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TASC 2021.11 MADH Moving Average Difference, Hann█  OVERVIEW Presented here is code for the "Moving Average Difference, Hann" indicator originally conceived by John ​Ehlers. The code is also published in the November 2021 issue of Trader's Tips by Technical Analysis of Stocks & ​Commodities (TASC) magazine. █  CONCEPTS By employing a Hann windowed finite impulse response filter (FIR), John ​Ehlers has enhanced the Moving Average Difference (MAD) to provide an oscillator with exceptional smoothness. ​Of notable mention, the wave form of MADH resembles ​Ehlers' "Reverse EMA" Indicator, formerly revealed in the September 2017 issue of TASC. Many variations of the "Reverse EMA" were published in TradingView's Public Library. █  FEATURES Three values in the script's "Settings/Inputs" provide control over the oscillators behavior:  • The price source  • A "Short Length" with a default of 8, to manage the lower band edge of the oscillator  • The "Dominant Cycle", originally set at 27, which appears to be a placeholder for an adaptive control mechanism Two coloring options are provided for the line's fill:  • "ZeroCross", the default, uses the line's position above/below the zero level. This is the mode used in the top version of MADH on this chart.  • "Momentum" uses the line's up/down state, as shown in the bottom version of the indicator on the chart. █  NOTES Calculations The source price is used in two independent Hann windowed FIR filters having two different periods (lengths) of historical observation for calculation, one being a "Short Length" and the other termed "Dominant Cycle". These are then passed to a "rate of change" calculation and then returned by the reusable function. The secret ​sauce is that a "windowed Hann FIR filter" is superior tp a generic SMA filter, and that ultimately reveals Ehlers' clever enhancement. We'll have to wait and see what ingenuities ​Ehlers has next to unleash. Stay tuned... The `madh()` function code was optimized for computational efficiency in Pine, differing visibly from ​Ehlers' original formula, but yielding the same results as ​Ehlers' version. Background This indicator has a sibling indicator discussed in the "The MAD Indicator, Enhanced" article by ​Ehlers. MADH is an evolutionary update from the prior MAD indicator code published in the October 2021 issue of TASC. Sibling Indicators  • Moving Average Difference (MAD)  • Cycle/Trend Analytics Related Information  • Cycle/Trend Analytics And The MAD Indicator  • The Reverse ​EMA Indicator  • Hann Window  • ROC Join TradingView!
Pine Script® Indikator
von PineCodersTASC
7
Alma Moving Average Ribbon Reverse Length [DM]Greetings Colleagues Following some recommendations and ideas I share this moving average, put all of them together The length calculation is automatic there is only one input. The length is inverse so it will wrap from the longest reference point, hence using phi Moving averages will wrap around the price. I've also added gradient color to plots and fill plots There is an alert selector in case you are interested in a particular crossing, "remember that the order is reversed". There is an alert visual plotshapes with offset signal. Finally, after spending a few hours with the Williams alligator moving averages I found nothing special, but I added the individual offset adjustment for each moving average in case someone comes up with something. Enjoy” Some references about alma by "tradingview pinecoders" What to look for The Arnaud Legoux Moving Average has three elements to it: Window: This element is the period. By default, the window is set to 9 periods, but it can be customized to fit any trading style. Offset: This element is the Gaussian that is applied to the combo line and can be aligned to the current price. It’s default is set to 0.85, but by setting it to 1, you can make it align fully to the current price (similar to how an Exponential Moving Average (EMA) with a setting of 0 is like a Simple Moving Average (SMA)). 0.85 is what is recommended, however, you can customize it like with the window element. Sigma: This element is a standard deviation that is applied to the combo line in order for it to appear more sharp. The default is set to 6 and it is not recommended to change the setting. The value of 6 is inspired by the Six Sigma process. www.tradingview.com
Pine Script® Indikator
von dgmoon
[blackcat] L2 Ehlers FilterLevel: 2 Background John F. Ehlers introuced Ehlers Filter in his "Rocket Science for Traders" chapter 18 on 2001. Function blackcat L2 Ehlers Filter is used to follow trend. The filters Dr. Ehlers have invented are nonlinear FIR filters. It turns out that they provide both extraordinary smoothing in sideways markets and aggressively follow major price movements with minimal lag. The development of Ehlers filters starts with a general class of FIR filters called Order Statistic (OS) filters. These filters are well-known for speech and image processing, to sharpen edges, increase contrast, and for robust estimation. In contrast to linear filters, where temporal ordering of the samples is preserved, OS filters base their operation on the ranking of samples within the filter window. The data are ranked by their summary statistics, such as their mean or variance, rather than by their temporal position. Among OS filters, the Median filter is the best known. In a Median filter, the output is the median value of all the data values within the observation window. As opposed to an averaging filter, the Median filter simply discards all data except the median value. In this way, impulsive noise spikes and extreme price data are eliminated rather than included in the average. The median value can fall at the first sample in the data window, at the last sample, or anywhere in between. Thus, temporal characteristics are lost. The Median filter tends to smooth out short-term variations that lead to whipsaw trades with linear filters. However, the lag of a Median filter in response to a sharp and sustained price movement is substantial --- it necessarily is about half the filter window width. Key Signal Coef --> Ehlers filter coefficients array Filt --> Ehlers filter output Pros and Cons 100% John F. Ehlers definition translation of original work, even variable names are the same. This help readers who would like to use pine to read his book. If you had read his works, then you will be quite familiar with my code style. Remarks The 14th script for Blackcat1402 John F. Ehlers Week publication. Readme In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts. The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works. Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element. Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level. Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated. Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop. Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
Pine Script® Indikator
von blackcat1402
MultiSessions traderglobal.topEste indicador de sesiones está diseñado para traders intradía que desean visualizar con precisión la actividad y la volatilidad característica de cada mercado. Basado en Pine Script v5 y optimizado para la zona horaria “America/New_York”, divide el día en sub-sesiones configurables y resalta sus rangos de precio en tiempo real. En particular, incorpora tres bloques para New York (NY1, NY2, NY3), dos para Londres (LON1, LON2), dos para Tokio (TKO1, TKO2) y mantiene Sídney como sesión opcional. Cada bloque puede activarse o desactivarse de forma independiente y cuenta con su propio color ajustable, lo que permite construir mapas visuales claros para estrategias basadas en horario, solapamientos y micro-estructuras de mercado. El panel de inputs incluye la opción “Activate High/Low View”. Cuando está activada, el indicador calcula de manera incremental el mínimo y máximo de cada sub-sesión y sombrea el área entre ambos con fill, proporcionando una referencia inmediata del rango intrasesión (útil para medir compresión/expansión y posibles rompimientos). Cuando está desactivada, emplea un simple bgcolor por bloque, ideal para traders que prefieren un gráfico más limpio y solo desean distinguir visualmente los tramos horarios. La lógica central utiliza dos funciones auxiliares: is_session(sess), que detecta si la vela actual pertenece a un tramo horario concreto, e is_newbar(sess), que determina el inicio de una nueva barra de referencia según la resolución elegida (D, W o M). Gracias a esta combinación, en cada sub-sesión el indicador reinicia sus contadores de alto y bajo al comenzar el período y los actualiza vela a vela mientras el bloque siga activo. Este enfoque evita mezclas de datos entre sesiones y asegura que el rango que se muestra corresponda estrictamente al segmento horario configurado. Los horarios por defecto están pensados para Forex y contemplan casos que cruzan medianoche (por ejemplo, Tokio 2 y Sídney). Pine Script admite rangos como 2200-0200; no obstante, si tu bróker o la zona horaria del gráfico generan un sombreado parcial, basta con dividir el tramo en dos: 2200-2359 y 0000-0200. Asimismo, cada input.session incluye el patrón :1234567 para habilitar los siete días; puedes restringir días según tu operativa. En cuanto al uso práctico, el indicador facilita identificar: (1) la estructura del rango por sub-sesión (útil para estrategias de breakout/mean-reversion), (2) los solapamientos entre Londres y New York, donde suele concentrarse la liquidez, y (3) períodos de menor volatilidad (tramos tardíos de Asia o previos a noticias). El color independiente por bloque te permite codificar visualmente la importancia o tu plan de trading (por ejemplo, tonos más intensos en ventanas de alta probabilidad). Finalmente, su diseño modular hace sencilla la personalización: puedes ajustar colores, activar/desactivar bloques, cambiar horarios y modificar la resolución de reseteo del rango. Como posible mejora, se pueden añadir alertas de ruptura de máximos/mínimos de sub-sesión o etiquetas con la altura del rango (pips) al cierre. Este indicador no sustituye el juicio del trader ni constituye recomendación financiera, pero ofrece una base visual robusta para integrar el factor tiempo en la toma de decisiones. This sessions indicator is built for intraday traders who want a precise, time-aware view of market activity and typical volatility patterns across the day. Written in Pine Script v5 and optimized for the “America/New_York” timezone, it divides the trading day into configurable sub-sessions and highlights their price ranges in real time. Specifically, it provides three blocks for New York (NY1, NY2, NY3), two for London (LON1, LON2), two for Tokyo (TKO1, TKO2), and keeps Sydney as an optional session. Each block can be enabled or disabled independently and comes with its own adjustable color, letting you build clear visual maps for time-based strategies, overlaps, and microstructure nuances. In the inputs panel you’ll find the “Activate High/Low View” option. When enabled, the indicator incrementally computes each sub-session’s low and high and shades the area between them with fill, giving you an immediate reference to the intra-session range (useful for gauging compression/expansion and potential breakouts). When disabled, it switches to a clean bgcolor background by block—ideal if you prefer a minimal chart and simply want to distinguish time windows at a glance. The core logic relies on two helper functions: is_session(sess), which detects whether the current bar falls within a given time window, and is_newbar(sess), which identifies the start of a new reference bar according to your chosen reset resolution (D, W, or M). With this combination, each sub-session resets its high/low at the beginning of the period and updates them bar by bar while the block remains active. This prevents cross-contamination between sessions and ensures the range you see belongs strictly to the configured segment. Default hours are suited to Forex and include segments that cross midnight (e.g., Tokyo 2 and Sydney). Pine Script supports ranges like 2200-0200; however, if your broker or chart timezone causes partial shading, simply split the segment into two: 2200-2359 and 0000-0200. Each input.session uses the :1234567 suffix to enable all seven days; you can easily restrict days to match your plan. Practically speaking, the indicator helps you identify: (1) range structure by sub-session (great for breakout or mean-reversion frameworks), (2) overlaps between London and New York, where liquidity and directional moves often concentrate, and (3) lower-volatility windows (late Asia or pre-news lulls). Independent colors per block let you visually encode priority or your trading plan (for example, richer tones in high-probability windows). Thanks to its modular design, customization is straightforward: adjust colors, toggle blocks, change hours, and tweak the range-reset resolution to suit your routine. As a natural extension, you can add alerts for sub-session high/low breakouts or labels that display the range height (in pips) at session close. While no indicator replaces trader judgment or constitutes financial advice, this tool offers a robust visual foundation for incorporating the time factor directly into your decision-making, helping you contextualize price action within the rhythm of global trading sessions.
Pine Script® Indikator
von traderglobaltop
MERV: Market Entropy & Rhythm Visualizer [BullByte]The MERV (Market Entropy & Rhythm Visualizer) indicator analyzes market conditions by measuring entropy (randomness vs. trend), tradeability (volatility/momentum), and cyclical rhythm. It provides traders with an easy-to-read dashboard and oscillator to understand when markets are structured or choppy, and when trading conditions are optimal. Purpose of the Indicator MERV’s goal is to help traders identify different market regimes. It quantifies how structured or random recent price action is (entropy), how strong and volatile the movement is (tradeability), and whether a repeating cycle exists. By visualizing these together, MERV highlights trending vs. choppy environments and flags when conditions are favorable for entering trades. For example, a low entropy value means prices are following a clear trend line, whereas high entropy indicates a lot of noise or sideways action. The indicator’s combination of measures is original: it fuses statistical trend-fit (entropy), volatility trends (ATR and slope), and cycle analysis to give a comprehensive view of market behavior. Why a Trader Should Use It Traders often need to know when a market trend is reliable vs. when it is just noise. MERV helps in several ways: it shows when the market has a strong direction (low entropy, high tradeability) and when it’s ranging (high entropy). This can prevent entering trend-following strategies during choppy periods, or help catch breakouts early. The “Optimal Regime” marker (a star) highlights moments when entropy is very low and tradeability is very high, typically the best conditions for trend trades. By using MERV, a trader gains an empirical “go/no-go” signal based on price history, rather than guessing from price alone. It’s also adaptable: you can apply it to stocks, forex, crypto, etc., on any timeframe. For example, during a bullish phase of a stock, MERV will turn green (Trending Mode) and often show a star, signaling good follow-through. If the market later grinds sideways, MERV will shift to magenta (Choppy Mode), warning you that trend-following is now risky. Why These Components Were Chosen Market Entropy (via R²) : This measures how well recent prices fit a straight line. We compute a linear regression on the last len_entropy bars and calculate R². Entropy = 1 - R², so entropy is low when prices follow a trend (R² near 1) and high when price action is erratic (R² near 0). This single number captures trend strength vs noise. Tradeability (ATR + Slope) : We combine two familiar measures: the Average True Range (ATR) (normalized by price) and the absolute slope of the regression line (scaled by ATR). Together they reflect how active and directional the market is. A high ATR or strong slope means big moves, making a trend more “tradeable.” We take a simple average of the normalized ATR and slope to get tradeability_raw. Then we convert it to a percentile rank over the lookback window so it’s stable between 0 and 1. Percentile Ranks : To make entropy and tradeability values easy to interpret, we convert each to a 0–100 rank based on the past len_entropy periods. This turns raw metrics into a consistent scale. (For example, an entropy rank of 90 means current entropy is higher than 90% of recent values.) We then divide by 100 to plot them on a 0–1 scale. Market Mode (Regime) : Based on those ranks, MERV classifies the market: Trending (Green) : Low entropy rank (<40%) and high tradeability rank (>60%). This means the market is structurally trending with high activity. Choppy (Magenta) : High entropy rank (>60%) and low tradeability rank (<40%). This is a mostly random, low-momentum market. Neutral (Cyan) : All other cases. This covers mixed regimes not strongly trending or choppy. The mode is shown as a colored bar at the bottom: green for trending, magenta for choppy, cyan for neutral. Optimal Regime Signal : Separately, we mark an “optimal” condition when entropy_norm < 0.3 and tradeability > 0.7 (both normalized 0–1). When this is true, a ★ star appears on the bottom line. This star is colored white when truly optimal, gold when only tradeability is high (but entropy not quite low enough), and black when neither condition holds. This gives a quick visual cue for very favorable conditions. What Makes MERV Stand Out Holistic View : Unlike a single-oscillator, MERV combines trend, volatility, and cycle analysis in one tool. This multi-faceted approach is unique. Visual Dashboard : The fixed on-chart dashboard (shown at your chosen corner) summarizes all metrics in bar/gauge form. Even a non-technical user can glance at it: more “█” blocks = a higher value, colors match the plots. This is more intuitive than raw numbers. Adaptive Thresholds : Using percentile ranks means MERV auto-adjusts to each market’s character, rather than requiring fixed thresholds. Cycle Insight : The rhythm plot adds information rarely found in indicators – it shows if there’s a repeating cycle (and its period in bars) and how strong it is. This can hint at natural bounce or reversal intervals. Modern Look : The neon color scheme and glow effects make the lines easy to distinguish (blue/pink for entropy, green/orange for tradeability, etc.) and the filled area between them highlights when one dominates the other. Recommended Timeframes MERV can be applied to any timeframe, but it will be more reliable on higher timeframes. The default len_entropy = 50 and len_rhythm = 30 mean we use 30–50 bars of history, so on a daily chart that’s ~2–3 months of data; on a 1-hour chart it’s about 2–3 days. In practice: Swing/Position traders might prefer Daily or 4H charts, where the calculations smooth out small noise. Entropy and cycles are more meaningful on longer trends. Day trader s could use 15m or 1H charts if they adjust the inputs (e.g. shorter windows). This provides more sensitivity to intraday cycles. Scalpers might find MERV too “slow” unless input lengths are set very low. In summary, the indicator works anywhere, but the defaults are tuned for capturing medium-term trends. Users can adjust len_entropy and len_rhythm to match their chart’s volatility. The dashboard position can also be moved (top-left, bottom-right, etc.) so it doesn’t cover important chart areas. How the Scoring/Logic Works (Step-by-Step) Compute Entropy : A linear regression line is fit to the last len_entropy closes. We compute R² (goodness of fit). Entropy = 1 – R². So a strong straight-line trend gives low entropy; a flat/noisy set of points gives high entropy. Compute Tradeability : We get ATR over len_entropy bars, normalize it by price (so it’s a fraction of price). We also calculate the regression slope (difference between the predicted close and last close). We scale |slope| by ATR to get a dimensionless measure. We average these (ATR% and slope%) to get tradeability_raw. This represents how big and directional price moves are. Convert to Percentiles : Each new entropy and tradeability value is inserted into a rolling array of the last 50 values. We then compute the percentile rank of the current value in that array (0–100%) using a simple loop. This tells us where the current bar stands relative to history. We then divide by 100 to plot on . Determine Modes and Signal : Based on these normalized metrics: if entropy < 0.4 and tradeability > 0.6 (40% and 60% thresholds), we set mode = Trending (1). If entropy > 0.6 and tradeability < 0.4, mode = Choppy (-1). Otherwise mode = Neutral (0). Separately, if entropy_norm < 0.3 and tradeability > 0.7, we set an optimal flag. These conditions trigger the colored mode bars and the star line. Rhythm Detection : Every bar, if we have enough data, we take the last len_rhythm closes and compute the mean and standard deviation. Then for lags from 5 up to len_rhythm, we calculate a normalized autocorrelation coefficient. We track the lag that gives the maximum correlation (best match). This “best lag” divided by len_rhythm is plotted (a value between 0 and 1). Its color changes with the correlation strength. We also smooth the best correlation value over 5 bars to plot as “Cycle Strength” (also 0 to 1). This shows if there is a consistent cycle length in recent price action. Heatmap (Optional) : The background color behind the oscillator panel can change with entropy. If “Neon Rainbow” style is on, low entropy is blue and high entropy is pink (via a custom color function), otherwise a classic green-to-red gradient can be used. This visually reinforces the entropy value. Volume Regime (Dashboard Only) : We compute vol_norm = volume / sma(volume, len_entropy). If this is above 1.5, it’s considered high volume (neon orange); below 0.7 is low (blue); otherwise normal (green). The dashboard shows this as a bar gauge and percentage. This is for context only. Oscillator Plot – How to Read It The main panel (oscillator) has multiple colored lines on a 0–1 vertical scale, with horizontal markers at 0.2 (Low), 0.5 (Mid), and 0.8 (High). Here’s each element: Entropy Line (Blue→Pink) : This line (and its glow) shows normalized entropy (0 = very low, 1 = very high). It is blue/green when entropy is low (strong trend) and pink/purple when entropy is high (choppy). A value near 0.0 (below 0.2 line) indicates a very well-defined trend. A value near 1.0 (above 0.8 line) means the market is very random. Watch for it dipping near 0: that suggests a strong trend has formed. Tradeability Line (Green→Yellow) : This represents normalized tradeability. It is colored bright green when tradeability is low, transitioning to yellow as tradeability increases. Higher values (approaching 1) mean big moves and strong slopes. Typically in a market rally or crash, this line will rise. A crossing above ~0.7 often coincides with good trend strength. Filled Area (Orange Shade) : The orange-ish fill between the entropy and tradeability lines highlights when one dominates the other. If the area is large, the two metrics diverge; if small, they are similar. This is mostly aesthetic but can catch the eye when the lines cross over or remain close. Rhythm (Cycle) Line : This is plotted as (best_lag / len_rhythm). It indicates the relative period of the strongest cycle. For example, a value of 0.5 means the strongest cycle was about half the window length. The line’s color (green, orange, or pink) reflects how strong that cycle is (green = strong). If no clear cycle is found, this line may be flat or near zero. Cycle Strength Line : Plotted on the same scale, this shows the autocorrelation strength (0–1). A high value (e.g. above 0.7, shown in green) means the cycle is very pronounced. Low values (pink) mean any cycle is weak and unreliable. Mode Bars (Bottom) : Below the main oscillator, thick colored bars appear: a green bar means Trending Mode, magenta means Choppy Mode, and cyan means Neutral. These bars all have a fixed height (–0.1) and make it very easy to see the current regime. Optimal Regime Line (Bottom) : Just below the mode bars is a thick horizontal line at –0.18. Its color indicates regime quality: White (★) means “Optimal Regime” (very low entropy and high tradeability). Gold (★) means not quite optimal (high tradeability but entropy not low enough). Black means neither condition. This star line quickly tells you when conditions are ideal (white star) or simply good (gold star). Horizontal Guides : The dotted lines at 0.2 (Low), 0.5 (Mid), and 0.8 (High) serve as reference lines. For example, an entropy or tradeability reading above 0.8 is “High,” and below 0.2 is “Low,” as labeled on the chart. These help you gauge values at a glance. Dashboard (Fixed Corner Panel) MERV also includes a compact table (dashboard) that can be positioned in any corner. It summarizes key values each bar. Here is how to read its rows: Entropy : Shows a bar of blocks (█ and ░). More █ blocks = higher entropy. It also gives a percentage (rounded). A full bar (10 blocks) with a high % means very chaotic market. The text is colored similarly (blue-green for low, pink for high). Rhythm : Shows the best cycle period in bars (e.g. “15 bars”). If no calculation yet, it shows “n/a.” The text color matches the rhythm line. Cycle Strength : Gives the cycle correlation as a percentage (smoothed, as shown on chart). Higher % (green) means a strong cycle. Tradeability : Displays a 10-block gauge for tradeability. More blocks = more tradeable market. It also shows “gauge” text colored green→yellow accordingly. Market Mode : Simply shows “Trending”, “Choppy”, or “Neutral” (cyan text) to match the mode bar color. Volume Regime : Similar to tradeability, shows blocks for current volume vs. average. Above-average volume gives orange blocks, below-average gives blue blocks. A % value indicates current volume relative to average. This row helps see if volume is abnormally high or low. Optimal Status (Large Row) : In bold, either “★ Optimal Regime” (white text) if the star condition is met, “★ High Tradeability” (gold text) if tradeability alone is high, or “— Not Optimal” (gray text) otherwise. This large row catches your eye when conditions are ripe. In short, the dashboard turns the numeric state into an easy read: filled bars, colors, and text let you see current conditions without reading the plot. For instance, five blue blocks under Entropy and “25%” tells you entropy is low (good), and a row showing “Trending” in green confirms a trend state. Real-Life Example Example : Consider a daily chart of a trending stock (e.g. “AAPL, 1D”). During a strong uptrend, recent prices fit a clear upward line, so Entropy would be low (blue line near bottom, perhaps below the 0.2 line). Volatility and slope are high, so Tradeability is high (green-yellow line near top). In the dashboard, Entropy might show only 1–2 blocks (e.g. 10%) and Tradeability nearly full (e.g. 90%). The Market Mode bar turns green (Trending), and you might see a white ★ on the optimal line if conditions are very good. The Volume row might light orange if volume is above average during the rally. In contrast, imagine the same stock later in a tight range: Entropy will rise (pink line up, more blocks in dashboard), Tradeability falls (fewer blocks), and the Mode bar turns magenta (Choppy). No star appears in that case. Consolidated Use Case : Suppose on XYZ stock the dashboard reads “Entropy: █░░░░░░░░ 20%”, “Tradeability: ██████████ 80%”, Mode = Trending (green), and “★ Optimal Regime.” This tells the trader that the market is in a strong, low-noise trend, and it might be a good time to follow the trend (with appropriate risk controls). If instead it reads “Entropy: ████████░░ 80%”, “Tradeability: ███▒▒▒▒▒▒ 30%”, Mode = Choppy (magenta), the trader knows the market is random and low-momentum—likely best to sit out until conditions improve. Example: How It Looks in Action Screenshot 1: Trending Market with High Tradeability (SOLUSD, 30m) What it means: The market is in a clear, strong trend with excellent conditions for trading. Both trend-following and active strategies are favored, supported by high tradeability and strong volume. Screenshot 2: Optimal Regime, Strong Trend (ETHUSD, 1h) What it means: This is an ideal environment for trend trading. The market is highly organized, tradeability is excellent, and volume supports the move. This is when the indicator signals the highest probability for success. Screenshot 3: Choppy Market with High Volume (BTC Perpetual, 5m) What it means: The market is highly random and choppy, despite a surge in volume. This is a high-risk, low-reward environment, avoid trend strategies, and be cautious even with mean-reversion or scalping. Settings and Inputs The script is fully open-source; here are key inputs the user can adjust: Entropy Window (len_entropy) : Number of bars used for entropy and tradeability (default 50). Larger = smoother, more lag; smaller = more sensitivity. Rhythm Window (len_rhythm ): Bars used for cycle detection (default 30). This limits the longest cycle we detect. Dashboard Position : Choose any corner (Top Right default) so it doesn’t cover chart action. Show Heatmap : Toggles the entropy background coloring on/off. Heatmap Style : “Neon Rainbow” (colorful) or “Classic” (green→red). Show Mode Bar : Turn the bottom mode bar on/off. Show Dashboard : Turn the fixed table panel on/off. Each setting has a tooltip explaining its effect. In the description we will mention typical settings (e.g. default window sizes) and that the user can move the dashboard corner as desired. Oscillator Interpretation (Recap) Lines : Blue/Pink = Entropy (low=trend, high=chop); Green/Yellow = Tradeability (low=quiet, high=volatile). Fill : Orange tinted area between them (for visual emphasis). Bars : Green=Trending, Magenta=Choppy, Cyan=Neutral (at bottom). Star Line : White star = ideal conditions, Gold = good but not ideal. Horizontal Guides : 0.2 and 0.8 lines mark low/high thresholds for each metric. Using the chart, a coder or trader can see exactly what each output represents and make decisions accordingly. Disclaimer This indicator is provided as-is for educational and analytical purposes only. It does not guarantee any particular trading outcome. Past market patterns may not repeat in the future. Users should apply their own judgment and risk management; do not rely solely on this tool for trading decisions. Remember, TradingView scripts are tools for market analysis, not personalized financial advice. We encourage users to test and combine MERV with other analysis and to trade responsibly. -BullByte
Pine Script® Indikator
von BullByte
6
[Mad]Triple Bollinger Bands ForecastTriple Bollinger Bands Forecast (BBx3+F) This open-source indicator is an advanced version of the classic Bollinger Bands, designed to provide a more comprehensive and forward-looking view of market volatility and potential price levels. It plots three distinct sets of Bollinger Bands and projects them into the future based on statistical calculations. How It Is Built and Key Features Triple Bollinger Bands: Instead of a single set of bands, this indicator plots three. All three share the same central basis line (a Simple Moving Average), but each has a different standard deviation multiplier. This creates three distinct volatility zones for analyzing price deviation from its mean. Multi-Timeframe (MTF) Capability: The indicator can calculate and display Bollinger Bands from a higher timeframe (e.g., showing daily bands on a 4-hour chart). This allows for contextualizing price action within the volatility structure of a more significant trend. (Lower HTF selection will result in script-crash!) Future Forecasting: This is the indicator's main feature. It projects the calculated Bollinger Bands up to 8 bars into the future. This forecast is a recalculation of the Simple Moving Average and Standard Deviation based on a projected future source price. Selectable Forecast Methods: The mathematical model for estimating the future source price can be selected: Flat: A model that uses the most recent closing price as the price for all future bars in the calculation window. Linreg (Linear Regression): A model that calculates a linear regression trend on the last few bars and projects it forward to estimate the future source price. Efficient Drawing with Polylines: The future projections are drawn on the chart using Pine Script's polyline object. This is an efficient method that draws the forecast data only on the last bar, which avoids repainting issues. Differences from a Classical Bollinger Bands Indicator Band Count: A classical indicator shows one set of bands. This indicator plots three sets for a multi-layered view of volatility. Perspective: Classical Bollinger Bands are purely historical. This indicator is both historical and forward-looking . Forecasting: The classic version has no forecasting capability. This indicator projects the bands into the future . Timeframe: The classic version works only on the current timeframe. This indicator has full Multi-Timeframe (MTF) support . The Mathematics Behind the Future Predictions The core challenge in forecasting Bollinger Bands is that a future band value depends on future prices, which are unknown. This indicator solves this by simulating a future price series. Here is the step-by-step logic: Forecast the Source Price for the Next Bar First, the indicator estimates what the price will be on the next bar. Flat Method: The forecasted price is the current bar's closing price. Price_forecast = close Linreg Method: A linear regression is calculated on the last few bars and extrapolated one step forward. Price_forecast = ta.linreg(close, linreglen, 1) Calculate the Future SMA (Basis) To calculate the Simple Moving Average for the next bar, a new data window is simulated. This window includes the new forecasted price and drops the oldest historical price. For a 1-bar forecast, the calculation is: SMA_future = (Price_forecast + close + close + ... + close ) / length Calculate the Future Standard Deviation Similarly, the standard deviation for the next bar is calculated over this same simulated window of prices, using the new SMA_future as its mean. // 1. Calculate the sum of squared differences from the new mean d_f = Price_forecast - SMA_future d_0 = close - SMA_future // ... and so on for the rest of the window's prices SumOfSquares = (d_f)^2 + (d_0)^2 + ... + (d_length-2)^2 // 2. Calculate future variance and then the standard deviation Var_future = SumOfSquares / length StDev_future = sqrt(Var_future) Extending the Forecast (2 to 8 Bars) For forecasts further into the future (e.g., 2 bars), the script uses the same single Price_forecast for all future steps in the calculation. For a 2-bar forecast, the simulated window effectively contains the forecasted price twice, while dropping the two oldest historical prices. This provides a statistically-grounded projection of where the Bollinger Bands are likely to form. Usage as a Forecast Extension This indicator's functionality is designed to be modular. It can be used in conjunction with as example Mad Triple Bollinger Bands MTF script to separate the rendering of historical data from the forward-looking forecast. Configuration for Combined Use: Add both the Mad Triple Bollinger Bands MTF and this Triple Bollinger Bands Forecast indicator to your chart. Open the Settings for this indicator (BBx3+F). In the 'General Settings' tab, disable the Activate Plotting option. To ensure data consistency, the Bollinger Length, Multipliers, and Higher Timeframe settings should be identical across both indicators. This configuration prevents the rendering of duplicate historical bands. The Mad Triple Bollinger Bands MTF script will be responsible for visualizing the historical and current bands, while this script will overlay only the forward-projected polyline data.
Pine Script® Indikator
von djmad
Linear Regression ForecastDescription: This indicator computes a series of simple linear regressions anchored at the current bar, using look-back windows from 2 bars up to the user-defined maximum. Each regression line is projected forward by the same number of bars as its look-back, producing a family of forecast endpoints. These endpoints are then connected into a continuous polyline: ascending segments are drawn in green, and descending segments in red. Inputs: maxLength – Maximum number of bars to include in the longest regression (minimum 2) priceSource – Price series used for regression (for example, close, open, high, low) lineWidth – Width of each line segment Calculation: For each window size N (from 2 to maxLength): • Compute least-squares slope and intercept over the N most recent bars (with bar 0 = current bar, bar 1 = one bar ago, etc.). • Project the regression line to bar_index + N to obtain the forecast price. Collected forecast points are sorted by projection horizon and then joined: • First segment: current bar’s price → first forecast point • Subsequent segments: each forecast point → next forecast point Segment colors reflect slope direction: green for non-negative, red for negative. Usage: Apply this overlay to any price chart. Adjust maxLength to control the depth and reach of the forecast fan. Observe how shorter windows produce nearer-term, more reactive projections, while longer windows yield smoother, more conservative forecasts. Use the colored segments to gauge the overall bias of the fan at each step. Limitations: This tool is for informational and educational purposes only. It relies on linear regression assumptions and past price behavior; it does not guarantee future performance. Users should combine it with other technical or fundamental analyses and risk management practices.
Pine Script® Indikator
von Tradenometry
LGMM (flat buffers) — multivariate poly + latent statesLGMM POLYNOMIAL BANDS — DISCOVER THE MARKET’S HIDDEN STATES Overview Latent-Gaussian-Mixture-Models (LGMMs) view price action as a mix of several invisible regimes: trending up, drifting sideways, sudden volatility spikes, and so on. A Gaussian Mixture learns these states directly from data and outputs, for every bar, the probability that the market is in each state. This indicator feeds those probabilities into a rolling polynomial regression that draws a fair-value line, then builds adaptive upper and lower bands. Band width expands when recent residuals are large *and* when the state mix is uncertain, and contracts when price is calm or one regime clearly dominates. Crossing back into the band from below generates a buy flag; crossing back into the band from above generates a sell flag (or take-profit for longs). Key Inputs Price source – default is Close; you can choose HL2, OHLC4, etc. Training window (bars) – look-back length for every retrain. 252 bars (one trading year) is a balanced default for US stocks on daily timeframe. Use fewer bars for intraday charts (say 7*24=168 for 1H bars on crypto), more for weekly periods. Polynomial degree – 1 for a straight trend line, 2 for a curved fit. Curved fits are better when the symbol shows persistent drift. Hidden states K – number of regimes the mixture tracks (1 to 3). Three states often map well to up-trend, chop, down-trend. Band width ×σ – multiplier on the entropy-weighted standard deviation. Smaller values (1.5-2) give more trades; larger values (2.5-3) give fewer, higher-conviction trades. Offline μ,σ pairs (optional) – paste component means and sigmas from an offline LGMM (format: mu1,sigma1;mu2,sigma2;…). Leave blank to let the script use its built-in approximation. Quick Start Add the indicator to a chart and wait until the initial Training window has filled. Watch for green BUY triangles when price closes back above the lower band and red SELL triangles when price closes back below the upper band. Fine-tune: – Increase Training window to reduce noise. – Decrease Band width ×σ for more frequent signals. – Experiment with Hidden states K; more states capture richer behaviour but need longer windows to stay reliable. Tips Bands widen automatically in chaotic periods and tighten when one regime dominates. Combine with a volume filter or a higher-time-frame trend to reduce whipsaws. If you already run an LGMM in Python or Matlab, paste its component parameters for a perfect match between your back-test and the TradingView plot. Works on all markets and time-frames, provided you have at least five times the Training window’s bars in history. Happy trading!
Pine Script® Indikator
von vsov
Silver Bullet 5 minutes Box - By KaVeHThis indicator plots high-low range boxes based on selected intraday time windows on the 5-minute chart. It's inspired by the "Silver Bullet" trading concept, highlighting key liquidity grabs and volatility pockets at predefined times. It helps traders visually identify potential smart money trading windows during the New York session and other time anchors. ⚠️ This script only works on the 5-minute chart. 📦 Main Features: ⏰ Customizable Time Boxes: Define up to 4 separate time windows per day: 3:00 AM – 3:05 AM (New York time) (Box 1) 10:00 AM – 10:05 AM (New York time) (Box 2) 2:00 PM – 2:05 PM (New York time) (Box 3) 8:00 PM – 8:05 PM (New York time) (Box 4) 🎨 Color and Visibility Control: Each box can be independently toggled and colored for visual distinction. 🕔 New York Time Based: All timestamps are automatically adjusted to New York Time, aligning with institutional market behavior. 📉 Post-Box Projection: After each time window closes, a box extends forward 6 hours (72 bars on a 5-minute chart) to highlight the range. 💡 Use Case: These boxes are best used to: Detect liquidity sweeps. Mark potential entry or exit zones. Track price behavior after specific time-based events. For example, the 10 AM box is often used to identify setups just after the NYSE open and into the first hour of volatility. ⚠️ TradingView Compliance Notes: This script is original and does not replicate or resell premium/paid indicators. All logic is coded from scratch by kaveh_mirmousavi, using public concepts from ICT/Smart Money Trading. Fully complies with the Mozilla Public License 2.0. Does not include financial advice or signals — for educational use only. ✅ How to Use: Apply to a 5-minute chart. Adjust the desired time boxes in the input panel. Watch for price action within and after the boxes. Enjoy and feel free to share feedback or ideas for improvement!
Pine Script® Indikator
von UnknownUnicorn3205499
Harmony in Havoc - The Entropy of VoVix Harmony in Havoc – The Entropy of VoVix There are moments in the market when chaos and order are not opposites, but partners in a dance. Harmony in Havoc is not just an indicator—it’s a window into that dance. Most tools try to tame the market by smoothing it, boxing it in, or chasing after what’s already happened. This script does the opposite: it listens for the music beneath the noise, the rare moments when volatility and unpredictability align, and the market’s next movement is about to begin. What is Harmony in Havoc? VoVix Spike: The pulse of volatility-of-volatility. Not just how much the market is moving, but how violently its own heartbeat is changing. Entropy: A real-time measure of surprise. When entropy is high, the market is not just moving—it’s breaking its own patterns, rewriting its own rules. Progression Bar & Status: The yellow bar is your visual gauge of tension. As it fills, the market is winding up. Wait: The world is calm. Get ready!: The storm is building. Take Action!!: The probability of a regime eruption is at its peak. Yellow Background: When the background glows, the market is at its most unstable—this is not a buy or sell signal, but a quant alert. How does it work? Every tick, Harmony in Havoc measures the distance between the market’s current volatility and its own unpredictability. When the VoVix spike approaches or exceeds the entropy threshold, the system knows: “This is the moment when the improbable becomes possible.” Why is this different? It doesn’t tell you what to do. It doesn’t chase price. It doesn’t care about trends, bands, or the past. Instead, it gives you a quantitative sense of anticipation—a way to see when the market is most likely to break from its own history, and when the edge is at its sharpest. How to use it: Watch for the yellow background and “Take Action!!” status. Use it as a regime filter, a volatility dashboard, or a warning system for your own strategies. Tune the inputs for your asset and timeframe—make it your own. Inputs—explained for you: VoVix Fast/Slow ATR & Stdev: Control how sensitive the system is to volatility shocks. Lower = more signals, higher = only the rarest events. Entropy Window & Bins: Control how “surprised” the entropy engine is by current volatility. Shorter window = more responsive, more bins = finer detail. Show/Hide Controls: Toggle the VoVix spike, entropy line, and their glows to customize your visual experience. Bottom line: This is not a buy or sell script. This is a quant regime detector for those who want to feel the market’s tension—to sense when harmony and havoc are about to collide. Disclaimer: Trading is risky. This script is for research and informational purposes only, not financial advice. Backtest, paper trade, and know your risk before going live. Past performance is not a guarantee of future results. *I've only tested this on 1 and 5 min frames. Use with discipline. Trade your edge. — Dskyz, for DAFE Trading Systems 3 days ago Release Notes * Now mobile friendly. I've added a toggle to switch the dashboard on/off, and added a mobile information line that shows the same information on the dashboard. This is to allow the script to stay visually in balance and this also has a toggle. * Background color added that coresponds with Buy or Sell areas.
Pine Script® Indikator
von DskyzInvestments
Anomaly DetectorPrice Anomaly Detector This is a script designed to identify unusual price movements. By analyzing deviations from typical price behavior, this tool helps traders spot potential trading opportunities and manage risks effectively. --- Features - Anomaly Detection: Flags price points that significantly deviate from the average. - Visual Indicators: Highlights anomalies with background colors and cross markers. - Customizable Settings: Adjust sensitivity and window size to match your trading strategy. - Real-Time Analysis: Continuously updates anomaly signals as new data is received. --- Usage After adding the indicator to your chart: 1. View Anomalies: Red backgrounds and cross markers indicate detected anomalies. 2. Adjust Settings: Modify the `StdDev Threshold` and `Window Length` to change detection sensitivity. 3. Interpret Signals: - Red Background: Anomaly detected on that bar. - Red Cross: Specific point of anomaly. --- Inputs - StdDev Threshold: Higher values reduce anomaly sensitivity. Default: 2.0. - Window Length: Larger windows smooth data, reducing false positives. Default: 20. --- Limitations - Approximation Method: Uses a simple method to detect anomalies, which may not capture all types of unusual price movements. - Performance: Extremely large window sizes may impact script performance. - Segment Detection: Does not group consecutive anomalies into segments. --- Disclaimer : This tool is for educational purposes only. Trading involves risk, and you should perform your own analysis before making decisions. The author is not liable for any losses incurred.
Pine Script® Indikator
von chauduyphanvu
LIT - TimingIntroduction This Script displays the Asia Session Range, the London Open Inducement Window, the NY Open Inducement Window, the Previous Week's high and low, the Previous Day's highs and lows, and the Day Open price in the cleanest way possible. Description The Indicator is based on UTC -7 timing but displays the Session Boxes automatically correct at your chart so you do not have to adjust any timings based on your Time Zone and don't have to do any calculations based on your UTC. It is already perfect. You will see on default settings the purple Asia Box and 2 grey boxes, the first one is for the London Open Inducement Window (1 hour) and the second grey box is for the NY Open Inducement Window (also 1 hour) Asia Range comes with default settings with the Asia Range high, low, and midline, you can remove these 3 lines in the settings "style" and untick the "Lines" box, that way you only will have the boxes displayed. Special Feature Most Timing-based Indicators have "bugged" boxes or don't show clean boxes at all and don't adjust at daylight savings times, we made sure that everything automatically gets adjusted so you don't have to! So the timings will always display at the correct time regarding the daylight savings times. Combining Timing with Liquidity Zones the right way and in a clear, clean, and simple format. Different than others this script also shows the "true" Asia range as it respects the "day open gap" which affects the Asia range in other scripts and it also covers the full 8 hours of Asia Session. Additions You can add in the settings menu the last week's high and low, the previous day's high and low, and also the day's open price by ticking the boxes in the settings menu All colors of the boxes are fully adjustable and customizable for your personal preferences. Same for the previous weeks and day highs and lows. Just go to "Style" and you can adjust the Line types or colors to your preferred choice. Recommended Use The most beautiful display is on the M5 Timeframe as you have a clear overview of all sessions without losing the intraday view. You can also use it on the M1 for more details or the M15 for the bigger picture. The Template can hide on higher time frames starting from the H1 to not flood your chart with boxes. How to use the Asia Session Range Box Use the Asia Range Box as your intraday Guide, keep in mind that a Breakout of Asia high or low induces Liquidity and a common price behavior is a reversal after the fake breakout of that range. How to use the London Open and NY Open Inducement Windows Both grey boxes highlight the Open of either London Open or NY Open and you should keep an eye out for potential Liquditiy Graps or Mitigations during that times as this is when they introduce major Liquidity for the regarding Session. How to use the Asia high, low and midline and day open price After Asia Range got taken out in one direction, often price comes back to those levels to mitigate or bounce off, so you can imagine those zones as support and resistance on some occasions, recommended in combination with Imbalances. How to use the previous day and week's highs and lows Once added in the settings, you can display those price levels, you can use them either as Liquidity Targets or as Inducement Levels once they are taken out. Enjoy!
Pine Script® Indikator
von Reimfx
35
Candlestick Pattern Criteria and Analysis Indicator█  OVERVIEW Define, then locate the presence of a candle that fits a specific criteria. Run a basic calculation on what happens after such a candle occurs. Here, I’m not giving you an edge, but I’m giving you a clear way to find one. IMPORTANT NOTE: PLEASE READ: THE INDICATOR WILL ALWAYS INITIALLY LOAD WITH A RUNTIME ERROR. WHEN INITIALLY LOADED THERE NO CRITERIA SELECTED. If you do not select a criteria or run a search for a criteria that doesn’t exist, you will get a runtime error. If you want to force the chart to load anyway, enable the debug panel at the bottom of the settings menu. Who this is for: - People who want to engage in TradingView for tedious and challenging data analysis related to candlestick measurement and occurrence rate and signal bar relationships with subsequent bars. People who don’t know but want to figure out what a strong bullish bar or a strong bearish bar is. Who this is not for: - People who want to be told by an indicator what is good or bad or buy or sell. Also, not for people that don’t have any clear idea on what they think is a strong bullish bar or a strong bearish bar and aren’t willing to put in the work. Recommendation: Use on the candle resolution that accurately reflects your typical holding period. If you typically hold a trade for 3 weeks, use 3W candles. If you hold a trade for 3 minutes, use 3m candles. Tldr; Read the tool tips and everything above this line. Let me know any issues that arise or questions you have. █  CONCEPTS Many trading styles indicate that a certain candle construct implies a bearish or bullish future for price. That said, it is also common to add to that idea that the context matters. Of course, this is how you end up with all manner of candlestick patterns accounting for thousands of pages of literature. No matter the context though, we can distill a discretionary trader's decision to take a trade based on one very basic premise: “A trader decides to take a trade on the basis of the rightmost candle's construction and what he/she believes that candle construct implies about the future price.” This indicator vets that trader’s theory in the most basic way possible. It finds the instances of any candle construction and takes a look at what happens on the next bar. This current bar is our “Signal Bar.” █  GUIDE I said that we vet the theory in the most basic way possible. But, in truth, this indicator is very complex as a result of there being thousands of ways to define a ‘strong’ candle. And you get to define things on a very granular level with this indicator. Features: 1. Candle Highlighting When the user’s criteria is met, the candle is highlighted on the chart. The following candle is highlighted based on whether it breaks out, breaks down, or is an inside bar. 2. User-Defined Criteria Criteria that you define include: Candle Type: Bull bars, Bear bars, or both Candle Attributes Average Size based on Standard Deviation or Average of all potential bars in price history Search within a specific price range Search within a specific time range Clarify time range using defined sessions and with or without weekends 3. Strike Lines on Candle Often you want to know how price reacts when it gets back to a certain candle. Also it might be true that candle types cluster in a price region. This can be identified visually by adding lines that extend right on candles that fit the criteria. 4. User-Defined Context Labeled “Alternative Criteria,” this facet of the script allows the user to take the context provided from another indicator and import it into the indicator to use as a overriding criteria. To account for the fact that the external indicator must be imported as a float value, true (criteria of external indicator is met) must be imported as 1 and false (criteria of external indicator is not met) as 0. Basically a binary Boolean. This can be used to create context, such as in the case of a traditional fractal, or can be used to pair with other signals. If you know how to code in Pinescript, you can save a copy and simply add your own code to the section indicated in the code and set your bull and bear variables accordingly and the code should compile just fine with no further editing needed. Included with the script to maximize out-of-the-box functionality, there is preloaded as alternative criteria a code snippet. The criteria is met on the bull side when the current candle close breaks out above the prior candle high. The bear criteria is met when the close breaks below the prior candle. When Alternate Criteria is run by itself, this is the only criteria set and bars are highlighted when it is true. You can qualify these candles by adding additional attributes that you think would fit well. Using Alternative Criteria, you are essentially setting a filter for the rest of the criteria. 5. Extensive Read Out in the Data Window (right side bar pop out window). As you can see in the thumbnail, there is pasted a copy of the Data Window Dialogue. I am doubtful I can get the thumbnail to load up perfectly aligned. Its hard to get all these data points in here. It may be better suited for a table at this point. Let me know what you think. The primary, but not exclusive, purpose of what is in the Data Window is to talk about how often your criteria happens and what happens on the next bar. There are a lot of pieces to this. Red = Values pertaining to the size of the current bar only Blue = Values pertaining or related to the total number of signals Green = Values pertaining to the signal bars themselves, including their measurements Purple = Values pertaining to bullish bars that happen after the signal bar Fuchsia = Values pertaining to bearish bars that happen after the signal bar Lime = Last four rows which are your percentage occurrence vs total signals percentages The best way I can explain how to understand parts you don’t understand otherwise in the data window is search the title of the row in the code using ‘ctrl+f’ and look at it and see if it makes more sense. █ [b}Available Candle Attributes Candle attributes can be used in any combination. They include: [*}Bodies [*}High/Low Range [*}Upper Wick [*}Lower Wick [*}Average Size [*}Alternative Criteria Criteria will evaluate each attribute independently. If none is set for a particular attribute it is bypassed. Criteria Quantity can be in Ticks, Points, or Percentage. For percentage keep in mind if using anything involving the candle range will not work well with percentage. Criteria Operators are “Greater Than,” “Less Than,” and “Threshold.” Threshold means within a range of two numbers. █ Problems with this methodology and opportunities for future development: #1 This kind of work is hard. If you know what you’re doing you might be able to find success changing out the inputs for loops and logging results in arrays or matrices, but to manually go through and test various criteria is a lot of work. However, it is rewarding. At the time of publication in early Oct 2022, you will quickly find that you get MUCH more follow through on bear bars than bull bars. That should be obvious because we’re in the middle of a bear market, but you can still work with the parameters and contextual inputs to determine what maximizes your probability. I’ve found configurations that yield 70% probability across the full series of bars. That’s an edge. That means that 70% of the time, when this criteria is met, the next bar puts you in profit. #2 The script is VERY heavy. Takes an eternity to load. But, give it a break, it’s doing a heck of a lot! There is 10 unique arrays in here and a loop that is a bit heavy but gives us the debug window. #3 If you don’t have a clear idea its hard to know where to start. There are a lot of levers to pull on in this script. Knowing which ones are useful and meaningful is very challenging. Combine that with long load times… its not great. #4 Your brain is the only thing that can optimize your results because the criteria come from your mind. Machine learning would be much more useful here, but for now, you are the machine. Learn. #5 You can’t save your settings. So, when you find a good combo, you’ll have to write it down elsewhere for future reference. It would be nice if we could save templates on custom indicators like we can on some of the built in drawing tools, but I’ve had no success in that. So, I recommend screenshotting your settings and saving them in Notion.so or some other solid record keeping database. Then you can go back and retrieve those settings. #6 no way to export these results into conditions that can be copy/pasted into another script. Copy/Paste of labels or tables would be the best feature ever at this point. Because you could take the criteria and put it in a label, copy it and drop it into another strategy script or something. But… men can dream. █ Opportunities to PineCoders Learn: 1. In this script I’m importing libraries, showing some of my libraries functionality. Hopefully that gives you some ideas on how to use them too. The price displacement library (which I love!) Creative and conventional ways of using debug() how to display arrays and matrices on charts I didn’t call in the library that holds the backtesting function. But, also demonstrating, you can always pull the library up and just copy/paste the function out of there and into your script. That’s fine to do a lot of the time. 2. I am using REALLY complicated logic in this script (at least for me). I included extensive descriptions of this ? : logic in the text of the script. I also did my best to bracket () my logic groups to demonstrate how they fit together, both for you and my future self. 3. The breakout, built-in, “alternative criteria” is actually a small bit of genius built in there if you want to take the time to understand that block of code and think about some of the larger implications of the method deployed. As always, a big thank you to TradingView and the Pinescript community, the Pinescript pros who have mentored me, and all of you who I am privileged to help in their Pinescripting journey. "Those who stay will become champions" - Bo Schembechler
Pine Script® Indikator
von kurtsmock
6
Debug_Window_LibraryLibrary "Debug_Window_Library" Provides a framework for logging debug information to a window on the chart. consoleWrite(txt, maxLines) Adds a line of text to the debug window. The text is rolled off the bottom of the window as it fills up.   Parameters:      txt : - this is the text to be appended to the window      maxLines : - this is the size of the window in lines.   Returns: nothing The example above shows the close value for the last 10 bars. Here's the code. //@version=5 indicator("Debug Library test Script", overlay=true) import sp2432/Debug_Window_Library/1 as dbg // add some text to the debug window dbg .consoleWrite( str .tostring(close), 10)
Pine Script® Bibliothek
von sp2432
1
`security()` revisited [PineCoders]NOTE The non-repainting technique in this publication that relies on bar states is now deprecated, as we have identified inconsistencies that undermine its credibility as a universal solution. The outputs that use the technique are still available for reference in this publication. However, we do not endorse its usage. See this publication for more information about the current best practices for requesting HTF data and why they work. █  OVERVIEW This script presents a new function to help coders use security() in both repainting and non-repainting modes. We revisit this often misunderstood and misused function, and explain its behavior in different contexts, in the hope of dispelling some of the coder lure surrounding it. The function is incredibly powerful, yet misused, it can become a dangerous WMD and an instrument of deception, for both coders and traders. We will discuss:  • How to use our new `f_security()` function.  • The behavior of Pine code and security() on the three very different types of bars that make up any chart.  • Why what you see on a chart is a simulation, and should be taken with a grain of salt.  • Why we are presenting a new version of a function handling security() calls.  • Other topics of interest to coders using higher timeframe (HTF) data. █  WARNING We have tried to deliver a function that is simple to use and will, in non-repainting mode, produce reliable results for both experienced and novice coders. If you are a novice coder, stick to our recommendations to avoid getting into trouble, and DO NOT change our `f_security()` function when using it. Use `false` as the function's last argument and refrain from using your script at smaller timeframes than the chart's. To call our function to fetch a non-repainting value of close from the 1D timeframe, use: f_security(_sym, _res, _src, _rep) => security(_sym, _res, _src ) previousDayClose = f_security(syminfo.tickerid, "D", close, false) If that's all you're interested in, you are done. If you choose to ignore our recommendation and use the function in repainting mode by changing the `false` in there for `true`, we sincerely hope you read the rest of our ramblings before you do so, to understand the consequences of your choice. Let's now have a look at what security() is showing you. There is a lot to cover, so buckle up! But before we dig in, one last thing. What is a chart? A chart is a graphic representation of events that occur in markets. As any representation, it is not reality, but rather a model of reality. As Scott Page eloquently states in The Model Thinker : "All models are wrong; many are useful". Having in mind that both chart bars and plots on our charts are imperfect and incomplete renderings of what actually occurred in realtime markets puts us coders in a place from where we can better understand the nature of, and the causes underlying the inevitable compromises necessary to build the data series our code uses, and print chart bars. Traders or coders complaining that charts do not reflect reality act like someone who would complain that the word "dog" is not a real dog. Let's recognize that we are dealing with models here, and try to understand them the best we can. Sure, models can be improved; TradingView is constantly improving the quality of the information displayed on charts, but charts nevertheless remain mere translations. Plots of data fetched through security() being modelized renderings of what occurs at higher timeframes, coders will build more useful and reliable tools for both themselves and traders if they endeavor to perfect their understanding of the abstractions they are working with. We hope this publication helps you in this pursuit. █  FEATURES This script's "Inputs" tab has four settings:  • Repaint : Determines whether the functions will use their repainting or non-repainting mode.   Note that the setting will not affect the behavior of the yellow plot, as it always repaints.  • Source : The source fetched by the security() calls.  • Timeframe : The timeframe used for the security() calls. If it is lower than the chart's timeframe, a warning appears.  • Show timeframe reminder : Displays a reminder of the timeframe after the last bar. █  THE CHART The chart shows two different pieces of information and we want to discuss other topics in this section, so we will be covering:  A — The type of chart bars we are looking at, indicated by the colored band at the top.  B — The plots resulting of calling security() with the close price in different ways.  C — Points of interest on the chart. A — Chart bars The colored band at the top shows the three types of bars that any chart on a live market will print. It is critical for coders to understand the important distinctions between each type of bar:  1 — Gray : Historical bars, which are bars that were already closed when the script was run on them.  2 — Red : Elapsed realtime bars, i.e., realtime bars that have run their course and closed.    The state of script calculations showing on those bars is that of the last time they were made, when the realtime bar closed.  3 — Green : The realtime bar. Only the rightmost bar on the chart can be the realtime bar at any given time, and only when the chart's market is active. Refer to the Pine User Manual's Execution model page for a more detailed explanation of these types of bars. B — Plots The chart shows the result of letting our 5sec chart run for a few minutes with the following settings: "Repaint" = "On" (the default is "Off"), "Source" = `close` and "Timeframe" = 1min. The five lines plotted are the following. They have progressively thinner widths:  1 — Yellow : A normal, repainting security() call.  2 — Silver : Our recommended security() function.  3 — Fuchsia : Our recommended way of achieving the same result as our security() function, for cases when the source used is a function returning a tuple.  4 — White : The method we previously recommended in our MTF Selection Framework , which uses two distinct security() calls.  5 — Black : A lame attempt at fooling traders that MUST be avoided. All lines except the first one in yellow will vary depending on the "Repaint" setting in the script's inputs. The first plot does not change because, contrary to all other plots, it contains no conditional code to adapt to repainting/no-repainting modes; it is a simple security() call showing its default behavior. C — Points of interest on the chart Historical bars do not show actual repainting behavior To appreciate what a repainting security()  call will plot in realtime, one must look at the realtime bar and at elapsed realtime bars, the bars where the top line is green or red on the chart at the top of this page. There you can see how the plots go up and down, following the close value of each successive chart bar making up a single bar of the higher timeframe. You would see the same behavior in "Replay" mode. In the realtime bar, the movement of repainting plots will vary with the source you are fetching: open will not move after a new timeframe opens, low and high will change when a new low or high are found, close will follow the last feed update. If you are fetching a value calculated by a function, it may also change on each update. Now notice how different the plots are on historical bars. There, the plot shows the close of the previously completed timeframe for the whole duration of the current timeframe, until on its last bar the price updates to the current timeframe's close when it is confirmed (if the timeframe's last bar is missing, the plot will only update on the next timeframe's first bar). That last bar is the only one showing where the plot would end if that timeframe's bars had elapsed in realtime. If one doesn't understand this, one cannot properly visualize how his script will calculate in realtime when using repainting. Additionally, as published scripts typically show charts where the script has only run on historical bars, they are, in fact, misleading traders who will naturally assume the script will behave the same way on realtime bars. Non-repainting plots are more accurate on historical bars Now consider this chart, where we are using the same settings as on the chart used to publish this script, except that we have turned "Repainting" off this time: The yellow line here is our reference, repainting line, so although repainting is turned off, it is still repainting, as expected. Because repainting is now off, however, plots on historical bars show the previous timeframe's close until the first bar of a new timeframe, at which point the plot updates. This correctly reflects the behavior of the script in the realtime bar, where because we are offsetting the series by one, we are always showing the previously calculated—and thus confirmed—higher timeframe value. This means that in realtime, we will only get the previous timeframe's values one bar after the timeframe's last bar has elapsed, at the open of the first bar of a new timeframe. Historical and elapsed realtime bars will not actually show this nuance because they reflect the state of calculations made on their close , but we can see the plot update on that bar nonetheless. ► This more accurate representation on historical bars of what will happen in the realtime bar is one of the two key reasons why using non-repainting data is preferable.    The other is that in realtime, your script will be using more reliable data and behave more consistently. Misleading plots Valiant attempts by coders to show non-repainting, higher timeframe data updating earlier than on our chart are futile. If updates occur one bar earlier because coders use the repainting version of the function, then so be it, but they must then also accept that their historical bars are not displaying information that is as accurate. Not informing script users of this is to mislead them. Coders should also be aware that if they choose to use repainting data in realtime, they are sacrificing reliability to speed and may be running a strategy that behaves very differently from the one they backtested, thus invalidating their tests. When, however, coders make what are supposed to be non-repainting plots plot artificially early on historical bars, as in examples "c4" and "c5" of our script, they would want us to believe they have achieved the miracle of time travel. Our understanding of the current state of science dictates that for now, this is impossible. Using such techniques in scripts is plainly misleading, and public scripts using them will be moderated. We are coding trading tools here—not video games. Elementary ethics prescribe that we should not mislead traders, even if it means not being able to show sexy plots. As the great Feynman said: You should not fool the layman when you're talking as a scientist. You can readily appreciate the fantasy plot of "c4", the thinnest line in black, by comparing its supposedly non-repainting behavior between historical bars and realtime bars. After updating—by miracle—as early as the wide yellow line that is repainting, it suddenly moves in a more realistic place when the script is running in realtime, in synch with our non-repainting lines. The "c5" version does not plot on the chart, but it displays in the Data Window. It is even worse than "c4" in that it also updates magically early on historical bars, but goes on to evaluate like the repainting yellow line in realtime, except one bar late. Data Window The Data Window shows the values of the chart's plots, then the values of both the inside and outside offsets used in our calculations, so you can see them change bar by bar. Notice their differences between historical and elapsed realtime bars, and the realtime bar itself. If you do not know about the Data Window, have a look at this essential tool for Pine coders in the Pine User Manual's page on Debugging . The conditional expressions used to calculate the offsets may seem tortuous but their objective is quite simple. When repainting is on, we use this form, so with no offset on all bars: security(ticker, i_timeframe, i_source ) // which is equivalent to: security(ticker, i_timeframe, i_source) When repainting is off, we use two different and inverted offsets on historical bars and the realtime bar: // Historical bars: security(ticker, i_timeframe, i_source ) // Realtime bar (and thus, elapsed realtime bars): security(ticker, i_timeframe, i_source ) The offsets in the first line show how we prevent repainting on historical bars without the need for the `lookahead` parameter. We use the value of the function call on the chart's previous bar. Since values between the repainting and non-repainting versions only differ on the timeframe's last bar, we can use the previous value so that the update only occurs on the timeframe's first bar, as it will in realtime when not repainting. In the realtime bar, we use the second call, where the offsets are inverted. This is because if we used the first call in realtime, we would be fetching the value of the repainting function on the previous bar, so the close of the last bar. What we want, instead, is the data from the previous, higher timeframe bar , which has elapsed and is confirmed, and thus will not change throughout realtime bars, except on the first constituent chart bar belonging to a new higher timeframe. After the offsets, the Data Window shows values for the `barstate.*` variables we use in our calculations. █  NOTES Why are we revisiting security()  ? For four reasons:  1 — We were seeing coders misuse our `f_secureSecurity()` function presented in How to avoid repainting when using security() .    Some novice coders were modifying the offset used with the history-referencing operator in the function, making it zero instead of one,    which to our horror, caused look-ahead bias when used with `lookahead = barmerge.lookahead_on`.    We wanted to present a safer function which avoids introducing the dreaded "lookahead" in the scripts of unsuspecting coders.  2 — The popularity of security() in screener-type scripts where coders need to use the full 40 calls allowed per script made us want to propose    a solid method of allowing coders to offer a repainting/no-repainting choice to their script users with only one security() call.  3 — We wanted to explain why some alternatives we see circulating are inadequate and produce misleading behavior.  4 — Our previous publication on security() focused on how to avoid repainting, yet many other considerations worthy of attention are not related to repainting. Handling tuples When sending function calls that return tuples with security() , our `f_security()` function will not work because Pine does not allow us to use the history-referencing operator with tuple return values. The solution is to integrate the inside offset to your function's arguments, use it to offset the results the function is returning, and then add the outside offset in a reassignment of the tuple variables, after security() returns its values to the script, as we do in our "c2" example. Does it repaint? We're pretty sure Wilder was not asked very often if RSI repainted. Why? Because it wasn't in fashion—and largely unnecessary—to ask that sort of question in the 80's. Many traders back then used daily charts only, and indicator values were calculated at the day's close, so everybody knew what they were getting. Additionally, indicator values were calculated by generally reputable outfits or traders themselves, so data was pretty reliable. Today, almost anybody can write a simple indicator, and the programming languages used to write them are complex enough for some coders lacking the caution, know-how or ethics of the best professional coders, to get in over their heads and produce code that does not work the way they think it does. As we hope to have clearly demonstrated, traders do have legitimate cause to ask if MTF scripts repaint or not when authors do not specify it in their script's description. ► We recommend that authors always use our `f_security()` with `false` as the last argument to avoid repainting when fetching data dependent on OHLCV information. This is the only way to obtain reliable HTF data. If you want to offer users a choice, make non-repainting mode the default, so that if users choose repainting, it will be their responsibility. Non-repainting security() calls are also the only way for scripts to show historical behavior that matches the script's realtime behavior, so you are not misleading traders. Additionally, non-repainting HTF data is the only way that non-repainting alerts can be configured on MTF scripts, as users of MTF scripts cannot prevent their alerts from repainting by simply configuring them to trigger on the bar's close. Data feeds A chart at one timeframe is made up of multiple feeds that mesh seamlessly to form one chart. Historical bars can use one feed, and the realtime bar another, which brokers/exchanges can sometimes update retroactively so that elapsed realtime bars will reappear with very slight modifications when the browser's tab is refreshed. Intraday and daily chart prices also very often originate from different feeds supplied by brokers/exchanges. That is why security() calls at higher timeframes may be using a completely different feed than the chart, and explains why the daily high value, for example, can vary between timeframes. Volume information can also vary considerably between intraday and daily feeds in markets like stocks, because more volume information becomes available at the end of day. It is thus expected behavior—and not a bug—to see data variations between timeframes. Another point to keep in mind concerning feeds it that when you are using a repainting security() plot in realtime, you will sometimes see discrepancies between its plot and the realtime bars. An artefact revealing these inconsistencies can be seen when security() plots sometimes skip a realtime chart bar during periods of high market activity. This occurs because of races between the chart and the security() feeds, which are being monitored by independent, concurrent processes. A blue arrow on the chart indicates such an occurrence. This is another cause of repainting, where realtime bar-building logic can produce different outcomes on one closing price. It is also another argument supporting our recommendation to use non-repainting data. Alternatives There is an alternative to using security() in some conditions. If all you need are OHLC prices of a higher timeframe, you can use a technique like the one Duyck demonstrates in his security free MTF example - JD script. It has the great advantage of displaying actual repainting values on historical bars, which mimic the code's behavior in the realtime bar—or at least on elapsed realtime bars, contrary to a repainting security() plot. It has the disadvantage of using the current chart's TF data feed prices, whereas higher timeframe data feeds may contain different and more reliable prices when they are compiled at the end of the day. In its current state, it also does not allow for a repainting/no-repainting choice. When `lookahead` is useful When retrieving non-price data, or in special cases, for experiments, it can be useful to use `lookahead`. One example is our Backtesting on Non-Standard Charts: Caution! script where we are fetching prices of standard chart bars from non-standard charts. Warning users Normal use of security() dictates that it only be used at timeframes equal to or higher than the chart's. To prevent users from inadvertently using your script in contexts where it will not produce expected behavior, it is good practice to warn them when their chart is on a higher timeframe than the one in the script's "Timeframe" field. Our `f_tfReminderAndErrorCheck()` function in this script does that. It can also print a reminder of the higher timeframe. It uses one security() call. Intrabar timeframes security() is not supported by TradingView when used with timeframes lower than the chart's. While it is still possible to use security() at intrabar timeframes, it then behaves differently. If no care is taken to send a function specifically written to handle the successive intrabars, security() will return the value of the last intrabar in the chart's timeframe, so the last 1H bar in the current 1D bar, if called at "60" from a "D" chart timeframe. If you are an advanced coder, see our FAQ entry on the techniques involved in processing intrabar timeframes. Using intrabar timeframes comes with important limitations, which you must understand and explain to traders if you choose to make scripts using the technique available to others. Special care should also be taken to thoroughly test this type of script. Novice coders should refrain from getting involved in this. █  TERMINOLOGY Timeframe Timeframe , interval and resolution are all being used to name the concept of timeframe. We have, in the past, used "timeframe" and "resolution" more or less interchangeably. Recently, members from the Pine and PineCoders team have decided to settle on "timeframe", so from hereon we will be sticking to that term. Multi-timeframe (MTF) Some coders use "multi-timeframe" or "MTF" to name what are in fact "multi-period" calculations, as when they use MAs of progressively longer periods. We consider that a misleading use of "multi-timeframe", which should be reserved for code using calculations actually made from another timeframe's context and using security() , safe for scripts like Duyck's one mentioned earlier, or TradingView's Relative  Volume  at  Time , which use a user-selected timeframe as an anchor to reset calculations. Calculations made at the chart's timeframe by varying the period of MAs or other rolling window calculations should be called "multi-period", and "MTF-anchored" could be used for scripts that reset calculations on timeframe boundaries. Colophon Our script was written using the PineCoders Coding Conventions for Pine . The description was formatted using the techniques explained in the How We Write and Format Script Descriptions PineCoders publication. Snippets were lifted from our MTF Selection Framework , then massaged to create the `f_tfReminderAndErrorCheck()` function. █  THANKS Thanks to apozdnyakov for his help with the innards of security() . Thanks to bmistiaen for proofreading our description. Look first. Then leap.
Pine Script® Indikator
von PineCoders
61
Institutional Session VWAP Bands (Zeiierman)█ Overview Institutional Session VWAP Bands (Zeiierman) plots a clean, session-aware VWAP that restarts at the “True Close” (end of the first trading hour) for each session you enable (Sydney, Tokyo, London, New York). From that anchor, the script computes a classic volume-weighted average price plus optional standard-deviation bands to frame session fair value and dispersion. By aligning VWAP to when institutional flows settle (the first hour), you get a reference that matches real execution behavior, yielding more credible pullbacks, retests, and mean-reversion reads inside each session. █ How It Works ⚪ Session Detection You choose the sessions (on/off), their UTC-aligned time windows, and colors. The script detects when each session is active on your chart timeframe. ⚪ True-Close Anchoring At session open the indicator waits. When the first hour completes, it flips the anchor on and starts a fresh VWAP for that session, mirroring how many desks treat the first hour as the real close for the prior day’s positioning. ⚪ VWAP Core From the true-close anchor, VWAP is calculated in the standard way: cumulative (price × volume) / cumulative volume using your chosen price source (default hlc3). ⚪ VWAP Bands (σ) Upper/Lower bands are built using a running standard deviation of the price source since the anchor. You control the σ multiplier and line width, and you can optionally fill between the bands. █ Why Sessions + True-Close Anchoring ⚪ Institutional Timing Matters A new anchor at the first-hour close reflects where real flows have settled, giving you a session fair-value line that aligns with how many funds evaluate prices intraday. ⚪ Cleaner Session Reads Because VWAP and σ-bands restart each session, your retests, squeezes, and mean-reversion signals are based on today’s order-flow context, not yesterday’s inertia. Result: a session-true fair-value with dispersion bands that stay close to the action, improving the quality of pullback entries and risk framing. █ How to Use ⚪ Session Fair-Value Guide Treat VWAP as the magnet for intraday value. Impulsive moves away from VWAP that fold back often present retest opportunities. ⚪ σ-Band Reversion & Breaks Reversion: Tests beyond the upper/lower band that snap back inside can flag exhaustion. Trend: Price riding the VWAP band in a strong trend ⚪ Session Handoffs When one session hands to the next, watch how price behaves around the new session’s VWAP Bands after its anchor triggers. Continuation through the new VWAP vs. rejection often sets the tone. █ Settings UTC: Choose the timezone used to evaluate session windows (e.g., UTC+2). Sessions (Sydney, Tokyo, London, New York): Toggle visibility and define each HHMM-HHMM window. VWAP Price: Source for weighting. Band Multiplier (σ): Standard deviation multiplier. █ Related publications True Close – Institutional Trading Sessions (Zeiierman) ----------------- Disclaimer The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information. All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Pine Script® Indikator
von Zeiierman
13
Low Volatility Breakout in Trend █ OVERVIEW "Low Volatility Breakout in Trend" is a technical analysis tool that identifies periods of low-volatility consolidation within an ongoing trend and signals potential breakouts aligned with the trend's direction. The indicator detects trends using a simple moving average (SMA) of price, identifies consolidation zones based on the size of candle bodies, and displays the percentage change in volume (volume delta) at the breakout moment. █ CONCEPTS The core idea of the indicator is to pinpoint moments where traders can join an ongoing trend by capitalizing on breakouts from consolidation zones, supported by additional information such as volume delta. It provides clear visualizations of trends, consolidation zones, and breakout signals to facilitate trading decisions. Why Use It? * Breakout Identification: The indicator locates low-volatility consolidation zones (measured by the size of individual candle bodies, not the price range of the consolidation) and signals breakouts, enabling traders to join the trend at key moments. * Volume Analysis: Displays the percentage change in volume (delta) relative to its simple moving average, providing insight into market activity rather than acting as a signal filter. * Visual Clarity: Colored trend lines, consolidation boxes (drawn only after the breakout candle closes, not on subsequent candles), and volume delta labels enable quick chart analysis. * Flexibility: Adjustable parameters, such as the volatility window length or SMA period, allow customization for various trading strategies and markets. How It Works * Trend Detection: The indicator calculates a simple moving average (SMA) of price (default: based on the midpoint of high/low) and creates dynamic trend bands, offset by a percentage of the average candle height (band scaling). A price above the upper band signals an uptrend, while a price below the lower band indicates a downtrend. Trend changes occur not when the price crosses the SMA but when it crosses above the upper band or below the lower band (offset by the average candle height multiplied by the scaling factor). * Consolidation Identification: Identifies low-volatility zones when the candle body size is smaller than the average body size over a specified period (default: 20 candles) multiplied by a volatility threshold — the maximum allowable body size as a percentage of the average body (e.g., 2 means the candle body must be less than twice the average body to be considered low-volatility). * Breakout Signals: A breakout occurs when the candle body exceeds the volatility threshold, is larger than the maximum body in the consolidation, and aligns with the trend direction (bullish in an uptrend, bearish in a downtrend). * Visualization: Draws a trend line with a gradient, consolidation boxes (appearing only after the breakout candle closes, marking the consolidation zone), and volume delta labels. Optionally displays breakout signal arrows. * Signals and Alerts: The indicator generates signals for bullish and bearish breakouts, including the volume delta percentage. Alerts are an additional feature that can be enabled for notifications. Settings and Customization * Volatility Window: Length of the period for calculating the average candle body size (default: 20). * Volatility Threshold: Maximum candle body size as a percentage of the average body (default: 2). * Minimum Consolidation Bars: Number of candles required for a consolidation (default: 10). * SMA Length for Trend: Period of the SMA for trend detection (default: 100). * Band Scaling: Offset of trend bands as a percentage of the average candle height (default: 250%), determining the distance from the SMA. * Visualization Options: Enable/disable consolidation boxes (Show Consolidation Boxes, drawn after the breakout candle closes), volume delta labels (Show Volume Delta Labels), and breakout signals (Show Breakout Signals, e.g., triangles). * Colors: Customize colors for the trend line, consolidation boxes, and volume delta labels. █ OTHER SECTIONS Usage Examples * Joining an Uptrend: When the price breaks out of a consolidation in an uptrend with a volume delta of +50%, open a long position; the signal is stronger if the breakout candle surpasses a local high. * Avoiding False Breakouts: Ignore breakout signals with low volume delta (e.g., below 0%) and combine the indicator with other tools (e.g., support/resistance levels or oscillators) to confirm moves in low-activity zones. Notes for Users * On markets that do not provide volume data, the indicator will not display volume delta — disable volume labels and enable breakout signals (e.g., triangles) instead. * Adjust parameters to suit the market's characteristics to minimize noise. * Combine with other tools, such as Fibonacci levels or oscillators, for greater precision.
Pine Script® Indikator
von Uncle_the_shooter
Indicador Millo SMA20-SMA200-AO-RSI M1This indicator is designed for scalping in 1-minute timeframes on crypto pairs, combining trend direction, momentum, and oscillator confirmation. Logic: Trend Filter: Only BUY signals when price is above the SMA200. Only SELL signals when price is below the SMA200. Entry Trigger: BUY: Price crosses above the SMA20. SELL: Price crosses below the SMA20. Confirmation Window: After the price cross, the Awesome Oscillator (AO) must cross the zero line in the same direction within a maximum of N bars (configurable, default = 4). RSI must be > 50 for BUY and < 50 for SELL at the moment AO confirms. Cooldown: A cooldown period (configurable, default = 10 bars) prevents multiple signals of the same type in a short time, reducing noise in sideways markets. Features: Works on any crypto pair and can be used in other markets. Adjustable confirmation window, RSI threshold, and cooldown. Alerts ready for BUY and SELL conditions. Can be converted into a strategy for backtesting with TP/SL. Suggested Use: Pair: BTC/USDT M1 or similar high-liquidity asset. Combine with manual support/resistance or higher timeframe trend analysis. Recommended to confirm entries visually and with additional confluence before trading live.
Pine Script® Indikator
von hernangarcia_78
2
Ichimoku Cloud Signals [sgbpulse] Ichimoku Cloud Signals – Your Advanced Trading Tool Meet Ichimoku Cloud Signals, the enhanced and interactive version of the classic Ichimoku Cloud indicator, designed specifically for TradingView traders seeking precision and flexibility in their trading decisions. This indicator allows you to maximize the Ichimoku's potential by customizing trend criteria, receiving clear visual signals for entering and exiting positions, and getting alerts to keep you informed. Introduction to the Ichimoku Cloud The Ichimoku Cloud, also known as Ichimoku Kinko Hyo, is a comprehensive technical analysis tool developed in Japan. It provides a broad view of the market: trend direction, momentum, and support and resistance levels. "Ichimoku Cloud Signals" takes this power and amplifies it with advanced features. Key Components of the Ichimoku Cloud The indicator displays all five familiar Ichimoku lines, along with the "Cloud" (Kumo): Tenkan-sen (Conversion Line): Calculated as the average of the highest high and lowest low over the past 9 periods. A fast, short-term indicator used as a measure of immediate momentum. Kijun-sen (Base Line): Calculated as the average of the highest high and lowest low over the past 26 periods. A medium-term reference line serving as a significant support/resistance level. Senkou Span A (Leading Span A): The average of the Tenkan-sen and Kijun-sen, shifted 26 periods forward into the future. Senkou Span B (Leading Span B): The average of the highest high and lowest low over the past 52 periods, also shifted 26 periods forward into the future. Kumo (Cloud): The area between Senkou Span A and Senkou Span B. Its color changes: green for an uptrend (when Senkou Span A is above Senkou Span B) and red for a downtrend (when Senkou Span B is above Senkou Span A). The Cloud serves as a dynamic area of support/resistance and a tool for forecasting future trends. Chikou Span (Lagging Span): The current closing price, shifted 26 periods backward into the past. It serves as a powerful trend confirmation tool. How the Ichimoku Cloud Works and How to Interpret It Trend Identification : - Uptrend (Bullish): The price is above the Cloud. The higher the price is above the Cloud, the stronger the trend. - Downtrend (Bearish): The price is below the Cloud. The lower the price is below the Cloud, the stronger the trend. - Range/Consolidation: The price is within the Cloud. This indicates a market without a clear direction or one that is consolidating. Support and Resistance: - The Cloud itself acts as a dynamic area of support and resistance. In an uptrend, the Cloud serves as support. In a downtrend, it serves as resistance. - A thick Cloud indicates stronger support/resistance levels, while a thin Cloud indicates weaker levels. The Cloud as a Predictive Indicator: The uniqueness of the Kumo (Cloud) lies in its ability to be shifted 26 periods forward. This part of the Cloud provides forecasts for future support and resistance levels and even suggests expected trend changes (like a "Kumo Twist" – a change in Cloud color), giving you a planning advantage. Unique Advantages of Ichimoku Cloud Signals: Ichimoku Cloud Signals takes the classic Ichimoku principles and gives you unprecedented control: Focused Trend Selection: Choose whether you want to analyze a bullish (uptrend) or bearish (downtrend) trend. The indicator will focus on the relevant criteria for your selection. Customizable Trend Confirmation Criteria (8 Criteria): The indicator relies on 8 key criteria for clear trend confirmation. You can enable or disable each criterion individually based on your trading strategy and desired risk level. Each criterion plays a vital role in confirming the strength of the trend: - Price position relative to the Cloud (Kumo) (Default: true): Determines the main trend direction and whether it's bullish or bearish. - Price position relative to Kijun-sen (Base Line) (Default: true): Indicates the medium-term trend and acts as a critical equilibrium level. - Price position relative to Tenkan-sen (Conversion Line) (Default: false): Provides quick confirmation of current momentum and short-term market changes. - Tenkan-sen (Conversion Line) / Kijun-sen (Base Line) Crossover (Default: true): A classic signal for momentum change, crucial for identifying entry points. - Current Cloud trend (Kumo) (Default: false): Cloud color confirms the main trend direction in real-time. - Projected Future Cloud trend (Kumo) (Default: true): Indicates an expected future change in the Cloud's trend, providing strong visual insight. - Chikou Span (Lagging Span) position relative to the Cloud (Kumo) (Default: true): Confirms the current trend strength by comparing the price to the Ichimoku 26 periods ago. - Chikou Span (Lagging Span) position relative to the Price (Default: false): Additional confirmation of trend strength, indicating buyer/seller dominance. Full Customization of Ichimoku Parameters: You can change the period lengths for each Ichimoku component, depending on your strategy: - Conversion Line Length (Default: 9) - Base Line Length (Default: 26) - Leading Span Length (Default: 52) - Cloud Lagging Length (Default: 26) - Lagging Span Length (Default: 26) Visual Criteria Table on the Chart: Get immediate and clear feedback! A visual table is placed on the chart, showing in real-time which of the 8 criteria you have defined are met for your chosen trend. Criteria you have enabled will be highlighted with a blue color and a "➤" symbol, while disabled criteria will appear in a subtle gray shade. For each criterion, the table shows its real-time status with a "✔" symbol if the condition is met and an "✘" symbol if it is not met. This powerful visual tool provides a quick assessment, helps with learning, and allows for strategy optimization at the click of a button. Precise Criteria Details in the Data Window: Beyond the visual table, the indicator provides an additional critical layer of detail: for any point on the chart, you can hover over a candle and see in TradingView's Data Window the precise status and values of all eight criteria. For each criterion, you'll see a clear numerical value (1 or 0) indicating whether it's fully met (1) or not met (0). Additionally, you can inspect the exact numerical values of the Ichimoku lines (Tenkan-sen, Kijun-sen, etc.) at that specific moment. This comprehensive data supports in-depth analysis, strategy debugging, and long-term optimization, providing complete transparency regarding every component of the signal. Smart and Customizable Alerts: Ichimoku Cloud Signals provides a powerful alert system to keep you informed of key market movements, so you never miss an opportunity. There are eight unique alerts you can enable in TradingView's alert panel: Uptrend Entry Alert: Triggers when all of your selected criteria for an uptrend are met on a new candle. Uptrend Exit Alert: Triggers when one of your selected uptrend criteria is no longer met, signaling a potential exit point. Downtrend Entry Alert: Triggers when all of your selected criteria for a downtrend are met on a new candle. Downtrend Exit Alert: Triggers when one of your selected downtrend criteria is no longer met, signaling a potential exit point. Bullish Crossover Alert: Triggers when the Conversion Line (Tenkan-sen) crosses above the Base Line (Kijun-sen), a classic signal for an upward momentum shift. Bearish Crossover Alert: Triggers when the Conversion Line (Tenkan-sen) crosses below the Base Line (Kijun-sen), signaling a potential shift to downward momentum. Bullish Cloud Breakout Alert: Triggers when the price closes above the Ichimoku Cloud (Kumo), indicating a strong bullish trend. Bearish Cloud Breakout Alert: Triggers when the price closes below the Ichimoku Cloud (Kumo), indicating a strong bearish trend. Each alert can be independently configured in TradingView's alert panel, allowing you to tailor your notifications to fit your exact trading strategy and risk management preferences. Summary: Ichimoku Cloud Signals is an essential tool for TradingView traders seeking control, clarity, and precision. It combines the power of the classic Ichimoku Cloud indicator with advanced customization capabilities, a convenient visual table, and clear signals, empowering you to make informed trading decisions and stay focused on managing your positions. Important Note: Trading Risk This indicator is intended for educational and informational purposes only and does not constitute investment advice or a recommendation for trading in any form whatsoever. Trading in financial markets involves significant risk of capital loss. It is important to remember that past performance is not indicative of future results. All trading decisions are your sole responsibility. Never trade with money you cannot afford to lose.
Pine Script® Indikator
von sgbpulse
LANZ Strategy 5.0 [Backtest]🔷 LANZ Strategy 5.0 — Rule-Based BUY Logic with Time Filter, Session Limits and Auto SL/TP Execution This is the backtest version of LANZ Strategy 5.0, built as a strategy script to evaluate real performance under fixed intraday conditions. It automatically places BUY and SELL trades based on structured candle confirmation, EMA trend alignment, and session-based filters. The system simulates real-time execution with precise Stop Loss and Take Profit levels. 📌 Built for traders seeking to simulate clean intraday logic with fully automated entries and performance metrics. 🧠 Core Logic & Strategy Conditions ✅ BUY Signal Conditions: Price is above the EMA200 The last 3 candles are bullish (close > open) The signal occurs within the defined session window (NY time) Daily trade limit has not been exceeded If all are true, a BUY order is executed at market, with SL and TP set immediately. 🔻 SELL Signal Conditions (Optional): Exactly inverse to BUY (below EMA + 3 bearish candles). Disabled by default. 🕐 Operational Time Filter (New York Time) You can fully customize your intraday window: Start Time: e.g., 01:15 NY End Time: e.g., 16:00 NY The system evaluates signals only within this range, even across midnight if configured. 🔁 Trade Management System One trade at a time per signal Trades include a Stop Loss (SL) and Take Profit (TP) based on pip distance Trade result is calculated automatically Each signal is shown with a triangle marker (BUY only, by default) 🧪 Backtest Accuracy This version uses: strategy.order() for entries strategy.exit() for SL and TP strategy.close_all() at the configured manual closing time This ensures realistic behavior in the TradingView strategy tester. ⚙️ Flow Summary (Step-by-Step) On every bar, check: Is the time within the operational session? Is the price above the EMA? Are the last 3 candles bullish? If conditions met → A BUY trade is opened: SL = entry – X pips TP = entry + Y pips Trade closes: If SL or TP is hit Or at the configured manual close time (e.g., 16:00 NY) 📊 Settings Overview Timeframe: 1-hour (ideal) SL/TP: Configurable in pips Max trades/day: User-defined (default = 99 = unlimited) Manual close: Adjustable by time Entry type: Market (not limit) Visuals: Plotshape triangle for BUY entry 👨‍💻 Credits: 💡 Developed by: LANZ 🧠 Strategy logic & execution: LANZ ✅ Designed for: Clean backtesting, clarity in execution, and intraday logic simulation
Pine Script® Strategie
von rau_u_lanz
Price Statistical Strategy-Z Score V 1.01 Price Statistical Strategy – Z Score V 1.01 Overview A technical breakdown of the logic and components of the “Price Statistical Strategy – Z Score V 1.01”. This script implements a smoothed Z-Score crossover mechanism applied to the closing price to detect potential statistical deviations from local price mean. The strategy operates solely on price data (close) and includes signal spacing control and momentum-based candle filters. No volume-based or trend-detection components are included. Core Methodology The strategy is built on the statistical concept of Z-Score, which quantifies how far a value (closing price) is from its recent average, normalized by standard deviation. Two moving averages of the raw Z-Score are calculated: a short-term and a long-term smoothed version. The crossover between them generates long entries and exits. Signal Conditions Entry Condition: A long position is opened when the short-term smoothed Z-Score crosses above the long-term smoothed Z-Score, and additional entry conditions are met. Exit Condition: The position is closed when the short-term Z-Score crosses below the long-term Z-Score, provided the exit conditions allow. Signal Gapping: A minimum number of bars (Bars gap between identical signals) must pass between repeated entry or exit signals to reduce noise. Momentum Filter: Entries are prevented during sequences of three or more consecutively bullish candles, and exits are prevented during three or more consecutively bearish candles. Z-Score Function The Z-Score is calculated as: Z = (Close - SMA(Close, N)) / STDEV(Close, N) Where N is the base period selected by the user. Input Parameters Enable Smoothed Z-Score Strategy Enables or disables the Z-Score strategy logic. When disabled, no trades are executed. Z-Score Base Period Defines the number of bars used to calculate the simple moving average and standard deviation for the Z-Score. This value affects how responsive the raw Z-Score is to price changes. Short-Term Smoothing Sets the smoothing window for the short-term Z-Score. Higher values produce smoother short-term signals, reducing sensitivity to short-term volatility. Long-Term Smoothing Sets the smoothing window for the long-term Z-Score, which acts as the reference line in the crossover logic. Bars gap between identical signals Minimum number of bars that must pass before another signal of the same type (entry or exit) is allowed. This helps reduce redundant or overly frequent signals. Trade Visualization Table A table positioned at the bottom-right displays live PnL for open trades: Entry Price Unrealized PnL % Text colors adapt based on whether unrealized profit is positive, negative, or neutral. Technical Notes This strategy uses only close prices — no trend indicators or volume components are applied. All calculations are based on simple moving averages and standard deviation over user-defined windows. Designed as a minimal, isolated Z-Score engine without confirmation filters or multi-factor triggers.
Pine Script® Strategie
von ata_sabanci
Tangent Extrapolation ForecastTangent Extrapolation Forecast This indicator visually projects price direction by drawing a smoothed sequence of tangent lines based on recent price movements. For each bar in a user-defined lookback window, it calculates the slope over a smoothing period and extends the projected price forward. The resulting polyline forecast connect the endpoints of the extrapolations, and is color-coded to reflect directional changes: green for upward moves, red for downward, and gray for flat segments. This tool can assist traders in visualizing short-term momentum and potential trend continuity without introducing artificial future gaps. Inputs: Bars to Use: Number of historical bars used in the forecast. Slope Smoothing Window: The number of bars used to calculate slope for projection. Source: Price input for calculations (default is close). This indicator does not generate buy/sell signals. It is intended as a visual aid to support discretionary analysis.
Pine Script® Indikator
von Tradenometry
FibSync - DynamicFibSupportWhat is this indicator? FibSync – DynamicFibSupport overlays your chart with both static and dynamic Fibonacci retracement levels, making it easy to spot potential areas of support and resistance. Static Fibs: Calculated from the highest and lowest price over a user-defined lookback period. Dynamic Fibs: Calculated from the most recent swing high and swing low, automatically adapting as new swings form. How to use Add the indicator to your chart. Configure the settings: Static Fib Period: Sets the lookback window for static fib levels. Show Dynamic Fibonacci Levels: Toggle dynamic fibs on/off. Dynamic Fib Swing Search Window: How far back to search for valid swing highs/lows. Swing Strength (bars left/right): How many bars define a swing high/low (higher = stronger swing). Interpret the levels: Solid lines are static fibs. Transparent lines are dynamic fibs (if enabled). Colors match standard fib conventions (yellow = 0.236, red = 0.382, blue = 0.618, green = 0.786, gray = 0.5). Tips Static and dynamic fibs can overlap-this often highlights especially important support/resistance zones. Adjust the swing strength for your trading style: lower values for short-term, higher for long-term swings. Hide/show individual lines using the indicator’s style settings in TradingView. Trading Ideas (for higher timeframes and static fibs) Close above the blue line (0.618 static fib): This can be interpreted as a potential long (buy) signal, suggesting the market is breaking above a key resistance level. Close below the red line (0.382 static fib): This can be interpreted as a potential short (sell) signal, indicating the market is breaking below a key support level. Note: These signals are most meaningful on higher timeframes and when using the static fib lines. Always confirm with your own strategy and risk management.
Pine Script® Indikator
von mr_uponly
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