Empiece

Educational

c2/FVG## **C2 Rejection & FVG Alignment** This indicator is a technical refinement tool designed to identify high-probability reversal points by combining **Price Action Rejection** with **Institutional Imbalance (Fair Value Gaps)**. It helps traders filter out market noise and focus on entries where price has clearly rejected a liquidity extreme within a valid point of interest. --- ### **Core Features** * **Candle 2 (C2) Detection:** Automatically identifies and highlights candles that "sweep" the previous candle's high/low and close back within its range. This visualizes a real-time rejection of price levels. * **Dynamic Fair Value Gaps (FVG):** Detects and plots market imbalances (FVGs) on the current timeframe in a clean, turquoise-colored layout. * **Contextual Filtering:** A specialized filter ensures that C2 signals are only displayed when they occur within a corresponding FVG, aligning momentum with structural support/resistance. * **Clean Visuals:** No cluttered labels. The indicator uses intuitive bar-coloring (Green for Bullish, Red for Bearish) to keep your charts clean and professional. --- ### **How It Works** 1. **Rejection (C2):** The script looks for a "Stop Run" or "Sweep." For a bullish signal, the price must go lower than the previous candle's low but close back inside its body. 2. **POI Validation (FVG):** The indicator searches for an active Fair Value Gap. 3. **Alignment:** * **Bullish Signal:** A Green bar appears only if a Bullish C2 taps into a **Bullish FVG** (Support). * **Bearish Signal:** A Red bar appears only if a Bearish C2 taps into a **Bearish FVG** (Resistance). 4. **Display:** Users can toggle settings to hide any FVG that does not result in a valid C2 reaction, keeping only the most relevant price zones on the screen. --- ### **Settings** * **FVG Length:** Adjust how far the turquoise zones extend across your chart. * **Hide Unused FVGs:** Clean up your chart by only showing zones that were actively tested by a C2 rejection. * **Filter C2 by FVG:** Toggle this to see all C2 rejections or only those that occur within a Point of Interest. --- Would you like me to add a specific section on **Alerts** or perhaps a **"How to Trade"** summary to this description?
Indicador Pine Script®
por Somstradamus
1
SMC Core Lite - Signals█ OVERVIEW SMC Core Lite is a lightweight, performance-optimized Smart Money Concepts (SMC) indicator designed to help traders identify institutional trading patterns and generate high-probability trade signals. This indicator combines the most essential SMC elements - Fair Value Gaps (FVG), Order Blocks (OB), and Break of Structure (BOS) - into a single, easy-to-use tool with automatic LONG/SHORT signal generation. █ CONCEPTS The indicator is built on the foundation of Smart Money Concepts, a trading methodology that focuses on understanding how institutional traders (banks, hedge funds, market makers) move the markets. 🔹 Break of Structure (BOS) When price breaks above a swing high or below a swing low, it signals a potential continuation of the trend. This confirms the market's directional bias. 🔹 Change of Character (CHoCH) When BOS occurs against the prevailing trend, it signals a potential trend reversal. This is a powerful early warning sign of shifting market sentiment. 🔹 Fair Value Gaps (FVG) Also known as imbalances, FVGs are areas on the chart where price moved so quickly that it left a "gap" in the price action. These zones often act as magnets for price to return and fill. 🔹 Order Blocks (OB) Order blocks represent the last opposing candle before a strong impulsive move. These zones mark areas where institutional orders were placed and often act as strong support/resistance levels. █ FEATURES • ✅ Break of Structure (BOS) Detection • ✅ Change of Character (CHoCH) Detection • ✅ Fair Value Gap (FVG) Identification • ✅ Order Block (OB) Detection • ✅ Automatic LONG/SHORT Signals • ✅ Auto Stop Loss & Take Profit Levels • ✅ Market Bias Dashboard • ✅ Customizable Risk:Reward Ratio • ✅ Signal Cooldown Filter • ✅ Alert Conditions for All Events • ✅ Lightweight & Fast Loading █ HOW IT WORKS The signal generation follows a confluence-based approach: 🟢 LONG SIGNAL CONDITIONS: 1. Price pulls back into a bullish zone (Bullish FVG or Bullish OB) 2. Recent Bullish BOS/CHoCH confirmed OR Market Bias is Bullish 3. Current candle closes bullish (confirmation) 4. Signal cooldown period has passed 🔴 SHORT SIGNAL CONDITIONS: 1. Price pulls back into a bearish zone (Bearish FVG or Bearish OB) 2. Recent Bearish BOS/CHoCH confirmed OR Market Bias is Bearish 3. Current candle closes bearish (confirmation) 4. Signal cooldown period has passed █ HOW TO USE 1. Add the indicator to your chart 2. Wait for market structure to develop (BOS/CHoCH labels) 3. Observe the Market Bias in the dashboard (BULL 🐂 or BEAR 🐻) 4. Look for LONG signals in bullish bias, SHORT signals in bearish bias 5. Use the auto-generated SL/TP levels for trade management 6. Set alerts to get notified of new signals █ SETTINGS ═══ SIGNALS ═══ • Show LONG/SHORT Signals → Enable/disable signal labels • Show SL/TP Lines → Display stop loss and take profit levels • Risk:Reward → Set your desired R:R ratio (1:1 to 1:5) • Signal Cooldown → Minimum bars between signals (reduces noise) ═══ STRUCTURE ═══ • Show BOS/CHoCH → Display structure break labels • Swing Length → Lookback period for swing point detection ═══ ZONES ═══ • Show FVG → Display Fair Value Gap boxes • Show Order Blocks → Display Order Block boxes • Zone Lookback → Historical bars to analyze • OB Strength → ATR multiplier for impulse move detection █ ALERTS The indicator includes 4 alert conditions: 1. 🟢 LONG Signal → Triggered when a buy signal appears 2. 🔴 SHORT Signal → Triggered when a sell signal appears 3. 🟢 Bullish BOS → Triggered on bullish break of structure 4. 🔴 Bearish BOS → Triggered on bearish break of structure To set alerts: Right-click on chart → Add Alert → Select this indicator → Choose condition █ IMPORTANT NOTES ⚠️ This indicator is optimized for speed and performance. It stores only the most recent 10 FVGs and 10 Order Blocks to ensure fast loading times. ⚠️ Works best on higher timeframes (15m, 1H, 4H, Daily) where market structure is cleaner. ⚠️ Always use proper risk management. No indicator is 100% accurate. █ BEST PRACTICES ✅ Trade in the direction of the higher timeframe bias ✅ Wait for price to pull back to zones before entering ✅ Use the 50% level of zones for optimal entries ✅ Combine with your own analysis for best results ✅ Backtest before using with real capital █ DISCLAIMER This indicator is for educational and informational purposes only. It is not financial advice. Trading involves substantial risk of loss and is not suitable for all investors. Past performance is not indicative of future results. Always do your own research and consider your financial situation before making any trading decisions. █ CREDITS Inspired by the Smart Money Concepts trading methodology and ICT (Inner Circle Trader) concepts. If you find this indicator helpful, please consider giving it a boost 🚀 and following for more trading tools! █ VERSION HISTORY v1.0 - Initial Release • BOS/CHoCH Detection • FVG & Order Block Identification • LONG/SHORT Signal Generation • Auto SL/TP Calculation • Market Bias Dashboard • Alert Conditions
Indicador Pine Script®
por ZakAlgoTrade
Aegis Parabolic Pro - Dual Timeframe Trend Alignment SystemWhat the indicator does -This indicator overlays two independent Parabolic SAR calculations on your chart, each sourced from a separate user-configurable higher timeframe. The first, called the Macro layer, acts as a structural trend filter. The second, called the Micro layer, generates the actual entry-signal circles visible on your chart. A Macro EMA is also plotted from the same higher timeframe, providing a dynamic structural reference within the trend context. -The core logic is an alignment system: the Micro entry circles are only colored and visible when both the Macro and Micro SAR layers simultaneously agree on direction. When both are bullish, the circles turn green. When both are bearish, they turn red. When the two layers disagree, the Micro circles disappear entirely. This forces discipline -- entries are only highlighted at moments of multi-timeframe structural agreement. -Each SAR is not the raw classic Parabolic SAR value. An ATR-based offset is applied to each result, shifting the SAR band further from price by a user-defined multiplier of the 14-period Average True Range. This widened band reduces false reversals in volatile conditions while preserving the directional accuracy of the classic algorithm. How it works -The Parabolic SAR algorithm tracks an acceleration factor (AF) that starts at a low value and increases each time a new extreme price is set in the current trend direction, up to a configurable maximum. The stop-and-reverse point moves progressively closer to price as momentum builds. When price closes on the wrong side of the SAR level, the trend flips and the AF resets. This produces the characteristic curved trailing stop-and-reverse mechanism that Welles Wilder originally designed in 1978. -In this indicator the standard formula is extended in two ways. First, all calculations run inside request.security() on higher timeframe datasets -- the SAR is computed entirely on the Macro or Micro timeframe bars before the result is mapped back to your chart. This means the SAR is not computing against the noise of your execution-timeframe candles; it reflects the momentum structure of a higher timeframe. Second, the ATR offset shifts the SAR level further from price: a bullish SAR value is reduced by (ATR14 * multiplier) and a bearish SAR value is increased by the same amount. This creates a buffer zone that absorbs intrabar volatility spikes without triggering false trend flips. -The directional state of each layer is simply whether the current close sits above or below the Aegis-adjusted SAR level. If close > adjusted SAR, the layer is bullish. If close < adjusted SAR, the layer is bearish. The alignment condition is met when both layers share the same directional state. -On repainting: all three request.security() calls use exclusively barmerge.lookahead_off. The "Wait for Bar Confirmation" toggle controls whether the SAR and EMA calculations reference the last fully closed bar of their respective timeframe (bar index offset 1) or the current in-progress bar close (offset 0). The offset value is derived from a simple input.bool -- a compile-time constant, not a runtime series -- making it safe to use as a bar offset inside the security context. When the toggle is on, signals never change retroactively. Zero repainting. What makes it original -Standard Parabolic SAR is calculated on your current chart timeframe. It reacts to every candle. Applied to a 5-minute or 15-minute chart, the SAR flips constantly and has poor signal quality. This indicator eliminates that problem entirely by computing the SAR on a higher timeframe and projecting it onto your execution chart -- you see the clean momentum structure of a 4-hour or daily SAR while trading on a lower timeframe. -The ATR multiplier is a second layer of noise filtering on top of the timeframe filter. The raw SAR level is already smoother due to the HTF sourcing; the ATR band makes it further resistant to the kind of intrabar spike that causes classic SAR to generate premature reversals on volatile instruments like crypto or small-cap equities. -The dual-layer alignment architecture is the primary original contribution. Rather than using a single SAR and filtering it with a separate trend indicator, both the trend filter and the entry signal use the same core algorithm (Parabolic SAR) at different timeframe scales. This produces structural consistency: both layers speak the same language. When they agree, you know both the macro structural momentum and the intermediate-term momentum point in the same direction. The color logic makes this alignment visually immediate -- green circles mean both layers agree up, red circles mean both layers agree down, no circles mean they disagree. -The color system is fully customizable. The Macro SAR has separate bullish and bearish color inputs (default white/black). The background tint has its own independent bull and bear color inputs, also defaulting to white and black but adjustable without affecting the SAR circles. This means you can set the Macro SAR bullish circles to white while using a custom teal or blue for the bullish background wash -- two independent color systems that can match or contrast as you prefer. -The built-in trade style reference table provides pre-configured AF and EMA settings for four common trading profiles. This is a practical utility that saves significant manual experimentation and makes the indicator immediately useful to traders unfamiliar with SAR parameter tuning. The table is hidden by default and can be enabled from the Display settings group. How to use it -Set your chart to your execution timeframe. Set the Micro timeframe to approximately four to six times your chart timeframe. Set the Macro timeframe to a major structural reference -- Daily is the standard default. The Micro timeframe generates your directional bias confirmation; the Macro timeframe is the filter that qualifies whether that bias is worth acting on. -Wait for the Micro circles to color. When both layers align and green circles appear below price, that is the bullish entry zone for the current Micro timeframe cycle. When red circles appear above price, that is the bearish entry zone. Use your standard entry trigger (price action, volume, or momentum) to time the actual entry within that zone. -The Macro EMA provides an additional structural reference. In a bullish alignment, entries taken while price is above the Macro EMA carry higher structural quality than those taken below it. -For the Macro SAR circles: the bullish color (default white, fully adjustable) appears below price in an uptrend. The bearish color (default black, fully adjustable) appears above price in a downtrend. The background tint independently reinforces these states using its own configurable bull and bear colors -- both are independent from the SAR circle colors. A standard approach is to take only green Micro circles when the background shows the bullish tint, and only red Micro circles when the background shows the bearish tint. -Alerts: the Bullish Full Alignment and Bearish Full Alignment alerts are the primary signals -- set them to fire on bar close with the confirmation toggle enabled. The four individual layer alerts (Macro and Micro turning bull or bear separately) are secondary warnings, disabled by default to avoid alert fatigue. Settings -Wait for Bar Confirmation: When on, all calculations reference the last fully closed bar of each respective timeframe. Prevents signals from changing while a bar is still forming. Strongly recommended for all live alert use. -Macro Timeframe: The higher timeframe for the structural trend filter. Default Daily. For equity day traders this is appropriate. For crypto swing traders, Weekly is a stronger macro anchor. -Macro Start AF / Increment AF / Max AF: The three acceleration factor parameters for the Macro Parabolic SAR. Lower values across all three produce a more stable, slower-turning macro filter. The reference table provides preset values for each trading style. -Macro ATR Multiplier: How far the ATR-based offset shifts the Macro SAR from its raw value. Default 1.5. Raise to 2.0-2.5 for highly volatile markets. Lower to 1.0-1.2 for steadier instruments. -Micro Timeframe: The intermediate timeframe for entry signals. Default 4H. For 15-minute chart traders, 1H or 4H works well. For 1-hour chart traders, Daily is more appropriate as the Micro layer. -Micro Start AF / Increment AF / Max AF: Higher start and increment values produce faster, more responsive entry signals. Lower values produce fewer, higher-quality signals. -Micro ATR Multiplier: Default 1.0. Raise to reduce noise in choppy conditions. -EMA Length: Period of the Macro EMA. Default 21 on the Daily timeframe tracks the short-term institutional moving average. Common alternatives: 50 for intermediate macro structure, 200 for long-term primary trend. -Macro SAR Bullish Color: Color of the large Macro SAR circles when the macro trend is bullish. Default white. Independently adjustable from the background bull tint. -Macro SAR Bearish Color: Color of the large Macro SAR circles when the macro trend is bearish. Default black. Independently adjustable from the background bear tint. Useful when using a light chart theme or a non-standard color scheme. -Micro SAR Aligned Bullish Color / Bearish Color: Colors of the Micro entry circles during full alignment. These only appear when both layers agree. -Show Trade Style Table: Hidden by default. Enable to display the parameter reference table in the top-right corner of the chart. The table has a white background with gray headers, purple AF and timeframe values, and dark red EMA values. -Show Background Tint: The background wash is driven by the Macro SAR state. The bull and bear tint colors are fully independent from the Macro SAR circle colors -- changing one does not affect the other. -Background Bull Color: Color of the background tint during a bullish Macro SAR state. Default white. Fully independent from the Macro SAR Bullish Color input. -Background Bear Color: Color of the background tint during a bearish Macro SAR state. Default black. Fully independent from the Macro SAR Bearish Color input. -Background Tint Transparency: Default 92. Range 85-98 covers subtle-to-visible tinting. Applies equally to both bull and bear background colors. Markets and timeframes -Works on all markets: equities, indices, crypto, forex, and commodities. The ATR offset makes it particularly useful on high-volatility instruments where classic Parabolic SAR is prone to excessive whipsaw. -For intraday scalpers using 1-minute to 5-minute charts: use the Scalping preset from the reference table. Micro timeframe 15-minute, Macro timeframe 1-hour. Best suited to liquid, high-volume instruments during active market sessions where momentum is directional. -For day traders on 15-minute to 30-minute charts: use the Day Trade preset. Micro 4H, Macro Daily. This is the default configuration and covers the widest range of instruments and market conditions. -For swing traders holding positions for days to weeks: use the Swing preset. Micro Daily, Macro Weekly. The alignment requirement produces significantly fewer but structurally higher-quality signals. -For long-term position traders monitoring macro turning points: use the Long Term preset. The indicator becomes a broad structural regime-change detector rather than an entry-timing tool at this scale. Disclaimer -Past indicator performance does not guarantee future results. This tool is for informational and educational purposes only and does not constitute financial advice or a trading recommendation. All trading involves risk. Suitable for all markets and all timeframes. Always apply appropriate position sizing, stop-loss management, and risk-reward assessment independent of any indicator signal.
Indicador Pine Script®
por TheScalpingAnt
NEXOUScl Quantum Terminal V4 - FinalInstitutional Grade Market Microstructure & Order Flow Suite 1. Description The NEXOUScl Quantum Terminal V4 is a high-performance visual trading ecosystem designed for TradingView. It transforms standard price charts into an advanced institutional workstation. By integrating real-time algorithmic scanning, volume-based whale detection, and automated session liquidity tracking (Kill Zones), this suite reveals the "hidden" side of the market. The terminal features a full-height vertical Matrix Dashboard that provides a continuous stream of probability-weighted market actions, designed specifically for high-frequency analysis and professional content creation. 2. Technical Analysis (Engine Specifications) A. Quantum Whale Detection Engine Logic: Uses a dynamic standard deviation multiplier on volume. When current volume exceeds the 50-period Simple Moving Average (SMA) by 220%, the system triggers a "Whale Alert." Significance: Identifies massive liquidity injections that represent institutional position building or major stop hunts. B. Matrix Probability Scoring (Strength %) Calculation: A real-time processing unit that calculates the "Conviction Level" of the current trend. Dynamic Scaling: Fluctuates between 88% and 99% during active sessions to reflect the continuous shifting of micro-liquidity and institutional participation. C. Structural Delivery & Session Mapping Kill Zones: Automatically maps the London (09:00-12:00) and New York (15:00-18:00) sessions. These are the "High-Volatility Windows" where 85% of institutional orders are executed. Rich Candle Tech: Replaces standard candles with high-contrast neon-glow visualizations to highlight momentum and price rejection points. D. Vertical Matrix Dashboard Action Logic: Categorizes market movements into four tiers: WHALE, INST (Institutional), BUY, and SELL. Power Visualization: Uses "Power Bars" |||||||||| to represent the relative volume intensity of each historical transaction. 3. User Guide (Manual) How to Read the Matrix Terminal ACTION Column: * 🐋 WHALE: Critical institutional activity. High impact on price. 🏢 INST: Programmatic/Algorithmic trading detected. BUY/SELL: Standard trend-following momentum. STRENGTH %: >95%: High-conviction move. Likely to continue to the next liquidity level. <90%: Market indecision or minor profit-taking. SCANNER (Bottom Right): * When the scanner blinks "📡 SCANNING...", the algorithm is actively looking for unfilled orders (Institutional Liquidity). Trading Strategy: The NEXOUScl Execution Step 1: Identify the current Kill Zone. Institutional moves are most reliable during the Purple (London) or Orange (NY) shaded backgrounds. Step 2: Look for a Huge Label on the chart (BUY/SELL/WHALE). Step 3: Confirm with the Matrix Dashboard. If the top 3 rows show matching colors and high Strength (95%+), the probability of success is maximized. Step 4: Follow the Signal Lines. These dashed arrows show the directional flow of smart money. 4. Technical Notes for Creators Screen Position: The terminal is optimized for a 16:9 or 9:16 (TikTok) aspect ratio. Visual Fidelity: Best used with Dark Mode on TradingView for maximum "Neon Matrix" effect. Alerts: Ensure "NEXOUScl Quantum" alerts are enabled to catch Whale movements instantly. © 2026 NEXOUScl Quantum. All Rights Reserved. This software is for institutional analysis and market educational purposes.
Indicador Pine Script®
por NEXOUS_cl
1
Time Based FVG/IFVG & MSS [Advanced] A very powerful, mathematically precise ICT tool that combines several advanced concepts into a single, clean workspace. Precision Timing: 9:30 AM Open Level (Horizontal) with a trailing label and Silver Bullet sessions. Market Structure: Adjustable MSS sensitivity to filter out noise on low timeframes. Imbalance Analysis: Time-filtered FVG & IFVG detection with a 3/5 day historical lookback for only unmitigated gaps. Custom Visuals: Center-aligned box labels and customizable Consequent Encroachment (CE) lines. For traders that want to focus on Time specific FVG & IFVG plus MSS. Your charts will be less crowded.
Indicador Pine Script®
por Jentrade24
Market Microstructure AnalyticsThe Hidden Toll on Every Trade Every time you buy or sell a financial instrument, you pay a cost that never appears on your brokerage statement. It is not a commission. It is not a fee. It is the spread between the price at which someone is willing to sell to you and the price at which someone is willing to buy from you. That gap, measured in ticks, basis points, or fractions of a percent, is the bid-ask spread. Over a single trade it looks small. Over thousands of trades, across a year, for a fund managing billions, it compounds into one of the most significant sources of performance drag in all of finance. For decades, institutional traders have measured this cost obsessively. Research desks at hedge funds and investment banks have dedicated entire teams to understanding when spreads are wide, why they widen, who is causing them to widen, and what that signal implies about the near-term behaviour of a market. Retail traders, however, have had almost no access to this kind of analysis. The reason is simple: measuring the bid-ask spread in real time requires access to the order book, tick-by-tick trade data, and quote data that most platforms either do not provide or lock behind expensive data terminals. This indicator changes that. Using only the OHLCV data that every chart on TradingView already contains, it reconstructs spread estimates and liquidity conditions through seven statistically validated models drawn directly from the academic market microstructure literature. It cannot replicate what a full order book feed provides, and the documentation is explicit about where the approximations are. But it gets considerably closer than anything available to the typical chart-based trader, and on short intraday charts it delivers information that is genuinely useful for both execution decisions and regime assessment. What Market Microstructure Actually Measures Market microstructure is the academic field that studies how prices are formed at the level of individual transactions. Its central question is not where a price will go tomorrow but how the mechanics of trading itself affect price formation right now. Two papers published decades apart established the framework this indicator builds on. The first was by Roll (1984), who noticed something elegant: in an efficient market, the prices of consecutive trades should not be correlated with each other, because any predictability would be arbitraged away. But if you look at actual trade-by-trade price changes, you consistently find negative autocorrelation. Prices bounce back and forth. The reason, Roll argued, is the bid-ask spread itself. Buyers trade at the ask and sellers at the bid, so consecutive trades alternate between two price levels. This bouncing creates a predictable negative covariance in price changes, and the size of that covariance is directly related to the size of the spread. From this insight he derived the formula S = 2 times the square root of the negative covariance of consecutive price changes. If you observe a series of trades and measure how negatively they correlate with each other, you can back out the spread without ever seeing a quote. The second foundational contribution came from Kyle (1985), who approached the problem from a completely different angle. He asked: if a market contains some traders who have private information about the true value of an asset, how do their orders affect price? His answer was the lambda coefficient, a measure of how much the price moves per unit of net order flow. A high lambda means the market is thin and informed: each additional unit of buying or selling pushes the price significantly. A low lambda means the market absorbs flow without moving much. Lambda is not just a spread measure; it is a measure of how much information asymmetry exists in the market at any given moment. This is the adverse selection component of the spread, and it is arguably the most strategically useful signal the indicator produces. The Spread Estimators The first layer of computation produces four distinct estimates of the bid-ask spread, each using a different statistical approach. The Roll (1984) estimator is the oldest and most widely cited. It computes the rolling covariance between a price change and the price change that came before it, then takes two times the square root of the negative of that covariance. One important detail: Roll's model is defined in terms of absolute price changes, not log-returns. Using log-returns introduces a scaling distortion tied to the price level of the asset, which biases the spread estimate upward at high prices. This implementation correctly uses delta-P throughout. The Corwin-Schultz (2012) estimator takes a fundamentally different approach. Rather than looking at the serial structure of price changes, it uses the high-low range of a bar. The core insight is that the high price of any trading period is most likely a transaction that occurred at the ask, while the low price is most likely a transaction at the bid. If you look at a two-period window, the combined high-low range reflects the true price variance over those two periods plus the spread component. A single-period range conflates variance and spread; the two-period structure allows them to be separated algebraically. The resulting formula involves a decomposition using the constant k = 3 minus 2 times the square root of 2, which emerges from the statistical properties of the high-low range under continuous diffusion. Corwin and Schultz (2012) validated this estimator extensively against actual quoted spreads across thousands of US equities and found it performs well both in cross-section and over time. The Abdi-Ranaldo (2017) estimator is the most recent of the three and, in empirical tests, the most stable. For each bar, it computes a quantity called c, defined as the log of the close price minus the average of the log-high and log-low. This is the signed deviation of the close price from the geometric midpoint of the bar's range, expressed in log-space. Abdi and Ranaldo proved that the expected value of the product of c at time t and c at time t plus one equals negative one quarter of the spread squared. This means that by measuring how negatively c correlates with the next period's c, you can recover the spread. The estimator inherits much of the intuition of Roll but anchors itself to the intrabar price range rather than the close-to-close change, which tends to reduce noise substantially. To handle cases where the high and low are identical, which occurs on 1-tick bars or extremely liquid instruments, the implementation excludes invalid pairs from the covariance calculation rather than substituting zeros, which would bias the estimate toward zero. The effective spread proxy takes yet another approach. Rather than estimating the quoted spread, it attempts to estimate the effective spread, which is the actual cost paid by a specific trade. The formula is two times the trade direction multiplied by the distance between the transaction price and the quote midpoint. Trade direction is approximated using the tick rule, which assigns a positive sign to transactions at prices higher than the previous price and a negative sign to those at lower prices, carrying the previous sign forward when the price is unchanged. This classification method was formalised by Lee and Ready (1991) and remains the standard approach for assigning direction when quote data is unavailable. The bar midpoint substitutes for the true quote midpoint, which introduces a systematic upward bias because the high and low of a bar are extreme transaction prices, not quotes. The effective spread proxy is therefore most reliable as a relative indicator of whether transaction costs are rising or falling, rather than as an absolute estimate of the quoted spread. The Liquidity Metrics The second layer moves beyond spread estimation into broader liquidity measurement. The key distinction is this: the spread tells you what it costs to execute one trade right now. Liquidity metrics tell you something about the structure of the market, how deep it is, how much information is embedded in the current order flow, and how efficiently prices are absorbing volume. The Amihud (2002) illiquidity ratio is the most widely used liquidity measure in the academic asset pricing literature. Its construction is conceptually simple: it divides the absolute value of a log return by the dollar volume of trading in the same period. What this measures is price impact per dollar traded. If a stock moves one percent and 10 million dollars changed hands, the ratio is small. If the same one percent move happened on only 50,000 dollars of volume, the ratio is large, indicating a thin market where small amounts of capital move prices significantly. Unlike the spread measures, which capture the cost of a single round trip, the Amihud ratio captures market depth. This implementation uses dollar volume rather than share or contract volume, which is the correct specification for comparability across instruments at different price levels. The ratio is scaled by a factor of 100 million for display purposes; its absolute level is asset-dependent and should always be interpreted relative to the instrument's own history. Kyle lambda, estimated here via ordinary least squares regression of price changes on signed volume, is the most theoretically sophisticated metric in the indicator. Each bar's signed volume is the total volume signed by the tick rule direction: positive if the bar closed higher than the previous bar, negative if it closed lower. The regression coefficient from regressing price changes on this signed volume is the lambda estimate. A high positive lambda means prices are moving more than expected for the amount of flow being absorbed, which is the signature of informed trading. When lambda rises, someone in the market likely knows something that others do not, and market makers are widening their spreads in response. The critical implementation detail here is that the volume must not be normalised before the regression. Normalising the signed volume changes the regression coefficient from a price-impact-per-share measure to a dimensionless sensitivity measure, which is a different quantity and does not correspond to Kyle's original model. The Parkinson (1980) range-based volatility estimator serves a supporting role: it estimates intrabar variance from the high-low range using the formula sigma-squared equals one over four times the natural log of two, multiplied by the square of the log ratio of high to low. This estimator is approximately five times more statistically efficient than the classic close-to-close variance estimator for the same number of observations (Parkinson 1980). Its role in this indicator is to help decompose the high-low range: the range reflects both volatility and the spread, and the ratio of the composite spread estimate to the Parkinson volatility tells you which component is dominant at any given time. The Composite and the Regime System Having computed multiple independent estimates of the spread, the natural question is how to combine them. Simple averaging is theoretically suboptimal when the estimators have different levels of noise. The precision-weighted composite assigns each estimator a weight inversely proportional to its robust variance, so that noisier estimators contribute less to the final reading. The key word is robust. Rather than computing standard rolling variance, which is dominated by extreme observations and can make a normally well-behaved estimator look unreliable for weeks after a single outlier bar, this implementation uses a variance estimator based on the Median Absolute Deviation, or MAD. The MAD is the median of the absolute deviations from the rolling median. Multiplied by the consistency factor 1.4826, it provides an equivalent to the standard deviation that is resistant to outliers with a breakdown point of 0.5, meaning up to half the observations in a window can be extreme values without corrupting the estimate. This approach follows Rousseeuw and Croux (1993), who established the formal properties of MAD-based scale estimators. Two further safeguards stabilise the weights. A ridge regularisation term, set to five percent of the mean robust variance across active estimators, prevents any weight from exploding toward infinity when an estimator is temporarily near-constant. And a weight cap, set by default at 70 percent of the total, prevents any single estimator from dominating the composite during regimes where it happens to be locally smooth. The live weights are displayed in the dashboard so the user can always see how the composite is currently distributed. The regime detection system answers the question of whether the current spread level is historically unusual. This is done through a robust z-score: the composite spread is compared to its rolling median, and the deviation is normalised by the MAD. The result is a standardised score that tells you how many robust standard deviations the current spread is from its recent typical level. A score of two or above signals a statistically unusual widening event. The same procedure is applied independently to the Amihud illiquidity ratio and to the absolute value of Kyle lambda. These three scores are then combined into the Liquidity Stress Index, computed as their equal-weighted average after each component has been winsorised at plus or minus three robust standard deviations. The winsorisation prevents a single extreme reading in one dimension from overwhelming the composite. Each component is then winsorised before averaging to prevent a single extreme dimension from dominating. The result is mapped to a zero-to-100 scale using the hyperbolic tangent function, where 50 represents neutral conditions, readings in the 65 to 80 range indicate elevated stress, and readings above 80 indicate severe stress across multiple liquidity dimensions simultaneously. Practical Use Cases For a retail trader, the most immediately useful output is the composite spread and its regime classification. When the composite spread widens and the regime indicator shifts to Elevated or Stress, entering a new position becomes more expensive than usual. On illiquid instruments this widening can be dramatic, consuming a significant fraction of the expected profit in transaction costs before the trade even begins. Conversely, when spreads are compressed, the market is functioning efficiently and execution is cheap. Timing entries and exits around spread conditions is a simple, evidence-based way to reduce the invisible drag that erodes returns over time. The spread trend indicator, which compares a five-period exponential moving average of the composite spread against a twenty-period average, provides a simple directional signal. A widening trend often precedes a period of higher volatility, lower liquidity, or increased uncertainty. This does not tell you which direction the price will move, but it tells you that the environment is becoming less predictable and more costly to trade, which is operationally important information. For professional traders and systematic strategy developers, the Kyle lambda signal has specific applications. When lambda is elevated relative to its own history, which the dashboard displays as the adverse selection z-score, it indicates that price changes are disproportionate to the measured order flow. This is consistent with the presence of informed traders, a phenomenon central to the theoretical work of Kyle (1985) and Glosten and Milgrom (1985). Elevated adverse selection is one of the clearest early warning signs of an impending directional move driven by asymmetric information, such as pre-announcement positioning, earnings whispers, or macroeconomic data leakage. The Amihud illiquidity ratio is particularly valuable for cross-asset comparisons and for monitoring the liquidity conditions of a specific instrument over time. Portfolio managers can use it to time their entries and exits in less liquid securities: entering when illiquidity is below its historical median and exiting before a period of known low liquidity such as a holiday period or low-volume session. Research by Amihud and Mendelson (1986) established that expected returns are positively correlated with illiquidity, meaning that investors demand higher compensation for holding assets where transaction costs are high. The illiquidity z-score in this indicator allows that premium to be tracked in real time. The spread-to-volatility ratio is a metric that practitioners familiar with the work of Corwin and Schultz (2012) will recognise immediately. It expresses the composite spread as a percentage of the Parkinson volatility estimate. When this ratio is high, the spread accounts for a large fraction of the observed price range, which typically indicates a market where market makers are cautious and price discovery is slow. When it is low, the price range is driven primarily by genuine information, not by the mechanics of the spread. This ratio is useful for distinguishing between a volatile and actively traded market, which is generally healthy, and a wide-spread market that looks volatile but is actually just illiquid. The Liquidity Stress Index in its scaled zero-to-100 form provides an accessible summary for traders who do not want to track multiple metrics simultaneously. During normal market conditions the reading sits near 50. When all three components, the spread, the illiquidity ratio, and the adverse selection estimate, are simultaneously elevated relative to their own histories, the index rises sharply. The historical examples of this pattern occurring together include the flash crash of May 2010, the August 2015 China-driven volatility spike, the COVID-19 crash of March 2020, and various cryptocurrency deleveraging events. In each case, the simultaneous widening of spreads, collapse of market depth, and spike in price impact coefficients preceded the most severe price dislocations by enough time to be actionable. Configuration and Settings The Estimation Window controls the rolling window for all covariance and liquidity calculations. A shorter window, around 10 to 20 bars, makes the estimators more responsive to recent changes but increases noise. A longer window, around 50 bars, produces smoother estimates that better reflect structural conditions but lag more. The default of 20 is a reasonable starting point for most intraday timeframes. The EMA Smoothing parameter applies an exponential moving average to each raw spread estimate before it is used in the composite and displayed on the chart. This reduces bar-to-bar noise without introducing the same lag that a longer estimation window would create. Setting it to 1 disables smoothing entirely, which is useful for research purposes but not for trading. The Regime Window determines how far back the robust z-scores look when assessing whether current conditions are unusual. A setting of 100 means the indicator asks whether the current spread is unusual relative to the last 100 bars. For daily charts, 100 bars is approximately five months of trading. For tick charts, it represents the most recent 100 tick bars. This parameter should be set large enough to capture at least one full market cycle of the relevant timeframe. The Maximum Composite Weight prevents any single estimator from being assigned more than the specified fraction of total weight. The default of 70 percent is conservative; in practice, during regimes where all three estimators agree and produce similar variances, the weights tend to distribute fairly evenly. The cap becomes most important when one estimator is temporarily quiet and its MAD-based variance falls to near zero, which would otherwise assign it almost all the weight. The LSI Winsorisation Cap limits the influence of extreme readings in any single component before they contribute to the Liquidity Stress Index. At the default of three robust standard deviations, a reading of ten, which would represent a truly exceptional event, contributes the same as a reading of three. This prevents a single data anomaly or calculation artifact from permanently elevating the stress index. Structural Limitations No representation is made that these outputs are equivalent to actual exchange quote data. They are not. TradingView provides bars, not tick-by-tick trades, and the academic models on which this indicator is based were developed for transaction-level data. The Roll estimator assumes that each observation is a single trade; when a bar aggregates hundreds or thousands of trades, the covariance structure it observes is a convolution of many individual trade-level covariances, and the result understates the true spread. This bias grows with bar duration and trade frequency. On 1-tick or 5-tick bars the bias is minimal; on daily bars it can be substantial. The tick rule classification, which assigns trade direction to bars and underpins both the Kyle lambda and effective spread estimates, was designed for individual trades. Applied to the close price of aggregated bars, it misclassifies a material fraction of bars. Ellis, Michaely and O'Hara (2000) documented misclassification rates of 30 to 50 percent on daily stock data. On short intraday bars the performance is better, but it never reaches the accuracy achievable with actual quote data. The rolling MAD computation is a streaming approximation to the exact finite-window MAD. In a stationary process the difference is negligible and the heavy-tail robustness property is preserved. In rapidly changing regimes the approximation introduces a small second-order error that does not materially affect the interpretation of the outputs. The effective spread proxy suffers from a systematic upward bias because it uses the bar midpoint rather than the true quote midpoint. This bias is largest when the intrabar range is wide relative to the actual spread, which is precisely when the estimate is most needed. On very short tick bars the range collapses toward the actual spread and the bias diminishes, but on longer bars the effective spread reading should be treated as an upper bound rather than a point estimate. Pine Script v6 introduced the built-in variables bid and ask, which return the current best bid and ask prices from a connected broker feed when accessed on the 1-tick timeframe via request.security(syminfo.tickerid, "1T", bid) and request.security(syminfo.tickerid, "1T", ask). This is a genuine improvement over bar-based proxies for the single most recent bar. However, these variables carry three constraints that prevent them from replacing the statistical estimators in this indicator. First, they carry no historical record: the values exist only at the current bar and return na on all prior bars, which makes it impossible to compute rolling covariances, MAD-based z-scores, or any of the regime detection logic that requires a lookback window. Second, the data is only available through a live broker connection on TradingView. Users on free accounts, paper trading environments, or instruments not covered by their connected broker will receive na throughout. Third, instrument coverage is uneven: major forex pairs, selected cryptocurrency pairs on exchanges such as Binance, and equities through brokers such as Interactive Brokers are generally supported, but futures, CFDs on many instruments, and equities through data-only feeds often return no data. The statistical estimators in this indicator therefore remain the primary analytical engine. If a broker connection is active, the live bid-ask spread retrieved via these built-in variables can serve as a real-time reference point to validate whether the rolling estimates are in a plausible range for the current session, but it cannot contribute to the historical signal calculations. None of the outputs should be used as the sole basis for any trading decision. References Abdi, F. & Ranaldo, A. (2017) A Simple Estimation of Bid-Ask Spreads from Daily Close, High, and Low Prices. Review of Financial Studies, 30(12). Amihud, Y. (2002) Illiquidity and Stock Returns: Cross-Section and Time-Series Effects. Journal of Financial Markets, 5(1), 31-56. Amihud, Y. & Mendelson, H. (1986) Asset Pricing and the Bid-Ask Spread. Journal of Financial Economics, 17(2). Corwin, S.A. & Schultz, P. (2012) A Simple Way to Estimate Bid-Ask Spreads from Daily High and Low Prices. Journal of Finance, 67(2). Ellis, K., Michaely, R. & O'Hara, M. (2000) The Accuracy of Trade Classification Rules: Evidence from Nasdaq. Journal of Financial and Quantitative Analysis, 35(4). Glosten, L.R. & Milgrom, P.R. (1985) Bid, Ask and Transaction Prices in a Specialist Market with Heterogeneously Informed Traders. Journal of Financial Economics, 14(1). Hasbrouck, J. (2009) Trading Costs and Returns for U.S. Equities: Estimating Effective Costs from Daily Data. Journal of Finance, 64(3). Kyle, A.S. (1985) Continuous Auctions and Insider Trading. Econometrica, 53(6). Lee, C.M.C. & Ready, M.J. (1991) Inferring Trade Direction from Intraday Data. Journal of Finance, 46(2). Parkinson, M. (1980) The Extreme Value Method for Estimating the Variance of the Rate of Return. Journal of Business, 53(1). Roll, R. (1984) A Simple Implicit Measure of the Effective Bid-Ask Spread in an Efficient Market. Journal of Finance, 39(4). Rousseeuw, P.J. & Croux, C. (1993) Alternatives to the Median Absolute Deviation. Journal of the American Statistical Association, 88(424).
Indicador Pine Script®
por EdgeTools
2
Breakout Trend Bar AlertsEvery trend has a starting point. It's rarely a gradual drift — it's one massive, decisive candle that breaks the market out of consolidation and kicks off a sustained move. Breakout Bar Alerts is built to catch that exact moment. The indicator monitors price action in real time and identifies when a bar forms that dwarfs everything around it — the largest high-to-low range of any candle in the last 250 bars. These are the bars where conviction enters the market, weak hands get flushed, and a new trend begins. When one appears, you get an instant alert so you're never late to the move. Why these bars matter: Big range bars represent a sudden surge of momentum and volume-backed commitment from one side of the market. Bulls or bears have taken control decisively. What follows is often the beginning of a trend leg — not a random spike. Built to filter out the noise: The opening bar of every session is excluded entirely. That first chaotic candle never skews your data or triggers a false signal. Only bars within your active session window are counted. Off-hours price action is completely ignored, so your benchmark is always built from real, tradeable market conditions. Three alert conditions — Bull Breakout Bar, Bear Breakout Bar, or Both — so you only get notified for the setups you actually trade. Inputs: Lookback Period — how many bars back to measure the largest range (default: 250) Enable Time Filter — restricts detection and calculations to your active trading session Active Session — define your session window in exchange time Bull / Bear colors — fully customizable Best used on intraday timeframes (1m – 15m) on futures, forex, or high-volume equities. When this fires, pay attention — the trend may already be starting.
Indicador Pine Script®
por confidencewindow
Risk AwarenessRisk Awareness - Liquidation Level Indicator A clean, professional tool for displaying liquidation prices on leveraged positions. Designed for traders who need instant visibility of their risk levels without chart clutter. KEY FEATURES Real-time liquidation price calculation for long and short positions Adjustable leverage from 1x to 200x Fire engine red (long) and lime green (short) color-coded levels Two label modes: Compact (minimal) and Detailed (full info) Horizontal lines extending left from current price Optional P&L tracking and display Background alerts when approaching liquidation Customizable maintenance margin and liquidation fee parameters HOW IT WORKS The indicator calculates liquidation prices using the standard formula: Long Liquidation = Entry Price x (1 - 1/Leverage - Liquidation Fee + Maintenance Margin) Short Liquidation = Entry Price x (1 + 1/Leverage + Liquidation Fee - Maintenance Margin) Default parameters (0.5% maintenance margin, 0.5% liquidation fee) are calibrated for major crypto futures exchanges like Binance, Bybit, and OKX. DISPLAY MODES Compact Mode: Shows only leverage and price (e.g., "40x: 48750.00") Detailed Mode: Shows full information including percentage distance and optional P&L CUSTOMIZATION OPTIONS Position Settings: Adjust leverage, toggle long/short, select entry price source Custom Parameters: Fine-tune maintenance margin and liquidation fee for your specific exchange Visual Settings: Colors, line width, label size, historical bands, disclaimer display Alert Settings: Set distance threshold for liquidation warnings Risk Management: Track unrealized P&L based on position size ALERTS Built-in alert conditions for: Price crossing liquidation levels Approaching liquidation threshold Critical loss levels (50%+) IMPORTANT DISCLAIMER This indicator provides ESTIMATED liquidation levels for Tier 1 positions (small to medium size). Actual liquidation prices may vary due to: - Position size tiers (larger positions = higher maintenance margins) - Accumulated funding rates - Market volatility and order book depth - Cross margin vs isolated margin mode - Exchange-specific liquidation engines Always verify liquidation prices on your exchange platform before trading. This tool is for educational and risk awareness purposes only. IDEAL FOR Crypto futures traders on Binance, Bybit, OKX, and similar platforms Day traders managing leveraged positions Swing traders monitoring overnight risk Anyone trading with leverage who needs clear visual risk management PRO TIPS Use Compact mode with Tiny/Small label size for minimal chart clutter Enable the Info Table for detailed metrics when needed Set Alert Distance to 1-2% for advance warning before liquidation Toggle "Show Historical Bands" OFF (default) for cleaner charts Adjust Custom Parameters if trading on exchanges with different fee structures Stay aware. Trade smart. Manage your risk.
Indicador Pine Script®
por MessyJess
2
Break Even (BE) Alert Break Even (BE) Alert & Profit Target Visualizer Overview This indicator is designed for traders whose brokers do not support automatic "Move to Break Even" functionality within the TradingView interface. It provides a clear visual target on your chart and triggers a real-time alert once your trade reaches a specific profit threshold (measured in ticks), signaling that it is time to manually adjust your stop loss to break even. Key Features Dynamic Visual Target: Draws a clear, dashed horizontal line at your specified profit goal. Editable Tick Offset: Easily adjust the "BE Trigger" distance (e.g., 200 ticks) directly from the settings menu. Bidirectional Support: Works for both Long and Short positions with a simple toggle. Real-Time Alerts: Includes a built-in alert condition that fires the moment price crosses your target level, ensuring you never miss the window to protect your capital. How to Use Input Entry: Once you have placed a trade, open the indicator settings and enter your Entry Price. Set Direction: Select whether you are in a Long or Short position. Define Goal: Set your preferred Tick Target (e.g., 200). Activate Alert: Create a new alert on your chart, select this indicator, and choose the "Move Stop to BE" condition. Why use this? Managing risk is the most critical part of trading. This tool removes the guesswork and constant chart-watching by automating the notification process for capital protection, allowing you to focus on finding the next setup while your current trade is monitored for its "safety" trigger.
Indicador Pine Script®
por TheFuturesMonk
NEXOUS_cl Ultimate Institutional SuiteThe NEXOUS_cl Ultimate Suite is a professional-grade trading ecosystem designed to reveal institutional market mechanics. It combines three core engines: Quantum Order Flow Engine: Analyzes sub-second transaction data (up to 1S granularity) to classify orders into 7 tiers, from retail noise to massive institutional whales. Structural Delivery (CISD) Engine: Detects the "Change in State of Delivery" to identify high-probability reversals and liquidity sweeps. Adaptive Ichimoku PTS Engine: A revolutionary cloud system that automatically adjusts its lengths based on volume oscillators (TFS, OBV, Klinger) and dual-ATR volatility. Equipped with real-time dashboard tables, automated support/resistance zones, and a logic-driven pattern recognition system, NEXOUS_cl provides unprecedented visibility into the smart money footprint. 🛠️ Technical Analysis & Features 1. NEXOUS_cl Quantum Order Flow Analyzes the flow of orders in Lower Timeframe (1S) to reveal what is happening within each candle. 7-Tier Classification: Separates trades into Standard, Significant, Major, Massive, Institutional, Reversal and Trap. Flow Delta Bar: A dynamic bar at the top of the chart that shows the net pressure of buyers/sellers in real time. Whale Tracking: Detects "Massive" orders that have the power to move the market autonomously. 2. NEXOUS_cl Structural CISD (Change in State of Delivery) Detects when the market changes "delivery state" (from Accumulation to Distribution and vice versa). Liquidity Sweeps: Detects when Swing Highs/Lows (Stop Hunts) are "swept" before large moves. Noise Filter System: Uses advanced algorithms to reject false structure changes (Market Noise). Dynamic Candle Coloring: Candles change color automatically based on the current Market State (Bullish/Bearish Delivery). 3. NEXOUS_cl Adaptive Ichimoku Cloud The first Ichimoku system that is not static, but changes length depending on market momentum. Adaptive Lengths: Tenkan, Kijun and Senkou are automatically adjusted via 5 different Volume Oscillators. Kijun Divider Tool: Creates up to 4 Kijun sub-levels for more accurate Support & Resistance. Volatility Sync: The system "stretches" or "contracts" depending on the ATR (Volatility Ratio). 📊 User Manual How to read the Order Book Standard (Gray): Retail noise. Ignore it. Major/Massive (Purple/Orange): This is where the "Big Fish" are. Follow their direction. Institutional Pattern (Light Blue): Indicates algorithmic order execution. It is the most reliable trend indicator. Trap (Fuchsia): Beware! The market has set a liquidity trap. Expect an immediate opposite move. Reversal & Sweep Strategy Wait for the Structural Engine to detect a Liquidity Sweep (green or red arrow ▲/▼). Confirm via Order Flow that Major or Institutional orders appear in the opposite direction. Enter the trade when the Adaptive Ichimoku changes color (Kumo Twist). ⚠️ Caution & Error Handling Data Latency: Using 1 second (1S) data is demanding. Make sure your Internet is stable. Market Context: Do not use signals in isolation. Order Flow shows what is happening, Structure (CISD) shows where it is happening. Their combination is key. Validation: If the selected Timeframe is larger than the chart, the algorithm automatically reverts to 1S to avoid calculation errors. ⚖️ Copyright & Legal Notice © 2026 NEXOUS_cl. All Rights Reserved. This software and technical analysis are the intellectual property of NEXOUS_cl. Reproduction, redistribution or sale without prior written permission is prohibited. Disclaimer: Trading involves risk. NEXOUS_cl Ultimate Suite is an analysis tool and not guaranteed financial advice.
Indicador Pine Script®
por NEXOUS_cl
ORB + Overnight Horizontal LevelsThis indicator plots the key price levels I use for intraday futures trading. It automatically calculates the 30-minute Opening Range (ORB) from the regular market open (9:30–10:00) and displays the ORB High and ORB Low as horizontal levels that extend through the session. The script also tracks the Overnight High and Overnight Low from the extended session leading into the market open. These levels help identify important liquidity zones and areas where the market may react during the trading day. I personally use these levels together with a manually placed Fibonacci retracement tool. Depending on which level is stronger or gets taken first (ORB or Overnight), I anchor my Fibonacci tool to measure potential retracements and continuation moves. The goal of this indicator is to keep the chart clean while highlighting the most important intraday reference levels. Features • Automatic 30-minute Opening Range levels • Overnight High and Overnight Low detection • Horizontal levels that extend across the trading session • Minimal visual clutter for clean charting • Designed to be used alongside manual Fibonacci analysis
Indicador Pine Script®
por jeangie_ortiz
3C Setup + Targets & BoxesFeatures in This Script: Candle 2 Box — shows exact trigger zone for entries. Candle 2 High/Low — breakout lines for confirmation. Candle 1 High/Low — primary target levels. Previous Day High/Low — optional target levels. Liquidity zones — can be represented by previous day high/low (simple version). Alerts — triggers when price breaks Candle 2 High/Low. Background highlights & labels — visually marks long/short breaks.
Indicador Pine Script®
por MoneyDailysniper
Untouched Highs & LowsUntouched Highs & Lows Tracks and displays the most recent untouched high and low levels for five key level types — London session, New York session, Asia session, the prior 4H candle, and the prior Daily candle. The moment price closes through a level, the line is automatically removed (or dimmed if you prefer to keep swept levels visible). Only clean, untagged levels remain on your chart at all times. Features: ✅ Per-session high/low tracking (London, New York, Asia) — lines appear only after the session closes and vanish when a new session starts ✅ Prior 4H and Daily high/low levels — always showing the most recently completed candle ✅ Touch detection with optional buffer (in points/ticks) for tolerance ✅ "Show Touched (dimmed)" mode — keep swept levels visible at 70% transparency instead of deleting them ✅ Fully customisable: colour, line style (Solid / Dashed / Dotted), and width per level type ✅ Shorthand label mode for cleaner charts ✅ Built-in alert condition fires when any level is swept How to use: Load on any intraday chart (1m–1H recommended). Session times default to London UTC+0 hours — adjust them in the FX Sessions group to match your broker's timezone. Enable only the level types relevant to your strategy to keep the chart clean. Note: Session levels display only after the session has closed. No levels will appear during an active session or before the first session of that type completes on your chart history.
Indicador Pine Script®
por hary349veo3
RSI 50 Pivot ExtensionRSI 50 Pivot Extension RSI 50 Pivot Extension is a momentum-based indicator that helps identify potential market highs and lows using RSI pivot points relative to the 50 midline. The indicator detects pivot highs and lows in the RSI and extends those levels forward, allowing traders to visualize areas where momentum previously reversed. RSI is also color-coded based on position relative to the 50 level, making it easy to see whether momentum is currently bullish or bearish. Features • Detects RSI pivot highs and lows • Extends pivot levels forward to highlight potential reaction zones • Color-coded RSI above or below the 50 midline • Helps visualize momentum shifts and potential turning points Designed for traders who want a clearer view of momentum structure and reversal zones within the RSI.
Indicador Pine Script®
por benjamenharper
Trend Pullback DetectorDetects high-momentum impulse legs in real time and alerts you the moment they complete — so you're ready when the 50% retracement sets up. How it works The indicator scans for consecutive large bullish or bearish candles that together form a significant directional leg. When a qualifying run ends, it locks in two points: Leg A — the origin of the move (open of the first candle) Leg B — the terminus of the move (high/low of the last candle) From there it plots the 50% midpoint of the leg and watches for price to retrace into that zone. When price pulls back the right amount and begins to recover, it marks the Entry, Stop Loss, and Profit Target directly on the chart. Three alert conditions A/B Bull Leg Detected A/B Bear Leg Detected A/B Bull or Bear Leg Detected Set your preferred alert and get notified the moment a leg completes — giving you time to watch for the retracement before the next move begins. Key settings Min Consecutive Candles — how many qualifying candles define a leg Min Candle Size — filters out small or indecisive candles within the run Min Total Leg Size — ensures the full move is significant relative to current volatility (ATR-based) Retrace Zone — the pullback depth range that qualifies as a valid 50% setup (default 38–65%) Works on any market and timeframe. Best used on liquid instruments where momentum legs are clean and decisive — equities, ETFs, futures, crypto.
Indicador Pine Script®
por confidencewindow
New Day Opening Gap NDOGThis Pine Script plots the New Day Open Gap (NDOG) — the price gap between the previous day’s 5:00 PM NY close and the current day’s 6:00 PM NY open (excludes weekends). It displays the gap as a semi-transparent box and draws multiple reference levels across the trading day: NDOG High and Low (gap lines) Consequent Encroachment Quartile / Quadrant lines (.25 / .75) 1/8th lines (.125 / .375 / .625 / .875) Optional previous 5 PM close line (extendable) Optional High-Low Gap box (previous day 5 PM candle extremes vs current day 6 PM open) Premium / Discount Table A real-time table shows whether current price is trading at a premium or discount relative to the average of the last several NDOG ranges (user-selectable count). Additional Features Day-specific colors (Monday–Friday) for boxes and lines Last two Monday NDOGs and last two Friday NDOGs (toggleable) Full Premium / Discount gradient levels with optional labels Right-extension of all boxes and lines Historical boxes/lines/labels control Label positioning and sizing options Timezone offsets for non-US indices “No plot session” to stop painting during specified hours while still extending right Intended Use Designed primarily for SPX, ES, NQ, and major indices on intraday timeframes up to the selected maximum (default 15 min). The indicator helps identify institutional reference levels, gap-fill probability zones, and premium/discount conditions for the trading day. All visuals are fully customizable through grouped inputs. No repainting, no external data required.
Indicador Pine Script®
por MadMonkTrading
MTF RSI Grid FullMTF RSI Grid Full displays RSI values from multiple timeframes in a clean grid, allowing traders to quickly assess momentum alignment across the market. The indicator pulls RSI readings from several higher and lower timeframes and organizes them into an easy-to-read table so you can instantly see whether momentum is bullish, bearish, or neutral across the broader structure. Features • Multi-timeframe RSI readings in a compact grid layout • Quickly identify momentum alignment or divergence • Color-coded values for faster interpretation • Helps traders understand higher-timeframe bias while trading lower timeframes Built for traders who want a simple way to monitor RSI structure across multiple timeframes without switching charts.
Indicador Pine Script®
por benjamenharper