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Viprasol Trendline Volume Breakout## Overview The Trendline Volume Breakout (TVB) indicator automatically detects trendlines from pivot points, extends them in real time, and confirms breakouts with volume surge validation. It handles both bearish (descending) and bullish (ascending) trendlines, scoring every breakout on a 0-10 scale based on trendline age, volume quality, slope steepness, and candle displacement. Designed for breakout traders, this tool eliminates manual trendline drawing while adding institutional-quality filters that separate high-probability breaks from noise. ## How It Works **Trendline Detection:** The indicator identifies consecutive pivot highs (for bearish/descending trendlines) and pivot lows (for bullish/ascending trendlines). A slope factor threshold ensures only meaningfully angled trendlines are tracked. Duplicate/overlapping trendlines are automatically filtered out. **Breakout Confirmation:** A breakout fires when price closes beyond the trendline by a configurable percentage. Before display, each breakout is validated through: - Volume surge gate: volume must exceed its moving average by a user-defined percentage - The breakout candle must satisfy both price and volume conditions simultaneously **Breakout Scoring (0-10):** Every confirmed breakout receives a quality rating: - Trendline age (+1 to +3 — older trendlines = more significant breaks) - Volume surge present (+3) - Slope steepness (+1 to +2) - Displacement candle quality (+2 — large body ratio) **Retest Detection:** After a breakout, the indicator watches for price to return to the broken trendline level within a configurable window. A confirmed retest (touch + close in breakout direction) is marked with an RT label. ## Key Features - **Dual Trendline Detection** — both descending (bearish) and ascending (bullish) trendlines from pivot points - **Volume Surge Gate** — configurable volume threshold filters out low-conviction breakouts - **Breakout Scoring (0-10)** — transparent quality rating with star system and tooltip breakdown - **Retest Detection** — automatic identification of pullbacks to broken trendline levels - **Smart TP/SL** — ATR-based targets (TP1/TP2) with stop loss projected from breakout point - **Channel / Polygon Modes** — parallel channel bands or polygon fill from trendline to extreme - **Trendline Age Labels** — periodic display of how many bars old each active trendline is - **Volume % Bar** — optional visual bar showing volume surge magnitude on breakout - **Duplicate Filtering** — overlapping trendlines are automatically removed - **Info Dashboard** — active trendline count, breakout totals, last score, volume surge status - **Dynamic v6 Alerts** — ticker, timeframe, price, score, and volume % in every alert message - **6 Alert Conditions** — bullish/bearish breakout, high-confidence, any breakout, volume surge ## How to Use 1. **Apply to a standard candlestick chart** on any liquid instrument 2. **Trendlines appear automatically** as pivot highs/lows form 3. **Watch for BO labels** — breakouts are marked with direction arrows and star ratings 4. **Check tooltips** on breakout labels for detailed score breakdown 5. **Monitor retest labels (RT)** for potential re-entry opportunities 6. **TP/SL lines** give clear risk-reward targets from the breakout point 7. **Dashboard** shows active trendline count and breakout statistics **Recommended Settings:** - Scalping (1m-5m): Pivot Length 2, Breakout % 1-2, Volume Surge 30% - Day Trading (5m-15m): Default settings (Pivot 3, Breakout 3%, Volume 50%) - Swing Trading (1H-4H): Pivot Length 4-5, Breakout % 4-5, Volume Surge 60% ## Settings | Group | Description | |---|---| | Trendline Detection | Pivot length, slope factor, bearish/bullish toggle, age labels | | Breakout Settings | Breakout percentage threshold | | Volume Confirmation | Surge %, require volume toggle, volume MA period, volume bar | | Visual Mode | Channel vs Polygon, shading toggle | | Retest Detection | Enable/disable, retest window, tolerance % | | Take Profit / Stop Loss | ATR-based SL, R:R ratios for TP1/TP2, display bars | | Dashboard | Position, size, visibility | | Style | Bull/bear/channel/breakout/background colors | ## Alerts **Dynamic Alerts (v6):** - Bullish breakout (descending TL broken upward) with score, volume %, ticker, price - Bearish breakout (ascending TL broken downward) with score, volume %, ticker, price **Static Alert Conditions:** - Bullish Breakout / Bearish Breakout - High Score Bullish BO (7+/10) / High Score Bearish BO (7+/10) - Any Breakout (either direction) - Volume Surge (above threshold) ## Limitations & Disclaimer - This is an analytical overlay, NOT a trading system. Always use proper risk management. - Trendline detection is based on pivot points — very short-term noise can create false trendlines on low timeframes. - Breakout scoring is a heuristic guide — higher scores correlate with but do not guarantee better outcomes. - Channel mode uses polylines which have a TradingView limit of 100 per chart. - Best used on liquid markets where volume data is reliable. - Use standard candlestick charts for accurate breakout detection. ## Credits Based on the "Trendline Breakout with Volume Confirmation" concept by Dots3Red. Significantly enhanced with bullish trendline detection, breakout scoring, retest detection, smart TP/SL, trendline age labels, configurable volume gate, dashboard, and dynamic alerts under Viprasol branding.
Pine Script®指標
由viprasol提供
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Viprasol Volatility Channel Oscillator## Overview The Volatility Channel Oscillator (VCO) measures where the current close sits within a dynamic volatility channel, producing a bounded oscillator (-100 to +100) with a signal SMA, momentum histogram, divergence detection, squeeze detection, and multiple crossover signal modes. It combines volatility-normalized price positioning with momentum analysis to identify overbought/oversold conditions, divergence setups, and potential breakout opportunities from low-volatility squeezes. ## How It Works **Channel Construction:** The volatility channel is built from three components: (1) a Simple Moving Average of the candle midpoint `(high + low) / 2` over the user-defined period (default 30), (2) the average candle range `SMA(high - low, period)`, and (3) the average candle body `SMA(|close - open|, period)`. The channel offset is calculated as: `offset = avg_range * (band_scale / 100) * (1 + avg_body / avg_range)`. This means the channel widens when candles have larger bodies relative to their wicks, adapting to market character. Upper and lower bands are `midpoint_SMA +/- offset`. **Oscillator Calculation:** The raw oscillator normalizes the close position within the channel: `raw = 100 * (close - lower) / (upper - lower) - 50`. This produces values centered on 0, where +50 means close is at the upper band and -50 means close is at the lower band. Values are clamped to the -100 to +100 range. **Signal SMA:** A Simple Moving Average of the oscillator (default 20 periods) acts as a smoothed reference. Crossovers between the oscillator and this signal, or between the signal and zero, generate trading signals. **Momentum Histogram:** The difference between the raw oscillator and its signal SMA is plotted as color-coded columns. Four colors indicate momentum direction: growing bullish (positive and increasing), fading bullish (positive but decreasing), growing bearish (negative and decreasing), and fading bearish (negative but increasing). **Squeeze Detection:** The channel bandwidth is measured as a percentage of the midpoint SMA. When this bandwidth falls below its own N-period SMA (default 50 bars) multiplied by a threshold factor (default 0.8), a squeeze condition is flagged with diamond markers on the zero line. **Divergence Engine:** The indicator detects regular divergences by comparing pivot highs/lows on price against pivot highs/lows on the oscillator. A bullish divergence occurs when price makes a lower low but the oscillator makes a higher low. A bearish divergence occurs when price makes a higher high but the oscillator makes a lower high. **Signal Confluence Filter:** When enabled, OB/OS crossover signals only fire if a divergence was detected within the last 10 bars, filtering for higher-probability setups. **Signal Cooldown:** A configurable minimum bar gap (default 5 bars) between consecutive signals of the same direction prevents rapid-fire noise in choppy markets. **Zone Classification:** The oscillator is classified into five zones: Strong Bull (above OB), Weak Bull (0 to OB), Neutral (0), Weak Bear (OS to 0), and Strong Bear (below OS). Each zone has a distinct color displayed in the dashboard and optionally as background shading. ## Key Features - **Bounded Oscillator (-100 to +100)** — normalized close position within a volatility-adaptive channel - **Signal SMA** — smoothed reference line for crossover and momentum analysis - **Momentum Histogram** — oscillator minus signal with 4-color directional coding - **Squeeze Detection** — bandwidth contraction flagging potential breakout conditions - **Divergence Detection** — regular bullish/bearish divergences between price and oscillator - **Signal Confluence Filter** — combine OB/OS crossovers with divergence for higher-quality setups - **Signal Cooldown** — configurable minimum bar gap between same-direction signals - **Zone Classification** — 5-level trend strength meter (Strong Bull to Strong Bear) - **3 Signal Modes** — OB/OS crossover, zero line cross, MA zero line cross (or All) - **5-Layer Gradient Fill** — smooth visual fade from oscillator to zero line - **Zone Background Shading** — subtle pane coloring based on active zone - **Info Dashboard** — oscillator, signal, histogram, zone, squeeze, divergence status - **Dynamic v6 Alerts** — ticker, price, osc value, zone, and squeeze in every message - **11 Alert Conditions** — divergences, crosses, squeeze, aggregate signals ## How to Use 1. **Apply to any liquid instrument** — works on crypto, forex, indices, stocks 2. **Oscillator above 0 = bullish bias**, below 0 = bearish bias 3. **Watch for OB/OS crossovers** — oscillator crossing back from extreme zones signals potential reversals 4. **Monitor divergences** — "Bull" and "Bear" labels highlight price/oscillator disagreements 5. **Enable confluence filter** for higher-probability OB/OS signals (requires divergence confirmation) 6. **Squeeze diamonds** on the zero line warn of low-volatility coiling before potential breakouts 7. **Histogram direction** reveals momentum shifts before oscillator crosses zero 8. **Dashboard** gives a quick summary of all conditions at a glance **Recommended Settings:** - Scalping (1m-5m): SMA Length 15-20, Signal 10, Cooldown 3 - Day Trading (5m-15m): Default settings (SMA 30, Signal 20, Cooldown 5) - Swing Trading (1H-4H): SMA Length 40-60, Signal 30, Cooldown 8 ## Settings | Group | Description | |---|---| | Oscillator Settings | SMA length, band scaling, signal SMA period | | Threshold Levels | Overbought/oversold and MA overbought/oversold thresholds | | Divergence Detection | Pivot length, enable/disable | | Signal Settings | Signal type mode, confluence filter, cooldown bars | | Squeeze Detection | Enable, lookback period, threshold multiplier | | Momentum Histogram | Show/hide, 4 directional colors | | Dashboard | Position, size, visibility | | Gradient Settings | Toggle and transparency for each gradient layer | | Style | Oscillator, signal, divergence, zone, and label colors | ## Alerts **Dynamic Alerts (v6):** - Bullish/Bearish signal with osc value, zone, ticker, price, squeeze status - Squeeze started with bandwidth percentage **Static Alert Conditions:** - Bullish Divergence / Bearish Divergence - Buy/Sell Signal (OB/OS) — with cooldown applied - Buy/Sell Signal (Zero Line) - Buy/Sell Signal (MA Zero Line) - Squeeze Started - Any Bullish Signal / Any Bearish Signal ## Limitations & Disclaimer - This is an analytical oscillator, not a trading system. Always use proper risk management. - The oscillator is derived from a volatility channel — during extremely low-volatility periods, small price moves can cause large oscillator swings. - Squeeze detection identifies bandwidth contraction but does not predict breakout direction. - Divergence detection uses historical pivots and is plotted with an offset — it is confirmatory, not predictive. - Best used on liquid markets with consistent volume data. - Past signal patterns do not guarantee future results. . Significantly enhanced with momentum histogram, squeeze detection, signal confluence filter, signal cooldown, zone classification, dashboard, dynamic v6 alerts, and zone background shading under Viprasol branding.
Pine Script®指標
由viprasol提供
Multi-TF Keltner Heatmap# Multi-TF Keltner Heatmap A multi-timeframe volatility structure indicator designed to show where momentum pivots are forming across timeframes. Instead of plotting a single Keltner Channel, this script overlays Keltner envelopes from 12 timeframes simultaneously, allowing traders to see when lower timeframe volatility begins pivoting relative to higher timeframe structure. For options traders, these pivot points often represent the moments where momentum changes fastest while options are still relatively cheap. The goal is to identify the earliest structural shift in volatility expansion before the larger move becomes obvious. ## Core Idea Momentum rarely appears suddenly on higher timeframes. Instead, it typically builds from smaller timeframes upward. Lower timeframes begin expanding volatility until they interact with or surpass the volatility boundaries of larger timeframes. When this occurs, the script identifies it as a pivot event. A pivot means the shorter timeframe volatility envelope has reached or crossed the adjacent higher timeframe envelope, indicating that momentum pressure is shifting. As these pivots propagate upward through the timeframe ladder, a momentum chain forms. This chain represents how many layers of the market structure are currently shifting direction. ## Timeframes Included The script pulls Keltner Channel data from the following timeframes: - 1 Minute - 3 Minute - 5 Minute - 10 Minute - 15 Minute - 30 Minute - 45 Minute - 1 Hour - 2 Hour - 4 Hour - 1 Day - 1 Week These timeframes together create a stacked volatility structure showing how pressure builds through the market. ## Keltner Channel Construction Each timeframe uses the same parameters. Basis EMA (default length: 200) Volatility Envelope ATR (default length: 200) Bandwidth Multiplier ATR × 8 These intentionally large settings create structural volatility envelopes rather than short-term reactive channels. The focus is on major volatility shifts rather than micro fluctuations. ## Visual Structure The indicator uses color to separate layers of the timeframe hierarchy. ### White Bands (1m – 15m) These represent short-term market microstructure. They allow traders to see: - short-term compression - micro volatility expansion - early directional pressure Opacity is reduced so these bands remain informational rather than dominant. ### Intermediate Layer (30m / 45m) Upper bands are colored green. Lower bands are colored red. These timeframes often act as the bridge between intraday volatility and higher timeframe momentum. When price begins interacting strongly with these bands, it often signals that pressure is building toward a larger pivot. ### Higher Timeframe Bands (1H – 1W) Higher timeframe bands are hidden by default. They only appear when a pivot condition occurs. A pivot occurs when: Shorter timeframe upper band ≥ adjacent higher timeframe upper band or Shorter timeframe lower band ≤ adjacent higher timeframe lower band Example: 45m upper ≥ 1H upper When this happens, the 1H upper band becomes visible. This signals that short-term volatility is now interacting with higher timeframe structure. ## Pivot Chain Momentum shifts are tracked using adjacent timeframe pivots. Upper band pivots follow this sequence: - 45m → 1H - 1H → 2H - 2H → 4H - 4H → 1D - 1D → 1W Lower band pivots follow the same sequence. This adjacency logic reflects how momentum realistically propagates through the market rather than skipping timeframes. ## Pivot Chain Depth The indicator calculates two values shown in the status line and data window. Bull Chain Number of upward pivot steps currently active. Example: 45m pivoting above 1H 1H pivoting above 2H 2H pivoting above 4H Bull Chain = 3 Bear Chain Number of downward pivot steps currently active. Example: 45m pivoting below 1H 1H pivoting below 2H 2H pivoting below 4H Bear Chain = 3 ## Interpreting Chain Depth Lower chain values typically indicate: - localized volatility - range conditions - early momentum shifts Higher chain values indicate: - stronger structural alignment - expanding volatility - sustained directional momentum Deep pivot chains are relatively rare and often occur during: - breakouts - strong trend continuation - macro directional moves ## Why This Matters for Options Options traders benefit most when they can identify large momentum shifts early, before volatility expansion fully develops. When lower timeframes begin pivoting relative to higher timeframe envelopes, it often means: - directional pressure is building - volatility expansion may follow - option pricing has not fully reacted yet This creates the opportunity to enter positions before volatility and delta expansion make contracts expensive. ## Practical Uses This indicator can help traders: - identify early momentum pivots - visualize multi-timeframe volatility alignment - detect volatility expansion before breakouts - confirm trend continuation across timeframes It is particularly useful when looking for high momentum opportunities while options remain relatively inexpensive. ## Conceptual Summary Momentum builds from smaller timeframes upward. When lower timeframe volatility begins interacting with and pivoting against larger timeframe envelopes, the market is often entering a structural shift phase. This indicator visualizes that process so traders can see momentum transitions while they are still forming.
Pine Script®指標
由Jysun提供
Ornstein-Uhlenbeck Mean Reversion Probability Bands [UAlgo]Ornstein-Uhlenbeck Mean Reversion Probability Bands is a statistical mean reversion indicator that models price as a mean reverting process and projects dynamic probability style zones around an estimated equilibrium mean. The script uses a rolling lookback of closing prices, fits an Ornstein-Uhlenbeck inspired parameter set from recent behavior, and then converts that estimate into inner and outer deviation bands around the current mean. The indicator runs directly on price ( overlay=true ) and is built to help traders identify when price is stretched away from its estimated equilibrium. Instead of using a fixed moving average and static standard deviation, the script attempts to infer a mean reverting structure from the data itself. It estimates the long term mean, the speed of reversion, and an equilibrium style dispersion measure, then plots two upside and two downside mean reversion zones. When price pushes into the upper or lower band regions, the script calculates a standardized distance from the estimated mean and displays a probability style label with both the percentage score and the current z score. This gives the user a quick visual read of how statistically extended price is relative to the model. A key strength of this script is that it combines: A rolling Ornstein-Uhlenbeck style parameter estimation Adaptive mean reversion zones Probability style stretch labels at band events A clean overlay presentation with visible upper and lower probability regions Important note: The percentage label in this script is a normal distribution coverage style score derived from the current z score. It is best understood as a probabilistic stretch measure, not a literal exact OU first passage probability. 🔹 Features 🔸 1) Ornstein-Uhlenbeck Inspired Mean Reversion Model The script estimates a mean reverting process from recent closing prices instead of relying only on a moving average. It uses a rolling regression style approach on consecutive price observations, then converts those estimates into Ornstein-Uhlenbeck style parameters. This makes the indicator more model driven than a standard band tool. 🔸 2) Rolling Adaptive Mean Line The central mean line is not a fixed average only. It is the estimated equilibrium level ( mu ) of the fitted process. As the rolling price sample changes, the model updates and the mean shifts with changing market structure. The mean line also changes color depending on whether current price is above or below that estimated equilibrium. 🔸 3) Dual Mean Reversion Zones (Inner and Outer) The script builds two sets of reversion bands around the mean: Inner bands using the inner multiplier Outer bands using the outer multiplier This creates a layered framework where the inner zone marks an early stretch area and the outer zone marks a more extreme statistical extension. 🔸 4) Probability Style Stretch Labels When price crosses into the upper or lower band regions, the script calculates a z score based on current distance from the estimated mean and converts it into a percentage style probability score. The label shows: A directional marker The probability style percentage The current z score This gives the user both a visual event trigger and a numeric measure of extension. 🔸 5) Visual Zone Based Design The indicator uses filled upper and lower zones rather than emphasizing the band lines themselves. This creates a cleaner chart display where the mean line stays visible and the stretch regions are highlighted as colored areas above and below it. This makes the indicator easy to read during fast chart scanning. 🔸 6) Configurable Lookback, Time Step, and Band Width Users can customize: The rolling lookback period used for model estimation The time step parameter ( dt ) used in OU conversion The inner band multiplier The outer band multiplier This makes the script adaptable to different timeframes, instruments, and preferred sensitivity levels. 🔸 7) Built In Estimation Safeguards The parameter estimation logic includes fallback protections. If the inferred model parameters are unstable or unrealistic, the script falls back to simpler sample statistics. This helps prevent unusable outputs during difficult market regimes or low quality fits. 🔸 8) Directional Touch Event Logic The script tracks both upper side and lower side band interaction: Upper side events can signal statistically stretched bullish price movement Lower side events can signal statistically stretched bearish price movement Labels are only created on crossing events, which helps reduce repeated prints while price remains outside the band. 🔹 Calculations 1) Rolling Price Queue Management The script stores recent closing prices in an array with a fixed maximum length: price_array.update_queue(close, length_input) The queue update method behaves differently depending on bar state: On a new bar, it pushes the latest value On an updating live bar, it overwrites the last stored value This keeps the rolling sample aligned with the current chart state without duplicating the active bar. 2) Fallback Mean and Dispersion Estimates Before attempting the OU style fit, the script calculates simple fallback values: float fallback_mu = src_array.avg() float fallback_sigma = src_array.stdev() These act as safety defaults if the regression based OU estimate is not reliable. Important note: In this script, fallback_sigma is a simple sample standard deviation of price levels, not return volatility. 3) AR(1) Style Regression on Consecutive Prices The model estimation is built from consecutive price pairs: x = price y = price The script computes: Mean of x Mean of y Covariance between x and y Variance of x Then it estimates: float b = sum_cov / sum_var_x This creates an AR(1) style coefficient that is later translated into OU style parameters. 4) Conversion from AR(1) Form to OU Style Parameters If the estimated b is within a valid range: if b > 0.05 and b < 0.95 the script computes: float a = mean_y - b * mean_x float mu_exact = a / (1.0 - b) float theta_exact = -math.log(b) / dt Interpretation: mu_exact is the estimated long run mean. theta_exact is the implied mean reversion speed. The conversion assumes the AR(1) relation is a discrete time representation of a mean reverting process. 5) Residual Variance and Equilibrium Dispersion The script next measures residual error from the AR(1) fit: float err = y_i - (a + b * x_i) float var_err = sum_err_sq / (n - 1) Then it converts that residual variance into an equilibrium variance estimate: float var_eq = var_err / (1.0 - b * b) Finally: float calc_sigma = math.sqrt(var_eq) Important implementation note: The variable named sigma in this script is used as an equilibrium style standard deviation around the mean, not as the continuous time OU diffusion coefficient from the SDE form. 6) Stability Filter for the Estimated Sigma Even if the AR(1) fit is mathematically valid, the script only accepts the calculated sigma when it is reasonably close to the fallback sample standard deviation: if calc_sigma < fallback_sigma * 1.5 and calc_sigma > fallback_sigma * 0.5 If this test fails, the script keeps the fallback values instead. This helps avoid unstable band widths caused by bad short term fits. 7) Final Parameter Output The estimation method returns: OU_Params.new(theta, mu, sigma_eq) Where: theta is the estimated reversion speed mu is the estimated equilibrium mean sigma_eq is the accepted equilibrium dispersion measure These parameters are then used to build the bands. 8) Band Construction The script computes four band levels around the estimated mean: float up_out = mean_val + (dev_val * mult_outer) float up_in = mean_val + (dev_val * mult_inner) float dn_in = mean_val - (dev_val * mult_inner) float dn_out = mean_val - (dev_val * mult_outer) Interpretation: Inner bands represent a milder deviation from the mean. Outer bands represent a more extreme deviation from the mean. 9) Mean and Zone Visualization The mean line is explicitly plotted: p_mean = plot(ou_bands.mean, color=color_mean, linewidth=2, title="Mean") The inner and outer band plots are also created, but their colors are fully transparent: color color_inner_up = color.new(#ffb74d, 100) color color_outer_up = color.new(#ef5350, 100) ... This means the visible structure mainly comes from the zone fills: fill(p_ui, p_uo, ...) fill(p_li, p_lo, ...) So the user sees clean upper and lower probability zones rather than several bright boundary lines. 10) Touch and Crossing Logic The script first checks whether price is currently inside a stretch area: bool touch_upper = close >= ou_bands.upper_inner bool touch_lower = close <= ou_bands.lower_inner Then it checks for fresh crossings: bool cross_up_in = ta.crossover(close, ou_bands.upper_inner) bool cross_up_out = ta.crossover(close, ou_bands.upper_outer) bool cross_dn_in = ta.crossunder(close, ou_bands.lower_inner) bool cross_dn_out = ta.crossunder(close, ou_bands.lower_outer) Labels are only created when price is touching the region and a fresh crossing occurs. This avoids creating labels on every bar that remains outside the band. 11) Z Score Calculation When an event occurs, the script calculates the standardized distance from the mean: float current_z_score = dev_val != 0 ? math.abs(close - mean_val) / dev_val : 0.0 Interpretation: A z score of 1 means price is one equilibrium standard deviation away from the estimated mean. Higher values indicate a more statistically stretched condition. 12) Probability Style Score Calculation The script converts the z score into a percentage style score using an approximation of the error function: float x = math.abs(z_score) / math.sqrt(2.0) ... float prob = erf_approx * 100.0 Because erf(|z| / sqrt(2)) corresponds to the probability mass within plus or minus that z distance under a normal distribution, the output behaves like a confidence or coverage score. Important note: This is not a direct OU mean reversion probability in the strict stochastic process sense. It is a normal distribution style stretch score based on the current z distance. 13) Upper Event Label Logic When price crosses into the upper band region: if (touch_upper and cross_up_in) or (touch_upper and cross_up_out) the script prints a bearish styled label above the bar: "▼ %" + str.tostring(probability, "#.##") + " (Z:" + str.tostring(current_z_score, "#.##") + ")" This reflects the idea that price is statistically extended above the mean and may be vulnerable to reversion. 14) Lower Event Label Logic When price crosses into the lower band region: if (touch_lower and cross_dn_in) or (touch_lower and cross_dn_out) the script prints a bullish styled label below the bar: "▲ %" + str.tostring(probability, "#.##") + " (Z:" + str.tostring(current_z_score, "#.##") + ")" This reflects the idea that price is statistically extended below the mean and may be vulnerable to reversion. 15) Role of the Time Step Input The dt_input parameter affects the conversion from the AR(1) coefficient into the OU reversion speed: float theta_exact = -math.log(b) / dt A larger dt lowers the inferred theta for the same b . A smaller dt raises the inferred theta for the same b .
Pine Script®指標
由UAlgo提供
Donchian Ribbon [UAlgo]Donchian Ribbon is a chart-overlay Donchian Channel ribbon that visualizes multiple lookback lengths at the same time. Instead of plotting a single Donchian Channel, the script builds a fixed stack of channels that increase in length and blends them into a clean, layered ribbon above and below price using progressive fills. The goal is to make market structure and regime easier to read without clutter: - When the ribbon expands and stays orderly (fast boundaries leading, slow boundaries following), it often reflects sustained range expansion and more directional flow. - When the ribbon compresses and bands overlap frequently, it typically reflects consolidation, rotational behavior, and reduced clarity. - The slowest channel provides the structural “outer frame” of the market’s recent range, while shorter channels react first and show how quickly the range is shifting. This indicator is designed as a context tool. It does not attempt to “predict” direction by itself, but it gives a high-quality visual map of evolving highs/lows across multiple sensitivities so you can align entries, risk, and expectations with the current regime. 🔹 Features 1) Multi-Length Donchian Stack (Ribbon Engine) The script constructs several Donchian Channels from a Base Length and a Step Length. Each band represents a different sensitivity level: - Fast bands respond quickly to recent highs and lows. - Slow bands respond more conservatively and define broader containment. By stacking these lengths together, you can see short-term responsiveness and higher-level structure simultaneously. 2) Two-Sided Ribbon (Upper and Lower Envelopes) The indicator visualizes both sides of the Donchian framework: - Upper ribbon is built from stacked Donchian highs (highest highs per length). - Lower ribbon is built from stacked Donchian lows (lowest lows per length). This keeps interpretation intuitive: price pressing into the upper ribbon suggests pressure toward recent highs, while leaning into the lower ribbon suggests pressure toward recent lows. 3) Gradient Depth via Layered Fills (Clean Charts) Instead of drawing many lines, the script fills the space between consecutive bands. Transparency is gradually adjusted from the fast band to the slow band, producing a smooth depth effect that stays readable even on busy charts. Intermediate plots are intentionally hidden so the ribbon remains the main visual output. 4) Regime Readability (Expansion vs Compression) Because each band has a different lookback length, the ribbon naturally communicates volatility and state: - Expansion: spacing between fast and slow bands increases, commonly seen in stronger directional phases. - Compression: spacing collapses and bands cluster, commonly seen in ranges, pauses, or choppy rotation. This helps you quickly decide whether to treat price action as breakout-oriented, trend-continuation, or mean-reverting. 5) Trend Baseline Reference (Slow Midpoint) A baseline is plotted using the midpoint of the slowest channel. This provides a stable reference that helps you judge whether price is operating in the upper or lower half of the broader range structure. 🔹 Calculations 1) Donchian High, Low, and Midpoint Per Band Each Donchian band is computed from its own length: - High = highest high over the lookback length - Low = lowest low over the lookback length - Mid = average of High and Low id.high := ta.highest(id.length) id.low := ta.lowest(id.length) id.mid := math.avg(id.high, id.low) 2) Length Sequencing (Base Length + Step Length) The indicator creates a fixed number of bands. Lengths are built as: - Band 1: base_length - Band 2: base_length + step_length - Band 3: base_length + 2 * step_length - ... - Final band: base_length + (ribbon_count - 1) * step_length This yields a consistent progression from fast to slow sensitivity. int len = base_length + (i * step_length) channels.push(DonchianChannel.new(len)) 3) Iterative Updates with Arrays and Methods All bands are stored in an array and updated every bar using a unified method call. This ensures every band follows identical rules and makes the logic scalable and maintainable. for dc in channels dc.update() 4) Upper Ribbon Construction (Layered Fills Between Highs) The upper ribbon is created by filling between consecutive Donchian highs. Each layer uses the same upper tone with progressively stronger visibility toward the slow band. fill(p_fast_high, p_mid1_high, color.new(col_upper, 90), "Ribbon Upper 1") fill(p_mid1_high, p_mid2_high, color.new(col_upper, 80), "Ribbon Upper 2") fill(p_mid2_high, p_mid3_high, color.new(col_upper, 70), "Ribbon Upper 3") fill(p_mid3_high, p_slow_high, color.new(col_upper, 60), "Ribbon Upper 4") 5) Lower Ribbon Construction (Layered Fills Between Lows) The lower ribbon is created by filling between consecutive Donchian lows with the lower tone, again using progressive transparency. fill(p_fast_low, p_mid1_low, color.new(col_lower, 90), "Ribbon Lower 1") fill(p_mid1_low, p_mid2_low, color.new(col_lower, 80), "Ribbon Lower 2") fill(p_mid2_low, p_mid3_low, color.new(col_lower, 70), "Ribbon Lower 3") fill(p_mid3_low, p_slow_low, color.new(col_lower, 60), "Ribbon Lower 4") 6) Trend Baseline (Slow Midpoint) The baseline is the midpoint of the slowest Donchian band, plotted as a stable center reference for the broadest range framework. plot(dc_slow.mid, "Trend Baseline", color = color.from_gradient(0.5, 0, 1, col_lower, col_upper), linewidth = 2) 7) Visualization Choice (Hidden Internals, Visible Structure) To keep charts clean, most intermediate plots are hidden and the ribbon fills do the heavy lifting visually, while the slow boundaries remain visible as the outer frame. p_fast_high = plot(dc_fast.high, "Fast High", color = color.new(col_upper, 80), display = display.none) p_fast_low = plot(dc_fast.low, "Fast Low", color = color.new(col_lower, 80), display = display.none) p_slow_high = plot(dc_slow.high, "Slow High", color = color.new(col_upper, 50)) p_slow_low = plot(dc_slow.low, "Slow Low", color = color.new(col_lower, 50))
Pine Script®指標
由UAlgo提供
Rolling Liquidity Clusters Channel [LuxAlgo]The Rolling Liquidity Clusters Channel indicator identifies dynamic support and resistance zones by calculating levels that maximize candle wick touches while strictly avoiding intersections with candle bodies within a rolling window. This tool provides a unique perspective on liquidity clusters, highlighting price levels where historical rejection is most concentrated without being invalidated by price "closing" through them. 🔶 USAGE The indicator plots a channel consisting of an Upper Level, a Lower Level, and a Mid Level. The space between these levels is filled with a vertical gradient to visually represent the strength of the liquidity zone. Upper Level (Red): Represents a resistance zone where the most upper wicks are concentrated without any candle body in the lookback window crossing above it. Lower Level (Green): Represents a support zone where the most lower wicks are concentrated without any candle body in the lookback window crossing below it. Mid Level (Orange): Represents the equilibrium or average of the current liquidity channel. Traders can use these levels to identify potential reversal points or areas of price consolidation. A breakout from the channel might indicate a shift in market structure as price moves beyond the most inclusive "non-broken" wick levels. 🔶 DETAILS The script employs a specific constraint logic to ensure the levels represent true "untouched" liquidity: 🔹 Body-Crossing Constraint Before identifying the wick touches, the script calculates the highest candle body high and lowest candle body low within the user-defined window. The resulting levels are guaranteed to stay outside of this "body zone," ensuring that the plotted levels represent prices that the market reached but failed to sustain via a close. 🔹 Maximizing Touches To find the most significant level, the algorithm searches for the most inclusive price point. For the upper level, it identifies the lowest "high" that remains above all candle bodies. For the lower level, it identifies the highest "low" that remains below all candle bodies. This mathematical approach effectively finds the level where the most price action "clusters" via wicks. 🔹 Vertical Gradient Fills The visual style uses a vertical gradient fill. The upper half fades from 90% transparency at the Upper Level (Red) to 100% transparency at the Mid Level. The lower half follows a similar logic, fading from the Lower Level (Green) toward the center. This creates a "glow" effect, emphasizing the outer boundaries where liquidity is highest. 🔶 SETTINGS Window Size: The number of bars used for the rolling calculation. A larger window creates more stable, long-term levels, while a smaller window adapts quickly to recent price action. Upper Level: Customize the color of the upper resistance level and its associated gradient fill. Lower Level: Customize the color of the lower support level and its associated gradient fill. Mid Level: Customize the color of the central equilibrium line.
Pine Script®指標
由LuxAlgo提供
Adaptive Bounds RSI [LuxAlgo]The Adaptive Bounds RSI indicator utilizes online 1D K-Means clustering to dynamically adapt RSI overbought and oversold bounds based on evolving market conditions. Unlike traditional RSI thresholds (70/30) that remain static, this tool identifies five shifting clusters to better categorize price action into regimes ranging from deep discount to extreme premium. 🔶 USAGE The indicator provides a more responsive way to identify overextended market conditions by learning from recent RSI distributions. Instead of relying on fixed levels that may be irrelevant in strong trends, the adaptive bounds expand and contract based on the volatility and momentum of the asset. 🔹 Regime Classification The tool classifies the market into five distinct regimes based on five internal centroids (clusters): Extreme Premium (Upper Bound): Represents highly overextended bullish conditions. Bullish: The zone between the center and the upper bound. Neutral: The area surrounding the 50-level midline. Bearish: The zone between the center and the lower bound. Deep Discount (Lower Bound): Represents highly overextended bearish conditions. 🔹 Signal Markers The indicator plots circular markers directly on the RSI line when the oscillator crosses the adaptive bounds: A Bullish Marker appears when the RSI crosses below the adaptive lower bound (Deep Discount). A Bearish Marker appears when the RSI crosses above the adaptive upper bound (Extreme Premium). To prevent signal clutter, these markers only reappear once the RSI has returned to cross the 50-level midline, ensuring the market has "reset" before a new overextended signal is generated. 🔶 DETAILS The core of this indicator is an Online 1D K-Means algorithm. Unlike standard clustering which requires a full dataset, this online version updates its centroids bar-by-bar. When a new RSI value is calculated, the algorithm determines which of the five centroids is closest to that value. It then shifts that "winning" centroid toward the RSI value by a factor determined by the Learning Rate. This allows the boundaries to "breathe" with the market; in a persistent uptrend, the upper bound will naturally migrate higher to avoid premature overbought signals. 🔶 SETTINGS 🔹 Oscillator Settings RSI Length: Determines the lookback period for the underlying Relative Strength Index calculation. 🔹 K-Means Settings Learning Rate (K-Means): Controls how quickly the adaptive bounds react to new data. A higher value makes the bounds move faster, while a lower value provides more stable, "sticky" boundaries. 🔹 Visuals Lower Bound Color: Sets the color for the lower adaptive boundary and bullish signals. Upper Bound Color: Sets the color for the upper adaptive boundary and bearish signals. Auto RSI Color: When enabled, the RSI line matches the chart's foreground color. RSI Color: Sets the color of the RSI line when "Auto RSI Color" is disabled. 🔶 ALERTS Regime Flip: Triggers when the market transitions from a Neutral state into a trending cluster (Bullish or Bearish). Lower Bound Cross: Triggers when the RSI crosses into the Deep Discount zone. Upper Bound Cross: Triggers when the RSI crosses into the Extreme Premium zone.
Pine Script®指標
由LuxAlgo提供
3
Neighboring Price Bands [LuxAlgo]The Neighboring Price Bands indicator provides dynamic support and resistance levels based on the local statistical distribution of historical prices relative to the current market position. Unlike traditional volatility bands that rely on fixed standard deviations, this tool identifies "price neighbors" within a sorted historical buffer to determine where the market has previously found friction. 🔶 USAGE The indicator helps traders identify potential reversal zones and breakout opportunities by analyzing the density of price action around the current level. 🔹 Support and Resistance The bands act as flexible zones of interest. The upper (green) band represents a bullish boundary derived from historical prices slightly higher than the current price, while the lower (red) band represents a bearish boundary from prices slightly lower. When the price interacts with these bands, it is entering a zone where historical price density suggests a potential reaction. 🔹 Price Discovery & Breakouts A unique feature of this tool is the "Discovery" mechanism. If the current price moves beyond the range of its historical "neighbors" (e.g., reaching a new multi-period high or low), the corresponding band will disappear, and a background highlight will appear. Bullish Discovery: A green background highlight indicates the price is entering uncharted territory relative to the historical buffer, suggesting a strong bullish breakout. Bearish Discovery: A red background highlight indicates the price is dropping below its local historical distribution, suggesting a strong bearish breakdown. 🔶 DETAILS The script maintains a historical buffer of prices, which it constantly sorts to create a price distribution. For every new bar, the algorithm performs the following: It locates the current price within the sorted distribution. It identifies a specific number of "neighbors" (K) above and below that position. It calculates a specific percentile within those neighbors to plot the bands. Because the bands are derived from actual price frequency rather than a calculation like standard deviation (Bollinger Bands) or Average True Range (Keltner Channels), they adapt more specifically to "sticky" price levels where the market has historically spent time. 🔶 SETTINGS Historical Buffer (Bars): The total number of past bars used to build the price distribution. A larger buffer includes more historical context, while a smaller buffer makes the bands more reactive to recent local ranges. Neighboring Range (K): Determines how many samples from the sorted distribution are used to calculate the bands. A smaller K makes the bands tighter and more sensitive to the immediate price position. Percentile: Controls the width of the bands within the neighbor groups. Higher values push the bands further away from the current price. Smoothing: Applies an SMA to the resulting bands to reduce noise and provide a cleaner visual output.
Pine Script®指標
由LuxAlgo提供
LOWESS Channel & Extrapolation [LuxAlgo]The LOWESS Channel & Extrapolation indicator calculates a Locally Weighted Scatterplot Smoothing (LOWESS) curve to define a non-linear trend and projects it into future bars using local regression slopes. It provides a dynamic channel based on the standard deviation of residuals, helping traders identify overextended price levels and potential mean-reversion points. The LOWESS Channel & Extrapolation indicator is subject to repainting and displayed retrospectively. 🔶 USAGE This tool is primarily designed for trend analysis and identifying exhaustion points. Because the LOWESS algorithm recalculates based on the most recent data window, the entire historical curve can adjust, making it a powerful tool for backtesting and analyzing past market structures rather than for real-time signal generation without confirmation. 🔹 Trend Identification The central fit line represents the smoothed local trend. When the curve is sloping upward, the local market sentiment is considered bullish; conversely, a downward slope indicates bearish sentiment. 🔹 Overbought/Oversold Conditions The dashed outer channels represent a volatility-adjusted boundary. When price moves outside these boundaries, it is statistically overextended relative to the local trend, often preceding a move back toward the mid-line. 🔹 Extrapolation The indicator extends the most recent local regression slope into the future. This provides a "path of least resistance" projection based on the current momentum of the smoothed curve. 🔶 DETAILS The LOWESS (Locally Weighted Scatterplot Smoothing) algorithm works by performing a separate weighted linear regression for every data point in the window. It uses a "tricube" weighting function, which ensures that data points closer to the focal point have a higher influence on the fit than points further away. This results in a curve that is much more flexible than a simple moving average and can adapt to complex price cycles without the lag associated with traditional filters. The channel width is determined by calculating the Standard Deviation of the residuals (the difference between the actual price and the LOWESS fit). This ensures the channel expands during high volatility and contracts during consolidation. 🔶 SETTINGS Length : Determines the number of historical observations used to fit the LOWESS curve. Larger values result in a smoother, more macro trend. Span : The fraction of data points used for each local regression. A higher span (closer to 1.0) creates a smoother line, while a lower span allows the curve to follow price more tightly. Channel Multiplier : Multiplier applied to the standard deviation of residuals to define the distance of the upper and lower bands from the mid-line. Extrapolation Bars : The number of bars to project the current trend into the future. Fit Color : Sets the color and transparency of the central LOWESS line. Channel Color : Sets the color of the dashed outer bands and the background fill. Line Width : Adjusts the thickness of the central fit line.
Pine Script®指標
由LuxAlgo提供
Rolling Trendline [LuxAlgo]The Rolling Trendline indicator provides a dynamic, self-adjusting trendline that tracks price action using linear regression slope projections and automatically resets when price deviates beyond a specific threshold. 🔶 USAGE The indicator is designed to provide a continuous trend bias without the "lag" often associated with static linear regression lines. It projects a line forward based on a calculated slope and only shifts its trajectory when the market demonstrates a significant change in momentum. The addition of ATR-based volatility zones allows traders to visualize a range of expected price action around the projected trend, providing a buffer that accounts for market volatility at the time of each trend reset. 🔹 Interpreting the Line and Zones Bullish Phase (Green): Indicates an upward-sloping trajectory. The trendline and its surrounding ATR zones will be colored green, suggesting a bullish bias. Bearish Phase (Red): Indicates a downward-sloping trajectory. The trendline and its surrounding ATR zones will be colored red, suggesting a bearish bias. ATR Zones: These shaded areas represent a volatility-adjusted range. As long as price remains within the deviation threshold, the zones follow the trendline's trajectory. Reset Points: Visualized by a small circle and a break in the line, these occur when price moves too far from the projection. At this moment, the indicator re-anchors to the current price and recalculates both the slope and the ATR zone width. 🔶 DETAILS The indicator follows a specific logic flow to maintain its "Rolling" characteristic: 1. Slope Calculation: It calculates the Linear Regression slope over a user-defined lookback period. This slope represents the average rate of change in price. 2. Projection: On every new bar, the indicator projects the next value of the trendline by adding the active slope to the previous trendline value. 3. Deviation Check: The indicator calculates a Standard Deviation threshold. If the distance between the current price and the projected trendline value exceeds this threshold, a reset is triggered. 4. Re-Anchoring: Upon a reset, the trendline "rolls" to the current price and adopts the most recent linear regression slope. Simultaneously, it captures the current ATR to set the width of the new trend zones. 🔶 SETTINGS 🔹 Trend Settings Slope Lookback: The period used to calculate the linear regression slope. Higher values result in a slope that considers more historical data. Deviation Multiplier: Determines how far price can deviate from the trendline before a reset occurs. Slope Divisor: This setting allows you to tame the trajectory of the line. Higher values divide the captured slope, resulting in flatter trendlines. Source: The price data used for all calculations (default is Close). 🔹 ATR Zones ATR Length: The lookback period used for the Average True Range calculation, which determines the width of the volatility bands. ATR Multiplier: Controls the width of the shaded zones around the trendline. 🔹 Visuals Bullish/Bearish Trend Colors: Customizes the colors for the trendline and zones based on the slope direction. Zone Color: Sets the base color for the ATR area fills. Line Width: Adjusts the thickness of the primary rolling trendline.
Pine Script®指標
由LuxAlgo提供
2
Whittaker Envelope [LuxAlgo]The Whittaker Envelope indicator is a visualization tool that uses Asymmetric Least Squares (ALS) to create a smooth, non-linear envelope that adapts to price extremes and troughs. This indicator is for visualization purposes only and should not be used for direct trading signals without confirmation. It is important to note that this script is displayed retrospectively . Because it calculates the best fit over a fixed historical window (the last N bars) using an iterative optimization process, the entire shape of the envelope can change as new data arrives. This means the indicator repaints and should be used to analyze overall market structure and volatility rather than for real-time execution. 🔶 USAGE The Whittaker Envelope provides a unique way to visualize the "breathing" of the market. By applying different asymmetry parameters, the indicator generates a lower boundary that seeks out price troughs and an upper boundary that seeks out price peaks. 🔹 Trend and Volatility Analysis The area between the upper and lower bounds represents the smoothed price range. A widening envelope suggests increasing volatility, while a narrowing one indicates consolidation. The dashed midline acts as a smoothed average of these two extremes, providing a baseline for the current trend. 🔹 Extrapolation The tool includes a linear extrapolation feature that projects the current trajectory of the envelope into the future. This can help users visualize the potential direction of the trend if the current momentum persists. 🔶 DETAILS The script implements the Whittaker-Eilers smoothing algorithm, which balances two conflicting goals: fitting the data points closely and keeping the resulting curve smooth. By using Asymmetric Least Squares (ALS), we assign different weights to prices depending on whether they are above or below the curve. For the upper band, we use a high asymmetry value ( p ) so the curve is "pushed" toward the peaks. For the lower band, a very low p value is used to "pull" the curve toward the troughs. 🔶 SETTINGS Length : The number of recent bars included in the calculation window. Lambda (λ) : The smoothing factor. Higher values result in a stiffer, straighter envelope, while lower values allow the bands to follow price more closely. Lower Asymmetry (p) : Controls how the lower band reacts to prices. Typically set to a very low value (e.g., 0.001) to ensure it follows the bottom of the price action. Upper Asymmetry (p) : Controls how the upper band reacts to prices. Typically set to a very high value (e.g., 0.999) to ensure it follows the top of the price action. Iterations : The number of times the ALS algorithm runs to refine the fit. More iterations provide a more accurate envelope but require more computational power. Extrapolation : The number of bars to project the current slope of the bands into the future. Source : The price data used for the calculation (default is Close).
Pine Script®指標
由LuxAlgo提供
Dynamic Extreme Channels & Reversals [LuxAlgo]The Dynamic Extreme Channels & Reversals indicator provides an adaptive framework for identifying price extremes and trend shifts through self-adjusting boundaries. Unlike static channels, this tool dynamically resets its levels based on price activity, offering a responsive environment for trend following and mean-reversion analysis. 🔶 USAGE The indicator functions by tracking the highest highs and lowest lows over a specific window. When the price fails to make a new extreme within the defined period, the boundaries contract toward the current price action. This behavior creates a "breathing" channel that adapts to market volatility and consolidation phases. Users can toggle between two primary viewing modes: Channel Mode: Displays the upper, lower, and midline boundaries. This is ideal for identifying overextended price levels and potential mean-reversion targets. Trailing Stop Mode: Simplifies the visual output into a single step-line that tracks the lower boundary during uptrends and the upper boundary during downtrends, serving as a dynamic exit or trend-following level. 🔹 Reversal Signals The script includes built-in reversal signals designed to catch "blow-off" tops or "panic" bottoms where price briefly exceeds a boundary but immediately loses momentum. Bullish Signal (▲): Occurs when the price hits a new lower extreme (LL) but the current candle manages to peak back above the channel midline. Bearish Signal (▼): Occurs when the price hits a new higher extreme (HH) but the current candle manages to drop below the channel midline. The sensitivity and frequency of these signals are directly influenced by the Lookback Period and Reset Alpha % : Lookback Period: A shorter lookback causes the channel boundaries to "reset" more frequently. This results in tighter channels and more frequent reversal signals, as the midline becomes easier to cross. A longer lookback creates wider, more stable channels, resulting in fewer, high-conviction signals. Reset Alpha %: This determines how aggressively the levels move toward the price after the lookback period expires. A high Alpha (e.g., 100%) creates sharp adjustments, which can lead to rapid signal generation during choppy markets. A lower Alpha creates smoother transitions, filtering out noise in the reversal logic. 🔶 DETAILS The core logic avoids standard rolling maximum/minimum functions to provide a more "sticky" boundary. Instead of the channel edge constantly moving with every bar, it remains fixed until a new extreme is reached or the "timer" (Lookback Period) runs out. When the timer runs out, the level interpolates toward the price based on the Reset Alpha. This simulates a decaying memory of past price extremes, ensuring the indicator remains relevant even after long periods of sideways movement. 🔶 SETTINGS 🔹 Core Settings Lookback Period: The number of bars the indicator waits before adjusting an extreme level if no new high/low is found. Reset Alpha %: Controls the intensity of the level adjustment. 100% resets the level entirely to the current price, while 0% keeps it static. Trailing Stop Mode: Switches the display from a three-line channel to a single trend-following stop line. 🔹 Visuals Show Reversal Signals: Toggles the visibility of the triangle reversal labels. Upper Color: Customizes the color and transparency of the upper boundary. Midline Color: Customizes the color and transparency of the center line. Lower Color: Customizes the color and transparency of the lower boundary. 🔹 Dashboard Dashboard: Toggles the on-screen information panel. Position: Controls the location of the dashboard on the chart. Size: Controls the scale of the dashboard text and cells.
Pine Script®指標
由LuxAlgo提供
3
Flexible S/R Channels🟩 Flexible S/R Channels is a visualization tool that draws curved support and resistance boundaries through user-defined anchor points. Unlike traditional trendlines and channels that force linear interpretation onto price action, this indicator captures the curved structures that markets frequently form—rounded tops and bottoms, parabolic advances and declines, arcing rallies and pullbacks. Three anchor points per curve define the shape; the indicator fits a smooth mathematical curve through these points and projects it forward. The approach is simple: draw what you see. Curved market structure that resists precise definition with traditional tools can now be rendered with mathematical accuracy. The indicator bridges the gap between static drawing tools and programmable indicators. TradingView's arc tool draws curves but produces only visual pixels with no analytical value. Flexible S/R Channels creates live data series that integrate with other analysis tools. Four curve-fitting methods—Quadratic, Quadratic-Linear, Weighted Linear, and Natural Cubic Spline—accommodate different market structures. The curved levels naturally lend themselves to breakout and reversion strategies—applications left to the trader's discretion. The open-source code invites experimentation and customization. 💡 THEORY AND CONCEPT 💡 Traders have long relied on horizontal levels and diagonal trendlines to define support and resistance. Linear tools assume constant slope—a property rarely exhibited by actual market movement. When momentum accelerates or decelerates, price trajectories curve rather than hold to fixed angles. The resulting structures—parabolic advances during expansion phases, arcing pullbacks during consolidation, rounded formations at reversal points—represent changes in the rate of change itself. Traditional drawing tools cannot accommodate this variable geometry without sacrificing mathematical precision.. Flexible S/R Channels extends familiar support and resistance concepts into curved space. The approach is simple: draw what you see. When the eye recognizes a curved boundary in price action, this indicator provides the means to define it precisely. Three anchor points per curve—an initial point, an intermediate point, and a recent point—are all that is required. The indicator fits a smooth mathematical curve through these points and extends it forward as a projection. This indicator represents a blend of human pattern recognition and algorithmic precision. Fully automated indicators make decisions without user input—efficient but detached from trader discretion. Manual drawing tools rely entirely on freehand skill—expressive but imprecise. Flexible S/R Channels occupies the middle ground. The trader identifies the curved structure; the algorithm renders it mathematically. The result is human insight expressed with computational accuracy—for traders who recognize curved structure in price action but lack precise tools to define it. This projection is not a prediction. It is a visual hypothesis—a structured way of asking "if this trajectory continues, where would price be?" The underlying assumption is simple: like Newton's first law of motion, a trajectory in motion tends to continue unless acted upon by an external force. Future price action validates or invalidates the projection, just as it does with any trendline or channel. TradingView offers an arc drawing tool for freehand curved lines, but these are purely visual—static pixels on a screen with no programmable value. Flexible S/R Channels bridges this gap. The fitted curves exist as data series that can generate alerts, trigger signals, and interact with other analysis tools. The visual drawing becomes operational structure. 🔁 CURVE METHODS 🔁 The indicator offers four curve-calculation methods, each producing different shapes suited to different market structures: Quadratic — Fits a parabolic arc through the three anchor points. Best for smooth, continuous curves such as rounded tops and bottoms. It captures the natural "swing" of the market, assuming the momentum will maintain its current rate of acceleration or deceleration. Quadratic-Linear — Uses a parabolic curve through the anchor points, then transitions to a straight line after the final anchor. Useful when curved structure gives way to linear trend continuation. This is the "bridge" between a turning market and a steady, directed move, preventing the projection from curving back on itself when the price begins to run. Weighted Linear — Connects anchor points with straight line segments rather than a smooth curve. Suited for angular market structures with distinct inflection points. It treats the market as a series of rigid shifts, providing a clear "corridor" when the price is bouncing between sharp, diagonal levels. Natural Cubic Spline — Produces the smoothest curve by minimizing abrupt directional changes. Ideal for organic, flowing market movements. It acts as a flexible spine that adapts to complex transitions without the rigid constraints of a fixed geometric shape. Quadratic Fitting : A smooth, parabolic arc defines a curved resistance boundary. By fitting a mathematical path through three anchor points, the curve captures rounded structures and arcing price action that traditional linear trendlines fail to represent. Weighted Linear Fitting : This method produces an angular, segmented path by connecting anchor points with distinct linear slopes. Unlike the continuous smoothness of a quadratic arc, the weighted linear approach creates a more jointed geometry, allowing for a precise match to market structures that exhibit sharp, localized changes in trajectory. Natural Cubic Spline Fitting : This method creates a highly fluid, elastic curve that can accommodate complex price oscillations. In this instance, the curves define a narrowing range as support and resistance converge, highlighting the volatility compression that often precedes a significant breakout or breakdown from established structures. 🖱️ HOW IT WORKS 🖱️ 1️⃣ Initial Setup Unlike traditional indicators that calculate values automatically from price data, Flexible S/R Channels requires user-defined anchor points. This is intentional. The trader's eye is the pattern recognition engine—no algorithm can see the curved structure that experience and intuition reveal. The indicator waits for this input, then applies mathematical precision to render what the trader has identified. The Recognition of Natural Structure : Effective analysis begins when a curved rhythm becomes visible within price action that traditional trendlines cannot satisfy. Identifying the specific swing highs and swing lows that define these boundaries is the first step in organizing a chart. By isolating three key pivots for resistance and three for support, the underlying framework of the market's trajectory is established, providing the necessary coordinates to accurately map the path. Interactive Setup Workflow : Upon loading, the indicator prompts for the sequential selection of six points—three swing highs and three swing lows—to serve as the raw data for the calculation. While the chart remains blank during this initial phase, the curves generate instantly once the final anchor is confirmed. These points are not permanent; they appear as interactive grips that can be dragged in real time to refine the boundaries as the market structure evolves. The indicator prompts for six sequential selections—three for resistance, three for support. The first three selections define the resistance boundary; the final three define support. This sequential grouping is distinct from zigzag-style selection patterns. Within each group, clicking order is flexible—the algorithm automatically sorts points chronologically, allowing traders to select visually prominent pivots in whatever sequence feels natural. Structural Anchor Identification : Identifying three key swing highs and three key swing lows provides the foundation for the dual-curve geometry. These specific structural peaks and troughs serve as the coordinates for the mathematical models, ensuring that the resulting boundaries accurately reflect the underlying skeleton of the market action. 2️⃣ Interactive Adjustment After the initial setup, all six anchor points are fully adjustable: Points are automatically sorted chronologically regardless of selection order Grip handles appear at each anchor location Any point can be repositioned by clicking and dragging its grip handle The curves recalculate instantly as points are adjusted The algorithm produces a mathematically perfect curve based on the anchor points provided. If the result does not match the trader's vision, adjustments are immediate. This iterative refinement—see, adjust, refine—continues until the rendered curve represents what the trader sees in the price action. The user remains in control; the algorithm remains in service. Interactive Channel Boundaries : Six user-defined anchor points—three for resistance and three for support —establish a non-linear range that moves beyond the constraints of a flat, horizontal channel. This configuration captures the arcing trajectory of the market while showing price action respecting the curved boundaries in a classic reversion pattern. By manually positioning these anchors, a dynamic dimension is added to the chart that maintains structural integrity even as the price follows a rounded path. 🛠️ SETTINGS 🛠️ Customizable Visual Feedback : Beyond the core geometry, the visualization offers various user-defined settings to tailor the chart's information density. From identifying specific price targets to toggling structural labels, these options allow the trader to adjust the level of detail to suit their personal analysis style while maintaining a clear view of the non-linear boundaries. Configuration Options Curve Method — Select the curve-fitting algorithm: Quadratic, Quadratic-Linear, Weighted Linear, or Natural Cubic Spline. Projection Length — Number of bars to project the curves beyond current price action. Projections appear as dashed lines. Visual Settings Grip Size — Size of the draggable handles displayed at each anchor point. Set to zero to hide grips entirely. Line Width — Thickness of the support and resistance curves. Support Color / Resistance Color — Color settings for each curve. Show Info Table — Toggle display of the info table showing the current curve method in the chart corner. Advanced: Time/Price Coordinates The settings panel includes precise time and price values for each of the six anchor points, grouped under Resistance Time/Price and Support Time/Price. These values are populated automatically when points are selected on the chart. Adjusting anchor points by dragging the grip handles directly on the chart is faster and more intuitive. The time/price fields are available for situations requiring exact coordinate entry—such as aligning an anchor to a specific candle timestamp or a precise price level. These fields can be safely ignored unless fine-tuning is necessary. 🖼️ CHART EXAMPLES 🖼️ The Flexible S/R Channels indicator adapts to diverse market structures across multiple timeframes and instruments. Curved boundaries can define subtle momentum shifts in near-linear trends, dramatic reversals in rounding formations, or volatility compression as channels converge toward breakout points. The four curve-fitting methods accommodate different geometries—smooth parabolic arcs for continuous momentum changes, segmented linear paths for angular structures, and elastic splines for complex oscillations. Each anchor point adjustment instantly recalculates the curves, allowing iterative refinement until the rendered boundaries align with the trader's interpretation of market structure. Forward projections extend these mathematical relationships into future territory, providing visual context for hypothetical support and resistance levels if current trajectories persist. Subtle Curve Alignment : Even in structures that appear linear, subtle curvature allows the channel boundaries to breathe with the market’s internal momentum. By utilizing three anchor points rather than two, the channel adapts to the slight acceleration of a trend, providing a more precise fit than a rigid, straight corridor. Decelerating Momentum and Convergence : This classic rounding structure illustrates a transition where the initial wide oscillations between highs and lows begin to contract. As the boundaries converge, the curve captures the diminishing volatility and the shift in market energy, providing a clear visual representation of a trend losing its expansive momentum as it approaches a potential turning point. Organic Trend Modeling : In an accelerating uptrend, the Natural Cubic Spline provides a highly adaptable boundary that mirrors the organic flow of momentum. This non-traditional approach allows the channel to follow complex price pulses that a standard linear trendline would likely cut through, maintaining a precise fit even as the angle of the trend shifts over time. Non-Linear Projections : Unlike standard trendlines that converge at a fixed rate, curved projections adapt to the historical momentum of the move. This allows the indicator to map a dynamic squeeze, capturing the subtle nuances of how price action tightens toward an apex. It provides a more sophisticated view of future convergence points that traditional linear channels often fail to anticipate. The "Draw What You See" Philosophy : Market structures are rarely perfect, and this example highlights the indicator’s ability to map unconventional rhythms. Rather than forcing price into a predefined category, the tool remains flexible enough to define any structural path the trader identifies. If you can see a trend's trajectory, the indicator can provide the mathematical framework to support it. Comparative Projection Modeling : Using identical anchor points as above, this example demonstrates how selecting a different calculation method can alter the projected path. While the historical fit remains precise, the variation in the forward-looking trajectory allows traders to explore multiple mathematical interpretations of the same market structure, choosing the model that best aligns with the current volatility and trend behavior. Extended Timeframe Channel Definition : This multi-year perspective demonstrates the indicator's ability to define curved channel boundaries across extended timeframes spanning hundreds of bars and multiple market cycles. The resistance curve captures the rounded distribution of swing highs while the support curve follows the accelerating base formation, creating a non-linear channel that frames long-term structural trends more precisely than traditional parallel channels or static trendlines. Rounding Bottom Reversal and Channel Convergence : This example captures a classic rounding bottom formation—a reversal pattern that linear tools cannot adequately define. The Quadratic method produces a smooth parabolic arc through the resistance anchors, tracing the deceleration of the downtrend, the capitulation low, and the subsequent re-acceleration upward as a single continuous curve. The support boundary mirrors this momentum shift from below, creating a curved channel that narrows toward current price. This convergence represents structural compression—the boundaries tightening as volatility contracts and directional resolution approaches. Price action oscillates within these non-linear boundaries, demonstrating that channel behavior persists even when the geometry is curved rather than parallel. The projection extends both curves forward, mapping the hypothetical trajectory if the current momentum structure continues, providing visual context for potential breakout or breakdown levels as the channel reaches its apex. Built-in Precision vs. Algorithmic Power : While TradingView offers basic curve drawing tools (shown here as dashed lines), the Flexible S/R Channels indicator elevates this concept into a functional analytical framework. By converting manual observations into mathematical models, it moves beyond mere drawing to provide a data-driven structure that can be utilized for advanced technical analysis and future Pine Script trading logic. ⚙️ TECHNICAL DETAILS ⚙️ Curve Fitting vs. Overfitting: The term curve fitting often carries negative connotations in quantitative analysis due to its association with overfitting—the practice of adjusting a model until it perfectly matches historical data, producing an illusion of accuracy that fails when applied to new data. The application here is fundamentally different. Flexible S/R Channels does not optimize parameters to maximize historical fit; it constructs a mathematical curve through user-selected anchor points, then projects that curve into unknown territory. The curve is not fitted to price data—it is fitted to structural pivots identified by the trader. The projection represents a hypothesis about trajectory continuation, not a prediction derived from statistical optimization. Future price action validates or invalidates this hypothesis in real time, exactly as it does with any trendline or channel. The anchor points remain fixed unless manually adjusted, ensuring the curve does not adapt to new data retroactively. Non-Repainting Behavior: The indicator does not repaint historical bars. The mathematical coefficients that define each curve are calculated once—when the final anchor point is set—and stored as fixed values. These coefficients remain constant unless an anchor point is manually repositioned. The backfit polyline is drawn once using these coefficients, spanning the known range from the first to last anchor point. The plot() function applies the same coefficients to each subsequent bar, updating in real-time as new bars form but never altering previously plotted values. The projection polyline extends forward from the current bar using the same fixed coefficients, projecting a user-defined number of future bars (maximum 500). This projection redraws on each tick to maintain its position relative to the moving current bar, but the mathematical trajectory remains constant—only the starting point advances. The current bar's curve value will update tick-by-tick as price develops, which is standard real-time behavior, not repainting. Once a bar closes, all curve values on that bar are permanent. The hybrid architecture (backfit polyline for known history, plot() for unlimited real-time range, projection polyline for controlled forward extension) prevents overflow errors while maintaining non-repainting integrity across all components. 🗒️ NOTES 🗒️ The indicator renders curves based on any anchor points provided without validation. Unusual anchor placement produces mathematically accurate but potentially non-useful results. Adjustment is iterative—if the curve doesn't match expectations, reposition the anchors. Because anchor points are stored as specific time and price coordinates, a new instance of the indicator should be added when analyzing a different chart or timeframe. Grip handles can be hidden by setting Grip Size to zero in the settings. This is useful for clean chart screenshots or presentations where interactive elements are not needed. Projection length can be set to zero if forward-looking curves are not desired. The indicator will still render the backfit curves through the anchor points and continue plotting in real-time without the dotted projection extensions. Anchor points remain fixed at their selected time-price coordinates as new bars form. The curves extend forward automatically from these historical anchors, allowing observation of how projected trajectories align with developing price action. ⚠️ DISCLAIMER ⚠️ The Flexible S/R Channels indicator is a visual analysis tool designed to illustrate geometric market inertia and serve as a framework for understanding dynamic support and resistance. While the indicator generates structural channels and projected paths, no guarantee is made regarding the accuracy or profitability of these projections. Like all technical indicators, the curves and boundaries generated by this tool may appear to align with favorable trading opportunities in hindsight. However, these visualizations are not intended as standalone recommendations for trading decisions. This indicator is intended for educational and analytical purposes, complementing other tools and methods of market analysis. 🧠 BEYOND THE CODE 🧠 Flexible S/R Channels is part of a broader collection of tools designed to provide structured market analysis. This includes the Grid Bot Simulator , the Grid Bot Auto , the Grid Bot Parabolic , and the Gridbot Ping Pong . While each tool serves a distinct purpose, they all utilize dynamic anchor mechanics and non-linear boundaries to adapt to evolving market conditions. This indicator shares the same educational philosophy as the Fibonacci Time-Price Zones and the Fibonacci Geometry Series - providing frameworks for understanding market concepts through visualization and experimentation rather than black-box signals. The Flexible S/R Channels indicator, like other xxattaxx indicators , is designed to encourage both education and community engagement. Feedback and insights are invaluable to refining and enhancing this tool. We look forward to the creative applications, observations, and discussions this indicator inspires within the trading community.
Pine Script®指標
由xxattaxx提供
3
Power Hour Trendlines [LuxAlgo]The Power Hour Trendlines indicator is based on Power Hours detection, and includes up to three displayed trendlines derived from the closing prices of all the bars within the last user-selected Power Hours. Users can edit the time of Power Hours, choose how many sessions to take into account, enable or disable any trendlines, and change their colors. 🔶 USAGE The Power Hour is defined as the last hour of the trading session and is set by default from 3:00 p.m. to 4:00 p.m. New York time. During this period, volume and volatility enter the market. Traders using higher timeframes may use this period to enter or exit positions by placing MOC (Market on Close) orders. This tool works under the hypothesis that prices made during power hours (periods with high trading activity) are more relevant when used for the construction of trendlines. An initial trendline is fit using linear regression; prices from power hours located above this initial fit are used for the upper trendline, while the ones below the fit are used for the lower one. As with any trendline, traders can analyze the slope to determine the market's direction: Positive slope: The market is trending up. Negative slope: The market is trending down. No slope: The market is trending sideways. As we can see in the image, Nasdaq and Bitcoin are clearly in downtrends, gold is clearly in an uptrend, and the euro/U.S. dollar is in a sideways market over the last visible sessions. As you can see, the trend lines may or may not be parallel to each other. The wider the area, the more volatile the data. The narrower the area, the less volatile the data. Let's look at an example. In the image, the Dow30 and the euro/U.S. dollar have opposite behaviors. The volatility above the middle trendline is growing in the first case but shrinking in the second. In both cases, the volatility in the bottom area seems steady, so there are no big surprises there. Traders can adjust the number of sessions for calculations, making the tool ideal for analyzing price behavior over different time frames. As the image shows, we can clearly see how the market behaves over different time periods. XLY has been moving down over the last 10, 20, and 40 sessions, with a steeper decline over shorter periods. However, it has been moving sideways over the last 70 sessions. One of the main uses of trendlines is to provide key support and resistance. In the image, SPY is shown with trendlines over the last 20 sessions. These lines provide excellent reference points for trading and observing price behavior in those areas, such as whether prices are accepted or rejected, which may trigger a response from other traders. 🔹 Not Allowed Timeframes For obvious reasons, timeframes larger than 1H are not allowed. The Power Hour is defined as the last hour of the trading session. The tool will display a warning message if the timeframe is longer than 60 minutes. 🔶 SETTINGS Power Hour (NY Time): Choose a custom Power Hour in New York time Sessions Memory: Select how many Power Hours to take into account for calculations. 🔹 Style Top: Enable or disable the top line and choose the line and background colors. Middle: Enable or disable the middle line and choose the line color. Bottom: Enable or disable the bottom line and choose the line and background colors. Background: Enable or disable the background color for top and bottom lines.
Pine Script®指標
由LuxAlgo提供
2
ATR Bands (MA Distance)ATR Bands (MA Distance) plots volatility-based bands at a multiple of ATR away from a selected moving average. Unlike percentage envelopes or standard deviation bands, this indicator measures distance from the moving average using ATR, representing the market’s normal “breathing range” rather than statistical probability. Key Features The center line is a selectable moving average (EMA, SMA, RMA/Wilder, or WMA). Upper and lower bands are calculated as: Moving Average ± ATR × Multiplier Band width automatically adapts to changing market volatility. Designed for consistent use across different markets and timeframes without parameter re-optimization. Non-repainting: all values are calculated only from confirmed historical bars. Intended Use ATR Bands (MA Distance) is best used as a context and preparation tool , not as a direct entry or exit signal. Typical use cases include: Identifying areas where price is extended relative to its recent volatility. Visualizing normal vs. stretched price distance from the moving average. Supporting range-based analysis or trade preparation when combined with other indicators (e.g., oscillators). Important Notes / How NOT to Use This indicator does NOT generate buy or sell signals by itself . Touching or crossing a band does not imply an automatic reversal. In strong trending markets, price may stay outside the bands for extended periods. ATR Bands should not be interpreted as overbought/oversold levels on their own. This indicator does NOT repaint. Once a bar is closed, its values will not change. For best results: Use ATR Bands as a preparation zone, then wait for confirmation from your own entry logic. Disable or ignore band-based mean-reversion ideas during strong trend conditions. Concept Summary (Short) ATR Bands (MA Distance) visualize how far price has moved from its moving average in terms of volatility, without repainting and without relying on percentage deviation or statistical assumptions. Optional Short Description (Preview) Volatility-based, non-repainting ATR bands plotted at a distance from a moving average. Designed for market context and trade preparation — not standalone signals.
Pine Script®指標
由SunnySpots提供
HMA 34 Dual-Fractal Projections - VdubusVdubus MacD Divergence Trend Break Signal Generator :Here:- HMA 18 Dual-Fractal Projections Overview The HMA 18 Dual-Fractal Projections is a technical analysis tool designed to identify market structure and potential breakout patterns by analyzing the pivots of a Hull Moving Average (HMA). Unlike standard trendline indicators that struggle to balance "big picture" trends with immediate price action, this indicator utilizes a Dual-Fractal approach. It simultaneously calculates two separate timelines—Macro and Micro—to visualize both the dominant channel and the developing chart patterns (such as wedges or triangles) in real-time. Visual Guide The indicator plots three key elements on the main chart: The HMA Line (Blue): A smooth, fast-acting moving average (default length 34) that serves as the baseline for all calculations. Macro Structure (Solid, Thick Lines): Red (Solid): Major Resistance. Green (Solid): Major Support. Purpose: Identifies the long-term trend channel. These lines react slowly and filter out noise. Micro Structure (Dashed, Thin Lines): Red (Dashed): Immediate Resistance. Green (Dashed): Immediate Support. Purpose: Identifies the short-term market structure. These lines react quickly to show forming wedges, triangles, or flags. How It Works The indicator applies a "Pivot High/Low" algorithm directly to the HMA data rather than raw price data. This filters out candle wicks and volatility, ensuring lines are drawn based on established momentum shifts. Layer 1 (Macro): Uses a large "Lookback" period (default 44 bars) to find significant peaks and valleys. It connects the most recent major pivot to the previous one, projecting a line forward to show where the major trend channel lies. Layer 2 (Micro): Uses a small "Lookback" period (default 10 bars) to find local peaks and valleys. This allows you to see how price is behaving within the larger channel. Settings & Configuration HMA Settings HMA Length: The length of the Hull Moving Average. Default: 34 (Matches the "visually pleasing" setting from recent testing). Note: Set to 18 for a faster, more reactive baseline (scalping). Layer 1: Macro (Big Channel) Macro Lookback: Determines how many bars must pass before a peak is confirmed. Default: 44. High values find broad, established channels. Max Macro Lines: How many historical lines to keep on the chart. Default: 1 (Keeps the chart clean, showing only the current structure). Extend Macro Lines: Projects the lines infinitely to the right to predict future support/resistance zones. Layer 2: Micro (Current Pattern) Micro Lookback: A lower sensitivity setting to catch immediate structure. Default: 10. Low values will pinpoint the exact boundaries of small wedges or flags forming right now. Trading Strategy & Interpretation 1. The "Squeeze" (Wedge Identification) This is the primary use case. Look for scenarios where the Macro Lines (Solid) are wide/parallel, but the Micro Lines (Dashed) are rapidly converging (pointing towards each other). This indicates that while the main trend is intact, momentum is compressing. A breakout is imminent where the dashed lines intersect. 2. Trend Channels When both Solid and Dashed lines are roughly parallel and sloping in the same direction, the trend is healthy and strong. Price is respecting both the short-term and long-term momentum. 3. Divergence / Early Reversal Warning If the Macro Line is sloping UP, but the Micro Line starts sloping DOWN (crossing inside), it indicates a loss of momentum and a potential reversal before the price actually breaks the major trendline. =========================================================================== 2. Micro/Macro Cross Alert A new input, Enable Micro/Macro Cross Alert, has been added under the "Alerts & Features" section. This alert condition is triggered when the momentum of the Micro Structure exceeds the momentum of the Macro Structure, which is a high-probability signal for a breakout: Bullish Alert: The Micro High (dashed red line) crosses above the Macro High (solid red line). Bearish Alert: The Micro Low (dashed green line) crosses below the Macro Low (solid green line). To set up the actual alert on your chart: Right-click on the chart. Select "Add alert on HMA 34 Dual-Fractal Projections". In the Condition dropdown, select the indicator's name. For the main alert criteria, choose "Any alert()". Select your preferred alert actions (e.g., notification, email).
Pine Script®指標
由vdubus提供
1
Kernel Channel [BackQuant]Kernel Channel A non-parametric, kernel-weighted trend channel that adapts to local structure, smooths noise without lagging like moving averages, and highlights volatility compressions, expansions, and directional bias through a flexible choice of kernels, band types, and squeeze logic. What this is This indicator builds a full trend channel using kernel regression rather than classical averaging. Instead of a simple moving average or exponential weighting, the midline is computed as a kernel-weighted expectation of past values. This allows it to adapt to local shape, give more weight to nearby bars, and reduce distortion from outliers. You can think of it as a sliding local smoother where you define both the “window” of influence (Window Length) and the “locality strength” (Bandwidth). The result is a flexible midline with optional upper and lower bands derived from kernel-weighted ATR or kernel-weighted standard deviation, letting you visualize volatility in a structurally consistent way. Three plotting modes help demonstrate this difference: When the midline is shown alone, you get a smooth, adaptive baseline that behaves almost like a regression moving average, as shown in this view: When full channels are enabled, you see how standard deviation reacts to local structure with dynamically widening and tightening bands, a mode illustrated here: When ATR mode is chosen instead of StdDev, band width reflects breadth of movement rather than variance, creating a volatility-aware envelope like the example here: Why kernels Classical moving averages allocate fixed weights. Kernels let the user define weighting shape: Epanechnikov — emphasizes bars near the current bar, fades fast, stable and smooth. Triangular — linear decay, simple and responsive. Laplacian — exponential decay from the current point, sharper reactivity. Cosine — gentle periodic decay, balanced smoothness for trend filters. Using these in combination with a bandwidth parameter gives fine control over smoothness vs responsiveness. Smaller bandwidths give sharper local sensitivity, larger bandwidths give smoother curvature. How it works (core logic) The indicator computes three building blocks: 1) Kernel-weighted midline For every bar, a sliding window looks back Window Length bars. Each bar in this window receives a kernel weight depending on: its index distance from the present the chosen kernel shape the bandwidth parameter (locality) Weights form the denominator, weighted values form the numerator, and the resulting ratio is the kernel regression mean. This midline is the central trend. 2) Kernel-based width You choose one of two band types: Kernel ATR — ATR values are kernel-averaged, producing a smooth, volatility-based width that is not dependent on variance. Ideal for directional trend channels and regime separation. Kernel StdDev — local variance around the midline is computed through kernel weighting. This produces a true statistical envelope that narrows in quiet periods and widens in noisy areas. Width is scaled using Band Multiplier , controlling how far the envelope extends. 3) Upper and lower channels Provided midline and width exist, the channel edges are: Upper = midline + bandMult × width Lower = midline − bandMult × width These create smooth structures around price that adapt continuously. Plotting modes The indicator supports multiple visual styles depending on what you want to emphasize. When only the midline is displayed, you get a pure kernel trend: a smooth regression-like curve that reacts to local structure while filtering noise, demonstrated here: This provides a clean read on direction and slope. With full channels enabled, the behavior of the bands becomes visible. Standard deviation mode creates elastic boundaries that tighten during compressions and widen during turbulence, which you can see in the band-focused demonstration: This helps identify expansion events, volatility clusters, and breakouts. ATR mode shifts interpretation from statistical variance to raw movement amplitude. This makes channels less sensitive to outliers and more consistent across trend phases, as shown in this ATR variation example: This mode is particularly useful for breakout systems and bar-range regimes. Regime detection and bar coloring The slope of the midline defines directional bias: Up-slope → green Down-slope → red Flat → gray A secondary regime filter compares close to the channel: Trend Up Strong — close above upper band and midline rising. Trend Down Strong — close below lower band and midline falling. Trend Up Weak — close between midline and upper band with rising slope. Trend Down Weak — close between lower band and midline with falling slope. Compression mode — squeeze conditions. Bar coloring is optional and can be toggled for cleaner charts. Squeeze logic The indicator includes non-standard squeeze detection based on relative width , defined as: width / |midline| This gives a dimensionless measure of how “tight” or “loose” the channel is, normalized for trend level. A rolling window evaluates the percentile rank of current width relative to past behavior. If the width is in the lowest X% of its last N observations, the script flags a squeeze environment. This highlights compression regions that may precede breakouts or regime shifts. Deviation highlighting When using Kernel StdDev mode, you may enable deviation flags that highlight bars where price moves outside the channel: Above upper band → bullish momentum overextension Below lower band → bearish momentum overextension This is turned off in ATR mode because ATR widths do not represent distributional variance. Alerts included Kernel Channel Long — midline turns up. Kernel Channel Short — midline turns down. Price Crossed Midline — crossover or crossunder of the midline. Price Above Upper — early momentum expansion. Price Below Lower — downward volatility expansion. These help automate regime changes and breakout detection. How to use it Trend identification The midline acts as a bias filter. Rising midline means trend strength upward, falling midline means downward behavior. The channel width contextualizes confidence. Breakout anticipation Kernel StdDev compressions highlight areas where price is coiling. Breakouts often follow narrow relative width. ATR mode provides structural expansion cues that are smooth and robust. Mean reversion StdDev mode is suitable for fade setups. Moves to outer bands during low volatility often revert to the midline. Continuation logic If price breaks above the upper band while midline is rising, the indicator flags strong directional expansion. Same logic for breakdowns on the lower band. Volatility characterization Kernel ATR maps raw bar movements and is excellent for identifying regime shifts in markets where variance is unstable. Tuning guidance For smoother long-term trend tracking Larger window (150–300). Moderate bandwidth (1.0–2.0). Epanechnikov or Cosine kernel. ATR mode for stable envelopes. For swing trading / short-term structure Window length around 50–100. Bandwidth 0.6–1.2. Triangular for speed, Laplacian for sharper reactions. StdDev bands for precise volatility compression. For breakout systems Smaller bandwidth for sharp local detection. ATR mode for stable envelopes. Enable squeeze highlighting for identifying setups early. For mean-reversion systems Use StdDev bands. Moderate window length. Highlight deviations to locate overextended bars. Settings overview Kernel Settings Source Window Length Bandwidth Kernel Type (Epanechnikov, Triangular, Laplacian, Cosine) Channel Width Band Type (Kernel ATR or Kernel StdDev) Band Multiplier Visuals Show Bands Color Bars By Regime Highlight Squeeze Periods Highlight Deviation Lookback and Percentile settings Colors for uptrend, downtrend, squeeze, flat Trading applications Trend filtering — trade only in direction of the midline slope. Breakout confirmation — expansion outside the bands while slope agrees. Squeeze timing — compression periods often precede the next directional leg. Volatility-aware stops — ATR mode makes channel edges suitable for adaptive stop placement. Structural swing mapping — StdDev bands help locate midline pullbacks vs distributional extremes. Bias rotation — bar coloring highlights when regime shifts occur. Notes The Kernel Channel is not a signal generator by itself, but a structural map. It helps classify trend direction, volatility environment, distribution shape, and compression cycles. Combine it with your entry and exit framework, risk parameters, and higher-timeframe confirmation. It is designed to behave consistently across markets, to avoid the bluntness of classical averages, and to reveal subtle curvature in price that traditional channels miss. Adjust kernel type, bandwidth, and band source to match the noise profile of your instrument, then use squeeze logic and deviation highlighting to guide timing.
Pine Script®指標
由BackQuant提供
MIG and MC 发布简介（中文） MIG and MC 指标帮助日内交易者快速识别微型缺口（Micro Gap）与微型通道（Micro Channel）。脚本支持过滤开盘跳空、合并连续缺口，并自动绘制 FPL（Fair Price Line）延伸线，既可追踪缺口是否被填补，也能直观标注潜在的趋势结构。为了确保跨周期一致性，最新版本对开盘前后和跨日场景做了专门处理 主要特性 - 自动检测并显示看涨/看跌微型缺口，支持按需合并连续缺口。 - 自定义是否忽略开盘缺口、缺口显示范围与 FPL 样式。 - FPL 触及后即停止延伸，辅助研判缺口是否真正回补。 - 内置强收盘与缺口过滤的微型通道识别，可选多种严格程度。 - 适用于 1/5/9 分钟等日内周期，也适用于更长周期。 Recommended English Description The MIG and MC indicator highlights Micro Gaps and Micro Channels so you can track true intraday imbalances without noise. It merges consecutive gaps, projects Fair Price Lines (FPL) that stop once touched, and offers a full intraday-ready opening-gap filter so your early bars stay clean. The latest update refines cross-session handling, giving reliable gap plots on 1-, 5-, and 9-minute charts as well as higher time frames. Key Features - Detects bullish and bearish micro gaps with optional gap merging. - Toggle opening-gap filters and configure look back, visibility, and FPL style. - FPL lines stop as soon as price revisits the gap, making gap closure obvious. - Micro Channel mode uses strong-close and gap filters to mark high-quality trend legs. - Consistent behavior across intraday and higher time frames.
Pine Script®指標
由WendellZhang提供
Auto Channel [SciQua]Auto Channel Purpose Auto Channel finds the single best parallel price channel from recent price action and keeps it updated in real time. It uses ZigZag pivots to build candidate channels, scores each candidate for quality, then plots the winner. When price closes outside the channel, the script flags a breakout and can fire alerts. How it works 1. ZigZag pivots The script uses TradingView’s TradingView/ZigZag/7 library to generate a stream of swing highs and lows based on a percentage reversal threshold and a leg depth. These pivots are the only points the channel logic evaluates, which keeps the search fast and focused on structure rather than noise. 2. Channel candidates From the most recent pivots, the script forms all combinations of two swing highs and two swing lows. It computes a slope for the high line and a slope for the low line and requires that they be nearly parallel within a user-defined tolerance. 3. Quality scoring and selection For every valid candidate, the script checks the recent pivot segments against the trial channel and computes: Inside ratio: fraction of tested pivots that sit fully inside the channel after applying the tolerance buffer. Violation sum: total magnitude of the breaches for any pivots outside the channel. Current width: distance between upper and lower lines at the current bar. The “best” channel is chosen by: 1. highest inside ratio 2. then widest current width 3. then smallest violation sum 4. Plot and projection The upper and lower lines are anchored to the chosen pivot pairs and extend to the left. The script also projects each line to the current bar to compute the live upper and lower channel prices. Those levels drive the breakout checks and alerts. 5. Breakouts and alerts A breakout is detected when the bar closes above the projected upper line or closes below the projected lower line, after applying the tolerance buffer. Triangle markers highlight fresh breakouts, and you can enable alert conditions to automate notification or strategy handoff. Inputs: ZigZag Price deviation for reversals (%) Default 0.2. Larger values produce fewer, larger swings. Smaller values produce more, smaller swings. Pivot legs Default 2. Controls the lookback depth ZigZag uses to confirm pivots. ZigZag Color Visual only. Tip: If you are not seeing a stable channel, increase the ZigZag percentage to reduce minor swings. Channel search Number of recent pivots to consider Default 12. Higher values search more history and try more channel combinations. Lower values make the search faster and more reactive. Max slope difference for parallel Default 0.0005. Maximum allowed difference between the upper and lower line slopes. Smaller values enforce stricter parallelism. Max price tolerance outside channel Default 0.0. A buffer added to the channel boundaries during validation and breakout checks. Use this to ignore tiny wicks that poke the lines. Minimum inside to outside pivots ratio for valid channel (0.00–1.00) Default 1.00. Require that at least this fraction of checked pivots lie inside the channel. For a more permissive fit, try 0.60 to 0.85. Styling Upper Line Color Lower Line Color Breakout Above Color Breakout Below Color Plots and visuals Upper channel line Lower channel line Triangle markers on the bar that first confirms a close outside the channel, above or below. Lines extend left from their pivot anchors. Projection to the current bar is used internally to test for breakouts and to set alerts. Alerts The script defines two alert conditions: Close Above Channel Triggers when the bar closes above the projected upper line plus tolerance. Close Below Channel Triggers when the bar closes below the projected lower line minus tolerance. Practical usage Trend channels In a steady trend, a high inside ratio with a moderate width often highlights the dominant channel. Consider trend entries near the lower line in an uptrend or near the upper line in a downtrend, with exits or stops beyond the opposite boundary. Breakout trades Combine the channel breakout alert with volume or a separate momentum filter. The tolerance input helps avoid false triggers from small wicks. Tuning for timeframe and symbol • Faster markets or lower timeframes usually benefit from a larger ZigZag percentage and a smaller pivot count. • Slower markets or higher timeframes can use more pivots and a tighter slope difference to enforce cleaner geometry. Notes and limitations Channels are derived from ZigZag pivots. If your ZigZag settings change, the detected channel will also change. The script plots only the single best channel at any time to keep the chart clean. Breakout markers appear on confirmed bars. For historical bars, markers appear only where a breakout would have been confirmed at that time. Lines extend left from their anchors. The script projects the lines internally to the current bar for checks and alerts. License and attribution License Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). Open source for educational and personal use only. Commercial use requires written permission. Attribution © 2025 SciQua — Joshua Danford Libraries Uses TradingView/ZigZag/7. Changelog v1.0 Initial release. Automatic parallel channel detection from ZigZag pivots, quality scoring, live plotting, and close-based breakout alerts. FAQ Why do I not see any channel sometimes? There may not be a valid pair of highs and lows that pass the slope, inside ratio, and tolerance checks. Loosen the constraints by increasing Max slope difference, lowering Minimum inside ratio, or increasing the ZigZag percentage. The channel looks too narrow or too wide? Adjust Number of recent pivots and Minimum inside ratio. A higher inside ratio tends to favor cleaner, sometimes wider channels. A lower ratio may admit narrower, more reactive channels. How can I reduce false breakout alerts? Increase Max price tolerance outside channel to ignore small wicks. Add a volume or momentum confirmation in your personal alert workflow. Thank you for using Auto Channel . Feedback and improvements are welcome.
Pine Script®指標
由JoshuaDanford提供
4
Step Channel Momentum Trend [ChartPrime]OVERVIEW Step Channel Momentum Trend is a momentum-based price filtering system that adapts to market structure using pivot levels and ATR volatility. It builds a dynamic channel around a stepwise midline derived from swing highs and lows. The system colors price candles based on whether price remains inside this channel (low momentum) or breaks out (strong directional flow). This allows traders to clearly distinguish ranging conditions from trending ones and take action accordingly. ⯁ STRUCTURAL MIDLNE (STEP CHANNEL CORE) The midline acts as the backbone of the trend system and is based on structure rather than smoothing. Calculated as the average of the most recent confirmed Pivot High and Pivot Low. The result is a step-like horizontal line that only updates when new pivot points are confirmed. This design avoids lag and makes the line "snap" to recent structural shifts. It reflects the equilibrium level between recent bullish and bearish control. This unique step logic creates clear regime shifts and prevents noise from distorting trend interpretation. ⯁ DYNAMIC VOLATILITY BANDS (ATR FILTERING) To detect momentum strength, the script constructs upper and lower bands using the ATR (Average True Range): The distance from the midline is determined by ATR × multiplier (default: 200-period ATR × 0.6). These bands adjust dynamically to volatility, expanding in high-ATR environments and contracting in calm markets. The area between upper and lower bands represents a neutral or ranging market state. Breakouts outside the bands are treated as significant momentum shifts. This filtering approach ensures that only meaningful breakouts are visually emphasized — not every candle fluctuation. ⯁ MOMENTUM-BASED CANDLE COLORING The system visually transforms price candles into momentum indicators: When price (hl2) is above the upper band, candles are green → bullish momentum. When price is below the lower band, candles are red → bearish momentum. When price is between the bands, candles are orange → low or no momentum (range). The candle body, wick, and border are all colored uniformly for visual clarity. This gives traders instant feedback on when momentum is expanding or fading — ideal for breakout, pullback, or trend-following strategies. ⯁ PIVOT-BASED SWING ANCHORS Each confirmed pivot is plotted as a label ⬥ directly on the chart: They also serve as potential manual entry zones, SL/TP anchors, or confirmation points. ⯁ MOMENTUM STATE LABEL To reinforce the current market mode, a live label is displayed at the most recent candle: Displays either: “ Momentum Up ” when price breaks above the upper band. “ Momentum Down ” when price breaks below the lower band. “ Range ” when price remains between the bands. Label color matches the candle color for quick identification. Automatically updates on each bar close. This helps discretionary traders filter trades based on market phase. USAGE Use the green/red zones to enter with momentum and ride trending moves. Use the orange zone to stay out or fade ranges. The step midline can act as a breakout base, pullback anchor, or bias reference. Combine with other indicators (e.g., order blocks, divergences, or volume) to build high-confluence systems. CONCLUSION Step Channel Momentum Trend gives traders a clean, adaptive framework for identifying trend direction, volatility-based breakouts, and ranging environments — all from structural logic and ATR responsiveness. Its stepwise midline provides clarity, while its dynamic color-coded candles make momentum shifts impossible to miss. Whether you’re scalping intraday momentum or managing swing entries, this tool helps you trade with the market’s rhythm — not against it.
Pine Script®指標
由ChartPrime提供
16
Rolling VWAP Channel [LuxAlgo]The Rolling VWAP Channel indicator creates a channel by analyzing a large number of Volume Weighted Average Prices (VWAPs) and determining a Channel based on percentile linear interpolation throughout the VWAPs. 🔶 USAGE In this indicator, we have formed a Channel by first calculating multiple VWAPs, each with their respective anchor, then locating prices using "Percentile Linear Interpolation". Note: Percentile Linear Interpolation locates the price point at which a specified percentage of VWAPs fall below it. For example, a percentile of 50% would mean that 50% of the VWAP values fall below this price. This method of analysis is important since the VWAPs are not often evenly distributed; therefore, we are able to draw importance to different levels by analyzing in percentiles. When visualized, there is typically clustering of the VWAP values, which occurs at any given time, as seen below. The channel can be tailored to each individual, with full control of each percentile represented in the channel. That being said, a general concept is that these clustered areas are clear results of sideways price action, which would lead us to believe that after interactions at these levels, we should expect to see a directional decision made by the market closely after. 🔶 DETAILS The Rolling VWAP calculation calculates a user-specified number of VWAPs (up to 500), each anchored to a unique starting point in the chart based on the start of a new timeframe. Each new timeframe that occurs causes a new VWAP to initialize. When the total number of desired VWAPs is reached, the oldest VWAP is removed and re-initialized, anchored to the current bar. Hence, the name " Rolling " VWAPs This method allows us to automatically generate and manage large amounts of VWAPs without the need for user interaction. After we have generated these VWAPs, we are able to run analyses on their returned values, such as the "Percentile Linear Interpolation" mentioned in the section above. 🔶 SETTINGS Anchor Period: Choose which time period to use as the anchor point to initialize new VWAPs from. VWAP Source: Choose the source for your VWAPs to calculate. VWAP Amount: Sets the number of VWAPs to use. After this amount is on the chart, the oldest will be rolled. 🔹 Channel Lines Toggle: Enable the associated VWAP Channel percentile line. Percentile: Adjust each line's percentile independently for your needs. Width: Adjust the width of the associated percentile line. 🔹 Calculation Calculated Bars: Tells the indicator how many bars to calculate on, for faster calculations with less history, use a lower value. Setting this to 0 will remove the bar constraint.
Pine Script®指標
由LuxAlgo提供
6