Empiece

Buysell

Mean Deviation Trail | Lyro RSIntroduction: The Mean Deviation Trail (MDT) is an adaptive trend-following overlay that pairs Mean Absolute Deviation (MAD) volatility normalization with a signed, smoothed deviation signal to produce a dynamic, self-adjusting trail. Instead of relying on a fixed-width channel, MDT continuously measures how far — and in which direction — price departs from its mean, then modulates the trail width in real time. The outcome is a trail that tightens during strong directional regimes and widens during low-momentum or choppy phases. How It Works Deviation Engine — All calculations are anchored to an EMA of the source. From this anchor, the signed normalized deviation is computed: Deviation Raw = (Price − EMA) / MAD This captures both the direction and the relative magnitude of price displacement. A user-selectable smoothing MA (16 types) is then applied to filter noise from the raw signal. MAD Volatility Normalizer — Mean Absolute Deviation is calculated across a rolling lookback: MAD = Σ |Price − EMA| / Length Unlike standard deviation, MAD is not inflated by squared error terms, making it more resistant to outlier spikes and producing a smoother volatility anchor. Adaptive Trail Width — The smoothed deviation signal is scaled against its 80-bar peak to produce sigNorm (a value between 0 and 1). This drives the multiplier between two user-defined extremes: Strong deviation → multiplier approaches the Tight value → trail hugs price. Weak deviation → multiplier approaches the Wide value → trail drifts away. Multiplier = Wide − sigNorm × (Wide − Tight) Bandwidth = MAD × Multiplier Trail & Outer Band — The trail sits below price in uptrends and above price in downtrends, offset from the EMA by the adaptive bandwidth. An optional outer band plots at half-bandwidth on the opposite side, useful as a soft confirmation level. Trend State — Trend flips when the smoothed deviation crosses zero. Each flip prints a Long or Short label and resets the trail on the opposite side of price. Key Features 16 Smoothing MA Types — SMA, EMA, WMA, VWMA, DEMA, TEMA, RMA, HMA, LSMA, SMMA, ALMA, ZLSMA, FRAMA, KAMA, JMA, T3. Adaptive Trail Width — Tight in high-deviation regimes, wide when momentum decays. Optional Outer Band — A half-width band on the opposite side for additional context. Gradient & Trend Color Modes — Gradient scales color intensity with deviation strength; Trend applies flat directional coloring. Colored Candles & Bar Color — Full chart integration with signal-aware candle coloring. Long / Short Signal Labels — Printed at trend crossovers with 𝓛𝓸𝓷𝓰 / 𝓢𝓱𝓸𝓻𝓽 labels. Color Palettes — Classic, Mystic, Accented, Royal, or fully custom. Status Table — Displays live Trend direction and Strength (Weak / Moderate / Strong). Alerts — Confirmed Bullish and Bearish alert conditions included. Signal Interpretation A Long signal (𝓛𝓸𝓷𝓰 label, below bar) fires when the smoothed deviation crosses above zero — price is pulling away from the mean to the upside and the trail flips below price. A Short signal (𝓢𝓱𝓸𝓻𝓽 label, above bar) fires when the smoothed deviation crosses below zero — price is pulling away from the mean to the downside and the trail flips above price. Strength = Strong indicates the deviation signal is near its recent peak — trend is mature and the trail is tight. Weak indicates a fading or compressing regime — the trail loosens, and continuation should be treated with more caution. Recommended Settings Long-Term Investing: 1D, MA Length 40, Smoothing 20, MAD 14 Swing Trading: 4h, default settings Intraday Trading: 15m, MA Length 20, Smoothing 9, MAD 7, Tight 0.4, Wide 1.8 ⚠️ Disclaimer This indicator is for educational and informational purposes only. It does not constitute financial, investment, or trading advice. Past performance is not indicative of future results. Always combine with price action, proper risk management, and additional analysis.
Indicador Pine Script®
por LyroRS
Liquidity Pools Pro [WillyAlgoTrader]💧 Liquidity Pools Pro is a fully free overlay indicator that automatically detects liquidity zones (equal highs and equal lows), scores them on a 4-factor strength model, catches sweeps (liquidity grabs) with reversal confirmation, and instantly delivers a complete trade plan: entry, stop-loss, three take-profits, and automatic break-even on TP1. It unifies into a single coherent engine what traders usually have to assemble from 5–7 separate scripts: an adaptive pivot detector, a 4-factor pool scoring system (touches + recency + volume + HTF), sweep detection with close-back confirmation, an ATR-based risk calculator, risk presets, and an informative dashboard. Works on any instrument (BTC, EURUSD, stocks, indices, futures) and any timeframe without retuning — every threshold is scaled through ATR. 🧩 WHY THESE COMPONENTS WORK TOGETHER A simple pivot detector just plots dots. A simple sweep signal fires on every wick. A plain ATR stop-loss ignores context. Individually these are noise. Combined, they form a complete mechanism for identifying zones where smart money harvests liquidity, and trading the reversal from them. Integration chain: Adaptive Pivot Detection → ATR-based Equality Tolerance → Pool Matching & Clustering → 4-Factor Strength Scoring → HTF Confluence Boost → Sweep Detection (wick + close-back) → Risk Engine (SL/TP/BE) → Position Lock + State Machine → Dashboard + Alerts — The pivot detector adapts to volatility: length grows when ATR is high (less noise on crypto) and shrinks when ATR is low (faster reaction on forex). — Tolerance in ATR units lets the engine treat highs/lows as "equal" on any instrument — no manual tick configuration. — Matching clusters pivots into pools (multiple touches at one zone = thicker liquidity). — Scoring filters out weak pools and highlights exactly the ones price returns to for stop-runs. — HTF Confluence adds +20 to strength when a pivot on the higher timeframe aligns — a filter against lower-timeframe traps. — Sweep is identified as a wick beyond the level + close back inside (classic failed breakout / liquidity grab). — The risk engine builds a complete trade plan for each signal and trails the stop to break-even after TP1. — Position Lock prevents opposite signals from silently overwriting the SL/TP of an open position. Remove any one link and the chain breaks. Sweeps without scoring = noise. Scoring without sweeps = pretty boxes that never trigger. Risk engine without position lock = silent overwrite of an open trade. This pipeline solves all three problems. 🔍 WHAT MAKES IT ORIGINAL 1️⃣ Adaptive Pivot Length — pivot length that adjusts itself to the market. Most indicators use a fixed pivot length (5, 10, 20). That works on one timeframe of one instrument — and breaks on anything else. Here the length is computed dynamically: — volRatio = ATR(14) / ATR(50) — adaptiveLen = round( clamp( 10 / max(0.5, volRatio), 4, 16 ) ) In high-volatility regimes (volRatio > 1) length shrinks to 4–6 bars — the indicator reacts faster. In low-volatility regimes (volRatio < 1) length grows to 14–16 bars — small noise is filtered out. Can be disabled and set manually (default 8 when Adaptive is OFF). 2️⃣ ATR Equality Tolerance — scale-invariant definition of "equal" levels. Two pivots are treated as touches of the same liquidity zone if the distance between them ≤ ATR × tolerance (default 0.25). — 0.15 = strict (tight pools, fewer matches) — 0.25 = balanced (recommended) — 0.50 = loose (wider pools, more matches) This solves a fundamental problem: on BTCUSD, "equal within $50" is normal; on EURUSD the same value is huge. ATR-based tolerance gives one setting that works across all instruments. 3️⃣ 4-factor Strength Score — pool weight on a 0–100 scale. Every pool is scored as the sum of four components, clamped to 0–100: — 🎯 Touches (up to 35 points) : (touchCount − 1) × 9, capped at 35. One pivot = 0, two = 9, three = 18, four = 27, five+ = 35. — ⏳ Recency (up to 35 points) : 35 × 0.5^(ageBars / halfLife). Fresh pool = 35, after one half-life = 17.5, after two = 8.75. Default halfLife = 150 bars. — 📊 Volume (up to 20 points) : log(max(1, cumVol / median)) × 8, capped at 20. Accumulated on every bar that touches the zone — not just the pivot bar. — 🔭 HTF Confluence (+20 bonus) : if a higher-timeframe pivot exists within tolerance × 1.5 — +20 added to the total. Examples: — Fresh 1-touch pool, no volume, no HTF: 0 + 35 + 0 + 0 = 35 — Fresh 2-touch pool: 9 + 35 + 0 + 0 = 44 — Fresh 3-touch pool with 2× median volume: 18 + 35 + 5.5 + 0 = 58.5 — Old (1 half-life) 2-touch pool: 9 + 17.5 + 0 + 0 = 26.5 4️⃣ Sweep Detection with close-back confirmation — real liquidity grabs, not false wicks. Pool state transitions follow strict logic: — STATE_ACTIVE → STATE_SWEPT: wick pierced the level but bar closed beyond it (this is a breakout, not a reversal) — STATE_ACTIVE → STATE_MITIGATED: wick pierced AND bar closed back inside (real liquidity sweep) The default signal (Require Body Reversal = ON) only fires on MITIGATED. This is classic SMC "fakeout → reversal" logic. Disable it and any wick sweep will fire (more aggressive, more noise). 5️⃣ Volume-at-Level Accumulation — real volume at the level, not just at the pivot. Most indicators count volume only on the pivot bar. That's misleading — true liquidity accumulates across all the touches. Here, on every confirmed bar the engine checks for a zone touch (high or low inside levelBot–levelTop), and if found, adds the bar's volume to the pool's cumVol. Across 40 active pools this is O(P) per bar — fast. 6️⃣ HTF Confluence Engine — higher-timeframe pivots as a filter. When enabled, pivots from the configured HTF (default 4H) are requested via request.security with lookahead_on on a closed bar (no repaint). If a pool aligns with an HTF pivot within tolerance × 1.5 — +20 is added to its score. Used to filter signals: HTF-confluent pools cross the strength threshold faster. 7️⃣ 5 Risk Presets + Custom — ready-made SL/TP per trading style. — Conservative: SL 2.5×ATR, TP 1R/2R/4R — Balanced: SL 1.5×ATR, TP 1R/2R/3R (default) — Aggressive: SL 1.0×ATR, TP 1.5R/2.5R/4R — Scalping: SL 0.8×ATR, TP 0.8R/1.5R/2R — Custom: manual multipliers Calculation: — slDistance = ATR(14) × slMult — entry = close on the signal bar — SL = entry ∓ slDistance — TP1/2/3 = entry ± slDistance × tpMult 8️⃣ Automatic Break-Even after TP1 — stop trails to entry on its own. After TP1 is touched (and SL didn't fire on the same bar), the active SL is moved to entry. From that point on, any pullback to entry = break-even exit. TP2/TP3 logic continues to track. Edge case is handled: if both TP1 and SL fire on the same bar, the stop is evaluated against the ORIGINAL value (effectiveSL captured before the BE update). No "magic" loss-saving. 9️⃣ Position Lock — protection against silent trade overwrites. While a trade is active (activeDir ≠ 0), new signals are blocked. Exception: if the current bar is closing the position (SL or TP3 hit), it's treated as "closing now" and an opposite signal is allowed through. Without this protection, a fresh signal would silently overwrite the SL/TP of an open position — critical for both manual trading and webhook-based autotrading. 🔟 Pro-style visuals with adaptive contrast. — Liquidity zones: colored boxes with transparency tied to strength (transparency = 88 − strength × 0.33) — Mid-line: dotted line through the center of each zone — Pool labels: SSL/BSL × touch count volume — SL: solid red line (dims when BE activates) — Entry: dotted blue — TP1/2/3: dashed green (turn cyan + ✓ when hit) — Themes: Auto/Dark/Light with WCAG AA contrast on every background 1️⃣1️⃣ Full alert suite for autotrading — JSON or plain text. Every signal and trade event triggers alert() in one of two formats: — Plain text: "🟢 SWEEP BUY | TICKER | TF | Price: X | Pool: 58/100 | SL: ... | TP1: ... | TP2: ... | TP3: ... | R:R: 1.0" — JSON for webhooks: {"action":"buy","ticker":...,"tf":...,"price":...,"sl":...,"tp1":...,"tp2":...,"tp3":...,"rr":...,"pool_strength":...} All alerts use alert.freq_once_per_bar_close (no intra-bar duplicates). ⚙️ HOW IT WORKS — CALCULATION FLOW Step 1 — Pivot detection: on each bar, ta.pivothigh and ta.pivotlow are evaluated with the dynamic left length (adaptiveLen) and the configured right confirmation. Step 2 — Matching: each new pivot is compared against all active pools of the same type (high/low). If distance ≤ tolerance AND age ≤ maxLookback, it's added as a new touch (level is recalculated as a weighted average). Step 3 — Pool creation: if no match is found, a new pool is created with touchCount = 1 and the current volume. The HTF bonus is applied if confluent. Step 4 — Volume accumulation: on each confirmed bar, if high or low touches an active zone, the bar's volume is added to that pool's cumVol. Step 5 — Strength compute: on demand (lazy), the final strength is calculated using the 4-factor formula. Step 6 — Sweep check: for every active pool, wickSweep (wick beyond the level) and closeBack (close back inside) are evaluated. State becomes MITIGATED if both true; SWEPT if only wickSweep. Step 7 — Signal generation: if pool strength ≥ minStrengthSignal AND mitigation is confirmed (or Body Reversal is OFF) AND signals are enabled — a BUY/SELL fires. Step 8 — Risk setup: on a confirmed signal, entry/SL/TP1/TP2/TP3 are constructed, position lock is engaged, and lines + labels are drawn. Step 9 — Trade tracking: every bar, SL/TP1/TP2/TP3 hits are evaluated with same-bar-misfire protection (justOpened flag). Step 10 — Break-even: on TP1 first touch (without simultaneous SL hit), SL is moved to entry, the original SL line dims, and the ENTRY label gets a "→ SL (BE)" suffix. Step 11 — Auto-reset: on SL hit or TP3 hit, all trade-state variables reset, lines are deleted, position = FLAT. Step 12 — Pruning: when active pools > maxActivePools (default 40), the oldest swept pool is removed first, then the weakest active pool. 📖 HOW TO USE — STEP-BY-STEP FOR NEWCOMERS 🎯 Quick start (5 minutes): 1. Add the indicator to any instrument and any timeframe. 2. Wait 50–100 bars for the warmup period — the indicator needs to accumulate ATR and pivot history. 3. Keep the dashboard ON (default position: Top Right) — it shows how many pools are tracked. 4. Pick a Risk Preset for your style: Scalping for M1–M5, Balanced for M15–H1, Conservative for H4–D1. 5. Create an alert: right-click on the chart → Add alert → Condition: Liquidity Pools Pro → Any alert() function call → Frequency: Once per bar close. 👁️ Reading the chart: — 🔴 Red box = Sell-Side Liquidity (SSL) = equal highs where long stops sit. Price tends to wick into them to harvest stops. — 🟢 Green box = Buy-Side Liquidity (BSL) = equal lows where short stops sit. — 🔢 Number in brackets = pool strength, 0–100. Higher = thicker liquidity. — ✖ ×3, ×4 = number of touches at this zone. More touches = more reliable. — 📊 2.5M, 850K = cumulative volume traded at the level. — ⚪ Dimmed gray box = swept or mitigated pool (already triggered). — 🟢 "Long" below the bar = buy signal (BSL sweep + reversal). — 🔴 "Short" above the bar = sell signal (SSL sweep + reversal). — 🔵 Blue dotted line = ENTRY. — 🔴 Red solid line = SL (stop-loss). — 🟢 Green dashed lines = TP1/TP2/TP3. Cyan with ✓ = already hit. — 🟠 Amber ENTRY label with "→ SL (BE)" = stop has been moved to break-even. 📊 Dashboard fields: — Symbol / TF: current instrument and timeframe. — Pivot Len: pivot length (with "(adapt)" tag when Adaptive is ON). — Active Pools: total active pools and side breakdown (↑ highs, ↓ lows). — Strong SSL ↑ / Strong BSL ↓: price and strength of the strongest pool on each side. — Nearest Above / Below: pools closest to current price. — Stats: Mit:N Sig:M/T — number of mitigations, signals, total pools. If Sig = 0 — lower the sensitivity (see Tuning). — Position: current trade state (LONG/SHORT/FLAT). — SL / TP1 / TP2 / TP3: levels of the active trade. ✓ = hit. "BE @" = stop at break-even. — Plan R:R: TP1 multiplier (1.0R, 1.5R, 2.0R, etc.). — Risk %: percent risk from entry to SL. 🔧 Tuning guide — when something feels off: — Too few signals (Stats Sig: 0/N): lower Min Pool Strength for Signal from 25 to 15. Or disable Require Body Reversal — pure wick sweeps will fire. — Too many signals, lots of noise: raise Min Pool Strength to 40 (only 2-touch pools) or 60 (only strong multi-touch with volume). Enable HTF Confluence. — Too many zones, chart is crowded: raise Min Strength to Display to 30–40 — weak pools will be hidden but still tracked internally. — Zones too narrow, false equality: increase Equality Tolerance from 0.25 to 0.40. — Zones too wide, catching everything: decrease Equality Tolerance to 0.15. — Stops getting hit too often: switch from Balanced to Conservative (SL 2.5×ATR instead of 1.5×ATR). — Signals appear but no position opens: a trade is already active (Position Lock). Check the Position row in the dashboard. — Strange scoring on forex: disable Volume-Weighted Strength (forex often lacks reliable volume data). 💡 TRADING IDEAS — Manual trading on signals: only take trades where pool strength ≥ 50 and HTF Confluence is enabled. — Zones only, no signals: disable Enable Sweep Signals and use the indicator as a pure liquidity map for manual setups. — Scalping setup: preset Scalping + M1–M5 + Min Strength 15 + Adaptive Pivot ON. — Swing setup: preset Conservative + H4–D1 + Min Strength 50 + HTF Confluence ON (Daily HTF). — Webhook autotrading: enable Webhook JSON Format + alert.freq_once_per_bar_close + connect a bot to the JSON payload. — Confluence with other indicators: combine signals with a trend filter (EMA50, SuperTrend) — only longs above EMA50, only shorts below. ⚙️ KEY SETTINGS 🎯 Liquidity Detection: — Adaptive Pivot Length (default ON): auto-adjust pivot length to volatility. — Manual Pivot Length (8): used when Adaptive is OFF. — Right Confirmation Bars (2): bars to the right needed to confirm a pivot. — Equality Tolerance ×ATR (0.25): level equality threshold. — Max Pivot Lookback (200): how far back to search for matches. — Max Active Pools (40): hard cap on simultaneously tracked pools. 💪 Strength Scoring: — Min Strength to Display (0): pools below this score are hidden (visual only). — Strength Half-Life (150): bars after which the recency factor halves. — Volume-Weighted Strength (ON): include the volume factor in scoring. 📡 Sweep Signals: — Enable Sweep Signals (ON): generate BUY/SELL signals. — Min Pool Strength for Signal (25): minimum pool strength to fire. — Require Body Reversal (ON): require close-back inside the level (recommended). 🔭 HTF Confluence: — Enable HTF Confluence (default OFF): use higher-timeframe pivots as a filter. — Higher Timeframe (240 = 4H): which HTF to query. 🛡️ Risk Management: — Risk Preset (Balanced): Conservative / Balanced / Aggressive / Scalping / Custom. — ATR Length (Risk) (14): ATR period for SL distance. — Custom SL/TP1/TP2/TP3 ×ATR / ×Risk : manual multipliers. — Show SL/TP Lines & Labels (ON): draw trade levels on the chart. — Break-Even After TP1 (ON): auto-trail stop to entry. — Show % Distance on Labels (ON): append % from entry to SL/TP labels. 🎨 Visual: — Theme (Auto): Auto / Dark / Light with adaptive contrast. — Show Liquidity Zones / Strength Bar / Labels / Volume / Swept Zones / Buy-Sell Markers / Watermark : visual toggles. — Label Font Size / Signal Marker Size : Tiny → Huge. 📊 Dashboard: — Show Dashboard (ON), Position (Top Right): corner placement. 🔔 Alerts: — Webhook JSON Format (OFF): JSON or plain text. — Alert on SL Hit (ON), Alert on TP Hits & BE (OFF): alert toggles. 🎨 Colors: — Bullish (Demand) Color / Bearish (Supply) Color : zone colors. 🔔 ALERTS — 🟢 SWEEP BUY — BSL sweep + reversal, payload: ticker, tf, price, sl, tp1, tp2, tp3, rr, pool_strength — 🔴 SWEEP SELL — SSL sweep + reversal, same payload structure — 🛑 SL HIT — stop-loss triggered (or 🛡️ BE STOP-OUT when Break-Even is active) — 🎯 TP1 HIT / 🎯 TP2 HIT / 🏆 TP3 HIT — take-profit hits (only fired when SL didn't trigger on the same bar) — 🛡️ BREAK-EVEN — stop moved to entry All alerts support both plain text and JSON webhook formats. All fire on alert.freq_once_per_bar_close — no intra-bar duplicates and no repaint. ⚠️ IMPORTANT NOTES — 🚫 No repainting. Signals are generated only on barstate.isconfirmed (closed bar). Pivots are confirmed with a right window of rightConfirmInput bars (default 2) — meaning the actual swing point is in the past by N bars, but the indicator does not redraw already-drawn pools. HTF data via request.security uses lookahead_on on the offset bar — a standard non-repainting technique. — 📐 Warmup period: the first 50+ bars (max(50, atrLenRisk + 10)) the indicator does not generate signals — it accumulates ATR and pivot history. — ⚖️ Position Lock is not absolute against opposite signals: if the active trade closes on the current bar (SL or TP3 hit), an opposite signal will pass. This is by design — instant two-way blocking is impossible. — 📊 Volume factor is optional: on forex instruments without reliable volume, disable Volume-Weighted Strength. — 🛠️ This is an analysis tool, not a trading bot. The indicator detects liquidity zones, scores them, identifies sweeps, and proposes a trade plan — but the decision to open a position is yours. Past performance does not guarantee future results. Test on demo before trading live. — 🌐 Universal compatibility: works on any instrument (crypto, forex, stocks, indices, futures) and any timeframe (M1 → M). Version v1.1.5. Fully free. Open-source.
Indicador Pine Script®
por WillyAlgoTrader
16
Self-Aware Trend System [WillyAlgoTrader]🧠 Self-Aware Trend System (SATS) is an adaptive SuperTrend-based trend-following system that continuously measures its own operating environment through a 4-factor Trend Quality Index (TQI) and modulates band width, asymmetry, and flip logic in real time. Unlike a fixed SuperTrend — which uses the same ATR multiplier forever — SATS knows when the market is trending vs. chopping, compresses bands in clean trends to lock profit tighter, widens them in noisy conditions to avoid whipsaws, and can detect regime collapse through a "character-flip" even when price hasn't broken the band yet. Each confirmed signal comes with a full trade plan (Entry, SL, TP1/TP2/TP3 at user-defined R multiples), and the system tracks its own realized R, win rate, drawdown, and per-regime edge — building an honest, instrument-specific performance log directly on your chart. The name "Self-Aware" refers to one specific property: the indicator measures the quality of its own environment every bar and feeds that measurement back into its band width and flip conditions. It doesn't predict the future — it reacts to present conditions with mathematically defined adaptation rules. 🧩 WHY THESE COMPONENTS WORK TOGETHER A classic SuperTrend has one problem: its ATR multiplier is fixed. In a clean trending market the bands are too wide, giving back profit on every pullback. In a choppy market the bands are too tight, generating whipsaw after whipsaw. Traders try to fix this by manually switching multipliers per timeframe or per instrument — but that's guesswork. SATS chains a different approach: Market state measurement (TQI) → Non-linear band modulation → Asymmetric band widths → Character-flip detection → R-multiple trade plan → Outcome tracking → Regime-aware statistics The TQI engine measures market quality from four independent angles each bar (efficiency, volatility regime, structure, momentum persistence). The non-linear modulation translates that quality into band width — high quality compresses bands, low quality expands them, using a power curve that avoids both over-reacting to mild fluctuations and under-reacting to severe regime changes. Asymmetric bands tighten the active side (in the direction of the trend) while loosening the passive side — creating a "ratchet with leverage" that locks in profit faster than it invalidates the trend. Character-flip detection catches regime collapses (high quality → low quality) even when price hasn't broken the band — critical for exiting stale trends before they fully reverse. And performance tracking records every signal's realized R, building a real statistical picture of how the system performs on your specific instrument and timeframe. Without TQI, the bands are blind. Without asymmetry, profit-taking lags. Without character-flip, exits happen too late. Without performance tracking, you have no idea if the system has a real edge on your instrument. All four work together — each layer addresses a specific weakness of classic SuperTrend. 🔍 WHAT MAKES IT ORIGINAL 1️⃣ Trend Quality Index (TQI) — 4-factor continuous quality measurement. TQI is computed every bar as a weighted combination of four independent 0..1 factors: — 🧭 Efficiency (default weight 0.35) : Kaufman Efficiency Ratio = |close − close | / sum(|close − close |). Measures directional movement vs. total path. 1.0 = perfect straight line, 0.0 = pure noise. Default window 20 bars. — 📊 Volatility Regime (weight 0.20) : uses Volume Z-score when volume data is available (z = (volume − sma) / stdev, mapped from to ), or falls back to ATR ratio (current ATR vs. long-baseline ATR) on volume-less instruments. — 🏗️ Structure (weight 0.25) : price position within its recent range. pricePos = (close − lowest) / (highest − lowest). Then tqiStruct = |pricePos − 0.5| × 2. Trends pin price to one edge (1.0), chop oscillates around the midpoint (0.0). No ATR dependency. — ⏩ Momentum Persistence (weight 0.20) : of the last N bars, what fraction moved in the same direction as the overall window change? alignedBars / N. Default 10 bars. Final TQI = (factor1 × w1 + factor2 × w2 + factor3 × w3 + factor4 × w4) / sum(weights), clamped to 0..1. Each weight is user-configurable. 2️⃣ Non-linear band modulation with power curve. Instead of a linear "multiplier × (1 − tqi)", SATS uses a power curve: qualityDeviation = (1 − tqi)^curvePower tqiMult = 1 − qStrength + qStrength × (0.6 + 0.8 × qualityDeviation) With curvePower = 1.5 (default), mild quality drops (from 0.9 to 0.7) cause small band expansion, but severe drops (0.5 to 0.2) cause rapid expansion. This matches how traders actually think: ignore small wobbles, react strongly to clear regime changes. 3️⃣ Asymmetric band widths — ratchet with leverage. In a strong uptrend, the lower band (active, trailing price up) tightens while the upper band (passive, not used as stop) widens: activeMult = symMult × (1 − asymStrength × tqi × 0.3) passiveMult = symMult × (1 + asymStrength × tqi × 0.4) Effect: as trend quality rises, the trailing stop moves closer to price (locking profit faster) while the opposite band moves away (so an accidental pullback doesn't trigger a flip). This is the "leverage" — asymmetric response to confirmed trend strength. 4️⃣ EMA-smoothed multipliers before ratchet application. Raw TQI can spike bar-to-bar. If those spikes fed directly into the SuperTrend ratchet logic, bands would compress at a high-TQI bar and stay stuck there (SuperTrend math never loosens active bands against the trend). SATS EMA-smooths the multipliers (alpha 0.15) before ratchet application — preventing stickiness. This is the critical fix that makes adaptive SuperTrend actually work in practice. 5️⃣ Efficiency-weighted ATR. Used for band construction and SL/TP sizing (not for TQI itself, to avoid circular feedback): effATR = rawATR × (0.5 + 0.5 × ER) Clean trending volatility counts full (ER = 1.0 → effATR = rawATR). Noisy chop volatility is halved (ER = 0.0 → effATR = 0.5 × rawATR). This makes SL/TP distances proportional to "useful" volatility, not total volatility. 6️⃣ Character-flip detection with age guard. Classic SuperTrend only flips on price breaks. But a trend can die internally — quality collapses, momentum fades — before price actually breaches the band. Character-flip catches this: charFlipDown = prevTQI > 0.55 (high) AND currentTQI < 0.25 (low) AND trendAge ≥ minAge AND close < source The age guard (default 5 bars) prevents whipsaw on fresh trends — a newborn trend hasn't had time to establish quality, so early TQI noise can't kill it. After the age threshold, a quality collapse triggers an immediate flip even without price break. 7️⃣ Auto-fixed TP order. If a user accidentally sets TP1 > TP2 (or TP3 < TP2), the indicator automatically sorts them. Math: fixedMin = min(all), fixedMax = max(all), middle = sum − min − max. The three TP lines always end up in correct order on the chart regardless of user input order. 8️⃣ R-multiple trade planning with pivot-anchored SL. On each signal: — Entry = close at bar of confirmed flip — SL = min(pivot − slMult×ATR, entry − slMult×ATR) for longs (mirror for shorts) — TP1/2/3 = entry ± risk × R-multiple The SL uses whichever is further from entry — the recent pivot (if available) or a pure ATR distance. This ensures the stop always has a minimum ATR buffer regardless of how close the nearest pivot is. 9️⃣ Performance tracking with realized R accounting. Every signal is tracked bar-by-bar for TP hits, SL hits, and timeout (default 100 bars). On close-out, realized R is calculated assuming 1/3 position per TP: — TP3 hit: realized = (tp1R + tp2R + tp3R) / 3 (all three filled) — SL hit after TP1: realized = (1/3) × tp1R + (2/3) × (−1R) — SL hit after TP1+TP2: realized = (1/3) × tp1R + (1/3) × tp2R + (1/3) × (−1R) — Pure SL: realized = −1R — Timeout: realized = sum of already-hit TP portions (no penalty) Results feed a rolling buffer (up to 100 signals), which drives: — Rolling Win Rate — Rolling Avg R — Rolling drawdown (window DD) — All-time drawdown — Current and max win/loss streaks 🔟 9-cell regime edge tracking. Every completed signal is bucketed by the market regime at entry time: Efficiency bin (low/mid/high) × Volatility bin (low/normal/high) = 3×3 = 9 cells. Each cell accumulates its own EWMA of realized R. The dashboard shows the current regime's historical edge — e.g., "Trending + High Vol: +0.85R (23 trades)". This lets you see which market conditions the system actually profits in. 1️⃣1️⃣ Experimental self-calibration (off by default). When enabled, the system monitors its rolling avg R and drifts the Quality Influence parameter toward the user default if recent edge is poor (below threshold). This is explicitly marked experimental — no claim of improved results — and recommended off until validated on your instrument. ⚙️ HOW IT WORKS — CALCULATION FLOW Step 1 — TQI computation : Compute four factors (Efficiency, Volatility Regime, Structure, Momentum Persistence). Weight and combine into a single 0..1 value. Step 2 — ATR and effective ATR : rawATR = ta.atr(len). effATR = rawATR × (0.5 + 0.5 × ER). Step 3 — Adaptive multiplier : Apply legacy ER adaptation (optional) and non-linear TQI curve. If asymmetric bands enabled, split into active/passive multipliers. Step 4 — EMA smoothing : Smooth both multipliers with alpha 0.15 to prevent ratchet stickiness. Step 5 — SuperTrend bands : upperBand = source + upperMult × effATR. lowerBand = source − lowerMult × effATR. Ratchet logic: lower only rises, upper only falls, until a flip. Step 6 — Flip detection : Price flip (close crosses opposite band) OR character-flip (TQI collapse + age guard). On flip: reset trend age, start new segment. Step 7 — Trade plan : On confirmed flip, compute Entry/SL/TP1/TP2/TP3. Draw lines and labels. Cache the market regime (ER bin × Vol bin) for later edge attribution. Step 8 — Outcome tracking : Each bar, check active trade for TP1/TP2/TP3/SL hits and timeout. On close-out, calculate realized R, push to history buffer, update rolling stats, drawdown, streaks, and regime cell. Step 9 — Dashboard render : On last bar, render live state (Trend, TQI, regime, performance stats, TQI breakdown, regime edge). 📖 HOW TO USE 🎯 Quick start: 1. Add indicator — preset is "Auto" (adapts to your current timeframe) 2. Green line = bullish trend, red = bearish trend 3. Line transparency reflects TQI: bright = high quality, faded = low quality 4. ▲ BUY / ▼ SELL labels appear on confirmed flips 5. Entry, SL, TP1, TP2, TP3 lines drawn automatically at the signal 6. Copy levels to your exchange, let the dashboard track outcomes 👁️ Reading the chart: — 🟢 Bright green line = bullish trend with high TQI — aggressive participation — 🟢 Faded green line = bullish trend with low TQI — cautious, possible regime shift — 🔴 Bright red line = bearish trend with high TQI — 🔴 Faded red line = bearish trend with low TQI — Line flip + label = new trade signal — Dashed TP lines turning solid + "✓" = TP was hit — Score on label (e.g., "85/102") = multi-factor confluence strength 📊 Dashboard fields: — Preset: Auto-resolved (Scalping / Default / Swing / Crypto) — Trend: Bullish ▲ / Bearish ▼ — TQI: current quality index (0..1) — Q.Strength: effective Quality Influence (may drift if auto-calibration enabled) — Signal: current bar signal (BUY / SELL / —) — Regime: Trending / Mixed / Choppy + Low/Norm/High Vol — ER / RSI / Vol Z: raw filter values — TQI Components breakdown: Efficiency / Volatility / Structure / Momentum (each 0..1) — Performance section: Win Rate, Avg R, Window DD, All-Time DD, Streak W/L, Regime Edge 🔧 Tuning guide: — Too many whipsaws : increase Quality Influence (0.5–0.7), increase Structure weight, increase Base Band Width — Missing moves / signals too late : decrease Quality Influence (0.2–0.3), decrease Base Band Width, increase asymmetry — Choppy instrument : use Swing preset, enable Character-Flip, raise minAge to 10+ — Strong trending instrument : use Scalping preset, enable Asymmetric Bands with strength 0.6+ — No volume data : automatically falls back to ATR ratio for volatility regime — no action needed ⚙️ KEY SETTINGS REFERENCE ⚙️ Main: — Preset : Auto / Custom / Scalping / Default / Swing / Crypto 24/7 (auto-adapts ATR, band width, ER window, RSI, SL multiplier) — ATR Length (13), Base Band Width (2.0 × ATR) 📐 Trend Quality Engine: — Enable TQI (default On) — Quality Influence (0.4): how strongly TQI compresses/expands bands — Quality Curve Power (1.5): non-linearity — Smooth Adaptive Multipliers (On): critical fix for ratchet stickiness — Asymmetric Bands (On) + Asymmetry Strength (0.5) — Efficiency-Weighted ATR (On) — Character-Flip (On) + Min Age (5) + High/Low TQI thresholds (0.55 / 0.25) — TQI factor weights : ER 0.35, Volatility 0.20, Structure 0.25, Momentum 0.20 🎯 Risk: — SL Buffer (1.5 × ATR), TP1/2/3 R-multiples (1.0 / 2.0 / 3.0), Trade Timeout (100 bars) 🤖 Self-Learning (experimental): — Auto-calibration (default Off), calibration window, bad/good R thresholds, quality step, cooldown, floor/ceiling — Reset Learning Memory button 📊 Dashboard: position, TQI breakdown toggle, performance stats toggle, score breakdown toggle 🔔 Alerts — 🟢 BUY — ticker, TF, price, TQI, score, SL, TP1, TP2, TP3 — 🔴 SELL — same payload Plain text and JSON webhook formats supported. Bar-close confirmed. ⚠️ IMPORTANT NOTES — 🚫 No repainting. All signals require barstate.isconfirmed. SuperTrend ratchet logic is monotonic — once the trailing band moves, it cannot move back against the trend until a flip. Character-flip uses only previous-bar TQI and current-bar close, both available at bar close. — 📊 TQI is descriptive, not predictive. It measures current market quality from 4 factors — it does not forecast future price. A high TQI reading means "the market is currently behaving like a trend" — it can still fail on the next bar. — 📏 Performance stats are walk-forward, not backtested. The rolling buffer records signals as they happen, bar by bar. Drawdown, win rate, and regime edge are honest forward-looking statistics on your specific instrument and timeframe — not curve-fitted optimization results. — ⚖️ The realized R accounting assumes 1/3 position per TP . This mirrors a standard "scale out at each target" approach. Traders who hold full position to a single target should interpret the R values accordingly. — 🔄 Auto-calibration is experimental. It's off by default and should stay off until you've validated it on your specific instrument. The drift is mean-reverting (toward your user default), not profit-maximizing — no claim of improvement is made. — 🔒 The Reset Learning Memory button clears the rolling buffer, regime cells, drawdown, and streak stats. Use when changing instruments or after significant market regime shifts. — 🛠️ SATS is a decision-support and trade-planning tool , not an automated bot. It identifies trend conditions, measures environmental quality, provides structured trade plans with R-based targets, and tracks outcomes — trade decisions and execution remain yours. — 🌐 Works on all markets and timeframes. Volume-dependent features (Volume Z in TQI) auto-fall-back to ATR-based measurement when volume data is unavailable.
Indicador Pine Script®
por WillyAlgoTrader
120
ABCD Harmonic Projection [WillyAlgoTrader]📐 ABCD Harmonic Projection is an overlay indicator that automatically detects ABCD harmonic patterns from ZigZag pivots, validates them against Fibonacci ratio constraints (BC/AB retracement + CD/AB extension), scores each pattern with a 4-factor quality engine (0–100), projects the D-point completion zone, and draws Target and Stop zones with Fibonacci extension and retracement levels — with full TP/SL outcome tracking and separate bull/bear win rate statistics. The ABCD pattern is one of the foundational harmonic structures: four alternating swing points (A→B→C→D) where the BC leg retraces a Fibonacci portion of the AB leg, and the CD leg extends from C toward a projected D-point that is a Fibonacci ratio of the AB leg. When price reaches the D-point, the pattern completes — and a reversal or continuation move is expected. This indicator automates the entire detection-to-target workflow: find the swings, measure the ratios, validate the geometry, project the target, and track the outcome. 🧩 WHY THESE COMPONENTS WORK TOGETHER Manually identifying ABCD patterns requires eyeballing four pivot points, measuring two Fibonacci ratios, estimating the D-point projection, and drawing the target zone — across multiple instruments and timeframes. Most traders miss patterns or miscalculate ratios. This indicator chains each step into an automated pipeline: ZigZag pivot detection → 4-point ABCD extraction → BC/AB ratio validation → CD/AB extension calculation → D-point projection → 4-factor quality scoring → Target Zone + Stop Zone placement → Fibonacci extension/retracement overlay → TP/SL outcome tracking → Win rate statistics The ZigZag engine ensures only confirmed alternating swings are used (no noise pivots). The ratio validation filters patterns to only those within Fibonacci-valid ranges. The quality scoring ranks patterns by how close they are to ideal geometry. The D-point projection gives a specific price target — not a vague area. And the Target/Stop zones provide precise trade management levels anchored to the pattern's own geometry. 🔍 WHAT MAKES IT ORIGINAL 1️⃣ ZigZag pivot engine with direction management. The indicator uses a directional ZigZag that enforces strict alternation: after a swing high, only a swing low is accepted (and vice versa). If price makes a higher high during an existing up-leg, the previous swing high is updated in place (not duplicated). This prevents the common problem of multiple consecutive highs being treated as separate pivots. Pivots are detected using ta.pivothigh/ta.pivotlow with configurable lookback (default 8 bars). The ZigZag stores prices, bar indices, and directions in parallel arrays — providing the last 200 pivots for pattern scanning. 2️⃣ Fibonacci-validated ABCD pattern detection. When a new pivot is confirmed and at least 4 pivots exist, the indicator extracts the most recent A, B, C points and validates: — BC/AB retracement ratio : must be between minBcAbRatio (default 0.382) and maxBcAbRatio (default 0.886). Classic ABCD ratios are 0.382, 0.500, 0.618, 0.786, and 0.886. Patterns outside this range are rejected. — ATR minimum swing filter : the AB leg must be at least 1× ATR in size — filtering out noise patterns during low-volatility bars. — Minimum leg depth : AB must span at least 3 bars — ensuring the pattern has temporal structure, not just a single spike. Pattern direction: if B > A → bullish ABCD (D projected above C). If B < A → bearish ABCD (D projected below C). The D-point is projected from C using the average of the configurable CD/AB ratio range: projectedD = C + direction × |AB| × avgCdAbRatio. 3️⃣ 4-factor pattern quality scoring (0–100). Each detected pattern receives a quality score from four dimensions: — 📐 Fibonacci precision (45 pts) : how close BC/AB is to the nearest standard Fibonacci level (0.382, 0.500, 0.618, 0.786, 0.886, 1.000, 1.272, 1.618). Exact Fib ratio = full points. 0.05 away = partial. 0.18+ away = zero. This is the most heavily weighted factor because Fibonacci alignment is the core of harmonic pattern validity. — ⏱️ Time symmetry (25 pts) : the ratio of estimated CD bars to AB bars. Perfect symmetry (CD bars = AB bars) = 25 points. Asymmetric patterns (one leg much longer) score lower. — ⚖️ Price symmetry (20 pts) : BC retracement depth relative to 0.618 — deeper retests (closer to 0.618) score higher. Very shallow pullbacks (e.g., 0.236) receive fewer points. — 📏 Leg maturity (10 pts) : AB leg length in bars — patterns with 8+ bars get full points, 5+ get 7, 3+ get 3. Single-bar spikes score zero. Patterns below the Min Pattern Score threshold (default 40) are not displayed. 4️⃣ Fibonacci extension levels projected from C. Four AB extension levels are drawn from point C in the direction of the pattern: — 0.786 × |AB| — shallow completion — 1.000 × |AB| — classic equal-leg ABCD — 1.272 × |AB| — extended completion — 1.618 × |AB| — maximum extension The 1.0 level is drawn thicker (2px, less transparency) as it represents the ideal equal-leg completion. Each level includes a price label. Additionally, the measured BC/AB retracement ratio is displayed at the midpoint of the BC leg for reference. 5️⃣ Fibonacci retracement levels within C→D (partial TP targets). For active patterns, three retracement levels are drawn between C and the projected D: — 0.382 of CD range — first partial profit target — 0.500 of CD range — mid-target — 0.618 of CD range — aggressive partial take These provide natural exit levels before the full D-point is reached — useful for scaling out of positions progressively. 6️⃣ Target Zone + Stop Zone with geometric sizing. On each pattern: — TARGET ZONE : a band around the projected D-point, sized at 10% of the CD range. For bullish patterns: the zone sits just below D. For bearish: just above D. This is where the pattern completion trade expects to reach profit. — STOP ZONE : a band around point C, also sized at 10% of CD range. For bullish patterns: below C. For bearish: above C. If price returns past C, the pattern structure is broken. Both zones extend rightward until price touches the target zone (tracked by touch bar), or the pattern resolves (TP/SL hit). Zones use distinct colors: green for target, red for stop. 7️⃣ TP/SL outcome tracking with separate bull/bear statistics. Each active pattern monitors: — TP hit : price reaches the projected D-point (high ≥ D for bull, low ≤ D for bear) — SL hit : price returns past C against the pattern direction (low ≤ C for bull, high ≥ C for bear) — Simultaneous TP+SL on the same bar → resolved as loss (conservative) On TP hit: R:R is calculated as |entry to TP| / |entry to SL| and accumulated. The dashboard shows separate bull and bear win rates with average R:R on wins. 8️⃣ Active-only display mode. When "Show Active Only" is enabled (default), completed patterns (TP or SL already hit) are hidden — only the current live pattern remains on the chart. When disabled, up to maxPatterns historical patterns are shown for context. This prevents chart clutter while maintaining full statistical tracking. 9️⃣ One-active-pattern constraint. The indicator only allows one active pattern at a time. When an active pattern exists (status = 0), no new patterns are detected. This prevents overlapping projections and conflicting zones. A new pattern can only be detected after the current one resolves (TP or SL). ⚙️ HOW IT WORKS — CALCULATION FLOW Step 1 — ZigZag: Directional pivot detection with alternation enforcement. Higher highs update existing swing (no duplicate). Lower lows same. Pivots stored in parallel arrays. Step 2 — Pattern extraction: On each new confirmed pivot: extract A (3rd-to-last), B (2nd-to-last), C (latest). Compute AB length, BC length, BC/AB ratio. Step 3 — Validation: BC/AB within Fibonacci range? AB ≥ ATR? AB ≥ 3 bars? No active pattern already? Step 4 — Scoring: 4 factors: Fibonacci precision (45), time symmetry (25), price symmetry (20), leg maturity (10). Score ≥ minScore → pattern accepted. Step 5 — Projection: D = C + direction × |AB| × avgCdAbRatio. Bars capped at maxBarsProjection. Step 6 — Drawing: On barstate.islast: delete-and-redraw all visible patterns. AB and BC legs as solid lines. CD projection as dotted. A/B/C/D labels. Score label. Target/Stop zones as boxes. Fib extension and retracement levels as dashed lines with price labels. Step 7 — Evaluation: Each bar: check all active patterns for TP/SL hits. Update status, accumulate win/loss stats, record R:R. 📖 HOW TO USE 🎯 Quick start: 1. Add the indicator — ABCD patterns appear automatically as colored leg lines with A/B/C/D labels 2. Yellow dotted line from C = projected path to D 3. Green "TARGET ZONE" box = where price should reach (take profit) 4. Red "STOP ZONE" box = where the pattern is invalidated (stop loss) 5. Blue dashed lines = Fibonacci extension levels (0.786, 1.0, 1.272, 1.618) 6. Blue dotted lines = partial TP targets (0.382, 0.5, 0.618 of CD) 7. "Long"/"Short" label = confirmed entry signal 👁️ Reading the chart: — 🟢 Green legs + labels = bullish ABCD (D above C, expecting up-move) — 🔴 Red legs + labels = bearish ABCD (D below C, expecting down-move) — 🟡 Dotted projection line = expected path C → D — 🟢 "TARGET ZONE" box = profit target area around projected D — 🔴 "STOP ZONE" box = invalidation area around C — 🔵 Dashed lines = Fib extension levels from C (0.786/1.0/1.272/1.618 of AB) — 🔵 Dotted lines = CD retracement levels (partial TPs: 0.382/0.5/0.618) — Score label (e.g., "72%") = pattern quality 📊 Dashboard fields: — Patterns: active / total count — Last Signal: direction + status (Active/TP ✓/SL ✗) + score — Bull W/L: wins/losses and win rate for bullish patterns — Bear W/L: wins/losses and win rate for bearish patterns — Avg R:R: average reward-to-risk on winning bull/bear trades — ATR: current value for reference — Timeframe, version 🔧 Tuning guide: — Too many patterns: increase ZigZag Length (12–21), increase Min Score (60+), enable ATR filter — Too few patterns: decrease ZigZag Length (5–8), decrease Min Score (30), widen BC/AB ratio range — Patterns too small: increase ATR filter or ZigZag Length — Want only perfect geometry: narrow BC/AB to 0.500–0.786, set CD/AB to 0.9–1.1, Min Score 70+ — Extended patterns: set Max CD/AB to 1.618 or higher ⚙️ KEY SETTINGS REFERENCE ⚙️ Main: — ZigZag Length (default 8): pivot detection lookback — Pivot Sources : configurable high/low sources 📐 Pattern: — Min/Max BC/AB Ratio (default 0.382/0.886): Fibonacci retracement range — Min/Max CD/AB Ratio (default 0.786/1.618): extension range for D projection — Min Pattern Score (default 40): quality threshold — ATR Filter (default On): minimum swing size — Max Patterns (default 3): display limit — Active Only (default On): hide completed patterns 🎨 Visual: — Buy/Sell signals, D projection, Fib levels, TP/SL zones, A/B/C/D labels, score (all toggleable) — Auto / Dark / Light theme 🔧 Advanced: — Max Bars for D Projection (default 200): limits distant projections 🔔 Alerts — 🟢 LONG ABCD / 🔴 SHORT ABCD — entry, TP, SL, score, pattern type All support plain text and JSON webhook format. Bar-close confirmed. ⚠️ IMPORTANT NOTES — 🚫 No repainting. All signals require barstate.isconfirmed and newPivot (confirmed ZigZag pivot). Patterns are detected after the pivot bar closes. Drawings are rendered on barstate.islast using delete-and-redraw — previous bar's pattern state is final. — 📐 The ZigZag enforces strict alternation : high → low → high → low. If price makes a higher high during an existing up-swing, the previous high is updated in place — no duplicate pivots are created. This is essential for correct A/B/C/D extraction. — ⚖️ Only one active pattern is allowed at a time. New patterns are blocked until the current one resolves (TP or SL). This prevents conflicting signals and overlapping zones. — 📊 The quality score is heavily weighted toward Fibonacci precision (45 out of 100 points). A pattern with BC/AB exactly at 0.618 scores much higher than one at 0.450. This reflects the harmonic principle that Fibonacci alignment is the primary measure of pattern validity. — 🔒 Simultaneous TP+SL on the same bar is resolved as a loss (conservative) . This prevents ambiguous outcomes from inflating win rates. — 📏 The D-point projection uses the average of the min/max CD/AB ratio range — not the exact 1.0 (equal legs). With default settings (0.786–1.618), the projected D is at 1.202× AB from C — between classic and extended. Adjust the CD/AB range to target specific completion types. — 🛠️ This is a harmonic pattern detection and projection tool , not an automated trading bot. It identifies ABCD geometry, projects D-point targets, and provides structured trade zones — trade decisions remain yours. — 🌐 Works on all markets and timeframes.
Indicador Pine Script®
por WillyAlgoTrader
Super StochasticAdded Features (Originality Enhancements) Divergence Detection: Instead of relying solely on price action for "BUY/SELL" signals, we've integrated an algorithm that identifies discrepancies between price movement and the oscillator. This helps in spotting potential trend reversals before they happen. Alarm System: We have added code and features that allow you to set alerts based on Buy and Sell conditions directly on the indicator. You can now easily catch signals and set up alerts. Dynamic Background & Alert Infrastructure: To enhance visual clarity, we’ve added dynamic background coloring for trend changes. Additionally, the script includes a robust alert system compatible with trading bots and real-time notifications. Refined Signal Logic: The downward momentum triggered when the %K line crosses below the %D line at peaks has been redesigned for higher clarity and directly reflected on the %K line. User-Friendly Visuals: Added "Buy" and "Sell" labels to help traders—especially beginners—identify entry and exit points more easily within extreme zones. Improved Navigation: Made it simpler for new traders to capture market movements effectively.It enables novice traders to capture buy and sell opportunities more easily. "It works best on the daily timeframe with settings of K: 14 / D: 3 / Smooth: 3." Good Luck!
Indicador Pine Script®
por Rmzn4406
1
Pulse Trend Radar [WillyAlgoTrader]⦿ Pulse Trend Radar is an overlay indicator built on a Kaufman Adaptive Moving Average (KAMA) core with median-ATR volatility bands — producing an adaptive trend system that speeds up in trending markets and slows down in noise. Every trend flip generates a signal scored by a 4-factor quality engine (0–100) with letter grades (A+ through C). The indicator also detects and visualizes liquidity zones from pivot highs/lows, marks order blocks from the last opposite candle before each trend flip, tracks real-time P&L with a live trade tracker, and monitors win/loss outcomes — creating a complete trend-following framework with Smart Money context. 🧩 WHY THESE COMPONENTS WORK TOGETHER A trend indicator alone tells you direction — but not whether the entry is near a liquidity pool (where stops cluster), not whether there's institutional supply/demand nearby (order blocks), not how strong the signal is (all flips treated equally), and not how the system performs over time (no feedback). This indicator layers four analysis dimensions onto the adaptive trend core: KAMA adaptive trend + median ATR bands → Trend direction and flip detection Liquidity zones from pivots → Where stop-hunts and liquidity grabs are likely Order blocks from pre-flip candles → Where institutional supply/demand was established 4-factor signal scoring → Quality filtering — not all flips are equal Win/loss tracker → Performance feedback on this instrument and timeframe The KAMA core adapts its speed via the Efficiency Ratio — in a strong trend, the MA tracks price closely and the bands tighten, producing early signals. In choppy conditions, the MA barely moves and the bands widen, filtering out noise. The liquidity zones show where clusters of stops sit (above pivot highs, below pivot lows) — entries near these zones have higher follow-through because the liquidity grab fuels the move. The order blocks mark the institutional footprint before each trend change — these zones often act as support/resistance on retests. And the signal score combines trend strength, volume delta, efficiency acceleration, and liquidity proximity into a single quality metric — letting you prioritize A+ setups over C-grade ones. 🔍 WHAT MAKES IT ORIGINAL 1️⃣ Kaufman Adaptive Moving Average (KAMA) trend core. The KAMA computes a smoothing constant from the Efficiency Ratio: ER = |price − price | / sum(|price − price |, N) fastSc = 2 / (fastLen + 1), slowSc = 2 / (slowLen + 1) sc = (ER × (fastSc − slowSc) + slowSc)² KAMA = KAMA + sc × (price − KAMA ) When ER → 1 (pure trend): sc approaches fastSc² → KAMA tracks price tightly. When ER → 0 (pure noise): sc approaches slowSc² → KAMA barely moves. This produces a line that accelerates into trends and goes flat in chop — without any manual period switching. 2️⃣ Median ATR volatility bands. Instead of standard ATR (arithmetic mean of true ranges), the indicator uses a median of recent true ranges computed via a ring buffer over the volatility lookback (default 50 bars). The median is more robust to outlier spikes (gap bars, flash wicks) than the mean — producing smoother, more stable band widths. Bands: upper = KAMA + medianATR × multiplier, lower = KAMA − medianATR × multiplier. Trend flips when the previous bar's source price crosses beyond a band: source > upper → bullish, source < lower → bearish. The active band (lower in uptrend, upper in downtrend) is plotted as the trend line. 3️⃣ Displacement-based gradient fill. The fill between the trend line and price is not a fixed transparency — it scales with displacement: displacement = |price − KAMA| / (medianATR × multiplier). The further price stretches from KAMA, the more intense the fill becomes (transparency decreases from 95 to 60). This creates a visual "heat map" effect: faint fill near KAMA (low extension), bright fill far from KAMA (overbought/oversold). This gives immediate visual feedback on how extended the current move is without needing a separate oscillator. 4️⃣ Liquidity zone detection and sweep tracking. Pivot highs and lows (configurable lookback, default 4 bars) are marked as liquidity zones: — Above pivot highs → bearish liquidity (buy stops cluster above swing highs — potential sell-side liquidity) — Below pivot lows → bullish liquidity (sell stops cluster below swing lows — potential buy-side liquidity) Each zone extends rightward as a thin box (height = 0.15× medianATR). Zones are automatically removed when price sweeps through them (high crosses above bearish zone top, or low crosses below bullish zone bottom) — representing the liquidity grab event. Up to 15 zones per side (configurable). The signal scoring engine measures the nearest liquidity zone distance on each trend flip — entries closer to a liquidity pool receive a higher quality score because the stop-hunt provides fuel for the ensuing move. 5️⃣ Order block detection on trend flips. When the trend flips, the previous bar is marked as an order block: — Bullish flip → demand order block (the last bearish candle before the reversal — where institutional buying absorbed selling pressure) — Bearish flip → supply order block (the last bullish candle before the drop — where institutions distributed) Each OB is drawn as a box from the previous candle's high to low, extending rightward. OBs are automatically invalidated (deleted) when price closes beyond the opposite edge after 3+ bars — indicating the zone has been broken. Up to 10 OBs per side (configurable). 6️⃣ 4-factor signal quality scoring (0–100). Each trend flip is scored on four factors: — 📐 Trend strength (25 pts) : combined from ER (directional efficiency) and displacement from KAMA — measures how strong the trend is at the moment of the flip — 📊 Volume delta alignment (25 pts) : buy volume vs sell volume accumulated during the previous trend leg — bullish flip with positive volume delta scores higher (smart money was accumulating) — ⚡ Efficiency acceleration (25 pts) : current ER minus previous ER — positive acceleration means the trend is gaining momentum, not losing it — 💧 Liquidity proximity (25 pts) : distance to the nearest liquidity zone — closer = higher score (the flip is near a liquidity grab point) Grades: A+ (≥ 80), A (≥ 60), B (≥ 40), C (< 40). Signal labels display "Long A+" / "Short B" etc. 7️⃣ OBV-based volume regime detection. On Balance Volume (OBV) delta = OBV − SMA(OBV, 20). Classified as: — Accumulation : OBV delta > 0 — more volume on up-moves than down-moves (institutional buying) — Distribution : OBV delta < 0 — more volume on down-moves (institutional selling) Displayed in the dashboard with directional coloring. Auto-displays "N/A" on instruments without volume data. 8️⃣ Live trade tracker with P&L. On each signal: a dashed entry line extends horizontally, a vertical connector line tracks from entry to current price, and a P&L label updates in real-time showing percentage gain/loss. Green = profit, red = loss. Replaced on each new signal. 9️⃣ Win/loss markers + win rate tracking. Each signal is tracked as a mini-trade: entry at signal close, SL at entry ± medianATR × SL multiplier, TP1 at entry ± risk × TP1 multiplier. If TP1 is reached before SL → green ● marker at the signal bar (win). If SL is reached first → red ● marker (loss). Running win rate displayed in the dashboard as "67% (4W/2L)". 🔟 ATR-based TP/SL with hit tracking. Three take-profit levels as risk multiples (default 1.0/2.0/3.0 × risk) plus SL (default 3× medianATR from entry). Lines extend rightward with labels showing price + percentage. Labels update with ✓ on hit (green) or ✗ on SL hit (red). Active until the next signal replaces them. ⚙️ HOW IT WORKS — CALCULATION FLOW Step 1 — KAMA: Efficiency Ratio from configurable lookback → adaptive smoothing constant → KAMA line that accelerates in trends, goes flat in chop. Step 2 — Median ATR bands: True ranges stored in ring buffer → median computed → upper/lower bands = KAMA ± median × multiplier. Step 3 — Trend detection: Previous bar's source > upper band → bullish flip. Source < lower band → bearish flip. Active band plotted as trend line. Gradient fill scales with displacement. Step 4 — Liquidity zones: Pivot highs/lows → boxes above/below. Swept zones auto-deleted. Step 5 — Order blocks: On flip → previous candle becomes OB. Invalidated when price closes beyond opposite edge. Step 6 — Signal scoring: 4 factors (trend strength, volume delta, ER acceleration, liquidity proximity) → 0–100 → A+/A/B/C grade. Step 7 — Trade tracking: SL/TP placed, lines extend, win/loss evaluated per trade. 📖 HOW TO USE 🎯 Quick start: 1. Add the indicator — adaptive trend line, liquidity zones, and order blocks appear 2. "Long A+" / "Short B" labels = trend flip signals with quality grade 3. Green/red liquidity zone boxes = where stops cluster (potential sweep targets) 4. Green/red order blocks = institutional supply/demand zones 5. SL/TP lines auto-appear with P&L tracker 👁️ Reading the chart: — 🟢 Green trend line = bullish (lower band active) — 🔴 Red trend line = bearish (upper band active) — 🟢/🔴 Gradient fill = displacement from KAMA (brighter = more extended) — 🟢 Small boxes below price = bullish liquidity zones (buy-side stops) — 🔴 Small boxes above price = bearish liquidity zones (sell-side stops) — 🟢 Larger boxes = demand order blocks (institutional buying zone) — 🔴 Larger boxes = supply order blocks (institutional selling zone) — 🟢 ● = win (TP1 reached), 🔴 ● = loss (SL hit) — Dashed line + PnL label = live trade tracker 📊 Dashboard fields: — Trend: ▲ Bullish / ▼ Bearish — Last Signal: BUY/SELL with grade — Score: 0–100 quality rating — Strength: trend strength percentage — P&L: current trade percentage — Win Rate: wins/losses with percentages — SL / TP1: current trade levels with ✓/✗ status — Vol Regime: Accumulation / Distribution — Vol Delta: buy vs sell volume percentage — Efficiency: current ER percentage 🔧 Tuning guide: — Too many signals: increase Band Multiplier (2.0–2.5) or ER Length (15–20) — Too few signals: decrease Band Multiplier (1.2–1.5) or ER Length (8–10) — Signals too late: decrease Slow Smoothing (15–20), decrease Volatility Length (20–30) — Stops too tight: increase SL ATR Multiplier (2.5–4.0) — Want only A+/A signals: monitor grades in dashboard, skip B/C entries ⚙️ KEY SETTINGS REFERENCE ⚙️ Main: — Efficiency Ratio Length (default 13): KAMA lookback — higher = smoother — Fast/Slow Smoothing (default 2/30): KAMA acceleration/deceleration — Band Multiplier (default 1.8): band width in median ATR — Volatility Length (default 50): median ATR ring buffer size 🎯 SL/TP: — SL (× ATR) (default 3): stop distance in median ATR — TP1/TP2/TP3 (× risk) (default 1.0/2.0/3.0): R:R multiples 💧 Liquidity: — Pivot Lookback (default 4) / Max Zones (default 15) 🟧 Order Blocks: — Max Order Blocks (default 10) 🎨 Visual: — Gradient fill, trade tracker, win/loss markers (all toggleable) — Configurable signal label size (Tiny–Large) — Configurable dashboard font size (Tiny–Normal) — Auto / Dark / Light theme 🔔 Alerts — 🟢 BUY / 🔴 SELL — ticker, price, TF, SL, TP1, TP3 All support plain text and JSON webhook format. Bar-close confirmed. ⚠️ IMPORTANT NOTES — 🚫 No repainting. All signals require barstate.isconfirmed. Trend flips use the previous bar's source vs the previous bar's band value — the signal fires on the bar after the crossing bar closes. KAMA and band values are deterministic once a bar is confirmed. — 📐 The median ATR is more robust than standard ATR . A single flash wick or gap bar shifts the mean (standard ATR) significantly but barely affects the median. This produces more stable band widths and fewer false flips during anomalous bars. — 📊 Volume delta is accumulated within each trend leg and resets on every trend flip. It represents the buy/sell balance during the specific move — not the overall volume profile. The pre-reset delta value is used for the signal score (capturing the exiting leg's character). — 💧 Liquidity zones are automatically swept and removed when price touches them. This prevents stale zones from cluttering the chart. If a zone disappears, it means price swept through it — the liquidity has been taken. — 🟧 Order blocks are invalidated after 3+ bars if price closes beyond the opposite edge. This prevents old OBs that have clearly failed from persisting. — ⚖️ The 4-factor score uses the volume delta from before the trend reset (preResetVolDelta) — not the current leg's delta, which would be zero at the moment of the flip. This correctly captures whether the previous leg had accumulation or distribution behind it. — 📏 Win/loss tracking evaluates TP1 vs SL only — if TP1 is reached before SL, it's a win. The trade closes on the first event and is not re-evaluated. — 🛠️ This is a trend-following signal and analysis tool , not an automated trading bot. It provides adaptive trend detection, liquidity context, order block zones, and signal quality grading — trade decisions remain yours. — 🌐 Works on all markets and timeframes. Volume features auto-adapt to instruments without volume data (OBV and volume delta show "N/A").
Indicador Pine Script®
por WillyAlgoTrader
9
Smooths Trend BreakerSmooths Trend Breaker Overview Smooths Trend Breaker is a trend identification and entry timing tool that combines an adaptive ATR-based supertrend, a higher timeframe EMA trend filter, volume confirmation, an RSI gate, a price compression range detector, and FVG-gated star candlestick pattern recognition. Each component was chosen to address a specific weakness in standalone supertrend systems — noise in choppy markets, late entries, and signals that contradict the larger trend — and all components work together as a single decision framework rather than as separate overlapping indicators. Component Methodology Adaptive Supertrend Engine The core engine uses an ATR-based supertrend calculation. True Range is computed on each bar as the maximum of the current high-low range, the absolute distance from the prior close to the current high, and the absolute distance from the prior close to the current low. ATR is then derived using Wilder's smoothing method — a modified exponential moving average with a smoothing factor of 1/N — rather than a simple average, which gives more weight to recent volatility while maintaining memory of past conditions. The upper and lower bands are calculated as the midpoint of the bar's high-low range plus or minus the ATR multiplied by a user-defined multiplier. Bands are then locked directionally — the lower band can only move upward and the upper band can only move downward — preventing the line from retreating when price moves against the trend. The trend direction flips only when a closing price crosses the opposite band, not on intrabar wicks, ensuring signals are close-confirmed. Rather than using fixed ATR settings across all timeframes, the indicator auto-selects ATR length and multiplier based on the chart's timeframe in seconds. Shorter timeframes receive a shorter ATR period and higher multiplier to account for proportionally larger noise relative to signal. Longer timeframes receive a longer period and lower multiplier to avoid over-sensitivity on slower-moving instruments. This eliminates the need to manually adjust parameters when switching timeframes. Higher Timeframe EMA Filter When enabled, the indicator uses `request.security()` to retrieve a 50-period EMA from a higher timeframe selected automatically based on the chart timeframe — for example a 15-minute EMA is referenced when viewing a 5-minute chart, and a 4-hour EMA is referenced when viewing a 1-hour chart. A Buy label is only confirmed when price closes above this EMA and a Sell label is only confirmed when price closes below it, aligning entries with the larger structural trend. Volume Confirmation The volume filter computes a 20-bar simple moving average of volume. A signal is confirmed only when the flip bar's volume exceeds this average by a user-defined threshold, defaulting to 1.2 times the average. This filters out supertrend flips that occur on low-participation bars, which have historically higher failure rates. RSI Gate A 14-period RSI using Wilder's smoothing is computed on each bar. Buy signals are blocked when RSI exceeds a user-defined overbought level (default 70) and Sell signals are blocked when RSI falls below a user-defined oversold level (default 30). This prevents chasing exhausted moves at extremes. Range Breaker The Range Breaker compares the current N-bar rolling range (highest high minus lowest low) against the prior N-bar rolling range from the equivalent lookback window shifted N bars back. When the current range is less than a defined ratio of the prior range — meaning price has compressed significantly relative to its recent volatility — a consolidation zone is declared. Horizontal lines are drawn at the highest high and lowest low of the active zone and extend forward with the current bar. When a closing price breaks outside either level the zone is sealed and a breakout marker fires. Star Pattern Detection with FVG Gate Morning Star, Morning Doji Star, Evening Star, and Evening Doji Star patterns are detected using strict 3-candle criteria. The first candle must be a strong directional bar with a body filling at least 50% of its range. The middle candle — the star — must have a body of 25% or less of its range and a total range smaller than 80% of the first candle's body. The confirmation candle must be directionally opposite to the first candle with a body filling at least 40% of its range, closing past the midpoint of the first candle's body. Additionally, a Fair Value Gap check is applied to the candle immediately before the star. A bearish FVG exists when the high of bar N is below the low of bar N+2, creating a downward price gap. A bullish FVG exists when the low of bar N is above the high of bar N+2, creating an upward price gap. An Inverse FVG check scans back 45 bars for a prior FVG zone whose price range overlaps with the pre-star candle, indicating price has returned to fill an old imbalance. If neither an FVG nor an IFVG is present on the candle before the star, the pattern does not fire regardless of candle structure. This ensures every star signal is anchored to a real price imbalance. How to Use It The highest probability setups occur when the supertrend line has already established direction, the range detector is not showing an active chop zone, and a signal fires with volume and HTF agreement. The Range Breaker lines are a caution flag — while they are active and unbroken, the supertrend will produce lower quality signals due to market compression. The star patterns provide a precision entry trigger that can be used to time entries at reversal points, particularly when a star fires near an active Range High or Range Low level. Trend continuation Wait for a pullback toward the supertrend line, then enter when the next Buy or Sell label prints in the direction of the established trend. Breakout entries When a range zone has been active for several bars and the supertrend is already pointing in one direction, a range breakout marker firing in that same direction is a high-quality entry trigger. Star entries A star pattern firing at or near a Range High or Range Low, with the supertrend already in agreement, represents the highest confluence setup available in the indicator. What to avoid Do not enter trend signals while a range zone is active with no breakout. Do not take signals that contradict the HTF EMA. Do not enter late into an extended trend where price is far from the supertrend line. Settings ATR Length and Multiplier auto-scale by timeframe but can be manually overridden. Volume threshold multiplier defaults to 1.2× the 20-bar average. RSI overbought and oversold levels default to 70 and 30. Range sensitivity has three modes controlling lookback period, compression ratio, and minimum bar count. Past zones to display defaults to 5, maximum 20.
Indicador Pine Script®
por CaptainSmooth
Breakout Pattern Setup [WillyAlgoTrader]📐 Breakout Pattern Setup is an overlay indicator that automatically detects converging price channels (wedges, triangles, pennants) by fitting trendlines to confirmed pivot points using a boundary-fit algorithm, then monitors for breakouts confirmed by a 5-factor strength scoring engine — with directional probability scoring while price is inside the channel, volume contraction verification, and automatic TP/SL placement based on the measured move (channel width projected from breakout). Once a breakout fires, the trade stays open until TP3 (full measured move) or SL is reached — with trailing to breakeven after TP1. The core concept: converging channels compress volatility — when price breaks out of a narrowing range, the ensuing move tends to be proportional to the channel's maximum width. This indicator automates the entire workflow: detect pivots, fit upper and lower trendlines, verify convergence and volume contraction, score the breakout quality when it occurs, set targets based on the measured move, and track the trade to completion. 🧩 WHY THESE COMPONENTS WORK TOGETHER Manual channel drawing is subjective — two traders will draw different trendlines from the same pivots. A breakout without strength scoring treats strong and weak breaks equally. Targets without measured-move anchoring are arbitrary. This indicator chains each component into a sequential pipeline: Pivot detection → Boundary-fit algorithm (best trendline pairs) → Convergence + width + volume contraction verification → Channel visualization → Directional probability scoring → Breakout detection + 5-factor strength scoring → TP/SL from measured move → Trailing SL to breakeven after TP1 → Trade outcome tracking (win rate) The pivot detection feeds raw swing points to the boundary-fit algorithm. The algorithm tests all pivot pair combinations and selects the lines with the most touches and least deviation — producing objective, reproducible trendlines. The convergence filter ensures only narrowing channels qualify (not parallel channels or expanding formations). Volume contraction confirms the volatility squeeze is genuine. The directional score gives real-time probability before the breakout occurs. The 5-factor strength score evaluates the breakout candle itself. And the measured-move TP/SL system manages the trade from entry through breakeven trail to final outcome. 🔍 WHAT MAKES IT ORIGINAL 1️⃣ Boundary-fit trendline algorithm. The algorithm finds optimal upper and lower trendlines by exhaustive search over confirmed pivots: Upper boundary: For every pair of pivot highs (A, B) within the lookback window: — Project a line through A and B — Check all other pivot highs: none may exceed the line by more than deviationMax × ATR (no overshoots beyond tolerance) — Count how many pivot highs fall within touchTolerance × ATR of the line (touches) — Keep the pair with the most touches Lower boundary: Same process for pivot lows — no undershoot beyond tolerance, maximize touches. A trendline is projected via: y = y1 + (y2 − y1) × (x − x1) / (x2 − x1). The touch tolerance (default 0.15× ATR) and deviation maximum (default 0.3× ATR) are both ATR-normalized, adapting to the instrument's volatility. The scan runs on new pivots and every 10 bars (configurable interval), testing up to 15 recent pivots per side — producing the objectively best-fitting converging channel from available data. 2️⃣ Multi-criteria channel validation. A detected channel must pass all five checks: — 📏 Convergence : the channel is narrowing — current width < starting width. Convergence rate = 1 − (widthNow / widthStart) ≥ minConvergence (default 0.02 = at least 2% narrower) — 📐 Width range : current width ≥ minChannelWidth × ATR (not too thin) AND < 10× ATR (not too wide) — 📊 Volume contraction (when enabled): average volume inside the channel < 85% of average volume before the channel — confirms the volatility squeeze is accompanied by declining participation — 📍 Price position : previous bar's close is inside the channel (not already broken out) — ⚡ No inversion : upper boundary > lower boundary at the current bar 3️⃣ 5-factor breakout strength scoring (0–100). When price closes beyond a channel boundary: — 📏 Penetration depth (25%) : (close − boundary) / ATR, normalized to 0–1 (capped at 2× ATR). Deeper penetration = stronger commitment. — 📊 Body ratio (15%) : candle body / candle range. Full-body candles (small wicks) indicate conviction. Doji/pin bars = weak. — 📍 Body commitment (15%) : body midpoint beyond the boundary = 1.0, inside channel = 0.3. Full body commitment means the entire candle moved through, not just a wick. — 📈 Volume confirmation (25%) : volume > SMA(20) × volumeSpikeMult = 1.0, otherwise 0.4. Above-average volume on the breakout bar confirms institutional participation. — 💪 Momentum confirmation (20%) : RSI(14) > 50 for bullish (or < 50 for bearish) = 1.0, otherwise 0.4. Classification: Strong (≥ 65), Medium (35–65), Weak (< 35). The strength is displayed on the breakout label and in the dashboard. 4️⃣ Directional probability scoring (0–100) while inside channel. Before the breakout occurs, the indicator provides a real-time directional score: — 📐 Channel slope bias (35%) : midline slope normalized by ATR — upward-sloping channels bias bullish, downward bias bearish — 📊 RSI bias (35%) : (RSI − 50) / 50 — momentum direction — 📍 Position in channel (30%) : (close − lower) / width — price near upper boundary biases bullish, near lower biases bearish Score > 60% = bullish lean, < 40% = bearish lean, 40–60 = neutral. Displayed in the dashboard as "Bull Prob" — gives you a heads-up before the breakout direction is confirmed. 5️⃣ Measured-move TP/SL with trailing to breakeven. On breakout: — Target = breakout boundary + channel maximum width (the classic measured-move projection) — TP1 = entry + fullMove / 3 — TP2 = entry + fullMove × 2/3 — TP3 = entry + fullMove (full measured move) — SL = opposite channel boundary ± ATR padding (configurable, default 0) After TP1 is hit, the SL moves to breakeven (entry price) — the entry label updates to show "(SL → BE)" and the original SL label dims. Trade stays open until TP3 (full measured move) or SL is reached. TP/SL labels show percentage distance from entry and update with ✓ / ✗ markers on hit. SL has priority on same-bar conflicts (SL checked before TPs). 6️⃣ Win/loss tracking with historical statistics. The indicator tracks: total patterns detected, bull/bear breakout counts, wins (TP1 hit before SL), losses (SL hit before TP1), and win rate — all displayed in the dashboard. Two display modes: "All" (full history of all channels and trades) or "Last Only" (clean chart showing only the most recent pattern + trade, automatically cleaned up when a new pattern is detected). 7️⃣ Channel visualization with breakout color shift. Before breakout: neutral channel lines (configurable color, default yellow) with optional fill. On bullish breakout: lines and fill shift to green. On bearish breakout: lines shift to red. Channel timeout (max width bars with no breakout) resets the scanner to look for new patterns. ⚙️ HOW IT WORKS — CALCULATION FLOW Step 1 — Pivot detection: ta.pivothigh/ta.pivotlow with configurable lookback. Pivots stored in arrays (up to 60 recent, capped). Step 2 — Boundary-fit scan: On new pivot or every 10 bars (if no active channel and no open trade): test all pairs of pivot highs for upper boundary, all pairs of pivot lows for lower boundary. Select best-fit lines by maximum touches. Step 3 — Channel validation: Convergence rate ≥ minimum, width within range, volume contraction passes, price is inside, no inversion → channel activated. Step 4 — Inside-channel monitoring: Directional probability score updated each bar. Channel lines extend. Background optional. Step 5 — Breakout detection: Close beyond boundary + bar confirmed → 5-factor strength scoring → signal + TP/SL placement → channel lines recolored. Step 6 — Trade tracking: TP1/TP2/TP3 and SL hit detection with SL priority. TP1 hit → trailing SL to breakeven. TP3 or SL → trade closed, channel reset, scanner resumes. 📖 HOW TO USE 🎯 Quick start: 1. Add the indicator — it scans for converging channels automatically 2. Yellow channel lines appear when a valid pattern is detected 3. Dashboard shows "Active" + "Bull Prob" percentage 4. On breakout → "Long"/"Short" label + Entry/SL/TP1–TP3 lines appear 5. TP1 hit → SL moves to breakeven. TP3 → trade complete. 👁️ Reading the chart: — 🟡 Channel lines = active converging pattern (pre-breakout) — 🟢 Channel turns green = confirmed bullish breakout — 🔴 Channel turns red = confirmed bearish breakout — 🟢 "Long" / 🔴 "Short" label = confirmed breakout signal with strength — 🔵 Blue line = entry, 🔴 red = SL, 🟢 green dashed = TP1/TP2/TP3 — ✓ on TP labels = target hit, ✗ on SL = stopped out 📊 Dashboard fields: — Pattern: Active / Bull Break / Bear Break / Scanning — Strength: Strong / Medium / Weak (5-factor score) — Trade: Active / TP1 ✓ (BE) / TP2 ✓ / TP3 ✓ / SL Hit — Bull Prob: directional probability (0–100%) while inside channel — R:R (TP1): risk-to-reward ratio — Touches: upper/lower boundary touch counts — Vol Contraction: in-channel vs pre-channel volume ratio — Convergence: narrowing rate percentage — Patterns / Breaks / Win Rate: cumulative statistics 🔧 Tuning guide: — No patterns found: decrease Min Touches (2), increase Max Channel Width (150+), decrease Min Convergence (0.01) — Too many weak patterns: increase Min Touches (3), increase Min Channel Width ATR (0.7+) — Weak breakouts: increase Volume Spike Mult (1.5+), enable Momentum Confirmation — SL too tight: increase SL Padding (0.2–0.3 ATR) — Want clean chart: set Pattern History to "Last Only" ⚙️ KEY SETTINGS REFERENCE ⚙️ Main: — Pivot Detection Length (default 5): swing lookback — Min Touches (default 2): pivots per boundary — Max Channel Width (default 120 bars): lookback limit — Min Convergence Rate (default 0.02): narrowing threshold 🔍 Filters: — Volume Spike Mult (default 1.2): breakout bar volume requirement — Volume Contraction (default On): require declining volume in channel — Momentum Confirmation (default On): RSI alignment 🛡️ Risk: — SL Padding (default 0 ATR): buffer beyond opposite boundary — Label Offset (default 20 bars): right-side level label distance 🔧 Advanced: — Touch Tolerance (default 0.15 ATR): pivot proximity to trendline — Max Deviation (default 0.3 ATR): maximum pivot overshoot — Min Channel Width (default 0.5 ATR): filter out thin channels 📐 Channel Lines: — Show Channel Fill (default On), color and width configurable 🔔 Alerts — 🟢 BUY / 🔴 SELL — breakout with strength, entry, SL, TP1–TP3 — 🟡 PATTERN DETECTED — new channel found — 🎯 TP1 / TP2 / 🏆 TP3 HIT — trade progress — 🛑 SL HIT — stopped out All support plain text and JSON webhook format. Bar-close confirmed. ⚠️ IMPORTANT NOTES — 🚫 No repainting. All breakout signals require barstate.isconfirmed. Channel detection runs on confirmed pivots (equal left/right lookback). The boundary-fit algorithm selects the best trendlines from historical pivots — the resulting lines are objective and reproducible. — 📐 The boundary-fit algorithm tests all valid pivot pairs (up to 15 per side) and selects the combination with the most touches that satisfies the deviation constraint. This is an exhaustive search, not a linear regression — it produces the tightest-fitting boundary lines possible from the data. — ⚖️ The measured-move target (channel width projected from breakout) is the classic technical analysis projection for converging patterns. TP1/TP2/TP3 divide this move into thirds: TP1 = 33%, TP2 = 67%, TP3 = 100% of the projected move. — 📊 Volume contraction compares average volume inside the channel vs before the channel over the same number of bars. A ratio below 85% confirms genuine volatility compression. — 🔒 Once a breakout fires, the trade stays open until TP3 or SL is reached — there is no intermediate invalidation. The channel remains active while the trade is open. Channels without a breakout timeout after the max channel width in bars. — 📏 SL priority: on a bar where both SL and TP are touched, SL is checked first . After TP1, SL moves to breakeven (entry price). — 🛠️ This is a pattern detection and breakout scoring tool , not an automated trading bot. It identifies converging channels, scores breakouts, and sets measured-move targets — trade decisions remain yours. — 🌐 Works on all markets and timeframes. Volume features auto-adapt to instruments without volume data.
Indicador Pine Script®
por WillyAlgoTrader
29
StealthTrail SuperTrend ML Pro [WillyAlgoTrader]🤖 StealthTrail SuperTrend ML Pro is an overlay indicator that builds on the adaptive SuperTrend core from StealthTrail and adds three layers of intelligence: an instrument profiling engine that classifies the market into Trending, Ranging, or Volatile regimes and auto-tunes all SuperTrend parameters accordingly; a 13-feature machine learning scoring system that evaluates every candidate signal on momentum, trend, volatility, structure, volume, HTF alignment, divergence, session quality, and regime context — producing a 0–100 confidence score; and a self-learning mechanism that tracks signal outcomes over time and dynamically adjusts the confidence gate to optimize signal quality. The result is a SuperTrend that configures itself, scores its own signals, and learns from its results. 🧩 WHY THESE COMPONENTS WORK TOGETHER A standard SuperTrend has fixed parameters that work well in one market regime and fail in another. Manually tuning ATR length, multiplier, and filters for each instrument and timeframe is time-consuming and becomes outdated when conditions change. This indicator solves the problem through a three-layer intelligence stack: Layer 1 — Regime classification → Auto-tuning: The instrument profiler continuously measures efficiency ratio (trend strength), autocorrelation (serial dependence), volatility clustering, and normalized volatility — classifying the market into TRENDING, RANGING, or VOLATILE. Each regime produces different optimal SuperTrend parameters. The auto-tuner interpolates ATR length, multiplier, cushion, cooldown, and RSI threshold using regime-weighted blending — so the SuperTrend self-configures for current conditions. Layer 2 — ML signal scoring: Even with auto-tuned parameters, not every SuperTrend flip is a good trade. The 13-feature ML engine evaluates each flip against momentum, volume, trend efficiency, volatility shock, band distance, MACD, price structure, regime confidence, MTF alignment, ADX strength, RSI divergence, volume profile zone, and session quality. Each feature is normalized to 0–100, weighted, passed through a sigmoid function, and combined into a single confidence score. Signals below the confidence gate are rejected — they pass the classic SuperTrend logic but fail the multi-dimensional quality check. Layer 3 — Self-learning gate: The ML confidence gate itself adapts over time. The system tracks each signal's outcome (win/loss evaluated after N bars using the ATR at entry for fair comparison). When the win rate exceeds 70%, the gate lowers (allowing more signals). When it drops below 50%, the gate raises (becoming stricter). A decay factor prevents old signals from dominating. This creates a feedback loop: the indicator learns which confidence level produces profitable signals on this specific instrument and timeframe. Without auto-tuning, the SuperTrend uses static parameters. Without ML scoring, good and bad flips are treated equally. Without self-learning, the confidence gate is a fixed guess. Each layer eliminates a specific category of bad signals that the previous layer can't catch. 🔍 WHAT MAKES IT ORIGINAL 1️⃣ Instrument profiling and regime classification. The profiler computes four metrics over a configurable lookback (default 100 bars): — 📐 Efficiency Ratio : ER = |close − close | / sum(|close − close |, N). Measures net directional movement vs total path. ER → 1.0 = pure trend, ER → 0.0 = pure chop. — 🔄 Autocorrelation : correlation between return and return over a sliding window. High positive autocorrelation = trending persistence. Near-zero = random. Negative = mean-reverting. — 📏 Volatility Clustering : ratio of short-term ATR (20 bars) to long-term ATR (lookback). Values > 1.0 indicate a volatility spike (breakout or crash). Values < 1.0 indicate compression. — 📈 Normalized Volatility : ATR / close × 100. Measures absolute volatility as percentage of price — allows cross-instrument comparison. These are smoothed with EMA and combined into three regime scores: — trendScore = ER × regimeSensitivity — rangeScore = (1 − ER) × (1 − |autocorrelation|) × regimeSensitivity — volatScore = clamp(volClustering − 1, 0, 2) × regimeSensitivity The highest score determines the regime: TRENDING, RANGING, or VOLATILE. Regime confidence = highest_score / total_scores × 100%. 2️⃣ Regime-weighted auto-tuning (6 parameters). Each SuperTrend parameter is computed as a weighted blend of regime-optimal values: effectiveParam = wT × trendOptimal + wR × rangeOptimal + wV × volatileOptimal Where wT, wR, wV are the normalized regime weights. The parameters and their regime-optimal ranges: — ATR Length: Trending=10, Ranging=16, Volatile=21 (further scaled by normalized volatility) — Base Multiplier: Trending=2.0, Ranging=3.2, Volatile=3.8 (scaled by normalized vol) — Flip Cushion: Trending=0.05, Ranging=0.25, Volatile=0.15 — Signal Cooldown: Trending=2, Ranging=5, Volatile=3 — RSI Threshold: Trending=40, Ranging=52, Volatile=45 — RSI Length: derived as ATR Length × 0.9 — Adaptive Smoothing: ATR Length × 4.0 This means in a trending regime, the SuperTrend uses shorter ATR, lower multiplier (tighter bands), minimal cushion, and permissive RSI — catching trends early. In a ranging regime: longer ATR, wider multiplier, large cushion, strict RSI — avoiding chop. In volatile conditions: intermediate settings with wider bands to accommodate spikes. 3️⃣ 13-feature ML scoring engine. Each feature is normalized to 0–100, multiplied by its weight, summed, normalized by total weight, and passed through a sigmoid function to produce the final 0–100 confidence score. Features and their weights: — 💪 F1: Momentum (RSI alignment with trend) — w=0.15 — 📈 F2: Volume Surge (volume / SMA ratio) — w=0.08 — 📐 F3: Trend Efficiency (ER × 100) — w=0.15 — ⚡ F4: Volatility Shock (inverted vol clustering) — w=−0.08 (negative = penalizes vol spikes) — 📏 F5: Band Distance (sigmoid of close-to-band ATR distance) — w=0.10 — 📊 F6: MACD (normalized histogram vs ATR) — w=0.08 — 🏗️ F7: Price Structure (HH/HL for bull, LL/LH for bear over 10 bars) — w=0.08 — 🧠 F8: Regime Confidence (% confidence in current regime) — w=0.04 — 🌐 F9: MTF Confluence (aligned with HTF = 100, not = 0) — w=0.12 — 💪 F10: ADX Strength (ADX × 2.5, capped at 100) — w=0.10 — 🔀 F11: RSI Divergence (aligned div = 100, counter div = 10) — w=0.08 — 📊 F12: Volume Profile Zone (proximity to highest-volume bar) — w=0.06 — 🕐 F13: Session Quality (hour-based scoring for optimal trading sessions) — w=0.04 The raw weighted sum is normalized, then passed through: mlScore = 100 / (1 + exp(−0.08 × (normalizedScore − 50))). This sigmoid compresses extreme values and centers the output around 50. All 13 weights plus the bias term are user-configurable — you can adjust how much each factor contributes. Negative weights penalize a factor (e.g., W4 = −0.08 means high volatility shock reduces the score). 4️⃣ Self-learning confidence gate. The system maintains 5 pending signal slots. Each stores the entry price, direction, bar index, and ATR at entry. After the evaluation horizon (default 15 bars), the outcome is assessed: win = (close − entryPrice) × direction > 0.5 × entryATR (profitable by at least half an ATR, using the ATR at entry time — not current ATR — for fair comparison) A decay factor (0.98) is applied to historical totals before adding new results, preventing stale data from dominating. When total tracked signals ≥ 8: — Win rate > 70% → gate decreases by 1.5 (more permissive) — Win rate < 50% → gate increases by 1.5 (more restrictive) — Gate is clamped to The dashboard shows the current gate value, whether it's auto-adjusted, and the tracked win rate with sample size. 5️⃣ Multi-timeframe confluence with auto-HTF selection. The indicator automatically selects the appropriate higher timeframe based on your current TF: 1M→15M, 5M→30M, 15M→1H, 1H→4H, 4H→D, D→W. Or you can manually specify the HTF. Three strictness levels: — Loose: MTF misalignment adds negative ML score but doesn't block — Moderate: MTF misalignment reduces signal quality — Strict: MTF misalignment hard-blocks the signal entirely HTF trend is determined by EMA(20) vs EMA(50) on the higher timeframe. 6️⃣ Adaptive SuperTrend core (from StealthTrail). The band calculation uses pre-computed interpolated ATR values (ATR bank at 9 fixed periods with lerp interpolation) for smooth adaptation to any auto-tuned ATR length. Same mechanics as StealthTrail: adaptive multiplier (ATR / SMA ratio), band ratcheting, flip cushion, and cooldown — but now all parameters are regime-driven. 7️⃣ Three-mode trailing TP/SL system. Three SL modes: ATR (entry ± mult × ATR), Band (SuperTrend band as SL), Fixed % (percentage from entry). Three trailing modes: — ATR : trail at fixed ATR distance from price — simple, consistent — Band : use the SuperTrend band itself as trailing stop — structurally anchored — ATR → Band (hybrid) : start with tight ATR trail, switch to band when it catches up — best of both The trail only ratchets in the profit direction (never moves away from price). TP1/TP2/TP3 hit markers (✓) appear on the chart. On TP3 or SL hit, the trade closes and lines are removed. 8️⃣ RSI divergence detection. Scans for bullish divergence (price lower low, RSI higher low, RSI < 40) and bearish divergence (price higher high, RSI lower high, RSI > 60). Divergences aligned with the signal direction boost the ML score (F11 = 100). Counter-divergences penalize it (F11 = 10). Optional visualization as dots on the chart. 9️⃣ Volume profile zone proximity. Tracks the highest-volume bar in the last 50 bars. Proximity to this bar's price level is scored: within 1.5× ATR = 100 (near institutional activity), further = proportionally lower. Signals near high-volume zones tend to have more follow-through. 🔟 Session quality scoring. For intraday timeframes, each hour receives a quality score based on typical institutional activity: London/NY overlap (13–17 UTC) = 100, European session (8–12) = 80, US afternoon (18–20) = 70, Asian session (0–7) = 30. An optional kill zone filter suppresses all signals during specified hours. ⚙️ HOW IT WORKS — CALCULATION FLOW Step 1 — Instrument profiling: ER, autocorrelation, vol clustering, normalized vol → EMA-smoothed → regime classification (TRENDING / RANGING / VOLATILE) with confidence %. Step 2 — Auto-tuning: Regime weights blend optimal parameters for ATR length, multiplier, cushion, cooldown, RSI threshold/length. Step 3 — SuperTrend calculation: Interpolated ATR from pre-computed bank → adaptive multiplier (ATR/SMA ratio) → upper/lower bands → ratcheting → flip detection with cushion + cooldown. Step 4 — Classic filters: Momentum (RSI), volume, session, MTF hard-block (if strict). Step 5 — ML feature extraction: 13 features normalized to 0–100 from current market state. Step 6 — ML scoring: Weighted sum → weight normalization → sigmoid → 0–100 confidence score. Step 7 — Signal decision: Classic filters pass AND (ML disabled OR mlScore ≥ gate) → confirmed signal. Step 8 — Self-learning: Signal stored in pending slot → evaluated after horizon bars → win rate updated → gate adjusted. Step 9 — TP/SL placement: SL from band/ATR/fixed% → TPs as ATR multiples → trailing stop ratchets per mode. 📖 HOW TO USE 🎯 Quick start: 1. Add the indicator — Auto-Tune is ON by default, parameters self-configure 2. The SuperTrend band and Long/Short labels appear 3. Dashboard shows: trend, strength, regime, ML score, gate, win rate, TP/SL status 4. Enable ML Filter for quality scoring (off by default — enable after reviewing signal quality) 5. Self-Learning auto-adjusts the gate over time 👁️ Reading the chart: — 🟢 Green band + "Long" label = confirmed bullish signal — 🔴 Red band + "Short" label = confirmed bearish signal — ⚫ Gray dot = classic filter blocked the flip — 🟡 Yellow triangle = ML rejected the signal (score below gate) — 🟢 Green dot below bar = bullish RSI divergence — 🔴 Red dot above bar = bearish RSI divergence — 📈 Regime badge = current market classification (📈 TRENDING / 📊 RANGING / ⚡ VOLATILE) — 🟢 Green dashed = TP1/TP2/TP3, 🔴 Red dashed = SL, 🔵 Blue dotted = entry — "TP1 ✓" / "SL ✗" labels = outcome markers 📊 Dashboard sections: — Main: trend, signal, strength, ADX, HTF alignment — 🤖 ML Engine: ML score, confidence gate (fixed or auto), win rate with sample size — 🎯 Position: status (LONG/SHORT/FLAT), entry, SL (with trail mode icon), TP levels (✓ for hit), R:R ratio — 🧠 Regime: classification + confidence % 🔧 Tuning guide: — Start simple: Auto-Tune ON, ML OFF — let the regime engine handle parameters — Add ML: Enable ML Filter after 50+ signals to see which score level produces winners — Enable Self-Learning: after 100+ bars of ML being active — let the gate auto-calibrate — Adjust weights: if you know your market (e.g., volume is unreliable on forex → set W2 to 0) — Strict MTF: for higher-timeframe alignment — reduces signals, increases quality — Trail Mode: Band for trend-following, ATR for scalping, ATR→Band for hybrid ⚙️ KEY SETTINGS REFERENCE ⚙️ Main: — Auto-Tune (default On): regime-driven parameter self-configuration — ATR Length / Base Multiplier : manual overrides when auto-tune is off 🧠 Adaptive Engine: — Profiling Lookback (default 100): bars for regime classification — Regime Sensitivity (default 1.0): scaling factor for regime scores 📐 Multi-Timeframe: — MTF Confluence (default On): Auto/Manual HTF selection — Strictness (default Moderate): Loose / Moderate / Strict 🤖 ML Signal Filter: — Enable ML (default Off): activate 13-feature scoring — Confidence Gate (default 21): minimum ML score to pass — Self-Learning (default On): auto-adjust gate from tracked outcomes — Evaluation Horizon (default 15 bars): outcome assessment window — 13 individual weights + bias : fully configurable feature importance 🔍 Filters: — Flip Cushion, Cooldown, RSI Momentum, Volume, Session Kill Zone 🎯 TP/SL: — SL Mode (default Band): ATR / Band / Fixed % — Trail Mode (default Band): ATR / Band / ATR → Band — TP Levels (1–3): ATR multipliers (default 1.5 / 2.5 / 4.0) 🔔 Alerts — 🟢 LONG / 🔴 SHORT — ticker, price, TF, band, ML score, ADX, HTF, SL, TP1, regime — 🎯 TP1 / TP2 / TP3 HIT — trade progress — 🛑 SL HIT — stopped out All support plain text and JSON webhook format. Bar-close confirmed. ⚠️ IMPORTANT NOTES — 🚫 No repainting. All signals require barstate.isconfirmed. The confirmed trend direction is stored separately from the real-time calculation — signals only fire on closed bars. HTF data uses lookahead_off. A warmup period (max of profiling lookback and 55 bars) prevents signals during insufficient data. — 🤖 The ML scoring is not machine learning in the neural network sense . It's a weighted linear model with sigmoid activation — a logistic regression analog. The 13 features are hand-crafted from market microstructure, and the weights are configurable by the user. There is no gradient descent, backpropagation, or training phase. The "self-learning" adjusts only the confidence gate threshold, not the feature weights. — 📐 Auto-tuning produces different parameters on every bar as the regime shifts. The ATR length and multiplier change continuously — this is by design. If you prefer fixed parameters, disable Auto-Tune. — ⚖️ The self-learning gate requires at least 8 tracked signals before it begins adjusting. With the decay factor (0.98), the effective sample is weighted toward recent signals. The gate moves slowly (±1.5 per adjustment) and is clamped to . — 📊 Win rate evaluation uses ATR at entry time , not current ATR. A signal is a "win" if price moves > 0.5× entry ATR in the signal direction within the evaluation horizon. This prevents volatile periods from inflating win counts. — 🔄 The pre-computed ATR bank (9 fixed periods with lerp interpolation) is a performance optimization that allows smooth ATR adaptation to any auto-tuned length without calling ta.atr() dynamically — which Pine Script doesn't support with variable-length arguments. — 📏 Volume Profile Zone tracks the single highest-volume bar in the last 50 bars, not a full volume profile. It decays after 50 bars with no new volume peak. — 🕐 Session scoring uses UTC-based hours. On daily or higher timeframes, session quality defaults to 50 (neutral) as intraday session distinctions don't apply. — 🛠️ This is a signal scoring and analysis tool , not an automated trading bot. It classifies regimes, scores signals, tracks outcomes, and manages TP/SL — trade decisions remain yours. — 🌐 Works on all markets and timeframes. Volume features auto-adapt to instruments without volume data.
Indicador Pine Script®
por WillyAlgoTrader
8
Adaptive Ichimoku Nexus [WillyAlgoTrader]☁️ Adaptive Ichimoku Nexus — a modern approach to the legendary all-time indicator Ichimoku Kinko Hyo. This overlay indicator replaces the fixed periods of the classic Ichimoku system with a volatility-adaptive engine that dynamically scales Tenkan-Sen, Kijun-Sen, and Senkou Span B lookback periods based on current market conditions. Every TK cross signal is scored by an 8-factor confluence engine (0–100) that combines all five Ichimoku dimensions with volume, momentum pulse, and momentum acceleration. The indicator also includes a dedicated Kumo breakout engine with retest detection, three Ichimoku-anchored SL modes with R:R-based TP levels, and a multi-timeframe Ichimoku alignment panel — creating a complete trading system built entirely on Ichimoku principles enhanced with adaptive intelligence. Ichimoku Kinko Hyo was designed in the 1930s with fixed periods (9/26/52) calibrated for the Japanese trading week. These periods remain the default worldwide, but modern markets are faster, more volatile, and trade 24/7. A fixed 26-period Kijun-Sen responds identically whether the market is in a tight range or a momentum breakout — producing late signals in trends and whipsaws in consolidation. This indicator preserves the complete Ichimoku structure — all five lines, the cloud, and the displacement — while making the periods responsive to current volatility. In high-volatility environments, all three Donchian-based periods shorten → the Tenkan reacts faster, the Kijun adapts sooner, the cloud thins and pivots quicker. In low-volatility consolidation, the periods lengthen → noise is filtered, fewer false TK crosses, thicker cloud provides stronger S/R. The entire Ichimoku system breathes with the market. 🧩 WHY THESE COMPONENTS WORK TOGETHER Classic Ichimoku already integrates five components into one system: Tenkan-Sen (momentum), Kijun-Sen (trend), Senkou Span A/B (future S/R), and Chikou Span (lagging confirmation). The genius of Ichimoku is that these five dimensions are designed to confirm each other — a "5/5 alignment" is one of the strongest signals in technical analysis. This indicator enhances the system at three levels: Level 1 — Adaptive periods: The volatility engine scales all three Donchian-based components (Tenkan, Kijun, Span B) proportionally, preserving the Ichimoku ratios while adapting the speed. This means the relationship between Tenkan and Kijun (the core signal mechanism) stays consistent — they just both become faster or slower together. Level 2 — Confluence scoring: Instead of manually checking "Is Tenkan above Kijun? Is price above cloud? Is Chikou confirming?" — the 8-factor engine quantifies every Ichimoku dimension plus volume and momentum into a single 0–100 score. A score of 85 means virtually every Ichimoku component plus momentum and volume agrees. A score of 35 means the signal is conflicted — skip it. Level 3 — Structural TP/SL: The Kumo edge and Kijun-Sen are natural Ichimoku support/resistance levels. Using them as stop-loss anchors (instead of arbitrary ATR multiples) produces structurally meaningful stops that respect the same framework generating the signals. Level 4 — Momentum Pulse: Classic Ichimoku has no built-in momentum acceleration measure. The Momentum Pulse engine quantifies how fast the TK spread is changing and which direction the future cloud is rotating — capturing the urgency behind each signal. Without adaptive periods, the system is rigid. Without scoring, you must manually assess 5+ factors. Without structural SL, your risk management ignores Ichimoku's own S/R levels. Without the Momentum Pulse, you can't distinguish between a strong and a fading TK cross. Each layer adds a dimension that classic Ichimoku lacks. 🔍 WHAT MAKES IT ORIGINAL 1️⃣ Volatility-adaptive Ichimoku periods. When Adaptive mode is on, each Donchian midline (Tenkan, Kijun, Span B) uses a volatility-scaled period: adaptedPeriod = basePeriod × (1 + strength × (1 − 2 × volRatio)) Where volRatio = (currentATR − lowestATR) / (highestATR − lowestATR) over the volatility lookback (default 50 bars), normalized to 0–1. When volRatio → 1 (high volatility): adaptedPeriod = basePeriod × (1 − strength) — periods shorten When volRatio → 0 (low volatility): adaptedPeriod = basePeriod × (1 + strength) — periods lengthen The Adapt Strength parameter (default 0.4 = ±40%) controls the range of scaling. With basePeriod=26 and strength=0.4: periods range from 16 (high vol) to 36 (low vol). Each adapted period is clamped to a valid range and fed into the standard Donchian midline formula: (highest(high, period) + lowest(low, period)) / 2. This means all five Ichimoku lines (Tenkan, Kijun, Senkou A, Senkou B, Chikou) adapt proportionally — the system remains internally consistent. In Classic mode, the standard fixed periods are used unchanged. 2️⃣ 8-factor confluence scoring engine (0–100). Every bar computes both a bullish and bearish score from 8 factors: — 📐 Price vs Cloud (20 pts) : above cloud = 20, inside = 8, below = 0 (bull). Symmetric for bear. The cloud is the strongest S/R in Ichimoku. — ⚡ TK alignment (15 pts) : Tenkan > Kijun = 15 (bull). The core Ichimoku momentum signal. — 👁️ Chikou confirmation (15 pts) : Chikou Span above price at displaced position = 15 (bull). The lagging confirmation. — ☁️ Cloud direction (10 pts) : Span A slope > Span B slope = 10 (bull). Future cloud turning bullish indicates trend momentum. — 📏 Kumo thickness (8 pts) : thick cloud = 8, thin cloud = 2. Thick cloud provides stronger S/R backing. — 📈 Volume (10 pts) : volume > SMA(20) × 1.2 = 10. Confirms institutional participation. — 💪 Momentum alignment (12 pts) : Momentum Pulse > 20 = 12, > 0 = 6. Strong momentum behind the signal. — 🚀 Momentum acceleration (10 pts) : Momentum Pulse rising = 10. Trend is accelerating, not fading. Max score = 100. Signals require score ≥ Min Confluence Score (default 50). Grades: Strong (≥ 80), Standard (≥ 50), Weak (< 50). 3️⃣ Momentum Pulse engine (−100 to +100). A composite momentum measure built from three Ichimoku-derived components: — TK spread normalized by ATR (weight 40): tkSpreadNorm = (Tenkan − Kijun) / ATR. Measures how far apart the momentum and trend lines are relative to volatility. — TK spread acceleration (weight 100): tkSpreadNorm − tkSpreadNorm . Measures how fast the spread is changing — captures momentum buildup. — Cloud slope differential (weight 30): (ΔSpanA − ΔSpanB) / ATR over 5 bars. Measures whether the future cloud is rotating bullish or bearish. Combined: momentumPulse = tkSpread×40 + tkAcceleration×100 + cloudSlope×30, clamped to , smoothed with EMA(5). States: Accelerating (rising + positive), Bull Fading (falling + positive), Bear Accelerating (falling + negative), Bear Fading (rising + negative). 4️⃣ Three Ichimoku-anchored SL modes. Stop-loss placement uses Ichimoku structure: — Kumo Edge (default): SL at the nearest cloud boundary (kumoBot for longs, kumoTop for shorts) + ATR buffer. The cloud is Ichimoku's primary S/R — placing the stop here means your stop is at the strongest structural level in the framework. — Kijun : SL at the Kijun-Sen ± ATR buffer. The Kijun is Ichimoku's equilibrium line — price tends to return to it. — ATR : SL at entry ± 2× ATR. Pure volatility-based fallback. TP1/TP2/TP3 are R:R multiples of the risk distance (default 1.5/2.5/4.0). A minimum risk distance of 0.5× ATR is enforced. 5️⃣ Kumo breakout engine with retest detection. Detects when price closes above the cloud (was below or inside on the previous bar) with volume confirmation: — kumoBreakUp: close > kumoTop AND previous close ≤ kumoTop AND volume > SMA(20) × breakoutMultiplier — kumoBreakDown: close < kumoBot AND previous close ≥ kumoBot AND same volume condition After a breakout, a retest signal fires if within 10 bars, price touches the cloud edge and closes back on the breakout side — confirming the cloud has flipped from resistance to support (or vice versa). Retest signals appear as small circles distinct from the larger diamond breakout markers. 6️⃣ Kijun-Sen S/R zone detection. When the Kijun-Sen has been flat for 4+ consecutive bars and then starts moving, the flat level is marked as a support/resistance zone (shaded box ± 0.15× ATR). Flat Kijun is a well-known Ichimoku S/R concept — price tends to be attracted to flat Kijun levels. The indicator automates this detection and visualization. 7️⃣ Multi-timeframe Ichimoku alignment panel. Three configurable timeframes (default 15M/1H/4H) each compute a full Ichimoku state using the classic periods: — Bull ● : close > cloud AND Tenkan > Kijun — Bear ● : close < cloud AND Tenkan < Kijun — Neutral ○ : anything else The panel shows per-TF alignment plus a summary: ALL BULL ✓ (all 3 TFs bullish), ALL BEAR ✓ (all 3 bearish), or Mixed. All MTF data uses + lookahead_on for non-repainting. ⚙️ HOW IT WORKS — CALCULATION FLOW Step 1 — Volatility measurement: ATR(14) is normalized to 0–1 by its position within the recent high-low range over the volatility lookback. Step 2 — Period adaptation: Each base period (9/26/52) is scaled by the adapt strength and vol ratio. High vol → shorter periods, low vol → longer. Classic mode bypasses this. Step 3 — Ichimoku calculation: Tenkan = Donchian midline (adapted period). Kijun = Donchian midline (adapted period). Senkou A = avg(Tenkan, Kijun). Senkou B = Donchian midline (adapted period). Chikou = source price. Cloud displaced forward by displacement bars. Step 4 — Kumo at current bar: Span A and Span B are read at displacement offset to get the current cloud boundaries. Thickness, price position (above/below/inside), and thin-cloud status are computed. Step 5 — Momentum Pulse: TK spread, spread acceleration (vs 3 bars ago), and cloud slope differential — combined and EMA-smoothed. Step 6 — Confluence scoring: 8 factors evaluated. Bull and bear scores computed independently. Step 7 — Signals: TK cross + score threshold + enabled filters (Kumo thickness, volume, Chikou) → confirmed buy/sell. Kumo breakout: cloud boundary cross + volume surge → breakout signal. Retest: cloud edge touch within 10 bars of breakout. Step 8 — TP/SL: SL from Kumo edge / Kijun / ATR mode. TPs as R:R multiples. TP/SL hits tracked per trade. 📖 HOW TO USE 🎯 Quick start: 1. Add the indicator — the Ichimoku cloud and lines appear (adaptive by default) 2. "Long 78%" / "Short 65%" labels = TK cross signals with confluence score 3. ☁▲ / ☁▼ diamonds = Kumo breakout signals 4. Entry, SL, TP1–TP3 lines appear on each signal 5. Check the MTF panel for multi-timeframe alignment 👁️ Reading the chart: — 🔵 Blue line = Tenkan-Sen (conversion, fast) — 🔴 Pink line = Kijun-Sen (base, slow) — 🟠 Orange line (displaced back) = Chikou Span — 🟩🟥 Cloud fill = Kumo (green bullish, red bearish) — 🟢 "Long XX%" label = confirmed bullish TK cross with score — 🔴 "Short XX%" label = confirmed bearish TK cross with score — 💎 Cyan diamond = Kumo breakout (☁▲ up / ☁▼ down) — ⚫ Small circle = Kumo edge retest — 🟪 Shaded zone = flat Kijun S/R area — 🔵 Blue line = entry, 🔴 red = SL, 🟢 green = TP1/TP2/TP3 📊 Dashboard fields: — Mode: Adaptive / Classic — Trend: Bullish / Bearish / Neutral (price vs cloud + TK alignment) — Signal: last signal with bars elapsed — Score: confluence percentage with color grade — Momentum: Pulse state + value (Accelerating / Bull Fading / Bear Accel / etc.) — Cloud: price position (Above / Below / Inside / Thin) — Trade: TP/SL progress (→ TP1, TP1 ✓ → TP2, TP3 ✓ Closed, SL ✗ Closed) — MTF: 3-timeframe Ichimoku alignment + summary (ALL BULL / ALL BEAR / Mixed) — Version 🔧 Tuning guide: — Too many weak signals: increase Min Score (60–80), enable all filters — Missing signals: decrease Min Score (30–40), disable Chikou filter — Adaptive too aggressive: decrease Adapt Strength (0.2–0.3) or increase Volatility Lookback (100+) — Want classic Ichimoku: switch to Classic mode — pure 9/26/52 with scoring and TP/SL — Stops too tight: increase SL ATR Buffer (0.7–1.0) or switch to ATR SL mode — Scalping: Conversion 5, Base 13, Span B 26, Displacement 13, Min Score 40 — Swing: Conversion 12, Base 34, Span B 68, Displacement 34, Min Score 65 ⚙️ KEY SETTINGS REFERENCE ⚙️ Main: — Calculation Mode (default Adaptive): Adaptive / Classic — Conversion/Base/Span B/Displacement (default 9/26/52/26) 🔄 Adaptive Engine: — Volatility Lookback (default 50): ATR normalization window — Adapt Strength (default 0.4): period scaling range (±40%) 🔍 Filters: — Min Confluence Score (default 50): 0–100 threshold — Kumo Thickness Filter (default On): suppress in thin cloud — Volume Filter (default On): auto-disabled on forex — Chikou Confirmation (default On): require lagging span alignment 🎯 Smart TP/SL: — SL Mode (default Kumo Edge): Kumo Edge / Kijun / ATR — SL ATR Buffer (default 0.5): padding beyond SL level — TP1/TP2/TP3 R:R (default 1.5/2.5/4.0) 💥 Kumo Breakout: — Breakout Vol Mult (default 1.3): volume surge requirement — Show Retest Signals (default On): cloud edge retest detection 🔄 Multi-Timeframe: — TF 1/2/3 (default 15/60/240): configurable timeframes 🔔 Alerts — 🟢 BUY / 🔴 SELL — TK cross with score, SL, TP1–TP3 — ☁️▲ KUMO BREAK UP / ☁️▼ KUMO BREAK DOWN — 🎯 TP1 HIT / 🛑 SL HIT All support plain text and JSON webhook format. Bar-close confirmed. ⚠️ IMPORTANT NOTES — 🚫 No repainting. All TK cross signals and Kumo breakouts require barstate.isconfirmed. MTF data uses + lookahead_on. A warmup period (Span B + displacement, minimum 80 bars) prevents signals during insufficient data. — ☁️ This preserves the complete Ichimoku structure. All five lines, the cloud, displacement, and Chikou are computed exactly as Ichimoku specifies — the only change is that in Adaptive mode, the three Donchian periods scale with volatility. Switching to Classic mode produces a standard Ichimoku with no modifications. — 📐 The adaptive engine scales all three periods proportionally using the same vol ratio and strength. The relationship between Tenkan (fast) and Kijun (slow) is preserved — they don't drift independently. — ⚖️ The confluence score is Ichimoku-native . Six of eight factors (price vs cloud, TK alignment, Chikou, cloud direction, Kumo thickness, momentum) are derived directly from Ichimoku components. Only volume and momentum acceleration are external additions. — 📊 The Momentum Pulse is not a standalone oscillator — it's derived from TK spread dynamics and cloud rotation, both Ichimoku-native measurements. It quantifies what experienced Ichimoku traders assess visually: "Is this TK cross strong and accelerating, or weak and fading?" — 🔄 Kumo breakout retest detection uses a 10-bar window after the initial breakout. Retests beyond 10 bars are not tracked. — 🛠️ This is a signal and analysis tool , not an automated trading bot. It enhances Ichimoku with adaptive periods, scoring, and risk management — trade decisions remain yours. — 🌐 Works on all markets and timeframes. Volume filter auto-disables on instruments without volume data.
Indicador Pine Script®
por WillyAlgoTrader
16
Precision Sniper [WillyAlgoTrader]🎯 Precision Sniper is an overlay indicator that generates entry signals only when a 10-factor confluence scoring engine reaches a configurable threshold — combining EMA alignment, RSI momentum, MACD direction, VWAP position, volume confirmation, ADX trend strength, DI directional pressure, and higher-timeframe bias into a single composite score (0–10). Every signal comes with automatic TP/SL placement using either ATR-based or structure-based stops, plus a progressive trailing stop system that ratchets the stop to breakeven after TP1 and to TP1 level after TP2. The core principle: instead of using a single crossover or oscillator reading to trigger a signal, this indicator requires multiple independent market dimensions to agree simultaneously. An EMA crossover alone can produce false signals in choppy markets. RSI confirmation alone can be early or late. Volume alone doesn't tell you direction. But when EMA alignment + RSI momentum + MACD direction + VWAP position + volume + ADX + DI + HTF trend all point the same way — and the composite score exceeds your threshold — the probability of a genuine directional move is significantly higher than any single factor alone. 🧩 WHY THESE COMPONENTS WORK TOGETHER Each factor in the scoring engine measures a different market dimension: — EMA Fast/Slow crossover → detects the momentum shift that initiates the signal (trigger) — EMA Trend → confirms the macro direction (structural filter) — RSI → confirms momentum is in the non-extreme zone (avoids overbought entries) — MACD histogram + MACD vs signal → confirms momentum is accelerating, not decelerating (2 factors) — VWAP position → confirms price is on the right side of institutional fair value — Volume → confirms market participation (not a low-liquidity wick) — ADX + DI → confirms the market is trending AND directional pressure aligns (not ranging) — HTF EMA bias → confirms the higher-timeframe trend agrees with the entry direction These factors are deliberately orthogonal: EMA alignment can occur without volume, MACD can be bullish without RSI confirming, price can be above VWAP while ADX shows no trend. The scoring engine counts how many factors agree — only when enough dimensions align does the signal pass. The entry signal feeds into the risk management system: structure-based SL provides a structurally meaningful stop (recent swing low/high), the R:R-based TPs create consistent reward targets, and the progressive trailing stop automatically manages the trade after entry — ratcheting protection as each target is hit. Without the trailing system, a signal that hits TP1 can still reverse to SL for a full loss. With it, after TP1 the worst case is breakeven. 🔍 WHAT MAKES IT ORIGINAL 1️⃣ 10-factor confluence scoring engine (0–10 scale). Every bar, both a bullish and bearish score are computed from 10 independent factors: Bullish score calculation: — 📐 EMA Fast > EMA Slow → +1.0 (short-term momentum is upward) — 📏 Close > EMA Trend → +1.0 (price is above macro trend) — 📊 RSI > 50 AND RSI < 75 → +1.0 (momentum is bullish but not overbought) — 📈 MACD Histogram > 0 → +1.0 (momentum is positive) — 📈 MACD Line > Signal Line → +1.0 (MACD has bullish crossover) — ⚖️ Close > VWAP → +1.0 (price above institutional fair value) — 📊 Volume > SMA(20) × 1.2 → +1.0 (above-average participation) — 💪 ADX > 20 AND +DI > −DI → +1.0 (trending market with bullish pressure) — 🌐 HTF EMA Fast > HTF EMA Slow → +1.5 (higher timeframe confirms direction) — ✅ Close > EMA Fast → +0.5 (price is above the fast MA — minor confirmation) Maximum bullish score: 10.0. Bearish score uses symmetric conditions (< instead of >, −DI > +DI, etc.). The HTF factor carries 1.5× weight because higher-timeframe alignment is the single strongest predictor of signal quality. The close > EMA Fast factor carries 0.5× because it's partially redundant with the crossover — it adds a minor confirmation that price didn't just touch the crossover but is clearly above it. A signal fires when: EMA crossover occurs + price is on the correct side of both EMAs + RSI is not extreme + composite score ≥ Min Confluence Score (default 5 out of 10). 2️⃣ Structure-based stop loss with ATR fallback. When enabled (default on), the stop loss is placed at the most structurally meaningful level: For long trades: — structureStop = recent swing low (over configurable lookback, default 10 bars) − 0.2× ATR padding — atrStop = entry − ATR × SL multiplier — finalStop = max(structureStop, atrStop) — the HIGHER (tighter) of the two This "pick the tighter stop" logic ensures the SL is always at a meaningful structural level but never further than the ATR-based maximum. A minimum distance of 0.5× ATR is enforced to prevent unrealistically tight stops when the swing low is very close to entry. For short trades: symmetric logic with min() instead of max(), swing high + padding. When structure SL is disabled, the stop uses pure ATR: SL = entry ± ATR × multiplier. 3️⃣ Progressive trailing stop system. After entry, the stop ratchets progressively as targets are hit: — Initial state : SL at structure/ATR level — After TP1 hit : SL moves to entry price (breakeven) — worst case is now 0 loss — After TP2 hit : SL moves to TP1 level — worst case is now TP1 profit locked — After TP3 hit : SL moves to TP2 level — TP2 profit locked, runner continues The trailing stop line updates dynamically on the chart (orange dotted line with label). The SL hit check uses the pre-update trail value to prevent same-bar conflicts: if TP1 and the trail are both touched on the same candle, the TP1 hit processes first, then the trail is checked against its PRE-move value. This progressive system means that once a trade reaches TP1, it can only end in breakeven or profit — never a loss. After TP2, the minimum outcome is TP1 profit locked. 4️⃣ Four presets with parameter scaling. Each preset adjusts two key parameters: — Conservative : min score floor 7/10, SL floor 2.0× ATR — requires strong consensus, wider stop — Default : uses your manual settings — Aggressive : min score ceiling 3/10, manual SL — accepts lighter consensus — Scalping : min score ceiling 4/10, SL ceiling 1.0× ATR — lower bar, tighter stop The preset modifies the effective score threshold and SL multiplier — the underlying 10 factors don't change, only how many must agree and how wide the stop is. 5️⃣ Volatility regime detection. The dashboard displays the current volatility regime: volRatio = ATR(14) / SMA(ATR, 42). High (ratio > 1.3) = volatility above average — consider wider stops. Low (ratio < 0.7) = volatility compressed — watch for breakout. Normal = standard conditions. This provides at-a-glance context for how the current environment affects your settings. 6️⃣ EMA ribbon with macro trend overlay. Three EMAs create a visual trend system: — EMA Fast (default 9) = short-term momentum direction — EMA Slow (default 21) = medium-term trend — EMA Trend (default 55) = macro trend filter (shown as dot-style line) The fast/slow ribbon fills green when fast > slow (bullish momentum) and red when fast < slow. Signals only fire when the EMA crossover occurs AND price confirms by closing on the correct side of both EMAs. 7️⃣ RSI extreme avoidance. The signal engine requires RSI to be in a non-extreme zone: bullish signals require RSI > 50 AND < 75 (not overbought). Bearish signals require RSI < 50 AND > 25 (not oversold). This prevents the most common failure mode of momentum-based entries: buying into an already overbought market or selling into an oversold bounce. 8️⃣ Direction lock — one signal per trend leg. After a buy signal fires, the next signal can only be a sell (and vice versa). This prevents signal clustering during strong trends where the confluence score might cross the threshold multiple times. If both buy and sell trigger on the same bar (rare edge case), buy takes priority (mutual exclusion). ⚙️ HOW IT WORKS — CALCULATION FLOW Step 1 — Core indicators: EMA Fast(9), EMA Slow(21), EMA Trend(55), RSI(13), MACD(12/26/9), VWAP(hlc3), Volume SMA(20), ADX/DI(14), HTF EMAs via request.security with + lookahead_on. Step 2 — Confluence scoring: 10 factors evaluated independently for both bullish and bearish directions. Each factor adds its weight (1.0, 1.5, or 0.5) to the composite score. Max score = 10.0 per direction. Step 3 — Signal trigger: EMA crossover (fast crosses slow) + price above/below both EMAs + RSI not extreme + composite score ≥ threshold + direction lock → confirmed signal on barstate.isconfirmed. Step 4 — SL calculation: Structure mode: recent swing low/high ± 0.2× ATR padding, then pick the tighter of structure vs ATR stop. Minimum distance enforced at 0.5× ATR. Risk = |entry − SL|. Step 5 — TP placement: TP1 = entry ± risk × tp1RR, TP2 = entry ± risk × tp2RR, TP3 = entry ± risk × tp3RR. Step 6 — Trade monitoring: Each bar: check TP1/TP2/TP3 hits → ratchet trailing stop. Check SL hit against pre-ratchet trail value. Update visual lines and labels. 📖 HOW TO USE 🎯 Quick start: 1. Add the indicator — the EMA ribbon appears showing current trend 2. Select a preset (Conservative for swing, Scalping for 1–5M) 3. Wait for a "Long" or "Short" label — check the dashboard for score 4. Entry, SL, TP1, TP2, TP3 lines appear automatically 5. After TP1 → orange trailing stop line moves to breakeven 6. After TP2 → trail moves to TP1 level. After TP3 → trail moves to TP2. 👁️ Reading the chart: — 🟢 Green EMA ribbon fill = bullish momentum (fast > slow) — 🔴 Red EMA ribbon fill = bearish momentum — ⚫ Dot-style line = EMA Trend (55) — macro direction filter — 🟢 "Long" label below bar = confirmed buy signal — 🔴 "Short" label above bar = confirmed sell signal — 🔵 Blue solid line = entry price — 🔴 Red solid line = stop loss — 🟢 Green dashed lines = TP1, TP2, TP3 — 🟠 Orange dotted line = trailing stop (updates after each TP hit) 📊 Dashboard fields: — Trend: current EMA alignment (Bullish / Bearish / Neutral) — Score: confluence score (e.g., "7.5 / 10") — Status: trade state (Active / TP1 ✓ — Trail / TP2 ✓ — Trail / No Trade) — HTF Bias: higher-timeframe trend (Bullish / Bearish / Neutral) — Volatility: regime (High / Normal / Low) — RSI, ADX: current values — Timeframe, preset, version 🔧 Tuning guide: — Too many signals: increase Min Score (6–8), use Conservative preset, set HTF filter to a higher TF — Too few signals: decrease Min Score (3–4), use Aggressive preset — Stops too tight: increase SL ATR Multiplier (2.0–2.5), increase Swing Lookback (12–20) — Stops too wide: decrease SL ATR Multiplier (1.0), enable Structure-Based SL — Scalping 1–5M: Scalping preset, EMA Fast 5/Slow 13/Trend 34, TP1 0.75/TP2 1.5/TP3 2.5 — Swing 4H–1D: Conservative preset, EMA Fast 12/Slow 26/Trend 100, TP3 5.0+ ⚙️ KEY SETTINGS REFERENCE ⚙️ Main: — HTF Trend Filter (default current TF): higher timeframe for bias. Leave empty = disabled. — Preset (default Default): Conservative / Default / Aggressive / Scalping 🎯 Entry Engine: — EMA Fast (default 9) / Slow (default 21) / Trend (default 55) — Min Confluence Score (default 5): minimum score out of 10 to trigger signal — RSI Length (default 13) 🛡️ Risk Management: — ATR Length (default 14) / SL ATR Multiplier (default 1.5) — TP1/TP2/TP3 R:R (default 1.0 / 2.0 / 3.0) — Trailing Stop (default On): ratchets SL to BE after TP1, to TP1 after TP2 — Structure-Based SL (default On): recent swing low/high as stop anchor — Swing Lookback (default 10): bars for structure SL detection 🎨 Visual: — EMA ribbon, TP/SL lines, trailing stop line, background tint (all toggleable) — Configurable signal label size (Tiny–Huge) — Auto / Dark / Light theme 🔔 Alerts — 🟢 BUY / 🔴 SELL — ticker, price, SL, TP1, TP2, TP3, score, timeframe — 🎯 TP1 HIT / TP2 HIT / 🏆 TP3 HIT — trade progress — 🛑 SL HIT — stopped out All support plain text and JSON webhook format. Bar-close confirmed. ⚠️ IMPORTANT NOTES — 🚫 No repainting. All signals require barstate.isconfirmed. HTF data uses + lookahead_on for non-repainting values. TP/SL hits are checked only on bars after the entry bar (canCheckTPSL = bar_index > entryBar). A warmup period (max of EMA Trend length and 50 bars) prevents signals during insufficient data. — 📐 The confluence score is not a win-rate predictor . A score of 8/10 means eight market dimensions agree on direction — it measures consensus quality. Higher scores correlate with stronger setups but do not guarantee outcomes. — ⚖️ Structure-based SL picks the tighter of structure vs ATR stop — not the wider one. This means your actual risk per trade may be less than SL ATR Multiplier × ATR. Check the SL label on each trade for the actual stop level. — 🔒 The trailing stop uses pre-update values for SL hit detection. If TP1 is hit and the trail moves to breakeven on the same bar, the SL check uses the old trail value — preventing false same-bar stop-outs. — 📊 VWAP factor auto-falls back to close on instruments where ta.vwap returns na. Volume factor auto-passes (returns true) on instruments without volume data. — 🔄 If buy and sell trigger simultaneously (extremely rare edge case), buy takes priority and the sell is suppressed. — 🛠️ This is a signal and risk management tool , not an automated trading bot. It scores confluence, generates signals, places targets, and trails stops — trade decisions remain yours. — 🌐 Works on all markets and timeframes. All factors auto-adapt to available data.
Indicador Pine Script®
por WillyAlgoTrader
220
Smart Breakout Targets [WillyAlgoTrader]📡 Smart Breakout Targets is an overlay indicator that detects volatility squeezes using a dual-engine system (Bollinger Band Width compression + ATR contraction), builds adaptive consolidation range boxes, waits for a confirmed impulse candle to break the range, and then automatically places entry, stop-loss, and three take-profit levels based on the breakout's risk distance — with full trade lifecycle tracking that monitors TP/SL hits and marks the outcome directly on the chart. The core concept: volatility compression precedes expansion. When price coils into a tight range, a breakout from that range tends to produce a directional move proportional to how compressed the range was. This indicator automates the entire workflow: detect the compression, define the range, confirm the breakout, calculate the targets, track the outcome. Most breakout indicators on TradingView use a single volatility measure (typically Bollinger Band Width or Keltner Channel squeeze) to detect compression. A single measure can produce false positives — BB Width can narrow during a one-directional drift without true consolidation, or ATR can compress during a holiday session without tradeable structure. This indicator requires both engines to agree: BB Width must be below its threshold AND ATR must be below its compression ratio simultaneously. This dual confirmation eliminates the majority of false squeezes. 🧩 WHY THESE COMPONENTS WORK TOGETHER A squeeze detector alone tells you volatility is low — but it doesn't give you a range to trade against. A range box alone tells you where support and resistance are — but it doesn't confirm whether the breakout is genuine. An impulse filter alone measures candle quality — but without knowing the range boundaries, it doesn't know what's being broken. And TP/SL levels without range context have no structural anchor. This indicator connects them into a complete breakout workflow: BB Width squeeze + ATR compression → Range duration check → Adaptive Donchian range → Resistance/Support zones → Impulse candle confirmation → Filter gate (volume + HTF) → Entry at breakout → SL at opposite boundary + ATR buffer → TP1/TP2/TP3 as R:R multiples → Trade lifecycle tracking → Outcome labeling The dual squeeze engine defines WHEN compression exists. The minimum squeeze duration confirms the consolidation is established, not momentary. The adaptive Donchian tracks the range boundaries DURING the squeeze (expanding with each new high/low). The impulse filter confirms the breakout candle has sufficient body size relative to ATR. The volume and HTF filters add optional quality gates. And the R:R-based targets anchor to the actual risk distance (entry to opposite range boundary), not to arbitrary ATR multiples. Removing the dual engine reintroduces single-measure false squeezes. Removing the minimum duration allows momentary vol dips to create ranges. Removing the impulse filter lets weak candles trigger breakouts. Removing the ATR-buffered SL places stops too close to range boundaries. Each component solves a specific failure mode. 🔍 WHAT MAKES IT ORIGINAL 1️⃣ Dual-engine squeeze detection (BB Width + ATR compression). Two independent volatility measures must agree before a squeeze is confirmed: Engine 1 — Bollinger Band Width: bbWidth = (upperBB − lowerBB) / basisBB, where upperBB = SMA(close, len) + mult × stdev(close, len). The BB Width is compared to its own SMA: bbSqueeze = bbWidth < SMA(bbWidth, len) × squeezeThreshold (default 0.6). This detects when the bands are significantly tighter than their recent average. Engine 2 — ATR Compression: atrVal = ATR(len/2), atrSma = SMA(ATR, len). Compression = atrVal < atrSma × atrCompressRatio (default 0.75). This detects when absolute volatility (measured by ATR) has contracted below its recent average. The ATR period is half the squeeze length for faster response to volatility changes. Combined: isSqueeze = bbSqueeze AND atrCompress. Both engines must agree simultaneously. BB Width can narrow during a drift (price moving slowly but directionally) while ATR remains normal — the ATR engine blocks this false squeeze. Conversely, ATR can compress during a holiday while BB Width is normal — the BB engine blocks this. Dual agreement ensures genuine consolidation. 2️⃣ Minimum squeeze duration filter. A squeeze counter tracks consecutive bars where both engines agree. The range box is only created when the squeeze has lasted at least minSqueezeBars (default 5). This prevents momentary dips in volatility (single-bar BB Width contraction during a large candle, for example) from creating spurious ranges. The counter resets to zero when either engine disagrees. 3️⃣ Adaptive Donchian range boundaries. When a squeeze begins, the indicator initializes squeezeHigh and squeezeLow from the first bar. On each subsequent bar during the squeeze, the boundaries expand: squeezeHigh = max(squeezeHigh, high), squeezeLow = min(squeezeLow, low). This creates an adaptive Donchian channel that captures the full consolidation range — not just a fixed lookback but the exact range from squeeze start to squeeze end. If the resulting range exceeds 6× ATR (extreme outlier), it's clamped to 3× ATR above and below the range center. This prevents excessively wide ranges from producing unreachable targets. The range box also includes a resistance zone (top half-ATR, red-tinted) and a support zone (bottom half-ATR, green-tinted), highlighting the areas where price is most likely to be rejected on a false breakout. 4️⃣ Impulse candle breakout confirmation. A breakout requires more than just closing beyond the range — the breakout candle must be an impulse candle: Bullish breakout: close > rangeTop AND close > open AND |close − open| > ATR × impulseMultiplier (default 0.8) Bearish breakout: close < rangeBottom AND close < open AND |close − open| > ATR × impulseMultiplier This body size filter ensures the breakout candle has genuine momentum behind it — not a thin wick that barely clips the boundary. The impulse multiplier is configurable: lower values (0.3–0.5) accept weaker candles, higher values (1.0–1.5) require strong conviction bars. 5️⃣ R:R-based TP/SL with ATR-buffered stop. On breakout, the indicator calculates: — Entry = close of breakout candle — Stop Loss = opposite range boundary ± ATR × slBuffer (default 0.5). For a bullish breakout: SL = rangeBottom − ATR × 0.5. The buffer prevents the stop from sitting exactly at the range boundary where it would be clipped by a retest wick. — Risk distance = |entry − SL| — TP1 = entry ± risk × tp1RR (default 1.0 = 1:1 R:R) — TP2 = entry ± risk × tp2RR (default 2.0 = 1:2 R:R) — TP3 = entry ± risk × tp3RR (default 3.0 = 1:3 R:R) All levels are drawn as extending lines with price labels, plus linefill zones (red = risk area from entry to SL, green = reward area from entry to TP3). 6️⃣ Trade lifecycle tracking with outcome labels. After a breakout fires, the indicator actively monitors whether price hits TP1, TP2, TP3, or SL: TP hit detection: for long trades, high ≥ TPx AND high < TPx (first touch). For short trades, low ≤ TPx AND low > TPx. This ensures each TP is counted exactly once. Trade close conditions: — TP3 hit → trade marked as "Win (TP3)" → ✔ label placed on chart → all target lines removed — SL hit → trade marked as "Loss (SL)" → ✘ label placed on chart → all target lines removed — New breakout while trade active → previous trade replaced The dashboard shows: Active / Win (TP3) / Loss (SL) with the last P&L in price units. Close labels include tooltips with full trade details (entry, TP3/SL level, P&L). 7️⃣ Overlap prevention for range boxes. When enabled (default on), the indicator prevents a new range box from overlapping with an existing one. The squeezeStartBar of a new range must be after the right edge of the most recent existing box. This prevents cluttered, overlapping consolidation zones that would create confusing breakout levels. 8️⃣ Signal strength scoring (0–4). Each breakout receives a strength score based on how many quality factors are present: — +1 for impulse candle (always true on breakout, baseline) — +1 for volume surge (if volume filter enabled and passed) — +1 for HTF alignment (if HTF filter enabled and aligned) — +1 for extended squeeze (squeeze duration ≥ 2× minimum) Classification: Strong (≥3), Medium (≥2), Normal (<2). Displayed in the dashboard. ⚙️ HOW IT WORKS — CALCULATION FLOW Step 1 — Volatility measurement: BB Width = (upperBB − lowerBB) / basis. ATR computed with period = squeezeLenght / 2. Both compared to their SMAs. Step 2 — Squeeze detection: isSqueeze = (bbWidth < bbWidthSMA × threshold) AND (ATR < atrSMA × compressionRatio). Counter tracks consecutive squeeze bars. Step 3 — Range construction: When squeeze starts, init boundaries from first bar's high/low. Each bar during squeeze: boundaries expand to include new highs/lows. Range capped at 6× ATR. Step 4 — Range box creation: When squeeze ends (isSqueeze transitions from true to false) AND duration ≥ minimum bars AND not overlapping → create range box with resistance/support zones and centerline. Step 5 — Breakout scan: On each confirmed bar, iterate through existing range boxes. If close > rangeTop with bullish impulse + filter pass → bullish breakout. If close < rangeBottom with bearish impulse + filter pass → bearish breakout. The broken range box is removed. Step 6 — Target placement: Entry = close. SL = opposite boundary ± ATR buffer. TP1/TP2/TP3 = entry ± risk × R:R multipliers. Lines, labels, and fill zones are drawn. Step 7 — Trade monitoring: Each bar, check if price touched TP1/TP2/TP3 or SL (first-touch detection using current vs previous bar comparison). On TP3 or SL → close trade, label outcome, remove visuals. 📖 HOW TO USE 🎯 Quick start: 1. Add the indicator — gray range boxes appear at detected consolidation zones 2. Red-tinted zone at top = resistance, green-tinted at bottom = support 3. When price breaks out with an impulse candle → "Long" or "Short" label appears 4. Entry, SL, TP1, TP2, TP3 lines are automatically drawn 5. When price reaches TP3 → ✔ label. When SL hit → ✘ label. Trade auto-closes. 👁️ Reading the chart: — ⬜ Gray box = consolidation range (detected squeeze zone) — 🟥 Red-tinted top zone = resistance area within range — 🟩 Green-tinted bottom zone = support area within range — ➖ Dashed centerline = range midpoint — 🟢 "Long" label below bar = confirmed bullish breakout — 🔴 "Short" label above bar = confirmed bearish breakout — Green solid line = entry price — Red dashed line = stop loss — Green dotted lines = TP1, TP2, TP3 levels — 🟩 Green fill = reward zone (entry to TP3) — 🟥 Red fill = risk zone (entry to SL) — ✔ TP3 label = trade closed at target (win) — ✘ SL label = trade stopped out (loss) — 🟡 Yellow background (optional) = active squeeze 📊 Dashboard fields: — Status: Active / Win (TP3) / Loss (SL) — Signal: last breakout direction with bars elapsed — Strength: signal quality (Strong / Medium / Normal) — Trend: current trade direction — Squeeze: active status with bar count — Entry / Stop Loss: current trade levels — Last P&L: profit/loss of last completed trade — HTF Bias: higher-timeframe trend direction — Version / TF 🔧 Tuning guide: — Too many false squeezes: decrease Squeeze Threshold (0.4–0.5), decrease ATR Compression Ratio (0.6–0.7), increase Min Squeeze Bars (8–12) — Missing squeezes: increase Squeeze Threshold (0.7–0.8), increase ATR Compression Ratio (0.8–0.9), decrease Min Squeeze Bars (3–4) — Breakouts too weak: increase Impulse Body Threshold (1.0–1.5), enable Volume Filter — Stops too tight: increase SL ATR Buffer (0.7–1.0) — Want only trend-aligned breakouts: enable HTF Trend Filter — Scalping 1–5M: Squeeze Length 15, Min Squeeze 3, Impulse 0.5, TP1 0.75 — Swing 4H–1D: Squeeze Length 30, Min Squeeze 8, Impulse 1.0, TP3 5.0 ⚙️ KEY SETTINGS REFERENCE ⚙️ Main: — Squeeze Detection Length (default 20): lookback for BB Width and ATR baseline — BB Multiplier (default 2.0): standard deviation multiplier for Bollinger Bands — Squeeze Threshold (default 0.6): BB Width must be below this fraction of its SMA — ATR Compression Ratio (default 0.75): ATR must be below this fraction of its SMA — Min Squeeze Bars (default 5): minimum consecutive squeeze bars for valid range — Impulse Body Threshold (default 0.8): breakout candle body ≥ ATR × this value — Prevent Overlap (default On): no overlapping range boxes 🎯 Targets: — SL ATR Buffer (default 0.5): extra ATR distance beyond range boundary for stop — TP1 R:R (default 1.0) / TP2 R:R (default 2.0) / TP3 R:R (default 3.0): risk-to-reward multiples 🔍 Filters: — Volume Filter (default Off): breakout volume > SMA(20) × multiplier (default 1.5×) — HTF Trend Filter (default Off): align breakouts with SMA(50) trend on HTF (default Daily) 🎨 Visual: — Range boxes, resistance/support zones, centerline (all toggleable) — Breakout signals, target levels, close labels (all toggleable) — Squeeze background highlight (default Off) — Configurable label sizes (signal, target, close — separate controls) — Auto / Dark / Light theme 🔔 Alerts — 🟢 BULL BREAKOUT / 🔴 BEAR BREAKOUT — ticker, price, SL, TP1, timeframe — ✅ TP1 HIT / TP2 HIT / TP3 HIT — trade progress — ✅ TP3 TRADE CLOSED — full win with P&L — ❌ SL TRADE CLOSED — stopped out with P&L All support plain text and JSON webhook format. Bar-close confirmed. ⚠️ IMPORTANT NOTES — 🚫 No repainting. All breakout signals require barstate.isconfirmed. Range boxes are created on the bar after the squeeze ends (confirmed transition). TP/SL hit detection uses first-touch logic (current bar vs previous bar comparison). HTF filter uses + lookahead_on for non-repainting. A warmup period (max of squeeze length and 50 bars) prevents signals during insufficient data. — 📐 The dual-engine squeeze is not a standard Bollinger/Keltner squeeze . It combines BB Width percentile compression with ATR contraction ratio — both must agree. This is stricter than a single-measure approach and produces fewer but higher-quality consolidation zones. — ⚖️ The trade is tracked until TP3 or SL — there is no partial close logic. TP1 and TP2 are marked as they're hit (for visual reference and alerts) but the trade remains open until the final outcome. You can manage partial closes manually using the TP1/TP2 alerts. — 📊 Signal strength reflects how many quality factors aligned at the time of breakout. A "Strong" signal had volume surge, HTF alignment, AND extended squeeze — but strength does not predict outcome. — 🔄 If a new breakout occurs while a trade is active, the previous trade is replaced. The indicator tracks one trade at a time. — 📏 Range box boundaries are adaptive Donchian — they expand during the squeeze to capture every high and low. They do not contract. This means the range can be wider than the BB Width suggests if a spike occurred during the squeeze. — 🛠️ This is a breakout detection and target visualization tool , not an automated trading bot. It identifies squeeze zones, confirms breakouts, and places structural targets — trade decisions remain yours. — 🌐 Works on all markets and timeframes. Volume filter auto-adapts to instruments without volume data.
Indicador Pine Script®
por WillyAlgoTrader
22
VWAP Z-Score & Exhaustion Matrix [AlgoPoint]AlgoPoint VWAP Z-Score & Order Flow Matrix Overview The AlgoPoint VWAP Z-Score Matrix is a quantitative oscillator designed to identify statistical extremes in price action relative to a dynamic volume-weighted baseline. By combining a Rolling VWAP, Volume-Weighted Standard Deviation, Volume Exhaustion, and an Intrabar Order Flow Delta proxy, this indicator provides a comprehensive framework for modeling mean-reversion (fade) setups. Mathematical Core & Components This indicator relies on three primary quantitative mechanics:Rolling VWAP & Z-Score: Unlike a traditional anchored VWAP that resets daily, this script calculates a Rolling VWAP over a user-defined lookback window. The standard deviation is volume-weighted, ensuring that high-volume nodes have a proportional impact on the variance. The Z-Score normalizes the price deviation from the VWAP, creating a 0-centered oscillator. - Volume Exhaustion: The script compares the current bar's volume against a Simple Moving Average (SMA) of volume. If the current volume is lower than the average, it flags a state of "exhaustion," indicating a potential deceleration in the current price push. - Order Flow Delta Proxy: To evaluate microstructure without requiring lower timeframe data, the indicator estimates intrabar buying and selling pressure. It apportions the total bar volume into "Up Volume" and "Down Volume" based on where the close occurs relative to the high-low range. The net difference establishes the Volume Delta. Visual Elements & Interpretation Dual-Gradient Bar Coloring: The main chart candles and the oscillator line are dynamically colored using a dual-gradient system. The color smoothly transitions from a neutral gray at the mean (0) to green at negative extremes and red at positive extremes. Reference Thresholds: Default extreme limits are set at +2.5 and -2.5 Z-Scores.Exhaustion Nodes: Circular nodes appear on the oscillator line when the price reaches an extreme Z-Score simultaneously with volume exhaustion. Quant Dashboard: A real-time table displaying the current Z-Score, Volume Status (Active/Exhausted), Order Flow Delta (Net Buyers/Sellers), and the absolute Rolling VWAP price. Signal Generation "Fade Long" and "Fade Short" labels are generated only when all structural conditions are met and the bar is confirmed (barstate.isconfirmed) Fade Short: Z-Score > Upper Threshold AND Volume is Exhausted AND Delta is Negative (Sellers taking control). Fade Long: Z-Score < Lower Threshold AND Volume is Exhausted AND Delta is Positive (Buyers taking control). Alerts The indicator includes standard alert conditions and dynamic JSON webhook strings for automated trading systems, providing real-time data on the asset, price, Z-Score, and Delta values upon signal generation.
Indicador Pine Script®
por Iamalala
4
Adaptive Momentum Fusion [WillyAlgoTrader]📡 Adaptive Momentum Fusion is a separate-pane oscillator that replaces the fixed EMAs inside a standard MACD with selectable adaptive moving averages — six different adaptation engines that each respond to a different market dimension (efficiency, volatility, fractal structure, momentum, volume, or a weighted composite of all five). The oscillator line and signal line are then processed through Jurik-style smoothing to reduce jitter without adding lag. The result is a MACD-like oscillator where the core moving averages automatically adjust their speed to current market conditions, producing cleaner crossovers, more meaningful histogram readings, and built-in divergence detection. A standard MACD uses fixed-length EMAs (typically 12/26/9). This means the same smoothing is applied whether the market is trending strongly, ranging sideways, experiencing a volatility spike, or consolidating. The result: late crossovers in trends, whipsaws in ranges, and false divergences during choppy periods. This indicator solves the problem at the source — the moving averages themselves. Instead of fixed EMAs, each adaptation engine dynamically adjusts the smoothing constant (alpha) on every bar based on a real-time market measurement. In a strong trend, the Efficiency engine detects high directional efficiency and increases alpha → faster MA → earlier crossover. In a range, efficiency drops and alpha decreases → slower MA → fewer whipsaws. Each engine uses a different measurement to achieve this adaptation, and the user selects which dimension matters most for their market. 🧩 WHY THESE COMPONENTS WORK TOGETHER A MACD with adaptive MAs alone would still produce a noisy signal line (the EMA of the oscillator). Adding adaptation to the base MAs but keeping a fixed EMA for the signal line creates a mismatch: the oscillator adapts but the signal doesn't, causing crossover lag to reappear at the signal level. This indicator addresses the full signal chain: Adaptive fast MA → Adaptive slow MA → Oscillator (MACD or PPO) → Jurik-smoothed signal line → 4-state histogram → Divergence scanner The adaptive MAs eliminate the fixed-speed problem at the source. The MACD/PPO dual mode lets you choose between absolute (price-scaled) and percentage (normalized) output. The Jurik smoother replaces the standard signal EMA with a 3-stage filter that reduces jitter while preserving crossover timing — critical because adaptive oscillators produce more variable readings than fixed ones. The 4-state histogram (accelerating/decelerating × bullish/bearish) quantifies momentum acceleration, not just direction. And the divergence scanner works on the adaptive oscillator itself, which produces more reliable pivots than a fixed MACD because the adaptive MAs have already filtered out noise-driven fluctuations. Removing the adaptive engines returns you to a standard MACD. Removing the Jurik smoother reintroduces signal line jitter that the adaptive engines amplify. Removing the histogram states loses momentum acceleration information. The full pipeline produces cleaner signals than any subset. 🔍 WHAT MAKES IT ORIGINAL 1️⃣ Six selectable adaptation engines. Each engine computes a dynamic smoothing constant (alpha) that controls how fast the moving average reacts. All engines feed into the same adaptive EMA core: result = alpha × source + (1 − alpha) × result . The difference is how alpha is calculated: Efficiency (Kaufman AMA): Computes the Efficiency Ratio: ER = |price − price | / sum(|price − price |, N). ER ranges from 0 (pure chop — price moves a lot bar-to-bar but goes nowhere net) to 1 (pure trend — every bar moves in the same direction). The smoothing constant: sc = (ER × (fastSc − slowSc) + slowSc)², where fastSc = 2/3, slowSc = 2/31. This is the classic Kaufman Adaptive Moving Average approach. Best all-around engine. Volatility (ATR-based): Computes volRatio = ATR(len) / SMA(ATR, len×2). When current volatility exceeds its average (ratio > 1), alpha increases → MA speeds up to track the expanding price action. When volatility contracts (ratio < 1), alpha decreases → MA slows down to avoid noise. Alpha = baseAlpha × volRatio, clamped to . Best for instruments with distinct volatility regimes (crypto, commodities). Fractal (Hurst-inspired): Estimates the fractal dimension of the price series using rescaled range analysis: the full-range is compared to the sum of two half-ranges. fracDim = 1 + log(sumHalf) / log(2 × rangeFull). A fractal dimension near 1.0 indicates trending behavior (smooth), near 2.0 indicates mean-reverting (rough). Alpha = exp(−4.6 × (fracDim − 1)), which maps: fracDim ≈ 1.0 → alpha ≈ 1.0 (fast, trending), fracDim ≈ 2.0 → alpha ≈ 0.01 (slow, ranging). Best for detecting regime changes between trending and mean-reverting markets. Momentum (ROC-based): Computes the Rate of Change normalized against its recent maximum: norm = |ROC| / highest(|ROC|, len×2). When momentum is strong relative to recent history, alpha increases. Alpha = baseAlpha + norm × (1 − baseAlpha) × 0.5. This makes the MA react faster during breakouts and momentum surges while staying smooth during low-momentum drift. Best for breakout-oriented strategies. Volume: Computes volRatio = volume / SMA(volume, len). When volume exceeds its average (institutional participation), the MA speeds up. Alpha = baseAlpha × √(volRatio). The square root prevents extreme volume spikes from making the MA too reactive. Auto-disabled on instruments without volume data (forex) — falls back to baseAlpha. Best for stocks and crypto where volume confirms moves. Composite (weighted blend): Runs all five engines simultaneously and blends the results: with volume = 30% Efficiency + 20% Volatility + 20% Fractal + 15% Momentum + 15% Volume. Without volume = 35% Efficiency + 25% Volatility + 25% Fractal + 15% Momentum. This produces the most robust adaptation but is slightly slower because it averages five different smoothing perspectives. Best for users who don't want to choose a single engine. 2️⃣ Jurik-style signal line smoothing. The standard MACD signal line is a simple EMA of the oscillator. This indicator replaces it with a 3-stage Jurik-inspired filter: beta = 0.45 × (len − 1) / (0.45 × (len − 1) + 2) alphaJ = beta³ e0 = (1 − alphaJ) × source + alphaJ × e0 e1 = (source − e0) × (1 − beta) + beta × e1 e2 = (e0 + phase × e1 − e2 ) × (1 − alphaJ)² + alphaJ² × e2 The three stages progressively remove jitter while maintaining phase alignment. The phase parameter (Jitter Reduction, default 0.7) controls how much additional smoothing is applied: 0.0 = minimal smoothing (fast but noisy), 1.0 = maximum smoothing (smooth but slightly more lag). This is particularly important for adaptive oscillators because the variable-speed MAs produce a more erratic oscillator line than fixed EMAs — the Jurik filter absorbs this variability at the signal level. 3️⃣ MACD/PPO dual output mode. — MACD mode : oscillator = fastMA − slowMA (absolute difference, price-scaled). Readings scale with instrument price — useful for single-instrument analysis. — PPO mode : oscillator = (fastMA − slowMA) / slowMA × 100 (percentage difference, normalized). Readings are comparable across instruments and time — useful for scanning, multi-market analysis, or consistent threshold settings. 4️⃣ 4-state momentum histogram. The histogram (oscillator − signal) is classified into four states based on value and direction of change: — 🟢 Accelerating bullish : histogram > 0 AND rising (momentum strengthening) — 🟢 Decelerating bullish : histogram > 0 AND falling (momentum fading, potential reversal ahead) — 🔴 Accelerating bearish : histogram < 0 AND falling (selling pressure increasing) — 🔴 Decelerating bearish : histogram < 0 AND rising (selling pressure easing, potential bounce) Each state has a distinct color intensity: accelerating = fully saturated, decelerating = faded. This provides immediate visual recognition of whether momentum is building or exhausting — the most actionable information from a histogram. 5️⃣ Divergence detection with adaptive oscillator. The indicator scans for regular divergences between price and the adaptive oscillator: — Regular Bullish Divergence : price makes a lower low, but the oscillator makes a higher low → selling pressure is weakening despite lower prices → potential reversal up — Regular Bearish Divergence : price makes a higher high, but the oscillator makes a lower high → buying pressure is weakening despite higher prices → potential reversal down Pivots are detected using a custom function with configurable lookback (default 30 bars) and a fixed right-bar confirmation of 5 bars. Divergences are labeled on the oscillator pane and optionally drawn as connecting lines. The divergence state persists in the dashboard for 20 bars after detection, then decays. Divergences detected on the adaptive oscillator are more reliable than on a standard MACD because the adaptive MAs have already filtered regime-inappropriate noise — the pivots in the oscillator correspond to genuine momentum shifts, not noise-driven wiggles. 6️⃣ Zero-line cross signals. When enabled, the indicator marks when the oscillator crosses the zero line — which corresponds to the fast adaptive MA crossing the slow adaptive MA. In MACD terms, this is the equivalent of the "MACD crossing zero." Because the MAs are adaptive, these crossovers occur at more structurally meaningful points than with fixed EMAs. 7️⃣ Signal strength scoring (0–100). Each bar's histogram absolute value is normalized against its recent maximum over 50 bars: strength = |histogram| / highest(|histogram|, 50) × 100. This provides a relative measure: 100 = histogram is at its strongest in the last 50 bars, 0 = no momentum. Classified as Strong (≥ 70), Medium (≥ 40), Weak (< 40). Displayed in the dashboard. ⚙️ HOW IT WORKS — CALCULATION FLOW Step 1 — Engine selection: The selected adaptation engine computes a dynamic alpha value on each bar based on its specific market measurement (efficiency ratio, ATR ratio, fractal dimension, ROC normalization, volume ratio, or composite blend). Step 2 — Adaptive MA calculation: The fast MA and slow MA are each computed using the adaptive EMA formula: result = alpha × source + (1 − alpha) × result . The same engine is used for both, with different length parameters (fast = default 8, slow = default 21). Step 3 — Oscillator: MACD mode: osc = fastMA − slowMA. PPO mode: osc = (fastMA − slowMA) / slowMA × 100. Step 4 — Signal line: The oscillator is passed through the Jurik 3-stage filter with the configured signal length (default 7) and jitter reduction factor (default 0.7). Step 5 — Histogram: hist = oscillator − signal. Classified into 4 states (accelerating/decelerating × bullish/bearish) based on sign and direction of change. Step 6 — Divergence scan: Custom pivot detection identifies local highs and lows in both the oscillator and price. When a new pivot is found, it's compared to the previous pivot to check for divergence conditions (price lower low + osc higher low, or price higher high + osc lower high). Step 7 — Signals: Crossovers (oscillator crossing signal line) and zero-line crosses are detected. All signals require barstate.isconfirmed + warmup check. 📖 HOW TO USE 🎯 Quick start: 1. Add the indicator — the adaptive oscillator appears in a separate pane 2. Select an adaptation engine matching your market (Efficiency for general use) 3. Green line above red = bullish momentum, below = bearish 4. Histogram bars show momentum acceleration (bright) vs deceleration (faded) 5. Divergence labels mark potential reversals 👁️ Reading the pane: — 🟢 Green oscillator line above signal line = bullish momentum — 🔴 Red oscillator line below signal line = bearish momentum — 🟢 Bright green histogram = accelerating bullish momentum — 🟢 Faded green histogram = decelerating bullish (momentum fading) — 🔴 Bright red histogram = accelerating bearish momentum — 🔴 Faded red histogram = decelerating bearish (selling easing) — ▲ label = buy crossover signal (oscillator crosses above signal) — ▼ label = sell crossover signal — ● dot on zero line = zero-line cross — "Bull Div" / "Bear Div" labels = detected divergences 🔧 Engine selection guide: — Efficiency : best default for most markets — adapts to trending vs ranging — Volatility : best for instruments with clear vol regimes (crypto, commodities) — Fractal : best for detecting regime shifts (trending ↔ mean-reverting) — Momentum : best for breakout strategies — speeds up on strong moves — Volume : best for stocks/crypto where volume confirms participation — Composite : most robust — blends all dimensions, good when unsure 🔧 Tuning guide: — Too many whipsaws: increase Slow Length, increase Signal Length, increase Jitter Reduction — Signals too late: decrease Fast/Slow Length, decrease Signal Length, decrease Jitter Reduction — Histogram too noisy: increase Jitter Reduction toward 0.8–1.0 — Divergences too frequent: increase Divergence Lookback (40–60) — Cross-market comparison: switch to PPO mode for normalized output ⚙️ KEY SETTINGS REFERENCE ⚙️ Main: — Adaptation Engine (default Efficiency): Efficiency / Volatility / Fractal / Momentum / Volume / Composite — Fast Length (default 8): fast adaptive MA period — Slow Length (default 21): slow adaptive MA period — Signal Length (default 7): Jurik signal smoothing period — Output Mode (default MACD): MACD (absolute) or PPO (percentage) 🔍 Filters: — Detect Divergences (default On): scan for regular divergences — Divergence Lookback (default 30): pivot search depth — Zero Line Cross Signals (default On): mark zero crossings 🔧 Advanced: — Jitter Reduction (default 0.7): Jurik phase parameter (0.0–1.0) — Auto / Dark / Light theme 📊 Dashboard — Trend: oscillator vs signal line direction (Bullish / Bearish / Neutral) — Signal: last crossover (BUY / SELL / Wait) — Strength: histogram normalized to 50-bar max (Strong / Medium / Weak with %) — Momentum: 4-state acceleration (Accel ▲ / Decel ▽ / Accel ▼ / Decel △) — Divergence: current divergence state (Bull Div / Bear Div / None) — Engine / TF: selected engine and timeframe — Version 🔔 Alerts — 🟢 BUY / 🔴 SELL — oscillator-signal crossover (ticker, price, timeframe, engine) — 🟡 ZERO BULL CROSS / ZERO BEAR CROSS — zero-line crossing — 🔵 BULL DIVERGENCE / BEAR DIVERGENCE — detected divergence All support plain text and JSON webhook format. Bar-close confirmed. ⚠️ IMPORTANT NOTES — 🚫 No repainting. All signals and divergences require barstate.isconfirmed. A warmup period (2× slow length, minimum 50 bars) prevents signals during insufficient data. The adaptive MAs are deterministic — once a bar closes, the MA value for that bar never changes. — 📐 This is a separate-pane oscillator, not an overlay. It displays in its own pane below the chart. The oscillator values are momentum readings, not price levels. Use it alongside your chart for confluence, not as a standalone trading system. — ⚖️ The six engines produce different signals on the same data . Efficiency and Composite tend to produce the most similar results. Fractal can diverge significantly during regime transitions. Volume engine auto-falls back to base alpha on instruments without volume data. — 📊 Signal strength is relative to recent 50 bars , not absolute. A "Strong" reading during a low-volatility week may be weaker in absolute terms than a "Weak" reading during a high-volatility week. — 🔄 Divergences use a 5-bar right confirmation — they appear 5 bars after the actual pivot. This delay is inherent to pivot detection and cannot be eliminated without introducing false positives. — 📏 PPO mode normalizes the output as a percentage, making threshold settings (e.g., "divergence when oscillator > 2") comparable across instruments. MACD mode values scale with price — a reading of 5.0 on a $100 stock is different from 5.0 on a $50,000 BTC chart. — 🛠️ This is a momentum analysis tool , not an automated trading bot. It measures and visualizes adaptive momentum — trade decisions remain yours. — 🌐 Works on all markets and timeframes. Volume engine auto-adapts to available data.
Indicador Pine Script®
por WillyAlgoTrader
12
EMA Crossover Pro + Dynamic Targets + Live Dashboard with Time ETA Method — choose between three modes: ATR-Based — divides distance to target by the current ATR value. More stable since ATR reflects actual volatility. Linear Velocity — divides distance by the average absolute price move per bar over the last N bars. More responsive to recent momentum. Both — shows both estimates side by side in the dashboard. Velocity Lookback — how many bars back to measure average speed (default 20). Show ETA labels on chart — toggles floating labels to the right of each target line. Dashboard additions (rows 9–13): A header row showing ⏱ ETA TO TARGET with the active method. One row per target (TG1–TG4) showing: Human-readable time estimate: < 1 min / ~45 min / ~2h 30m / ~1d 4h Bar count in parentheses: (12 bars) Percentage distance remaining: (1.23% away) Once a target is hit it shows ✅ HIT in gray. On-chart labels: small navy labels appear just to the right of each un-hit target line showing the ETA inline. Note: These are statistical estimates based on recent volatility/speed — not predictions. Strong trend moves will arrive faster, consolidations slower. Use them as a rough waiting-time guide rather than a guarantee.
Indicador Pine Script®
por demantprasad
CUSUM Trend [AlgoPoint]The CUSUM Trend by AlgoPoint brings hedge-fund-level quantitative analysis directly to your charts. While standard moving averages suffer from lag and fakeouts, this script utilizes an advanced Cumulative Sum (CUSUM) algorithm, deeply re-engineered with adaptive volatility and volume-weighted metrics to identify true market regimes. It is designed to protect traders from choppy markets and explicitly capture high-probability, volume-backed trend breakouts before they become obvious to the retail crowd. 🧠 Under the Hood: The Quant Mechanics Instead of a basic price deviation model, the CUSUM Trend operates on four advanced pillars: - Zero-Lag Kernel (Ehlers SuperSmoother): We replaced traditional MAs with John Ehlers' SuperSmoother filter to establish a mathematically zero-lag baseline. - Volume-Weighted Residuals: Price deviations (residuals) only build up the CUSUM pressure pools if they are backed by institutional volume. Low-volume spikes are treated as noise and explicitly filtered out. - Fractal Dimension (Adaptive Thresholds): By using a proxy for the Hurst Exponent, the engine "reads" the market state. In choppy conditions, the bands expand defensively to prevent fakeouts. In trending conditions, they tighten aggressively. - Asymmetric Volatility: The algorithm calculates upside and downside variance independently, recognizing that market drops are often much sharper than rallies. 📊 How to Read the Chart - The Dynamic Trend Cloud: The asymmetric bands represent the institutional pressure thresholds. When price breaks and confirms outside this zone, a regime change (Bull/Bear trend) is triggered. - Gradient Candles: Candle colors dynamically shift based on the built-up CUSUM pressure. Bright green/red indicates extreme breakout momentum, while faded colors represent a stable trend or a ranging market. - Trailing Stop: Once a trend is established, the opposite side of the threshold acts as a dynamic trailing stop line, allowing you to ride the trend to its mathematical exhaustion. - Hybrid Dashboard: Monitor the internal breakout pressure, fractal regime, and exact trailing stop value in real-time without cluttering your main view. ⚙️ How to Use It - Sensitivity Profiles: Choose between Fast (Day Trade), Balanced (Swing), or Slow (Trend) in the settings. The engine automatically recalculates all internal variance and fractal thresholds based on your choice. - Automation Ready: Fully compatible with webhook automation (3Commas, PineConnector, etc.) via dynamic JSON alerts triggering on confirmed regime breakouts. Disclaimer: This indicator is for educational and analytical purposes only. Past performance is not indicative of future results.
Indicador Pine Script®
por Iamalala
5
StealthTrail SuperTrend [WillyAlgoTrader]📡 StealthTrail SuperTrend is an overlay indicator that takes the classic SuperTrend concept and adds five layers of noise reduction: an adaptive multiplier that scales bands to current volatility, a flip cushion that requires price to push beyond the band by a configurable ATR distance before confirming a trend change, a cooldown timer that enforces a minimum gap between flips, an RSI momentum filter that blocks trend changes without directional confirmation, and a composite trend strength score (0–100) that quantifies how committed the current trend is. The result is a SuperTrend that stays in trends longer, flips less often in chop, and gives you a real-time confidence reading on every trend leg. 🧩 WHY THESE COMPONENTS WORK TOGETHER The standard SuperTrend has one well-known problem: whipsaws. In ranging or choppy markets, price repeatedly crosses the band boundary, triggering rapid bullish→bearish→bullish flips that produce losing signals. The root causes are: 1. Fixed multiplier — the band width doesn't adapt when volatility contracts or expands, so the same multiplier is too tight in high-vol and too wide in low-vol 2. Instant flip — a single close beyond the band triggers a trend change, even if it's a minor wick-driven overshoot 3. No recovery time — the indicator can flip back on the very next bar, creating same-bar or next-bar whipsaws 4. No momentum context — the flip happens regardless of whether momentum actually supports the new direction StealthTrail addresses each root cause with a dedicated mechanism: Adaptive multiplier → solves #1 : bands automatically widen when ATR is above its average (high volatility) and tighten when below (low volatility), keeping the band distance proportional to current market conditions. Flip cushion → solves #2 : price must close beyond the band by an additional cushion (configurable fraction of ATR) before the flip is accepted, filtering out marginal crossovers. Cooldown timer → solves #3 : after a flip, the indicator ignores further flip attempts for N bars (default 3), preventing rapid back-and-forth in chop. Momentum filter → solves #4 : a bullish flip requires RSI above a threshold, a bearish flip requires RSI below the symmetric threshold, confirming that momentum actually supports the direction change. Trend strength scoring → provides context : combines price distance from band + RSI alignment into a 0–100 score, so you know whether the current trend is strong, fading, or about to flip. These five mechanisms work as a pipeline: the adaptive multiplier sets the right band width → the cushion prevents marginal crossovers → the cooldown prevents rapid reversals → the momentum filter confirms directional support → and the strength score tells you how committed the trend is. Removing any one layer reintroduces the specific whipsaw pattern it was designed to prevent. 🔍 WHAT MAKES IT ORIGINAL 1️⃣ Adaptive volatility multiplier. Instead of using a fixed ATR multiplier (classic SuperTrend), StealthTrail scales the multiplier dynamically: adaptiveMult = baseMultiplier × (currentATR / SMA(ATR, adaptationPeriod)) Where currentATR = ta.atr(atrLength), and SMA(ATR) is the volatility baseline over the adaptation smoothing period (default 55 bars). The ratio currentATR / averageATR measures whether volatility is currently above (ratio > 1.0) or below (ratio < 1.0) its recent norm. The adaptive multiplier is clamped between configurable min (default 1.0) and max (default 5.0) to prevent extreme values. When volatility spikes (e.g., news event), the multiplier increases → bands widen → the trend doesn't flip on a volatility-driven spike. When volatility compresses (consolidation), the multiplier decreases → bands tighten → the indicator catches the breakout earlier. This can be toggled off for classic fixed-multiplier behavior. 2️⃣ Flip cushion — requires extra ATR distance beyond the band. A standard SuperTrend flips the moment close crosses the band. StealthTrail requires: Bullish flip: close > upperBand + cushion × ATR Bearish flip: close < lowerBand − cushion × ATR The cushion (default 0.15× ATR) creates a dead zone around the band boundary. Price must push meaningfully beyond the band — not just touch it — before a flip is accepted. This single mechanism eliminates a large portion of marginal crossover whipsaws where price briefly clips the band before returning. Setting the cushion to 0.0 restores classic SuperTrend behavior (flip exactly at the band). 3️⃣ Signal cooldown timer. After every confirmed trend flip, a counter starts. No new flip can occur for N bars (default 3). This prevents the most destructive whipsaw pattern: a bearish flip immediately followed by a bullish flip on the next bar (or vice versa), which generates two consecutive losing signals. The cooldown is tracked as barsSinceFlip, incremented each bar, and checked before any flip is processed. Only when barsSinceFlip ≥ cooldownInput can a new flip occur. This is independent of the cushion — both must pass. 4️⃣ RSI momentum filter. On every raw trend flip (band crossed + cushion passed + cooldown passed), an additional RSI check is applied: Bullish flip requires: RSI(rsiLength) ≥ rsiThreshold (default 45) Bearish flip requires: RSI(rsiLength) ≤ (100 − rsiThreshold) = 55 This is deliberately asymmetric around the center by design (threshold 45, not 50): a bullish flip only needs RSI ≥ 45 (slightly below center), meaning it passes unless momentum is actively bearish. A bearish flip only needs RSI ≤ 55. This permissive threshold blocks the worst counter-momentum flips without being so strict that it delays legitimate trend changes. When the filter blocks a flip, the trend direction does not change and the band continues ratcheting in the original direction. An optional "Show Filtered Flips" setting displays a muted dot where a flip was blocked — useful for understanding filter behavior. 5️⃣ Composite trend strength score (0–100). On every bar, a strength score is calculated from two components: Distance score (0–50): How far price is from the SuperTrend band, measured in ATR units: distScore = min(|close − band| / ATR × 20, 50) A large distance means price is well away from the band — the trend has room before a potential flip. Momentum score (0–50): How well RSI aligns with the current trend direction: For bullish: momScore = min(max(RSI − 50, 0), 50) For bearish: momScore = min(max(50 − RSI, 0), 50) RSI reading that confirms the trend direction contributes up to 50 points. Total: strength = round(min(distScore + momScore, 100)) Classification: Strong ≥ 70, Medium ≥ 40, Weak < 40. Displayed in the dashboard and included in alert messages. This gives you a real-time confidence reading: a Strong reading means price is far from the band with confirming momentum — the trend is well-established. A Weak reading means price is near the band or momentum is fading — a flip may be imminent. 6️⃣ Filtered flip visualization. When "Show Filtered Flips" is enabled, a muted gray dot appears on the band at every point where a raw flip occurred but was blocked by a filter (momentum or volume). This is a transparency feature: instead of silently suppressing signals, the indicator shows you exactly where it intervened and what it filtered out. You can evaluate whether the filter saved you from a bad signal or delayed a good one. 7️⃣ Gradient fill between price and band. The space between close and the SuperTrend band is filled with a directional gradient: bullish trends fade from green (near band) to transparent (near price), bearish trends fade from red to transparent. The gradient uses fill() with top/bottom color mapping — the visual intensity naturally increases as the band is further from price, creating an intuitive "strength of trend" visual without needing to read the dashboard. ⚙️ HOW IT WORKS — CALCULATION FLOW Step 1 — ATR calculation: ta.atr(atrLength) with a high-low fallback for early bars where ATR is unavailable. Step 2 — Adaptive multiplier: If adaptive mode is on: multiplier = baseMultiplier × (ATR / SMA(ATR, adaptSmoothing)), clamped to . If off: multiplier = baseMultiplier (fixed). Step 3 — Band calculation: upperBand = hl2 + multiplier × ATR. lowerBand = hl2 − multiplier × ATR. Bands are calculated from hl2 (midpoint) for symmetry. Step 4 — Band ratcheting: In an uptrend, the lower band can only rise — it is set to max(current_lowerBand, previous_band). In a downtrend, the upper band can only fall — min(current_upperBand, previous_band). This ratcheting prevents the band from retreating during a trend, which would prematurely trigger a flip. Step 5 — Flip detection: In an uptrend: if close < band − cushion × ATR AND barsSinceFlip ≥ cooldown → raw bearish flip. In a downtrend: if close > band + cushion × ATR AND barsSinceFlip ≥ cooldown → raw bullish flip. On flip, the band resets to the opposite band value and barsSinceFlip resets to 0. Step 6 — Filter gate: If RSI momentum filter is on: bullish flip requires RSI ≥ threshold, bearish requires RSI ≤ (100 − threshold). If volume filter is on: volume must exceed SMA(volume, 20) × multiplier. Both must pass for the flip to become a confirmed signal. If either fails, the flip is recorded as "filtered" (visualizable) but the trend direction reverts — no signal is emitted. Step 7 — Signal emission: Confirmed flip + barstate.isconfirmed + warmup check → Buy (▲) or Sell (▼) label appears. Strength score is calculated and updated. 📖 HOW TO USE 🎯 Quick start: 1. Add the indicator — the adaptive SuperTrend band appears immediately 2. Green band = bullish trend, red band = bearish trend 3. ▲ label below bar = confirmed buy (trend flipped bullish through all filters) 4. ▼ label above bar = confirmed sell (trend flipped bearish) 5. Check dashboard for strength score — Strong trends are more reliable 👁️ Reading the chart: — 🟢 Green step-line = SuperTrend band in bullish mode (following lower band) — 🔴 Red step-line = SuperTrend band in bearish mode (following upper band) — 🟢 Large green dot on band = confirmed bullish flip — 🔴 Large red dot on band = confirmed bearish flip — ⚫ Gray dot on band (optional) = raw flip that was blocked by a filter — 🟩🟥 Gradient fill = visual trend strength (denser = further from band = stronger trend) — Background tint (optional) = overall trend direction shading 📊 Dashboard fields: — Trend: current direction (Bullish / Bearish) — Signal: last confirmed signal with bars elapsed — Strength: 0–100 score with classification (Strong / Medium / Weak) — Multiplier: current adaptive multiplier value (e.g., 2.83×) — RSI: current RSI reading — Timeframe and version 🔧 Tuning guide: — Too many whipsaws: increase Flip Cushion (0.2–0.3), increase Cooldown (4–6), enable Momentum Filter — Signals too late: decrease Flip Cushion (0.05–0.10), decrease Cooldown (1–2), lower Base Multiplier — Bands too wide in low-vol: decrease Min Adaptive Mult (0.8), decrease Adaptation Smoothing (30–40) — Bands too tight in high-vol: increase Max Adaptive Mult (5.0–6.0), increase Base Multiplier — Ranging/choppy market: enable Momentum Filter, increase Cooldown, increase Cushion — all three work together to suppress chop signals — Strong trending market: decrease Cushion (0.05), decrease Cooldown (1), disable Momentum Filter — let the indicator react faster to trend continuation ⚙️ KEY SETTINGS REFERENCE ⚙️ Main: — ATR Length (default 13): volatility measurement period — Base Multiplier (default 2.5): base ATR multiplier for band width — Adaptive Multiplier (default On): scale bands by current/average ATR ratio — Adaptation Smoothing (default 55): SMA lookback for ATR baseline 🔍 Filters: — Flip Cushion (default 0.15× ATR): extra distance beyond band required for flip — Signal Cooldown (default 3 bars): minimum gap between flips — Momentum Filter (default On): RSI confirmation for trend changes — RSI Length (default 13) / RSI Threshold (default 45): momentum filter parameters — Volume Filter (default Off): above-average volume confirmation 🔧 Advanced: — Min Adaptive Mult (default 1.0): floor for adaptive scaling — Max Adaptive Mult (default 5.0): ceiling for adaptive scaling 🎨 Visual: — Band line, gradient fill, filtered flip dots, trend background (all toggleable) — Auto / Dark / Light theme 🔔 Alerts — 🟢 BUY — ticker, price, band level, timeframe, strength score — 🔴 SELL — same fields Both support plain text and JSON webhook format. Bar-close confirmed, filter-gated, cooldown-enforced. ⚠️ IMPORTANT NOTES — 🚫 No repainting. All signals require barstate.isconfirmed. Band ratcheting is deterministic — the band value on a closed bar never changes retroactively. A warmup period (max of ATR length, adaptation smoothing, and 50 bars) prevents signals during insufficient data. — 📐 This is not a standard SuperTrend. The adaptive multiplier, flip cushion, cooldown, and momentum filter fundamentally change the signal generation logic. A classic SuperTrend flip would occur significantly earlier (or later, depending on volatility) than a StealthTrail flip — they are not interchangeable. — ⚖️ The flip cushion and cooldown work independently . Both must pass for a flip to occur. In chop, the cooldown may block a flip even after the cushion is satisfied, or the cushion may prevent a flip even after the cooldown expires. This dual-gate design is intentional. — 📊 Trend strength is a real-time reading , not a prediction. A strength of 85 means price is far from the band with confirming momentum right now — it does not predict how long the trend will continue. — 🔄 "Filtered Flips" (gray dots) show where a trend change would have occurred in a classic SuperTrend but was blocked by the momentum or volume filter. This transparency helps you understand the filter's impact and tune the threshold accordingly. — 📈 Volume filter auto-disables on instruments without volume data (many forex pairs). On these instruments, only the momentum filter, cushion, and cooldown provide noise reduction. — 🛠️ This is a trend-following signal tool , not an automated trading bot. It identifies trend direction, scores trend strength, and generates filtered signals — trade decisions remain yours. — 🌐 Works on all markets and timeframes. The adaptive multiplier self-calibrates to any instrument's volatility profile.
Indicador Pine Script®
por WillyAlgoTrader
14
Adaptive Momentum Classifier [WillyAlgoTrader]📡 Adaptive Momentum Classifier is an overlay indicator that evaluates four independent market dimensions — momentum, trend, volatility position, and money flow — ranks each one against its own historical distribution using percentile scoring, and combines them into a single composite score (0–100%) that drives signal generation. Signals fire only when the composite score crosses a threshold with minimum feature agreement across axes, passes through five independent filters, and is confirmed on bar close. The core idea: instead of using one indicator to generate signals, this tool treats four market dimensions as independent measurement axes, normalizes each to a uniform 0–1 scale via percentile ranking, weights and combines them into a consensus score, and then requires both the score threshold AND a minimum number of agreeing axes before allowing a signal. This multi-axis + agreement gate architecture filters out situations where a single strong reading (e.g., RSI spike) would trigger a false signal while the other dimensions disagree. 🧩 WHY THESE COMPONENTS WORK TOGETHER Traditional signal generators face a fundamental problem: a single indicator measures one market dimension. RSI measures momentum speed but is blind to trend direction. MACD measures trend but ignores where price sits within its volatility envelope. Volume-based indicators measure flow but know nothing about price momentum. Using any one of these alone produces signals that ignore critical market context. Simply combining indicators with AND/OR logic (e.g., "buy when RSI > 50 AND MACD > 0") doesn't solve the deeper problem: the indicators are on different scales, have different distributions, and their raw values aren't comparable. RSI = 55 and MACD histogram = 0.002 both "lean bullish" but you can't meaningfully average them. This indicator solves both problems: Step 1 — Orthogonal axis design: Each axis measures a genuinely different market dimension. Momentum (how fast), Trend (which direction), Volatility Position (where within the range), Flow (where is money going). They are deliberately chosen to be as independent as possible. Step 2 — Percentile normalization: Each axis's raw value is ranked against its own recent history. "Is this RSI-ROC blend reading higher than 75% of the last 89 readings?" This converts every axis to a uniform 0–1 scale where 0.5 = median. Now all four axes are directly comparable and combinable. Step 3 — Weighted consensus: The four normalized scores are combined with weights (Trend 1.2×, Momentum 1.0×, Flow 1.0×, Volatility 0.8×) into a single composite score. The weighting reflects that trend conviction is slightly more predictive than raw momentum. Step 4 — Agreement gate: Even with a high composite score, the signal is blocked unless at least half the axes independently agree (each reading > 0.6 for bullish or < 0.4 for bearish). This prevents one extreme axis from dominating the composite and producing a false consensus. Step 5 — Filter stack: Five independent filters (trend alignment, volatility regime, volume, score acceleration, HTF bias) provide additional context gates. The signal only fires when all enabled filters pass simultaneously. No single component is useful alone. Percentile ranking without multiple axes just normalizes one indicator. Multiple axes without percentile ranking can't be meaningfully combined. A combined score without the agreement gate can be dominated by one outlier. And all of this without filters would still fire in unsuitable market conditions. The full pipeline is required. 🔍 WHAT MAKES IT ORIGINAL 1️⃣ Four-axis percentile scoring engine. Each axis is built from two sub-components blended together, then converted to a 0–1 percentile rank against the scoring lookback window (default 89 bars). The percentile function counts what fraction of historical values are below the current value — producing a uniform distribution with no dead zones (unlike z-score normalization which compresses values near the mean). Axis 1 — Momentum (weight 1.0): Sub-components: RSI(13) centered at 50, and ROC(9). Each is percentile-ranked independently, then blended 60% RSI + 40% ROC. RSI provides stable momentum reading, ROC provides faster reaction to price acceleration. The blend captures both speed (ROC) and sustained momentum (RSI) in a single axis. Axis 2 — Trend (weight 1.2): Sub-components: MACD histogram (12/26/9), and EMA slope normalized by ATR. EMA slope = (EMA − EMA ) / (ATR × 5), making it scale-independent across instruments. Each percentile-ranked, blended 60% MACD + 40% slope. MACD histogram captures momentum of the trend itself (acceleration), while EMA slope captures sustained directional movement. This axis receives the highest weight (1.2) because directional conviction is the strongest single predictor of continuation. Axis 3 — Volatility Position (weight 0.8): Sub-components: Bollinger %B (21-period, showing where price sits within the band envelope, 0 = lower band, 1 = upper band), and ATR expansion ratio (current ATR / SMA of ATR over lookback). Combined as: (BB%B − 0.5) × min(ATR_ratio, 2.5), then percentile-ranked. This creates a directional volatility signal: price at upper band during volatility expansion scores high (strong bullish breakout), price at upper band during contraction scores lower (potential mean-reversion). The ATR ratio is capped at 2.5 to prevent extreme volatility spikes from distorting the axis. Lower weight (0.8) reflects that volatility position is a confirming factor, not a primary driver. Axis 4 — Flow (weight 1.0, auto-disabled without volume): Sub-components: MFI(13) centered at 50, and OBV slope (smoothed OBV EMA(21), slope = (OBV_EMA − OBV_EMA ) / |OBV_EMA|). Each percentile-ranked, blended 50/50. MFI combines price and volume into a single money flow reading, OBV slope shows whether accumulation is accelerating or decelerating. On instruments without volume data (forex), this axis returns 0.5 (neutral) and its weight drops to 0, so the composite score is calculated from three axes only. 2️⃣ Composite score with symmetric thresholds. The four axes are combined: composite = (1.0 × momentum + 1.2 × trend + 0.8 × volatility_position + 1.0 × flow) / total_weight. Result is 0–1 where 0 = maximum bearish consensus, 0.5 = neutral, 1 = maximum bullish consensus. A buy signal fires when the composite crosses above the threshold (default 0.618). A sell signal fires when it crosses below (1 − threshold = 0.382). This creates symmetric entry conditions: the same strength of consensus is required for both directions. 3️⃣ Feature agreement gate. Independent of the composite score, each axis is evaluated for directional agreement: > 0.6 = bullish vote, < 0.4 = bearish vote, 0.4–0.6 = abstain. The agreement ratio = max(bull_votes, bear_votes) / active_axes. Signals require agreement ≥ 0.5 (at least half the axes independently confirming the same direction). This prevents false signals from composite score averaging: if momentum = 0.95 but trend = 0.3 and volatility = 0.4, the composite might cross the threshold but only 1/4 axes agree — signal is blocked. 4️⃣ Score acceleration filter. The rate of change of the composite score: acceleration = score − score . Signals require |acceleration| ≥ Min Score Acceleration (default 0.02). This filters out slow-drift crossovers where the score gradually creeps past the threshold without any decisive move — these typically represent noise, not genuine momentum shifts. Only fast, decisive threshold crosses produce signals. 5️⃣ Five-filter stack. Each filter is independently toggleable: — Trend Alignment (default On): price must be above EMA(50) for longs, below for shorts — prevents counter-trend entries — Volatility Regime (default On): ATR ratio must be between 0.4 and 3.0 — suppresses signals during dead markets (ATR < 40% of average) and crash conditions (ATR > 300% of average) — Volume Confirmation (default On): volume must exceed 80% of its 20-period SMA — confirms market participation. Auto-disabled on instruments without volume data — Score Acceleration (default 0.02): described above. Set to 0 to disable — Higher TF Bias (default disabled): when a timeframe is selected, price must be above/below EMA(21) on the higher timeframe for longs/shorts. Uses + lookahead_on for non-repainting HTF data 6️⃣ Direction lock — no consecutive same-direction signals. After a buy signal fires, the next signal can only be a sell (and vice versa). This prevents signal clustering where multiple buy signals fire in sequence during a strong trend — you get one entry per direction until the trend reverses. 7️⃣ Four sensitivity presets. Each preset overrides two parameters simultaneously: — Conservative : threshold 0.80, lookback 150 — requires very strong consensus over a long history, fewer but higher-conviction signals — Default : uses your manual settings (threshold 0.618, lookback 89) — Aggressive : threshold 0.60, lookback 60 — lower bar for signals, shorter history, faster adaptation — Scalping : threshold 0.55, lookback 40 — minimum consensus required, very short history, designed for 1–5M charts The lookback affects all four axes simultaneously (percentile ranking window), so the entire scoring engine adapts as a unit. 8️⃣ Dynamic trend band. A visual EMA ± 0.5× ATR band colored by the composite score: green (score > 55%), red (< 45%), yellow (neutral). This provides an at-a-glance trend context without needing to read the dashboard. The band width adapts to volatility automatically. 9️⃣ Signal strength classification. Each signal is classified based on the composite score at the moment of firing: Strong (score ≥ 85%), Medium (≥ 75%), Weak (< 75%). Displayed in the dashboard and available in alert messages. This helps you size positions or filter setups based on conviction level. ⚙️ HOW IT WORKS — CALCULATION FLOW Step 1 — Raw feature calculation: RSI(13), ROC(9), MACD(12/26/9) histogram, EMA slope (normalized by ATR), BB%B(21), ATR ratio, MFI(13), OBV slope — eight raw values computed from price and volume. Step 2 — Percentile ranking: Each raw value is ranked against its own history over the scoring lookback (default 89 bars). The pctRank function iterates through the lookback window and counts what fraction of past values are below the current value. Result: 0.0 (lower than all history) to 1.0 (higher than all history). This normalization is performed for each of the eight sub-components independently. Step 3 — Axis blending: Each pair of sub-components is blended into one axis score: momentum = 0.6 × pctRSI + 0.4 × pctROC, trend = 0.6 × pctMACD + 0.4 × pctSlope, volatility = pctVolPosition (single combined raw), flow = 0.5 × pctMFI + 0.5 × pctOBV. Step 4 — Weighted composite: composite = (1.0 × momentum + 1.2 × trend + 0.8 × volatility + 1.0 × flow) / total_weight. On instruments without volume: flow weight = 0, total_weight = 3.0 instead of 4.0. Step 5 — Threshold crossing: Buy triggers when composite crosses above the threshold (default 0.618) from below. Sell triggers when composite crosses below (1 − 0.618 = 0.382) from above. Both require barstate.isconfirmed. Step 6 — Agreement check: Each axis is independently classified as bullish (> 0.6), bearish (< 0.4), or neutral. At least 50% of active axes must agree with the signal direction. Step 7 — Filter stack: All five enabled filters must pass. Any failure blocks the signal. Step 8 — Direction lock: Signal must be opposite to the last confirmed signal. Step 9 — Emission: Buy (▲) or Sell (▼) label placed on the confirmed bar. 📖 HOW TO USE 🎯 Quick start: 1. Add the indicator to your chart 2. Select a sensitivity preset matching your style (or use Default) 3. The trend band immediately shows the current momentum bias (green/red/yellow) 4. Wait for a ▲ (buy) or ▼ (sell) label — check the dashboard for score and strength 5. Use the agreement ratio (e.g., 3/4) to confirm multi-axis consensus 👁️ Reading the chart: — 🟢 Green trend band = bullish momentum (score > 55%) — 🟡 Yellow trend band = neutral / transition zone — 🔴 Red trend band = bearish momentum (score < 45%) — 🟢 ▲ label below bar = confirmed buy signal — 🔴 ▼ label above bar = confirmed sell signal — Band width = current volatility (wider = more volatile) 📊 Dashboard fields: — Trend: current composite direction (Bullish / Bearish / Neutral) — Last Signal: most recent signal with bars elapsed — Strength: signal quality (Strong / Medium / Weak) — Score: current composite as percentage — Agreement: how many axes confirm (e.g., 3/4) — Volatility: ATR regime (High / Normal / Low) — TF and version 🔧 Tuning guide: — Too many signals: increase threshold (0.70–0.85), enable more filters, use Conservative preset — Too few signals: decrease threshold (0.55–0.60), reduce lookback (50–70), use Aggressive preset — Signals too late: shorten RSI/ROC/MACD lengths, reduce lookback — Too many false signals in ranging markets: enable ADX-aware Volatility Regime filter, increase Min Score Acceleration to 0.03–0.05 — Scalping 1–5M: use Scalping preset (threshold 0.55, lookback 40), lower filter aggressiveness — Swing 4H–1D: use Conservative preset (threshold 0.80, lookback 150), enable HTF bias filter ⚙️ KEY SETTINGS REFERENCE ⚙️ Main: — Sensitivity Preset (default Default): Conservative / Default / Aggressive / Scalping — Scoring Lookback (default 89): percentile ranking window — higher = more stable, lower = faster adaptation — Signal Threshold (default 0.618): minimum composite score for buy signals (sell = 1 − threshold) 📊 Feature Engine: — RSI Length (default 13) / ROC Length (default 9): momentum axis sub-components — MACD Fast/Slow/Signal (default 12/26/9): trend axis MACD — Bollinger Length (default 21): volatility position axis — MFI Length (default 13) / OBV Smooth (default 21): flow axis 🔍 Filters: — Trend Alignment (default On): EMA(34) trend direction gate — Volatility Regime (default On): ATR ratio 0.4–3.0 range gate — Volume Confirmation (default On): volume > 80% of 20-SMA — Min Score Acceleration (default 0.02): minimum speed of score change — Higher TF Bias (default Off): optional HTF EMA(21) alignment 🎨 Visual: — Trend band (EMA ± 0.5× ATR, scored coloring) — Background tint / Dynamic bar coloring (optional) — Auto / Dark / Light theme 🔔 Alerts — 🟢 BUY — ticker, price, timeframe, composite score — 🔴 SELL — same fields Both support plain text and JSON webhook format. Bar-close confirmed, direction-locked (no consecutive same-direction alerts). ⚠️ IMPORTANT NOTES — 🚫 No repainting. All signals require barstate.isconfirmed. HTF bias uses + lookahead_on. A warmup period (max of lookback, MACD slow period, and trend EMA length, minimum 50 bars) prevents signals during insufficient data. — 📐 The composite score is not a probability . A score of 80% means four market dimensions, percentile-ranked against recent history, strongly agree on bullish conditions. It measures consensus quality, not prediction accuracy. — ⚖️ Percentile ranking is relative to the lookback window . A score of 0.9 means "higher than 90% of the last N bars" — it does not mean the same thing on different instruments or timeframes. Each chart creates its own distribution. — 📊 The Flow axis (MFI + OBV) auto-disables on instruments without volume data (many forex pairs). The composite then runs on three axes with adjusted total weight. Signal quality is slightly lower without flow data but the other three axes remain fully functional. — 🔒 Direction lock means you get one signal per trend leg . After a buy, only a sell can fire next. This prevents clustering but means you won't get "add to position" signals — the tool provides one entry per direction. — 🔄 The agreement gate requires ≥ 50% of axes to independently confirm. On 4-axis instruments, this means ≥ 2. On 3-axis (no volume), ≥ 2. This is a deliberately moderate threshold — raising it to 75%+ would make signals extremely rare. — 🛠️ This is a signal and analysis tool , not an automated trading bot. It classifies momentum consensus and generates signals — trade decisions remain yours. — 🌐 Works on all markets and timeframes. Volume-dependent features auto-adapt to available data.
Indicador Pine Script®
por WillyAlgoTrader
2
SmartTrend Pro [WillyAlgoTrader]📡 SmartTrend Pro is an overlay indicator built around a custom trend detection algorithm — the Adaptive Volatility Trend Engine (AVTE) — that replaces the standard Supertrend approach with Ehlers Super Smoother filtering and Kaufman adaptive ATR bands. Every trend flip is scored by a multi-factor confluence system (0–100) before becoming a signal. The result is a trend-following tool that adapts to current volatility conditions, filters out low-confidence entries, and provides dynamic TP/SL levels — all with full anti-repaint protection. 🧩 WHY THESE COMPONENTS WORK TOGETHER A traditional Supertrend uses a simple moving average of True Range to calculate bands. This works in steady markets but produces false signals during volatility spikes and misses early reversals during compression. SmartTrend Pro replaces every component of this pipeline with an adaptive alternative, creating a system where each stage feeds the next: Ehlers-filtered price → Kaufman-adaptive ATR → Volatility bands → Trend direction → Confluence scoring → Filtered signal → Risk levels The Ehlers Super Smoother removes high-frequency noise from the price before the trend bands are calculated — this prevents the trend engine from reacting to random wicks. The Kaufman adaptive ATR widens bands when volatility is real (sustained directional movement) and tightens them during choppy, low-efficiency conditions — making the trend change threshold automatically adjust. The confluence scoring system then evaluates each trend flip against five independent market factors before allowing the signal to fire. And the TP/SL system freezes its risk distance at entry (using the ATR at signal time) so targets don't drift as volatility changes post-entry. No single component here is sufficient on its own. An Ehlers filter without adaptive bands still produces false crossovers. Adaptive bands without scoring still trigger on weak trend flips. Scoring without frozen TP/SL creates drifting targets. The integrated pipeline solves all three problems simultaneously. 🔍 WHAT MAKES IT ORIGINAL 1️⃣ Adaptive Volatility Trend Engine (AVTE) — custom trend algorithm. The AVTE replaces the standard Supertrend calculation at every stage: Stage 1 — Price filtering: Instead of using raw price, the AVTE applies an Ehlers 2-pole Super Smoother to the source. The Ehlers filter uses the transfer function: ss = c1 × (src + src ) × 0.5 + c2 × ss + c3 × ss where c1 = 1 − c2 − c3, c2 = 2a × cos(√2 × π / period), c3 = −a², and a = exp(−√2 × π / period). This produces zero-lag frequency-domain filtering — it removes high-frequency noise without the phase distortion that a simple moving average introduces. The filter period is derived from the ATR period (ATR_period / 2, minimum 3). Stage 2 — Adaptive volatility measurement: Instead of a fixed-length ATR, the AVTE uses a Kaufman Adaptive ATR. First, a standard ATR(period) is calculated. Then the Kaufman Efficiency Ratio (ER) is computed: ER = |close − close | / sum(|close − close |, period). The ER measures how much net directional movement exists relative to total path traveled — ranging from 0 (pure chop) to 1 (clean trend). The ER then modulates a smoothing constant: sc = (ER × (fast − slow) + slow)², where fast = 2/3 and slow = 2/31. The adaptive ATR blends: aATR = aATR + sc × (rawATR − aATR ). In trending conditions (high ER), the adaptive ATR reacts quickly to volatility changes. In choppy conditions (low ER), it smooths aggressively, preventing false band expansions. Stage 3 — Band calculation and trend direction: Upper band = filtered_price + sensitivity × adaptive_ATR. Lower band = filtered_price − sensitivity × adaptive_ATR. Bands ratchet in the trend direction: the lower band can only rise (never fall) during uptrends, the upper band can only fall during downtrends. When close crosses above the upper band, trend flips bullish. When close crosses below the lower band, trend flips bearish. The trend line follows the lower band in uptrends, upper band in downtrends (step-line visualization). The Sensitivity parameter (default 2.5) controls how far the bands sit from filtered price. Lower = tighter bands, more signals, faster reaction. Higher = wider bands, fewer signals, smoother. 2️⃣ Multi-confluence scoring system (0–100). Every AVTE trend flip is evaluated against five independent market factors before becoming a signal: Factor 1 — EMA alignment (±15 pts): Checks whether close > EMA(50) > EMA(200) for bullish alignment, or close < EMA(50) < EMA(200) for bearish. Full alignment = +15 (bull) or −15 (bear). No alignment = 0. This confirms the trend flip aligns with the broader trend structure. Factor 2 — RSI position (±10 pts): RSI(14) between 50–70 = +10 (bullish momentum without overextension). RSI 30–50 = −10 (bearish). Extremes (>70 or <30) score 0 — avoiding signals at overbought/oversold levels where reversals are more likely. Factor 3 — MACD histogram direction (±12 pts): MACD(12,26,9) histogram > 0 and rising = +12 (accelerating bullish momentum). Histogram < 0 and falling = −12 (accelerating bearish). This captures momentum acceleration, not just direction. Factor 4 — Volume confirmation (0–8 pts): Volume > 20-period SMA × 1.2 = +8. This confirms institutional participation. Auto-disabled on instruments without volume data (forex). Factor 5 — ADX strength (0–10 pts): ADX(14) > 25 = +10, ADX > 20 = +5. Confirms the market is trending, not ranging. The base score starts at 50. Bullish factors add, bearish factors subtract. Final score is clamped to 0–100. A buy signal fires when the AVTE flips bullish AND score ≥ Min Signal Score (default 55). A sell signal fires when AVTE flips bearish AND score ≤ (100 − Min Signal Score), creating symmetric thresholds around 50. Signals with score ≥ 75 (buy) or ≤ 25 (sell) are classified as "Strong" and receive a distinct label. 3️⃣ Ehlers Super Smoother trend cloud. A dual-band cloud system using two Ehlers Super Smoothers at different periods. The fast period depends on the Cloud Style setting: — Adaptive: auto-adjusts between 13 and 55 based on current volatility — calculated as 34 × (1 + stdev(close, 20) / adaptive_ATR × 0.5) — Fast: fixed at 21 (tight cloud for scalping) — Smooth: fixed at 55 (wide cloud for swing) — Minimal: fixed at 34 (single line, no fill) The slow period = fast period × 2.618 (golden ratio). Cloud is bullish when fast > slow (green fill), bearish when fast < slow (red fill). The AVTE step-line is overlaid on the cloud for immediate trend-direction clarity. An optional trend tracer (EMA, default 233-period) provides institutional-level long-term bias. 4️⃣ Four-preset system with parameter scaling. Presets modify three core parameters simultaneously using multipliers: — Conservative : sensitivity × 1.4, ATR period × 1.3, min score floor 70 — fewer but higher-quality signals, for swing trading — Balanced : no modification — default parameters, good for 15M–4H — Aggressive : sensitivity × 0.7, ATR period × 0.8, min score ceiling 45 — more signals, faster entries — Scalping : sensitivity × 0.5, ATR period × 0.6, min score ceiling 40 — optimized for 1–5M, tightest bands Each preset adjusts the effective sensitivity, ATR length, and minimum score threshold proportionally, so one selection adapts the entire signal pipeline rather than requiring manual tuning of individual parameters. 5️⃣ Dynamic TP/SL with frozen risk distance. Three stop-loss modes: — ATR : SL distance = adaptive ATR × configurable multiplier (default 1.5×) — Percentage : SL distance = fixed percentage of entry price — Structure : SL distance = half the recent swing range (highest high − lowest low over swing lookback) TP levels are calculated as multiples of SL distance: TP1 = SL × 1.5 (default), TP2 = SL × 2.5, TP3 = SL × 4.0. The SL distance is frozen at entry — once a signal fires, the risk distance is locked and does not change with subsequent volatility. This prevents TP/SL levels from drifting as ATR changes post-entry. TP hit markers (×) appear on the chart as each level is reached. An optional Chandelier Exit trailing stop follows price using the ATR multiplier, ratcheting in the profit direction. 6️⃣ Pullback signals within established trends. In addition to trend-flip signals, the indicator detects pullback entries within an existing trend: — Bullish pullback: AVTE trend is bullish (no flip), price retraces to EMA(pullback_sensitivity × 3), RSI(pullback_sensitivity) drops below 35 then starts rising — catching the bounce off trend support — Bearish pullback: AVTE trend is bearish, price rallies to EMA, RSI exceeds 65 then starts falling Pullback signals appear as small circles (distinct from the main Buy/Sell labels), providing additional entries within a confirmed trend direction. They are bar-close confirmed and warmup-protected. 7️⃣ Volatility gauge with statistical normalization. The dashboard displays a real-time volatility reading (0–100%) calculated as: gauge = (ATR(10) − (SMA(ATR, 20) − StDev(ATR, 20))) / (2 × StDev(ATR, 20)) × 100, clamped to 0–100. This measures where current volatility sits relative to its recent statistical distribution: > 70% = High (above 1 standard deviation), 40–70% = Medium, < 40% = Low. This helps you assess whether the current environment suits your strategy: high volatility favors wider stops and fewer signals, low volatility favors tighter approaches. 8️⃣ Multi-timeframe trend panel (non-repainting). The dashboard includes an MTF panel showing trend direction on 5M, 15M, 1H, 4H, and 1D — using close > EMA(200) with lookahead_on for guaranteed non-repainting. When most timeframes align in one direction, trend-flip signals in that direction have higher confluence. 9️⃣ Session detection. The dashboard shows the current active trading session: Tokyo, London, New York, Sydney, or overlaps (London/New York, Tokyo/London). Sessions are calculated using UTC-based time windows. This helps you contextualize volatility: London/New York overlap is typically the highest-volume period, while off-hours have thinner liquidity. 🔟 Four optional filters. Each filter can be independently toggled: — Trend filter : only signals aligned with the Ehlers cloud direction — Volume filter : only signals with volume EMA(10) > EMA(25) — auto-disabled for instruments without volume — ADX filter : only signals when ADX > 20 (trending market) — Momentum filter : only signals with MACD histogram aligned (positive + rising for buys, negative + falling for sells) All filters default to Off — enabling them progressively reduces signal frequency while increasing average quality. ⚙️ HOW IT WORKS — CALCULATION FLOW Step 1 — Ehlers filtering: Source price is passed through the 2-pole Super Smoother with period = max(round(ATR_period / 2), 3). This removes intrabar noise while preserving trend structure. Step 2 — Adaptive ATR: Kaufman Efficiency Ratio is calculated over the ATR period. The ER modulates the smoothing speed of ATR: trending conditions → fast adaptation, choppy conditions → slow adaptation. Step 3 — Band construction: Upper = filtered_price + sensitivity × adaptive_ATR. Lower = filtered_price − sensitivity × adaptive_ATR. Bands ratchet: lower band can only rise in uptrends, upper band can only fall in downtrends. Step 4 — Trend detection: Close above upper band → bullish. Close below lower band → bearish. The trend line is the active band (lower in uptrends, upper in downtrends). Step 5 — Confluence scoring: On every bar, five factors are evaluated and combined into a 0–100 score. On a trend flip bar, the score determines whether the signal qualifies. Step 6 — Filter gate: If any enabled filter disagrees, the signal is suppressed. Step 7 — Signal emission: Buy or Sell label appears on the confirmed bar. Score ≥ 75 / ≤ 25 → "Strong Buy/Sell". Step 8 — TP/SL placement: Risk distance is calculated and frozen. TP1/TP2/TP3 are placed as R:R multiples. Labels persist on the right side of the chart. Hit markers appear as each level is reached. 📖 HOW TO USE 🎯 Quick start: 1. Select a preset matching your style: Scalping (1–5M), Balanced (15M–4H), Conservative (4H–1D) 2. Add the indicator to your chart — the AVTE trend line and cloud appear immediately 3. Wait for a Buy or Sell label — the score next to it tells you the confluence quality 4. Check the dashboard: trend direction, score, market state (trending/ranging), volatility, session 5. TP/SL levels appear automatically — manage the trade using the marked levels 👁️ Reading the chart: — 🟩 Green cloud fill = bullish trend (Ehlers fast > slow) — 🟥 Red cloud fill = bearish trend — Step-line on the cloud = AVTE trend boundary (the level that must break for a trend flip) — 🟢 "Buy" / "Strong Buy" label below bar = confirmed bullish signal — 🔴 "Sell" / "Strong Sell" label above bar = confirmed bearish signal — 🟢 Small circle below bar = pullback buy (trend continuation entry) — 🔴 Small circle above bar = pullback sell — Orange line = entry price | Red line = stop loss | Green lines = TP1/TP2/TP3 — × markers = TP hit confirmations — HH/HL/LH/LL labels (optional) = market structure swing points 📊 Dashboard fields: — Trend: current AVTE direction (Bullish/Bearish) — Signal: last confirmed signal (Buy/Sell/Wait) — Score: current confluence score (0–100) — Market: ADX-based state (Trending > 25 / Ranging > 20 / No Trend) — Volatility: statistical gauge (High/Medium/Low with percentage) — Session: current active session (Tokyo/London/New York/Sydney/overlaps) — MTF Panel: 5M/15M/1H/4H/1D trend direction (close vs 200 EMA) 🔧 Tuning guide: — Too many signals: increase Min Score, enable filters, switch to Conservative preset — Too few signals: decrease Min Score, switch to Aggressive/Scalping, lower Sensitivity — Signals too late: lower Sensitivity (tighter bands), use Fast cloud style — Too many false signals: enable ADX filter (filters ranging markets), increase Min Score to 65+ — Scalping 1–5M: use Scalping preset, ATR mode SL with multiplier 1.0–1.5, TP1 R:R 1.0–1.5 — Swing 4H–1D: use Conservative preset, ATR mode SL with multiplier 2.0–3.0, TP3 R:R 5.0+ ⚙️ KEY SETTINGS REFERENCE ⚙️ Main: — Trend Sensitivity (default 2.5): AVTE band distance — lower = more signals, higher = fewer — ATR Period (default 21): volatility measurement lookback — Preset (default Balanced): Conservative / Balanced / Aggressive / Scalping 📡 Signal Tuning: — Min Signal Score (default 55): minimum confluence to trigger signals — Strong Signals Only (default Off): only show score ≥ 75 — Show Pullback Signals (default On): trend continuation entries — Pullback Sensitivity (default 8): retracement detection lookback ☁️ Trend Cloud: — Cloud Style (default Adaptive): Adaptive / Fast / Smooth / Minimal — Trend Tracer (default Off): long-term EMA bias line (default 233) 🔍 Filters (all default Off): — Trend Filter (cloud alignment) / Volume Filter / ADX Filter / Momentum Filter 🛡️ Risk Management: — SL Mode (default ATR): ATR / Percentage / Structure — SL ATR Multiplier (default 1.5×) / SL Percentage (default 1.0%) — TP1/TP2/TP3 Risk:Reward (default 1.5 / 2.5 / 4.0) — Trailing Stop (default Off): Chandelier Exit method — Market Structure (default Off): HH/HL/LH/LL swing labels 🎨 Visual: — Auto / Dark / Light theme — Bar coloring: Trend Gradient / Signal Based / Momentum / None — Background trend shading (default Off) 📊 Dashboard: — Position, font size, MTF panel toggle 🔔 Alerts — 🟢 Buy / Strong Buy — ticker, price, timeframe, score — 🔴 Sell / Strong Sell — same fields — 🎯 TP1 / TP2 / TP3 Hit — ticker, price — 🛑 SL Hit — ticker, price — ☁️ Cloud Cross Bullish / Bearish — ticker, timeframe All alerts support plain text and JSON webhook format. Bar-close confirmed. ⚠️ IMPORTANT NOTES — 🚫 No repainting. All signals require barstate.isconfirmed. TP/SL distances are frozen at entry and do not change retroactively. MTF data uses + lookahead_on for non-repainting HTF values. A warmup period (minimum 200 bars or 3× ATR period) prevents signals during insufficient data. — 📐 The AVTE is not a standard Supertrend . It replaces every component: Ehlers Super Smoother instead of raw price, Kaufman adaptive ATR instead of fixed ATR, ratcheting bands instead of simple ±ATR. The mathematics are described in detail above. — ⚖️ The confluence score is not a win-rate predictor . A score of 75 means five independent market factors align strongly — it measures confluence quality, not outcome probability. Use it to prioritize, not to guarantee. — 📊 The scoring system uses standard indicators (EMA, RSI, MACD, Volume, ADX) as confluence factors , not as independent signal generators. None of these indicators alone triggers a signal — they only contribute to the score that gates an AVTE trend flip. — 🔧 Presets modify parameters proportionally. After selecting a preset, you can still adjust individual settings — the preset sets the starting point, your adjustments override it. — 📏 TP/SL levels are frozen at entry . The SL distance calculated at the signal bar persists until the next signal — it does not drift with changing ATR. This is by design for consistent risk management. — 🔄 Pullback signals are continuation entries , not reversal signals. They only appear within an established AVTE trend and require RSI reversion from oversold/overbought — catching bounces off trend support/resistance. — 🛠️ This is a signal and analysis tool , not an automated trading bot. It generates signals, scores them, and visualizes TP/SL — trade decisions remain yours. — 🌐 Works on all markets and timeframes. Volume filter auto-disables on instruments without volume data.
Indicador Pine Script®
por WillyAlgoTrader
14
Optimized Buy/Sell Pro + Live Trade DashboardOptimized Buy/Sell Pro + Live Trade Dashboard Active Trade Table: Displays Entry, SL, TP, and Exit Price (if closed). Live R:R Calculation: Shows the math behind the trade while it's running. Automatic Cleanup: The trade table updates to "IDLE" when no trade is active to keep your chart clean. Understanding the Dashboard: Net Profit (R): This is your most important metric. If it says 5.2R, it means even if you only risked $100 per trade, you are up $520. Win Rate: Don't be alarmed if this is below 50%. Because your Risk:Reward is 3.0, you only need a 26% win rate to be profitable! Current State: Quickly tells you if the script is currently managing a trade or waiting for a fresh EMA cross.
Indicador Pine Script®
por demantprasad
Flow EngineFlow Engine Most indicators tell you which direction price is moving. Flow Engine tells you whether to trust it . It does this by combining momentum, volume, trend, and a higher timeframe check all into one pane, plus it draws divergence signals directly on your price chart so you never have to look away. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ WHAT'S ON THE SCREEN ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ The Histogram (the bars) This is the main thing. The height of each bar shows how strong the momentum is. The color tells you the direction — cyan for up, red for down. The part that makes this different is the opacity . If a bar is bright and vivid, it means big volume is behind that move. If a bar looks faded or ghosted, the move happened on low volume and probably won't last. You can see this instantly without checking a separate volume pane. Tall vivid cyan bar = strong upward move with real volume behind it Tall faded cyan bar = price went up but nobody really showed up Same logic applies on the red side The OB/OS Line This line tells you when things are getting stretched too far in one direction. When it goes above +70 — the move is getting overdone on the upside. When it drops below -70 — the selloff is getting overdone. In between — cyan means leaning bullish, red means leaning bearish The Trend Line A slow moving line that tells you what the overall structure looks like on your current timeframe. Lime green above zero — uptrend Soft red below zero — downtrend Think of it as the background context. When this line is green, you want to be looking for longs. When it's red, be careful going long or look for shorts instead. The Background Tint (HTF Bias) A very subtle color behind everything that comes from a higher timeframe — by default the Daily chart. Cyan tint — the daily trend is bullish Red tint — the daily trend is bearish No tint — daily is mixed, no clear direction This is the big picture check. If you are trading a 15 minute chart and the background is red, you know you are going against the daily trend. That doesn't mean you can't trade, but you should be more careful. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ DIVERGENCE SIGNALS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Divergence is when price and momentum stop agreeing with each other. It usually means the current move is running out of steam. Bearish divergence — price made a higher high but the histogram made a lower high. The rally is weakening. Orange triangle appears above the candle on your price chart. Bullish divergence — price made a lower low but the histogram made a higher low. The selloff is weakening. Green triangle appears below the candle on your price chart. You also get a dashed line drawn on the Flow Engine pane connecting the two points so you can see exactly where the divergence happened. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SETTINGS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Momentum Length (14) — how many bars the momentum calculation looks back. Lower number reacts quicker but gives more false signals. Higher number is slower but cleaner. Volume MA Length (20) — the average used to judge whether current volume is high or low. Leave this at default unless you have a reason to change it. Overbought Level (70) — where the OB/OS line turns orange. Lower this if you want earlier warnings. Oversold Level (-70) — where the OB/OS line turns green. Change this together with the overbought level. Trend Length (50) — how slow the trend line moves. Higher number = smoother line. Pivot Lookback Left & Right (5) — controls how strict the divergence detection is. Raise both to 8 or 10 if you are getting too many signals. Lower to 3 if you want more. HTF Timeframe (D) — the higher timeframe for the background tint. Set this one step above whatever chart you are on. D = Daily, W = Weekly, 240 = 4 Hour. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ HOW TO USE IT ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Every time you look at the indicator, go through it top to bottom: Check the background tint — what is the daily (or higher TF) saying? Check the trend line — is the current chart agreeing with that? Check the OB/OS line — are we stretched? If yes, don't chase. Check the histogram — is momentum vivid (real) or faded (weak)? The best setup looks like this: Background is cyan + trend line above zero + OB/OS line near oversold + bullish divergence triangle on the chart + histogram bars turning bright cyan When all of that lines up, the move has multiple things confirming it at the same time. That's when you pay attention. A quick tip on the faded bars: Don't get excited about a tall bar if it's faded. Price can move fast on thin volume and snap right back. The vivid bars are the ones that tend to follow through. Which timeframe to set HTF to: Trading 1m or 5m → set HTF to 1H or 4H Trading 15m or 1H → keep HTF on Daily Trading 4H or Daily → set HTF to Weekly ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ GOOD TO KNOW ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Does not repaint — signals are based on confirmed bars only Divergence signals show up a few bars after the actual pivot Looks best on a dark theme
Indicador Pine Script®
por AdarshShrma
1
Smart Money Failure Detector This indicator identifies moments when price fakes a breakout above a key high or below a key low, only to get violently rejected back inside the range. These are known as liquidity grabs or stop hunts moments where smart money runs retail breakout traders out of their positions before reversing hard in the opposite direction. HOW IT WORKS The indicator defines a dynamic range using a configurable lookback period. When price sweeps above the range high or below the range low but closes back inside with a strong reversal body, a rejection wick larger than the body, and a volume spike above average therefore a trap is confirmed. Two trap types are detected: → Single-bar trap — the entire sweep and rejection happens within one candle → Multi-bar trap — price holds outside the range for a few candles before failing and closing back inside with conviction SIGNAL TYPES 🐂 Bull Trap → SHORT Price swept above the high, rejected, and closed bearish. Sellers are now in control. 🐻 Bear Trap → LONG Price swept below the low, rejected, and closed bullish. Buyers absorbed all the selling. WHAT APPEARS ON THE CHART → Triangle marker above or below the trap candle → Background highlight on the trap candle → Dashed stop line plotted at the wick tip → Dashed target line at your chosen Risk:Reward distance → Label showing the exact stop and target price STOP LOSS LOGIC The stop is placed at the extreme of the sweep wick. The high of the trap candle for shorts, the low for longs. If price returns to that level the trap thesis is invalidated. The target is the stop distance multiplied by your R:R setting, default is 2:1. SETTINGS Range Lookback — bars used to define the prior high and low Max Bars to Close Back Inside — how long the multi-bar trap window stays open after a breakout Volume Spike Multiplier — how far above average volume must be to confirm smart money activity Min Body % — minimum body size relative to the full candle range to ensure reversal conviction Min Wick Ratio — minimum rejection wick to body ratio to confirm a hard sweep occurred Risk:Reward Target — how much risk to reward you want RECOMMENDED USAGE Best used on custom Risk:reward and other custom settings as all assets work very different to each other. Please do some backtests before live trading. ─────────────────────────────────────────
Indicador Pine Script®
por AdarshShrma