Empiece

Osciladores centrados

Tidal Volume Oscillator [JOAT]Tidal Volume Oscillator Introduction The Tidal Volume Oscillator is a separate-pane oscillator that attempts to answer a single question: is the current price movement being carried by genuine volume participation, or is it occurring on weak flow? It constructs a volume-weighted momentum score, normalizes it to a bounded range of −100 to +100, applies a Fourier-inspired exponential decay smoothing pass to reduce noise without introducing phase lag, and then scales the result with an adaptive trend filter. A flow momentum line tracks the acceleration of the oscillator itself. A divergence engine scans for all four divergence types simultaneously — regular bullish, regular bearish, hidden bullish, and hidden bearish — and plots them directly in the oscillator panel. The indicator does not predict future price. It contextualizes current price movement relative to volume behavior and flags when price action and volume-weighted momentum are moving in opposite directions, which historically precedes changes in directional character — though not always, and not reliably in all instruments or conditions. --- Core Concepts The VZO Foundation The Volume Zone Oscillator (VZO) is an established concept that categorizes volume as positive or negative based on the direction of price change, then computes a ratio of positive to negative volume over a rolling window. This indicator rebuilds that concept from the ground up using a different normalization approach: Relative Volume: Instead of using raw volume, the oscillator first normalizes each bar's volume against a rolling SMA of volume. This produces a relative volume reading — a value above 1.0 means the bar traded heavier than average, below 1.0 means lighter. This step removes the absolute scale of volume from the calculation, allowing the oscillator to behave comparably across instruments with vastly different volume profiles and across timeframes where absolute volume differs by orders of magnitude. Volume-Weighted Momentum: The price change on each bar is smoothed via EMA, and the relative volume is separately smoothed via EMA. Multiplying these two smoothed values produces a volume-weighted momentum signal. This is then smoothed again to form a base momentum reading. RSI-Style Normalization: Positive and negative portions of the base momentum are separated, each independently smoothed, and their ratio is fed into an RSI-style formula: vzo = 100 * (ratio - 1) / (ratio + 1) . This bounds the oscillator strictly between −100 and +100 and gives it a symmetric zero-line structure where positive values indicate dominant upward volume momentum and negative values indicate dominant downward volume momentum. Fourier Exponential Decay Smoothing After the initial VZO is computed, a second smoothing pass is applied using exponential decay weights. For each bar, the contribution of each of the prior N bars is weighted by exp(-i / (len * 0.3)) , where i is the number of bars back. This means the most recent bar carries maximum weight and each earlier bar contributes exponentially less. The window clips naturally as the weights approach zero. The result is a smoothing pass that is inspired by frequency-domain thinking: it emphasizes recent values and de-emphasizes older values in a continuous decay rather than in the binary on/off fashion of a simple rolling average. The smoothed output tracks the oscillator's underlying shape while suppressing high-frequency noise without the phase shift that a centered moving average would introduce. ADF Trend Filter An adaptive multiplier is derived by comparing a short SMA and a long SMA of price, normalizing their difference by the rolling standard deviation of price over a matching window. This produces a dimensionless value that reflects the strength of the current trend relative to recent volatility — conceptually analogous to the logic behind an Augmented Dickey-Fuller trend test applied in a simplified real-time form. This multiplier is kept close to 1.0 intentionally. Its role is not to dramatically change the oscillator's value but to apply a mild scaling that slightly amplifies the VZO when trend conditions are strong and slightly suppresses it during choppy, mean-reverting conditions. The effect is subtle but helps the oscillator's readings align better with the underlying market character. Final Blended VZO The final oscillator value blends the EMA-smoothed VZO and the Fourier-smoothed VZO according to a blend parameter, scales the result by the ADF multiplier, and clamps the output to the range. The blend parameter controls how much weight goes to the Fourier-smoothed version versus the EMA-smoothed version, allowing the user to tune between responsiveness and smoothness. Flow Momentum Line A secondary line is plotted alongside the main oscillator, computed as: flow_momentum = (vzo - ema(vzo, lookback)) * 0.5 This measures the rate of change of the oscillator — its acceleration — and scales it to stay visually proportional. When the flow momentum line is rising, the oscillator is accelerating upward. When it is falling, the oscillator is losing momentum regardless of its absolute level. Crossovers between the oscillator and the flow momentum line can highlight inflection points in volume-weighted momentum. Divergence Engine The divergence engine uses pivot high and pivot low detection to identify four divergence types: Regular Bullish Divergence: Price makes a lower low while the oscillator makes a higher low. Suggests weakening downward volume participation on the new price low. Regular Bearish Divergence: Price makes a higher high while the oscillator makes a lower high. Suggests weakening upward volume participation on the new price high. Hidden Bullish Divergence: Price makes a higher low while the oscillator makes a lower low. Often associated with pullbacks within an established uptrend where volume momentum remains stronger than the pullback's depth implies. Hidden Bearish Divergence: Price makes a lower high while the oscillator makes a higher high. Often associated with rallies within an established downtrend where volume momentum is failing to confirm the price bounce. The engine uses ta.valuewhen to retrieve the oscillator's value at the most recent prior pivot of the same type, then compares it to the current pivot. Lines and labels are drawn directly in the oscillator pane, keeping all divergence context in a single panel. Dynamic Color Blending The oscillator line and histogram (if enabled) use color blending that responds to both the direction of the oscillator and the intensity of the flow momentum. Colors transition smoothly between bull and bear palettes as conditions shift, with intensity modulated by momentum acceleration. This avoids binary color flips and gives a continuous visual read of the oscillator's strength and direction. --- Features Relative-volume-normalized VZO foundation — removes absolute volume scale bias RSI-style normalization producing a symmetric −100 to +100 oscillator Fourier exponential decay smoothing pass for noise reduction without phase lag ADF-inspired adaptive trend multiplier for regime-sensitive scaling Blended output combining EMA and Fourier smoothing with user-adjustable weighting Flow momentum line showing oscillator acceleration Full four-type divergence engine: regular bull/bear and hidden bull/bear Divergence lines and labels rendered directly in the oscillator pane Dynamic color blending based on direction and momentum intensity Overbought/oversold level lines at user-defined thresholds (default ±80) Fully toggleable visual components including divergence types individually --- Input Parameters VZO Length: Primary lookback for the volume-weighted momentum and normalization calculations (default: 14) Smoothing Length: Short EMA length used in the initial volume-weighted momentum construction (default: 5) Signal Length: EMA length applied to the final VZO for the signal/flow line (default: 9) Fourier Window: Number of bars used in the exponential decay smoothing pass (default: 20) Fourier Blend: Proportion of the final output taken from the Fourier-smoothed VZO versus the EMA-smoothed VZO (default: 0.4, meaning 40% Fourier / 60% EMA) Overbought Level: Upper reference line threshold (default: +80) Oversold Level: Lower reference line threshold (default: −80) Pivot Bars: Number of bars on each side required to confirm a pivot high or low for divergence detection Visual Toggles: Individual controls for divergence types (regular bull, regular bear, hidden bull, hidden bear), flow momentum line, bar coloring, and OB/OS lines --- How to Use Reading the oscillator: Values above zero indicate that volume-weighted momentum favors buyers over the lookback window. Values below zero indicate it favors sellers. The magnitude reflects how dominant one side is. A reading of +60 is meaningfully different from +20 — the former suggests strong participation on the upside, the latter suggests modest positive lean. Overbought/oversold levels: The default ±80 levels are deliberately set wide. Reaching ±80 indicates a statistically strong skew in volume momentum, not simply a directional bias. A reading at +85 that begins to decline is worth noting; a reading that has been above +80 for many bars without declining suggests strong persistent flow, not an automatic reversal condition. Flow momentum line: Use the flow momentum line to identify when the oscillator is accelerating or decelerating. If the oscillator is above zero but the flow momentum line is falling and crossing below the oscillator, volume-weighted momentum is losing strength even if it has not crossed zero. This can be an early warning of a fading move. Divergences: Divergence signals appear as labeled lines in the oscillator pane. They flag a disagreement between price structure and volume momentum structure. Regular divergences are typically associated with potential trend reversal conditions; hidden divergences are typically associated with trend continuation conditions during a pullback. Neither type is a standalone entry signal — they require context from price structure, higher timeframe trend, and other confirmation. Combining types: A regular bearish divergence occurring while the oscillator is above +60 and the flow momentum line is declining is a more compelling condition than a divergence occurring at a neutral oscillator reading. Look for confluence between divergence signals, oscillator level, and flow momentum direction. Timeframe notes: On lower timeframes, the divergence engine will fire frequently and many signals will resolve as noise. On higher timeframes, divergence signals are structurally more significant but rarer. The Fourier blend and VZO length should be calibrated to the timeframe being traded. --- Limitations This indicator does not predict future price movement. All readings are computed from past and current bar data. Volume data quality varies significantly across instruments and data providers. On instruments with unreliable, synthetic, or missing volume data (some forex pairs, certain CFDs, spread-betting instruments), the oscillator's readings will be distorted or meaningless. Divergences are detected only at confirmed pivot points, which by definition require a lookback into past bars. A divergence signal will appear after the pivot is confirmed, not at the pivot bar itself. This is inherent to pivot-based divergence detection and is not a bug. Hidden divergences can occur frequently during strong trends and produce many signals that resolve without follow-through on shorter timeframes. The ADF-inspired filter is a simplified heuristic, not a formal statistical test. It does not guarantee that the adaptive scaling accurately reflects whether a market is trending or mean-reverting at any given moment. The Fourier exponential decay smoothing is not a formal frequency-domain Fourier transform. The term is used descriptively to indicate the exponential weighting pattern, not to imply that the calculation resolves into sinusoidal components. Extreme or sustained overbought/oversold readings do not guarantee a reversal. Strong trends can keep the oscillator pinned at extremes for extended periods. The oscillator is bounded at ±100 by construction. This means that at extreme readings, additional strengthening of volume momentum does not move the line further — the clamping obscures incremental changes at extremes. Past divergence performance on a given instrument is not indicative of future performance. --- Originality Statement The VZO concept is established in the public domain. This implementation departs from the standard in several meaningful ways. Using relative volume (each bar's volume divided by a rolling SMA of volume) rather than raw volume removes the absolute scale of volume from the oscillator's behavior — a standard VZO applied to a futures contract and a low-float equity will behave differently purely due to volume magnitude; this version will not. The RSI-style normalization of the volume-weighted momentum ratio is retained from the VZO concept but is applied to a momentum signal constructed differently from the standard signed-volume approach. The Fourier exponential decay smoothing layer is an original addition: it is not a standard EMA, WMA, or VWMA — it applies a decaying weight function that is conceptually distinct from any standard Pine Script built-in smoothing function, producing a cleaner oscillator output with less phase distortion than an equivalent EMA. The ADF-inspired adaptive multiplier is a real-time regime-sensitivity mechanism not present in any standard oscillator. The four-type divergence engine built into the same panel, detecting all four divergence classes simultaneously using pivot comparison logic, provides complete divergence coverage without requiring additional scripts or manual line drawing. The combination of these elements — relative-volume normalization, Fourier decay smoothing, adaptive trend scaling, blended output, flow momentum line, and full-coverage divergence detection — into a single oscillator panel represents an original synthesis that is not replicated by any standard built-in indicator. --- Disclaimer This indicator is provided for educational and informational purposes only. It does not constitute financial advice, investment advice, or a recommendation to buy or sell any financial instrument. Trading involves substantial risk of loss. Past performance of any indicator or strategy is not indicative of future results. Always conduct your own research and consult a qualified financial professional before making any trading decisions. -Made with passion by officialjackofalltrades
Indicador Pine Script®
por officialjackofalltrades
GTS5.alvin - HMA Tracker 2.0Momentum. Strength. Clarity. 🚀 Overview HMA Tracker™ 2.0 is a next-generation momentum indicator that transforms the Hull Moving Average into a real-time trend intelligence system. Instead of simply showing direction, it reveals: 📍 Market bias (Bullish / Bearish) ⚡ Momentum strength (0–100%) 🧠 Expansion vs exhaustion phases 🎨 Dynamic visual intensity based on volatility This is not just a moving average… 👉 It’s a live momentum radar for price action. 🧠 What Makes It Different Traditional indicators tell you: “Price is going up or down” HMA Tracker™ tells you : “How strong the move is… and whether it’s accelerating or dying.” It achieves this by comparing: ⚡ Current HMA (momentum) 📊 HMA Lookback Average (equilibrium) Then measuring the distance between them as a normalized strength score. 📊 Core Features 🎯 1. Real-Time Bias Detection 🟢 Bullish trend detection 🔴 Bearish trend detection Instant flip signals when momentum shifts ⚡ 2. Strength-Based Momentum Engine (0–100%) 📉 0–30% → Weak / Chop / Range 📊 30–70% → Building momentum 🚀 70–100% → Strong expansion or exhaustion zone 🎨 3. Dynamic Color Intensity System 🌫️ Faded colors → weak momentum 🔥 Bright neon colors → strong expansion Color intensity automatically adapts to volatility conditions. 🧩 4. Smart Dashboard (Top-Right Panel) Live readout of: 🟢 BULLISH / 🔴 BEARISH bias 📊 Strength percentage ⚡ Market state (Weak / Building / Expansion) 🧠 5. Expansion vs Exhaustion Logic This indicator helps you visually identify: 🚀 Expansion phases (trend acceleration) ⚠️ Exhaustion zones (momentum fading) 🔄 Early reversal signals 🔥 How to Use It 📈 Trend Continuation Setup Bias = Bullish Strength = 60%–100% 👉 Ride momentum, avoid early exits 🧨 Exhaustion Warning Strength spikes (80–100%) Then begins fading 👉 Possible reversal or pullback incoming ⚪ Chop / No Trade Zone Strength below 30% 👉 Market is ranging or indecisive 🎯 Flip Signals 🔴 → 🟢 = bullish transition 🟢 → 🔴 = bearish transition Best used with structure or liquidity zones. 💡 Built For Traders Who Want Clarity Perfect for: ⚡ Scalpers (1m–5m) 📊 Intraday traders 🧠 Momentum traders 🎯 Trend followers 🧪 Best Markets 🥇 Gold (XAUUSD) 💱 Forex pairs 🪙 Crypto (BTC / ETH) 📈 Indices (NAS100 / US30) ⚙️ Default Settings ⏱️ HMA Length: 55 📊 Lookback Average: 55 📏 Strength Normalization: 100 🖥️ Timeframe: Optimized for 1-minute charts 🔥 Why Traders Use It ✔ Eliminates guessing ✔ Shows real momentum strength ✔ Adapts to volatility automatically ✔ Works across all markets ✔ Combines trend + momentum in one tool 🧠 Pro Strategy Tip The real edge comes from: 👉 Watching strength transitions, not just direction Weak → Strong = Entry confirmation Strong → Weak = Exit / reversal warning 💬 Final Note HMA Tracker™ 2.0 doesn’t just show direction… 👉 It shows the force behind the move So you’re no longer trading candles. You’re trading momentum itself. ⚠️ Disclaimer This indicator is for educational and informational purposes only. It does not constitute financial advice. Trading involves risk.
Indicador Pine Script®
por alvinandfriends
3
Aura Trend Cloud Navigator [Pineify]Aura Trend Cloud Navigator This indicator builds a trend-following system around a Trend Regularity Adaptive Moving Average — an adaptive MA that adjusts its responsiveness based on how frequently price makes new period highs or lows. When the market trends, the baseline tracks price closely; when it ranges, the baseline goes nearly flat, cutting down on false crossover signals. An ATR-based volatility cloud wraps around the baseline to frame the trend's expected range. Key Features Adaptive baseline that self-adjusts speed — fast in trends, nearly frozen in ranges Dynamic ATR cloud that expands and contracts with real-time volatility Gradient-filled cloud with automatic color shifts between bullish and bearish states Crossover-based buy/sell signals filtered by the adaptive regime detection Bar coloring for quick visual trend identification How It Works The core is a recursive adaptive moving average controlled by a trend coefficient derived from market structure: On each bar, the script checks whether a new highest high or lowest low has been established over the lookback period (default 99 bars). If either condition is met, a binary signal of 1 is recorded; otherwise 0. The average of this binary signal over the same period is computed via SMA, then squared. Squaring creates a nonlinear response — the coefficient drops sharply when trend activity fades and rises steeply when price consistently prints new extremes. This squared value becomes the smoothing factor in a recursive formula: baseline = baseline + coefficient × (close − baseline) . A high coefficient pulls the baseline toward price; a near-zero coefficient locks it in place. An Average True Range envelope is then added above and below the baseline, scaled by a user-defined multiplier. This forms the cloud — a corridor representing expected price movement around the trend. How the Components Work Together The adaptive baseline and the ATR cloud serve complementary roles. The baseline handles trend direction and generates entry signals, but because it adapts to market regime, it sidesteps the main weakness of fixed-period moving averages: constant whipsawing during consolidation. The cloud adds a volatility dimension on top of that directional read. When price stays inside the cloud, it is oscillating within the normal range of the current trend. Price pushing beyond the cloud edges may signal overextension or trend acceleration. In short, the baseline answers "which direction" while the cloud answers "how far is normal." Trading Ideas and Insights When the baseline shifts color and a triangle signal fires, treat it as a potential trend change. Confirmation improves if the crossover happens near or beyond the opposite cloud edge, suggesting genuine momentum rather than a range poke. In a bullish regime, price hugging the upper cloud boundary suggests strong follow-through. A pullback toward the baseline that holds can offer a continuation entry — especially if the baseline remains clearly sloped upward. Watch for the baseline going flat while the cloud tightens — this is the indicator explicitly telling you to stand aside. Crossovers that occur while the baseline is flat carry less conviction than those during a clearly sloped baseline, since the adaptive mechanism has detected a low-regularity environment. Unique Aspects The trend regularity approach counts how often new period extremes occur rather than measuring price direction or momentum directly. Most adaptive MAs rely on efficiency ratios or volatility scaling; this one responds to the structural behavior of the market itself — whether it is consistently making progress or stalling out. Squaring the trend coefficient means the MA doesn't merely slow down in ranges — it practically stops. This creates clear visual separation between trending and non-trending regimes that is immediately readable on the chart. The gradient cloud gives volatility context without the visual clutter of multi-line band systems. One glance tells you both direction and how stretched the current move is. How to Use Add the indicator to your chart. The thick colored line is the adaptive baseline — green for bullish, red for bearish. Triangle markers appear at crossover points: upward green triangles below bars for potential long entries, downward red triangles above bars for potential short entries or exits. Use the cloud as context. Price within the cloud is behaving normally for the trend. Moves beyond the cloud edges are stretched and may revert or signal acceleration. On higher timeframes (4H, Daily), the default 99-period length works well as a medium-term trend filter. On lower timeframes, consider reducing the length for faster adaptation — though this increases sensitivity to noise. Customization Trend Filter Length (default: 99) — How many bars are used to assess trend regularity. Higher values produce a smoother, slower baseline that only reacts to sustained directional moves. Lower values increase sensitivity but also raise whipsaw risk in choppy markets. Cloud Width / ATR Multiplier (default: 2.0) — Scales the ATR-based cloud. Wider values capture more price action within the corridor; tighter values make cloud-edge touches more frequent and potentially more meaningful as overextension signals. ATR Length (default: 14) — Period for the Average True Range calculation. The standard 14 suits most instruments. Increase it for smoother cloud behavior on volatile assets. Conclusion The Aura Trend Cloud Navigator provides a regime-adaptive trend filter that goes quiet when the market goes quiet. The TRAMA baseline combined with an ATR cloud delivers both directional guidance and volatility context in a single overlay. It suits swing and position traders looking for a trend filter that avoids generating noise during consolidation — though the adaptive smoothing does introduce lag at trend reversals, so pairing it with a momentum oscillator for timing may improve entries on faster-moving instruments.
Indicador Pine Script®
por Pineify
Trend Momentum (Algionics) - Ribbon Pressure FieldTrend Momentum interprets a 28-line EMA ribbon field as a physical force landscape. It reads what directional pressure price is under, how strong that pressure is, and what the current market state is, all within a single framework. The ribbon spans periods 20 to 236 in steps of 8. Each line is not a simple EMA. It passes through a multi-stage smoothing kernel: f_rb(int len) => float ama = (ta.ema(src, len) + ta.sma(src, len)) / 2 int k = int(math.ceil(len * 0.08)) float kl = ta.ema(ama, k) (kl + ta.sma(kl, k + 2)) / 2 The average of EMA and SMA is computed first, then a secondary smoothing pass is applied using a kernel length equal to 8 percent of the original period. This dual-smoothing structure suppresses both the phase lag of a pure EMA and the ripple noise of a pure SMA simultaneously. Because the kernel ratio scales proportionally with the period, short lines and long lines maintain consistent smoothing characteristics across the entire ribbon. Force Boundary The histogram plots Bull Force above the zero line and Bear Force below it. float bullForce = math.max(v001 - rb_min, 0.0) float bearForce = math.min(v001 - rb_max, 0.0) Bull Force is the distance from price to the bottom edge of the field. Bear Force is the distance from price to the top edge. When price is inside the field, both are active. When price breaks above, Bear Force converges to zero. When price drops below, Bull Force converges to zero. The space between them defines the force boundary. When the boundary widens, price is moving away from the field edges. When it narrows, price is returning toward the center. Pressure Ratio Where Force Boundary measures raw displacement between price and the field edges, Pressure Ratio measures the internal pressure distribution within the field. float bp_a = math.max(v001-v020,0)+math.max(v001-v028,0)+math.max(v001- v036,0)+math.max(v001-v044,0)+... float total_p = bull_pressure + bear_pressure float bull_dom = total_p > 0 ? (bull_pressure / total_p) * 100.0 : 50.0 For each of the 28 lines, the distance from price is measured individually. Lines below price contribute to bull pressure. Lines above contribute to bear pressure. Both sides are summed independently, then the ratio is computed. This is not a simple count of how many lines are above or below. A line 10 points below price contributes 10 times more bull pressure than a line 1 point below. The ratio reflects both the number of lines favoring each side and how far they are from price. At 100, every line sits below price. At 0, every line sits above. At 50, the total upward and downward distances are equal. Bias Line The Bias Line sits inside the force boundary. Its position is determined by the pressure ratio. float biasLine = bearForce + (bullForce - bearForce) * (bull_dom / 100.0) It divides the space between Bull Force and Bear Force using the pressure ratio as a positioning weight. A 73 percent bull reading does not place the line at 73 percent of the field. It places the line at 73 percent of the distance between Bear Force and Bull Force at that moment. The Bias Line responds to two independent inputs: how far the field edges are from price, and how the internal pressure is distributed. The separation between boundary logic and positioning logic is the structural core of this design. The color follows a gradient based on its position within the force boundary. Ribbon Overlay The ribbon draws two boundary lines on the price chart. The upper line marks the highest value across the field. The lower line marks the lowest. Each boundary changes color independently based on price crossovers. When price crosses above a boundary, it turns bull color. When price crosses below, it turns bear color. The moment both boundaries switch to the same color confirms that price has moved fully to one side of the field. A gradient fill appears between price and the nearest boundary, fading as price moves away from the edge. Price Candles When enabled, candles on the main chart are colored based on where the Bias Line sits within the force boundary. float sig_pos = tm_range > 0 ? ((biasLine - bearForce) / tm_range) * 2.0 - 1.0 : 0.0 color candle_col = color.from_gradient(sig_pos, -1.0, 1.0, C_BEAR, C_BULL) The Bias Line position is converted to a scale from minus 1 to plus 1, then mapped to a color gradient. Bear color at the bottom, bull color at the top. This coloring reflects pressure balance, not price direction. A rising candle with bear coloring means price moved up but field pressure remains tilted to the downside. When candle color and price direction disagree, the field is telling a different story than the bar itself. Dashboard BIAS Displays bull and bear pressure percentages. Each value updates with a directional arrow indicating whether the percentage increased or decreased from the previous bar. A segment bar provides a visual representation of the pressure distribution. Flow Tracks whether the dominant pressure is accelerating or decelerating. It compares the current pressure percentage against its own smoothed average. float bias_smooth = ta.ema(bull_dom, GM_LEN) The smoothing length is derived as the geometric mean of the ribbon endpoints: int GM_LEN = int(math.round(math.sqrt(float(START_P) * float(END_P)))) No arbitrary period. A natural interaction scale derived from the ribbon structure. When the percentage is above its average, the label reads Rising. When below, Falling. When pressure reaches full saturation, Maxed. Status A four-state market condition classifier. Trend activates when price moves outside the field entirely. Hold activates when the dominant side remains intact but price is inside the field. Weakening activates when the dominant side still leads but its pressure is declining. Reversal Warning activates when price crosses the center of mass to the opposing side. The state engine uses two mechanisms. A trend latch and a condition matrix. if bull_dom >= 100 is_bull := true if bull_dom <= 0 is_bull := false The latch sets only when the pressure ratio touches either extreme. It does not reset at any intermediate value. It only changes at the next full saturation on the opposite side. 100 and 0 are mathematical boundaries. 50 is the equilibrium point where upward and downward pressure are equal. There is no arbitrary threshold in this system. The natural state progression is Trend to Hold to Weakening to Reversal Warning. When states skip steps, for example jumping from Trend directly to Reversal Warning, it signals a sharp shift in pressure. The faster the sequence moves, the less time available to react. Trend Confirms the established directional bias. It reads Bull when the last confirmed extreme was at full bullish saturation, and Bear when at full bearish saturation. The direction holds until the opposite extreme is reached. Note A one-line contextual summary tied to the active status. Each of the four states has its own message describing the current condition and what to watch for. Technical Implementation Ribbon Kernel Structure Each ribbon line is not a simple EMA. The EMA-SMA average serves as a first-stage compromise between exponential responsiveness and rectangular stability. The secondary kernel, scaled to 8 percent of the input period, applies consistent proportional smoothing across the entire ribbon. Short-period lines receive short kernels. Long-period lines receive long kernels. The noise suppression ratio remains uniform regardless of where a line sits in the ribbon. Distance-Weighted Pressure Measurement Conventional ribbon-based indicators measure strength as the count of lines above or below price divided by the total number of lines. This approach treats every line equally. A line barely below price and a line far below price contribute the same. This engine converts the absolute distance to each line into pressure. A line 10 points below price contributes 10 times more bull pressure than a line 1 point below. Because this distance weighting is embedded in the ratio, the system reads the pressure gradient inside the field, which a simple count cannot capture. Dual Separation Architecture Force Boundary and Pressure Ratio are computed independently. Force Boundary measures only the raw displacement between price and the field edges. Pressure Ratio measures only the distance-weighted sum across all 28 individual lines. The Bias Line is the sole point where these two independent inputs converge. The boundary defines the range of possible positions. The pressure ratio determines the position within that range. A change in one does not affect the calculation of the other. Latch-Based State Engine State transitions are driven by mathematical extremes, not arbitrary thresholds. The latch sets only at 100 (all lines below price) or 0 (all lines above price). These are physical limits of the distribution, not chosen values. 50 is the point where the sum of upward distances exactly equals the sum of downward distances. The condition matrix uses only these three structural boundaries: 0, 50, and 100. Interlocking Constant Architecture Every parameter in this system branches from a single root: int START_P = 20 int END_P = 236 From these two constants the 28-line ribbon is defined, and from that ribbon: Force Boundary, Pressure Ratio, Bias Line, Flow smoothing length, and every boundary in the state engine are all derived. The smoothing length used for Flow is the geometric mean of the two endpoints. The state classification boundaries of 0, 50, and 100 derive directly from the mathematical limits of the pressure distribution. Change one constant and the ribbon structure shifts, the field boundaries move, the pressure distribution recalculates, and every downstream output cascades accordingly. Settings Ribbon Overlay: displays the upper and lower field boundaries on the price chart with color-coded crossover states. Price Candles: colors candles on the main chart based on the Bias Line position within the force boundary. Dashboard: shows the status panel with BIAS percentages, segment bar, Flow, Status classification, Trend direction, and Note. Force Boundary: plots the Bull Force and Bear Force histogram in the indicator pane. Bias Line: plots the pressure-weighted position line inside the force boundary. Position Point: marks the current Bias position on the last bar.
Indicador Pine Script®
por Algionics
Big C Key LevelsBig C Key Levels plots the most important price levels for intraday trading — all in one clean, customizable indicator. Levels included: CDH / CDL — Current Day High and Low, updates live as the session develops PMH / PML — Premarket High and Low, locked in at 9:30 AM EST PDH / PDL — Previous Day High and Low PWH / PWL — Previous Week High and Low Features: Full customization — colors, line style, line width, and show/hide toggles for each level group Alert system built in — set alerts for any level break directly from the indicator Clean visual hierarchy — each level group has its own distinct style so your chart never looks cluttered Works on all intraday timeframes from 30 seconds up to 4H How to use: Open Settings → Inputs to customize each level group to match your chart setup. Use the Alert dropdown to set notifications on any level break.
Indicador Pine Script®
por xfactor101
Apex Volatility Squeeze & Breakout [Pineify]Apex Volatility Squeeze & Breakout The Apex Volatility Squeeze & Breakout indicator is a dynamic volatility analysis tool that identifies market compression (squeeze) phases and highlights potential breakout opportunities in real time. Built on the well-established principles of Bollinger Bands and Keltner Channels, this indicator synthesizes both into a single, unified volatility channel with a clear three-state trend system — giving traders an intuitive and actionable view of market volatility conditions on any symbol and timeframe. Key Features Unified volatility channel combining Bollinger Band width and Keltner Channel (ATR) threshold Three-state trend detection: Bullish, Bearish, and Squeeze (consolidation) Smoothed bands using EMA to reduce noise and false signals Color-coded volatility cloud with dynamic candle coloring Built-in Buy and Sell breakout signal labels Alert conditions for automated trading notifications Fully customizable parameters for lookback period, multipliers, smoothing, and colors How It Works This indicator operates on a core concept: when volatility contracts, a breakout is imminent . Here is how the calculation pipeline works: A Simple Moving Average (SMA) of the close price is calculated over the user-defined lookback period to establish the basis line. Standard deviation of price is computed and scaled by a Band Multiplier to determine the upper and lower Bollinger-style volatility bands. The Average True Range (ATR) is computed over the same period and scaled by a Squeeze Multiplier to establish the Keltner Channel threshold. A squeeze state is detected when the Bollinger Band width (scaled standard deviation) is less than the Keltner Channel width (scaled ATR) — this means volatility has compressed below normal levels. Both the upper band, lower band, and basis are smoothed using an Exponential Moving Average (EMA) to produce a clean, noiseless visual channel. A trend state machine determines the current market phase: Bullish (+1) when price trades above the upper band outside a squeeze, Bearish (-1) when price trades below the lower band outside a squeeze, and Squeeze (0) when volatility is compressed. Trading Ideas and Insights The squeeze state is the most critical signal this indicator provides. When the bands contract and the channel turns orange (default squeeze color), the market is consolidating and building energy. Traders should watch closely for the following scenarios: A bullish breakout occurs when price crosses above the upper smoothed band after a squeeze period, indicating upward momentum. A bearish breakout occurs when price crosses below the lower smoothed band after a squeeze period, indicating downward momentum. During the squeeze phase, traders may choose to reduce position sizes and wait for directional confirmation. The color transition of the volatility cloud — from orange (squeeze) to green (bullish) or red (bearish) — provides a clear visual cue for trend changes. How Multiple Indicators Work Together This script merges two complementary volatility methodologies into a single coherent system: Bollinger Bands (Standard Deviation) measure statistical volatility — how far price deviates from the mean. They expand during volatile markets and contract during quiet markets. Keltner Channels (ATR) measure range-based volatility — the average true range of price movement. They provide a more stable, less reactive volatility baseline. By comparing these two measures, the indicator identifies squeeze conditions: when the faster-reacting Bollinger Band width falls below the slower ATR threshold, it signals abnormal compression. This is the classic "squeeze" concept pioneered by John Carter's TTM Squeeze, adapted here with EMA smoothing for cleaner signals. The EMA smoothing layer is applied on top of the raw bands to eliminate whipsaw noise. This creates a smoother channel that is easier to read and trade, especially on lower timeframes. The trend state machine ties everything together by classifying the market into three clear phases, which then drive the dynamic coloring of the bands, cloud fill, and candle colors — creating a unified visual experience. Unique Aspects Unlike standard squeeze indicators that only display a binary squeeze/no-squeeze state, this indicator provides a full directional trend classification with three states, color-coded across all visual elements. The EMA-smoothed volatility channel is visually cleaner than traditional Bollinger Bands or Keltner Channels, making it easier to identify trend direction at a glance. The volatility cloud fill adapts its color in real time based on the current trend state, providing immediate visual feedback on whether the market is trending bullish, bearish, or consolidating. Candle coloring is also driven by the volatility state, allowing traders to spot trend alignment without needing to inspect the bands directly. How to Use Add the indicator to your chart. It overlays directly on the price chart. Watch for the orange squeeze zone — this indicates low volatility and a potential breakout ahead. When the channel transitions from orange to green, the market is breaking out bullish. When it turns red, the breakout is bearish. Use the BUY and SELL labels as entry signals when price escapes the squeeze zone and crosses the smoothed bands. Set up alerts using the built-in alert conditions ("Bullish Volatility Breakout" and "Bearish Volatility Breakout") to receive notifications without watching the chart. Combine with volume analysis or momentum oscillators for additional confirmation of breakout strength. Customization Lookback Length (default: 20) — The period for calculating the SMA, Standard Deviation, and ATR. Shorter periods make the indicator more reactive; longer periods produce smoother, more reliable signals. Band Multiplier (StDev) (default: 2.0) — Controls the width of the volatility bands. Higher values create wider bands and fewer breakout signals. Squeeze Multiplier (ATR) (default: 1.5) — Sets the threshold for squeeze detection. Lower values detect squeezes more aggressively; higher values require stronger compression. Band Smoothing (default: 5) — The EMA smoothing period applied to the bands. Higher values produce smoother bands with more lag. Color Settings — Fully customizable colors for bullish, bearish, and squeeze states. Candle Coloring — Toggle on/off to color candles based on the current volatility trend state. Conclusion The Apex Volatility Squeeze & Breakout indicator offers traders a clean, intuitive way to identify low-volatility squeeze conditions and potential breakout points. By fusing Bollinger Band width analysis with Keltner Channel ATR thresholds and applying EMA smoothing, it delivers a unified volatility channel that is both visually elegant and analytically powerful. Whether you trade stocks, forex, crypto, or futures, this tool helps you spot the moments when the market is coiling for its next big move — and positions you to act on it with confidence.
Indicador Pine Script®
por Pineify
1
RSI ULTIMATE TERMINAL PRO [ MATRIX TRADING LAB ]RSI ULTIMATE TERMINAL PRO is not a standard RSI indicator. This is a complete decision-support trading terminal designed to transform raw RSI data into a structured, high-precision trading framework. Instead of showing only overbought/oversold levels, this system provides: Market bias detection Adaptive RSI zones Momentum strength analysis Volume confirmation Reversal & continuation signals Signal quality scoring system Professional dashboard interface 👉 This allows traders to analyze context, not just signals. ⚙️ CORE FEATURES 🧠 Smart RSI Engine Advanced RSI calculation with EMA smoothing Momentum slope & acceleration tracking RSI spread analysis (RSI vs RSI EMA) 📊 Adaptive Zone System Unlike traditional RSI: Dynamic upper/lower zones Extreme overbought / oversold detection Volatility-based zone expansion 👉 The market is not static — this RSI adapts. ⚡ Signal Intelligence Engine The system produces 3 types of signals: 🔄 Reversal Signals Detects potential turning points Based on exhaustion + momentum shift 📈 Continuation Signals Detects trend continuation opportunities Designed for professional trend-following entries ⚠️ Exit Warnings Identifies weakening positions Helps protect profits and reduce risk 🧪 Quality Scoring System Each signal is scored in real-time: WEAK MODERATE STRONG ELITE 👉 This allows you to filter out low-quality trades and focus only on high-probability setups. 🖥️ Terminal Dashboard A professional trading panel showing: RSI value RSI EMA Momentum state Market bias Zone structure Volume strength Active signal Signal quality Last signal 👉 Everything you need in one clean interface. 🎯 HOW TO USE (PROFESSIONAL METHOD) This indicator should NOT be used like a basic RSI. Use the following sequence: 1️⃣ Bias BULLISH → prioritize long setups BEARISH → prioritize short setups NEUTRAL → reduce risk / wait 2️⃣ Zone Understand market position: Bullish range Bearish range Overbought Oversold Extreme zones 👉 Context is everything. 3️⃣ Signal REV LONG → potential bottom reversal REV SHORT → potential top reversal CONT LONG → trend continuation CONT SHORT → trend continuation EXIT WARN → position weakening 4️⃣ Quality Only focus on: STRONG ELITE 👉 Professionals don’t trade every signal. 5️⃣ Momentum + Volume Momentum confirms direction Volume confirms strength Best setups occur when: Momentum is strong Volume is high Signal quality is strong 📈 BEST USE CASES ✔ Trend continuation trading ✔ Pullback entries ✔ Reversal detection ✔ Scalping & intraday setups ✔ Swing trading confirmation ⚠️ IMPORTANT NOTES Overbought ≠ Sell Oversold ≠ Buy This system focuses on: 👉 Context + Confirmation + Quality 🧬 WHY THIS IS DIFFERENT Most RSI indicators: Show levels This system: Interprets the market Filters signals Scores opportunities Guides decision-making 👉 This is not an indicator. 👉 This is a trading system. FINAL THOUGHT If you are still trading RSI like a beginner… This will completely change how you see the market.
Indicador Pine Script®
por goktugozi26
Vigilant Asset Allocation (VAA)1. Where VAA comes from The basic observation behind VAA is not new. Jegadeesh and Titman showed in 1993 that stocks with strong recent returns keep outperforming for roughly three to twelve months. That finding was initially confined to equities, but Asness, Moskowitz and Pedersen (2013) later confirmed that the same pattern holds across bonds, currencies and commodities. Momentum, it turns out, is not just a stock-picking anomaly. It works at the asset-class level too. Moskowitz, Ooi and Pedersen (2012) took this one step further. They looked at time-series momentum rather than cross-sectional momentum. The distinction matters: cross-sectional momentum asks "which asset is doing best?", while time-series momentum asks "is this asset going up at all?". VAA uses both questions, but the time-series version is what drives the breadth filter. Faber (2007) probably deserves credit for bringing momentum into mainstream tactical allocation. His rule was simple: hold an asset when it trades above its ten-month average, sell when it drops below. Crude, but it cut drawdowns significantly. Antonacci (2014) refined this into dual momentum, combining trend direction with relative strength across two universes. Keller and Keuning (2017) built on all of this but added something the earlier models lacked: a breadth dimension. Instead of looking at each asset independently, they count how many offensive assets carry positive momentum. If even one drops below zero (in the aggressive B=1 variant), the entire allocation goes defensive. The reasoning is straightforward. When breadth deteriorates, trouble is usually on the way. Waiting for every asset to turn negative is waiting too long. In their original backtest (1970-2016, using Shiller extended data for the early period and ETF prices from inception), VAA-G4 produced roughly 17.7% annualised with a maximum drawdown of about 16.1% (Keller and Keuning, 2017, Table 2). These are in-sample numbers. They tell you what happened, not what will happen. 2. How the model works 2.1 Momentum scoring Every asset gets a 13612W score, a weighted combination of four return lookbacks: mom = 12 * r1 + 4 * r3 + 2 * r6 + r12 The r values are simple returns: r1 = close / close - 1, and so on for 63, 126 and 252 bars. The one-month return gets the heaviest weight (12), the twelve-month return the lightest (1). Recent momentum matters more, but the yearly anchor keeps the score from overreacting to short-term noise. There is no normalisation. The raw score is used only for two things: ranking assets within each universe, and checking whether it is positive or negative for the breadth count. 2.2 The two universes Keller and Keuning specified these defaults: Offensive (growth): - SPY (S&P 500) - EFA (international developed) - EEM (emerging markets) - AGG (US aggregate bonds) Defensive (preservation): - LQD (investment-grade corporate bonds) - IEF (7-10 year treasuries) - SHY (1-3 year treasuries) All seven are changeable in the settings. If you swap in other ETFs, make sure they have enough history. 2.3 The breadth rule Each day the indicator counts how many offensive assets have positive momentum. Call the count of non-positive ones n_negative. The rule: - n_negative >= B (default 1): go to the top defensive asset - n_negative < B: go to the top offensive asset With B=1, one single negative asset triggers the switch. That is aggressive in the sense of being quick to flee. Keller and Keuning argue this is the right trade-off. Breadth erosion tends to precede broader sell-offs, so early rotation is worth the occasional whipsaw. 2.4 Rebalancing The paper prescribes monthly rebalancing. The indicator locks the allocation at the close of the last trading day of each month. Everything that happens between rebalances is monitoring only. The dashboard shows both the locked position ("held") and what the model would do today ("live"). Daily rebalancing is available as an option. It is not what the paper tested. 2.5 Ties When two assets have the exact same momentum score, the one listed first wins. Sounds arbitrary because it is. But four overlapping return windows make exact ties rare in practice. 3. What you need - TradingView, any plan (free works, Pro lifts the alert cap) - A daily chart. The lookbacks assume daily bars. On weekly or intraday charts the periods are wrong and the dashboard flags it. - 252 bars of history for every symbol. Until that is available, the model shows "warming up". 4. Setup and settings 4.1 Getting started Add the indicator to any daily chart via the TradingView indicator search. It loads with the Keller/Keuning defaults. The status row at the bottom of the dashboard tells you when the model is ready. 4.2 Strategy Breadth Threshold (B): 1 matches the paper. Raising it to 2 means two assets have to go negative before the model rotates. Fewer whipsaws, slower reaction. Monthly Rebalancing: On by default. Off gives you daily updates, which is useful for experimentation but not what the literature tested. 4.3 Symbols Offensive and defensive universes are fully configurable. If you replace an ETF, check that TradingView has daily data going back at least a year. 4.4 Visuals Background Mode: "Position" tints the background green (offensive) or red (defensive). "Off" removes it. Candle Colouring: Paints candles by breadth strength. Full green at 4/4 positive, full red at 0/4, faded tones in between. Transparency is adjustable. Color Theme: Eight palettes. All of them work in both dark and light mode. Glow Effect: Adds layered transparent lines behind the main plot. Useful if the signal gets lost in a busy chart. Off by default. 4.5 Dashboard The table in the top right (moveable) shows: - Regime: offensive or defensive, with the breadth count - Allocate: which specific ETF to hold (100% always) - Live: intra-month reading (only visible in monthly mode) - Individual asset rows: 13612W scores and a trend arrow (up, down, or flat compared to 5 bars ago) - Status: "active", "warming up", or "wrong timeframe" 4.6 Alerts Five conditions, all behind a master switch: - Regime switches to offensive at month-end - Regime switches to defensive at month-end - Held asset changed (same regime, different pick) - Live breadth dropped between rebalances - Live breadth recovered between rebalances The live alerts are early warnings, not trade signals. They tell you the next rebalance might produce a change. 5. Reading the chart The step line maps the breadth count to a 0-10 scale: | Breadth | Value | What it means | | 4/4 positive | 0.0 | Everything trending up | | 3/4 positive | 2.5 | One weak link, still offensive with B=1 | | 2/4 positive | 5.0 | Defensive if B is 2 or below | | 1/4 positive | 7.5 | Broad weakness | | 0/4 positive | 10.0 | Nothing working | The threshold line sits at B * 2.5. Above it means defensive. The zone fill below the threshold marks the offensive region. One thing to keep in mind: the distances between these steps do not mean anything quantitative. 5.0 is not "twice as bad" as 2.5. It is an ordinal display, not a risk score. 6. How to actually use it The simplest workflow: check the dashboard on the last trading day of the month. Look at the "Allocate" row. Buy that ETF at the open of the next session. Done until next month. If you want a heads-up, turn on the live alerts. A "breadth dropped" alert mid-month tells you the next rebalance might flip regimes. That gives you time to plan, not to act early. The month-end values are what count. VAA does not know about your taxes, your broker fees, or your risk tolerance. Treat it as one input to your decision process, not the whole process. 7. What the model does not do It does not model execution. There is no bid-ask spread, no slippage, no market impact. It cannot protect you from whipsaws. Momentum systems by nature struggle in choppy, directionless markets. The breadth filter helps, but a month where sentiment flips back and forth will still produce unnecessary trades. Monthly rebalancing is both a feature and a weakness. It keeps you from overtrading, but it also means a crash in the middle of a month does not trigger any action until month-end. The backtests in the paper used extended data that goes back to 1970. The actual ETFs (EEM, AGG) only started trading in 2003. TradingView data will not replicate the full historical period. The model is always invested. There is no cash option. You are either in the top offensive or the top defensive ETF. Momentum can stop working. Correlations change. What the academic literature documents as a persistent anomaly can go through multi-year stretches of underperformance. The 2009 recovery, for instance, was fast enough to catch most trend-following systems off-guard. 8. Common questions Why does it say "warming up"? The model needs 252 daily bars per symbol. Loading the indicator on a chart without enough history means it cannot compute the twelve-month return component. Can I run this on a 4-hour chart? You can, but 21 bars on a 4-hour chart is not a month. The lookbacks will be wrong. The dashboard will flag this. I changed the symbols and the readings look off. Make sure the replacement ETFs actually have a year of daily data on TradingView. Some regional ETFs or newer funds do not. The live reading disagrees with the held position. That is expected in monthly mode. The held position only updates at month-end. The live reading shows what would happen if you rebalanced today. They diverge by design. Should I trade every time the live reading changes? No. Unless you deliberately turned off monthly rebalancing, the live reading is for awareness, not for execution. References Antonacci, G. (2014) Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk. New York: McGraw-Hill. Asness, C.S., Moskowitz, T.J. and Pedersen, L.H. (2013) 'Value and Momentum Everywhere', The Journal of Finance, 68(3), pp. 929-985. doi:10.1111/jofi.12021. Faber, M.T. (2007) 'A Quantitative Approach to Tactical Asset Allocation', The Journal of Wealth Management, 9(4), pp. 69-79. Jegadeesh, N. and Titman, S. (1993) 'Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency', The Journal of Finance, 48(1), pp. 65-91. doi:10.1111/j.1540-6261.1993.tb04702.x. Keller, W. and Keuning, J.W. (2017) 'Breadth Momentum and Vigilant Asset Allocation (VAA): Winning More by Losing Less', SSRN Electronic Journal. doi:10.2139/ssrn.3002624. Moskowitz, T.J., Ooi, Y.H. and Pedersen, L.H. (2012) 'Time series momentum', Journal of Financial Economics, 104(2), pp. 228-250. doi:10.1016/j.jfineco.2011.11.003.
Indicador Pine Script®
por EdgeTools
MACD Pro Signals Full v8.52. Detailed Description (Large Text Box) 🌟 Indicator Introduction This is a full-featured enhanced MACD indicator. Based on the classic MACD formula, it adds advanced visual upgrades, signal enhancements, and automatic divergence detection. It is suitable for all markets such as Stocks, Futures, Forex, and Cryptocurrencies. It helps you quickly identify trends, momentum, trading signals, and reversal opportunities at a glance. ✨ Core Features Color-Coded Momentum HistogramAutomatically distinguishes 4 states: Strong Bullish / Weak Bullish / Strong Bearish / Weak Bearish.Clearly shows the strength of current momentum and trend continuity, making it easy to judge whether the price is accelerating or weakening. MACD & Signal Line Candle VisualizationConverts the traditional MACD line and Signal line into candlestick style.The color changes automatically with upward/downward trends, making trend turning points and momentum more intuitive than traditional lines. Dual-Position Golden/Death Cross Markers Main Chart: Displays "👍" (Golden Cross) and "👎" (Death Cross) above/below price bars for clear entry signals. Subwindow: Synchronous markers on the MACD area, no overlap on the main chart, double confirmation without missing signals. Auto Bullish/Bearish Divergence DetectionAutomatically scans price and MACD divergence structures.Draws divergence lines in the subwindow and marks strength percentage (0-100%) on the main chart.Perfect for capturing high-probability trend reversals. Full CustomizationSupports adjusting MACD periods, all element colors, label offsets, and pivot parameters.Adaptable to different assets and time frames. 📊 How to Use Bullish Signal: Golden Cross 👍 + Zero Line Above + Expanding Bullish Histogram + Bullish Divergence = Strong Long Opportunity Bearish Signal: Death Cross 👎 + Zero Line Below + Expanding Bearish Histogram + Bearish Divergence = Strong Short Opportunity Divergence Usage: The higher the percentage, the stronger the divergence signal, and the higher the probability of a trend reversal.
Indicador Pine Script®
por j9798
Flexible Moving Averages with MACD and RSI Every stock momentum can be identified either by crossing of higher EMA by lower EMA or MACD line crossing signal line and moving up or RSI value rising above 45 or 50. This indicator combines Moving averages with MACD and RSI How to use: Configure any or all of 5 moving averages according to your preference. It can be EMA or SMA. Configure symbols for MACD crossing or RSI rising. By default, if RSI crosses above 50, green triangle appears below candle. If RSI crosses 50 and comes down, red inverted triangle appears above candle By default, if MACD line crosses signal line and moves above, green dot appears below candle. If MACD line crosses signal line and moves down, red dot appears above candle These indications can give the user how much time RSI and MACD crossing happened along with EMA crossovers. User can take calculated decision and risk
Indicador Pine Script®
por Naathaz
QuantEdge Momentum ML [PRO]🟦 QuantEdge Momentum ML PRO is a k-Nearest Neighbors driven momentum oscillator built on an adaptive machine-learning core. Unlike RSI, Stochastic, or MACD — which apply the same static formula to every asset — QE-ML PRO learns the dual-horizon RSI fingerprints that have historically led to bullish versus bearish outcomes on the exact instrument being traded, then scores the current bar against the N closest historical matches. The result is a non-parametric, self-calibrating oscillator whose decision boundary is shaped by the asset's own behaviour rather than a hard-coded curve. The indicator integrates nine independent layers — feature engine, training sampler, k-NN predictor, WMA signal line, stdev-adjusted OB/OS bands, filtered signal dots, gradient channel, theme-adaptive dashboard, and a nine-theme palette — all rendered on a single, clean oscillator panel. 🟦 HOW THE CORE ENGINE WORKS **Dual-Horizon RSI Feature Vector** Each bar, the Feature Engine computes two RSI values at different lookback windows and smooths both through a shared trend-length WMA: - `rsiFast = WMA(RSI(close, FastPeriod), TrendLength)` — reactive short-term momentum - `rsiSlow = WMA(RSI(close, SlowPeriod), TrendLength)` — structural mid-term momentum The pair `(rsiSlow, rsiFast)` is a 2-dimensional point in RSI feature space. Every training sample stores one such point along with a ±1 label that records whether price rose or fell since the previous sample. Over time the dataset accumulates a cloud of labelled points that maps which RSI states historically preceded up-moves versus down-moves on this exact asset. **Training Sampler — Multi-Trigger Collector** Three collection modes decide when to append a new labelled sample: | Mode | Trigger | Use Case | |---|---|---| | **MA Crossover** | Fast WMA crosses Slow WMA | Clean, sparse samples — classic single-trigger behaviour | | **Periodic** | Every N bars (user-set) | Fills dataset fast on new / low-history charts | | **Hybrid** | MA crossover **OR** every N bars | Richest training set — recommended for fresh assets | Sampling is gated by `barstate.isconfirmed` so the dataset never absorbs unconfirmed values from a flickering live bar. **k-NN Predictor with Adaptive k** On every bar, the predictor computes Euclidean distance in the 2D RSI feature space between the live `(rsiSlow, rsiFast)` point and every historical sample: ``` d = sqrt((rsiSlow_now - rsiSlow_hist)² + (rsiFast_now - rsiFast_hist)²) ``` The K closest historical points vote by summing their ±1 labels. The effective K is resolved adaptively using the classical statistical heuristic: ``` kEff = max(3, min(kMax, floor(sqrt(N)))) ``` This means early bars — when only a handful of samples exist — use a small K, and the value stabilises as the dataset fills. On a fresh chart you never get a noisy prediction from an undersized neighborhood, and on a mature dataset K automatically scales up for smoother output. **Bias Correction — Label-Mean Recentering** Raw k-NN output is biased whenever the label distribution is skewed. On a trending asset, Periodic sampling fills the dataset with mostly +1 (or mostly −1) labels, pushing every prediction off zero. QE-ML PRO subtracts the expected value from the raw sum: ``` prediction = neighborLabelSum − (kEff × meanLabelAcrossDataset) ``` This keeps the mid-level visually centred at zero regardless of how trending the underlying asset has been. The correction is applied on every bar and is what makes the oscillator read cleanly on both sideways and strongly trending markets. **Minimum Sample Gate** Until the dataset has reached the user-defined Minimum Training Samples threshold, the predictor outputs exactly zero. This prevents unreliable readings during the warm-up phase on fresh charts. **FIFO Rotation** The dataset is hard-capped at Max Dataset Size. Once the cap is reached, the oldest sample is discarded on every new insertion — classical rolling window memory that keeps the k-NN scan bounded and the indicator fast on long histories. 🟦 PREDICTION LINE — FIVE VISUAL STYLES All five styles are line-based. Only the visual effect differs — the underlying k-NN math is identical across styles. | Style | Character | |---|---| | **Stratum** | Thick adaptive line with zone-based opacity: solid in extreme zones, semi-transparent in the mid zone. Layered intensity aesthetic — default | | **Neon** | Bright core line with an outer glow halo. Cyberpunk luminous effect, best on dark backgrounds | | **Resonance** | LRI-style gradient line that fades near the midline and brightens toward the rolling extremes | | **Pulse** | Adaptive bull/bear color (above midline = bull, below = bear) plus the WMA signal line. The QE-ML PRO classic look | | **Mono** | Single flat theme-bull line, no gradient, no adaptive coloring. Minimalist single-color silhouette | 🟦 SIGNAL LINE A WMA of the raw prediction output, used as a crossover trigger line in the MACD convention. Crossovers between the prediction and signal line mark momentum regime changes. **Two Visual Styles** | Style | Rendering | |---|---| | **Neon** | Bright core line wrapped in a wider semi-transparent glow halo — cyberpunk aesthetic | | **Flat** | Plain single-color line, no halo, no gradient — minimalist clean look | 🟦 SIGNAL DOTS — FILTERED CROSSOVER MARKERS A two-layer neon cross-dot renderer fires on every Prediction × Signal crossover that survives the active filter mode. Four progressive filters decide which raw crosses reach the chart: | Filter Mode | Behaviour | Signal Count | |---|---|---| | **All Crosses** | Every cross becomes a dot | Highest — noisy on choppy assets | | **Zone Only** | Only crosses inside an OB or OS strip | Mean-reversion triggers — strongest reversal setups | | **Mid Aligned** | Bull dots only above mid, bear dots only below | Trend-following — keeps you on regime side | | **Strict** | Zone Only + Mid Aligned + extra strength multiplier on mid-zone crosses | Fewest signals, highest conviction — default | Two additional gates filter out whipsaws: - **Cooldown (bars)** — minimum spacing between consecutive dots, prevents cluster spam in ranges - **Min Strength** — minimum `|prediction − signal|` separation at the moment of the cross, drops razor-thin crossovers that close back on themselves Each dot is a two-layer plot: an outer glow halo with user-adjustable size and opacity, and a bright solid core on top — independently sized and opacity-controlled so users can dial in the exact visual weight they want. The dot is placed at the actual cross point: bull dots at `min(prediction, signalLine)`, bear dots at `max(prediction, signalLine)`. 🟦 DYNAMIC BANDS — STDEV-ADJUSTED OB / OS ZONES QE-ML PRO does not use fixed 80 / 20 overbought / oversold levels. Instead, the bands adapt to the actual historical range of the prediction output: - **Channel Extremes** — rolling highest / lowest of the prediction over a user-configurable lookback - **Stdev Band** — EMA of rolling standard deviation of the prediction, multiplied by the user's stdev length - **OB Level** = `rangeHi − stdevBand` (inner boundary of the overbought strip) - **OS Level** = `rangeLo + stdevBand` (inner boundary of the oversold strip) The result is a pair of mean-reversion zones that tighten during quiet markets and widen during volatile ones — no manual recalibration needed across assets. The strips are rendered as gradient fills anchored on the live prediction plot, so they only appear visually while the prediction is actually inside the zone. 🟦 CHANNEL GRADIENT Two symmetric gradient fills bracket the mid line. The upper fill stretches from `midValue` to `rangeHi`, the lower fill from `midValue` to `rangeLo`. Opacity fades from full intensity at the extremes to fully transparent at the midline — a visual range meter showing how close the prediction is sitting to its historical boundaries. Colors are pulled from the active Theme. A single opacity slider controls the gradient intensity. 🟦 DASHBOARD — LIVE DATA PANEL A compact 2-column × 7-row monospace panel drawn on the last bar only (zero historical overhead). Every field updates in real time on the live bar. | Row | Left | Right | |---|---|---| | Header | QE-ML PRO | Regime (▲ BULL / ▼ BEAR / ■ NEUTRAL) | | Row 1 | Prediction | Raw value + trend arrow vs previous bar | | Row 2 | Signal | WMA trigger line value | | Row 3 | Strength | 10-block gauge of `|prediction − signal|` normalised against rolling channel | | Row 4 | Zone | OB / MID / OS tag | | Row 5 | Dataset | Sample count / effective k | | Row 6 | Mode | Active Learning Mode (MA Cross / Periodic / Hybrid) | **Theme-Aware Auto-Invert** The panel background scaffolds auto-switch: - **Tropic / Amber / Pastel / Cyber / Gold / Electric / Candy** → dark panel with bright theme accent text - **Midnight / Graphite** → light panel with dark theme accent text This guarantees legibility on every theme without breaking the theme's color identity — because Midnight and Graphite use deep dark bull tones that would drown against a black panel. **Direction via Glyphs, Not Color** Both columns share the same full-strength theme tone. Regime direction is conveyed by `▲ ▼ ■` glyphs rather than color shifts, which keeps the panel reading cleanly even on the most minimal themes. 🟦 NINE COLOR THEMES One theme selector drives every colored component — Prediction line, Signal line, Channel fill, OB / OS strips, Mid-level line, Signal Dots, and Dashboard panel. No per-color manual inputs. | Theme | Character | Bull | Bear | |---|---|---|---| | **Tropic** | Cyan steel + deep orange — electric contrast (default) | Cyan | Deep Orange | | **Amber** | Warm amber + indigo blue — fire tones | Amber | Red | | **Pastel** | Sky blue + soft lavender — cool arctic glow | Sky Blue | Lavender | | **Cyber** | Neon lime + hot crimson — cyber terminal | Neon Green | Crimson | | **Gold** | Bright gold + scarlet — solar warmth | Yellow Gold | Red | | **Electric** | Electric aqua + magenta — high-voltage neon | Aqua | Magenta | | **Candy** | Neon green + hot pink — dark energy pop | Mint Green | Hot Pink | | **Midnight** | Deep navy + dark crimson — dark depth (auto light dashboard) | Navy Blue | Dark Red | | **Graphite** | Near-black + silver grey — monochrome minimal (auto light dashboard) | Near Black | Grey | 🟦 ALERT SYSTEM — TEN CONDITIONS Every alert is gated by its matching "Show X" visibility toggle — if a component is hidden from the chart, its alerts are automatically suppressed. This eliminates the mismatch between visual signals and alert signals that plagues many indicators. | Alert | Condition | Gated By | |---|---|---| | Crossover OB | Prediction crosses above the overbought boundary | Show OB/OS Fill | | Crossunder OB | Prediction crosses back down through OB | Show OB/OS Fill | | Crossover OS | Prediction crosses up through oversold boundary | Show OB/OS Fill | | Crossunder OS | Prediction crosses below the oversold boundary | Show OB/OS Fill | | Crossover Mid | Prediction crosses above the mid line — bullish regime flip | Show Mid Level | | Crossunder Mid | Prediction crosses below the mid line — bearish regime flip | Show Mid Level | | Crossover Signal | Prediction crosses above its WMA signal line (MACD bullish) | Show Signal Line | | Crossunder Signal | Prediction crosses below its WMA signal line (MACD bearish) | Show Signal Line | | Bull Signal Dot | A filtered Bull Signal Dot is plotted (uses Filter Mode + Cooldown + Min Strength) | Show Signal Dots | | Bear Signal Dot | A filtered Bear Signal Dot is plotted (uses Filter Mode + Cooldown + Min Strength) | Show Signal Dots | 🟦 SETTINGS REFERENCE **Visual** - Theme — nine cohesive palettes. Default: Tropic **Machine Learning** - Neighbors (k) — upper bound on neighbors used by the predictor. Default: 100 - Adaptive k — scales k with dataset size using the `floor(sqrt(N))` heuristic. Default: ON - Learning Mode — MA Crossover / Periodic / Hybrid. Default: MA Crossover - Sample Every (bars) — bar interval for the Periodic / Hybrid trigger. Default: 5 - Minimum Training Samples — warm-up gate, predictor outputs zero until reached. Default: 30 - Max Dataset Size — hard FIFO cap. Default: 500 (safe on all timeframes) **Feature Engine** - Trend Length — WMA smoothing applied to both RSI features. Default: 20 - RSI Fast Period — first feature dimension. Default: 5 - RSI Slow Period — second feature dimension. Default: 20 - MA Fast Period — fast WMA for the crossover training trigger. Default: 5 - MA Slow Period — slow WMA for the crossover training trigger. Default: 20 **Prediction Line** - Show Prediction Line — master toggle. Default: ON - Prediction Style — Stratum / Neon / Resonance / Pulse / Mono. Default: Stratum - Prediction Width — 1 to 5. Default: 2 **Signal Line** - Show Signal Line — toggle. Default: ON - Signal Style — Neon / Flat. Default: Neon - Signal Period — WMA length of the signal line. Default: 20 - Signal Width — 1 to 5. Default: 1 **Signal Dots** - Show Signal Dots — toggle. Default: ON - Filter Mode — All Crosses / Zone Only / Mid Aligned / Strict. Default: Strict - Cooldown (bars) — minimum spacing between dots. Default: 5 - Min Strength — minimum `|prediction − signal|` at the cross. Default: 0.5 - Core Dot Size — 1 to 8. Default: 3 - Core Dot Opacity — 0 to 100. Default: 100 - Glow Dot Size — 1 to 12. Default: 8 - Glow Dot Opacity — 0 to 100. Default: 30 **Channel Fill** - Show Channel Fill — toggle. Default: ON - Channel Opacity — 0 to 100. Default: 25 - Channel Lookback — rolling highest / lowest window. Default: 500 **OB / OS Fill** - Show OB/OS Fill — toggle. Default: ON - Zone Stdev Length — stdev window that offsets the OB / OS boundaries inward. Default: 20 **Mid Level** - Show Mid Level — toggle. Default: ON - Mid Level Value — Y-value of the reference line. Default: 0 - Mid Level Style — Solid / Dashed / Dotted. Default: Dashed **Dashboard** - Show Dashboard — toggle. Default: ON - Panel Position — six slots (Top/Middle/Bottom × Right/Left). Default: Middle Right - Panel Text Size — Tiny / Small / Normal / Large. Default: Small **Alerts** - Ten opt-in toggles, one per alert condition. All default: ON 🟦 TRADER PRESETS — SETTINGS BY STYLE QE-ML PRO is volatility-agnostic thanks to the adaptive bands and bias correction, but the reactivity of the predictor scales directly with the feature and sampler parameters. The four presets below are tested starting points you can drop straight into the settings panel — adjust by ±20% to taste. --- ** SCALPER — 1m / 3m / 5m** High-frequency entries, tight stops, many signals per session. Priority is reaction speed — you want the predictor to flip states within a handful of bars of an actual move. | Setting | Value | |---|---| | Trend Length | 10 | | RSI Fast Period | 3 | | RSI Slow Period | 14 | | MA Fast Period | 3 | | MA Slow Period | 10 | | Signal Period | 8 | | Neighbors (k) | 40 | | Adaptive k | ON | | Learning Mode | **Hybrid** | | Sample Every | 2 | | Minimum Training Samples | 20 | | Max Dataset Size | **300** (keeps 1m charts fast) | | Filter Mode | **All Crosses** or Zone Only | | Cooldown | 2 | | Min Strength | 0.3 | | Channel Lookback | 200 | | Zone Stdev Length | 10 | | Prediction Style | Neon or Stratum | **Why:** Low smoothing (Trend=10) + short RSI pair (3/14) keeps the features razor-sharp. Hybrid learning means you never wait for an MA crossover during quiet 1m sessions. Max Dataset capped at 300 protects you from the TradingView per-bar calculation limit on long 1m histories. --- ** DAY TRADER — 15m / 30m / 1H** Balanced reactivity and conviction — the default profile. You want clean crosses without noise spam, and signals that survive the open / close volatility spikes. | Setting | Value | |---|---| | Trend Length | 20 (default) | | RSI Fast Period | 5 (default) | | RSI Slow Period | 20 (default) | | MA Fast Period | 5 (default) | | MA Slow Period | 20 (default) | | Signal Period | 20 (default) | | Neighbors (k) | 100 (default) | | Adaptive k | ON | | Learning Mode | **MA Crossover** (default) | | Minimum Training Samples | 30 (default) | | Max Dataset Size | 500 (default) | | Filter Mode | **Strict** (default) | | Cooldown | 5 (default) | | Min Strength | 0.5 (default) | | Channel Lookback | 500 (default) | | Zone Stdev Length | 20 (default) | | Prediction Style | Stratum (default) | **Why:** Every default value was tuned for this range. Strict filter + 5-bar cooldown keeps the dot count honest on a 30m chart. MA Crossover sampling gives you clean sparse data since 15m+ charts already have enough crossover events. --- ** SWING TRADER — 4H / 1D** Lower signal frequency, higher conviction per signal. You're holding for days or weeks — every dot needs to mean something. | Setting | Value | |---|---| | Trend Length | 30 | | RSI Fast Period | 7 | | RSI Slow Period | 30 | | MA Fast Period | 7 | | MA Slow Period | 30 | | Signal Period | 30 | | Neighbors (k) | 150 | | Adaptive k | ON | | Learning Mode | MA Crossover | | Minimum Training Samples | 50 | | Max Dataset Size | 800 | | Filter Mode | **Strict** | | Cooldown | 10 | | Min Strength | 0.8 | | Channel Lookback | 800 | | Zone Stdev Length | 30 | | Prediction Style | Stratum or Mono | **Why:** Longer feature periods mean the predictor only moves on genuine structural shifts. Larger k (150) + bigger dataset (800) gives the k-NN vote a wider base so outliers don't flip the sign. Cooldown of 10 bars on a 4H chart = 40 hours minimum between dots — exactly what a swing trader wants. --- ** POSITION / LONG-TERM — 1D / 1W / 1M** Macro regime detection. You're looking for the handful of generational setups per year — noise is the enemy. | Setting | Value | |---|---| | Trend Length | 50 | | RSI Fast Period | 10 | | RSI Slow Period | 40 | | MA Fast Period | 10 | | MA Slow Period | 40 | | Signal Period | 40 | | Neighbors (k) | 200 | | Adaptive k | ON | | Learning Mode | **Hybrid** | | Sample Every | 3 | | Minimum Training Samples | 40 | | Max Dataset Size | 1000 | | Filter Mode | **Strict** | | Cooldown | 15 | | Min Strength | 1.0 | | Channel Lookback | 1000 | | Zone Stdev Length | 40 | | Prediction Style | Mono or Pulse | **Why:** Weekly and monthly charts have few crossover events per year — without Hybrid mode the dataset starves. Sample Every = 3 on a weekly chart means one sample every 3 weeks, which is plenty of structural density. Min Strength 1.0 filters out every shallow cross — you only see dots on generational momentum inflections. --- **Tuning Tip** If the predictor feels **too reactive** → increase Trend Length and Signal Period by 25%, raise Cooldown. If the predictor feels **too sluggish** → switch Learning Mode to Hybrid, decrease Min Samples, lower Trend Length. If the dashboard shows **Dataset N is stuck low** → switch Learning Mode from MA Crossover to Hybrid — crossover events are too rare on your current settings. If you see **runtime / timeout errors** on long histories → drop Max Dataset Size to 300 and Channel Lookback to 300. 🟦 COMPATIBILITY Works on all asset classes and all timeframes in TradingView Pine Script v6. - **Crypto** — Spot, futures, perpetual contracts - **Forex** — All pairs - **Equities** — Stocks, ETFs, indices - **Commodities** — Metals, energy, agriculture - **Timeframes** — 1m through Monthly The k-NN engine learns each asset's own RSI fingerprint distribution, and the stdev-adjusted bands auto-scale to the volatility of that distribution, so the indicator is truly self-calibrating across assets and timeframes — no manual recalibration required. 🟦 TECHNICAL NOTES - Pine Script v6 - No repainting — training samples are gated by `barstate.isconfirmed` so the dataset never absorbs unconfirmed live-bar values - Dataset is hard-capped via FIFO rotation; no unbounded memory growth - Dashboard renders only on `barstate.islast` — zero historical overhead - All drawing objects are stateless plots (no label / box / line object pools), so `max_*_count` limits cannot be exceeded - k-NN distance pass is O(N), sort is O(N log N), both bounded by Max Dataset Size - Default Max Dataset Size of 500 is tuned to stay within TradingView's per-bar calculation budget on histories up to ~50,000 bars - Bias correction uses a single extra accumulator pass during the distance sweep — no performance penalty 🟦 DISCLAIMER This indicator is provided for educational and informational purposes only. It does not constitute financial advice. Past performance does not guarantee future results. The k-NN engine learns from historical patterns, but markets do not guarantee that historical patterns will repeat. Always conduct your own analysis and apply proper risk management.
Indicador Pine Script®
por a_jabbaroff
6
Anchored Value Distribution Oscillator (Zeiierman)█ Overview Anchored Value Distribution Oscillator (Zeiierman) is a structure-driven oscillator that models price as a dynamic value distribution, then measures where price is positioned within that structure to reveal balance, imbalance, and shifting market conditions. Instead of relying purely on price momentum, the indicator builds a rolling, volume-weighted distribution of price over time. From this structure, it extracts key reference levels such as the value center, high/low distribution bands, and peak activity zones. These are then used to normalize the price into a bounded oscillator. Alongside the distribution, the script constructs an adaptive trailing anchor that reacts to structural shifts and volatility. The oscillator combines both the structural distribution and the adaptive anchor into a single positioning score, producing a contextual view of trend, extension, and balance. The result is an oscillator that reflects not just direction, but where price sits within its evolving value landscape. █ How It Works ⚪ Distribution Engine (Value Model) The core of the indicator is a rolling value distribution built from price and volume. Each bar contributes to a log-scaled price histogram, where: price ranges are segmented into rows volume is distributed across those rows candle bodies and wicks are weighted differently older data gradually decays over time This produces a continuously updating view of: Point of Control (vp) Value High / Value Low (vh / vl) Outer extremes (xh / xl) Distribution center (cen) Unlike a static volume profile, this model evolves with the market and adapts to both recent and historical activity. ⚪ Adaptive Anchor (Trend Engine) On top of the distribution, the script builds an adaptive trend anchor (anc). The anchor is derived from a structural base: blended from the distribution center and peak activity offset using volatility (ATR) constrained to trail price in the active direction The anchor flips direction when the price crosses it, and then trails using a volatility-adjusted distance. This creates a structure-aware trend model that behaves similarly to a trailing stop, but is grounded in value distribution rather than raw price movement. ⚪ Normalized Positioning Model The oscillator converts price into a normalized position within the distribution. Two independent scores are calculated: Position relative to the adaptive anchor (scAnc) Position relative to the value distribution (scVp) Each score maps price into a bounded range: -50 → extreme downside -25 - 20 → fair value +50 → extreme upside These scores are then combined into a single output using a weighted blend. A confidence factor reduces the distribution score's contribution when it disagrees with the anchor, ensuring cleaner signals in conflicting conditions. ⚪ Smoothed Oscillator Output The final oscillator (outAvg) is a smoothed combination of: trend-aware positioning (anchor) structure-aware positioning (distribution) █ How to Use ⚪ Read Position Relative to Value Use the oscillator to understand where the price sits within its value distribution: Above 25 → price is positioned above fair value Below -25 → price is positioned below fair value Near extremes (±50) → price is extended relative to structure This helps distinguish between: continuation conditions mean reversion zones balanced market states ⚪ Follow the Adaptive Trend Anchor The trailing anchor provides a clear trend reference: Price above anchor → bullish regime Price below anchor → bearish regime Anchor flips → potential regime shift █ Settings Lookback – Controls how much historical data is used to build the value distribution. Higher values produce smoother structure, while lower values increase responsiveness. Canvas Pad – Expands the distribution range to include more extreme price levels. Increasing this captures broader moves but reduces precision. Rebuild Drift – Determines how much the distribution can drift before being recalculated. Lower values rebuild more frequently, higher values allow more continuity. Signal Length – Controls the smoothing of the signal line. Higher values reduce noise but increase lag. Profile Center Bias – Blends between the value distribution center and the point of control to define the structural base. Higher values anchor the trail to the broader distribution center, while lower values make it follow peak activity more closely. Trail Acceleration – Controls how quickly the trailing stop tightens as the price accelerates. Higher values make the trail react more aggressively to impulsive moves, reducing lag during strong trends. Max Trail Acceleration – Limits how much the acceleration can compress the trailing distance. Higher values allow the stop to tighten more during rapid expansion, while lower values keep behavior closer to the original, smoother trail. ----------------- Disclaimer The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information. All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Indicador Pine Script®
por Zeiierman
4
Adaptive Pivot-Length RSIAdaptive Pivot-Length RSI (APL-RSI) An RSI that tunes its own length to whatever cycle the market is actually trading, rather than locking you into a fixed 14-period window. How it works The indicator runs a multi-scale pivot sweep across strengths from 14 to 100, measuring the distance between consecutive confirmed swing highs and lows. Those distances build a probability mass function (PMF) of the market’s dominant pivot spacing. The mode of that PMF — the most frequently occurring swing-to-swing length — becomes the RSI period. Updates are sticky (gated by a tolerance threshold) to prevent length flicker, and the engine waits for a minimum sample count before engaging. An “alternate H/L only” toggle enforces true zig-zag spacing by ignoring same-type pivots in a row. The RSI itself is a true Wilder implementation with manually maintained gain/loss state (α = 1/L), which avoids the unreliability of ta.rma when fed a series-int length. A companion smoothed line uses a WMA of length √L, which preserves phase at the dominant cycle rather than lagging it. Levels Instead of fixed 70/30 thresholds, overbought/oversold and upper/lower mid-bands are computed as empirical percentiles of the adaptive RSI’s own distribution over a configurable lookback. A live percent-rank readout shows where the current value sits in that distribution. Readouts The info table shows the current adaptive length, smoothing length, divergence pivot length, total pivot samples collected, current RSI value, self-percentile rank, OB/OS levels, and zone state (OB / Upper / Mid / Lower / OS). Notes All pivots are confirmed (non-repainting). Bar coloring and optional signal shapes are available in the UI Options. Alerts fire on OB/OS crosses and divergence detections.​​​​​​​​​​​​​​​​
Indicador Pine Script®
por Cmo22
Seykota Trend SystemHere's a breakdown of everything the script does: EMA Engine Three EMAs: fast (default 15), slow (default 150), and a signal EMA (default 9) used as a confirmation layer. The 150/15 pairing mirrors Seykota's published S&P model on his TSP website. The cloud fill between fast and slow gives an instant read on trend health — teal when bullish, red when bearish. Trailing Stop — Two Modes ATR mode ratchets the stop upward in a long (or downward in a short) so it can never move against you. Swing mode uses the highest/lowest bar over a lookback period instead — closer to how Seykota described using support/resistance corridors in his Gold model. Switch between them in settings. Position Sizing Output The core Seykota formula: Units = (Account × Risk%) ÷ Stop Distance. Every entry label shows the calculated position size live on the chart. As volatility expands (wider ATR → wider stop → fewer units), the system automatically sizes down. As volatility contracts, it sizes up. This is the mechanism behind "keep bets small" — it's dynamic, not a fixed number. ADX Filter Seykota only wanted to be in trending markets. The ADX filter blocks signals when ADX is below your threshold (default 20), keeping the system out of choppy sideways conditions where trend-following underperforms. Volume Filter Optional confirmation that the move has institutional participation behind it — volume must be above its MA multiplied by a factor you control. HUD Table Bottom-right panel shows live: trend state, both EMAs, ATR, trailing stop level, ADX reading, risk dollars per trade, and current position size. Alerts Four alert conditions are wired up — long signal, short signal, trend flip to bull, trend flip to bear — ready to connect to TradingView webhooks or notifications. Suggested starting parameters by market: Futures/commodities: 150/15 EMA, ATR ×3.0, ADX 20 Equities (daily): 200/50 EMA, ATR ×2.5, ADX 20 Crypto (daily): 100/25 EMA, ATR ×2.0, ADX 25 (crypto is noisier)
Indicador Pine Script®
por yavuzsikca
MACD 6-20 Fast MACD with Signal ArrowsMACD 6/20 — Fast MACD with Signal Arrows A faster MACD variant using EMA 6/20 instead of the standard 12/26 settings, with a 9-period signal line. Designed for traders who want earlier trend detection and quicker crossover signals. What it does: This indicator plots the MACD line (EMA 6 minus EMA 20) against a 9-period EMA signal line, with a color-coded histogram and visual crossover arrows. Features: - MACD line (blue) and Signal line (orange) - Histogram: green when MACD > Signal, red when MACD < Signal - Green triangle arrows at bullish crossovers (MACD crosses above Signal) - Red triangle arrows at bearish crossovers (MACD crosses below Signal) - All parameters adjustable (Fast Length, Slow Length, Signal Smoothing) - Histogram can be toggled on/off Why 6/20 instead of 12/26? The shorter EMA periods make the indicator more responsive to price changes. The 6/20 combination catches trend shifts earlier than the standard MACD, which is useful for swing trading and intraday setups. The trade-off is more signals — filter with higher timeframe context or price action confirmation. How to use: - Bullish signal: green arrow (MACD crosses above Signal) - Bearish signal: red arrow (MACD crosses below Signal) - Histogram expansion confirms momentum - Works on all timeframes — best combined with multi-timeframe analysis (e.g. Weekly/Daily for direction, 5min for entries) Settings: - Fast Length: 6 (default) - Slow Length: 20 (default) - Signal Smoothing: 9 (default) - Source: Close (default)
Indicador Pine Script®
por ChMaKa1000
Structural Momentum Gauge [JOAT]Structural Momentum Gauge Introduction Structural Momentum Gauge is an open-source overlay indicator that fuses an adaptive Kalman filter with a Supertrend ratchet trail and a WMA-based volatility envelope to produce three clearly defined regime states: Bull Trend, Bear Trend, and Range-Bound. Rather than relying on a fixed moving average, the Kalman filter continuously self-calibrates its noise estimate each bar, delivering a smoothed price proxy that adapts to changing market conditions without introducing unnecessary lag. The Supertrend ratchet applied directly to the Kalman value — rather than to a raw price midpoint — generates directional bias changes that are markedly more stable than those produced by conventional price-based systems. The core problem this indicator addresses is that most trend-following tools either repaint (flipping signals on the same bar as price reverses) or commit to a direction far too slowly. The Kalman filter's gain calculation absorbs noise on low-momentum bars while remaining sensitive during genuine impulses. Layering an envelope breach condition on top means both the Kalman direction and price location relative to the volatility band must agree before a trend regime is confirmed — a dual-gate that substantially reduces false readings on choppy, sideways charts. Core Concepts 1. Adaptive Kalman Filter The Kalman filter maintains two persistent state variables: the current estimate (k_est) and the error variance (k_err). Each bar the Kalman gain is computed as k_err / (k_err + noise), where noise equals kAlpha * kPeriod. The gain controls how much the estimate shifts toward the current close. After updating the estimate, the error variance is revised: (1 - gain) * k_err + kBeta / kPeriod. This means a large prediction error pushes the variance higher, increasing the gain on the next bar and making the filter more responsive. When price action settles, the gain contracts and the filter smooths out. The result is a price proxy that is neither the fixed-lag of a simple moving average nor the noise sensitivity of a raw close. 2. Supertrend Ratchet on Kalman ATR-scaled upper and lower bands are applied around the Kalman value rather than the raw hl2. The ratchet rule then applies: the upper band can only move down (or reset when the Kalman value crosses above it), and the lower band can only move up (or reset when the Kalman value crosses below it). Direction flips when the Kalman value closes through the active band. Applying the ratchet to a pre-filtered price removes the micro-fluctuations that cause excessive direction changes when using hl2 directly. 3. WMA Volatility Envelope A WMA of the high-low range, multiplied by the deviation parameter, defines half the envelope width. The envelope upper and lower levels are placed symmetrically around the Kalman value. An extended outer cloud — 1.35x the inner envelope — is plotted for spatial context. A price close above the upper envelope sets the range state to 1; a close below the lower sets it to -1. Regime confirmation requires both the Kalman Supertrend direction and the envelope range state to agree in sign: 4. Regime Classification combined = kBias * rState, where kBias is +1 when the Kalman Supertrend is bullish and rState is +1 when close is above the upper envelope. combined == 1 with kBias == 1 is a confirmed bull trend. combined == 1 with kBias == -1 is a confirmed bear trend. All other states are range or opposing. A rolling 50-bar history computes what percentage of recent bars were in a trending state, producing a Trend Strength percentage. 5. K-Velocity The rate of change of the Kalman value over three bars, normalized by the current ATR, yields a K-Velocity score from 0 to 1. Velocity dots appear on the Kalman line when the score exceeds 0.5, with their transparency inversely proportional to the velocity — faster moves produce more saturated dots. This creates a visual intensity signal on the trail itself, communicating acceleration and deceleration without a separate panel. Features Adaptive Kalman Filter: Self-calibrating price proxy with alpha and beta gain controls — responds faster during impulses, smooths more during consolidation Supertrend Ratchet on Kalman: Direction-persistent trail applied to the Kalman value, eliminating noise-driven flips on raw price crossovers Outer Envelope Cloud: Wide ATR envelope filled directionally, providing spatial context at a glance Inner Envelope Fill: Standard WMA envelope bands with conditional fills that activate in range regime Triple-Layer Kalman Glow: Three stacked plots at widths 9, 5, and 2 with decreasing transparency create a neon glow shadow effect on the Kalman line Gradient Core Fills: 6-argument fill() between Kalman and candle mid-body, transparent at the Kalman line and saturated at the body — colored by confirmed regime K-Velocity Dots: Pulsing circles on the trail during high-velocity trend bars, intensity scales with normalized velocity score Regime Transition Circles: Circle marker fires at every confirmed regime change — immediate visual alert to state transitions Bull/Bear Trend Start Arrows: Triangle up/down plotshape fires at the exact bar where both Kalman direction and envelope breach first agree Trend End Marker: X marker fires when the trending regime ends, helping traders tighten stops or close positions Kalman Flip Labels: K▲ / K▼ labels placed below/above the Supertrend level when the Kalman bias flips direction Envelope Squeeze Marker: Golden diamond when envelope width drops below 80% of its recent SMA — flags compression before potential breakout Gradient Bar Coloring: Bars saturate based on distance from Kalman within envelope range, fading to neutral in range-bound conditions 10-Row Dashboard: Regime state, K-Trend direction, Kalman price, upper/lower band levels, trend bar count, T-Strength %, K-Velocity %, volatility state Input Parameters Kalman Filter: Alpha (Smoothing): Controls base noise level — lower values produce a smoother, higher-lag filter (default 0.01) Beta (Adapt Rate): Controls how quickly error variance recovers after a large miss — higher values make the filter adapt faster (default 0.10) Period: Normalises the gain magnitude — acts as a scaling factor on both noise and beta (default 77) Supertrend: ST Factor: ATR multiplier for the ratchet bands around the Kalman value (default 0.7) ST ATR Length: ATR lookback for the Supertrend band calculation (default 7) Volatility Envelope: Envelope WMA Length: Lookback for the WMA of high-low range (default 200) Envelope Deviation: Multiplier on the WMA to set envelope half-width (default 1.2) Visuals: Toggles for Supertrend line, envelope bands, gradient fills, Kalman glow, envelope cloud, and dashboard Bull Color (default cyan #22d3ee), Bear Color (default rose #f43f5e), Range Color (default slate #94a3b8) How to Use This Indicator Primary Setup — Trend Confirmation Entry: Wait for a trend start arrow (triangle up or down) to fire. This marks the bar where the Kalman Supertrend direction and the envelope breach state first agree. Enter in the arrow direction. Trail your stop below the Kalman line for longs or above it for shorts. Exit on a Trend End X marker or when the K▲/K▼ flip label fires against your position. Using K-Velocity for Sizing: When velocity dots are dense and bright, momentum is expanding — the trending move is accelerating. When dots thin out or disappear, momentum is fading even if the regime has not changed yet. Reduce size on fade or tighten stops before the trend end marker appears. Squeeze Setup: When the golden diamond squeeze marker fires, the envelope is compressing. Wait for price to break the envelope band in either direction. If a trend start arrow follows within the next few bars, this is a high-probability breakout entry aligned with both volatility expansion and regime confirmation. Reading the Dashboard: T-Strength above 60% indicates a mature, sustained trend. Values below 30% indicate the regime state is new or unstable — the trend is young and position sizing should reflect that uncertainty. Indicator Limitations The Kalman filter's gain is bounded by the alpha and beta parameters. Very low alpha values may make the filter too sluggish to capture short, sharp reversal moves before the ratchet trail catches them The envelope breach condition for regime confirmation means the indicator will not register a trend until price has already moved far enough from the Kalman center to exit the band — entries will not be at the very start of a move On instruments with consistently narrow true range (low-liquidity futures, off-hours sessions), the WMA envelope may be so tight that price is rarely inside the band, causing permanent range state classification The Kalman filter uses close-to-close data and has no concept of intrabar price action; on daily charts, a spike high that closes near the open may produce a different Kalman trajectory than on a lower timeframe Trend Strength is a rolling 50-bar measure. On very fast timeframes, 50 bars may represent only minutes, making the percentage less meaningful as a maturity gauge Originality Statement This indicator is original in its application of a Kalman filter as the supertrend base, the dual-gate regime confirmation system, and the K-velocity visual intensity layer. The publication is justified because: Applying the Supertrend ratchet to a Kalman-filtered price rather than raw hl2 produces direction changes that are measurably more stable — the Kalman pre-filters noise that would otherwise cause excessive band crossings The dual-gate regime system (Kalman direction AND envelope breach must agree) produces a stricter trending classification than any single-condition approach, reducing false trend readings in sideways conditions The K-velocity normalization layer embeds a momentum acceleration measure directly into the trail visualization without requiring a separate panel, communicating both direction and rate-of-change simultaneously The envelope squeeze detection integrated with trend start arrows identifies the specific condition where compressed volatility resolves into a confirmed regime shift — a novel combination for a Kalman-based system The Trend Strength rolling percentage provides a trend maturity measure that distinguishes freshly flipped regimes from mature, sustained trends, enabling differentiated position sizing without a separate indicator Disclaimer This indicator is provided for educational and informational purposes only and does not constitute financial advice or a recommendation to buy or sell any financial instrument. Past performance of any pattern or signal does not guarantee future results. All trading involves substantial risk. Always use proper risk management and conduct your own independent analysis. — Made with passion by officialjackofalltrades
Indicador Pine Script®
por officialjackofalltrades
NoLos MACDA clean and visually improved MACD oscillator designed for better readability and faster decision-making. Key Features: Area-style histogram – Smooth filled area between the MACD histogram and the zero line (instead of traditional columns) Dynamic coloring: Bright colors when momentum is strengthening, softer tones when weakening Clear MACD line (blue) and Signal line (orange) Subtle background highlight near the zero line for easier identification of momentum shifts Optional Overbought and Oversold levels (toggleable) Clean, modern look that works exceptionally well on all timeframes Settings: Fast, Slow, and Signal lengths (default 12, 26, 9) Choice between EMA or SMA for both MACD and Signal lines Toggle to show/hide Area, MACD line, and Signal line Option to display Overbought/Oversold horizontal levels Alerts Included: MACD Bullish / Bearish Crossovers Histogram crossing above/below zero Momentum weakening (area turning from rising to falling or vice versa) Perfect for trend traders, momentum traders, and anyone who prefers a cleaner, less cluttered MACD visualization compared to the classic column version. Best used on cryptocurrency, forex, and stock charts across all timeframes.
Indicador Pine Script®
por Cryptonologic
Trend Trader Pro - Dynamic Volume & Trend v1.0Overview Pro Trend Trader is a sophisticated trend-following system designed for professional-grade execution across Equities, Forex, and Crypto. Unlike standard crossover indicators, this engine integrates Volatility-Adjusted Spacing, Momentum Exhaustion Exits, and a Dynamic Persistence Engine to provide the cleanest possible visual experience without sacrificing data depth. The Logic: How It Works The script uses a "Tri-Layer" validation process to ensure you only enter when the market has genuine participation: Dynamic Trend Core: Utilizes a specialized 9/21 EMA crossover logic. It includes a "Fast Reversal Mode" that prioritizes immediate price action, allowing for quicker pivots during sharp V-reversals. Volatility-Adjusted Spacing (ATR): All signals and labels utilize an ATR-based offset. This ensures that labels never clutter the price action; they move further away during high volatility and tuck closer during consolidation. Momentum & Volume Confirmation: Signals are cross-verified against the MACD Histogram and Relative Volume (RVOL) to ensure institutional support behind every move. Advanced New Features Visual Precision Connectors: Every signal (BUY/SELL/EXIT) is linked to its specific trigger candle via a vertical dotted connector. This removes ambiguity, showing you exactly which wick triggered the execution. Smart Persistence Engine: To assist with post-trade analysis, the script features a 15-bar visibility timer. After a trade closes, the entry labels, TP hits, and exit markers remain on your chart for 15 bars, allowing you to review the trade before the "Auto-Cleanup" scrubs the chart for the next setup. Zero-Delay Session Warm-Up: A background calculation engine ensures that all indicators are "warm" and mathematically accurate the moment the market opens, preventing the standard "indicator lag" seen in most session-restricted scripts. Sequential TP Scaling: Visual targets (TP1–TP6) unlock dynamically. The script tracks multiple Take Profit hits simultaneously using an internal array system for flawless management. How To Use It The Entry: Look for the BUY/SELL labels. The dotted line will point to the exact candle. The Management: Watch for TP HIT messages. The script will automatically draw the next target once the current one is secured. The Exit: The script triggers an EXIT signal when MACD momentum shifts, allowing you to lock in gains before the lagging EMA crossover occurs. The Review: Once the trade is over, you have 15 bars (customizable) to see your performance before the chart resets. Settings Guide Label Visibility (Bars): Adjust how long the trade history stays on your screen after an exit. Signal Spacing: Increase this value if you use many other indicators (like VWAP or multiple EMAs) to move the labels further out of the way. RVOL Multiplier: Set to 1.2x for standard stocks; increase for more volatile assets like Crypto or 0DTE Options. Moderator & Open-Source Note This script is written in Pine Script v6. It features advanced state management using Arrays to handle multiple TP labels and uses a Global Persistence Flag to manage the delayed-deletion logic. It is a complete, original work designed for clean, institutional-style chart aesthetics.
Indicador Pine Script®
por Myo_Aung
6