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標準偏差 (ボラティリティ)

V-AEMA VMR [LB]Concept The V-AEMA VMR (Volume-Adaptive Exponential Moving Average with Volatility-Modulated Regime) is a hybrid trend-following indicator that combines an EMA baseline with a volatility-based drift component. It produces a dynamic core line whose colour reflects the trend regime, surrounded by two levels of adaptive bands that expand or contract based on volume intensity. The indicator generates directional entry signals when price breaks the first band in the direction of the trend, and projects take-profit zones when price fully exits both bands. Mathematical Foundation The core line (Hybrid Line) is a weighted blend of a standard EMA and a volatility-shifted version of that same EMA : HybridLine = EMA * W + (EMA + Drift) * (1 - W) where the drift is derived from the Z-Score of price relative to the EMA, scaled by ATR : Drift = Z_Score * ATR * 0.35 Z_Score = (Price - EMA) / StdDev(Price, L_vola) Band width starts from a base volatility measure combining standard deviation and ATR : BaseWidth = StdDev * 0.65 + ATR * 0.35 This base is then adjusted by a volume ratio and user-defined multipliers : UpperWidth = BaseWidth * (BaseUpMult + (VolRatio - 1) * VolImpactUp) LowerWidth = BaseWidth * (BaseDnMult + (VolRatio - 1) * VolImpactDn) where VolRatio = min(max(Volume / SMA(Volume, L_vol), 0.35), 2.50) . Two band levels are generated : Band 1 at HybridLine +/- Width, and Band 2 (extreme) at HybridLine +/- Width * 1.55 (upper) / 1.40 (lower). What Problem Does It Solve ? Conventional envelope indicators (Bollinger Bands, Keltner Channels) apply fixed multipliers to a single volatility metric and ignore volume dynamics. The V-AEMA VMR adapts its band width to both volatility and volume surges, producing wider bands during high-participation moves and narrower bands during quiet periods. The hybrid core line reduces pure EMA lag by incorporating a volatility offset, while the dual-band structure filters signals by strength : a break of Band 1 triggers an entry, while a break of Band 2 confirms an explosive move and projects a take-profit zone. How To Interpret Core line colour – cyan/green indicates the hybrid line is rising (bull regime) ; magenta/red indicates it is falling (bear regime). Cloud and bands – the area between Band 1 and Band 2 forms a halo that thickens when volume expands. Narrow bands suggest low conviction or consolidation. Entry signals – a triangle appears below the bar when price crosses above Upper Band 1 while the hybrid line is rising (long). A triangle appears above the bar when price crosses below Lower Band 1 while the hybrid line is falling (short). These signals are confirmed by the trend direction. Take-profit zones – when the entire bar (high and low for shorts, low and high for longs) clears the extreme band (Band 2) in the direction of the signal, a coloured box is projected forward. The box represents a potential target zone based on the breakout amplitude and ATR, scaled by the TP Factor. Info panel – displays the current regime (BULL/BEAR), the volume ratio (values above 1.0 indicate above-average participation), and the current upper/lower deviation values in price units. Parameters EMA Length – period of the base exponential moving average (default 55). Volatility Length – period for the standard deviation used in the Z-Score calculation (default 34). Volume Length – period for the volume moving average used in the volume ratio (default 34). EMA Weight – blend ratio between the pure EMA and the volatility-drifted version. Higher values produce a smoother line ; lower values make it more reactive to volatility (default 0.80). Upper Base Deviation – core multiplier for the upper band width before volume adjustment (default 1.55). Lower Base Deviation – core multiplier for the lower band width before volume adjustment (default 1.05). Volume Impact Upper/Lower – sensitivity of the upper and lower bands to the volume ratio. Higher values make bands expand more aggressively when volume surges (default 0.95 / 0.55). ATR Length – period of the Average True Range used in band width and TP zone calculations (default 14). Show Cloud – toggles the filled areas between bands. Show Info Panel – toggles the real-time dashboard. Show Signals – toggles the entry triangles. Show TP Zones – toggles the take-profit projection boxes. TP Projection Bars – how many bars forward the TP zone extends. TP Factor – scales the height of the TP zone relative to the breakout range. Max Historical TP Zones – limits the number of TP boxes kept on the chart. Reference This indicator is a proprietary design synthesising concepts from adaptive moving averages (Kaufman, Ehlers), volatility envelopes (Bollinger, Keltner), and volume-weighted band models. It does not correspond to a single academic publication.
Pine Script® インジケーター
luis_barlierの投稿
3
Session VWAP + StdDev Bands [ChartPrime]🔶 OVERVIEW Session VWAP + StdDev Bands is a professional-grade anchored VWAP system that resets on a user-defined higher timeframe and builds a full standard deviation band structure around it. Unlike a rolling VWAP, this indicator recalculates from the first bar of each new session, giving you a clean, unbiased volume-weighted price reference that reflects exactly where the market has traded relative to volume since the session opened. The tool goes beyond a simple VWAP line by tracking how many times price has retested each individual band, using that retest count to dynamically intensify the color of each line — the more a level is tested, the more significant it becomes visually. Cumulative volume at each retest is also tracked and displayed, giving traders institutional-grade context directly on the chart. • Anchored VWAP with configurable higher timeframe reset (Daily, Weekly, Monthly, etc.) • Three independent standard deviation band pairs (1σ, 2σ, 3σ) • Per-line retest counter with dynamic color intensity — more retests = brighter line • Cumulative volume tracking per band displayed in live edge labels • High/Low wick-based band touch signals with cooldown control • Clean session break with automatic label and state reset 🔶 CORE CONCEPT — ANCHORED VWAP WITH VOLUME-WEIGHTED STANDARD DEVIATION Standard VWAP indicators use session time as the anchor. This indicator uses a higher timeframe bar close as the reset trigger, giving you full control over the session definition: • Anchored Reset: When the selected higher timeframe (e.g. Weekly) closes a new bar, the VWAP and all standard deviation calculations reset from zero. This ensures the VWAP always reflects the current session's volume distribution. • True StdDev Bands: Bands are calculated using a volume-weighted variance formula — not ATR, not simple standard deviation. This means the bands expand and contract based on how dispersed price has been relative to volume, not just raw price movement. • Dynamic Color Intensity: Each of the seven lines (VWAP + 6 band lines) tracks its own retest count independently. As price crosses a line more times, its transparency decreases and the line becomes fully saturated — a visual heatmap of the most contested price levels in the session. 🔶 RETEST COUNTING & VOLUME TRACKING The intelligence of this indicator lives in its per-line memory system: Independent Counters: Every line — VWAP, 1σ Upper, 1σ Lower, 2σ Upper, 2σ Lower, 3σ Upper, 3σ Lower — has its own retest counter that increments on every close-based cross. Color Intensity Mapping: Each retest reduces the line's transparency by 10 points. A line with 0 retests starts at 100% transparent (invisible). After 10 retests it reaches full opacity. This creates a natural visual hierarchy where the most-tested levels stand out. Cumulative Volume: Every time a line is crossed, the bar's volume is added to that line's running total. The edge label displays both the retest count and the total volume that flowed through that level — e.g. "1σ↑ 4 (vol. 2.3M)". Session Reset: All counters, volumes, and labels reset cleanly at the start of each new session. 🔶 BAND TOUCH SIGNALS Signal shapes fire when price wicks into a band rather than waiting for a close-based cross, making them more responsive to intrabar reactions at key levels: Bull Signal (Blue Diamond): The bar's low drops to or below a band line while the previous bar's low was above it — a wick touch from above, indicating potential support reaction. Bear Signal (Orange Diamond): The bar's high reaches or exceeds a band line while the previous bar's high was below it — a wick touch from below, indicating potential resistance reaction. Cooldown Filter: A configurable cooldown (default 20 bars) prevents signal clusters at the same level. Once a signal fires, the same direction cannot fire again until the cooldown expires. 🔶 LIVE EDGE LABELS Each band line carries a floating label anchored to the right edge of the chart that updates every bar: Labels display the band name, retest count, and cumulative volume in a compact single-line format. Label text color matches the line's current dynamic color — as the line intensifies, the label text intensifies with it. Labels reset and reposition automatically on each new session, always staying aligned with the current band price level. Label size is fully configurable from Tiny to Huge to suit any screen or timeframe. 🔶 HOW TO USE Identifying Key Levels: Watch which bands accumulate the most retests during a session. A 1σ band with 6+ retests and high cumulative volume is a high-conviction support or resistance zone — treat it like a volume node. Trend Bias: Price consistently closing above VWAP signals bullish session bias. Price consistently closing below signals bearish bias. Use the VWAP retest count to gauge how contested the mean is. Breakout Confirmation: When price breaks through a 2σ or 3σ band with a strong close, the band color will begin to intensify on subsequent retests. A bright outer band that holds as support after a breakout is a high-probability continuation signal. Fading Extremes: Bear signals at 2σ or 3σ upper bands and bull signals at 2σ or 3σ lower bands are mean-reversion opportunities, especially when cumulative volume at those levels is low (few retests, thin volume). Timeframe Selection: Use Weekly reset on daily charts for swing trading context. Use Daily reset on intraday charts for intraday VWAP analysis. Use Monthly reset on daily or weekly charts for macro-level value area mapping. 🔶 CONCLUSION Session VWAP + StdDev Bands turns a standard VWAP into a living, session-aware price map. By combining anchored volume-weighted calculations with per-line retest memory and cumulative volume tracking, it gives traders a clear picture of where the market has spent the most energy — and which levels are likely to matter most as the session develops.
Pine Script® インジケーター
ChartPrimeの投稿
Orion Regression Field [JOAT]Orion Regression Field Introduction Orion Regression Field builds a weighted regression valuation field with standard error bands, curvature options, compression detection, and reprice signals. This open-source indicator is designed as a context tool, not a standalone trading system. It focuses on explaining the current market state with restrained visuals and confirmed-bar logic where signals are used. Core Concepts 1. Weighted Regression Recent bars can receive more influence while still preserving a full model window. 2. Standard Error Bands Inner and outer bands show statistical distance from the modeled path. 3. Curvature and Confidence Optional curvature and R2-style confidence control when the field is considered reliable. 4. Pinch and Reprice Compression and outer-band reactions create filtered reprice events. mid = weightedRegression(close, len); band = standardError * multiplier Features Weighted regression midline Inner and outer SEE bands Optional curvature Pinch shading and projection field Filtered reprice labels Input Parameters Regression window and projection bars Curvature toggle and weight floor Minimum R2 confidence Inner and outer band multipliers Pinch ratio and cooldown How to Use This Script Use the field as statistical fair-value context. Outer band interaction means stretch, not automatic reversal. Limitations The script uses historical OHLCV data and cannot know future prices. Signals and states can be late during fast reversals because confirmed-bar logic is used to reduce repainting. Model outputs should be interpreted with market context, risk controls, and independent analysis. No visual state should be treated as a certain trade outcome. Originality Statement Orion is original in combining weighted regression, curvature, standard error fields, compression context, and filtered reprice logic. Disclaimer This indicator is provided for educational and informational purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any financial instrument. All calculations are derived from historical market data and may produce inaccurate readings in some market conditions. No indicator can predict future market behavior. Use proper risk management and independent judgment. -Made with passion by jackofalltrades
Pine Script® インジケーター
officialjackofalltradesの投稿
Sigma Structure [RWCS]What it is: Sigma Structure is a confluence-based trading indicator that unifies three distinct analytical layers into a single, cohesive view: a Z-Score oscillator measuring price deviation from its 20 EMA, a normalized MACD histogram for momentum context, and an Order Block detection engine that identifies structural demand and supply zones directly on the price chart. The result is an indicator that tells you not just when price is statistically extended, but where that extension is occurring relative to meaningful price structure — giving every signal a location and every location a statistical weight. How it works: 1. Z-Score layer: Price is measured as the number of standard deviations it sits above or below its 20-period EMA. This produces an oscillator that reads consistently across any asset or timeframe — a reading of +2 on Bitcoin means the same thing structurally as +2 on the S&P or EURUSD. The line color intensifies from faded to full aqua as it moves above zero, and faded to full fuchsia below, so the degree of extension is immediately legible at a glance. Fixed bands at ±1, ±2, and ±3 sigma define the statistical landscape. 2. MACD layer: A standard MACD histogram is computed normally, then linearly scaled so its rolling peak aligns with the ±3σ band. No calculation is modified — only the display axis is shared with the Z-Score. This means crossovers, divergences, and momentum shifts read identically to a standard MACD, but now live in the same visual space as the bands, letting you see momentum and mean-reversion context simultaneously. 3. Order Block layer: The indicator scans for order blocks using a sequential candle method — a bearish candle followed by a configurable number of consecutive bullish candles (demand), or a bullish candle followed by consecutive bearish candles (supply). Detected zones are drawn directly on the price chart as shaded regions with solid top boundaries and dashed bottom boundaries, color-coded aqua for demand and fuchsia for supply. Zones extend rightward bar by bar and self-invalidate the moment price closes through them, so what you see on the chart is always live and relevant. 4. Confluence signals: Two signal types fire when the Z-Score and Order Block layers align. An OB Reversal label appears when price is inside an Order Block while the Z-Score is at or beyond ±2σ — the statistical extension and the structural level are confirming each other as a fade opportunity. An OB Continuation label appears when price pulls back into an Order Block and the Z-Score reclaims zero — the trend is reasserting after a mean-reversion dip into demand or supply. 5. Volatility divergence: A background highlight layer compares price's rolling highs and lows against the rolling highs and lows of realized volatility (standard deviation of log returns). When price makes a new low without a corresponding expansion in realized volatility, a bullish divergence is flagged. The inverse flags bearish divergence. These are not entry signals on their own — they indicate moments where price action and volatility are telling different stories and warrant closer attention. Possible ways to use it: 1. Reversal setups: When the Z-Score reaches ±2σ or beyond and price simultaneously tags an active Order Block zone, the statistical extension and structural level are aligned. The OB Reversal label marks these bars. Look for MACD histogram compression or a zero cross in the same window for additional confirmation before acting. 2. Trend continuation entries: In trending markets, price frequently pulls back into demand or supply zones and finds support exactly where it should. When the Z-Score crosses back through zero inside an active zone, the OB Continuation label fires — this is your structural retest with momentum confirmation. 3. Divergence as a filter: The volatility divergence highlights flag potential exhaustion in price moves that lack volatility confirmation. Use these as a reason to tighten risk or wait for the OB/Z-Score confluence before entering, rather than chasing the move. 4. EMA trend bias: The fast and slow EMA overlay on the price chart provides a quick structural read. Aligning your OB Reversal or Continuation signals in the direction of the EMA cross adds a higher-timeframe trend filter without requiring a second indicator. 5. Alert-driven scanning: Three configurable alerts cover the ±2σ Trade Zone cross, OB Reversal confluence, and OB Continuation setup. Set these across a watchlist to surface actionable conditions without manual chart monitoring. Settings guide: 1. EMA / Std Dev Length: Both default to 20, matching a standard Bollinger Band configuration. Increase for smoother, slower signals on higher timeframes. 2. MACD Norm Lookback: Controls how far back the indicator looks to find the MACD histogram's peak for scaling. Higher values produce more stable scaling; lower values make the histogram more reactive to recent momentum. 3. Sequential Candles for OB: The number of consecutive candles required after the origin candle to confirm a block. Higher values produce fewer, higher-quality zones. 4. Max Active Zones: How many demand and supply zones can coexist on each side. Older zones are removed when the limit is reached. 5. Divergence Lookback: The rolling window for comparing price extremes against volatility extremes. Shorter values produce more frequent signals; longer values are more selective. Disclaimer: This indicator is published for educational and informational purposes only. Nothing presented here constitutes financial advice, a solicitation, or a recommendation to buy or sell any financial instrument. All trading involves risk, including the possible loss of principal. Past performance of any indicator or methodology is not indicative of future results. You are solely responsible for your own trading decisions. Always conduct your own research and consult a qualified financial professional before making any investment decisions.
Pine Script® インジケーター
RWCS_LTDの投稿
Mean Reversion Corridors [AGPro Series]Mean Reversion Corridors 🔹 Overview Mean Reversion Corridors is a volatility-adaptive deviation framework that maps how far price has stretched from a chosen fair-value center and classifies that stretch into two actionable zones. An inner corridor marks the early reversion band where price is meaningfully extended but not yet extreme; an outer corridor marks statistical exhaustion where continuation becomes less probable under normal conditions. A higher-timeframe trend filter separates controlled mean reversion from failure-continuation expansions, so traders can tell fading the edge from respecting a real break — all from a single clean overlay. 🔸 Unique Edge Most band systems (Bollinger, Keltner, ATR channels) offer a single width engine and a single band pair, leaving the trader to guess whether a tag is an exhaustion or a breakout. Mean Reversion Corridors is built around three ideas that work together: - A dual-engine width unit that linearly blends ATR (range-based) and Standard Deviation (dispersion-based) so the corridor is stable on both gap-heavy and low-dispersion regimes. - A two-layer corridor with distinct roles — inner for early stretch, outer for exhaustion — rendered as transparent zones you can read at a glance. - A regime-aware state machine that uses a higher-timeframe trend filter to reclassify outer tags as either reversion candidates or failure-continuation, tracked as explicit REV and FAIL states with a bounded confirmation window. 🧠 Methodology - Center Model — user choice of EMA, VWMA (volume-aware, default) or HMA (responsive), calculated on chart closes. - Width Unit — the current volatility unit is a linear blend: (1 − blend) × ATR + blend × StDev, protected against empty volatility periods. - Corridors — inner band at ±(width × inner multiplier), outer band at ±(width × outer multiplier). Stretch is reported in width-unit sigma. - Trend Filter — the same center model is evaluated on a higher-timeframe via request.security with lookahead off, and its slope is normalized by ATR so the "strong" threshold is volatility-aware, not symbol-specific. - State Machine — tracks the most recent outer-band extreme with a rolling 20-bar confirmation window. A reversion is confirmed only when price closes back inside the inner corridor and the trend filter is not strongly aligned with the original stretch. When the trend is strongly aligned, the outer break is reclassified as corridor failure (continuation). - All conditions evaluate on confirmed bars to avoid repainting behavior. ⚡ Signals & Alerts On-chart markers: - REV — reversion confirmed back through the inner band after an outer extreme, trend-filtered. - FAIL — corridor failure / trend-aligned continuation beyond the outer band. Six bar-close alert conditions: - Inner corridor entered — upside stretch - Inner corridor entered — downside stretch - Outer corridor hit — upside exhaustion - Outer corridor hit — downside exhaustion - Reversion confirmed - Corridor failure (continuation) ⚙️ Key Inputs - Center Model — EMA / VWMA / Hull - Center Length and Volatility Length — independent lookbacks - ATR ↔ StDev Blend — balance between range and dispersion engines - Inner Corridor Width and Outer Corridor Width — in volatility units - Trend Filter — enable, timeframe, length, strength threshold - Visuals — outer-only mode, center line, fills, edge tags, state labels, label size - Info Panel — show/hide, position (six options), font size - Alerts — individually toggleable for each of the six events 📖 How to Use - Start with the defaults on your main chart timeframe. The 34-period VWMA center, balanced blend and 1.0 / 2.2 inner/outer multipliers are chosen to work as a neutral starting point across liquid markets. - Inner corridor tags are early stretch cues — they flag that price is extended, not that a turn is due. Use them as context for setups, not as standalone signals. - Outer corridor tags with the trend filter neutral or opposed are the primary mean reversion setup; wait for a REV confirmation back inside the inner band before acting. - When FAIL appears, the stretch is trend-aligned; treat the outer band as continuation, not resistance. This is the signal to stop fading. - Use the Info Panel to read current state, reversion bias, trend regime and stretch magnitude in sigma at a glance. ⚠️ Limitations & Transparency - This is an analytical tool, not a trading strategy or financial advice. It does not predict future price. - Band-based classification assumes statistical behavior; during shocks, news events or illiquid sessions the width engine can lag. - The trend filter uses a higher-timeframe slope — it reacts slower than short-term momentum by design, which is the intended behavior. - Signals are evaluated on confirmed bars; intrabar crosses are not counted as events. - Past behavior of any indicator does not guarantee future results. Always apply your own risk management.
Pine Script® インジケーター
AGProLabsの投稿
Adaptive Velocity Oscillator [UAlgo]Adaptive Velocity Oscillator is a momentum and reversal framework built around the rate of change of an Adaptive Moving Average. Instead of using a fixed smoothing engine, the script first creates a Kaufman style adaptive average whose responsiveness changes according to market efficiency, then measures how fast that adaptive baseline is moving from one bar to the next. That velocity becomes the core oscillator. The main idea is straightforward. When the adaptive average starts accelerating upward, the oscillator rises above zero. When the adaptive average starts decelerating or turning lower, the oscillator falls below zero. This gives the user a direct view of directional pressure, but in a way that remains sensitive to changing market conditions because the underlying average itself is adaptive rather than static. To make the oscillator more practical, the script surrounds the velocity with dynamic filter bands derived from the standard deviation of the AMA series. These bands act like a contextual noise threshold. Small fluctuations inside the band are treated as less important, while stronger moves through the band can be interpreted as meaningful directional expansion or reversal activity. The script also supports two signal styles. Standard mode reacts to velocity transitions through the regular filter band. Extreme Reversal mode requires a deeper stretch into an expanded threshold before signaling a reversal style response. Optional price confirmation can then require bullish candle structure for buy signals and bearish candle structure for sell signals. A cooldown filter is added on top so the same type of signal cannot repeat too rapidly. The result is an oscillator that can be used for trend context, reversal spotting, and momentum transition analysis. It is especially useful for traders who want something more adaptive than a traditional moving average crossover or a simple rate of change calculation. 🔹 Features 🔸 Adaptive AMA Core The script uses an adaptive moving average whose smoothing constant changes according to the Efficiency Ratio. When price is moving efficiently in one direction, the average becomes more responsive. When price is noisy and directionless, the average becomes slower and more stable. 🔸 Velocity Based Oscillator The oscillator is not built from price directly. It is built from the bar to bar change of the adaptive average. This means the indicator measures how quickly the smoothed baseline itself is moving, which creates a cleaner momentum signal than raw price change alone. 🔸 Dynamic Filter Bands A statistical filter band is calculated from the standard deviation of the AMA series and then scaled by the user selected gamma value. This creates a noise threshold that expands and contracts with market conditions. 🔸 Standard and Extreme Reversal Modes In Standard mode, signals are generated when velocity crosses back through the regular filter threshold. In Extreme Reversal mode, the script requires a deeper stretch using an expanded band before a signal can trigger. This gives the user a choice between more responsive and more selective behavior. 🔸 Optional Price Confirmation Signals can require candle confirmation. Bullish signals may be restricted to bars where close is above open, and bearish signals may be restricted to bars where close is below open. This can help reduce signals that appear without supportive candle structure. 🔸 Cooldown Protection A built in cooldown logic prevents repeated same side signals from firing too close together. This helps reduce clustering during noisy or oscillatory phases. 🔸 Trend State From Zero Crosses The script also tracks velocity crosses through zero. These zero transitions can be interpreted as broader positive or negative momentum regime shifts. 🔸 Visual Context Through Color and Bands The histogram and line coloring change according to whether velocity is strongly positive, strongly negative, or neutral relative to the filter zone. This makes the oscillator easy to read at a glance. 🔸 Signal Labels and Alerts The indicator places buy and sell labels around qualifying signal bars and includes alert conditions for bullish signals, bearish signals, positive trend shifts, and negative trend shifts. 🔹 Calculations 1) AMA State Container type AMACalculator float value = na float value_prev = na float velocity = 0.0 float filterBand = 0.0 This object stores the internal state of the adaptive average engine. value holds the latest AMA value. value_prev stores the previous AMA value. velocity stores the bar to bar change of that AMA. filterBand stores the active dynamic threshold used later for signal filtering. So before any signal logic begins, the script already has a dedicated structure for the adaptive average, its momentum, and its statistical band. 2) Efficiency Ratio Calculation float change = math.abs(src - src ) float volatility = math.sum(math.abs(src - src ), lengthER) float ER = volatility == 0 ? 0 : change / volatility This is the first major step inside the AMA calculation. The script compares two quantities. change measures the net directional move from the current price back to the price lengthER bars ago. volatility measures the total path traveled during that same interval by summing all absolute bar to bar changes. The Efficiency Ratio is then: ER = change / volatility If price moved smoothly in one direction, net change will be large relative to total movement, and ER will be high. If price moved in a noisy back and forth way, total movement will be large but net change will be smaller, so ER will be low. This ratio tells the AMA how efficiently price has been moving, which directly controls how responsive the adaptive average should become. 3) Building the Adaptive Smoothing Constant float fastest = 2.0 / (fastLen + 1) float slowest = 2.0 / (slowLen + 1) float sc = math.pow(ER * (fastest - slowest) + slowest, 2) This block converts the Efficiency Ratio into a smoothing constant. First, the script computes the EMA style constants for the chosen fast and slow lengths. Then it blends between them using ER. When ER is high, the result moves closer to the fast setting. When ER is low, the result stays closer to the slow setting. Finally, the blended value is squared. This is a classic AMA technique that makes the adaptive response more sensitive to efficiency changes. So the smoothing constant automatically shifts between fast and slow behavior depending on market structure. 4) Updating the Adaptive Moving Average this.value_prev := this.value float prevAma = na(this.value_prev) ? src : this.value_prev this.value := prevAma + sc * (src - prevAma) This is the actual AMA update formula. The script first stores the previous AMA value. If no previous value exists yet, it uses the current source as the starting point. Then it updates the average using: new AMA = previous AMA + smoothing constant × (source minus previous AMA) So the adaptive average moves toward price, but the speed of that movement depends entirely on the previously calculated smoothing constant. When the market is efficient, the average reacts more quickly. When the market is noisy, it reacts more slowly. 5) Computing Velocity this.velocity := this.value - prevAma This single line is the core of the oscillator. Velocity here is simply the difference between the current AMA value and the previous AMA value. If the adaptive average is rising, velocity is positive. If the adaptive average is falling, velocity is negative. If the adaptive average is barely moving, velocity stays close to zero. So the oscillator is not measuring price change directly. It is measuring the momentum of the adaptive baseline itself. 6) Creating the Dynamic Filter Band float amaGlobalSeries = amaObj.value float sigma = ta.stdev(amaGlobalSeries, n) amaObj.filterBand := gamma * sigma After the AMA is calculated, the script builds a dynamic filter threshold from its standard deviation. sigma measures how much the AMA has been varying over the selected period. That value is then scaled by gamma to create the final filter band. So the band expands when the adaptive average becomes more variable and contracts when the average becomes quieter. This creates a context aware threshold that helps separate meaningful momentum movement from smaller background fluctuations. 7) Regular Band and Extreme Band float currentVelocity = amaObj.velocity float currentFilter = amaObj.filterBand float extremeBand = currentFilter * extMulti This block prepares the two signal thresholds used later. currentFilter is the normal band. extremeBand is a larger band created by multiplying the normal band by the user selected extreme multiplier. So the script supports two layers of selectivity: a regular threshold for Standard mode, and a deeper threshold for Extreme Reversal mode. 8) Raw Signal Logic bool rawBullSignal = sigMode == "Standard" ? ta.crossover(currentVelocity, -currentFilter) : ta.crossover(currentVelocity, -extremeBand) bool rawBearSignal = sigMode == "Standard" ? ta.crossunder(currentVelocity, currentFilter) : ta.crossunder(currentVelocity, extremeBand) This is the primary signal engine. In Standard mode: a bullish signal appears when velocity crosses upward through the negative regular filter level. a bearish signal appears when velocity crosses downward through the positive regular filter level. In Extreme Reversal mode: a bullish signal requires velocity to recover upward through the deeper negative extreme band. a bearish signal requires velocity to fall downward through the deeper positive extreme band. The important idea is that signals are not based on zero line crosses alone. They are based on velocity reentering from stretched territory. That makes the logic more reversal oriented than a simple trend flip model. 9) Optional Price Confirmation if reqPriceConf rawBullSignal := rawBullSignal and close > open rawBearSignal := rawBearSignal and close < open This block adds an extra candle structure filter. If price confirmation is enabled: bullish signals are only allowed when the bar closes above its open. bearish signals are only allowed when the bar closes below its open. This can help reduce signals that occur mathematically in the oscillator but do not have supportive price behavior on the actual candle. So the oscillator can be used either in pure indicator form or with a stricter candle aligned confirmation layer. 10) Cooldown Filter Logic method filterSignal(array arr, bool cond, int waitBars) => bool isValid = false if cond int lastSignalBar = arr.size() > 0 ? arr.get(0) : -waitBars - 1 if (bar_index - lastSignalBar) >= waitBars isValid := true arr.unshift(bar_index) if arr.size() > 2 arr.pop() isValid This method prevents signals from firing too frequently. When a new raw signal appears, the script looks at the most recent stored signal bar for that direction. If enough bars have passed since the previous signal, the new one is accepted. Otherwise it is ignored. The accepted signal bar index is then stored at the front of the array. Only a small recent history is kept. So this method acts as a timing gate that stops repetitive same side signals during choppy conditions. 11) Final Signal Construction var array lastBull = array.new() var array lastBear = array.new() bool finalBullSignal = lastBull.filterSignal(rawBullSignal, cooldown) bool finalBearSignal = lastBear.filterSignal(rawBearSignal, cooldown) This is where raw signals become final trade style signals. Bullish signals are passed through the bullish cooldown array. Bearish signals are passed through the bearish cooldown array. That means buy and sell signals are filtered independently. A recent bullish signal only blocks another bullish signal, and a recent bearish signal only blocks another bearish signal. So the script maintains clean directional spacing for both sides. 12) Histogram Coloring Logic color histColor = currentVelocity > currentFilter ? color.new(colorUp, 20) : currentVelocity < -currentFilter ? color.new(colorDn, 20) : currentVelocity > 0 ? color.new(colorUp, 70) : color.new(colorDn, 70) This block assigns visual meaning to oscillator strength. If velocity is above the upper regular filter, the histogram uses a stronger bullish color. If velocity is below the lower regular filter, it uses a stronger bearish color. If velocity is still positive but inside the filter region, it uses a softer bullish color. If velocity is negative but inside the filter region, it uses a softer bearish color. So the color logic tells the user both direction and intensity at the same time. 13) Drawing the Filter Bands plot(currentFilter, "Upper Filter Band", color=color.new(colorDn, 40), linewidth=1, style=plot.style_line) plot(-currentFilter, "Lower Filter Band", color=color.new(colorUp, 40), linewidth=1, style=plot.style_line) plot(extremeBand, "Upper Extreme Band", color=color.new(colorDn, 60), linewidth=1, style=plot.style_line, display=sigMode == "Extreme Reversal" ? display.all : display.none) plot(-extremeBand, "Lower Extreme Band", color=color.new(colorUp, 60), linewidth=1, style=plot.style_line, display=sigMode == "Extreme Reversal" ? display.all : display.none) These plots create the visual threshold system. The regular upper and lower filter bands are always shown. The wider extreme bands are shown only when Extreme Reversal mode is selected. This makes it easy to see whether current velocity is operating inside the neutral zone, beyond the regular band, or at deeper stretch levels. 14) Filling the Neutral Filter Region p_upper = plot(currentFilter, display=display.none) p_lower = plot(-currentFilter, display=display.none) fill(p_upper, p_lower, color=color.new(colorNeu, 95), title="Filter Band Fill") This block shades the area between the upper and lower regular filter bands. The filled zone visually represents the neutral or lower conviction region. When velocity remains inside this zone, momentum is more muted relative to recent adaptive average behavior. So the fill acts as a quick background cue for whether velocity is still inside normal fluctuation territory. 15) Plotting Velocity as Histogram and Line plot(currentVelocity, "AMA Velocity", color=histColor, style=plot.style_columns) plot(currentVelocity, "Velocity Line", color=histColor, linewidth=2) The same velocity value is drawn in two forms. The column plot gives a strong histogram style momentum read. The line plot overlays the same data as a smoother continuous path. Using both together makes the oscillator easier to read because the columns highlight amplitude while the line emphasizes turning points and transitions. 16) Signal Label Placement if finalBullSignal label.new(x=bar_index, y=math.min(0, currentVelocity) - math.abs(sigMode == "Extreme Reversal" ? extremeBand : currentFilter) - (math.abs(currentFilter) * 1.5), text="▲ BUY", color=color.new(color.white, 100), textcolor=colorUp, style=label.style_none, size=size.small) if finalBearSignal label.new(x=bar_index, y=math.max(0, currentVelocity) + math.abs(sigMode == "Extreme Reversal" ? extremeBand : currentFilter) + (math.abs(currentFilter) * 1.5), text="SELL ▼", color=color.new(color.white, 100), textcolor=colorDn, style=label.style_none, size=size.small) These blocks place the signal labels outside the oscillator body rather than directly on top of the bars. For bullish signals, the label is positioned below the relevant lower threshold area. For bearish signals, the label is positioned above the relevant upper threshold area. This helps keep the chart readable and visually separates the signal from the oscillator itself. 17) Alert Conditions alertcondition(finalBullSignal, "Buy Signal", "AMA Velocity Buy Signal") alertcondition(finalBearSignal, "Sell Signal", "AMA Velocity Sell Signal") bool posTrend = ta.crossover(currentVelocity, 0) bool negTrend = ta.crossunder(currentVelocity, 0) alertcondition(posTrend, "Positive Trend", "AMA Velocity crossed above zero") alertcondition(negTrend, "Negative Trend", "AMA Velocity crossed below zero") The script provides four alert types. The first two alert on final buy and sell signals after all filters and cooldown checks are applied. The second two alert when velocity crosses the zero line, which can be interpreted as broader momentum regime shifts. So the indicator supports both reversal style event monitoring and general trend transition monitoring.
Pine Script® インジケーター
UAlgoの投稿
LSMA SD | GForgeLSMA SD | GForge LSMA SD is a trend-following oscillator built for swing trading on higher timeframes. It generates rules-based long and exit signals by measuring where price sits within a statistically-defined volatility envelope anchored to a regression-based trend line. Core Calculation The basis line is a Least Squares Moving Average. Unlike a standard moving average which weights past prices, LSMA computes the mathematically optimal straight-line fit across a defined lookback window. This means the basis reflects the actual gradient of a trend — its slope tells you the rate and direction of price movement, not a smoothed echo of where price has been. A short EMA pass is applied to the raw LSMA output as a robustness measure, absorbing single-bar snap artifacts that occur when outlier candles enter or exit the regression window. This is not a smoothing aesthetic — it directly addresses a known fragility in raw LinReg endpoints. The default source is hlc3 — the average of high, low, and close — rather than close alone. This distributes the regression input across the full bar range, reducing sensitivity to end-of-session price mechanics such as stop runs and last-minute order flow that can distort the trend line without reflecting genuine directional movement. A Standard Deviation envelope is then constructed around the LSMA basis at a fixed multiplier. The band width is driven entirely by actual price volatility — it widens during high-volatility periods and tightens during quiet ones. There is no secondary adaptive scaling layer. This is intentional: additional dynamic scaling introduces a second noisy signal on top of the basis movement, which in practice degrades signal quality. The Oscillator The oscillator expresses where price currently sits within the SD bands on a 0–100 scale. A reading of 0 means price is at the lower band. A reading of 100 means price is at the upper band. A reading of 50 means price is sitting directly on the LSMA trend line itself — the neutral zone between the two signal thresholds represents price consolidating around the regression basis. Long signals fire when the oscillator crosses above the long threshold (default 74), meaning price has broken decisively into the upper band zone — a momentum confirmation in the direction of the trend, not a mean-reversion trigger. Exit and short signals fire when the oscillator crosses below the short threshold (default 33). This is a trend-continuation system, not a reversal indicator. Parameters The indicator is intentionally low-parameter. LSMA Length sets the regression window. StdDev Length sets the band width lookback and can differ from the LSMA length. StdDev Multiplier sets the fixed band scale. Endpoint Smoothing controls how aggressively window-edge artifacts are absorbed — setting it to 1 disables it entirely. Fewer parameters means less surface area for curve-fitting to historical data. Default settings are optimised for BTC on the 1D timeframe. Optimize thresholds and lengths for different assets and timeframes before use. Risk Warning This indicator is provided for informational and educational purposes only. Past performance, including any results visible on historical bars, does not guarantee or imply future returns. All trading involves risk. You should not make trading decisions based solely on any single indicator. Always apply independent analysis and appropriate risk management. Developed by GForge
Pine Script® インジケーター
GForgeの投稿
1
SmartVol SuperTrend | OquantOverview The SmartVol SuperTrend is an evolution of the traditional SuperTrend indicator. While the standard SuperTrend uses Average True Range (ATR) to calculate volatility bands, this version utilizes Volume-Weighted Standard Deviation (VWSD). By integrating volume into the volatility calculation, the indicator attempts to filter out "quiet" price movements and reacts more dynamically to price action supported by high trading activity. How It Works The script follows a multi-step process to define trend direction: Smoothing: It applies a 5-period EMA to the source price to reduce minor noise before calculating the bands. Volume-Weighted Volatility: Instead of a simple Standard Deviation, the script uses a custom volume standard deviation function. It measures the dispersion of price around its Volume Weighted Moving Average (VWMA), weighting each price point's contribution by the volume of that bar. Recursive Band Logic: Like the classic SuperTrend, the bands are "locked" in place. The lower band can only move up, and the upper band can only move down, until price closes on the opposite side, triggering a trend flip. Visuals: The script highlights the trend by coloring the candles and the space between the price and the trend line, providing a clear visual of the current market bias. Usefulness By using Volume-Weighted Standard Deviation, this indicator accounts for real market activity. Consequently, it expands its bands more aggressively during high-volume breakouts while dampening its reaction to price moves when volume fades, potentially offering more robust band levels anchored to true market participation. How to Use Trend Identification: When the line is green and below price, the trend is bullish. When the line is purple and above price, the trend is bearish. Factor Adjustment: Increase the Factor (default 1.8) to reduce sensitivity and avoid whipsaws in volatile markets. Decrease it for tighter tracking. EMA Length: Adjust the EMA length to change how much price smoothing is applied before the trend calculation. Note on Signals This indicator is designed for trend-following. Like all lagging indicators, it performs best in trending markets and may produce false signals during sideways consolidation. Settings Source: The price source used for calculations (default: Close). EMA Length: The lookback for the initial price smoothing (default: 5). VWSD Length: The period used to calculate the volume-weighted volatility (default: 30). Factor: The multiplier applied to the VWSD to determine the distance of the bands (default 1.8). ⚠️ Disclaimer: This indicator is intended for educational and informational purposes only. Trading involves risk, and past performance does not guarantee future results. Always test and evaluate indicators/strategies before applying them in live markets. Use at your own risk.
Pine Script® インジケーター
oquantの投稿
2
Open Interest Weighted Average Price [Arjo]Open Interest Weighted Average Price , or OIWAP , is a simple visual indicator that shows the average price of an asset based on changes in open interest . Instead of using trading volume like VWAP, this indicator gives more weight to prices where new futures contracts are being added or removed . This helps highlight the price levels where traders are actively building or closing positions. The indicator shows: A main line that represents the average price weighted by open interest changes. Upper and lower bands (standard deviation bands) that show how far the price moves away from this average. OIWAP is mainly useful for NSE futures markets , where open interest data is available. It helps traders visually understand where most market participation and positioning are taking place relative to price . Concepts: Applies statistical concepts, including weighted averaging and standard deviation, to open interest data Uses the absolute change in open interest as a weighting factor for each price point Creates a dynamic average that reflects where significant open interest activity has occurred during a given period Standard deviation bands are computed from this weighted average to show the statistical spread of prices around the OIWAP line Resets calculations based on user-selected time periods (daily, weekly, monthly, or session-based) Allows for fresh analysis at regular intervals Similar concept to volume-weighted average price (VWAP) indicators, but uses open interest changes as the weighting component Features: Weighted Average: Calculates a central line based on contract activity. Flexible Anchors: Allows users to choose the reset period for the calculation. Volatility Bands: Displays outer and mid-bands to visualize price stretches. Data Check: Built-in alerts notify you if Open Interest data is missing for a symbol. Visual Zones: Color-coded areas help identify price location at a glance. How To Use When you add the indicator to your chart, you will see: A main OIWAP line — the open-interest-weighted price level Mid-bands around the line (±0.5 standard deviations) Outer bands farther away (±2.0 standard deviations) Shaded background zones between these lines You can: Change the reset period to see how the average behaves over different time ranges Adjust the timeframe for open-interest data Turn mid-bands on or off Adjust colors and styles to improve readability Conclusion The OIWAP indicator serves as an educational tool for visualizing the relationship between price movements and open interest activity in futures markets Presents a weighted average price line along with statistical deviation bands Offers a structured framework for chart analysis Customizable settings allow users to adapt the display to their analytical preferences Maintains focus on visual interpretation rather than directional predictions Functions as a supplementary charting overlay that may complement other forms of technical and fundamental analysis Disclaimer This indicator is for educational and visual-analysis purposes only. It does not provide trading signals, financial advice, or guaranteed outcomes . You should perform your own research and consult a licensed financial professional when needed. All trading decisions are solely the responsibility of the user.
Pine Script® インジケーター
ARJO_2019の投稿
2
Uptrick: Dynamic Z-Score DivergenceIntroduction Uptrick: Dynamic Z-Score Divergence is an oscillator that combines multiple momentum sources within a Z-Score framework, allowing for the detection of statistically significant mean-reversion setups, directional shifts, and divergence signals. It integrates a multi-source normalized oscillator, a slope-based signal engine, structured divergence logic, a slope-adaptive EMA with dynamic bands, and a modular bar coloring system. This script is designed to help traders identify statistically stretched conditions, evolving trend dynamics, and classical divergence behavior using a unified statistical approach. Overview At its core, this script calculates the Z-Score of three momentum sources—RSI, Stochastic RSI, and MACD—using a user-defined lookback period. These are averaged and smoothed to form the main oscillator line. This normalized oscillator reflects how far short-term momentum deviates from its mean, highlighting statistically extreme areas. Signals are triggered when the oscillator reverses slope within defined inner zones, indicating a shift in direction while the signal remains in a statistically stretched state. These mean-reversion flips (referred to as TP signals) help identify turning points when price momentum begins to revert from extended zones. In addition, the script includes a divergence detection engine that compares oscillator pivot points with price pivot points. It confirms regular bullish and bearish divergence by validating spacing between pivots and visualizes both the oscillator-side and chart-side divergences clearly. A dynamic trend overlay system is included using a Slope Adaptive EMA (SA-EMA). This trend line becomes more responsive when Z-Score deviation increases, allowing the trend line to adapt to market conditions. It is paired with ATR-based bands that are slope-sensitive and selectively visible—offering context for dynamic support and resistance. The script includes configurable bar coloring logic, allowing users to color candles based on oscillator slope, last confirmed divergence, or the most recent signal of any type. A full alert system is also built-in for key signals. Originality The script is based on the well-known concept of Z-Score valuation, which is a standard statistical method for identifying how far a signal deviates from its mean. This foundation—normalizing momentum values such as RSI or MACD to measure relative strength or weakness—is not unique to this script and is widely used in quantitative analysis. What makes this implementation original is how it expands the Z-Score foundation into a fully featured, signal-producing system. First, it introduces a multi-source composite oscillator by combining three momentum inputs—RSI, Stochastic RSI, and MACD—into a unified Z-Score stream. Second, it builds on that stream with a directional slope logic that identifies turning points inside statistical zones. The most distinctive additions are the layered features placed on top of this normalized oscillator: A structured divergence detection engine that compares oscillator pivots with price pivots to validate regular bullish and bearish divergence using precise spacing and timing filters. A fully integrated slope-adaptive EMA overlay, where the smoothing dynamically adjusts based on real-time Z-Score movement of RSI, allowing the trend line to become more reactive during high-momentum environments and slower during consolidation. ATR-based dynamic bands that adapt to slope direction and offer real-time visual zones for support and resistance within trend structures. These features are not typically found in standard Z-Score indicators and collectively provide a unique approach that bridges statistical normalization, structure detection, and adaptive trend modeling within one script. Features Z-Score-based oscillator combining RSI, StochRSI, and MACD Configurable smoothing for stable composite signal output Buy/Sell TP signals based on slope flips in defined zones Background highlighting for extreme outer bands Inner and outer zones with fill logic for statistical context Pivot-based divergence detection (regular bullish/bearish) Divergence markers on oscillator and price chart Slope-Adaptive EMA (SA-EMA) with real-time adaptivity based on RSI Z-Score ATR-based upper and lower bands around the SA-EMA, visibility tied to slope direction Configurable bar coloring (oscillator slope, divergence, or most recent signal) Alerts for TP signals and confirmed divergences Optional fixed Y-axis scaling for consistent oscillator view The full setup mode can be seen below: Input Parameters General Settings Full Setup: Enables rendering of the full visual system (lines, bands, signals) Z-Score Lookback: Lookback period for normalization (mean and standard deviation) Main Line Smoothing: EMA length applied to the averaged Z-Score Slope Detection Index: Used to calculate directional flips for signal logic Enable Background Highlighting: Enables visual region coloring in overbought/oversold areas Force Visible Y-Axis Scale: Forces max/min bounds for a consistent oscillator range Divergence Settings Enable Divergence Detection: Toggles divergence logic Pivot Lookback Left / Right: Defines the structure of oscillator pivot points Minimum / Maximum Bars Between Pivots: Controls the allowed spacing range for divergence validation Bar Coloring Settings Bar Coloring Mode: ➜ Line Color: Colors bars based on oscillator slope ➜ Latest Confirmed Signal: Colors bars based on the most recent confirmed divergence ➜ Any Latest Signal: Colors based on the most recent signal (TP or divergence) SA-EMA Settings RSI Length: RSI period used to determine adaptivity Z-Score Length: Lookback for normalizing RSI in adaptive logic Base EMA Length: Base length for smoothing before adaptivity Adaptivity Intensity: Scales the smoothing responsiveness based on RSI deviation Slope Index: Determines slope direction for coloring and band logic Band ATR Length / Band Multiplier: Controls the width and responsiveness of the trend-following bands Alerts The script includes the following alert conditions: Buy Signal (TP reversal detected in oversold zone) Sell Signal (TP reversal detected in overbought zone) Confirmed Bullish Divergence (oscillator HL, price LL) Confirmed Bearish Divergence (oscillator LH, price HH) These alerts allow integration into automation systems or signal monitoring setups. Summary Uptrick: Dynamic Z-Score Divergence is a statistically grounded trading indicator that merges normalized multi-momentum analysis with real-time slope logic, divergence detection, and adaptive trend overlays. It helps traders identify mean-reversion conditions, divergence structures, and evolving trend zones using a modular system of statistical and structural tools. Its alert system, layered visuals, and flexible input design make it suitable for discretionary traders seeking to combine quantitative momentum logic with structural pattern recognition. Disclaimer This script is for educational and informational purposes only. No indicator can guarantee future performance, and trading involves risk. Always use risk management and test strategies in a simulated environment before deploying with live capital.
Pine Script® インジケーター
Uptrickの投稿
14
Smarter Money Volume Rejection Blocks [PhenLabs]📊 Smarter Money Volume Rejection Blocks – Institutional Rejection Zone Detection The Smarter Money Volume Rejection Blocks indicator combines high-volume analysis with statistical confidence intervals to identify where institutional traders are actively defending price levels through volume spikes and rejection patterns. 🔥 Core Methodology Volume Spike Detection analyzes when current volume exceeds moving average by configurable multipliers (1.0-5.0x) to identify institutional activity Rejection Candle Analysis uses dual-ratio system measuring wick percentage (30-90%) and maximum body ratio (10-60%) to confirm genuine rejections Statistical Confidence Channels create three-level zones (upper, center, lower) based on ATR or Standard Deviation calculations Smart Invalidation Logic automatically clears zones when price significantly breaches confidence levels to maintain relevance Dynamic Channel Projection extends confidence intervals forward up to 200 bars with customizable length Support Zone Identification detects bullish rejections where smart money absorbs selling pressure with high volume and strong lower wicks Resistance Zone Mapping identifies bearish rejections where institutions defend price levels with volume spikes and pronounced upper wicks Visual Information Dashboard displays real-time status table showing volume spike conditions and active support/resistance zones ⚙️ Technical Configuration Dual Confidence Interval Methods: Choose between ATR-Based for trend-following environments or StdDev-Based for range-bound statistical precision Volume Moving Average: Configurable period (default 20) for baseline volume comparison calculations Volume Spike Multiplier: Adjustable threshold from 1.0 to 5.0 times average volume to filter institutional activity Rejection Wick Percentage: Set minimum wick size from 30% to 90% of candle range for valid rejection detection Maximum Body Ratio: Configure body-to-range ratio from 10% to 60% to ensure genuine rejection structures Confidence Multiplier: Statistical multiplier (default 1.96) for 95% confidence interval calculations Channel Projection Length: Extend confidence zones forward from 10 to 200 bars for anticipatory analysis ATR Period: Customize Average True Range lookback from 5 to 50 bars for volatility-based calculations StdDev Period: Adjust Standard Deviation period from 10 to 100 bars for statistical precision 🎯 Real-World Trading Applications Identify high-probability support zones where institutional buyers have historically defended price with significant volume Map resistance levels where smart money sellers consistently reject higher prices with volume confirmation Combine with price action analysis to confirm breakout validity when price approaches confidence channel boundaries Use invalidation signals to exit positions when smart money zones are definitively breached Monitor the real-time dashboard to quickly assess current market structure and active rejection zones Adapt strategy based on calculation method: ATR for trending markets, StdDev for ranging conditions Set alerts on confidence level breaches to catch potential trend reversals or continuation patterns 📈 Visual Interpretation Guide Green Zones indicate bullish rejection blocks where buyers defended with high volume and lower wicks Red Zones indicate bearish rejection blocks where sellers defended with high volume and upper wicks Solid Center Lines represent the core rejection price level where maximum volume activity occurred Dashed Confidence Boundaries show upper and lower statistical limits based on volatility calculations Zone Opacity decreases as channels extend forward to indicate decreasing confidence over time Dashboard Color Coding provides instant visual feedback on active volume spike and zone conditions ⚠️ Important Considerations Volume-based indicators identify historical rejection zones but cannot predict future price action with certainty Market conditions change rapidly and institutional activity patterns evolve continuously High volume does not guarantee level defense as market structure can shift without warning Confidence intervals represent statistical probabilities, not guaranteed price boundaries
Pine Script® インジケーター
PhenLabsの投稿
Kernel Regression Bands SuiteMulti-Kernel Regression Bands A versatile indicator that applies kernel regression smoothing to price data, then dynamically calculates upper and lower bands using a wide variety of deviation methods. This tool is designed to help traders identify trend direction, volatility, and potential reversal zones with customizable visual styles. Key Features Multiple Kernel Types: Choose from 17+ kernel regression styles (Gaussian, Laplace, Epanechnikov, etc.) for smoothing. Flexible Band Calculation: Select from 12+ deviation types including Standard Deviation, Mean/Median Absolute Deviation, Exponential, True Range, Hull, Parabolic SAR, Quantile, and more. Adaptive Bands: Bands are calculated around the kernel regression line, with a user-defined multiplier. Signal Logic: Trend state is determined by crossovers/crossunders of price and bands, coloring the regression line and band fills accordingly. Custom Color Modes: Six unique color palettes for visual clarity and personal preference. Highly Customizable Inputs: Adjust kernel type, lookback, deviation method, band source, and more. How to Use Trend Identification: The regression line changes color based on the detected trend (up/down) Volatility Zones: Bands expand/contract with volatility, helping spot breakouts or mean-reversion opportunities. Visual Styling: Use color modes to match your chart theme or highlight specific market states. Credits: Kernel regression logic adapted from: ChartPrime | Multi-Kernel-Regression-ChartPrime (Link in the script) Disclaimer This script is for educational and informational purposes only. Not financial advice. Use at your own risk.
Pine Script® インジケーター
Galeenの投稿
1
Standard Deviation (fadi)The Standard Deviation indicator uses standard deviation to map out price movements. Standard deviation measures how much prices stray from their average—small values mean steady trends, large ones mean wild swings. Drawing from up to 20 years of data, it plots key levels using customizable Fibonacci lines tied to that standard deviation, giving traders a snapshot of typical price behavior. These levels align with a bell curve: about 68% of price moves stay within 1 standard deviation, 95% within roughly 2, and 99.7% within roughly 3. When prices break past the 1 StDev line, they’re outliers—only 32% of moves go that far. Prices often snap back to these lines or the average, though the reversal might not happen the same day. How Traders Use It If prices surge past the 1 StDev line, traders might wait for momentum to fade, then trade the pullback to that line or the average, setting a target and stop. If prices dip below, they might buy, anticipating a bounce—sometimes a day or two later. It’s a tool to spot overstretched prices likely to revert and/or measure the odds of continuation. Settings Higher Timeframe: Sets the Higher Timeframe to calculate the Standard Deviation for Show Levels for the Last X Days: Displays levels for the specified number of days. Based on X Period: Number of days to calculate standard deviation (e.g., 20 years ≈ 5,040 days). Larger periods smooth out daily level changes. Mirror Levels on the Other Side: Plots symmetric positive and negative levels around the average. Fibonacci Levels Settings: Defines which levels and line styles to show. With mirroring, negative values aren’t needed. Background Transparency: Turn on Background color derived from the level colors with the specified transparency Overrides: Lets advanced users input custom standard deviations for specific tickers (e.g., NQ1! at 0.01296).
Pine Script® インジケーター
fadizeidanの投稿
43
Volume Block Order AnalyzerCore Concept The Volume Block Order Analyzer is a sophisticated Pine Script strategy designed to detect and analyze institutional money flow through large block trades. It identifies unusually high volume candles and evaluates their directional bias to provide clear visual signals of potential market movements. How It Works: The Mathematical Model 1. Volume Anomaly Detection The strategy first identifies "block trades" using a statistical approach: ``` avgVolume = ta.sma(volume, lookbackPeriod) isHighVolume = volume > avgVolume * volumeThreshold ``` This means a candle must have volume exceeding the recent average by a user-defined multiplier (default 2.0x) to be considered a significant block trade. 2. Directional Impact Calculation For each block trade identified, its price action determines direction: - Bullish candle (close > open): Positive impact - Bearish candle (close < open): Negative impact The magnitude of impact is proportional to the volume size: ``` volumeWeight = volume / avgVolume // How many times larger than average blockImpact = (isBullish ? 1.0 : -1.0) * (volumeWeight / 10) ``` This creates a normalized impact score typically ranging from -1.0 to 1.0, scaled by dividing by 10 to prevent excessive values. 3. Cumulative Impact with Time Decay The key innovation is the cumulative impact calculation with decay: ``` cumulativeImpact := cumulativeImpact * impactDecay + blockImpact ``` This mathematical model has important properties: - Recent block trades have stronger influence than older ones - Impact gradually "fades" at rate determined by decay factor (default 0.95) - Sustained directional pressure accumulates over time - Opposing pressure gradually counteracts previous momentum Trading Logic Signal Generation The strategy generates trading signals based on momentum shifts in institutional order flow: 1. Long Entry Signal: When cumulative impact crosses from negative to positive ``` if ta.crossover(cumulativeImpact, 0) strategy.entry("Long", strategy.long) ``` *Logic: Institutional buying pressure has overcome selling pressure, indicating potential upward movement* 2. Short Entry Signal: When cumulative impact crosses from positive to negative ``` if ta.crossunder(cumulativeImpact, 0) strategy.entry("Short", strategy.short) ``` *Logic: Institutional selling pressure has overcome buying pressure, indicating potential downward movement* 3. Exit Logic: Positions are closed when the cumulative impact moves against the position ``` if cumulativeImpact < 0 strategy.close("Long") ``` *Logic: The original signal is no longer valid as institutional flow has reversed* Visual Interpretation System The strategy employs multiple visualization techniques: 1. Color Gradient Bar System: - Deep green: Strong buying pressure (impact > 0.5) - Light green: Moderate buying pressure (0.1 < impact ≤ 0.5) - Yellow-green: Mild buying pressure (0 < impact ≤ 0.1) - Yellow: Neutral (impact = 0) - Yellow-orange: Mild selling pressure (-0.1 < impact ≤ 0) - Orange: Moderate selling pressure (-0.5 < impact ≤ -0.1) - Red: Strong selling pressure (impact ≤ -0.5) 2. Dynamic Impact Line: - Plots the cumulative impact as a line - Line color shifts with impact value - Line movement shows momentum and trend strength 3. Block Trade Labels: - Marks significant block trades directly on the chart - Shows direction and volume amount - Helps identify key moments of institutional activity 4. Information Dashboard: - Current impact value and signal direction - Average volume benchmark - Count of significant block trades - Min/Max impact range Benefits and Use Cases This strategy provides several advantages: 1. Institutional Flow Detection: Identifies where large players are positioning themselves 2. Early Trend Identification: Often detects institutional accumulation/distribution before major price movements 3. Market Context Enhancement: Provides deeper insight than simple price action alone 4. Objective Decision Framework: Quantifies what might otherwise be subjective observations 5. Adaptive to Market Conditions: Works across different timeframes and instruments by using relative volume rather than absolute thresholds Customization Options The strategy allows users to fine-tune its behavior: - Volume Threshold: How unusual a volume spike must be to qualify - Lookback Period: How far back to measure average volume - Impact Decay Factor: How quickly older trades lose influence - Visual Settings: Labels and line width customization This sophisticated yet intuitive strategy provides traders with a window into institutional activity, helping identify potential trend changes before they become obvious in price action alone.
Pine Script® ストラテジー
ennoiDの投稿
12
Daily Standard Deviation (fadi)The Daily Standard Deviation indicator uses standard deviation to map out daily price movements. Standard deviation measures how much prices stray from their average—small values mean steady trends, large ones mean wild swings. Drawing from up to 20 years of data, it plots key levels using customizable Fibonacci lines tied to that standard deviation, giving traders a snapshot of typical price behavior. These levels align with a bell curve: about 68% of price moves stay within 1 standard deviation, 95% within roughly 2, and 99.7% within roughly 3. When prices break past the 1 StDev line, they’re outliers—only 32% of moves go that far. Prices often snap back to these lines or the average, though the reversal might not happen the same day. How Traders Use It If prices surge past the 1 StDev line, traders might wait for momentum to fade, then trade the pullback to that line or the average, setting a target and stop. If prices dip below, they might buy, anticipating a bounce—sometimes a day or two later. It’s a tool to spot overstretched prices likely to revert and/or measure the odds of continuation. Settings Open Hour: Sets the trading day’s start (default: 18:00 EST). Show Levels for the Last X Days: Displays levels for the specified number of days. Based on X Period: Number of days to calculate standard deviation (e.g., 20 years ≈ 5,040 days). Larger periods smooth out daily level changes. Mirror Levels on the Other Side: Plots symmetric positive and negative levels around the average. Fibonacci Levels Settings: Defines which levels and line styles to show. With mirroring, negative values aren’t needed. Overrides: Lets advanced users input custom standard deviations for specific tickers (e.g., NQ1! at 0.01296).
Pine Script® インジケーター
fadizeidanの投稿
23
Prime Bands [ChartPrime]The Prime Standard Deviation Bands indicator uses custom-calculated bands based on highest and lowest price values over specific period to analyze price volatility and trend direction. Traders can set the bands to 1, 2, or 3 standard deviations from a central base, providing a dynamic view of price behavior in relation to volatility. The indicator also includes color-coded trend signals, standard deviation labels, and mean reversion signals, offering insights into trend strength and potential reversal points. ⯁ KEY FEATURES AND HOW TO USE ⯌ Standard Deviation Bands : The indicator plots upper and lower bands based on standard deviation settings (1, 2, or 3 SDs) from a central base, allowing traders to visualize volatility and price extremes. These bands can be used to identify overbought and oversold conditions, as well as potential trend reversals. Example of 3-standard-deviation bands around price: ⯌ Dynamic Trend Indicator : The midline of the bands changes color based on trend direction. If the midline is rising, it turns green, indicating an uptrend. When the midline is falling, it turns orange, suggesting a downtrend. This color coding provides a quick visual reference to the current trend. Trend color examples for rising and falling midlines: ⯌ Standard Deviation Labels : At the end of the bands, the indicator displays labels with price levels for each standard deviation level (+3, 0, -3, etc.), helping traders quickly reference where price is relative to its statistical boundaries. Price labels at each standard deviation level on the chart: ⯌ Mean Reversion Signals : When price moves beyond the upper or lower bands and then reverts back inside, the indicator plots mean reversion signals with diamond icons. These signals indicate potential reversal points where the price may return to the mean after extreme moves. Example of mean reversion signals near bands: ⯌ Standard Deviation Scale on Chart : A visual scale on the right side of the chart shows the current price position in relation to the bands, expressed in standard deviations. This scale provides an at-a-glance view of how far price has deviated from the mean, helping traders assess risk and volatility. ⯁ USER INPUTS Length : Sets the number of bars used in the calculation of the bands. Standard Deviation Level : Allows selection of 1, 2, or 3 standard deviations for upper and lower bands. Colors : Customize colors for the uptrend and downtrend midline indicators. ⯁ CONCLUSION The Prime Standard Deviation Bands indicator provides a comprehensive view of price volatility and trend direction. Its customizable bands, trend coloring, and mean reversion signals allow traders to effectively gauge price behavior, identify extreme conditions, and make informed trading decisions based on statistical boundaries.
Pine Script® インジケーター
ChartPrimeの投稿
8
HMA Gaussian Volatility AdjustedOverview The "HMA Gaussian Volatility Adjusted" indicator introduces a unique combination of HMA smoothing with a Gaussian filter and two components to measure volatility (Average True Range (ATR) and Standard Deviation (SD)). This tool provides traders with a stable and accurate measure of price trends by integrating a Gaussian Filter smoothed using HMA with a customized calculation of volatility. This innovative approach allows for enhanced sensitivity to market fluctuations while filtering out short-term price noise. Technical Composition and Calculation The "HMA Gaussian Volatility Adjusted" indicator incorporates HMA smoothing and dynamic standard deviation calculations to build upon traditional volatility measures. HMA & Gaussian Smoothing: HMA Calculation (HMA_Length): The script applies a Hull Moving Average (HMA) to smooth the price data over a user-defined period, reducing noise and helping focus on broader market trends. Gaussian Filter Calculation (Length_Gaussian): The smoothed HMA data is further refined by putting it into a Gaussian filter to incorporate a normal distribution. Volatility Measurement: ATR Calculation (ATR_Length, ATR_Factor): The indicator incorporates the Average True Range (ATR) to measure market volatility. The user-defined ATR multiplier is applied to this value to calculate upper and lower trend bands around the Gaussian, providing a dynamic measure of potential price movement based on recent volatility. Standard Deviation Calculation (SD_Length): The script calculates the standard deviation of the price over a user-defined length, providing another layer of volatility measurement. The upper and lower standard deviation bands (SDD, SDU) act as additional indicators of price extremes. Momentum Calculation & Scoring When the indicator signals SHORT: Diff = Price - Upper Boundary of the Standard Deviation (calculated on a Gaussian filter). When the indicator signals LONG: Diff = Price - Upper Boundary of the ATR (calculated on a Gaussian filter). The calculated Diff signals how close the indicator is to changing trends. An EMA is applied to the Diff to smooth the data. Positive momentum occurs when the Diff is above the EMA, and negative momentum occurs when the Diff is below the EMA. Trend Detection Trend Logic: The indicator uses the calculated bands to identify whether the price is moving within or outside the standard deviation and ATR bands. Crosses above or below these bands, combined with positive/negative momentum, signals potential uptrends or downtrends, offering traders a clear view of market direction. Features and User Inputs The "HMA Gaussian Volatility Adjusted" script offers a variety of user inputs to customize the indicator to suit traders' styles and market conditions: HMA Length: Allows traders to adjust the sensitivity of the HMA smoothing to control the amount of noise filtered from the price data. Gaussian Length: Users can define the length at which the Gaussian filter is applied. ATR Length and Multiplier: These inputs let traders fine-tune the ATR calculation, affecting the size of the dynamic upper and lower bands to adjust for price volatility. Standard Deviation Length: Controls how the standard deviation is calculated, allowing further customization in detecting price volatility. EMA Confluence: This input lets traders determine the length of the EMA used to calculate price momentum. Type of Plot Setting: Allows users to determine how the indicator signal is plotted on the chart (Background color, Trend Lines, BOTH (backgroung color and Trend Lines)). Transparency: Provides users with customization of the background color's transparency. Color Long/Short: Offers users the option to choose their preferred colors for both long and short signals. Summary and Usage Tips The "HMA Gaussian Volatility Adjusted" indicator is a powerful tool for traders looking to refine their analysis of market trends and volatility. Its combination of HMA smoothing, Gaussian filtering, and standard deviation analysis provides a nuanced view of market movements by incorporating various metrics to determine direction, momentum, and volatility. This helps traders make better-informed decisions. It's recommended to experiment with the various input parameters to optimize the indicator for specific needs.
Pine Script® インジケーター
Patito_1の投稿
3
Dema Percentile Standard DeviationDema Percentile Standard Deviation The Dema Percentile Standard Deviation indicator is a robust tool designed to identify and follow trends in financial markets. How it works? This code is straightforward and simple: The price is smoothed using a DEMA (Double Exponential Moving Average). Percentiles are then calculated on that DEMA. When the closing price is below the lower percentile, it signals a potential short. When the closing price is above the upper percentile and the Standard Deviation of the lower percentile, it signals a potential long. Settings Dema/Percentile/SD/EMA Length's: Defines the period over which calculations are made. Dema Source: The source of the price data used in calculations. Percentiles: Selects the type of percentile used in calculations (options include 60/40, 60/45, 55/40, 55/45). In these settings, 60 and 55 determine percentile for long signals, while 45 and 40 determine percentile for short signals. Features Fully Customizable Fully Customizable: Customize colors to display for long/short signals. Display Options: Choose to show long/short signals as a background color, as a line on price action, or as trend momentum in a separate window. EMA for Confluence: An EMA can be used for early entries/exits for added signal confirmation, but it may introduce noise—use with caution! Built-in Alerts. Indicator on Diffrent Assets INDEX:BTCUSD 1D Chart (6 high 56 27 60/45 14) CRYPTO:SOLUSD 1D Chart (24 open 31 20 60/40 14) CRYPTO:RUNEUSD 1D Chart (10 close 56 14 60/40 14) Remember no indicator would on all assets with default setting so FAFO with setting to get your desired signal.
Pine Script® インジケーター
Patito_1の投稿
6
STANDARD DEVIATION INDICATOR BY WISE TRADERWISE TRADER STANDARD DEVIATION SETUP: The Ultimate Volatility and Trend Analysis Tool Unlock the power of STANDARD DEVIATIONS like never before with the this indicator, a versatile and comprehensive tool designed for traders who seek deeper insights into market volatility, trend strength, and price action. This advanced indicator simultaneously plots three sets of customizable Deviations, each with unique settings for moving average types, standard deviations, and periods. Whether you’re a swing trader, day trader, or long-term investor, the STANDARD DEVIATION indicator provides a dynamic way to spot potential reversals, breakouts, and trend-following opportunities. Key Features: STANDARD DEVIATIONS Configuration : Monitor three different Bollinger Bands at the same time, allowing for multi-timeframe analysis within a single chart. Customizable Moving Average Types: Choose from SMA, EMA, SMMA (RMA), WMA, and VWMA to calculate the basis of each band according to your preferred method. Dynamic Standard Deviations: Set different standard deviation multipliers for each band to fine-tune sensitivity for various market conditions. Visual Clarity: Color-coded bands with adjustable thicknesses provide a clear view of upper and lower boundaries, along with fill backgrounds to highlight price ranges effectively. Enhanced Trend Detection: Identify potential trend continuation, consolidation, or reversal zones based on the position and interaction of price with the three bands. Offset Adjustment: Shift the bands forward or backward to analyze future or past price movements more effectively. Why Use Triple STANDARD DEVIATIONS ? STANDARD DEVIATIONS are a popular choice among traders for measuring volatility and anticipating potential price movements. This indicator takes STANDARD DEVIATIONS to the next level by allowing you to customize and analyze three distinct bands simultaneously, providing an unparalleled view of market dynamics. Use it to: Spot Volatility Expansion and Contraction: Track periods of high and low volatility as prices move toward or away from the bands. Identify Overbought or Oversold Conditions: Monitor when prices reach extreme levels compared to historical volatility to gauge potential reversal points. Validate Breakouts: Confirm the strength of a breakout when prices move beyond the outer bands. Optimize Risk Management: Enhance your strategy's risk-reward ratio by dynamically adjusting stop-loss and take-profit levels based on band positions. Ideal For: Forex, Stocks, Cryptocurrencies, and Commodities Traders looking to enhance their technical analysis. Scalpers and Day Traders who need rapid insights into market conditions. Swing Traders and Long-Term Investors seeking to confirm entry and exit points. Trend Followers and Mean Reversion Traders interested in combining both strategies for maximum profitability. Harness the full potential of STANDARD DEVIATIONS with this multi-dimensional approach. The "STANDARD DEVIATIONS " indicator by WISE TRADER will become an essential part of your trading arsenal, helping you make more informed decisions, reduce risks, and seize profitable opportunities. Who is WISE TRADER ? Wise Trader is a highly skilled trader who launched his channel in 2020 during the COVID-19 pandemic, quickly building a loyal following. With thousands of paid subscribed members and over 70,000 YouTube subscribers, Wise Trader has become a trusted authority in the trading world. He is known for his ability to navigate significant events, such as the Indian elections and stock market crashes, providing his audience with valuable insights into market movements and volatility. With a deep understanding of macroeconomics and its correlation to global stock markets, Wise Trader shares informed strategies that help traders make better decisions. His content covers technical analysis, trading setups, economic indicators, and market trends, offering a comprehensive approach to understanding financial markets. The channel serves as a go-to resource for traders who want to enhance their skills and stay informed about key market developments.
Pine Script® インジケーター
thisiskaniskの投稿
4
E9 Bollinger RangeThe E9 Bollinger Range is a technical trading tool that leverages Bollinger Bands to track volatility and price deviations, along with additional trend filtering via EMAs. The script visually enhances price action with a combination of trend-filtering EMAs, bar colouring for trend direction, signals to indicate potential buy and sell points based on price extension and engulfing patterns. Here’s a breakdown of its key components: Bollinger Bands: The strategy plots multiple Bollinger Band deviations to create different price levels. The furthest deviation bands act as warning signs for traders when price extends significantly, signaling potential overbought or oversold conditions. Bar Colouring: Visual bar colouring is applied to clearly indicate trend direction: green bars for an uptrend and red bars for a downtrend. EMA Filtering: Two EMAs (50 and 200) are used to help filter out false signals, giving traders a better sense of the underlying trend. This combination of signals, visual elements, and trend filtering provides traders with a systematic approach to identifying price deviations and taking advantage of market corrections. Brief History of Bollinger Bands Bollinger Bands were developed by John Bollinger in the early 1980s as a tool to measure price volatility in financial markets. The bands consist of a moving average (typically 20 periods) with upper and lower bands placed two standard deviations away. These bands expand and contract based on market volatility, offering traders a visual representation of price extremes and potential reversal zones. John Bollinger’s work revolutionized technical analysis by incorporating volatility into trend detection. His bands remain widely used across markets, including stocks, commodities, and cryptocurrencies. With the ability to highlight overbought and oversold conditions, Bollinger Bands have become a staple in many trading strategies.
Pine Script® インジケーター
E9XBTの投稿
2
Standard Deviation-Based Fibonacci Band by zdmre This indicator is designed to better understand market dynamics by focusing on standard deviation and the Fibonacci sequence. This indicator includes the following components to assist investors in analyzing price movements: Weighted Moving Average (WMA) : The indicator creates a central band by utilizing the weighted moving average of standard deviation. WMA provides a more current and accurate representation by giving greater weight to recent prices. This central band offers insights into the general trend of the market, helping to identify potential buying and selling opportunities. Fibonacci Bands : The Fibonacci bands located above and below the central band illustrate potential support and resistance levels for prices. These bands enable investors to pinpoint areas where the price may exhibit indecisiveness. When prices move within these bands, it may be challenging for investors to discern the market's preferred direction. Indecisiveness Representation : When prices fluctuate between the Fibonacci bands, they may reflect a state of indecisiveness. This condition is critical for identifying potential reversal points and trend changes. Investors can evaluate these periods of indecisiveness to develop suitable buying and selling strategies. This indicator is designed to assist investors in better analyzing market trends and supporting their decision-making processes. The integration of standard deviation and the Fibonacci sequence offers a new perspective on understanding market movements. #DYOR
Pine Script® インジケーター
zdmreの投稿
Sinc Bollinger BandsKaiser Windowed Sinc Bollinger Bands Indicator The Kaiser Windowed Sinc Bollinger Bands indicator combines the advanced filtering capabilities of the Kaiser Windowed Sinc Moving Average with the volatility measurement of Bollinger Bands. This indicator represents a sophisticated approach to trend identification and volatility analysis in financial markets. Core Components At the heart of this indicator is the Kaiser Windowed Sinc Moving Average, which utilizes the sinc function as an ideal low-pass filter, windowed by the Kaiser function. This combination allows for precise control over the frequency response of the moving average, effectively separating trend from noise in price data. The sinc function, representing an ideal low-pass filter, provides the foundation for the moving average calculation. By using the sinc function, analysts can independently control two critical parameters: the cutoff frequency and the number of samples used. The cutoff frequency determines which price movements are considered significant (low frequency) and which are treated as noise (high frequency). The number of samples influences the filter's accuracy and steepness, allowing for a more precise approximation of the ideal low-pass filter without altering its fundamental frequency response characteristics. The Kaiser window is applied to the sinc function to create a practical, finite-length filter while minimizing unwanted oscillations in the frequency domain. The alpha parameter of the Kaiser window allows users to fine-tune the trade-off between the main-lobe width and side-lobe levels in the frequency response. Bollinger Bands Implementation Building upon the Kaiser Windowed Sinc Moving Average, this indicator adds Bollinger Bands to provide a measure of price volatility. The bands are calculated by adding and subtracting a multiple of the standard deviation from the moving average. Advanced Centered Standard Deviation Calculation A unique feature of this indicator is its specialized standard deviation calculation for the centered mode. This method employs the Kaiser window to create a smooth deviation that serves as an highly effective envelope, even though it's always based on past data. The centered standard deviation calculation works as follows: It determines the effective sample size of the Kaiser window. The window size is then adjusted to reflect the target sample size. The source data is offset in the calculation to allow for proper centering. This approach results in a highly accurate and smooth volatility estimation. The centered standard deviation provides a more refined and responsive measure of price volatility compared to traditional methods, particularly useful for historical analysis and backtesting. Operational Modes The indicator offers two operational modes: Non-Centered (Real-time) Mode: Uses half of the windowed sinc function and a traditional standard deviation calculation. This mode is suitable for real-time analysis and current market conditions. Centered Mode: Utilizes the full windowed sinc function and the specialized Kaiser window-based standard deviation calculation. While this mode introduces a delay, it offers the most accurate trend and volatility identification for historical analysis. Customizable Parameters The Kaiser Windowed Sinc Bollinger Bands indicator provides several key parameters for customization: Cutoff: Controls the filter's cutoff frequency, determining the divide between trends and noise. Number of Samples: Sets the number of samples used in the FIR filter calculation, affecting the filter's accuracy and computational complexity. Alpha: Influences the shape of the Kaiser window, allowing for fine-tuning of the filter's frequency response characteristics. Standard Deviation Length: Determines the period over which volatility is calculated. Multiplier: Sets the number of standard deviations used for the Bollinger Bands. Centered Alpha: Specific to the centered mode, this parameter affects the Kaiser window used in the specialized standard deviation calculation. Visualization Features To enhance the analytical value of the indicator, several visualization options are included: Gradient Coloring: Offers a range of color schemes to represent trend direction and strength for the moving average line. Glow Effect: An optional visual enhancement for improved line visibility. Background Fill: Highlights the area between the Bollinger Bands, aiding in volatility visualization. Applications in Technical Analysis The Kaiser Windowed Sinc Bollinger Bands indicator is particularly useful for: Precise trend identification with reduced noise influence Advanced volatility analysis, especially in the centered mode Identifying potential overbought and oversold conditions Recognizing periods of price consolidation and potential breakouts Compared to traditional Bollinger Bands, this indicator offers superior frequency response characteristics in its moving average and a more refined volatility measurement, especially in centered mode. These features allow for a more nuanced analysis of price trends and volatility patterns across various market conditions and timeframes. Conclusion The Kaiser Windowed Sinc Bollinger Bands indicator represents a significant advancement in technical analysis tools. By combining the ideal low-pass filter characteristics of the sinc function, the practical benefits of Kaiser windowing, and an innovative approach to volatility measurement, this indicator provides traders and analysts with a sophisticated instrument for examining price trends and market volatility. Its implementation in Pine Script contributes to the TradingView community by making advanced signal processing and statistical techniques accessible for experimentation and further development in technical analysis. This indicator serves not only as a practical tool for market analysis but also as an educational resource for those interested in the intersection of signal processing, statistics, and financial markets. Related:
Pine Script® インジケーター
The_Peaceful_Lizardの投稿
4
Fear/Greed Zone Reversals [UAlgo]The "Fear/Greed Zone Reversals " indicator is a custom technical analysis tool designed for TradingView, aimed at identifying potential reversal points in the market based on sentiment zones characterized by fear and greed. This indicator utilizes a combination of moving averages, standard deviations, and price action to detect when the market transitions from extreme fear to greed or vice versa. By identifying these critical turning points, traders can gain insights into potential buy or sell opportunities. 🔶 Key Features Customizable Moving Averages: The indicator allows users to select from various types of moving averages (SMA, EMA, WMA, VWMA, HMA) for both fear and greed zone calculations, enabling flexible adaptation to different trading strategies. Fear Zone Settings: Fear Source: Select the price data point (e.g., close, high, low) used for Fear Zone calculations. Fear Period: This defines the lookback window for calculating the Fear Zone deviation. Fear Stdev Period: This sets the period used to calculate the standard deviation of the Fear Zone deviation. Greed Zone Settings: Greed Source: Select the price data point (e.g., close, high, low) used for Greed Zone calculations. Greed Period: This defines the lookback window for calculating the Greed Zone deviation. Greed Stdev Period: This sets the period used to calculate the standard deviation of the Greed Zone deviation. Alert Conditions: Integrated alert conditions notify traders in real-time when a reversal in the fear or greed zone is detected, allowing for timely decision-making. 🔶 Interpreting Indicator Greed Zone: A Greed Zone is highlighted when the price deviates significantly above the chosen moving average. This suggests market sentiment might be leaning towards greed, potentially indicating a selling opportunity. Fear Zone Reversal: A Fear Zone is highlighted when the price deviates significantly below the chosen moving average of the selected price source. This suggests market sentiment might be leaning towards fear, potentially indicating a buying opportunity. When the indicator identifies a reversal from a fear zone, it suggests that the market is transitioning from a period of intense selling pressure to a more neutral or potentially bullish state. This is typically indicated by an upward arrow (▲) on the chart, signaling a potential buy opportunity. The fear zone is characterized by high price volatility and overselling, making it a crucial point for traders to consider entering the market. Greed Zone Reversal: Conversely, a Greed Zone is highlighted when the price deviates significantly above the chosen moving average. This suggests market sentiment might be leaning towards greed, potentially indicating a selling opportunity. When the indicator detects a reversal from a greed zone, it indicates that the market may be moving from an overbought condition back to a more neutral or bearish state. This is marked by a downward arrow (▼) on the chart, suggesting a potential sell opportunity. The greed zone is often associated with overconfidence and high buying activity, which can precede a market correction. 🔶 Why offer multiple moving average types? By providing various moving average types (SMA, EMA, WMA, VWMA, HMA) , the indicator offers greater flexibility for traders to tailor the indicator to their specific trading strategies and market preferences. Different moving averages react differently to price data and can produce varying signals. SMA (Simple Moving Average): Provides an equal weighting to all data points within the specified period. EMA (Exponential Moving Average): Gives more weight to recent data points, making it more responsive to price changes. WMA (Weighted Moving Average): Allows for custom weighting of data points, providing more flexibility in the calculation. VWMA (Volume Weighted Moving Average): Considers both price and volume data, giving more weight to periods with higher trading volume. HMA (Hull Moving Average): A combination of weighted moving averages designed to reduce lag and provide a smoother curve. Offering multiple options allows traders to: Experiment: Traders can try different moving averages to see which one produces the most accurate signals for their specific market. Adapt to different market conditions: Different market conditions may require different moving average types. For example, a fast-moving market might benefit from a faster moving average like an EMA, while a slower-moving market might be better suited to a slower moving average like an SMA. Personalize: Traders can choose the moving average that best aligns with their personal trading style and risk tolerance. In essence, providing a variety of moving average types empowers traders to create a more personalized and effective trading experience. 🔶 Disclaimer Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals. Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator. Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies. Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses. No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Pine Script® インジケーター
UAlgoの投稿
5