Weekday-tinted boxes and labels for today plus up to six prior days. Weekday average range drives a dashed projection (“ghost”) sized by a user-defined percentage. Per-weekday hit statistics recorded as hits over totals and displayed in the table. ATR-based vertical offsets keep labels readable. Live updates intraday; state is finalized at the local day switch. Practical effect: The chart shows where current price sits inside a known daily envelope, plus how “typical” the day’s movement is for this weekday, aiding expectations and planning. How it works (technical) The script computes a local daily timestamp using the user’s UTC offset. A day change finalizes the prior day, writes its high, low, start and end indices, and records the bar indices of the terminal high and low. For each weekday, it maintains a running average of realized ranges with a cap on the lookback count. The ghost projection length is the weekday average scaled by the user’s percentage setting. Anchor selection for the ghost uses the most recent extreme and the close relative to the intraday midpoint to choose a low-anchored or high-anchored box. A five-column table (Day, High, Low, Range, Ghost OK) is refreshed on the last bar. The “Ghost OK” column shows per-weekday cumulative hits over totals with a percentage, calculated before including the just-finished day. Object counts are bounded to seven days by pruning arrays and deleting old boxes and labels. Visual updates for historical objects occur on the last bar to minimize overhead. No `security()` calls are used. Parameter Guide UTC (+/−) — Controls local day boundaries — Default: minus five hours — Set to your venue’s local time. Session (for Time gate) — Session string — Default: full week — (Optional) computed internally; not applied to gating. Show 7-Day High/Low Table — Toggles the table — Default: true — Disable to reduce UI load. Show Day Boxes in Chart — Toggles day boxes — Default: true — Disable for a cleaner chart. Table Position — Nine-point anchor — Default: Middle Right — Move to avoid overlap. Table Background / Text Color / Min Cell Width — Styling controls — Defaults: gray background, white text, width twelve characters. Weekday Colors (Sun…Sat) — Row and box tints — Defaults: semi-transparent hues — Adjust for your theme. Triangle Transparency — Marker opacity — Default: zero — Increase to fade high/low dots. Day Label Transparency — Day name opacity — Default: zero — Increase to reduce emphasis. Box Border Width — Box stroke width — Default: one — Increase for stronger edges. Extend Boxes Right — Extend current box — Default: false — Useful for forward planning. Show Average Range Ghost Box — Dashed projection — Default: true — Disable if distracting. Ghost Border Color / Width — Ghost styling — Defaults: gray, width one. Ghost Length percent of AvgRange — Projection scale — Default: one hundred; bounds zero to five hundred — Lower to be conservative. Max History Days for Average — Cap per-weekday averaging — Default: two hundred fifty-two; bounds thirty to five hundred. ATR Length / Day Label ATR Multiplier / Triangle Up ATR Multiplier / Triangle Down ATR Multiplier — Offsets for label placement — Defaults: length one hundred; multipliers zero — Increase on dense instruments to prevent overlap. Reading & Interpretation Day boxes: The filled rectangle marks each day’s full high-low span; color encodes the weekday. Markers: Small dots near the terminal high and low highlight where the final extremes occurred. Ghost box: A dashed box sized by the weekday average range, anchored based on recent behavior. It is a typical span, not a target. Table: Row one shows “Today”. Rows below list up to six prior days. “Ghost OK” shows per-weekday cumulative hits over totals with a percentage, which reflects historical coverage quality for that weekday. Practical Workflows & Combinations Trend following: Use the current box plus recent boxes to read expansion or compression days; combine with basic structure such as higher-highs and higher-lows or lower-lows and lower-highs for confirmation. Exits and risk: When price nears the ghost boundary late in the session, consider managing exposure more conservatively. Multi-asset and multi-timeframe: Works on minute charts. As a starting point, use five to less than sixty minutes. For cross-checks, pair with a higher timeframe bias filter. Behavior, Constraints & Performance Repaint/confirmation: The indicator updates intraday; extremes and ghost position can move while the day is open. Values are finalized on the next local day start. HTF/security: None used; repaint risk is limited to live-bar movement. Resources: `max_bars_back` five thousand; arrays are pruned to seven days; the table and color sync run on the last bar; the live ghost updates only in real time. Known limits: Weekday averages can be unrepresentative during regime shifts, events, or gaps. Day boundaries depend on the UTC offset being set correctly. No alerts are included. The script displays warning labels when the timeframe is below five minutes or at sixty minutes and above. Sensible Defaults & Quick Tuning Start with the defaults. Ghost too aggressive: Lower the percent scale. Labels overlap: Increase ATR multipliers. Clutter or performance issues: Hide the table or boxes, or disable the ghost. Day boundary misaligned: Adjust the UTC offset to your market. What this indicator is—and isn’t This is a visualization and context layer for daily extremes and a weekday-based typical span. It does not predict direction, does not manage orders, and is not a complete trading system. Use it alongside market structure, risk controls, and position management. Disclaimer The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context. Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved. By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk. Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts. Best regards and happy trading Chervolino
Indicador Pine Script®
por chervolino
Smart Flow Tracker [The_lurker] Smart Flow Tracker (SFT): Advanced Order Flow Tracking Indicator Overview Smart Flow Tracker (SFT) is an advanced indicator designed for real-time tracking and analysis of order flows. It focuses on detecting institutional patterns, massive orders, and potential reversals through analysis of lower timeframes (Lower Timeframe) or live ticks. It provides deep insights into market behavior using a multi-layered intelligent detection system and a clear visual interface, giving traders a competitive edge. SFT focuses on trade volumes, directions, and frequencies to uncover unusual activity that may indicate institutional intervention, massive orders, or manipulation attempts (traps). Indicator Operation Levels SFT operates on three main levels: 1. Microscopic Monitoring: Tracks every trade at precise timeframes (down to one second), providing visibility not available in standard timeframes. 2. Advanced Statistical Analysis: Calculates averages, deviations, patterns, and anomalies using precise mathematical algorithms. 3. Behavioral Artificial Intelligence: Recognizes behavioral patterns such as hidden institutional accumulation, manipulation attempts and traps, and potential reversal points. Key Features SFT features a set of advanced functions to enhance the trader's experience: 1. Intelligent Order Classification System: Classifies orders into six categories based on size and pattern: - Standard: Normal orders with typical size. - Significant 💎: Orders larger than average by 1.5 times. - Major 🔥: Orders larger than average by 2.5 times. - Massive 🐋: Orders larger than average by 3 times. - Institutional 🏛️: Consistent patterns indicating institutional activity. - Reversal 🔄: Large orders indicating direction change. - Trap ⚠️: Patterns that may be price traps. 2. Institutional Patterns Detection: Tracks sequences of similar-sized orders, detects organized institutional activity, and is customizable (number of trades, variance ratio). 3. Reversals Detection: Compares recent flows with previous ones, detects direction shifts from up to down or vice versa, and operates only on large orders (Major/Massive/Institutional). 4. Traps Detection: Identifies sequences of large orders in one direction, followed by an institutional order in the opposite direction, with early alerts for false moves. 5. Flow Delta Bar: Displays the difference between buy and sell volumes as a percentage for balance, with instant updates per trade. 6. Dynamic Statistics Panel: Displays overall buy and sell ratios with real-time updates and interactive colors. How It Works and Understanding SFT relies on logical sequential stages for data processing: A. Data Collection: Uses the `request.security_lower_tf()` function to extract data from a lower timeframe (like 1S) even on a higher timeframe (like 5D). For each time unit, it calculates: - Adjusted Volume: Either normal volume or "price-weighted volume" (hlc3 * volume) based on user choice. - Trade Direction: Compared to previous close (rise → buy, fall → sell). B. Building Temporary Memory: Maintains a dynamic list (sizeHistory) of the last 100 trade sizes, continuously calculating the moving average (meanSize). C. Intelligent Classification: Compares each new trade to the average: - > 1.5 × average → Significant. - > 2.5 × average → Major. - > 3.0 × average → Massive. - Institutional Patterns Check: A certain number of trades (e.g., 5) with a specified variance ratio (±5%) → Institutional. D. Advanced Detection: - Reversal: Compares buy/sell totals in two consecutive periods. - Trap: Sequence of large trades in one direction followed by an opposite institutional trade. E. Display and Alerts: Results displayed in an automatically updated table, with option to enable alerts for notable events. Settings (Fully Customizable) SFT offers extensive options to adapt to the trader's needs: A. Display Settings: - Language: English / Arabic. - Table Position: 9 options (e.g., Top Right, Middle Right, Bottom Left). - Display Size: Tiny / Small / Normal / Large. - Max Rows: 10–100. - Enable Flow Delta Bar: Yes / No. - Enable Statistics Panel: Yes / No (displays buy/sell % ratio). B.- Technical Settings: - Data Source: Lower Timeframe / Live Tick (simulation). - Timeframe: Optional (e.g., 1S, 5S, 1). - Calculation Type: Volume / Price Volume. C. Intelligent Detection System: - Enable Institutional Patterns Detection. - Pattern Length: 3–20 trades. - Allowed Variance Ratio: 1%–20%. - Massive Orders Detection Factor: 2.0–10.0. D. Classification Criteria: - Significant Orders Factor: 1.2–3.0. - Major Orders Factor: 2.0–5.0. E. **Advanced Detection**: - Enable Reversals Detection (with review period). - Enable Traps Detection (with minimum sequence limit). F. Alerts System: - Enable for each type: Massive orders, institutional patterns, reversals, traps, severe imbalance (60%–90%). G. Color System: Manual customization for each category: - Standard Buy 🟢: Dark gray green. - Standard Sell 🔴: Dark gray red. - Significant Buy 🟢: Medium green. - Significant Sell 🔴: Medium red. - Major Orders 🟣: Purple. - Massive Orders 🟠: Orange. - Institutional 🟦: Sky blue. - Reversal 🔵: Blue. - Trap 🟣: Pink-purple. Target Audiences SFT benefits a wide range of traders and investors: 1. Scalpers: Instant detection of large orders, liquidity points identification, avoiding traps in critical moments. 2. Day Traders: Tracking smart money footprint, determining real session direction, early reversals detection. 3. Swing Traders: Confirming trend strength, detecting institutional accumulation/distribution, identifying optimal entry points. 4. Investors: Understanding true market sentiments, avoiding entry at false peaks, identifying real value zones. ⚠️ Disclaimer: This indicator is for educational and analytical purposes only. It does not constitute financial, investment, or trading advice. Use it in conjunction with your own strategy and risk management. Neither TradingView nor the developer is liable for any financial decisions or losses. Smart Flow Tracker (SFT): مؤشر متقدم لتتبع تدفقات الأوامر نظرة عامة Smart Flow Tracker (SFT) مؤشر متقدم مصمم لتتبع وتحليل تدفقات الأوامر في الوقت الفعلي. يركز على كشف الأنماط المؤسسية، الأوامر الضخمة، والانعكاسات المحتملة من خلال تحليل الأطر الزمنية الأقل (Lower Timeframe) أو التيك الحي. يوفر رؤية عميقة لسلوك السوق باستخدام نظام كشف ذكي متعدد الطبقات وواجهة مرئية واضحة، مما يمنح المتداولين ميزة تنافسية. يركز SFT على حجم الصفقات، اتجاهها، وتكرارها لكشف النشاط غير العادي الذي قد يشير إلى تدخل مؤسسات، أوامر ضخمة، أو محاولات تلاعب (فخاخ). مستويات عمل المؤشر يعمل SFT على ثلاثة مستويات رئيسية: 1. المراقبة المجهرية: يتتبع كل صفقة على مستوى الأطر الزمنية الدقيقة (حتى الثانية الواحدة)، مما يوفر رؤية غير متوفرة في الأطر الزمنية العادية. 2. التحليل الإحصائي المتقدم: يحسب المتوسطات، الانحرافات، الأنماط، والشذوذات باستخدام خوارزميات رياضية دقيقة. 3. الذكاء الاصطناعي السلوكي: يتعرف على أنماط سلوكية مثل التراكم المؤسسي المخفي، محاولات التلاعب والفخاخ، ونقاط الانعكاس المحتملة. الميزات الرئيسية يتميز SFT بمجموعة من الوظائف المتقدمة لتحسين تجربة المتداول: 1. نظام تصنيف الأوامر الذكي: يصنف الأوامر إلى ست فئات بناءً على الحجم والنمط: - Standard (قياسي)**: أوامر عادية بحجم طبيعي. - Significant 💎 (مهم)**: أوامر أكبر من المتوسط بـ1.5 ضعف. - Major 🔥 (كبير)**: أوامر أكبر من المتوسط بـ2.5 ضعف. - Massive 🐋 (ضخم)**: أوامر أكبر من المتوسط بـ3 أضعاف. - Institutional 🏛️ (مؤسسي)**: أنماط متسقة تشير إلى نشاط مؤسسي. - Reversal 🔄 (انعكاس)**: أوامر كبيرة تشير إلى تغيير اتجاه. - Trap ⚠️ (فخ)**: أنماط قد تكون فخاخًا سعرية. 2. كشف الأنماط المؤسسية: يتتبع تسلسل الأوامر المتشابهة في الحجم، يكشف النشاط المؤسسي المنظم، وقابل للتخصيص (عدد الصفقات، نسبة التباين). 3. كشف الانعكاسات: يقارن التدفقات الأخيرة بالسابقة، يكشف تحول الاتجاه من صعود إلى هبوط أو العكس، ويعمل فقط على الأوامر الكبيرة (Major/Massive/Institutional). 4. كشف الفخاخ: يحدد تسلسل أوامر كبيرة في اتجاه واحد، يليها أمر مؤسسي في الاتجاه المعاكس، مع تنبيه مبكر للحركات الكاذبة. 5. شريط دلتا التدفق: يعرض الفرق بين حجم الشراء والبيع كنسبة مئوية للتوازن، مع تحديث فوري لكل صفقة. 6. لوحة إحصائيات ديناميكية: تعرض نسبة الشراء والبيع الإجمالية مع تحديث لحظي وألوان تفاعلية. طريقة العمل والفهم يعتمد SFT على مراحل منطقية متسلسلة لمعالجة البيانات: أ. جمع البيانات: يستخدم دالة `request.security_lower_tf()` لاستخراج بيانات من إطار زمني أدنى (مثل 1S) حتى على إطار زمني أعلى (مثل 5D). لكل وحدة زمنية، يحسب: - الحجم المعدّل: إما الحجم العادي (volume) أو "الحجم المرجّح بالسعر" (hlc3 * volume) حسب الاختيار. - اتجاه الصفقة: مقارنة الإغلاق الحالي بالسابق (ارتفاع → شراء، انخفاض → بيع). ب. بناء الذاكرة المؤقتة: يحتفظ بقائمة ديناميكية (sizeHistory) لآخر 100 حجم صفقة، ويحسب المتوسط المتحرك (meanSize) باستمرار. ج. التصنيف الذكي: يقارن كل صفقة جديدة بالمتوسط: - > 1.5 × المتوسط → Significant. - > 2.5 × المتوسط → Major. - > 3.0 × المتوسط → Massive. - فحص الأنماط المؤسسية: عدد معين من الصفقات (مثل 5) بنسبة تباين محددة (±5%) → Institutional. د. الكشف المتقدم: - الانعكاس: مقارنة مجموع الشراء/البيع في فترتين متتاليتين. - الفخ: تسلسل صفقات كبيرة في اتجاه واحد يتبعها صفقة مؤسسية معاكسة. هـ. العرض والتنبيه: عرض النتائج في جدول محدّث تلقائيًا، مع إمكانية تفعيل تنبيهات للأحداث المميزة. لإعدادات (قابلة للتخصيص بالكامل) يوفر SFT خيارات واسعة للتكييف مع احتياجات المتداول: أ. إعدادات العرض: - اللغة: English / العربية. - موقع الجدول: 9 خيارات (مثل Top Right, Middle Right, Bottom Left). - حجم العرض: Tiny / Small / Normal / Large. - الحد الأقصى للصفوف: 10–100. - تفعيل شريط دلتا التدفق: نعم / لا. - تفعيل لوحة الإحصائيات: نعم / لا (تعرض نسبة الشراء/البيع %). ب. الإعدادات التقنية: - مصدر البيانات: Lower Timeframe / Live Tick (محاكاة). - الإطار الزمني: اختياري (مثل 1S, 5S, 1). - نوع الحساب: Volume / Price Volume. ج. نظام الكشف الذكي: - تفعيل كشف الأنماط المؤسسية. - طول النمط: 3–20 صفقة. - نسبة التباين: 1%–20%. - عامل كشف الأوامر الضخمة: 2.0–10.0. د. معايير التصنيف: - عامل الأوامر المهمة: 1.2–3.0. - عامل الأوامر الكبرى: 2.0–5.0. هـ. الكشف المتقدم: - تفعيل كشف الانعكاسات (مع فترة مراجعة). - تفعيل كشف الفخاخ (مع حد أدنى للتسلسل). و. نظام التنبيهات: - تفعيل لكل نوع: أوامر ضخمة، أنماط مؤسسية، انعكاسات، فخاخ، عدم توازن شديد (60%–90%). ز. نظام الألوان**: تخصيص يدوي لكل فئة: - شراء قياسي 🟢: أخضر رمادي داكن. - بيع قياسي 🔴: أحمر رمادي داكن. - شراء مهم 🟢: أخضر متوسط. - بيع مهم 🔴: أحمر متوسط. - أوامر كبرى 🟣: بنفسجي. - أوامر ضخمة 🟠: برتقالي. - مؤسسي 🟦: أزرق سماوي. - انعكاس 🔵: أزرق. - فخ 🟣: وردي-أرجواني. الفئات المستهدفة يستفيد من SFT مجموعة واسعة من المتداولين والمستثمرين: 1. السكالبرز (Scalpers): كشف لحظي للأوامر الكبيرة، تحديد نقاط السيولة، تجنب الفخاخ في اللحظات الحرجة. 2. المتداولون اليوميون (Day Traders): تتبع بصمة الأموال الذكية، تحديد اتجاه الجلسة الحقيقي، كشف الانعكاسات المبكرة. 3. المتداولون المتأرجحون (Swing Traders): تأكيد قوة الاتجاه، كشف التراكم/التوزيع المؤسسي، تحديد نقاط الدخول المثلى. 4. المستثمرون: فهم معنويات السوق الحقيقية، تجنب الدخول في قمم كاذبة، تحديد مناطق القيمة الحقيقية. ⚠️ إخلاء مسؤولية: هذا المؤشر لأغراض تعليمية وتحليلية فقط. لا يُمثل نصيحة مالية أو استثمارية أو تداولية. استخدمه بالتزامن مع استراتيجيتك الخاصة وإدارة المخاطر. لا يتحمل TradingView ولا المطور مسؤولية أي قرارات مالية أو خسائر.
Indicador Pine Script®
por The_lurker
4
Volume Area 80 Rule Pro - Adaptive RTHSummary in one paragraph Adaptive value area 80 percent rule for index futures large cap equities liquid crypto and major FX on intraday timeframes. It focuses activity only when multiple context gates align. It is original because the classic prior day value area traverse is fused with a daily regime classifier that remaps the operating parameters in real time. Scope and intent • Markets. ES NQ SPY QQQ large cap equities BTC ETH major FX pairs and other liquid RTH instruments • Timeframes. One minute to one hour with daily regime context • Default demo used in the publication. ES1 on five minutes • Purpose. Trade only the balanced days where the 80 percent traverse has edge while standing aside or tightening rules during trend or shock Originality and usefulness • Unique fusion. Prior day value area logic plus a rolling daily regime classifier using percentile ranks of realized volatility and ADX. The regime remaps hold time end of window stop buffer and value area coverage on each session • Failure mode addressed. False starts during strong trend or shock sessions and weak traverses during quiet grind • Testability. All gates are visible in Inputs and debug flags can be plotted so users can verify why a suggestion appears • Portable yardstick. The regime uses ATR divided by close and ADX percent ranks which behave consistently across symbols Method overview in plain language The script builds the prior session profile during regular trading hours. At the first regular bar it freezes yesterday value area low value area high and point of control. It then evaluates the current session open location the first thirty minute volume rank the open gap rank and an opening drive test. In parallel a daily series classifies context into Calm Balance Trend or Shock from rolling percentile ranks of realized volatility and ADX. The classifier scales the rules. Calm uses longer holds and a slightly wider value area. Trend and Shock shorten the window reduce holds and enlarge stop buffers. Base measures • Range basis. True Range smoothed over a configurable length on both the daily and intraday series • Return basis. Not required. ATR over close is the unit for regime strength Components • Prior Value Area Engine. Builds yesterday value area low value area high and point of control from a binned volume profile with automatic TPO fallback and minimum integrity guards • Opening Location. Detects whether the session opens above the prior value area or below it • Inside Hold Counter. Counts consecutive bars that hold inside the value area after a re entry • Volume Gate. Percentile of the first thirty minutes volume over a rolling sample • Gap Gate. Percentile rank of the regular session open gap over a rolling sample • Drive Gate. Opening drive check using a multiple of intraday ATR • Regime Classifier. Percentile ranks of daily ATR over close and daily ADX classify Calm Balance Trend Shock and remap parameters • Session windows optional. Windows follow the chart exchange time Fusion rule Minimum satisfied gates approach. A re entry must hold inside the value area for a regime scaled number of bars while the volume gap and drive gates allow the setup. The regime simultaneously scales value area coverage end minute time stop and stop buffer. Signal rule • Long suggestion appears when price opens below yesterday value area then re enters and holds for the required bars while all gates allow the setup • Short suggestion appears when price opens above yesterday value area then re enters and holds for the required bars while all gates allow the setup • WAIT shows implicitly when any required gate is missing • Exit labels mark target touch stop touch or a time based close Inputs with guidance Setup • Signal timeframe. Uses the chart by default • Session windows optional. Start and end minutes inside regular trading hours • Invert direction is not used. The logic is symmetric Logic • Hold bars inside value area. Typical range 3 to 12. Raising it reduces trades and favors better traverses. Lowering it increases frequency and risk of false starts • Earliest minute since RTH open and Latest minute since RTH open. Typical range 0 to 390. Reducing the latest minute cuts late session trades • Time stop bars after entry. Typical range 6 to 30. Larger values give setups more room Filters • Value area coverage. Typical range 0.70 to 0.85. Higher coverage narrows the traverse but accepts fewer days • Bin size in ticks. Typical range 1 to 8. Larger bins stabilize noisy profiles • Stop buffer ticks beyond edge. Typical range 2 to 20. Larger buffers survive noise • First thirty minute volume percentile. Typical range 0.30 to 0.70. Higher values require more active opens • Gap filter percentile. Typical range 0.70 to 0.95. Lower values block more gap days • Opening drive multiple and bars. Higher multiple or longer bars block strong directional opens Adaptivity • Lookback days for regime ranks. Typical 150 to 500 • Calm RV percentile. Typical 25 to 45 • Trend ADX percentile. Typical 55 to 75 • Shock RV percentile. Typical 75 to 90 • End minute ratio in Trend and Shock. Typical 0.5 to 0.8 • Hold and Time stop scales per regime. Use values near one to keep behavior close to static settings Realism and responsible publication • No performance claims. Past results never guarantee future outcomes • Shapes can move while a bar forms and settle on close • Sessions use the chart exchange time Honest limitations and failure modes • Economic releases and thin liquidity can break the balance premise • Gap heavy symbols may work better with stronger gap filters and a True Range focus • Very quiet regimes reduce signal contrast. Consider longer windows or higher thresholds Legal Education and research only. Not investment advice. Test in simulation before any live use.
Indicador Pine Script®
por exlux
Camarilla Pivot Plays (Lite) [BruzX]█ OVERVIEW This indicator implements the Camarilla Pivot Points levels and a system for suggesting particular plays. It only 3rd, 4th, and 6th levels, as these are the only ones used by the system. It also optionally shows the Central Pivot Range, which is in fact between S2 and R2. In total, there are 12 possible plays, grouped into two groups of six. The algorithm evaluates in real-time which plays fulfil their precondition and shows the candidate plays. The user must then decide if and when to take the play. █ CREDITS The Camarilla pivot plays are defined in a strategy developed by Thor Young, and the whole system is explained in his book "A Complete Day Trading System". This description is self-sufficient for effective use. █ FEATURES Display the 3rd, 4th and 6th Camarilla pivot levels Works for stocks, futures, indices, forex and crypto Automatically switches between RTH and ETH data based on criteria defined by the system. Option to force RTH/ETH data and force a close price to be used in the calculation. Preconditions for the plays can be toggled on/off Works correctly on both RTH and ETH charts Well-documented options tooltips Well-documented and high-quality open-source code for those who are interested █ HOW TO USE The defaults work well; at a minimum, just add the indicator and watch the plays being called. For US futures, you will probably want to chat the "Timezone for sessions" to New York and the regular session times to 09:30 - 16:00. The following diagram shows its key features. By default, the indicator draws plays 1 days back; this can be changed up to 20 days. The labels can be shifted left/right using the "label offset" option to avoid overlapping with other labels in this indicator or those of another indicator. An information box at the top-right of the chart shows: The data currently in use for the main pivots. This can switch in the pre-market if the H/L range exceeds the previous day's H/L, and if it does, you will see that switch at the time that it happens Whether the current day's pivots are in a higher or lower range compared to the previous day's. The width of the pivots compared to the previous day The current candidate plays fulfilling preconditions. You then need to watch the price action to decide whether to take the play. The resistance pivots are all drawn in the same colour (red by default), as are the support pivots (green by default). You can change the resistance and support colours, but it is not possible to have different colours for different levels of the same kind. █ CONCEPTS The indicator is focused around daily Camarilla pivots and evaluates the preconditions for 12 possible plays: 6 when in a higher range, 6 when in a lower range. The plays are labelled by two letters—the first indicates the range, the second indicates the play—as shown in this diagram: The pivots can be calculated using only RTH (Regular Trading Hours) data, or ETH (Extended Trading Hours) data, which includes the pre-market and post-market. The indicator implements logic to automatically choose the correct data, based on the rules defined by the strategy. This is user-overridable. With the default options, ETH will be used when the H/L range in the previous day's post-market or current day's pre-market exceeds that of the previous day's regular market. In auto mode, the chosen pivots are considered the main pivots for that day and are the ones used for play evaluation. The "other" pivots can also be shown—"other" here meaning using ETH data when the main pivots use RTH data, and vice versa. The plays must fulfil a set of preconditions. There are preconditions for valid region and range, price sweeps into levels, correct pivot width, opening position, price action, and whether neutral range plays and premarket plays are enabled. When all the preconditions are fulfilled, the play will be shown as a candidate. █ NOTE FOR FUTURES Futures don't officially have a pre-market or post-market like equities. Let's take ES on CME as an example. It trades from 18:00 ET Sunday to 17:00 Friday (ET), with a daily pause between 17:00 and 18:00 ET. However, most of the trading activity is done between 09:30 and 16:00, which you can tell from the volume spikes at those times, and this coincides with NYSE/NASDAQ regular hours. So we define a pseudo-pre-market from 18:00 the previous day to 09:30 on the current day, then a pseudo-regular market from 08:30 to 16:00, then a pseudo-post-market from 16:00 to 17:00. The indicator then works exactly the same as with equities—all the options behave the same, just with different session times defined for the pre-, regular, and post-market, with "RTH" meaning just the regular market and "ETH" meaning all three. █ LIMITATIONS The pivots are very close to those shown in DAS Trader Pro. They are not to-the-cent exact, but within a few cents. The reasons are: TradingView provides free real-time data from CBOE One, not full exchange data (you can pay for this though, and it's not expensive), and the close/high/low are taken from the intraday timeframe you are currently viewing, not daily data—which are very close, but often not exactly the same. For example, the high on the daily timeframe may differ slightly from the daily high you'll see on an intraday timeframe. Despite these caveats, occasionally large spikes will be seem in one platform and not the other (even with paid data), or the spikes will reach significantly difference prices. Where these spikes create the daily high or low, this can cause significantly different pivots levels. The more traded the stock is, the less the difference tends to be. Highly traded stocks are usually within a few cents (but even they occasionally have large differences in spikes). There is nothing that can be done about this. The 6th Camarilla level does not have a standard definition and may not match the level shown on other platforms. It does match the definition used by DAS Trader Pro. Replay mode for stocks does not work correctly. This is due to some important Pine Script variables provided by the TradingView platform and used by the script not being assigned correct values in replay mode. Futures do not use these variables, so they should work in replay mode. The indicator is an intraday indicator (despite also being able to show weekly and monthly pivots on an intraday chart). It deactivates on a daily timeframe and higher. Sub-minute timeframes are also not supported. The indicator was developed and tested for US/European stocks, US futures and EURUSD forex and BTCUSD. It should work as intended for stocks and futures in different countries, and for all forex and crypto, but this is tested as much as the security it was developed for. █ DISCLAIMER This indicator is provided for information only and should not be used in isolation without a good understand of the system and without considering other factors. You should not take trades using real money based solely on what this indicator says. Any trades you take are entirely at your own risk.
Indicador Pine Script®
por BruzX
22
Scissors&Knifes V3.1✂️ The Scissors (PAG Chop V4 Engine) 🧠 Core idea Scissors measure market compression and breakout readiness. They use a modified Choppiness Index that looks at the relationship between: True Range volatility (ATR × period length) The total high–low range over the same window. The smaller the ratio (sum of TR vs range), the more directional and impulsive the market is. The higher the ratio, the more “sideways” the market trades. This version smooths the result over PAG_SMOOTHLEN bars and applies several color bands that correspond to volatility states. 🎨 Color code meaning Range State Color Interpretation ≤ 30 Strong Red #8B0000 Momentum exhaustion on downside, sellers dominating — about to reverse or already strong down-trend. 30 – 38 Brick Red #A52A2A Fading downside pressure; often the “bleeding edge” of a bearish climax. 38 – 55 Transparent black (α≈100) Neutral chop zone — indecision, range-building. 55 – 61.8 Yellow (optional) #DAA520 Early compression pocket where volatility starts contracting; the calm before a trend. 61.8 – 70 Bright Green #556B2F Energy release phase: volatility breaking out upward. ≥ 70 Strong Green #355E3B Sustained bullish drive, often continuation leg of a trend. 🪶 Secret nuance: The transition bands (38–45 and 45–55) are treated as fully transparent to mark “dead zones.” When PAG Chop sits here, all label activity pauses — the system resets its cluster memory so the next colored print begins a new “cluster”, letting you clearly see where fresh directional momentum starts. 🧩 Cluster logic Every time a colored (non-transparent) reading appears, it belongs to a “color cluster.” Grey labels (= count 1) mark the genesis of a new cluster, and following counts 2, 3, 4 … represent the internal continuity of that trend state. You can optionally hide the first N grey or count 2 labels to reduce clutter on the initial stabilization bars. ✂️ Label meaning Each label shows: Emoji ✂️ Current count (e.g. ✂️ = 3 means 3 timeframes are simultaneously firing) Optional list of the timeframes that contribute. So a high count (e.g. 8–10) means many lower TFs are synchronizing volatility breakout — a multiframe alignment, often just before an acceleration burst. 🔪 The Knife (Mr Blonde V4 Engine) 🧠 Core idea Mr Blonde converts the slope of a long EMA into an angle-of-attack metric — literally the “tilt” of market momentum. It computes the EMA gradient relative to price span and rescales it into degrees (-5 ° to +5 °). The steeper the angle, the stronger the directional push. 🎨 Color code meaning Angle range Color Interpretation ≥ +5 ° Transparent (Black 1) Fully over-extended up move — wait for reset. +3.57 – +5 ° Dark Red Strong upward slope, momentum apex. +2.14 – +3.57 ° Orange Medium upward slope, trend acceleration zone. +0.71 – +2.14 ° Light Orange Mild upward bias, pre-momentum phase. 0 to -0.71 ° Yellow Neutral transition. -0.71 – -2.14 ° Olive Green Soft bearish slope. -2.14 – -3.57 ° Olive Drab Building bearish momentum. -3.57 – -5 ° Hunter Green Strong downward angle, aggressive push. ≤ -5 ° Transparent (Black 2) Oversold/over-tilted — likely exhaustion. 🪶 Secret nuance: Mr Blonde uses a “span normalization” factor that divides EMA slope by the dynamic range of highs and lows. This lets it compare angles fairly across assets with different volatility profiles (e.g. BTC vs ES) — it’s one of the rare EMA-angle implementations that self-scales properly. 🗡 Label meaning Emoji 🔪 Count = how many TFs share the same momentum angle bias. When many TFs show the same slope polarity (e.g. knife = 8), you’re in a deep momentum cascade — a “knife trend.” 💫 Yellow knife The yellow state marks neutrality or slope flattening. If you enable yellow visibility (mb_show_yellow), you can see where momentum cools off — often the earliest reversal hint. ⚙️ Shared mechanics between ✂️ and 🔪 Multi-timeframe sweep The script cycles through 1 m → 10 m by default, running both engines once per TF. Each returning true adds +1 to the count. So: sc_hits = count of timeframes where PAG fires + 1 knife_hits = count of timeframes where MB fires + 1 That “+1 shift” means there’s always at least 1, letting count = 1 represent the local TF itself. Cluster limiter If Limit max labels per cluster is on, you cap how many total symbols (both ✂️ & 🔪, including trails) can appear within one color phase — avoiding chart spam during extended trends. Trails Each printed label seeds a short-lived “trail” sequence — faded copies extending N bars forward. Trails visualize the linger effect of the last signal, useful for visually connecting bursts in momentum. Grey or count = 1 labels can have shorter or longer trails depending on your overrides (*_trail_bars_grey). They’re purely visual and do not affect alerting. Alerts Alerts fire independently of whether you hide labels — unless you enable “respect filters”. This guarantees you never miss a structural signal even if you suppress visuals for clarity. 🌈 Interpreting Both Together Scenario Interpretation ✂️ = low (1–2) + 🔪 rising (red/orange) Market just leaving chop, early thrust stage. ✂️ = high (≥ 5) + 🔪 green Fully aligned breakout continuation — trend in progress. ✂️ = yellow cluster + 🔪 yellow Volatility squeeze, energy buildup — next expansion near. ✂️ = green cluster → 🔪 turns red Cross-state conflict; likely transition or correction. ✂️ = grey + 🔪 grey Reset condition — both engines cooling; stand aside. 💡 Hidden edge: Scissors signal potential, Knife measures kinetic force. The perfect storm is when ✂️ goes from yellow→green one bar before 🔪 shifts from orange→green — it catches the birth of directional flow while volatility is still tight. 🧭 Reading the labels intuitively Grey ✂️/🔪 = 1 → embryonic state, may fizzle or bloom. ✂️/🔪 = 2 or 3 → expansion taking hold. ✂️/🔪 ≥ 4 (mid black) → strong synchronized drive across TFs. Transparent gap → cluster reset; prepare for new phase. Trail lines → echo of previous cluster strength. Final secret tip 🗝 Because both engines are mathematically uncorrelated (volatility vs EMA angle), when they agree in color polarity on multiple TFs, you have one of the cleanest probabilistic trend windows possible. If you ever see ✂️ = 6 + 🔪 = 6 both pointing the same way — that’s a “knife-through-the-scissors” moment: volatility expansion and directional slope synchronized — those are the bars where institutional algorithms tend to add size.
Indicador Pine Script®
por CoderPAG
Opening Range Break LRSThis script is designed for a trend-following, opening range breakout strategy. The main idea is to only trade breakouts that happen in the same direction as the short-term trend, which the script identifies using a linear regression slope. 1. Identify the Short-Term Trend This is the first and most important step. The script does this for you using the Linear Regression and the bar coloring. • If the bars are colored BLUE: The linear regression slope is positive. This means the script considers the short-term trend to be UP. A trader using this script would only look for long (buy) trades. • If the bars are colored YELLOW: The linear regression slope is negative. This means the script considers the short-term trend to be DOWN. A trader using this script would only look for short (sell) trades. This filter is designed to prevent you from trading a "false breakout" against the immediate momentum. 2. Watch the Opening Ranges Form At the start of the trading session (8:30 AM by default), the script will begin drawing boxes for the 5, 15, 30, and 60-minute opening ranges you've enabled. • The 5-minute box (e.g., gray) will be set after the 8:30 - 8:35 period. • The 15-minute box (e.g., blue) will be set after the 8:30 - 8:45 period. • ...and so on. These boxes, which extend for the rest of the day, represent the key high and low levels established at the open. The "Live Box Extension" input simply keeps the right edge of the box a few bars away from the current price so you can see it clearly. 3. Look for a Filtered Breakout Signal This is where the trend filter (Step 1) and the range boxes (Step 2) come together. Bullish Trade Example (Long): 1. A trader sees the bars are colored BLUE (uptrend). They are now only looking for a break above one of the ORB highs. 2. They will ignore any break below the ORB lows, as that would be trading against the trend filter. 3. The price moves up and finally closes above the 15-minute ORB high. 4. The script will plot a green "Break 15" label. This is the trader's signal to enter a long trade. Bearish Trade Example (Short): 1. A trader sees the bars are colored YELLOW (downtrend). They are now only looking for a break below one of the ORB lows. 2. They will ignore any break above the ORB highs. 3. The price moves down and closes below the 5-minute ORB low. 4. The script will plot a red "Break 5" label. This is the trader's signal to enter a short trade. 4. Use Multiple Timeframes for Context The real power of this script is seeing all the ranges at once. A trader wouldn't just trade them in isolation. • Confirmation: A "Break 5" signal is a quick, early signal. But if the price also breaks the "15" and "30" minute highs, it signals much stronger bullish consensus, which might encourage the trader to hold the trade longer. • Support & Resistance: The other ORB levels act as a map for the day. o As Targets: If a trader takes a "Break 15" long signal, the 30-minute ORB high and 60-minute ORB high become logical profit targets. o As Warning Signs: If the price gives a "Break 5" long signal but is struggling right under the 15-minute high, a trader might wait for that 15-minute level to break before entering, seeing it as a key resistance level. Summary: A Trader's Workflow 1. Morning (8:30 AM): Watch the script. What color are the bars? (Blue = longs only, Yellow = shorts only). 2. Wait: Let the 5, 15, 30, and 60-minute ranges form. The boxes will be drawn on the chart. 3. Execute: Wait for a "Break" signal (a label) that matches your trend direction. 4. Manage: Use the other ORB levels as potential profit targets or as confirmation of the move's strength. 5. Single Signal: The "Single Signal Only" input, if checked, ensures they only get one signal per timeframe (e.g., one "Break 15" long, and that's it for the day), which helps prevent over-trading in choppy conditions.
Indicador Pine Script®
por j2m2t2
Session Streaks [LuxAlgo]The Session Streaks tool allows traders to identify whether a session is bullish or bearish on the chart. It also shows the current session streak, or the number of consecutive bullish or bearish sessions. The tool features a dashboard with information about the session streaks of the underlying product on the chart. 🔶 USAGE Analyzing session streaks is commonly used for market timing by studying the number of consecutive sessions over time and how long they last before the market changes direction. We identify a bullish session as one in which the closing price is equal to or greater than the opening price, and a bearish session as one in which the closing price is below the opening price. Each session is labeled according to its bias (bullish or bearish) and the number of consecutive sessions of the same type that conform the current streak. 🔹 Dashboard The dashboard at the top shows information about the current session. Under the "Streaks" header, historical information about session streaks is displayed, divided into bullish and bearish categories. Number: Total number of streaks. Median: The average duration of those streaks. We chose the median over the mean to avoid misrepresentation due to outliers. Mode: The most common streak duration. As the image shows, for this particular market, there are more bullish streaks than bearish ones. Bullish streaks have an average duration that is longer than that of bearish streaks, and both have the same most common streak duration. If the current session is bullish and the median streak duration for bullish sessions is three, then we could consider scenarios in which the next two sessions are bullish. 🔶 DETAILS 🔹 Streaks On Larger Timeframes On timeframes lower than or equal to Daily, the tool identifies each consecutive session, but this behavior changes on larger timeframes. On timeframes larger than daily, the tool identifies the last session of each bar. Let's use the chart in the image as a reference. At the top of the image, there is a daily chart where each session corresponds to each candle. One candle equals one day. In the middle, we have a weekly chart where each session is the last session of each week, which is usually Friday for the Nasdaq 100 futures contract. The levels and labels displayed correspond to the last session within each candle, which is the last day of each week. The levels and labels on the monthly chart correspond to the last session of each month, which is the last day of each month. 🔹 Gradient Style Traders can choose between two different color gradients for the session background. Each gradient provides different information about price behavior within each session. Horizontal: Green indicates prices at the top of the session range and red indicates prices at the bottom. Vertical: Green indicates prices that are equal to or greater than the open price and red indicates prices that are below the open price of the session. 🔶 SETTINGS 🔹 Dashboard Dashboard: Enable or disable the dashboard. Position: Select the location of the dashboard. Size: Select the dashboard size. 🔹 Style Bullish: Select a color for bullish sessions. Bearish: Select a color for bearish sessions. Transparency: Select a transparency level from 100 to 0. Gradient: Select a horizontal or vertical gradient.
Indicador Pine Script®
por LuxAlgo
14
pine script tradingbot - many ema oscillator## 🧭 **Many EMA Oscillator (TradingView Pine Script Indicator)** *A multi-layer EMA differential oscillator for trend strength and momentum analysis* --- ### 🧩 **Overview** The **Many EMA Oscillator** is a **TradingView Pine Script indicator** designed to help traders visualize **trend direction**, **momentum strength**, and **multi-timeframe EMA alignment** in one clean oscillator panel. It’s a **custom EMA-based trend indicator** that shows how fast or slow different **Exponential Moving Averages (EMAs)** are expanding or contracting — helping you identify **bullish and bearish momentum shifts** early. This **Pine Script EMA indicator** is especially useful for traders looking to combine multiple **EMA signals** into one **momentum oscillator** for better clarity and precision. --- ### ⚙️ **How It Works** 1. **Multiple EMA Layers:** The indicator calculates seven **EMAs** (default: 20, 50, 100, 150, 200, 300) and applies a **smoothing filter** using another EMA (default smoothing = 20). This removes short-term noise and gives a smoother, professional-grade momentum reading. 2. **EMA Gap Analysis:** The oscillator measures the **difference between consecutive EMAs**, revealing how trend layers are separating or converging. ``` diff1 = EMA(20) - EMA(50) diff2 = EMA(50) - EMA(100) diff3 = EMA(100) - EMA(150) diff4 = EMA(150) - EMA(200) diff5 = EMA(200) - EMA(300) ``` These gaps (or “differentials”) show **trend acceleration or compression**, acting like a **multi-EMA MACD system**. 3. **Color-Coded Visualization:** Each differential (`diff1`–`diff5`) is plotted as a **histogram**: - 🟢 **Green bars** → EMAs expanding → bullish momentum growing - 🔴 **Red bars** → EMAs contracting → bearish momentum or correction This gives a clean, compact view of **trend strength** without cluttering your chart. 4. **Automatic Momentum Signals:** - **🟡 Up Triangle** → All EMA gaps increasing → strong bullish trend alignment - **⚪ Down Triangle** → All EMA gaps decreasing → trend weakening or bearish transition --- ### 📊 **Inputs** | Input | Default | Description | |-------|----------|-------------| | `smmoth_emas` | 20 | Smoothing factor for all EMAs | | `Length2`–`Length7` | 20–300 | Adjustable EMA periods | | `Length21`, `Length31`, `Length41`, `Length51` | Optional | For secondary EMA analysis | --- ### 🧠 **Interpretation Guide** | Observation | Meaning | |--------------|----------| | Increasing green bars | Trend acceleration and bullish continuation | | Decreasing red bars | Trend exhaustion or sideways consolidation | | Yellow triangles | All EMA layers aligned bullishly | | White triangles | All EMA layers aligned bearishly | This **EMA oscillator for TradingView** simplifies **multi-EMA trading strategies** by showing alignment strength in one place. It works great for **swing traders**, **scalpers**, and **trend-following systems**. --- ### 🧪 **Best Practices for Use** - Works on **all TradingView timeframes** (1m, 5m, 1h, 1D, etc.) - Suitable for **stocks, forex, crypto, and indices** - Combine with **RSI**, **MACD**, or **price action** confirmation - Excellent for detecting **EMA compression zones**, **trend continuation**, or **momentum shifts** - Can be used as part of a **multi-EMA trading strategy** or **trend strength indicator setup** --- ### 💡 **Why It Stands Out** - 100% built in **Pine Script v6** - Optimized for **smooth EMA transitions** - Simple color-coded momentum visualization - Professional-grade **multi-timeframe trend oscillator** This is one of the most **lightweight and powerful EMA oscillators** available for TradingView users who prefer clarity over clutter. --- ### ⚠️ **Disclaimer** This indicator is published for **educational and analytical purposes only**. It does **not provide financial advice**, buy/sell signals, or investment recommendations. Always backtest before live use and trade responsibly. --- ### 👨‍💻 **Author** Developed by **@algo_coders** Built in **Pine Script v6** on **TradingView** Licensed under the (mozilla.org)
Indicador Pine Script®
por algo_coders
Power RSI Segment Runner [CHE] Power RSI Segment Runner — Tracks RSI momentum across higher timeframe segments to detect directional switches for trend confirmation. Summary This indicator calculates a running Relative Strength Index adapted to segments defined by changes in a higher timeframe, such as daily closes, providing a smoothed view of momentum within each period. It distinguishes between completed segments, which fix the final RSI value, and ongoing ones, which update in real time with an exponential moving average filter. Directional switches between bullish and bearish momentum trigger visual alerts, including overlay lines and emojis, while a compact table displays current trend strength as a progress bar. This segmented approach reduces noise from intra-period fluctuations, offering clearer signals for trend persistence compared to standard RSI on lower timeframes. Motivation: Why this design? Standard RSI often generates erratic signals in choppy markets due to constant recalculation over fixed lookback periods, leading to false reversals that mislead traders during range-bound or volatile phases. By resetting the RSI accumulation at higher timeframe boundaries, this indicator aligns momentum assessment with broader market cycles, capturing sustained directional bias more reliably. It addresses the gap between short-term noise and long-term trends, helping users filter entries without over-relying on absolute overbought or oversold thresholds. What’s different vs. standard approaches? - Baseline Reference: Diverges from the classic Wilder RSI, which uses a fixed-length exponential moving average of gains and losses across all bars. - Architecture Differences: - Segments momentum resets at higher timeframe changes, isolating calculations per period instead of continuous history. - Employs persistent sums for ups and downs within segments, with on-the-fly RSI derivation and EMA smoothing. - Integrates switch detection logic that clears prior visuals on reversal, preventing clutter from outdated alerts. - Adds overlay projections like horizontal price lines and dynamic percent change trackers for immediate trade context. - Practical Effect: Charts show discrete RSI endpoints for past segments alongside a curved running trace, making momentum evolution visually intuitive. Switches appear as clean, extendable overlays, reducing alert fatigue and highlighting only confirmed directional shifts, which aids in avoiding whipsaws during minor pullbacks. How it works (technical) The indicator begins by detecting changes in the specified higher timeframe, such as a new daily bar, to define segment boundaries. At each boundary, it finalizes the prior segment's RSI by summing positive and negative price changes over that period and derives the value from the ratio of those sums, then applies an exponential moving average for smoothing. Within the active segment, it accumulates ongoing ups and downs from price changes relative to the source, recalculating the running RSI similarly and smoothing it with the same EMA length. Points for the running RSI are collected into an array starting from the segment's onset, forming a curved polyline once sufficient bars accumulate. Comparisons between the running RSI and the last completed segment's value determine the current direction as long, short, or neutral, with switches triggering deletions of old visuals and creation of new ones: a label at the RSI pane, a vertical dashed line across the RSI range, an emoji positioned via ATR offset on the price chart, a solid horizontal line at the switch price, a dashed line tracking current close, and a midpoint label for percent change from the switch. Initialization occurs on the first bar by resetting accumulators, and visualization gates behind a minimum bar count since the segment start to avoid early instability. The trend strength table builds vertically with filled cells proportional to the rounded RSI value, colored by direction. All drawing objects update or extend on subsequent bars to reflect live progress. Parameter Guide EMA Length — Controls the smoothing applied to the running RSI; higher values increase lag but reduce noise. Default: 10. Trade-offs: Shorter settings heighten sensitivity for fast markets but risk more false switches; longer ones suit trending conditions for stability. Source — Selects the price data for change calculations, typically close for standard momentum. Default: close. Trade-offs: Open or high/low may emphasize gaps, altering segment intensity. Segment Timeframe — Defines the higher timeframe for segment resets, like daily for intraday charts. Default: D. Trade-offs: Shorter frames create more frequent but shorter segments; longer ones align with major cycles but delay resets. Overbought Level — Sets the upper threshold for potential overbought conditions (currently unused in visuals). Default: 70. Trade-offs: Adjust for asset volatility; higher values delay bearish warnings. Oversold Level — Sets the lower threshold for potential oversold conditions (currently unused in visuals). Default: 30. Trade-offs: Lower values permit deeper dips before signaling bullish potential. Show Completed Label — Toggles labels at segment ends displaying final RSI. Default: true. Trade-offs: Enables historical review but can crowd charts on dense timeframes. Plot Running Segment — Enables the curved polyline for live RSI trace. Default: true. Trade-offs: Visualizes intra-segment flow; disable for cleaner panes. Running RSI as Label — Displays current running RSI as a forward-projected label on the last bar. Default: false. Trade-offs: Useful for quick reads; may overlap in tight scales. Show Switch Label — Activates RSI pane labels on directional switches. Default: true. Trade-offs: Provides context; omit to minimize pane clutter. Show Switch Line (RSI) — Draws vertical dashed lines across the RSI range at switches. Default: true. Trade-offs: Marks reversal bars clearly; extends both ways for reference. Show Solid Overlay Line — Projects a horizontal line from switch price forward. Default: true. Trade-offs: Acts as dynamic support/resistance; wider lines enhance visibility. Show Dashed Overlay Line — Tracks a dashed line from switch to current close. Default: true. Trade-offs: Shows price deviation; thinner for subtlety. Show Percent Change Label — Midpoint label tracking percent move from switch. Default: true. Trade-offs: Quantifies progress; centers dynamically. Show Trend Strength Table — Displays right-side table with direction header and RSI bar. Default: true. Trade-offs: Instant strength gauge; fixed position avoids overlap. Activate Visualization After N Bars — Delays signals until this many bars into a segment. Default: 3. Trade-offs: Filters immature readings; higher values miss early momentum. Segment End Label — Color for completed RSI labels. Default: 7E57C2. Trade-offs: Purple tones for finality. Running RSI — Color for polyline and running elements. Default: yellow. Trade-offs: Bright for live tracking. Long — Color for bullish switch visuals. Default: green. Trade-offs: Standard for uptrends. Short — Color for bearish switch visuals. Default: red. Trade-offs: Standard for downtrends. Solid Line Width — Thickness of horizontal overlay line. Default: 2. Trade-offs: Bolder for emphasis on key levels. Dashed Line Width — Thickness of tracking and vertical lines. Default: 1. Trade-offs: Finer to avoid dominance. Reading & Interpretation Completed segment RSIs appear as static points or labels in purple, indicating the fixed momentum at period close—values drifting toward the upper half suggest building strength, while lower half implies weakness. The yellow curved polyline traces the live smoothed RSI within the current segment, rising for accumulating gains and falling for losses. Directional labels and lines in green or red flag switches: green for running momentum exceeding the prior segment's, signaling potential uptrend continuation; red for the opposite. The right table's header colors green for long, red for short, or gray for neutral/wait, with filled purple bars scaling from bottom (low RSI) to top (high), topped by the numeric value. Overlay elements project from switch bars: the solid green/red line as a price anchor, dashed tracker showing pullback extent, and percent label quantifying deviation—positive for alignment with direction, negative for counter-moves. Emojis (up arrow for long, down for short) float above/below price via ATR spacing for quick chart scans. Practical Workflows & Combinations - Trend Following: Enter long on green switch confirmation after a higher high in structure; filter with table strength above midpoint for conviction. Pair with volume surge for added weight. - Exits/Stops: Trail stops to the solid overlay line on pullbacks; exit if percent change reverses beyond 2 percent against direction. Use wait bars to confirm without chasing. - Multi-Asset/Multi-TF: Defaults suit forex/stocks on 1H-4H with daily segments; for crypto, shorten EMA to 5 for volatility. Scale segment TF to weekly for daily charts across indices. - Combinations: Overlay on EMA clouds for confluence—switch aligning with cloud break strengthens signal. Add volatility filters like ATR bands to debounce in low-volume regimes. Behavior, Constraints & Performance Signals confirm on bar close within segments, with running polyline updating live but gated by minimum bars to prevent flicker. Higher timeframe changes may introduce minor repaints on timeframe switches, mitigated by relying on confirmed HTF closes rather than intrabar peeks. Resource limits cap at 500 labels/lines and 50 polylines, pruning old objects on switches to stay efficient; no explicit loops, but array growth ties to segment length—suitable for up to 500-bar histories without lag. Known limits include delayed visualization in short segments and insensitivity to overbought/oversold levels, as thresholds are inputted but not actively visualized. Gaps in source data reset accumulators prematurely, potentially skewing early RSI. Sensible Defaults & Quick Tuning Start with EMA length 10, daily segments, and 3-bar wait for balanced responsiveness on hourly charts. For excessive switches in ranging markets, increase wait bars to 5 or EMA to 14 to dampen noise. If signals lag in trends, drop EMA to 5 and use 1H segments. For stable assets like indices, widen to weekly segments; tune colors for dark/light themes without altering logic. What this indicator is—and isn’t This tool serves as a momentum visualization and switch detector layered over price action, aiding trend identification and confirmation in segmented contexts. It is not a standalone trading system, predictive model, or risk calculator—always integrate with broader analysis, position sizing, and stop-loss discipline. View it as an enhancement for discretionary setups, not automated alerts without validation. Disclaimer The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context. Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved. By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk. Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts. Best regards and happy trading Chervolino
Indicador Pine Script®
por chervolino
4
PM Range Breaker [CHE] PM Range Breaker — Premarket bias with first-five range breaks, optional SWDEMA regime latch, and simple two-times-range targets Summary This indicator sets a once-per-day directional bias during New York premarket and then tracks a strict first-five-minutes range from the session open. After the first five complete, it marks clean breakouts and can project targets at two times the measured range. A second mode latches an EMA-based regime to inform the bias and optional background tinting. A compact panel reports live state, first-five levels, and rolling hit rates of both bias modes using a user-defined midday close for statistics. Motivation: Why this design? Intraday traders often get whipsawed by early noise or by fast flips in trend filters. This script commits to a bias at a single premarket minute and then waits for the market to present an objective structure: the first-five range. Breaks after that window are clearer and easier to manage. The alternative SWDEMA regime gives a slower, latched context for users who prefer a trend scaffold rather than a midpoint reference. What’s different vs. standard approaches? Baseline: Typical open-range-breakout lines or a single moving-average filter without daily commitment. Architecture differences: Bias decision at a fixed New York time using either a midpoint lookback (“Classic”) or a two-EMA regime latch (“SWDEMA”). Strict five-minute window from session open; breakout shapes print only after that window. Single-shot breakout direction per session (debounce) and optional two-times-range targets. On-chart panel with hit rates using a configurable midday close for statistics. Practical effect: Cleaner visuals, fewer repeated signals, and a traceable daily decision that can be evaluated over time. How it works (technical) Time handling uses New York session times for premarket decision, open, first-five end, and a midday statistics checkpoint. Classic bias: A midpoint is computed from the highest and lowest over a user period; at the premarket minute, the bias is set long when the close is above the midpoint, short otherwise. SWDEMA bias: Two EMAs define a regime score that requires price and trend agreement; when both agree on a confirmed bar, the regime latches. At the premarket minute, the daily bias is set from the current regime. The first-five range captures high and low from open until the end minute, then freezes. Breakouts are detected after that window using close-based cross logic. The script draws range lines and optional targets at two times the frozen range. A session break direction latch prevents duplicate break markers. Statistics compare daily open and a configurable midday close to record if the chosen bias aligned with the move. Optional elements include EMA lines, midpoint line, latched-regime background, and regime switch markers. Data aggregation for day logic and the first-five window is sampled on one-minute data with explicit lookahead off. On charts above one minute, values update intra-bar until the underlying minute closes. Parameter Guide Premarket Start (NY) — Minute when the bias is decided — Default: 08:30 — Move earlier for more stability; later for recency. Market Open (NY) — Session start used for the first-five window — Default: 09:30 — Align to instrument’s RTH if different. First-5 End (NY) — End of the first-five window — Default: 09:35 — Extend slightly to capture wider opening ranges. Day End (NY) for Stats — Midday checkpoint for hit rate — Default: 12:00 — Use a later time for a longer evaluation window. Show First-5 Lines — Draw the frozen range lines — Default: On — Turn off if your chart is crowded. Show Bias Background (Session) — Tint by daily bias during session — Default: On — Useful for directional context. Show Break Shapes — Print breakout triangles — Default: On — Disable if you only want lines and alerts. Show 2R Targets (Optional) — Plot targets at two times the range — Default: On — Switch off if you manage exits differently. Line Length Right — Extension length of drawn lines — Default: 20 (bars) — Increase for slower timeframes. High/Low Line Colors — Visual colors for range levels — Defaults: Green/Red — Adjust to your theme. Long/Short Bias Colors — Background tints — Defaults: Green/Red with high transparency — Lower transparency for stronger emphasis. Show Corner Panel — Enable the info panel — Default: On — Centralizes status and numbers. Show Hit Rates in Panel — Include success rates — Default: On — Turn off to reduce panel rows. Panel Position — Anchor on chart — Default: Top right — Move to avoid overlap. Panel Size — Text size in panel — Default: Small — Increase on high-resolution displays. Dark Panel — Dark theme for the panel — Default: On — Match your chart background. Show EMA Lines — Plot blue and red EMAs — Default: Off — Enable for SWDEMA context. Show Midpoint Line — Plot the midpoint — Default: Off — Useful for Classic mode visualization. Midpoint Lookback Period — Bars for high-low midpoint — Default: 300 — Larger values stabilize; smaller values respond faster. Midpoint Line Color — Color for midpoint — Default: Gray — A neutral line works best. SWDEMA Lengths (Blue/Red) — Periods for the two EMAs — Defaults: 144 and 312 — Longer values reduce flips. Sources (Blue/Red) — Price sources — Defaults: Close and HLC3 — Adjust if you prefer consistency. Offsets (Blue/Red) — Pixel offsets for EMA plots — Defaults: zero — Use only for visual shift. Show Latched Regime Background — Background by SWDEMA regime — Default: Off — Separate from session bias. Latched Background Transparency — Opacity of regime background — Default: eighty-eight — Lower value for stronger tint. Show Latch Switch Markers — Plot regime change markers — Default: Off — For auditing regime changes. Bias Mode — Classic midpoint or SWDEMA latch — Default: Classic — Choose per your style. Background Mode — Session bias or SWDEMA regime — Default: Session — Decide which background narrative you want. Reading & Interpretation Panel: Shows the active bias, first-five high and low, and a state that reads Building during the window, Ready once frozen, and Break arrows when a breakout occurs. Hit rates show the percentage of days where each bias mode aligned with the midday move. Colors and shapes: Green background implies long bias; red implies short bias. Triangle markers denote the first valid breakout after the first-five window. Optional regime markers flag regime changes. Lines: First-five high and low form the core structure. Optional targets mark a level at two times the frozen range from the breakout side. Practical Workflows & Combinations Trend following: Choose a bias mode. Wait for the first clean breakout after the first-five window in the direction of the bias. Confirm with structure such as higher highs and higher lows or lower highs and lower lows. Exits and risk: Conservative users can trail behind the opposite side of the first-five range. Aggressive users can scale near the two-times-range target. Multi-asset and multi-TF: Works well on intraday timeframes from one minute upward. For non-US sessions, adjust the time inputs to the instrument’s regular trading hours. Behavior, Constraints & Performance Repaint and confirmation: Bias and regime decisions use confirmed bars. Breakout signals evaluate on bar close at the chart timeframe. On higher timeframes, minute-based sources update within the live bar until the minute closes. security and HTF: The script samples one-minute data. Lookahead is off. Values stabilize once the source minute closes. Resources: `max_bars_back` is five thousand. Drawing objects and the panel update efficiently, with position extensions handled on the last bar. Known limits: Midday statistics use the configured time, not the official daily close. Session logic assumes New York session timing. Targets are simple multiples of the first-five range and do not adapt to volatility beyond that structure. Sensible Defaults & Quick Tuning Start with Classic bias, midpoint lookback at three hundred, and all visuals on. Too many flips in context → switch to SWDEMA mode or increase EMA lengths. Breakouts feel noisy → extend the first-five end by a minute or two, or wait for a retest by your own rules. Too sluggish → reduce midpoint lookback or shorten EMA lengths. Chart cluttered → hide EMA or midpoint lines and keep only range levels and breakout shapes. What this indicator is—and isn’t This is a visualization and signal layer for session bias and first-five structure. It does not manage orders, position sizing, or risk. It is not predictive. Use it alongside market structure, execution rules, and independent risk controls. Disclaimer The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context. Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved. By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk. Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts. Best regards and happy trading Chervolino Many thanks to LonesomeTheBlue for the original work. I adapted the midpoint calculation for this script. www.tradingview.com
Indicador Pine Script®
por chervolino
saodisengxiaoyu-lianghua-2.1- This indicator is a modular, signal-building framework designed to generate long and short signals by combining a chosen leading indicator with selectable confirmation filters. It runs on Pine Script version 5, overlays directly on price, and is built to be highly configurable so traders can tailor the signal logic to their market, timeframe, and trading style. It includes a dashboard to visualize which conditions are active and whether they validate a signal, and it outputs clear buy/sell labels and alert conditions so you can automate or monitor trades with confidence. Core Design - Leading Indicator: You choose one primary signal generator from a broad list (for example, Range Filter, Supertrend, MACD, RSI, Ichimoku, and many others). This serves as the anchor of the system and determines when a preliminary long or short setup exists. - Confirmation Filters: You can enable additional filters that validate the leading signal before it becomes actionable. Each “respect…” input toggles a filter on or off. These filters include popular tools like EMA, 2/3 EMA crosses, RQK (Nadaraya Watson), ADX/DMI, Bollinger-based oscillators, MACD variations, QQE, Hull, VWAP, Choppiness Index, Damiani Volatility, and more. - Signal Expiry: To avoid waiting indefinitely for confirmations, the indicator counts how many consecutive bars the leading condition holds. If confirmations do not align within a defined number of bars, the setup expires. This controls latency and helps reduce late or stale entries. - Alternating Signals: An optional mode enforces alternation (long must follow short and vice versa), helping avoid repeated entries in the same direction without a meaningful reset. - Aggregation Logic: The final long/short conditions are formed by combining the leading condition with all selected confirmation filters through logical conjunction. Only if all enabled filters validate the signal (within expiry constraints) does the indicator consider it a confirmed long or short. - Visualization and Alerts: The script plots buy/sell labels at signal points, provides alert conditions for automation, and displays a compact dashboard summarizing the leading indicator’s status and each confirmation’s pass/fail result using checkmarks. Leading Indicator Options - The indicator includes a very large menu of leading tools, each with its own logic to determine uptrend or downtrend impulses. Highlights include: - Range Filter: Uses a dynamic centerline and bands computed via conditional EMA/SMA and range sizing to define directional movement. It can operate in a default mode or an alternative “DW” mode. - Rational Quadratic Kernel (RQK): Applies a kernel smoothing model (Nadaraya Watson) to detect uptrends and downtrends with a focus on noise reduction. - Supertrend, Half Trend, SSL Channel: Classic trend-following tools that derive direction from ATR-based bands or moving average channels. - Ichimoku Cloud and SuperIchi: Multi-component systems validating trend via cloud position, conversion/base line relationships, projected cloud, and lagging span. - TSI (True Strength Index), DPO (Detrended Price Oscillator), AO (Awesome Oscillator), MACD, STC (Schaff Trend Cycle), QQE Mod: Momentum and cycle tools that parse direction from crossovers, zero-line behavior, and momentum shifts. - Donchian Trend Ribbon, Chandelier Exit: Trend and exit tools that can validate breakouts or sustained trend strength. - ADX/DMI: Measures trend strength and directional movement via +DI/-DI relationships and minimum ADX thresholds. - RSI and Stochastic: Use crossovers, level exits, or threshold filters to gate entries based on overbought/oversold dynamics or relative strength trends. - Vortex, Chaikin Money Flow, VWAP, Bull Bear Power, ROC, Wolfpack Id, Hull Suite: A diverse set of directional, momentum, and volume-based indicators to suit different markets and styles. - Trendline Breakout and Range Detector: Price-behavior filters that confirm signals during breakouts or within defined ranges. Confirmation Filters - Each filter is optional. When enabled, it must validate the leading condition for a signal to pass. Examples: - EMA Filter: Requires price to be above a specified EMA for longs and below for shorts, filtering signals that contradict broader trend or baseline levels. - 2 EMA Cross and 3 EMA Cross: Enforce moving average cross conditions (fast above slow for long, the reverse for short) or a three-line stacking logic for more stringent trend alignment. - RQK, Supertrend, Half Trend, Donchian, QQE, Hull, MACD (crossover vs. zero-line), AO (zero line or AC momentum variants), SSL: Each adds its characteristic validation pattern. - RSI family (MA cross, exits OB/OS zones, threshold levels) plus RSI MA direction and RSI/RSI MA limits: Multiple ways to constrain signals via relative strength behavior and trajectories. - Choppiness Index and Damiani Volatility: Prevent entries during ranging conditions or insufficient volatility; choppiness thresholds and volatility states gate the trade. - VWAP, Volume modes (above MA, simple up/down, delta), Chaikin Money Flow: Volume and flow conditions that ensure signals happen in supportive liquidity or accumulation/distribution contexts. - ADX/DMI thresholds: Demand a minimum trend strength and directional DI alignment to reduce whipsaw trades. - Trendline Breakout and Range Detector: Confirm that the price is breaking structure or remains within active range consistent with the leading setup. - By combining several filters you can create strict, conservative entries or looser setups depending on your goals. Range Filter Engine - A core building block, the Range Filter uses conditional EMA and SMA functions to compute adaptive bands around a dynamic centerline. It supports two types: - Type 1: The centerline updates when price exceeds the band thresholds; bands define acceptable drift ranges. - Type 2: Uses quantized steps (via floor operations) relative to the previous centerline to handle larger moves in discrete increments. - The engine offers smoothing for range values using a secondary EMA and can switch between raw and averaged outputs. Its hi/lo bands and centerline compose a corridor that defines directional movement and potential breakout confirmation. Signal Construction - The script computes: - leadinglongcond and leadingshortcond : The primary directional signals from the chosen leading indicator. - longCond and shortCond : Final signals formed by combining the leading conditions with all enabled confirmations. Each confirmation contributes a boolean gate. If a filter is disabled, it contributes a neutral pass-through, keeping the logic intact without enforcing that condition. - Expiry Logic: The code counts consecutive bars where the leading condition remains true. If confirmations do not line up within the user-defined “Signal Expiry Candle Count,” the setup is abandoned and the signal does not trigger. - Alternation: An optional state ensures that long and short signals alternate. This can reduce repeated entries in the same direction without a clear reset. - Finally, longCondition and shortCondition represent the actionable signals after expiry and alternation logic. These drive the label plotting and alert conditions. Visualization - Buy and Sell Labels: When longCondition or shortCondition confirm, the script plots annotated labels directly on the chart, making entries easy to see at a glance. The labels use color coding and clear text tags (“long” vs. “short”). - Dashboard: A table summarizes the status of the leading indicator and all confirmations. Each row shows the indicator label and whether it passed (✔️) or failed (❌) on the current bar. This intensely practical UI helps you diagnose why a signal did or did not trigger, empowering faster strategy iteration and parameter tuning. - Failed Confirmation Markers: If a setup expires (count exceeds the limit) and confirmations failed to align, the script can mark the chart with a small label and provide a tooltip listing which confirmations did not pass. It’s a helpful audit trail to understand missed trades or prevent “chasing” invalid signals. - Data Window Values: The script outputs signal states to the data window, which can be useful for debugging or building composite conditions in multi-indicator templates. Inputs and Parameters - You control the indicator from a comprehensive input panel: - Setup: Signal expiry count, whether to enforce alternating signals, and whether to display labels and the dashboard (including position and size). - Leading Indicator: Choose the primary signal generator from the large list. - Per-Filter Toggles: For each confirmation, a respect... toggle enables or disables it. Many include sub-options (like MACD type, Stochastic mode, RSI mode, ADX variants, thresholds for choppiness/volatility, etc.) to fine-tune behavior. - Range Filter Settings: Choose type and behavior; select default vs. DW mode and smoothing. The underlying functions adjust band sizes using ATR, average change, standard deviation, or user-defined scales. - Because everything is customizable, you can adapt the indicator to different assets, volatility regimes, and timeframes. Alerts and Automation - The script defines alert conditions tied to longCondition and shortCondition . You can set these alerts in your chart to trigger notifications or webhook calls for automated execution in external bots. The alert text is simple, and you can configure your own message template when creating alerts in the chart, including JSON payloads for algorithmic integration. Typical Workflow - Select a Leading Indicator aligned with your style. For trend following, Supertrend or SSL may be appropriate; for momentum, MACD or TSI; for range/trend-change detection, Range Filter, RQK, or Donchian. - Add a few key Confirmation Filters that complement the leading signal. For example: - Pair Supertrend with EMA Filter and RSI MA Direction to ensure trend alignment and positive momentum. - Combine MACD Crossover with ADX/DMI and Volume Above MA to avoid signals in low-trend or low-liquidity conditions. - Use RQK with Choppiness Index and Damiani Volatility to only act when the market is trending and volatile enough. - Set a sensible Signal Expiry Candle Count. Shorter expiry keeps entries timely and reduces lag; longer expiry captures setups that mature slowly. - Observe the Dashboard during live markets to see which filters pass or fail, then iterate. Tighten or loosen thresholds and filter combinations as needed. - For automation, turn on alerts for the final conditions and use webhook payloads to notify your trading robot. Strengths and Practical Notes - Flexibility: The indicator is a toolkit rather than a single rigid model. It lets you test different combinations rapidly and visualize outcomes immediately. - Clarity: Labels, dashboard, and failed-confirmation markers make it easy to audit behavior and refine settings without digging into code. - Robustness: The expiry and alternation options add discipline, avoiding the temptation to enter late or repeatedly in one direction without a reset. - Modular Design: The logical gates (“respect…”) make the behavior transparent: if a filter is on, it must pass; if it’s off, the signal ignores it. This keeps reasoning clean. - Avoiding Overfitting: Because you can stack many filters, it’s tempting to over-constrain signals. Start simple (one leading indicator and one or two confirmations). Add complexity only if it demonstrably improves your edge across varied market regimes. Limitations and Recommendations - No single configuration is universally optimal. Markets change; tune filters for the instrument and timeframe you trade and revisit settings periodically. - Trend filters can underperform in choppy markets; likewise, momentum filters can false-trigger in quiet periods. Consider using Choppiness Index or Damiani to gate signals by regime. - Use expiry wisely. Too short may miss good setups that need a few bars to confirm; too long may cause late entries. Balance responsiveness and accuracy. - Always consider risk management externally (position sizing, stops, profit targets). The indicator focuses on signal quality; combining it with robust trade management methods will improve results. Example Configurations - Trend-Following Setup: - Leading: Supertrend uptrend for longs and downtrend for shorts. - Confirmations: EMA Filter (price above 200 EMA for long, below for short), ADX/DMI (trend strength above threshold with +DI/-DI alignment), Volume Above MA. - Expiry: 3–4 bars to keep entries timely. - Result: Strong bias toward sustained moves while avoiding weak trends and thin liquidity. - Mean-Reversion to Momentum Crossover: - Leading: RSI exits from OB/OS zones (e.g., RSI leaves oversold for long and leaves overbought for short). - Confirmations: 2 EMA Cross (fast crossing slow in the same direction), MACD zero-line behavior for added momentum validation. - Expiry: 2–3 bars for responsive re-entry. - Result: Captures momentum transitions after short-term extremes, with extra confirmation to reduce head-fakes. - Range Breakout Focus: - Leading: Range Filter Type 2 or Donchian Trend Ribbon to detect breakouts. - Confirmations: Damiani Volatility (avoid low-volatility false breaks), Choppiness Index (prefer trend-ready states), ROC positive/negative threshold. - Expiry: 1–3 bars to act on breakout windows. - Result: Better alignment to breakout dynamics, gating trades by volatility and regime. Conclusion - This indicator is a comprehensive, configurable framework that merges a chosen leading signal with an array of corroborating filters, disciplined expiry handling, and intuitive visualization. It’s designed to help you build high-quality entry signals tailored to your approach, whether that’s trend-following, breakout trading, momentum capturing, or a hybrid. By surfacing pass/fail states in a dashboard and allowing alert-based automation, it bridges the gap between discretionary analysis and systematic execution. With sensible parameter tuning and thoughtful filter selection, it can serve as a robust backbone for signal generation across diverse instruments and timeframes.
Estrategia Pine Script®
por saodisengSeven
Aurum DCX AVE Gold and Silver StrategySummary in one paragraph Aurum DCX AVE is a volatility break strategy for gold and silver on intraday and swing timeframes. It aligns a new Directional Convexity Index with an Adaptive Volatility Envelope and an optional USD/DXY bias so trades appear only when direction quality and expansion agree. It is original because it fuses three pieces rarely combined in one model for metals: a convexity aware trend strength score, a percentile based envelope that widens with regime heat, and an intermarket DXY filter. Scope and intent • Markets. Gold and silver futures or spot, other liquid commodities, major indices • Timeframes. Five minutes to one day. Defaults to 30min for swing pace • Default demo used in this publication. TVC:GOLD on 30m • Purpose. Enter confirmed volatility breaks while muting chop using regime heat and USD bias • Limits. This is a strategy. Orders are simulated on standard candles only Originality and usefulness • Unique fusion. DCX combines DI strength with path efficiency and curvature. AVE blends ATR with a high TR percentile and widens with DCX heat. DXY adds an intermarket bias • Failure mode addressed. False starts inside compression and unconfirmed breakouts during USD swings • Testability. Each component has a named input. Entry names L and S are visible in the list of trades • Portable yardstick. Weekly ATR for stops and R multiples for targets • Open source. Method and implementation are disclosed for community review Method overview in plain language You score direction quality with DCX, size an adaptive envelope with a blend of ATR and a high TR percentile, and only allow breaks that clear the band while DCX is above a heat threshold in the same direction. An optional DXY filter favors long when USD weakens and short when USD strengthens. Orders are bracketed with a Weekly ATR stop and an R multiple target, with optional trailing to the envelope. Base measures • Range basis. True Range and ATR over user windows. A high TR percentile captures expansion tails used by AVE • Return basis. Not required Components • Directional Convexity Index DCX. Measures directional strength with DX, multiplies by path efficiency, blends a curvature term from acceleration, scales to 0 to 100, and uses a rise window • Adaptive Volatility Envelope AVE. Midline ALMA or HMA or EMA plus bands sized by a blend of ATR and a high TR percentile. The blend weight follows volatility of volatility. Band width widens with DCX heat • DXY Bias optional. Daily EMA trend of DXY. Long bias when USD weakens. Short bias when USD strengthens • Risk block. Initial stop equals Weekly ATR times a multiplier. Target equals an R multiple of the initial risk. Optional trailing to AVE band Fusion rule • All gates must pass. DCX above threshold and rising. Directional lead agrees. Price breaks the AVE band in the same direction. DXY bias agrees when enabled Signal rule • Long. Close above AVE upper and DCX above threshold and DCX rising and plus DI leads and DXY bias is bearish • Short. Close below AVE lower and DCX above threshold and DCX falling and minus DI leads and DXY bias is bullish • Exit and flip. Bracket exit at stop or target. Optional trailing to AVE band Inputs with guidance Setup • Symbol. Default TVC:GOLD (Correlation Asset for internal logic) • Signal timeframe. Blank follows the chart • Confirm timeframe. Default 1 day used by the bias block Directional Convexity Index • DCX window. Typical 10 to 21. Higher filters more. Lower reacts earlier • DCX rise bars. Typical 3 to 6. Higher demands continuation • DCX entry threshold. Typical 15 to 35. Higher avoids soft moves • Efficiency floor. Typical 0.02 to 0.06. Stability in quiet tape • Convexity weight 0..1. Typical 0.25 to 0.50. Higher gives curvature more influence Adaptive Volatility Envelope • AVE window. Typical 24 to 48. Higher smooths more • Midline type. ALMA or HMA or EMA per preference • TR percentile 0..100. Typical 75 to 90. Higher favors only strong expansions • Vol of vol reference. Typical 0.05 to 0.30. Controls how much the percentile term weighs against ATR • Base envelope mult. Typical 1.4 to 2.2. Width of bands • Regime adapt 0..1. Typical 0.6 to 0.95. How much DCX heat widens or narrows the bands Intermarket Bias • Use DXY bias. Default ON • DXY timeframe. Default 1 day • DXY trend window. Typical 10 to 50 Risk • Risk percent per trade. Reporting field. Keep live risk near one to two percent • Weekly ATR. Default 14. Basis for stops • Stop ATR weekly mult. Typical 1.5 to 3.0 • Take profit R multiple. Typical 1.5 to 3.0 • Trail with AVE band. Optional. OFF by default Properties visible in this publication • Initial capital. 20000 • Base currency. USD • request.security lookahead off everywhere • Commission. 0.03 percent • Slippage. 5 ticks • Default order size method percent of equity with value 3% of the total capital available • Pyramiding 0 • Process orders on close ON • Bar magnifier ON • Recalculate after order is filled OFF • Calc on every tick OFF 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 use standard candles for signals and orders only Honest limitations and failure modes • Economic releases and thin liquidity can break assumptions behind the expansion logic • Gap heavy symbols may prefer a longer ATR window • Very quiet regimes can reduce signal contrast. Consider higher DCX thresholds or wider bands • Session time follows the exchange of the chart and can change symbol to symbol • Symbol sensitivity is expected. Use the gates and length inputs to find stable settings Open source reuse and credits • None Mode Public open source. Source is visible and free to reuse within TradingView House Rules Legal Education and research only. Not investment advice. You are responsible for your decisions. Test on historical data and in simulation before any live use. Use realistic costs.
Estrategia Pine Script®
por exlux
2
Realtime RenkoI've been working on real-time renko for a while as a coding challenge. The interesting problem here is building renko bricks that form based on incoming tick data rather than waiting for bar closes. Every tick that comes through gets processed immediately, and when price moves enough to complete a brick, that brick closes and a new one opens right then. It's just neat because you can run it and it updates as you'd expect with renko, forming bricks based purely on price movement happening in real time rather than waiting for arbitrary time intervals to pass. The three brick sizing methods give you flexibility in how you define "enough movement" to form a new brick. Traditional renko uses a fixed price range, so if you set it to 10 ticks, every brick represents exactly 10 ticks of movement. This works well for instruments with stable tick sizes and predictable volatility. ATR-based sizing calculates the average true range once at startup using a weighted average across all historical bars, then divides that by your brick value input. If you want bricks that are one full ATR in size, you'd use a brick value of 1. If you want half-ATR bricks, use 2. This inverted relationship exists because the calculation is ATR divided by your input, which lets you work with multiples and fractions intuitively. Percentage-based sizing makes each brick a fixed percentage move from the previous brick's close, which automatically scales with price level and works well for instruments that move proportionally rather than in absolute tick increments. The best part about this implementation is how it uses varip for state management. When you first load the indicator, there's no history at all. Everything starts fresh from the moment you add it to your chart because varip variables only exist in real-time. This means you're watching actual renko bricks form from real tick data as it arrives. The indicator builds its own internal history as it runs, storing up to 250 completed bricks in memory, but that history only exists for the current session. Refresh the page or reload the indicator and it starts over from scratch. The visual implementation uses boxes for brick bodies and lines for wicks, drawn at offset bar indices to create the appearance of a continuous renko chart in the indicator pane. Each brick occupies two bar index positions horizontally, which spaces them out and makes the chart readable. The current brick updates in real time as new ticks arrive, with its high, low, and close values adjusting continuously until it reaches the threshold to close and become finalized. Once a brick closes, it gets pushed into the history array and a new brick opens at the closing level of the previous one. What makes this especially useful for debugging and analysis are the hover tooltips on each brick. Clicking on any brick brings up information showing when it opened with millisecond precision, how long it took to form from open to close, its internal bar index within the renko sequence, and the brick size being used. That time delta measurement is particularly valuable because it reveals the pace of price movement. A brick that forms in five seconds indicates very different market conditions than one that takes three minutes, even though both bricks represent the same amount of price movement. You can spot acceleration and deceleration in trend development by watching how quickly consecutive bricks form. The pine logs that generate when bricks close serve as breadcrumbs back to the main chart. Every time a brick finalizes, the indicator writes a log entry with the same information shown in the tooltip. You can click that log entry and TradingView jumps your main chart to the exact timestamp when that brick closed. This lets you correlate renko brick formation with what was happening on the time-based chart, which is critical for understanding context. A brick that closed during a major news announcement or at a key support level tells a different story than one that closed during quiet drift, and the logs make it trivial to investigate those situations. The internal bar indexing system maintains a separate count from the chart's bar_index, giving each renko brick its own sequential number starting from when the indicator begins running. This makes it easy to reference specific bricks in your analysis or when discussing patterns with others. The internal index increments only when a brick closes, so it's a pure measure of how many bricks have formed regardless of how much chart time has passed. You can match these indices between the visual bricks and the log entries, which helps when you're trying to track down the details of a specific brick that caught your attention. Brick overshoot handling ensures that when price blows through the threshold level instead of just barely touching it, the brick closes at the threshold and the excess movement carries over to the next brick. This prevents gaps in the renko sequence and maintains the integrity of the brick sizing. If price shoots up through your bullish threshold and keeps going, the current brick closes at exactly the threshold level and the new brick opens there with the overshoot already baked into its initial high. Without this logic, you'd get renko bricks with irregular sizes whenever price moved aggressively, which would undermine the whole point of using fixed-range bricks. The timezone setting lets you adjust timestamps to your local time or whatever reference you prefer, which matters when you're analyzing logs or comparing brick formation times across different sessions. The time delta formatter converts raw milliseconds into human-readable strings showing days, hours, minutes, and seconds with fractional precision. This makes it immediately clear whether a brick took 12.3 seconds or 2 minutes and 15 seconds to form, without having to parse millisecond values mentally. This is the script version that will eventually be integrated into my real-time candles library. The library version had an issue with tooltips not displaying correctly, which this implementation fixes by using a different approach to label creation and positioning. Running it as a standalone indicator also gives you more control over the visual settings and makes it easier to experiment with different brick sizing methods without affecting other tools that might be using the library version. What this really demonstrates is that real-time indicators in Pine Script require thinking about state management and tick processing differently than historical indicators. Most indicator code assumes bars are immutable once closed, so you can reference `close ` and know that value will never change. Real-time renko throws that assumption out because the current brick is constantly mutating with every tick until it closes. Using varip for state variables and carefully tracking what belongs to finalized bricks versus the developing brick makes it possible to maintain consistency while still updating smoothly in real-time. The fact that there's no historical reconstruction and everything starts fresh when you load it is actually a feature, not a limitation, because you're seeing genuine real-time brick formation rather than some approximation of what might have happened in the past.
Indicador Pine Script®
por The_Peaceful_Lizard
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