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NX - ICT PD Arrays (Enhanced) FVG & ORDER BLOCKS # NX - ICT PD Arrays (Enhanced) - Algorithm Explainer This indicator identifies high-probability Fair Value Gaps (FVGs) and Order Blocks (OBs) using Inner Circle Trader concepts with intelligent filtering to show only the most significant institutional footprints. ## How It Works **Smart Filtering System:** The algorithm uses a multi-factor scoring system (0-100 points) to evaluate each potential zone: **For FVGs (Fair Value Gaps):** - Gap size relative to ATR volatility (0-40 pts) - Price displacement strength (0-40 pts) - Formation at swing high/low structure (bonus 20 pts) - Only displays zones scoring 25+ points **For Order Blocks:** - Block size relative to ATR (0-30 pts) - Displacement momentum (0-35 pts) - Swing point formation (bonus 15 pts) - Market structure break confirmation (bonus 20 pts) - Only displays zones scoring 30+ points **Key Features:** - ATR-normalized sizing filters out noise across all timeframes - Swing detection identifies structurally significant levels - Displacement percentage measures institutional momentum - Optional structure break requirement for highest-probability OBs - Zones extend until price fills them completely **Adjustable Controls:** Fine-tune sensitivity via displacement %, ATR multiples, and swing lookback parameters to match your trading style and market conditions.
Pine Script® göstergesi
dannydholmes1 tarafından
Momentum Indikator (Avg Volume)Momentum Indicator (Avg Volume) 1. Purpose of the Indicator The WMT Momentum Indicator (Avg Volume) is designed to highlight strong price movements accompanied by increased trading volume. It specifically filters for trading days where: volume is increasing, volume is above its average, and the percentage price movement exceeds a defined threshold. The goal is to identify momentum days early — both bullish and bearish. 2. Display & Visualization Visualization: Histogram (columns) Panel: Separate indicator window (overlay = false) Y-Axis: Percentage price change compared to the previous close Colors: 🟢 Green: Positive daily movement (Close ≥ Open) 🔴 Red: Negative daily movement (Close < Open) Zero Line: Reference line separating positive and negative momentum 3. Input Parameters Parameter Description Default +/- Movement Threshold (%) Minimum absolute daily price movement in percent 4.0 % Volume Average (Days) Period for the moving average of volume 20 days 4. Logic & Calculations 4.1 Volume Conditions The indicator only considers days where: Volume is higher than the previous day volHigherPrev = volume > volume Volume is above the moving average avgVolume = ta.sma(volume, volLength) volAboveAvg = volume > avgVolume ➡️ This ensures that only days with unusually high market participation are taken into account. 4.2 Price Movement Percentage change vs. previous close priceMovePct = (close - close ) / close * 100 Absolute movement absMovePct = math.abs(priceMovePct) Intraday direction priceMoveDay = close - open 4.3 Direction Logic Condition Meaning priceMoveDay ≥ 0 Bullish day (green) priceMoveDay < 0 Bearish day (red) 4.4 Main Condition (Signal Filter) A bar is displayed only if all of the following conditions are met: showBar = volHigherPrev and volAboveAvg and absMovePct >= moveThreshold ➡️ Interpretation: Only strong price movements with rising and above-average volume are visualized. 5. Color Logic barColor = showBar and volGreen ? color.green : showBar and volRed ? color.red : na Color Meaning Green Strong bullish momentum Red Strong bearish momentum No bar Conditions not met 6. Plot Description Momentum Histogram plot( showBar ? priceMovePct : na, style = plot.style_columns ) Bars are plotted only when showBar = true Bar height represents the percentage change vs. previous close Direction and color indicate momentum direction Zero Line hline(0, "0-Line") Visual separation between positive and negative momentum Helps with quick interpretation 7. Typical Use Cases Identifying breakout days Confirming trend continuation Detecting distribution or accumulation Filtering for momentum trading & swing trading Complementing price action or volume-based strategies 8. Practical Interpretation Tall green bar: → Strong buying pressure, potential trend start or continuation Tall red bar: → Strong selling pressure, possible trend exhaustion or short signal No bars: → Market without relevant momentum (sideways / low volume)
Pine Script® göstergesi
kthiele tarafından
Magnus Bestest - Trade Manager1.) Ultra-useful trade manager for Futures trading on any asset, which automatically calculates the correct contract size based on your input of the dollar amount you’re willing to risk and the Stop Loss distance for your current trade. 2.) Additionally, you can place a very practical candle countdown label directly next to the currently forming candle, so you always know how long it is until it closes. This is especially useful for scalping, trading market opens, or trading news, where having this information instantly visible is crucial. 3.) This trade manager also marks the last candle before the London session, New York session, and New York Stock Exchange (NYSE) open, so you can always clearly see when you need to be ready to trade.
Pine Script® göstergesi
MagnusBestest tarafından
KCP MACD Pro [Dr. K. C. Prakash]📊 KCP MACD Pro KCP MACD Pro is a clean, low-noise momentum indicator designed for clear trend and momentum analysis without clutter. Unlike the classical MACD, this version is built without EMA, using Simple Moving Averages (SMA) to provide smoother, more stable signals, making it ideal for training, classroom use, and disciplined trading. 🔹 Core Concept The indicator measures momentum strength and direction by calculating the difference between: a Fast SMA and a Slow SMA (MACD line), and a Signal SMA applied to the MACD line. The result is a MACD-style oscillator that reacts less aggressively than EMA-based MACD, helping traders focus on structure and trend quality rather than short-term noise. 🔹 Components Explained MACD Line (SMA-based): Shows the underlying momentum by comparing short-term and long-term price averages. Signal Line (SMA): Smooths the MACD line to highlight momentum shifts. Histogram: Displays the distance between the MACD and Signal lines, visually representing momentum strength. Zero Line: Acts as a trend equilibrium level: Above zero → bullish momentum bias Below zero → bearish momentum bias 🔹 How to Use Trend Identification: Stay aligned with the market bias using the zero line. Momentum Analysis: Expanding histogram bars indicate strengthening momentum; contracting bars suggest weakening momentum. Manual Trade Decisions: Designed intentionally without buy/sell arrows, encouraging traders to combine it with price action, support–resistance, or market structure.
Pine Script® göstergesi
prakash1126 tarafından
Crypto Schlingel - Light Suite v5.19The Chart Indicator Suite Light combines a wide range of powerful tools that help traders accurately analyze market structures, volatility, and key price zones. With indicators such as pivot points, EMAs, VWAP and important market levels such as daily open, the suite offers a comprehensive overview of trends and market behavior. Supplemented by pvsra candles and the display of relevant stock market opening hours, it reliably supports traders in making informed trading decisions. Indicators are configurable All of the indicators mentioned are fully configurable and can be flexibly adapted to individual trading strategies. Users can freely adjust parameters, display types, and sensitivities to highlight exactly the market information that is relevant to their personal trading style. The individual fields in the configuration are self-explanatory or are explained in a toolbar, so that the possible settings become clear. PIVOT POINTS Pivot points are predefined price levels calculated from the previous day's price data (or a previous time unit). They help traders identify potential support and resistance zones for the current trading day (or period). Benefits of pivot points in chart analysis 1. Determining support and resistance areas The calculated pivot levels (P, S1, S2, R1, R2, etc.) show where the market is likely to react: Supports (S1, S2, S3) → possible downward turning points. Resistance (R1, R2, R3) → possible upward turning points. These zones are often observed by many traders at the same time, making them self-fulfilling marks. 2. Trend determination and market sentiment If the market opens above the pivot (P) and remains there → signals buying pressure. If the market trades below the pivot (P) → signals selling pressure. A break above R1 or below S1 may indicate a strong trend day. EMA Exponential Moving Average The EMA is the exponentially weighted moving average of a price. It shows the average price of a security over a certain period of time, weighted according to recency – that is: 👉 more recent price data has more influence than older data. This distinguishes it from the simple moving average (SMA), in which all values are weighted equally. Benefits of the EMA in chart analysis -> Identifying trends The EMA reacts more quickly to price changes than the SMA and is therefore ideal for: Identifying trend reversals at an early stage Confirming trend directions 👉 Rising EMA → Upward trend 👉 Falling EMA → Downward trend Traders often use combinations such as: EMA 50 / EMA 200 → Long-term trends SIGNIFICANCE OF HIGHS AND LOWS The daily high, daily low, weekly high, and weekly low are objective price zones that show: Where the market bought (high) or sold (low) the most, and where supply and demand reached their extremes in the past period. These levels often act as magnetic price zones in ongoing trading, where traders react (entry, profit-taking, or stop setting). 🎯 Use of yesterday's high and low (previous day high/low) 🔹Support and resistance levels Yesterday's high often acts as resistance when the price comes from below. Yesterday's low becomes support when the price falls from above. ➡️ Traders watch these levels closely to trade breakouts or reversals. EMA 9 / EMA 20 → Short-term movements 🎯 Benefits of weekly highs and lows (Weekly High/Low) Important structural markers in the higher time frame Weekly highs and lows show medium to long-term market structure. They are often considered stronger supports/resistances than daily levels. ➡️ For example, if the price breaks above the weekly high, this usually signals institutional interest and may indicate a continuation of the trend. ➡️ Conversely, failure to break above a weekly high may indicate market weakness or a reversal. DAILY OPEN The Daily Open is the price at which trading begins on a new day. It marks the first price after the close of the previous trading session. 👉 In many markets (e.g., Forex, index futures, crypto), this is the starting point of daily price movement, where market direction and sentiment realign. 🎯 Benefits of the Daily Open in chart analysis Direction indicator (daily bias) The Daily Open serves as a neutral center line for the current trading day. Traders use it to assess the market direction (bias): Price above the Daily Open → bullish day (buyers dominate) Price below the daily open → bearish day (sellers dominate) 📈 → If the daily open is broken and held above, this indicates upward momentum. 📉 → If it is broken below, this signals weakness. This simple observation helps traders trade with the daily trend rather than against it. STOCK MARKET OPENING HOURS Every major stock exchange has defined trading hours during which institutional capital is active. Examples (CET): Asia (Tokyo/ Hong Kong) 1:00 a.m. – 9:00 a.m. Europe (London/Frankfurt) 08:00 – 17:30 USA (New York) 15:30 – 22:00 Market dynamics change significantly during these time windows, as volume, liquidity, and volatility fluctuate depending on the session. 📈 Benefits in chart analysis 🔹Recognizing volatility and liquidity phases At the start of a session (e.g., 9:00 a.m. in Frankfurt or 3:30 p.m. in New York), trading volume rises sharply. This results in strong movements, often with changes in direction or breakouts. 👉 These phases are particularly suitable for: Breakout strategies Volume or momentum trades Example: If an index (e.g., DAX or S&P 500) reacts strongly at the US opening, this indicates institutional activity that may shape the rest of the day. VWAP (Volume Weighted Average Price) The VWAP is the volume-weighted average price of a security for a specific period of time – usually per day. 👉 Unlike a simple moving average (e.g., EMA), the VWAP takes into account how much was actually traded – not just where the price was. It therefore reflects the fair market value, taking into account the trading volume. 🎯 Benefits of VWAP in chart analysis 🔹 Determining the fair average price The VWAP shows where the majority of the trading volume took place – i.e., the price that the majority of market participants actually paid. ➡️ This is the “fair price of the day.” Price above VWAP → buyers dominate (bullish) Price below VWAP → sellers dominate (bearish) This information is particularly valuable for determining the intraday bias (direction of the day).
Pine Script® göstergesi
LM914 tarafından
HTF Candles Overlay by ARGPT Trader Club v1.1This indicator draws a small “HTF candle preview” on the right side of your chart, so you can see the most recent higher timeframe structure while staying on any lower timeframe. You choose the source timeframe from a dropdown (H1, H4, or D1), and it renders up to the last four candles from that timeframe, with an option to include or exclude the current developing candle. Each candle is built from a box (body) plus a line (wick), and it uses solid colors: green for bullish candles and red for bearish candles. Visually, it behaves like a compact dashboard overlay rather than a full chart change. H1 candles are drawn using true time width (bar time), while H4 and D1 candles are drawn using a fixed bar-index width so they stay readable and do not get distorted by large timeframe candle widths. The overlay is anchored into the future on the right side using a configurable padding value, and it only updates on the last bar to keep the script light and avoid unnecessary redraws. Join ARGPT Trader Club: linktr.ee
Pine Script® göstergesi
alrizqi_gpt tarafından
Liquidity OS [PyraTime]Trading the lower timeframes (1m-15m) often feels like navigating a minefield. Charts become cluttered with noise, making it nearly impossible to distinguish random price action from genuine institutional intent. Traders frequently suffer from "Analysis Paralysis," struggling to spot clean setups or reacting too slowly to calculate risk accurately in fast-moving markets. The Solution: A Clean Operating SystemPyraTime: Liquidity OS was engineered to solve this specific problem. It is not just a signal tool; it is a complete visual operating system designed to declutter your workspace and enforce discipline. By filtering price action through a strict confluence of Structure, Time, and Momentum, it highlights only high-probability liquidity sweeps while automating the complex mental math of risk management. How to Use This Indicator This tool is designed for Scalpers and Day Traders utilizing liquidity concepts (ICT/SMC). Wait for the Signal: The indicator automatically identifies valid "Unicorn" setups—a confluence of a Liquidity Sweep followed by a displacement (Breaker) and a Fair Value Gap. Verify the Context: Look for the "Elite Glass" Capsule. Cyan Glass: Bullish Setup (Long Opportunity). Pink Glass: Bearish Setup (Short Opportunity). Note: The capsule physically covers messy wicks, forcing your eye to focus solely on the clear path to profit or invalidation. Consult the Dashboard: Glance at the "Monitor" panel (bottom right). It instantly displays the Position Size required to trade the setup based on your pre-defined account risk (e.g., 1%). Execute & Focus: Use the visual TP (Take Profit) and SL (Stop Loss) lines provided by the capsule to set your orders. The system automatically dims old trades ("Smart Spotlight") so only the current opportunity competes for your attention. Key Features 🦁 "Elite Glass" Visual Engine: A proprietary rendering system that displays trade setups as high-transparency, polished capsules. This creates a "Focus-First" environment, reducing chart noise and visual fatigue. 🧠 Smart Spotlight: Automatically manages visual history. The two most recent active zones remain bright, while older setups automatically dim to reduce clutter. Mitigated zones can be set to turn into "Ghosts" or disappear entirely. 🛡️ Risk OS Dashboard: A real-time, persistent monitor that calculates: Dynamic Position Sizing: Tells you exactly how many units/contracts to trade. Session Metrics: Tracks Win Rate, Total R, and Expectancy live. Safety Warnings: Highlights "High Risk" inputs in red if you exceed safety thresholds. ⚡ Logic Filters: Killzones: Restrict signals to specific sessions (e.g., London/NY) with a custom timezone selector. Trend Flow: Filters signals to align with the 4H Trend (EMA 50). Deep Value: Ensures buys occur in Discount and sells in Premium zones. Specifications & Settings Risk OS: Customizable Target R:R, Stop Loss Padding (ATR Multiplier), and Risk Per Trade %. Liquidity Filters: "1m Scalp Mode" (increased sensitivity), Killzone Time/Timezone selector, and Force Reset button. Visual Interface: Fully customizable colors. Toggles for "Show Midlines" (50% of FVG) and "Show Structure Breaks" (BOS lines) to further reduce noise. Performance: Built on Pine Script v6 with null-safe execution and optimized garbage collection for zero-lag performance on all timeframes. Disclaimer: Risk metrics, position sizing, and performance data displayed by this indicator are for informational and educational purposes only. This tool does not execute trades, manage funds, or guarantee future results. Always trade with a regulated broker and verify calculations independently.
Pine Script® göstergesi
PyraTime tarafından
3
Desai's Path of Least Resistance v2 (1M)Desai’s Path of Least Resistance v2.2 (1M) – Text Guide and Full Explanation This script, “Desai’s Path of Least Resistance v2.2 (1M)”, is a cost‑based market impact model implemented as a TradingView indicator. It is designed to show you in real time which direction is cheaper for the market to move: up or down. Instead of focusing only on price patterns or simple volume, it estimates how many dollars are required to push the price by one unit of volatility (one ATR) upward versus downward. That difference in cost defines the “path of least resistance.” This 1‑minute edition is specially built to run on standard TradingView data, without requiring tick‑level tapes. It uses 1‑minute bars as building blocks, applies an “intensity” method to estimate buy versus sell pressure, aggregates these into clusters, and then applies an econometric model (a power‑law impact model) to estimate the cost of moving price. The result is a real‑time, statistically grounded view of where liquidity is thinner and where it is thicker. Below is a complete conceptual explanation of how it works and how to use it, written purely in plain text paragraphs as suitable for TradingView descriptions. Core Idea: Cost to Move Price by One ATR Most indicators focus on “What is price doing?” This script asks a deeper question: “How expensive is it to move the price in each direction?” It tries to answer: how many dollars of traded volume are needed to move the price by one ATR upward, and how many dollars are needed to move it by one ATR downward. The script calculates two main numbers: Cost Up: estimated dollar volume needed to push the price up by one ATR. Cost Down: estimated dollar volume needed to push the price down by one ATR. Once it has Cost Up and Cost Down, it forms a Cost Ratio defined conceptually as Cost Down divided by Cost Up. This Cost Ratio is the heart of the indicator. If the ratio is greater than 1, it means Cost Down is higher than Cost Up. In words: it is more expensive (takes more dollars) to push the price down than up. That implies that the path of least resistance is upward, and the indicator interprets this as a bullish liquidity condition. If the ratio is less than 1, it means Cost Up is higher than Cost Down. It takes more money to lift the market than to push it lower. That means downside is the cheaper direction, and the path of least resistance is downward, interpreted as a bearish liquidity condition. By framing the market in this way, the script is effectively tracking where limit orders and liquidity are stacked more heavily, and where the order book is thinner, without ever seeing the actual order book. It uses aggregated volume and price impact instead. The Intensity Method: Estimating Buy and Sell Volume from 1‑Minute OHLCV On many TradingView symbols you do not get tick-by-tick data with explicit buyer/seller flags. To overcome this, the script uses a well‑known idea sometimes called an “intensity” or “intraday intensity” approach. For each 1‑minute candle, it looks at where the close is within the bar’s high–low range. If the candle closes near its high, the assumption is that buying pressure dominated that minute. If it closes near its low, selling pressure dominated. If it closes near the middle, buying and selling were more balanced. Mathematically, the script computes a Buy Intensity value for every 1‑minute bar as: Buy Intensity = (Close − Low) divided by (High − Low). If the bar’s high equals its low (no range), buy intensity is set to 0.5 by default to represent a neutral 50/50 situation. The Sell Intensity is simply 1 minus the Buy Intensity. Using these intensities, the script takes the total traded volume of the bar, multiplies it by an average price for the bar (to convert it into dollar volume), and then assigns a portion of that dollar volume to “buy volume” and the rest to “sell volume”. For example, if Buy Intensity is 0.7, then 70% of that bar’s dollar volume is treated as buy-side volume and 30% as sell-side volume. This is a crucial step. It allows the script to split each minute’s trading into an estimated buy dollar volume and sell dollar volume without needing detailed tick direction. This intensity-based classification is much more nuanced than just looking at whether the close is higher or lower than the previous close. Clustering: Reducing Noise by Grouping 1‑Minute Bars Individual 1‑minute bars can be very noisy. Small random moves, tiny volume spikes, and microstructure effects can distort regression estimates if you try to model price impact one minute at a time. To deal with this, the script introduces the concept of “clusters.” A cluster is simply a group of N consecutive one-minute bars. The cluster size is adjustable via the “Cluster Size (1-min bars)” input. For example, if you set the cluster size to 5, the script groups the data into 5‑minute blocks. Within each cluster, the script: Records the open, high, low, and close across the entire cluster (like a 5‑minute candle built from 1‑minute bricks). Sums the total trading volume across those 1‑minute bars. Sums the estimated buy dollar volume and sell dollar volume (from the intensity method). Computes the cluster’s net return: the percentage change from the previous cluster’s close to this cluster’s close. Once a cluster is completed (for example, every 5 minutes), that cluster becomes a single observation fed into the impact model. This greatly reduces noise because each data point now represents multiple minutes of trading with more aggregated volume and a cleaner net price move. ATR: Normalizing the Movement by Volatility The script does not just care about raw price movement; it cares about how much movement relative to the asset’s typical volatility. To define “one unit” of movement, it uses ATR, the Average True Range. Here, ATR is computed on 1‑minute data over a configurable number of 1‑minute bars (for example, 3 or 5). For each minute, the true range (high minus low) is converted into “basis points” relative to the price level. Then a rolling average over the past ATR Length bars is taken. This produces an ATR in basis points (a percentage-like measure) and also an approximate ATR in price units. By using ATR, the model can compare different symbols and different volatility regimes more fairly. A one ATR move on a calm currency pair is smaller in absolute price terms than a one ATR move on a hyper‑volatile coin, but both represent a “normal” level of movement for each asset. When the script later talks about the cost to move “by one ATR,” it is always using this dynamically updated ATR based on recent 1‑minute volatility. The Impact Model: Lambda Up and Lambda Down The heart of the script is an impact model that links cluster dollar volume to cluster returns. Conceptually, it assumes that the absolute return for a cluster is related to the traded volume through a power law. In simple terms, larger dollar volume tends to create larger price moves, but not in a linear, one‑to‑one way. Instead, the relationship is sublinear (commonly the square root law). The script maintains two separate models: One model for upward moves, using clusters where price increased. One model for downward moves, using clusters where price decreased. For each cluster where the net return is positive, the script uses the cluster’s buy‑side dollar volume (since we assume buying pressure is the primary driver of upward moves). For each cluster with a negative return, it uses the cluster’s sell‑side dollar volume. Before feeding volume into the model, it scales that volume by a “Volume Scale Factor” (for example, one million) and then raises it to an “Impact Exponent.” The default exponent is 0.5, corresponding to a square root relationship, which is widely used in market microstructure literature. This exponent is configurable between 0.3 and 1.0 for experimentation. The script then performs an ongoing, exponentially weighted OLS (ordinary least squares) regression where: The dependent variable is the cluster return in basis points. The independent variable is the transformed buy or sell dollar volume (depending on direction). It maintains sums of products and squares with an exponential decay factor, so older observations gradually lose influence. The result of each regression is an estimated coefficient, which we can call “lambda up” for up moves and “lambda down” for down moves. Informally, lambda up measures how much upward price impact you get per unit of buy-side volume. Lambda down measures downward price impact per unit of sell-side volume. The script only starts trusting these lambda estimates after a minimum number of valid observations have been collected (configurable via “Minimum Observations”). There are also filters: Clusters with too small a price move (below a threshold in ticks) are ignored. Clusters with too low volume relative to the average are ignored. This keeps the regression from being polluted by trivial or irrelevant movements. From Lambda to Cost Up and Cost Down Once lambda up and lambda down exist, the script inverts the impact relationship to estimate how much dollar volume would be required to create a move equal to one ATR. Conceptually, it uses this logic: You know the “target move,” namely the current ATR in basis points. You know lambda (impact per unit volume). With a power-law relationship, you can solve backwards for the volume that would have been needed. Without writing the equation formally, the idea is: the cost is proportional to the ATR divided by lambda, adjusted by the impact exponent. The Volume Scale Factor is then applied back to express this in actual dollar terms. The result is: Cost Up: the estimated dollar volume required to create a one ATR upward move. Cost Down: the estimated dollar volume required to create a one ATR downward move. These two values are then displayed on the dashboard (for convenience often scaled into thousands, millions, or billions) and are used to derive the Cost Ratio. Cost Ratio, Log Ratio, and Directional Signal Once Cost Up and Cost Down are known, the script calculates the Cost Ratio as Cost Down divided by Cost Up. This single number drives the directional interpretation. If the Cost Ratio is significantly above 1, downward moves are “expensive” and upward moves are “cheap.” Liquidity is likely stronger below price and thinner above, which is a bullish condition. If the Cost Ratio is significantly below 1, upward moves are expensive and downward moves are cheap, implying a bearish liquidity condition. The script also computes the natural logarithm of the Cost Ratio. This log ratio is plotted as a histogram-style oscillator. A log ratio of zero corresponds to a Cost Ratio of 1. Values above zero indicate that down moves cost more than up moves; values below zero indicate the opposite. The log scale makes proportional differences symmetric: for example, a ratio of 2 (down cost is twice up cost) and a ratio of 0.5 (down cost is half up cost) are symmetric distances above and below zero in log space. The indicator internally converts the Cost Ratio and related thresholds into a discrete “Signal Strength,” an integer ranging from strongly bearish through neutral to strongly bullish. It uses three levels of strength in each direction: Strong up bias (path strongly upward). Moderate up bias. Slight up bias. Neutral. Slight down bias. Moderate down bias. Strong down bias. These are determined by comparing the Cost Ratio to user-defined “Strong Signal,” “Weak Signal,” and “Neutral Zone” thresholds. For example, if the strong threshold is 1.5, a ratio above 1.5 could be considered a strong bullish liquidity bias. Regime Filter: Validating When the Asymmetry Is Unusual Markets can oscillate around a small cost asymmetry without it being meaningful. To avoid overreacting to small, normal fluctuations, the script implements a “Regime Filter” based on statistical deviation. It keeps an exponentially weighted rolling average and variance of the Cost Ratio itself. From these, it computes a standardized score, often called a z-score: how many standard deviations the current ratio is away from its recent mean. You do not see any mathematical formula on screen, but conceptually: If the z-score is small in magnitude, the current asymmetry is normal noise. If the z-score is large (for example, greater than a threshold like 1.0 or 1.5 in absolute value), the current cost imbalance is unusual and worth more attention. The Regime Filter is optional and configurable. When enabled, a bullish cost asymmetry is considered “regime valid” only if the Cost Ratio is above 1 and the z-score exceeds the positive threshold. A bearish cost asymmetry is regime valid only if the Cost Ratio is below 1 and the z-score is below the negative threshold. The indicator uses this regime validity to strengthen or soften the final signal strength. Signals that are not regime validated may be downgraded (for example, a potential strong signal is treated only as moderate). When the asymmetry is both directional and statistically unusual, the script treats it as a high-conviction situation. Session Logic and Resetting Many instruments have daily sessions or long gaps (for example, equities with overnight gaps). The script includes logic to detect a new session based on a time gap in minutes. If the gap between consecutive 1‑minute intrabars exceeds the configured “Session Gap,” it treats this as a new session. On a new session, if “Reset on New Session” is enabled, the script resets its OLS statistics, ATR buffers, cost history, regime statistics, and session aggregates. This prevents old data from very different conditions (for example, illiquid after-hours trading) from polluting today’s live lambda and cost estimates. It then begins to warm up again as new data arrives. Dashboard Interpretation The script draws a multi-row dashboard table on the chart, which serves as a real-time control panel. While the exact layout is managed in code, conceptually it contains the following information segments. First, it shows basic configuration information: cluster size in minutes and ATR length in minutes, along with the current ATR in basis points and approximate price units. It also shows how many clusters have been processed, giving you a sense of how mature the session’s statistics are. Next, it shows the core cost metrics: Cost to move up by one ATR, formatted in K, M, or B dollars. Cost to move down by one ATR. The number of observations (clusters) that contributed to each of the lambda up and lambda down models. It highlights which path (up or down) is currently “cheap” by coloring the background and labeling the path as “CHEAP” or “COSTLY.” If the Cost Ratio is greater than 1, down is costly and up is the cheaper path; if less than 1, the roles are reversed. The dashboard then displays the Cost Ratio itself, along with a simple textual interpretation such as “up cheaper,” “down cheaper,” or “balanced.” It also shows the log ratio and whether that is currently bullish, bearish, or neutral. There is an intensity section showing: The fraction of total session dollar volume estimated as buying versus selling. The last observed bar’s buy intensity in percentage terms. If the Regime Filter display is enabled, a separate section shows: The current z-score of the Cost Ratio. Whether the current regime is marked as “UNUSUAL” or “NORMAL.” The rolling mean and standard deviation of the Cost Ratio. Further down, the main signal section summarizes the overall directional read using labels such as “STRONG UP,” “UP,” “LEAN UP,” “NEUTRAL,” “LEAN DOWN,” “DOWN,” or “STRONG DOWN.” It uses different colors and intensities to highlight the strength and combines it with a short text detail, like “UP is cheaper path” or “DOWN costs X percent more.” The divergence section compares the session’s net price return (from the session open) to the current path of least resistance. For example, if the session is down in price but the cheap path is up, it marks this as a “bull divergence,” hinting that price has moved opposite to the liquidity bias and might revert. Conversely, if price is up but down is cheaper, it flags a “bear divergence.” If model information is enabled, another section displays impact exponent, lambda up and lambda down values, and a summary of total session dollar volume. This is for users who want to understand the underlying model parameters more deeply. A cost history section shows recent snapshots of the last several ratios and cost values, allowing you to see whether the liquidity asymmetry is strengthening, weakening, or flipping direction over time. Optionally, there is also a debug section summarizing the script’s internal state: number of intrabars processed, number of valid observations, last true range in basis points, last cluster return, and so on. This can help advanced users diagnose whether the model is in warmup, active, or experiencing low-quality data. Visual Coloring and Oscillator Apart from the dashboard, the script also colors the chart background and bars based on the current signal strength and regime validity. During strong or moderate bullish signals, the background may be shaded greenish, with deeper colors when the regime filter validates the signal. During strong or moderate bearish signals, the background becomes reddish. Neutral or slight biases may have no background coloring or only subtle hints. Bars themselves can be recolored to reflect bullish or bearish cost asymmetry, with stronger, more opaque colors when the regime filter confirms the signal. This allows you to glance at the chart and instantly see the prevailing path of least resistance. In a separate pane, the script plots the log cost ratio as a column-style oscillator. The zero line represents balance between up and down costs. Columns above zero mean that the cost to push price down is higher than the cost to push it up (bullish bias). Columns below zero mean the opposite (bearish bias). Horizontal reference lines mark levels corresponding roughly to situations where one side costs 50 percent or 100 percent more than the other side, making it easy to spot extreme asymmetries. The script also calculates, but hides by default, time series for the raw cost values, lambda parameters, ATR, z-score, and signal strength, so that advanced users can enable and inspect them if desired. Alerts and Practical Trading Use The script defines a comprehensive set of alert conditions so that you can automate notifications rather than watching the dashboard constantly. There are alerts for: Strong bullish path with regime validation: when the model indicates that up is significantly cheaper than down and the regime filter confirms that this is an unusually strong asymmetry. Strong bearish path with regime validation. Strong bullish or bearish path without regime confirmation, for those who want earlier but possibly noisier signals. Moderate bullish or bearish path signals, when cost asymmetry is present but not extreme. There are also divergence alerts: Bullish divergence: when the session is down in price but the cost analysis says the cheap path is up with at least moderate strength. This may indicate an upcoming bullish reversal or at least a loss of downside efficiency. Bearish divergence: when the session is up in price but the cheap path is down, suggesting a possible bearish reversal. The script also detects regime flips in the cost ratio: situations where the cheap path switches from down to up or from up to down, crossing out of the neutral zone. Finally, it monitors the direction of change of the log ratio, and can fire alerts when the cost ratio is turning bullish or bearish from previously opposite territory, signaling a shift in liquidity momentum. In practical trading use, there are three main ways to use these signals: First, for trend-following: trade in the direction of the cheap path when the signal strength is at least moderate and ideally regime‑validated, using the background and bar colors as confirmation, and combining with your own trend, support/resistance, or structure analysis. Second, for reversals: watch for cases where the price trend and the cheap path disagree, especially when divergence alerts fire. For example, if price has been falling but the script shows that pushing it further down is becoming extremely expensive compared to lifting it, that is often a sign that the downtrend is running into strong buying liquidity and may soon exhaust. Third, for regime shifts: treat strong regime‑validated flips in the cost ratio as transitions in market structure. For example, when a previously bearish liquidity regime flips to a bullish one and remains there, you may switch from selling rallies to buying dips. Recommended Settings and Instrument Considerations Default settings are chosen to balance responsiveness and stability. A cluster size of 5 (five 1‑minute bars per cluster) and an ATR length of 3 (three 1‑minute bars for ATR) work well as an intraday “fast but not too noisy” configuration on many liquid instruments. For very fast, high-volume environments (like BTC or major FX pairs), a smaller cluster size such as 3 can give quicker reaction to changes in liquidity, at the cost of slightly more noise. For slower, choppier instruments or lower-liquidity stocks, a cluster size of 5 to 10 may provide smoother and more reliable signals. The default impact exponent of 0.5 corresponds to the square root law, which is widely supported by empirical research for liquid markets. You may experiment with values between 0.4 and 0.6, but large changes should be made cautiously. A higher exponent closer to 1 makes the model behave more like a linear impact model; that might be more realistic on very illiquid symbols. The OLS decay factor of around 0.985 implies a “memory” of roughly a few dozen to around a hundred observations. Lowering the decay (for example, to 0.95) will make the model adapt faster to sudden shifts, but also makes it more sensitive to short-term noise. Increasing it toward 0.99 makes the model more stable but slower to recognize regime changes. Because the script depends critically on both price and volume, it is not suitable for volume‑less indices or symbols with unreliable volume. Use it on futures, ETFs, spot forex pairs with synthetic volume, and liquid cryptocurrencies. For cash equities, it works best on regularly traded symbols during their main session, not in extremely thin pre‑market or after‑hours periods. Always remember the model requires a warmup period at the start of a session or when first loaded. During warmup, the status will indicate that the script is collecting observations and calculating ATR. Signals in this phase should be treated as preliminary until the minimum observations threshold is reached and the lambdas are marked as ready. Final Summary Desai’s Path of Least Resistance v2.2 (1M) is a cost-based impact model that converts everyday OHLCV data into a real‑time map of where the market can move most easily. It breaks each minute’s trading into estimated buy and sell dollar volume using an intensity method, aggregates these into clusters, and fits separate impact models for up and down moves. From these, it infers how many dollars it would take to push price by one ATR in each direction and compares those costs. The result is a live, statistically grounded signal of whether the path of least resistance is up or down, how strong that bias is, and whether it is unusually strong relative to recent behavior. Combined with a clear dashboard, background/bar coloring, and a rich set of alerts, this gives traders a new dimension to work with: not just “what price is doing,” but “where liquidity is weak or strong.” Used wisely and combined with structure, risk management, and your own strategy, this indicator can help you identify when trends are efficient, when they are running into thick liquidity, and when sharp reversals are likely because the current direction has become expensive while the opposite side remains cheap.
Pine Script® göstergesi
jaydesaigu tarafından
Gap Tracker Indicator v5Gap Tracker Indicator - Description Purpose: The Gap Tracker identifies price gaps on charts and visualizes unfilled gap zones that may act as future support/resistance levels. What it shows: Gap zones as colored rectangles: Red boxes = bearish gaps (price gapped down, leaving unfilled space above) Green boxes = bullish gaps (price gapped up, leaving unfilled space below) How gaps form: A gap occurs when the opening price of one candle is significantly different from the closing price of the previous candle Common after weekends, holidays, or major news events when markets are closed Gaps create "empty" price zones with no trading activity Trading significance: Many traders believe gaps tend to "fill" eventually (price returns to the gap zone) Unfilled gaps can act as magnetic levels - price often revisits them Gap zones may provide support (bullish gaps) or resistance (bearish gaps) On your chart: Multiple red boxes show unfilled bearish gaps where price gapped down Green boxes show unfilled bullish gaps where price gapped up The indicator tracks these zones until price fills them completely Right side shows "GAP TRACKER" panel with active gaps: Aktywne (2), Zamknięte (9), Zakres 7d (168) Key insight: The concentration of unfilled gaps suggests potential magnetic zones where price may return for "gap fill" trades. Traders often use these levels for entries, exits, or stop placement.
Pine Script® göstergesi
HubertLorenz tarafından
Ale tonkis Swing failure + 5MIndicator Description: Ale Tonkis Swing Failure (SFP) This script is an advanced Swing Failure Pattern (SFP) and Change in State of Delivery (CISD) indicator. It is designed to identify liquidity sweeps and market structure shifts across multiple timeframes simultaneously. Key Features Pivot Detection: Automatically identifies high and low pivot points based on a user-defined lookback period. Liquidity Sweep Analysis: Detects when the price "sweeps" (goes beyond) a previous pivot high or low without closing significantly past it, signaling a potential reversal. CISD (Change in State of Delivery): Tracks internal market structure shifts to confirm the SFP signal. Multi-Timeframe (MTF) Dashboard: A real-time table in the top-right corner monitors the trend state across four different timeframes: M1, M3, M5, and M15. Visual Alerts: The script uses dynamic bar coloring and labels (▲/▼) to signal entry points directly on the chart. Technical Updates (M5 Integration) The code has been specifically modified to include the 5-minute (M5) timeframe within the Multi-Timeframe logic: Data Fetching: A new request.security call was added to retrieve the sfp_trend_state from the 5-minute interval. Table Expansion: The display table was resized from 4 rows to 5 rows to accommodate the new data without overlapping. UI Alignment: The M5 state is now positioned between M3 and M15, providing a smoother transition for traders analyzing mid-range scalping opportunities. How to Read the Dashboard LONG (Green): Indicates a bullish SFP has occurred and the trend remains positive on that timeframe. SHORT (Red): Indicates a bearish SFP has occurred and the trend remains negative. Empty/Black: No active SFP trend is currently detected on that specific timeframe.
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diegovaldes2011 tarafından
GoM Scalping Pro V1.20 GoM Scalping Pro — Smart ALMA Signal System GoM Scalping Pro is a professional trading indicator designed to identify high-quality market entries using a smart trend-based signal engine combined with volatility filtering and built-in risk visualization. The indicator automatically highlights **potential BUY and SELL opportunities and displays structured trading levels directly on the chart, making it suitable for scalping, intraday, and short-term swing trading. 🔹 Key Features Smart trend-based signal detection Volatility filter to avoid low-quality market conditions Automatic calculation of Entry, Stop Loss, and Take Profit levels Multiple Take Profit targets for flexible trade management Clear and uncluttered chart visualization Customizable alerts (Push / Sound / Popup) Works on all markets and timeframes 📊 How to Use Signals appear directly on the chart when market conditions are valid Follow the displayed Entry, SL, and TP levels for structured execution Can be combined with your own market context or risk rules The indicator is designed to assist decision-making, not to replace trading discipline. 🎯 Recommended Markets For best performance, use on liquid instruments such as: Major Forex pairs Gold (XAUUSD) Major indices (US500, NAS100) Bitcoin (BTCUSD) ⚙️ Alerts Enable alerts to receive real-time notifications when new signals are detected. This allows you to monitor multiple instruments efficiently without staring at charts. ⚠️ Disclaimer This indicator is a technical analysis tool, not financial advice. Always test settings on a demo account and manage risk carefully. If you want, I can also provide: a shorter “store-style” description a premium / institutional tone version or a version optimized for conversions on TradingView
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god_of_markets_fx tarafından
Average CandleAverage Candle is a custom indicator that plots a synthetic candle built from the average open, high, low, and close of the last X periods, providing a smoother view of price behavior and trend. It helps filter noise by summarizing recent market action into a single, representative **candle** per bar. 1. Introduction Average Candle calculates the simple moving average of each OHLC component (Open, High, Low, Close) over a user-defined lookback period and renders that as a separate candle on the chart. This creates a smoothed representation of price that is less affected by short-term volatility while still respecting the overall structure of the market. By visualizing these averaged candles, traders can better identify underlying direction and momentum without removing the original price bars. 2. Key features - Uses the average of the last X opens, highs, lows, and closes to build a synthetic candle for each bar, allowing consistent smoothing across all OHLC components. - Colors the Average Candle bullish or bearish based on whether the average close is above or below the average open, making directional bias visually clear at a glance. - Can be overlaid on the main chart to compare raw price candles with their averaged counterpart, helping traders distinguish meaningful swings from short-term noise. 3. How to use - Add the indicator to your chart, choose the desired lookback length (X periods), and tune it according to your trading timeframe and style—for example, shorter lengths for more responsive signals and longer lengths for smoother trends. - Use the Average Candle to confirm trend direction, detect potential reversals, or validate entries and exits by checking whether price action aligns with the smoothed average structure. - Combine it with other tools such as support/resistance, volume, or momentum indicators, ensuring it is used as a complementary visualization aid rather than a standalone signal generator.
Pine Script® göstergesi
destrobr0685 tarafından
RSI Momentum SuperTrend█ OVERVIEW RSI Momentum SuperTrend is a momentum-based trend oscillator that combines classic RSI with a SuperTrend mechanism calculated directly on RSI values. Instead of using price-based ATR, the indicator measures volatility of RSI itself, allowing dynamic adaptation to different markets and timeframes. It is fast and responsive, designed for early detection of momentum shifts. It works especially well for divergence analysis, pullbacks within higher timeframe trends, and as a confirmation tool in contrarian strategies. █ CONCEPT The indicator was created to combine: - the sensitivity of an oscillator (RSI) - the stability of the SuperTrend mechanism The key element is calculating “ATR” directly on RSI changes and then normalizing it. This allows: - automatic adaptation to the instrument’s behavior - consistent performance across different markets and timeframes Dynamic upper and lower bands (RSI ± adaptive range) act as momentum control levels. A trend change occurs only after these levels are broken, helping to reduce market noise. █ FEATURES Data source: - RSI (default: close) - RSI length - EMA smoothing Additional: - Optional raw RSI display (can be used to build custom strategies and to compare with the SuperTrend line) Calculations: - EMA-smoothed RSI - Adaptive ATR calculated on RSI changes - Volatility normalization - Dynamic bands: RSI ± (ATR × multiplier) - Trailing mechanism: - Levels are dynamically updated according to trend direction - Direction changes only after they are broken - Trend change logic: - Down → Up: RSI > upper band - Up → Down: RSI < lower band Visualization: - RSI line with dynamic trend coloring - SuperTrend line on RSI - Gradient fill between RSI and ST - Candle coloring according to trend - Overbought / Oversold zones with fill - Fog on Price (optional). Trend direction visualization directly on the price chart Alerts: - Trend change to UP - Trend change to DOWN █ HOW TO USE Adding: Paste the code into Pine Editor or search for “RSI Momentum SuperTrend” Main settings: - RSI Length → default 14 - RSI Smoothing → signal smoothing - ATR Length (on RSI) → adaptation control - ATR Multiplier → main sensitivity parameter - Show Raw RSI → raw RSI preview - Color Candles → candle coloring according to trend - Fog on Price → trend visualization on price Interpretation: - Green color = uptrend - Red color = downtrend - Higher multiplier = fewer signals, higher quality - Lower multiplier = faster reaction, more signals █ APPLICATIONS It is recommended to use the indicator together with other technical tools. If you want to use it not as a trend indicator but as an entry tool, consider combining it with a slower trend indicator (e.g. classic SuperTrend). In this setup: - the main trend is defined by the slower indicator - entries are taken only in its direction - RSI Momentum ST helps to identify local pullbacks within the trend Ideal for: - Divergences e.g. price makes higher highs while RSI Momentum ST makes lower highs → possible trend weakness similarly: price goes down while the indicator goes up - Pullbacks in higher timeframe trends e.g. H4 uptrend, while on M15 RSI Momentum ST enters oversold zone → potential end of pullback - Contrarian strategies e.g. strong downtrend, while RSI Momentum ST starts turning up → possible market reaction Early detection of momentum shifts Best combined with: - Support and resistance levels - Market structure (HH, HL, LH, LL) - Volume - Price action - Higher timeframe analysis █ NOTES - Works on all markets and timeframes - Faster than classic price-based trend indicators - Best results are achieved when used with market context - Not a standalone trading system
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Uncle_the_shooter tarafından