Começar

Osciladores de Momentum

4EMAs, SQZMOM, ADX by PinchePatoDescription 4EMAs, SQZMOM, ADX by PinchePato is a comprehensive trend and momentum toolkit designed for traders who want a clean, all-in-one workspace. This script combines three essential technical analysis pillars—Trend (EMAs), Momentum (Squeeze), and Strength (ADX)—while offering unprecedented visual customization. Key Features 1. Quad Exponential Moving Averages (EMAs) Identify the trend at a glance with four fully configurable EMAs. Main Chart Overlay: Although the indicator sits in a separate pane, the EMAs are plotted directly on the price chart using force_overlay. Total Control: Individually toggle visibility, adjust lengths, and customize line widths and colors for each EMA to suit your strategy (e.g., 20, 50, 100, 200). 2. Independent Squeeze Momentum (LazyBear Logic) Based on the classic Squeeze Momentum logic by LazyBear, this version features a unique Independent Scaling System. Movable & Resizable: Unlike standard oscillators that get "squashed" by other data, you can move the Squeeze histogram vertically and adjust its height percentage using sliders. This allows you to float it above or below the ADX lines perfectly. Visual Styles: Choose between a smooth Gradient (mountain look) or a Solid fill. Smooth Curves: Uses a refined column-based plot for an organic, curved aesthetic. 3. Advanced ADX & DMI Monitor trend strength and directional movement with a modernized ADX/DMI suite. Directional Clarity: Clear plots for ADX, +DI, and -DI with customizable widths and colors. Key Level Tracker: A configurable Key Level (default 23) with adjustable line styles (Dashed, Dotted, Solid) to identify when a trend is gaining significant strength. How to Use Trend Identification: Use the 4 EMAs to determine the long-term and short-term trend direction. Volatility Breakouts: Watch the Squeeze dots (baseline). When the dots turn from Black (Squeeze On) to Gray/Blue (Squeeze Off), a volatility expansion is likely. Strength Confirmation: Use the ADX Key Level to confirm if a momentum move has enough "fuel" to continue. ADX rising above the Key Level indicates a strong trending environment. Settings & Customization This indicator was built for users who value aesthetics. Every single element—from the transparency of the gradients to the width of the Key Level—can be adjusted in the Inputs and Style tabs to match your dark or light mode chart theme. Disclaimer: Technical indicators are tools to assist in analysis, not financial advice. Always use proper risk management. Release Notes (v1.0) Initial Release: Combined 4 EMAs, Squeeze Momentum, and ADX/DMI into one optimized script. Independent Scaling: Developed a custom normalization engine for the Squeeze histogram, allowing it to be moved and resized independently of the ADX scale. Smart Signals: Added "Buy" and "Sell" labels that appear when the Squeeze fires in the direction of the EMA trend. Full Customization: Every line width, color, and visibility toggle is user-configurable. Visual Modes: Included a choice between Gradient and Solid fills for the Squeeze Momentum.
Indicador Pine Script®
por PatricioMarquezD
Aura Trend Momentum [Pineify]``` Aura Trend Momentum - Advanced Double-Smoothed Oscillator with Gradient Visualization The Aura Trend Momentum indicator is a sophisticated momentum oscillator that combines double exponential smoothing with normalized momentum calculations to provide clear, noise-filtered trend signals. Unlike traditional momentum oscillators that suffer from erratic movements and false signals, this indicator employs a dual-layer EMA smoothing technique on both the raw momentum and its absolute value, creating a stable, normalized oscillator that ranges between -100 and +100. This approach effectively eliminates market noise while preserving the essential momentum characteristics needed for accurate trend identification. Key Features Double-smoothed momentum calculation that significantly reduces false signals and whipsaw trades Normalized oscillator output (-100 to +100) for consistent interpretation across all market conditions and timeframes Four-color gradient histogram system that visually distinguishes between strong bullish, weak bullish, strong bearish, and weak bearish momentum states Signal line with cloud fill visualization showing the relationship between momentum and its smoothed average Smart crossover detection that filters signals by requiring reversals to occur in optimal zones (negative territory for bullish signals, positive territory for bearish signals) Built-in alert conditions for automated trading notifications and real-time monitoring Overbought (+50) and oversold (-50) reference levels with zero-line equilibrium How It Works The Aura Trend Momentum indicator utilizes a unique three-stage calculation methodology that sets it apart from conventional momentum oscillators: Stage 1: Momentum Extraction The indicator begins by calculating the raw price change (momentum) between consecutive bars using the selected source price (default: close). This represents the basic rate of change in the market. Stage 2: Double Exponential Smoothing Rather than using a single smoothing pass, the indicator applies two layers of exponential moving average (EMA) smoothing. The first EMA uses the "Trend Length" parameter (default: 21 periods) to capture the primary trend momentum, while the second EMA applies the "Signal Smoothing" parameter (default: 9 periods) to further refine the signal. This same double-smoothing process is applied to both the raw momentum and its absolute value, creating two parallel smoothed datasets. Stage 3: Normalization and Signal Generation The smoothed momentum is divided by the smoothed absolute momentum and multiplied by 100, creating a normalized oscillator that always ranges between -100 and +100. This normalization ensures consistent readings regardless of price levels or volatility conditions. A signal line is then generated by applying another EMA smoothing pass to the oscillator, creating a slower-moving reference line for crossover detection. Trading Ideas and Insights Momentum Reversal Strategy: The indicator excels at identifying momentum reversals in optimal zones. Bullish entry signals (green dots) appear when the oscillator crosses above the signal line while in negative territory (below zero), indicating that downward momentum is exhausting and a reversal is beginning. Conversely, bearish entry signals (red dots) trigger when the oscillator crosses below the signal line while in positive territory, signaling that upward momentum is weakening. Trend Strength Assessment: The four-color gradient system provides instant visual feedback on trend strength. Strong bullish momentum (bright green) occurs when the oscillator is positive and rising, indicating accelerating upward movement. Weak bullish momentum (light green) appears when the oscillator is positive but declining, suggesting the uptrend is losing steam. The same logic applies inversely for bearish conditions with red and light red colors. Overbought/Oversold Trading: The +50 and -50 reference levels serve as overbought and oversold zones. When the oscillator reaches these extremes, it suggests the current momentum may be overextended, potentially leading to mean reversion opportunities. Traders can watch for the oscillator to retreat from these levels as confirmation of momentum exhaustion. Divergence Detection: Like other momentum oscillators, Aura Trend Momentum can be used to identify divergences between price action and momentum. A bullish divergence occurs when price makes lower lows while the oscillator makes higher lows, suggesting weakening bearish momentum. Bearish divergences show the opposite pattern, warning of potential trend reversals. How Multiple Indicators Work Together The Aura Trend Momentum indicator integrates three distinct technical analysis components into a unified system: 1. Momentum Oscillator Component: At its core, this is a momentum-based oscillator similar to the Rate of Change (ROC) indicator, measuring the speed and magnitude of price movements. 2. Moving Average Smoothing Component: The double EMA smoothing technique borrows from the concept of DEMA (Double Exponential Moving Average), which reduces lag while maintaining smoothness. This component filters out market noise that would otherwise generate false signals. 3. Normalization Component: By dividing smoothed momentum by smoothed absolute momentum, the indicator incorporates a normalization technique similar to the Percentage Price Oscillator (PPO) or normalized RSI, ensuring readings are comparable across different securities and timeframes. These components work synergistically: the momentum calculation captures market dynamics, the double smoothing eliminates noise without excessive lag, and the normalization ensures universal applicability. The signal line adds a fourth dimension by providing a smoothed reference for timing entry and exit points, similar to how MACD uses a signal line for crossover detection. Unique Aspects What distinguishes Aura Trend Momentum from other momentum oscillators is its sophisticated approach to noise reduction and signal clarity. While indicators like RSI, Stochastic, or standard momentum oscillators either sacrifice responsiveness for smoothness or vice versa, this indicator achieves both through its double-smoothing methodology applied to both numerator and denominator of the normalization formula. The four-color gradient visualization system is another unique feature that goes beyond simple bullish/bearish coloring. By distinguishing between strong and weak states within each trend direction, traders gain immediate insight into momentum acceleration or deceleration without needing to analyze multiple indicators or chart patterns. Additionally, the smart signal filtering—requiring bullish crosses to occur below zero and bearish crosses above zero—dramatically reduces false signals that plague many oscillator-based systems. This zone-based filtering ensures that signals align with genuine momentum reversals rather than minor fluctuations within an established trend. How to Use Add the Aura Trend Momentum indicator to your chart from the indicators menu The oscillator will appear in a separate pane below your price chart, displaying the histogram, oscillator line, signal line, and cloud fill Watch for green dots (bullish entry signals) when the oscillator crosses above the signal line in negative territory—these indicate potential long entry opportunities Watch for red dots (bearish entry signals) when the oscillator crosses below the signal line in positive territory—these indicate potential short entry opportunities Monitor the histogram colors: bright green indicates strong bullish momentum, light green shows weakening bullish momentum, bright red indicates strong bearish momentum, and light red shows weakening bearish momentum Use the +50 level as an overbought reference and -50 as oversold—consider taking profits or tightening stops when these levels are reached The cloud fill between the oscillator and signal line provides additional context: green cloud suggests bullish control, red cloud suggests bearish control Set up alerts using the built-in alert conditions to receive notifications when buy or sell signals trigger Customization The indicator offers flexible customization options to adapt to different trading styles and market conditions: Oscillator Settings: Trend Length (default: 21): Controls the primary lookback period for momentum calculation. Increase for longer-term trend analysis (30-50), decrease for shorter-term trading (10-15) Signal Smoothing (default: 9): Adjusts the smoothing applied to both the oscillator and signal line. Higher values create smoother signals with fewer crossovers, lower values increase responsiveness Source (default: close): Select which price data to use for calculations—close, open, high, low, or various price averages like HL2 or HLC3 Visuals & Colors: Customize all four gradient colors (Bullish Strong, Bullish Weak, Bearish Strong, Bearish Weak) and the Signal Line color to match your chart theme or personal preferences. The color scheme helps with quick visual pattern recognition during live trading. Conclusion The Aura Trend Momentum indicator represents a refined approach to momentum analysis, combining proven technical analysis concepts—momentum calculation, exponential smoothing, and normalization—into a cohesive, noise-filtered system. Its double-smoothing methodology addresses the primary weakness of traditional momentum oscillators (excessive noise) while maintaining the responsiveness needed for timely trade entries. The four-color gradient system and smart signal filtering provide clear, actionable insights that help traders identify high-probability momentum reversals and trend continuation opportunities. Whether you're a day trader seeking precise entry points or a swing trader looking for trend confirmation, this indicator offers the clarity and reliability needed for confident decision-making in dynamic market conditions. ```
Indicador Pine Script®
por Pineify
Harmonic Periodicity Matrix [Pineify]Harmonic Periodicity Matrix — Multi-Cycle Stochastic Oscillator with Momentum Ribbon & Adaptive Signals The Harmonic Periodicity Matrix is an advanced cycle-detection oscillator that identifies market rhythm, momentum shifts, and high-probability reversal zones by harmonically combining three stochastic waves at different periodicities. Rather than relying on a single fixed lookback window — which inevitably misses cycles of differing durations — this indicator synthesizes a short-cycle , a primary-cycle , and a long-cycle stochastic into a single composite wave. The result is a smoother, more robust picture of where the market currently sits within its natural oscillation pattern. Key Features Three harmonically spaced stochastic cycles fused into one composite wave Weighted Moving Average (WMA) smoothing to reduce noise without excessive lag EMA-based signal line that generates precise momentum-crossover triggers Dynamic gradient coloring that visually encodes cycle strength and direction Momentum Ribbon fill between the cycle wave and signal line for at-a-glance bias confirmation Overbought / Oversold reference zones with subtle background shading Filtered Buy and Sell signals that fire only when reversals originate from extreme cycle territory How It Works At its core, the indicator computes three stochastic oscillators (%K) across three harmonically related lengths derived from a user-defined Primary Cycle Length : Short cycle — half the primary length ( cycleLen / 2 ), capturing fast intraday or shorter-term oscillations. Primary cycle — the user-defined length ( cycleLen ), representing the dominant market rhythm. Long cycle — 1.5× the primary length ( cycleLen × 1.5 ), anchoring the broader trend context. These three stochastic readings are averaged into a single composite cycle and then smoothed with a Weighted Moving Average (WMA) over the user-defined Smoothing Factor . Subtracting 50 centers the result around zero (range: −50 to +50), making overbought and oversold conditions immediately intuitive. A Signal Line — an EMA calculated over twice the smoothing period — acts as a lagging reference. Crossovers between the composite wave and the signal line mark momentum inflection points. Trading Ideas and Insights Zero-line crosses — When the composite wave crosses above 0, market momentum is transitioning bullish; below 0 signals bearish transition. Overbought / Oversold extremes — Readings above +25 indicate potential exhaustion; readings below −25 indicate potential recovery opportunity. Signal crossovers from extremes — The highest-conviction signals occur when the wave crosses the signal line while already in oversold (< −15, Buy) or overbought (> +15, Sell) territory. Momentum Ribbon color — A green ribbon confirms bullish momentum continuation; a red ribbon warns of bearish pressure even if price is still rising. How Multiple Indicators Work Together The power of the Harmonic Periodicity Matrix comes from the deliberate combination of three stochastic oscillators and two moving average types: The three stochastics represent different frequency bands of market activity — fast, medium, and slow. Averaging them suppresses random noise that would appear in any single stochastic while preserving genuine cyclical structure that repeats across all three timeframes simultaneously. The WMA smoothing is applied to the averaged cycle rather than to each individual stochastic. WMA front-weights recent data, keeping the smoothed line more responsive than a Simple Moving Average while avoiding the excessive lag of longer EMAs — the ideal balance for a cycle oscillator. The EMA signal line is computed over a longer period (2× the smoothing factor), intentionally lagging behind the main wave. This lag creates meaningful crossover events: when the faster composite wave crosses the slower signal line, it indicates a genuine shift in momentum rather than a transient fluctuation. The gradient coloring system encodes amplitude into color, providing an instant visual read of cycle intensity that raw numbers cannot convey. The background zone shading reinforces awareness of extreme readings without cluttering the visual space. Together, these components form a self-contained cycle analysis system: the three stochastics define the oscillation, the WMA refines it, the EMA signal line contextualizes momentum, and the visual layer communicates everything instantly. Unique Aspects Harmonic period spacing — Using 0.5×, 1×, and 1.5× ratios is inspired by harmonic analysis principles, where related frequencies reinforce true cyclical signals and cancel spurious noise. Amplitude-coded gradient — Color intensity scales with distance from zero (0→40 bullish, −40→0 bearish), making it easy to distinguish a mild rebound from a powerful trend. Filtered signals — Buy signals require the crossover to occur below −15; Sell signals require it above +15. This prevents signal generation in neutral mid-range territory where momentum reversals are statistically less reliable. Zero-centered display — Centering around 0 (rather than displaying 0–100) aligns naturally with how traders think about bullish vs. bearish bias. How to Use Add the indicator to any chart and timeframe. It plots in a separate panel below the price chart. Watch for green circles (Buy signals) — these appear when the cycle wave crosses up through the signal line from oversold territory (below −15). Watch for red circles (Sell signals) — these appear when the cycle wave crosses down through the signal line from overbought territory (above +15). Use the Momentum Ribbon fill color to confirm trend direction before entering trades. Pay attention to the overbought (+25) and oversold (−25) zones — readings beyond these thresholds suggest cycle exhaustion and potential reversal. Combine with price action or volume analysis for additional confirmation before executing trades. Customization Primary Cycle Length (default: 20) — Increase for longer-term swing cycle detection; decrease for faster, shorter-term cycle tracking. Smoothing Factor (default: 6) — Higher values produce a smoother wave with more lag; lower values are more reactive but noisier. Bullish Wave color — Default green (#089981); customizable. Bearish Wave color — Default red (#F23645); customizable. Equilibrium color — Default gray (#787b86); customizable. Conclusion The Harmonic Periodicity Matrix offers a methodologically grounded approach to market cycle analysis by combining multi-frequency stochastic decomposition, adaptive smoothing, and momentum-crossover detection into a single, visually intuitive oscillator. It is designed for traders who want more than a standard stochastic — those who seek to understand the rhythm of the market across multiple cycle lengths simultaneously. Whether you are swing trading, trend following, or timing entries within a larger move, this indicator provides a structured, repeatable framework for identifying when momentum is genuinely shifting versus when the market is simply oscillating in neutral territory.
Indicador Pine Script®
por Pineify
Momentum Oscillator (Zeiierman)█ Overview Momentum Oscillator (Zeiierman) is a regime-stable momentum engine designed to reveal when the market is quietly building pressure and when that pressure is already expanding. It measures long-lookback Rate of Change (ROC), smooths it for structural clarity, and then normalizes it into a clean −100 to +100 scale so momentum can be compared across assets and volatility regimes. You can choose between Z-Score normalization (adaptive to changing volatility) or Min/Max normalization (relative to recent extremes), followed by a final smoothing layer for readability and signal alignment. █ How It Works ⚪ 1) Momentum Measurement (ROC Engine) The script computes ROC across a cycle-based lookback: Lookback Bars = Ranking Period (Cycles) × Bars per Cycle ROC = (close / close − 1) × 100 ROC is smoothed with an EMA using Smoothing ⚪ 2) Normalization (Oscillator Mapping) To keep the oscillator comparable across different symbols and volatility regimes, ROC is normalized into a bounded oscillator: Mode A — Z-Score (default): Computes SMA and StDev over Lookback Converts ROC to Z-score Clamps Z using Z-Score Clamp Maps to −100…+100 Mode B — Min/Max: Finds the highest/lowest ROC over Lookback Converts the current ROC to a 0…1 percentile position Remaps to −100…+100 █ How to Use ⚪ Bullish Read Oscillator above 0 = bullish momentum regime Stronger bullish momentum as oscillator rises toward +60 ⚪ Bearish Read Oscillator below 0 = bearish momentum regime Stronger bearish momentum as oscillator falls toward −60 █ Settings Ranking Period (Cycles) — how far back momentum is measured (cycles). Bars per Cycle — converts cycles to bars (daily≈21). Smoothing — EMA smoothing applied to ROC before normalization. Lookback — window used to compute Z-Score or Min/Max ranges. Use Z-Score — stable regime-based normalization (recommended). Z-Score Clamp — limits extreme Z values to reduce spikes. ----------------- 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
3
Adaptive Squeeze Momentum Pro [WillyAlgoTrader]Adaptive Squeeze Momentum Pro is a non-overlay oscillator that combines volatility compression detection (squeeze) with an ATR-normalized momentum histogram and built-in divergence scanning — providing three layers of analysis in a single pane: when the market is coiling (squeeze), which direction the energy is building (momentum), and when momentum is diverging from price (divergence warnings). The classic squeeze momentum concept — Bollinger Bands contracting inside Keltner Channels — has been available on TradingView for years. What this indicator adds is an entirely different momentum calculation that is ATR-normalized (making it comparable across instruments and timeframes), a 4-state color-coded histogram that distinguishes between momentum acceleration and deceleration in both directions, automated divergence detection with optional HTF trend filtering, and a preset system tuned for different trading styles. The result is a modernized squeeze oscillator designed for practical trading rather than textbook demonstration. 🔍 WHAT MAKES IT ORIGINAL 1. ATR-normalized momentum oscillator. Most squeeze indicators use a raw linear regression value or simple price-minus-midline for their histogram. This makes the oscillator's scale dependent on the instrument's price level — a reading of 5.0 on BTCUSD means something completely different than 5.0 on EURUSD. This indicator solves that by dividing the raw momentum by the current ATR value, producing a dimensionless oscillator that typically ranges between −3 and +3 regardless of instrument or timeframe. The raw momentum itself is calculated as the distance between price and the average of the highest-high/lowest-low midpoint and an EMA — capturing both range-based and trend-based positioning. An optional EMA smoothing layer (configurable, default 3) reduces noise without excessive lag. 2. EMA-based volatility bands instead of standard Bollinger Bands. The squeeze detection uses an EMA (not SMA) as its basis, paired with standard deviation for the band width. EMA reacts faster to recent price changes than SMA, making the squeeze detection more responsive to volatility shifts — particularly useful on crypto and volatile instruments where compression phases can be short-lived. The ATR channel (replacing the traditional Keltner Channel) uses the same EMA basis. The squeeze fires when the volatility band width is less than the ATR channel width (ratio < 1.0). 3. Tiered squeeze intensity. Instead of a binary on/off squeeze state, the indicator classifies the compression into four tiers based on the ratio between the volatility band width and the ATR channel width: — EXTREME (ratio < 0.5): very tight compression, highest energy buildup — HIGH (ratio < 0.7): significant compression — MID (ratio < 0.9): moderate compression — LOW (ratio < 1.0): mild compression — NONE (ratio ≥ 1.0): no squeeze This lets you distinguish between a mild contraction (which may resolve quietly) and an extreme compression (which is more likely to produce a strong directional move). 4. 4-state histogram coloring. The momentum histogram uses four distinct colors to convey both direction and acceleration: — Bull Strong (bright green): momentum above zero AND rising — bulls are accelerating — Bull Weak (teal): momentum above zero BUT falling — bulls are decelerating, potential topping — Bear Strong (bright red): momentum below zero AND falling — bears are accelerating — Bear Weak (dark red): momentum below zero BUT rising — bears are decelerating, potential bottoming The transition from Strong to Weak (or vice versa) often precedes a zero-line cross, giving an early visual warning of momentum shifts. 5. Automated divergence detection with two modes. The indicator scans for classic divergences between price pivots and momentum pivots: — Bullish divergence : price makes a lower low while momentum makes a higher low — Bearish divergence : price makes a higher high while momentum makes a lower high Two detection modes are available: — Early mode (default): divergence is labeled on bar close at the pivot with zero right-side confirmation bars — fastest detection, may occasionally produce false signals — Confirmed mode : requires N confirmation bars on the right side of the pivot (same as the lookback length) — more reliable, but delayed Divergence lines are drawn on the oscillator connecting the two momentum pivots, and optional overlay labels are placed directly on the price chart (using force_overlay) so you can spot divergences without switching panes. 6. HTF trend filter for divergences. An optional higher-timeframe filter compares a 21-period EMA to a 50-period EMA on the selected HTF (default 60min). When enabled, bullish divergences are only shown when the HTF trend is bullish (fast EMA > slow EMA), and bearish divergences only when HTF is bearish. The HTF data uses the standard non-repainting pattern ( + lookahead_on). This filter reduces counter-trend signals that divergences often produce. ⚙️ HOW IT WORKS Squeeze detection: On each bar, the script calculates two band widths: — Volatility band width = StdDev(source, length) × multiplier × 2, centered on an EMA — ATR channel width = ATR(length) × multiplier × 2 The squeeze ratio = volatility width / ATR width. When this ratio falls below 1.0, volatility bands are inside the ATR channel — the market is in a squeeze. The tier is determined by how far below 1.0 the ratio is. Momentum calculation: — Midpoint 1: (highest high over N bars + lowest low over N bars) / 2 — Midpoint 2: EMA(source, N) — Combined midpoint: average of Midpoint 1 and Midpoint 2 — Raw momentum: source − combined midpoint — Normalized momentum: raw momentum / ATR(N) — Final momentum: EMA(normalized momentum, smoothing) if smoothing > 1, else raw normalized This approach blends range-based positioning (where is price within the recent range) with trend-based positioning (where is price relative to the EMA), then normalizes by ATR so the oscillator is instrument-agnostic. Divergence detection: The script uses ta.pivotlow() and ta.pivothigh() on both the momentum oscillator and price (low/high). For each new momentum pivot, it compares against the previous stored pivot. A bullish divergence is detected when the current price pivot low is lower than the previous one, but the current momentum pivot low is higher. Bearish divergence is the mirror. In Early mode (rightBars = 0), the pivot is identified at bar close without waiting for right-side confirmation. In Confirmed mode (rightBars = lookback), pivots are only confirmed after N bars pass. HTF filter: HTF EMAs are fetched with request.security() using the + lookahead_on non-repainting pattern. When the 21 EMA is above the 50 EMA on the higher timeframe, the HTF trend is bullish; below = bearish. Squeeze release alert: The "squeeze fired" alert triggers on the first confirmed bar after the squeeze condition ends (sqzOn transitions from true to false). The alert message includes the momentum direction at release (bullish if momentum > 0, bearish if ≤ 0). 📖 HOW TO USE Reading the histogram: — Bright green bars (Bull Strong) = momentum above zero and accelerating — strongest bullish phase — Teal bars (Bull Weak) = momentum above zero but decelerating — bulls losing steam — Bright red bars (Bear Strong) = momentum below zero and accelerating — strongest bearish phase — Dark red bars (Bear Weak) = momentum below zero but decelerating — bears losing steam — Transition from Strong → Weak = early warning of momentum exhaustion — Zero-line cross after Weak phase = momentum direction change Reading the squeeze: — Orange-tinted background = active squeeze (volatility compression) — The longer and tighter the squeeze, the more energy is stored — Watch for the first bar after the background clears (squeeze release) — the momentum direction at that moment often indicates the breakout direction Reading divergences: — Green "Div" label below the oscillator / below price = bullish divergence (potential bottom) — Red "Div" label above the oscillator / above price = bearish divergence (potential top) — Lines on the oscillator connect the two pivots that form the divergence — Divergences inside a squeeze are particularly powerful — they suggest the breakout direction before the squeeze releases Suggested workflow: — Wait for a squeeze to form (background tint appears) — Watch for divergences during the squeeze — they hint at breakout direction — On squeeze release, check momentum direction and histogram color — Bright green at release = bullish breakout bias; bright red = bearish — If HTF filter is enabled, only take signals aligned with the higher-timeframe trend Presets: — Conservative : length ≥ 25, BB mult ≥ 2.2, ATR mult ≤ 1.2, smoothing ≥ 7 — fewer signals, smoother histogram, suited for 4H–Daily — Default : uses your manual settings — balanced for 15min crypto — Aggressive : length ≤ 14, BB mult ≤ 1.6, ATR mult ≥ 1.6, smoothing ≤ 2 — more signals, faster reaction — Scalping : length ≤ 10, BB mult ≤ 1.4, ATR mult ≥ 1.8, no smoothing — optimized for 1–5min ⚙️ KEY SETTINGS REFERENCE — Squeeze Length (default 21): shared lookback for EMA, StdDev, and ATR — higher = slower squeeze detection, longer compression phases — Volatility Band Mult (default 1.8): multiplier for the EMA ± StdDev bands — higher = wider bands, squeeze triggers more easily — ATR Channel Mult (default 1.6): multiplier for the ATR channel — lower = narrower channel, squeeze triggers less — Momentum Length (default 20): lookback for highest-high, lowest-low, and momentum EMA — Momentum Smoothing (default 3): EMA smoothing on the normalized momentum — 1 = raw, higher = smoother — Divergence Lookback (default 3): pivot detection lookback for divergence scanning — Early Divergence (default On): label on bar close with no right-side confirmation — faster but less filtered — Use HTF Trend Filter (default Off): filter divergences by higher-timeframe EMA trend — Higher Timeframe (default 60): HTF for trend filter — should be 3–5× chart timeframe 🔔 Alerts Three alert conditions (all bar-close confirmed): — Squeeze Fire : squeeze releases — includes momentum direction (bullish/bearish) — Bullish Divergence : price lower low + momentum higher low — includes HTF trend status — Bearish Divergence : price higher high + momentum lower high — includes HTF trend status All support standard text and JSON webhook format. ⚠️ IMPORTANT NOTES — This indicator is a non-overlay oscillator — it appears in a separate pane below the chart. Optional divergence labels can be mirrored on the price chart via the "Show Divergences on Chart" toggle. — All signals require bar-close confirmation . The HTF filter uses the standard non-repainting security call pattern ( + lookahead_on). — Early divergence mode (default) labels divergences without waiting for right-side pivot confirmation — this provides faster signals but may occasionally flag a divergence that is later invalidated. Switch to Confirmed mode for higher reliability at the cost of delay. — A squeeze release indicates that volatility is expanding — it does not guarantee a directional move. False breakouts can and do occur, especially on lower timeframes. — Divergences signal momentum weakening, not guaranteed reversals. They are most effective as confluence with other analysis, not as standalone signals. — The ATR normalization makes the oscillator scale-independent, but the absolute readings (e.g. +2.0 vs +1.5) should be compared within the same instrument/timeframe context, not across different ones. — Works across all asset classes. Volume is not used in any calculation.
Indicador Pine Script®
por WillyAlgoTrader
Momentum Decay Field [BullByte]Momentum Decay Field : Physics-Based Momentum Energy Visualization WHAT IS THE MOMENTUM DECAY FIELD? The Momentum Decay Field (MDF) models price momentum as a decaying physical energy field using an exponential half-life model. MDF visualizes impulse energy on the price chart, detects exhaustion and energy divergence, and stores past exhaustion zones as reference levels. This is an informational visualization tool - not a buy/sell signal generator. In nuclear science, every radioactive element emits energy that decays exponentially over time following a precise mathematical law. MDF applies this exact principle to price momentum. Every strong price impulse carries kinetic energy. That energy does not last forever. It fades, weakens, and eventually depletes - just like a radioactive isotope losing its charge. MDF measures this process in real time and wraps price in a living energy field that expands, contracts, changes color, and ultimately signals exhaustion when the energy runs out. This is not a moving average. Not an oscillator. Not a mashup of existing tools . It is a standalone physics engine that models momentum as a decaying energy system directly on the price chart. THE CORE PHYSICS The engine is built on the exponential decay formula from nuclear physics: E(t) = E0 x exp(-lambda x t) Where: E(t) is the remaining energy at time t (measured in bars after the impulse) E0 is the initial energy assigned to the impulse at the moment it occurs lambda is the decay constant, derived from the half-life: lambda = ln(2) / Half-Life t is the number of bars elapsed since the impulse The half-life is the number of bars it takes for energy to decay to exactly 50% of its initial value. After two half-lives, 25% remains. After three, 12.5%. This creates the smooth, predictable decay curve visible in the dashboard sparkline. When the adaptive half-life option is enabled, stronger impulses automatically receive a longer half-life. This means powerful moves with high volume and velocity sustain their energy field longer before exhausting, while weak impulses fade quickly. This mirrors real market behavior where institutional-grade moves carry momentum further than retail noise. HOW IMPULSES ARE DETECTED Not every candle qualifies as an impulse. The detection engine requires three conditions to be met simultaneously: First , the candle body size (distance between open and close) must exceed a user-defined multiple of the Average True Range. This ensures only candles with genuine directional magnitude qualify. Second , the total candle range (high to low) must also exceed an ATR-based threshold. This confirms the move had real price displacement, not just a wide body on a small-range bar. Third , the body-to-range ratio must exceed 0.45. This filters out doji candles, pin bars, and high-wick candles that suggest indecision rather than conviction. Only candles where the body represents a significant portion of the total range pass through. When an impulse qualifies, its initial energy (E0) is calculated by combining three factors: the normalized body magnitude (body size divided by ATR), a velocity boost (how fast price moved over the velocity window compared to average), and an optional volume boost (current bar volume relative to the rolling volume average). The result is capped at 5.0 to prevent extreme outliers from dominating the field. THE ENERGY FIELD : WHAT YOU SEE ON THE CHART The energy field is the colored aura that appears around price. It communicates the current momentum state through three visual properties: Width: The field expands when energy is high and contracts as energy decays. At full energy, the field reaches its maximum width (controlled by the Max Field Width setting). As energy approaches zero, the field collapses to nothing. The width is always proportional to ATR so it adapts automatically to any instrument and timeframe. Color: The field color morphs through three stages as energy decays. At high energy levels (above 55%), the field displays the bright directional color - the bullish theme color for upward impulses, the bearish theme color for downward impulses. As energy drops into the mid range (20-55%), the color transitions through warm amber, a universal warning tone indicating momentum is fading. Below 20%, the field shifts to cool gray, signaling that momentum is nearly spent. This color morphing happens smoothly and continuously on every bar. Layering: The field is rendered in up to three concentric tiers - inner, mid, and outer - each progressively more transparent. The inner layer sits closest to price and is most opaque. The mid layer extends further with reduced opacity. The outer layer provides the widest aura at the lowest visibility. This creates a natural gradient that makes the field feel organic rather than blocky. THREE VISUAL MODES Clean mode renders no energy field at all. Only the signal markers (diamond, EXH, WEAK) and the dashboard appear on the chart. This mode is designed for traders who want a completely uncluttered chart and only care about the event markers and data panel. The momentum engine still runs in the background, powering the dashboard metrics and signals. Standard mode activates the inner and mid field layers along with the energy spine - a central reference line running through the price that pulses with momentum. This is the default mode and provides a balanced view of the energy state without overwhelming the chart. Full mode enables all three field tiers and adds candle tinting, where the candle bodies themselves are colored according to the current energy state and direction. High-energy bars glow with the directional color while depleted bars take on neutral tones. This mode provides maximum visual information for traders who want to see the full energy picture at a glance. SIGNAL MARKERS : WHAT EACH ONE MEANS Diamond (below bar for bullish, above bar for bearish): This marks the bar where a qualified impulse was detected and energy was injected into the system. It tells you that the decay physics engine has been activated or refreshed with new energy. Not every strong candle produces a diamond - the cooldown system prevents clustering by enforcing a minimum number of bars between consecutive impulse markers. EXH (cross shape, amber color): This marks the bar where the energy ratio dropped below the exhaustion threshold. It means the momentum that was driving price has fully depleted according to the decay model. These exhaustion points often coincide with areas where price pauses, reverses, or enters consolidation. The anti-repeat filter ensures that the same directional exhaustion does not fire consecutively without a change in context - either a new direction must establish or sufficient time must pass. WEAK (triangle shape, orange color): This marks an energy divergence. It appears when price makes a new high (for bullish) or new low (for bearish) but the impulse energy behind that move is at least 25% weaker than the previous impulse in the same direction. The price is extending but the fuel behind it is diminishing. This is a momentum divergence detected purely through the energy physics model, not through any traditional oscillator comparison. When WEAK fires on the same bar as an impulse, the diamond marker is automatically suppressed because the WEAK label already communicates that an impulse occurred - it simply carried less energy than its predecessor. EXHAUSTION MEMORY ZONES When an exhaustion event occurs, the indicator stores the price range of that bar as a memory zone. These zones are rendered as semi-transparent colored rectangles that extend from the exhaustion bar to the right edge of the chart. Bullish exhaustion zones use the bullish theme color and bearish exhaustion zones use the bearish theme color. These zones represent price levels where momentum previously failed to sustain. They often act as areas of interest for future price action because they mark locations where aggressive directional energy was fully consumed. Fresh zones appear more opaque and gradually fade as they age, eventually becoming fully transparent after the user-configured fade period. The Max Zones Displayed setting controls how many zones appear simultaneously. Only the most recent zones are shown. The Zone Fade Period controls how many bars a zone remains visible before disappearing. A three-stage memory management system runs continuously to prevent the zone array from growing unbounded on long-history charts: old zones beyond twice the fade period are pruned, the array is capped at a safe maximum, and the rendering loop enforces a drawing budget to stay within platform limits. THE DASHBOARD : EVERY ELEMENT EXPLAINED The dashboard uses a fully opaque dark background that renders identically on both light and dark chart themes. Every cell has its own explicit background color so nothing is inherited from the chart environment. ENERGY: A 16-character progress bar showing remaining energy as a visual fill gauge, followed by the numerical percentage. The bar transitions from bright green (charged) through cyan (active) to amber (decaying) to orange (fading) to red (depleted). PHASE: Displays the current energy state classification. CHARGED means energy is above 70% - momentum is strong and active. ACTIVE means 45-70% - momentum is present and sustaining. DECAYING means 20-45% - momentum is fading but not yet spent. FADING means energy is above the exhaustion threshold but below 20% - momentum is weak. DEPLETED means energy has fallen below the exhaustion threshold - the current cycle has exhausted. The directional bias (BULL, BEAR, or FLAT) appears alongside the phase to show which direction the current energy cycle belongs to. E0 INITIAL: Shows the initial energy magnitude that was assigned to the current impulse cycle when it began. The classification label (Extreme, Strong, Moderate, Light) provides quick context about how powerful the originating impulse was. HALF-LIFE: Displays the current half-life in bars - how long it takes for energy to decay to 50%. When adaptive half-life is enabled, this value changes with each impulse based on its strength. The ELP (elapsed) counter shows how many bars have passed since the last impulse event. ETA TO EXH: The predicted number of bars remaining until energy reaches the exhaustion threshold. This is calculated by solving the decay equation for time. The visual countdown bar (filled and empty blocks) provides a quick gauge of how close exhaustion is. When the current cycle has already exhausted, this displays EXHAUSTED in red. DECAY CURVE: A 20-character sparkline that projects how energy will diminish over approximately three half-lives into the future. Each character represents a future time step. The curve reads from left (current moment, marked by NOW) toward the right (future). Tall blocks indicate high energy, dots indicate near-zero energy. This gives traders a visual preview of the entire remaining decay trajectory at a glance. IMPULSES / EXHAUSTIONS / DIVERGENCES: Lifetime counters showing how many of each event type have occurred since the indicator was loaded on the chart. These provide context about the current session's activity level. CHART EXAMPLE Chart 1: ENERGY FIELD DYNAMICS & IMPULSE DETECTION What This Chart Represents This chart demonstrates the Momentum Decay Field's core visual engine showing how the energy field expands, contracts, and morphs in real-time as momentum cycles through impulse, sustain, and decay phases. Key Visual Elements Highlighted: 1. ENERGY FIELD COLOR MORPHING The aura transitions through three distinct color phases as energy decays: - Bright directional color (green for bullish, magenta for bearish) = High energy (>55% remaining) - Warm amber/orange = Mid-energy decay phase (20-55% remaining) - Cool gray = Low energy, momentum nearly spent (<20% remaining) 2. FIELD WIDTH DYNAMICS The energy band's width is directly proportional to remaining energy: Wide, expansive field = Strong active momentum with high kinetic energy Contracting field = Energy decaying, momentum losing strength Thin/collapsed field = Minimal momentum, approaching exhaustion Width scales with ATR to adapt across all instruments and timeframes 3. IMPULSE SIGNAL MARKERS (Diamonds) Pink/Green diamond markers identify the exact bars where qualified momentum impulses occurred: Below price = Bullish impulse (upward energy injection) Above price = Bearish impulse (downward energy injection) Each diamond represents a new E0 (initial energy) assignment Cooldown system prevents marker clustering during volatile periods 4. MULTI-CYCLE MOMENTUM VISUALIZATION The chart captures several complete momentum lifecycles: Fresh impulses creating wide, bright energy fields Progressive decay causing field contraction and color shift Direction changes showing energy field polarity reversals Energy stacking when same-direction impulses occur during active cycles 5.ENERGY DIVERGENCE SIGNAL (WEAK Marker) Orange triangle with "WEAK" label Triangle Up Position (Below Price): Signal Type: Bearish energy divergence Location: Bottom of the move after the bullish run What It Detected: Price made a new low BUT the impulse energy behind that low was 25%+ weaker than the previous bearish impulse CHART 2: EXHAUSTION SIGNALS, MEMORY ZONES & DASHBOARD DEEP DIVE What This Chart Represents This chart demonstrates the complete signal ecosystem of the Momentum Decay Field indicator, showcasing exhaustion detection, energy divergence, memory zones, and a full dashboard metrics breakdown. The chart captures a Solana (SOL/USDT) 15-minute timeframe showing the transition from strong bearish momentum through exhaustion to reversal with weakening energy. 1. ENERGY FIELD EVOLUTION LEFT SIDE (Early Period - 1:00 to 10:00): Bright magenta field = Strong bearish energy active Wide field width = High momentum magnitude Color morphing visible = Transition from bright magenta → brown/amber as energy decays Field shows downtrend = Bearish impulse energy driving price lower 2. EXHAUSTION SIGNAL (EXH Marker) Meaning: Momentum energy fully depleted - energy ratio dropped below 8% threshold Location: Above the price bars (bearish exhaustion that preceded the bullish reversal) Trigger Conditions Met: Energy ratio < 0.08 (exhaustion threshold) Minimum E0 > 0.5 (filters noise) Minimum 3 bars elapsed since impulse Cooldown period satisfied (8 bars between signals) Anti-repeat filter passed (different direction or sufficient time gap) What Happened Here: The strong bearish momentum (magenta field on left) progressively decayed until energy was fully consumed. The EXH marker fired at the exact bar where the decay equation calculated remaining energy had fallen below the 8% threshold. 3. EXHAUSTION MEMORY ZONE (Green Rectangle) Large semi-transparent green box Zone Type: Bullish exhaustion memory zone Price Range: Captures the high-low range of the bar where bullish momentum exhausted Color: Green with ~92% opacity at creation, fading over time Border: Green border at ~78% opacity Extension: Extends from exhaustion bar to right edge of chart (+10 bars beyond current) Why It Matters: Price levels where momentum exhausted represent areas where directional energy was fully consumed. Market often "remembers" these levels as they frequently become magnets for future price action, areas of consolidation, or reversal zones. 4.ENERGY SPINE (Coloured Line Through Price Center) Visible as dark line running through candle midpoints: Technical Details: Plots at hlc3 (average of high, low, close) Color matches field color, opacity varies with energy level Only visible when energy > 12% Provides visual anchor showing momentum center of gravity Style: Line breaks (plot.style_linebr) to avoid connecting across gaps Purpose: The spine acts as a dynamic momentum equilibrium line. When field is wide, spine shows the center of energy distribution. As field contracts, spine becomes the last visible element before total energy depletion. Helps traders identify the core momentum flow without relying solely on field boundaries. RECOMMENDED SETTINGS AND TIMEFRAMES The default settings are calibrated for intraday trading on timeframes between 1 minute and 15 minutes. The indicator works on all timeframes and all instruments but the default parameters are optimized for the pace of day trading where impulse-to-exhaustion cycles complete within a visible chart window. For scalping on 1-minute charts, consider reducing the Base Half-Life to 5-6 bars and the Impulse Lookback to 8-10. This makes the system more responsive to the rapid impulse cycles on lower timeframes.- For swing trading on 1-hour or 4-hour charts, consider increasing the Base Half-Life to 12-16 bars and the Impulse Threshold to 2.0-2.5. This filters out intrabar noise and focuses on only the most significant impulses that drive multi-hour moves. For daily charts, increase the Half-Life to 15-20 bars and enable Adaptive Half-Life to let strong institutional moves sustain their field across multiple sessions. The Volume Weighting option is recommended to be kept enabled on instruments with reliable volume data (stocks, futures, major crypto pairs). For forex pairs where volume represents tick count rather than actual traded volume, consider disabling it or treating it as a secondary factor. THOUGHT BEHIND THE INDICATOR The concept originated from a simple observation: every momentum move in the market follows a lifecycle that mirrors energy decay in physics. A strong impulse starts with maximum energy, sustains for a period, then gradually loses force until it is fully spent. Traditional momentum indicators attempt to measure this through oscillators that lag behind price. MDF takes a fundamentally different approach by modeling the decay process itself using established physics rather than measuring its symptoms through lagging mathematical transformations. The exponential decay model was chosen specifically because it matches the empirical behavior of momentum in financial markets. Momentum does not decay linearly - it holds relatively steady in the early phase after an impulse, then accelerates its decline as it approaches exhaustion. This is precisely the shape of an exponential decay curve and is why the half-life model produces a more accurate representation than a simple moving average or percentage-based countdown. The energy divergence detection was added after observing that many trend reversals are preceded by a sequence of price extremes with diminishing impulse energy. The price chart shows strength (higher highs or lower lows) while the underlying energy tells a different story (each push requires less fuel). This hidden weakness is invisible on a standard chart but becomes immediately apparent when measured through the energy model. WHAT THIS INDICATOR DOES NOT DO This indicator does not generate buy or sell signals. It does not tell you when to enter or exit a trade. It does not predict future price direction. It measures and visualizes the current state of momentum energy to help you make more informed decisions within your own trading framework. The exhaustion markers identify zones where momentum energy has depleted according to the physics model. Price may reverse at these zones, consolidate, or continue in the same direction after a new impulse injects fresh energy. The markers are informational reference points, not trading signals. The energy divergence detection (WEAK markers) highlights instances where price extremes are driven by weakening energy. This is an observation about momentum quality, not a prediction about price direction. Divergences can persist through multiple cycles before price responds. NON REPAINT BEHAVIOUR Every calculation in this indicator uses only confirmed bar data (open, high, low, close, volume) from completed bars. No future data is referenced. No calculations change retroactively after a bar closes. The impulse detection, energy assignment, decay computation, exhaustion detection, and divergence detection all operate exclusively on confirmed historical data. What you see on a closed bar will never change. DISCLAIMER Trading financial instruments involves substantial risk of loss. Past energy states and exhaustion patterns do not guarantee future price behavior. This tool visualizes momentum dynamics to support analysis - it does not provide financial advice. The author assumes no responsibility for trading decisions or losses. Always employ proper risk management and never risk capital you cannot afford to lose. - BullByte
Indicador Pine Script®
por BullByte
8
Extended Sentiment Pressure Oscillator (ESP)Extended Sentiment Pressure Oscillator (ESP) The ESP is a multi-purpose trend and bias oscillator designed to visualize who is in control: buyers or sellers. It measures the balance between upward and downward pressure inside each candle and across a lookback window, then converts that information into an easy-to-read visual signal. Unlike classic oscillators that only look at close prices, ESP evaluates price structure (High–Low–Open–Close), range behavior, and multiple normalization methods. This makes it adaptable to many markets—from fast crypto scalping to slower swing trading on stocks, forex, commodities... What makes ESP different? _______________________ Most oscillators give you a single line. ESP gives you a full pressure model: * Uptrend line – how strong buyers are * Downtrend line – how strong sellers are * Net Pressure (Bias) – the real battle result * Optional histogram and signals You can view it in: * Classic 0–100 mode (Average Sentiment Oscillator style) * Expanded centered mode (-50…+50) for intuitive bullish/bearish reading ESP is not “another RSI”. It focuses on market pressure and imbalance, not overbought/oversold. Core Features ____________ Multi-Normalization Engine - Choose how pressure is measured: * Bar Range – immediate candle structure * Window Range – broader context * Mix – blend of both, averaged. * Hybrid - pure blend of Bar- & Window Range, not averaged. * (Average) True Range (TR / ATR) – volatility-aware modes Adaptive Smoothing: Select your preferred MA type: SMA, EMA, HMA, SMMA (RMA), WMA, VWMA Sensitivity Control - A unique ESP Sensitivity knob lets you: * Reduce noise (<1.0) * Amplify reactions (>1.0) * or stay neutral (1.0) Signal Logic - Two modes: * ZeroCross – classic bias crossing * MomentumShift – early detection using consecutive rises/falls and slope strength Visual Tools: * Tricolor Net Pressure line * Bias histogram * Optional UP/DOWN flags * Focus mode to highlight the most important signal How to Use ESP (Practical Use Cases) ? ________________________________ 1) Trend Confirmation Use ESP as a trend filter for your main strategy: * Net Pressure above 0 → bullish environment * Net Pressure below 0 → bearish environment * Rising Net Pressure → momentum building Great companion to combine with: * Price Action * Other indicators like * Crossing EMA's * MACD * VWAP * RSI * ... * Breakout systems * ... 2) Early Momentum Detection With MomentumShift mode, ESP can react before a zero cross: * Two or more consecutive rises = early bullish shift * Two or more consecutive falls = early bearish shift * Optional minimum slope filters weak moves Ideal for: * Scalping pullbacks * Exit timing * Avoiding late entries 3) Regime & Strength Analysis by combining: * Up/Down lines * Net Pressure * Histogram This lets you read: * Strong trends * Weak consolidations * Momentum exhaustion * Diverging pressure vs price Who is this for? _____________ Anyone can use this indicator at will, while this could prove an extra aid especially for: * Discretionary traders needing clear bias visualization * Traders looking for a robust gate/filter aid * Multi-asset traders (crypto, stocks, forex, commodities,...) Important Notes ______________ ESP is an indicator or technical analytical tool, not a trading system Works best combined with price action and risk management Past performance ≠ future results Signals provided should not be used solely to make any trading decisions Trading always involves risk To conclude, ESP or Extended Sentiment Pressure oscillator can help you understand the pressure behind the candles, making decisions clearer based on structure rather than on noise.
Indicador Pine Script®
por PJooris1408
2
Bernoulli Process: Trend Probability & Entropy [MarkitTick]💡 This technical indicator introduces a rigorous probabilistic framework to the evaluation of market regimes by modeling price fluctuations as a Bernoulli Process. Unlike traditional oscillators that merely measure the magnitude of price movement, this script treats every bar as a discrete "trial" that either succeeds or fails based on specific conditions—such as directional price action, momentum thresholds, or trend alignment. By applying Information Theory and the principles of Maximum Likelihood Estimation (MLE), the script quantifies not just the direction of the market, but the statistical reliability and the "noise" content of the current sequence. This allows traders to distinguish between a structured trend and high-entropy market "chop," providing a level of objective clarity often missing in standard technical analysis. ● ✨ Originality and Utility The primary innovation of this script lies in its transition from deterministic price tracking to stochastic regime modeling. Most indicators suffer from the "binary trap," where they simply tell a trader if price is above or below a level without assessing the statistical significance of that state. • Quantifying Market Information By integrating Shannon’s Binary Entropy, the script measures the uncertainty inherent in a price sequence. When entropy is near 1.0, the market is in a state of maximum uncertainty (effectively a fair coin toss), signaling that a trader should likely avoid the "noise." Conversely, low entropy values indicate a high-information state where one side of the Bernoulli trial is dominating, suggesting a persistent trend. • Adaptive Definition of Success The script is not limited to a single logic; it allows the user to define what constitutes a "Success" in the Bernoulli trial. Whether you prioritize raw price action (Close > Open), momentum (RSI > 50), or trend-following (Price > Moving Average), the underlying probabilistic engine remains consistent, making it a versatile tool for various trading styles. • Z-Score Significance Testing It applies a Central Limit Theorem (CLT) approximation to calculate a Z-Score. This tells the trader how many standard deviations the current trend is away from a random walk (p=0.5). This provides a mathematical filter to avoid entering "trends" that are actually within the bounds of statistical randomness. ● 🔬 Methodology and Concepts The script operates through a four-stage mathematical pipeline that converts raw market data into probabilistic metrics. • Stage 1: The Bernoulli Trial (I) The foundation is the indicator variable (I). On every bar, the script evaluates a boolean condition. If the condition is met, the trial is a "Success" (1.0); otherwise, it is a "Failure" (0.0). This transforms complex candles into a simple binary sequence: {1, 0, 1, 1, 0...}. • Stage 2: Probability Estimation (p-hat) Using a rolling window of length N, the script calculates the Maximum Likelihood Estimate (MLE) of the probability parameter 'p'. This is essentially the sample mean of the successes within the window. A value of 0.7 suggests that in the last N trials, 70% were successful. • Stage 3: Binary Entropy Calculation The script calculates Entropy H(p) using the formula: H(p) = -p * log2(p) - (1-p) * log2(1-p) This provides a metric for "Trend Quality." If p is 0.5 (random), H(p) is 1.0 (maximum noise). If p is 1.0 or 0.0 (perfect trend), H(p) is 0.0 (maximum order). • Stage 4: Volatility-Adjusted Z-Score To determine if a sequence is truly anomalous, the script calculates the standard deviation of a fair process and compares the observed deviations to this baseline. This identifies "Significant Trends" that are mathematically distinct from a 50/50 random distribution. ● 🎨 Visual Guide The visual interface is designed to communicate complex statistical data through intuitive color-coded cues. • The Bernoulli Probability Line The main plot is a continuous line representing the estimated probability (p). A value above 0.5 indicates a bullish bias (p-hat > 0.5). A value below 0.5 indicates a bearish bias (p-hat < 0.5). • Dynamic Entropy Coloring The line does not just change color based on direction; it changes based on certainty. Vibrant Green: Strong bullish trend with low entropy (High Certainty). Vibrant Red: Strong bearish trend with low entropy (High Certainty). Gray/Faded Color: High entropy regime (Entropy > 0.9). This signals that the market is "choppy" and the probability of success is too close to random to be reliable. • Background Entropy Zones The chart background highlights areas of "Max Entropy" in a subtle gray color. When you see these zones, it suggests the current Bernoulli definition is failing to find a directional edge, signaling a period of market consolidation. • Real-Time Metrics Dashboard A table in the top-right corner displays: Probability (p): The exact decimal value of the current trend probability. Entropy (Bits): The current level of uncertainty in the sequence. Regime: A text-based label identifying the market state (Bull Trend, Bear Trend, or Noise/Chop). • Execution Signals Small triangles appear on the chart to mark high-probability transition points. A Triangle Up (Green) marks a bullish breakout from a low-entropy state, while a Triangle Down (Red) marks a bearish breakdown. ● 📖 How to Use • Identifying Low-Noise Entries Traders should look for instances where the Probability Line crosses the 0.5 threshold while Entropy is low (vibrant colors). If the line is gray, the "trend" lacks statistical significance, and the risk of a whip-saw is high. • Regime Filtering Use the indicator as a "Mode Filter." If the Dashboard displays "NOISE / CHOP," it is a signal to stay flat or use mean-reversion strategies. If it displays a "TREND" regime, trend-following strategies can be deployed with higher confidence. • Interpreting the Z-Score While not directly plotted, the Z-Score logic powers the signal generation. A signal is only produced when the deviation from the "Fair Coin" (0.5) is substantial enough to suggest a non-random event. ● ⚙️ Inputs and Settings • Bernoulli Trial Definition Choose between three calculation modes: Price Action: Uses the relationship between Close and Open (Directional bars). Momentum: Uses RSI relative to the 50-level (Standard momentum). Trend: Uses Price relative to a Simple Moving Average (Long-term regime). • Sample Window (N) Determines the "lookback" for the probability calculation. Smaller values (e.g., 10-15) are more responsive but noisier; larger values (e.g., 30-50) provide a smoother, more institutional view of the regime. • Risk Management (Alerts) Target R:R Ratio: Used to calculate the Take Profit level in the JSON alerts. Stop ATR Multiplier: Uses Average True Range to calculate a volatility-adjusted stop loss for signals. ● 🔍 Deconstruction of the Underlying Scientific and Academic Framework The "Bernoulli Process: Trend Probability & Entropy" script is built upon the pillars of Discrete Stochastic Processes and Information Theory. • The Law of Large Numbers (LLN) The script relies on the LLN, which states that as a sample size grows, its mean gets closer to the average of the whole population. By using a "Sample Window," we are performing a rolling MLE of the true underlying probability parameter of the market at that moment. • Shannon Entropy and Information Theory Claude Shannon’s 1948 work on information entropy is the bedrock of the "Noise" detection in this script. In the context of trading, entropy represents the "surprise" or "uncertainty" in the price sequence. A low-entropy market is one where the next bar's success/failure is highly predictable based on the recent past, which is the mathematical definition of a trend. • Bernoulli vs. Gaussian Distributions Most indicators assume a Normal (Gaussian) distribution of price returns. However, market states are often better modeled as discrete outcomes (Up/Down). By treating the market as a Bernoulli Process, we bypass the "fat-tail" problem of Gaussian distributions and focus purely on the frequency of successful outcomes, making the tool more robust against outliers. • The Z-Test for Proportions By applying a Z-score calculation to a Bernoulli distribution, the script treats the market like a "biased coin" experiment. It tests the Null Hypothesis ($H_0$): "The market is a fair coin (p=0.5)." When the Z-score is high, we reject $H_0$ in favor of the Alternative Hypothesis ($H_1$): "The market is trending (p != 0.5)." ⚠️ Disclaimer All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion.
Indicador Pine Script®
por MarkitTick
Quantum Mean Reversion Oscillator[Pineify]Quantum Mean Reversion Oscillator - Statistical Z-Score Based Trading Signals The Quantum Mean Reversion Oscillator (QMR) is a statistically-driven momentum indicator designed to identify high-probability mean reversion opportunities in any market. Built on the foundation of Z-score analysis, this oscillator measures how far price has deviated from its statistical mean, expressed in standard deviations. When price stretches too far from equilibrium, it tends to snap back—this indicator captures those precise moments. Key Features Z-Score based oscillator measuring price deviation from dynamic mean Adaptive EMA-based mean calculation for responsive trend detection Customizable standard deviation multiplier for volatility adjustment Built-in smoothing to filter market noise and reduce false signals Visual gradient glow effect showing momentum intensity Clear overbought/oversold threshold levels at +2.0 and -2.0 Automatic buy and sell signal generation on mean reversion events Pre-configured alert conditions for automated trading workflows How It Works The indicator employs a three-step calculation process rooted in statistical analysis: Dynamic Mean Calculation: Rather than using a simple moving average, the oscillator uses an Exponential Moving Average (EMA) as the basis. This makes the mean more responsive to recent price action while still maintaining statistical validity. Z-Score Computation: The core of this indicator is the Z-score formula: (Price - Mean) / Standard Deviation. This transforms raw price data into a normalized scale where values represent how many standard deviations price has moved from its mean. A reading of +2.0 means price is two standard deviations above average—a statistically significant extreme. Noise Reduction: The raw Z-score is smoothed using a Simple Moving Average to eliminate whipsaws and provide cleaner, more actionable signals. Trading Ideas and Insights Mean reversion is one of the most fundamental concepts in quantitative trading. Markets tend to oscillate around fair value, and extreme deviations often precede reversals. The QMR Oscillator quantifies this behavior: When the oscillator exceeds +2.0, price is statistically overbought—approximately 95% of price action occurs below this level under normal distribution When the oscillator drops below -2.0, price is statistically oversold—a zone where buying pressure typically emerges The crossback signals (crossing back inside from extremes) indicate the reversion has begun, providing entry timing This approach works particularly well in ranging markets and can identify exhaustion points in trending markets where pullbacks are likely. How Multiple Indicators Work Together The QMR Oscillator integrates three complementary statistical concepts into a unified framework: EMA for Mean: Provides a responsive baseline that adapts to changing market conditions faster than traditional SMA, ensuring the "fair value" reference point stays relevant. Standard Deviation for Volatility: Automatically adjusts the oscillator's sensitivity based on current market volatility. During high volatility, larger price moves are required to reach extreme readings, preventing false signals. SMA Smoothing: Applied as a final filter to remove noise without introducing significant lag, balancing responsiveness with reliability. These three components work synergistically—the EMA tracks the trend, standard deviation normalizes for volatility, and smoothing ensures signal quality. Unique Aspects Statistical Foundation: Unlike arbitrary oscillator boundaries, the +/-2.0 levels have statistical meaning—representing approximately 2 standard deviations from the mean Visual Gradient System: The glow effect intensifies as price moves further from equilibrium, providing intuitive visual feedback on momentum strength Adaptive Sensitivity: The deviation multiplier allows traders to adjust how extreme price must move before triggering signals, accommodating different trading styles and market conditions How to Use Add the indicator to your chart and observe the oscillator's position relative to the zero line and threshold levels Look for buy signals (B markers) when the oscillator crosses back above -2.0 from oversold territory Look for sell signals (S markers) when the oscillator crosses back below +2.0 from overbought territory Use the gradient glow intensity to gauge momentum strength—brighter colors indicate more extreme conditions Set up alerts using the built-in alert conditions for automated notifications Customization Mean Lookback (default: 20): Controls the EMA period for mean calculation. Shorter periods increase sensitivity; longer periods provide smoother readings Deviation Multiplier (default: 2.0): Adjusts how many standard deviations define the bands. Higher values require more extreme moves for signals Smoothing (default: 3): Controls noise filtering. Increase for smoother signals in choppy markets Bullish/Bearish Glow Colors: Customize the visual appearance to match your chart theme Show Reversion Signals: Toggle buy/sell markers on or off Conclusion The Quantum Mean Reversion Oscillator provides traders with a statistically rigorous tool for identifying mean reversion opportunities. By combining Z-score analysis with adaptive volatility measurement and intelligent smoothing, it offers a systematic approach to finding high-probability reversal points. Whether used as a standalone indicator or as confirmation for other analysis methods, the QMR Oscillator brings quantitative precision to mean reversion trading strategies.
Indicador Pine Script®
por Pineify
Nova Capital MACDNova Capital MACD is a momentum oscillator based on the classic MACD calculation, enhanced with a clean 4-state histogram and optional signal labels. Core calculation: MACD Line = Fast MA − Slow MA Signal Line = MA(MACD Line, Signal Length) Histogram = MACD Line − Signal Line Features in this version: 4-state histogram coloring (positive/negative + rising/falling) to visualize momentum changes more clearly. Optional confirmed-bar behavior (signals trigger only on closed bars). Optional zero-line directional filter: Long labels only when MACD is below 0. Short labels only when MACD is above 0. Built-in alert conditions for Long/Short events. How to use: Watch histogram state changes for momentum transitions. A Long label appears on MACD crossing above the Signal line (optionally below 0). A Short label appears on MACD crossing below the Signal line (optionally above 0). Note: This indicator is not a complete trading system. Use risk management and confirm signals with market context.
Indicador Pine Script®
por novacapitalvip
Blockcircle FTR - Follow Through ReversalWHAT THIS INDICATOR DOES Blockcircle FTR identifies failed directional moves followed by quality reversals. The indicator tracks structural pivot levels, monitors price interactions with those levels, and validates reversal sequences against a configurable threshold. A trend filter provides macro context so you can evaluate whether signals align with or oppose the broader direction. KEY FEATURES Reversal quality filtering via delivery threshold requirement Sweep confirmation when reversals follow liquidity grabs at structural levels ATR-adaptive origin zones marking reversal starting points Trend alignment indicator comparing signal bias to moving average direction Volume validation filter for participation confirmation Real-time dashboard with signal statistics and alignment status DETAILED BREAKDOWN Structural Level Tracking The indicator identifies pivot highs and lows based on the Structure Lookback parameter. These pivots serve as reference levels where liquidity typically accumulates. Levels remain active until price interacts with them or they exceed the Level Lifespan setting. When the price reaches a structural level, this interaction is logged. If a reversal then forms in the opposite direction within the Sweep Window, the signal qualifies as sweep-confirmed, indicating that stops were likely triggered before the move reversed. FTR Detection Logic The core detection looks for a specific sequence: a directional attempt that fails to follow through, followed by a counter-move that meets the Delivery Threshold ratio. This ratio measures the quality of the reversal relative to the failed move's structure. Higher threshold values (closer to 1.0) require cleaner, more convincing reversals. Lower values (closer to 0.1) allow weaker setups through. The default of 0.7 provides reasonable filtering without being overly restrictive. Trend Context Filter A moving average (EMA or SMA, configurable period) provides simple trend context. The dashboard displays three related metrics: Trend: Current price position relative to the MA (Bullish/Bearish) FTR Bias: Direction of the most recent confirmed signal (Long/Short) Aligned: Whether these two readings match (Yes/No) This helps identify situations where the FTR bias has become stale or is positioned against the prevailing trend. Signal Classification Standard signals appear as small triangles and represent FTR patterns that passed the delivery threshold and any active filters. Sweep-confirmed signals appear with an "S" label and represent the subset of signals where price swept a structural level shortly before the reversal formed. These carry higher conviction due to the additional liquidity context. Dashboard Metrics The information panel provides: Current trend direction and FTR bias Alignment status between the two Bars elapsed since the last signal Running totals for long and short signals Sweep-confirmed counts in parentheses Volume filter status Configuration Parameters Structure Lookback: Bars used for pivot detection. Higher values capture more significant swings. Delivery Threshold: Minimum ratio for valid reversals. Range 0.1 to 1.0. Level Lifespan: The maximum bars a structural level remains active. Sweep Window: Lookback period for sweep confirmation. Trend MA Period: Moving average length for trend context. Volume Spike Multiple: Required volume ratio when volume filter is active. Zone Depth: Origin zone width as ATR multiple. Practical Application Sweep-confirmed signals with trend alignment represent the highest-conviction setups. These combine a quality reversal pattern, liquidity sweep context, and trend support. Standard signals without sweep confirmation remain valid FTR patterns but warrant additional discretion. Counter-trend signals (Aligned showing NO) can still produce valid moves, but historically carry lower probability. Consider position sizing adjustments accordingly. Origin zones serve as potential support/resistance areas for subsequent price returns. Important Limitations The indicator may remain biased in the wrong direction during extended trends if no qualifying reversal pattern forms. The trend filter helps identify these situations, but does not automatically override the FTR bias. Signal counts are calculated on visible chart history and will vary based on the loaded timeframe and bar count. As with any technical tool, signals should be evaluated within the broader market context rather than traded mechanically. Hope you find it useful! If you have any questions, please don't hesitate to ask them!
Indicador Pine Script®
por blockcircle
2
Aura Vortex Oscillator [Pineify]Aura Vortex Oscillator – Adaptive Momentum with Visual Depth The Aura Vortex Oscillator is a sophisticated momentum indicator that transforms raw price action into a visually immersive analytical tool. By combining Sigmoid-based normalization through ArcTan mathematics with adaptive momentum calculations, this oscillator delivers clear, bounded signals while filtering market noise. The distinctive "Vortex Mesh" visualization creates a layered depth effect that reveals trend consensus across multiple smoothing periods. Key Features Sigmoid normalization using ArcTan function for bounded output (-100 to +100) Adaptive momentum calculation with standard deviation normalization Multi-layered "Vortex Mesh" creating visual depth and trend confluence signals Dynamic color-coded visualization for instant trend recognition Zero-line crossover signals with plotted reversal markers Extreme zone highlighting for overbought/oversold conditions How It Works The core calculation begins with computing the Z-score of price relative to its simple moving average, normalized by standard deviation. This adaptive component automatically adjusts sensitivity based on recent volatility. The normalized value then passes through an ArcTan function, which acts as a sigmoid transformation, "squarifying" the output to emphasize extreme conditions while keeping values bounded. os = atan(z × intensity) × 63.66 The multiplier 63.66 scales the output to approximately -100 to +100, providing intuitive overbought/oversold levels at ±50. Trading Ideas and Insights Use zero-line crossovers as primary trend change signals – bullish when crossing above, bearish when crossing below Monitor the Vortex Mesh thickness – a thick, solid aura indicates strong trend consensus across timeframes Watch for background highlighting at ±50 levels to identify statistical extremes for potential reversals Combine with price action analysis when the oscillator reaches boundary zones How Multiple Indicators Work Together The Aura Vortex Oscillator integrates three technical concepts into one cohesive system. The adaptive momentum calculation provides the raw signal, responding dynamically to market volatility. The ArcTan normalization bounds this signal and emphasizes extremes without clipping. Finally, the Vortex Mesh applies multiple EMA smoothing layers to the base signal, creating visual depth that shows whether different momentum speeds agree on trend direction. Unique Aspects Unlike traditional oscillators that show a single line, this indicator visualizes momentum as a "thermal field" through its layered mesh system. The mesh expands and contracts based on trend agreement – a thick, cohesive glow suggests high-confluence momentum, while a thin, scattered appearance warns of choppy, range-bound conditions. How to Use Add the indicator to your chart as a separate pane Look for color transitions (green to red or vice versa) at zero-line crosses for trend reversals Use the ±50 boundary zones and background highlighting to identify overextended conditions Enable the Vortex Mesh to visualize trend strength and momentum consensus Customization Vortex Sensitivity (20) : Base period for momentum calculation – lower values increase responsiveness Vortex Intensity (2.0) : Amplifies signal squarification – higher values push readings toward extremes faster Aura Smoothing (8) : EMA period for the main signal line – higher values reduce noise Enable Vortex Mesh : Toggle the layered visualization effect Color Settings : Customize bullish, bearish, and neutral colors Conclusion The Aura Vortex Oscillator offers traders a unique perspective on momentum analysis by combining mathematical rigor with innovative visualization. Its adaptive normalization ensures reliable signals across different market conditions, while the Vortex Mesh provides instant visual feedback on trend quality. Whether you are identifying trend reversals, measuring momentum strength, or seeking confluence confirmation, this oscillator delivers actionable insights in an intuitive format.
Indicador Pine Script®
por Pineify
BE-QuantFlow: Adaptive Momentum Trading█ Overview: QuantFlow: Adaptive Momentum Trading QuantFlow is a sophisticated algorithmic momentum trading method designed specifically for indices and high-beta stocks. However, its logic is universal; with appropriate parameter tuning, it adapts to various asset classes and timeframes. While the standard momentum indicators (like RSI or MACD) simply measure how fast price is moving (Velocity), QuantFlow analyzes the quality and conviction of the trend . Features like Dynamic Volatility Filtering and Trend Shielding, combined with volatility weighting and a "Dual-Line" approach to distinguish between a sustainable institutional trend and a temporary retail spike, make the indicator unique and more powerful. █ Why QuantFlow ? Quant (The Engine): This replaces subjective guessing with objective math. Instead of just seeing that the price is "up," we measure "how it got there". For example, a stock that rises 1 currency value every day for 10 days (smooth trend) gets a much higher score than a stock that jumps 10 currency value in one minute and does nothing else (erratic noise). This mathematical rigor provides the structure. █ Core Logic & Philosophy To understand how QuantFlow calculates momentum, imagine a "Tug-of-War" between Buyers (Bulls) and Sellers (Bears). Most indicators (like RSI) use a single line. If RSI is at 50, it means "Neutral." But "Neutral" can mean two very different things: Peace: Nothing is happening. No one is buying or selling. War: Buyers are pushing hard, but Sellers are pushing back equally hard. Volatility is massive. A single line hides this reality. QuantFlow splits the market into two separate scores: Bull Score (Green Line): How hard are the buyers pushing? Bear Score (Red Line): How hard are the sellers pushing? The Layman's Advantage: If both lines are low = Sleepy Market (Avoid). If Green is high and Red is low = Clean Uptrend (Buy). If Red is high and Green is low = Clean Downtrend (Sell). If both lines are high = Chaos/War Zone (Wait). █ How it Weight "Sustenance" (The Critical Quality Check) This is the most unique aspect of QuantFlow: Trend direction alone is not enough; Sustenance is weighed equally . Standard indicators treat every 10 currency value movements the same way with no distinction. However, QuantFlow asks, "Did you hold the ground you gained?" Scenario A (High Sustenance) : A stock opens at 100, marches to 110, and closes at 110. Verdict : Buyers pushed up and sustained the price. QuantFlow Weight : 100%. This is a high-quality move. Scenario B (Low Sustenance) : A stock opens at 100, spikes to 110, but gets sold off to close at 102. Verdict : Buyers pushed up (Trend is Up), but failed to sustain it (Long Wick). QuantFlow Weight : 20%. This is treated as "Noise" or a trap. By mathematically weighing the Close Location Value (where the candle closes relative to its high/low), QuantFlow filters out "Gap-and-Fade" traps and exhaustion spikes that fool traditional indicators. Comparisons: QuantFlow vs. The Rest Calculation Logic : Standard RSI/MACD measures simple price change over time. QuantFlow measures Price Change 'times (x)' Conviction (Sustenance Weighting). Visual Output : Standard tools show a single line (0-100), often hiding market conflict. QuantFlow displays Dual Lines (Bull vs Bear Intensity) to reveal the true state of the battle. Trap Handling : Standard indicators are often fooled by sharp spikes. QuantFlow ignores "Gap-and-Fade" moves with poor closing conviction. Adaptability : Standard tools use static levels (e.g., Overbought > 70). QuantFlow uses Dynamic Bands that adjust automatically to recent volatility. █ Dynamic Volatility Filtering Unlike standard indicators that use fixed levels (e.g., "Buy if RSI > 50"), QuantFlow acknowledges that "50" means something different in a quiet market versus a crashing market. This section explains the statistical engine driving the signals. The Problem with Static Levels : In a low-volatility environment, a momentum score of 55 might indicate a massive breakout. In a high-volatility environment, a score of 55 might just be random noise. A fixed threshold cannot handle both scenarios. The Solution: Adaptive Statistics : The script maintains a memory of the Momentum Events. It doesn't just look at price; it looks at where the momentum occurred in the past and draws a "Noise Zone" (Grey Band). This logic acts as a "Smart Gatekeeper" for trade entries: Scenario A: Inside the Noise (The Filter) If a new momentum signal happens inside the Noise Zone, the script assumes it is likely chop or noise. Action : It forces a wait period. The signal is delayed until the trend sustains itself for Confirm Bars; else the signal is cancelled. This filters out ~70% of false signals in sideways markets. Scenario B: Outside the Noise (The Breakout) If a new momentum signal happens outside the Noise Zone (or the momentum score smashes through the Upper Band), it is statistically significant (an outlier event). Action: It triggers an Immediate Entry. No waiting is required because the move is powerful enough to escape the historical noise zone. █ The ⚠️ "Warning" System (Heads-up for Smart Reversals) While you are directional if there is potential reversal signal, it provides the heads-up warning for a better decision-making █ Special Utility: Ghost Mode For intraday traders, the biggest disruption to "Flow" is the mandatory broker square-off at 3:15 PM (considering Indian Market). Often, a trend continues overnight, and the trader misses the gap-up opening the next morning because their algo was flat. Ghost Mode is a unique feature that runs silently in the background: At Square-off: The strategy closes your official position to satisfy the broker. In the Background: It keeps the trade "alive" virtually (Ghost). Next Morning: If the market opens in the trend's favor, the strategy re-enters the trade automatically. This approach ensures you capture the full swing of the trend, even if you are forced to exit at the previous session. █ Advice on this indicator: Parameter Calibration: The default settings are optimized for BankNifty on 5-minute charts. If you trade stocks, crypto, commodities, or any higher timeframes (e.g., 15-min or hourly), you must adjust these. Low Volatility Assets: Reduce Stop Multiplier to 2.0. High Volatility Assets: Increase Momentum Lookback to 50 to filter noise. Confluence (Additional Confirmation): While QuantFlow is a complete system, using it alongside Key Support/Resistance Levels or Volume Profile provides the highest probability setups.
Estratégia Pine Script®
por TradeWiseWithEase
2
Accumulative Swing Cloud [MarkitTick]💡This indicator presents a modernized hybrid approach to J. Welles Wilder’s classical Accumulative Swing Index (ASI). While the traditional ASI is often viewed as a simple line oscillator used to confirm price breakouts, the Accumulative Swing Cloud reconstructs this concept into a dynamic trend-following system. By smoothing the raw ASI data into multiple moving average layers, this script creates a "Cloud" structure that visualizes the strength, direction, and momentum of the swing index, effectively treating the ASI value itself as a tradeable price action entity. ● Originality and Utility The standard Accumulative Swing Index is a powerful tool for seeing through the "noise" of open, high, low, and close prices to find the real trend. However, looking at a raw ASI line can be jagged and difficult to interpret for sustained trends. This script innovates by applying "Cloud Dynamics" to the ASI. It calculates three distinct moving averages (Fast, Mid, and Slow) of the ASI value itself. The area between the Fast and Slow averages is filled with a dynamic gradient color. This allows traders to not only see the trend direction (Bullish or Bearish) but also gauge the volatility and strength of the move based on the expansion or contraction of the cloud's width. Additionally, this version introduces an optional Volume Integration feature, allowing the Swing Index calculations to be weighted by relative volume, giving more significance to moves backed by high market participation. ● Methodology and Calculations The core of this indicator relies on the Swing Index calculation. It compares the current bar's Open, High, Low, and Close against the previous bar's values to derive a variable "R" (a measure of the market's range). The script determines the largest price movement (K) among the High-Close, Low-Close, and High-Low ranges. It calculates the "R" value based on the relationship between the daily range and the gap between the prior close and current open. A Swing Index (SI) value is derived using the Limit Move value (T), the defined Multiplier, and the calculated R and K values. This SI is accumulated into a running total (ASI State). If Volume Integration is enabled, the SI is multiplied by a Volume Factor (Current Volume divided by Average Volume), capped at 3.0 to prevent outlier distortion. ● Visual Guide The indicator plots several key visual elements on the chart: Cloud Fast (Green Line): Represents the shorter-term moving average of the Accumulative Swing Index. Cloud Slow (Red Line): Represents the longer-term moving average. Cloud Fill (Gradient Area): The space between the Fast and Slow lines. Green Gradient: Indicates the Fast MA is above the Slow MA (Bullish Trend). Red Gradient: Indicates the Fast MA is below the Slow MA (Bearish Trend). Gradient Intensity: The opacity of the color scales dynamically based on the width of the cloud relative to its recent historical maximum. A wider cloud (stronger trend/higher volatility) appears more solid, while a narrow cloud appears more transparent. ASI Line (Color-Coded Line): The thick line represents the current raw Accumulative Swing Index value. It changes color (Green/Red) based on its position relative to the Signal Line. Signal Line (Gray Line): A Simple Moving Average of the ASI Line, acting as a trigger for immediate reversals. Bar Coloring: The main price candles are colored to match the current state of the Cloud (Green for Bullish Cloud, Red for Bearish Cloud). ● How to Use Trend Identification: Use the Cloud color to determine the primary trend. A Green Cloud suggests an uptrending market structure, while a Red Cloud suggests a downtrend. Entry Signals: Traders often look for the "ASI Line" to cross the "Signal Line" in the direction of the Cloud. For example, if the Cloud is Green, a crossover of the ASI Line above the Signal Line is a bullish confirmation. Cloud Crossovers: A crossover of the Fast and Slow Cloud lines represents a major structural shift in the Accumulative Swing Index trend. Volatility Filter: Pay attention to the gradient intensity. A very narrow (transparent) cloud indicates low momentum or consolidation, while a widening (solid) cloud indicates expanding momentum. ● Inputs and Settings ASI Core Engine: Configure the Daily Limit (T) and Multiplier to tune the sensitivity of the Swing Index calculation. Volume Integration: Toggle "Weight ASI by Volume" to factor in volume spikes. Adjust "Volume Avg Length" to define the baseline volume. Cloud Dynamics: Choose the Moving Average type (EMA, SMA, RMA, WMA) and set the Fast, Mid, and Slow lengths to customize the cloud's reactivity. Visual Enhancements: Toggle "Color Candles by Cloud Width" to apply the gradient coloring directly to the price bars. ● Disclaimer All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion.
Indicador Pine Script®
por MarkitTick
JRockets MACDThis is my favorite indicator, that I use as one of my conformations before entering a trade in the 15M timeframe This MACD is tailor made by me to work efficient, consistent, and effectively. I back tested tons of times, it helps if you're entering too early, late and even get faked out. The MACD is by far my favorite and one and only indicator, and here's why. The MACD contains 2 EMA lines where it gives me a signal on when to buy or sell. If the Blue line crosses the red line on the bottom of the indicator its giving buy signals as long as the blue line stays on top, and when the red line crosses the blue line on top of the indicator its giving sell signals as long as the redline stay on top. Be sure to pay attention to the candle stick patterns as well and has to be around key levels. What makes this a better signal as well, the MACD has a built-in momentum hologram, some see it as overbought/undersold, or volume indicator. By combining the momentum hologram with your buy/sell ema will prevent you from entering a trade in the wrong area. The momentum hologram is almost self-explanatory, when there is buying pressure, the hologram turns blue, the darker the blue the stronger the momentum as well as the length of the hologram, once is start losing momentum it starts to turn to a lighter blue. Eventually a light red to a solid red showing momentum for a strong sell, this works vice versa. Combing all that at once and built instincts it becomes very effective. You can also use the EMA signals as divergence, but I don't really trade with divergence but could possibly give you conformation. Using the MACD is like having 3-4 indicators in one with all of them working fluent together. I have the MACD locked on the 15M timeframe because that's where it works more accurately. You can make the EMA lines a bit thicker to be easier to see. I would change the MACD visible for the 15M timeframe only or 1M to 1H timeframe. I hope this indicator helps you, as it did for me. You can simply click add on your charts on the top left to get this free indicator. Peace out and enjoy! Be sure to share, this indicator with your friends as it may help someone out.
Indicador Pine Script®
por JRockets
15
QUANT TRADING ENGINE [PointAlgo]Quant Trading Engine is a quantitative market-analysis indicator that combines multiple statistical factors to study trend behavior, mean reversion, volatility, execution efficiency, and market stability. The indicator converts raw price behavior into standardized signals to help evaluate directional bias and risk conditions in a systematic way. This script focuses on factor alignment and regime awareness, not prediction certainty. Design Philosophy Markets move through different regimes such as trending, ranging, volatile expansion, and instability. This indicator attempts to model these regimes by blending: Momentum strength Mean-reversion pressure Volatility risk Trend filtering Execution context (VWAP) Correlation structure Each component is normalized and combined into a single Quant Alpha framework. Factor Construction 1. Momentum Factor Measures directional strength using percentage price change over a rolling window. Standardized using mean and standard deviation. Represents trend continuation pressure. 2. Mean Reversion Factor Measures deviation from a longer moving average. Standardized to identify stretched conditions. Designed to capture counter-trend behavior. Directional Clamping Mean-reversion signals are dynamically restricted: No counter-trend buying during downtrends. No counter-trend selling during uptrends. Allows both sides only in neutral regimes. This prevents conflicting signals in strong trends. 3. Volatility Factor Uses realized volatility derived from price changes. Penalizes environments where volatility deviates significantly from its norm. Acts as a risk adjustment rather than a directional driver. 4. Composite Quant Alpha The final Quant Alpha is a weighted blend of: Momentum Mean reversion (trend-clamped) Volatility risk The composite is standardized into a Z-score, allowing consistent interpretation across instruments and timeframes. Signal Logic Buy signal occurs when Quant Alpha crosses above zero. Sell signal occurs when Quant Alpha crosses below zero. Zero-cross logic is used to represent shifts from negative to positive statistical bias and vice versa. Signals reflect statistical regime change, not trade instructions. Volatility Smile Context Measures price deviation from its statistical distribution. Identifies skewed conditions where upside or downside volatility becomes dominant. Highlights extreme deviations that may imply elevated derivative risk. Exotic Risk Conditions Detects sudden price expansion combined with volatility spikes. Highlights environments where execution and risk become unstable. Visual background cues are used for awareness only. Execution Context (VWAP) Measures price distance from VWAP. Used to assess execution efficiency rather than direction. Helps identify stretched conditions relative to average traded price. Correlation Structure Evaluates short-term return correlations. Detects when price behavior becomes less predictable. Flags structural instability rather than trend direction. Visualization The indicator plots: Quant Alpha (scaled) with directional coloring Volatility smile deviation Price vs VWAP distance Correlation structure Signal markers indicate Quant Alpha zero-cross events and risk conditions. Dashboard A compact dashboard summarizes: Trend filter state Quant Alpha polarity and value Individual factor readings Current action state (Buy / Sell / Wait / Risk) The dashboard provides a real-time snapshot of internal model conditions. Usage Notes Designed for analytical interpretation and research. Best used alongside price action and risk management tools. Factor behavior depends on instrument liquidity and volatility. Not optimized for illiquid or irregular markets. Disclaimer This script is provided for educational and analytical purposes only. It does not provide financial, investment, or trading advice. All outputs should be independently validated before making any trading decisions.
Indicador Pine Script®
por pointalgo
Buyer-Seller Locomotive IndexBuyer-Seller Locomotive Index (BSLI) An original indicator that measures buyer and seller pressure, momentum shifts, and structural control in the market. Overview The Buyer-Seller Locomotive Index evaluates candle-level positioning relative to an adaptive EMA-based reference price. It calculates bull vs bear strength percentages and Total Power momentum using fast and slow EMAs, providing insight into which side currently dominates market structure. By combining pressure analysis with momentum smoothing, BSLI highlights both the intensity and direction of market control. Features Bull/Bear Strength Percentages: Normalized 0–100 values showing current dominance and threshold-based high-strength alerts. Total Power Momentum: Fast and slow EMA crossover signals with a histogram to visualize expansion or contraction of pressure. Visual Markers: Optional fight diamonds highlight candles intersecting the reference price, while dynamic labels show the exact strength percentages. Crossover Signals: Circles mark potential shifts in momentum, helping to identify early transitions in market control. Customizable Display: Users can toggle labels, markers, and histogram visibility for a clean or detailed chart view. How to Use BSLI provides traders with a multi-layered view of market structure: Observe shifts in buyer vs seller dominance. Spot early momentum transitions before trends become obvious. Confirm price structure with Total Power and strength percentages. Highlight periods of compression, conflict, or indecision for additional context. This indicator is intended as a supportive analysis tool. Traders should combine it with personal methodology, risk management, and other analysis techniques. It is not a standalone trade signal. Important Notes Measures relative pressure, not absolute volume. Percentages reflect current structure, not predicted price direction. Signals are contextual; do not rely solely on crossovers for trading decisions. Uses no lookahead; all calculations are based on completed bars. Results may vary by asset, timeframe, and market volatility. Originality BSLI uniquely combines adaptive pressure extraction, normalized strength percentages, dual-EMA power momentum, conflict detection, and integrated labeling. This multi-component approach provides a clear and actionable view of the evolving balance between buyers and sellers, supporting both short-term and structural analysis.
Indicador Pine Script®
por Cryptobingbong
Momentum Structural AnalysisMomentum Structural Analysis (MSA‑style Oscillator) This indicator implements a simple, MSA‑style momentum oscillator that measures how far price has moved above or below its own long‑term trend on the active timeframe, expressed in percentage terms. Instead of looking at raw price, it "oscillates" price around a timeframe‑appropriate simple moving average (SMA) and plots the percentage distance from that SMA as an orange line around a zero baseline. Zero means price is exactly at its structural trend; positive values mean price is extended above trend; negative values mean it is trading below trend. The script automatically selects the SMA length based on the chart timeframe: On daily charts it uses the configurable Daily SMA Length (default 252 trading days, roughly 1 year). On weekly charts it uses Weekly SMA Length (default 208 weeks). On monthly charts it uses Monthly SMA Length (default 120 months). This approach is inspired by the ideas behind Momentum Structural Analysis (MSA), which studies where a market trades relative to long‑term moving averages and then treats the momentum line (the oscillator) as the primary object of analysis. The goal is to highlight structural overbought/oversold conditions and regime changes that are often clearer on momentum than on the raw price chart. -------------------------------------------------- What the script computes and how it works For each bar, the indicator: Chooses an SMA length based on the current timeframe (daily/weekly/monthly). Calculates the SMA of the close. Computes the percentage distance: \text{Diff %} = \frac{\text{Close} - \text{SMA}}{\text{SMA}} \times 100 Plots this Diff % as an orange line, with a dashed horizontal zero line as the base. This produces a momentum oscillator that oscillates around zero and reflects the "structural" position of price versus its own long‑term mean. -------------------------------------------------- How to use it on index charts (e.g., NIFTY50) On indices like NIFTY50, use the indicator to see how stretched the index is versus its structural trend. Typical uses: Identify extremes: a). Historically high positive readings can signal euphoric, late‑stage conditions where risk is elevated. b). Deep negative readings can highlight panic/capitulation zones where downside may be exhausted. Draw structural levels: a). Mark horizontal bands on the oscillator where past turns have occurred (e.g., +15%, −10%, etc. specific to NIFTY50). b). Watch how price behaves when the oscillator revisits these zones: repeated rejections can validate them as structural bounds; clean breaks can indicate a change of regime. This is not a buy/sell signal generator by itself; it is a framework to understand where the index sits within its long‑term momentum structure and to support risk‑management decisions. -------------------------------------------------- How to use it on ratio charts Apply the same indicator to ratio symbols such as NIFTY50/GOLD, BANKNIFTY/NIFTY50, sector vs index, or any spread you plot as a ratio. On a ratio chart: The oscillator now measures relative momentum: how far that ratio is above or below its own long‑term mean. High positive readings = strong outperformance of the numerator vs the denominator (e.g., equities strongly outperforming gold). Deep negative readings = strong underperformance (e.g., equities structurally lagging gold). This is very much in the spirit of MSA’s work on spreads between asset classes: it helps visualize major rotations (equities → gold, financials → commodities, etc.) and whether a relative‑performance trend is stretched, reverting, or breaking into a new phase. -------------------------------------------------- Using multiple timeframes for better decisions You can stack information across timeframes to get a more robust view: Monthly : a). Use monthly charts to see secular/structural phases. b). Long multi‑year stretches above or below zero, and large bases or trendline breaks on the monthly oscillator, can mark major bull or bear cycles and big rotations between asset classes. Weekly : a). Use weekly charts for the primary trend. b). Weekly structures (multi‑month highs/lows, channels, or trendlines on the oscillator) are useful for medium‑term positioning and for confirming or rejecting signals seen on the monthly view. Daily : a). Use daily charts mainly for timing entries/exits once the higher‑timeframe direction is clear. b). Short‑term extremes on the daily oscillator that align with the larger weekly/monthly structure can offer better‑timed opportunities, while signals that contradict higher‑timeframe momentum are more likely to be noise. --------------------------------------------------
Indicador Pine Script®
por PrasadJoshi12
1
Reduced-Lag Chande Momentum Oscillator [BOSWaves]Reduced-Lag Chande Momentum Oscillator – Adaptive Momentum Geometry with Reduced-Latency Reversion Logic Overview The Reduced-Lag Chande Momentum Oscillator represents a sophisticated extension of the classical Chande Momentum Oscillator, preserving the foundational measurement of net directional pressure while addressing inherent limitations in lag, noise, and signal clarity. The traditional CMO provides reliable snapshots of upward versus downward force but reacts slowly to rapid market accelerations and can obscure meaningful momentum inflections with delayed readings. This iteration integrates a dual-stage reduced-lag filter, optional advanced smoothing, and acceleration-based analytics, producing a real-time, multi-dimensional representation of market momentum. The design reframes classical momentum using a layered curvature and gradient structure - main, midline, and shadow - to show trajectory, velocity, and intensity in one view. Instead of the usual ±70/30 extremes, it uses ±50 as a statistically grounded threshold where one side of the market begins exerting true dominance. This captures structural imbalance more reliably, exposing exhaustion and actionable inflection without amplifying noise. This visualization gives traders a continuous, responsive read on market structure, revealing not just direction but rate of change, acceleration alignment, and curvature behavior. The oscillator becomes a momentum map, expressing both probability and intensity behind directional shifts. Where conventional oscillators mislabel short-lived swings as signals, the Reduced-Lag CMO separates baseline shifts from high-conviction transitions, enabling cleaner, more decisive signal interpretation. Theoretical Foundation The classical Chande Momentum Oscillator, created by Tushar Chande, calculates the normalized net difference between consecutive upward and downward price changes over a defined window, generating readings from –100 to +100. While effective for capturing basic directional pressure, the unmodified CMO suffers from signal latency and sensitivity to abrupt market swings, which can obscure actionable inflection points. The Reduced-Lag CMO augments this foundation with three key mechanisms: Reduced-Lag Filtering : A dual-EMA structure eliminates inertial lag, aligning the oscillator curve closely with real-time market momentum without producing overshoot artifacts. Smoothing Architecture : Optional SMA, EMA, or WMA smoothing is applied post-filter, balancing noise reduction with trajectory fidelity. A multi-layer line system (shadow → midline → main) communicates depth, curvature, and gradient dynamics. Acceleration Integration : First and second derivatives of the smoothed curve quantify velocity and acceleration, allowing the indicator to identify not only momentum flips but the force behind each shift, forming the basis for the strong-signal overlay. The combination of these mechanisms produces an oscillator that respects the original CMO framework while delivering real-time, context-sensitive intelligence. The ±50 boundaries are selected as the statistically validated pressure zones where directional dominance exceeds neutral oscillation. Crosses and rejections at these boundaries are not arbitrary overbought/oversold events, but measurable imbalances with actionable significance. How It Works The Reduced-Lag CMO is constructed through a multi-stage process: Momentum Estimation Core : Raw CMO values are calculated and then passed through a reduced-lag filter to remove delay, creating a curve that closely tracks instantaneous directional pressure. Smoothing & Layered Representation : The filtered curve can be smoothed and split into three layers - shadow, midline, and main - giving visual depth, trajectory clarity, and curvature instead of a single-line oscillator. Gradient-Based Pressure Mapping : Color gradients encode momentum strength and polarity. Green-yellow transitions highlight increasing upward dominance, while red-yellow transitions indicate weakening downward force. Pressure-Zone Anchoring (±50) : The system defines statistically significant pressure zones at ±50. Moves beyond these levels reflect dominant directional control, and rejections inside the zone signal potential exhaustion. Signal Generation : Momentum events are evaluated through velocity and acceleration. Standard signals appear as triangle markers indicating validated momentum flips. Strong signals appear as triangles with diamonds when acceleration confirms a high-conviction transition. A cooldown rule spaces signals apart to reduce clutter and emphasize structurally meaningful events. Interpretation The Reduced-Lag CMO reframes momentum as a dynamic equilibrium between directional force and structural pressure: Positive Momentum Phases : Curves above zero with green-yellow gradients indicate sustained upward pressure. Shallow retracements or midline tests denote controlled pullbacks. Negative Momentum Phases : Curves below zero with red-yellow gradients show downward dominance. Rejections from –50 highlight potential exhaustion and reversal readiness. Pressure-Zone Dynamics (±50) : Crosses beyond ±50 confirm dominant directional force. Meanwhile, rejections and rotations inside the zone signal structural fatigue. Velocity & Acceleration Analysis : Rising momentum with decelerating velocity suggests fading force; acceleration alignment amplifies signal strength and forms the basis of strong signals. Signal Architecture The Reduced-Lag CMO produces a single event type with two intensities: a validated momentum inflection. Standard Signals - Triangles: Triggered by momentum flips confirmed by velocity. Represent moderate-intensity directional changes. Appear at zero-line crosses or ±50 rejections with aligned velocity. Strong Signals Triangles + Diamonds: Triggered when acceleration confirms the directional change. Represent high-intensity, high-conviction shifts. Rare by design; indicate robust momentum inflections. Cooldown mechanics prevent repeated signals in short succession, emphasizing structural reliability over noise. Strategy Integration Trend Confirmation : Align zero-line flips with higher-timeframe directional bias. Reversal Detection : Strong signals from ±50 zones highlight potential inflection points. Volatility Assessment : Gradient transitions reveal strengthening or weakening momentum. Pullback Timing : Multi-layer curvature identifies controlled retracements vs trend exhaustion. Confluence Mapping : Pair with structure-based indicators to filter signals in context. Technical Implementation Details Core Engine : Classical CMO with Ehlers reduced-lag extension Lag Reduction : Dual EMA filtering Smoothing : Optional SMA/EMA/WMA post-filter Multi-Layer Curve : Shadow, midline, main Signal System : Two-tier momentum-acceleration framework Pressure Zones : ±50 statistically validated thresholds Cooldown Logic : Bar-indexed suppression Gradient Mapping : Encodes magnitude and direction Alerts : Standard and strong signals Optimal Application Parameters Timeframes: 1 - 5 min : Intraday momentum tracking 15 - 60 min : Trend rotations & volatility transitions 4H - Daily : Macro momentum exhaustion & re-accumulation mapping Suggested Ranges: CMO Length : 7 - 12 Reduced-Lag Length : 5 - 15 Smoothing : 10 - 20 Cooldown Bars : 5 - 15 Performance Characteristics High Effectiveness: Markets with directional pulses & clean pressure transitions Trending phases with measurable pullbacks Instruments with stable volatility cycles Reduced Edge: Choppy consolidations Ultra-low volatility environments Disclaimer The Reduced-Lag Chande Momentum Oscillator is a professional-grade analytical tool. It is not predictive and carries no guaranteed profitability. Effectiveness depends on asset class, volatility regime, parameter selection, and disciplined execution. Any suggested application timeframes or recommended ranges are guidance only - they are not universally optimal and will not deliver consistent accuracy on every asset or market condition. BOSWaves recommends using it in conjunction with structure, liquidity, and momentum context.
Indicador Pine Script®
por BOSWaves
Squeeze Go Momentum Pro [KingThies] █ OVERVIEW The Squeeze Momentum Pro indicator identifies volatility compression phases and breakout opportunities by comparing Bollinger Bands to Keltner Channels. When price consolidates (squeeze), the bands contract inside the channels, signaling an imminent breakout. The momentum histogram shows directional bias, helping traders anticipate which way price will move when the squeeze releases. This indicator displays in a separate panel below the price chart, providing clear visual signals without cluttering price action. █ KEY FEATURES Momentum Histogram The histogram is the primary visual element, displaying momentum strength and direction with four distinct color states: • Dark Green (#00C853) — Strong bullish momentum that is increasing. This signals strengthening upward pressure and potential continuation. • Light Green (#26A69A) — Bullish momentum that is decreasing. Price remains in bullish territory but upward force is weakening. • Dark Red (#D32F2F) — Strong bearish momentum that is increasing. This signals strengthening downward pressure and potential continuation. • Light Red (#EF5350) — Bearish momentum that is decreasing. Price remains in bearish territory but downward force is weakening. The color intensity provides immediate feedback on momentum strength and trend health. Squeeze State Indicator Colored dots on the zero line communicate the current volatility state: • Orange Dots — Squeeze is ON. Bollinger Bands have contracted inside Keltner Channels, indicating consolidation and low volatility. A breakout is building and traders should prepare for directional movement. • Green Dots — Squeeze is OFF. Bollinger Bands have expanded outside Keltner Channels, indicating active momentum and higher volatility. Price is moving with conviction in the current direction. • Gray Dots — Neutral state. The bands are transitioning between squeeze states. Release Triangles Triangle shapes mark the exact bar when a squeeze releases, providing precise entry timing: • Green Triangle Up — Bullish squeeze release. The squeeze has ended with positive momentum, suggesting a long setup opportunity. • Red Triangle Down — Bearish squeeze release. The squeeze has ended with negative momentum, suggesting a short setup opportunity. Information Panel A compact dashboard in the top-right corner displays real-time trading intelligence: • Squeeze Status — Current state: ON, OFF, or NEUTRAL with color coding • Momentum Direction — Current bias: BULL or BEAR • Momentum Value — Precise numerical reading of momentum strength • Trading Signal — Actionable status: LONG SETUP, SHORT SETUP, WAIT, or MONITOR Configurable Parameters All calculation inputs are adjustable to match your trading style and timeframe: • BB Length — Bollinger Bands period (default: 20) • BB StdDev — Bollinger Bands standard deviation multiplier (default: 2.0) • KC Length — Keltner Channels period (default: 20) • KC ATR Multiplier — Keltner Channels range multiplier (default: 1.5) • Momentum Length — Linear regression period for momentum calculation (default: 20) Alert System Four alert conditions notify you of critical trading opportunities: • Bullish Squeeze Release — Squeeze has released with bullish momentum, indicating a potential long entry • Bearish Squeeze Release — Squeeze has released with bearish momentum, indicating a potential short entry • Squeeze Started — Volatility compression detected, prepare for upcoming breakout • Squeeze Ended — Volatility expansion confirmed, breakout is active █ TRADING METHODOLOGY The indicator follows a clear four-step process for identifying and trading squeeze breakouts: 1 - Wait for Orange Dots . When orange dots appear on the zero line, a squeeze is building. This indicates price consolidation and declining volatility. Do not enter trades during this phase. Instead, prepare by identifying key support and resistance levels and potential breakout directions. 2 - Watch for Release Triangle . When a triangle appears, the squeeze has released and a breakout is beginning. This is your entry signal. The triangle color (green up or red down) combined with the histogram direction indicates the breakout direction. 3 - Confirm with Histogram Direction . Check the momentum histogram for directional confirmation: • Green histogram + green triangle up = Go long. Bullish momentum supports upward breakout. • Red histogram + red triangle down = Go short. Bearish momentum supports downward breakout. 4 - Monitor Momentum Intensity . Stay in the trade while histogram bars maintain their dark, intense color. When colors lighten (dark green to light green, or dark red to light red), momentum is weakening and you should consider taking profits or tightening stops. █ INTERPRETATION GUIDE Squeeze Detection Logic A squeeze occurs when Bollinger Bands contract inside Keltner Channels. This happens when: • Standard deviation of price decreases (BB narrows) • Price consolidates within a tight range • Volatility compresses to unsustainable levels The orange dots signal this condition, warning traders that explosive movement is imminent. Squeeze Release Logic A squeeze releases when Bollinger Bands expand outside Keltner Channels. This happens when: • Price volatility increases sharply • Price breaks out of consolidation • Volume typically expands (check volume separately) The green dots and release triangles signal this condition, indicating the direction and timing of the breakout. Momentum Reading The histogram uses linear regression to calculate momentum relative to the midpoint of the recent range: • Above Zero : Price is trading above the range midpoint with bullish pressure • Below Zero : Price is trading below the range midpoint with bearish pressure • Increasing Bars : Momentum is strengthening in the current direction (darker color) • Decreasing Bars : Momentum is weakening in the current direction (lighter color) █ BEST PRACTICES • Timeframe Selection — The indicator works on all timeframes but performs best on 15-minute to daily charts. Lower timeframes may produce more false signals due to noise. • Confluence Trading — Combine squeeze releases with support/resistance levels, trend lines, or other indicators for higher probability setups. • Volume Confirmation — Check that squeeze releases occur with increasing volume. Low volume breakouts are more likely to fail. • Multiple Timeframe Analysis — Check higher timeframes for overall trend direction. Trade squeeze releases that align with the larger trend. • Parameter Adjustment — Increase BB and KC lengths for smoother signals on higher timeframes. Decrease for more sensitive signals on lower timeframes. █ LIMITATIONS • The indicator does not predict breakout direction before the squeeze releases. The momentum histogram provides bias but is not definitive until the breakout occurs. • False breakouts can occur, particularly in choppy or low-volume market conditions. Always use proper risk management and stop losses. • The indicator works best in trending markets. In deeply ranging markets with no clear direction, squeeze signals may be less reliable. • Momentum calculations use linear regression which can lag during extremely fast price movements. Confirm signals with price action. █ NOTES This implementation uses linear regression for momentum calculation rather than simple moving averages, providing more responsive and accurate directional signals. The four-color histogram system gives traders nuanced feedback on momentum strength that binary color schemes cannot provide. The indicator automatically adjusts to any symbol and timeframe without modification, making it suitable for stocks, forex, crypto, and futures markets. █ CREDITS Squeeze methodology inspired by John Carter's TTM Squeeze indicator. Momentum calculation and visual design optimized for modern trading workflows.
Indicador Pine Script®
por kingthies
1
CCI [Hash Adaptive]Adaptive CCI Pro: Professional Technical Analysis Indicator The Commodity Channel Index is a momentum oscillator developed by Donald Lambert in 1980. CCI measures the relationship between an asset's price and its statistical average, identifying cyclical turns and overbought/oversold conditions. The indicator oscillates around zero, with values above +100 indicating overbought conditions and values below -100 suggesting oversold conditions. Standard CCI Formula: (Typical Price - Moving Average) / (0.015 × Mean Deviation) This indicator transforms the traditional CCI into a sophisticated visual analysis tool through several key enhancements: Implements dual exponential moving average smoothing to eliminate market noise Preserves signal integrity while reducing false signals Adaptive smoothing responds to market volatility conditions Dynamic Color Visualization System Continuous gradient transitions from red (bearish momentum) to green (bullish momentum) Real-time color intensity reflects momentum strength Eliminates discrete color jumps for fluid visual interpretation Adaptive Intelligence Features Dynamic overbought/oversold thresholds adapt to market conditions Reduces false signals during high volatility periods Maintains sensitivity during low volatility environments Momentum Vector Analysis Incorporates velocity calculations for early trend identification Crossover detection with momentum confirmation Advanced signal filtering reduces market noise Extreme Level Analysis Values above +100: Strong overbought conditions, potential reversal zones Values below -100: Strong oversold conditions, potential buying opportunities Zero-line crossovers: Momentum shift confirmation Optimization Parameters CCI Period (Default: 14) Shorter periods (10-12): Increased sensitivity, more signals Standard periods (14-20): Balanced responsiveness and reliability Longer periods (21-30): Reduced noise, stronger signal confirmation Smoothing Factor (Default: 5) Lower values (1-3): Maximum responsiveness, suitable for scalping Medium values (4-6): Balanced approach for swing trading Higher values (7-10): Institutional-grade smoothness for position trading Signal Sensitivity (Default: 6) Conservative (7-10): High-probability signals, reduced frequency Balanced (5-6): Optimal risk-reward ratio Aggressive (1-4): Maximum signal generation, requires additional confirmation Strategic Implementation Oversold reversals in red zones with momentum confirmation Zero-line breaks with sustained color transitions Extreme readings followed by momentum divergence Risk Management Use extreme levels (+100/-100) for position sizing decisions Monitor color intensity for momentum strength assessment Combine with price action analysis for comprehensive market view Market Context Application Trending markets: Focus on momentum direction and extreme readings Range-bound markets: Utilize overbought/oversold levels for mean reversion Volatile markets: Increase smoothing parameters and signal sensitivity Professional Advantages Instantaneous momentum assessment through color visualization Reduced cognitive load compared to traditional oscillators Professional presentation suitable for client reporting Adaptive Technology Self-adjusting parameters reduce manual optimization requirements Consistent performance across varying market conditions Advanced mathematics eliminate common CCI limitations The Adaptive CCI Pro represents the evolution of momentum analysis, combining Lambert's foundational CCI concept with modern computational techniques to deliver institutional-grade market intelligence through an intuitive visual interface.
Indicador Pine Script®
por Hash_Capital
Momentum Variance OscillatorWhat MVO measures: -PV (Price-Volume) Oscillator – how far price is from a volatility-scaled basis, then weighted by relative volume. - > 0 = bullish pressure; < 0 = bearish pressure. -|PV| larger ⇒ stronger momentum. -Signal line (EMA of PV) – a smoother track of PV; crossings flag momentum shifts. -Zero line gradient – instantly shows direction (greenish bull / reddish bear) and strength (paler → stronger). -Extreme bands (±obLevel) – “hot zone” thresholds; being beyond them = exceptional push. -Variance histogram – MACD-like view (PV minus slower PV-EMA) to see thrust building vs. fading. -(Optional) Bar coloring & background tint – paints price bars and/or the panel on key events so you can read the regime at a glance. -Auto-Tune – searches a grid of (obLevel, weakLvl) pairs and (optionally) auto-applies the best, ranked by CAGR vs. drawdown. Core signals & how to trade them: 1) Define the regime: -Bullish regime: PV above 0 and/or PV above Signal; zero line is in bull gradient. -Bearish regime: PV below 0 and/or PV below Signal; zero line is in bear gradient. -Action: Prefer trades with the regime (avoid fading strong color/strength unless you have a clear reversal setup). 2) Entries: Momentum entry: -Long: PV crosses above Signal while PV > 0. -Short: PV crosses below Signal while PV < 0. Breakout/acceleration: -Long add-on: PV crosses above +obLevel (extreme top) and holds. -Short add-on: PV crosses below −obLevel (extreme bottom) and holds. -Histogram confirm: Growing bars in your direction = thrust improving; shrinking/flip = thrust stalling. 3) Exits / risk: -Soft exit / tighten stops: PV loses the extreme and re-enters inside, or histogram fades/turns against you. -Hard exit / reverse: Opposite PV↔Signal crossover and PV crosses the zero line. -Weak zone filter: If |PV| < weakLvl, treat signals as lower quality (smaller size or skip). 4) Practical setup - Suggested defaults (good starting point): -Signal length: 26 -Volume power: 0.50 -obLevel (extreme): 2.00 -weakLvl: 0.75 -Show histogram & dots: On -Auto-Tune (recommended) -Turn Auto-Select Best ON. MVO will scan obLevel 1.50→3.00 (step 0.05) and weakLvl 0.50→1.00 (step 0.05), then use the top-ranked pair (CAGR/(1+MDD)). -If you want to see the top combos, enable the Optimizer Table (Top-3). 5) Visual options -Bar Colors: Regime+Strength – bars follow the zero-line gradient (great for quick read). -Extremes – paint only when beyond ±obLevel. -Cross Signals – paint only on the bar that crosses an extreme. -Background on breach: A one-bar tint when PV crosses an extreme. 6) Example playbook: Long setup: -Zero line shows bull gradient and PV > 0. -PV crosses above Signal (entry). -If PV drives above +obLevel, consider add-on; trail under the last minor swing or use ATR. -Exit/trim on PV crossing below Signal or histogram turning negative; flatten on a drop through 0. Short setup mirrors the above on the bear side. 7) Tips to avoid common traps: -Don’t fade strong extremes without clear confirmation (e.g., PV re-entering inside + histogram flip). -Respect the weak zone: if |PV| < weakLvl, signals are fragile—size down or wait. -Align with structure: higher-timeframe trend and SR improve expectancy. -Instrument personality matters: use Auto-Tune or re-calibrate obLevel/weakLvl across assets/timeframes. 8) Alerts you can set: -Bull Signal X – PV crossed above Signal -Bear Signal X – PV crossed below Signal -Bull Baseline X – PV crossed above 0 -Bear Baseline X – PV crossed below 0
Indicador Pine Script®
por s3raphic333